Latest Articles Include:
- Proportional representation
- Nature genetics 42(3):187 (2010)
Nature Genetics | Editorial Proportional representation Journal name:Nature GeneticsVolume:42,Page:187Year published:(2010)DOI:doi:10.1038/ng0310-187 The journal publishes papers from a very broad geographical catchment, and we invite peer referees from among the world's best genetics researchers in order to attract and publish papers of a uniformly high standard. We need to do more to recruit outstanding referees from under-represented regions. View full text Additional data - Deciphering genetic susceptibility to frontotemporal lobar dementia
- Nature genetics 42(3):189-190 (2010)
A genome-wide association study has identified a new genetic susceptibility factor for a subtype of frontotemporal lobar dementia characterized by TDP-43 inclusions. The work illustrates how high-quality phenotyping can increase power to detect risk alleles for rare heterogeneous diseases. - Open chromatin and diabetes risk
- Nature genetics 42(3):190-192 (2010)
A new study has identified a large number of open chromatin regions harboring active regulatory elements in human pancreatic islets. A type 2 diabetes–associated SNP in TCF7L2 was found to be located in a region of allele-specific open chromatin and shows allele-specific enhancer activity, suggesting a potential mechanism for this disease association. - Understanding variable expressivity in microdeletion syndromes
- Nature genetics 42(3):192-193 (2010)
A new study reports an elevated frequency of second-site genomic alterations among children with severe developmental delay who carry a recurrent microdeletion at chromosome 16p12.1. The work highlights the complex relationship between genotype and phenotype and provides a model to explain the clinical variability associated with this and other common microdeletion syndromes. - Research highlights
- Nature genetics 42(3):195 (2010)
- Common variants near TERC are associated with mean telomere length
Codd V Mangino M van der Harst P Braund PS Kaiser M Beveridge AJ Rafelt S Moore J Nelson C Soranzo N Zhai G Valdes AM Blackburn H Leach IM de Boer RA Wellcome Trust Case Control Consortium Goodall AH Ouwehand W van Veldhuisen DJ van Gilst WH Navis G Burton PR Tobin MD Hall AS Thompson JR Spector T Samani NJ - Nature genetics 42(3):197-199 (2010)
Nature Genetics | Brief Communication Common variants near TERC are associated with mean telomere length * Veryan Codd1, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Massimo Mangino2, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Pim van der Harst1, 3, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Peter S Braund1 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Kaiser1 Search for this author in: * NPG journals * PubMed * Google Scholar * Alan J Beveridge1 Search for this author in: * NPG journals * PubMed * Google Scholar * Suzanne Rafelt1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jasbir Moore1 Search for this author in: * NPG journals * PubMed * Google Scholar * Chris Nelson1 Search for this author in: * NPG journals * PubMed * Google Scholar * Nicole Soranzo2, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Guangju Zhai2 Search for this author in: * NPG journals * PubMed * Google Scholar * Ana M Valdes2 Search for this author in: * NPG journals * PubMed * Google Scholar * Hannah Blackburn4 Search for this author in: * NPG journals * PubMed * Google Scholar * Irene Mateo Leach3 Search for this author in: * NPG journals * PubMed * Google Scholar * Rudolf A de Boer3 Search for this author in: * NPG journals * PubMed * Google Scholar * Wellcome Trust Case Control Consortium9 * Alison H Goodall1 Search for this author in: * NPG journals * PubMed * Google Scholar * Willem Ouwehand5 Search for this author in: * NPG journals * PubMed * Google Scholar * Dirk J van Veldhuisen3 Search for this author in: * NPG journals * PubMed * Google Scholar * Wiek H van Gilst3 Search for this author in: * NPG journals * PubMed * Google Scholar * Gerjan Navis6 Search for this author in: * NPG journals * PubMed * Google Scholar * Paul R Burton7 Search for this author in: * NPG journals * PubMed * Google Scholar * Martin D Tobin7 Search for this author in: * NPG journals * PubMed * Google Scholar * Alistair S Hall8 Search for this author in: * NPG journals * PubMed * Google Scholar * John R Thompson7 Search for this author in: * NPG journals * PubMed * Google Scholar * Tim Spector2, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Nilesh J Samani1, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:197–199Year published:(2010)DOI:doi:10.1038/ng.532 Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We conducted genome-wide association analyses of mean leukocyte telomere length in 2,917 individuals, with follow-up replication in 9,492 individuals. We identified an association with telomere length on 3q26 (rs12696304, combined P = 3.72 × 10−14) at a locus that includes TERC, which encodes the telomerase RNA component. Each copy of the minor allele of rs12696304 was associated with an ~75-base-pair reduction in mean telomere length, equivalent to ~3.6 years of age-related telomere-length attrition. View full text Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Veryan Codd, * Massimo Mangino, * Pim van der Harst, * Tim Spector & * Nilesh J Samani Affiliations * Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, UK. * Veryan Codd, * Pim van der Harst, * Peter S Braund, * Michael Kaiser, * Alan J Beveridge, * Suzanne Rafelt, * Jasbir Moore, * Chris Nelson, * Alison H Goodall & * Nilesh J Samani * Department of Twin Research and Genetic Epidemiology, King's College London, London, UK. * Massimo Mangino, * Nicole Soranzo, * Guangju Zhai, * Ana M Valdes & * Tim Spector * Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. * Pim van der Harst, * Irene Mateo Leach, * Rudolf A de Boer, * Dirk J van Veldhuisen & * Wiek H van Gilst * Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK. * Nicole Soranzo & * Hannah Blackburn * Department of Hematology, University of Cambridge, Cambridge, UK. * Willem Ouwehand * Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. * Gerjan Navis * Departments of Health Sciences and Genetics, University of Leicester, Leicester, UK. * Paul R Burton, * Martin D Tobin & * John R Thompson * Leeds Institute of Genetics, Health and Therapeutics, University of Leeds, Leeds, UK. * Alistair S Hall * A full list of members is provided is provided in the Supplementary Note. * Wellcome Trust Case Control Consortium Consortia * Wellcome Trust Case Control Consortium Contributions N.J.S. and T.S. conceived the study. V.C., M.M. and P.v.d.H. designed the laboratory work and conducted the analyses. V.C., P.S.B., M.K., J.M., I.M.L. and R.A.d.B. undertook the laboratory work. A.J.B. provided bioinformatics support and S.R., C.N. and N.S. undertook statistical support. A.S.H. and N.J.S. recruited and provided samples and data from the BHF Family Heart Study; W.T.C.C.C. and W.O. from the UKBS samples; A.H.G., P.R.B., M.D.T. and N.J.S. from the GRAPHIC study; G.Z., A.M.V., H.B. and T.S. from the TwinsUK study; and D.J.v.V., W.H.v.G. and G.N. from the PREVEND Study. J.R.T. oversaw the statistical analysis. The paper was written by V.C., M.M. and N.J.S. All authors contributed to the final version of the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Nilesh J Samani (njs@le.ac.uk) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (964K) Supplementary Figure 1, Supplementary Tables 1–5, Supplementary Methods and Supplementary Note Additional data - Variants in FAM13A are associated with chronic obstructive pulmonary disease
Cho MH Boutaoui N Klanderman BJ Sylvia JS Ziniti JP Hersh CP Demeo DL Hunninghake GM Litonjua AA Sparrow D Lange C Won S Murphy JR Beaty TH Regan EA Make BJ Hokanson JE Crapo JD Kong X Anderson WH Tal-Singer R Lomas DA Bakke P Gulsvik A Pillai SG Silverman EK - Nature genetics 42(3):200-202 (2010)
Nature Genetics | Brief Communication Variants in FAM13A are associated with chronic obstructive pulmonary disease * Michael H Cho1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Nadia Boutaoui1 Search for this author in: * NPG journals * PubMed * Google Scholar * Barbara J Klanderman1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jody S Sylvia1 Search for this author in: * NPG journals * PubMed * Google Scholar * John P Ziniti1 Search for this author in: * NPG journals * PubMed * Google Scholar * Craig P Hersh1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Dawn L DeMeo1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Gary M Hunninghake1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Augusto A Litonjua1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * David Sparrow3, 4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Christoph Lange6 Search for this author in: * NPG journals * PubMed * Google Scholar * Sungho Won6 Search for this author in: * NPG journals * PubMed * Google Scholar * James R Murphy7 Search for this author in: * NPG journals * PubMed * Google Scholar * Terri H Beaty8 Search for this author in: * NPG journals * PubMed * Google Scholar * Elizabeth A Regan7 Search for this author in: * NPG journals * PubMed * Google Scholar * Barry J Make7 Search for this author in: * NPG journals * PubMed * Google Scholar * John E Hokanson9 Search for this author in: * NPG journals * PubMed * Google Scholar * James D Crapo7 Search for this author in: * NPG journals * PubMed * Google Scholar * Xiangyang Kong10 Search for this author in: * NPG journals * PubMed * Google Scholar * Wayne H Anderson11 Search for this author in: * NPG journals * PubMed * Google Scholar * Ruth Tal-Singer10 Search for this author in: * NPG journals * PubMed * Google Scholar * David A Lomas12 Search for this author in: * NPG journals * PubMed * Google Scholar * Per Bakke13 Search for this author in: * NPG journals * PubMed * Google Scholar * Amund Gulsvik13 Search for this author in: * NPG journals * PubMed * Google Scholar * Sreekumar G Pillai11, 14 Search for this author in: * NPG journals * PubMed * Google Scholar * Edwin K Silverman1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:200–202Year published:(2010)DOI:doi:10.1038/ng.535 Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We performed a genome-wide association study for chronic obstructive pulmonary disease (COPD) in three population cohorts, including 2,940 cases and 1,380 controls who were current or former smokers with normal lung function. We identified a new susceptibility locus at 4q22.1 in FAM13A and replicated this association in one case-control group (n = 1,006) and two family-based cohorts (n = 3,808) (rs7671167, combined P = 1.2 × 10−11, combined odds ratio in case-control studies 0.76, 95% confidence interval 0.69–0.83). View full text Author information * Author information * Supplementary information Affiliations * Channing Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA. * Michael H Cho, * Nadia Boutaoui, * Barbara J Klanderman, * Jody S Sylvia, * John P Ziniti, * Craig P Hersh, * Dawn L DeMeo, * Gary M Hunninghake, * Augusto A Litonjua & * Edwin K Silverman * Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA. * Michael H Cho, * Craig P Hersh, * Dawn L DeMeo, * Gary M Hunninghake, * Augusto A Litonjua & * Edwin K Silverman * Veterans Administration Boston Healthcare System, Boston, Massachusetts, USA. * David Sparrow * School of Public Health, Boston University, Boston, Massachusetts, USA. * David Sparrow * School of Medicine, Boston University, Boston, Massachusetts, USA. * David Sparrow * Harvard School of Public Health, Harvard University, Boston, Massachusetts, USA. * Christoph Lange & * Sungho Won * National Jewish Medical and Research Center, Denver, Colorado, USA. * James R Murphy, * Elizabeth A Regan, * Barry J Make & * James D Crapo * Johns Hopkins School of Public Health, Baltimore, Maryland, USA. * Terri H Beaty * Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado, USA. * John E Hokanson * GlaxoSmithKline Research and Development, King of Prussia, Pennsylvania. * Xiangyang Kong & * Ruth Tal-Singer * GlaxoSmithKline Research and Development, Research Triangle Park, North Carolina, USA. * Wayne H Anderson & * Sreekumar G Pillai * Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK. * David A Lomas * Haukeland University Hospital and Institute of Medicine, University of Bergen, Bergen, Norway. * Per Bakke & * Amund Gulsvik * Current address: Hoffman La Roche, Nutley, New Jersey, USA. * Sreekumar G Pillai Contributions E.K.S., M.H.C., A.A.L., D.S., S.G.P., X.K., W.H.A., R.T.-S., D.A.L., P.B., A.G., J.R.M., T.H.B., E.A.R., B.J.M., J.E.H., J.D.C., C.P.H. and D.L.D. A.A.L., D.S., S.G.P., X.K., W.H.A., R.T.-S., D.A.L., P.B., A.G., E.A.R., B.J.M., J.D.C., E.K.S. N.B., B.J.K., M.H.C., S.G.P., X.K. M.H.C., J.S.S., J.P.Z., B.J.K., N.B. M.H.C., C.L., S.W., E.K.S. M.H.C., G.M.H., E.K.S. All authors reviewed and approved the manuscript. Competing financial interests E.K.S. has received grant support and consulting and speaker's fees from GlaxoSmithKline, consulting and speaker's fees from Astra-Zeneca and speaker's fees from Bayer and Wyeth. D.A.L. has received grant support, lecture fees and consultancy fees from GlaxoSmithKline. S.G.P, X.Q.K., W.H.A. and R.M.T. are employees of GlaxoSmithKline. Corresponding author Correspondence to: * Edwin K Silverman (remhc@channing.harvard.edu) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (468K) Supplementary Methods, Supplementary Note, Supplementary Figures 1–3 and Supplementary Tables 1–4 Additional data - A recurrent 16p12.1 microdeletion supports a two-hit model for severe developmental delay
Girirajan S Rosenfeld JA Cooper GM Antonacci F Siswara P Itsara A Vives L Walsh T McCarthy SE Baker C Mefford HC Kidd JM Browning SR Browning BL Dickel DE Levy DL Ballif BC Platky K Farber DM Gowans GC Wetherbee JJ Asamoah A Weaver DD Mark PR Dickerson J Garg BP Ellingwood SA Smith R Banks VC Smith W McDonald MT Hoo JJ French BN Hudson C Johnson JP Ozmore JR Moeschler JB Surti U Escobar LF El-Khechen D Gorski JL Kussmann J Salbert B Lacassie Y Biser A McDonald-McGinn DM Zackai EH Deardorff MA Shaikh TH Haan E Friend KL Fichera M Romano C Gécz J Delisi LE Sebat J King MC Shaffer LG Eichler EE - Nature genetics 42(3):203-209 (2010)
Nature Genetics | Article A recurrent 16p12.1 microdeletion supports a two-hit model for severe developmental delay * Santhosh Girirajan1, 30 Search for this author in: * NPG journals * PubMed * Google Scholar * Jill A Rosenfeld2, 30 Search for this author in: * NPG journals * PubMed * Google Scholar * Gregory M Cooper1 Search for this author in: * NPG journals * PubMed * Google Scholar * Francesca Antonacci1 Search for this author in: * NPG journals * PubMed * Google Scholar * Priscillia Siswara1 Search for this author in: * NPG journals * PubMed * Google Scholar * Andy Itsara1 Search for this author in: * NPG journals * PubMed * Google Scholar * Laura Vives1 Search for this author in: * NPG journals * PubMed * Google Scholar * Tom Walsh3 Search for this author in: * NPG journals * PubMed * Google Scholar * Shane E McCarthy4 Search for this author in: * NPG journals * PubMed * Google Scholar * Carl Baker1 Search for this author in: * NPG journals * PubMed * Google Scholar * Heather C Mefford1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jeffrey M Kidd1 Search for this author in: * NPG journals * PubMed * Google Scholar * Sharon R Browning5 Search for this author in: * NPG journals * PubMed * Google Scholar * Brian L Browning5 Search for this author in: * NPG journals * PubMed * Google Scholar * Diane E Dickel1 Search for this author in: * NPG journals * PubMed * Google Scholar * Deborah L Levy6, 7 Search for this author in: * NPG journals * PubMed * Google Scholar * Blake C Ballif2 Search for this author in: * NPG journals * PubMed * Google Scholar * Kathryn Platky8 Search for this author in: * NPG journals * PubMed * Google Scholar * Darren M Farber9 Search for this author in: * NPG journals * PubMed * Google Scholar * Gordon C Gowans8 Search for this author in: * NPG journals * PubMed * Google Scholar * Jessica J Wetherbee8 Search for this author in: * NPG journals * PubMed * Google Scholar * Alexander Asamoah8 Search for this author in: * NPG journals * PubMed * Google Scholar * David D Weaver10 Search for this author in: * NPG journals * PubMed * Google Scholar * Paul R Mark10 Search for this author in: * NPG journals * PubMed * Google Scholar * Jennifer Dickerson11 Search for this author in: * NPG journals * PubMed * Google Scholar * Bhuwan P Garg11 Search for this author in: * NPG journals * PubMed * Google Scholar * Sara A Ellingwood12 Search for this author in: * NPG journals * PubMed * Google Scholar * Rosemarie Smith12 Search for this author in: * NPG journals * PubMed * Google Scholar * Valerie C Banks12 Search for this author in: * NPG journals * PubMed * Google Scholar * Wendy Smith12 Search for this author in: * NPG journals * PubMed * Google Scholar * Marie T McDonald13 Search for this author in: * NPG journals * PubMed * Google Scholar * Joe J Hoo14 Search for this author in: * NPG journals * PubMed * Google Scholar * Beatrice N French14 Search for this author in: * NPG journals * PubMed * Google Scholar * Cindy Hudson15 Search for this author in: * NPG journals * PubMed * Google Scholar * John P Johnson15 Search for this author in: * NPG journals * PubMed * Google Scholar * Jillian R Ozmore16 Search for this author in: * NPG journals * PubMed * Google Scholar * John B Moeschler16 Search for this author in: * NPG journals * PubMed * Google Scholar * Urvashi Surti17 Search for this author in: * NPG journals * PubMed * Google Scholar * Luis F Escobar18 Search for this author in: * NPG journals * PubMed * Google Scholar * Dima El-Khechen18 Search for this author in: * NPG journals * PubMed * Google Scholar * Jerome L Gorski19 Search for this author in: * NPG journals * PubMed * Google Scholar * Jennifer Kussmann19 Search for this author in: * NPG journals * PubMed * Google Scholar * Bonnie Salbert20 Search for this author in: * NPG journals * PubMed * Google Scholar * Yves Lacassie21 Search for this author in: * NPG journals * PubMed * Google Scholar * Alisha Biser22 Search for this author in: * NPG journals * PubMed * Google Scholar * Donna M McDonald-McGinn22 Search for this author in: * NPG journals * PubMed * Google Scholar * Elaine H Zackai22 Search for this author in: * NPG journals * PubMed * Google Scholar * Matthew A Deardorff22 Search for this author in: * NPG journals * PubMed * Google Scholar * Tamim H Shaikh22 Search for this author in: * NPG journals * PubMed * Google Scholar * Eric Haan23, 24 Search for this author in: * NPG journals * PubMed * Google Scholar * Kathryn L Friend25 Search for this author in: * NPG journals * PubMed * Google Scholar * Marco Fichera26 Search for this author in: * NPG journals * PubMed * Google Scholar * Corrado Romano26 Search for this author in: * NPG journals * PubMed * Google Scholar * Jozef Gécz24, 25 Search for this author in: * NPG journals * PubMed * Google Scholar * Lynn E DeLisi7, 27 Search for this author in: * NPG journals * PubMed * Google Scholar * Jonathan Sebat28 Search for this author in: * NPG journals * PubMed * Google Scholar * Mary-Claire King1, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Lisa G Shaffer2 Search for this author in: * NPG journals * PubMed * Google Scholar * Evan E Eichler1, 29 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:203–209Year published:(2010)DOI:doi:10.1038/ng.534 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We report the identification of a recurrent, 520-kb 16p12.1 microdeletion associated with childhood developmental delay. The microdeletion was detected in 20 of 11,873 cases compared with 2 of 8,540 controls (P = 0.0009, OR = 7.2) and replicated in a second series of 22 of 9,254 cases compared with 6 of 6,299 controls (P = 0.028, OR = 2.5). Most deletions were inherited, with carrier parents likely to manifest neuropsychiatric phenotypes compared to non-carrier parents (P = 0.037, OR = 6). Probands were more likely to carry an additional large copy-number variant when compared to matched controls (10 of 42 cases, P = 5.7 × 10−5, OR = 6.6). The clinical features of individuals with two mutations were distinct from and/or more severe than those of individuals carrying only the co-occurring mutation. Our data support a two-hit model in which the 16p12.1 microdeletion both predisposes to neuropsychiatric phenotypes as a single event and exacerbates neurodevelopmental phenotyp! es in association with other large deletions or duplications. Analysis of other microdeletions with variable expressivity indicates that this two-hit model might be more generally applicable to neuropsychiatric disease. View full text Figures at a glance * Figure 1: High-resolution array-based CGH characterization of 16p12.1 microdeletion. Shown is validation of 16p12.1 microdeletions in a representative set of cases using high-resolution tiling-path custom array-based CGH. Probes with log2 ratios above or below a threshold of 1.5 s.d. from the normalized mean log2 ratio are colored green (duplication) or red (deletion), respectively. Dotted lines represent breakpoint regions. Subjects SG01–13 and SGA3–7 have indications of developmental delay or cognitive disability, sample 43163 is from the GAIN schizophrenia study and subject LD1205-03 has schizophrenia and intellectual disability (from family LD1205). Note that samples 26140 and 18125 were analyzed as part of the GAIN control cohort for schizophrenia. It is noteworthy that one control (subject 26140) was retrospectively diagnosed with a major depressive disorder. Six RefSeq genes map within the 16p12.1 microdeletion. Four subjects (SG04, SG07, SG11 (affected with hypoplastic left heart syndrome) and LD1205-03 (diagnosed with schizophrenia)) were sequen! ced for CDR2, EEF2K and UQCRC2; no recessive mutations were identified. * Figure 2: Genomic structure of 16p12.1 region. () A schematic of the 16p12.1 region shows the location of the microdeletion flanked by directly oriented 68-kb segmental duplication blocks (red boxes). The segmental duplication blocks (red and gray boxes) are connected by green and blue lines to indicate direct or inverted orientation, respectively. Also shown are representative genes in the region with the transcriptional direction. CNP indicates the copy-number polymorphism annotated by SNP genotyping16 for this region (CNP2157). () FISH analysis was performed on lymphoblast cell line from GM18956 using fosmid probes mapping to the 68-kb duplicon (WIBR2-2031K01, shown in red) and the flanking unique regions (WIBR2-3632J22 in green and WIBR2-1829F15 in blue). Results show that the 68-kb duplicon is polymorphic (that is, it has a variable number of copies) and that the orientation of the region is inverted in this HapMap sample compared to the human genome reference assembly. High copy numbers of the segmental duplication! s have complicated mapping of the inversion breakpoint for this region. * Figure 3: Representative photographs of individuals with 16p12.1 microdeletion. (–) Facial features of patient SG07 at 22 months (), patient SGA3 at 2.5 years (), patient SGA5 at 2 years (), patient SG04 at 15 months (), patient SG10 at 2 years () and patient 25514 at 5 years (). Specific consents were obtained to publish these photographs. * Figure 4: Family pedigrees of probands with 16p12.1 microdeletions. () Large CNVs outside the 16p12.1 region in a representative set of individuals with 16p12.1 microdeletions. The CNV regions are indicated by dotted lines, and the cytogenetic extent and size are labeled. We used a 135K NimbleGen array to identify these CNVs (with average probe density of 2.5 kb in regions flanked by segmental duplications and an average probe density of 35 kb in the genomic backbone). CNV calls were made using a Hidden Markov Model CNV-calling algorithm described previously15. () Pedigrees of individuals with 16p12.1 microdeletions and known available parental information. Circles indicate females; squares indicate males. The intellectual disability and congenital malformation category also includes congenital heart defects and seizures. Psychiatric illness includes depression or bipolar disorder, attention deficit hyperactive disorder and abnormal behavior. Note that there is an excess of transmitting parents with the microdeletion who also manifested a ne! uropsychiatric phenotype. NT, not tested. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Santhosh Girirajan & * Jill A Rosenfeld Affiliations * Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA. * Santhosh Girirajan, * Gregory M Cooper, * Francesca Antonacci, * Priscillia Siswara, * Andy Itsara, * Laura Vives, * Carl Baker, * Heather C Mefford, * Jeffrey M Kidd, * Diane E Dickel, * Mary-Claire King & * Evan E Eichler * Signature Genomic Laboratories, Spokane, Washington, USA. * Jill A Rosenfeld, * Blake C Ballif & * Lisa G Shaffer * Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA. * Tom Walsh & * Mary-Claire King * Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. * Shane E McCarthy * Department of Statistics, Faculty of Science, The University of Auckland, Auckland, New Zealand. * Sharon R Browning & * Brian L Browning * Psychology Research Laboratory, McLean Hospital, Belmont, Massachusetts, USA. * Deborah L Levy * Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA. * Deborah L Levy & * Lynn E DeLisi * Weisskopf Child Evaluation Center, Department of Pediatrics, University of Louisville, Louisville, Kentucky, USA. * Kathryn Platky, * Gordon C Gowans, * Jessica J Wetherbee & * Alexander Asamoah * Division of Child Neurology, Department of Neurology, University of Louisville, School of Medicine, Louisville, Kentucky, USA. * Darren M Farber * Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis, Indiana, USA. * David D Weaver & * Paul R Mark * Department of Neurology, Division of Pediatric Neurology, School of Medicine, Indiana University, Indianapolis, Indiana, USA. * Jennifer Dickerson & * Bhuwan P Garg * Division of Genetics, Maine Medical Partners Pediatric Specialty Care, Maine Medical Center, Portland, Maine, USA. * Sara A Ellingwood, * Rosemarie Smith, * Valerie C Banks & * Wendy Smith * Division of Medical Genetics, Duke University Medical Center, Durham, North Carolina, USA. * Marie T McDonald * Department of Pediatrics, University of Toledo Medical College and Northwest Ohio Regional Genetics Center, Toledo, Ohio, USA. * Joe J Hoo & * Beatrice N French * Medical Genetics, Shodair Children's Hospital, Helena, Montana, USA. * Cindy Hudson & * John P Johnson * Division of Clinical Genetics, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire, USA. * Jillian R Ozmore & * John B Moeschler * Magee-Womens Hospital of University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA. * Urvashi Surti * Medical Genetics and Neurodevelopmental Center, St. Vincent Children's Hospital, Indianapolis, Indiana, USA. * Luis F Escobar & * Dima El-Khechen * Division of Medical Genetics, University of Missouri, Columbia, Missouri, USA. * Jerome L Gorski & * Jennifer Kussmann * Geisinger Medical Center, Danville, Pennsylvania, USA. * Bonnie Salbert * Division of Genetics, Department of Pediatrics, Louisiana State University Health Sciences Center and Children's Hospital, New Orleans, Louisiana, USA. * Yves Lacassie * Department of Pediatrics and Genetics, University of Pennsylvania, and the Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA. * Alisha Biser, * Donna M McDonald-McGinn, * Elaine H Zackai, * Matthew A Deardorff & * Tamim H Shaikh * South Australian Clinical Genetics Service, South Australian Pathology at Women's and Children's Hospital, Adelaide, Australia. * Eric Haan * Department of Paediatrics, The University of Adelaide, Adelaide, Australia. * Eric Haan & * Jozef Gécz * Genetics and Molecular Pathology, and South Australian Pathology at Women's and Children's Hospital, Adelaide, Australia. * Kathryn L Friend & * Jozef Gécz * Oasi Institute for Research and Care in Mental Retardation and Brain Aging, Troina, Italy. * Marco Fichera & * Corrado Romano * VA Boston Healthcare System, Brockton, Massachusetts, USA. * Lynn E DeLisi * Departments of Psychiatry and Cellular and Molecular Medicine, University of California, San Diego, La Jolla, California, USA. * Jonathan Sebat * Howard Hughes Medical Institute, University of Washington, Seattle, Washington, USA. * Evan E Eichler Contributions This study was designed by S.G., L.G.S. and E.E.E. J.A.R., B.C.B. and L.G.S. supervised array-CGH experiments at Signature Genomics. J.A.R. coordinated clinical data collection. T.W., S.E.M., D.E.D., D.L.L., J.S., L.E.D. and M.-C.K. contributed to schizophrenia data collection and analysis. S.G., L.V. and C.B. performed high-density array-CGH experiments. G.M.C. and A.I. analyzed control CNV data. S.G., F.A. and J.M.K. performed genome structure analysis. F.A. performed FISH experiments. S.G. and P.S. sequenced and analyzed candidate genes. S.R.B. and B.L.B. performed haplotype analysis. K.P., D.M.F., G.C.G., J.J.W., A.A., D.D.W., P.R.M., J.D., B.P.G., S.A.E., R.S., V.C.B., W.S., M.T.M., J.J.H., B.N.F., C.H., J.P.J., J.R.O., J.B.M., U.S., L.F.E., D.E.-K., J.L.G., J.K., B.S., Y.L., A.B., D.M.M.-M., E.H.Z., M.A.D., T.H.S., E.H., K.L.F., M.F., C.R. and J.G. provided clinical information. H.C.M. provided 1q21.1 data. S.G., G.M.C., M.-C.K. and E.E.E. contributed to data interpret! ation. S.G. and E.E.E. wrote the manuscript. Competing financial interests E.E.E. is a member of the Scientific Advisory Board of Pacific Biosciences. J.A.R. and B.C.B. are employees of Signature Genomic Laboratories, LLC. L.G.S. is an employee of, owns shares in and sits on the Members' Board of Signature Genomic Laboratories, LLC. Corresponding author Correspondence to: * Evan E Eichler (eee@gs.washington.edu) Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1–4, Supplementary Tables 1–9 and Supplementary Note Additional data - Genome-wide association study of hematological and biochemical traits in a Japanese population
Kamatani Y Matsuda K Okada Y Kubo M Hosono N Daigo Y Nakamura Y Kamatani N - Nature genetics 42(3):210-215 (2010)
Nature Genetics | Article Genome-wide association study of hematological and biochemical traits in a Japanese population * Yoichiro Kamatani1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Koichi Matsuda1 Search for this author in: * NPG journals * PubMed * Google Scholar * Yukinori Okada3 Search for this author in: * NPG journals * PubMed * Google Scholar * Michiaki Kubo4 Search for this author in: * NPG journals * PubMed * Google Scholar * Naoya Hosono4 Search for this author in: * NPG journals * PubMed * Google Scholar * Yataro Daigo1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Yusuke Nakamura1, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Naoyuki Kamatani3 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:210–215Year published:(2010)DOI:doi:10.1038/ng.531 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We report genome-wide association studies for hematological and biochemical traits from ~14,700 Japanese individuals. We identified 60 associations for 8 hematological traits and 29 associations for 12 biochemical traits at genome-wide significance levels (P < 5 × 10−8). Of these, 46 associations were new to this study and 43 replicated previous reports. We compared these associated loci with those reported in similar GWAS in European populations. When the minor allele frequency was >10% in the Japanese population, 32 (94.1%) and 31 (91.2%) of the 34 hematological loci previously reported to be associated in a European population were replicated with P-values less than 0.05 and 0.01, respectively, and 31 (73.8%) and 27 (64.3%) of the 42 European biochemical loci were replicated. View full text Author information * Abstract * Author information * Supplementary information Affiliations * Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, the University of Tokyo, Tokyo, Japan. * Yoichiro Kamatani, * Koichi Matsuda, * Yataro Daigo & * Yusuke Nakamura * Department of Medical Genome Sciences, Graduate School of Frontier Sciences, the University of Tokyo, Tokyo, Japan. * Yoichiro Kamatani & * Yataro Daigo * Laboratory for Statistical Analysis, Kanagawa, Japan. * Yukinori Okada & * Naoyuki Kamatani * Laboratory for Genotyping Development, Kanagawa, Japan. * Michiaki Kubo & * Naoya Hosono * Center for Genomic Medicine, RIKEN, Kanagawa, Japan. * Yusuke Nakamura Contributions Y.K., K.M., M.K. and N.K. designed the study; Y.N. managed BioBank Japan; M.K. and N.H. conducted genotyping experiments and quality control; Y.K., Y.O. and N.K. performed the statistical analysis; Y.K., Y.O., K.M., M.K., Y.D. and N.K. wrote the manuscript; Y.N. obtained the funding for the study. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Naoyuki Kamatani (kamatani@msb.biglobe.ne.jp) Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1–3 and Supplementary Tables 1–4 Additional data - Identification of DOK genes as lung tumor suppressors
Berger AH Niki M Morotti A Taylor BS Socci ND Viale A Brennan C Szoke J Motoi N Rothman PB Teruya-Feldstein J Gerald WL Ladanyi M Pandolfi PP - Nature genetics 42(3):216-223 (2010)
Nature Genetics | Article Identification of DOK genes as lung tumor suppressors * Alice H Berger1, 2, 3, 4, 12 Search for this author in: * NPG journals * PubMed * Google Scholar * Masaru Niki2, 3, 5, 12 Search for this author in: * NPG journals * PubMed * Google Scholar * Alessandro Morotti1, 2, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Barry S Taylor6 Search for this author in: * NPG journals * PubMed * Google Scholar * Nicholas D Socci7 Search for this author in: * NPG journals * PubMed * Google Scholar * Agnes Viale8 Search for this author in: * NPG journals * PubMed * Google Scholar * Cameron Brennan9, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Janos Szoke3 Search for this author in: * NPG journals * PubMed * Google Scholar * Noriko Motoi3 Search for this author in: * NPG journals * PubMed * Google Scholar * Paul B Rothman5 Search for this author in: * NPG journals * PubMed * Google Scholar * Julie Teruya-Feldstein3 Search for this author in: * NPG journals * PubMed * Google Scholar * William L Gerald3, 10, 11 Search for this author in: * NPG journals * PubMed * Google Scholar * Marc Ladanyi3, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Pier Paolo Pandolfi1, 2, 3, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:216–223Year published:(2010)DOI:doi:10.1038/ng.527 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Genome-wide analyses of human lung adenocarcinoma have identified regions of consistent copy-number gain or loss, but in many cases the oncogenes and tumor suppressors presumed to reside in these loci remain to be determined. Here we identify the downstream of tyrosine kinase (Dok) family members Dok1, Dok2 and Dok3 as lung tumor suppressors. Single, double or triple compound loss of these genes in mice results in lung cancer, with penetrance and latency dependent on the number of lost Dok alleles. Cancer development is preceded by an aberrant expansion and signaling profile of alveolar type II cells and bronchioalveolar stem cells. In human lung adenocarcinoma, we identify DOK2 as a target of copy-number loss and mRNA downregulation and find that DOK2 suppresses lung cancer cell proliferation in vitro and in vivo. Given the genomic localization of DOK2, we propose it as an 8p21.3 haploinsufficient human lung tumor suppressor. View full text Figures at a glance * Figure 1: Dok1, Dok2 and Dok3 single- and compound-knockout mice develop lung cancer. () Immunoblot analysis of Dok1, Dok2, Dok3 and β-actin (loading control) in splenocyte lysates (Sp) or homogenized whole lung (Lu) from wild-type (WT), Dok1 knockout (KO), Dok2 knockout or Dok3 knockout mice. Arrowhead indicates a nonspecific band. Dok1 was detected in the spleen lysate at a longer exposure (data not shown) and in our previous work9. () Schematic map of the wild-type Dok3 locus (top), targeting vector (middle) and predicted targeted locus (bottom). The Dok3 genomic sequence is shown as a line, with solid boxes representing exons 1–5. Sequences from the pPNT plasmid are shown as boxes with lines, with shaded boxes representing the neomycin resistance cassette (neo), the herpes simplex virus thymidine kinase (TK) cassette and the GFP expression cassette, as indicated. The Dok3 genomic fragments used as probes for Southern blot analysis are indicated (5′ and 3′ probes), as well as the expected fragments (arrows) after hybridization with probes after dige! stion with EcoRI. EcoRI (E), SalI (Sa), HindIII (H), KpnI (K) and SmaI (S) restriction sites are shown. () Lung adenocarcinoma incidence in Dok1, Dok2 and Dok3 single-, double- and triple-knockout mice. Mouse numbers and statistics are summarized in Table 1. * Figure 2: Histopathology of lung tumors in Dok knockout mice. () Gross view of the five lung lobes from a Dok TKO mouse. Arrowheads indicate tumor nodules. Scale bar, 5 mm. () Left, H&E-stained adenocarcinoma with papillary features (*) and solid growth areas (**) from a Dok2/Dok3 DKO lung. Scale bar, 500 μm. Middle, close-up of solid growth region. Scale bar, 50 μm. Right, close-up of papillary growth region. Scale bar, 50 μm. () Immunohistochemical staining for phosphorylated histone H3 (phospho-H3; brown) on lung tissue from age-matched wild-type (top panels) or Dok TKO (bottom panels) mice. Scale bars, 200 μm (left panels) or 50 μm (right panels). () Quantification of phosphorylated histone H3 immunohistochemistry shown in . Data shown are mean + s.e.m. of three randomly selected tumor or normal fields. ***P < 0.001 by two-tailed t-test. () TTF-1 immunohistochemical staining (brown) of a Dok1/Dok3 DKO lung tumor. Scale bar, 50 μm. () Immunohistochemical staining for Ser473-phosphorylated Akt (pAkt; brown) in wild-type (top pa! nels) or Dok3 knockout (bottom panels) lung tissue, showing cytoplasmic positivity in the Dok3 knockout lung tissue. Scale bars, 200 μm (left panels), 50 μm (middle panels) or 10 μm (right panels). Arrowhead indicates positive staining in the lung tumor region. () Immunohistochemical staining for Thr202- and Tyr204-phosphorylated Erk1/2 (pErk1/2) in wild-type or Dok3 knockout lung tissue, showing predominantly nuclear staining. Scale bars, 200 μm (left panels), 50 μm (middle panels) or 10 μm (right panels). Arrowhead indicates positive staining in the lung tumor region. * Figure 3: Hyperplasia and tumors in Dok knockout mice consist of AT2 cells and BASCs. () Immunohistochemical staining for the AT2 cell marker proSP-C (brown) in a Dok1/Dok3 DKO tumor. Scale bar, 50 μm. () Immunohistochemical staining for the Clara cell marker CCSP (brown) in a Dok1/Dok3 DKO tumor. Left, arrowheads indicate positive bronchiolar staining. Right, arrowheads indicate scattered CCSP+ cells in the tumor area. Scale bars, 200 μm (left), 200 μm (middle) or 50 μm (right). () H&E staining of wild-type (top) or Dok TKO (bottom) lung tissue from 12-week-old mice. Scale bar, 200 μm. () Immunofluorescence staining for proSP-C (green), CCSP (red) and the nuclear dye DAPI (blue) on serial sections similar to those shown in . White boxes in middle panels indicate region magnified in the panels to the right. Arrows indicate proSP-C+ AT2 cells; arrowheads indicate proSP-C+CCSP+ BASCs. Scale bars, 200 μm (left panels), 50 μm (middle panels) or 10 μm (right panels). * Figure 4: Lung tumorigenesis in Dok TKO mice is preceded by an expansion of AT2 cells and BASCs. () Cellularity of wild-type and TKO CD45−PECAM− lung cells after dissociation, counting and flow cytometry. Data shown are mean + s.e.m. **P < 0.01 by two-tailed t-test. n = 5 wild-type and 4 TKO mice. () Immunofluorescence staining of the indicated populations, after flow cytometry, for DAPI (blue), proSP-C (green) and CCSP (red). R5, Sca-1−CD45−PECAM−Autofllo; R6 (AT2 cells), Sca-1−CD45−PECAM−Autoflhi; R7 (BASCs), Sca-1+CD45−PECAM−. Scale bars, 50 μm (left panels) or 10 μm (right panels). () Summary of percentages (left) and absolute numbers (right) of cell populations from 12-week-old wild-type and TKO mice. Data shown are mean + s.e.m. *P < 0.05, **P < 0.01, ***P < 0.001 by two-tailed t-test. n = 5 wild-type and 4 TKO mice. () Representative dot plot from flow cytometric analysis of wild-type and TKO CD45−PECAM− cell populations using allophycocyanin (APC)-conjugated antibody to PECAM, APC-conjugated antibody to CD45 and FITC-conjugated antibody! to Sca-1. () Western blot analysis of sorted cell populations. Cell lysates of splenocytes and thymocytes were used as controls. Arrows indicate Dok1, Dok2, Dok3, β-actin. () RT-PCR analysis of Dok1, Dok2 and Dok3 from wild-type and TKO unsorted lung, and wild-type R5, R6 and R7 fractions. Hprt was used as a loading control. Quantitative data are shown in Supplementary Figure 3b. () Western blot analysis of BASC lysates from 12-week-old mice. We pooled 40,000 cells from one to three mice for each lane. Wild-type lung was used as a positive control (+ control). Arrows indicate bands expected for each protein. A nonspecific band is also indicated (*). () Western blot analysis of AT2 lysates. Each lane contains a sample from a different mouse. Markings are as indicated for . * Figure 5: Loss of DOK2 expression in human lung adenocarcinomas and functional data implicate DOK2 as a human lung tumor suppressor. () Frequency of chromosome 8 copy-number aberration, as determined by aCGH analysis of 199 primary human lung adenocarcinoma samples. Shown are the percentages of samples with loss (green) or gain (red) of a particular genomic locus on chromosome 8. Regional gain or loss was defined with a log2 ratio threshold of ±0.15. Blue dashed line indicates genomic position of DOK2. () DOK2 mRNA expression from a microarray of primary lung adenocarcinoma samples, lymph node metastases (Mets), cell lines or normal lung tissue (control). ***P < 0.001 by two-tailed t-test. Data shown are mean + s.e.m. () Western blot analysis of DOK2 protein or β-actin (loading control) in paired lysates from primary human lung tumors (T) and adjacent normal lung from the same patients (N). Relative abundance of DOK2 was quantified using ImageJ software. Numbers represent the ratio of DOK2 to actin expression after normalization by setting the value of each N sample to 1. () Western blot analysis of DOK! 2 or β-actin (loading control) in human non–small-cell lung cancer cell lines. Jurkat and Raji cells were used as positive and negative controls, respectively. See Supplementary Figure 5d for the relative expression in these lines compared to normal, primary human lung tissue. * Figure 6: DOK2 suppresses lung cancer cell proliferation in vitro and in vivo. () Growth-curve analysis of H1299 cells with (+DOK2) or without (Empty) retroviral-mediated overexpression of DOK2. Relative cell number was determined after cell fixation and crystal violet staining using optical density at 595 nm (OD 595). Triplicate wells were analyzed, and data shown are mean ± s.d. of a representative experiment. The experiment was repeated five times. Western blotting (inset) confirmed expression of DOK2. () Analysis of Erk and Akt activation in the same cells used in . Cells were serum-starved in medium containing 0.1% FCS for 12 h, stimulated with 20% FCS for the times indicated, and then lysed and used for western blot analysis with antibodies to phosphorylated Erk1/2 or phosphorylated Akt. () Volume measurements of tumors formed from H1299 cells, with or without DOK2 expression, subcutaneously injected into the flanks of nude mice. The experiment was done in triplicate, and data shown are mean ± s.d. Western blotting (inset) confirmed expression ! of DOK2. () Tumors formed by H1299 cells, with or without DOK2 expression, taken at 5 weeks after cell injection. Arrowheads indicate tumor mass in each panel. * Figure 7: Lung tumorigenesis in Dok2+/− mice. () Summary of lung tumor incidence in Dok2+/− mice (n = 12) and wild-type controls (n = 13) at 15–19 months of age. *P < 0.05 by two-tailed Fisher's exact test. () PCR analysis of genomic DNA from tail DNA (top) or laser-capture microdissected lung cells (bottom) in four Dok2+/− mice (nos. 1–4). Tumor cells (T) or normal adjacent lung tissue (N) on the same slide were microdissected and then used for DNA extraction and PCR analysis with Dok2 genotyping primers that distinguish between the knockout allele (upper bands) and wild-type allele (lower bands). Double-distilled water (ddw) was used as a negative control for PCR. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Alice H Berger & * Masaru Niki Affiliations * Cancer Genetics Program, Beth Israel Deaconess Cancer Center, Departments of Medicine and Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA. * Alice H Berger, * Alessandro Morotti & * Pier Paolo Pandolfi * Cancer Biology and Genetics Program, Sloan-Kettering Institute, New York, New York, USA. * Alice H Berger, * Masaru Niki, * Alessandro Morotti & * Pier Paolo Pandolfi * Department of Pathology, Sloan-Kettering Institute, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. * Alice H Berger, * Masaru Niki, * Alessandro Morotti, * Janos Szoke, * Noriko Motoi, * Julie Teruya-Feldstein, * William L Gerald, * Marc Ladanyi & * Pier Paolo Pandolfi * Weill Graduate School of Medical Sciences, Cornell University, New York, New York, USA. * Alice H Berger & * Pier Paolo Pandolfi * Department of Internal Medicine, University of Iowa, Iowa City, Iowa, USA. * Masaru Niki & * Paul B Rothman * Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. * Barry S Taylor * Bioinformatics Core, Sloan-Kettering Institute, New York, New York, USA. * Nicholas D Socci * Genomics Core Laboratory, Sloan-Kettering Institute, New York, New York, USA. * Agnes Viale * Department of Neurosurgery, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. * Cameron Brennan * Human Oncology and Pathogenesis Program, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. * Cameron Brennan, * William L Gerald & * Marc Ladanyi * Deceased. * William L Gerald Contributions A.H.B., M.N., A.M. and P.P.P. designed and analyzed the experiments. B.S.T., C.B., W.L.G. and M.L. conducted the human genetic studies. A.V. and N.D.S. analyzed the SNP array data. J.S., N.M., J.T.F., W.L.G. and M.L. coordinated the human pathological sample acquisition and distribution. J.T.-F. reviewed all mouse pathology. Some of the experiments were conducted in the laboratory of P.B.R. A.H.B., M.N. and P.P.P. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Pier Paolo Pandolfi (ppandolf@bidmc.harvard.edu) Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (12M) Supplementary Figures 1–7 and Supplementary Tables 1 and 2 Additional data - A genome-wide association study identifies pancreatic cancer susceptibility loci on chromosomes 13q22.1, 1q32.1 and 5p15.33
- Nature genetics 42(3):224-228 (2010)
Nature Genetics | Letter A genome-wide association study identifies pancreatic cancer susceptibility loci on chromosomes 13q22.1, 1q32.1 and 5p15.33 * Gloria M Petersen1, 54 Search for this author in: * NPG journals * PubMed * Google Scholar * Laufey Amundadottir2, 3, 54 Search for this author in: * NPG journals * PubMed * Google Scholar * Charles S Fuchs4, 5, 54 Search for this author in: * NPG journals * PubMed * Google Scholar * Peter Kraft6, 7, 54 Search for this author in: * NPG journals * PubMed * Google Scholar * Rachael Z Stolzenberg-Solomon3, 54 Search for this author in: * NPG journals * PubMed * Google Scholar * Kevin B Jacobs3, 8, 9 Search for this author in: * NPG journals * PubMed * Google Scholar * Alan A Arslan10, 11, 12 Search for this author in: * NPG journals * PubMed * Google Scholar * H Bas Bueno-de-Mesquita13 Search for this author in: * NPG journals * PubMed * Google Scholar * Steven Gallinger14 Search for this author in: * NPG journals * PubMed * Google Scholar * Myron Gross15 Search for this author in: * NPG journals * PubMed * Google Scholar * Kathy Helzlsouer16 Search for this author in: * NPG journals * PubMed * Google Scholar * Elizabeth A Holly17 Search for this author in: * NPG journals * PubMed * Google Scholar * Eric J Jacobs18 Search for this author in: * NPG journals * PubMed * Google Scholar * Alison P Klein19, 20 Search for this author in: * NPG journals * PubMed * Google Scholar * Andrea LaCroix21 Search for this author in: * NPG journals * PubMed * Google Scholar * Donghui Li22 Search for this author in: * NPG journals * PubMed * Google Scholar * Margaret T Mandelson21, 23 Search for this author in: * NPG journals * PubMed * Google Scholar * Sara H Olson24 Search for this author in: * NPG journals * PubMed * Google Scholar * Harvey A Risch25 Search for this author in: * NPG journals * PubMed * Google Scholar * Wei Zheng26 Search for this author in: * NPG journals * PubMed * Google Scholar * Demetrius Albanes3 Search for this author in: * NPG journals * PubMed * Google Scholar * William R Bamlet1 Search for this author in: * NPG journals * PubMed * Google Scholar * Christine D Berg27 Search for this author in: * NPG journals * PubMed * Google Scholar * Marie-Christine Boutron-Ruault28 Search for this author in: * NPG journals * PubMed * Google Scholar * Julie E Buring29, 30 Search for this author in: * NPG journals * PubMed * Google Scholar * Paige M Bracci17 Search for this author in: * NPG journals * PubMed * Google Scholar * Federico Canzian31 Search for this author in: * NPG journals * PubMed * Google Scholar * Sandra Clipp32 Search for this author in: * NPG journals * PubMed * Google Scholar * Michelle Cotterchio33 Search for this author in: * NPG journals * PubMed * Google Scholar * Mariza de Andrade1 Search for this author in: * NPG journals * PubMed * Google Scholar * Eric J Duell34 Search for this author in: * NPG journals * PubMed * Google Scholar * J Michael Gaziano35, 36 Search for this author in: * NPG journals * PubMed * Google Scholar * Edward L Giovannucci5, 6, 37 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Goggins38 Search for this author in: * NPG journals * PubMed * Google Scholar * Göran Hallmans39 Search for this author in: * NPG journals * PubMed * Google Scholar * Susan E Hankinson5, 6 Search for this author in: * NPG journals * PubMed * Google Scholar * Manal Hassan22 Search for this author in: * NPG journals * PubMed * Google Scholar * Barbara Howard40 Search for this author in: * NPG journals * PubMed * Google Scholar * David J Hunter5, 6 Search for this author in: * NPG journals * PubMed * Google Scholar * Amy Hutchinson3, 8 Search for this author in: * NPG journals * PubMed * Google Scholar * Mazda Jenab34 Search for this author in: * NPG journals * PubMed * Google Scholar * Rudolf Kaaks31 Search for this author in: * NPG journals * PubMed * Google Scholar * Charles Kooperberg21 Search for this author in: * NPG journals * PubMed * Google Scholar * Vittorio Krogh41 Search for this author in: * NPG journals * PubMed * Google Scholar * Robert C Kurtz42 Search for this author in: * NPG journals * PubMed * Google Scholar * Shannon M Lynch43 Search for this author in: * NPG journals * PubMed * Google Scholar * Robert R McWilliams1 Search for this author in: * NPG journals * PubMed * Google Scholar * Julie B Mendelsohn3 Search for this author in: * NPG journals * PubMed * Google Scholar * Dominique S Michaud6, 44 Search for this author in: * NPG journals * PubMed * Google Scholar * Hemang Parikh2, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Alpa V Patel18 Search for this author in: * NPG journals * PubMed * Google Scholar * Petra H M Peeters44, 45 Search for this author in: * NPG journals * PubMed * Google Scholar * Aleksandar Rajkovic46 Search for this author in: * NPG journals * PubMed * Google Scholar * Elio Riboli44 Search for this author in: * NPG journals * PubMed * Google 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Brian M Wolpin4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Herbert Yu25 Search for this author in: * NPG journals * PubMed * Google Scholar * Kai Yu3 Search for this author in: * NPG journals * PubMed * Google Scholar * Anne Zeleniuch-Jacquotte11, 12 Search for this author in: * NPG journals * PubMed * Google Scholar * Joseph F Fraumeni Jr3 Search for this author in: * NPG journals * PubMed * Google Scholar * Robert N Hoover3, 54 Search for this author in: * NPG journals * PubMed * Google Scholar * Patricia Hartge3, 54 Search for this author in: * NPG journals * PubMed * Google Scholar * Stephen J Chanock2, 3, 54 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:224–228Year published:(2010)DOI:doi:10.1038/ng.522 Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We conducted a genome-wide association study of pancreatic cancer in 3,851 affected individuals (cases) and 3,934 unaffected controls drawn from 12 prospective cohort studies and 8 case-control studies. Based on a logistic regression model for genotype trend effect that was adjusted for study, age, sex, self-described ancestry and five principal components, we identified eight SNPs that map to three loci on chromosomes 13q22.1, 1q32.1 and 5p15.33. Two correlated SNPs, rs9543325 (P = 3.27 × 10−11, per-allele odds ratio (OR) 1.26, 95% CI 1.18–1.35) and rs9564966 (P = 5.86 × 10−8, per-allele OR 1.21, 95% CI 1.13–1.30), map to a nongenic region on chromosome 13q22.1. Five SNPs on 1q32.1 map to NR5A2, and the strongest signal was at rs3790844 (P = 2.45 × 10−10, per-allele OR 0.77, 95% CI 0.71–0.84). A single SNP, rs401681 (P = 3.66 × 10−7, per-allele OR 1.19, 95% CI 1.11–1.27), maps to the CLPTM1L-TERT locus on 5p15.33, which is associated with multiple cancer! s. Our study has identified common susceptibility loci for pancreatic cancer that warrant follow-up studies. View full text Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Gloria M Petersen, * Laufey Amundadottir, * Charles S Fuchs, * Peter Kraft, * Rachael Z Stolzenberg-Solomon, * Robert N Hoover, * Patricia Hartge & * Stephen J Chanock Affiliations * Department of Health Sciences Research, College of Medicine, Mayo Clinic, Rochester, Minnesota, USA. * Gloria M Petersen, * William R Bamlet, * Mariza de Andrade & * Robert R McWilliams * Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA. * Laufey Amundadottir, * Hemang Parikh & * Stephen J Chanock * Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department Health and Human Services, Bethesda, Maryland, USA. * Laufey Amundadottir, * Rachael Z Stolzenberg-Solomon, * Kevin B Jacobs, * Demetrius Albanes, * Amy Hutchinson, * Julie B Mendelsohn, * Hemang Parikh, * Gilles Thomas, * Geoffrey S Tobias, * Zhaoming Wang, * Kai Yu, * Joseph F Fraumeni Jr, * Robert N Hoover, * Patricia Hartge & * Stephen J Chanock * Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA. * Charles S Fuchs & * Brian M Wolpin * Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA. * Charles S Fuchs, * Edward L Giovannucci, * Susan E Hankinson, * David J Hunter & * Brian M Wolpin * Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA. * Peter Kraft, * Edward L Giovannucci, * Susan E Hankinson, * David J Hunter, * Dominique S Michaud & * Dimitrios Trichopoulos * Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA. * Peter Kraft * Core Genotyping Facility, SAIC-Frederick Inc., National Cancer Institute-Frederick, Frederick, Maryland, USA. * Kevin B Jacobs, * Amy Hutchinson & * Zhaoming Wang * Bioinformed Consulting Services, Gaithersburg, Maryland, USA. * Kevin B Jacobs * Department of Obstetrics and Gynecology, New York University School of Medicine, New York, New York, USA. * Alan A Arslan * Department of Environmental Medicine, New York University School of Medicine, New York, New York, USA. * Alan A Arslan & * Anne Zeleniuch-Jacquotte * New York University Cancer Institute, New York, New York, USA. * Alan A Arslan & * Anne Zeleniuch-Jacquotte * National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands and Department of Gastroenterology and Hepatology, University Medical Centre Utrecht, Utrecht, The Netherlands. * H Bas Bueno-de-Mesquita * Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada. * Steven Gallinger * Department of Laboratory Medicine and Pathology, School of Medicine, University of Minnesota, Minneapolis, Minnesota, USA. * Myron Gross * Prevention and Research Center, Mercy Medical Center, Baltimore, Maryland, USA. * Kathy Helzlsouer * Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA. * Elizabeth A Holly & * Paige M Bracci * Department of Epidemiology, American Cancer Society, Atlanta, Georgia, USA. * Eric J Jacobs & * Alpa V Patel * Department of Oncology, the Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. * Alison P Klein * Department of Epidemiology, Bloomberg School of Public Health, The Sol Goldman Pancreatic Research Center, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA. * Alison P Klein * Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. * Andrea LaCroix, * Margaret T Mandelson & * Charles Kooperberg * Department of Gastrointestinal Medical Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA. * Donghui Li & * Manal Hassan * Group Health Center for Health Studies, Seattle, Washington, USA. * Margaret T Mandelson * Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. * Sara H Olson * Yale University School of Public Health, New Haven, Connecticut, USA. * Harvey A Risch & * Herbert Yu * Department of Medicine and Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, Tennessee, USA. * Wei Zheng & * Xiao-Ou Shu * Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA. * Christine D Berg * Inserm, Paris-Sud University, Institut Gustave-Roussy, Villejuif, France. * Marie-Christine Boutron-Ruault * Divisions of Preventive Medicine and Aging, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA. * Julie E Buring * Department of Ambulatory Care and Prevention, Harvard Medical School, Boston, Massachusetts, USA. * Julie E Buring * German Cancer Research Center (DKFZ), Heidelberg, Germany. * Federico Canzian & * Rudolf Kaaks * Johns Hopkins Bloomberg School of Public Health, George W. Comstock Center for Public Health Research and Prevention, Hagerstown, Maryland, USA. * Sandra Clipp * Cancer Care Ontario and Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada. * Michelle Cotterchio * Catalan Institute of Oncology (ICO), Barcelona, Spain. * Eric J Duell & * Mazda Jenab * Physicians' Health Study, Divisions of Aging, Cardiovascular Disease, and Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA. * J Michael Gaziano * Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, Massachusetts, USA. * J Michael Gaziano * Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, USA. * Edward L Giovannucci * Departments of Oncology, Pathology and Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. * Michael Goggins * Department of Public Health and Clinical Medicine, Nutritional Research, Umeå University, Umeå, Sweden. * Göran Hallmans * MedStar Research Institute, Georgetown University, Hyattsville, Maryland, USA. * Barbara Howard * Nutritional Epidemiology Unit, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumoridi Milano, Milan, Italy. * Vittorio Krogh * Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. * Robert C Kurtz * Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland, USA. * Shannon M Lynch & * Daniela Seminara * Division of Epidemiology, Public Health and Primary Care, Imperial College London, London, UK. * Dominique S Michaud, * Petra H M Peeters & * Elio Riboli * Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. * Petra H M Peeters * Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. * Aleksandar Rajkovic * Public Health and Participation Directorate, Health and Health Care Services Council, Asturias, Spain. * Laudina Rodriguez * Synergie-Lyon-Cancer, Inserm, Centre Leon Berard, Lyon, Cedex, France. * Gilles Thomas * Institute of Cancer Epidemiology, Danish Cancer Society, Copenhagen, Denmark. * Anne Tjønneland * Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece. * Dimitrios Trichopoulos * Division of Research, Kaiser Permanente, Northern California Region, Oakland, California, USA. * Stephen K Van Den Eeden * Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland. * Jarmo Virtamo * Department of Social and Preventive Medicine, University at Buffalo, State University of New York, Buffalo, New York, USA. * Jean Wactawski-Wende Contributions G.M.P., L.A., C.S.F., P.K., R.Z.S.-S., K.B.J., S.M.L., J.B.M., G.S.T., R.N.H., P.H. and S.J.C. organized and designed the study. L.A., A.H., K.B.J., G.T. and S.J.C. supervised genotyping of samples. L.A., P.K., R.Z.S.-S., C.S.F., K.B.J., C.K., H.P., Z.W., K.Y., R.N.H., P.H. and S.J.C. contributed to the design and execution of statistical analysis. L.A., G.M.P., P.K., R.Z.S.-S., R.N.H., P.H. and S.J.C. wrote the first draft of the manuscript. G.M.P., C.S.F., R.Z.S.-S., A.A.A., H.B.B., S.G., M.G., K.H., E.A.H., E.J.J., A.P.K., A.L., D.L., M.T.M., S.H.O., H.A.R., W.Z., D.A., W.R.B., C.D.B., M.-C.B.-R., J.E.B., P.M.B., F.C., S.C., M.C., M.deA., E.J.D., J.M.G., E.L.G., M.G., G.H., S.E.H., M.H., B.H., D.J.H., M.J., R.K., V.K., R.C.K., R.R.M., D.S.M., A.V.P., P.H.M.P., A.R., E.R., L.R., X.-O.S., A.T., D.T., S.K.V.D.E., J.V., J.W.-W., B.M.W., H.Y., A.Z.-J. and J.F.F.Jr. conducted the epidemiologic studies and contributed samples to the PanScan GWAS and/or replication. All authors c! ontributed to the writing of the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Stephen J Chanock (chanocks@mail.nih.gov) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (732K) Supplementary Figures 1–6, Supplementary Tables 1–3 and Supplementary Note Additional data - Germline mutations in TMEM127 confer susceptibility to pheochromocytoma
Qin Y Yao L King EE Buddavarapu K Lenci RE Chocron ES Lechleiter JD Sass M Aronin N Schiavi F Boaretto F Opocher G Toledo RA Toledo SP Stiles C Aguiar RC Dahia PL - Nature genetics 42(3):229-233 (2010)
Nature Genetics | Letter Germline mutations in TMEM127 confer susceptibility to pheochromocytoma * Yuejuan Qin1 Search for this author in: * NPG journals * PubMed * Google Scholar * Li Yao1 Search for this author in: * NPG journals * PubMed * Google Scholar * Elizabeth E King1 Search for this author in: * NPG journals * PubMed * Google Scholar * Kalyan Buddavarapu1 Search for this author in: * NPG journals * PubMed * Google Scholar * Romina E Lenci1 Search for this author in: * NPG journals * PubMed * Google Scholar * E Sandra Chocron2, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * James D Lechleiter2, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Meghan Sass4 Search for this author in: * NPG journals * PubMed * Google Scholar * Neil Aronin4 Search for this author in: * NPG journals * PubMed * Google Scholar * Francesca Schiavi5 Search for this author in: * NPG journals * PubMed * Google Scholar * Francesca Boaretto5 Search for this author in: * NPG journals * PubMed * Google Scholar * Giuseppe Opocher5 Search for this author in: * NPG journals * PubMed * Google Scholar * Rodrigo A Toledo6 Search for this author in: * NPG journals * PubMed * Google Scholar * Sergio P A Toledo6 Search for this author in: * NPG journals * PubMed * Google Scholar * Charles Stiles7 Search for this author in: * NPG journals * PubMed * Google Scholar * Ricardo C T Aguiar1, 8 Search for this author in: * NPG journals * PubMed * Google Scholar * Patricia L M Dahia1, 2, 8 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:229–233Year published:(2010)DOI:doi:10.1038/ng.533 Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Pheochromocytomas, which are catecholamine-secreting tumors of neural crest origin, are frequently hereditary1. However, the molecular basis of the majority of these tumors is unknown2. We identified the transmembrane-encoding gene TMEM127 on chromosome 2q11 as a new pheochromocytoma susceptibility gene. In a cohort of 103 samples, we detected truncating germline TMEM127 mutations in approximately 30% of familial tumors and about 3% of sporadic-appearing pheochromocytomas without a known genetic cause. The wild-type allele was consistently deleted in tumor DNA, suggesting a classic mechanism of tumor suppressor gene inactivation. Pheochromocytomas with mutations in TMEM127 are transcriptionally related to tumors bearing NF1 mutations and, similarly, show hyperphosphorylation of mammalian target of rapamycin (mTOR) effector proteins. Accordingly, in vitro gain-of-function and loss-of-function analyses indicate that TMEM127 is a negative regulator of mTOR. TMEM127 dynamically ! associates with the endomembrane system and colocalizes with perinuclear (activated) mTOR, suggesting a subcompartmental-specific effect. Our studies identify TMEM127 as a tumor suppressor gene and validate the power of hereditary tumors to elucidate cancer pathogenesis. View full text Figures at a glance * Figure 1: TMEM127 localizes to the plasma membrane and cytoplasm. () Immunoblot of HEK293 cells transfected with wild-type TMEM127 tagged with the Flag epitope at the C terminus (C-Flag-TMEM127) and N terminus (N-Flag-TMEM127), and the N-tagged TMEM127 mutants M158 and M99 or empty murine stem cell virus (MSCV) retroviral vector, probed with an antibody to Flag. A translation product was not detectable from mutant constructs. β-actin was used as a loading control. () Immunoblot of 293E cells transfected with TMEM127 tagged with HA at the N terminus (HA-TMEM127) or the N-Flag-TMEM127 construct shown in , with corresponding empty vector controls, probed with an antibody to HA (left) or Flag (right). β-actin was used as a loading standard. () Confocal microscopy of HEK293T cells expressing wild-type TMEM127 tagged with Flag on the N terminus (left) or C terminus (central) or with an HA N-terminal tag (right). TMEM127 immunoreactivity determined by Flag or HA (red) is present both at the plasma membrane (left) and cytoplasm, with punctate (m! iddle and right) or perinuclear (right, arrows) signals, but is absent from the nucleus (DAPI, blue). These distinct staining patterns were observed with the various constructs in at least three independent experiments (Supplementary Fig. 4b). Plasma membrane–associated TMEM127 distribution was detected on average in 38% (± 13% (s.d.), n = 200) of cells under standard culture conditions. A similar variance in the percentage of plasma membrane–associated signal was noted for each of the constructs. * Figure 2: TMEM127 colocalizes with multiple components of the endomembrane system. (,) Confocal images of HA-TMEM127-transfected HEK293E cells fixed and immunofluorescently labeled with an antibody to the early endosome marker Rab5 (red, ) or to the Golgi marker syntaxin 6 (red, ) along with an antibody to HA (green) and DAPI (blue). Regions identified by the white-dashed rectangles are presented at higher magnification at right and below. Middle, separate presentations of the red and green channel images. Below, overlap (yellow) of red and green pixels, irrespective of their intensity. Right image shows intensity values of the product of the difference of the means (PDMs) as described in the Online Methods. The PDM intensity scale ranges from−0.5 to 0.5 in and −0.6 to 0.6 in . Optical sections are ~0.4 μm thick. Bars, 2 μm. These results are representative of multiple cells assessed in independent experiments. () HEK293E cells stably transfected with HA-TMEM127 were left untreated (top) or were cultured in the presence of a potassium-depleting buffe! r (bottom). Cells were fixed and stained with antibodies specific for HA (green) or Rab5 (red) before imaging. DAPI (blue) shows the nuclei. An increase in plasma-membrane–associated TMEM127 and control Rab5 is seen after inhibition of endocytosis promoted by this treatment. Bars, 10 μm. () HEK293E cells stably transfected with HA-TMEM127 were left untreated (top) or were exposed to ammonium chloride (bottom). Cells were fixed and stained as in (). Expansion of endosomal structures is seen both for HA-TMEM127 and Rab5. Bars, 5 μm. * Figure 3: TMEM127 modulates mTORC1 signaling in vitro and in vivo. () RAS activation measured by a RAS pull-down assay (RAS-GTP expression) of 293E cells with TMEM127 knockdown by two independent shRNA sequences (T1 and T2) or a control knockdown (C) in the absence or presence of serum. Total RAS is shown as the sample loading control. () AKT phosphorylation in TMEM127 (T1) or GFP (C) knockdown 293E cells in the presence or absence of serum; () Phosphorylation of mTORC2 target AKT in 293E cells overexpressing HA-tagged TMEM127 (TMEM127) or an empty vector (V) in the presence or absence of serum. () Effects of transient TMEM127 knockdown (T) on 4EBP1 phosphorylation in HEK293, A2058 and HeLa cells. C, GFP control knockdown. () Phosphorylation of mTORC1 targets S6K and S6 in 293E cells depleted for TMEM127 by two independent shRNA sequences (T1 and T2); C, GFP control knockdown. () Effects of TMEM127 knockdown (T1) on 4EBP1 and S6 phosphorylation in HEK293 in the presence or absence of 10% serum. C, GFP control knockdown. () Phosphorylation o! f mTORC1 targets, as above, in 293E cells expressing HA-tagged TMEM127 (TMEM127) or a control HA-empty vector (V); T-4EBP1 = total 4EBP1. () Forward scatter fluorescence-activated cell sorting (FACS) analysis of TMEM127 (T1) or control (C) knockdown in HEK293 cells. () Proliferation of TMEM127 or control knockdown 293E cells measured after addition of serum (P < 0.002, t-test). Error bars are ± s.e.m. of triplicate experiments. () S6K phosphorylation in pheochromocytoma lysates. Two normal adrenal medulla samples (NL, lanes 1 and 2) were compared with TMEM127-mutant (Mut TMEM127) samples (lanes 3, 4 and 5, corresponding to samples from families 5, 6 and 1, respectively) and four tumors with wild-type TMEM127 sequence: two sporadic- (lanes 6 and 7), one NF1-mutant- (lane 8) and one VHL-mutant tumor sample (lane 9). Densitometric measurements are shown below each lane (lane 3 was set to 1). β-actin is a loading control. * Figure 4: TMEM127 colocalizes with amino acid–activated mTORC1. () Effect of 1 h amino acid (AA) starvation, followed or not by replenishment (15 min), on S6K and S6 phosphorylation of 293E cells with TMEM127 knockdown by two independent shRNA sequences, T1 and T2. A control knockdown (C) is shown for comparison. () Effect of amino acid (AA) treatment as in on 4EBP1 and S6 phosphorylation of 293E cells overexpressing HA-TMEM127 or empty vector (EV). HA indicates TMEM127 expression. β-actin is the loading control. P-S6K, phosphorylated S6 kinase at residue T389; P-S6, phosphorylated S6 at residues S235-236; P-4EBP1, phosphorylated 4EBP1 at residues T37-46; S6K, total S6 kinase. () HEK293T cells cotransfected with HA-TMEM127 and Myc-mTOR were serum-starved overnight, depleted of amino acids for 1 h followed by re-exposure for 15 min (AA+). Cells were fixed and stained with antibodies specific for HA (green), Myc (red) or DAPI (blue) before imaging. Myc-mTOR was diffusely present in the cytoplasm in the absence of amino acid and became loc! alized to a perinuclear region where TMEM127 was detected after amino acid exposure. Similar results were obtained with two independent TMEM127 constructs. Bars, 5 μm. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE19987 Author information * Accession codes * Author information * Supplementary information Affiliations * Departments of Medicine, San Antonio, Texas, USA. * Yuejuan Qin, * Li Yao, * Elizabeth E King, * Kalyan Buddavarapu, * Romina E Lenci, * Ricardo C T Aguiar & * Patricia L M Dahia * Cellular and Structural Biology, San Antonio, Texas, USA. * E Sandra Chocron, * James D Lechleiter & * Patricia L M Dahia * Physiology, University of Texas Health Science Center, San Antonio, Texas, USA. * E Sandra Chocron & * James D Lechleiter * University of Massachusetts, Worcester, Massachusetts, USA. * Meghan Sass & * Neil Aronin * Veneto Institute of Oncology, Padova, Italy. * Francesca Schiavi, * Francesca Boaretto & * Giuseppe Opocher * University of São Paulo School of Medicine, São Paulo, Brazil. * Rodrigo A Toledo & * Sergio P A Toledo * Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA. * Charles Stiles * Cancer Therapy and Research Center at the University of Texas Health Science Center, San Antonio, Texas, USA. * Ricardo C T Aguiar & * Patricia L M Dahia Contributions Y.Q., L.Y., E.E.K., K.B., R.E.L., E.S.C., J.D.L., F.S., R.A.T., R.C.T.A. and P.L.M.D. performed and analyzed experiments. M.S., N.A., F.S., F.B., G.O., R.A.T., S.P.A.T. and C.S. contributed reagents, clinical information and discussions. R.C.T.A., J.D.L. and P.L.M.D. designed experiments. R.C.T.A. and P.L.M.D. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Patricia L M Dahia (dahia@uthscsa.edu) Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–8 and Supplementary Tables 1–7. Additional data - Common variants at 7p21 are associated with frontotemporal lobar degeneration with TDP-43 inclusions
Van Deerlin VM Sleiman PM Martinez-Lage M Chen-Plotkin A Wang LS Graff-Radford NR Dickson DW Rademakers R Boeve BF Grossman M Arnold SE Mann DM Pickering-Brown SM Seelaar H Heutink P van Swieten JC Murrell JR Ghetti B Spina S Grafman J Hodges J Spillantini MG Gilman S Lieberman AP Kaye JA Woltjer RL Bigio EH Mesulam M Al-Sarraj S Troakes C Rosenberg RN White CL Ferrer I Lladó A Neumann M Kretzschmar HA Hulette CM Welsh-Bohmer KA Miller BL Alzualde A de Munain AL McKee AC Gearing M Levey AI Lah JJ Hardy J Rohrer JD Lashley T Mackenzie IR Feldman HH Hamilton RL Dekosky ST van der Zee J Kumar-Singh S Van Broeckhoven C Mayeux R Vonsattel JP Troncoso JC Kril JJ Kwok JB Halliday GM Bird TD Ince PG Shaw PJ Cairns NJ Morris JC McLean CA Decarli C Ellis WG Freeman SH Frosch MP Growdon JH Perl DP Sano M Bennett DA Schneider JA Beach TG Reiman EM Woodruff BK Cummings J Vinters HV Miller CA Chui HC Alafuzoff I Hartikainen P Seilhean D Galasko D Masliah E Cotman CW Tuñón MT Martínez MC Munoz DG Carroll SL Marson D Riederer PF Bogdanovic N Schellenberg GD Hakonarson H Trojanowski JQ Lee VM - Nature genetics 42(3):234-239 (2010)
Nature Genetics | Letter Common variants at 7p21 are associated with frontotemporal lobar degeneration with TDP-43 inclusions * Vivianna M Van Deerlin1, 106 Search for this author in: * NPG journals * PubMed * Google Scholar * Patrick M A Sleiman2, 106 Search for this author in: * NPG journals * PubMed * Google Scholar * Maria Martinez-Lage1, 3, 106 Search for this author in: * NPG journals * PubMed * Google Scholar * Alice Chen-Plotkin1, 4, 106 Search for this author in: * NPG journals * PubMed * Google Scholar * Li-San Wang1 Search for this author in: * NPG journals * PubMed * Google Scholar * Neill R Graff-Radford5 Search for this author in: * NPG journals * PubMed * Google Scholar * Dennis W Dickson6 Search for this author in: * NPG journals * PubMed * Google Scholar * Rosa Rademakers6 Search for this author in: * NPG journals * PubMed * Google Scholar * Bradley F Boeve7 Search for this author in: * NPG journals * PubMed * Google Scholar * Murray Grossman4 Search for this author in: * NPG journals * PubMed * Google Scholar * Steven E Arnold4, 8 Search for this author in: * NPG journals * PubMed * Google Scholar * David M A Mann9 Search for this author in: * NPG journals * PubMed * Google Scholar * Stuart M Pickering-Brown9 Search for this author in: * NPG journals * PubMed * Google Scholar * Harro Seelaar10 Search for this author in: * NPG journals * PubMed * Google Scholar * Peter Heutink11 Search for this author in: * NPG journals * PubMed * Google Scholar * John C van Swieten10 Search for this author in: * NPG journals * PubMed * Google Scholar * Jill R Murrell12, 13 Search for this author in: * NPG journals * PubMed * Google Scholar * Bernardino Ghetti12, 13 Search for this author in: * NPG journals * PubMed * Google Scholar * Salvatore Spina12, 13, 14 Search for this author in: * NPG journals * PubMed * Google Scholar * Jordan Grafman15 Search for this author in: * NPG journals * PubMed * Google Scholar * John Hodges16 Search for this author in: * NPG journals * PubMed * Google Scholar * Maria Grazia Spillantini17 Search for this author in: * NPG journals * PubMed * Google Scholar * Sid Gilman18 Search for this author in: * NPG journals * PubMed * Google Scholar * Andrew P Lieberman19 Search for this author in: * NPG journals * PubMed * Google Scholar * Jeffrey A Kaye20 Search for this author in: * NPG journals * PubMed * Google Scholar * Randall L Woltjer21 Search for this author in: * NPG journals * PubMed * Google Scholar * Eileen H Bigio22, 23 Search for this author in: * NPG journals * PubMed * Google Scholar * Marsel Mesulam23 Search for this author in: * NPG journals * PubMed * Google Scholar * Safa al-Sarraj24 Search for this author in: * NPG journals * PubMed * Google Scholar * Claire Troakes25 Search for this author in: * NPG journals * PubMed * Google Scholar * Roger N Rosenberg26 Search for this author in: * NPG journals * PubMed * Google Scholar * Charles L White III27 Search for this author in: * NPG journals * PubMed * Google Scholar * Isidro Ferrer28 Search for this author in: * NPG journals * PubMed * Google Scholar * Albert Lladó29 Search for this author in: * NPG journals * PubMed * Google Scholar * Manuela Neumann30 Search for this author in: * NPG journals * PubMed * Google Scholar * Hans A Kretzschmar31 Search for this author in: * NPG journals * PubMed * Google Scholar * Christine Marie Hulette32 Search for this author in: * NPG journals * PubMed * Google Scholar * Kathleen A Welsh-Bohmer33, 34 Search for this author in: * NPG journals * PubMed * Google Scholar * Bruce L Miller35 Search for this author in: * NPG journals * PubMed * Google Scholar * Ainhoa Alzualde36 Search for this author in: * NPG journals * PubMed * Google Scholar * Adolfo Lopez de Munain37 Search for this author in: * NPG journals * PubMed * Google Scholar * Ann C McKee38, 39, 40 Search for this author in: * NPG journals * PubMed * Google Scholar * Marla Gearing41, 42, 43 Search for this author in: * NPG journals * PubMed * Google Scholar * Allan I Levey42, 43, 44 Search for this author in: * NPG journals * PubMed * Google Scholar * James J Lah44 Search for this author in: * NPG journals * PubMed * Google Scholar * John Hardy45, 46 Search for this author in: * NPG journals * PubMed * Google Scholar * Jonathan D Rohrer47 Search for this author in: * NPG journals * PubMed * Google Scholar * Tammaryn Lashley46, 48 Search for this author in: * NPG journals * PubMed * Google Scholar * Ian R A Mackenzie49, 50 Search for this author in: * NPG journals * PubMed * Google Scholar * Howard H Feldman50, 51, 52 Search for this author in: * NPG journals * PubMed * Google Scholar * Ronald L Hamilton53 Search for this author in: * NPG journals * PubMed * Google Scholar * Steven T Dekosky54 Search for this author in: * NPG journals * PubMed * Google Scholar * Julie van der Zee55, 56 Search for this author in: * NPG journals * PubMed * Google Scholar * Samir Kumar-Singh55, 56 Search for this author in: * NPG journals * PubMed * Google Scholar * Christine Van Broeckhoven55, 56 Search for this author in: * NPG journals * PubMed * Google Scholar * Richard Mayeux57 Search for this author in: * NPG journals * PubMed * Google Scholar * Jean Paul G Vonsattel57, 58, 59 Search for this author in: * NPG journals * PubMed * Google Scholar * Juan C Troncoso60, 61 Search for this author in: * NPG journals * PubMed * Google Scholar * Jillian J Kril62, 63 Search for this author in: * NPG journals * PubMed * Google Scholar * John B J Kwok64 Search for this author in: * NPG journals * PubMed * Google Scholar * Glenda M Halliday64 Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas D Bird65, 66 Search for this author in: * NPG journals * PubMed * Google Scholar * Paul G Ince67 Search for this author in: * NPG journals * PubMed * Google Scholar * Pamela J Shaw67 Search for this author in: * NPG journals * PubMed * Google Scholar * Nigel J Cairns68, 69 Search for this author in: * NPG journals * PubMed * Google Scholar * John C Morris68, 69 Search for this author in: * NPG journals * PubMed * Google Scholar * Catriona Ann McLean70 Search for this author in: * NPG journals * PubMed * Google Scholar * Charles DeCarli71 Search for this author in: * NPG journals * PubMed * Google Scholar * William G Ellis72 Search for this author in: * NPG journals * PubMed * Google Scholar * Stefanie H Freeman73, 74 Search for this author in: * NPG journals * PubMed * Google Scholar * Matthew P Frosch73, 74 Search for this author in: * NPG journals * PubMed * Google Scholar * John H Growdon74, 75 Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel P Perl76 Search for this author in: * NPG journals * PubMed * Google Scholar * Mary Sano77, 78 Search for this author in: * NPG journals * PubMed * Google Scholar * David A Bennett79 Search for this author in: * NPG journals * PubMed * Google Scholar * Julie A Schneider79 Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas G Beach80 Search for this author in: * NPG journals * PubMed * Google Scholar * Eric M Reiman81, 82 Search for this author in: * NPG journals * PubMed * Google Scholar * Bryan K Woodruff83 Search for this author in: * NPG journals * PubMed * Google Scholar * Jeffrey Cummings84 Search for this author in: * NPG journals * PubMed * Google Scholar * Harry V Vinters85, 86 Search for this author in: * NPG journals * PubMed * Google Scholar * Carol A Miller87 Search for this author in: * NPG journals * PubMed * Google Scholar * Helena C Chui87 Search for this author in: * NPG journals * PubMed * Google Scholar * Irina Alafuzoff88, 89 Search for this author in: * NPG journals * PubMed * Google Scholar * Päivi Hartikainen90 Search for this author in: * NPG journals * PubMed * Google Scholar * Danielle Seilhean91, 92 Search for this author in: * NPG journals * PubMed * Google Scholar * Douglas Galasko93 Search for this author in: * NPG journals * PubMed * Google Scholar * Eliezer Masliah93, 94 Search for this author in: * NPG journals * PubMed * Google Scholar * Carl W Cotman95 Search for this author in: * NPG journals * PubMed * Google Scholar * M Teresa Tuñón96, 97 Search for this author in: * NPG journals * PubMed * Google Scholar * M Cristina Caballero Martínez97, 98 Search for this author in: * NPG journals * PubMed * Google Scholar * David G Munoz99 Search for this author in: * NPG journals * PubMed * Google Scholar * Steven L Carroll100 Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel Marson101, 102 Search for this author in: * NPG journals * PubMed * Google Scholar * Peter F Riederer103 Search for this author in: * NPG journals * PubMed * Google Scholar * Nenad Bogdanovic104 Search for this author in: * NPG journals * PubMed * Google Scholar * Gerard D Schellenberg1 Search for this author in: * NPG journals * PubMed * Google Scholar * Hakon Hakonarson2, 105 Search for this author in: * NPG journals * PubMed * Google Scholar * John Q Trojanowski1 Search for this author in: * NPG journals * PubMed * Google Scholar * Virginia M-Y Lee1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume:42,Pages:234–239Year published:(2010)DOI:doi:10.1038/ng.536 Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Frontotemporal lobar degeneration (FTLD) is the second most common cause of presenile dementia. The predominant neuropathology is FTLD with TAR DNA-binding protein (TDP-43) inclusions (FTLD-TDP)1. FTLD-TDP is frequently familial, resulting from mutations in GRN (which encodes progranulin). We assembled an international collaboration to identify susceptibility loci for FTLD-TDP through a genome-wide association study of 515 individuals with FTLD-TDP. We found that FTLD-TDP associates with multiple SNPs mapping to a single linkage disequilibrium block on 7p21 that contains TMEM106B. Three SNPs retained genome-wide significance following Bonferroni correction (top SNP rs1990622, P = 1.08 × 10−11; odds ratio, minor allele (C) 0.61, 95% CI 0.53–0.71). The association replicated in 89 FTLD-TDP cases (rs1990622; P = 2 × 10−4). TMEM106B variants may confer risk of FTLD-TDP by increasing TMEM106B expression. TMEM106B variants also contribute to genetic risk for FTLD-TDP in in! dividuals with mutations in GRN. Our data implicate variants in TMEM106B as a strong risk factor for FTLD-TDP, suggesting an underlying pathogenic mechanism. View full text Figures at a glance * Figure 1: Region of genome-wide association at 7p21. () Manhattan plot of −log10 (observed P value) showing region of genome-wide significant association on chromosome 7. () Regional plot of the TMEM106B-associated interval. Foreground shows scatter plot of the −log10P values plotted against physical position (NCBI build 36). Background shows estimated recombination rates (from phase 2 of the HapMap analysis) plotted to reflect the local LD structure. The color of the dots represents the strength of LD between the top SNP (rs1990622) and its proxies (red, r2 ≥ 0.8; orange, 0.8 < r2 ≥ 0.4; blue, r2 < 0.4). Gene annotations were obtained from assembly 18 of the UCSC genome browser. () Location of the three most strongly associated SNPs (green arrows) relative to the gene structure of TMEM106B (blue bars, 3′ and 5′ untranslated regions; larger red bars, coding exons; thick gray line, intronic regions; gray dashed line, downstream chromosome sequence) and the location of chromosome 7. * Figure 2: TMEM106B expression variation by genotype and disease state. () TMEM106B mRNA expression by QRT-PCR in the frontal cortex differed significantly by genotype at rs1990622 (overall P = 0.027; genotype TT versus TC, P = 0.017; TT versus CC, P = 0.03). Black circles, FTLD-TDP (n = 18); open squares, unaffected (n = 7); horizontal lines, group mean. Significance of P values is denoted by the number of asterisks. () TMEM106B mRNA expression in the frontal cortex was significantly higher in samples from cases with FTLD-TDP compared to those from unaffected controls (P = 0.045). () TMEM106B expression in frontal cortex samples in FTLD-TDP cases with (GRN pos, n = 8) or without (GRN neg, n = 10) GRN mutations compared to unaffected controls (n = 7). Carriers of the GRN mutation had significantly higher levels of TMEM106B expression (overall P = 0.0009; cases with GRN mutations versus controls, P = 0.0005; cases with GRN mutations verses those without, P = 0.002). () When only cases heterozygous at rs1990622 (n = 14) were evaluated, GRN mutatio! ns remained significantly associated with a higher level of TMEM106B expression (P = 0.039) in the frontal cortex. QRT-PCR was performed in triplicate for all expression studies. Expression values were normalized to the geometric mean of two housekeeping genes and are shown here relative to a single reference control sample23. Error bars, s.e.m. Normalized gene expression data and sample genotype and gender data used for these analyses are provided in Supplementary Data 1 and 2. * Figure 3: Manhattan plot in cases with and without GRN mutations. (,) Manhattan plot of −log10 (observed P value) across the genome in cases with () and without () GRN mutations. The subset of cases with GRN mutations shows regions of genome-wide significant association on chromosomes 7 and 17. The chromosome 17 association was confirmed to be driven by a shared haplotype in carriers of the C1477T (R493X) mutation in GRN, representing ~20% of mutation-positive cases; however, the chromosome 7 association is not related to any single GRN mutation and remains when the cases with the C1477T mutation are removed from the analysis (P = 1.4 × 10−10). The same locus on chromosome 7 identified in the cases with the GRN mutation is also the strongest signal in the cases without the GRN mutation, although it does not reach genome-wide significance. A list of the SNPs with the highest signals in is given in Supplementary Table 8. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions GenBank * NM_002087.2 * NM_018374.3 Author information * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Vivianna M Van Deerlin, * Patrick M A Sleiman, * Maria Martinez-Lage & * Alice Chen-Plotkin Affiliations * Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA. * Vivianna M Van Deerlin, * Maria Martinez-Lage, * Alice Chen-Plotkin, * Li-San Wang, * Gerard D Schellenberg, * John Q Trojanowski & * Virginia M-Y Lee * The Center for Applied Genomics, Division of Human Genetics, The Children's Hospital of Philadelphia, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA. * Patrick M A Sleiman & * Hakon Hakonarson * Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain. * Maria Martinez-Lage * Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA. * Alice Chen-Plotkin, * Murray Grossman & * Steven E Arnold * Department of Neurology, Mayo College of Medicine, Jacksonville, Florida, USA. * Neill R Graff-Radford * Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA. * Dennis W Dickson & * Rosa Rademakers * Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA. * Bradley F Boeve * Department of Psychiatry and Penn Memory Center, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA. * Steven E Arnold * Mental Health and Neurodegeneration, School of Community Based Medicine, University of Manchester, Manchester, UK. * David M A Mann & * Stuart M Pickering-Brown * Erasmus Medical Centre, Rotterdam, The Netherlands. * Harro Seelaar & * John C van Swieten * Section of Medical Genomics, Department of Clinical Genetics, Vrije Universiteit Medical Center, Amsterdam, The Netherlands. * Peter Heutink * Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA. * Jill R Murrell, * Bernardino Ghetti & * Salvatore Spina * Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana, USA. * Jill R Murrell, * Bernardino Ghetti & * Salvatore Spina * Department of Neurological, Neurosurgical and Behavioral Sciences, University of Siena, Siena, Italy. * Salvatore Spina * Cognitive Neuroscience Section, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA. * Jordan Grafman * Prince of Wales Medical Research Institute, New South Wales, Australia. * John Hodges * Cambridge Centre for Brain Repair, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK. * Maria Grazia Spillantini * Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA. * Sid Gilman * Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA. * Andrew P Lieberman * Department of Neurology and Biomedical Engineering, Oregon Health and Science University, Portland, Oregon, USA. * Jeffrey A Kaye * Department of Pathology, Oregon Health and Science University, Portland, Oregon, USA. * Randall L Woltjer * Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA. * Eileen H Bigio * Cognitive Neurology and Alzheimer Disease Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA. * Eileen H Bigio & * Marsel Mesulam * Department of Clinical Neuropathology, Institute of Psychiatry, Kings College Hospital, London, UK. * Safa al-Sarraj * Medical Research Council London Neurodegenerative Diseases Brain Bank, Institute of Psychiatry, Kings College Hospital, London, UK. * Claire Troakes * Alzheimer's Disease Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA. * Roger N Rosenberg * Department of Pathology, University of Texas Southwestern Medical Center, Dallas, Texas, USA. * Charles L White III * Institut de Neuropatologia, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL)-Hospital Universitari de Bellvitge, Barcelona, Spain. * Isidro Ferrer * Alzheimer's Disease and Cognitive Disorders Unit, Service of Neurology, Institut Clinic de Neurociencies, Hospital Clínic Barcelona, Barcelona, Spain. * Albert Lladó * Institute for Neuropathology, University Hospital Zurich, Zurich, Switzerland. * Manuela Neumann * Center for Neuropathology and Prion Research, Ludwig Maximilians University, Munich, Germany. * Hans A Kretzschmar * Department of Pathology, Duke University Health Sciences Center, Durham, North Carolina, USA. * Christine Marie Hulette * Department of Psychiatry, Duke University Medical Center, Durham, North Carolina, USA. * Kathleen A Welsh-Bohmer * Bryan Alzheimer's Disease Research Center, Duke University Medical Center, Durham, North Carolina, USA. * Kathleen A Welsh-Bohmer * Department of Neurology, University of California at San Francisco, San Francisco, California, USA. * Bruce L Miller * Neurogenetic Unit, Instituto Biodonostia, San Sebastián, Spain. * Ainhoa Alzualde * Servicio de Neurología, Hospital Donostia, San Sebastián, Spain. * Adolfo Lopez de Munain * Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, USA. * Ann C McKee * Department of Pathology, Boston University School of Medicine, Boston, Massachusetts, USA. * Ann C McKee * Bedford Veterans Administration Medical Center, Geriatric Research Education and Clinical Center (GRECC), Bedford, Massachusetts, USA. * Ann C McKee * Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, Georgia, USA. * Marla Gearing * Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, Georgia, USA. * Marla Gearing & * Allan I Levey * Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, Georgia, USA. * Marla Gearing & * Allan I Levey * Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA. * Allan I Levey & * James J Lah * Reta Lila Laboratories, University College London Institute of Neurology, London, UK. * John Hardy * Department of Molecular Neuroscience, University College London Institute of Neurology, London, UK. * John Hardy & * Tammaryn Lashley * Dementia Research Centre, University College London Institute of Neurology, London, UK. * Jonathan D Rohrer * Queen Square Brain Bank for Neurological Disorders, University College London Institute of Neurology, London, UK. * Tammaryn Lashley * Department of Pathology, Vancouver General Hospital, Vancouver, Canada. * Ian R A Mackenzie * The University of British Columbia, Vancouver, Canada. * Ian R A Mackenzie & * Howard H Feldman * Division of Neurology, Vancouver General Hospital and the University of British Columbia, Vancouver, Canada. * Howard H Feldman * Neuroscience, Bristol Myers Squibb, Wallingford, Connecticut, USA. * Howard H Feldman * Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. * Ronald L Hamilton * Department of Neurology, University of Virginia School of Medicine, Charlottesville, Virginia, USA. * Steven T Dekosky * Neurodegenerative Brain Diseases Group, Department of Molecular Genetics, VIB, Antwerpen, Belgium. * Julie van der Zee, * Samir Kumar-Singh & * Christine Van Broeckhoven * Institute Born-Bunge, University of Antwerp, Antwerpen, Belgium. * Julie van der Zee, * Samir Kumar-Singh & * Christine Van Broeckhoven * Taub Institute for Research on Alzheimer's Disease, Columbia University, New York, New York, USA. * Richard Mayeux & * Jean Paul G Vonsattel * New York Brain Bank, Columbia University, New York, New York, USA. * Jean Paul G Vonsattel * Department of Pathology, Columbia University, New York, New York, USA. * Jean Paul G Vonsattel * Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. * Juan C Troncoso * Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. * Juan C Troncoso * Discipline of Medicine, University of Sydney, Sydney, New South Wales, Australia. * Jillian J Kril * Discipline of Pathology, University of Sydney, Sydney, New South Wales, Australia. * Jillian J Kril * Prince of Wales Medical Research Institute, University of New South Wales, Sydney, New South Wales, Australia. * John B J Kwok & * Glenda M Halliday * GRECC, Veteran's Affairs Puget Sound Health Care System, Seattle, Washington, USA. * Thomas D Bird * Department of Neurology, University of Washington, Seattle, Washington, USA. * Thomas D Bird * Department of Neuroscience, University of Sheffield, Sheffield, UK. * Paul G Ince & * Pamela J Shaw * Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, Missouri, USA. * Nigel J Cairns & * John C Morris * Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA. * Nigel J Cairns & * John C Morris * Department of Anatomical Pathology, The Alfred Hospital, Melbourne, Victoria, Australia. * Catriona Ann McLean * Department of Neurology, Alzheimer's Disease Center, Imaging of Dementia and Aging Laboratory, Center for Neuroscience, University of California at Davis, Sacramento, California, USA. * Charles DeCarli * Department of Pathology, University of California at Davis, Sacramento, California, USA. * William G Ellis * C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital, Boston, Massachusetts, USA. * Stefanie H Freeman & * Matthew P Frosch * Harvard Medical School, Boston, Massachusetts, USA. * Stefanie H Freeman, * Matthew P Frosch & * John H Growdon * Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA. * John H Growdon * Department of Pathology, Mount Sinai School of Medicine, New York, New York, USA. * Daniel P Perl * Department of Pyschiatry, Mount Sinai School of Medicine, New York, New York, USA. * Mary Sano * James J Peters Veteran's Affairs Medical Center, New York, New York, USA. * Mary Sano * Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA. * David A Bennett & * Julie A Schneider * Sun Health Research Institute, Sun City, Arizona, USA. * Thomas G Beach * Banner Alzheimer's Institute, Translational Genomics Research Institute, University of Arizona, Phoenix, Arizona, USA. * Eric M Reiman * Arizona Alzheimer's Consortium, Phoenix, Arizona, USA. * Eric M Reiman * Mayo Clinic Arizona, Scottsdale, Arizona, USA. * Bryan K Woodruff * Mary S. Easton Center for Alzheimer's Disease Research, David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, California, USA. * Jeffrey Cummings * Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, California, USA. * Harry V Vinters * Department of Neurology, David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, California, USA. * Harry V Vinters * Keck School of Medicine, University of Southern California, Los Angeles, California, USA. * Carol A Miller & * Helena C Chui * Department of Genetics and Pathology, Uppsala University, Uppsala, Sweden. * Irina Alafuzoff * Department of Clinical Medicine, Kuopio University, Kuopio, Finland. * Irina Alafuzoff * Department of Neurology, Kuopio University, Kuopio, Finland. * Päivi Hartikainen * Universitaire Pierre et Marie Curie Paris 06, Paris, France. * Danielle Seilhean * Assistance Publique–Hôpitaux de Paris, Paris, France. * Danielle Seilhean * Department of Neurosciences, University of California, San Diego, San Diego, California, USA. * Douglas Galasko & * Eliezer Masliah * Department of Pathology, University of California, San Diego, San Diego, California, USA. * Eliezer Masliah * Department of Neurology, University of California, Irvine, Irvine, California, USA. * Carl W Cotman * Hospital de Navarra Pathology Department, Navarra, Spain. * M Teresa Tuñón * Brain Bank of Navarra, Navarra, Spain. * M Teresa Tuñón & * M Cristina Caballero Martínez * Biomedical Research Center, Navarra Health Service-Osasunbidea, Navarra, Spain. * M Cristina Caballero Martínez * Department of Laboratory Medicine and Pathobiology, Li Ka Shing Knowledge Institute of St. Michael's Hospital, University of Toronto, Toronto, Canada. * David G Munoz * Department of Pathology, University of Alabama at Birmingham, Birmingham, Alabama, USA. * Steven L Carroll * Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA. * Daniel Marson * Alzheimer's Disease Research Center, University of Alabama at Birmingham, Birmingham, Alabama, USA. * Daniel Marson * Clinical Neurochemistry, Clinic and Policlinic of Psychiatry, Psychosomatic and Psychotherapy of the University of Wuerzburg, Wuerzburg, Germany. * Peter F Riederer * Geriatric Medicine and Neuropathology at Department of Geriatric Medicine, Karolinska University Hospital, Stockholm, Sweden. * Nenad Bogdanovic * Division of Pulmonary Medicine, Department of Pediatrics, The Children's Hospital of Philadelphia, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA. * Hakon Hakonarson Contributions V.M.V.D., P.M.A.S., M.M.-L. and A.C.-P. contributed equally to this manuscript. The overall study was designed and implemented by V.M.-Y.L., J.Q.T., V.M.V.D., H.H. and M.M.-L. and discussed with G.D.S., L.-S.W. and A.C.-P. Coordination, sample handling, DNA extraction, genetic analysis and data management were done primarily by V.M.V.D. and M.M.-L. Genotyping and additional testing, including immunohistochemical analysis, was done by P.M.A.S., H.H., V.M.V.D. or M.M.-L. Data analysis and quality control were performed by P.M.A.S., L.-S.W. and A.C.-P. and discussed and reviewed by V.M.V.D., H.H., G.D.S., V.M.-Y.L., J.Q.T. and M.M.-L. Expression analysis was designed and implemented by A.C.-P. The manuscript was prepared by A.C.-P., V.M.V.D. and P.M.A.S. and reviewed by M.M.-L., G.D.S., H.H., J.Q.T., V.M.-Y.L. and L.-S.W. The members of the International FTLD Collaboration, which includes all other authors, contributed cases, evaluated pathology, performed genetic studies and r! eviewed the manuscript. Competing financial interests A patent application on TMEM106B has been submitted. J.L. is currently involved in clinical trials involving Elan, Janssen, Medivation and Ceregene. H.F. is a full-time employee in Neuroscience Global Clinical Research and Development at Bristol-Myers Squibb from January 2009. Corresponding authors Correspondence to: * Vivianna M Van Deerlin (vivianna@mail.med.upenn.edu) or * John Q Trojanowski (trojanow@mail.med.upenn.edu) Supplementary information * Accession codes * Author information * Supplementary information Excel files * Supplementary Data 1 (16K) Raw data for the experiments shown in Figure 2a-c and Supplementary Figure 2. * Supplementary Data 2 (16K) Raw data for the experiment shown in Figure 2d. PDF files * Supplementary Text and Figures (776K) Supplementary Figures 1–4 and Supplementary Tables 1–10. Additional data - Common variants in KCNN3 are associated with lone atrial fibrillation
Ellinor PT Lunetta KL Glazer NL Pfeufer A Alonso A Chung MK Sinner MF de Bakker PI Mueller M Lubitz SA Fox E Darbar D Smith NL Smith JD Schnabel RB Soliman EZ Rice KM Van Wagoner DR Beckmann BM van Noord C Wang K Ehret GB Rotter JI Hazen SL Steinbeck G Smith AV Launer LJ Harris TB Makino S Nelis M Milan DJ Perz S Esko T Köttgen A Moebus S Newton-Cheh C Li M Möhlenkamp S Wang TJ Linda Kao WH Vasan RS Nöthen MM Macrae CA Ch Stricker BH Hofman A Uitterlinden AG Levy D Boerwinkle E Metspalu A Topol EJ Chakravarti A Gudnason V Psaty BM Roden DM Meitinger T Wichmann HE Witteman JC Barnard J Arking DE Benjamin EJ Heckbert SR Kääb S - Nature genetics 42(3):240-244 (2010)
Nature Genetics | Letter Common variants in KCNN3 are associated with lone atrial fibrillation * Patrick T Ellinor1, 2, 3, 60 Search for this author in: * NPG journals * PubMed * Google Scholar * Kathryn L Lunetta4, 5, 60 Search for this author in: * NPG journals * PubMed * Google Scholar * Nicole L Glazer6, 60 Search for this author in: * NPG journals * PubMed * Google Scholar * Arne Pfeufer7, 8, 60 Search for this author in: * NPG journals * PubMed * Google Scholar * Alvaro Alonso9, 60 Search for this author in: * NPG journals * PubMed * Google Scholar * Mina K Chung10, 60 Search for this author in: * NPG journals * PubMed * Google Scholar * Moritz F Sinner11, 60 Search for this author in: * NPG journals * PubMed * Google Scholar * Paul I W de Bakker12, 13 Search for this author in: * NPG journals * PubMed * Google Scholar * Martina Mueller11, 14, 15 Search for this author in: * NPG journals * PubMed * Google Scholar * Steven A Lubitz1, 16 Search for this author in: * NPG journals * PubMed * Google Scholar * Ervin Fox17 Search for this author in: * NPG journals * PubMed * Google Scholar * Dawood Darbar18 Search for this author in: * NPG journals * PubMed * Google Scholar * Nicholas L Smith19, 20 Search for this author in: * NPG journals * PubMed * Google Scholar * Jonathan D Smith21 Search for this author in: * NPG journals * PubMed * Google Scholar * Renate B Schnabel5 Search for this author in: * NPG journals * PubMed * Google Scholar * Elsayed Z Soliman22 Search for this author in: * NPG journals * PubMed * Google Scholar * Kenneth M Rice23 Search for this author in: * NPG journals * PubMed * Google Scholar * David R Van Wagoner10 Search for this author in: * NPG journals * PubMed * Google Scholar * Britt-M Beckmann11 Search for this author in: * NPG journals * PubMed * Google Scholar * Charlotte van Noord24, 25, 26 Search for this author in: * NPG journals * PubMed * Google Scholar * Ke Wang4 Search for this author in: * NPG journals * PubMed * Google Scholar * Georg B Ehret27, 59 Search for this author in: * NPG journals * PubMed * Google Scholar * Jerome I Rotter28 Search for this author in: * NPG journals * PubMed * Google Scholar * Stanley L Hazen10 Search for this author in: * NPG journals * PubMed * Google Scholar * Gerhard Steinbeck11 Search for this author in: * NPG journals * PubMed * Google Scholar * Albert V Smith29, 30 Search for this author in: * NPG journals * PubMed * Google Scholar * Lenore J Launer31 Search for this author in: * NPG journals * PubMed * Google Scholar * Tamara B Harris31 Search for this author in: * NPG journals * PubMed * Google Scholar * Seiko Makino1 Search for this author in: * NPG journals * PubMed * Google Scholar * Mari Nelis32, 33 Search for this author in: * NPG journals * PubMed * Google Scholar * David J Milan1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Siegfried Perz34 Search for this author in: * NPG journals * PubMed * Google Scholar * Tõnu Esko32, 33, 35 Search for this author in: * NPG journals * PubMed * Google Scholar * Anna Köttgen36 Search for this author in: * NPG journals * PubMed * Google Scholar * Susanne Moebus37 Search for this author in: * NPG journals * PubMed * Google Scholar * Christopher Newton-Cheh1, 3, 13, 38 Search for this author in: * NPG journals * PubMed * Google Scholar * Man Li36 Search for this author in: * NPG journals * PubMed * Google Scholar * Stefan Möhlenkamp39 Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas J Wang5, 38 Search for this author in: * NPG journals * PubMed * Google Scholar * W H Linda Kao36 Search for this author in: * NPG journals * PubMed * Google Scholar * Ramachandran S Vasan5, 40, 41 Search for this author in: * NPG journals * PubMed * Google Scholar * Markus M Nöthen42, 43 Search for this author in: * NPG journals * PubMed * Google Scholar * Calum A MacRae44 Search for this author in: * NPG journals * PubMed * Google Scholar * Bruno H Ch Stricker24, 26, 45, 46, 47 Search for this author in: * NPG journals * PubMed * Google Scholar * Albert Hofman24, 26 Search for this author in: * NPG journals * PubMed * Google Scholar * André G Uitterlinden24, 26, 45 Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel Levy48 Search for this author in: * NPG journals * PubMed * Google Scholar * Eric Boerwinkle49, 50 Search for this author in: * NPG journals * PubMed * Google Scholar * Andres Metspalu32, 33, 35 Search for this author in: * NPG journals * PubMed * Google Scholar * Eric J Topol51 Search for this author in: * NPG journals * PubMed * Google Scholar * Aravinda Chakravarti27 Search for this author in: * NPG journals * PubMed * Google Scholar * Vilmundur Gudnason29, 30 Search for this author in: * NPG journals * PubMed * Google Scholar * Bruce M Psaty52, 53 Search for this author in: * NPG journals * PubMed * Google Scholar * Dan M Roden54 Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas Meitinger7, 8 Search for this author in: * NPG journals * PubMed * Google Scholar * H-Erich Wichmann14, 15, 55 Search for this author in: * NPG journals * PubMed * Google Scholar * Jacqueline C M Witteman24, 26, 60 Search for this author in: * NPG journals * PubMed * Google Scholar * John Barnard56, 60 Search for this author in: * NPG journals * PubMed * Google Scholar * Dan E Arking27, 60 Search for this author in: * NPG journals * PubMed * Google Scholar * Emelia J Benjamin5, 57, 58, 60 Search for this author in: * NPG journals * PubMed * Google Scholar * Susan R Heckbert19, 53, 60 Search for this author in: * NPG journals * PubMed * Google Scholar * Stefan Kääb11, 60 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume:42,Pages:240–244Year published:(2010)DOI:doi:10.1038/ng.537 Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Atrial fibrillation (AF) is the most common sustained arrhythmia. Previous studies have identified several genetic loci associated with typical AF. We sought to identify common genetic variants underlying lone AF. This condition affects a subset of individuals without overt heart disease and with an increased heritability of AF. We report a meta-analysis of genome-wide association studies conducted using 1,335 individuals with lone AF (cases) and 12,844 unaffected individuals (referents). Cases were obtained from the German AF Network, Heart and Vascular Health Study, the Atherosclerosis Risk in Communities Study, the Cleveland Clinic and Massachusetts General Hospital. We identified an association on chromosome 1q21 to lone AF (rs13376333, adjusted odds ratio = 1.56; P = 6.3 × 10−12), and we replicated this association in two independent cohorts with lone AF (overall combined odds ratio = 1.52, 95% CI 1.40–1.64; P = 1.83 × 10−21). rs13376333 is intronic to KCNN3, wh! ich encodes a potassium channel protein involved in atrial repolarization. View full text Figures at a glance * Figure 1: Manhattan plot of meta-analysis results for genome-wide association to lone AF. The −log10(P value) is plotted against the physical positions of each SNP on each chromosome. The threshold for genome-wide significance, P < 5 × 10−8, is indicated by the dashed line. * Figure 2: Regional plot for locus on chromosome 1 associated with lone atrial fibrillation. Figures were prepared using SNAP20. SNPs are plotted with the meta-analysis P value and genomic position (NCBI Build 36). The SNP of interest is labeled. The strength of the LD is indicated by gradient of red. Blue line indicates estimated recombination rates and dark green arrows indicate gene annotations. LD and recombination rates are based on the CEU HapMap release 22. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Entrez Nucleotide * NM_002249 Author information * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Patrick T Ellinor, * Kathryn L Lunetta, * Nicole L Glazer, * Arne Pfeufer, * Alvaro Alonso, * Mina K Chung, * Moritz F Sinner, * Jacqueline C M Witteman, * John Barnard, * Dan E Arking, * Emelia J Benjamin, * Susan R Heckbert & * Stefan Kääb Affiliations * Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA. * Patrick T Ellinor, * Steven A Lubitz, * Seiko Makino, * David J Milan & * Christopher Newton-Cheh * Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, Massachusetts, USA. * Patrick T Ellinor & * David J Milan * Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA. * Patrick T Ellinor & * Christopher Newton-Cheh * Department of Biostatistics, School of Public Health, Boston University, Boston, Massachusetts, USA. * Kathryn L Lunetta & * Ke Wang * National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Massachusetts, USA. * Kathryn L Lunetta, * Renate B Schnabel, * Thomas J Wang, * Ramachandran S Vasan & * Emelia J Benjamin * Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA. * Nicole L Glazer * Institute of Human Genetics, Klinikum Rechts der Isar Technische Universität München, Munich, Germany. * Arne Pfeufer & * Thomas Meitinger * Institute of Human Genetics, Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt, Neuherberg, Germany. * Arne Pfeufer & * Thomas Meitinger * Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA. * Alvaro Alonso * Department of Cardiovascular Medicine, Heart and Vascular Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA. * Mina K Chung, * David R Van Wagoner & * Stanley L Hazen * Department of Medicine I, University Hospital Grosshadern, Ludwig-Maximilians-Universität, Munich, Germany. * Moritz F Sinner, * Martina Mueller, * Britt-M Beckmann, * Gerhard Steinbeck & * Stefan Kääb * Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA. * Paul I W de Bakker * Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Paul I W de Bakker & * Christopher Newton-Cheh * Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. * Martina Mueller & * H-Erich Wichmann * Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany. * Martina Mueller & * H-Erich Wichmann * Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA. * Steven A Lubitz * Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, USA. * Ervin Fox * Division of Cardiovascular Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA. * Dawood Darbar * Department of Epidemiology, University of Washington, Seattle, Washington, USA. * Nicholas L Smith & * Susan R Heckbert * Seattle Epidemiologic Research and Information Center of the Department of Veterans Affairs Office of Research and Development, Seattle, Washington, USA. * Nicholas L Smith * Department of Cell Biology, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA. * Jonathan D Smith * Epidemiological Cardiology Research Center (EPICARE), Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA. * Elsayed Z Soliman * Department of Biostatistics, University of Washington, Seattle, Washington, USA. * Kenneth M Rice * Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands. * Charlotte van Noord, * Bruno H Ch Stricker, * Albert Hofman, * André G Uitterlinden & * Jacqueline C M Witteman * Dutch Medicines Evaluation Board, The Hague, The Netherlands. * Charlotte van Noord * Netherlands Consortium on Healthy Aging (NCHA), Leiden, The Netherlands. * Charlotte van Noord, * Bruno H Ch Stricker, * Albert Hofman, * André G Uitterlinden & * Jacqueline C M Witteman * McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. * Georg B Ehret, * Aravinda Chakravarti & * Dan E Arking * Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA. * Jerome I Rotter * Icelandic Heart Association, Kópavogur, Iceland. * Albert V Smith & * Vilmundur Gudnason * University of Iceland, Reykjavik, Iceland. * Albert V Smith & * Vilmundur Gudnason * Laboratory of Epidemiology, Demography and Biometry, Intramural Research Program, National Institute on Aging, Bethesda, Maryland, USA. * Lenore J Launer & * Tamara B Harris * Estonian Biocenter, Genotyping Core Facility, Tartu, Estonia. * Mari Nelis, * Tõnu Esko & * Andres Metspalu * Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia. * Mari Nelis, * Tõnu Esko & * Andres Metspalu * Institute for Biological and Medical Imaging, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. * Siegfried Perz * Estonian Genome Center, University of Tartu, Tartu, Estonia. * Tõnu Esko & * Andres Metspalu * Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland, USA. * Anna Köttgen, * Man Li & * W H Linda Kao * Institute of Medical Informatics, Biometry and Epidemiology, University Duisburg-Essen, Essen, Germany. * Susanne Moebus * Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA. * Christopher Newton-Cheh & * Thomas J Wang * Department of Cardiology, West German Heart Center Essen, University Duisburg-Essen, Essen, Germany. * Stefan Möhlenkamp * Section of Preventive Medicine, Boston University School of Medicine, Boston, Massachusetts, USA. * Ramachandran S Vasan * Section of Cardiology, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USA. * Ramachandran S Vasan * Institute of Human Genetics, University of Bonn, Bonn, Germany. * Markus M Nöthen * Department of Genomics, Life and Brain Center Bonn, Bonn, Germany. * Markus M Nöthen * Cardiovascular Division, Brigham and Woman's Hospital, Boston, Massachusetts, USA. * Calum A MacRae * Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands. * Bruno H Ch Stricker & * André G Uitterlinden * Inspectorate for Health Care, The Hague, The Netherlands. * Bruno H Ch Stricker * Department of Medical Informatics, Erasmus Medical Center, Rotterdam, The Netherlands. * Bruno H Ch Stricker * Center for Population Studies, National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA. * Daniel Levy * Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas, USA. * Eric Boerwinkle * Institute for Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, USA. * Eric Boerwinkle * Scripps Translational Science Institute, The Scripps Research Institute, Scripps Health, La Jolla, California, USA. * Eric J Topol * Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, Washington, USA. * Bruce M Psaty * Group Health Research Institute, Group Health, Seattle, Washington, USA. * Bruce M Psaty & * Susan R Heckbert * Division of Clinical Pharmacology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA. * Dan M Roden * Klinikum Grosshadern, Munich, Germany. * H-Erich Wichmann * Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA. * John Barnard * Department of Epidemiology, School of Public Health, Boston University, Boston, Massachusetts, USA. * Emelia J Benjamin * Cardiology and Preventive Medicine Division, Evans Department of Medicine, Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, Massachusetts. * Emelia J Benjamin * Present address: Cardiology Center, Geneva University Hospital, Geneva, Switzerland. * Georg B Ehret Contributions P.T.E., K.L.L., N.L.G., A.P., M.K.C., A.A., J.C.M.W., D.E.A., E.J.B., S.R.H. and S.K. Acquisition of data: P.T.E., K.L.L., N.L.G., A.P., A.A., M.K.C., M.F.S., P.I.W.d.B., M.M., S.A.L., E.F., D.D., N.L.S., J.D.S., R.B.S., E.Z.S., K.M.R., D.R.V.W., B.-M.B, C.v.N., K.W., G.B.E., J.I.R., S.L.H., G.S., A.V.S., L.J.L., T.B.H., S.M., M.N., D.J.M., S.P., T.E., S.M., C.N.-C., M.L., S.M., K.W., T.J.W., W.H.L.K., E.B., V.G., B.M.P., J.C.M.W., J.B., D.E.A., E.J.B., S.R.H. and S.K. K.L.L., N.L.G., A.P., M.M., J.B., D.E.A. and K.W. P.T.E., K.L.L., E.J.B., S.R.H. and S.K. K.L.L., N.L.G., A.P., A.A., M.K.C., M.F.S., P.I.W.d.B., M.M., S.A.L., E.F., D.D., N.L.S., J.D.S., R.B.S., E.Z.S., K.M.R., D.R.V.W., B.-M.B., C.v.N., K.W., G.B.E., S.L.H., G.S., A.V.S., L.J.L., T.B.H., S.M., M.M.N., D.J.M., S.P., T.E., A.K., S.M., C.N.-C., M.L., S.M.,T.J.W., W.H.L.K., R.S.V., M.N., C.A.M., B.H.C.S., A.H., A.G.U., D.L., E.B., A.M., E.J.T., A.C., V.G., B.M.P., D.M.R., T.M., H.-E.W., J.C.M.W., J.B., D.E.A., E.J.B. and S.R.H. K.L.L., N.L.G., A.P., M.M., J.B., D.E.A. and K.W. P.T.E., A.P., A.A., M.K.C., M.F.S., P.I.W.d.B., M.M., S.A.L., E.F., N.L.S., J.D.S., K.M.R., D.R.V.W., J.I.R., S.L.H., S.M., B.H.Ch.S., A.H., A.G.U., D.L., E.B., A.M., E.J.T., A.C., V.G., B.M.P., D.M.R., T.M., J.C.M.W., J.B., D.E.A., E.J.B., S.R.H. and S.K. P.T.E., K.L.L., N.L.G., A.P., A.A., M.K.C., M.F.S., J.C.M.W., J.B., D.E.A., E.J.B., S.R.H. and S.K. P.T.E., K.L.L., N.L.G., A.P., A.A., M.K.C., M.F.S., J.C.M.W., J.B., D.E.A., E.J.B., S.R.H. and S.K. had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Competing financial interests A.C. is a paid member of the Scientific Advisory Board of Affymetrix, a role that is managed by the Committee on Conflict of Interest of the Johns Hopkins University School of Medicine. Corresponding authors Correspondence to: * Patrick T Ellinor (pellinor@partners.org) or * Stefan Kääb (stefan.kaab@med.uni-muenchen.de) Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Note, Supplementary Tables 1–3 and Supplementary Figures 1 and 2 Additional data - Mutations in PNKP cause microcephaly, seizures and defects in DNA repair
- Nature genetics 42(3):245-249 (2010)
Nature Genetics | Letter Mutations in PNKP cause microcephaly, seizures and defects in DNA repair * Jun Shen1, 12 Search for this author in: * NPG journals * PubMed * Google Scholar * Edward C Gilmore2, 3, 12 Search for this author in: * NPG journals * PubMed * Google Scholar * Christine A Marshall1 Search for this author in: * NPG journals * PubMed * Google Scholar * Mary Haddadin4, 11 Search for this author in: * NPG journals * PubMed * Google Scholar * John J Reynolds5 Search for this author in: * NPG journals * PubMed * Google Scholar * Wafaa Eyaid6 Search for this author in: * NPG journals * PubMed * Google Scholar * Adria Bodell1 Search for this author in: * NPG journals * PubMed * Google Scholar * Brenda Barry1 Search for this author in: * NPG journals * PubMed * Google Scholar * Danielle Gleason2 Search for this author in: * NPG journals * PubMed * Google Scholar * Kathryn Allen1 Search for this author in: * NPG journals * PubMed * Google Scholar * Vijay S Ganesh1 Search for this author in: * NPG journals * PubMed * Google Scholar * Bernard S Chang1 Search for this author in: * NPG journals * PubMed * Google Scholar * Arthur Grix7 Search for this author in: * NPG journals * PubMed * Google Scholar * R Sean Hill2 Search for this author in: * NPG journals * PubMed * Google Scholar * Meral Topcu8 Search for this author in: * NPG journals * PubMed * Google Scholar * Keith W Caldecott5 Search for this author in: * NPG journals * PubMed * Google Scholar * A James Barkovich9 Search for this author in: * NPG journals * PubMed * Google Scholar * Christopher A Walsh1, 2, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:245–249Year published:(2010)DOI:doi:10.1038/ng.526 Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Maintenance of DNA integrity is crucial for all cell types, but neurons are particularly sensitive to mutations in DNA repair genes, which lead to both abnormal development and neurodegeneration1. We describe a previously unknown autosomal recessive disease characterized by microcephaly, early-onset, intractable seizures and developmental delay (denoted MCSZ). Using genome-wide linkage analysis in consanguineous families, we mapped the disease locus to chromosome 19q13.33 and identified multiple mutations in PNKP (polynucleotide kinase 3′-phosphatase) that result in severe neurological disease; in contrast, a splicing mutation is associated with more moderate symptoms. Unexpectedly, although the cells of individuals carrying this mutation are sensitive to radiation and other DNA-damaging agents, no such individual has yet developed cancer or immunodeficiency. Unlike other DNA repair defects that affect humans, PNKP mutations universally cause severe seizures. The neurologi! cal abnormalities in individuals with MCSZ may reflect a role for PNKP in several DNA repair pathways. View full text Figures at a glance * Figure 1: Pedigrees of MCSZ families. Family 1 represents a consanguineous Palestinian pedigree in Jordan. Family 2 shows another consanguineous Palestinian pedigree that is reportedly unrelated to family 1, also in Jordan. Family 3 is also consanguineous and Palestinian, but the family now resides in the United States. Family 4 is from the Kingdom of Saudi Arabia, and the parents were not known to be consanguineous. Family 5 is from Turkey, and the parents were not known to be related. Family 6 is of mixed European descent from the United States (German-Irish). Family 7 is also of mixed European (Swedish, Italian, Irish and English) heritage, from the United States. The individuals from whom samples were obtained are indicated by the label 'DNA'. The individuals from whom we established lymphoid cell lines are indicated by the label 'Cells'. Cells and DNA were available for all members of family 7. * Figure 2: Brain MRIs of individuals with MCSZ. Representative MRI images are shown from families 4 (; severely affected) and 7 (; moderately affected) with aged-matched controls. MRIs of severely affected individuals from other families were similar to the representative images in . Sagittal images are shown on the left (T1), axial images in the middle (T2) and coronal images on the right (T2 () and FLAIR ()), with the MRI sequence noted above the image. The MRIs show that, despite the microencephaly (small brain), the gyral pattern is not clearly abnormal, indicating an absence of visible neuronal migration abnormality. The cerebellum is proportionately small compared to the cerebrum, and the subpallium (basal ganglia or ventral cerebrum) is proportionate to the pallium (dorsal cerebrum). There is no evidence of atrophy or glial scarring. Scale bar indicates 5 cm for both unaffected and MCSZ images. * Figure 3: PNKP mutations in individuals with MCSZ. () The diagram shows four different mutations identified in human PNKP genomic DNA, mRNA and protein, including protein domains (forkhead is indicated by 'FHA'). The human PNKP gene consists of 17 exons (boxes) and encodes a peptide of 521 amino acids. Filled boxes represent untranslated regions and open boxes represent coding regions. Lines connecting the exons represent introns. () Protein blot for PNKP. Lanes 1 and 2 show samples from an individual with MCSZ (VI:3 with the E326K mutation) and an unaffected brother (VI:1), respectively, from family 3. Lanes 3 and 4 represent individuals with MCSZ (II:1 and II:4, with both a 17-bp duplication (dup) and a 17-bp intron 15 deletion (del)) from family 7. In contrast, lanes 5 and 6 represent the father (I:1) and brother (II:3) from this family, who are both heterozygous for the 17-bp intron 15 del. The band indicates a molecular weight of ~60 kDa (predicted size 57 kDa). Anti–β-actin is a loading control. () RT-PCR products o! f mRNA from members of family 7 show the expected size from the normal copy of PNKP cDNA (636 bp), seen in lanes 3 and 4 from unaffected carriers. The 17-bp dup results in a 653-bp fragment, seen in lanes 1, 2 and 3. The band in lanes 1, 2 and 4 corresponding to a size of 548 bp is found in samples with the intron 15 deletion lacking exon 15 (determined from sequencing; data not shown). A small amount of normal-sized transcript is seen in lanes 1 and 2 with higher exposure (data not shown), indicating that a small amount of normal PNKP mRNA can be produced. * Figure 4: Lymphocytes from individuals with MCSZ show abnormal DNA repair. () Examples of comet assay results. The intensity of the fluorescence is represented in pseudocolor, as the electrical field drives damaged, loose DNA from left to right. The image at left shows a cell with 50% tail DNA with the body of the nucleus (green) on the left and the tail of the comet derived from the damaged DNA extending to the right. The images middle and right show progressively less damage, with 29% and 11% tail DNA, respectively. () After hydrogen peroxide treatment with 0 min for recovery, cells show their maximum damage. Cells derived from individuals with MCSZ (blue and red) show significant impairment in their ability to repair DNA after hydrogen peroxide was removed, whereas cells derived from unaffected family members were able to repair DNA much more efficiently. () After camptothecin (CPT) treatment, there was also statistically significantly slower repair in cells derived from individuals with MCSZ compared with those from unaffected family members (g! reen and purple). However, after 45 min, the MCSZ-derived cells were able to repair all CPT damage, in contrast to hydrogen peroxide–treated cells. All cells were derived from family 7. Blue diamonds and red squares indicate cells from individuals with MCSZ carrying the exon 14 17-bp duplication and the intron 15 17-bp deletion (II:1 and II:4, respectively); green triangles represent an unaffected parent who is heterozygous for the intron 15 17-bp deletion (I:1); purple crosses represent an unaffected sibling with no mutation (II:2). *P = 0.05; **P < 0.005; ***P < 0.0005. Scale bar, 50 μm. * Figure 5: PNKP in situ hybridization. (,) In situ hybridization of Carnegie Stage 22 human embryos (~54 postovulatory days) with an antisense probe to human PNKP (). The sense strand (not shown) showed no specific hybridization. A higher-magnification image of the boxed area in the developing cerebral cortex is shown (). The ventricular zone (VZ), containing proliferating cells, shows PNKP mRNA expression, whereas the cell-sparse marginal zone (MZ) has no staining. (,) Mouse embryonic day 14 cerebral cortex () (with high-magnification view of the boxed region ()) shows a similar staining pattern, with high expression within the proliferating VZ and lower but maintained expression within differentiated neurons of the cortical plate (CP). and are in the transverse plane, and and are coronal. Scale bars indicate 1 mm (), 100 μm (), 150 μm () and 75 μm (). Author information * Author information * Supplementary information Primary authors * These authors contributed equally to the work. * Jun Shen & * Edward C Gilmore Affiliations * Howard Hughes Medical Institute, Department of Neurology, Beth Israel Deaconess Medical Center and Program in Neuroscience, Harvard Medical School, Boston, Massachusetts, USA. * Jun Shen, * Christine A Marshall, * Adria Bodell, * Brenda Barry, * Kathryn Allen, * Vijay S Ganesh, * Bernard S Chang & * Christopher A Walsh * Division of Genetics and The Manton Center for Orphan Disease Research, Department of Medicine, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts, USA. * Edward C Gilmore, * Danielle Gleason, * R Sean Hill & * Christopher A Walsh * Division of Child Neurology, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA. * Edward C Gilmore * Department of Pathology, Cytogenetics Laboratory, Al-Bashir Hospital, Ministry of Health, Amman, Jordan. * Mary Haddadin * Genome Damage and Stability Centre, University of Sussex, Falmer, Brighton, UK. * John J Reynolds & * Keith W Caldecott * Genetics & Endocrinology, Department of Pediatrics, King Fahad National Guard Hospital, King Abdul Aziz Medical City, Saudi Arabia. * Wafaa Eyaid * Department of Medical Genetics, Kaiser-Permanente Point West Medical Offices, Sacramento, California, USA. * Arthur Grix * Hacettepe University, Medical Faculty, Ihsan Dogramaci Children's Hospital, Department of Pediatrics, Section of Pediatric Neurology, Ankara, Turkey. * Meral Topcu * Department of Radiology, Department of Neurology and Department of Pediatrics, University of California at San Francisco, San Francisco, California, USA. * A James Barkovich * Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, USA. * Christopher A Walsh * Present address: Quest Diagnostics, Nichols Institute, San Juan Capistrano, California, USA. * Mary Haddadin Contributions J.S. helped to characterize MCSZ syndrome, identified the MCSZ locus and calculated lod scores, sequenced genes in the MCSZ locus to identify PNKP mutations and wrote the manuscript; E.C.G. helped to characterize MCSZ syndrome, identified the moderately affected MCSZ family, performed RT-PCR on moderately affected family samples, performed comet assays, organized and analyzed Sequenom experiments, did analysis of PNKP mutation, performed mouse RNAi experiments, helped perform mouse in situ hybridizations and wrote the manuscript; C.A.M. sequenced genes in the MCSZ locus to identify PNKP mutations and helped perform human in situ hybridizations; M.H. identified affected patients and provided clinical information; J.J.R. performed PNKP protein blots and confirmatory comet assays; W.E. identified affected patients and provided clinical information; A.B. organized clinical information and patient samples; B.B. organized clinical information and patient samples; D.G. organized pa! tient samples and helped perform Sequenom experiments; K.A. organized patient samples and helped perform sequencing experiments; V.S.G. helped analyze Sequenom experiments; B.S.C. helped organize clinical information to identify MCSZ syndrome; A.G. identified affected patients and provided clinical information; R.S.H. helped organize genetic data and calculate lod scores; M.T. identified affected patients and provided clinical information; K.W.C. advised on comet assays, supervised PNKP protein blotting and edited the manuscript; A.J.B. characterized MRIs for patient classification; C.A.W. directed the overall research and wrote the manuscript. The genetic study was approved by Beth Israel Deaconess Medical Center and Children's Hospital Boston Institutional Review Boards. Appropriate informed consent was obtained from all involved human subjects. All animal work was approved by Harvard Medical School, Beth Israel Deaconess Medical Center and Children's Hospital Boston Institutional Animal Care and Use Committees. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Christopher A Walsh (Christopher.Walsh@childrens.harvard.edu) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–7, Supplementary Tables 1–4 and Supplementary Note Additional data - Genome-wide association mapping identifies multiple loci for a canine SLE-related disease complex
- Nature genetics 42(3):250-254 (2010)
Nature Genetics | Letter Genome-wide association mapping identifies multiple loci for a canine SLE-related disease complex * Maria Wilbe1 Search for this author in: * NPG journals * PubMed * Google Scholar * Päivi Jokinen2, 9 Search for this author in: * NPG journals * PubMed * Google Scholar * Katarina Truvé1, 9 Search for this author in: * NPG journals * PubMed * Google Scholar * Eija H Seppala2 Search for this author in: * NPG journals * PubMed * Google Scholar * Elinor K Karlsson3, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Tara Biagi3 Search for this author in: * NPG journals * PubMed * Google Scholar * Angela Hughes5 Search for this author in: * NPG journals * PubMed * Google Scholar * Danika Bannasch6 Search for this author in: * NPG journals * PubMed * Google Scholar * Göran Andersson1 Search for this author in: * NPG journals * PubMed * Google Scholar * Helene Hansson-Hamlin7, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Hannes Lohi2, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Kerstin Lindblad-Toh3, 8, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:250–254Year published:(2010)DOI:doi:10.1038/ng.525 Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The unique canine breed structure makes dogs an excellent model for studying genetic diseases. Within a dog breed, linkage disequilibrium is extensive1, 2, enabling genome-wide association (GWA) with only around 15,000 SNPs and fewer individuals than in human studies1, 3. Incidences of specific diseases are elevated in different breeds, indicating that a few genetic risk factors might have accumulated through drift or selective breeding. In this study, a GWA study with 81 affected dogs (cases) and 57 controls from the Nova Scotia duck tolling retriever breed identified five loci associated with a canine systemic lupus erythematosus (SLE)–related disease complex that includes both antinuclear antibody (ANA)–positive immune-mediated rheumatic disease (IMRD) and steroid-responsive meningitis-arteritis (SRMA). Fine mapping with twice as many dogs validated these loci. Our results indicate that the homogeneity of strong genetic risk factors within dog breeds allows multigenic! disorders to be mapped with fewer than 100 cases and 100 controls, making dogs an excellent model in which to identify pathways involved in human complex diseases. View full text Figures at a glance * Figure 1: Genome-wide association identified five loci associated with a canine SLE-related disease. () Genome-wide association of all cases together showed one strong peak on chromosome 32. () For ANA-positive IMRD dogs, four highly associated regions were found (canine chromosomes 3, 8, 11 and 24), with chromosomes 8 and 24 reaching genome-wide significance. () SRMA dogs showed one region of genome-wide significance on chromosome 32. * Figure 2: Fine mapping and validation of three risk loci for ANA-positive IMRD. (–) The strongest associations were found on chromosomes Cfa 11 (), Cfa 24 () and Cfa 3 (). Plots show haplotype (dark blue dots, with lines connecting SNPs on the same haplotype) and single SNP (black dots) associations in NSDTRs. * Figure 3: The Cfa32 locus confers risk to multiple subphenotypes. (–) A 1.6-Mb region was defined where ANA-positive IMRD dogs (), SRMA-affected dogs () and all cases together () show association. This region might reflect a common locus involved in all phenotypes or could contain multiple separate risk factors. The region is potentially composed of three separate associated peaks, where the leftmost peak is most strongly associated in all three analyses. Plots show haplotype (dark blue dots, with lines connecting SNPs on the same haplotype) and single SNP (black dots) associations in NSDTRs. * Figure 4: The products of four of the candidate genes are involved in T-cell activation through the NF-AT pathway. PPP3CA is activated by the influx of calcium, which in turn results in the activation of the transcription factor NF-AT. PPP3CA is also reported to be the target of the immunosuppressive drugs cyclosporine A and FK506. HOMER2 competes with PPP3CA for binding to NF-AT, which acts as a negative regulator of T-cell activation. Both DAPP1 and PTPN3 inhibit T-cell activation through the TCR and reduce activation of reporter genes driven by NF-AT. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to the manuscript. * Päivi Jokinen & * Katarina Truvé Affiliations * Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Biomedical Centre, Uppsala, Sweden. * Maria Wilbe, * Katarina Truvé & * Göran Andersson * Department of Veterinary Biosciences, Department of Medical Genetics, Program in Molecular Medicine, Folkhälsan Institute of Genetics, Biomedicum Helsinki, University of Helsinki, Helsinki, Finland. * Päivi Jokinen, * Eija H Seppala & * Hannes Lohi * Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Elinor K Karlsson, * Tara Biagi & * Kerstin Lindblad-Toh * FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, USA. * Elinor K Karlsson * Department of Animal Science, University of California, Davis, California, USA. * Angela Hughes * Department of Population Health and Reproduction, University of California, Davis, School of Veterinary Medicine, Davis, California, USA. * Danika Bannasch * Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden. * Helene Hansson-Hamlin * Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden. * Kerstin Lindblad-Toh * These authors jointly directed the work. * Helene Hansson-Hamlin, * Hannes Lohi & * Kerstin Lindblad-Toh Contributions K.L.-T., H.H.-H., G.A. and H.L. conceived the study. H.H.-H., H.L., M.W., P.J., D.B. and A.H. were responsible for collection of field material. H.H.-H. was responsible for phenotypic characterization of the field material. K.L.-T. was responsible for designing the GWA and fine-mapping experiments with input from H.L., G.A. and M.W. M.W., K.T., P.J. and E.H.S. were responsible for the GWA analysis. M.W., T.B. and E.K.K. carried out the fine-mapping analysis. K.L.-T. directed the study with input from H.H.-H., G.A. and H.L. K.L.-T., M.W., K.T. and G.A. were responsible for preparation of the manuscript with input from the other authors. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Kerstin Lindblad-Toh (kersli@broadinstitute.org) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (568K) Supplementary Table 1 and Supplementary Figures 1 and 2 Additional data - A map of open chromatin in human pancreatic islets
- Nature genetics 42(3):255-259 (2010)
Nature Genetics | Letter A map of open chromatin in human pancreatic islets * Kyle J Gaulton1, 11 Search for this author in: * NPG journals * PubMed * Google Scholar * Takao Nammo2, 3, 11 Search for this author in: * NPG journals * PubMed * Google Scholar * Lorenzo Pasquali2, 3, 11 Search for this author in: * NPG journals * PubMed * Google Scholar * Jeremy M Simon1, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Paul G Giresi4 Search for this author in: * NPG journals * PubMed * Google Scholar * Marie P Fogarty1 Search for this author in: * NPG journals * PubMed * Google Scholar * Tami M Panhuis1 Search for this author in: * NPG journals * PubMed * Google Scholar * Piotr Mieczkowski1 Search for this author in: * NPG journals * PubMed * Google Scholar * Antonio Secchi5 Search for this author in: * NPG journals * PubMed * Google Scholar * Domenico Bosco6 Search for this author in: * NPG journals * PubMed * Google Scholar * Thierry Berney6 Search for this author in: * NPG journals * PubMed * Google Scholar * Eduard Montanya3, 7 Search for this author in: * NPG journals * PubMed * Google Scholar * Karen L Mohlke1, 8, 9 Search for this author in: * NPG journals * PubMed * Google Scholar * Jason D Lieb4, 8, 9 Search for this author in: * NPG journals * PubMed * Google Scholar * Jorge Ferrer2, 3, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume:42,Pages:255–259Year published:(2010)DOI:doi:10.1038/ng.530 Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Tissue-specific transcriptional regulation is central to human disease1. To identify regulatory DNA active in human pancreatic islets, we profiled chromatin by formaldehyde-assisted isolation of regulatory elements2, 3, 4 coupled with high-throughput sequencing (FAIRE-seq). We identified ~80,000 open chromatin sites. Comparison of FAIRE-seq data from islets to that from five non-islet cell lines revealed ~3,300 physically linked clusters of islet-selective open chromatin sites, which typically encompassed single genes that have islet-specific expression. We mapped sequence variants to open chromatin sites and found that rs7903146, a TCF7L2 intronic variant strongly associated with type 2 diabetes5, is located in islet-selective open chromatin. We found that human islet samples heterozygous for rs7903146 showed allelic imbalance in islet FAIRE signals and that the variant alters enhancer activity, indicating that genetic variation at this locus acts in cis with local chromati! n and regulatory changes. These findings illuminate the tissue-specific organization of cis-regulatory elements and show that FAIRE-seq can guide the identification of regulatory variants underlying disease susceptibility. View full text Figures at a glance * Figure 1: FAIRE-seq in human pancreatic islets. () Chromatin is cross-linked using formaldehyde, sonicated and subjected to phenol-chloroform extraction. DNA fragments recovered in the aqueous phase are then sequenced. () Reads obtained from sequencing were highly concordant with FAIRE signals obtained from tiling microarrays covering the ENCODE pilot project regions (FAIRE-chip). Arrows indicate the direction of gene transcription. * Figure 2: Both proximal and distal FAIRE sites harbor functional regulatory elements. () Genes with high expression in islets (top 20%, red) have more FAIRE enrichment at promoters than genes with moderate (middle 20%, green) or low (bottom 20%, blue) expression. () Promoters (−750 to +250 bp) bound by RNA polymerase II, HNF4A or HNF1A in human islets11 are significantly over-represented among islet FAIRE sites (red dash indicates expected value; all bars, P < 0.001). () Intergenic islet-selective and ubiquitous FAIRE sites that are located >2 kb from a TSS are enriched for evolutionarily conserved sequences (P < 0.001), predicted regulatory modules (PreMod, P < 0.001) and transcription factor binding sites (conserved TFBS and MotifMap, both P < 0.001). CTCF binding, however, is enriched in ubiquitous FAIRE sites only. Over half of intergenic open chromatin sites are coincident with an experimentally or computationally determined functional annotation (expected value for random sites, 27%). () Open chromatin is most enriched directly at sites of experimenta! lly determined CTCF binding. () In contrast to ubiquitous FAIRE sites, islet-selective FAIRE sites are rarely located within 2 kb upstream of a TSS or in the first exon of a gene but are instead located predominantly in more distal regions. Shown is the percentage of bases covered by each annotation category in islet-selective FAIRE sites (blue), ubiquitous FAIRE sites (red) and the mappable genome (gray). * Figure 3: Islet-selective FAIRE sites form clusters of open regulatory elements (COREs). () FAIRE sites are highly clustered. We divided the genome in windows of varying size (x axis) and calculated a χ2 statistic to determine if the number of windows with 0, 1 or >1 FAIRE sites differed from randomly distributed sites. The highest significance was observed in ~20 kb windows. () Same procedure as in but for islet-selective sites. () We defined islet-selective clusters of open chromatin regulatory elements (COREs) as three or more islet-selective FAIRE sites separated from each other by <20 kb. () We identified 3,348 islet-selective COREs (blue points). Fewer COREs were generated using randomized FAIRE sites (orange points) and they were smaller than in vivo COREs. () Most islet-selective COREs were associated with a single gene. () RefSeq genes associated with islet-selective COREs were on average inactive in non-islet human tissues, except for brain tissue. Asterisks indicate P < 1 × 10−5 (one-way ANOVA). a.u., arbitrary units. () Chromatin landscape of the! PDX1 locus showing an extended cluster of islet-selective FAIRE sites, contrasting with a closed conformation of the adjacent gut-specific homeodomain gene CDX2. Top, the density of FAIRE-seq reads centered on the genomic average density value, the location of moderate stringency FAIRE sites in islets (blue) or in any of the five non-islet cells (red), and the binding sites of the CTCF insulator protein in K562 cells. CTCF sites demarcate regions that show broadly consistent FAIRE-seq enrichment patterns. Bottom, a closer view of a portion of the PDX1 islet-selective CORE, with islet-selective open chromatin sites at previously characterized regulatory elements (area I–III and area IV) and in an evolutionarily conserved putative enhancer. * Figure 4: Allele-specific open chromatin and enhancer activity at the TCF7L2 locus. () Schematic representation of how FAIRE-seq enables the identification of human sequence variants located in islet open chromatin. From ~4 million SNPs present in dbSNP with average heterozygosity >1%, 38 SNPs associated with T2D or fasting glycemia mapped to islet open chromatin sites. The analysis was carried out with all SNPs in strong linkage disequilibrium (r2 > 0.8) with a fasting glycemia- or T2D-associated variant, which are labeled as FG or T2D SNPs, and FAIRE-seq sites identified with a liberal threshold. () Among TCF7L2 variants in linkage disequilibrium with rs7903146 (r2 > 0.2, top), only rs7903146 maps to an islet-selective FAIRE site. () In all nine human islet samples that were heterozygous for rs7903146, the risk allele T was more abundant than the non-risk C allele in the open chromatin fraction, in contrast to input DNA or genomic DNA from unrelated heterozygous individuals. () Allelic imbalance for the open chromatin at rs7903146 was verified in independ! ent assays using quantitative Sanger sequencing (see also Supplementary Fig. 4b). (,) The risk allele T of rs7903146 shows greater enhancer activity than the non-risk allele C in MIN6 cells () and 832/13 cells (). The s.d. values represent four independent clones for each alleles. Results for inserts in the reverse direction are provided in Supplementary Figure 4. P values were calculated by two-sided t-test. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE17616 Author information * Accession codes * Author information * Supplementary information Primary authors * Authors contributed equally to this work. * Kyle J Gaulton, * Takao Nammo & * Lorenzo Pasquali Affiliations * Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. * Kyle J Gaulton, * Jeremy M Simon, * Marie P Fogarty, * Tami M Panhuis, * Piotr Mieczkowski & * Karen L Mohlke * Genomic Programming of Beta Cells, Institut d'Investigacions Biomediques August Pi i Sunyer, Barcelona, Spain. * Takao Nammo, * Lorenzo Pasquali & * Jorge Ferrer * Centro de Investigación Biomédica en Red (CIBER) de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain. * Takao Nammo, * Lorenzo Pasquali, * Eduard Montanya & * Jorge Ferrer * Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. * Jeremy M Simon, * Paul G Giresi & * Jason D Lieb * Clinical Transplant Unit, San Raffaele Scientific Institute, Milano, Italy. * Antonio Secchi * Cell Isolation and Transplantation Center, Geneva, Switzerland. * Domenico Bosco & * Thierry Berney * Laboratory of Diabetes and Experimental Endocrinology, Endocrine Unit, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL)-Hospital Universitari Bellvitge, University of Barcelona, Spain. * Eduard Montanya * Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. * Karen L Mohlke & * Jason D Lieb * Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. * Karen L Mohlke & * Jason D Lieb * Department of Endocrinology, Hospital Clínic de Barcelona, Barcelona, Spain. * Jorge Ferrer Contributions J.F. and J.D.L. conceived the study. K.J.G., T.N., L.P., J.M.S., K.L.M., J.D.L. and J.F. designed the experiments, interpreted results and wrote the manuscript. T.N. conducted FAIRE experiments, and developed and performed allelic imbalance assays. P.G.G. optimized the FAIRE protocol and performed microarray studies. K.J.G., J.M.S., and P.G.G. performed sequence analysis and K.J.G., L.P., T.N. and J.M.S. performed data analysis. L.P. conducted the analysis of COREs. M.P.F. and T.M.P. conducted reporter assays. P.M. conducted high-throughput sequencing. A.S., D.B., T.B. and E.M. provided purified human islet samples. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Jorge Ferrer (jferrer@clinic.ub.es) or * Jason D Lieb (jlieb@bio.unc.edu) or * Karen L Mohlke (mohlke@med.unc.edu) Supplementary information * Accession codes * Author information * Supplementary information Excel files * Supplementary Table 2 (204K) RefSeq transcripts with preferential islet FAIRE enrichment * Supplementary Table 4 (60K) Over- and under-represented transcription factor binding motifs in intergenic islet FAIRE sites * Supplementary Table 5 (556K) Islet-selective Clusters of Open Regulatory Elements (COREs) * Supplementary Table 7 (96K) Islet-selective CORES that extend > 2 kb from the transcription start or termination site of overlapping genes PDF files * Supplementary Text and Figures (4M) Supplementary Figures 1–4 and Supplementary Tables 1–9. Additional data - Population resequencing reveals local adaptation of Arabidopsis lyrata to serpentine soils
- Nature genetics 42(3):260-263 (2010)
Nature Genetics | Letter Population resequencing reveals local adaptation of Arabidopsis lyrata to serpentine soils * Thomas L Turner1, 2, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Elizabeth C Bourne3 Search for this author in: * NPG journals * PubMed * Google Scholar * Eric J Von Wettberg4 Search for this author in: * NPG journals * PubMed * Google Scholar * Tina T Hu1 Search for this author in: * NPG journals * PubMed * Google Scholar * Sergey V Nuzhdin1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:260–263Year published:(2010)DOI:doi:10.1038/ng.515 Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg A powerful way to map functional genomic variation and reveal the genetic basis of local adaptation is to associate allele frequency across the genome with environmental conditions1, 2, 3, 4, 5. Serpentine soils, characterized by high heavy-metal content and low calcium-to-magnesium ratios, are a classic context for studying adaptation of plants to local soil conditions6, 7. To investigate whether Arabidopsis lyrata is locally adapted to serpentine soil, and to map the polymorphisms responsible for such adaptation, we pooled DNA from individuals from serpentine and nonserpentine soils and sequenced each 'gene pool' with the Illumina Genome Analyzer. The polymorphisms that are most strongly associated with soil type are enriched at heavy-metal detoxification and calcium and magnesium transport loci, providing numerous candidate mutations for serpentine adaptation. Sequencing of three candidate loci in the European subspecies of A. lyrata indicates parallel differentiation of ! the same polymorphism at one locus, confirming ecological adaptation, and different polymorphisms at two other loci, which may indicate convergent evolution. View full text Author information * Author information * Supplementary information Affiliations * Molecular and Computational Biology, University of Southern California, Los Angeles, California, USA. * Thomas L Turner, * Tina T Hu & * Sergey V Nuzhdin * Gregor Mendel Institute, Austrian Academy of Sciences, Vienna, Austria. * Thomas L Turner * The Macaulay Land Use Research Institute, Craigiebuckler, Aberdeen, UK. * Elizabeth C Bourne * Evolution and Ecology, University of California, Davis, California, USA. * Eric J Von Wettberg * Present address: Evolution, Ecology, and Marine Biology Department, University of California Santa Barbara, Santa Barbara, California, USA. * Thomas L Turner Contributions T.L.T. and S.V.N. designed experiments; T.L.T., E.C.B. and T.T.H. performed analyses; E.C.B. and E.J.V.W. designed and performed all field collections; T.L.T., E.J.V.W. and S.V.N. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Thomas L Turner (tturner@lifesci.ucsb.edu) Supplementary information * Author information * Supplementary information Excel files * Supplementary Table 2 (40K) Number of mismatches per aligned read PDF files * Supplementary Text and Figures (824K) Supplementary Tables 1–3 and Supplementary Figures 1–9 Additional data - A basic helix-loop-helix transcription factor controls cell growth and size in root hairs
Yi K Menand B Bell E Dolan L - Nature genetics 42(3):264-267 (2010)
Nature Genetics | Letter A basic helix-loop-helix transcription factor controls cell growth and size in root hairs * Keke Yi1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Benoît Menand1, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Elizabeth Bell1 Search for this author in: * NPG journals * PubMed * Google Scholar * Liam Dolan1, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:264–267Year published:(2010)DOI:doi:10.1038/ng.529 Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Postmitotic cell growth defines cell shape and size during development. However, the mechanisms regulating postmitotic cell growth in plants remain unknown. Here we report the discovery of a basic helix-loop-helix (bHLH) transcription factor called RSL4 (ROOT HAIR DEFECTIVE 6-LIKE 4) that is sufficient to promote postmitotic cell growth in Arabidopsis thaliana root-hair cells. Loss of RSL4 function resulted in the development of very short root hairs. In contrast, constitutive RSL4 expression programmed constitutive growth, resulting in the formation of very long root hairs. Hair-cell growth signals, such as auxin and low phosphate availability, modulate hair cell extension by regulating RSL4 transcript and protein levels. RSL4 is thus a regulator of growth that integrates endogenous developmental and exogenous environmental signals that together control postmitotic growth in root hairs. The control of postmitotic growth by transcription factors may represent a general mecha! nism for regulating cell size across diverse organisms. View full text Figures at a glance * Figure 1: RSL4 is an immediate target of RHD6. () Appearance of root hairs 24 h after an rhd6-3 rsl1-1 double mutant harboring GR-RHD6 was treated with MS liquid medium without DEX. Scale bar, 1 mm. () Appearance of root hairs 24 h after an rhd6-3 rsl1-1 double mutant harboring GR-RHD6 was treated with MS liquid medium with 20 mM DEX. Scale bar, 1 mm. () RT-PCR indicates that RSL4 expression is repressed in plants with rhd6-3 and rhd6-3 rsl1-1 mutant backgrounds. () Quantitative RT-PCR (qRT-PCR) analysis of RNA from rhd6-3 rsl1-1 double mutants harboring GR-RHD6 treated with DEX for 2 h (open bar), 24 h (black bar) and treated with DEX and CHX for 2 h (hatched bar). Values represent mean ± s.d., n = 3. * Figure 2: RSL4 is expressed in root-hair cells and regulates hair growth. () Showing RSL4 in initiating and elongating root-hair cells, from left to right: bright-field image of a root; fluorescent image of GFP-RSL4 in the same root showing RSL4 in hair cell nuclei, scale bar: 200 μm; confocal image of a GFP-RSL4 root (cell walls were counterstained with propidium iodide, red signal) showing that RSL4 is only present in root-hair cells, scale bar: 50 μm. () Root hair phenotype of rsl4 mutants and their complementation with RSL4 genomic DNA (rsl4-1/RSL4), scale bar: 500 μm. () Root-hair length (mean ± s.e.m., n > 600) and density (mean ± s.d., n = 3 experiments) of rsl4 mutants and rsl4-1 mutants complemented with RSL4 genomic DNA. Different letters are used to indicate means that differ significantly (P < 0.05, Tukey's honestly significant difference (HSD) tests). * Figure 3: Constitutive RSL4 expression leads to constitutive postmitotic growth of root-hair cells. () Root-hair phenotype of col-0 plants (left) and a plant transformed with CaMV 35S-RSL4 (right). Scale bar, 1 mm. () GFP-RHD2 protein accumulated in the growing root-hair tip in col-0 plants (left) and plants transformed with CaMV 35S-RSL4 (right). Scale bar, 200 μm. () Root-hair growth rates are similar in wild-type compared to lines that constitutively express RSL4. Above, typical root-hair growth curve of col-0 and two individual lines transformed with CaMV 35S-RSL4. Below, average root-hair growth rate of col-0 and the lines transformed with CaMV 35S-RSL4. Values are mean ± s.d., n = 3 experiments. * Figure 4: Auxin modulates RSL4 expression to control hair cell growth. () qRT-PCR analysis of mRNAs isolated from col-0 and the rhd6-3 rsl1-1 double mutant under control and 150 nM 1-naphthaleneacetic acid (NAA) treatments show that RSL4 is induced by auxin treatment. Values are mean ± s.d., n = 3. () Pseudo-color images of GFP-RSL2 (above) and GFP-RSL4 (below) under normal conditions (left) and NAA (150 nM) treatments (right) showing that auxin treatment induces the accumulation of RSL4 and represses the accumulation of RSL2. Scale bar, 20 μm. () In contrast to col-0 plants (above), no accumulation of GFP-RSL4 was detected in rhd6-3 rsl1-1 plants (middle). However, auxin treatment restored the accumulation of GFP-RSL4 in the rhd6-3 rsl1-1 mutant background (bottom). Scale bar, 50 μm. () Auxin treatment can induce root-hair growth in rhd6-3 rsl1-1 plants but not in rhd6-3 rsl1-1 rsl4-1 and rsl2-1 rsl4-1 plants. Above, normal conditions; below, NAA treatment. Scale bar, 500 μm. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE19530 Author information * Accession codes * Author information * Supplementary information Affiliations * Department of Cell and Developmental Biology, John Innes Centre, Norwich, United Kingdom. * Keke Yi, * Benoît Menand, * Elizabeth Bell & * Liam Dolan * State Key Laboratory of Plant Physiology and Biochemistry, College of Life Science, Zhejiang University, Hangzhou, China. * Keke Yi * Laboratoire de Génétique et Biophysique des Plantes, Centre National de la Recherche Scientifique, Commissariat à l'Energie Atomique (CEA), Aix-Marseille Université, Marseille, France. * Benoît Menand * Department of Plant Sciences, University of Oxford, Oxford, United Kingdom. * Liam Dolan Contributions K.Y. carried out all experiments except for the identification of genes that act downstream of RSL4, which was carried out by E.B. L.D. and K.Y. wrote the paper with the assistance of B.M. and E.B. K.Y., B.M. and L.D. planned the experiments. L.D. supervised and initiated the study. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Liam Dolan (liam.dolan@plants.ox.ac.uk) Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Note, Supplementary Figures 1–10 and Supplementary Tables 1 and 2. Additional data - Plasmodium falciparum genome-wide scans for positive selection, recombination hot spots and resistance to antimalarial drugs
- Nature genetics 42(3):268-271 (2010)
Nature Genetics | Letter Plasmodium falciparum genome-wide scans for positive selection, recombination hot spots and resistance to antimalarial drugs * Jianbing Mu1 Search for this author in: * NPG journals * PubMed * Google Scholar * Rachel A Myers2, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Hongying Jiang1 Search for this author in: * NPG journals * PubMed * Google Scholar * Shengfa Liu1, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Stacy Ricklefs5 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Waisberg6 Search for this author in: * NPG journals * PubMed * Google Scholar * Kesinee Chotivanich7 Search for this author in: * NPG journals * PubMed * Google Scholar * Polrat Wilairatana7 Search for this author in: * NPG journals * PubMed * Google Scholar * Srivicha Krudsood8 Search for this author in: * NPG journals * PubMed * Google Scholar * Nicholas J White9 Search for this author in: * NPG journals * PubMed * Google Scholar * Rachanee Udomsangpetch10 Search for this author in: * NPG journals * PubMed * Google Scholar * Liwang Cui11 Search for this author in: * NPG journals * PubMed * Google Scholar * May Ho12 Search for this author in: * NPG journals * PubMed * Google Scholar * Fengzhen Ou13 Search for this author in: * NPG journals * PubMed * Google Scholar * Haibo Li13 Search for this author in: * NPG journals * PubMed * Google Scholar * Jianping Song13 Search for this author in: * NPG journals * PubMed * Google Scholar * Guoqiao Li13 Search for this author in: * NPG journals * PubMed * Google Scholar * Xinhua Wang14 Search for this author in: * NPG journals * PubMed * Google Scholar * Suon Seila15 Search for this author in: * NPG journals * PubMed * Google Scholar * Sreng Sokunthea15 Search for this author in: * NPG journals * PubMed * Google Scholar * Duong Socheat15 Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel E Sturdevant5 Search for this author in: * NPG journals * PubMed * Google Scholar * Stephen F Porcella5 Search for this author in: * NPG journals * PubMed * Google Scholar * Rick M Fairhurst1 Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas E Wellems1 Search for this author in: * NPG journals * PubMed * Google Scholar * Philip Awadalla2 Search for this author in: * NPG journals * PubMed * Google Scholar * Xin-zhuan Su1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Corresponding authorsJournal name:Nature GeneticsVolume:42,Pages:268–271Year published:(2010)DOI:doi:10.1038/ng.528 Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Antimalarial drugs impose strong selective pressure on Plasmodium falciparum parasites and leave signatures of selection in the parasite genome1, 2; screening for genes under selection may suggest potential drug or immune targets3. Genome-wide association studies (GWAS) of parasite traits have been hampered by the lack of high-throughput genotyping methods, inadequate knowledge of parasite population history and time-consuming adaptations of parasites to in vitro culture. Here we report the first Plasmodium GWAS, which included 189 culture-adapted P. falciparum parasites genotyped using a custom-built Affymetrix molecular inversion probe 3K malaria panel array with a coverage of ~1 SNP per 7 kb. Population structure, variation in recombination rate and loci under recent positive selection were detected. Parasite half-maximum inhibitory concentrations for seven antimalarial drugs were obtained and used in GWAS to identify genes associated with drug responses. This study provi! des valuable tools and insight into the P. falciparum genome. View full text Figures at a glance * Figure 1: Population structure and principal component analysis (PCA) of Plasmodium falciparum parasite populations. () Population partitions identified using STRUCTURE (v2.2)10. The Cambodian group (red) consists of parasites CP195, CP201, CP216, CP285, CP286, CP291, CP313, CP268, CP325, CP305, CP307, CP256, CP238 and CP211. () PCA plot of all the parasites. Parasite continental origins are color coded, and 'X' indicates outliers. PNG, Papua New Guinea. () PCA plot of the Thai-Cambodian parasites showing outliers from the region. * Figure 2: Loci subject to positive selection in P. falciparum populations from Africa, Asia and America. () Plots of −log P values showing loci significantly under positive selection. Arrowheads point to loci containing the genes encoding the chloroquine resistance transporter (pfcrt) on chromosome 7, the apical membrane antigen (pfama-1) on chromosome 11 and an ABC transporter on chromosome 13, respectively; dots above the dash lines indicate significance. () Plots of integrated haplotype scores (iHS) showing loci under selection. Arrowheads indicate the pfcrt and pfama-1 loci on chromosome 7 and 11, respectively. SNPs with |iHS| values ≥ 2.3 were those above the horizontal line in each graph. Each dot represents an |iHS| value from a window of 21 SNPs (a core SNP plus ten SNPs on each side). () Plots of −log P values from XP-EHH analyses. AF/AM, comparison of African and American populations; AF/AS, comparison of African and Asian populations; AS/AM, comparison of Asian and American populations. The horizontal lines indicate significant P values (P < 0.05), and the arro! wheads point to the pfcrt locus on chromosome 7 and PFE1445c locus on chromosome 5, respectively. * Figure 3: In vitro parasite responses (IC50) to seven antimalarial drugs. () IC50 values to seven different antimalarial drugs from 185 parasites were sorted from the lowest to the highest values. Note gaps in IC50 values in parasite responses to chloroquine (CQ) and sulfadoxine-pyrimethamine (SP) but continuous distributions for the other drugs. IC50 curves for each drug as marked in the figure. () Plots similar to those in for parasites from Thai-Cambodian population. (,) Multivariate analyses showing correlations between responses to seven different drugs for all the parasites () and Thai-Cambodian parasites (). Dihydroartemisinin (DHA) and mefloquine (MQ) had strong positive correlation; CQ, amodiaquine (AMQ), piperaquine (PQ), quinine (QN) and SP also had positive correlation to some degree; AMQ and DHA, and AMQ and MQ, had negative correlation. * Figure 4: Genome-wide scan for SNPs associated with responses to antimalarial drugs in the Asian population. Values of −log P for four drugs were plotted against chromosomal positions. The arrowheads indicate SNPs with Bonferroni-corrected P < 0.05. (,) Plots from EIGENSOFT () and PLINK (). CQ, chloroquine; QN, quinine; MQ, mefloquine; DHA, dihydroartemisinin. Author information * Author information * Supplementary information Affiliations * Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, Maryland, USA. * Jianbing Mu, * Hongying Jiang, * Shengfa Liu, * Rick M Fairhurst, * Thomas E Wellems & * Xin-zhuan Su * Department of Pediatrics, University of Montreal, Faculty of Medicine, Sainte Justine Research Centre, Montreal, Quebec, Canada. * Rachel A Myers & * Philip Awadalla * Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina, USA. * Rachel A Myers * School of Life Sciences, Xiamen University, Xiamen, Fujian, China. * Shengfa Liu * Genomics Unit, Research Technologies Section, Research Technologies Branch, Rocky Mountain Laboratories, NIAID, NIH, Hamilton, Montana, USA. * Stacy Ricklefs, * Daniel E Sturdevant & * Stephen F Porcella * Laboratory of Immunogenetics, NIAID, NIH, Bethesda, Maryland, USA. * Michael Waisberg * Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand. * Kesinee Chotivanich & * Polrat Wilairatana * Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand. * Srivicha Krudsood * Wellcome Trust–Mahidol University–Oxford Tropical Medicine Research Programme, Mahidol University, Bangkok, Thailand. * Nicholas J White * Pathobiology Department, Faculty of Science, Mahidol University, Bangkok, Thailand. * Rachanee Udomsangpetch * Department of Entomology, Pennsylvania State University, University Park, Pennsylvania, USA. * Liwang Cui * Department of Microbiology and Infectious Disease, University of Calgary, Calgary, Alberta, Canada. * May Ho * Research Center for Qinghao, Guangzhou, China. * Fengzhen Ou, * Haibo Li, * Jianping Song & * Guoqiao Li * Guangzhou University of Chinese Medicine, Guangzhou, China. * Xinhua Wang * National Centre for Parasitology, Entomology and Malaria Control, Phnom Penh, Cambodia. * Suon Seila, * Sreng Sokunthea & * Duong Socheat Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Xin-zhuan Su (xsu@niaid.nih.gov) or * Philip Awadalla (philip.awadalla@umontreal.ca) or * Jianbing Mu (jmu@niaid.nih.gov) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1 and 2 and Supplementary Tables 1–6 Additional data - Prevalent positive epistasis in Escherichia coli and Saccharomyces cerevisiae metabolic networks
He X Qian W Wang Z Li Y Zhang J - Nature genetics 42(3):272-276 (2010)
Nature Genetics | Letter Prevalent positive epistasis in Escherichia coli and Saccharomyces cerevisiae metabolic networks * Xionglei He1, 3, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Wenfeng Qian1, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Zhi Wang1, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Ying Li1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Jianzhi Zhang1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:272–276Year published:(2010)DOI:doi:10.1038/ng.524 Article tools * Full text * 日本語要約 * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Epistasis refers to the interaction between genes. Although high-throughput epistasis data from model organisms are being generated and used to construct genetic networks1, 2, 3, the extent to which genetic epistasis reflects biologically meaningful interactions remains unclear4, 5, 6. We have addressed this question through in silico mapping of positive and negative epistatic interactions amongst biochemical reactions within the metabolic networks of Escherichia coli and Saccharomyces cerevisiae using flux balance analysis. We found that negative epistasis occurs mainly between nonessential reactions with overlapping functions, whereas positive epistasis usually involves essential reactions, is highly abundant and, unexpectedly, often occurs between reactions without overlapping functions. We offer mechanistic explanations of these findings and experimentally validate them for 61 S. cerevisiae gene pairs. View full text Figures at a glance * Figure 1: Functions of E. coli metabolic reactions in glucose minimal medium. () Functions of 255 important reactions in producing 49 biomass constituents. Columns represent reactions and rows represent biomass constituents. () Distribution of the number of biomass constituents affected by a reaction. * Figure 2: Pairwise epistasis and functional association among 255 important reactions in E. coli. () An overview of epistasis and functional association among reactions. Both rows and columns represent reactions. Scaled epistasis between reactions is shown in the lower left triangle by the heat map. Functional association between reactions is presented in the upper right triangle, where a gray dot is shown when two reactions have overlapping functions. Epistasis and reaction functions are both determined in the glucose minimal medium. () Frequency distribution of scaled epistasis between nonessential reactions. () Frequency distribution of scaled epistasis between two reactions that include at least one essential reaction. E, essential; N, nonessential. Note the difference in y scale between and . * Figure 3: Pairwise epistasis and functional association among 212 important reactions in yeast. () Frequency distribution of scaled epistasis between nonessential reactions. () Frequency distribution of scaled epistasis between two reactions that include at least one essential reaction. E, essential; N, nonessential. Note the difference in y scale between and . * Figure 4: Epistasis (ϵ) and scaled epistasis () among 17 yeast genes. Circles show ϵ and squares . Blue and red indicate positive and negative epistasis, respectively, whereas the areas of the circles and squares are proportional to the absolute values of ϵ and , respectively, with the scales given on the top and left sides of each panel. Solid symbols indicate statistically significant epistasis (P < 0.05), whereas open symbols indicate insignificant epistasis. The shaded area in the lower right corner shows relationships between nonessential genes. Fitness values of strains with genes replaced or inserted by LEU2, relative to the wild types, are presented on the x axis. () Epistasis among eight haploinsufficient genes, measured in diploid cells after deletion of one allele per gene. All genes belong to different functional categories with the exception of RPS5 and RPL14A, both of which encode ribosomal proteins. () Epistasis among nine haplosufficient genes, measured in haploid cells after reduction of protein expression of essential genes! and deletion of nonessential genes. All genes belong to different functional categories, with the exception of GAA1 and GAS1. MET22 and CHO2 are metabolic genes, with FBA-predicted scaled epistasis equal to 1. '−' indicates that double-perturbation cells could not be obtained, probably because of unsuccessful experiments or synthetic lethality. '?' indicates that epistasis could not be measured owing to the lack of fitness effect of single perturbations with the URA3 marker. In Supplementary Figure 3, we explain why here negative epistasis between nonessential genes seems to be more abundant than expected. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Xionglei He, * Wenfeng Qian & * Zhi Wang Affiliations * Department of Ecology and Evolutionary Biology, Ann Arbor, Michigan, USA. * Xionglei He, * Wenfeng Qian, * Zhi Wang, * Ying Li & * Jianzhi Zhang * Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China. * Ying Li * Present address: State Key Laboratory of Bio-control, College of Life Sciences, Sun Yat-Sen University, Guangzhou, China. * Xionglei He Contributions X.H. and J.Z. conceived the research; X.H., Z.W., W.Q. and J.Z. designed the experiments; X.H., W.Q., Z.W., Y.L. and J.Z. conducted the experiments; X.H., W.Q., Z.W. and J.Z. analyzed the data; X.H. and J.Z. drafted the manuscript and all authors contributed to the final manuscript writing and its revisions. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Jianzhi Zhang (jianzhi@umich.edu) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1–5, Supplementary Tables 1–5 and Supplementary Note Additional data
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