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• Chocolate and strawberries
  - Nat Genet 43(2):85 (2011)
  Nature Genetics | Editorial Chocolate and strawberries Journal name:Nature GeneticsVolume: 43,Page:85Year published:(2011)DOI:doi:10.1038/ng0211-85Published online27 January 2011 As genome sequencing becomes more versatile and easier, the journal prioritizes those genomic sequences that maximize the prospects of harnessing genome variation and understanding evolutionary processes. View full text Additional data
• A cornucopia of maize genes
  - Nat Genet 43(2):87-88 (2011)
  Nature Genetics | News and Views A cornucopia of maize genes * Chris Haley1 Contact Chris Haley Search for this author in: * NPG journals * PubMed * Google ScholarJournal name:Nature GeneticsVolume: 43,Pages:87–88Year published:(2011)DOI:doi:10.1038/ng0211-87Published online27 January 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Genetics for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Two studies illustrate that with the appropriate resources and scale of study, most of the heritability of complex traits in maize is not missing, but can be located within the genome. Given that maize is one of the world's most important crop plants, this has implications for feeding a growing population with minimum carbon footprint as well as for understanding the genetics of complex traits in a range of species. View full text Author 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 * Chris Haley is at the Medical Research Council Human Genetics Unit, Western General Hospital, Edinburgh, UK and the Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Chris Haley Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Genetics for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Additional data
• The (new) new synthesis and epigenetic capacitors of morphological evolution
  - Nat Genet 43(2):88-89 (2011)
  Nature Genetics | News and Views The (new) new synthesis and epigenetic capacitors of morphological evolution * Douglas M Ruden1 Contact Douglas M Ruden Search for this author in: * NPG journals * PubMed * Google ScholarJournal name:Nature GeneticsVolume: 43,Pages:88–89Year published:(2011)DOI:doi:10.1038/ng0211-88Published online27 January 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Genetics for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. A new study shows that the piRNA-binding protein Piwi interacts with Hsp90 and suppresses phenotypic variation in Drosophila melanogaster by preventing the expression of hidden epigenetic variation. This suggests that Hsp90 and Piwi function are dampened in times of stress to increase genetic and epigenetic variability, providing a last-ditch mechanism for a species to survive. View full text Author 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 * Douglas M. Ruden is at the Institute for Environmental Health Sciences and the C.S. Mott Center for Human Growth and Development, Wayne State University, Detroit, Michigan, USA. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Douglas M Ruden Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Genetics for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Additional data
• TRAPing a new gene for autoimmunity
  - Nat Genet 43(2):90-91 (2011)
  Nature Genetics | News and Views TRAPing a new gene for autoimmunity * Timothy W Behrens1 Contact Timothy W Behrens Search for this author in: * NPG journals * PubMed * Google Scholar * Robert R Graham1 Contact Robert R Graham Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:90–91Year published:(2011)DOI:doi:10.1038/ng0211-90Published online27 January 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Genetics for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Two new studies show that mutations in tartrate-resistant acid phosphatase (TRAP) cause spondyloenchondrodysplasia, a rare recessive disease associated with short stature, brain calcifications and lupus-like autoimmunity. The complex clinical syndrome is probably mediated by impaired dephosphorylation of osteopontin. View full text Author 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 * Timothy W. Behrens and Robert R. Graham are in the Departments of Biomarker Discovery and Human Genetics, Genentech Inc., South San Francisco, California, USA. Competing financial interests T.W.B. and R.R.G. are full-time employees of Genentech. Corresponding authors Correspondence to: * Timothy W Behrens or * Robert R Graham Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Genetics for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Additional data
• Research highlights
  - Nat Genet 43(2):93 (2011)
  Nature Genetics | Research Highlights Research highlights Journal name:Nature GeneticsVolume: 43,Page:93Year published:(2011)DOI:doi:10.1038/ng0211-93Published online27 January 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Genetics for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Strong hearts Cardiac muscle cells respond to increased pressure and/or volume with growth. It is well known that exercise induces cardiac growth, but pathological factors, such as hypertension, induce this response as well. Now, Bruce Spiegelman and colleagues report that C/EBPβ regulates exercise-induced cardiac growth and that mice with a reduction in C/EBPβ are resistant to pathological hypertrophy (Cell143, 1072–1083, 2010). Using a quantitative PCR–based method, they analyzed expression levels of all transcriptional components in exercised mice as well as in mice subjected to transaortic constriction (TAC). TAC mice showed equivalent levels of hypertrophy as exercised mice, although TAC mice displayed signs of pathological hypertrophy. The authors identified five genes expressed in cardiomyocytes that were regulated in exercised-induced or TAC-induced hypertrophy. Consistent with decreases seen in cardiomyocytes after exercise, reduction of C/EBPβ with short interfering RNA l! ed to an increase in both cell size and number in rat cardiomyocytes in vitro. C/EBPβ heterozygotes showed a reduction of C/EBPβ mRNA similar to that seen in exercised mice. To assess a potential protective effect of loss of C/EBPβ, the authors performed TAC on C/EBPβ mice. These mice showed only a minor reduction in cardiomyocyte function after TAC, suggesting that C/EBPβ mice are resistant to pathological stress on the heart. PC NFKBIA deletions in glioblastoma Glioblastomas typically show excessive activation of the EGFR pathway accompanied by deregulation of NF-κB, a transcription factor activated by EGFR signaling. Amplification of EGFR and activating mutations in EGFR are frequently observed in the classical subtype of glioblastoma but are less common in the nonclassical subtypes, suggesting alternate mechanisms for EGFR pathway deregulation in these tumors. Markus Bredel and colleagues (N. Engl. J. Med. published online, doi:10.1056/NEJMoa1006312, 22 December 2010) now report that deletions of NFKBIA, which encodes an inhibitor of NF-κB, are common in glioblastomas and are associated with unfavorable clinical outcomes. The authors analyzed 760 glioblastomas and detected heterozygous deletions of NFKBIA in more than 20% of cases. NFKBIA deletions occurred more frequently in nonclassical subtypes of glioblastoma and in tumors lacking EGFR amplification and were correlated with reduced survival. Notably, restoring NFKBIA expres! sion in glioblastoma cell lines reduced their malignant properties and rendered the cells more sensitive to treatment with temozolomide, a drug commonly used in glioblastoma chemotherapy. These findings suggest that strategies to restore or stabilize NFKBIA expression might be an effective means of counteracting the oncogenic effects of deregulated EGFR signaling in glioblastoma and other cancers. KV View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Genetics for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Additional data
• Non-genetic heterogeneity from stochastic partitioning at cell division
  - Nat Genet 43(2):95-100 (2011)
  Nature Genetics | Analysis Non-genetic heterogeneity from stochastic partitioning at cell division * Dann Huh1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Johan Paulsson1 Contact Johan Paulsson Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:95–100Year published:(2011)DOI:doi:10.1038/ng.729Published online26 December 2010 Abstract * Abstract * Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Gene expression involves inherently probabilistic steps that create fluctuations in protein abundances. The results from many in-depth analyses and genome-scale surveys have suggested how such fluctuations arise and spread, often in ways consistent with stochastic models of transcription and translation. But fluctuations also arise during cell division when molecules are partitioned stochastically between the two daughters. Here we mathematically demonstrate how stochastic partitioning contributes to the non-genetic heterogeneity. Our results show that partitioning errors are hard to correct, and that the resulting noise profiles are remarkably difficult to separate from gene expression noise. By applying these results to common experimental strategies and distinguishing between creation versus transmission of noise, we hypothesize that much of the cell-to-cell heterogeneity that has been attributed to various aspects of gene expression instead comes from random segregation ! at cell division. We propose experiments to separate between these two types of fluctuations and discuss future directions. View full text Figures at a glance * Figure 1: Growing and dividing cells. () Cartoon of an individual cell line and segregating units (dots) followed through rounds of growth and division. () Sample-time trace of copy number per cell (gray) and their average (black). Random changes are due to births and deaths during the cell cycle and segregation at cell division (time T ). * Figure 2: Partitioning errors mimic gene expression noise. () The CV (standard deviation divided by mean) in protein numbers per cell halfway through the cell cycle as a function of the average protein level for different mechanisms of gene expression and segregation. The solid line corresponds to the gene expression model above with probabilistic births and deaths but no cell cycle or division. For all other scenarios, mRNAs are made at constant intensities, degraded exponentially and independently partitioned at cell division and a stable protein is produced with constant intensity per transcript. Circles correspond to an average burst size of 4.4 and independent protein segregation. Squares correspond to clustered protein segregation with an average of 13 proteins per vesicle and a Poisson distributed number of vesicles with an average value proportional to the number of proteins and all other reactions are modeled as deterministic. Triangles correspond to independent partitioning of proteins and deterministic reactions during ce! ll growth. () Bars correspond to a model in which mRNAs and proteins are made deterministically during the cell cycle and then discretized and independently partitioned at cell division. The distribution is fitted to a negative binomial (line) that is expected from commonly used stochastic gene expression models. () Protein time-series for a simplistic model including a protein, its unsaturated protease and the two corresponding mRNAs. All synthesis and degradation reactions are approximated as deterministic and discretized, and heterogeneity is only created through independent partitioning errors (Online Methods) that eventually are transmitted to protein levels. The assumptions about deterministic effects in – are of course physically unrealistic and included only to demonstrate the fits even in extreme cases. * Figure 3: Partitioning errors are difficult to effectively correct during the cell cycle. () Negative feedback can exacerbate the effect of partitioning errors. First we consider an open loop system where component w is synthesized at a constant rate, components x and y are synthesized at constant rates per w and x molecule, respectively, and all three components are degraded exponentially. Synthesis and degradation reactions are modeled as deterministic, and independent partitioning of each component is the only source of randomness. The negative feedback model system is identical, except that the synthesis rate of w is downregulated by y according to a negative Hill function, with a Hill coefficient of three (Online Methods). As the half-life of y relative to the cell cycle time increases, the closed-loop system exhibits noisier behavior of x than the open loop. The average abundances of each species are kept the same for the open and the closed loop system and for all half-lives by changing the synthesis rate constant of w. () The total effect of random segreg! ation can increase with shorter half-lives of the components. The mRNA fluctuations originating from segregation, assuming that a stable transcription factor is made at a constant intensity and that the mRNA birth rate is proportional to the number of transcription factor molecules, where both transcription factor and mRNA molecules segregate independently. The CV is evaluated halfway through the cell cycle, with 5 transcription factors and 25 mRNAs per average newborn cell. As the mRNA half-life relative to the cell cycle time increases, the randomizing effect of its own segregation (green) increases, but the transmitted fluctuations from random transcription factor segregation (red) instead go through a maximum and then decrease. Shorter lifetimes can thus increase the contribution of random segregation to the population heterogeneity (purple). See Online Methods for derivations and details. Author information * Abstract * Author information Affiliations * Department of Systems Biology, Harvard University, Boston, Massachusetts, USA. * Dann Huh & * Johan Paulsson * Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, USA. * Dann Huh Contributions D.H. and J.P. jointly conceived the study, derived the results and wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Johan Paulsson Additional data
• The genome of Theobroma cacao
  - Nat Genet 43(2):101-108 (2011)
  Nature Genetics | Article Open The genome of Theobroma cacao * Xavier Argout1, 24 Contact Xavier Argout Search for this author in: * NPG journals * PubMed * Google Scholar * Jerome Salse2, 24 Search for this author in: * NPG journals * PubMed * Google Scholar * Jean-Marc Aury3, 4, 5, 24 Search for this author in: * NPG journals * PubMed * Google Scholar * Mark J Guiltinan6, 7, 24 Search for this author in: * NPG journals * PubMed * Google Scholar * Gaetan Droc1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jerome Gouzy8 Search for this author in: * NPG journals * PubMed * Google Scholar * Mathilde Allegre1 Search for this author in: * NPG journals * PubMed * Google Scholar * Cristian Chaparro9 Search for this author in: * NPG journals * PubMed * Google Scholar * Thierry Legavre1 Search for this author in: * NPG journals * PubMed * Google Scholar * Siela N Maximova6 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Abrouk2 Search for this author in: * NPG journals * PubMed * Google Scholar * Florent Murat2 Search for this author in: * NPG journals * PubMed * Google Scholar * Olivier Fouet1 Search for this author in: * NPG journals * PubMed * Google Scholar * Julie Poulain3, 4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Manuel Ruiz1 Search for this author in: * NPG journals * PubMed * Google Scholar * Yolande Roguet1 Search for this author in: * NPG journals * PubMed * Google Scholar * Maguy Rodier-Goud1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jose Fernandes Barbosa-Neto9 Search for this author in: * NPG journals * PubMed * Google Scholar * Francois Sabot9 Search for this author in: * NPG journals * PubMed * Google Scholar * Dave Kudrna10 Search for this author in: * NPG journals * PubMed * Google Scholar * Jetty Siva S Ammiraju10 Search for this author in: * NPG journals * PubMed * Google Scholar * Stephan C Schuster11 Search for this author in: * NPG 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Guignon1 Search for this author in: * NPG journals * PubMed * Google Scholar * Xavier Sabau1 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael J Axtell17 Search for this author in: * NPG journals * PubMed * Google Scholar * Zhaorong Ma17 Search for this author in: * NPG journals * PubMed * Google Scholar * Yufan Zhang15, 7 Search for this author in: * NPG journals * PubMed * Google Scholar * Spencer Brown18 Search for this author in: * NPG journals * PubMed * Google Scholar * Mickael Bourge18 Search for this author in: * NPG journals * PubMed * Google Scholar * Wolfgang Golser10 Search for this author in: * NPG journals * PubMed * Google Scholar * Xiang Song10 Search for this author in: * NPG journals * PubMed * Google Scholar * Didier Clement1 Search for this author in: * NPG journals * PubMed * Google Scholar * Ronan Rivallan1 Search for this author in: * NPG journals * PubMed * Google Scholar * Mathias Tahi19 Search for this author in: * NPG journals * PubMed * Google Scholar * Joseph Moroh Akaza19 Search for this author in: * NPG journals * PubMed * Google Scholar * Bertrand Pitollat1 Search for this author in: * NPG journals * PubMed * Google Scholar * Karina Gramacho20 Search for this author in: * NPG journals * PubMed * Google Scholar * Angélique D'Hont1 Search for this author in: * NPG journals * PubMed * Google Scholar * Dominique Brunel16 Search for this author in: * NPG journals * PubMed * Google Scholar * Diogenes Infante21 Search for this author in: * NPG journals * PubMed * Google Scholar * Ismael Kebe18 Search for this author in: * NPG journals * PubMed * Google Scholar * Pierre Costet22 Search for this author in: * NPG journals * PubMed * Google Scholar * Rod Wing10 Search for this author in: * NPG journals * PubMed * Google Scholar * W Richard McCombie15 Search for this author in: * NPG journals * PubMed * Google Scholar * Emmanuel Guiderdoni1 Search for this author in: * NPG journals * PubMed * Google Scholar * Francis Quetier23 Search for this author in: * NPG journals * PubMed * Google Scholar * Olivier Panaud9 Search for this author in: * NPG journals * PubMed * Google Scholar * Patrick Wincker3, 4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Stephanie Bocs1 Search for this author in: * NPG journals * PubMed * Google Scholar * Claire Lanaud1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:101–108Year published:(2011)DOI:doi:10.1038/ng.736Received10 August 2010Accepted01 December 2010Published online26 December 2010 Abstract * Abstract * 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 We sequenced and assembled the draft genome of Theobroma cacao, an economically important tropical-fruit tree crop that is the source of chocolate. This assembly corresponds to 76% of the estimated genome size and contains almost all previously described genes, with 82% of these genes anchored on the 10 T. cacao chromosomes. Analysis of this sequence information highlighted specific expansion of some gene families during evolution, for example, flavonoid-related genes. It also provides a major source of candidate genes for T. cacao improvement. Based on the inferred paleohistory of the T. cacao genome, we propose an evolutionary scenario whereby the ten T. cacao chromosomes were shaped from an ancestor through eleven chromosome fusions. View full text Figures at a glance * Figure 1: FISH analysis of T. cacao chromosomes. () In situ hybridization of T. cacao chromosomes stained with DAPI (blue) using a ThCen repeat probe (red). () In situ hybridization using Gaucho LTR retrotransposon (green) and ThCen repeat (red) probes. * Figure 2: T. cacao genome heat map. The ten T. cacao chromosomes harboring 11 chromosome fusions (in black dotted boxes) identified in these genomes are illustrated according to their ancestral chromosomal origin (see paleo-chromosome color code in Fig. 4). Centromeres are marked 'Cent'. For the ten chromosomes, heat maps are provided for the CDS (blue <60%, yellow 60%–90% and red >90%), class I and II transposable elements (blue <80%, yellow >80% and red ~100%), ThCen and Gaucho elements (blue <50% of maximum, yellow ≥50% of maximum and red = maximum) and telomeric repeats (blue = 0, yellow <40% and red >40%). Only the elements present in the assembled part of the genome are represented. Therefore, the genome distribution of the repeated sequences represented in this figure could be biased due to the major limitations of de novo sequencing of complex genomes using next-generation sequencing (NGS), which is limited in its ability to assemble highly repeated sequences. * Figure 3: Venn diagram showing the distribution of shared gene families among Theobroma cacao, Arabidopsis thaliana, Populus trichocarpa, Glycine max and Vitis vinifera. Numbers in parentheses indicate the number of genes in each cluster. The Venn diagram was created with web tools provided by the Bioinformatics and Systems Biology of Gent (see URLs). * Figure 4: T. cacao genome paleohistory. () T. cacao genome synteny. A schematic representation of the orthologs identified between cacao chromosomes (c1 to c10) at the center and the grape (g1 to g19), Arabidopsis (a1 to a5), poplar (p1 to p19), soybean (s1 to s20) and papaya (p1 to p9) chromosomes. Each line represents an orthologous gene. The seven different colors used to represent the blocks reflect the origin from the seven ancestral eudicot linkage groups. () T. cacao genome duplication. The seven major triplicated chromosomes groups in T. cacao (c1 to c10) are illustrated (colored blocks) and related with paralogous gene pairs identified between the T. cacao chromosomes (colored lines). The seven different colors reflect the seven ancestral eudicot linkage groups. () T. cacao genome evolutionary model updated from Abrouk et al.46. The eudicot chromosomes are represented with a seven-color code to illustrate the evolution of segments from a common ancestor with seven protochromosomes (top). The different lin! eage-specific shuffling events that have shaped the structure of the six genomes during their evolution from the common paleo-hexaploid ancestor are indicated as R (for rounds of whole-genome duplication (WGD)) and F (for fusions of chromosomes). The current structure of the eudicot genomes is represented at the bottom of the figure. Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions DNA Data Bank of Japan * CACC01000001–CACC01025912 Author information * Abstract * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Xavier Argout, * Jerome Salse, * Jean-Marc Aury & * Mark J Guiltinan Affiliations * Centre de coopération Internationale en Recherche Agronomique pour le Développement (CIRAD)-Biological Systems Department-Unité Mixte de Recherche Développement et Amélioration des Plantes (UMR DAP) TA A 96/03-34398, Montpellier, France. * Xavier Argout, * Gaetan Droc, * Mathilde Allegre, * Thierry Legavre, * Olivier Fouet, * Manuel Ruiz, * Yolande Roguet, * Maguy Rodier-Goud, * Anne Dievart, * Christopher Viot, * Michel Boccara, * Ange Marie Risterucci, * Valentin Guignon, * Xavier Sabau, * Didier Clement, * Ronan Rivallan, * Bertrand Pitollat, * Angélique D'Hont, * Emmanuel Guiderdoni, * Stephanie Bocs & * Claire Lanaud * Institut National de la Recherché Agronomique UMR 1095, Clermont-Ferrand, France. * Jerome Salse, * Michael Abrouk & * Florent Murat * Commissariat à l'Energie Antomique (CEA), Institut de Génomique (IG), Genoscope, Evry, France. * Jean-Marc Aury, * Julie Poulain & * Patrick Wincker * Centre National de Recherche Scientifique (CNRS), UMR 8030, CP5706, Evry, France. * Jean-Marc Aury, * Julie Poulain & * Patrick Wincker * Université d'Evry, Evry, France. * Jean-Marc Aury, * Julie Poulain & * Patrick Wincker * Penn State University, Department of Horticulture and the Huck Institutes of the Life Sciences, University Park, Pennsylvania, USA. * Mark J Guiltinan & * Siela N Maximova * Penn State University, Plant Biology Graduate Program and the Huck Institutes of the Life Sciences, University Park, Pennsylvania, USA. * Mark J Guiltinan, * Zi Shi & * Yufan Zhang * Institut National de la Recherche Agronomique (INRA)-CNRS Laboratoire des Interactions Plantes Micro-organismes (LIPM), Castanet Tolosan Cedex, France. * Jerome Gouzy & * Erika Sallet * UMR 5096 CNRS-Institut de Recherche pour le Développement (IRD)-Université de Perpignan Via Domitia (UPVD), Laboratoire Génome et Développement des Plantes, Perpignan Cedex, France. * Cristian Chaparro, * Jose Fernandes Barbosa-Neto, * Francois Sabot & * Olivier Panaud * Arizona Genomics Institute and School of Plant Sciences, University of Arizona, Tucson, Arizona, USA. * Dave Kudrna, * Jetty Siva S Ammiraju, * Wolfgang Golser, * Xiang Song & * Rod Wing * Penn State University, Department of Biochemistry and Molecular Biology, University Park, Pennsylvania, USA. * Stephan C Schuster * Penn State University, the School of Forest Resources and the Huck Institutes of the Life Sciences, University Park, Pennsylvania, USA. * John E Carlson * The Department of Bioenergy Science and Technology (WCU), Chonnam National University, Buk-Gu, Gwangju, Korea. * John E Carlson * Unité de Biométrie et d'Intelligence Artificielle (UBIA), UR875 INRA, Castanet Tolosan, France. * Thomas Schiex * Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. * Melissa Kramer, * Laura Gelley, * Yufan Zhang & * W Richard McCombie * INRA, UR 1279 Etude du Polymorphisme des Génomes Végétaux, CEA Institut de Génomique, Centre National de Génotypage, CP5724, Evry, France. * Aurélie Bérard & * Dominique Brunel * Penn State University, Bioinformatics and Genomics PhD Program and Department of Biology, University Park, Pennsylvania, USA. * Michael J Axtell & * Zhaorong Ma * Institut des Sciences du Végétal, UPR 2355, CNRS, Gif-Sur-Ivette, France. * Spencer Brown, * Mickael Bourge & * Ismael Kebe * Centre National de la Recherche Agronomique (CNRA), Divo, Côte d'Ivoire. * Mathias Tahi & * Joseph Moroh Akaza * Comissão Executiva de Planejamento da Lavoura Cacaueira (CEPLAC), Itabuna Bahia, Brazil. * Karina Gramacho * Centro Nacional de Biotecnología Agrícola, Instituto de Estudios Avanzados (IDEA), Caracas, Venezuela. * Diogenes Infante * Chocolaterie VALRHONA, Tain l'Hermitage, France. * Pierre Costet * Département de Biologie, Université d'Evry Val d'Essonne, Evry, France. * Francis Quetier Contributions X.A., J.S., J.-M.A., M.J.G., J.G., D.K., M.J.A., S. Brown, K.G., A. D'Hont, A. Dievart, D.B., D.I., P.C., R.W., W.R.M., E.G., F.Q., O.P., P.W., S. Bocs and C.L. designed the analyses. X.A., J.S., J.-M.A., M.J.G., J.G., M.R., D.K., M.J.A., S. Brown, A. D'Hont, D.B., W.R.M., O.P., P.W., S. Bocs and C.L. managed the several components of the project. X.A., M.A., O.F., Y.R., A.B., M. Bocca, D.C., R.R., M.T., J.M.A., K.G., I.K., J.-M.A. and C.L. performed material preparation and multiplication, DNA and RNA extractions, genotyping, genetic mapping and anchoring of the assembly. D.K., J.S.S.A., W.G. and X.S. performed BAC libraries. J.-M.A., J.P., S.C.S., J.E.C., M.K., L.G. and W.R.M. performed sequencing and assembly. X.A., G.D., J.G., M. Allegre, T.L., S.N.M., E.S., T.S., Z.S., C.V., V.G., Y.Z., B.P. and S. Bocs performed automatic and manual gene annotations and database management. C.C., J.F.B.-N., F.S., A.M.R., M.J.A., Z.M., O.P. and S. Brown performed repeated elements and miRNA analyses. M.R.-G., M. Bourge, S. Brown and A. D'Hont performed in situ hybridizations and genome-size evaluations. M.J.G., G.D., T.L., S.N.M., M.R., A. Dievart, Z.S., X.S. and Y.Z. performed gene family analyses. J.S., M. Abrouk and F.M. performed evolution analyses. X.A., J.S., J.-M.A., M.J.G., G.D., J.G., C.C., T.L., S.N.M., M.R., M.R.-G., D.K., S.C.S., A. D'Hont, A. Dievart, X.S., M.J.A., S. Brown, P.C., F.Q., O.P., S. Bocs and C.L. wrote and/or revised the paper. C.L. initiated and coordinated the whole project. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Xavier Argout Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (6M) Supplementary Note, Supplementary Tables 1–19 and Supplementary Figures 1–18 Creative Commons Attribution-Noncommercial-Share Alike license This article is distributed under the terms of the Creative Commons Attribution-Non-Commercial-ShareAlike license (http://creativecommons.org/licenses/by-nc-sa/3.0/), which permits distribution, and reproduction in any medium, provided the original author and source are credited. This license does not permit commercial exploitation, and derivative works must be licensed under the same or similar license. Additional data
• The genome of woodland strawberry (Fragaria vesca)
  - Nat Genet 43(2):109-116 (2011)
  Nature Genetics | Article Open The genome of woodland strawberry (Fragaria vesca) * Vladimir Shulaev1 Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel J Sargent2 Search for this author in: * NPG journals * PubMed * Google Scholar * Ross N Crowhurst3 Search for this author in: * NPG journals * PubMed * Google Scholar * Todd C Mockler4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Otto Folkerts6 Search for this author in: * NPG journals * PubMed * Google Scholar * Arthur L Delcher7 Search for this author in: * NPG journals * PubMed * Google Scholar * Pankaj Jaiswal4 Search for this author in: * NPG journals * PubMed * Google Scholar * Keithanne Mockaitis8 Search for this author in: * NPG journals * PubMed * Google Scholar * Aaron Liston4 Search for this author in: * NPG journals * PubMed * Google Scholar * Shrinivasrao P Mane9 Search for this author in: * NPG journals * PubMed * Google Scholar * Paul Burns10 Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas M Davis11 Search for this author in: * NPG journals * PubMed * Google Scholar * Janet P Slovin12 Search for this author in: * NPG journals * PubMed * Google Scholar * Nahla Bassil13 Search for this author in: * NPG journals * PubMed * Google Scholar * Roger P Hellens3 Search for this author in: * NPG journals * PubMed * Google Scholar * Clive Evans9 Search for this author in: * NPG journals * PubMed * Google Scholar * Tim Harkins14 Search for this author in: * NPG journals * PubMed * Google Scholar * Chinnappa Kodira14 Search for this author in: * NPG journals * PubMed * Google Scholar * Brian Desany14 Search for this author in: * NPG journals * PubMed * Google Scholar * Oswald R Crasta6 Search for this author in: * NPG journals * PubMed * Google Scholar * Roderick V Jensen15 Search for this author in: * NPG journals * PubMed * Google Scholar * Andrew C Allan3, 16 Search for this author in: * NPG journals * PubMed * Google Scholar * Todd P Michael17 Search for this author in: * NPG journals * PubMed * Google Scholar * Joao Carlos Setubal9, 18 Search for this author in: * NPG journals * PubMed * Google Scholar * Jean-Marc Celton19 Search for this author in: * NPG journals * PubMed * Google Scholar * D Jasper G Rees19 Search for this author in: * NPG journals * PubMed * Google Scholar * Kelly P Williams9 Search for this author in: * NPG journals * PubMed * Google Scholar * Sarah H Holt20, 21 Search for this author in: * NPG journals * PubMed * Google Scholar * Juan Jairo Ruiz Rojas20 Search for this author in: * NPG journals * PubMed * Google Scholar * Mithu Chatterjee22, 23 Search for this author in: * NPG journals * PubMed * Google Scholar * Bo Liu11 Search for this author in: * NPG journals * PubMed * Google Scholar * Herman Silva24 Search for this author in: * NPG journals * PubMed * Google Scholar * Lee Meisel25 Search for this author in: * NPG journals * PubMed * Google Scholar * Avital Adato26 Search for this author in: * NPG journals * PubMed * Google Scholar * Sergei A Filichkin4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Michela Troggio27 Search for this author in: * NPG journals * PubMed * Google Scholar * Roberto Viola27 Search for this author in: * NPG journals * PubMed * Google Scholar * Tia-Lynn Ashman28 Search for this author in: * NPG journals * PubMed * Google Scholar * Hao Wang29 Search for this author in: * NPG journals * PubMed * Google Scholar * Palitha Dharmawardhana4 Search for this author in: * NPG journals * PubMed * Google Scholar * Justin Elser4 Search for this author in: * NPG journals * PubMed * Google Scholar * Rajani Raja4 Search for this author in: * NPG journals * PubMed * Google Scholar * Henry D Priest4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Douglas W Bryant Jr4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Samuel E Fox4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Scott A Givan4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Larry J Wilhelm4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Sushma Naithani30 Search for this author in: * NPG journals * PubMed * Google Scholar * Alan Christoffels31 Search for this author in: * NPG journals * PubMed * Google Scholar * David Y Salama22 Search for this author in: * NPG journals * PubMed * Google Scholar * Jade Carter8 Search for this author in: * NPG journals * PubMed * Google Scholar * Elena Lopez Girona2 Search for this author in: * NPG journals * PubMed * Google Scholar * Anna Zdepski17 Search for this author in: * NPG journals * PubMed * Google Scholar * Wenqin Wang17 Search for this author in: * NPG journals * PubMed * Google Scholar * Randall A Kerstetter17 Search for this author in: * NPG journals * PubMed * Google Scholar * Wilfried Schwab32 Search for this author in: * NPG journals * PubMed * Google Scholar * Schuyler S Korban33 Search for this author in: * NPG journals * PubMed * Google Scholar * Jahn Davik34 Search for this author in: * NPG journals * PubMed * Google Scholar * Amparo Monfort35, 36 Search for this author in: * NPG journals * PubMed * Google Scholar * Beatrice Denoyes-Rothan37 Search for this author in: * NPG journals * PubMed * Google Scholar * Pere Arus35, 36 Search for this author in: * NPG journals * PubMed * Google Scholar * Ron Mittler1 Search for this author in: * NPG journals * PubMed * Google Scholar * Barry Flinn21 Search for this author in: * NPG journals * PubMed * Google Scholar * Asaph Aharoni25 Search for this author in: * NPG journals * PubMed * Google Scholar * Jeffrey L Bennetzen29 Search for this author in: * NPG journals * PubMed * Google Scholar * Steven L Salzberg7 Search for this author in: * NPG journals * PubMed * Google Scholar * Allan W Dickerman9 Search for this author in: * NPG journals * PubMed * Google Scholar * Riccardo Velasco27 Search for this author in: * NPG journals * PubMed * Google Scholar * Mark Borodovsky10, 38 Search for this author in: * NPG journals * PubMed * Google Scholar * Richard E Veilleux20 Search for this author in: * NPG journals * PubMed * Google Scholar * Kevin M Folta22, 23 Contact Kevin M Folta Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:109–116Year published:(2011)DOI:doi:10.1038/ng.740Received09 June 2010Accepted02 December 2010Published online26 December 2010 Abstract * Abstract * 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 The woodland strawberry, Fragaria vesca (2n = 2x = 14), is a versatile experimental plant system. This diminutive herbaceous perennial has a small genome (240 Mb), is amenable to genetic transformation and shares substantial sequence identity with the cultivated strawberry (Fragaria × ananassa) and other economically important rosaceous plants. Here we report the draft F. vesca genome, which was sequenced to ×39 coverage using second-generation technology, assembled de novo and then anchored to the genetic linkage map into seven pseudochromosomes. This diploid strawberry sequence lacks the large genome duplications seen in other rosids. Gene prediction modeling identified 34,809 genes, with most being supported by transcriptome mapping. Genes critical to valuable horticultural traits including flavor, nutritional value and flowering time were identified. Macrosyntenic relationships between Fragaria and Prunus predict a hypothetical ancestral Rosaceae genome that had nine c! hromosomes. New phylogenetic analysis of 154 protein-coding genes suggests that assignment of Populus to Malvidae, rather than Fabidae, is warranted. View full text Figures at a glance * Figure 1: Anchoring the F. vesca genome to the diploid Fragaria reference map, FV × FN. Scaffolds representing 198.1 Mb of scaffolded sequence with embedded gaps (99.2% of all contiguous sequence over 10 kb in length) were anchored to the genetic map with 390 genetic markers. Blue scaffolds were anchored and oriented using map positions of markers in the full FV × FN progeny, whereas the yellow scaffolds were anchored to mapping bins. * Figure 2: A schematic representation of the positions of 389 RosCOS markers on the seven pseudochromosomes (FC1-7) of F. vesca in relation to their bin map positions on the eight linkage groups (PG1-8) of the Prunus T × E reference map10. The diagram was plotted using Circos; map positions from the Prunus reference map were converted to approximate physical positions for comparison by multiplying the marker positions in cM by 400,000. Markers were spaced at 100,000 nucleotide intervals within each T × E mapping bin (see URLs). * Figure 3: Gene ontology mapping and functional annotation of strawberry genes. Overrepresented gene ontology categories in fruit () and root () expressed genes. The circles are shaded based on significance level (yellow, false discovery rate < 0.05), and the radius of each circle denotes the number of genes in each category. * Figure 4: Venn diagram showing unique and shared gene families between and among rice, grape, Arabidopsis and strawberry. Comparative analysis with rice, Arabidopsis, grape and strawberry genes revealed that a total of 103,570 genes from those four species were shared among all four species. In the case of strawberry, 18,170 genes of the total 33,264 protein-coding genes (from ab initio predictions; Supplementary Table 5) aligned in 9,895 clusters. Comparison of the four species revealed 681 gene clusters unique to strawberry. There were 663 gene clusters unique to strawberry and Arabidopsis, whereas there were 262 gene clusters unique to rice and strawberry. Additionally, there were 6,233 gene clusters that were shared among all four species. The analysis was done using a total of 21 species to find the clusters. * Figure 5: Maximum likelihood phylogeny relating Fragaria to seven other eudicot genomes with two monocot outgroups. The tree is based on alignments of 154 genes present in at least eight of ten genomes. Genes exhibiting little or no duplication were selected, and duplicates, predominant in Glycine, were removed. Species in the Fabidae clade are colored red and species in the Malvidae clade are colored blue. The placement of Populus in Malvidae and not Fabidae, as found in previous studies, was strongly supported by topology and resampling tests. Bootstrap values are shown at nodes. The scale is amino acid substitutions per site. Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Entrez Nucleotide * AEMH00000000 Sequence Read Archive * SRA026350.1 * SRA020125 * SRA026350 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Department of Biological Sciences, University of North Texas, Denton, Texas, USA. * Vladimir Shulaev & * Ron Mittler * East Malling Research, Kent, UK. * Daniel J Sargent & * Elena Lopez Girona * The New Zealand Institute for Plant and Food Research Limited (Plant and Food Research), Mt. Albert Research Centre, Auckland, New Zealand. * Ross N Crowhurst, * Roger P Hellens & * Andrew C Allan * Department of Botany and Plant Pathology, Oregon State University, Corvallis, Oregon, USA. * Todd C Mockler, * Pankaj Jaiswal, * Aaron Liston, * Sergei A Filichkin, * Palitha Dharmawardhana, * Justin Elser, * Rajani Raja, * Henry D Priest, * Douglas W Bryant Jr, * Samuel E Fox, * Scott A Givan & * Larry J Wilhelm * Center for Genome Research and Biocomputing (CGRB), Oregon State University, Corvallis, Oregon, USA. * Todd C Mockler, * Sergei A Filichkin, * Henry D Priest, * Douglas W Bryant Jr, * Samuel E Fox, * Scott A Givan & * Larry J Wilhelm * Chromatin Inc., Champaign, Illinois, USA. * Otto Folkerts & * Oswald R Crasta * Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, USA. * Arthur L Delcher & * Steven L Salzberg * The Center for Genomics and Bioinformatics, Indiana University, Bloomington, Indiana, USA. * Keithanne Mockaitis & * Jade Carter * Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA. * Shrinivasrao P Mane, * Clive Evans, * Joao Carlos Setubal, * Kelly P Williams & * Allan W Dickerman * Joint Georgia Tech and Emory Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, USA. * Paul Burns & * Mark Borodovsky * Department of Biological Sciences, University of New Hampshire, Durham, New Hampshire, USA. * Thomas M Davis & * Bo Liu * United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Henry Wallace Beltsville Agricultural Research Center, Beltsville, Maryland, USA. * Janet P Slovin * (USDA), ARS, National Clonal Germplasm Repository, Corvallis, Oregon, USA. * Nahla Bassil * Roche Diagnostics, Roche Applied Science, Indianapolis, Indiana, USA. * Tim Harkins, * Chinnappa Kodira & * Brian Desany * Department of Biological Sciences, Virginia Tech, Blacksburg, Virginia, USA. * Roderick V Jensen * School of Biological Sciences, University of Auckland, Auckland, New Zealand. * Andrew C Allan * Waksman Institute of Microbiology, Rutgers, The State University of New Jersey, New Jersey, USA. * Todd P Michael, * Anna Zdepski, * Wenqin Wang & * Randall A Kerstetter * Department of Computer Science, Virginia Tech, Blacksburg, Virginia USA. * Joao Carlos Setubal * Department of Biotechnology, University of the Western Cape, Bellville, South Africa. * Jean-Marc Celton & * D Jasper G Rees * Department of Horticulture, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA. * Sarah H Holt, * Juan Jairo Ruiz Rojas & * Richard E Veilleux * Institute for Sustainable and Renewable Resources, Institute for Advanced Learning and Research, Danville, Virginia, USA. * Sarah H Holt & * Barry Flinn * Horticultural Sciences Department, University of Florida, Gainesville, Florida, USA. * Mithu Chatterjee, * David Y Salama & * Kevin M Folta * The Graduate Program for Plant Molecular and Cellular Biology, University of Florida, Gainesville, Florida, USA. * Mithu Chatterjee & * Kevin M Folta * Millennium Nucleus in Plant Cell Biotechnology and Faculty of Agronomy, University of Chile, Santiago, Chile. * Herman Silva * Millennium Nucleus in Plant Cell Biotechnology and Centro de Biotecnología Vegetal, Facultad de Ciencias Biológicas, Universidad Andres Bello, Santiago, Chile. * Lee Meisel & * Asaph Aharoni * Department of Plant Sciences, Weizmann Institute of Science, Rehovot, Israel. * Avital Adato * Istituto Agrario San Michele all'Adige (IASMA), Research and Innovation Centre, Foundation Edmund Mach, San Michele all'Adige, Trento, Italy. * Michela Troggio, * Roberto Viola & * Riccardo Velasco * Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. * Tia-Lynn Ashman * Department of Genetics, University of Georgia, Athens, Georgia, USA. * Hao Wang & * Jeffrey L Bennetzen * Department of Horticulture, Oregon State University, Corvallis, Oregon, USA. * Sushma Naithani * South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa. * Alan Christoffels * Biotechnology of Natural Products, Technical University München, Germany. * Wilfried Schwab * Department of Natural Resources and Environmental Sciences, University of Illinois, Urbana, Illinois, USA. * Schuyler S Korban * Norwegian Institute for Agricultural and Environmental Research, Genetics and Biotechnology, Kvithamar, Stjordal, Norway. * Jahn Davik * Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Cabrils, Barcelona, Spain. * Amparo Monfort & * Pere Arus * Centre de Recerca en Agrigenòmica (CSIC-IRTA-UAB), Cabrils, Barcelona, Spain. * Amparo Monfort & * Pere Arus * Institut National de la Recherche Agronomique (INRA)-Unité de Recherche des Espèces Fruitières (UREF), Villenave d'Ornon, France. * Beatrice Denoyes-Rothan * School of Computational Science and Engineering, Georgia Tech, Atlanta, Georgia, USA. * Mark Borodovsky Contributions K.M.F., V.S., R.E.V. O.F., T.C.M., D.J.S., T.M.D., J.P.S., N.B., T.-L.A., L.M., H.S., A.C.A., R.N.C., T.P.M. T.P.M., J.P.S., A.Z., D.Y.S., K.M.F., S.H.H. O.F., T.C.M., R.V.J., C.E., T.H., J.C., K.M., C.K., B.D., O.R.C., M.T., R. Velasco, J.D., S.A.F., T.P.M., S.E.F., R.P.H., B.F., R.A.K.,W.W. A.L.D., S.L.S., M.T., S.P.M., R. Velasco, R. Viola, T.C.M., H.D.P., D.W.B., R.P.H., A.L., S.F., T.P.M. D.J.S., J.-M.C., J.G.R., A.C., J.J.R.R., E.L.G., M.T., R. Velasco, T.M.D., B.L., T.-L.A., B.D.-R., A.M., P.A. R.N.C., S.P.M., S.A.G., H.D.P., L.J.W. P.B., M.B., T.C.M., H.D.P., D.W.B., R.N.C., R.P.H., N.B., J.P.S., S.F., A.C.A., K.P.W. P.J., T.C.M., P.D., J.E., R.R., S.N. A.L., A.W.D., D.J.S. D.J.S., A.L., J.C.S., E.L.G., M.C., K.M.F. A.C.A., A. Adato, A. Aharoni. H.S., L.M., T.C.M., D.J.S., B.L., T.M.D., W.S., A.L., P.J., H.W., J.L.B., R.E.V. V.S., R.E.V., R. Velasco, R. Viola, K.M.F., T.C.M., C.E., J.G.R., J.P.S., K.M., S.S.K., R.P.H., B.F., R.M. K.M.F., R.E.V., T.M.D., T.-L.A., J.P.S., A.L., N.B., D.J.S., T.C.M., P.J., A.C.A., V.S., K.M., J.C.S., H.S., L.M., A. Adato, H.W., S.S.K., A. Aharoni, J.L.B., R. Velasco. T.C.M., R.E.V., K.M., T.M.D., J.P.S., M.B., N.B., T.-L.A., H.S., L.M., K.M.F. All authors critically read and approved the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Kevin M Folta Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Note, Supplementary Tables 1–18 and Supplementary Figures 1–10 Creative Commons Attribution-Noncommercial-Share Alike license This article is distributed under the terms of the Creative Commons Attribution-Non-Commercial-Share Alike licence (http://creativecommons.org/licenses/by-nc-sa/3.0/), which permits distribution, and reproduction in any medium, provided the original author and source are credited. This licence does not permit commercial exploitation, and derivative works must be licensed under the same or similar license. Additional data
• Common variants near ATM are associated with glycemic response to metformin in type 2 diabetes
  - Nat Genet 43(2):117-120 (2011)
  Nature Genetics | Letter Common variants near ATM are associated with glycemic response to metformin in type 2 diabetes * The GoDARTS and UKPDS Diabetes Pharmacogenetics Study Group1, 2 * The Wellcome Trust Case Control Consortium 22 * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:117–120Year published:(2011)DOI:doi:10.1038/ng.735Received21 July 2010Accepted30 November 2010Published online26 December 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Metformin is the most commonly used pharmacological therapy for type 2 diabetes. We report a genome-wide association study for glycemic response to metformin in 1,024 Scottish individuals with type 2 diabetes with replication in two cohorts including 1,783 Scottish individuals and 1,113 individuals from the UK Prospective Diabetes Study. In a combined meta-analysis, we identified a SNP, rs11212617, associated with treatment success (n = 3,920, P = 2.9 × 10−9, odds ratio = 1.35, 95% CI 1.22–1.49) at a locus containing ATM, the ataxia telangiectasia mutated gene. In a rat hepatoma cell line, inhibition of ATM with KU-55933 attenuated the phosphorylation and activation of AMP-activated protein kinase in response to metformin. We conclude that ATM, a gene known to be involved in DNA repair and cell cycle control, plays a role in the effect of metformin upstream of AMP-activated protein kinase, and variation in this gene alters glycemic response to metformin. View full text Figures at a glance * Figure 1: Regional association plots around the ATM locus for the logistic regression analysis. The solid and open triangles are from directly typed and imputed SNPs, respectively. * Figure 2: Effect of KU-55933 on AMPK activation by metformin. We pre-treated H4IIE cells with or without 10 μM KU-55933 for 30 min and then with various concentrations of metformin for 1 h, and we then measured the AMPK activity. Results are the mean ± standard deviation (n = 2). **Significantly different from incubation without KU-55933 by two-way ANOVA (P < 0.01). * Figure 3: A protein blot comparing the phosphorylation status of Thr172 of AMPK and Ser79 of ACC (a well characterized marker of AMPK activation). H4IIE cells were pre-treated with or without 10 μM KU-55933 (KU) for 1 h and then for 3 h with or without 2.5 mmol/l metformin. Metformin-induced phosphorylation of AMPK and subsequent phosphorylation of ACC was partially reduced by KU-55933. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Kaixin Zhou & * Celine Bellenguez Affiliations * A full list of authors and affiliations is provided at the end of the paper. * The GoDARTS and UKPDS Diabetes Pharmacogenetics Study Group * A full list of members is provided in the Supplementary Note. * The GoDARTS and UKPDS Diabetes Pharmacogenetics Study Group & * The Wellcome Trust Case Control Consortium 2 * Biomedical Research Institute, University of Dundee, Dundee, UK. * Kaixin Zhou, * Roger Tavendale, * Louise A Donnelly, * Chris Schofield, * Lindsay Burch, * Fiona Carr, * Helen Colhoun, * Andrew D Morris, * Calum Sutherland, * Colin N A Palmer & * Ewan R Pearson * UK Wellcome Trust Centre for Human Genetics, Oxford, UK. * Celine Bellenguez, * Chris C A Spencer, * Amy Strange, * Colin Freeman, * Anna Rautanen, * Mark I McCarthy & * Peter Donnelly * Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK. * Amanda J Bennett, * Ruth L Coleman, * Christopher J Groves, * Mark I McCarthy & * Rury R Holman * Diabetes Trials Unit, University of Oxford, Oxford, UK. * Ruth L Coleman & * Rury R Holman * College of Life Sciences, University of Dundee, Dundee, UK. * Simon A Hawley & * D Grahame Hardie * Institute for Child Health Research, Centre for Child Health Research, University of Western Australia, Subiaco, Western Australia, Australia. * Jenefer M Blackwell * Cambridge Institute for Medical Research, University of Cambridge School of Clinical Medicine, Cambridge, UK. * Jenefer M Blackwell * Department of Psychosis Studies, National Institute for Health Research Biomedical Research Centre for Mental Health at the Institute of Psychiatry, King's College London, London, UK. * Elvira Bramon * The South London and Maudsley National Health Service Foundation Trust, Denmark Hill, London, UK. * Elvira Bramon * Diamantina Institute of Cancer, Immunology and Metabolic Medicine, Princess Alexandra Hospital, University of Queensland, Brisbane, Queensland, Australia. * Matthew A Brown * Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK. * Juan P Casas * Department of Epidemiology and Public Health, University College London, London, UK. * Juan P Casas * Neuropsychiatric Genetics Research Group, Institute of Molecular Medicine, Trinity College Dublin, Dublin, Ireland. * Aiden Corvin * Department of Psychological Medicine, Cardiff University School of Medicine, Heath Park, Cardiff, UK. * Nicholas Craddock * Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. * Panos Deloukas, * Serge Dronov, * Sarah Edkins, * Emma Gray, * Sarah Hunt, * Cordelia Langford & * Leena Peltonen * Molecular and Physiological Sciences, The Wellcome Trust, London, UK. * Audrey Duncanson * Centre for Digestive Diseases, Queen Mary University of London, London, UK. * Janusz Jankowski * Digestive Diseases Centre, Leicester Royal Infirmary, Leicester, UK. * Janusz Jankowski * Department of Clinical Pharmacology, Old Road Campus, University of Oxford, Oxford, UK. * Janusz Jankowski * Clinical Neurosciences, St George's University of London, London, UK. * Hugh S Markus * Department of Medical and Molecular Genetics, King's College London School of Medicine, Guy's Hospital, London, UK. * Christopher G Mathew & * Richard Trembath * King's College London Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Denmark Hill, London, UK. * Robert Plomin * University of Cambridge, Department of Clinical Neurosciences, Addenbrooke's Hospital, Cambridge, UK. * Stephen J Sawcer * Department of Cardiovascular Science, University of Leicester, Glenfield Hospital, Leicester, UK. * Nilesh J Samani * National Institute for Health Research Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital National Health Service Foundation Trust, London, UK. * Ananth C Viswanathan * University College London Institute of Ophthalmology, London, UK. * Ananth C Viswanathan * Department of Molecular Neuroscience, Institute of Neurology, Queen Square, London, UK. * Nicholas W Wood * Peninsula College of Medicine and Dentistry, University of Exeter, Exeter, UK. * Lorna W Harries & * Andrew T Hattersley * Ninewells Hospital and Medical School, Dundee, UK. * Alex S F Doney * UK Oxford National Institute for Health Research Biomedical Research Centre, Churchill Hospital, Oxford, UK. * Mark I McCarthy * Department of Statistics, University of Oxford, Oxford, UK. * Peter Donnelly * A full list of members is provided in the Supplementary Note. * MAGIC investigators * These authors jointly directed this work. * Colin N A Palmer, * Peter Donnelly & * Ewan R Pearson Consortia * The GoDARTS and UKPDS Diabetes Pharmacogenetics Study Group * Kaixin Zhou, * Celine Bellenguez, * Chris C A Spencer, * Amanda J Bennett, * Ruth L Coleman, * Roger Tavendale, * Simon A Hawley, * Louise A Donnelly, * Chris Schofield, * Christopher J Groves, * Lindsay Burch, * Fiona Carr, * Amy Strange, * Colin Freeman, * Jenefer M Blackwell, * Elvira Bramon, * Matthew A Brown, * Juan P Casas, * Aiden Corvin, * Nicholas Craddock, * Panos Deloukas, * Serge Dronov, * Audrey Duncanson, * Sarah Edkins, * Emma Gray, * Sarah Hunt, * Janusz Jankowski, * Cordelia Langford, * Hugh S Markus, * Christopher G Mathew, * Robert Plomin, * Anna Rautanen, * Stephen J Sawcer, * Nilesh J Samani, * Richard Trembath, * Ananth C Viswanathan, * Nicholas W Wood, * Lorna W Harries, * Andrew T Hattersley, * Alex S F Doney, * Helen Colhoun, * Andrew D Morris, * Calum Sutherland, * D Grahame Hardie, * Leena Peltonen, * Mark I McCarthy, * Rury R Holman, * Colin N A Palmer, * Peter Donnelly, * Ewan R Pearson & * MAGIC investigators * The Wellcome Trust Case Control Consortium 2 Contributions A.D.M., C.N.A.P., E.R.P., A.S.F.D. H.C., A.T.H. and M.I.M. oversaw cohort collection for GoDARTS. R.R.H., M.I.M., R.L.C. and C.J.G. oversaw cohort collection for the UKPDS. The WTCCC2 DNA, genotyping, data quality control and informatics group (S.D., S.E., E.G., S.H. and C.L.) executed GWAS sample handling, genotyping and quality control. A.J.B., R. Tavendale, L.B., C.J.G. and F.C. performed the replication genotyping. The WTCCC2 Management Committee (P. Donnelly, J.M.B., E.B., M.A.B., J.P.C., A.C., N.C., P. Deloukas, A.D., J.J., H.S.M., C.G.M., R.P., A.R., S.J.S., N.J.S., R. Trembath, A.C.V., L.P. and N.W.W.) monitored the execution of the GWAS. K.Z., C.B., C.C.A.S., L.A.D., A.S. and C.F. performed statistical analyses. K.Z. and L.W.H. performed bioinformatic analyses. S.A.H., D.G.H., C. Schofield and C. Sutherland performed the functional studies. MAGIC investigators provided summary data on glycemic quantitative trait association. K.Z., C.B., C.C.A.S., C.N.P., A.D.M., C. ! Sutherland, D.G.H., R.R.H., M.I.M., P. Donnelly and E.R.P. contributed to writing the manuscript. All authors reviewed the final manuscript. Kaixin Zhou1,33, Celine Bellenguez2,33, Chris C A Spencer2, Amanda J Bennett3, Ruth L Coleman3,4, Roger Tavendale1, Simon A Hawley5, Louise A Donnelly1, Chris Schofield1, Christopher J Groves3, Lindsay Burch1, Fiona Carr1, Amy Strange2, Colin Freeman2, Jenefer M Blackwell6,7, Elvira Bramon8,9, Matthew A Brown10, Juan P Casas11,12, Aiden Corvin13, Nicholas Craddock14, Panos Deloukas15, Serge Dronov15, Audrey Duncanson16, Sarah Edkins15, Emma Gray15, Sarah Hunt15, Janusz Jankowski17,18,19, Cordelia Langford15, Hugh S Markus20, Christopher G Mathew21, Robert Plomin22, Anna Rautanen2, Stephen J Sawcer23, Nilesh J Samani24, Richard Trembath21, Ananth C Viswanathan25,26, Nicholas W Wood27, MAGIC investigators32, Lorna W Harries28, Andrew T Hattersley28, Alex S F Doney29, Helen Colhoun1, Andrew D Morris1, Calum Sutherland1, D Grahame Hardie5, Leena Peltonen15, Mark I McCarthy2,3,30, Rury R Holman3,4, Colin N A Palmer1,34, Peter Donnelly2,31,34 & Ewan R Pearson1,34 Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Ewan R Pearson Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (600K) Supplementary Tables 1–6, Supplementary Figures 1–3 and Supplementary Note. Additional data
• Mutations in SMAD3 cause a syndromic form of aortic aneurysms and dissections with early-onset osteoarthritis
  - Nat Genet 43(2):121-126 (2011)
  Nature Genetics | Letter Mutations in SMAD3 cause a syndromic form of aortic aneurysms and dissections with early-onset osteoarthritis * Ingrid M B H van de Laar1, 14 Search for this author in: * NPG journals * PubMed * Google Scholar * Rogier A Oldenburg1, 14 Search for this author in: * NPG journals * PubMed * Google Scholar * Gerard Pals2 Search for this author in: * NPG journals * PubMed * Google Scholar * Jolien W Roos-Hesselink3 Search for this author in: * NPG journals * PubMed * Google Scholar * Bianca M de Graaf1 Search for this author in: * NPG journals * PubMed * Google Scholar * Judith M A Verhagen1 Search for this author in: * NPG journals * PubMed * Google Scholar * Yvonne M Hoedemaekers1 Search for this author in: * NPG journals * PubMed * Google Scholar * Rob Willemsen1 Search for this author in: * NPG journals * PubMed * Google Scholar * Lies-Anne Severijnen1 Search for this author in: * NPG journals * PubMed * Google Scholar * Hanka Venselaar4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Gert Vriend4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Peter M Pattynama6 Search for this author in: * NPG journals * PubMed * Google Scholar * Margriet Collée1 Search for this author in: * NPG journals * PubMed * Google Scholar * Danielle Majoor-Krakauer1 Search for this author in: * NPG journals * PubMed * Google Scholar * Don Poldermans7 Search for this author in: * NPG journals * PubMed * Google Scholar * Ingrid M E Frohn-Mulder8 Search for this author in: * NPG journals * PubMed * Google Scholar * Dimitra Micha2 Search for this author in: * NPG journals * PubMed * Google Scholar * Janneke Timmermans9 Search for this author in: * NPG journals * PubMed * Google Scholar * Yvonne Hilhorst-Hofstee10 Search for this author in: * NPG journals * PubMed * Google Scholar * Sita M Bierma-Zeinstra11 Search for this author in: * NPG journals * PubMed * Google Scholar * Patrick J Willems12 Search for this author in: * NPG journals * PubMed * Google Scholar * Johan M Kros13 Search for this author in: * NPG journals * PubMed * Google Scholar * Edwin H G Oei6 Search for this author in: * NPG journals * PubMed * Google Scholar * Ben A Oostra1 Search for this author in: * NPG journals * PubMed * Google Scholar * Marja W Wessels1 Search for this author in: * NPG journals * PubMed * Google Scholar * Aida M Bertoli-Avella1 Contact Aida M Bertoli-Avella Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:121–126Year published:(2011)DOI:doi:10.1038/ng.744Received12 August 2010Accepted24 November 2010Published online09 January 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Thoracic aortic aneurysms and dissections are a main feature of connective tissue disorders, such as Marfan syndrome and Loeys-Dietz syndrome. We delineated a new syndrome presenting with aneurysms, dissections and tortuosity throughout the arterial tree in association with mild craniofacial features and skeletal and cutaneous anomalies. In contrast with other aneurysm syndromes, most of these affected individuals presented with early-onset osteoarthritis. We mapped the genetic locus to chromosome 15q22.2–24.2 and show that the disease is caused by mutations in SMAD3. This gene encodes a member of the TGF-β pathway that is essential for TGF-β signal transmission1, 2, 3. SMAD3 mutations lead to increased aortic expression of several key players in the TGF-β pathway, including SMAD3. Molecular diagnosis will allow early and reliable identification of cases and relatives at risk for major cardiovascular complications. Our findings endorse the TGF-β pathway as the primary ! pharmacological target for the development of new treatments for aortic aneurysms and osteoarthritis. View full text Figures at a glance * Figure 1: Clinical features of cases from family 1. Written consent was obtained for publication of these images. () Physical examination (from left to right). Facial features including a long face, hypertelorism, flat orbital ridges and malar flattening in individual IV-10; bifid uvula in individual IV-9; and translucency of the skin with visible thread veins in individual III-6. () Aneurysms and dissections (from left to right). Multi-slice computed tomography angiogram of thoracic aorta showing an aneurysm of the aortic root (45 mm, arrow) of individual IV-11 at the age of 29 years; multi-slice computed tomography angiogram in 50-year-old female (individual III-12) shows a Stanford type A aortic dissection (arrows) with the dissection flap extending from the aortic valve into the descending aorta at a maximal aortic diameter of 40 mm; and a 3D-reconstructed computed tomography angiogram (left posterior view) shows a fusiform aneurysm of the left vertebral artery (arrow) in a 46-year-old female (individual IV-1). () Osteoar! thritis and osteochondritis (from left to right). A 12-year-old boy (individual V-3) with early degenerative abnormalities of the lumbar spine, deformations of the vertebral body (arrow) and narrowing of the intervertebral disc space at multiple levels; advanced osteoarthritis of the first carpometacarpal joint of the left hand (arrow) in a 46-year-old female (individual IV-1); and magnetic resonance imaging of the left knee of a 12-year-old individual (individual V-3) shows a large osteochondral lesion without separation in the medial femoral condyle (arrow). * Figure 2: SMAD3 and mutations. () Schematic representation of SMAD3. Boxes represent exons 1–9 with the untranslated regions (UTRs) and the open reading frame. The three main functional domains, MH1, MH2 and the linker region, are indicated. The mutations (resulting in p.Thr247fsX61, p.Thr261I1e and p.Arg287Trp) are located in the MH2 domain, which mediates oligomerization of SMAD3 with SMAD4 and SMAD-dependent transcriptional activation. () Predicted SMAD3 protein sequence resulting from the mutation resulting in p.Thr247fsX61. Premature protein termination occurs after 61 amino acids. () Cross-species protein conservation of SMAD3 and protein conservation of human receptor and co-SMAD proteins around the altered amino acids p.Arg287 and p.Thr261. () Overview of the heterotrimeric complex formed by SMAD3/SMAD3/SMAD4 MH2 domains. The proteins are shown in ribbon presentations. The SMAD3 domains are colored green and blue, whereas the SMAD4 domain is shown in yellow. The altered amino acids (p.Thr261 and! p.Arg287) are colored magenta and are shown in ball representation. Note that the two mutated residues are located on and close to the interaction surface of the SMAD monomers. A close-up of a SMAD3-SMAD3 interaction site with the two altered residues, p.Thr261 and p.Arg287, shown (one SMAD3 monomer is displayed with its surface and the other monomer is displayed in ribbon representation). * Figure 3: Histology of aortic media in aneurysms-osteoarthritis syndrome. Aortic media from a control (donor, left column) and case (right column) with a SMAD3 mutation resulting in p.Thr247fsX61 (III-2, family 2). Scale bars correspond to 100 μm. Hematoxylin-eosin (H&E) staining displaying abnormal architecture of the aortic media and a dissection tear in the case. A Verhoeff-van Gieson staining for elastin (dark purple fibers); note the disarray, fragmentation and loss of elastic fibers in case versus control. A dissection tear is shown. A Masson's trichrome staining for collagen (green) showing intense collagen staining and disruption of the medial architecture in the case. * Figure 4: Immunohistochemistry in aneurysms-osteoarthritis syndrome. Aortic wall (from top to bottom, adventitia, media and intima layers) from a control (donor) and a case with a SMAD3 mutation resulting in p.Arg287Trp (IV-3, family 1). TGF-β1 immunostaining; note the increased TGF-β1 expression through the aortic media, whereas the control only shows marked expression in the outer media adjacent to the adventitia. Connective tissue growth factor immunolabeling (CTGF) is shown. CTGF is a TGF-β–responsive product which normally induces collagen synthesis. Note the increased labeling in the cytoplasm of media cells from the case compared to the donor. Scale bars, 200 μm; inset scale bars, 50 μm. Photomicrographs from the middle section of the aortic media showing phosphorylated SMAD2 (pSMAD2) immunolabeling with marked nuclear staining in the case. Total SMAD3 (phosphorylated and non-phosphorylated SMAD3) immunostaining showing increased nuclear and cytoplasmatic labeling in the case as compared to the donor. Scale bars, 100 μm; inset ! scale bars, 50 μm. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Entrez Nucleotide * NM_005902.3 Author information * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Ingrid M B H van de Laar & * Rogier A Oldenburg Affiliations * Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands. * Ingrid M B H van de Laar, * Rogier A Oldenburg, * Bianca M de Graaf, * Judith M A Verhagen, * Yvonne M Hoedemaekers, * Rob Willemsen, * Lies-Anne Severijnen, * Margriet Collée, * Danielle Majoor-Krakauer, * Ben A Oostra, * Marja W Wessels & * Aida M Bertoli-Avella * Department of Clinical Genetics, Vrije Universiteit Medical Center, Amsterdam, The Netherlands. * Gerard Pals & * Dimitra Micha * Department of Cardiology, Erasmus Medical Center, Rotterdam, The Netherlands. * Jolien W Roos-Hesselink * Nijmegen Center for Molecular Life Sciences (NCMLS), Radboud University Nijmegen Medical Center, The Netherlands. * Hanka Venselaar & * Gert Vriend * Center for Molecular and Biomolecular Informatics (CMBI), Nijmegen, The Netherlands. * Hanka Venselaar & * Gert Vriend * Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands. * Peter M Pattynama & * Edwin H G Oei * Department of Vascular Surgery, Erasmus Medical Center, Rotterdam, The Netherlands. * Don Poldermans * Department of Pediatric Cardiology, Erasmus Medical Center, Rotterdam, The Netherlands. * Ingrid M E Frohn-Mulder * Department of Cardiology, Radboud University Nijmegen Medical Center, The Netherlands. * Janneke Timmermans * Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands. * Yvonne Hilhorst-Hofstee * Department of General Practice, Erasmus Medical Center, Rotterdam, The Netherlands. * Sita M Bierma-Zeinstra * GENDIA (GENetic DIAgnostic Network), Antwerp, Belgium. * Patrick J Willems * Department of Pathology, Erasmus Medical Center, Rotterdam, The Netherlands. * Johan M Kros Contributions A.M.B.-A. designed and directed the study. I.M.B.H.v.d.L., R.A.O., J.W.R.-H., Y.M.H., E.H.G.O., J.M.A.V., P.M.P., D.M.-K., D.P., I.M.E.F.-M., S.M.B.-Z., Y.H.-H., M.C., J.T. and M.W.W. evaluated the cases and relatives. G.P., D.M., J.M.A.V., D.P. and D.M.-K. contributed with DNA sample collections. B.M.d.G. generated and processed genotype and sequence data. L.-A.S. and R.W. performed and interpreted the immunohistochemistry. J.M.K. supervised the histopathological studies. H.V. and G.V. performed, analyzed and described the protein molecular modeling. B.A.O. contributed to the interpretation and supervision of the genetic work. I.M.B.H.v.d.L. and A.M.B.-A. wrote the manuscript. P.J.W., M.W.W. and G.P. contributed to the analysis and interpretation of the genetic data and substantially contributed to the manuscript. All authors have read and contributed to the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Aida M Bertoli-Avella Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (976K) Supplementary Figures 1–5, Supplementary Note and Supplementary Table 1 Additional data
• Tartrate-resistant acid phosphatase deficiency causes a bone dysplasia with autoimmunity and a type I interferon expression signature
  - Nat Genet 43(2):127-131 (2011)
  Nature Genetics | Letter Tartrate-resistant acid phosphatase deficiency causes a bone dysplasia with autoimmunity and a type I interferon expression signature * Tracy A Briggs1 Search for this author in: * NPG journals * PubMed * Google Scholar * Gillian I Rice1 Search for this author in: * NPG journals * PubMed * Google Scholar * Sarah Daly1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jill Urquhart1 Search for this author in: * NPG journals * PubMed * Google Scholar * Hannah Gornall1 Search for this author in: * NPG journals * PubMed * Google Scholar * Brigitte Bader-Meunier2 Search for this author in: * NPG journals * PubMed * Google Scholar * Kannan Baskar3 Search for this author in: * NPG journals * PubMed * Google Scholar * Shankar Baskar3 Search for this author in: * NPG journals * PubMed * Google Scholar * Veronique Baudouin4 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael W Beresford5 Search for this author in: * NPG journals * PubMed * Google Scholar * Graeme C M Black1 Search for this author in: * NPG journals * PubMed * Google Scholar * Rebecca J Dearman6 Search for this author in: * NPG journals * PubMed * Google Scholar * Francis de Zegher7 Search for this author in: * NPG journals * PubMed * Google Scholar * Emily S Foster6 Search for this author in: * NPG journals * PubMed * Google Scholar * Camille Francès8 Search for this author in: * NPG journals * PubMed * Google Scholar * Alison R Hayman9 Search for this author in: * NPG journals * PubMed * Google Scholar * Emma Hilton1 Search for this author in: * NPG journals * PubMed * Google Scholar * Chantal Job-Deslandre10 Search for this author in: * NPG journals * PubMed * Google Scholar * Muralidhar L Kulkarni3 Search for this author in: * NPG journals * PubMed * Google Scholar * Martine Le Merrer11 Search for this author in: * NPG journals * PubMed * Google Scholar * Agnes Linglart12 Search for this author in: * NPG journals * PubMed * Google Scholar * Simon C Lovell6 Search for this author in: * NPG journals * PubMed * Google Scholar * Kathrin Maurer13 Search for this author in: * NPG journals * PubMed * Google Scholar * Lucile Musset14 Search for this author in: * NPG journals * PubMed * Google Scholar * Vincent Navarro15 Search for this author in: * NPG journals * PubMed * Google Scholar * Capucine Picard16, 17, 18 Search for this author in: * NPG journals * PubMed * Google Scholar * Anne Puel16, 17 Search for this author in: * NPG journals * PubMed * Google Scholar * Frederic Rieux-Laucat17, 19 Search for this author in: * NPG journals * PubMed * Google Scholar * Chaim M Roifman20 Search for this author in: * NPG journals * PubMed * Google Scholar * Sabine Scholl-Bürgi21 Search for this author in: * NPG journals * PubMed * Google Scholar * Nigel Smith22 Search for this author in: * NPG journals * PubMed * Google Scholar * Marcin Szynkiewicz1 Search for this author in: * NPG journals * PubMed * Google Scholar * Alice Wiedeman23, 24 Search for this author in: * NPG journals * PubMed * Google Scholar * Carine Wouters7 Search for this author in: * NPG journals * PubMed * Google Scholar * Leo A H Zeef6 Search for this author in: * NPG journals * PubMed * Google Scholar * Jean-Laurent Casanova16, 17, 25 Search for this author in: * NPG journals * PubMed * Google Scholar * Keith B Elkon23, 24 Search for this author in: * NPG journals * PubMed * Google Scholar * Anthony Janckila26 Search for this author in: * NPG journals * PubMed * Google Scholar * Pierre Lebon27 Search for this author in: * NPG journals * PubMed * Google Scholar * Yanick J Crow1 Contact Yanick J Crow Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:127–131Year published:(2011)DOI:doi:10.1038/ng.748Received19 August 2010Accepted06 December 2010Published online09 January 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 studied ten individuals from eight families showing features consistent with the immuno-osseous dysplasia spondyloenchondrodysplasia. Of particular note was the diverse spectrum of autoimmune phenotypes observed in these individuals (cases), including systemic lupus erythematosus, Sjögren's syndrome, hemolytic anemia, thrombocytopenia, hypothyroidism, inflammatory myositis, Raynaud's disease and vitiligo. Haplotype data indicated the disease gene to be on chromosome 19p13, and linkage analysis yielded a combined multipoint log10 odds (LOD) score of 3.6. Sequencing of ACP5, encoding tartrate-resistant acid phosphatase, identified biallelic mutations in each of the cases studied, and in vivo testing confirmed a loss of expressed protein. All eight cases assayed showed elevated serum interferon alpha activity, and gene expression profiling in whole blood defined a type I interferon signature. Our findings reveal a previously unrecognized link between tartrate-resistant acid! phosphatase activity and interferon metabolism and highlight the importance of type I interferon in the genesis of autoimmunity. View full text Figures at a glance * Figure 1: Bone, brain and skin involvement in cases with mutations in ACP5. () Enchondromatous lesions are seen in the distal ulna and radius of case 1, with sclerosis and irregularity of the metaphyseal plate. () Lateral spine radiographs demonstrate platyspondyly and irregularity of the vertebral endplates in case 4. () Dense calcification of the basal ganglia, thalami and deep gyri is observed in case 1. () The hands of case 1 illustrate substantial sclerotic changes. Note the loss of tissue from several digits. Severe gangrenous changes led to amputation of the left index finger. * Figure 2: Summary of mutation data. () The AutoSNPa output for Chromosome 19p generated from genome-wide SNP analysis of five unrelated individuals (C denotes case). We identified a shared region of homozygosity (indicated by the red box) in three cases (4, 6 and 7) born to consanguineous parents between base-pair positions 10,527,380 and 13,214,722 (black and yellow bars indicate homozygous and heterozygous SNPs, respectively). Within this homozygous region, case 1 showed a failure of hybridization for a copy number probe and an adjacent SNP probe. () We performed quantitative multiplex PCR of short fluorescent fragments to confirm the presence of the putative deletion in this case. Representative data from an analysis of exons 4 and 6 indicates that no products were seen using DNA from the proband (with a predicted copy number of 0), consistent with a homozygous ACP5 deletion, whereas her mother carries a heterozygous deletion as expected (with a predicted copy number of 1, compared to a predicted copy numbe! r of 2 in the control). DNA from the father was unavailable. () A schematic of the disease-critical interval on chromosome 19p. The deleted region included sequence for ACP5, in which we identified single base-pair mutations, a frame shift mutation and two gene deletions. Deletions are indicated by solid lines and double arrows indicate extension beyond the coordinates shown. No other genes were involved in either of these deletions. * Figure 3: Levels of TRAP protein and interferon alpha activity in cases with mutations in ACP5. () We used monoclonal antibodies to measure levels of total TRAP protein and TRAP isoform 5a in plasma from six cases with ACP5 mutations and compared them with levels in age and sex-matched control samples. We also tested an unaffected sibling of cases 2 and 3 who was homozygous for the wildtype allele on gene sequencing (designated control 001). All six cases demonstrated only background levels of total protein and an absence of 5a protein. () We obtained serum samples from eight cases with mutations in ACP5, and we measured interferon alpha levels using a biological assay of antiviral activity. Five cases were assayed serially, with greater than one month intervals between assay points. On only one occasion was the level of interferon alpha within the normal range (<2 IU/ml) in any of the cases sampled. * Figure 4: Computational analysis of missense mutations in the context of protein structure. We modeled each of the four missense mutations in the context of the crystal structure22. Interactions between the mutated side chains and the rest of the protein are indicated; pink and yellow spikes indicate destabilizing van der Waals overlaps and green lenses represent stabilizing hydrogen bonds. Van der Waals contacts are omitted for clarity. The least destabilizing side chain conformation ('rotamer') is shown in each case. Insets illustrate the wildtype residues and their interactions with the rest of the protein shown from the same viewpoint. () The alteration of isoleucine 89 to threonine. () The alteration of glycine 215 to arginine. () The alteration of aspartate 241 to asparganine. () The alteration of methionine 264 to lysine. For each alteration, van der Waals overlaps are large enough that they are likely to substantially destabilize the structure. In addition, in , there is loss of a hydrogen bond that is stabilizing in the wildtype, and in , the charged NH3 g! roup of the lysine is buried from solvent and not able to make a neutralizing charge-charge interaction, further destabilizing the mutant structure. * Figure 5: Gene expression analysis in cases with TRAP deficiency. () We undertook whole-transcriptome microarray expression analysis in three cases and compared the results to the data derived from three age-matched control samples. We identified a subset of 18 genes that were fourfold or more upregulated in cases, with a significance level for the comparisons of P < 0.0005 and a false discovery value of <0.2 (Supplementary Fig. 3). Fifteen of these genes are known to be interferon stimulated, characteristic of a type I interferon signature. The intensity plot was generated from the gene expression values (log 2) that had been standardized (for each gene, the mean was set to zero and the standard deviation was set to 1) using Partek Genomics Solution (version 6.5, Partek Inc.). () qPCR data for a representative sample of these upregulated genes: LY6E, MX1, USP18, RSAD2, OAS1, IFI44L, IL-10 and IL-12. All genes assessed in the case group were significantly upregulated (P < 0.001) compared to controls, except for IL-10 and IL-12, confirming ! the type 1 interferon signature seen on microarray analysis and showing an absence of up- or down-regulation of IL-10 and IL-12. RQ is equal to 2−ΔΔCt, with ΔΔCt ± standard deviations, that is the normalized fold change relative to a calibrator. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions ArrayExpress * E-MEXP-2699 Author information * Accession codes * Author information * Supplementary information Affiliations * Manchester Academic Heath Science Centre, University of Manchester, Genetic Medicine, Manchester, UK. * Tracy A Briggs, * Gillian I Rice, * Sarah Daly, * Jill Urquhart, * Hannah Gornall, * Graeme C M Black, * Emma Hilton, * Marcin Szynkiewicz & * Yanick J Crow * Assistance Publique-Hôpitaux de Paris (AP-HP), Necker Hospital, Department of Pediatric Immunology, Hematology and Rheumatology, Paris, France. * Brigitte Bader-Meunier * J.J.M. Medical College, Department of Pediatrics, Davangere, India. * Kannan Baskar, * Shankar Baskar & * Muralidhar L Kulkarni * AP-HP, Robert Debré Hospital, Pediatric Nephrology Department, Paris, France. * Veronique Baudouin * University of Liverpool, Institute of Child Health, Liverpool, UK. * Michael W Beresford * University of Manchester, Faculty of Life Sciences, Manchester, UK. * Rebecca J Dearman, * Emily S Foster, * Simon C Lovell & * Leo A H Zeef * University of Leuven, Department of Paediatrics, Leuven, Belgium. * Francis de Zegher & * Carine Wouters * Hôpital Tenon, Department of Dermatology and Allergy, Paris, France. * Camille Francès * University of Bristol, Department of Clinical Veterinary Science, Bristol, UK. * Alison R Hayman * AP-HP Cochin, Service de Rheumatology A, Paris, France. * Chantal Job-Deslandre * Necker Hospital, Institut National de la Santé et de la Recherche Médicale (INSERM) U781, Paris, France. * Martine Le Merrer * INSERM U986, Paris, France. * Agnes Linglart * Innsbruck Medical University, Department of Radiology, Innsbruck, Austria. * Kathrin Maurer * AP-HP, Department of Immunochemistry, Paris, France. * Lucile Musset * AP-HP, Epilepsy Unit, Paris, France. * Vincent Navarro * INSERM-U980 Necker Faculty, Laboratory of Human Genetics of Infectious Diseases, Paris, France. * Capucine Picard, * Anne Puel & * Jean-Laurent Casanova * Necker faculty, Paris Descartes University, Paris, France. * Capucine Picard, * Anne Puel, * Frederic Rieux-Laucat & * Jean-Laurent Casanova * The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada. * Capucine Picard * Innsbruck Medical University, Department of Pediatrics IV, Neonatology, Neuropediatrics and Inherited Metabolic Disorders, Innsbruck, Austria. * Frederic Rieux-Laucat * Paterson Institute for Cancer Research, University of Manchester, Clinical and Experimental Pharmacology Group, Manchester, UK. * Chaim M Roifman * University of Washington, Department of Medicine, Seattle, Washington, USA. * Sabine Scholl-Bürgi * Department of Immunology, Seattle, Washington, USA. * Nigel Smith * The Rockefeller University, Laboratory of Human Genetics of Infectious Diseases, New York, New York, USA. * Alice Wiedeman & * Keith B Elkon * University of Washington, Department of Immunology, Seattle, Washington, USA. * Alice Wiedeman & * Keith B Elkon * St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, Laboratory of Human Genetics of Infectious Diseases, New York, New York, USA. * Jean-Laurent Casanova * Robley Rex Department of Veterans Affairs Medical Center, Special Hematology Laboratory, Louisville, Kentucky, USA. * Anthony Janckila * Université Paris Descartes, Service Virologie, Paris, France. * Pierre Lebon Contributions S.D., J.U. and T.A.B. performed SNP genotyping. T.A.B. performed sequencing with contributions from S.D., H.G., G.I.R. and M.S. QMPSF analysis was undertaken by J.U. and M.S. Interferon assays were conducted by P.L. L.A.H.Z. performed microarray analysis. RT-PCR and qPCR was conducted by G.I.R., T.A.B., H.G., E.H. and E.S.F. Protein assays were preformed by A.J. for TRAP and by N.S. for OPN. ACP5 expression in different human cell types was assessed by K.B.E. and A.W. Lymphocyte subset analysis was conducted by C.P., A.P. and F.R.-L. Bioinformatics analysis was conducted by S.C.L. All other coauthors identified subjects with SPENCD and performed related clinical and laboratory studies (B.B.-M., K.B., S.B., V.B., M.W.B., F.d.Z., C.F., C.J.-D., M.L.K., M.L.M., A.L., K.M., L.M., V.N., C.M.R., S.S.-B. and C.W.). G.I.R., J.-L.C., A.R.H., R.J.D. and G.C.M.B. provided critical input into project development and manuscript preparation. Y.J.C. designed and supervised the project and ! wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Yanick J Crow Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (492K) Supplementary Note, Supplementary Figures 1–4 and Supplementary Tables 1–7 Additional data
• Genetic deficiency of tartrate-resistant acid phosphatase associated with skeletal dysplasia, cerebral calcifications and autoimmunity
  - Nat Genet 43(2):132-137 (2011)
  Nature Genetics | Letter Genetic deficiency of tartrate-resistant acid phosphatase associated with skeletal dysplasia, cerebral calcifications and autoimmunity * Ekkehart Lausch1 Search for this author in: * NPG journals * PubMed * Google Scholar * Andreas Janecke2 Search for this author in: * NPG journals * PubMed * Google Scholar * Matthias Bros3 Search for this author in: * NPG journals * PubMed * Google Scholar * Stefanie Trojandt3 Search for this author in: * NPG journals * PubMed * Google Scholar * Yasemin Alanay4 Search for this author in: * NPG journals * PubMed * Google Scholar * Corinne De Laet5 Search for this author in: * NPG journals * PubMed * Google Scholar * Christian A Hübner6 Search for this author in: * NPG journals * PubMed * Google Scholar * Peter Meinecke7 Search for this author in: * NPG journals * PubMed * Google Scholar * Gen Nishimura8 Search for this author in: * NPG journals * PubMed * Google Scholar * Mari Matsuo9 Search for this author in: * NPG journals * PubMed * Google Scholar * Yoshiko Hirano9 Search for this author in: * NPG journals * PubMed * Google Scholar * Sylvie Tenoutasse5 Search for this author in: * NPG journals * PubMed * Google Scholar * Andrea Kiss10 Search for this author in: * NPG journals * PubMed * Google Scholar * Rafael Fabiano Machado Rosa10 Search for this author in: * NPG journals * PubMed * Google Scholar * Sharon L Unger11 Search for this author in: * NPG journals * PubMed * Google Scholar * Raffaele Renella12, 13 Search for this author in: * NPG journals * PubMed * Google Scholar * Luisa Bonafé13 Search for this author in: * NPG journals * PubMed * Google Scholar * Jürgen Spranger1 Search for this author in: * NPG journals * PubMed * Google Scholar * Sheila Unger1, 14 Search for this author in: * NPG journals * PubMed * Google Scholar * Bernhard Zabel1 Search for this author in: * NPG journals * PubMed * Google Scholar * Andrea Superti-Furga1, 13 Contact Andrea Superti-Furga Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:132–137Year published:(2011)DOI:doi:10.1038/ng.749Received19 August 2010Accepted06 December 2010Published online09 January 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Vertebral and metaphyseal dysplasia, spasticity with cerebral calcifications, and strong predisposition to autoimmune diseases are the hallmarks of the genetic disorder spondyloenchondrodysplasia. We mapped a locus in five consanguineous families to chromosome 19p13 and identified mutations in ACP5, which encodes tartrate-resistant phosphatase (TRAP), in 14 affected individuals and showed that these mutations abolish enzyme function in the serum and cells of affected individuals. Phosphorylated osteopontin, a protein involved in bone reabsorption and in immune regulation, accumulates in serum, urine and cells cultured from TRAP-deficient individuals. Case-derived dendritic cells exhibit an altered cytokine profile and are more potent than matched control cells in stimulating allogeneic T cell proliferation in mixed lymphocyte reactions. These findings shed new light on the role of osteopontin and its regulation by TRAP in the pathogenesis of common autoimmune disorders. View full text Figures at a glance * Figure 1: Pleiotropism of SPENCD. (–) Characteristic metaphyseal changes produced by extension of cartilaginous tissue from the growth plate into the metaphyses (distal radius, distal femur and proximal fibula), as well as changes of the vertebral bodies. () Calcifications of the basal ganglia and of the subcortical region (case 6). The last two panels show a lupus erythematosus cell () and a rosette () in the peripheral blood smear of case 1 (original photographs from the 1956 chart); both are typical of florid systemic lupus erythematosus. * Figure 2: Mutations in ACP5 and their effect on TRAP activity. () Molecular model of the TRAP protein based on the crystal structure (PDB 2BQ; Online Methods). The two gray globules in the middle are the two iron atoms of the reactive center. The labels indicate the position of mutations identified in individuals with SPENCD (missense and in-frame deletion mutations are in yellow and frameshift or premature stops are in red). The graphs in show the levels of TRAP activity in serum and in leukocyte homogenate of controls (CTL, blue), SPENCD cases (PAT, red) and of their parents (PAR, gray); horizontal lines in the scatter plot indicate the mean; error bars indicate the standard deviation of the mean (s.d.m.). () Histochemical detection of TRAP activity (purple cytoplasmic staining) in dendritic cells from a matched control (left) and from case 2 (right). No activity is detectable in the cells from the cases. * Figure 3: Osteopontin deregulation in SPENCD. () Plasma OPN concentrations of SPENCD cases (n = 4) and matched controls (n = 12). Results are presented as a scatter plot and horizontal lines indicate the mean; we used the Mann-Whitney rank sum test and a two-tailed t-test with Welch's correction to assess differences (P < 0.05). () Protein blot analysis of OPN in protein preparations from urine of two representative age- and sex-matched unaffected controls and SPENCD cases. We loaded equal amounts of total urinary protein and used 50 ng of phosphorylated recombinant OPN (pOPN) as the control. All cases and controls had normal renal function at the time of urine sampling. () Protein blot analysis of recombinant OPN (rOPN) incubated with dendritic cell lysates from SPENCD cases and controls using tag antibody to assess the amount of loaded rOPN (top panel) and anti-ACP5 antibody to detect TRAP in dendritic cell lysates (second panel from top). We immunoprecipitated protein preparations using a V5 antibody detected and the! amount of precipitated OPN and its phosphorylation state by OPN (third panel from top) and phospho-serine antibodies (pSer, bottom panel). Note dephosphorylation of precipitated OPN by recombinant TRAP (rTRAP) and control lysate but not by cases' lysates. () OPN concentrations in the supernatants of immature dendritic cells derived from individuals with SPENCD (n = 4) and matched controls (n = 12) at day 5 (d5) and assayed after 2 days of culture (d7) differ significantly, as analyzed by a two-tailed t-test with Welch's correction. Error bars, s.d.m. of triplicate values. * Figure 4: TRAP-deficient dendritic cells secrete Th1-polarizing cytokines and show enhanced T cell allostimulatory activity. () Supernatants of immature dendritic cells from SPENCD cases and controls were analyzed by ELISA for the secretion of IL-10, IL-12 (p70), IL-13 and TNF-alpha (full bars). As a positive control, recombinant OPN (0.5 μg/ml) was added to both cell populations from days 5–7 of culture (hatched bars). Mean cytokine concentration per million dendritic cells from four independent experiments is shown. Error bars, s.d.m. of triplicate values. We used a two-tailed t-test with Welch's correction to assess differences. () We performed mixed lymphocyte reactions (MLR) with allogeneic T cells and immature dendritic cells from SPENCD cases and controls on day 5 and on day 7 of dendritic cell culture; dendritic cells and T cells were combined at a ratio of 1:10. T cell proliferation was measured by 3H-thymidine incorporation for 16 h on day 5 of co-culture. Squares in the scatter plot represent mean counts per minute (cpm) of quadruplicate cultures; horizontal lines indicate the mean. ! We analyzed the differences between cases and controls of four independent experiments by one-way analysis of variance (ANOVA). () The concentration of IL-4, IL-10, IL-12 (p70), IL-13 and IFN-gamma was determined by ELISA in the supernatants from MLRs with immature dendritic cells (d5) after 2 days of co-culture; mean concentrations of quadruplicate measurements are shown. Error bars, s.d.m. We used a two-tailed t-test with Welch's correction to assess differences. n.s., not significant. * Figure 5: Variable serum cytokine patterns in individuals with SPENCD. We determined serum cytokine concentrations of () IL-4, () IL-10, () IL-12, () IL-17, () IFN-alpha and () TNF-alpha by ELISA in SPENCD cases (n = 4) and in age- and sex-matched controls (n = 16). IFN-gamma levels were below the detection limit of the assay in all samples (data not shown). Results of triplicate measurements of each sample are presented as scatter plots; horizontal lines indicate the mean. We used the Mann-Whitney rank sum test and a two-tailed t-test with Welch's correction to assess differences. n.s., not significant. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Protein Data Bank * 2BQ8 * 2BQ8 Author information * Accession codes * Author information * Supplementary information Affiliations * Centre for Pediatrics and Adolescent Medicine, Freiburg University Hospital, University of Freiburg, Freiburg, Germany. * Ekkehart Lausch, * Jürgen Spranger, * Sheila Unger, * Bernhard Zabel & * Andrea Superti-Furga * Department of Pediatrics II and Division of Human Genetics, Innsbruck Medical University, Innsbruck, Austria. * Andreas Janecke * Department of Dermatology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany. * Matthias Bros & * Stefanie Trojandt * Pediatric Genetics Unit, Department of Pediatrics, Hacettepe University Medical Faculty, Ankara, Turkey. * Yasemin Alanay * Nutrition and Metabolism Unit, Queen Fabiola Children's University Hospital, Bruxelles, Belgium. * Corinne De Laet & * Sylvie Tenoutasse * Institute of Human Genetics, University Hospital Jena, Friedrich-Schiller-University, Jena, Germany. * Christian A Hübner * Clinical Genetics Unit, Children's Hospital Altona, Hamburg, Germany. * Peter Meinecke * Department of Pediatric Imaging, Tokyo Metropolitan Children's Medical Center, Fuchu, Tokyo, Japan. * Gen Nishimura * Department of Pediatrics, Tokyo Women's Medical University, Tokyo, Japan. * Mari Matsuo & * Yoshiko Hirano * Clinical Genetics Division and the Graduate Program in Pathology, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil. * Andrea Kiss & * Rafael Fabiano Machado Rosa * Division of Neonatology, Mount Sinai Hospital, University of Toronto, Toronto, Canada. * Sharon L Unger * Department of Pediatric Hematology-Oncology, Children's Hospital and Dana-Farber Cancer Institute, Boston, Massachusetts, USA. * Raffaele Renella * Department of Pediatrics, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland. * Raffaele Renella, * Luisa Bonafé & * Andrea Superti-Furga * Department of Medical Genetics, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland. * Sheila Unger Contributions E.L. and A.S.-F. conceived and initiated the project and E.L. designed functional studies. B.Z., A.S.-F. and E.L. secured financial support. Y.A., C.D.L., C.A.H., P.M., G.N., M.M., Y.H., S. Tenoutasse, A.K., R.F.M.R., S.L.U., R.R., L.B., J.S., B.Z., E.L. and A.S.-F. identified cases of SPENCD, provided clinical information and collected biologic materials. S.U., R.R., J.S., E.L. and A.S.-F. assessed the clinical and radiographic data for inclusion in the study. A.S.-F., E.L. and A.J. performed linkage and mutation analysis. E.L. performed biochemical analyses and statistical evaluation. E.L., M.B. and S. Trojandt performed the expression studies as well as the functional and immunological studies with dendritic cells. B.Z., S.U. and R.R. discussed the ongoing experiments with E.L. and A.S.-F. Finally, E.L., S.U., B.Z. and A.S.-F. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Andrea Superti-Furga Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (492K) Supplementary Note, Supplementary Table 1 and Supplementary Figures 1–3 Additional data
• SLX4, a coordinator of structure-specific endonucleases, is mutated in a new Fanconi anemia subtype
  - Nat Genet 43(2):138-141 (2011)
  Nature Genetics | Letter SLX4, a coordinator of structure-specific endonucleases, is mutated in a new Fanconi anemia subtype * Chantal Stoepker1 Search for this author in: * NPG journals * PubMed * Google Scholar * Karolina Hain2 Search for this author in: * NPG journals * PubMed * Google Scholar * Beatrice Schuster3 Search for this author in: * NPG journals * PubMed * Google Scholar * Yvonne Hilhorst-Hofstee4 Search for this author in: * NPG journals * PubMed * Google Scholar * Martin A Rooimans1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jurgen Steltenpool1 Search for this author in: * NPG journals * PubMed * Google Scholar * Anneke B Oostra1 Search for this author in: * NPG journals * PubMed * Google Scholar * Katharina Eirich3 Search for this author in: * NPG journals * PubMed * Google Scholar * Elisabeth T Korthof4 Search for this author in: * NPG journals * PubMed * Google Scholar * Aggie W M Nieuwint1 Search for this author in: * NPG journals * PubMed * Google Scholar * Nicolaas G J Jaspers5 Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas Bettecken6 Search for this author in: * NPG journals * PubMed * Google Scholar * Hans Joenje1 Search for this author in: * NPG journals * PubMed * Google Scholar * Detlev Schindler3 Contact Detlev Schindler Search for this author in: * NPG journals * PubMed * Google Scholar * John Rouse2 Contact John Rouse Search for this author in: * NPG journals * PubMed * Google Scholar * Johan P de Winter1 Contact Johan P de Winter Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume: 43,Pages:138–141Year published:(2011)DOI:doi:10.1038/ng.751Received21 June 2010Accepted15 December 2010Published online16 January 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg DNA interstrand crosslink repair requires several classes of proteins, including structure-specific endonucleases and Fanconi anemia proteins. SLX4, which coordinates three separate endonucleases, was recently recognized as an important regulator of DNA repair. Here we report the first human individuals found to have biallelic mutations in SLX4. These individuals, who were previously diagnosed as having Fanconi anemia, add SLX4 as an essential component to the FA-BRCA genome maintenance pathway. View full text Figures at a glance * Figure 1: Cellular characteristics of individuals with Fanconi anemia with a defect in SLX4. () Spontaneous and mitomycin C (MMC)-induced chromosomal breakage in EBV-immortalized lymphoblasts from a healthy individual (EUFA045-L), a FANCA-deficient individual (HSC72) and individual EUFA1354. Percentages of cells with up to ten or more break events per metaphase are shown. () Growth inhibition of EUFA1354, 457/1 and 457/3 lymphoblasts upon exposure to MMC or () camptothecin (CPT). Lymphoblasts from a healthy individual (HSC93) and a FANCM-deficient individual (EUFA867-L) were analyzed as controls. Data represent means and s.e.m. from at least two independent experiments. () Immunoprecipitation and protein blot analysis showing reduced SLX4 expression in lymphoblasts from the affected siblings 457/1 and 457/3 and the absence of full-length SLX4 in lymphoblasts from EUFA1354. The mutant protein in 457/1 and 457/3 interacts with ERCC1, XPF and MUS81, whereas these proteins are not co-precipitated in EUFA1354-L. We performed immunoprecipitation with antibodies against th! e SLX4 N terminus (1–300) and protein blotting with an antibody against the SLX4 C terminus (1,534–1,834). SE and LE indicate short and long exposures of the blot, respectively. () Immunoprecipitation and protein blot analysis demonstrating the absence of full-length SLX4 and impaired interactions with MUS81 and ERCC1 in SV40-immortalized EUFA1354 fibroblasts. We used wildtype fibroblasts (LN9SV) as a control. () Subcellular fractionation of EUFA1354 lymphoblasts and fibroblasts showing reduced chromatin binding of ERCC1 and XPF. We analyzed the cytoplasmic fraction (CE), nuclear extract (NE) and chromatin fraction (CB) and used tubulin, p300 and histone H3 as controls for these fractions. WT, wildtype; FA-A, Fanconi anemia type A; FA-M, Fanconi anemia type M. * Figure 2: Functional correction of EUFA1354 fibroblasts and lymphoblasts by exogenous SLX4. ERCC1 foci are absent in () primary and () SV40-immortalized EUFA1354 fibroblasts. Bebu and LN9SV were used as wildtype controls. () Transient transfection of FLAG-SLX4 in SV40-immortalized EUFA1354 fibroblasts restored their ability to form nuclear ERCC1 foci. An empty vector (pcDNA3) was used as a control. () Transient transfection of GFP-SLX4 in SV40-immortalized EUFA1354 fibroblasts restored their ability to form nuclear ERCC1 foci. Transient transfection of GFP was used as a control. ERCC1 foci are more pronounced after brief pre-permeabilization with Triton-X100 before fixation, but this removed exogenous GFP. ERCC1 antibody FL297 was used for immunofluoresence, and DAPI (blue) was used as a nuclear counterstaining. () A mouse Slx4 protein that lacks the Slx1 binding site (FLAG-Slx4ΔSlx1) is stably expressed in EUFA1354 lymphoblasts and interacts with ERCC1. () FLAG-Slx4ΔSlx1 partially corrects MMC-induced growth inhibition in EUFA1354 lymphoblasts. Data represent me! ans and s.e.m. from two independent experiments. () FLAG-Slx4ΔSlx1 partially corrects MMC-induced chromosomal breakage in EUFA1354 lymphoblasts. WT, wildtype. Author information * Author information * Supplementary information Affiliations * Department of Clinical Genetics, Vrije Universiteit (VU) Medical Center, Amsterdam, The Netherlands. * Chantal Stoepker, * Martin A Rooimans, * Jurgen Steltenpool, * Anneke B Oostra, * Aggie W M Nieuwint, * Hans Joenje & * Johan P de Winter * Medical Research Council Protein Phosphorylation Unit, College of Life Sciences, University of Dundee, Dundee, Scotland, UK. * Karolina Hain & * John Rouse * Department of Human Genetics, University of Wuerzburg, Biozentrum, Wuerzburg, Germany. * Beatrice Schuster, * Katharina Eirich & * Detlev Schindler * Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands. * Yvonne Hilhorst-Hofstee & * Elisabeth T Korthof * Department of Genetics, Erasmus Medical Center, Rotterdam, The Netherlands. * Nicolaas G J Jaspers * Center for Applied Genotyping Munich, Max-Planck-Institut für Psychiatrie, Munich, Germany. * Thomas Bettecken Contributions The study was designed by J.P.d.W., J.R., D.S. and H.J. Clinical information of affected individuals and referral for Fanconi anemia diagnosis was coordinated by E.T.K. and Y.H.-H. Fanconi anemia diagnosis was confirmed by A.W.M.N. SNP array studies were coordinated by T.B. Mutational analysis and functional studies were carried out by C.S., K.H., B.S., M.A.R., J.S., A.B.O. and K.E. The ERCC1 focus formation assay was coordinated by N.G.J.J. The manuscript was written by C.S., J.P.d.W., J.R. and D.S., with help from the other authors. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Johan P de Winter or * John Rouse or * Detlev Schindler Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (6M) Supplementary Table 1 and Supplementary Figures 1–9 Additional data
• Mutations of the SLX4 gene in Fanconi anemia
  - Nat Genet 43(2):142-146 (2011)
  Nature Genetics | Letter Mutations of the SLX4 gene in Fanconi anemia * Yonghwan Kim1, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Francis P Lach1, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Rohini Desetty1 Search for this author in: * NPG journals * PubMed * Google Scholar * Helmut Hanenberg2, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Arleen D Auerbach4 Search for this author in: * NPG journals * PubMed * Google Scholar * Agata Smogorzewska1 Contact Agata Smogorzewska Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:142–146Year published:(2011)DOI:doi:10.1038/ng.750Received31 August 2010Accepted15 December 2010Published online16 January 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Fanconi anemia is a rare recessive disorder characterized by genome instability, congenital malformations, progressive bone marrow failure and predisposition to hematologic malignancies and solid tumors1. At the cellular level, hypersensitivity to DNA interstrand crosslinks is the defining feature in Fanconi anemia2. Mutations in thirteen distinct Fanconi anemia genes3 have been shown to interfere with the DNA-replication–dependent repair of lesions involving crosslinked DNA at stalled replication forks4. Depletion of SLX4, which interacts with multiple nucleases and has been recently identified as a Holliday junction resolvase5, 6, 7, results in increased sensitivity of the cells to DNA crosslinking agents. Here we report the identification of biallelic SLX4 mutations in two individuals with typical clinical features of Fanconi anemia and show that the cellular defects in these individuals' cells are complemented by wildtype SLX4, demonstrating that biallelic mutations in! SLX4 (renamed here as FANCP) cause a new subtype of Fanconi anemia, Fanconi anemia-P. View full text Figures at a glance * Figure 1: Characterization of cell lines from individuals with Fanconi anemia with SLX4 mutations. () Protein blot analysis with a FANCD2 antibody of U2OS cells transfected with the indicated siRNAs and treated with 1 μM MMC for 24 h. L (long) indicates a monoubiquitinated form and S (short) indicates the non-monoubiquitinated form of FANCD2. () RT-quantitative PCR in U2OS cells transfected with various siRNAs against SLX4 used in the experiment shown in . Error bars indicate the standard deviation (s.d.) of three replicates. () Protein blot analysis with a FANCD2 antibody of BJ, RA3083 and RA3331 fibroblasts. Cells were left untreated or were treated with 1 μM MMC for 24 h. () Pedigrees of the two families described in this study showing accession numbers for cell lines (RA) and peripheral blood samples (B, RB). The two probands are indicated with filled symbols. Mutation carriers are indicated by half-filled symbols. () Examples of metaphases of the LCL RA3042 (no drug treatment) and fibroblast RA3083 cell lines from individual 1084/1 and the fibroblasts RA3331 from i! ndividual 414/1 (treatment with diepoxybutane (DEB)). * Figure 2: SLX4 is defective in two individuals with Fanconi anemia. () Schematic of SLX4 (based on ref. 7) showing the domain architecture, the interacting proteins and the predicted protein effect of SLX4 mutations in IFAR1084/1 and IFAR414/1 individuals. () Analysis of the mutant SLX4 protein in the cell lines. We subjected cell extracts of primary BJ, RA3083 and RA3331 fibroblasts to immunoprecipitation using a control rabbit antibody (control IgG) or the SLX4 antibody. Asterisks indicate the crossreacting bands. Note that the antibody does not identify SLX4 in straight protein blotting (lanes 7 to 9). WT, wildtype. * Figure 3: Complementation of RA3083 and RA3331 cells with the SLX4 cDNA. () Complementation of MMC sensitivity. We exposed fibroblasts stably transduced with empty vector (control) or the vector expressing wildtype SLX4 or the mutant SLX4 cDNAs to different levels of MMC ranging from 0–100 nM. After 8 days, the cell number was determined using a coulter counter. Total cell numbers at each dose were divided by the number of cells in the untreated sample to arrive at percent survival. Error bars indicate s.d. () Complementation of the cell cycle defect after MMC treatment. Indicated cells were treated with 100 nM MMC, and the cell cycle was analyzed 48 h later. Untreated samples were analyzed in parallel. Expression levels of the exogenous proteins are shown in Supplementary Figure 4a–c. Quantification of the data is shown in Supplementary Figure 4d,e. WT, wildtype. * Figure 4: Interaction of mutant forms of SLX4 with its partners and with ubiquitin. () Analysis of SLX4-interacting partners in SLX4 mutant cells. We subjected cell extracts of primary fibroblasts (BJ, RA3083 and RA3331) to immunoprecipitation using the SLX4 antibody. We identified interacting proteins by immunoblotting with the indicated antibodies. () Analysis of SLX4-interacting partners in RA3331 cells. We subjected cell extracts of RA3331 E6E7 cells expressing HA-tagged control vector, wild-type SLX4 or the p.Leu672ValfsX119 SLX4 alteration to immunoprecipitation using HA antibody or HA antibody in the presence of 30 μg of HA peptide. We identified interacting proteins by immunoblotting with the indicated antibodies. () Interaction of the UBZ domains with ubiquitin. We incubated GST-purified GST control, wild-type UBZ domains (SLX4 amino acids 251–402) and UBZ domains with four cysteines mutated to alanines (SLX4 amino acids 251–402 p.Cys296Ala, p.Cys299Ala, p.Cys336Ala and p.Cys339Ala) with the indicated forms of ubiquitin, purified by binding to! GST beads, separated on a PAGE gel and immunoblotted with ubiquitin antibody. The bottom panel shows Ponceau staining of the GST proteins. WT, wild type; MUT, mutated. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Entrez Nucleotide * NM_032444.2 Author information * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Yonghwan Kim & * Francis P Lach Affiliations * Laboratory of Genome Maintenance, The Rockefeller University, New York, New York, USA. * Yonghwan Kim, * Francis P Lach, * Rohini Desetty & * Agata Smogorzewska * Division of Pediatric Hematology/Oncology, Herman B. Wells Center for Pediatric Research, Riley Hospital for Children, Indiana University School of Medicine, Indianapolis, Indiana, USA. * Helmut Hanenberg * Department of Otorhinolaryngology, Heinrich Heine University, Duesseldorf, Germany. * Helmut Hanenberg * Human Genetics and Hematology, The Rockefeller University, New York, New York, USA. * Arleen D Auerbach Contributions The study was designed by A.S., Y.K. and F.P.L. Subject recruitment and sample collection was done by A.D.A., F.P.L. and A.S. Characterization with respect to Fanconi anemia subgroups was performed by A.S., F.P.L., H.H. and A.D.A. Mutation analysis and functional studies were performed by A.S., Y.K., F.P.L. and R.D. The manuscript was written by A.S. with help from other authors. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Agata Smogorzewska Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–5 and Supplementary Tables 1–3 Additional data
• Disruption of mouse Slx4, a regulator of structure-specific nucleases, phenocopies Fanconi anemia
  - Nat Genet 43(2):147-152 (2011)
  Nature Genetics | Letter Disruption of mouse Slx4, a regulator of structure-specific nucleases, phenocopies Fanconi anemia * Gerry P Crossan1 Search for this author in: * NPG journals * PubMed * Google Scholar * Louise van der Weyden2 Search for this author in: * NPG journals * PubMed * Google Scholar * Ivan V Rosado1 Search for this author in: * NPG journals * PubMed * Google Scholar * Frederic Langevin1 Search for this author in: * NPG journals * PubMed * Google Scholar * Pierre-Henri L Gaillard3 Search for this author in: * NPG journals * PubMed * Google Scholar * Rebecca E McIntyre2 Search for this author in: * NPG journals * PubMed * Google Scholar * Sanger Mouse Genetics Project2 * Ferdia Gallagher4 Search for this author in: * NPG journals * PubMed * Google Scholar * Mikko I Kettunen4 Search for this author in: * NPG journals * PubMed * Google Scholar * David Y Lewis4 Search for this author in: * NPG journals * PubMed * Google Scholar * Kevin Brindle4 Search for this author in: * NPG journals * PubMed * Google Scholar * Mark J Arends5 Search for this author in: * NPG journals * PubMed * Google Scholar * David J Adams2 Search for this author in: * NPG journals * PubMed * Google Scholar * Ketan J Patel1, 6 Contact Ketan J Patel Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:147–152Year published:(2011)DOI:doi:10.1038/ng.752Received21 June 2010Accepted15 December 2010Published online16 January 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The evolutionarily conserved SLX4 protein, a key regulator of nucleases, is critical for DNA damage response. SLX4 nuclease complexes mediate repair during replication and can also resolve Holliday junctions formed during homologous recombination. Here we describe the phenotype of the Btbd12 knockout mouse, the mouse ortholog of SLX4, which recapitulates many key features of the human genetic illness Fanconi anemia. Btbd12-deficient animals are born at sub-Mendelian ratios, have greatly reduced fertility, are developmentally compromised and are prone to blood cytopenias. Btbd12−/− cells prematurely senesce, spontaneously accumulate damaged chromosomes and are particularly sensitive to DNA crosslinking agents. Genetic complementation reveals a crucial requirement for Btbd12 (also known as Slx4) to interact with the structure-specific endonuclease Xpf-Ercc1 to promote crosslink repair. The Btbd12 knockout mouse therefore establishes a disease model for Fanconi anemia and g! enetically links a regulator of nuclease incision complexes to the Fanconi anemia DNA crosslink repair pathway. View full text Figures at a glance * Figure 1: Btbd12 deficiency results in growth retardation and compromised fertility. () A representative image of Btbd12+/+ and Btbd12−/− littermates at 7 weeks, revealing obvious growth retardation. () Weights of male and female Btbd12+/+, Btbd12+/− and Btbd12−/− animals at 12 weeks, confirming growth retardation of Btbd12−/− mice. n = 10 for each genotype, the central line represents the median, the box represents the interquartile range and the whiskers represent the 90th centiles. ***P < 0.001, **P < 0.01. () Microscopic analysis of hematoxylin and eosin (H&E)-stained sections of ovary (×400 magnification), testis (×50 magnification) and epididymis (×400 magnification) from Btbd12+/+, Btbd12−/− and Fanca−/− animals at 16 weeks. This revealed absence of oocyte maturation in Btbd12−/− females and a similar pattern of impaired spermatogenesis in testis of Btbd12−/− and Fanca−/− mice, with absence of spermatozoa from the epididymis. * Figure 2: Some Btbd12−/− mice died prematurely and displayed brain and eye developmental defects. () The Kaplan-Meier survival curve for cohorts of Btbd12+/+, Btbd12+/− and Btbd12−/− mice (n = 28 per genotype, P = 0.011); a sharp drop in survival is evident in the Btbd12−/− colony occurring within the first 3 months of life. () An increased prevalence of hydrocephalus was observed among the cohort of Btbd12−/− mice. **P = 0.006, Fisher's exact test (Btbd12+/+, n = 3 mice with hydrocephalus out of a total of 72; Btbd12+/−, n = 13 mice out of a total of 163; and Btbd12−/−, n = 10 mice out of a total of 48). () High-resolution X-ray computed tomography of a representative Btbd12−/− mouse compared with a Btbd12+/+ littermate control; an obvious skull deformity is apparent in the Btbd12−/− mouse. () H&E-stained sectioned hydrocephalic brain from a Btbd12−/− mouse showing dilatation of the lateral ventricles (1) and rupture of the third ventricle (3). () High-resolution MRI of a Btbd12+/+ mouse compared with a hydrocephalic Btbd12−/− mouse. ! The image shows a large hydrocephalus (*), and the arrow points to disrupted brainstem structure. () An increased prevalence of a spectrum of eye abnormalities was observed in Btbd12−/− mice. ***P = 0.0008, Fisher's exact test (Btbd12+/+, n = 2 mice with eye abnormalities out of a total of 71; Btbd12+/−, n = 0 mice out of 163; and Btbd12−/−, n = 11 mice out of 48). () High-resolution MRI of a representative Btbd12−/− mouse compared with a wild-type littermate showing unilateral anophthalmia. () Slit-lamp images revealing the spectrum of ocular abnormalities observed in the cohort of Btbd12−/− mice. These abnormalities range from corneal opacity (left), to microphthalmia (center) and, finally, anophthalmia (right). * Figure 3: A proportion of Btbd12−/− mice developed blood cytopenias associated with genomic instability. (–) Full blood count analysis of 4–12-week-old Btbd12−/− mice with wild-type littermates (n = 22 for each group). () Peripheral blood erythrocyte concentration. ns, not significant; P = 0.0617. () Peripheral white cell concentration. *P = 0.0155. Note a sub-population of markedly leukopenic animals. () Peripheral thrombocyte concentration. **P = 0.0027. Note a sub-population of severely thrombocytopenic animals. In –, the central line represents the mean and the error bars represent the s.e.m. () Proficiency of Btbd12+/+ and Btbd12−/− bone marrow progenitor cells to form myeloid colony-forming units (CFU) from 2 × 104 nucleated bone marrow cells. Data obtained is the average of results from three individual mice. ***P < 0.0001. The bar represents the mean of three independent experiments and the error bars are the s.e.m. () We assessed lymphoid lineage through the ability of bone marrow cells to form pre–B-cell CFU per 5 × 104 bone marrow cells (average of ! three independent mice). *P = 0.017. The bar represents the mean of three independent experiments and the error bars are the s.e.m. () Flow cytometric analysis revealing the frequency of micronucleated normochromic erythrocytes (Mn-NCE) in peripheral blood of unchallenged 16-week-old Btbd12+/+ and Btbd12−/− mice (n = 12 per genotype). ***P < 0.0001. The central line represents the mean and the error bars are the s.e.m. Micronuclei are a marker for genomic instability. * Figure 4: Btbd12-deficient cells undergo premature replicative senescence, exhibiting spontaneous and inducible chromosomal instability. () Primary MEFs obtained from Btbd12+/+, Btbd12+/− and Btbd12−/− embryos were grown in culture under normoxic conditions and monitored for population doubling. The Btbd12−/− MEF lines prematurely cease growing. () Metaphases from early passage (P3) MEFs were prepared and individually imaged. Each metaphase was then scored blind for the presence of chromosome abnormalities revealing an increased number of aberrations per metaphase () (*P = 0.0268, t-test; the bar represents the mean and the error bars are the s.e.m.) and an increased frequency of abnormal metaphases (). (**P = 0.0092, Fisher's exact test). () Image of a single Btbd12−/− metaphase spread revealing chromosome aberrations similar to those seen in Fanconi anemia cells (black arrows, radial structures; red arrows, chromatid break). () We exposed cells to MMC and scored metaphases from these cells for chromosome aberrations. MMC exposure leads to chromosomal instability in Btbd12−/−- and Fanca−/! −-transformed MEFs. *P < 0.05, ***P < 0.0001, t-test. The central line represents the mean, and the error bars are the s.e.m. * Figure 5: Btbd12-deficient MEFs are hypersensitive to DNA interstrand crosslinking agents. (–) Two independent Btbd12−/−-transformed MEF lines were compared with congenic wild-type–transformed MEFs for cellular sensitivity to a range of mutagens by MTS cell viability assay. Btbd12−/− MEFs were extremely sensitive to mitomycin C (MMC) () and cisplatinum (), whereas they were not hypersensitive to ultraviolet irradiation (), methyl methanesulfonate (MMS) () or γ irradiation (). Btbd12−/− MEFs were mildly sensitive to camptothecin (CPT) (). The cellular sensitivities of Btbd12−/−, Ercc1−/−, Fanca−/− and Fancc−/− MEFs were compared next to each other to the DNA crosslinking agent MMC () and ultraviolet irradiation (). Each point represents the mean of three independent experiments, each carried out in triplicate, and the error bars represent the s.e.m. * Figure 6: The interaction between Slx4 and Xpf-Ercc1 is required for crosslink repair. () Cartoon representation of the Slx4 polypeptide, domain boundaries and interaction sites for the relevant SSEs (Xpf-Ercc1, Mus81-Eme1 and Slx1). Two deletion constructs that were predicted to disrupt the interaction with Slx1 (Slx4ΔSlx1) or the interaction with Xpf-Ercc1 (Slx4ΔErcc1) are described. () Anti-FLAG protein blot showing the expression of FLAG-Slx4 and the truncations FLAG-Slx4ΔSlx1 and FLAG-Slx4ΔErcc1 in transfected Btbd12−/− tMEFs. After FLAG immunoprecipitation, eluates were protein blotted for Ercc1; the full-length and FLAG-Slx4ΔSlx1 constructs retained interaction with this SSE subcomponent, whereas FLAG-Slx4 Ercc1 abolished this interaction. The IP was also blotted for Mus81, showing that all truncations interact with Mus81. () MTS cell survival of Btbd12−/−, Btbd12−/− + Slx4ΔErcc1 and Btbd12−/− + Slx4ΔSlx1 strains in response to MMC. Each point represents the mean of three independent experiments carried out in triplicate and error! bars represent the s.e.m. () Upper panel: sub-cellular fractionation followed by protein blot for Ercc1 in cellular fractions without DNA damage (cyt, cytoplasmic; nuc, nuclear; chr, chromatin). A reduction of Ercc1 in the chromatin fraction is seen in the Btbd12−/− cell line without DNA damage. Lower panel: protein blot analysis of Ercc1 in the chromatin fractions of Btbd12−/− and Btbd12+/+ tMEFs exposed to MMC (u, untreated; 4, 4 hours; 8, 8 hours). The accumulation of Ercc1 on chromatin is reduced after MMC treatment in Btbd12−/− cells. Author information * Author information * Supplementary information Affiliations * Medical Research Council, Laboratory of Molecular Biology, Cambridge, UK. * Gerry P Crossan, * Ivan V Rosado, * Frederic Langevin & * Ketan J Patel * Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK. * Sanger Mouse Genetics Project, * Louise van der Weyden, * Rebecca E McIntyre & * David J Adams * Genome Instability and Carcinogenesis UPR3081 Centre National de la Recherche Scientifique (CNRS), Conventionné par l'Université d'Aix-Marseille 2, Marseille, France. * Pierre-Henri L Gaillard * Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK. * Ferdia Gallagher, * Mikko I Kettunen, * David Y Lewis & * Kevin Brindle * Department of Pathology, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK. * Mark J Arends * Department of Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK. * Ketan J Patel Consortia * Sanger Mouse Genetics Project Contributions K.J.P. and G.P.C. designed the study, the experiments and wrote the paper. G.P.C. performed the majority of the experiments presented. D.J.A. helped in the design of the experiments. M.J.A. analyzed histological samples and provided useful discussion. L.v.d.W. managed the colony and weighed and performed necropsies on mice at Wellcome Trust Sanger Institute. I.V.R. analyzed Fanconi pathway activation. F.L. assisted in analysis of developmental abnormalities. P.-H.L.G. helped in the design of some experiments. R.E.M. performed the micronucleus assay. S.M.G.P. performed the mouse phenotype pipeline analysis. F.G., M.I.K., D.Y.L. and K.B. performed imaging studies. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Ketan J Patel Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (520K) Supplementary Figures 1–12 and Supplementary Tables 1–4. Additional data
• Drosophila Piwi functions in Hsp90-mediated suppression of phenotypic variation
  - Nat Genet 43(2):153-158 (2011)
  Nature Genetics | Letter Drosophila Piwi functions in Hsp90-mediated suppression of phenotypic variation * Vamsi K Gangaraju1 Search for this author in: * NPG journals * PubMed * Google Scholar * Hang Yin2 Search for this author in: * NPG journals * PubMed * Google Scholar * Molly M Weiner1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jianquan Wang1 Search for this author in: * NPG journals * PubMed * Google Scholar * Xiao A Huang1 Search for this author in: * NPG journals * PubMed * Google Scholar * Haifan Lin1 Contact Haifan Lin Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:153–158Year published:(2011)DOI:doi:10.1038/ng.743Received21 September 2010Accepted22 November 2010Published online26 December 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Canalization, also known as developmental robustness, describes an organism's ability to produce the same phenotype despite genotypic variations and environmental influences1, 2. In Drosophila, Hsp90, the trithorax-group proteins and transposon silencing have been previously implicated in canalization3, 4. Despite this, the molecular mechanism underlying canalization remains elusive. Here using a Drosophila eye-outgrowth assay sensitized by the dominant Krirregular facets-1(KrIf-1) allele3, we show that the Piwi-interacting RNA (piRNA) pathway, but not the short interfering RNA or micro RNA pathway, is involved in canalization. Furthermore, we isolated a protein complex composed of Hsp90, Piwi and Hop, the Hsp70/Hsp90 organizing protein homolog, and we demonstrated the function of this complex in canalization. Our data indicate that Hsp90 and Hop regulate the piRNA pathway through Piwi to mediate canalization. Moreover, they point to epigenetic silencing of the expression of! existing genetic variants and the suppression of transposon-induced new genetic variation as two major mechanisms underlying piRNA pathway-mediated canalization. View full text Figures at a glance * Figure 1: Maternal Piwi is an enhancer of ectopic outgrowth phenotype. () Genetic cross to check if Piwi is an enhancer of the eye outgrowth phenotype caused by ectopic expression of Kr, where CyO or CyO-GFP balancer chromosomes carries a piwi+ allele. Reverse crosses with piwi1 and piwi2 males are not shown here. () Light microscopic images of the adult fly eyes with various types of ectopic outgrowths (black arrows). Images of the eyes of control flies with wildtype levels of Piwi are shown in the upper panel. () Overexpression of maternal Piwi suppresses eye outgrowths when Hsp90 is inhibited. From each cross, 50 flies with KrIf-1/KrIf-1 background were collected and scored for the phenotype. Each experiment was repeated five times with five independent crosses. The average of five independent crosses with the standard deviation (s.d.) are plotted. We performed an unpaired t test to calculate statistical significance. *P = 0.0254. () Genetic linkage between Piwi and Hsp90 in mediating canalization. * Figure 2: Biochemical isolation of Hop as an interactor of Piwi. () Fractionation scheme for identifying peptides interacting with Piwi. () We resolved fraction #27 obtained from Superdex 200 chromatography on a 7.5% SDS polyacrylamide gel and stained it with silver stain. We obtained the identities of individual bands by excising bands from a colloidal coomassie blue stained gel (not shown here), followed by mass spectrometry. Peptides identified but not relevant to this study are marked by asterisks. () Protein blotting analysis showing the co-migration of Piwi and Hop in the Superdex 200 column. Fraction numbers are marked above and the fraction corresponding to ~150 kDa is marked below. () Coimmunoprecipitation of Piwi and Hsp90 with Hop. Control reactions (-IP) did not contain Hop-specific antibody. () Coimmunoprecipitation of Piwi with Hsp90. Control reactions (-IP) did not contain Hsp90-specific antibody. () Piwi, Hop and Hsp90 function in the same complex. Left panel shows the scheme of the serial immunoprecipitation experiment. R! ight panel shows the protein blotting analysis of Piwi, Hop and Hsp90 after the first and second immunoprecipitations. Control reactions (-Myc IP and –HA IP) contained protein A/G plus agarose beads. * Figure 3: Hop is a maternal enhancer of the eye outgrowth phenotype. () The genetic cross to test if Hop is a maternal enhancer of the outgrowths. Reverse cross with Hopk00616 males is not shown here. () KrIf-1/Hopk00616 fly eyes exhibiting the outgrowths (arrows). () Quantification of the outgrowths observed in KrIf-1/Hopk00616 flies. Four hundred seventy-nine flies were collected from three independent crosses and scored for the outgrowths. Average percentage of flies with the outgrowths and s.d are plotted. The error bar indicates s.d. * Figure 4: Germline transmission of Piwi- and Hop-induced mutations. () Genetic crosses for the Hopk00616 selection experiment. A similar cross was setup with piwi1. Hopk00616 and piwi1 mutations are present only in the F1 KrIf-1 flies. A single male F1 fly with outgrowth was crossed with virgin wildtype Canton S female flies to remove Hopk00616 and piwi1 mutations. From the F4 generation, KrIf-1/KrIf-1 males and females containing the outgrowths were selected and intercrossed. () Quantification of flies with the outgrowths in each generation. One hundred flies per generation were scored, and counts of male and female flies with the outgrowths are individually plotted. () Overexpression of wg is 'fixed' over multiple generations. Kr and wg mRNA expression in the heads of five F8 males and five F8 females with eye outgrowths were quantified by quantitative PCR, with the same number of F8 flies without the eye outgrowths as in the controls. The average values of three independent experiments and the s.d. are plotted. Statistical significance wa! s calculated using a paired t test, with P values that are less than 0.05 and 0.001 indicated by * and **, respectively. * Figure 5: Hsp90-dependent phosphorylation of Piwi. () Hsp90 inactivation by geldanamycin does not change Piwi protein levels. Two-fold serial dilutions of total ovary lysate were used for protein blotting using antibodies as indicated. Human B-Raf antibody was used to detect Drosophila Pole Hole protein. Non-specific detection of an abundant protein by B-Raf antibody was used as loading control. () Piwi levels did not change in ovary lysates from either Hsp8308445/TM3 or Hsp8308445/Hsp8308445 flies. Coomassie staining of the most abundant protein (~60 kDa) in the ovary lysate was used as loading control. () Protein blot analysis of 2D SDS PAGE gel electrophoresis using Piwi antibody. Different isoforms of Piwi are marked from '1' through '4', with '1' being the most positive isoform. White arrowhead represents the isoform enriched in the presence of geldanamycin. Black arrow (compare with dashed arrow) and black arrowhead represent isoforms that are either depleted or enriched in Hsp8308445/Hsp8308445 mutants, respectively. ! The black circle marks two isoforms that get depleted upon calf intestinal phosphatase (CIP) treatment (dashed circle). () Immunoprecipitation of Piwi with phospho-serine, phospho-threonine and phospho-tyrosine antibodies from wildtype ovary lysate. IgG(H) were used to monitor loading in each lane. Darker exposure of the upper panel is included to show that absence of Piwi in phospho-threonine immunoprecipitation is not due to less loading. () CIP treatment of Piwi depletes it from phospho-serine and phospho-tyrosine immunoprecipitations. () Immunoprecipitation of Piwi with phospho-serine and phospho-tyrosine antibodies from either wildtype or Hsp8308445/Hsp8308445 ovary lysate. () Model, see text. * Figure 6: A schematic illustration for the role of the Hsp90-Hop-Piwi complex in canalization. See text for details. Author information * Author information * Supplementary information Affiliations * Yale Stem Cell Center and Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut, USA. * Vamsi K Gangaraju, * Molly M Weiner, * Jianquan Wang, * Xiao A Huang & * Haifan Lin * Present address: Regenerative Medicine Program, Sprott Centre for Stem Cell Research, Ottawa, Ontario, Canada. * Hang Yin Contributions V.K.G. and H.L. designed the project and wrote the paper. H.Y. made the initial observation that piwi mutations affect canalization. M.M.W. showed that Hop mutations enhance eye outgrowth phenotype. J.W. performed two-dimensional gel electrophoresis and X.A.H. assisted with column chromatography. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Haifan Lin Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (7M) Supplementary Figures 1–4 and Supplementary Table 1 Additional data
• Genome-wide association study of leaf architecture in the maize nested association mapping population
  - Nat Genet 43(2):159-162 (2011)
  Nature Genetics | Letter Genome-wide association study of leaf architecture in the maize nested association mapping population * Feng Tian1, 11 Search for this author in: * NPG journals * PubMed * Google Scholar * Peter J Bradbury2, 11 Search for this author in: * NPG journals * PubMed * Google Scholar * Patrick J Brown1, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Hsiaoyi Hung4 Search for this author in: * NPG journals * PubMed * Google Scholar * Qi Sun5 Search for this author in: * NPG journals * PubMed * Google Scholar * Sherry Flint-Garcia6, 7 Search for this author in: * NPG journals * PubMed * Google Scholar * Torbert R Rocheford3, 8 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael D McMullen6, 7 Search for this author in: * NPG journals * PubMed * Google Scholar * James B Holland4, 9 Search for this author in: * NPG journals * PubMed * Google Scholar * Edward S Buckler1, 2, 10 Contact Edward S Buckler Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:159–162Year published:(2011)DOI:doi:10.1038/ng.746Received02 June 2010Accepted15 December 2010Published online09 January 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg US maize yield has increased eight-fold in the past 80 years, with half of the gain attributed to selection by breeders. During this time, changes in maize leaf angle and size have altered plant architecture, allowing more efficient light capture as planting density has increased. Through a genome-wide association study (GWAS) of the maize nested association mapping panel, we determined the genetic basis of important leaf architecture traits and identified some of the key genes. Overall, we demonstrate that the genetic architecture of the leaf traits is dominated by small effects, with little epistasis, environmental interaction or pleiotropy. In particular, GWAS results show that variations at the liguleless genes have contributed to more upright leaves. These results demonstrate that the use of GWAS with specially designed mapping populations is effective in uncovering the basis of key agronomic traits. View full text Figures at a glance * Figure 1: Low genetic overlap between leaf traits. The correlations of allelic effect estimates across founders for each pair of traits at colocalized QTLs were used to test the genetic overlap between different traits. Number in red, number of shared QTLs between traits. Number in blue, phenotypic correlation in r2 between traits. * Figure 2: Summary of NAM-GWAS results for three leaf architecture traits. * Figure 3: Associations around lg1 and lg2 explained the two most significant QTLs for upper leaf angle. () Overview of GWAS results for upper leaf angle. Red dotted lines, joint linkage QTL peaks; scale, −log10 of P value of QTLs. Triangles, associations identified by GWAS; scale, BPP. Four liguleless genes are indicated based on their physical position. Bottom, recombination rate along the chromosome. () Associations identified by GWAS at the lg1 locus. chr2, chromosome 2. () Associations identified by GWAS at the lg2 locus. Arrows pointing right and left, annotated genes on the positive- and negative-sense strands of DNA. chr3, chromosome 3. * Figure 4: Comparison of allele frequency distributions of QTLs, associated SNPs and random SNPs. For comparison, a random SNP allele frequency distribution was produced by sampling 1.6 million HapMap SNPs. Both the allele frequency distributions of QTL and GWAS QTN differ from the random SNP allele frequency distribution. Notably, the associated SNPs show lower allele frequencies than QTL. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Feng Tian & * Peter J Bradbury Affiliations * Institute for Genomic Diversity, Cornell University, Ithaca, New York, USA. * Feng Tian, * Patrick J Brown & * Edward S Buckler * US Department of Agriculture–Agricultural Research Service (USDA-ARS), Ithaca, New York, USA. * Peter J Bradbury & * Edward S Buckler * Department of Crop Sciences, University of Illinois, Urbana, Illinois, USA. * Patrick J Brown & * Torbert R Rocheford * Department of Crop Science, North Carolina State University, Raleigh, North Carolina, USA. * Hsiaoyi Hung & * James B Holland * Computational Biology Service Unit, Cornell University, Ithaca, New York, USA. * Qi Sun * USDA-ARS, Columbia, Missouri, USA. * Sherry Flint-Garcia & * Michael D McMullen * Division of Plant Sciences, University of Missouri, Columbia, Missouri, USA. * Sherry Flint-Garcia & * Michael D McMullen * Department of Agronomy, Purdue University, Urbana, Illinois, USA. * Torbert R Rocheford * USDA-ARS, Raleigh, North Carolina, USA. * James B Holland * Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, USA. * Edward S Buckler Contributions F.T. and P.J. Bradbury contributed equally to this work. M.D.M., J.B.H. and E.S.B. contributed to the study design. S.F.-G., T.R.R., M.D.M., J.B.H. and E.S.B. collected phenotypes. F.T., P.J. Bradbury, P.J. Brown, H.H., Q.S. and E.S.B. carried out analysis. F.T., P.J. Bradbury and E.S.B. wrote the paper. All authors discussed the results and commented on the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Edward S Buckler Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Note, Supplementary Figures 1–7 and Supplementary Tables 1–14 Additional data
• Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population
  - Nat Genet 43(2):163-168 (2011)
  Nature Genetics | Letter Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population * Kristen L Kump1 Search for this author in: * NPG journals * PubMed * Google Scholar * Peter J Bradbury2, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Randall J Wisser4 Search for this author in: * NPG journals * PubMed * Google Scholar * Edward S Buckler2, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Araby R Belcher5 Search for this author in: * NPG journals * PubMed * Google Scholar * Marco A Oropeza-Rosas1 Search for this author in: * NPG journals * PubMed * Google Scholar * John C Zwonitzer5 Search for this author in: * NPG journals * PubMed * Google Scholar * Stephen Kresovich3 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael D McMullen6 Search for this author in: * NPG journals * PubMed * Google Scholar * Doreen Ware3 Search for this author in: * NPG journals * PubMed * Google Scholar * Peter J Balint-Kurti5, 7 Search for this author in: * NPG journals * PubMed * Google Scholar * James B Holland1, 7 Contact James B Holland Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:163–168Year published:(2011)DOI:doi:10.1038/ng.747Received09 July 2010Accepted15 December 2010Published online09 January 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Nested association mapping (NAM) offers power to resolve complex, quantitative traits to their causal loci. The maize NAM population, consisting of 5,000 recombinant inbred lines (RILs) from 25 families representing the global diversity of maize, was evaluated for resistance to southern leaf blight (SLB) disease. Joint-linkage analysis identified 32 quantitative trait loci (QTLs) with predominantly small, additive effects on SLB resistance. Genome-wide association tests of maize HapMap SNPs were conducted by imputing founder SNP genotypes onto the NAM RILs. SNPs both within and outside of QTL intervals were associated with variation for SLB resistance. Many of these SNPs were within or near sequences homologous to genes previously shown to be involved in plant disease resistance. Limited linkage disequilibrium was observed around some SNPs associated with SLB resistance, indicating that the maize NAM population enables high-resolution mapping of some genome regions. View full text Figures at a glance * Figure 1: Parental and RIL family mean values ± s.e.m. of SLB index scores. Black bars, parental SLB best linear unbiased predictor (BLUP) index value; Gray bars, average index value for all RILs derived from the cross of B73 and that parent. * Figure 2: Genetic map of NAM population with support intervals of 32 QTLs and positions of 51 HapMap SNPs retained in final model for SLB resistance. Ten chromosomes of maize genome are shown. Detailed information on these 51 SNPs is in Table 1. * Figure 3: Heat map of additive effect estimates of 25 founder inbred alleles at QTLs for SLB resistance relative to B73 on the nine-point SLB index scale. QTLs are indicated by their chromosome and bin numbers (rows) and the allelic effect estimates for each founder allele (columns) are coded by color according to 0.05 score increments (see legend). Squares surrounded by bold lines, allelic effects significantly different from zero at 5% false discovery rate. * Figure 4: Results of GWA subsampling analysis. All SNPs detected as significant in at least one subsample are triangles relative to their physical sequence position. Red upward triangles, SNPs at which the diverse parent allele increases SLB resistance relative to the reference B73 allele. Blue downward triangles, SNPs at which the diverse parent allele decreases SLB resistance relative to the reference B73 allele. Vertical positions of triangles represent bootstrap posterior probability (BPP) of the SNP. SLB QTLs, green circles whose vertical positions represent their F-test log(1/P) in the final joint linkage QTL model. Horizontal green bars, QTL support intervals. * Figure 5: Linkage disequilibrium. (,) LD (r2) between significant SNPs on chromosome 7 (), physical position 127 Mb, and chromosome 1 (), physical position 191 Mb, and all other SNPs on the same chromosome. Position of the significant SNP to which all others are compared, dashed vertical line (this SNP has r2 = 1.0 with itself on the line). Red circles, observed r2 values in the 25 NAM founders. Black circles, expected r2 values in the NAM RILs. Shaded vertical bars, all QTL support intervals on a chromosome. Top, LD across an entire chromosome. Bottom, LD across an entire QTL support interval (if the significant SNP is inside of a QTL support interval) or a length of chromosome representing 5 cM of genetic distance to either side of the significant SNP (if the SNP is outside of a QTL support interval). Discrete bands of founder LD in result from the high allele frequency of this SNP (it segregates in 23 of 25 NAM families) and the limited sample size of 25 founders. Author information * Author information * Supplementary information Affiliations * Department of Crop Science, North Carolina State University, Raleigh, North Carolina, USA. * Kristen L Kump, * Marco A Oropeza-Rosas & * James B Holland * US Department of Agriculture–Agricultural Research Service (USDA-ARS) and Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, USA. * Peter J Bradbury & * Edward S Buckler * Institute for Genomic Diversity, Cornell University, Ithaca, New York, USA. * Peter J Bradbury, * Edward S Buckler, * Stephen Kresovich & * Doreen Ware * Department of Plant and Soil Sciences, University of Delaware, Newark, Delaware, USA. * Randall J Wisser * Department of Plant Pathology, North Carolina State University, Raleigh, North Carolina, USA. * Araby R Belcher, * John C Zwonitzer & * Peter J Balint-Kurti * USDA-ARS and Division of Plant Sciences, University of Missouri, Columbia, Missouri, USA. * Michael D McMullen * USDA-ARS, Raleigh, North Carolina, USA. * Peter J Balint-Kurti & * James B Holland Contributions E.S.B., M.D.M., S.K. and J.B.H. developed the NAM population. K.L.K., R.J.W., A.R.B., M.A.O.-R., J.C.Z., P.J.B.-K. and J.B.H. conducted the field experiments. E.S.B. and D.W. created HapMap data. P.J.B. and E.S.B. developed GWAS methods and software. K.L.K. and J.B.H. analyzed the data. K.L.K., R.J.W., P.J.B.-K. and J.B.H. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * James B Holland Supplementary information * Author information * Supplementary information Excel files * Supplementary Table 7 (140K) Information on 245 significantly associated SNPs. PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–9, Supplementary Tables 1–9 and Supplementary Note Additional data
• INTERMEDIUM-C, a modifier of lateral spikelet fertility in barley, is an ortholog of the maize domestication gene TEOSINTE BRANCHED 1
  - Nat Genet 43(2):169-172 (2011)
  Nature Genetics | Letter INTERMEDIUM-C, a modifier of lateral spikelet fertility in barley, is an ortholog of the maize domestication gene TEOSINTE BRANCHED 1 * Luke Ramsay1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jordi Comadran1 Search for this author in: * NPG journals * PubMed * Google Scholar * Arnis Druka1 Search for this author in: * NPG journals * PubMed * Google Scholar * David F Marshall1 Search for this author in: * NPG journals * PubMed * Google Scholar * William T B Thomas1 Search for this author in: * NPG journals * PubMed * Google Scholar * Malcolm Macaulay1 Search for this author in: * NPG journals * PubMed * Google Scholar * Katrin MacKenzie2 Search for this author in: * NPG journals * PubMed * Google Scholar * Craig Simpson1 Search for this author in: * NPG journals * PubMed * Google Scholar * John Fuller1 Search for this author in: * NPG journals * PubMed * Google Scholar * Nicola Bonar1 Search for this author in: * NPG journals * PubMed * Google Scholar * Patrick M Hayes3 Search for this author in: * NPG journals * PubMed * Google Scholar * Udda Lundqvist4 Search for this author in: * NPG journals * PubMed * Google Scholar * Jerome D Franckowiak5 Search for this author in: * NPG journals * PubMed * Google Scholar * Timothy J Close6 Search for this author in: * NPG journals * PubMed * Google Scholar * Gary J Muehlbauer7 Search for this author in: * NPG journals * PubMed * Google Scholar * Robbie Waugh1 Contact Robbie Waugh Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume: 43,Pages:169–172Year published:(2011)DOI:doi:10.1038/ng.745Received21 May 2010Accepted10 December 2010Published online09 January 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The domestication of cereals has involved common changes in morphological features, such as seed size, seed retention and modification of vegetative and inflorescence architecture that ultimately contributed to an increase in harvested yield1. In barley, this process has resulted in two different cultivated types, two-rowed and six-rowed forms, both derived from the wild two-rowed ancestor, with archaeo-botanical evidence indicating the origin of six-rowed barley early in the domestication of the species, some 8,600–8,000 years ago2. Variation at SIX-ROWED SPIKE 1 (VRS1) is sufficient to control this phenotype. However, phenotypes imposed by VRS1 alleles are modified by alleles at the INTERMEDIUM-C (INT-C) locus. Here we show that INT-C is an ortholog of the maize domestication gene TEOSINTE BRANCHED 1 (TB1) and identify 17 coding mutations in barley TB1 correlated with lateral spikelet fertility phenotypes. View full text Figures at a glance * Figure 1: The inflorescence and tillering phenotypes of alleles of INTERMEDIUM-C. () Photographs of mature, dried barley inflorescences (lateral view) of the two-rowed cv Bowman (int-c.b) at left, its Intermedium NIL BW421 (int-c.5) in the middle, and the six-rowed cv Morex at right, showing the lateral grain phenotypes that result from differential lateral floret development. () Schematic representation of the structure of spikelets (floret and two outer glumes) from the inflorescences shown in (). Central spikelets are colored green (central floret, light green; central outer glumes, dark green) and lateral spikelets are colored orange (lateral floret) and yellow (lateral outer glumes). Lateral (right) and abaxial (left) views are shown for each genotype. () Photographs of three plants of Bowman (int-c.b) on the left and three plants of BW421 (int-c.5) on the right showing increased tillering in BW421 at growth stage GS24–GS25 (six weeks). * Figure 2: Genome-wide and local association scans and mutant analyses. () Graph showing a genome-wide association scan of a panel of 190 barley cultivars with 2,463 SNPs with the six-rowed or two-rowed trait. Below the graph is a cartoon representing the genotype of the NIL BW421 that carries an introgression (marked with an arrow) containing the X-ray–induced int-c.5 mutant allele in the cv Bowman background. () Detailed plot of the associated region of barley chromosome 4HS against a 'virtual' physical order of genes assuming conservation of synteny with rice chromosome 3. Solid circles represent SNPs in the initial genome scan and open circles represent SNPs and indels observed in sequenced PCR amplicons. The most significant association is with the barley ortholog of LOC_Os03g49880 (OsTB1) marked with an arrow. () Diagram showing the structure of HvTB1 with the location of the conserved SP, TCP and R domains. The positions of the seventeen independent int-c mutant alleles listed in Table 1 are shown above the gene structure, and the codin! g differences between Int-c.a and int-c.b in the region between the SP and TCP domains are shown below.*Premature stop codon; :, small deletion resulting in a frameshift; >, non-synonymous change in the coding domain. Author information * Author information * Supplementary information Affiliations * Genetics Programme, Scottish Crop Research Institute, Invergowrie, Dundee, Scotland, UK. * Luke Ramsay, * Jordi Comadran, * Arnis Druka, * David F Marshall, * William T B Thomas, * Malcolm Macaulay, * Craig Simpson, * John Fuller, * Nicola Bonar & * Robbie Waugh * Biomathematics and Statistics Scotland, Scottish Crop Research Institute, Invergowrie, Dundee, Scotland, UK. * Katrin MacKenzie * Barley Project Crop Science Building, Oregon State University Corvallis, Oregon, USA. * Patrick M Hayes * Nordic Genetic Resource Center, Alnarp, Sweden. * Udda Lundqvist * Queensland Primary Industries and Fisheries, Hermitage Research Station, Warwick, Queensland, Australia. * Jerome D Franckowiak * Department of Botany and Plant Sciences, University of California, Riverside, California, USA. * Timothy J Close * Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota, USA. * Gary J Muehlbauer Contributions L.R., J.C. and R.W. drafted the manuscript. J.C. and K.M. performed statistical analyses. T.J.C. led the SNP genotyping effort. L.R., A.D., N.B. and M.M. provided additional genotyping information. A.D. performed detailed phenotyping data, including scanning electron microscopy work. C.S. and J.F. provided expression data. A.D., D.F.M., W.T.B.T., P.M.H., U.L., J.D.F., T.J.C. and G.J.M. made important suggestions to the analytical plan, aided interpretation of results and participated in revising the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Robbie Waugh Supplementary information * Author information * Supplementary information Excel files * Supplementary Table 1 (36K) List of the 190 lines used in survey showing VRS1 and INT-C alleles PDF files * Supplementary Text and Figures (352K) Supplementary Note, Supplementary Tables 2–4 and Supplementary Figure 1–8 Additional data