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• The rugged landscape of drug design
  - Nat Genet 43(12):1165 (2011)
  Nature Genetics | Editorial The rugged landscape of drug design Journal name:Nature GeneticsVolume: 43,Page:1165Year published:(2011)DOI:doi:10.1038/ng.1030Published online28 November 2011 How can we get more therapies into preclinical testing and increase the proportion that succeed in preclinical testing? How can we increase the efficacy of therapies? How can we ensure that therapies are developed for rare diseases? View full text Additional data
• Evidence for dosage compensation between the X chromosome and autosomes in mammals
  - Nat Genet 43(12):1167-1169 (2011)
  Nature Genetics | Correspondence Evidence for dosage compensation between the X chromosome and autosomes in mammals * Peter V Kharchenko1, 2 * Ruibin Xi1 * Peter J Park1, 2, 3 * Affiliations * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:1167–1169Year published:(2011)DOI:doi:10.1038/ng.991Published online28 November 2011 To the Editor: It has been hypothesized that, in addition to the inactivation of one of the female X chromosomes, X-linked expression in mammals is regulated through dosage compensation that involves a twofold upregulation of expression from the active X chromosome. This idea was initially based on evolutionary arguments and has subsequently been supported by the analysis of microarray expression data, which suggested that the median transcriptional magnitude of genes on the single active X chromosome is similar to that of genes on the two-copy autosomes (X:AA ratio of ~1)1, 2. However, in a recent Nature Genetics article, Xiong et al. state, on the basis of their examination of multiple human and mouse RNA sequencing (RNA-seq) data sets, that global X-chromosome upregulation is absent, thus necessitating a major revision of the current model3. The authors argue that the increased accuracy of the RNA-seq data reveals the true X:AA ratio to be close to 0.5, about half of the value obtained ! by examining microarray data. Here we contend that the low estimate of the X:AA ratio by Xiong et al. stems from the disproportionate contribution of transcriptionally inactive genes, which are not relevant for the evaluation of dosage compensation mechanisms, to the X chromosome average. We show that when only active genes are considered, the RNA-seq data give X:AA ratios closer to 1, and the observed minor deviation of the X:AA ratio from 1 is within the range expected when taking into account chromosome-to-chromosome variability. View full text Accession codes * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Referenced accessions Gene Expression Omnibus * GSE12946 * GSE13652 * GSE21860 * GSE22131 Sequence Read Archive * SRA001030 Author information * Accession codes * Author information * Supplementary information Affiliations * Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA. * Peter V Kharchenko, * Ruibin Xi & * Peter J Park * Informatics Program, Children's Hospital Boston, Boston, Massachusetts, USA. * Peter V Kharchenko & * Peter J Park * Division of Genetics, Brigham and Women's Hospital, Boston, Massachusetts, USA. * Peter J Park Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Peter J Park Author Details * Peter V Kharchenko Search for this author in: * NPG journals * PubMed * Google Scholar * Ruibin Xi Search for this author in: * NPG journals * PubMed * Google Scholar * Peter J Park Contact Peter J Park Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (430K) Supplementary Figures 1 and 2, Supplementary Table 1 and Supplementary Methods Additional data
• Relative overexpression of X-linked genes in mouse embryonic stem cells is consistent with Ohno's hypothesis
  - Nat Genet 43(12):1169-1170 (2011)
  Nature Genetics | Correspondence Relative overexpression of X-linked genes in mouse embryonic stem cells is consistent with Ohno's hypothesis * Hong Lin1, 3 * John A Halsall1 * Philipp Antczak2 * Laura P O'Neill1 * Francesco Falciani2 * Bryan M Turner1 * Affiliations * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:1169–1170Year published:(2011)DOI:doi:10.1038/ng.992Published online28 November 2011 To the Editor: In a recent issue of Nature Genetics, Xiong et al.1 presented an analysis of published RNA sequencing (RNA-seq) data that they claimed shows that genes on the X chromosome were not expressed at higher levels than autosomal genes, thus refuting Ohno's hypothesis2 and "...necessitating a major revision of the current model of dosage compensation in the evolution of sex chromosomes." The authors gave reasons to dismiss previous data-mining studies by Nguyen and Disteche3 and Gupta et al.4, as well as a study from our group that included experiments specifically designed to measure X-linked gene expression in embryonic stem (ES) cells5, all of which provided data supporting Ohno's hypothesis. Here we present further analysis of our experimental results, thereby both confirming our original interpretation and refuting the criticisms of Xiong and colleagues. View full text Accession codes * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Referenced accessions Gene Expression Omnibus * GSE8593 * GSM212951 * GSM212955 * GSM212990 * GSM213198 Author information * Accession codes * Author information * Supplementary information Affiliations * Chromatin and Gene Expression Group, Institute of Biomedical Research, University of Birmingham, Birmingham, UK. * Hong Lin, * John A Halsall, * Laura P O'Neill & * Bryan M Turner * School of Biosciences, University of Birmingham, Birmingham, UK. * Philipp Antczak & * Francesco Falciani * Present address: National Blood Service, Vincent Drive, Birmingham, UK. * Hong Lin Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Bryan M Turner Author Details * Hong Lin Search for this author in: * NPG journals * PubMed * Google Scholar * John A Halsall Search for this author in: * NPG journals * PubMed * Google Scholar * Philipp Antczak Search for this author in: * NPG journals * PubMed * Google Scholar * Laura P O'Neill Search for this author in: * NPG journals * PubMed * Google Scholar * Francesco Falciani Search for this author in: * NPG journals * PubMed * Google Scholar * Bryan M Turner Contact Bryan M Turner Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (127K) Supplementary Methods, Supplementary Table 1 and Supplementary Figure 1 Additional data
• He et al. reply
  - Nat Genet 43(12):1171-1172 (2011)
  Nature Genetics | Correspondence He et al. reply * Xionglei He1 * Xiaoshu Chen1 * Yuanyan Xiong1 * Zhidong Chen1 * Xunzhang Wang1 * Suhua Shi1 * Xueqin Wang2, 3 * Jianzhi Zhang4 * Affiliations * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:1171–1172Year published:(2011)DOI:doi:10.1038/ng.1010Published online28 November 2011 He et al. reply: In his seminal book titled Sex Chromosomes and Sex-Linked Genes, Susumu Ohno1 wrote: "During the course of evolution, an ancestor to placental mammals must have escaped a peril resulting from the hemizygous existence of all the X-linked genes in the male by doubling the rate of product output of each X-linked gene." In principle, Ohno's hypothesis should be tested by comparing the expression levels of the genes located on the present-day X chromosome with those of the orthologous genes located on the ancestral proto-X chromosome (X), the autosomal progenitor of X. Ohno's hypothesis would be supported if the gene expression ratio of X:XX was ~1. Because the X chromosome is unavailable, Ohno's hypothesis is commonly tested indirectly by estimating the expression ratio between the X chromosome and present-day autosomes (AA), under the assumption that expression levels are comparable between the XX chromosomes, ancestral autosomes (AA) and present-day AA (Fig. 1a). View full text Author information * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * State Key Laboratory of Biocontrol and College of Life Sciences, Sun Yat-sen University, Guangzhou, China. * Xionglei He, * Xiaoshu Chen, * Yuanyan Xiong, * Zhidong Chen, * Xunzhang Wang & * Suhua Shi * School of Mathematics and Computational Science, Sun Yat-sen University, Guangzhou, China. * Xueqin Wang * Zhongshan Medical School, Sun Yat-sen University, Guangzhou, China. * Xueqin Wang * Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, USA. * Jianzhi Zhang Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Xionglei He or * Jianzhi Zhang Author Details * Xionglei He Contact Xionglei He Search for this author in: * NPG journals * PubMed * Google Scholar * Xiaoshu Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Yuanyan Xiong Search for this author in: * NPG journals * PubMed * Google Scholar * Zhidong Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Xunzhang Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Suhua Shi Search for this author in: * NPG journals * PubMed * Google Scholar * Xueqin Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Jianzhi Zhang Contact Jianzhi Zhang Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (455K) Supplementary Methods and Supplementary Figure 1 Additional data
• Fine points in mapping autoimmunity
  - Nat Genet 43(12):1173-1174 (2011)
  Article preview View full access options Nature Genetics | News and Views Fine points in mapping autoimmunity * Constantin Polychronakos1Journal name:Nature GeneticsVolume: 43,Pages:1173–1174Year published:(2011)DOI:doi:10.1038/ng.1015Published online28 November 2011 An efficient way to design genotyping arrays for fine mapping is to group phenotypes with common biology. The first application of the Immunochip to celiac disease provides an insightful view of what this strategy can achieve. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Genetics for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Constantin Polychronakos is at the Endocrine Genetics Laboratory, Research Institute of the McGill University Health Centre, The Montreal Children's Hospital, Montréal, Québec, Canada. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Constantin Polychronakos Author Details * Constantin Polychronakos Contact Constantin Polychronakos Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Chance and necessity in the evolution of a bacterial pathogen
  - Nat Genet 43(12):1174-1176 (2011)
  Article preview View full access options Nature Genetics | News and Views Chance and necessity in the evolution of a bacterial pathogen * Richard E. Lenski1Journal name:Nature GeneticsVolume: 43,Pages:1174–1176Year published:(2011)DOI:doi:10.1038/ng.1011Published online28 November 2011 The combination of genomic, epidemiological and evolutionary analyses provides a powerful toolbox for understanding how pathogens adapt to their human hosts. By sequencing 112 Burkholderia dolosa genomes from an outbreak among patients with cystic fibrosis, a new study documents evolution in action and identifies a set of genes that contributed to the pathogen's adaptation. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Genetics for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Richard E. Lenski is at the BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, Michigan, USA. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Richard E. Lenski Author Details * Richard E. Lenski Contact Richard E. Lenski Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• A rare variant in CFH directly links age-related macular degeneration with rare glomerular nephropathies
  - Nat Genet 43(12):1176-1177 (2011)
  Article preview View full access options Nature Genetics | News and Views A rare variant in CFH directly links age-related macular degeneration with rare glomerular nephropathies * Alan F. Wright1Journal name:Nature GeneticsVolume: 43,Pages:1176–1177Year published:(2011)DOI:doi:10.1038/ng.1012Published online28 November 2011 A careful analysis of risk haplotypes in relation to age-related macular degeneration (AMD) susceptibility has led to the identification of a rare, high-penetrance variant in the complement factor H (CFH) gene that is also causally associated with atypical hemolytic uremic syndrome (aHUS) and related glomerulopathies. This finding provides a convincing causal mechanism linking the two diseases and develops a paradigm for the genetic architecture of a common and complex disease. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Genetics for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Alan F. Wright is at the Medical Research Council Human Genetics Unit at the Institute of Genetics and Molecular Medicine, Edinburgh, UK. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Alan F. Wright Author Details * Alan F. Wright Contact Alan F. Wright Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Evidence for compensatory upregulation of expressed X-linked genes in mammals, Caenorhabditis elegans and Drosophila melanogaster
  - Nat Genet 43(12):1179-1185 (2011)
  Nature Genetics | Analysis Evidence for compensatory upregulation of expressed X-linked genes in mammals, Caenorhabditis elegans and Drosophila melanogaster * Xinxian Deng1 * Joseph B Hiatt2 * Di Kim Nguyen1 * Sevinc Ercan3 * David Sturgill4 * LaDeana W Hillier5 * Felix Schlesinger6 * Carrie A Davis6 * Valerie J Reinke7 * Thomas R Gingeras6 * Jay Shendure2 * Robert H Waterston2 * Brian Oliver4 * Jason D Lieb8 * Christine M Disteche1, 9 * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:1179–1185Year published:(2011)DOI:doi:10.1038/ng.948Received07 February 2011Accepted25 August 2011Published online23 October 2011 Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Many animal species use a chromosome-based mechanism of sex determination, which has led to the coordinate evolution of dosage-compensation systems. Dosage compensation not only corrects the imbalance in the number of X chromosomes between the sexes but also is hypothesized to correct dosage imbalance within cells that is due to monoallelic X-linked expression and biallelic autosomal expression, by upregulating X-linked genes twofold (termed 'Ohno's hypothesis'). Although this hypothesis is well supported by expression analyses of individual X-linked genes and by microarray-based transcriptome analyses, it was challenged by a recent study using RNA sequencing and proteomics. We obtained new, independent RNA-seq data, measured RNA polymerase distribution and reanalyzed published expression data in mammals, C. elegans and Drosophila. Our analyses, which take into account the skewed gene content of the X chromosome, support the hypothesis of upregulation of expressed X-linked g! enes to balance expression of the genome. View full text Figures at a glance * Figure 1: Distributions of gene expression are similar between the X chromosome and autosomes in human, except for reproduction-related X-linked genes not expressed in somatic tissues. () Expression distributions are similar for X-linked (red) and autosomal genes (blue) in human brain based on RNA-seq data (P = 0.71, by Kolmogorov-Smirnov test). Left, frequency of genes with 0 FPKM; center, histograms of X-linked and autosomal expression distributions; right, cumulative frequencies for genes with >0 FPKM. A theoretical curve (dotted red line) generated by doubling X-linked expression does not result in equal X-linked and autosomal distributions (P = 1 × 10−12, by Kolmogorov-Smirnov test). () Box plots of expression of genes with >0 FPKM are similar from each human chromosome in brain. () Left, the frequency of genes with 0 FPKM is significantly higher on the X chromosome than each autosome except for chr. 21 in 41 lymphoblastoid cell lines (P < 0.05, by Fisher's exact test). Right, histograms of expression distribution for genes with >0 FPKM on each human chromosome. () X:A median expression ratios increase depending on FPKM cutoffs (>0, ≥0.1, ≥0.5,! ≥1 and ≥2). Ratios calculated for individual lymphoblastoid cell lines (17 female, orange and 24 male, green) reveal variability between lines but no differences between males and females (P > 0.05, by Student's t-test). () X:A median expression ratios calculated after separately rank-ordering X-linked and autosomal genes with >0 FPKM by dividing them into16 bins based on expression. Bins 1–5 contain genes with <1 FPKM (shadowed). () Pairwise comparison of the distribution of gene expression in the testis versus liver. Histograms of expression distribution for the subsets of X-linked (X) and autosomal (A) genes expressed in testis (>0 FPKM) but not expressed (0 FPKM) in liver. * Figure 2: Distributions of gene expression are similar between the X chromosome and autosomes in mouse tissues. () Expression distributions are similar for X-linked (red) and autosomal genes (blue) in mouse brain (embryonic day 15 (E15) brain) based on RNA-seq data (P = 0.04, by Kolmogorov-Smirnov test). Left, frequency of genes with 0 FPKM; center, histograms of X-linked and autosomal expression distributions; right, cumulative frequencies for genes with >0 FPKM. A theoretical curve (dotted red line) generated by doubling X-linked expression does not result in equal X-linked and autosomal distributions (P = 1 × 10−13 for E15 brain, by Kolmogorov-Smirnov test). () Box plots of expression of genes with >0 FPKM are similar from each mouse chromosome in E15 brain (P > 0.05 for expression comparison of the X chromosome versus 14 of 19 autosomes, one-way ANOVA test). () Median X:A expression ratios increase depending on FPKM cutoffs (>0, ≥0.1, ≥0.5, ≥1 and ≥2). Reanalysis of RNA-seq data for mouse brain, liver and muscle. Error bars show 95% bootstrap confidence intervals. * Figure 3: Expressed X-linked genes are enriched in RNA PolII-S5p. () Average PolII-S5p occupancy at the 5′ end of 647 X-linked genes (red) is higher in a 1-kb window downstream of the transcription start site (TSS) compared to 16,141 autosomal genes (blue) in undifferentiated female ES cells. Average occupancy (log2 ChIP:input ratio) is plotted using a 500-bp sliding window (100-bp interval) 3 kb up- and downstream of the TSS. () Snapshot of PolII-S5p occupancy in a 2-kb window downstream of the TSS relative to gene expression. Occupancy is higher on X-linked genes (red) compared to autosomal genes (blue) for expressed genes (bins 6–9) but not for weakly- or non-expressed genes (bins 1–5). X-linked and autosomal genes sorted in nine bins based on expression as determined by RNA-seq. Bin 1 contains 124 X-linked and 2,905 autosomal genes with 0 FPKM; bins 2–9 each contain 63 X-linked and 1,596 autosomal genes. X:A median expression ratios are shown in black for bins 2–9. Same ChIP-chip analysis as in . Error bars show 95% bootstrap! confidence intervals. () Gene expression is correlated to PolII-S5p occupancy at the 5′ end of genes. Scatter plots of average PolII-S5p occupancy in a 1-kb region downstream of the TSS against X-linked (red) and autosomal (blue) gene expression in log2 FPKM. Same ChIP-chip analysis as in . * Figure 4: X:A expression ratios in adult C. elegans result from the presence of germ cells in which the X chromosomes are silenced. We rank-ordered X-linked genes according to their expression values and divided them into 55 bins of 50 genes each. Bin 1 contained the lowest-expressed genes, and bin 55 the highest. We likewise ranked the autosomal genes and divided them into 55 bins. The X:A ratio of expression levels were calculated for each bin. Genes with zero reads were included in the binning. Bins 22–48, which represent the middle of the distribution of expression values, are plotted. This ordering removes the effect of very highly or very weakly expressed genes (for example, in early embryo, bins 1–21 account for 0.3% of X-linked expression and 0.06% of autosomal expression). Weakly expressed genes (for example, bins 22–31) may have higher X:A expression ratios if dosage-compensation mechanisms work most efficiently on appreciably expressed genes. * Figure 5: X chromosome dosage compensation in early mitotic cells in the Drosophila germline. Distributions of gene-level expression values in log2 FPKM are shown by chromosome arm (≥1 FPKM). (–) Red dashed lines indicate the median value for genes on the X chromosome for ovary () and testis () from wild-type Drosophila and for ovary () and testis () from bam mutant Drosophila. Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE26284 * GSE16921 * GSE22131 * GSE30690 * GSE30689 * GSE20136 * GSE16960 Sequence Read Archive * SRA001030 * SRA012213 * SRA003622 * SRA008646 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Department of Pathology, University of Washington School of Medicine, Seattle, Washington, USA. * Xinxian Deng, * Di Kim Nguyen & * Christine M Disteche * Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA. * Joseph B Hiatt, * Jay Shendure & * Robert H Waterston * Department of Biology and Center for Genomics and Systems Biology, New York University, New York, New York, USA. * Sevinc Ercan * Section of Developmental Genomics, Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases, US National Institutes of Health, Bethesda, Maryland, USA. * David Sturgill & * Brian Oliver * Genome Sequencing Center, Washington University School of Medicine, Saint Louis, Missouri, USA. * LaDeana W Hillier * Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. * Felix Schlesinger, * Carrie A Davis & * Thomas R Gingeras * Department of Genetics, Yale University, New Haven, Connecticut, USA. * Valerie J Reinke * Department of Biology, Carolina Center for the Genome Sciences and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. * Jason D Lieb * Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA. * Christine M Disteche Contributions X.D., C.M.D., J.D.L. and B.O. conceived the project and wrote the manuscript. X.D., J.B.H., D.K.N., F.S., C.A.D., T.R.G., J.S., C.M.D. and B.O. analyzed the mammalian data; R.H.W., L.W.H., J.D.L., V.J.R. and S.E. analyzed the C. elegans data; B.O. and D.S. analyzed the Drosophila data; X.D., J.B.H. and J.S. performed or analyzed the RNA-seq and ChIP-seq data from mouse ES cells. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Christine M Disteche or * Brian Oliver or * Jason D Lieb Author Details * Xinxian Deng Search for this author in: * NPG journals * PubMed * Google Scholar * Joseph B Hiatt Search for this author in: * NPG journals * PubMed * Google Scholar * Di Kim Nguyen Search for this author in: * NPG journals * PubMed * Google Scholar * Sevinc Ercan Search for this author in: * NPG journals * PubMed * Google Scholar * David Sturgill Search for this author in: * NPG journals * PubMed * Google Scholar * LaDeana W Hillier Search for this author in: * NPG journals * PubMed * Google Scholar * Felix Schlesinger Search for this author in: * NPG journals * PubMed * Google Scholar * Carrie A Davis Search for this author in: * NPG journals * PubMed * Google Scholar * Valerie J Reinke Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas R Gingeras Search for this author in: * NPG journals * PubMed * Google Scholar * Jay Shendure Search for this author in: * NPG journals * PubMed * Google Scholar * Robert H Waterston Search for this author in: * NPG journals * PubMed * Google Scholar * Brian Oliver Contact Brian Oliver Search for this author in: * NPG journals * PubMed * Google Scholar * Jason D Lieb Contact Jason D Lieb Search for this author in: * NPG journals * PubMed * Google Scholar * Christine M Disteche Contact Christine M Disteche Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (6M) Supplementary Figs 1–5 and Supplementary Table 1 Excel files * Supplementary Table 2 (37K) Comparisons of X-linked and autosomal gene expression by RNA-seq in human and mouse * Supplementary Table 3 (37K) Expression of testis-expressed X-linked genes is low in human somatic tissues. * Supplementary Table 4 (37K) Expression of reproduction-related X-linked genes in mouse somatic tissues. Additional data
• Loss-of-function variant in DNASE1L3 causes a familial form of systemic lupus erythematosus
  - Nat Genet 43(12):1186-1188 (2011)
  Nature Genetics | Brief Communication Loss-of-function variant in DNASE1L3 causes a familial form of systemic lupus erythematosus * Sulaiman M Al-Mayouf1, 11 * Asma Sunker2, 11 * Reem Abdwani3, 11 * Safiya Al Abrawi4 * Fathiya Almurshedi5 * Nadia Alhashmi4 * Abdullah Al Sonbul1 * Wafaa Sewairi6 * Aliya Qari7 * Eiman Abdallah3 * Mohammed Al-Owain7, 8 * Saleh Al Motywee6 * Hanan Al-Rayes9 * Mais Hashem2 * Hanif Khalak2 * Latifa Al-Jebali2 * Fowzan S Alkuraya2, 8, 10 * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:1186–1188Year published:(2011)DOI:doi:10.1038/ng.975Received20 June 2011Accepted19 September 2011Published online23 October 2011 Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Systemic lupus erythematosus (SLE) is a complex autoimmune disease that causes substantial morbidity. As is typical for many other multifactorial disorders, much of the heritability of SLE remains unknown. We identified a rare autosomal recessive form of SLE, in which autozygome analysis revealed a null mutation in the DNASE1L3 gene. The DNASE1L3-related SLE we describe was always pediatric in onset and correlated with a high frequency of lupus nephritis. Our findings confirm the critical role of impaired clearance of degraded DNA in SLE pathogenesis. View full text Accession codes * Accession codes * Author information * Supplementary information Referenced accessions GenBank * NM_004944.2 Author information * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Sulaiman M Al-Mayouf, * Asma Sunker & * Reem Abdwani Affiliations * Rheumatology Section, Department of Pediatrics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia. * Sulaiman M Al-Mayouf & * Abdullah Al Sonbul * Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia. * Asma Sunker, * Mais Hashem, * Hanif Khalak, * Latifa Al-Jebali & * Fowzan S Alkuraya * Department of Child Health, Sultan Qaboos University Hospital, Muscat, Oman. * Reem Abdwani & * Eiman Abdallah * Department of Child Health, Royal Hospital, Muscat, Oman. * Safiya Al Abrawi & * Nadia Alhashmi * Department of Genetics, Sultan Qaboos University Hospital, Muscat, Oman. * Fathiya Almurshedi * Division of Rheumatology, Department of Medicine, King Fahad National Guard Hospital and King Abdullah International Medical Research Center, Riyadh, Saudi Arabia. * Wafaa Sewairi & * Saleh Al Motywee * Department of Medical Genetics, King Faisal Specialist Hospital, Riyadh, Saudi Arabia. * Aliya Qari & * Mohammed Al-Owain * Department of Anatomy and Cell Biology, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia. * Mohammed Al-Owain & * Fowzan S Alkuraya * Department of Medicine, Riyadh Military Hospital, Riyadh, Saudi Arabia. * Hanan Al-Rayes * Department of Pediatrics, King Khalid University Hospital and College of Medicine, King Saud University, Riyadh, Saudi Arabia. * Fowzan S Alkuraya Contributions The study was conceived of by S.M.A.-M., F.A., M.A.-O., L.A.-J. and F.S.A. Data were collected by S.M.A.-M., A.S., R.A., S.A.A., F.A., N.A., A.A.-S., W.S., A.Q., E.A., M.A.-O., S.A.M., H.A.-R., M.H., L.A.-J. and F.S.A. Data analysis was performed by A.S., R.A., H.K., L.A.-J. and F.S.A. The manuscript was written by F.S.A. and edited by S.M.A.-M., A.S., R.A., S.A.A., F.A., N.A. and L.A.-J. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Fowzan S Alkuraya Author Details * Sulaiman M Al-Mayouf Search for this author in: * NPG journals * PubMed * Google Scholar * Asma Sunker Search for this author in: * NPG journals * PubMed * Google Scholar * Reem Abdwani Search for this author in: * NPG journals * PubMed * Google Scholar * Safiya Al Abrawi Search for this author in: * NPG journals * PubMed * Google Scholar * Fathiya Almurshedi Search for this author in: * NPG journals * PubMed * Google Scholar * Nadia Alhashmi Search for this author in: * NPG journals * PubMed * Google Scholar * Abdullah Al Sonbul Search for this author in: * NPG journals * PubMed * Google Scholar * Wafaa Sewairi Search for this author in: * NPG journals * PubMed * Google Scholar * Aliya Qari Search for this author in: * NPG journals * PubMed * Google Scholar * Eiman Abdallah Search for this author in: * NPG journals * PubMed * Google Scholar * Mohammed Al-Owain Search for this author in: * NPG journals * PubMed * Google Scholar * Saleh Al Motywee Search for this author in: * NPG journals * PubMed * Google Scholar * Hanan Al-Rayes Search for this author in: * NPG journals * PubMed * Google Scholar * Mais Hashem Search for this author in: * NPG journals * PubMed * Google Scholar * Hanif Khalak Search for this author in: * NPG journals * PubMed * Google Scholar * Latifa Al-Jebali Search for this author in: * NPG journals * PubMed * Google Scholar * Fowzan S Alkuraya Contact Fowzan S Alkuraya Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (942K) Supplementary Methods, Supplementary Figures 1–3 and Supplementary Table 1 Additional data
• Mutations in MEGF10, a regulator of satellite cell myogenesis, cause early onset myopathy, areflexia, respiratory distress and dysphagia (EMARDD)
  - Nat Genet 43(12):1189-1192 (2011)
  Nature Genetics | Brief Communication Mutations in MEGF10, a regulator of satellite cell myogenesis, cause early onset myopathy, areflexia, respiratory distress and dysphagia (EMARDD) * Clare V Logan1, 8 * Barbara Lucke2, 8 * Caroline Pottinger3, 8 * Zakia A Abdelhamed1, 4 * David A Parry1 * Katarzyna Szymanska1 * Christine P Diggle1 * Anne van Riesen2 * Joanne E Morgan1 * Grace Markham1 * Ian Ellis5 * Adnan Y Manzur6 * Alexander F Markham1 * Mike Shires1 * Tim Helliwell7 * Mariacristina Scoto6 * Christoph Hübner2 * David T Bonthron1 * Graham R Taylor1 * Eamonn Sheridan1 * Francesco Muntoni6 * Ian M Carr1 * Markus Schuelke2, 9 * Colin A Johnson1, 9 * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:1189–1192Year published:(2011)DOI:doi:10.1038/ng.995Received11 July 2011Accepted05 October 2011Published online20 November 2011 Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Infantile myopathies with diaphragmatic paralysis are genetically heterogeneous, and clinical symptoms do not assist in differentiating between them. We used phased haplotype analysis with subsequent targeted exome sequencing to identify MEGF10 mutations in a previously unidentified type of infantile myopathy with diaphragmatic weakness, areflexia, respiratory distress and dysphagia. MEGF10 is highly expressed in activated satellite cells and regulates their proliferation as well as their differentiation and fusion into multinucleated myofibers, which are greatly reduced in muscle from individuals with early onset myopathy, areflexia, respiratory distress and dysphagia. View full text Accession codes * Accession codes * Author information * Supplementary information Referenced accessions GenBank * NM_032446.2 * NP_115822.1 Author information * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Clare V Logan, * Barbara Lucke & * Caroline Pottinger Affiliations * Leeds Institute of Molecular Medicine, The University of Leeds, Leeds, UK. * Clare V Logan, * Zakia A Abdelhamed, * David A Parry, * Katarzyna Szymanska, * Christine P Diggle, * Joanne E Morgan, * Grace Markham, * Alexander F Markham, * Mike Shires, * David T Bonthron, * Graham R Taylor, * Eamonn Sheridan, * Ian M Carr & * Colin A Johnson * Department of Neuropediatrics and NeuroCure Clinical Research Center, Charité Universitätsmedizin Berlin, Berlin, Germany. * Barbara Lucke, * Anne van Riesen, * Christoph Hübner & * Markus Schuelke * Clinical Genetics Unit, West Midlands Regional Genetics Service, Birmingham Women's Hospital, Birmingham, UK. * Caroline Pottinger * Department of Anatomy and Embryology, Faculty of Medicine (Girls' Section), Al-Azhar University, Cairo, Egypt. * Zakia A Abdelhamed * Department of Clinical Genetics, Alder Hey Children's Hospital, Liverpool, UK. * Ian Ellis * Dubowitz Neuromuscular Centre, Institute of Child Health and Great Ormond Street Hospital for Children, London, UK. * Adnan Y Manzur, * Mariacristina Scoto & * Francesco Muntoni * Royal Liverpool University Hospital, Liverpool, UK. * Tim Helliwell * These authors jointly directed this work. * Markus Schuelke & * Colin A Johnson Contributions K.S., M. Schuelke and I.M.C. performed genetic mapping. C.V.L., B.L., D.A.P., C.P.D., G.M., M. Schuelke and C.A.J. performed mutation analyses in the cohorts of affected individuals. C.V.L., J.E.M., D.A.P. and G.R.T. generated the next-generation sequencing data. C.V.L. and D.A.P. performed the control genotyping. D.A.P., I.M.C., M. Schuelke and G.R.T. analyzed the SNP genotyping and next-generation sequencing data. C.V.L. examined the complementary DNA and protein expression in cell lines from affected individuals. Z.A.A. and M. Shires performed the immunohistochemistry staining experiments. C.P., A.v.R., I.E., A.F.M., T.H., E.S., C.H., F.M., A.Y.M., M. Scoto and M. Schuelke recruited subjects, gathered clinical information and contributed clinical samples. A.F.M., D.T.B., E.S., F.M., I.M.C., C.H., M. Schuelke and C.A.J. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Colin A Johnson or * Markus Schuelke Author Details * Clare V Logan Search for this author in: * NPG journals * PubMed * Google Scholar * Barbara Lucke Search for this author in: * NPG journals * PubMed * Google Scholar * Caroline Pottinger Search for this author in: * NPG journals * PubMed * Google Scholar * Zakia A Abdelhamed Search for this author in: * NPG journals * PubMed * Google Scholar * David A Parry Search for this author in: * NPG journals * PubMed * Google Scholar * Katarzyna Szymanska Search for this author in: * NPG journals * PubMed * Google Scholar * Christine P Diggle Search for this author in: * NPG journals * PubMed * Google Scholar * Anne van Riesen Search for this author in: * NPG journals * PubMed * Google Scholar * Joanne E Morgan Search for this author in: * NPG journals * PubMed * Google Scholar * Grace Markham Search for this author in: * NPG journals * PubMed * Google Scholar * Ian Ellis Search for this author in: * NPG journals * PubMed * Google Scholar * Adnan Y Manzur Search for this author in: * NPG journals * PubMed * Google Scholar * Alexander F Markham Search for this author in: * NPG journals * PubMed * Google Scholar * Mike Shires Search for this author in: * NPG journals * PubMed * Google Scholar * Tim Helliwell Search for this author in: * NPG journals * PubMed * Google Scholar * Mariacristina Scoto Search for this author in: * NPG journals * PubMed * Google Scholar * Christoph Hübner Search for this author in: * NPG journals * PubMed * Google Scholar * David T Bonthron Search for this author in: * NPG journals * PubMed * Google Scholar * Graham R Taylor Search for this author in: * NPG journals * PubMed * Google Scholar * Eamonn Sheridan Search for this author in: * NPG journals * PubMed * Google Scholar * Francesco Muntoni Search for this author in: * NPG journals * PubMed * Google Scholar * Ian M Carr Search for this author in: * NPG journals * PubMed * Google Scholar * Markus Schuelke Contact Markus Schuelke Search for this author in: * NPG journals * PubMed * Google Scholar * Colin A Johnson Contact Colin A Johnson Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–5, Supplementary Tables 1 and 2, Supplementary Methods and Supplementary Note. Additional data
• Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease
  - Nat Genet 43(12):1193-1201 (2011)
  Nature Genetics | Article Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease * Gosia Trynka1, 36 * Karen A Hunt2, 36 * Nicholas A Bockett2 * Jihane Romanos1 * Vanisha Mistry2 * Agata Szperl1 * Sjoerd F Bakker3 * Maria Teresa Bardella4, 5 * Leena Bhaw-Rosun6 * Gemma Castillejo7 * Emilio G de la Concha8 * Rodrigo Coutinho de Almeida1 * Kerith-Rae M Dias6 * Cleo C van Diemen1 * Patrick C A Dubois2 * Richard H Duerr9, 10 * Sarah Edkins11 * Lude Franke1 * Karin Fransen1, 12 * Javier Gutierrez1 * Graham A R Heap2 * Barbara Hrdlickova1 * Sarah Hunt11 * Leticia Plaza Izurieta13 * Valentina Izzo14 * Leo A B Joosten15, 16 * Cordelia Langford11 * Maria Cristina Mazzilli17 * Charles A Mein6 * Vandana Midah18 * Mitja Mitrovic1, 19 * Barbara Mora17 * Marinita Morelli14 * Sarah Nutland20 * Concepción Núñez8 * Suna Onengut-Gumuscu21 * Kerra Pearce22 * Mathieu Platteel1 * Isabel Polanco23 * Simon Potter11 * Carmen Ribes-Koninckx24 * Isis Ricaño-Ponce1 * Stephen S Rich21 * Anna Rybak25 * José Luis Santiago8 * Sabyasachi Senapati26 * Ajit Sood18 * Hania Szajewska27 * Riccardo Troncone28 * Jezabel Varadé8 * Chris Wallace20 * Victorien M Wolters29 * Alexandra Zhernakova30 * Spanish Consortium on the Genetics of Coeliac Disease (CEGEC) * PreventCD Study Group * Wellcome Trust Case Control Consortium (WTCCC) * B K Thelma26 * Bozena Cukrowska32 * Elena Urcelay8 * Jose Ramon Bilbao13 * M Luisa Mearin33 * Donatella Barisani34 * Jeffrey C Barrett11 * Vincent Plagnol35 * Panos Deloukas11 * Cisca Wijmenga1, 37 * David A van Heel2, 37 * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:1193–1201Year published:(2011)DOI:doi:10.1038/ng.998Received15 April 2011Accepted05 October 2011Published online06 November 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Using variants from the 1000 Genomes Project pilot European CEU dataset and data from additional resequencing studies, we densely genotyped 183 non-HLA risk loci previously associated with immune-mediated diseases in 12,041 individuals with celiac disease (cases) and 12,228 controls. We identified 13 new celiac disease risk loci reaching genome-wide significance, bringing the number of known loci (including the HLA locus) to 40. We found multiple independent association signals at over one-third of these loci, a finding that is attributable to a combination of common, low-frequency and rare genetic variants. Compared to previously available data such as those from HapMap3, our dense genotyping in a large sample collection provided a higher resolution of the pattern of linkage disequilibrium and suggested localization of many signals to finer scale regions. In particular, 29 of the 54 fine-mapped signals seemed to be localized to single genes and, in some instances, to gene r! egulatory elements. Altogether, we define the complex genetic architecture of the risk regions of and refine the risk signals for celiac disease, providing the next step toward uncovering the causal mechanisms of the disease. View full text Figures at a glance * Figure 1: Manhattan plot of association statistics for previously known and newly discovered celiac disease risk loci. Newly discovered loci are indicated in blue; loci with multiple signals are shown in a gray highlighted box. The significance threshold used was P = 5 × 10−8. * Figure 2: Loci with multiple independent signals. (–) Non-conditioned P values are shown for loci with multiple independent signals (Table 2). The most strongly associated variant for a given signal is shown in bold, and further variants with r2 > 0.90 (calculated from the 24,269-sample Immunochip dataset) are shown with normal weight. At each locus, the first signal is shown in blue, second is shown in red and third is shown in green. Squares indicate markers present in our previous celiac disease GWAS dataset after applying quality control filters (Illumina Hap550)5. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Gosia Trynka & * Karen A Hunt Affiliations * Genetics Department, University Medical Center and University of Groningen, Groningen, The Netherlands. * Gosia Trynka, * Jihane Romanos, * Agata Szperl, * Rodrigo Coutinho de Almeida, * Cleo C van Diemen, * Lude Franke, * Karin Fransen, * Javier Gutierrez, * Barbara Hrdlickova, * Mitja Mitrovic, * Mathieu Platteel, * Isis Ricaño-Ponce & * Cisca Wijmenga * Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK. * Karen A Hunt, * Nicholas A Bockett, * Vanisha Mistry, * Patrick C A Dubois, * Graham A R Heap & * David A van Heel * Department of Gastroenterology, Vrije Universiteit (VU) Medical Center, Amsterdam, The Netherlands. * Sjoerd F Bakker * Fondazione Istituto Di Ricovero e Cura a Carattere Scientifico (IRCCS) Ospedale Maggiore Policlinico, Mangiagalli e Regina Elena, Milan, Italy. * Maria Teresa Bardella * Department of Medical Sciences, University of Milan, Milan, Italy. * Maria Teresa Bardella * Genome Centre, Barts and the London School of Medicine and Dentistry, John Vane Science Centre, Charterhouse Square, London, UK. * Leena Bhaw-Rosun, * Kerith-Rae M Dias & * Charles A Mein * Universitat Rovira I Virgili, Department of Paediatric Gastroenterology, Hospital Univesitari de Sant Joan de Reus, Reus, Spain. * Gemma Castillejo * Immunology Department, Hospital Clínico S. Carlos, Instituto de Investigación Sanitaria San Carlos (IdISSC), Madrid, Spain. * Emilio G de la Concha, * Concepción Núñez, * José Luis Santiago, * Jezabel Varadé & * Elena Urcelay * Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA. * Richard H Duerr * Department of Human Genetics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania, USA. * Richard H Duerr * Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. * Sarah Edkins, * Sarah Hunt, * Cordelia Langford, * Simon Potter, * Jeffrey C Barrett & * Panos Deloukas * Department of Gastroenterology, University Medical Center and Groningen University, Groningen, The Netherlands. * Karin Fransen * Immunogenetics Research Laboratory, Hospital de Cruces, Barakaldo, Bizkaia, Spain. * Leticia Plaza Izurieta & * Jose Ramon Bilbao * European Laboratory for Food Induced Disease, University of Naples Federico II, Naples, Italy. * Valentina Izzo & * Marinita Morelli * Department of Medicine, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. * Leo A B Joosten * Nijmegen Institute for Infection, Inflammation and Immunity (N4i), Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. * Leo A B Joosten * Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy. * Maria Cristina Mazzilli & * Barbara Mora * Dayanand Medical College and Hospital, Ludhiana, Punjab, India. * Vandana Midah & * Ajit Sood * University of Maribor, Faculty of Medicine, Center for Human Molecular Genetics and Pharmacogenomics, Maribor, Slovenia. * Mitja Mitrovic * Juvenile Diabetes Research Foundation, Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK. * Sarah Nutland & * Chris Wallace * Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA. * Suna Onengut-Gumuscu & * Stephen S Rich * University College London Genomics, Institute of Child Health, University College London, London, UK. * Kerra Pearce * Pediatrics Gastroenterology Department, Hospital La Paz, Madrid, Spain. * Isabel Polanco * Pediatric Gastroenterology Department, La Fe University Hospital, Valencia, Spain. * Carmen Ribes-Koninckx * Department of Gastroenterology, Hepatology and Immunology, Children's Memorial Health Institute, Warsaw, Poland. * Anna Rybak * Department of Genetics, University of Delhi, South Campus, New Delhi, India. * Sabyasachi Senapati & * B K Thelma * Department of Pediatrics, The Medical University of Warsaw, Warsaw, Poland. * Hania Szajewska * Department of Pediatrics, University of Naples Federico II, Naples, Italy. * Riccardo Troncone * Department of Paediatric Gastroenterology, University Medical Centre Utrecht, Utrecht, The Netherlands. * Victorien M Wolters * Department of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands. * Alexandra Zhernakova * Department of Pathology, Children's Memorial Health Institute, Warsaw, Poland. * Bozena Cukrowska * Department of Paediatrics, Leiden University Medical Centre, Leiden, The Netherlands. * M Luisa Mearin * Department of Experimental Medicine, Faculty of Medicine, University of Milano-Bicocca, Monza, Italy. * Donatella Barisani * University College London Genetics Institute, University College London, London, UK. * Vincent Plagnol * These authors jointly directed this work. * Cisca Wijmenga & * David A van Heel Consortia * Spanish Consortium on the Genetics of Coeliac Disease (CEGEC) * PreventCD Study Group * Wellcome Trust Case Control Consortium (WTCCC) Contributions D.A.v.H. and C. Wijmenga led the study. D.A.v.H., K.A.H., G.T. and C. Wijmenga wrote the paper. K.A.H., G.T., V.Mistry, N.A.B., J.R., M.P., M.Mitrovic, R.H.D. and K.F. performed DNA sample preparation and genotyping assays. D.A.v.H., V.P., K.A.H. and G.T. performed the statistical analysis. All other authors contributed primarily to the sample collection and phenotyping. P.D. led the formation of the Immunochip Consortium, and SNP selection was performed by J.C.B. and C. Wallace. All authors reviewed the final manuscript. A full list of members is provided in the Supplementary Note. Spanish Consortium on the Genetics of Coeliac Disease (CEGEC) PreventCD Study Group Wellcome Trust Case Control Consortium (WTCCC) Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * David A van Heel or * Cisca Wijmenga Author Details * Gosia Trynka Search for this author in: * NPG journals * PubMed * Google Scholar * Karen A Hunt Search for this author in: * NPG journals * PubMed * Google Scholar * Nicholas A Bockett Search for this author in: * NPG journals * PubMed * Google Scholar * Jihane Romanos Search for this author in: * NPG journals * PubMed * Google Scholar * Vanisha Mistry Search for this author in: * NPG journals * PubMed * Google Scholar * Agata Szperl Search for this author in: * NPG journals * PubMed * Google Scholar * Sjoerd F Bakker Search for this author in: * NPG journals * PubMed * Google Scholar * Maria Teresa Bardella Search for this author in: * NPG journals * PubMed * Google Scholar * Leena Bhaw-Rosun Search for this author in: * NPG journals * PubMed * Google Scholar * Gemma Castillejo Search for this author in: * NPG journals * PubMed * Google Scholar * Emilio G de la Concha Search for this author in: * NPG journals * PubMed * Google Scholar * Rodrigo Coutinho de Almeida Search for this author in: * NPG journals * PubMed * Google Scholar * Kerith-Rae M Dias Search for this author in: * NPG journals * PubMed * Google Scholar * Cleo C van Diemen Search for this author in: * NPG journals * PubMed * Google Scholar * Patrick C A Dubois Search for this author in: * NPG journals * PubMed * Google Scholar * Richard H Duerr Search for this author in: * NPG journals * PubMed * Google Scholar * Sarah Edkins Search for this author in: * NPG journals * PubMed * Google Scholar * Lude Franke Search for this author in: * NPG journals * PubMed * Google Scholar * Karin Fransen Search for this author in: * NPG journals * PubMed * Google Scholar * Javier Gutierrez Search for this author in: * NPG journals * PubMed * Google Scholar * Graham A R Heap Search for this author in: * NPG journals * PubMed * Google Scholar * Barbara Hrdlickova Search for this author in: * NPG journals * PubMed * 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author in: * NPG journals * PubMed * Google Scholar * Concepción Núñez Search for this author in: * NPG journals * PubMed * Google Scholar * Suna Onengut-Gumuscu Search for this author in: * NPG journals * PubMed * Google Scholar * Kerra Pearce Search for this author in: * NPG journals * PubMed * Google Scholar * Mathieu Platteel Search for this author in: * NPG journals * PubMed * Google Scholar * Isabel Polanco Search for this author in: * NPG journals * PubMed * Google Scholar * Simon Potter Search for this author in: * NPG journals * PubMed * Google Scholar * Carmen Ribes-Koninckx Search for this author in: * NPG journals * PubMed * Google Scholar * Isis Ricaño-Ponce Search for this author in: * NPG journals * PubMed * Google Scholar * Stephen S Rich Search for this author in: * NPG journals * PubMed * Google Scholar * Anna Rybak Search for this author in: * NPG journals * PubMed * Google Scholar * José Luis Santiago Search for this author in: * NPG journals * PubMed * Google Scholar * Sabyasachi Senapati Search for this author in: * NPG journals * PubMed * Google Scholar * Ajit Sood Search for this author in: * NPG journals * PubMed * Google Scholar * Hania Szajewska Search for this author in: * NPG journals * PubMed * Google Scholar * Riccardo Troncone Search for this author in: * NPG journals * PubMed * Google Scholar * Jezabel Varadé Search for this author in: * NPG journals * PubMed * Google Scholar * Chris Wallace Search for this author in: * NPG journals * PubMed * Google Scholar * Victorien M Wolters Search for this author in: * NPG journals * PubMed * Google Scholar * Alexandra Zhernakova Search for this author in: * NPG journals * PubMed * Google Scholar * Spanish Consortium on the Genetics of Coeliac Disease (CEGEC) * PreventCD Study Group * Wellcome Trust Case Control Consortium (WTCCC) * B K Thelma Search for this author in: * NPG journals * PubMed * Google Scholar * Bozena Cukrowska Search for this author in: * NPG journals * PubMed * Google Scholar * Elena Urcelay Search for this author in: * NPG journals * PubMed * Google Scholar * Jose Ramon Bilbao Search for this author in: * NPG journals * PubMed * Google Scholar * M Luisa Mearin Search for this author in: * NPG journals * PubMed * Google Scholar * Donatella Barisani Search for this author in: * NPG journals * PubMed * Google Scholar * Jeffrey C Barrett Search for this author in: * NPG journals * PubMed * Google Scholar * Vincent Plagnol Search for this author in: * NPG journals * PubMed * Google Scholar * Panos Deloukas Search for this author in: * NPG journals * PubMed * Google Scholar * Cisca Wijmenga Contact Cisca Wijmenga Search for this author in: * NPG journals * PubMed * Google Scholar * David A van Heel Contact David A van Heel Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (6M) Supplementary Note, Supplementary Tables 3 and 5 and Supplementary Figures 1 and 2. Excel files * Supplementary Table 1 (61K) Comparison of risk signals reported in our 2010 celiac disease GWAS versus the current Immunochip dataset * Supplementary Table 2 (78K) Functional annotation of identified risk variants and strongly correlated (r2 > 0.9) variants * Supplementary Table 4 (37K) Genotype count and allele frequency data by sample collection and affection status Additional data
• Insertional mutagenesis identifies multiple networks of cooperating genes driving intestinal tumorigenesis
  - Nat Genet 43(12):1202-1209 (2011)
  Nature Genetics | Article Insertional mutagenesis identifies multiple networks of cooperating genes driving intestinal tumorigenesis * H Nikki March1 * Alistair G Rust2 * Nicholas A Wright3 * Jelle ten Hoeve4 * Jeroen de Ridder4, 5 * Matthew Eldridge1 * Louise van der Weyden2 * Anton Berns6 * Jules Gadiot6 * Anthony Uren6 * Richard Kemp1 * Mark J Arends7 * Lodewyk F A Wessels4, 5 * Douglas J Winton1 * David J Adams2 * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:1202–1209Year published:(2011)DOI:doi:10.1038/ng.990Received28 January 2011Accepted03 October 2011Published online06 November 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The evolution of colorectal cancer suggests the involvement of many genes. To identify new drivers of intestinal cancer, we performed insertional mutagenesis using the Sleeping Beauty transposon system in mice carrying germline or somatic Apc mutations. By analyzing common insertion sites (CISs) isolated from 446 tumors, we identified many hundreds of candidate cancer drivers. Comparison to human data sets suggested that 234 CIS-targeted genes are also dysregulated in human colorectal cancers. In addition, we found 183 CIS-containing genes that are candidate Wnt targets and showed that 20 CISs-containing genes are newly discovered modifiers of canonical Wnt signaling. We also identified mutations associated with a subset of tumors containing an expanded number of Paneth cells, a hallmark of deregulated Wnt signaling, and genes associated with more severe dysplasia included those encoding members of the FGF signaling cascade. Some 70 genes had co-occurrence of CIS pairs, clus! tering into 38 sub-networks that may regulate tumor development. View full text Figures at a glance * Figure 1: Sleeping Beauty transposon mobilization increases morbidity and tumor burden of Apc-deficient mice. () Kaplan-Meier survival curve comparing Apcfl/+ experimental (Ah-Cre; Apcfl/+;Rosa26Lox66SBLox71/+;T2/Onc+/−, black line) and control mice (Ah-Cre+/−; Apcfl/+; T2/Onc and Ah-Cre+/−; Apcfl/+;Rosa26Lox66SBLox71/+, gray line) (log-rank P < 0.001). () Kaplan-Meier survival curve comparing Apcmin/+ experimental (Apcmin/+; RosaSB/+; T2/Onc, black line), Apcmin/+ control mice (Apcmin/+; RosaSB/+ and Apcmin/+; T2/Onc, gray line) and RosaSB/+; T2/Onc control mice (green line) (log-rank P < 0.0057). () Average polyp size and number in Apcfl/+ experimental mice (N = 3) and matched littermate Apcfl/+ control mice (N = 3) at 18 weeks postinduction. All polyps visible under the dissecting microscope at 6× magnification were counted and grouped into those that were non-excisable (black bars, <3 mm) and those that could be excised for further analysis (gray bars, >3 mm). Average polyp number for the small intestine, cecum and colon is shown. () Average number of excisable polyps (>3! mm) from the small intestine, cecum and colon of Apcmin/+ experimental mice (N = 10) and Apcmin/+ control mice (N = 7) at 10–22 and 17–30 weeks of age, respectively. Error bars in and show s.e.m. (–) β-catenin immunohistochemistry (top) and hematoxylin and eosin staining (bottom) of representative tissue from Apcfl/+ mice showing a tubulovillous adenoma at 18 weeks postinduction (), an adenoma at 28 weeks postinduction () and an adenoma at 17 weeks postinduction (), with the arrow indicating the region of adenocarcinoma in the submucosa. () Lysozyme staining of representative tissue from an Apcfl/+ mouse at 22 weeks postinduction, with the arrow indicating Paneth cell differentiation. All scale bars = 100 μm. * Figure 2: Comparison of Sleeping Beauty insertions in the K-Ras, p53 and TGFβ signaling pathways. Genes that encode pathway components immediately up- or downstream of K-Ras, p53 or Smad4 were identified and analyzed for the occurrence of transposon insertions. The percentages of tumors with insertions in these genes are indicated in italics. Percentages in bold show the overall proportion of tumors with insertions in each pathway. * Figure 3: Cross-species comparison implicates CISs irrespective of rank position. () Human colorectal cancer data sets implicate up to 234 CIS-targeted genes. A, the proteins encoded by CIS-containing genes (46) matching gene products found to be up- or downregulated in a comparison of nuclear matrix fractions from human adenomas and adenocarcinomas (Supplementary Table 14)56. B, orthologs of CIS-containing genes (43) identified through exon resequencing of human colorectal tumors, 13 of which were highlighted as potential drivers by the authors (P = 0.003) (Supplementary Table 13)47. C, orthologs of CIS-containing genes (35) reported in the Catalogue of Somatic Mutations in Cancer (COSMIC)57 as harboring mutations in human sporadic CRCs (Supplementary Table 12). D, orthologs of CIS-containing genes (154) found in deleted or amplified regions in 123 human sporadic CRCs through array-CGH analysis (Q < 25%; P = 0.025) (Supplementary Tables 10 and 11)44. Genes shown in black are orthologs of CIS-containing genes that overlap in two or more data sets. () Dist! ribution of orthologs for CIS-containing genes in the 30-kb GKC analysis. Genes are shown in rank order according to the percentage of tumors containing a given CIS (and then by height of the CIS peak). Some genes, such as Mll3, contain two CIS regions and are therefore shown twice. Genes in bold indicate well-known CRC-associated genes. * Figure 4: Identification of new Wnt targets with tumorigenic potential. Potential regulators of Wnt signaling were identified by analysis with TRANSFAC 2009.3. The resulting candidate genes were then cross-referenced with CIS-containing genes that corresponded to orthologs identified in the array-CGH analysis of human sporadic CRCs44 to generate a final set of CIS-containing genes for further study. SW480 cells containing a stably integrated β-lactamase reporter gene under the control of the LEF and TCF consensus binding sequence were transiently transfected with siRNA (final concentration of 20 nM) and processed after 72 h. Fluorescence resonance energy transfer (FRET) analysis was performed, and the fold change represented in the graph was calculated relative to the GC control. Error bars show s.d, N = 4. Data were pooled from three independent experiments to determine statistical significance by the Student's t test (*P < 0.05, **P < 0.01, ***P < 0.001). * Figure 5: Co-occurring CISs can be grouped into interacting networks. CISs generated from the 30-kb and 120-kb GKC analyses were merged, and pairwise comparisons between each CIS were performed. Contingency tables were constructed for each comparison, and a Fisher's exact test was performed. To account for multiple testing, a Q value was generated for each test and adjusted P values of P < 0.05 were reported. This analysis generated 70 coordinate relationships in 38 networks, 3 of which are shown. CISs are represented by the nearest associated gene, and the thickness of each interconnecting line between two genes represents the level of significance of the co-occurrence. Author information * Abstract * Author information * Supplementary information Affiliations * Cancer Research UK Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK. * H Nikki March, * Matthew Eldridge, * Richard Kemp & * Douglas J Winton * Experimental Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. * Alistair G Rust, * Louise van der Weyden & * David J Adams * Histopathology Unit, London Research Institute, Cancer Research UK, London, UK. * Nicholas A Wright * Bioinformatics and Statistics Group, Netherlands Cancer Institute, Amsterdam, The Netherlands. * Jelle ten Hoeve, * Jeroen de Ridder & * Lodewyk F A Wessels * Delft Bioinformatics Laboratory, Delft University of Technology, Delft, The Netherlands. * Jeroen de Ridder & * Lodewyk F A Wessels * Division of Molecular Genetics, Netherlands Cancer Institute, Amsterdam, The Netherlands. * Anton Berns, * Jules Gadiot & * Anthony Uren * Department of Pathology, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK. * Mark J Arends Contributions H.N.M. performed the majority of the experiments. D.J.W., L.v.d.W. and R.K. assisted with sample processing and analysis of transposon mobilization. A.G.R., J.t.H., J.d.R., L.F.A.W. and M.E. performed data analysis and algorithm development. A.U., J.G. and A.B. provided targeted embryonic stem cells carrying the conditional Sleeping Beauty transposon allele. N.A.W. performed the majority of the histopathological analysis with assistance from M.J.A. The study was jointly designed and supervised by D.J.W. and D.J.A., who contributed to some of the experiments. H.N.M., D.J.W. and D.J.A. wrote the paper with input from some of the other authors. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Douglas J Winton Author Details * H Nikki March Search for this author in: * NPG journals * PubMed * Google Scholar * Alistair G Rust Search for this author in: * NPG journals * PubMed * Google Scholar * Nicholas A Wright Search for this author in: * NPG journals * PubMed * Google Scholar * Jelle ten Hoeve Search for this author in: * NPG journals * PubMed * Google Scholar * Jeroen de Ridder Search for this author in: * NPG journals * PubMed * Google Scholar * Matthew Eldridge Search for this author in: * NPG journals * PubMed * Google Scholar * Louise van der Weyden Search for this author in: * NPG journals * PubMed * Google Scholar * Anton Berns Search for this author in: * NPG journals * PubMed * Google Scholar * Jules Gadiot Search for this author in: * NPG journals * PubMed * Google Scholar * Anthony Uren Search for this author in: * NPG journals * PubMed * Google Scholar * Richard Kemp Search for this author in: * NPG journals * PubMed * Google Scholar * Mark J Arends Search for this author in: * NPG journals * PubMed * Google Scholar * Lodewyk F A Wessels Search for this author in: * NPG journals * PubMed * Google Scholar * Douglas J Winton Contact Douglas J Winton Search for this author in: * NPG journals * PubMed * Google Scholar * David J Adams Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Note, Supplementary Figures 1–12, and Supplementary Tables 1, 3, 4, 6–19 and 21. Excel files * Supplementary Table 2 (3M) Catalog of CIS regions * Supplementary Table 5 (4M) Catalog of tumor by gene insertions * Supplementary Table 20 (136K) Firestein Wnt candidates Text files * Supplementary Data 1 (10M) Transposon insertion site data file * Supplementary Data 2 (25M) 30 kb kernel convolution CIS data file * Supplementary Data 3 (6M) 120 kb kernel convolution CIS data file * Supplementary Data 4 (124K) Merged 30kb and 120kb kernel convolution CIS data file * Supplementary Data 5 (4M) Monte Carlo peaks and regions data file Additional data
• A common variant at the TERT-CLPTM1L locus is associated with estrogen receptor–negative breast cancer
  - Nat Genet 43(12):1210-1214 (2011)
  Nature Genetics | Letter A common variant at the TERT-CLPTM1L locus is associated with estrogen receptor–negative breast cancer * Christopher A Haiman1 * Gary K Chen1 * Celine M Vachon2 * Federico Canzian3 * Alison Dunning4 * Robert C Millikan5 * Xianshu Wang6 * Foluso Ademuyiwa7 * Shahana Ahmed4 * Christine B Ambrosone8 * Laura Baglietto9 * Rosemary Balleine10 * Elisa V Bandera11 * Matthias W Beckmann12 * Christine D Berg13 * Leslie Bernstein14 * Carl Blomqvist15 * William J Blot16, 17 * Hiltrud Brauch18, 19 * Julie E Buring20 * Lisa A Carey21 * Jane E Carpenter22 * Jenny Chang-Claude23 * Stephen J Chanock24 * Daniel I Chasman20 * Christine L Clarke22 * Angela Cox25 * Simon S Cross26 * Sandra L Deming16 * Robert B Diasio27 * Athanasios M Dimopoulos28 * W Ryan Driver29 * Thomas Dünnebier30 * Lorraine Durcan31 * Diana Eccles31 * Christopher K Edlund1 * Arif B Ekici32 * Peter A Fasching12, 33 * Heather S Feigelson34 * Dieter Flesch-Janys35 * Florentia Fostira36 * Asta Försti37, 38 * George Fountzilas39 * Susan M Gerty31 * The Gene Environment Interaction and Breast Cancer in Germany (GENICA) Consortium * Graham G Giles9 * Andrew K Godwin41 * Paul Goodfellow42 * Nikki Graham31 * Dario Greco43 * Ute Hamann30 * Susan E Hankinson44, 45 * Arndt Hartmann46 * Rebecca Hein23 * Judith Heinz35 * Andrea Holbrook1 * Robert N Hoover24 * Jennifer J Hu47 * David J Hunter45, 48 * Sue A Ingles1 * Astrid Irwanto49 * Jennifer Ivanovich42 * Esther M John50, 51 * Nicola Johnson52 * Arja Jukkola-Vuorinen53 * Rudolf Kaaks54 * Yon-Dschun Ko55 * Laurence N Kolonel56 * Irene Konstantopoulou36 * Veli-Matti Kosma57 * Swati Kulkarni58 * Diether Lambrechts59, 60 * Adam M Lee27 * Loïc Le Marchand56 * Timothy Lesnick2 * Jianjun Liu49 * Sara Lindstrom45, 48 * Arto Mannermaa61, 62 * Sara Margolin63 * Nicholas G Martin64 * Penelope Miron65 * Grant W Montgomery64 * Heli Nevanlinna43 * Stephan Nickels23 * Sarah Nyante5 * Curtis Olswold2 * Julie Palmer66 * Harsh Pathak67 * Dimitrios Pectasides68 * Charles M Perou69 * Julian Peto70 * Paul D P Pharoah4 * Loreall C Pooler1 * Michael F Press71 * Katri Pylkäs72 * Timothy R Rebbeck73 * Jorge L Rodriguez-Gil47 * Lynn Rosenberg66 * Eric Ross74 * Thomas Rüdiger75 * Isabel dos Santos Silva70 * Elinor Sawyer76 * Marjanka K Schmidt77 * Rüdiger Schulz-Wendtland46 * Fredrick Schumacher1 * Gianluca Severi9 * Xin Sheng1 * Lisa B Signorello16, 17 * Hans-Peter Sinn78 * Kristen N Stevens2 * Melissa C Southey79 * William J Tapper31 * Ian Tomlinson80 * Frans B L Hogervorst81 * Els Wauters59, 60 * JoEllen Weaver67 * Hans Wildiers82 * Robert Winqvist72 * David Van Den Berg1 * Peggy Wan1 * Lucy Y Xia1 * Drakoulis Yannoukakos36 * Wei Zheng16 * Regina G Ziegler24 * Afshan Siddiq83 * Susan L Slager2 * Daniel O Stram1 * Douglas Easton4 * Peter Kraft45, 48, 84 * Brian E Henderson1 * Fergus J Couch2, 6 * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:1210–1214Year published:(2011)DOI:doi:10.1038/ng.985Received03 May 2011Accepted28 September 2011Published online30 October 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Estrogen receptor (ER)-negative breast cancer shows a higher incidence in women of African ancestry compared to women of European ancestry. In search of common risk alleles for ER-negative breast cancer, we combined genome-wide association study (GWAS) data from women of African ancestry (1,004 ER-negative cases and 2,745 controls) and European ancestry (1,718 ER-negative cases and 3,670 controls), with replication testing conducted in an additional 2,292 ER-negative cases and 16,901 controls of European ancestry. We identified a common risk variant for ER-negative breast cancer at the TERT-CLPTM1L locus on chromosome 5p15 (rs10069690: per-allele odds ratio (OR) = 1.18 per allele, P = 1.0 × 10−10). The variant was also significantly associated with triple-negative (ER-negative, progesterone receptor (PR)-negative and human epidermal growth factor-2 (HER2)-negative) breast cancer (OR = 1.25, P = 1.1 × 10−9), particularly in younger women (<50 years of age) (OR = 1.48, P! = 1.9 × 10−9). Our results identify a genetic locus associated with estrogen receptor negative breast cancer subtypes in multiple populations. View full text Author information * Author information * Supplementary information Affiliations * Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, California, USA. * Christopher A Haiman, * Gary K Chen, * Christopher K Edlund, * Andrea Holbrook, * Sue A Ingles, * Loreall C Pooler, * Fredrick Schumacher, * Xin Sheng, * David Van Den Berg, * Peggy Wan, * Lucy Y Xia, * Daniel O Stram & * Brian E Henderson * Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA. * Celine M Vachon, * Timothy Lesnick, * Curtis Olswold, * Kristen N Stevens, * Susan L Slager & * Fergus J Couch * Genomic Epidemiology Group, DKFZ, Heidelberg, Germany. * Federico Canzian * Centre for Cancer Genetic Epidemiology, Strangeways Laboratory, Worts Causeway, Cambridge, UK. * Alison Dunning, * Shahana Ahmed, * Paul D P Pharoah & * Douglas Easton * Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, USA. * Robert C Millikan & * Sarah Nyante * Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA. * Xianshu Wang & * Fergus J Couch * Department of Medicine, Roswell Park Cancer Institute, Buffalo, New York, USA. * Foluso Ademuyiwa * Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, New York, USA. * Christine B Ambrosone * Cancer Epidemiology Centre, The Cancer Council Victoria & Centre for Molecular, Environmental, Genetic, and Analytic Epidemiology, The University of Melbourne, Victoria, Australia. * Laura Baglietto, * Graham G Giles & * Gianluca Severi * Department of Translational Oncology, Westmead Hospital, Western Sydney Local Health Network, Westmead, New South Wales, Australia. * Rosemary Balleine * The Cancer Institute of New Jersey, New Brunswick, New Jersey, USA. * Elisa V Bandera * Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany. * Matthias W Beckmann & * Peter A Fasching * Division of Cancer Prevention, National Cancer Institute, US National Institutes of Health, Bethesda, Maryland, USA. * Christine D Berg * Division of Cancer Etiology, Department of Population Science, Beckman Research Institute, City of Hope, California, USA. * Leslie Bernstein * Department of Oncology, Helsinki University Central Hospital, Helsinki, Finland. * Carl Blomqvist * Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA. * William J Blot, * Sandra L Deming, * Lisa B Signorello & * Wei Zheng * International Epidemiology Institute, Rockville, Maryland, USA. * William J Blot & * Lisa B Signorello * Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany. * Hiltrud Brauch * University of Tübingen, Tübingen, Germany. * Hiltrud Brauch * Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA. * Julie E Buring & * Daniel I Chasman * Department of Medicine, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, USA. * Lisa A Carey * Australian Breast Cancer Tissue Bank, University of Sydney at the Westmead Millennium Institute, Westmead, New South Wales, Australia. * Jane E Carpenter & * Christine L Clarke * Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany. * Jenny Chang-Claude, * Rebecca Hein & * Stephan Nickels * Division of Cancer Epidemiology and Genetics, National Cancer Institute, US National Institutes of Health, Bethesda, Maryland, USA. * Stephen J Chanock, * Robert N Hoover & * Regina G Ziegler * Institute for Cancer Studies, Department of Oncology, Faculty of Medicine, Dentistry & Health, University of Sheffield, Sheffield, UK. * Angela Cox * Academic Unit of Pathology, Department of Neuroscience, Faculty of Medicine, Dentistry & Health, University of Sheffield, Sheffield, UK. * Simon S Cross * Department of Pharmacology, Mayo Clinic, Rochester, Minnesota, USA. * Robert B Diasio & * Adam M Lee * Department of Clinical Therapeutics, "Alexandra" Hospital, University of Athens School of Medicine, Athens, Greece. * Athanasios M Dimopoulos * Epidemiology Research Program, American Cancer Society, Atlanta, Georgia, USA. * W Ryan Driver * Molecular Genetics of Breast Cancer, DKFZ, Heidelberg, Germany. * Thomas Dünnebier & * Ute Hamann * Wessex Clinical Genetics Service, Princess Anne Hospital, Southampton, UK. * Lorraine Durcan, * Diana Eccles, * Susan M Gerty, * Nikki Graham & * William J Tapper * Institute of Human Genetics, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany. * Arif B Ekici * Department of Medicine, Division of Hematology and Oncology, David Geffen School of Medicine, University of California–Los Angeles, Los Angeles, California, USA. * Peter A Fasching * Kaiser Permanente Colorado, Denver, Colorado, USA. * Heather S Feigelson * Institute for Medical Biometrics and Epidemiology, University Clinic Hamburg-Eppendorf, Hamburg, Germany. * Dieter Flesch-Janys & * Judith Heinz * Molecular Diagnostics Laboratory Institute of Radioisotopes and Radiodiagnostic Products, National Centre for Scientific Research "Demokritos", Athens, Greece. * Florentia Fostira, * Irene Konstantopoulou & * Drakoulis Yannoukakos * Division of Molecular Genetic Epidemiology, DKFZ, Heidelberg, Germany. * Asta Försti * Center for Primary Health Care Research, University of Lund, Malmö, Sweden. * Asta Försti * Department of Medical Oncology, Aristotle University of Thessaloniki, Papageorgiou Hospital, Thessaloniki, Greece. * George Fountzilas * Department of Pathology and Laboratory Medicine, Kansas University Medical Center, Lawrence, Kansas, USA. * Andrew K Godwin * Washington University School of Medicine, Barnes-Jewish Hospital and Siteman Cancer Center, St. Louis, Missouri, USA. * Paul Goodfellow & * Jennifer Ivanovich * Department of Obstetrics and Gynecology, Helsinki University Central Hospital, Helsinki, Finland. * Dario Greco & * Heli Nevanlinna * Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA. * Susan E Hankinson * Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA. * Susan E Hankinson, * David J Hunter, * Sara Lindstrom & * Peter Kraft * Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany. * Arndt Hartmann & * Rüdiger Schulz-Wendtland * Sylvester Comprehensive Cancer Center and Department of Epidemiology and Public Health, University of Miami Miller School of Medicine, Miami, Florida, USA. * Jennifer J Hu & * Jorge L Rodriguez-Gil * Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA. * David J Hunter, * Sara Lindstrom & * Peter Kraft * Human Genetics Division, Genome Institute of Singapore, Singapore. * Astrid Irwanto & * Jianjun Liu * Cancer Prevention Institute of California, Fremont, California. * Esther M John * Stanford University School of Medicine and Stanford Cancer Center, Stanford, California, USA. * Esther M John * Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK. * Nicola Johnson * Department of Oncology, Oulu University Hospital, University of Oulu, Oulu, Finland. * Arja Jukkola-Vuorinen * Division of Cancer Epidemiology, DKFZ, Heidelberg, Germany. * Rudolf Kaaks * Department of Internal Medicine, Evangelische Kliniken Johanniter- und Waldkrankenhaus Bonn gGmbH, Bonn, Germany. * Yon-Dschun Ko * Epidemiology Program, Cancer Research Center, University of Hawaii, Honolulu, Hawaii, USA. * Laurence N Kolonel & * Loïc Le Marchand * Department of Pathology, Imaging Centre, Kuopio University Hospital, Kuopio, Finland. * Veli-Matti Kosma * Department of Surgical Oncology, Roswell Park Cancer Institute, Buffalo, New York, USA. * Swati Kulkarni * Vesalius Research Center, Vlaams Instituut voor Biotechnologie, Leuven, Belgium. * Diether Lambrechts & * Els Wauters * Vesalius Research Center, University of Leuven, Leuven, Belgium. * Diether Lambrechts & * Els Wauters * Institute of Clinical Medicine, Department of Pathology, University of Eastern Finland Biocenter Kuopio, Kuopio, Finland. * Arto Mannermaa * Department of Pathology, Imaging Centre, Kuopio University Hospital, Kuopio, Finland. * Arto Mannermaa * Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden. * Sara Margolin * Queensland Institute of Medical Research (QIMR) Genome-Wide Association Study Collective, Brisbane, Queensland, Australia. * Nicholas G Martin & * Grant W Montgomery * Dana-Farber Cancer Institute, Boston, Massachusetts, USA. * Penelope Miron * Slone Epidemiology Center at Boston University, Boston, Massachusetts, USA. * Julie Palmer & * Lynn Rosenberg * Department of Medical Oncology, Fox Chase Cancer Center, Philadelphia, Pennsylvania, USA. * Harsh Pathak & * JoEllen Weaver * Department of Internal Medicine, Oncology Section, "Hippokration" Hospital, Athens, Greece. * Dimitrios Pectasides * Departments of Genetics and Pathology, Lineberger Comprehensive Cancer Center, The University of North Carolina, Chapel Hill, North Carolina, USA. * Charles M Perou * Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK. * Julian Peto & * Isabel dos Santos Silva * Department of Pathology, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California. * Michael F Press * Laboratory of Cancer Genetics, Department of Clinical Genetics and Biocenter Oulu, University of Oulu, Oulu University Hospital, Oulu, Finland. * Katri Pylkäs & * Robert Winqvist * University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA. * Timothy R Rebbeck * Department of Biostatistics, Fox Chase Cancer Center, Philadelphia, Pennsylvania, USA. * Eric Ross * Institute of Pathology, Städtisches Klinikum Karlsruhe, Karlsruhe, Germany. * Thomas Rüdiger * National Institute for Health Research Comprehensive Biomedical Research Centre, Guy's & St. Thomas' National Health Service Foundation Trust, London, UK. * Elinor Sawyer * Division of Experimental Therapy and Molecular Pathology and Division of Epidemiology, Netherlands Cancer Institute–Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands. * Marjanka K Schmidt * Department of Pathology, University Hospital Heidelberg, Heidelberg, Germany. * Hans-Peter Sinn * Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Melbourne, Victoria, Australia. * Melissa C Southey * Wellcome Trust Centre for Human Genetics and Oxford Biomedical Research Centre, University of Oxford, Oxford, UK. * Ian Tomlinson * Family Cancer Clinic, Netherlands Cancer Institut–Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands. * Frans B L Hogervorst * Multidisciplinary Breast Center, University Hospital Gasthuisberg, Leuven, Belgium. * Hans Wildiers * Imperial College, London, UK. * Afshan Siddiq * Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA. * Peter Kraft Consortia * The Gene Environment Interaction and Breast Cancer in Germany (GENICA) Consortium Contributions Conceived of and designed the experiments: C.A.H. and F.J.C. Performed the experiments and analyzed the data: C.A.H., L.C.P., D.V.D.B., X.S., G.K.C., A. Holbrook, P.W., F.C., D.O.S., X.W., T.L., C.O., K.N.S., A.M.L., L.Y.X., S.L.S. and C.M.V. Contributed reagents, materials, analysis tools or comments on the manuscript: C.A.H., C.M.V., A.D., R.C.M., X.W., F.A., S.A., C.B.A., L. Baglietto, R.B., E.V.B., M.W.B., C.D.B., L. Bernstein, C.B., W.J.B., H.B., J.E.B., L.A.C., J.E.C., J.C.-C., S.J.C., D.I.C., C.L.C., A.C., S.S.C., S.L.D., R.B.D., A.M.D., W.R.D., T.D., L.D., D.E., C.K.E., A.B.E., P.A.F., H.S.F., D.F.-J., F.F., A.F., G.F., S.M.G., G.G.G., A.K.G., P.G., N.G., D.G., U.H., S.E.H., A. Hartmann, R.H., J.H., R.N.H., J.J.H., D.J.H., S.A.I., A.I., J.I., E.M.J., N.J., A.J.-V., R.K., Y.-D.K., L.N.K., I.K., V.-M.K., S.K., D.L., A.M.L., L.L.M., T.L., J.L., S.L., A.M., S.M., N.G.M., P.M., G.W.M., H.N., S. Nickels, S. Nyante, C.O., J. Palmer, H.P., D.P., C.M.P., J. Peto, P.D.P.P., L.! C.P., M.F.P., K.P., T.R.R., J.L.R.-G., L.R., E.R., T.R., I.d.S.S., E.S., M.K.S., R.S.-W., F.S., G.S., X.S., L.B.S., H.-P.S., K.N.S., M.C.S., W.J.T., I.T., F.B.L.H., E.W., J.W., H.W., R.W., D.Y., W.Z., R.G.Z., A.S., S.L.S., D.O.S., D.E., P.K., B.E.H. and F.J.C. Wrote the paper: C.A.H. and F.J.C. A full list of members is provided in the Supplementary Note. The Gene Environment Interaction and Breast Cancer in Germany (GENICA) Consortium Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Christopher A Haiman or * Fergus J Couch Author Details * Christopher A Haiman Contact Christopher A Haiman Search for this author in: * NPG journals * PubMed * Google Scholar * Gary K Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Celine M Vachon Search for this author in: * NPG journals * PubMed * Google Scholar * Federico Canzian Search for this author in: * NPG journals * PubMed * Google Scholar * Alison Dunning Search for this author in: * NPG journals * PubMed * Google Scholar * Robert C Millikan Search for this author in: * NPG journals * PubMed * Google Scholar * Xianshu Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Foluso Ademuyiwa Search for this author in: * NPG journals * PubMed * Google Scholar * Shahana Ahmed Search for this author in: * NPG journals * PubMed * Google Scholar * Christine B Ambrosone Search for this author in: * NPG journals * PubMed * Google Scholar * Laura 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• A genome-wide association study identifies new susceptibility loci for non-cardia gastric cancer at 3q13.31 and 5p13.1
  - Nat Genet 43(12):1215-1218 (2011)
  Nature Genetics | Letter A genome-wide association study identifies new susceptibility loci for non-cardia gastric cancer at 3q13.31 and 5p13.1 * Yongyong Shi1, 9 * Zhibin Hu2, 3, 4, 9 * Chen Wu5, 9 * Juncheng Dai2 * Huizhang Li2 * Jing Dong2 * Meilin Wang6 * Xiaoping Miao7 * Yifeng Zhou8 * Feng Lu2 * Hanze Zhang2 * Lingmin Hu2 * Yue Jiang2 * Zhiqiang Li1 * Minjie Chu2 * Hongxia Ma2 * Jiaping Chen2, 3 * Guangfu Jin2, 3 * Wen Tan5 * Tangchun Wu7 * Zhengdong Zhang6 * Dongxin Lin5 * Hongbing Shen2, 3, 4 * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:1215–1218Year published:(2011)DOI:doi:10.1038/ng.978Received07 June 2011Accepted21 September 2011Published online30 October 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Gastric cancer, including the cardia and non-cardia types, is the second leading cause of cancer-related deaths worldwide. To identify genetic risk variants for non-cardia gastric cancer, we performed a genome-wide association study in 3,279 individuals (1,006 with non-cardia gastric cancer and 2,273 controls) of Chinese descent. We replicated significant associations in an additional 6,897 subjects (3,288 with non-cardia gastric cancer and 3,609 controls). We identified two new susceptibility loci for non-cardia gastric cancer at 5p13.1 (rs13361707 in the region including PTGER4 and PRKAA1; odds ratio (OR) = 1.41; P = 7.6 × 10−29) and 3q13.31 (rs9841504 in ZBTB20; OR = 0.76; P = 1.7 × 10−9). Imputation analyses also confirmed previously reported associations of rs2294008 and rs2976392 on 8q24, rs4072037 on 1q22 and rs13042395 on 20p13 with non-cardia gastric cancer susceptibility in the Han Chinese population. View full text Figures at a glance * Figure 1: Plot of the genome-wide P values of association with non-cardia gastric cancer in the Han Chinese population. Scatter plot of P values in −log10 scale from the additive model in 1,006 cases and 2,273 controls. Blue horizontal line, P = 1.0 × 10−5; red horizontal line, P = 1.0 × 10−7; green dots, rs9841504 and rs13361707. * Figure 2: Regional plot of the two new susceptibility loci for non-cardia gastric cancer. () 5p13.1 and () 3q13.31. Association results (−log10P) of both genotyped (filled circle) and imputed (open diamond) SNPs in the GWAS samples are shown for SNPs in the regions 400 kb upstream and downstream of the marker SNPs. The marker SNPs are shown in purple, and the r2 values of the remaining SNPs are indicated by color. The genes within the region are annotated and shown as arrows. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Yongyong Shi, * Zhibin Hu & * Chen Wu Affiliations * Bio-X Institutes, Ministry of Education Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai, China. * Yongyong Shi & * Zhiqiang Li * Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory for Modern Toxicology, School of Public Health, Nanjing Medical University, Nanjing, China. * Zhibin Hu, * Juncheng Dai, * Huizhang Li, * Jing Dong, * Feng Lu, * Hanze Zhang, * Lingmin Hu, * Yue Jiang, * Minjie Chu, * Hongxia Ma, * Jiaping Chen, * Guangfu Jin & * Hongbing Shen * Section of Clinical Epidemiology, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Nanjing Medical University, Nanjing, China. * Zhibin Hu, * Jiaping Chen, * Guangfu Jin & * Hongbing Shen * State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China. * Zhibin Hu & * Hongbing Shen * Department of Etiology and Carcinogenesis, State Key Laboratory of Molecular Oncology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. * Chen Wu, * Wen Tan & * Dongxin Lin * Department of Occupational Medicine and Environmental Health, School of Public Health, Nanjing Medical University, Nanjing, China. * Meilin Wang & * Zhengdong Zhang * Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. * Xiaoping Miao & * Tangchun Wu * Cyrus Tang Hematology Center, Jiangsu Institute of Hematology, Medical College, Soochow University, Suzhou, China. * Yifeng Zhou Contributions H.S. took full responsibility for the study, including study design, obtaining financial support, data interpretation and manuscript submission. D.L. and Y.S. co-directed the study, obtained financial support and were responsible for study design, the interpretation of results and writing the manuscript. Z.H. contributed financial support, performed overall project management, performed statistical analyses along with J. Dai and drafted the initial manuscript. H. Li, F.L., H.Z., L.H., Y.J., Z.L. and M.C. were responsible for sample processing and managed the genotyping data. M.W., Y.Z., H. Li, J. Dong, H. Ma, G.J., J.C. and Z.Z. were responsible for subject recruitment and sample preparation for the Jiangsu samples. C.W., X.M. and W.T. were responsible for subject recruitment and sample preparation for the Beijing samples and reviewed the manuscript. T.W. participated in the study design and reviewed the manuscript. All authors approved the final manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Hongbing Shen or * Dongxin Lin or * Yongyong Shi Author Details * Yongyong Shi Contact Yongyong Shi Search for this author in: * NPG journals * PubMed * Google Scholar * Zhibin Hu Search for this author in: * NPG journals * PubMed * Google Scholar * Chen Wu Search for this author in: * NPG journals * PubMed * Google Scholar * Juncheng Dai Search for this author in: * NPG journals * PubMed * Google Scholar * Huizhang Li Search for this author in: * NPG journals * PubMed * Google Scholar * Jing Dong Search for this author in: * NPG journals * PubMed * Google Scholar * Meilin Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Xiaoping Miao Search for this author in: * NPG journals * PubMed * Google Scholar * Yifeng Zhou Search for this author in: * NPG journals * PubMed * Google Scholar * Feng Lu Search for this author in: * NPG journals * PubMed * Google Scholar * Hanze Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Lingmin Hu Search for this author in: * NPG journals * PubMed * Google Scholar * Yue Jiang Search for this author in: * NPG journals * PubMed * Google Scholar * Zhiqiang Li Search for this author in: * NPG journals * PubMed * Google Scholar * Minjie Chu Search for this author in: * NPG journals * PubMed * Google Scholar * Hongxia Ma Search for this author in: * NPG journals * PubMed * Google Scholar * Jiaping Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Guangfu Jin Search for this author in: * NPG journals * PubMed * Google Scholar * Wen Tan Search for this author in: * NPG journals * PubMed * Google Scholar * Tangchun Wu Search for this author in: * NPG journals * PubMed * Google Scholar * Zhengdong Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Dongxin Lin Contact Dongxin Lin Search for this author in: * NPG journals * PubMed * Google Scholar * Hongbing Shen Contact Hongbing Shen Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (614K) Supplementary Figure 1 and Supplementary Tables 1–6 Additional data
• Exome sequencing identifies frequent mutation of ARID1A in molecular subtypes of gastric cancer
  - Nat Genet 43(12):1219-1223 (2011)
  Nature Genetics | Letter Exome sequencing identifies frequent mutation of ARID1A in molecular subtypes of gastric cancer * Kai Wang1, 7 * Junsuo Kan2, 7 * Siu Tsan Yuen2 * Stephanie T Shi3 * Kent Man Chu4 * Simon Law4 * Tsun Leung Chan2 * Zhengyan Kan1 * Annie S Y Chan2 * Wai Yin Tsui2 * Siu Po Lee2 * Siu Lun Ho2 * Anthony K W Chan2 * Grace H W Cheng2 * Peter C Roberts5 * Paul A Rejto1 * Neil W Gibson1, 6 * David J Pocalyko1 * Mao Mao1 * Jiangchun Xu1 * Suet Yi Leung2 * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:1219–1223Year published:(2011)DOI:doi:10.1038/ng.982Received18 May 2011Accepted23 September 2011Published online30 October 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Gastric cancer is a heterogeneous disease with multiple environmental etiologies and alternative pathways of carcinogenesis1, 2. Beyond mutations in TP53, alterations in other genes or pathways account for only small subsets of the disease. We performed exome sequencing of 22 gastric cancer samples and identified previously unreported mutated genes and pathway alterations; in particular, we found genes involved in chromatin modification to be commonly mutated. A downstream validation study confirmed frequent inactivating mutations or protein deficiency of ARID1A, which encodes a member of the SWI-SNF chromatin remodeling family, in 83% of gastric cancers with microsatellite instability (MSI), 73% of those with Epstein-Barr virus (EBV) infection and 11% of those that were not infected with EBV and microsatellite stable (MSS). The mutation spectrum for ARID1A differs between molecular subtypes of gastric cancer, and mutation prevalence is negatively associated with mutations i! n TP53. Clinically, ARID1A alterations were associated with better prognosis in a stage-independent manner. These results reveal the genomic landscape, and highlight the importance of chromatin remodeling, in the molecular taxonomy of gastric cancer. View full text Figures at a glance * Figure 1: Relationship of ARID1A alterations (mutation or protein deficiency) with molecular subtypes of gastric cancer. () Incidence of ARID1A mutation and protein deficiency in different molecular subtypes of gastric cancer. Blue color indicates samples with ARID1A mutation, and shaded area indicates samples with protein deficiency, as determined by immunohistochemistry. **P < 0.01, ***P < 0.001 for both ARID1A mutation and alteration (see Supplementary Table 12 for detail). () TP53 mutation rate in gastric cancer samples with or without ARID1A alterations. * Figure 2: Difference in the mutation spectrum of ARID1A between molecular subtypes of gastric cancer. Individual exons of the ARID1A gene are represented as numbered gray boxes. Mutations detected by sequencing the coding region of ARID1A in 23 MSI and 86 MSS gastric cancers are shown. cDNA and peptide positions are based on the ENST00000324856 transcript. Colors of text correspond to functional impact prediction by SIFT, as indicated at the bottom. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Kai Wang & * Junsuo Kan Affiliations * Oncology Research Unit, Pfizer Worldwide Research and Development, La Jolla, California, USA. * Kai Wang, * Zhengyan Kan, * Paul A Rejto, * Neil W Gibson, * David J Pocalyko, * Mao Mao & * Jiangchun Xu * Department of Pathology, The University of Hong Kong, Queen Mary Hospital, Pokfulam, Hong Kong. * Junsuo Kan, * Siu Tsan Yuen, * Tsun Leung Chan, * Annie S Y Chan, * Wai Yin Tsui, * Siu Po Lee, * Siu Lun Ho, * Anthony K W Chan, * Grace H W Cheng & * Suet Yi Leung * External Research Solutions, Pfizer Worldwide Research and Development, La Jolla, California, USA. * Stephanie T Shi * Department of Surgery, The University of Hong Kong, Queen Mary Hospital, Pokfulam, Hong Kong. * Kent Man Chu & * Simon Law * Research Embedded Business Technology, Pfizer Worldwide Research and Development, La Jolla, California, USA. * Peter C Roberts * Present address: Regulus Therapeutics, San Diego, California, USA. * Neil W Gibson Contributions D.J.P., P.A.R., N.W.G., M.M., J.X., S.T.Y. and S.Y.L. conceived of the study. S.T.Y., S.Y.L., J.X. and M.M. directed the study. K.W., S.T.S., P.A.R., J.X., M.M., S.T.Y. and S.Y.L. contributed to the project design. K.W., Z.K. and G.H.W.C. performed the bioinformatics data analysis. J.K., T.L.C., A.S.Y.C., W.Y.T., S.P.L., S.L.H. and A.K.W.C. performed experiments on ARID1A mutation and other molecular analysis. K.M.C. and S.L. contributed samples, data and comments on the manuscript. P.C.R. contributed to data management. K.W., J.K., S.T.Y., M.M., J.X. and S.Y.L. analyzed and interpreted data and wrote the manuscript with the assistance and final approval from all authors. Competing financial interests K.W., S.T.S., Z.K., P.C.R., P.A.R., N.W.G., D.J.P., M.M. and J.X. are employees of Pfizer Inc. Corresponding authors Correspondence to: * Suet Yi Leung or * Jiangchun Xu Author Details * Kai Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Junsuo Kan Search for this author in: * NPG journals * PubMed * Google Scholar * Siu Tsan Yuen Search for this author in: * NPG journals * PubMed * Google Scholar * Stephanie T Shi Search for this author in: * NPG journals * PubMed * Google Scholar * Kent Man Chu Search for this author in: * NPG journals * PubMed * Google Scholar * Simon Law Search for this author in: * NPG journals * PubMed * Google Scholar * Tsun Leung Chan Search for this author in: * NPG journals * PubMed * Google Scholar * Zhengyan Kan Search for this author in: * NPG journals * PubMed * Google Scholar * Annie S Y Chan Search for this author in: * NPG journals * PubMed * Google Scholar * Wai Yin Tsui Search for this author in: * NPG journals * PubMed * Google Scholar * Siu Po Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Siu Lun Ho Search for this author in: * NPG journals * PubMed * Google Scholar * Anthony K W Chan Search for this author in: * NPG journals * PubMed * Google Scholar * Grace H W Cheng Search for this author in: * NPG journals * PubMed * Google Scholar * Peter C Roberts Search for this author in: * NPG journals * PubMed * Google Scholar * Paul A Rejto Search for this author in: * NPG journals * PubMed * Google Scholar * Neil W Gibson Search for this author in: * NPG journals * PubMed * Google Scholar * David J Pocalyko Search for this author in: * NPG journals * PubMed * Google Scholar * Mao Mao Search for this author in: * NPG journals * PubMed * Google Scholar * Jiangchun Xu Contact Jiangchun Xu Search for this author in: * NPG journals * PubMed * Google Scholar * Suet Yi Leung Contact Suet Yi Leung Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1–4, Supplementary Tables 1–3, 5, 8, 11, 12 and 14–17 and Supplementary Note Excel files * Supplementary Table 4 (623K) List of all somatic mutations identified in the SureSelect All Exon kit baited regions in 22 gastric cancers * Supplementary Table 6 (164K) Comparison of list of gastric cancer genes with protein altering mutations detected in exome study versus kinome study * Supplementary Table 7 (61K) List of genes with protein-altering somatic mutations in at least two patients in the gastric cancer cohort and their driver gene scores * Supplementary Table 9 (41K) Pathways enriched in somatically mutated genes in gastric cancer * Supplementary Table 10 (33K) List of all protein-altering somatic mutations involving chromatin modification genes in 22 gastric cancers * Supplementary Table 13 (45K) Complete list of ARID1A and TP53 somatic mutations in 109 gastric cancers and their associated molecular parameters Additional data
• Common variants on 8p12 and 1q24.2 confer risk of schizophrenia
  - Nat Genet 43(12):1224-1227 (2011)
  Nature Genetics | Letter Common variants on 8p12 and 1q24.2 confer risk of schizophrenia * Yongyong Shi1, 2, 3, 32 * Zhiqiang Li1, 2, 32 * Qi Xu4, 32 * Ti Wang1 * Tao Li1 * Jiawei Shen1 * Fengyu Zhang5 * Jianhua Chen6 * Guoquan Zhou3 * Weidong Ji3 * Baojie Li1 * Yifeng Xu6 * Dengtang Liu6 * Peng Wang7 * Ping Yang7 * Benxiu Liu8 * Wensheng Sun8 * Chunling Wan1 * Shengying Qin1, 2 * Guang He1, 2 * Stacy Steinberg9 * Sven Cichon10, 11, 12 * Thomas Werge13 * Engilbert Sigurdsson14 * Sarah Tosato15 * Aarno Palotie16, 17, 18, 19, 20 * Markus M Nöthen10, 11, 21 * Marcella Rietschel22, 23 * Roel A Ophoff24, 25, 26 * David A Collier27 * Dan Rujescu28 * David St Clair29 * Hreinn Stefansson9 * Kari Stefansson9 * Jue Ji1 * Qingzhong Wang1 * Wenjin Li1 * Linqing Zheng1 * Hairong Zhang1 * Guoyin Feng5 * Lin He1, 2, 30, 31 * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:1224–1227Year published:(2011)DOI:doi:10.1038/ng.980Received13 April 2011Accepted22 September 2011Published online30 October 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Schizophrenia is a severe mental disorder affecting ~1% of the world population, with heritability of up to 80%. To identify new common genetic risk factors, we performed a genome-wide association study (GWAS) in the Han Chinese population. The discovery sample set consisted of 3,750 individuals with schizophrenia and 6,468 healthy controls (1,578 cases and 1,592 controls from northern Han Chinese, 1,238 cases and 2,856 controls from central Han Chinese, and 934 cases and 2,020 controls from the southern Han Chinese). We further analyzed the strongest association signals in an additional independent cohort of 4,383 cases and 4,539 controls from the Han Chinese population. Meta-analysis identified common SNPs that associated with schizophrenia with genome-wide significance on 8p12 (rs16887244, P = 1.27 × 10−10) and 1q24.2 (rs10489202, P = 9.50 × 10−9). Our findings provide new insights into the pathogenesis of schizophrenia. View full text Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Yongyong Shi, * Zhiqiang Li & * Qi Xu Affiliations * Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China. * Yongyong Shi, * Zhiqiang Li, * Ti Wang, * Tao Li, * Jiawei Shen, * Baojie Li, * Chunling Wan, * Shengying Qin, * Guang He, * Jue Ji, * Qingzhong Wang, * Wenjin Li, * Linqing Zheng, * Hairong Zhang & * Lin He * Shanghai genomePilot Institutes for Genomics and Human Health, Shanghai, China. * Yongyong Shi, * Zhiqiang Li, * Shengying Qin, * Guang He & * Lin He * Changning Mental Health Center, Shanghai, China. * Yongyong Shi, * Guoquan Zhou & * Weidong Ji * National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. * Qi Xu * Genes, Cognition and Psychosis Program, National Institute of Mental Health, the National Institutes of Health, Bethesda, Maryland, USA. * Fengyu Zhang & * Guoyin Feng * Shanghai Institute of Mental Health, Shanghai, China. * Jianhua Chen, * Yifeng Xu & * Dengtang Liu * Fourth People's Hospital, Wuhu, China. * Peng Wang & * Ping Yang * Longquan Mountain Hospital of Guangxi Province, Liuzhou, China. * Benxiu Liu & * Wensheng Sun * deCODE genetics, Reykjavik, Iceland. * Stacy Steinberg, * Hreinn Stefansson & * Kari Stefansson * Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany. * Sven Cichon & * Markus M Nöthen * Institute of Human Genetics, University of Bonn, Bonn, Germany. * Sven Cichon & * Markus M Nöthen * Institute of Neuroscience and Medicine (INM-1), Structural and Functional Organization of the Brain Genomic Imaging, Research Center Juelich, Juelich, Germany. * Sven Cichon * Institute of Biological Psychiatry, Mental Health Centre Saint Hans, Copenhagen University Hospital, Roskilde, Denmark. . * Thomas Werge * Department of Psychiatry, National University Hospital, Reykjavik, Iceland. * Engilbert Sigurdsson * Section of Psychiatry and Clinical Psychology, University of Verona, Verona, Italy. * Sarah Tosato * Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. * Aarno Palotie * Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland. * Aarno Palotie * Program in Medical and Population Genetics and Genetic Analysis Platform, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. * Aarno Palotie * Department of Medical Genetics, University of Helsinki, Helsinki, Finland. * Aarno Palotie * Department of Medical Genetics, Helsinki University Central Hospital, Helsinki, Finland. * Aarno Palotie * German Center for Neurodegenerative Disorders, Bonn, Germany. * Markus M Nöthen * Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany. * Marcella Rietschel * Department of Psychiatry, University of Bonn, Bonn, Germany. * Marcella Rietschel * Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands. * Roel A Ophoff * Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands. * Roel A Ophoff * Center for Neurobehavioral Genetics, University of California, Los Angeles, Los Angeles, California, USA. * Roel A Ophoff * Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College, London, London, UK. * David A Collier * Division of Molecular and Clinical Neurobiology, Department of Psychiatry, Ludwig-Maximilians-University, Munich, Germany. * Dan Rujescu * Department of Mental Health, University of Aberdeen, Royal Cornhill Hospital, Aberdeen, UK. * David St Clair * Institutes of Biomedical Sciences, Fudan University, Shanghai, China. * Lin He * Institute for Nutritional Sciences, Shanghai Institute of Biological Sciences, Chinese Academy of Sciences, Shanghai, China. * Lin He Contributions Y.S. and L.H. conceived of and designed the study. Y.S. supervised all the experiments and data analysis. Y.S. and Z.L. conducted data analyses and drafted the manuscript. Y.S., Z.L., F.Z., D.S.C., S.S., D.R. and L.H. revised the manuscript. Y.S., G.F., Q.X., J.C., Y.X., D.L., P.W., P.Y., B. Liu, W.S., G.Z. and W.J. recruited samples. T. Wang, J.J., T.L., J.S., J.C., Q.W., W.L., L.Z., H.Z., B. Li, C.W., S.Q. and G.H. performed or contributed to the experiments. S.S., S.C., T.W., E.S., S.T., A.P., M.M.N., M.R., R.A.O., D.A.C., D.R., D.S.C., H.S. and K.S. provided the SGENE-plus data. All authors critically reviewed and approved the manuscript. Competing financial interests The authors declare no competing financial interests. 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• Genome-wide association study identifies a susceptibility locus for schizophrenia in Han Chinese at 11p11.2
  - Nat Genet 43(12):1228-1231 (2011)
  Nature Genetics | Letter Genome-wide association study identifies a susceptibility locus for schizophrenia in Han Chinese at 11p11.2 * Wei-Hua Yue1, 2, 18 * Hai-Feng Wang3, 4 * Liang-Dan Sun5, 6, 18 * Fu-Lei Tang1, 2 * Zhong-Hua Liu7 * Hong-Xing Zhang8, 9 * Wen-Qiang Li8, 9 * Yan-Ling Zhang1, 2 * Yang Zhang1, 2 * Cui-Cui Ma10 * Bo Du11 * Li-Fang Wang1, 2 * Yun-Qing Ren5, 6 * Yong-Feng Yang8, 9 * Xiao-Feng Hu1, 2 * Yi Wang3, 4 * Wei Deng12 * Li-Wen Tan13 * Yun-Long Tan14 * Qi Chen15 * Guang-Ming Xu16 * Gui-Gang Yang14 * Xian-bo Zuo5, 6 * Hao Yan1, 2 * Yan-Yan Ruan1, 2 * Tian-Lan Lu1, 2 * Xue Han13 * Xiao-Hong Ma12 * Yan Wang1, 2 * Li-Wei Cai1, 2 * Chao Jin10 * Hong-Yan Zhang1, 2 * Jun Yan1, 2 * Wei-Feng Mi1, 2 * Xian-Yong Yin5, 6 * Wen-Bin Ma10 * Qi Liu1, 2 * Lan Kang1, 2 * Wei Sun1, 2 * Cheng-Ying Pan1, 2 * Mei Shuang1, 2 * Fu-De Yang14 * Chuan-Yue Wang15 * Jian-Li Yang16 * Ke-Qing Li11 * Xin Ma15 * Ling-Jiang Li13 * Xin Yu1, 2 * Qi-Zhai Li17 * Xun Huang7 * Lu-Xian Lv8, 9 * Tao Li12 * Guo-Ping Zhao3 * Wei Huang3, 4 * Xue-Jun Zhang5, 6 * Dai Zhang1, 2 * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:1228–1231Year published:(2011)DOI:doi:10.1038/ng.979Received07 March 2011Accepted21 September 2011Published online30 October 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg To identify susceptibility loci for schizophrenia, we performed a two-stage genome-wide association study (GWAS) of schizophrenia in the Han Chinese population (GWAS: 746 individuals with schizophrenia and 1,599 healthy controls; validation: 4,027 individuals with schizophrenia and 5,603 healthy controls). We identified two susceptibility loci for schizophrenia at 6p21-p22.1 (rs1233710 in an intron of ZKSCAN4, Pcombined = 4.76 × 10−11, odds ratio (OR) = 0.79; rs1635 in an exon of NKAPL, Pcombined = 6.91 × 10−12, OR = 0.78; rs2142731 in an intron of PGBD1, Pcombined = 5.14 × 10−10, OR = 0.79) and 11p11.2 (rs11038167 near the 5′ UTR of TSPAN18, Pcombined = 1.09 × 10−11, OR = 1.29; rs11038172, Pcombined = 7.21 × 10−10, OR = 1.25; rs835784, Pcombined = 2.73 × 10−11, OR = 1.27). These results add to previous evidence of susceptibility loci for schizophrenia at 6p21-p22.1 in the Han Chinese population. We found that NKAPL and ZKSCAN4 were expressed in postnatal! day 0 (P0) mouse brain. These findings may lead to new insights into the pathogenesis of schizophrenia. View full text Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Wei-Hua Yue & * Liang-Dan Sun Affiliations * Institute of Mental Health, Peking University, Beijing, China. * Wei-Hua Yue, * Fu-Lei Tang, * Yan-Ling Zhang, * Yang Zhang, * Li-Fang Wang, * Xiao-Feng Hu, * Hao Yan, * Yan-Yan Ruan, * Tian-Lan Lu, * Yan Wang, * Li-Wei Cai, * Hong-Yan Zhang, * Jun Yan, * Wei-Feng Mi, * Qi Liu, * Lan Kang, * Wei Sun, * Cheng-Ying Pan, * Mei Shuang, * Xin Yu & * Dai Zhang * Ministry of Health Key Laboratory of Mental Health, Peking University, Beijing, China. * Wei-Hua Yue, * Fu-Lei Tang, * Yan-Ling Zhang, * Yang Zhang, * Li-Fang Wang, * Xiao-Feng Hu, * Hao Yan, * Yan-Yan Ruan, * Tian-Lan Lu, * Yan Wang, * Li-Wei Cai, * Hong-Yan Zhang, * Jun Yan, * Wei-Feng Mi, * Qi Liu, * Lan Kang, * Wei Sun, * Cheng-Ying Pan, * Mei Shuang, * Xin Yu & * Dai Zhang * Shanghai–Ministry of Science and Technology of China Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai, Shanghai, China. * Hai-Feng Wang, * Yi Wang, * Guo-Ping Zhao & * Wei Huang * State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China. * Hai-Feng Wang, * Yi Wang & * Wei Huang * Institute of Dermatology and Department of Dermatology, No. 1 Hospital, Anhui Medical University, Hefei, China. * Liang-Dan Sun, * Yun-Qing Ren, * Xian-bo Zuo, * Xian-Yong Yin & * Xue-Jun Zhang * State Key Laboratory of Dermatology, Ministry of Science and Technology, Hefei, China. * Liang-Dan Sun, * Yun-Qing Ren, * Xian-bo Zuo, * Xian-Yong Yin & * Xue-Jun Zhang * Key Laboratory of Molecular and Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China. * Zhong-Hua Liu & * Xun Huang * Department of Psychiatry of the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China. * Hong-Xing Zhang, * Wen-Qiang Li, * Yong-Feng Yang & * Lu-Xian Lv * Henan Mental Hospital, Henan Key Laboratory of Biological Psychiatry, Xinxiang, China. * Hong-Xing Zhang, * Wen-Qiang Li, * Yong-Feng Yang & * Lu-Xian Lv * Jinzhou Kangning Hospital, Jinzhou, China. * Cui-Cui Ma, * Chao Jin & * Wen-Bin Ma * Hebei Mental Health Center, Baoding, China. * Bo Du & * Ke-Qing Li * Department of Psychiatry, West China Hospital, Sichuan University, Chengdu, China. * Wei Deng, * Xiao-Hong Ma & * Tao Li * Institute of Mental Health, Second Xiangya Hospital of Central South University, Changsha, China. * Li-Wen Tan, * Xue Han & * Ling-Jiang Li * Beijing Huilongguan Hospital, Beijing, China. * Yun-Long Tan, * Gui-Gang Yang & * Fu-De Yang * Beijing Anding Hospital, Capital Medical University, Beijing, China. * Qi Chen, * Chuan-Yue Wang & * Xin Ma * Tianjin Anding Hospital of Tianjin Municipality, Tianjin, China. * Guang-Ming Xu & * Jian-Li Yang * Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China. * Qi-Zhai Li Contributions D.Z., W.H., X.-J.Z., G.-P.Z. and T.L. designed the study. D.Z. and X.-J.Z. revised the manuscript. D.Z. and W.-H.Y. obtained financial support. W.-H.Y., L.-D.S. and L.-F.W. prepared the manuscript. H.-F.W., W.-H.Y. and L.-D.S. supervised the experiments and data analysis. H.-X.Z., W.-Q.L., Y.-L.Z., C.-C.M., B.D., Y.-Q.R., Y.-F.Y., X.-F.H., Y.W., W.D., L.-W.T., Y.-L.T., Q.C., G.-M.X., G.-G.Y., H.Y., Y.-Y.R., T.-L.L., X.H., X.-H.M., Y.W., L.-W.C., C.J., H.-Y.Z., J.Y., W.-F.M., X.-Y.Y., W.-B.M., Q.L., L.K., W.S., C.-Y.P., M.S., F.-D.Y., C.-Y.W., J.-L.Y., K.-Q.L., X.M., L.-J.L., X.Y. and L.-X.L. conducted sample selection and data management, undertook recruitment, collected phenotype data, undertook related data handling and calculation, managed recruitment and obtained biological samples. W.-H.Y., L.-F.W., X.B.Z. and Q.-Z.L. undertook data processing, statistical analysis and bioinformatics investigations. F.-L.T., Z.-H.L., Y.Z. and X.H. performed in situ hybridization and RNA! i experiments. All authors critically reviewed the manuscript and approved the final version. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Dai Zhang or * Wei Huang Author Details * Wei-Hua Yue Search for this author in: * NPG journals * PubMed * Google Scholar * Hai-Feng Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Liang-Dan Sun Search for this author in: * NPG journals * PubMed * Google Scholar * Fu-Lei Tang Search for this author in: * NPG journals * PubMed * Google Scholar * Zhong-Hua Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Hong-Xing Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Wen-Qiang Li Search for this author in: * NPG journals * PubMed * Google Scholar * Yan-Ling Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Yang Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Cui-Cui Ma Search for this author in: * NPG journals * PubMed * Google Scholar * Bo Du Search for this author in: * NPG journals * PubMed * Google Scholar * Li-Fang Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Yun-Qing Ren Search for this author in: * NPG journals * PubMed * Google Scholar * Yong-Feng Yang Search for this author in: * NPG journals * PubMed * Google Scholar * Xiao-Feng Hu Search for this author in: * NPG journals * PubMed * Google Scholar * Yi Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Wei Deng Search for this author in: * NPG journals * PubMed * Google Scholar * Li-Wen Tan Search for this author in: * NPG journals * PubMed * Google Scholar * Yun-Long Tan Search for this author in: * NPG journals * PubMed * Google Scholar * Qi Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Guang-Ming Xu Search for this author in: * NPG journals * PubMed * Google Scholar * Gui-Gang Yang Search for this author in: * NPG journals * PubMed * Google Scholar * Xian-bo Zuo Search for this author in: * NPG journals * PubMed * Google Scholar * Hao Yan Search for this author in: * NPG journals * PubMed * Google Scholar * Yan-Yan Ruan Search for this author in: * NPG journals * PubMed * Google Scholar * Tian-Lan Lu Search for this author in: * NPG journals * PubMed * Google Scholar * Xue Han Search for this author in: * NPG journals * PubMed * Google Scholar * Xiao-Hong Ma Search for this author in: * NPG journals * PubMed * Google Scholar * Yan Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Li-Wei Cai Search for this author in: * NPG journals * PubMed * Google Scholar * Chao Jin Search for this author in: * NPG journals * PubMed * Google Scholar * Hong-Yan Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Jun Yan Search for this author in: * NPG journals * PubMed * Google Scholar * Wei-Feng Mi Search for this author in: * NPG journals * PubMed * Google Scholar * Xian-Yong Yin Search for this author in: * NPG journals * PubMed * Google Scholar * Wen-Bin Ma Search for this author in: * NPG journals * PubMed * Google Scholar * Qi Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Lan Kang Search for this author in: * NPG journals * PubMed * Google Scholar * Wei Sun Search for this author in: * NPG journals * PubMed * Google Scholar * Cheng-Ying Pan Search for this author in: * NPG journals * PubMed * Google Scholar * Mei Shuang Search for this author in: * NPG journals * PubMed * Google Scholar * Fu-De Yang Search for this author in: * NPG journals * PubMed * Google Scholar * Chuan-Yue Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Jian-Li Yang Search for this author in: * NPG journals * PubMed * Google Scholar * Ke-Qing Li Search for this author in: * NPG journals * PubMed * Google Scholar * Xin Ma Search for this author in: * NPG journals * PubMed * Google Scholar * Ling-Jiang Li Search for this author in: * NPG journals * PubMed * Google Scholar * Xin Yu Search for this author in: * NPG journals * PubMed * Google Scholar * Qi-Zhai Li Search for this author in: * NPG journals * PubMed * Google Scholar * Xun Huang Search for this author in: * NPG journals * PubMed * Google Scholar * Lu-Xian Lv Search for this author in: * NPG journals * PubMed * Google Scholar * Tao Li Search for this author in: * NPG journals * PubMed * Google Scholar * Guo-Ping Zhao Search for this author in: * NPG journals * PubMed * Google Scholar * Wei Huang Contact Wei Huang Search for this author in: * NPG journals * PubMed * Google Scholar * Xue-Jun Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Dai Zhang Contact Dai Zhang Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Tables 1–6, Supplementary Figures 1–6 and Supplementary Note Additional data
• A rare penetrant mutation in CFH confers high risk of age-related macular degeneration
  - Nat Genet 43(12):1232-1236 (2011)
  Nature Genetics | Letter A rare penetrant mutation in CFH confers high risk of age-related macular degeneration * Soumya Raychaudhuri1, 2, 3, 4 * Oleg Iartchouk3 * Kimberly Chin5 * Perciliz L Tan6, 7 * Albert K Tai8 * Stephan Ripke4, 9 * Sivakumar Gowrisankar3 * Soumya Vemuri3 * Kate Montgomery3 * Yi Yu5 * Robyn Reynolds5 * Donald J Zack10 * Betsy Campochiaro10 * Peter Campochiaro10 * Nicholas Katsanis6, 7 * Mark J Daly4, 9 * Johanna M Seddon5, 11 * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:1232–1236Year published:(2011)DOI:doi:10.1038/ng.976Received11 April 2011Accepted20 September 2011Published online23 October 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Two common variants in the gene encoding complement factor H (CFH), the Y402H substitution (rs1061170, c.1204C>T)1, 2, 3, 4 and the intronic rs1410996 SNP5, 6, explain 17% of age-related macular degeneration (AMD) liability. However, proof for the involvement of CFH, as opposed to a neighboring transcript, and knowledge of the potential mechanism of susceptibility alleles are lacking. Assuming that rare functional variants might provide mechanistic insights, we used genotype data and high-throughput sequencing to discover a rare, high-risk CFH haplotype with a c.3628C>T mutation that resulted in an R1210C substitution. This allele has been implicated previously in atypical hemolytic uremic syndrome, and it abrogates C-terminal ligand binding7, 8. Genotyping R1210C in 2,423 AMD cases and 1,122 controls demonstrated high penetrance (present in 40 cases versus 1 control, P = 7.0 × 10−6) and an association with a 6-year-earlier onset of disease (P = 2.3 × 10−6). This resul! t suggests that loss-of-function alleles at CFH are likely to drive AMD risk. This finding represents one of the first instances in which a common complex disease variant has led to the discovery of a rare penetrant mutation. View full text Figures at a glance * Figure 1: A rare CFH haplotype is associated with AMD risk. () Phasing 21 markers in the CFH–CFHR3–CFHR1 region. Here we present association statistics of 11 haplotypes with frequencies >0.3%, resulting from phasing 20 SNP markers and a CFHR1–CFHR3 common copy-number polymorphism. We specifically note the CFH rs800292 SNP (encoding the V62I substitution); the CFH Y402H substitution proxy, rs10801555; CFH rs1410996 proxy, rs10737680; and CFHR1–3Δ. For most SNPs we list the nucleotide; for CFHR1–3Δ, the empty circles indicate the region that is deleted, whereas the filled circles indicate the region that is not deleted. To the right of each haplotype, we note the observed frequency in cases and controls. To the far right of each haplotype, we plot the ratio of the odds of disease for each haplotype relative to H1. Beside the H5 odds ratio, for comparison we note the aggregate odds ratio of haplotypes H4–H11 depicted with a red dot. () Case-control permutations preserving genotype at four common AMD-associated markers. Her! e we present a histogram of the number of H5 heterozygous individuals who are cases for each of the 100,000 permutations. An arrow is placed at 10, corresponding to the observed number of H5 heterozygous individuals who are cases in the actual data (P = 0.00081). * Figure 2: Sequencing the H5 haplotype identifies an R1210C-encoding mutation. We applied capillary electrophoresis sequencing to 84 individuals representing the common CFH haplotypes depicted in Figure 1. Each circle represents an individual. The position on the grid indicates the two haplotypes for the individual at the CFH locus; individuals along the diagonal are homozygous for a haplotype. Individuals who do not have the R1210C mutation are depicted with an empty circle and those heterozygous for the R1210C mutation with a filled red circle. All ten individuals with the R1210C mutation are heterozygous for the H5 haplotype, strongly suggesting that the mutation is on that haplotype and accounts for the increased risk associated with that haplotype. * Figure 3: The phenotype of the R1210C-encoding mutation. () Histogram of the age of onset for 23 individuals with the R1210C mutation, and also for 1,887 individuals without the R1210C mutation from the Boston-phased data and Boston replication for whom data was available. Age of onset is defined as the age when the patient starts to show signs of AMD. The median age of diagnosis for affected individuals with the R1210C mutation is 6 years younger than those without (65 versus 71 years), and the mean age is 8.6 years younger (61.9 versus 70.5 years). () Fundus photograph of the right eye of a subject with the R1210C mutation showing central geographic atrophy (advanced dry age-related macular degeneration) surrounded by numerous large and very large drusen in the posterior pole and along the vascular arcades. Drusen were present nasal and temporal to the macula and in all four quadrants out to the mid-peripheral retina. Author information * Author information * Supplementary information Affiliations * Division of Genetics, Brigham and Women's Hospital, Boston, Massachusetts, USA. * Soumya Raychaudhuri * Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Boston, Massachusetts, USA. * Soumya Raychaudhuri * Partners HealthCare Center for Personalized Genetic Medicine, Boston, Massachusetts, USA. * Soumya Raychaudhuri, * Oleg Iartchouk, * Sivakumar Gowrisankar, * Soumya Vemuri & * Kate Montgomery * Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA. * Soumya Raychaudhuri, * Stephan Ripke & * Mark J Daly * Ophthalmic Epidemiology and Genetics Service, New England Eye Center, Tufts Medical Center, Boston, Massachusetts, USA. * Kimberly Chin, * Yi Yu, * Robyn Reynolds & * Johanna M Seddon * Center for Human Disease Modeling, Department of Cell Biology, Duke University, Durham, North Carolina, USA. * Perciliz L Tan & * Nicholas Katsanis * Department of Pediatrics, Duke University, Durham, North Carolina, USA. * Perciliz L Tan & * Nicholas Katsanis * Study Center on the Immunogenetics of Infectious Disease, Department of Pathology, Tufts University School of Medicine, Boston, Massachusetts, USA. * Albert K Tai * Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA. * Stephan Ripke & * Mark J Daly * McKusick-Nathans Institute of Genetic Medicine, Department of Ophthalmology, Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. * Donald J Zack, * Betsy Campochiaro & * Peter Campochiaro * Department of Ophthalmology, Tufts University School of Medicine, Boston, Massachusetts, USA. * Johanna M Seddon Contributions S. Raychaudhuri, J.M.S., N.K. and M.J.D. conceptualized this study, wrote the initial manuscript and interpreted all results. S. Raychaudhuri oversaw the statistical analyses and coordinated collaborative experimental efforts. J.M.S. and M.J.D. oversaw genome-wide genotyping of the Boston-phased data. S. Ripke analyzed the genome-wide Boston-phased genotype data to assess population stratification and recent ancestry. J.M.S., K.C., R.R. and Y.Y. organized the Boston clinical cohort. B.C., P.C. and D.J.Z. organized the Baltimore clinical cohort. P.L.T. and N.K. genotyped the Baltimore samples. A.T. genotyped the Boston samples. O.I., S.G., S.V. and K.M. sequenced the CFH gene. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Soumya Raychaudhuri or * Johanna M Seddon Author Details * Soumya Raychaudhuri Contact Soumya Raychaudhuri Search for this author in: * NPG journals * PubMed * Google Scholar * Oleg Iartchouk Search for this author in: * NPG journals * PubMed * Google Scholar * Kimberly Chin Search for this author in: * NPG journals * PubMed * Google Scholar * Perciliz L Tan Search for this author in: * NPG journals * PubMed * Google Scholar * Albert K Tai Search for this author in: * NPG journals * PubMed * Google Scholar * Stephan Ripke Search for this author in: * NPG journals * PubMed * Google Scholar * Sivakumar Gowrisankar Search for this author in: * NPG journals * PubMed * Google Scholar * Soumya Vemuri Search for this author in: * NPG journals * PubMed * Google Scholar * Kate Montgomery Search for this author in: * NPG journals * PubMed * Google Scholar * Yi Yu Search for this author in: * NPG journals * PubMed * Google Scholar * Robyn Reynolds Search for this author in: * NPG journals * PubMed * Google Scholar * Donald J Zack Search for this author in: * NPG journals * PubMed * Google Scholar * Betsy Campochiaro Search for this author in: * NPG journals * PubMed * Google Scholar * Peter Campochiaro Search for this author in: * NPG journals * PubMed * Google Scholar * Nicholas Katsanis Search for this author in: * NPG journals * PubMed * Google Scholar * Mark J Daly Search for this author in: * NPG journals * PubMed * Google Scholar * Johanna M Seddon Contact Johanna M Seddon Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–5 and Supplementary Tables 1–3 and 5–8 Excel files * Supplementary Table 4 (102K) Polymorphic variants from high throughput sequencing of CFH in 33 cases and 27 controls Additional data
• A genome-wide association study identifies common variants near LBX1 associated with adolescent idiopathic scoliosis
  - Nat Genet 43(12):1237-1240 (2011)
  Nature Genetics | Letter A genome-wide association study identifies common variants near LBX1 associated with adolescent idiopathic scoliosis * Yohei Takahashi1, 2 * Ikuyo Kou1 * Atsushi Takahashi3 * Todd A Johnson4 * Katsuki Kono5 * Noriaki Kawakami6 * Koki Uno7 * Manabu Ito8 * Shohei Minami9 * Haruhisa Yanagida10 * Hiroshi Taneichi11 * Taichi Tsuji6 * Teppei Suzuki7 * Hideki Sudo8 * Toshiaki Kotani9 * Kota Watanabe2 * Kazuhiro Chiba2 * Naoya Hosono12 * Naoyuki Kamatani3 * Tatsuhiko Tsunoda4 * Yoshiaki Toyama2 * Michiaki Kubo12 * Morio Matsumoto2 * Shiro Ikegawa1 * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:1237–1240Year published:(2011)DOI:doi:10.1038/ng.974Received25 July 2011Accepted19 September 2011Published online23 October 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Adolescent idiopathic scoliosis is a pediatric spinal deformity affecting 2–3% of school-age children worldwide1. Genetic factors have been implicated in its etiology2. Through a genome-wide association study (GWAS) and replication study involving a total of 1,376 Japanese females with adolescent idiopathic scoliosis and 11,297 female controls, we identified a locus at chromosome 10q24.31 associated with adolescent idiopathic scoliosis susceptibility. The most significant SNP (rs11190870; combined P = 1.24 × 10−19; odds ratio (OR) = 1.56) is located near LBX1 (encoding ladybird homeobox 1). The identification of this susceptibility locus provides new insights into the pathogenesis of adolescent idiopathic scoliosis. View full text Figures at a glance * Figure 1: Manhattan plot showing the P values from the genome-wide association study (Cochran-Armitage trend test). The horizontal line represents the genome-wide significance threshold (P = 1.0 × 10−7). * Figure 2: LD map, genomic structure and P-value plot of the adolescent idiopathic scoliosis susceptibility locus at chromosome 10q24. () The LD map (r2) was drawn using loci with MAF ≥0.10 from Phase II HapMap (release 24) JPT individuals. The genotyped SNPs in the GWAS are boxed. All SNPs are shaded according to their pairwise r2 value. () The association results are shown as −log10 of Cochran-Armitage trend P values. The black diamonds and white squares represent the result of the GWAS and the imputation analysis, respectively. The rs11190870 SNP, located 3′ of LBX1, is the SNP most significantly associated with adolescent idiopathic scoliosis. Author information * Author information * Supplementary information Affiliations * Laboratory of Bone and Joint Diseases, Center for Genomic Medicine, RIKEN, Tokyo, Japan. * Yohei Takahashi, * Ikuyo Kou & * Shiro Ikegawa * Department of Orthopaedic Surgery, School of Medicine, Keio University, Tokyo, Japan. * Yohei Takahashi, * Kota Watanabe, * Kazuhiro Chiba, * Yoshiaki Toyama & * Morio Matsumoto * Laboratory for Statistical Analysis, Center for Genomic Medicine, RIKEN, Yokohama, Japan. * Atsushi Takahashi & * Naoyuki Kamatani * Laboratory for Medical Informatics, Center for Genomic Medicine, RIKEN, Yokohama, Japan. * Todd A Johnson & * Tatsuhiko Tsunoda * Scoliosis Center, Saiseikai Central Hospital, Tokyo, Japan. * Katsuki Kono * Department of Orthopaedic Surgery, Meijo Hospital, Nagoya, Japan. * Noriaki Kawakami & * Taichi Tsuji * Department of Orthopaedic Surgery, National Hospital Organization, Kobe Medical Center, Kobe, Japan. * Koki Uno & * Teppei Suzuki * Department of Advanced Medicine for Spine and Spinal Cord Disorders, Hokkaido University Graduate School of Medicine, Sapporo, Japan. * Manabu Ito & * Hideki Sudo * Department of Orthopaedic Surgery, Seirei Sakura Citizen Hospital, Sakura, Japan. * Shohei Minami & * Toshiaki Kotani * Department of Orthopaedic Surgery, Fukuoka Children's Hospital, Fukuoka, Japan. * Haruhisa Yanagida * Department of Orthopaedic Surgery, Dokkyo Medical University School of Medicine, Mibu, Japan. * Hiroshi Taneichi * Laboratory for Genotyping Development, Center for Genomic Medicine, RIKEN, Yokohama, Japan. * Naoya Hosono & * Michiaki Kubo Contributions Y. Takahashi, K.C., M.M. and S.I. designed the study. M.K. and N. Kamatani contributed to overall GWAS design. Y. Takahashi, Y. Toyama, M.M. and S.I. drafted the manuscript. A.T., T.A.J. and T. Tsunoda analyzed the GWAS data. N.H. and M.K. performed the genotyping for the GWAS. M.M., K.K., K.W., N. Kawakami, T. Tsuji, K.U., T.S., M.I., H.S., S.M., T.K., H.Y. and H.T. managed DNA samples from individuals with adolescent idiopathic scoliosis and clinical data. M.K. managed DNA samples from control individuals. Y. Takahashi, I.K., M.M. and S.I. summarized the results. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Shiro Ikegawa Author Details * Yohei Takahashi Search for this author in: * NPG journals * PubMed * Google Scholar * Ikuyo Kou Search for this author in: * NPG journals * PubMed * Google Scholar * Atsushi Takahashi Search for this author in: * NPG journals * PubMed * Google Scholar * Todd A Johnson Search for this author in: * NPG journals * PubMed * Google Scholar * Katsuki Kono Search for this author in: * NPG journals * PubMed * Google Scholar * Noriaki Kawakami Search for this author in: * NPG journals * PubMed * Google Scholar * Koki Uno Search for this author in: * NPG journals * PubMed * Google Scholar * Manabu Ito Search for this author in: * NPG journals * PubMed * Google Scholar * Shohei Minami Search for this author in: * NPG journals * PubMed * Google Scholar * Haruhisa Yanagida Search for this author in: * NPG journals * PubMed * Google Scholar * Hiroshi Taneichi Search for this author in: * NPG journals * PubMed * Google Scholar * Taichi Tsuji Search for this author in: * NPG journals * PubMed * Google Scholar * Teppei Suzuki Search for this author in: * NPG journals * PubMed * Google Scholar * Hideki Sudo Search for this author in: * NPG journals * PubMed * Google Scholar * Toshiaki Kotani Search for this author in: * NPG journals * PubMed * Google Scholar * Kota Watanabe Search for this author in: * NPG journals * PubMed * Google Scholar * Kazuhiro Chiba Search for this author in: * NPG journals * PubMed * Google Scholar * Naoya Hosono Search for this author in: * NPG journals * PubMed * Google Scholar * Naoyuki Kamatani Search for this author in: * NPG journals * PubMed * Google Scholar * Tatsuhiko Tsunoda Search for this author in: * NPG journals * PubMed * Google Scholar * Yoshiaki Toyama Search for this author in: * NPG journals * PubMed * Google Scholar * Michiaki Kubo Search for this author in: * NPG journals * PubMed * Google Scholar * Morio Matsumoto Search for this author in: * NPG journals * PubMed * Google Scholar * Shiro Ikegawa Contact Shiro Ikegawa Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1-5 and Supplementary Tables 1 and 2 Additional data
• Genome-wide association study identifies FCGR2A as a susceptibility locus for Kawasaki disease
  - Nat Genet 43(12):1241-1246 (2011)
  Nature Genetics | Letter Genome-wide association study identifies FCGR2A as a susceptibility locus for Kawasaki disease * Chiea Chuen Khor1, 2, 3, 73 * Sonia Davila2, 4, 73 * Willemijn B Breunis5, 6, 73 * Yi-Ching Lee7 * Chisato Shimizu8, 9 * Victoria J Wright10 * Rae S M Yeung11, 12, 13 * Dennis E K Tan4 * Kar Seng Sim4 * Jie Jin Wang14, 15 * Tien Yin Wong14, 16, 17 * Junxiong Pang1, 18 * Paul Mitchell14 * Rolando Cimaz19, 20 * Nagib Dahdah21 * Yiu-Fai Cheung22 * Guo-Ying Huang23 * Wanling Yang22 * In-Sook Park24 * Jong-Keuk Lee25 * Jer-Yuarn Wu7 * Michael Levin10, 74 * Jane C Burns8, 9, 74 * David Burgner26, 27, 74 * Taco W Kuijpers5, 6, 74 * Martin L Hibberd1, 3, 74 * Hong Kong–Shanghai Kawasaki Disease Genetics Consortium72 * Korean Kawasaki Disease Genetics Consortium72 * Taiwan Kawasaki Disease Genetics Consortium74 * International Kawasaki Disease Genetics Consortium72 * US Kawasaki Disease Genetics Consortium72 * Blue Mountains Eye Study72 * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:1241–1246Year published:(2011)DOI:doi:10.1038/ng.981Received27 May 2011Accepted22 September 2011Published online13 November 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Kawasaki disease is a systemic vasculitis of unknown etiology, with clinical observations suggesting a substantial genetic contribution to disease susceptibility. We conducted a genome-wide association study and replication analysis in 2,173 individuals with Kawasaki disease and 9,383 controls from five independent sample collections. Two loci exceeded the formal threshold for genome-wide significance. The first locus is a functional polymorphism in the IgG receptor gene FCGR2A (encoding an H131R substitution) (rs1801274; P = 7.35 × 10−11, odds ratio (OR) = 1.32), with the A allele (coding for histadine) conferring elevated disease risk. The second locus is at 19q13, (P = 2.51 × 10−9, OR = 1.42 for the rs2233152 SNP near MIA and RAB4B; P = 1.68 × 10−12, OR = 1.52 for rs28493229 in ITPKC), which confirms previous findings1. The involvement of the FCGR2A locus may have implications for understanding immune activation in Kawasaki disease pathogenesis and the mechanism ! of response to intravenous immunoglobulin, the only proven therapy for this disease. View full text Accession codes * Accession codes * Author information * Supplementary information Referenced accessions GenBank * NM_001136219 * NM_021642 * NM_025194 * NM_001202553 * NM_006533 * NM_016154 Author information * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Chiea Chuen Khor, * Sonia Davila & * Willemijn B Breunis Affiliations * Infectious Diseases, Genome Institute of Singapore, Singapore. * Chiea Chuen Khor, * Junxiong Pang & * Martin L Hibberd * National University of Singapore–Genome Institute of Singapore Centre for Molecular Epidemiology, Singapore. * Chiea Chuen Khor & * Sonia Davila * Department of Paediatrics, Faculty of Medicine, National University of Singapore, Singapore. * Chiea Chuen Khor & * Martin L Hibberd * Human Genetics, Genome Institute of Singapore, Singapore. * Sonia Davila, * Dennis E K Tan & * Kar Seng Sim * Department of Pediatric Hematology, Immunology and Infectious Diseases, Emma Children's Hospital Academic Medical Center, Amsterdam, The Netherlands. * Willemijn B Breunis & * Taco W Kuijpers * Department of Blood Cell Research, Sanquin Research and Landsteiner Laboratory, University of Amsterdam, Amsterdam, The Netherlands. * Willemijn B Breunis & * Taco W Kuijpers * Institute of Biomedical Sciences, Academia Sinica, Nankang, Taipei, Taiwan. * Yi-Ching Lee & * Jer-Yuarn Wu * Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California, USA. * Chisato Shimizu & * Jane C Burns * Department of Pediatrics, Rady Children's Hospital, San Diego, California, USA. * Chisato Shimizu & * Jane C Burns * Department of Pediatrics, Imperial College London, London, UK. * Victoria J Wright & * Michael Levin * Department of Pediatrics, University of Toronto, The Hospital for Sick Children, Toronto, Ontario, Canada. * Rae S M Yeung * Department of Immunology, University of Toronto, The Hospital for Sick Children, Toronto, Canada. * Rae S M Yeung * Department of Medical Science, University of Toronto, The Hospital for Sick Children, Toronto, Canada. * Rae S M Yeung * Centre for Eye Research Australia, University of Melbourne, Melbourne, Victoria, Australia. * Jie Jin Wang, * Tien Yin Wong & * Paul Mitchell * Centre for Vision Research, The University of Sydney, Sydney, New South Wales, Australia. * Jie Jin Wang * Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. * Tien Yin Wong * Singapore Eye Research Institute, Singapore National Eye Centre, Singapore. * Tien Yin Wong * Department of Epidemiology and Public Health, Faculty of Medicine, National University of Singapore, Singapore. * Junxiong Pang * Rheumatology Unit, Anna Meyer Children's Hospital, Florence, Italy. * Rolando Cimaz * Department of Pediatrics, University of Florence, Florence, Italy. * Rolando Cimaz * Division of Pediatric Cardiology, Sainte-Justine University Hospital Center, University of Montreal, Montreal, Quebec, Canada. * Nagib Dahdah * Department of Paediatrics and Adolescent Medicine, The University of Hong Kong, Hong Kong. * Yiu-Fai Cheung, * Wanling Yang, * Yu-Lung Lau & * Jing Zhang * Pediatric Cardiovascular Center, Children's Hospital, Fudan University, Shanghai, China. * Guo-Ying Huang * Department of Pediatrics, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea. * In-Sook Park & * Nigel Curtis * Asan Institute for Life Sciences, University of Ulsan College of Medicine, Seoul, South Korea. * Jong-Keuk Lee, * Jae-Jung Kim, * Young-Mi Park & * Miranda Odam * Murdoch Childrens Research Institute, The Royal Children's Hospital, Parkville, Victoria, Australia. * David Burgner * School of Paediatrics and Child Health, University of Western Australia, Perth, Western Australia, Australia. * David Burgner * Pediatric Cardiovascular Center, Children's Hospital, Fudan University, Shanghai, China. * Xiao-Jing Ma, * Fang Liu & * Lin Wu * Department of Pediatrics, Asan Medical Center, Seoul, Korea. * Jeong-Jin Yoo, * Soo-Jong Hong & * Kwi-Joo Kim * Department of Pediatrics, Ewha Womans University Hospital, Seoul, Korea. * Young Mi Hong & * Sejung Sohn * Department of Pediatrics, Korea University Hospital, Seoul, Korea. * Gi Young Jang, * Kee-Soo Ha, * Hyo-Kyoung Nam & * Jung-Hye Byeon * Department of Pediatrics, Chung-Ang University Hospital, Seoul, Korea. * Sin Weon Yun * Department of Pediatrics, University of Ulsan, Gangneung Asan Hospital, Gangneung, Korea. * Myung Ki Han * Department of Pediatrics, The Catholic University of Korea, Daejeon St. Mary's Hospital, Daejeon, Korea. * Kyung-Yil Lee, * Ja-Young Hwang & * Jung-Woo Rhim * Department of Pediatrics, Inje University Paik Hospital, Busan, Korea. * Min Seob Song * Department of Pediatrics, Pusan National University Hospital, Busan, Korea. * Hyoung-Doo Lee * Department of Pediatrics, Yonsei University College of Medicine, Severance Children's Hospital, Seoul, Korea. * Dong Soo Kim * Seoul Clinical Laboratories, Seoul, Korea. * Jae-Moo Lee * Department of Pediatrics, China Medical University and Hospital, Taichung, Taiwan. * Jeng-Sheng Chang & * Fuu-Jen Tsai * Department of Pediatrics, Chang Gung Memorial Hospital–Kaohsiung Medical Center, Kaohsiung, Taiwan. * Chi-Di Liang, * Ho-Chang Kuo & * Kao-Pin Huang * Department of Pediatrics, Mackay Memorial Hospital, Taipei, Taiwan. * Ming-Ren Chen, * Hsin Chi, * Nan-Chang Chiu & * Fu-Yuan Huang * Department of Pediatrics, National Taiwan University Hospital, Taipei, Taiwan. * Luan-Yin Chang & * Li-Min Huang * Department of Allergy and Immunology, Chang Gung Memorial Hospital–Kaohsiung Medical Center, Kaohsiung, Taiwan. * Ho-Chang Kuo & * Kao-Pin Huang * Department of Pediatrics and Division of Pediatric Cardiology, Changhua Christian Hospital, Changhua, Taiwan. * Meng-Luen Lee * Department of Pediatrics, Taipei City Hospital, Zhongxiao Branch, Taipei, Taiwan. * Betau Hwang * Department of Pediatrics, Chang Gung Memorial Hospital, Linkou, Taiwan. * Yhu-Chering Huang * Department of Pediatrics, Taipei Veterans General Hospital, Taipei, Taiwan. * Pi-Chang Lee * School of Pathology and Laboratory Medicine, University of Western Australia, Perth, Western Australia, Australia. * Miranda Odam & * Frank T Christiansen * Department of Clinical Immunology and Immunogenetics, PathWest Royal Perth Hospital, Perth, Western Australia, Australia. * Campbell Witt * SA Pathology at the Women's and Children's Hospital, North Adelaide, South Australia, Australia. * Paul Goldwater * School of Paediatrics and Reproductive Health, University of Adelaide, Adelaide, South Australia, Australia. * Paul Goldwater * The University of Melbourne and Royal Children's Hospital Melbourne, Parkville, Victoria, Australia. * Nigel Curtis * Paediatric HIV Service, Sydney Children's Hospital, Randwick, New South Wales, Australia. * Pamela Palasanthiran & * John Ziegler * Australian Infectious Disease Centre, School of Medicine, Faculty of Health Sciences, University of Queensland, Brisbane, Queensland, Australia. * Michael Nissen * Mater Children's Hospital, Faculty of Paediatrics, University of Queensland, Brisbane, Queensland, Australia. * Clare Nourse * Emma Children's Hospital Academic Medical Center, Amsterdam, The Netherlands. * Irene M Kuipers, * Jaap J Ottenkamp, * Judy Geissler, * Maarten Biezeveld & * Carline Tacke * Department of Paediatrics, Juliana Children's Hospital, The Hague, The Netherlands. * Luc Filippini * Infectious Disease and Microbiology, The Institute of Child Health, London, UK. * Paul Brogan, * Nigel Klein, * Vanita Shah & * Michael Dillon * Academic Unit of Paediatrics, Barts and The London School of Medicine and Dentistry, Royal London Hospital, London, UK. * Robert Booy, * Delane Shingadia, * Anu Bose & * Thomas Mukasa * Bristol Congenital Heart Centre, University Hospitals Bristol National Health Services Foundation Trust, Bristol, UK. * Robert Tulloh * Department of Paediatrics, Ealing Hospital, London, UK. * Colin Michie * Department of Cardiology, Boston Children's Hospital, Boston, Massachusetts, USA. * Jane W Newburger & * Annette L Baker * Department of Pediatrics, Northwestern University Feinberg School of Medicine, Children's Memorial Hospital, Chicago, Illinois, USA. * Anne H Rowley & * Stanford T Shulman * Department of Pediatrics, Children's Hospital Los Angeles, California, USA. * Wilbert Mason * Department of Cardiology, Los Angeles Children's Hospital, Los Angeles, California, USA. * Masato Takahashi * Department of Pediatrics, Kapliolani Children's Hospital, Honolulu, Hawaii, USA. * Marian E Melish * Department of Pediatrics, Children's Hospital Los Angeles, California, USA. * Adriana H Tremoulet * National Institute for Health Research Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital National Health Services Foundation Trust and University College London Institute of Ophthalmology, London, UK. * Ananth Viswanathan * Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute, The University of Sydney, Sydney, New South Wales, Australia. * Elena Rochtchina * Hunter Medical Research Institute, Newcastle, New South Wales, Australia. * John Attia, * Rodney Scott & * Elizabeth Holliday * Department of Physiology, University of Melbourne, Melbourne, Victoria, Australia. * Stephen Harrap * A complete list of authors and affiliations appears at the end of this paper. * Hong Kong–Shanghai Kawasaki Disease Genetics Consortium, * Korean Kawasaki Disease Genetics Consortium, * International Kawasaki Disease Genetics Consortium, * US Kawasaki Disease Genetics Consortium & * Blue Mountains Eye Study * These authors jointly directed this work. * Taiwan Kawasaki Disease Genetics Consortium, * Michael Levin, * Jane C Burns, * David Burgner, * Taco W Kuijpers & * Martin L Hibberd Consortia * Hong Kong–Shanghai Kawasaki Disease Genetics Consortium * Yu-Lung Lau, * Jing Zhang, * Xiao-Jing Ma, * Fang Liu & * Lin Wu * Korean Kawasaki Disease Genetics Consortium * Jeong-Jin Yoo, * Soo-Jong Hong, * Kwi-Joo Kim, * Jae-Jung Kim, * Young-Mi Park, * Young Mi Hong, * Sejung Sohn, * Gi Young Jang, * Kee-Soo Ha, * Hyo-Kyoung Nam, * Jung-Hye Byeon, * Sin Weon Yun, * Myung Ki Han, * Kyung-Yil Lee, * Ja-Young Hwang, * Jung-Woo Rhim, * Min Seob Song, * Hyoung-Doo Lee, * Dong Soo Kim & * Jae-Moo Lee * Taiwan Kawasaki Disease Genetics Consortium * Jeng-Sheng Chang, * Fuu-Jen Tsai, * Chi-Di Liang, * Ming-Ren Chen, * Hsin Chi, * Nan-Chang Chiu, * Fu-Yuan Huang, * Luan-Yin Chang, * Li-Min Huang, * Ho-Chang Kuo, * Kao-Pin Huang, * Meng-Luen Lee, * Betau Hwang, * Yhu-Chering Huang & * Pi-Chang Lee * International Kawasaki Disease Genetics Consortium * Miranda Odam, * Frank T Christiansen, * Campbell Witt, * Paul Goldwater, * Nigel Curtis, * Pamela Palasanthiran, * John Ziegler, * Michael Nissen, * Clare Nourse, * Irene M Kuipers, * Jaap J Ottenkamp, * Judy Geissler, * Maarten Biezeveld, * Carline Tacke, * Luc Filippini, * Paul Brogan, * Nigel Klein, * Vanita Shah, * Michael Dillon, * Robert Booy, * Delane Shingadia, * Anu Bose, * Thomas Mukasa, * Robert Tulloh & * Colin Michie * US Kawasaki Disease Genetics Consortium * Jane W Newburger, * Annette L Baker, * Anne H Rowley, * Stanford T Shulman, * Wilbert Mason, * Masato Takahashi, * Marian E Melish & * Adriana H Tremoulet * Blue Mountains Eye Study * Ananth Viswanathan, * Elena Rochtchina, * John Attia, * Rodney Scott, * Elizabeth Holliday & * Stephen Harrap Contributions M.L., J.C.B., D.B., T.W.K. and M.L.H. are the principal investigators who conceived of and obtained funding for this project. C.C.K. and S.D. organized and supervised the GWAS and replication genotyping pipeline, devised the overall analysis plan and wrote the first draft of the manuscript with input from W.B.B., M.L., J.C.B., D.B., T.W.K., M.L.H., T.Y.W., J.-Y.W., J.-K.L. and Y.-F.C. C.C.K., S.D., W.B.B.,Y.-C.L., K.S.S., W.Y. and J.-Y.W. analyzed the data. W.B.B., C.S., V.J.W., R.S.M.Y., J.J.W., T.Y.W., P.M., R.C., N.D., Y.-F.C., G.-Y.H., W.Y., I.-S.P., J.-K.L. and J.-Y.W. coordinated and contributed subjects and database phenotype collections as lead investigators for their respective sample collections. D.E.K.T. and J.P. performed genotyping and DNA quality control analysis. All authors critically reviewed the manuscript revisions and contributed intellectually to the final manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Michael Levin or * Jane C Burns or * David Burgner or * Taco W Kuijpers or * Martin L Hibberd Author Details * Chiea Chuen Khor Search for this author in: * NPG journals * PubMed * Google Scholar * Sonia Davila Search for this author in: * NPG journals * PubMed * Google Scholar * Willemijn B Breunis Search for this author in: * NPG journals * PubMed * Google Scholar * Yi-Ching Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Chisato Shimizu Search for this author in: * NPG journals * PubMed * Google Scholar * Victoria J Wright Search for this author in: * NPG journals * PubMed * Google Scholar * Rae S M Yeung Search for this author in: * NPG journals * PubMed * Google Scholar * Dennis E K Tan Search for this author in: * NPG journals * PubMed * Google Scholar * Kar Seng Sim Search for this author in: * NPG journals * PubMed * Google Scholar * Jie Jin Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Tien Yin Wong Search for this author in: * NPG journals * PubMed * Google Scholar * Junxiong Pang Search for this author in: * NPG journals * PubMed * Google Scholar * Paul Mitchell Search for this author in: * NPG journals * PubMed * Google Scholar * Rolando Cimaz Search for this author in: * NPG journals * PubMed * Google Scholar * Nagib Dahdah Search for this author in: * NPG journals * PubMed * Google Scholar * Yiu-Fai Cheung Search for this author in: * NPG journals * PubMed * Google Scholar * Guo-Ying Huang Search for this author in: * NPG journals * PubMed * Google Scholar * Wanling Yang Search for this author in: * NPG journals * PubMed * Google Scholar * In-Sook Park Search for this author in: * NPG journals * PubMed * Google Scholar * Jong-Keuk Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Jer-Yuarn Wu Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Levin Contact Michael Levin Search for this author in: * NPG journals * PubMed * Google Scholar * Jane C Burns Contact Jane C Burns Search for this author in: * NPG journals * PubMed * Google Scholar * David Burgner Contact David Burgner Search for this author in: * NPG journals * PubMed * Google Scholar * Taco W Kuijpers Contact Taco W Kuijpers Search for this author in: * NPG journals * PubMed * Google Scholar * Martin L Hibberd Contact Martin L Hibberd Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (565K) Supplementary Note, Supplementary Tables 1–7 and Supplementary Figures 1–4 Additional data
• Identification of two new loci at IL23R and RAB32 that influence susceptibility to leprosy
  - Nat Genet 43(12):1247-1251 (2011)
  Nature Genetics | Letter Identification of two new loci at IL23R and RAB32 that influence susceptibility to leprosy * Furen Zhang1, 2, 3, 4 * Hong Liu1, 3 * Shumin Chen1, 3 * Huiqi Low5 * Liangdan Sun6, 7 * Yong Cui6, 7 * Tongsheng Chu1, 3 * Yi Li5 * Xi'an Fu1, 3 * Yongxiang Yu1, 3 * Gongqi Yu1, 3 * Benqing Shi2, 4 * Hongqing Tian2, 4 * Dianchang Liu1, 3 * Xiulu Yu1, 3 * Jinghui Li1, 3 * Nan Lu1, 3 * Fangfang Bao1, 3 * Chunying Yuan1, 3 * Jian Liu1, 3 * Huaxu Liu1, 3 * Lin Zhang1, 3 * Yonghu Sun1, 3 * Mingfei Chen1, 3 * Qing Yang1, 3 * Haitao Yang8 * Rongde Yang9 * Lianhua Zhang8 * Qiang Wang10 * Hong Liu1, 3 * Fuguang Zuo1, 3 * Haizhen Zhang1, 3 * Chiea Chuen Khor5, 11 * Martin L Hibberd5, 12 * Sen Yang6, 7 * Jianjun Liu1, 5, 11, 13 * Xuejun Zhang6, 7 * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:1247–1251Year published:(2011)DOI:doi:10.1038/ng.973Received09 May 2011Accepted19 September 2011Published online23 October 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We performed a genome-wide association study with 706 individuals with leprosy and 5,581 control individuals and replicated the top 24 SNPs in three independent replication samples, including a total of 3,301 individuals with leprosy and 5,299 control individuals from China. Two loci not previously associated with the disease were identified with genome-wide significance: rs2275606 (combined P = 3.94 × 10−14, OR = 1.30) on 6q24.3 and rs3762318 (combined P = 3.27 × 10−11, OR = 0.69) on 1p31.3. These associations implicate IL23R and RAB32 as new susceptibility genes for leprosy. Furthermore, we identified evidence of interaction between the NOD2 and RIPK2 loci, which is consistent with the biological association of the proteins encoded by these genes (NOD2-RIPK2 complex) in activating the NF-κB pathway as a part of the host defense response to infection. Our findings have expanded the biological functions of IL23R by uncovering its involvement in infectious disease susc! eptibility and suggest a potential involvement of autophagocytosis in leprosy pathogenesis. The IL23R association supports previous observations of the marked overlap of susceptibility genes for leprosy and Crohn's disease, implying common pathogenesis mechanisms. View full text Author information * Author information * Supplementary information Affiliations * Shandong Provincial Institute of Dermatology and Venereology, Provincial Academy of Medical Science, Jinan, China. * Furen Zhang, * Hong Liu, * Shumin Chen, * Tongsheng Chu, * Xi'an Fu, * Yongxiang Yu, * Gongqi Yu, * Dianchang Liu, * Xiulu Yu, * Jinghui Li, * Nan Lu, * Fangfang Bao, * Chunying Yuan, * Jian Liu, * Huaxu Liu, * Lin Zhang, * Yonghu Sun, * Mingfei Chen, * Qing Yang, * Hong Liu, * Fuguang Zuo, * Haizhen Zhang & * Jianjun Liu * Shandong Provincial Hospital for Skin Diseases, Shandong University, Jinan, China. * Furen Zhang, * Benqing Shi & * Hongqing Tian * Shandong Provincial Key Lab for Dermatovenereology, Jinan, China. * Furen Zhang, * Hong Liu, * Shumin Chen, * Tongsheng Chu, * Xi'an Fu, * Yongxiang Yu, * Gongqi Yu, * Dianchang Liu, * Xiulu Yu, * Jinghui Li, * Nan Lu, * Fangfang Bao, * Chunying Yuan, * Jian Liu, * Huaxu Liu, * Lin Zhang, * Yonghu Sun, * Mingfei Chen, * Qing Yang, * Hong Liu, * Fuguang Zuo & * Haizhen Zhang * Shandong Provincial Medical Center for Dermatovenereology, Jinan, China. * Furen Zhang, * Benqing Shi & * Hongqing Tian * Human Genetics, Genome Institute of Singapore, A*STAR, Singapore. * Huiqi Low, * Yi Li, * Chiea Chuen Khor, * Martin L Hibberd & * Jianjun Liu * Institute of Dermatology and Department of Dermatology at No.1 hospital, Anhui Medical University, Hefei, China. * Liangdan Sun, * Yong Cui, * Sen Yang & * Xuejun Zhang * State Key Laboratory Incubation Base of Dermatology, Ministry of National Science and Technology, Hefei, China. * Liangdan Sun, * Yong Cui, * Sen Yang & * Xuejun Zhang * Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China. * Haitao Yang & * Lianhua Zhang * Wenshan Institute of Dermatology, Wenshan, China. * Rongde Yang * Anhui Provincial Institute of Dermatology, Hefei, China. * Qiang Wang * Center for Molecular Epidemiology, National University of Singapore, Singapore. * Chiea Chuen Khor & * Jianjun Liu * Department of Epidemiology and Public Health, National University of Singapore, Singapore. . * Martin L Hibberd * School of Life Sciences, Anhui Medical University, Hefei, China. * Jianjun Liu Contributions F. Zhang, X.Z. and Jianjun Liu conceived of and designed the study. S.C., T.C., X.Y., Lin Zhang, D.L., R.Y., H.Y., Lianhua Zhang and Q.W. undertook recruitment and collected phenotype data. Hong Liu, X.F., G.Y., Y.Y., Q.L., F.B., N.L., C.Y., Y.S., M.C., Hong Liu, H.Z., F. Zuo and Q.Y. conducted sample selection and performed the genotyping of the validation study. Hong Liu, X.F., Jian Liu, B.S., H.T. and Huaxu Liu collected phenotype data, undertook related data handling and calculation, managed recruitment and obtained biological samples. Jianjun Liu, H. Low, Hong Liu and Y.L. undertook data checking, statistical analysis and bioinformatics analyses. S.Y., Hong Liu, L.S. and Y.C. were responsible for sample selection, genotyping and project management. C.C.K. and M.L.H. helped to revise the manuscript. All authors contributed to the final manuscript, with F. Zhang, Jianjun Liu, X.Z. and Hong Liu having key roles. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Furen Zhang Author Details * Furen Zhang Contact Furen Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Hong Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Shumin Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Huiqi Low Search for this author in: * NPG journals * PubMed * Google Scholar * Liangdan Sun Search for this author in: * NPG journals * PubMed * Google Scholar * Yong Cui Search for this author in: * NPG journals * PubMed * Google Scholar * Tongsheng Chu Search for this author in: * NPG journals * PubMed * Google Scholar * Yi Li Search for this author in: * NPG journals * PubMed * Google Scholar * Xi'an Fu Search for this author in: * NPG journals * PubMed * Google Scholar * Yongxiang Yu Search for this author in: * NPG journals * PubMed * Google Scholar * Gongqi Yu Search for this author in: * NPG journals * PubMed * Google Scholar * Benqing Shi Search for this author in: * NPG journals * PubMed * Google Scholar * Hongqing Tian Search for this author in: * NPG journals * PubMed * Google Scholar * Dianchang Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Xiulu Yu Search for this author in: * NPG journals * PubMed * Google Scholar * Jinghui Li Search for this author in: * NPG journals * PubMed * Google Scholar * Nan Lu Search for this author in: * NPG journals * PubMed * Google Scholar * Fangfang Bao Search for this author in: * NPG journals * PubMed * Google Scholar * Chunying Yuan Search for this author in: * NPG journals * PubMed * Google Scholar * Jian Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Huaxu Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Lin Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Yonghu Sun Search for this author in: * NPG journals * PubMed * Google Scholar * Mingfei Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Qing Yang Search for this author in: * NPG journals * PubMed * Google Scholar * Haitao Yang Search for this author in: * NPG journals * PubMed * Google Scholar * Rongde Yang Search for this author in: * NPG journals * PubMed * Google Scholar * Lianhua Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Qiang Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Hong Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Fuguang Zuo Search for this author in: * NPG journals * PubMed * Google Scholar * Haizhen Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Chiea Chuen Khor Search for this author in: * NPG journals * PubMed * Google Scholar * Martin L Hibberd Search for this author in: * NPG journals * PubMed * Google Scholar * Sen Yang Search for this author in: * NPG journals * PubMed * Google Scholar * Jianjun Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Xuejun Zhang Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (578K) Supplementary Tables 1–5 and Supplementary Figures 1-3 Additional data
• Exome sequencing identifies truncating mutations in PRRT2 that cause paroxysmal kinesigenic dyskinesia
  - Nat Genet 43(12):1252-1255 (2011)
  Nature Genetics | Letter Exome sequencing identifies truncating mutations in PRRT2 that cause paroxysmal kinesigenic dyskinesia * Wan-Jin Chen1, 2 * Yu Lin2 * Zhi-Qi Xiong3 * Wei Wei2 * Wang Ni1, 2 * Guo-He Tan3 * Shun-Ling Guo3 * Jin He2 * Ya-Fang Chen2 * Qi-Jie Zhang2 * Hong-Fu Li1 * Yi Lin2 * Shen-Xing Murong2 * Jianfeng Xu4, 5 * Ning Wang2 * Zhi-Ying Wu1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:1252–1255Year published:(2011)DOI:doi:10.1038/ng.1008Received02 June 2011Accepted20 October 2011Published online20 November 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Paroxysmal kinesigenic dyskinesia is the most common type of paroxysmal movement disorder and is often misdiagnosed clinically as epilepsy. Using whole-exome sequencing followed by Sanger sequencing, we identified three truncating mutations within PRRT2 (NM_145239.2) in eight Han Chinese families with histories of paroxysmal kinesigenic dyskinesia: c.514_517delTCTG (p.Ser172Argfs*3) in one family, c.649dupC (p.Arg217Profs*8) in six families and c.972delA (p.Val325Serfs*12) in one family. These truncating mutations co-segregated exactly with the disease in these families and were not observed in 1,000 control subjects of matched ancestry. PRRT2 is a newly discovered gene consisting of four exons encoding the proline-rich transmembrane protein 2, which encompasses 340 amino acids and contains two predicted transmembrane domains. PRRT2 is highly expressed in the developing nervous system, and a truncating mutation alters the subcellular localization of the PRRT2 protein. The fu! nction of PRRT2 and its role in paroxysmal kinesigenic dyskinesia should be further investigated. View full text Figures at a glance * Figure 1: The pedigrees of the eight families affected by paroxysmal kinesigenic dyskinesia included in the present study. Filled-in symbols indicate individuals with paroxysmal kinesigenic dyskinesia, empty circles indicate unaffected individuals, and symbols with a slash through them indicate deceased individuals. #, affected individuals that were found to carry mutations within PRRT2 in mutation analysis; *, unaffected individuals from whom samples were obtained for mutation analysis of PRRT2. Arrows indicate the probands of the families. The mutation present in PRRT2 in each family is indicated in a box below the corresponding pedigree. * Figure 2: PRRT2 protein domain structure. The PRRT2 gene contains four exons that encode several domains in the PRRT2 protein, including two extracellular domains, two transmembrane domains and one cytoplasmic domain. The proline-rich domain overlaps with the N-terminal extracellular domain. * Figure 3: Expression of PRRT2 in the mouse brain. () RT-PCR analysis of PRRT2 mRNA levels in mouse brain, spinal cord, muscle, heart, liver, spleen, lung, kidney and skin. GAPDH was used as an internal control. () RT-PCR analysis of PRRT2 mRNA levels in whole-brain lysates from mice at the indicated stages of development. () PRRT2 mRNA levels in the developing mouse brain (N = 4 at each time point) determined by qPCR and normalized to the levels in P0 mice. Error bars represent s.e.m. () RT-PCR analysis of PRRT2 mRNA levels in the different brain regions. (,) In situ hybridization (ISH) for PRRT2 in the P14 mouse brain. Ctx, cortex; Ob, olfactory bulb; Cb, cerebellum; Tha, thalamus; Hip, hippocampus; Pir, piriform cortex; ML, molecular layer; GCL, granule cell layer; WM, white matter. Roman numerals (I–VI) indicate layers of the cerebral cortex. ISH with sense probe served as a negative control. Scale bars, 300 μm in , 30 μm in . * Figure 4: Truncated PPRT2 has altered cellular localization. () Schematic diagrams of the protein structure of wild-type PRRT2 fused to GFP (WT PRRT2-GFP) and of a truncated form of PRRT2 fused to GFP (Δc PRRT2-GFP). () Representative images showing the localization of WT PRRT2-GFP (left) and Δc PRRT2-GFP (right) in COS-7 cells. Scale bar, 10 μm. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Ensembl * ENSG00000167371 Author information * Accession codes * Author information * Supplementary information Affiliations * Department of Neurology and Institute of Neurology, Huashan Hospital, Institutes of Brain Science and State Key Laboratory of Medical Neurobiology, Shanghai Medical College, Fudan University, Shanghai, China. * Wan-Jin Chen, * Wang Ni, * Hong-Fu Li & * Zhi-Ying Wu * Department of Neurology and Institute of Neurology, First Affiliated Hospital, Fujian Medical University, Fuzhou, China. * Wan-Jin Chen, * Yu Lin, * Wei Wei, * Wang Ni, * Jin He, * Ya-Fang Chen, * Qi-Jie Zhang, * Yi Lin, * Shen-Xing Murong & * Ning Wang * Institute of Neuroscience, State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China. * Zhi-Qi Xiong, * Guo-He Tan & * Shun-Ling Guo * Fudan Institute of Urology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China. * Jianfeng Xu * Fudan–Van Andel Research Institute (VARI) Center for Genetic Epidemiology, School of Life Science, Fudan University, Shanghai, China. * Jianfeng Xu Contributions N.W. and Z.-Y.W. planned the project. Z.-Q.X., J.X., N.W. and Z.-Y.W. conceived of and designed the study. W.-J.C., Yu Lin, Yi Lin, S.-X.M., N.W. and Z.-Y.W. performed the sample collection. W.-J.C., Yu Lin, W.W., W.N., J.H., Y.-F.C., Q.-J.Z. and H.-F.L. performed sequence analysis. J.-F.X. and Z.-Y.W. performed linkage and haplotype analyses. Z.-Q.X., G.-H.T. and S.-L.G. performed the expression analysis. W.-J.C., Z.-Q.X., J.X., N.W. and Z.-Y.W. analyzed the data. W.-J.C., Z.-Q.X. and Z.-Y.W. wrote the manuscript, and J.X. and Z.-Y.W. revised it. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Ning Wang or * Zhi-Ying Wu Author Details * Wan-Jin Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Yu Lin Search for this author in: * NPG journals * PubMed * Google Scholar * Zhi-Qi Xiong Search for this author in: * NPG journals * PubMed * Google Scholar * Wei Wei Search for this author in: * NPG journals * PubMed * Google Scholar * Wang Ni Search for this author in: * NPG journals * PubMed * Google Scholar * Guo-He Tan Search for this author in: * NPG journals * PubMed * Google Scholar * Shun-Ling Guo Search for this author in: * NPG journals * PubMed * Google Scholar * Jin He Search for this author in: * NPG journals * PubMed * Google Scholar * Ya-Fang Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Qi-Jie Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Hong-Fu Li Search for this author in: * NPG journals * PubMed * Google Scholar * Yi Lin Search for this author in: * NPG journals * PubMed * Google Scholar * Shen-Xing Murong Search for this author in: * NPG journals * PubMed * Google Scholar * Jianfeng Xu Search for this author in: * NPG journals * PubMed * Google Scholar * Ning Wang Contact Ning Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Zhi-Ying Wu Contact Zhi-Ying Wu Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–3 and Supplementary Tables 1 and 2 Additional data
• Somatic mosaic IDH1 and IDH2 mutations are associated with enchondroma and spindle cell hemangioma in Ollier disease and Maffucci syndrome
  - Nat Genet 43(12):1256-1261 (2011)
  Nature Genetics | Letter Somatic mosaic IDH1 and IDH2 mutations are associated with enchondroma and spindle cell hemangioma in Ollier disease and Maffucci syndrome * Twinkal C Pansuriya1 * Ronald van Eijk1 * Pio d'Adamo2 * Maayke A J H van Ruler1 * Marieke L Kuijjer1 * Jan Oosting1 * Anne-Marie Cleton-Jansen1 * Jolieke G van Oosterwijk1 * Sofie L J Verbeke1, 3 * Daniëlle Meijer1 * Tom van Wezel1 * Karolin H Nord4 * Luca Sangiorgi5 * Berkin Toker6 * Bernadette Liegl-Atzwanger7 * Mikel San-Julian8 * Raf Sciot9 * Nisha Limaye10 * Lars-Gunnar Kindblom11 * Soeren Daugaard12 * Catherine Godfraind13 * Laurence M Boon9, 14 * Miikka Vikkula9, 15 * Kyle C Kurek16 * Karoly Szuhai17 * Pim J French18 * Judith V M G Bovée1 * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:1256–1261Year published:(2011)DOI:doi:10.1038/ng.1004Received20 June 2011Accepted12 October 2011Published online06 November 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Ollier disease and Maffucci syndrome are non-hereditary skeletal disorders characterized by multiple enchondromas (Ollier disease) combined with spindle cell hemangiomas (Maffucci syndrome). We report somatic heterozygous mutations in IDH1 (c.394C>T encoding an R132C substitution and c.395G>A encoding an R132H substitution) or IDH2 (c.516G>C encoding R172S) in 87% of enchondromas (benign cartilage tumors) and in 70% of spindle cell hemangiomas (benign vascular lesions). In total, 35 of 43 (81%) subjects with Ollier disease and 10 of 13 (77%) with Maffucci syndrome carried IDH1 (98%) or IDH2 (2%) mutations in their tumors. Fourteen of 16 subjects had identical mutations in separate lesions. Immunohistochemistry to detect mutant IDH1 R132H protein suggested intraneoplastic and somatic mosaicism. IDH1 mutations in cartilage tumors were associated with hypermethylation and downregulated expression of several genes. Mutations were also found in 40% of solitary central cartilagino! us tumors and in four chondrosarcoma cell lines, which will enable functional studies to assess the role of IDH1 and IDH2 mutations in tumor formation. View full text Figures at a glance * Figure 1: Frequency of IDH1 and IDH2 alterations. () Distribution of the different Arg132 alterations in IDH1 and Arg172 alterations in IDH2 among the subjects with Ollier disease, Maffucci syndrome and solitary tumors. () Frequency of somatic heterozygous IDH (IDH1 and IDH2) mutations in tumors of subjects with Ollier disease or Maffucci syndrome in comparison to different subtypes of solitary cartilaginous tumors and angiosarcomas. * Figure 2: Immunostaining for mutant IDH1 R132H protein. (,) Enchondroma (L1490) of subject with Ollier disease showing strong cytoplasmic and nuclear staining for IDH1 R132H. Note the mixture of cells expressing wild-type and mutant IDH1 indicating intraneoplastic mosaicism. Overall, the percentage of tumor cells positive for mutant IDH1 ranged from 50–95%. Inset shows viability of the negatively stained cells at higher magnification. () Grade II chondrosarcoma is negative for IDH1 R132H expression. (,) Enchondromas from subjects with Ollier disease showing occasional cells positive for mutant IDH1 in the surrounding normal bone. Some positively stained osteocytes (arrows) and osteoblasts (arrowheads) are seen. T, tumor tissue (scale bars, 5 μm). * Figure 3: CpG island methylator phenotype in enchondromas with IDH1 mutations. Heatmap depicting unsupervised clustering analysis of the 2,000 most variable CpG sites of enchondromas with (orange, N = 8) and without (gray, N = 4) IDH1 mutation. The level of DNA methylation (beta value) for each probe (columns) in each sample (rows) is represented by color, ranging from 0 (0% methylation, blue) to 1 (100% methylation, yellow). The asterisk indicates sample L2357 in which the mutated allele of IDH1 encoding R132G was detected in a subpopulation of cells. However, the mutation escaped detection by Sanger sequencing, and therefore the sample is labeled wild type. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions GenBank * NM_005896.2 * NM_002168.2 Gene Expression Omnibus * GSE30844 Author information * Accession codes * Author information * Supplementary information Affiliations * Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands. * Twinkal C Pansuriya, * Ronald van Eijk, * Maayke A J H van Ruler, * Marieke L Kuijjer, * Jan Oosting, * Anne-Marie Cleton-Jansen, * Jolieke G van Oosterwijk, * Sofie L J Verbeke, * Daniëlle Meijer, * Tom van Wezel & * Judith V M G Bovée * Institute for Maternal and Child Health, Instituto di Ricovero e Cura a Carattere Scientifico, Burlo Garofolo, University of Trieste, Trieste, Italy. * Pio d'Adamo * Department of Pathology, University Hospital Antwerp, Antwerp, Belgium. * Sofie L J Verbeke * Department of Clinical Genetics, Lund University Hospital, Lund, Sweden. * Karolin H Nord * Department of Medical Genetics, Rizzoli Orthopedic Institute, Bologna, Italy. * Luca Sangiorgi * Istanbul University Medical School, Istanbul, Turkey. * Berkin Toker * Institute of Pathology, Medical University, Graz, Austria. * Bernadette Liegl-Atzwanger * Department of Orthopaedic Surgery and Traumatology, University Clinic of Navarra, Pamplona, Spain. * Mikel San-Julian * Department of Pathology, University of Leuven, Leuven, Belgium. * Raf Sciot, * Laurence M Boon & * Miikka Vikkula * de Duve Institute, Université catholique de Louvain, Brussels, Belgium. * Nisha Limaye * Department of Musculoskeletal Pathology, Royal Orthopaedic Hospital, Birmingham, UK. * Lars-Gunnar Kindblom * Department of Pathology, University of Copenhagen, Copenhagen, Denmark. * Soeren Daugaard * Laboratory of Pathology, Cliniques universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium. * Catherine Godfraind * Center for Vascular Anomalies, Division of Plastic Surgery, Cliniques universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium. * Laurence M Boon * Walloon Excellence in Lifesciences and Biotechnology (WELBIO), Université catholique de Louvain, Brussels, Belgium. * Miikka Vikkula * Department of Pathology, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts, USA. * Kyle C Kurek * Department of Molecular Cell Biology, Leiden University Medical Center, Leiden, The Netherlands. * Karoly Szuhai * Department of Neurology, Erasmus University Medical Center, Erasmus University, Rotterdam, The Netherlands. * Pim J French Contributions The study was designed, written and reviewed by T.C.P. and J.V.M.G.B. Mutation analysis was designed and performed by T.C.P., M.A.J.H.v.R., J.V.M.G.B., K.S., T.v.W. and R.v.E. Immunohistochemistry was conducted and evaluated by T.C.P., M.A.J.H.v.R. and J.V.M.G.B. T.C.P., S.L.J.V., J.G.v.O. and D.M. contributed tissue microarrays. Expression profiling was designed and performed by A.-M.C.-J., T.C.P., J.V.M.G.B. and J.O. and analyzed by J.O. and M.L.K. Methylation profiling was designed by A.-M.C.-J., J.V.M.G.B. and L.S., performed by P.d.A., and the results analyzed by P.d.A. and P.J.F. K.H.N., S.D., L.S., B.T., B.L.-A., M.S.-J., R.S., N.L., L.-G.K., C.G., M.V., L.M.B. and K.C.K. each contributed frozen or paraffin-embedded tissues for multiple subjects with Ollier disease or Maffucci syndrome and acquired data for these individuals. The manuscript was approved by all authors. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Judith V M G Bovée Author Details * Twinkal C Pansuriya Search for this author in: * NPG journals * PubMed * Google Scholar * Ronald van Eijk Search for this author in: * NPG journals * PubMed * Google Scholar * Pio d'Adamo Search for this author in: * NPG journals * PubMed * Google Scholar * Maayke A J H van Ruler Search for this author in: * NPG journals * PubMed * Google Scholar * Marieke L Kuijjer Search for this author in: * NPG journals * PubMed * Google Scholar * Jan Oosting Search for this author in: * NPG journals * PubMed * Google Scholar * Anne-Marie Cleton-Jansen Search for this author in: * NPG journals * PubMed * Google Scholar * Jolieke G van Oosterwijk Search for this author in: * NPG journals * PubMed * Google Scholar * Sofie L J Verbeke Search for this author in: * NPG journals * PubMed * Google Scholar * Daniëlle Meijer Search for this author in: * NPG journals * PubMed * Google Scholar * Tom van Wezel Search for this author in: * NPG journals * PubMed * Google Scholar * Karolin H Nord Search for this author in: * NPG journals * PubMed * Google Scholar * Luca Sangiorgi Search for this author in: * NPG journals * PubMed * Google Scholar * Berkin Toker Search for this author in: * NPG journals * PubMed * Google Scholar * Bernadette Liegl-Atzwanger Search for this author in: * NPG journals * PubMed * Google Scholar * Mikel San-Julian Search for this author in: * NPG journals * PubMed * Google Scholar * Raf Sciot Search for this author in: * NPG journals * PubMed * Google Scholar * Nisha Limaye Search for this author in: * NPG journals * PubMed * Google Scholar * Lars-Gunnar Kindblom Search for this author in: * NPG journals * PubMed * Google Scholar * Soeren Daugaard Search for this author in: * NPG journals * PubMed * Google Scholar * Catherine Godfraind Search for this author in: * NPG journals * PubMed * Google Scholar * Laurence M Boon Search for this author in: * NPG journals * PubMed * Google Scholar * Miikka Vikkula Search for this author in: * NPG journals * PubMed * Google Scholar * Kyle C Kurek Search for this author in: * NPG journals * PubMed * Google Scholar * Karoly Szuhai Search for this author in: * NPG journals * PubMed * Google Scholar * Pim J French Search for this author in: * NPG journals * PubMed * Google Scholar * Judith V M G Bovée Contact Judith V M G Bovée Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (22M) Supplementary Figures 1 and 2 and Supplementary Tables 1, 2 and 4–6 Excel files * Supplementary Table 3 (401K) Differentially methylated sites in enchondromas with and without IDH1 mutation at Sanger sequencing Additional data
• Ollier disease and Maffucci syndrome are caused by somatic mosaic mutations of IDH1 and IDH2
  - Nat Genet 43(12):1262-1265 (2011)
  Nature Genetics | Letter Ollier disease and Maffucci syndrome are caused by somatic mosaic mutations of IDH1 and IDH2 * M Fernanda Amary1 * Stephen Damato1, 9 * Dina Halai1, 9 * Malihe Eskandarpour2 * Fitim Berisha1 * Fiona Bonar3 * Stan McCarthy4 * Valeria R Fantin5 * Kimberly S Straley5 * Samira Lobo1 * Will Aston6 * Claire L Green7 * Rosemary E Gale7 * Roberto Tirabosco1 * Andrew Futreal8 * Peter Campbell8 * Nadège Presneau2 * Adrienne M Flanagan1, 2 * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:1262–1265Year published:(2011)DOI:doi:10.1038/ng.994Received31 May 2011Accepted05 October 2011Published online06 November 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Ollier disease and Maffucci syndrome are characterized by multiple central cartilaginous tumors that are accompanied by soft tissue hemangiomas in Maffucci syndrome. We show that in 37 of 40 individuals with these syndromes, at least one tumor has a mutation in isocitrate dehydrogenase 1 (IDH1) or in IDH2, 65% of which result in a R132C substitution in the protein. In 18 of 19 individuals with more than one tumor analyzed, all tumors from a given individual shared the same IDH1 mutation affecting Arg132. In 2 of 12 subjects, a low level of mutated DNA was identified in non-neoplastic tissue. The levels of the metabolite 2HG were measured in a series of central cartilaginous and vascular tumors, including samples from syndromic and nonsyndromic subjects, and these levels correlated strongly with the presence of IDH1 mutations. The findings are compatible with a model in which IDH1 or IDH2 mutations represent early post-zygotic occurrences in individuals with these syndromes. View full text Figures at a glance * Figure 1: Clinical features of individuals with Ollier disease or Maffucci syndrome who harbor an IDH1 mutation encoding an R132C substitution. () Bilateral deformities of several digits caused by cartilaginous tumors and soft tissue hemangiomas in an individual with Maffucci syndrome who has a brain stem glioma. () Plain radiograph showing multiple central cartilaginous tumors in bones of the hand and phleboliths (arrow) representing calcification within a hemangioma. () A sagittal section of tibia showing multiple central cartilaginous tumors from an individual with Ollier disease. () A photomicrograph of the tumor in showing a low-grade intramedullary cartilaginous tumor. * Figure 2: Comparison of 2HG levels in tumors with wild-type (WT) or mutated IDH1 and IDH2. The continuous lines depict the average 2HG values in both tumor groups: 3,852.995 ng/ml (s.d. 12,538.79 ng/ml, range 32.5–9,640 ng/ml) for tumors with WT sequences and 32,294.48 ng/ml (s.d. 25,342.17 ng/ml, range 1,460–102,000 ng/ml) for tumors with mutant IDH1 or IDH2. The open diamonds and circles represent individual tumors from subjects with Ollier disease or Maffucci syndrome that had WT (N = 3) and mutated (N = 4) IDH1 or IDH2 sequences, respectively, from individuals with multiple tumor types. The filled-in circles and squares represent individuals with solitary cartilaginous tumors (N = 44) with WT and mutated sequences, respectively. P < 0.0001 by Mann-Whitney test. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Stephen Damato & * Dina Halai Affiliations * Histopathology Unit, Royal National Orthopaedic Hospital National Health Service Trust, Stanmore, UK. * M Fernanda Amary, * Stephen Damato, * Dina Halai, * Fitim Berisha, * Samira Lobo, * Roberto Tirabosco & * Adrienne M Flanagan * Sarcoma Genetics, University College London Cancer Institute, London, UK. * Malihe Eskandarpour, * Nadège Presneau & * Adrienne M Flanagan * Douglass Hanly Moir Pathology, Sydney, Australia. * Fiona Bonar * School of Medicine, The University of Sydney, Sydney, Australia. * Stan McCarthy * Agios Pharmaceuticals, Cambridge, Massachusetts, USA. * Valeria R Fantin & * Kimberly S Straley * Bone Tumour Unit, Royal National Orthopaedic Hospital National Health Service Trust, Stanmore, UK. * Will Aston * Experimental Therapeutics, University College London Cancer Institute, London, UK. * Claire L Green & * Rosemary E Gale * Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. * Andrew Futreal & * Peter Campbell Contributions A.M.F., M.F.A. and A.F. conceived of the project. A.M.F., M.F.A., A.F., D.H. and N.P. planned the experiments. D.H., M.E., N.P., F. Berisha, S.L., C.L.G. and R.E.G. performed the experiments. F. Bonar, R.T., S.M., A.M.F., M.F.A. and W.A. reviewed the histopathology and selected and provided the samples. V.R.F. and K.S.S. performed 2HG measurements. A.M.F., M.F.A. and S.D. wrote the manuscript. P.C. performed the statistical analysis. All authors reviewed the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Adrienne M Flanagan Author Details * M Fernanda Amary Search for this author in: * NPG journals * PubMed * Google Scholar * Stephen Damato Search for this author in: * NPG journals * PubMed * Google Scholar * Dina Halai Search for this author in: * NPG journals * PubMed * Google Scholar * Malihe Eskandarpour Search for this author in: * NPG journals * PubMed * Google Scholar * Fitim Berisha Search for this author in: * NPG journals * PubMed * Google Scholar * Fiona Bonar Search for this author in: * NPG journals * PubMed * Google Scholar * Stan McCarthy Search for this author in: * NPG journals * PubMed * Google Scholar * Valeria R Fantin Search for this author in: * NPG journals * PubMed * Google Scholar * Kimberly S Straley Search for this author in: * NPG journals * PubMed * Google Scholar * Samira Lobo Search for this author in: * NPG journals * PubMed * Google Scholar * Will Aston Search for this author in: * NPG journals * PubMed * Google Scholar * Claire L Green Search for this author in: * NPG journals * PubMed * Google Scholar * Rosemary E Gale Search for this author in: * NPG journals * PubMed * Google Scholar * Roberto Tirabosco Search for this author in: * NPG journals * PubMed * Google Scholar * Andrew Futreal Search for this author in: * NPG journals * PubMed * Google Scholar * Peter Campbell Search for this author in: * NPG journals * PubMed * Google Scholar * Nadège Presneau Search for this author in: * NPG journals * PubMed * Google Scholar * Adrienne M Flanagan Contact Adrienne M Flanagan Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (262K) Supplementary Tables 1–4 Additional data
• Natural variation in GS5 plays an important role in regulating grain size and yield in rice
  - Nat Genet 43(12):1266-1269 (2011)
  Nature Genetics | Letter Natural variation in GS5 plays an important role in regulating grain size and yield in rice * Yibo Li1 * Chuchuan Fan1 * Yongzhong Xing1 * Yunhe Jiang1 * Lijun Luo1 * Liang Sun1 * Di Shao1 * Chunjue Xu1 * Xianghua Li1 * Jinghua Xiao1 * Yuqing He1 * Qifa Zhang1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:1266–1269Year published:(2011)DOI:doi:10.1038/ng.977Received28 May 2010Accepted21 September 2011Published online23 October 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Increasing crop yield is one of the most important goals of plant science research. Grain size is a major determinant of grain yield in cereals and is a target trait for both domestication and artificial breeding1. We showed that the quantitative trait locus (QTL) GS5 in rice controls grain size by regulating grain width, filling and weight. GS5 encodes a putative serine carboxypeptidase and functions as a positive regulator of grain size, such that higher expression of GS5 is correlated with larger grain size. Sequencing of the promoter region in 51 rice accessions from a wide geographic range identified three haplotypes that seem to be associated with grain width. The results suggest that natural variation in GS5 contributes to grain size diversity in rice and may be useful in improving yield in rice and, potentially, other crops2. View full text Figures at a glance * Figure 1: Map-based cloning of GS5. () Locations of GS5 and qSW5/GW5 in the genetic map. (,) Fine mapping of the GS5 region using two mapping population, with 4,374 and 5,265 plants, respectively. The thick bar represents the genomic region; numbers underneath the bars indicate the numbers of recombinants between GS5 and the molecular marker, and numbers in parentheses indicate the numbers of recombinants (for recombinants no. 30, 8936 and 57-5) whose phenotypes were affected by the qSW5/GW5 genotype and that were not used in fine mapping. () Genotypes of the recombinants assayed by sequencing an 8-kb region between C62 and G8, including the entire coding sequence and 2-kb promoter region (only three well-spaced SNP markers in the promoter region are placed in the map). Each recombinant was phenotyped by progeny testing to deduce the genotype of GS5 (Supplementary Table 2). Genotypes of qSW5/GW5 was determined using two functional markers N1212 and Indel2. A, homozygous for Zhenshan 97 genotype; B, homozygous ! for H94 genotype; H, heterozygote; No., identification number for each recombinant. () GS5 gene structure and natural variations between alleles from Zhenshan 97 and H94. * Figure 2: Effects of GS5 on grain size and filling. () Grains of Zhenshan 97, H94, NIL(ZS97), NIL(H94), Zhonghua 11 and Minghui 63. () Grains of the transformants. OX (+) indicates grains from T1 plants expressing the coding sequence of GS5 from H94 driven by the 35S promoter; ZpHc (+) indicates grains from T1 plants expressing the coding sequence of GS5 driven by the promoter from Zhenshan 97. OX (−) and ZpHc (−) are the corresponding negative segregants. (,) Time-course of grain weight (n = 90 grains for each point). Blue line, NIL(ZS97); black line, NIL(H94). * Figure 3: The effect of GS5 on cell number and size in lemma/palea. () Spikelets of NIL(ZS97) (left) and NIL(H94) (right) 4 d before heading. (,) Cross-sections of palea () and lemma () cut horizontally at the middle of the spikelets shown in . Scale bars, 200 μm for both and . (,) Comparisons of cell number () and cell size () between NIL(ZS97) and NIL(H94) in the cross-sections of the inner parenchyma cell layer of spikelets. All P values are based on two-tailed t-tests. Black bars, NIL(ZS97); yellow bars, NIL(H94). Error bars, s.e.m. * Figure 4: Regulation by GS5 of the expression of genes involved in the cell cycle. () Transcript levels of genes associated with cell cycle regulation in GS5 overexpressor OX(+) relative to negative segregants OX(−). Black bars, OX(−); light bars, OX(+). () Transcript levels of genes associated with cell cycle regulation in the gs5 mutant, relative to wild type. Black bars, wild type; gray bars, mutant. Expression levels were determined by qRT-PCR using 6- to 8-cm young panicles from at least five plants, in at least three biological samples and three replicates. Error bars, s.e.m. All P values are based on two-tailed t-tests. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Entrez Nucleotide * JN256055 * JN256056 * JN256057 * JN256058 GenBank * AK106800 Author information * Accession codes * Author information * Supplementary information Affiliations * National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China. * Yibo Li, * Chuchuan Fan, * Yongzhong Xing, * Yunhe Jiang, * Lijun Luo, * Liang Sun, * Di Shao, * Chunjue Xu, * Xianghua Li, * Jinghua Xiao, * Yuqing He & * Qifa Zhang Contributions Y.L. conducted most of the experiments, including fine mapping, gene cloning, genetic transformation, expression analysis, mutant analysis, histological analysis and other functional analysis; C.F., Y.X. and L.L. conducted the QTL primary mapping analysis and developed the NILs; Y.J. and L.S. carried out part of the cell division and expression analysis; D.S., C.X., X.L. and J.X. participated in the promoter sequencing; Y.H. and Q.Z. designed and supervised the study; and Y.L. and Q.Z. analyzed the data and wrote the paper. All of the authors discussed the results and commented on the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Yuqing He or * Qifa Zhang Author Details * Yibo Li Search for this author in: * NPG journals * PubMed * Google Scholar * Chuchuan Fan Search for this author in: * NPG journals * PubMed * Google Scholar * Yongzhong Xing Search for this author in: * NPG journals * PubMed * Google Scholar * Yunhe Jiang Search for this author in: * NPG journals * PubMed * Google Scholar * Lijun Luo Search for this author in: * NPG journals * PubMed * Google Scholar * Liang Sun Search for this author in: * NPG journals * PubMed * Google Scholar * Di Shao Search for this author in: * NPG journals * PubMed * Google Scholar * Chunjue Xu Search for this author in: * NPG journals * PubMed * Google Scholar * Xianghua Li Search for this author in: * NPG journals * PubMed * Google Scholar * Jinghua Xiao Search for this author in: * NPG journals * PubMed * Google Scholar * Yuqing He Contact Yuqing He Search for this author in: * NPG journals * PubMed * Google Scholar * Qifa Zhang Contact Qifa Zhang Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (840K) Supplementary Tables 1–10 and Supplementary Figures 1–5 Additional data
• Predicting phenotypic variation in yeast from individual genome sequences
  - Nat Genet 43(12):1270-1274 (2011)
  Nature Genetics | Letter Predicting phenotypic variation in yeast from individual genome sequences * Rob Jelier1 * Jennifer I Semple1 * Rosa Garcia-Verdugo1 * Ben Lehner1, 2 * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:1270–1274Year published:(2011)DOI:doi:10.1038/ng.1007Received31 May 2011Accepted19 October 2011Published online13 November 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg A central challenge in genetics is to predict phenotypic variation from individual genome sequences. Here we construct and evaluate phenotypic predictions for 19 strains of Saccharomyces cerevisiae. We use conservation-based methods to predict the impact of protein-coding variation within genes on protein function. We then rank strains using a prediction score that measures the total sum of function-altering changes in different sets of genes reported to influence over 100 phenotypes in genome-wide loss-of-function screens. We evaluate our predictions by comparing them with the observed growth rate and efficiency of 15 strains tested across 20 conditions in quantitative experiments. The median predictive performance, as measured by ROC AUC, was 0.76, and predictions were more accurate when the genes reported to influence a trait were highly connected in a functional gene network. View full text Figures at a glance * Figure 1: Genome-wide reverse genetic approach used to predict S. cerevisiae phenotypic variation from genomic sequences. () Overview of the procedure. First, polymorphisms are identified from high-coverage whole-genome sequences aligned to the S288c reference genome and are evaluated and combined to estimate for each gene whether its function had been altered (see Online Methods). Second, an S score is calculated for each individual strain, which predicts whether a given phenotype will be affected relative to the reference strain. The set of genes relevant for each condition is derived from genome-wide reverse genetic screens using the gene deletion collection. Third, phenotypic predictions are evaluated using quantitative phenotyping experiments. Growth experiments were performed under diverse environmental conditions or in the presence of small molecule inhibitors. For each phenotype, strains were classified according to deviations in either minimal doubling time or growth efficiency beyond a given threshold. The AUC from the ROC curve is used to characterize how well the strains with phenot! ypes are prioritized when sorted according to S score. () To evaluate the effect of nonsynonymous SNPs (resulting in amino acid alterations), the SIFT algorithm is used with a protein sequence alignment as input. Known fungal orthologs are identified, and a more sophisticated alignment algorithm is implemented before the retrieval of more distant homologs. () This substantially improved both coverage and prediction performance for a large reference set of polymorphisms with known functional consequences. * Figure 2: Testing predictive score performance for the identification of phenotypic variations in S. cerevisiae strains. () ROC curves were used to evaluate the prediction of growth phenotypes when strains were grown on the galactose (blue) and glycerol (red) alternative carbon sources. () Quantitative growth data for the 14 tested strains. Row 1, variation in the prediction score S; row 2, normalized deviation in doubling time (Td) expressed in s.d.; row 3, normalized deviation in growth efficiency (GE) expressed in s.d.; row 4, the strains scored with a phenotype (deviation in either Td or GE > 2 s.d.). () AUC performance for 17 conditions in which more than one strain was identified as having a growth defect. Random prediction gives an AUC of 0.5. (–) The significance of the overall AUC prediction is illustrated using three randomization experiments. The red arrow indicates the observed overall AUC. () A bootstrap of the strains (P < 0.0001). () Replacing the contents of the gene sets with genes randomly drawn from the set of genes represented by the haploid gene deletion collection (P < ! 0.0001). () A bootstrap of the gene sets. In this case, the mean of the distribution is shifted to >0.5 as a result of correlations between growth phenotypes (P < 0.001). * Figure 3: Influences on the classification performance of our predictive test score. () Performance, as measured by ROC AUC, of our prediction scores for a given condition and gene set correlates with the functional relationships within that gene set, as evaluated by examining the interactions in the YeastNet version 2 functional network17, 27 (Pearson's correlation = 0.5 between network AUC and ROC AUC from prediction, P = 0.0042). Conditions that matched several systematic gene deletion screens are color coded, and all gene sets are shown. () A higher threshold used to define strains with phenotypes improved predictive performance but reduced the number of strains with a phenotype and the number of conditions considered (conditions dropped out if no strain was considered to have a phenotype). The median prediction AUC is shown for each threshold between 2 and 8 s.d. () Median growth defects of strains with phenotypes for the different conditions. Conditions under which strains had larger Td defects were better predicted. Predictions were worse for conditio! ns in which most strains showed only GE phenotypes. The thresholds to define strains with phenotypes are indicated by the dotted lines. () Td phenotypes were better predicted than GE phenotypes or phenotypes defined by either a Td or GE defect. The mean number of strains with a phenotype per condition is also shown. The Td bar represents 16 conditions, as high CaCl2 concentration caused no Td phenotypes. () Adding false positive genes to the gene sets had a more severe effect on predictive performance than removing genes (introducing false negatives). The lines indicate the mean overall AUC over 100 simulations, and the shaded areas show 1 s.d. The effect of randomly replacing genes (introducing false positives and false negatives) is also shown. () Through network-guided pruning, a large fraction of genes can be removed from each gene set without reducing predictive performance. Genes were removed if they did not interact (or interacted below a log-likelihood score t) with! any other genes in the set in the YeastNet version 2 network.! For t = 1.5, the result is significantly better than random removal (P < 0.01, overall AUC, 1,000 simulations). * Figure 4: Per-gene contributions to overall S score variation across strains for each condition. For each condition, the covariance of the score per gene and S was divided by the variance of the S score as a proxy for the influence of each individual gene on the differences among strains. () Scaled covariance score per gene for each condition. Under some conditions, a few genes contributed considerably to the score differences between strains, whereas in other cases, individual genes contributed very little. In some cases, notably with high NaCl concentration, there were genes with negative covariance that were anti-correlated with the eventual scores per strain. Genes with a scaled covariance between −0.1 and 0.1 are indicated by crosses and other genes by open circles. () Evaluation of the number of genes required to explain the score differences between strains. The number of genes required to reach 50%, 75% and 90% of S variance is shown. Genes were added to the subset in the order of their absolute scaled covariance. Under some conditions, few genes were needed t! o reach 50% of the variance, although a large number of genes contributed to the overall scores. () The fraction of the total gene set for each condition required to achieve the three covariance levels. Author information * Author information * Supplementary information Affiliations * European Molecular Biology Laboratory—Centre for Genomic Regulation (EMBL-CRG) Systems Biology Research Unit, Centre for Genomic Regulation, Barcelona, Spain. * Rob Jelier, * Jennifer I Semple, * Rosa Garcia-Verdugo & * Ben Lehner * Institució Catalana de Recerca Estudis Avançats (ICREA), Centre for Genomic Regulation, Barcelona, Spain. * Ben Lehner Contributions B.L. and R.J. designed the study, evaluated the results and wrote the manuscript. R.J. performed the analyses. J.I.S., R.G.-V. and R.J. designed and performed the growth experiments and sequence validation. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Ben Lehner Author Details * Rob Jelier Search for this author in: * NPG journals * PubMed * Google Scholar * Jennifer I Semple Search for this author in: * NPG journals * PubMed * Google Scholar * Rosa Garcia-Verdugo Search for this author in: * NPG journals * PubMed * Google Scholar * Ben Lehner Contact Ben Lehner Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–5, Supplementary Tables 1 and 7 and Supplementary Note Excel files * Supplementary Table 2 (729K) Curated test set of gold standard positive and gold standard negative sequence variants in yeast proteins. * Supplementary Table 3 (45K) PCR and sequencing results. * Supplementary Table 4 (115K) Phenotypic predictions (Sh,i scores) for each strain based on each of 180 gene sets retrieved from genome-wide gene deletion collection screens. * Supplementary Table 5 (82K) The minimal doubling time and growth efficiency, normalized relative to the growth of S288c as the logarithmic strain coefficient (LSC), for all growth experiments. * Supplementary Table 6 (74K) The mean minimal doubling time and growth efficiency LSC for every condition. * Supplementary Table 8 (139K) Per gene and cumulative covariance over variance statistics. Additional data
• Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes
  - Nat Genet 43(12):1275-1280 (2011)
  Nature Genetics | Letter Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes * Tami D Lieberman1, 12 * Jean-Baptiste Michel1, 2, 12 * Mythili Aingaran3 * Gail Potter-Bynoe4 * Damien Roux5 * Michael R Davis Jr6 * David Skurnik5 * Nicholas Leiby1 * John J LiPuma7, 8 * Joanna B Goldberg6 * Alexander J McAdam9 * Gregory P Priebe3, 5, 10 * Roy Kishony1, 11 * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:1275–1280Year published:(2011)DOI:doi:10.1038/ng.997Received06 April 2011Accepted05 October 2011Published online13 November 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Bacterial pathogens evolve during the infection of their human host1, 2, 3, 4, 5, 6, 7, 8, but separating adaptive and neutral mutations remains challenging9, 10, 11. Here we identify bacterial genes under adaptive evolution by tracking recurrent patterns of mutations in the same pathogenic strain during the infection of multiple individuals. We conducted a retrospective study of a Burkholderia dolosa outbreak among subjects with cystic fibrosis, sequencing the genomes of 112 isolates collected from 14 individuals over 16 years. We find that 17 bacterial genes acquired nonsynonymous mutations in multiple individuals, which indicates parallel adaptive evolution. Mutations in these genes affect important pathogenic phenotypes, including antibiotic resistance and bacterial membrane composition and implicate oxygen-dependent regulation as paramount in lung infections. Several genes have not previously been implicated in pathogenesis and may represent new therapeutic targets. The! identification of parallel molecular evolution as a pathogen spreads among multiple individuals points to the key selection forces it experiences within human hosts. View full text Figures at a glance * Figure 1: Whole-genome sequencing of 112 epidemic B. dolosa isolates recovered from 14 subjects shows the steady accumulation of mutations over years. () An epidemic of B. dolosa spread to 39 individuals with cystic fibrosis (circles) over decades. Time of first attested infection for each subject is indicated in years after the collection of an isolate from patient zero (labeled A). A cohort of 14 individuals from this epidemic (gray circles) was studied retrospectively. () The genomes of 112 bacterial isolates were sequenced (diamonds; each horizontal line corresponds to a subject). Isolates were recovered over time from the subjects' airways (blue), bloodstreams (red) or other body compartments (yellow; for instance, tissue obtained during surgery). () The number of SNPs between each isolate and the outgroup is plotted as a function of time (years since first strain isolated). Linear fit is plotted (slope = 2.1 mutations fixed per year). * Figure 2: Bacterial phylogeny reveals a likely network of transmission between individuals and between organs. () Maximum-likelihood phylogenetic tree (SNP scale). The 112 isolates are indicated by thin dashed lines colored according to subject and labeled according to subject and time (for example, C:14-5 was recovered from subject C, 14 years and 5 months after isolation of the first strain). Blood isolates are indicated by an asterisk, and isolates with the same subject ID and date are distinguished by letters. The LCA of isolates from the same subject is represented as a circle of the appropriate color and label. Colored backgrounds indicate subject-specific genetic fingerprints. Subjects B, C, E and F share the same LCA (white background). () Phylogeny between the inferred LCAs suggests a likely network of infection between subjects (arrows). Dashed arrows indicate less certainty (fewer than three isolates). () Phylogeny between blood and lung isolates recovered from the same subject shows the transmission of multiple clones to the bloodstream during bacteremia (multiple arrows,! subjects K and N). * Figure 3: Pathogenic phenotypes are associated with point mutations in key genes. () Minimal inhibitory concentration (MIC) of ciprofloxacin for each isolate (vertical bars) is correlated with genotypic changes in BDAG_02180, a homolog of E. coli gyrA, which result in coding changes in amino acids 83 and 87. Phylogeny is indicated below as a dendrogram, and genotypes at BDAG_02180 are shown in the legend. () P values for correlation between the presence of mutations in each gene and drug resistance levels (Kendall's tau coefficient,τ). () Silver-stained gels showing the presence of O-antigen repeats (banded pattern) in the LPS of 20 isolates. Phylogeny is indicated below as a dendrogram, and genotypes at BDAG_02317, a homolog of the wbaD glycosyltransferase in E. coli, are shown in the legend. The presentation of O-antigen repeats corresponds to a recurrent gain-of-function mutation. () P values for correlation between the presence of mutations in each gene and O-antigen presentation (Fisher's exact test). * Figure 4: Parallel evolution identifies a set of genes under strong selection during pathogenesis. () The number of genes that acquired at least m mutations during the epidemic is plotted as a function of m (gray bars). This distribution contrasts sharply with the distribution expected for neutral evolution (black line). Under neutral evolution, the expectation is that only one gene would receive three or more mutations (m ≥3); instead, 17 such genes were observed. () The canonical signal for selection (dN/dS) was calculated for the 17 genes with three or more mutations (m ≥3; 109 mutations in all 17 genes), the 28 genes with m = 2 and the 247 genes with m = 1 (Supplementary Fig. 3 presents the contribution of these mutations to the molecular clock). dN/dS >1 indicates positive selection (blue), and dN/dS <1 indicates purifying selection (red). Error bars indicate 95% CIs. Calculated over all genes without regard to m, this analysis would not show selection. () Each of the 17 genes (rows) under positive selection contained an acquired mutation in several subjects, as ! signified by squares (color intensity indicates the number of mutations observed within this subject). The total number of mutations observed within that gene, m, is indicated left. Genes are grouped by biological function and labeled with the annotations of close homologs and, when available, with the names of these homologs. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Tami D Lieberman & * Jean-Baptiste Michel Affiliations * Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA. * Tami D Lieberman, * Jean-Baptiste Michel, * Nicholas Leiby & * Roy Kishony * Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts, USA. * Jean-Baptiste Michel * Department of Medicine, Division of Infectious Diseases, Children's Hospital Boston, Boston, Massachusetts, USA. * Mythili Aingaran & * Gregory P Priebe * Infection Prevention & Control, Children's Hospital Boston, Boston, Massachusetts, USA. * Gail Potter-Bynoe * Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA. * Damien Roux, * David Skurnik & * Gregory P Priebe * Department of Microbiology, University of Virginia Health System, Charlottesville, Virginia, USA. * Michael R Davis Jr & * Joanna B Goldberg * Department of Pediatrics, University of Michigan Medical School, Ann Arbor, Michigan, USA. * John J LiPuma * Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA. * John J LiPuma * Department of Laboratory Medicine, Children's Hospital Boston, Boston, Massachusetts, USA. * Alexander J McAdam * Department of Anesthesia, Division of Critical Care Medicine, Children's Hospital Boston, Boston, Massachusetts, USA. * Gregory P Priebe * School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA. * Roy Kishony Contributions J.-B.M., A.J.M. and R.K. conceived of the study. J.J.L., A.J.M. and G.P.P. collected the clinical samples. T.D.L. and N.L. performed resistance phenotyping. J.B.G., D.R., M.R.D., D.S. and G.P.P. performed LPS phenotyping and complementation. M.A., G.P.-B., A.J.M. and G.P.P. conducted chart review and provided medical information. T.D.L., J.-B.M. and R.K. performed whole-genome sequencing and data analysis. T.D.L., J.-B.M., J.J.L., A.J.M., G.P.P. and R.K. interpreted the results and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Roy Kishony or * Alexander J McAdam or * Gregory P Priebe Author Details * Tami D Lieberman Search for this author in: * NPG journals * PubMed * Google Scholar * Jean-Baptiste Michel Search for this author in: * NPG journals * PubMed * Google Scholar * Mythili Aingaran Search for this author in: * NPG journals * PubMed * Google Scholar * Gail Potter-Bynoe Search for this author in: * NPG journals * PubMed * Google Scholar * Damien Roux Search for this author in: * NPG journals * PubMed * Google Scholar * Michael R Davis Jr Search for this author in: * NPG journals * PubMed * Google Scholar * David Skurnik Search for this author in: * NPG journals * PubMed * Google Scholar * Nicholas Leiby Search for this author in: * NPG journals * PubMed * Google Scholar * John J LiPuma Search for this author in: * NPG journals * PubMed * Google Scholar * Joanna B Goldberg Search for this author in: * NPG journals * PubMed * Google Scholar * Alexander J McAdam Contact Alexander J McAdam Search for this author in: * NPG journals * PubMed * Google Scholar * Gregory P Priebe Contact Gregory P Priebe Search for this author in: * NPG journals * PubMed * Google Scholar * Roy Kishony Contact Roy Kishony Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–8, Supplementary Tables 1, 4 and 5 and Supplementary Note. Excel files * Supplementary Table 2 (225K) Polymorphic loci among 113 B. dolosa isolates * Supplementary Table 3 (29K) Genes mutated during an epidemic of B. dolosa Additional data