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Latest Articles Include:

• Primary research on existing data
  - Nat Genet 42(6):467 (2010)
  Nature Genetics | Editorial Primary research on existing data Journal name:Nature GeneticsVolume:42,Page:467Year published:(2010)DOI:doi:10.1038/ng0610-467 Articles in the Analysis format report primary research carried out on publications, datasets or research practices. We see Analyses as a way to generate new hypotheses, test data integrity and promote research integration. View full text Additional data
• Lack of support for association between the KIF1B rs10492972[C] variant and multiple sclerosis
  International Multiple Sclerosis Genetics Consortium (IMSGC)* Booth DR Heard RN Stewart GJ Cox M Scott RJ Lechner-Scott J Goris A Dobosi R Dubois B Saarela J Leppä V Peltonen L Pirttila T Cournu-Rebeix I Fontaine B Bergamaschi L D'Alfonso S Leone M Lorentzen AR Harbo HF Celius EG Spurkland A Link J Kockum I Olsson T Hillert J Ban M Baker A Kemppinen A Sawcer S Compston A Robertson NP De Jager PL Hafler DA Barcellos LF Ivinson AJ McCauley JL Pericak-Vance MA Oksenberg JR Hauser SL Sexton D Haines J - Nat Genet 42(6):469-470 (2010)
  Nature Genetics | Correspondence Lack of support for association between the KIF1B rs10492972[C] variant and multiple sclerosis * David R Booth1 Search for this author in: * NPG journals * PubMed * Google Scholar * Robert N Heard1 Search for this author in: * NPG journals * PubMed * Google Scholar * Graeme J Stewart1 Search for this author in: * NPG journals * PubMed * Google Scholar * Mathew Cox2 Search for this author in: * NPG journals * PubMed * Google Scholar * Rodney J Scott2 Search for this author in: * NPG journals * PubMed * Google Scholar * Jeannette Lechner-Scott2 Search for this author in: * NPG journals * PubMed * Google Scholar * An Goris3 Search for this author in: * NPG journals * PubMed * Google Scholar * Rita Dobosi3 Search for this author in: * NPG journals * PubMed * Google Scholar * Bénédicte Dubois3 Search for this author in: * NPG journals * PubMed * Google Scholar * Janna Saarela4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Virpi Leppä4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Leena Peltonen5, 6 Search for this author in: * NPG journals * PubMed * Google Scholar * Tuula Pirttila7 Search for this author in: * NPG journals * PubMed * Google Scholar * Isabelle Cournu-Rebeix8, 9 Search for this author in: * NPG journals * PubMed * Google Scholar * Bertrand Fontaine8, 9 Search for this author in: * NPG journals * PubMed * Google Scholar * Laura Bergamaschi10 Search for this author in: * NPG journals * PubMed * Google Scholar * Sandra D'Alfonso10 Search for this author in: * NPG journals * PubMed * Google Scholar * Maurizio Leone11 Search for this author in: * NPG journals * PubMed * Google Scholar * Åslaug R Lorentzen12, 13 Search for this author in: * NPG journals * PubMed * Google Scholar * Hanne F Harbo12 Search for this author in: * NPG journals * PubMed * Google Scholar * Elisabeth G Celius12 Search for this author in: * NPG journals * PubMed * Google Scholar * Anne Spurkland14 Search for this author in: * NPG journals * PubMed * Google Scholar * Jenny Link15 Search for this author in: * NPG journals * PubMed * Google Scholar * Ingrid Kockum15 Search for this author in: * NPG journals * PubMed * Google Scholar * Tomas Olsson15 Search for this author in: * NPG journals * PubMed * Google Scholar * Jan Hillert15 Search for this author in: * NPG journals * PubMed * Google Scholar * Maria Ban16 Search for this author in: * NPG journals * PubMed * Google Scholar * Amie Baker16 Search for this author in: * NPG journals * PubMed * Google Scholar * Anu Kemppinen16 Search for this author in: * NPG journals * PubMed * Google Scholar * Stephen Sawcer16 Search for this author in: * NPG journals * PubMed * Google Scholar * Alastair Compston16 Search for this author in: * NPG journals * PubMed * Google Scholar * Neil P Robertson17 Search for this author in: * NPG journals * PubMed * Google Scholar * Philip L De Jager18, 19, 20 Search for this author in: * NPG journals * PubMed * Google Scholar * David A Hafler20, 21 Search for this author in: * NPG journals * PubMed * Google Scholar * Lisa F Barcellos22 Search for this author in: * NPG journals * PubMed * Google Scholar * Adrian J Ivinson23 Search for this author in: * NPG journals * PubMed * Google Scholar * Jacob L McCauley24 Search for this author in: * NPG journals * PubMed * Google Scholar * Margaret A Pericak-Vance24 Search for this author in: * NPG journals * PubMed * Google Scholar * Jorge R Oksenberg25 Search for this author in: * NPG journals * PubMed * Google Scholar * Stephen L Hauser25 Search for this author in: * NPG journals * PubMed * Google Scholar * David Sexton26 Search for this author in: * NPG journals * PubMed * Google Scholar * Jonathan Haines26 Search for this author in: * NPG journals * PubMed * Google Scholar * for International Multiple Sclerosis Genetics Consortium (IMSGC)* * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:469–470Year published:(2010)DOI:doi:10.1038/ng0610-469 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg To the Editor: In their recent communication, Aulchenko et al.1 suggested that the rs10492972[C] variant of KIF1B increases susceptibility to multiple sclerosis. In an attempt to replicate this observation, we genotyped this variant in eight case-control and three trio-family collections (in total 22,854 individuals were considered, comprising 8,391 cases, 8,052 unrelated controls and 2,137 trio families). None of these studies showed evidence for a statistically significant association; more than half of the studies showed a trend in the opposite direction (Fig. 1). Based on the odds ratio (OR) reported by Aulchenko et al.1 (OR = 1.35), each of the collections we studied had >80% power to demonstrate association at the 5% significance level, except for the two smaller Australian studies; a population where association with this KIF1B variant has already essentially been excluded2. We also found no evidence for association with rs10492972[C] in analyses that considered all of our data toge! ther or those that pooled our new data with the allele counts reported by Aulchenko et al.1 (final P = 0.1). Given the P value originally reported by Aulchenko et al.1 (P = 2.5 × 10−10), it is important to consider why this association has not been replicated. View full text Author information * Author information * Supplementary information Affiliations * University of Sydney, Institute for Immunology and Allergy Research, Westmead Millennium Institute, Westmead Hospital, Sydney, Australia. * David R Booth, * Robert N Heard & * Graeme J Stewart * Hunter Medical Research Institute, University of Newcastle, Callaghan, Australia. * Mathew Cox, * Rodney J Scott & * Jeannette Lechner-Scott * Section for Experimental Neurology, Katholieke Universiteit Leuven, Leuven, Belgium. * An Goris, * Rita Dobosi & * Bénédicte Dubois * Public Health Genomics Unit, National Institute for Health and Welfare, Helsinki, Finland. * Janna Saarela & * Virpi Leppä * Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland. * Janna Saarela, * Virpi Leppä & * Leena Peltonen * The Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. * Leena Peltonen * Department of Neurology, Kuopio University Central Hospital, Kuopio, Finland. * Tuula Pirttila * INSERM, UMR_S975, Centre de Recherche Institut du Cerveau et de la Moelle, Université Pierre et Marie Curie Paris 06, Paris, France. * Isabelle Cournu-Rebeix & * Bertrand Fontaine * Fédération des maladies du système nerveux, Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France. * Isabelle Cournu-Rebeix & * Bertrand Fontaine * Department of Medical Sciences and Interdisciplinary Research Center of Autoimmune Diseases, University of Eastern Piedmont, Novara, Italy. * Laura Bergamaschi & * Sandra D'Alfonso * Clinica Neurologica, Ospedale Maggiore della Carità, Novara, Italy. * Maurizio Leone * Department of Neurology, University of Oslo and Oslo University Hospital, Oslo, Norway. * Åslaug R Lorentzen, * Hanne F Harbo & * Elisabeth G Celius * Institute of Immunology, Oslo University Hospital, Oslo, Norway. * Åslaug R Lorentzen * Institute of Basal Medical Sciences, University of Oslo, Oslo, Norway. * Anne Spurkland * Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden. * Jenny Link, * Ingrid Kockum, * Tomas Olsson & * Jan Hillert * University of Cambridge, Department of Clinical Neuroscience, Addenbrooke's Hospital, Cambridge, UK. * Maria Ban, * Amie Baker, * Anu Kemppinen, * Stephen Sawcer & * Alastair Compston * Department of Neurology, University Hospital of Wales, Heath Park, Cardiff, UK. * Neil P Robertson * Program in Translational NeuroPsychiatric Genomics, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts, USA. * Philip L De Jager * Harvard Medical School, Boston, Massachusetts, USA. * Philip L De Jager * Broad Institute of Harvard University and Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Philip L De Jager & * David A Hafler * Department of Neurology, Yale University School of Medicine, New Haven, Connecticut, USA. * David A Hafler * Division of Epidemiology, School of Public Health, University of California at Berkeley, Berkeley, California, USA. * Lisa F Barcellos * Harvard NeuroDiscovery Center, Harvard Medical School, Boston, Massachusetts, USA. * Adrian J Ivinson * John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida, USA. * Jacob L McCauley & * Margaret A Pericak-Vance * Department of Neurology, University of California San Francisco, San Francisco, California, USA. * Jorge R Oksenberg & * Stephen L Hauser * Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA. * David Sexton & * Jonathan Haines Consortia * International Multiple Sclerosis Genetics Consortium (IMSGC)* * David R Booth, * Robert N Heard, * Graeme J Stewart, * Mathew Cox, * Rodney J Scott, * Jeannette Lechner-Scott, * An Goris, * Rita Dobosi, * Bénédicte Dubois, * Janna Saarela, * Virpi Leppä, * Leena Peltonen, * Tuula Pirttila, * Isabelle Cournu-Rebeix, * Bertrand Fontaine, * Laura Bergamaschi, * Sandra D'Alfonso, * Maurizio Leone, * Åslaug R Lorentzen, * Hanne F Harbo, * Elisabeth G Celius, * Anne Spurkland, * Jenny Link, * Ingrid Kockum, * Tomas Olsson, * Jan Hillert, * Maria Ban, * Amie Baker, * Anu Kemppinen, * Stephen Sawcer, * Alastair Compston, * Neil P Robertson, * Philip L De Jager, * David A Hafler, * Lisa F Barcellos, * Adrian J Ivinson, * Jacob L McCauley, * Margaret A Pericak-Vance, * Jorge R Oksenberg, * Stephen L Hauser, * David Sexton & * Jonathan Haines Contributions D.R.B., R.N.H., G.J.S., M.C., R.J.S., J.L.-S., A.G., R.D., B.D., J.S., V.L., L.P., T.P., I.C.-R., B.F., L.B., S.D., M.L., A.R.L., E.G.C., H.F.H., A.S., J.L., I.K., T.O., J.H., M.B., A.B., A.K., S.S., A.C., N.P.R., P.L.D., D.A.H., L.F.B., A.J.I., J.L.M., M.A.P.-V., J.R.O., S.L.H., D.S. and J.H. designed the study, coordinated sample and data handling and contributed to the manuscript. M.C., A.G., R.D., V.L., I.C.-R., L.B., A.R.L., J.L. and A.B. performed the genotyping. M.B. and S.S. performed the statistical analysis. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Maria Ban (mb531@medschl.cam.ac.uk) Supplementary information * Author information * Supplementary information PDF files * Supplementary Note (33K) Additional data
• Reply to "Lack of support for association between the KIF1B rs10492972[C] variant and multiple sclerosis"
  Hintzen RQ Aulchenko YS Ramagopalan S Ebers G van Duijn CM - Nat Genet 42(6):470-471 (2010)
  Nature Genetics | Correspondence Reply to "Lack of support for association between the KIF1B rs10492972[C] variant and multiple sclerosis" * Rogier Q Hintzen1 Search for this author in: * NPG journals * PubMed * Google Scholar * Yurii S Aulchenko2 Search for this author in: * NPG journals * PubMed * Google Scholar * Sriram Ramagopalan3 Search for this author in: * NPG journals * PubMed * Google Scholar * George Ebers3 Search for this author in: * NPG journals * PubMed * Google Scholar * Cornelia M van Duijn2 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:470–471Year published:(2010)DOI:doi:10.1038/ng0610-470 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Hintzen et al. reply: We share the authors' surprise that in a large dataset from several countries, they failed to reproduce the association between variation at the KIF1B locus and multiple sclerosis (MS) that we observed1. A role for KIF1B (kinesin family member 1B) in MS is biologically plausible given both the increasingly recognized role of kinesins in neurological disease and the recent report on Kif1b and myelination2. Our original observation has been replicated in a study of Canadian multiplex MS families3, which showed an odds ratio (OR) of 1.65 for association between rs10492972[C] and MS (G.E., unpublished data; see Supplementary Note). The recent large study by the International Multiple Sclerosis Genetics Consortium (IMSGC) demonstrated evidence for an association with KIF21B4, which encodes a molecule that shares properties with KIF1B. A recent Australian–New Zealand screen found marginal association with an area around KIF1A5. View full text Author information * Author information * Supplementary information Affiliations * Department of Neurology, Erasmus MC, Rotterdam, The Netherlands. * Rogier Q Hintzen * Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands. * Yurii S Aulchenko & * Cornelia M van Duijn * Department of Clinical Neurology and The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK. * Sriram Ramagopalan & * George Ebers Corresponding author Correspondence to: * Rogier Q Hintzen (r.hintzen@erasmusmc.nl) Supplementary information * Author information * Supplementary information PDF files * Supplementary Note (33K) Additional data
• Reassessing evidence for a postnatal mitochondrial genetic bottleneck
  Samuels DC Wonnapinij P Cree LM Chinnery PF - Nat Genet 42(6):471-472 (2010)
  Mitochondrial DNA (mtDNA) mutations are a major cause of maternally inherited human disease. Mothers often harbor a mixture of mutated and wild-type mtDNA (heteroplasmy) and transmit varying proportions of mutated and wild-type mtDNA to different offspring.
• Reply to "Reassessing evidence for a postnatal mitochondrial genetic bottleneck"
  Wai T Shoubridge EA - Nat Genet 42(6):472-473 (2010)
  Nature Genetics | Correspondence Reply to "Reassessing evidence for a postnatal mitochondrial genetic bottleneck" * Timothy Wai1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Eric A Shoubridge1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:472–473Year published:(2010)DOI:doi:10.1038/ng0610-472 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Wai et al. reply: As pointed out in the Correspondence by Samuels et al.1, the mechanism responsible for producing the mitochondrial genetic bottleneck has been the subject of some controversy2, 3, 4, 5, 6. Our recent study5 concluded that most of the intergenerational variance in heteroplasmy occurs as a result of the replication of a subpopulation of mitochondrial genomes in postnatal life. Samuels et al.1 object to our analysis on the grounds that we failed to normalize the values of heteroplasmy variance in germline cells for the initial heteroplasmy levels in the mothers, and they suggest that our conclusions were premature. They correctly state that the variance in heteroplasmy is expected to be maximal when the initial level of heteroplasmy is 0.5 and is expected to decrease as initial heteroplasmy levels approach the boundary conditions of 0 and 1. Normalization for initial heteroplasmy levels has the effect of flattening all variance measurements (compare Fig. 1a,b in Samuel et al.1)! but in fact has very little impact on our data except for those data collected in postnatal day (P) 8 animals, where we concede the differences we reported could have been due to the very low initial values of heteroplasmy of the mothers. They focus their discussion on two data points (P8 and P11) and state that there does not appear to be any discernable difference between the two. View full text Author information * Author information * Supplementary information Affiliations * Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada. * Timothy Wai & * Eric A Shoubridge * Department of Human Genetics, McGill University, Montreal, Quebec, Canada. * Timothy Wai & * Eric A Shoubridge Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Eric A Shoubridge (eric@ericpc.mni.mcgill.ca) Supplementary information * Author information * Supplementary information PDF files * Supplementary Note (68K) Additional data
• Shaping a better rice plant
  Springer N - Nat Genet 42(6):475-476 (2010)
  Two studies describe how regulatory variation at the rice gene OsSPL14 can lead to altered plant morphology and improve grain yield. These studies support the possibility of improving rice yield through changing plant architecture.
• Relics of selection in the mycobacterial genome
  Sassetti CM Rubin EJ - Nat Genet 42(6):476-478 (2010)
  A new study reports the whole-genome sequences of 21 Mycobacterium tuberculosis complex strains, selected to represent geographically diverse isolates. Comparative genomic analyses identify surprising conservation of epitopes recognized by human T cells.
• Another piece of the autism puzzle
  State MW - Nat Genet 42(6):478-479 (2010)
  A new study has identified rare de novo mutations in SHANK2 in individuals with autism and/or mental retardation. SHANK2 encodes a scaffolding protein present in excitatory synapses. This finding sheds some light on the pathophysiology of social and cognitive disability.
• Research highlights
  - Nat Genet 42(6):481 (2010)
  
• De novo mutations of SETBP1 cause Schinzel-Giedion syndrome
  Hoischen A van Bon BW Gilissen C Arts P van Lier B Steehouwer M de Vries P de Reuver R Wieskamp N Mortier G Devriendt K Amorim MZ Revencu N Kidd A Barbosa M Turner A Smith J Oley C Henderson A Hayes IM Thompson EM Brunner HG de Vries BB Veltman JA - Nat Genet 42(6):483-485 (2010)
  Nature Genetics | Brief Communication De novo mutations of SETBP1 cause Schinzel-Giedion syndrome * Alexander Hoischen1, 14 Search for this author in: * NPG journals * PubMed * Google Scholar * Bregje W M van Bon1, 14 Search for this author in: * NPG journals * PubMed * Google Scholar * Christian Gilissen1, 14 Search for this author in: * NPG journals * PubMed * Google Scholar * Peer Arts1 Search for this author in: * NPG journals * PubMed * Google Scholar * Bart van Lier1 Search for this author in: * NPG journals * PubMed * Google Scholar * Marloes Steehouwer1 Search for this author in: * NPG journals * PubMed * Google Scholar * Petra de Vries1 Search for this author in: * NPG journals * PubMed * Google Scholar * Rick de Reuver1 Search for this author in: * NPG journals * PubMed * Google Scholar * Nienke Wieskamp1 Search for this author in: * NPG journals * PubMed * Google Scholar * Geert Mortier2 Search for this author in: * NPG journals * PubMed * Google Scholar * Koen Devriendt3 Search for this author in: * NPG journals * PubMed * Google Scholar * Marta Z Amorim4 Search for this author in: * NPG journals * PubMed * Google Scholar * Nicole Revencu5 Search for this author in: * NPG journals * PubMed * Google Scholar * Alexa Kidd6 Search for this author in: * NPG journals * PubMed * Google Scholar * Mafalda Barbosa7 Search for this author in: * NPG journals * PubMed * Google Scholar * Anne Turner8 Search for this author in: * NPG journals * PubMed * Google Scholar * Janine Smith9 Search for this author in: * NPG journals * PubMed * Google Scholar * Christina Oley10 Search for this author in: * NPG journals * PubMed * Google Scholar * Alex Henderson11 Search for this author in: * NPG journals * PubMed * Google Scholar * Ian M Hayes12 Search for this author in: * NPG journals * PubMed * Google Scholar * Elizabeth M Thompson13 Search for this author in: * NPG journals * PubMed * Google Scholar * Han G Brunner1 Search for this author in: * NPG journals * PubMed * Google Scholar * Bert B A de Vries1 Search for this author in: * NPG journals * PubMed * Google Scholar * Joris A Veltman1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:483–485Year published:(2010)DOI:doi:10.1038/ng.581Received09 February 2010Accepted08 April 2010Published online02 May 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Schinzel-Giedion syndrome is characterized by severe mental retardation, distinctive facial features and multiple congenital malformations; most affected individuals die before the age of ten. We sequenced the exomes of four affected individuals (cases) and found heterozygous de novo variants in SETBP1 in all four. We also identified SETBP1 mutations in eight additional cases using Sanger sequencing. All mutations clustered to a highly conserved 11-bp exonic region, suggesting a dominant-negative or gain-of-function effect. View full text Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Alexander Hoischen, * Bregje W M van Bon & * Christian Gilissen Affiliations * Department of Human Genetics, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. * Alexander Hoischen, * Bregje W M van Bon, * Christian Gilissen, * Peer Arts, * Bart van Lier, * Marloes Steehouwer, * Petra de Vries, * Rick de Reuver, * Nienke Wieskamp, * Han G Brunner, * Bert B A de Vries & * Joris A Veltman * Centre for Medical Genetics, Antwerp University Hospital, Antwerp, Belgium. * Geert Mortier * Centre for Human Genetics, Leuven University Hospital, Leuven, Belgium. * Koen Devriendt * Serviço de Genética de Coimbra, Hospital Pediátrico de Coimbra, Coimbra, Portugal. * Marta Z Amorim * Centre for Human Genetics, Cliniques Universitaires St. Luc, Université Catholique de Louvain, Brussels, Belgium. * Nicole Revencu * Canterbury Health Laboratories, Christchurch Hospital, Christchurch, New Zealand. * Alexa Kidd * Centro de Genética Médica Doutor Jacinto Magalhães, Instituto Nacional de Saúde Doutor Ricardo, Porto, Portugal. * Mafalda Barbosa * Department of Medical Genetics, Sydney Children's Hospital, Sydney, Australia. * Anne Turner * Department of Clinical Genetics, The Children's Hospital at Westmead, Sydney, Australia. * Janine Smith * Clinical Genetics Unit, Birmingham Women's Hospital, Birmingham, UK. * Christina Oley * Institute of Human Genetics, Newcastle upon Tyne Hospitals National Health Service Foundation Trust, Newcastle upon Tyne, UK. * Alex Henderson * Northern Regional Genetics Service, Auckland, New Zealand. * Ian M Hayes * South Australian Clinical Genetics Service, South Australian Pathology, Women's and Children's Hospital, North Adelaide, South Australia, Australia. * Elizabeth M Thompson Contributions A. Hoischen, B.W.M.v.B., C.G., H.G.B., B.B.A.d.V. and J.A.V. conceived the project and planned the experiments. B.W.M.v.B., H.G.B. and B.B.A.d.V. performed review of phenotypes and sample collection. G.M., K.D., M.Z.A., N.R., A.K., M.B., A.T., J.S., C.O., A. Henderson, I.M.H. and E.M.T. clinically characterized the Schinzel-Giedion syndrome cases and collected blood samples. A. Hoischen, P.A. and B.v.L. performed next-generation sequencing experiments. M.S. and P.d.V. performed validation experiments. C.G., R.d.R. and N.W. analyzed and interpreted the data. A. Hoischen, B.W.M.v.B., C.G. and J.A.V. prepared the draft manuscript. All authors contributed to the final manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Joris A Veltman (j.veltman@antrg.umcn.nl) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (920K) Supplementary Tables 1–3, Supplementary Figures 1–3 and Supplementary Note Additional data
• Mutations in the guanine nucleotide exchange factor gene IQSEC2 cause nonsyndromic intellectual disability
  - Nat Genet 42(6):486-488 (2010)
  Nature Genetics | Brief Communication Mutations in the guanine nucleotide exchange factor gene IQSEC2 cause nonsyndromic intellectual disability * Cheryl Shoubridge1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Patrick S Tarpey3 Search for this author in: * NPG journals * PubMed * Google Scholar * Fatima Abidi4 Search for this author in: * NPG journals * PubMed * Google Scholar * Sarah L Ramsden5 Search for this author in: * NPG journals * PubMed * Google Scholar * Sinitdhorn Rujirabanjerd1, 6 Search for this author in: * NPG journals * PubMed * Google Scholar * Jessica A Murphy7 Search for this author in: * NPG journals * PubMed * Google Scholar * Jackie Boyle8 Search for this author in: * NPG journals * PubMed * Google Scholar * Marie Shaw1 Search for this author in: * NPG journals * PubMed * Google Scholar * Alison Gardner1 Search for this author in: * NPG journals * PubMed * Google Scholar * Anne Proos9 Search for this author in: * NPG journals * PubMed * Google Scholar * Helen Puusepp9 Search for this author in: * NPG journals * PubMed * Google Scholar * F Lucy Raymond10 Search for this author in: * NPG journals * PubMed * Google Scholar * Charles E Schwartz4 Search for this author in: * NPG journals * PubMed * Google Scholar * Roger E Stevenson4 Search for this author in: * NPG journals * PubMed * Google Scholar * Gill Turner8 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Field8 Search for this author in: * NPG journals * PubMed * Google Scholar * Randall S Walikonis7 Search for this author in: * NPG journals * PubMed * Google Scholar * Robert J Harvey5 Search for this author in: * NPG journals * PubMed * Google Scholar * Anna Hackett8 Search for this author in: * NPG journals * PubMed * Google Scholar * P Andrew Futreal3 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael R Stratton3 Search for this author in: * NPG journals * PubMed * Google Scholar * Jozef Gécz1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume:42,Pages:486–488Year published:(2010)DOI:doi:10.1038/ng.588Received21 December 2009Accepted07 April 2010Published online16 May 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The first family identified as having a nonsyndromic intellectual disability was mapped in 1988. Here we show that a mutation of IQSEC2, encoding a guanine nucleotide exchange factor for the ADP-ribosylation factor family of small GTPases, caused this disorder. In addition to MRX1, IQSEC2 mutations were identified in three other families with X-linked intellectual disability. This discovery was made possible by systematic and unbiased X chromosome exome resequencing. View full text Figures at a glance * Figure 1: Identification of IQSEC2 mutations. cDNA (NM_001111125) and protein (NP_001104595) annotation of individual mutations is shown for each family. Pedigrees of MRX1 and MRX18 families have been updated since their last publication. Open symbols represent normal individuals, filled squares represent affected males, open circles with middle dots represent carrier females and cross-hatched squares represent males with learning problems but without an IQSEC2 mutation. Two carrier females with some learning problems from the MRX18 and AU128 families are shown with half the circle black. Individual generations are numbered with Roman numerals on the left of each pedigree. Individuals tested for the nucleotide substitution in each family are indicated either M (mutant allele) or M/N (mutant and normal allele). The genotypes of some females tested have not been shown due to privacy issues. * Figure 2: IQSEC2 structure and mutations. () Scheme of the human IQSEC2 protein (NP_001104595); shown are the IQ-like domain, Sec7 domain, pleckstrin homology domain (PH) and PDZ binding motif (UniprotKB/Swiss-Prot for Q5J85;1,488-amino-acid protein). Mutations in each family are shown above. () Missense mutations introduced into the Sec7 domain (light gray) diminish the GTP binding activity compared to the Sec7 wild-type (black) activity to levels seen with the E849A dominant negative mutant (dark gray) predicted to reduce GEF activity of the Sec7 domain. An all-groups comparison of the mean pMol of GTP bound to ARF6 was achieved by linear mixed model analysis. *P < 0.0001 compared to Sec7Wt. () Wild-type (Wt) ARF6-HA and Flag-tagged wild-type or mutant IQSEC2 were transfected into HEK293 cells and lysates were subjected to a pull-down assay with GST:GGA3 to isolate ARF6-GTP. The precipitates (above, top row) and lysates (above, bottom row) were probed with anti-HA to detect ARF6 and anti-Flag to detect expression ! of IQSEC2 (above, middle row). ARF6-GTP levels were normalized to total ARF6 levels and shown as the fold-increase over ARF6 transfected with empty vector. The E849K dominant negative mutation abolishes GEF activity of the Sec 7 domain8. Data are mean ± s.e.m. from three independent experiments (bottom panel). () The IQ-like motif sequence lacks the G and second basic residue of the IQ motif. Characters within parentheses can substitute for each other. The R359C mutation disrupts the basic (R) residue (in bold and boxed). Author information * Author information * Supplementary information Affiliations * Genetics and Molecular Pathology, SA Pathology, Adelaide, Australia. * Cheryl Shoubridge, * Sinitdhorn Rujirabanjerd, * Marie Shaw, * Alison Gardner & * Jozef Gécz * Department of Paediatrics, The University of Adelaide, Adelaide, Australia. * Cheryl Shoubridge & * Jozef Gécz * Cancer Genome Project, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. * Patrick S Tarpey, * P Andrew Futreal & * Michael R Stratton * J.C. Self Research Institute, Greenwood Genetic Center, Greenwood, South Carolina, USA. * Fatima Abidi, * Charles E Schwartz & * Roger E Stevenson * Department of Pharmacology, The School of Pharmacy, London, UK. * Sarah L Ramsden & * Robert J Harvey * Department of Pathology, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand. * Sinitdhorn Rujirabanjerd * Department of Physiology and Neurobiology, University of Connecticut, Storrs, Connecticut, USA. * Jessica A Murphy & * Randall S Walikonis * Genetics of Learning Disability Service of New South Wales, Hunter Genetics, Newcastle, Australia. * Jackie Boyle, * Gill Turner, * Michael Field & * Anna Hackett * Pacific Laboratory Medicine Services, Laboratory and Community Genetics, Royal North Shore Hospital, St. Leonards, New South Wales, Australia. * Anne Proos & * Helen Puusepp * Cambridge Institute of Medical Research, Cambridge, UK. * F Lucy Raymond Contributions C.S., M.S., F.A., A.G. and J.B. assembled the extended families and confirmed, tracked and analyzed the changes. A.P., H.P. and M.S. performed additional subject and control screening. P.S.T., A.F. and M.R.S. supervised the X-chromosome sequencing, collation and analysis of the sequencing data. A.H., M.F., R.E.S., G.T., C.E.S. and F.L.R. contributed families and clinical data on affected individuals. C.S., S.L.R., J.A.M., R.S.W., R.J.H. and S.R. performed functional assays. C.S. and J.G. conceived and designed the study and wrote the first draft of the manuscript. J.G. directed the study. All authors contributed to discussion of the results and manuscript preparation. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Cheryl Shoubridge (cheryl.shoubridge@adelaide.edu.au) or * Jozef Gécz (jozef.gecz@adelaide.edu.au) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (960K) Supplementary Methods, Supplementary Note, Supplementary Figures 1 and 2 and Supplementary Tables 1 and 2 Additional data
• Mutations in the SHANK2 synaptic scaffolding gene in autism spectrum disorder and mental retardation
  - Nat Genet 42(6):489-491 (2010)
  Nature Genetics | Brief Communication Mutations in the SHANK2 synaptic scaffolding gene in autism spectrum disorder and mental retardation * Simone Berkel1 Search for this author in: * NPG journals * PubMed * Google Scholar * Christian R Marshall2 Search for this author in: * NPG journals * PubMed * Google Scholar * Birgit Weiss1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jennifer Howe2 Search for this author in: * NPG journals * PubMed * Google Scholar * Ralph Roeth1 Search for this author in: * NPG journals * PubMed * Google Scholar * Ute Moog3 Search for this author in: * NPG journals * PubMed * Google Scholar * Volker Endris1 Search for this author in: * NPG journals * PubMed * Google Scholar * Wendy Roberts4 Search for this author in: * NPG journals * PubMed * Google Scholar * Peter Szatmari5 Search for this author in: * NPG journals * PubMed * Google Scholar * Dalila Pinto2 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Bonin6 Search for this author in: * NPG journals * PubMed * Google Scholar * Angelika Riess6 Search for this author in: * NPG journals * PubMed * Google Scholar * Hartmut Engels7 Search for this author in: * NPG journals * PubMed * Google Scholar * Rolf Sprengel8 Search for this author in: * NPG journals * PubMed * Google Scholar * Stephen W Scherer2, 9 Search for this author in: * NPG journals * PubMed * Google Scholar * Gudrun A Rappold1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:489–491Year published:(2010)DOI:doi:10.1038/ng.589Received21 January 2010Accepted15 April 2010Published online16 May 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Using microarrays, we identified de novo copy number variations in the SHANK2 synaptic scaffolding gene in two unrelated individuals with autism-spectrum disorder (ASD) and mental retardation. DNA sequencing of SHANK2 in 396 individuals with ASD, 184 individuals with mental retardation and 659 unaffected individuals (controls) revealed additional variants that were specific to ASD and mental retardation cases, including a de novo nonsense mutation and seven rare inherited changes. Our findings further link common genes between ASD and intellectual disability. View full text Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE20533 Author information * Accession codes * Author information * Supplementary information Affiliations * Department of Molecular Human Genetics, Ruprecht-Karls-University, Heidelberg, Germany. * Simone Berkel, * Birgit Weiss, * Ralph Roeth, * Volker Endris & * Gudrun A Rappold * The Centre for Applied Genomics, The Hospital for Sick Children, University of Toronto, Ontario, Canada. * Christian R Marshall, * Jennifer Howe, * Dalila Pinto & * Stephen W Scherer * Department of Human Genetics, Ruprecht-Karls-University, Heidelberg, Germany. * Ute Moog * Autism Research Unit, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada. * Wendy Roberts * Offord Centre for Child Studies, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada. * Peter Szatmari * Department of Medical Genetics, Institute of Human Genetics, Tübingen University, Tübingen, Germany. * Michael Bonin & * Angelika Riess * Institute of Human Genetics, Rheinische Friedrich-Wilhelms-University, Bonn University, Bonn, Germany. * Hartmut Engels * Max Planck Institute for Medical Research (MPI), Ruprecht-Karls-University, Heidelberg, Germany. * Rolf Sprengel * Department of Molecular Genetics, University of Toronto, Ontario, Canada. * Stephen W Scherer Contributions S.B. performed the majority of the experiments, designed the figures and contributed to the manuscript. C.R.M., D.P. and M.B. carried out array analyses. S.B. and C.R.M. performed breakpoint mapping. B.W., J.H., R.R. and V.E. performed sequencing and FISH analysis. R.S. contributed to the experimental design. U.M., W.R., P.S., H.E. and A.R. provided case material and clinical information. All co-authors commented on the manuscript. G.A.R. conceived and directed the study. Data interpretation and writing of the manuscript was carried out by S.W.S. and G.A.R. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Gudrun A Rappold (gudrun_rappold@med.uni-heidelberg.de) Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–4, Supplementary Tables 1–3 and Supplementary Methods Additional data
• Variation in CDKN2A at 9p21.3 influences childhood acute lymphoblastic leukemia risk
  - Nat Genet 42(6):492-494 (2010)
  Nature Genetics | Brief Communication Variation in CDKN2A at 9p21.3 influences childhood acute lymphoblastic leukemia risk * Amy L Sherborne1, 20 Search for this author in: * NPG journals * PubMed * Google Scholar * Fay J Hosking1, 20 Search for this author in: * NPG journals * PubMed * Google Scholar * Rashmi B Prasad2 Search for this author in: * NPG journals * PubMed * Google Scholar * Rajiv Kumar2 Search for this author in: * NPG journals * PubMed * Google Scholar * Rolf Koehler3 Search for this author in: * NPG journals * PubMed * Google Scholar * Jayaram Vijayakrishnan1 Search for this author in: * NPG journals * PubMed * Google Scholar * Elli Papaemmanuil1 Search for this author in: * NPG journals * PubMed * Google Scholar * Claus R Bartram3 Search for this author in: * NPG journals * PubMed * Google Scholar * Martin Stanulla4 Search for this author in: * NPG journals * PubMed * Google Scholar * Martin Schrappe4 Search for this author in: * NPG journals * PubMed * Google Scholar * Andreas Gast2 Search for this author in: * NPG journals * PubMed * Google Scholar * Sara E Dobbins1 Search for this author in: * NPG journals * PubMed * Google Scholar * Yussanne Ma1 Search for this author in: * NPG journals * PubMed * Google Scholar * Eamonn Sheridan5 Search for this author in: * NPG journals * PubMed * Google Scholar * Malcolm Taylor6 Search for this author in: * NPG journals * PubMed * Google Scholar * Sally E Kinsey7 Search for this author in: * NPG journals * PubMed * Google Scholar * Tracey Lightfoot8 Search for this author in: * NPG journals * PubMed * Google Scholar * Eve Roman8 Search for this author in: * NPG journals * PubMed * Google Scholar * Julie A E Irving9 Search for this author in: * NPG journals * PubMed * Google Scholar * James M Allan9 Search for this author in: * NPG journals * PubMed * Google Scholar * Anthony V Moorman9 Search for this author in: * NPG journals * PubMed * Google Scholar * Christine J Harrison9 Search for this author in: * NPG journals * PubMed * Google Scholar * Ian P Tomlinson10 Search for this author in: * NPG journals * PubMed * Google Scholar * Sue Richards11 Search for this author in: * NPG journals * PubMed * Google Scholar * Martin Zimmermann12 Search for this author in: * NPG journals * PubMed * Google Scholar * Csaba Szalai13 Search for this author in: * NPG journals * PubMed * Google Scholar * Ágnes F Semsei13 Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel J Erdelyi13 Search for this author in: * NPG journals * PubMed * Google Scholar * Maja Krajinovic14 Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel Sinnett14 Search for this author in: * NPG journals * PubMed * Google Scholar * Jasmine Healy14 Search for this author in: * NPG journals * PubMed * Google Scholar * Anna Gonzalez Neira15 Search for this author in: * NPG journals * PubMed * Google Scholar * Norihiko Kawamata16 Search for this author in: * NPG journals * PubMed * Google Scholar * Seishi Ogawa17 Search for this author in: * NPG journals * PubMed * Google Scholar * H Phillip Koeffler18 Search for this author in: * NPG journals * PubMed * Google Scholar * Kari Hemminki2 Search for this author in: * NPG journals * PubMed * Google Scholar * Mel Greaves19 Search for this author in: * NPG journals * PubMed * Google Scholar * Richard S Houlston1, 20 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:492–494Year published:(2010)DOI:doi:10.1038/ng.585Received25 January 2010Accepted26 March 2010Published online09 May 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Using data from a genome-wide association study of 907 individuals with childhood acute lymphoblastic leukemia (cases) and 2,398 controls and with validation in samples totaling 2,386 cases and 2,419 controls, we have shown that common variation at 9p21.3 (rs3731217, intron 1 of CDKN2A) influences acute lymphoblastic leukemia risk (odds ratio = 0.71, P = 3.01 × 10−11), irrespective of cell lineage. View full text Figures at a glance * Figure 1: Forest plots of effect size and direction for 9p21.3 (rs3731217) association. (–) Association between all cases of ALL (), BCP-ALL cases () and T-ALL cases and controls (). Boxes denote OR point estimates, with their areas being proportional to the inverse variance weight of the estimate. Horizontal lines represent 95% CIs. The diamond and dashed line represent the summary OR computed under a fixed effects model, with the 95% CI indicated by the width of the diamond. The unbroken vertical line is at the null value (OR = 1.0). * Figure 2: LD structure and association results for the 9p21.3 ALL locus. The local recombination rate is plotted in dark blue over this 174-kb chromosomal segment. Armitage trend test P values (as –log10P values along the left y axis; note the broken axis between 4.0 and 10.5) are shown for the SNPs analyzed. Each triangle represents a SNP genotyped in the GWA study, circles represent imputed SNPs, and the most associated SNP in the combined analysis, rs3731217, is marked by a triangle (blue in combined analysis). The color intensity of each □ reflects the extent of LD with rs3731217, indicated by red (r2 > 0.8) going to white (r2 < 0.2). Physical positions are based on NCBI build 36 of the human genome. Also shown are the relative positions of genes mapping to each region of association. Exons of genes have been redrawn to show the relative positions in the gene, and therefore maps are not to physical scale. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Amy L Sherborne, * Fay J Hosking & * Richard S Houlston Affiliations * Section of Cancer Genetics, Institute of Cancer Research, Sutton, Surrey, UK. * Amy L Sherborne, * Fay J Hosking, * Jayaram Vijayakrishnan, * Elli Papaemmanuil, * Sara E Dobbins, * Yussanne Ma & * Richard S Houlston * Division of Molecular Genetic Epidemiology, German Cancer Research Centre, Heidelberg, Germany. * Rashmi B Prasad, * Rajiv Kumar, * Andreas Gast & * Kari Hemminki * Institute of Human Genetics, University of Heidelberg, Heidelberg, Germany. * Rolf Koehler & * Claus R Bartram * Department of Pediatrics, Acute Lymphoblastic Leukemia–Berlin-Frankfurt-Munster (ALL-BFM) Clinical Trial Center, University of Kiel, Kiel, Germany. * Martin Stanulla & * Martin Schrappe * Yorkshire Regional Genetic Service, St. James's University Hospital, Leeds, UK. * Eamonn Sheridan * Cancer Immunogenetics Group, School of Cancer Sciences, University of Manchester, Research Floor, St. Mary's Hospital, Manchester, UK. * Malcolm Taylor * Department of Paediatric and Adolescent Oncology and Haematology, St. James's University Hospital, Leeds, UK. * Sally E Kinsey * Epidemiology and Genetics Unit, Department of Health Sciences, University of York, York, UK. * Tracey Lightfoot & * Eve Roman * Northern Institute for Cancer Research, Newcastle University, Newcastle upon Tyne, UK. * Julie A E Irving, * James M Allan, * Anthony V Moorman & * Christine J Harrison * Molecular and Population Genetics, Wellcome Trust Centre for Human Genetics, Oxford, UK. * Ian P Tomlinson * Clinical Trial Service Unit and Epidemiological Studies Unit, Richard Doll Building, Old Road Campus, Roosevelt Drive, Oxford, UK. * Sue Richards * Department of Pediatric Hematology and Oncology, Medical School, Hannover, Germany. * Martin Zimmermann * Department of Genetic, Cell- and Immunobiology, SNP Core Facility Laboratorium, Semmelweis University, Budapest, Hungary. * Csaba Szalai, * Ágnes F Semsei & * Daniel J Erdelyi * Division of Hematology-Oncology, Research Center of the Sainte-Justine University Health Center, University of Montréal, Montréal, Quebec, Canada. * Maja Krajinovic, * Daniel Sinnett & * Jasmine Healy * Spanish National Cancer Research Center (CNIO), Madrid, Spain. * Anna Gonzalez Neira * Division of Hematology and Oncology, Cedars-Sinai Medical Center, University of California Los Angeles School of Medicine, Los Angeles, California, USA. * Norihiko Kawamata * Regeneration Medicine of Hematopoiesis, University of Tokyo, School of Medicine, Tokyo, Japan. * Seishi Ogawa * National University of Singapore Institute of Human Genetics, Singapore, Singapore. * H Phillip Koeffler * Section of Haemato-oncology, Institute of Cancer Research, Sutton, Surrey, UK. * Mel Greaves Contributions R.S.H. and M.G. obtained financial support. R.S.H. designed and provided overall project management. R.S.H. drafted the manuscript with contributions from F.J.H., A.L.S. and M.G.; A.L.S. performed overall project management, development, database development and oversaw laboratory analyses; F.J.H. performed statistical analyses; F.J.H. and A.L.S. performed bioinformatics analyses; J.V. and E.P. performed UK sample preparation and genotyping; E.S. and S.E.K. performed curation and sample preparation of the Medical Research Council ALL 97 trial samples; T.L. and E.R. managed and maintained UKCCS sample data; M.T. performed curation and sample preparation of United Kingdom Childhood Cancer Study samples; J.M.A. and J.A.E.I. performed ascertainment, curation and sample preparation of the Northern Institute for Cancer Research case series. I.P.T. generated and managed UK colorectal cancer control genotypes. A.V.M. and C.J.H. performed UK CDKN2A deletion analysis; N.K., S.O. and H! .P.K. carried out German CDKN2A deletion analysis; S.E.D. and Y.M. carried out HapMap and 1000 Genomes imputation; S.R. carried out survival analysis of UK data; M.Z. carried out survival analysis of German data; K.H. oversaw analysis of the German cohort; R.B.P., A.G. and R.K. conducted genotyping of German samples; R. Koehler, M. Stanulla, M. Schrappe and C.R.B. provided German DNA for analysis; D.J.E. and C.S. coordinated the data and sample collection of the Hungarian ALL cohort; A.F.S. genotyped the Hungarian samples; M.K., D.S. and J.H. performed curation and preparation of Canadian samples; A.G.N. was responsible for curation, management and genotyping of Spanish samples. All authors contributed to the final paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Richard S Houlston (richard.houlston@icr.ac.uk) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Methods, Supplementary Tables 1–6 and Supplementary Figures 1–3. Additional data
• Variants within the immunoregulatory CBLB gene are associated with multiple sclerosis
  - Nat Genet 42(6):495-497 (2010)
  Nature Genetics | Brief Communication Variants within the immunoregulatory CBLB gene are associated with multiple sclerosis * Serena Sanna1, 18 Search for this author in: * NPG journals * PubMed * Google Scholar * Maristella Pitzalis2, 18 Search for this author in: * NPG journals * PubMed * Google Scholar * Magdalena Zoledziewska2, 18 Search for this author in: * NPG journals * PubMed * Google Scholar * Ilenia Zara3 Search for this author in: * NPG journals * PubMed * Google Scholar * Carlo Sidore1, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Raffaele Murru5 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael B Whalen4 Search for this author in: * NPG journals * PubMed * Google Scholar * Fabio Busonero1 Search for this author in: * NPG journals * PubMed * Google Scholar * Andrea Maschio1 Search for this author in: * NPG journals * PubMed * Google Scholar * Gianna Costa5 Search for this author in: * NPG journals * PubMed * Google Scholar * Maria Cristina Melis5 Search for this author in: * NPG journals * PubMed * Google Scholar * Francesca Deidda2 Search for this author in: * NPG journals * PubMed * Google Scholar * Fausto Poddie2 Search for this author in: * NPG journals * PubMed * Google Scholar * Laura Morelli2 Search for this author in: * NPG journals * PubMed * Google Scholar * Gabriele Farina6 Search for this author in: * NPG journals * PubMed * Google Scholar * Yun Li7, 8, 9 Search for this author in: * NPG journals * PubMed * Google Scholar * Mariano Dei1 Search for this author in: * NPG journals * PubMed * Google Scholar * Sandra Lai1 Search for this author in: * NPG journals * PubMed * Google Scholar * Antonella Mulas1 Search for this author in: * NPG journals * PubMed * Google Scholar * Gianmauro Cuccuru1 Search for this author in: * NPG journals * PubMed * Google Scholar * Eleonora Porcu1 Search for this author in: * NPG journals * PubMed * Google Scholar * Liming Liang7, 10, 11 Search for this author in: * NPG journals * PubMed * Google Scholar * Patrizia Zavattari12 Search for this author in: * NPG journals * PubMed * Google Scholar * Loredana Moi5 Search for this author in: * NPG journals * PubMed * Google Scholar * Elisa Deriu2 Search for this author in: * NPG journals * PubMed * Google Scholar * M Francesca Urru4 Search for this author in: * NPG journals * PubMed * Google Scholar * Michele Bajorek13 Search for this author in: * NPG journals * PubMed * Google Scholar * Maria Anna Satta14 Search for this author in: * NPG journals * PubMed * Google Scholar * Eleonora Cocco5 Search for this author in: * NPG journals * PubMed * Google Scholar * Paola Ferrigno15 Search for this author in: * NPG journals * PubMed * Google Scholar * Stefano Sotgiu6 Search for this author in: * NPG journals * PubMed * Google Scholar * Maura Pugliatti6 Search for this author in: * NPG journals * PubMed * Google Scholar * Sebastiano Traccis16 Search for this author in: * NPG journals * PubMed * Google Scholar * Andrea Angius4 Search for this author in: * NPG journals * PubMed * Google Scholar * Maurizio Melis15 Search for this author in: * NPG journals * PubMed * Google Scholar * Giulio Rosati6 Search for this author in: * NPG journals * PubMed * Google Scholar * Gonçalo R Abecasis7 Search for this author in: * NPG journals * PubMed * Google Scholar * Manuela Uda1 Search for this author in: * NPG journals * PubMed * Google Scholar * Maria Giovanna Marrosu5 Search for this author in: * NPG journals * PubMed * Google Scholar * David Schlessinger17 Search for this author in: * NPG journals * PubMed * Google Scholar * Francesco Cucca1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:495–497Year published:(2010)DOI:doi:10.1038/ng.584Received21 December 2009Accepted13 April 2010Published online09 May 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg A genome-wide association scan of ~6.6 million genotyped or imputed variants in 882 Sardinian individuals with multiple sclerosis (cases) and 872 controls suggested association of CBLB gene variants with disease, which was confirmed in 1,775 cases and 2,005 controls (rs9657904, overall P = 1.60 × 10−10, OR = 1.40). CBLB encodes a negative regulator of adaptive immune responses, and mice lacking the ortholog are prone to experimental autoimmune encephalomyelitis, the animal model of multiple sclerosis. View full text Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Serena Sanna, * Maristella Pitzalis & * Magdalena Zoledziewska Affiliations * Istituto di Neurogenetica e Neurofarmacologia, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Italy. * Serena Sanna, * Carlo Sidore, * Fabio Busonero, * Andrea Maschio, * Mariano Dei, * Sandra Lai, * Antonella Mulas, * Gianmauro Cuccuru, * Eleonora Porcu, * Manuela Uda & * Francesco Cucca * Dipartimento di Scienze Biomediche, Università di Sassari, Sassari, Italy. * Maristella Pitzalis, * Magdalena Zoledziewska, * Francesca Deidda, * Fausto Poddie, * Laura Morelli, * Elisa Deriu & * Francesco Cucca * Center for Advanced Studies, Research and Development in Sardinia (CRS4), Laboratorio di Bioinformatica, Parco tecnologico della Sardegna, Pula, Italy. * Ilenia Zara * CRS4, Laboratorio di Genomica, Parco tecnologico della Sardegna, Pula, Italy. * Carlo Sidore, * Michael B Whalen, * M Francesca Urru & * Andrea Angius * Centro Sclerosi Multipla, Dipartimento di Scienze Neurologiche e Cardiovascolari, Università di Cagliari, Cagliari, Italy. * Raffaele Murru, * Gianna Costa, * Maria Cristina Melis, * Loredana Moi, * Eleonora Cocco & * Maria Giovanna Marrosu * Istituto di Neurologia Clinica, Università di Sassari, Sassari, Italy. * Gabriele Farina, * Stefano Sotgiu, * Maura Pugliatti & * Giulio Rosati * Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA. * Yun Li, * Liming Liang & * Gonçalo R Abecasis * Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA. * Yun Li * Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, USA. * Yun Li * Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA. * Liming Liang * Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA. * Liming Liang * Dipartimento di Scienze Biomediche e biotecnologie, Università di Cagliari, Cagliari, Italy. * Patrizia Zavattari * Azienda Ospedaliera Brotzu, Centro Trasfusionale, Cagliari, Italy. * Michele Bajorek * Azienda Sanitaria Locale 1, Sassari, Italy. * Maria Anna Satta * Azienda Ospedaliera Brotzu, Divisione di Neurologia, Cagliari, Italy. * Paola Ferrigno & * Maurizio Melis * Presidio Ospedaliero, Divisione Neurologia, Ozieri, Italy. * Sebastiano Traccis * Laboratory of Genetics, National Institute on Aging, Baltimore, Maryland, USA. * David Schlessinger Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Francesco Cucca (francesco.cucca@inn.cnr.it) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (844K) Supplementary Methods, Supplementary Tables 1–3 and Supplementary Figures 1 and 2. Additional data
• Human T cell epitopes of Mycobacterium tuberculosis are evolutionarily hyperconserved
  - Nat Genet 42(6):498-503 (2010)
  Nature Genetics | Article Human T cell epitopes of Mycobacterium tuberculosis are evolutionarily hyperconserved * Iñaki Comas1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jaidip Chakravartti2 Search for this author in: * NPG journals * PubMed * Google Scholar * Peter M Small3 Search for this author in: * NPG journals * PubMed * Google Scholar * James Galagan4 Search for this author in: * NPG journals * PubMed * Google Scholar * Stefan Niemann5 Search for this author in: * NPG journals * PubMed * Google Scholar * Kristin Kremer6 Search for this author in: * NPG journals * PubMed * Google Scholar * Joel D Ernst2 Search for this author in: * NPG journals * PubMed * Google Scholar * Sebastien Gagneux1, 7, 8 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume:42,Pages:498–503Year published:(2010)DOI:doi:10.1038/ng.590Received16 November 2009Accepted20 April 2010Published online23 May 2010 Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Mycobacterium tuberculosis is an obligate human pathogen capable of persisting in individual hosts for decades. We sequenced the genomes of 21 strains representative of the global diversity and six major lineages of the M. tuberculosis complex (MTBC) at 40- to 90-fold coverage using Illumina next-generation DNA sequencing. We constructed a genome-wide phylogeny based on these genome sequences. Comparative analyses of the sequences showed, as expected, that essential genes in MTBC were more evolutionarily conserved than nonessential genes. Notably, however, most of the 491 experimentally confirmed human T cell epitopes showed little sequence variation and had a lower ratio of nonsynonymous to synonymous changes than seen in essential and nonessential genes. We confirmed these findings in an additional data set consisting of 16 antigens in 99 MTBC strains. These findings are consistent with strong purifying selection acting on these epitopes, implying that MTBC might benefit f! rom recognition by human T cells. View full text Figures at a glance * Figure 1: Neighbor-joining phylogeny based on 9,037 variable common nucleotide positions across 21 human M. tuberculosis complex genome sequences. The tree is rooted with M. canettii, the closest known outgroup. Node support after 1,000 bootstrap replications is indicated. Branches are colored according to the six main phylogeographic lineages of MTBC defined previously3, 7, 8. Highly congruent topologies were obtained by maximum likelihood and Bayesian inference (Supplementary Fig. 1). * Figure 2: Average gene-by-gene nucleotide diversity across three gene classes. Box plot indicates median (horizontal line), interquartile range (box) and minimum and maximum values (whiskers). * Figure 3: dN/dS in various gene classes of MTBC. We calculated overall dN/dS on the basis of the number of nonredundant synonymous and nonsynonymous changes after comparing each of the 21 MTBC genomes to the inferred most likely recent common ancestor of MTBC. This shows that essential genes are more conserved than nonessential genes and that antigens are as conserved as essential genes. Figures for the epitope and non-epitope regions refer to the calculations after we excluded the three outlier antigens esxH, pstS1 and Rv1986. * Figure 4: Number of variable amino acid positions in 491 human T cell epitopes of MTBC. This demonstrates the remarkable lack of genetic variability among the regions of the genome that interact with the human immune system. Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Entrez Nucleotide * NC_000962 GenBank * SRX002001 * SRX002005 * SRX002429 * SRX003589 * SRX003590 * SRX005394 * SRX007715 * SRX007716 * SRX007718 * SRX007726 * SRX012272 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Medical Research Council, National Institute for Medical Research, London, UK. * Iñaki Comas & * Sebastien Gagneux * New York University School of Medicine, New York, New York, USA. * Jaidip Chakravartti & * Joel D Ernst * The Institute for Systems Biology and the Bill and Melinda Gates Foundation, Seattle, Washington, USA. * Peter M Small * Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, USA. * James Galagan * Research Centre Borstel, Molecular Mycobacteriology, Borstel, Germany. * Stefan Niemann * Mycobacteria Reference Laboratory (CIb-LIS), National Institute for Public Health and the Environment, Bilthoven, The Netherlands. * Kristin Kremer * Swiss Tropical and Public Health Institute, Basel, Switzerland. * Sebastien Gagneux * University of Basel, Basel, Switzerland. * Sebastien Gagneux Contributions I.C., J.D.E. and S.G. designed the study; P.M.S., S.N., K.K. and S.G. contributed sources of M. tuberculosis DNA and demographic information; I.C., J.C. and J.G. performed DNA sequencing and bioinformatics; I.C., P.M.S., J.D.E. and S.G. wrote the manuscript with comments from all authors. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Joel D Ernst (joel.ernst@med.nyu.edu) or * Sebastien Gagneux (sebastien.gagneux@unibas.ch) Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (736K) Supplementary Figures 1 and 2 and Supplementary Tables 1–6. Additional data
• Genome-wide association study identifies five new breast cancer susceptibility loci
  - Nat Genet 42(6):504-507 (2010)
  Nature Genetics | Letter Genome-wide association study identifies five new breast cancer susceptibility loci * Clare Turnbull1 Search for this author in: * NPG journals * PubMed * Google Scholar * Shahana Ahmed2 Search for this author in: * NPG journals * PubMed * Google Scholar * Jonathan Morrison3 Search for this author in: * NPG journals * PubMed * Google Scholar * David Pernet1 Search for this author in: * NPG journals * PubMed * Google Scholar * Anthony Renwick1 Search for this author in: * NPG journals * PubMed * Google Scholar * Mel Maranian2 Search for this author in: * NPG journals * PubMed * Google Scholar * Sheila Seal1 Search for this author in: * NPG journals * PubMed * Google Scholar * Maya Ghoussaini2 Search for this author in: * NPG journals * PubMed * Google Scholar * Sarah Hines1 Search for this author in: * NPG journals * PubMed * Google Scholar * Catherine S Healey2 Search for this author in: * NPG journals * PubMed * Google Scholar * Deborah Hughes1 Search for this author in: * NPG journals * PubMed * Google Scholar * Margaret Warren-Perry1 Search for this author in: * NPG journals * PubMed * Google Scholar * William Tapper4 Search for this author in: * NPG journals * PubMed * Google Scholar * Diana Eccles4 Search for this author in: * NPG journals * PubMed * Google Scholar * D Gareth Evans5 Search for this author in: * NPG journals * PubMed * Google Scholar * The Breast Cancer Susceptibility Collaboration (UK)1, 10 * Maartje Hooning6 Search for this author in: * NPG journals * PubMed * Google Scholar * Mieke Schutte6 Search for this author in: * NPG journals * PubMed * Google Scholar * Ans van den Ouweland7 Search for this author in: * NPG journals * PubMed * Google Scholar * Richard Houlston1 Search for this author in: * NPG journals * PubMed * Google Scholar * Gillian Ross8 Search for this author in: * NPG journals * PubMed * Google Scholar * Cordelia Langford9 Search for this author in: * NPG journals * PubMed * Google Scholar * Paul D P Pharoah2, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael R Stratton1, 9 Search for this author in: * NPG journals * PubMed * Google Scholar * Alison M Dunning2 Search for this author in: * NPG journals * PubMed * Google Scholar * Nazneen Rahman1 Search for this author in: * NPG journals * PubMed * Google Scholar * Douglas F Easton2, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:504–507Year published:(2010)DOI:doi:10.1038/ng.586Received15 December 2009Accepted09 April 2010Published online09 May 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Breast cancer is the most common cancer in women in developed countries. To identify common breast cancer susceptibility alleles, we conducted a genome-wide association study in which 582,886 SNPs were genotyped in 3,659 cases with a family history of the disease and 4,897 controls. Promising associations were evaluated in a second stage, comprising 12,576 cases and 12,223 controls. We identified five new susceptibility loci, on chromosomes 9, 10 and 11 (P = 4.6 × 10−7 to P = 3.2 × 10−15). We also identified SNPs in the 6q25.1 (rs3757318, P = 2.9 × 10−6), 8q24 (rs1562430, P = 5.8 × 10−7) and LSP1 (rs909116, P = 7.3 × 10−7) regions that showed more significant association with risk than those reported previously. Previously identified breast cancer susceptibility loci were also found to show larger effect sizes in this study of familial breast cancer cases than in previous population-based studies, consistent with polygenic susceptibility to the disease. View full text Author information * Author information * Supplementary information Affiliations * Section of Cancer Genetics, The Institute of Cancer Research, Sutton, Surrey, UK. * The Breast Cancer Susceptibility Collaboration, * Clare Turnbull, * David Pernet, * Anthony Renwick, * Sheila Seal, * Sarah Hines, * Deborah Hughes, * Margaret Warren-Perry, * Richard Houlston, * Michael R Stratton & * Nazneen Rahman * Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK. * Shahana Ahmed, * Mel Maranian, * Maya Ghoussaini, * Catherine S Healey, * Paul D P Pharoah, * Alison M Dunning & * Douglas F Easton * Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK. * Jonathan Morrison, * Paul D P Pharoah & * Douglas F Easton * Academic Unit of Genetic Medicine, University of Southampton, Southampton General Hospital, Southampton, UK. * William Tapper & * Diana Eccles * Department of Genetic Medicine, St. Mary's Hospital, Manchester, UK. * D Gareth Evans * Department of Medical Oncology, Erasmus University Medical Center, Rotterdam, The Netherlands. * Maartje Hooning & * Mieke Schutte * Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, The Netherlands. * Ans van den Ouweland * Breast Cancer Unit, Royal Marsden National Health Service Foundation Trust, London, UK. * Gillian Ross * Wellcome Trust Sanger Institute, Hinxton, UK. * Cordelia Langford & * Michael R Stratton * A full list of members is provided in the Supplementary Note. * The Breast Cancer Susceptibility Collaboration Consortia * The Breast Cancer Susceptibility Collaboration (UK) Contributions D.F.E., N.R., M.R.S., P.D.P.P. and A.M.D. obtained funding for the study. D.F.E. designed the study and drafted the manuscript. D.F.E. and C.T. conducted the statistical analyses. J.M. provided data management and bioinformatics support. C.T. and N.R. coordinated the Familial Breast Cancer Study (FBCS). D.P., A.R., S.S., S.H., D.H., M.W.-P., C.T. and N.R. coordinated the FBCS genotyping. P.D.P.P. and D.F.E. coordinated Studies of Epidemiology and Risk Factors in Cancer Heredity (SEARCH). S.A., M.M., M.G., C.S.H. and A.M.D. coordinated the stage 2 genotyping of the SEARCH and RBCS samples. M.H., M.S. and A.v.d.O. coordinated and provided samples and data from RBCS. C.L. coordinated the stage 1 genotyping. G.R. and R.H. provided data and samples from the Royal Marsden Hospital (RMH) study. W.T. and D.E. provided data and samples from the Prospective study of Outcomes in Sporadic vs. Hereditary breast cancer (POSH) study. D.E. and D.G.E. provided data and samples for FBCS. All ! authors provided critical review of the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Douglas F Easton (douglas@srl.cam.ac.uk) Supplementary information * Author information * Supplementary information Excel files * Supplementary Table 3 (32K) Genotype counts in cases and controls for all SNPs tested in stages 1 and 2 PDF files * Supplementary Text and Figures (124K) Supplementary Tables 1–6, Supplementary Figure 1 and Supplementary Note Additional data
• Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci
  - Nat Genet 42(6):508-514 (2010)
  Nature Genetics | Letter Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci * Eli A Stahl1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Soumya Raychaudhuri1, 2, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Elaine F Remmers4 Search for this author in: * NPG journals * PubMed * Google Scholar * Gang Xie5 Search for this author in: * NPG journals * PubMed * Google Scholar * Stephen Eyre6 Search for this author in: * NPG journals * PubMed * Google Scholar * Brian P Thomson2 Search for this author in: * NPG journals * PubMed * Google Scholar * Yonghong Li7 Search for this author in: * NPG journals * PubMed * Google Scholar * Fina A S Kurreeman1, 2, 8 Search for this author in: * NPG journals * PubMed * Google Scholar * Alexandra Zhernakova9 Search for this author in: * NPG journals * PubMed * Google Scholar * Anne Hinks6 Search for this author in: * NPG journals * PubMed * Google Scholar * Candace Guiducci2 Search for this author in: * NPG journals * PubMed * Google Scholar * Robert Chen1 Search for this author in: * NPG journals * PubMed * Google Scholar * Lars Alfredsson10 Search for this author in: * NPG journals * PubMed * Google Scholar * Christopher I Amos11 Search for this author in: * NPG journals * PubMed * Google Scholar * Kristin G Ardlie2 Search for this author in: * NPG journals * PubMed * Google Scholar * BIRAC Consortium33 * Anne Barton6 Search for this author in: * NPG journals * PubMed * Google Scholar * John Bowes6 Search for this author in: * NPG journals * PubMed * Google Scholar * Elisabeth Brouwer12 Search for this author in: * NPG journals * PubMed * Google Scholar * Noel P Burtt2 Search for this author in: * NPG journals * PubMed * Google Scholar * Joseph J Catanese7 Search for this author in: * NPG journals * PubMed * Google Scholar * Jonathan Coblyn1 Search for this author in: * NPG journals * PubMed * Google Scholar * Marieke J H Coenen13 Search for this author in: * NPG journals * PubMed * Google Scholar * Karen H Costenbader1 Search for this author in: * NPG journals * PubMed * Google Scholar * Lindsey A Criswell14 Search for this author in: * NPG journals * PubMed * Google Scholar * J Bart A Crusius15 Search for this author in: * NPG journals * PubMed * Google Scholar * Jing Cui1 Search for this author in: * NPG journals * PubMed * Google Scholar * Paul I W de Bakker2, 16 Search for this author in: * NPG journals * PubMed * Google Scholar * Philip L De Jager2, 17 Search for this author in: * NPG journals * PubMed * Google Scholar * Bo Ding10 Search for this author in: * NPG journals * PubMed * Google Scholar * Paul Emery18 Search for this author in: * NPG journals * PubMed * Google Scholar * Edward Flynn6 Search for this author in: * NPG journals * PubMed * Google Scholar * Pille Harrison19 Search for this author in: * NPG journals * PubMed * Google Scholar * Lynne J Hocking20 Search for this author in: * NPG journals * PubMed * Google Scholar * Tom W J Huizinga8 Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel L Kastner4 Search for this author in: * NPG journals * PubMed * Google Scholar * Xiayi Ke6 Search for this author in: * NPG journals * PubMed * Google Scholar * Annette T Lee21 Search for this author in: * NPG journals * PubMed * Google Scholar * Xiangdong Liu5 Search for this author in: * NPG journals * PubMed * Google Scholar * Paul Martin6 Search for this author in: * NPG journals * PubMed * Google Scholar * Ann W Morgan18 Search for this author in: * NPG journals * PubMed * Google Scholar * Leonid Padyukov22 Search for this author in: * NPG journals * PubMed * Google Scholar * Marcel D Posthumus12 Search for this author in: * NPG journals * PubMed * Google Scholar * Timothy R D J Radstake23 Search for this author in: * NPG journals * PubMed * Google Scholar * David M Reid20 Search for this author in: * NPG journals * PubMed * Google Scholar * Mark Seielstad24 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael F Seldin25 Search for this author in: * NPG journals * PubMed * Google Scholar * Nancy A Shadick1 Search for this author in: * NPG journals * PubMed * Google Scholar * Sophia Steer26 Search for this author in: * NPG journals * PubMed * Google Scholar * Paul P Tak27 Search for this author in: * NPG journals * PubMed * Google Scholar * Wendy Thomson6 Search for this author in: * NPG journals * PubMed * Google Scholar * Annette H M van der Helm-van Mil8 Search for this author in: * NPG journals * PubMed * Google Scholar * Irene E van der Horst-Bruinsma28 Search for this author in: * NPG journals * PubMed * Google Scholar * C Ellen van der Schoot29 Search for this author in: * NPG journals * PubMed * Google Scholar * Piet L C M van Riel23 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael E Weinblatt1 Search for this author in: * NPG journals * PubMed * Google Scholar * Anthony G Wilson30 Search for this author in: * NPG journals * PubMed * Google Scholar * Gert Jan Wolbink29, 31 Search for this author in: * NPG journals * PubMed * Google Scholar * B Paul Wordsworth19 Search for this author in: * NPG journals * PubMed * Google Scholar * YEAR Consortium33 * Cisca Wijmenga9 Search for this author in: * NPG journals * PubMed * Google Scholar * Elizabeth W Karlson1 Search for this author in: * NPG journals * PubMed * Google Scholar * Rene E M Toes8 Search for this author in: * NPG journals * PubMed * Google Scholar * Niek de Vries27 Search for this author in: * NPG journals * PubMed * Google Scholar * Ann B Begovich7, 32 Search for this author in: * NPG journals * PubMed * Google Scholar * Jane Worthington6, 34 Search for this author in: * NPG journals * PubMed * Google Scholar * Katherine A Siminovitch5, 34 Search for this author in: * NPG journals * PubMed * Google Scholar * Peter K Gregersen21, 34 Search for this author in: * NPG journals * PubMed * Google Scholar * Lars Klareskog22, 34 Search for this author in: * NPG journals * PubMed * Google Scholar * Robert M Plenge1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:508–514Year published:(2010)DOI:doi:10.1038/ng.582Received24 November 2009Accepted25 February 2010Published online09 May 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg To identify new genetic risk factors for rheumatoid arthritis, we conducted a genome-wide association study meta-analysis of 5,539 autoantibody-positive individuals with rheumatoid arthritis (cases) and 20,169 controls of European descent, followed by replication in an independent set of 6,768 rheumatoid arthritis cases and 8,806 controls. Of 34 SNPs selected for replication, 7 new rheumatoid arthritis risk alleles were identified at genome-wide significance (P < 5 × 10−8) in an analysis of all 41,282 samples. The associated SNPs are near genes of known immune function, including IL6ST, SPRED2, RBPJ, CCR6, IRF5 and PXK. We also refined associations at two established rheumatoid arthritis risk loci (IL2RA and CCL21) and confirmed the association at AFF3. These new associations bring the total number of confirmed rheumatoid arthritis risk loci to 31 among individuals of European ancestry. An additional 11 SNPs replicated at P < 0.05, many of which are validated autoimmune r! isk alleles, suggesting that most represent genuine rheumatoid arthritis risk alleles. View full text Figures at a glance * Figure 1: Associations with rheumatoid arthritis risk across four loci. Regional association plots show strength of association (−log10(P)) versus chromosomal position (kb) for all SNPs across 1 Mb regions centered on the newly validated SNPs (labeled). PGWAS values are plotted with diamonds for all SNPs, shaded white to red by the degree of LD (r2; see inset) with the validated SNP (larger red diamond). Poverall in combined analysis of GWAS and replication collections is plotted with a blue diamond. Local recombination rates estimated from HapMap CEU (cM/Mb, blue line) are plotted against the secondary y axis, showing recombination hotspots across the region. Labeled green arrows below the plots indicate genes and their orientations. () 2p14, SPRED2 locus. () 5q11, IL6ST-ANKRD55 locus. () 5q21, C5orf30 locus. () 10p15, IL2RA locus. * Figure 2: Previously validated autoimmune SNPs tested in our replication study. Eighteen SNPs tested in our replication samples were in LD (defined as r2 > 0.3) with a validated autoimmune risk allele. Of these, five were validated as rheumatoid arthritis risk alleles in our study (Poverall < 5 × 10−8, inner most circle), six were suggestive associations (Preplication < 0.05 but Poverall > 5 × 10−8) and six demonstrated no evidence of association in our replication samples (Preplication ≥ 0.05). For the 12 SNPs with suggestive or no evidence of association, each SNP is plotted by the strength of association with rheumatoid arthritis risk in the replication samples; those closer to the inner circle have more significant Preplication. All of the rheumatoid arthritis risk alleles confer risk in the same direction as the validated autoimmune risk alleles (when the same allele or a near perfect proxy was tested). We include the following as 'autoimmune' diseases in our study, listed on the outside of the circle, although these reflect diseases along ! the autoimmune-inflammatory spectrum: systemic lupus erythematosus (SLE), celiac disease, Crohn's disease, multiple sclerosis (MS), psoriasis, and type 1 diabetes (T1D) but other autoimmune diseases are not included (for example, autoimmune thyroiditis). Note that there are SNPs associated with rheumatoid arthritis and other autoimmune diseases not shown; we only include those SNPs tested as part of the current study. See Online Methods for details about the SNPs validated in other autoimmune diseases. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Jane Worthington, * Katherine A Siminovitch, * Peter K Gregersen & * Lars Klareskog Affiliations * Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital, Boston, Massachusetts, USA. * Eli A Stahl, * Soumya Raychaudhuri, * Fina A S Kurreeman, * Robert Chen, * Jonathan Coblyn, * Karen H Costenbader, * Jing Cui, * Nancy A Shadick, * Michael E Weinblatt, * Elizabeth W Karlson & * Robert M Plenge * Broad Institute, Cambridge, Massachusetts, USA. * Eli A Stahl, * Soumya Raychaudhuri, * Brian P Thomson, * Fina A S Kurreeman, * Candace Guiducci, * Kristin G Ardlie, * Noel P Burtt, * Paul I W de Bakker, * Philip L De Jager & * Robert M Plenge * Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA. * Soumya Raychaudhuri * Genetics and Genomics Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases, US National Institutes of Health, Bethesda, Maryland, USA. * Elaine F Remmers & * Daniel L Kastner * Department of Medicine, University of Toronto, Mount Sinai Hospital and University Health Network, Toronto, Ontario, Canada. * Gang Xie, * Xiangdong Liu & * Katherine A Siminovitch * Arthritis Research UK Epidemiology Unit, Stopford Building, The University of Manchester, Manchester, UK. * Stephen Eyre, * Anne Hinks, * Anne Barton, * John Bowes, * Edward Flynn, * Xiayi Ke, * Paul Martin, * Wendy Thomson & * Jane Worthington * Celera, Alameda, California, USA. * Yonghong Li, * Joseph J Catanese & * Ann B Begovich * Department of Rheumatology, Leiden University Medical Centre, Leiden, The Netherlands. * Fina A S Kurreeman, * Tom W J Huizinga, * Annette H M van der Helm-van Mil & * Rene E M Toes * Department of Genetics, University Medical Center Groningen and University of Groningen, Groningen, The Netherlands. * Alexandra Zhernakova & * Cisca Wijmenga * Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden. * Lars Alfredsson & * Bo Ding * University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA. * Christopher I Amos * Department of Rheumatology and Clinical Immunology, University Medical Center Groningen and University of Groningen, Groningen, The Netherlands. * Elisabeth Brouwer & * Marcel D Posthumus * Department of Human Genetics, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. * Marieke J H Coenen * Rosalind Russell Medical Research Center for Arthritis, Department of Medicine, University of California at San Francisco, San Francisco, California, USA. * Lindsey A Criswell * Laboratory of Immunogenetics, Department of Pathology, Vrije Universiteit Medical Center, Amsterdam, The Netherlands. * J Bart A Crusius * Division of Genetics, Brigham and Women's Hospital, Boston, Massachusetts, USA. * Paul I W de Bakker * Department of Neurology, Center for Neurologic Diseases, Brigham and Women's Hospital, Boston, Massachusetts, USA. * Philip L De Jager * National Institute for Health Research-Leeds Musculoskeletal Biomedical Research Unit, Leeds Institute of Molecular Medicine, University of Leeds, Leeds, UK. * Paul Emery & * Ann W Morgan * University of Oxford Institute of Musculoskeletal Sciences, Botnar Research Centre, Oxford, UK. * Pille Harrison & * B Paul Wordsworth * Musculoskeletal and Genetics Section, Division of Applied Medicine, University of Aberdeen, Aberdeen, UK. * Lynne J Hocking & * David M Reid * The Feinstein Institute for Medical Research, North Shore–Long Island Jewish Health System, Manhasset, New York, USA. * Annette T Lee & * Peter K Gregersen * Rheumatology Unit, Department of Medicine, Karolinska Institutet and Karolinska University Hospital Solna, Stockholm, Sweden. * Leonid Padyukov & * Lars Klareskog * Department of Rheumatology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. * Timothy R D J Radstake & * Piet L C M van Riel * Genome Institute of Singapore, Singapore. * Mark Seielstad * Rowe Program in Genetics, University of California at Davis, Davis, California, USA. * Michael F Seldin * Clinical and Academic Rheumatology, Kings College Hospital National Health Service Foundation Trust, Denmark Hill, London, UK. * Sophia Steer * Clinical Immunology and Rheumatology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands. * Paul P Tak & * Niek de Vries * Department of Rheumatology, Vrije Universiteit University Medical Center, Amsterdam, The Netherlands. * Irene E van der Horst-Bruinsma * Sanquin Research Landsteiner Laboratory, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands. * C Ellen van der Schoot & * Gert Jan Wolbink * School of Medicine and Biomedical Sciences, Sheffield University, Sheffield, UK. * Anthony G Wilson * Jan van Breemen Institute, Amsterdam, The Netherlands. * Gert Jan Wolbink * Roche Diagnostics, Pleasanton, California, USA. * Ann B Begovich * A full list of members is provided in the Supplementary Note. * BIRAC Consortium & * YEAR Consortium Consortia * BIRAC Consortium * YEAR Consortium Contributions R.M.P., S.R., E.A.S. E.A.S. (lead), S.R., F.A.S.K., R.C. J.W., K.A.S., P.K.G., L.K., N.A.S., M.E.W., C.W., M.J.H.C., N.d.V., P.P.T., E.W.K., R.E.M.T., T.W.J.H., A.B.B. (leads); E.F.R., G.X., S.E., B.P.T., Y.L., A.Z., A.H., C.G., L.A., C.I.A., K.G.A., A.B., J.B., E.B., N.P.B., J.J.C., J. Coblyn, K.H.C., L.A.C., J.B.A.C., J. Cui, P.I.W.d.B., P.L.D.J., B.D., P.E., E.F., P.H., L.J.H., D.L.K., X.K., A.T.L., X.L., P.M., A.W.M., L.P., M.D.P., T.R.D.J.R., D.M.R., M.S., M.F.S., S.S., W.T., A.H.M.v.d.H.-v.M., I.E.v.d.H.-B., C.E.v.d.S., P.L.C.M.v.R., A.G.W., G.J.W., B.P.W., BIRAC and YEAR consortia. R.M.P., E.A.S. (leads); S.R., F.A.S.K. (primary contributors); J.W., K.A.S., P.K.G., L.K., N.A.S., M.E.W., C.W., M.J.H.C., N.d.V., P.P.T., E.W.K., R.E.M.T., T.W.J.H., A.B.B., E.F.R., G.X., S.E., B.P.T., Y.L., A.Z., A.H., C.G., L.A., C.I.A., K.G.A., A.B., J.B., E.B., N.P.B., J.J.C., J. Coblyn, K.H.C., L.A.C., J.B.A.C., J. Cui, P.I.W.d.B., P.L.D.J., B.D., P.E., E.F., P.H., L.J.H., D.L.K., ! X.K., A.T.L., X.L., P.M., A.W.M., L.P., M.D.P., T.R.D.J.R., D.M.R., M.S., M.F.S., S.S., W.T., A.H.M.v.d.H.-v.M., I.E.v.d.H.-B., C.E.v.d.S., P.L.C.M.v.R., A.G.W., G.J.W., B.P.W. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Robert M Plenge (rplenge@partners.org) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (14M) Supplementary Note, Supplementary Tables 1–6 and Supplementary Figures 1–7 Additional data
• A regulatory variant in CCR6 is associated with rheumatoid arthritis susceptibility
  - Nat Genet 42(6):515-519 (2010)
  Nature Genetics | Letter A regulatory variant in CCR6 is associated with rheumatoid arthritis susceptibility * Yuta Kochi1, 12 Search for this author in: * NPG journals * PubMed * Google Scholar * Yukinori Okada2, 3, 12 Search for this author in: * NPG journals * PubMed * Google Scholar * Akari Suzuki1 Search for this author in: * NPG journals * PubMed * Google Scholar * Katsunori Ikari4 Search for this author in: * NPG journals * PubMed * Google Scholar * Chikashi Terao5 Search for this author in: * NPG journals * PubMed * Google Scholar * Atsushi Takahashi2 Search for this author in: * NPG journals * PubMed * Google Scholar * Keiko Yamazaki6 Search for this author in: * NPG journals * PubMed * Google Scholar * Naoya Hosono6 Search for this author in: * NPG journals * PubMed * Google Scholar * Keiko Myouzen1 Search for this author in: * NPG journals * PubMed * Google Scholar * Tatsuhiko Tsunoda7 Search for this author in: * NPG journals * PubMed * Google Scholar * Naoyuki Kamatani2 Search for this author in: * NPG journals * PubMed * Google Scholar * Tatsuya Furuichi8 Search for this author in: * NPG journals * PubMed * Google Scholar * Shiro Ikegawa8 Search for this author in: * NPG journals * PubMed * Google Scholar * Koichiro Ohmura5 Search for this author in: * NPG journals * PubMed * Google Scholar * Tsuneyo Mimori5 Search for this author in: * NPG journals * PubMed * Google Scholar * Fumihiko Matsuda9 Search for this author in: * NPG journals * PubMed * Google Scholar * Takuji Iwamoto4 Search for this author in: * NPG journals * PubMed * Google Scholar * Shigeki Momohara4 Search for this author in: * NPG journals * PubMed * Google Scholar * Hisashi Yamanaka4 Search for this author in: * NPG journals * PubMed * Google Scholar * Ryo Yamada1, 9 Search for this author in: * NPG journals * PubMed * Google Scholar * Michiaki Kubo6 Search for this author in: * NPG journals * PubMed * Google Scholar * Yusuke Nakamura10, 11 Search for this author in: * NPG journals * PubMed * Google Scholar * Kazuhiko Yamamoto1, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:515–519Year published:(2010)DOI:doi:10.1038/ng.583Received19 January 2010Accepted06 April 2010Published online09 May 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Rheumatoid arthritis is a common autoimmune disease with a complex genetic etiology. Here, through a genome-wide association study of rheumatoid arthritis, we identified a polymorphism in CCR6, the gene encoding chemokine (C-C motif) receptor 6 (a surface marker for Th17 cells) at 6q27, that was associated with rheumatoid arthritis susceptibility and was validated in two independent replication cohorts from Japan (rs3093024, a total of 7,069 individuals with rheumatoid arthritis (cases) and 20,727 controls, overall odds ratio = 1.19, P = 7.7 × 10−19). We identified a triallelic dinucleotide polymorphism of CCR6 (CCR6DNP) in strong linkage disequilibrium with rs3093024 that showed effects on gene transcription. The CCR6DNP genotype was correlated with the expression level of CCR6 and was associated with the presence of interleukin-17 (IL-17) in the sera of subjects with rheumatoid arthritis. Moreover, CCR6DNP was associated with susceptibility to Graves' and Crohn's diseas! es. These results suggest that CCR6 is critically involved in IL-17–driven autoimmunity in human diseases. View full text Figures at a glance * Figure 1: Results of GWAS and expression analysis around CCR6. () A Manhattan plot showing the −log10 (P value) of SNPs in the GWAS for 2,303 Japanese rheumatoid arthritis cases and 3,380 controls. Some SNPs in the HLA region are not included because they exceeded the upper limit of the plot. () LD map (upper), genomic structure (middle) and −log10 (P value) of SNPs in the GWAS (lower) around CCR6. The D′-based LD map (upper) is drawn based on the genotype data of rheumatoid arthritis cases and controls enrolled in the GWAS using Haploview software version 4.1. LD blocks involved in the selection of tag SNPs and the expression analysis are highlighted with a yellow bar. The diamond dots (lower) represent respective SNPs. Their densities in red represent LD indices (R2), with rs3093024 indicated as the largest dot. () Correlation between the genotypes of rs3093024 and the transcript levels of CCR6-a (NM_031409) in EBV-transfected cell lines (n = 57) stimulated with PMA. () The coefficients of determination, r2, of SNPs in the corre! lation analysis between the genotypes and the expression levels of CCR6-a transcripts. The correlation peak was observed at rs3093024. The red or gray dotted lines represent the correspondence of the chromosomal positions in and (the red line represents rs3093024). The plots of and were drawn by using SNAP version 2.1. * Figure 2: CCR6DNP genotype is correlated with the expression level of CCR6 and IL-17 status of rheumatoid arthritis cases. () Genomic position of disease-associated polymorphisms in CCR6 (CCR6-a and CCR6-b correspond to transcripts NM_031409 and NM_004367 in GenBank, respectively). () A newly identified SNP in the 3′ flanking sequence of rs968334. () Binding of nuclear factors from PSC cells to the 31-bp sequences around each allele of CCR6DNP was evaluated by EMSA. Unlabeled probes in 400-fold excess as compared to the labeled probes were used for the competition experiment. The densities of bands were quantified and normalized to that of the TG allele, and significant allelic differences were observed (the mean intensities from four independent experiments were 0.26, 0.76 and 1 for CA, CG and TG, respectively; P < 0.0001 by Student's t-test). () Enhanced activity of the 31-bp sequence region around CCR6DNP as evaluated by luciferase assay. SV40, promoter sequence of SV40; luc, luciferase). Data represent mean ± s.e.m. Representative data from three experiments performed in octuplicate are s! hown. *P = 1.3 × 10−7, **P = 7.4 × 10−5 and ***P = 0.0024 by Student's t-test. () Correlation between CCR6DNP genotype and expression of CCR6 as measured by quantitative TaqMan PCR of PSC cells (n = 57). () Correlation between CCR6DNP genotype and IL-17 status in the sera of rheumatoid arthritis cases. The ratios of cases that showed detectable levels of IL-17 (>4 pg/ml) are shown above (IL-17 active cases) and are significantly associated with the CCR6DNP genotype (P = 1.2 × 10−3 by trend test). Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Entrez Nucleotide * NM_031409 * NM_004367 Author information * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Yuta Kochi & * Yukinori Okada Affiliations * Laboratory for Autoimmune Diseases, Center for Genomic Medicine (CGM), RIKEN, Yokohama, Japan. * Yuta Kochi, * Akari Suzuki, * Keiko Myouzen, * Ryo Yamada & * Kazuhiko Yamamoto * Laboratory for Statistical Analysis, CGM, RIKEN, Yokohama, Japan. * Yukinori Okada, * Atsushi Takahashi & * Naoyuki Kamatani * Department of Allergy and Rheumatology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan. * Yukinori Okada & * Kazuhiko Yamamoto * Institute of Rheumatology, Tokyo Women's Medical University, Tokyo, Japan. * Katsunori Ikari, * Takuji Iwamoto, * Shigeki Momohara & * Hisashi Yamanaka * Department of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto, Japan. * Chikashi Terao, * Koichiro Ohmura & * Tsuneyo Mimori * Laboratory for Genotyping Development, CGM, RIKEN, Yokohama, Japan. * Keiko Yamazaki, * Naoya Hosono & * Michiaki Kubo * Laboratory for Medical Informatics, CGM, RIKEN, Yokohama, Japan. * Tatsuhiko Tsunoda * Laboratory for Bone and Joint Diseases, CGM, RIKEN, Yokohama, Japan. * Tatsuya Furuichi & * Shiro Ikegawa * Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan. * Fumihiko Matsuda & * Ryo Yamada * Laboratory for International Alliance, CGM, RIKEN, Yokohama, Japan. * Yusuke Nakamura * Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, Japan. * Yusuke Nakamura Contributions Y.K., Y.O. and K. Yamamoto. designed the study and drafted the manuscript. Y.O., A.T., T.T. and R.Y. analyzed the GWAS data. N.H. and M.K. performed the genotyping for the GWAS. Y.K. performed expression analysis of CCR6 and functional analysis of CCR6 polymorphisms. Y.K. and K.M. established the genotyping method for CCR6DNP. K.I., S.M. and H.Y. analyzed data for the first replication cohort of rheumatoid arthritis. C.T., K.O., T.M., R.Y. and F.M. analyzed the data for the second replication cohort of rheumatoid arthritis. Y.K. analyzed the data for the Graves' disease cohort. K. Yamazaki analyzed the data for the Crohn's disease cohort. T.F. and S.I. analyzed the data for the fourth control cohort. T.I. and K.I. analyzed CCR6 expression in the synovial tissues. Y.K. and A.S. analyzed the sera of subjects with rheumatoid arthritis. M.K., N.K. and Y.N. contributed to overall GWAS study design. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Yuta Kochi (ykochi@src.riken.jp) Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (804K) Supplementary Note, Supplementary Tables 1–6 and Supplementary Figures 1–6 Additional data
• Genome-wide association study identifies variants at CSF1, OPTN and TNFRSF11A as genetic risk factors for Paget's disease of bone
  Albagha OM Visconti MR Alonso N Langston AL Cundy T Dargie R Dunlop MG Fraser WD Hooper MJ Isaia G Nicholson GC Del Pino Montez J Gonzalez-Sarmiento R di Stefano M Tenesa A Walsh JP Ralston SH - Nat Genet 42(6):520-524 (2010)
  Nature Genetics | Letter Genome-wide association study identifies variants at CSF1, OPTN and TNFRSF11A as genetic risk factors for Paget's disease of bone * Omar M E Albagha1 Search for this author in: * NPG journals * PubMed * Google Scholar * Micaela R Visconti1 Search for this author in: * NPG journals * PubMed * Google Scholar * Nerea Alonso1 Search for this author in: * NPG journals * PubMed * Google Scholar * Anne L Langston1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Tim Cundy3 Search for this author in: * NPG journals * PubMed * Google Scholar * Rosemary Dargie4 Search for this author in: * NPG journals * PubMed * Google Scholar * Malcolm G Dunlop5 Search for this author in: * NPG journals * PubMed * Google Scholar * William D Fraser6 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael J Hooper7 Search for this author in: * NPG journals * PubMed * Google Scholar * Gianluca Isaia8 Search for this author in: * NPG journals * PubMed * Google Scholar * Geoff C Nicholson9 Search for this author in: * NPG journals * PubMed * Google Scholar * Javier del Pino Montes10 Search for this author in: * NPG journals * PubMed * Google Scholar * Rogelio Gonzalez-Sarmiento10 Search for this author in: * NPG journals * PubMed * Google Scholar * Marco di Stefano8 Search for this author in: * NPG journals * PubMed * Google Scholar * Albert Tenesa5 Search for this author in: * NPG journals * PubMed * Google Scholar * John P Walsh11 Search for this author in: * NPG journals * PubMed * Google Scholar * Stuart H Ralston1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:520–524Year published:(2010)DOI:doi:10.1038/ng.562Received21 January 2010Accepted05 March 2010Published online02 May 2010Corrected online16 May 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Paget's disease of bone (PDB) is a common disorder with a strong genetic component characterized by focal increases in bone turnover, which in some cases is caused by mutations in SQSTM1. To identify additional susceptibility genes, we performed a genome-wide association study in 750 individuals with PDB (cases) without SQSTM1 mutations and 1,002 controls and identified three candidate disease loci, which were then replicated in an independent set of 500 cases and 535 controls. The strongest signal was with rs484959 on 1p13 near the CSF1 gene (P = 5.38 × 10−24). Significant associations were also observed with rs1561570 on 10p13 within the OPTN gene (P = 6.09 × 10−13) and with rs3018362 on 18q21 near the TNFRSF11A gene (P = 5.27 × 10−13). These studies provide new insights into the pathogenesis of PDB and identify OPTN, CSF1 and TNFRSF11A as candidate genes for disease susceptibility. View full text Figures at a glance * Figure 1: Detection of loci conferring susceptibility to PDB by genome-wide association. Manhattan plot of association test results from the discovery cohort showing chromosomal positions of the 294,633 SNPs passing quality control plotted against genomic control–adjusted −log10P. Association with PDB was tested using stratified CMH tests. The red horizontal line indicates the threshold for genome-wide significance (P < 1.7 × 10−7). * Figure 2: Details of loci associated with PDB. (–) Association and LD plots of regions showing genome-wide significant association with PDB located on () 1p13, () 10p13 and () 18q21. The chromosomal positions (based on NCBI human genome Build 36) of the SNPs are plotted against genomic control–adjusted −log10P. Genotyped SNPs are shown as red triangles and imputed SNPs are blue diamonds. The estimated recombination rates (cM/Mb) from HapMap CEU release 22 are shown as gray lines; the red horizontal line indicates the genome-wide significance threshold (P < 1.7 × 10−7). Genotyped SNPs were tested using stratified CMH tests; imputed SNPs were tested using a regression analysis based on imputed allelic dosage and adjusting for population clusters. SNPs reaching genome-wide significance are indicated with red text. LD plots for the indicated regions are based on HapMap CEU release 22 showing LD blocks depicted for alleles with MAF > 0.05 using the r2 coloring scheme of Haploview37. The blue arrows indicate known gen! es in the region; possible recombination hot spots (>20 cM/Mb) are shown as green arrows on the LD plots. Change history * Change history * Author information * Supplementary informationCorrected online 16 May 2010In the version of this paper originally published online, the name of the 12th author was misspelled (the correct spelling is Javier del Pino Montes), affiliation 10 was incorrect (the correct affiliation is "Unidad de Medicina Molecular, Departamento de Medicina, Universidad de Salamanca and Hospital Universitario de Salamanca, RETICEF, Salamanca, Spain") and the following sentence was missing from the Acknowledgments ( "The work was also supported by grants from Cancer Research UK (C348/A3758, C348/A8896), and the Medical Research Council (G0000657-53203) to M.G.D. and A.T."). These errors have been corrected for the print, PDF and HTML versions of this article. Author information * Change history * Author information * Supplementary information Affiliations * Rheumatic Diseases Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK. * Omar M E Albagha, * Micaela R Visconti, * Nerea Alonso, * Anne L Langston & * Stuart H Ralston * Edinburgh Clinical Trials Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK. * Anne L Langston & * Stuart H Ralston * Department of Medicine, University of Auckland, Auckland, New Zealand. * Tim Cundy * University Department of Medicine, Glasgow Royal Infirmary, Glasgow, UK. * Rosemary Dargie * Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK. * Malcolm G Dunlop & * Albert Tenesa * Department of Clinical Chemistry, Royal Liverpool University Hospital, Liverpool, UK. * William D Fraser * Department of Medicine, The University of Sydney and Central Sydney Area Health Service, Sydney, Australia. * Michael J Hooper * Medical and Surgical Department, Geriatric Section, University of Torino, Torino, Italy. * Gianluca Isaia & * Marco di Stefano * Department of Clinical and Biomedical Sciences, Barwon Health, Geelong Hospital, University of Melbourne, Melbourne, Australia. * Geoff C Nicholson * Unidad de Medicina Molecular, Departamento de Medicina, Universidad de Salamanca and Hospital Universitario de Salamanca, RETICEF, Salamanca, Spain. * Javier del Pino Montes & * Rogelio Gonzalez-Sarmiento * Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Perth, Australia. * John P Walsh Contributions O.M.E.A. contributed to study design, oversaw the genotyping, performed data management, quality control, statistical and bioinformatic analyses and wrote the first draft of the manuscript. S.H.R. designed the study, obtained funding, coordinated the sample collection and phenotyping and revised the manuscript. A.L.L., T.C., R.D., W.D.F., M.J.H., G.I., G.C.N., J.d.P.M., R.G.-S., M.d.S. and J.P.W. contributed toward clinical sample collection and phenotyping. M.G.D. and A.T. provided genotype data for the stage 1 control samples. M.R.V. and N.A. assisted in sample preparation and performed DNA sequencing to identify samples with SQSTM1 mutations. All authors critically reviewed the article for important intellectual content and approved the final manuscript. Competing financial interests S.H.R. and O.M.E.A. have submitted patents on the use of various genetic markers as diagnostic tests in PDB, including those described in this paper. Corresponding author Correspondence to: * Stuart H Ralston (stuart.ralston@ed.ac.uk) Supplementary information * Change history * Author information * Supplementary information PDF files * Supplementary Text and Figures (256K) Supplementary Figures 1–3 and Supplementary Tables 1–8 Additional data
• A genome-wide association study of cleft lip with and without cleft palate identifies risk variants near MAFB and ABCA4
  Beaty TH Murray JC Marazita ML Munger RG Ruczinski I Hetmanski JB Liang KY Wu T Murray T Fallin MD Redett RA Raymond G Schwender H Jin SC Cooper ME Dunnwald M Mansilla MA Leslie E Bullard S Lidral AC Moreno LM Menezes R Vieira AR Petrin A Wilcox AJ Lie RT Jabs EW Wu-Chou YH Chen PK Wang H Ye X Huang S Yeow V Chong SS Jee SH Shi B Christensen K Melbye M Doheny KF Pugh EW Ling H Castilla EE Czeizel AE Ma L Field LL Brody L Pangilinan F Mills JL Molloy AM Kirke PN Scott JM Arcos-Burgos M Scott AF - Nat Genet 42(6):525-529 (2010)
  Nature Genetics | Letter A genome-wide association study of cleft lip with and without cleft palate identifies risk variants near MAFB and ABCA4 * Terri H Beaty1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jeffrey C Murray2 Search for this author in: * NPG journals * PubMed * Google Scholar * Mary L Marazita3 Search for this author in: * NPG journals * PubMed * Google Scholar * Ronald G Munger4 Search for this author in: * NPG journals * PubMed * Google Scholar * Ingo Ruczinski1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jacqueline B Hetmanski1 Search for this author in: * NPG journals * PubMed * Google Scholar * Kung Yee Liang1 Search for this author in: * NPG journals * PubMed * Google Scholar * Tao Wu1, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Tanda Murray1 Search for this author in: * NPG journals * PubMed * Google Scholar * M Daniele Fallin1 Search for this author in: * NPG journals * PubMed * Google Scholar * Richard A Redett6 Search for this author in: * NPG journals * PubMed * Google Scholar * Gerald Raymond6 Search for this author in: * NPG journals * PubMed * Google Scholar * Holger Schwender1 Search for this author in: * NPG journals * PubMed * Google Scholar * Sheng-Chih Jin1 Search for this author in: * NPG journals * PubMed * Google Scholar * Margaret E Cooper3 Search for this author in: * NPG journals * PubMed * Google Scholar * Martine Dunnwald2 Search for this author in: * NPG journals * PubMed * Google Scholar * Maria A Mansilla2 Search for this author in: * NPG journals * PubMed * Google Scholar * Elizabeth Leslie2 Search for this author in: * NPG journals * PubMed * Google Scholar * Stephen Bullard7 Search for this author in: * NPG journals * PubMed * Google Scholar * Andrew C Lidral7 Search for this author in: * NPG journals * PubMed * Google Scholar * Lina M Moreno7 Search for this author in: * NPG journals * PubMed * Google Scholar * Renato Menezes3 Search for this author in: * NPG journals * PubMed * Google Scholar * Alexandre R Vieira3 Search for this author in: * NPG journals * PubMed * Google Scholar * Aline Petrin2 Search for this author in: * NPG journals * PubMed * Google Scholar * Allen J Wilcox8 Search for this author in: * NPG journals * PubMed * Google Scholar * Rolv T Lie9 Search for this author in: * NPG journals * PubMed * Google Scholar * Ethylin W Jabs6, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Yah Huei Wu-Chou11 Search for this author in: * NPG journals * PubMed * Google Scholar * Philip K Chen11 Search for this author in: * NPG journals * PubMed * Google Scholar * Hong Wang6 Search for this author in: * NPG journals * PubMed * Google Scholar * Xiaoqian Ye10, 12 Search for this author in: * NPG journals * PubMed * Google Scholar * Shangzhi Huang13 Search for this author in: * NPG journals * PubMed * Google Scholar * Vincent Yeow14 Search for this author in: * NPG journals * PubMed * Google Scholar * Samuel S Chong15 Search for this author in: * NPG journals * PubMed * Google Scholar * Sun Ha Jee16 Search for this author in: * NPG journals * PubMed * Google Scholar * Bing Shi17 Search for this author in: * NPG journals * PubMed * Google Scholar * Kaare Christensen18 Search for this author in: * NPG journals * PubMed * Google Scholar * Mads Melbye19 Search for this author in: * NPG journals * PubMed * Google Scholar * Kimberly F Doheny20 Search for this author in: * NPG journals * PubMed * Google Scholar * Elizabeth W Pugh20 Search for this author in: * NPG journals * PubMed * Google Scholar * Hua Ling20 Search for this author in: * NPG journals * PubMed * Google Scholar * Eduardo E Castilla21 Search for this author in: * NPG journals * PubMed * Google Scholar * Andrew E Czeizel22 Search for this author in: * NPG journals * PubMed * Google Scholar * Lian Ma23 Search for this author in: * NPG journals * PubMed * Google Scholar * L Leigh Field24 Search for this author in: * NPG journals * PubMed * Google Scholar * Lawrence Brody25 Search for this author in: * NPG journals * PubMed * Google Scholar * Faith Pangilinan25 Search for this author in: * NPG journals * PubMed * Google Scholar * James L Mills26 Search for this author in: * NPG journals * PubMed * Google Scholar * Anne M Molloy27 Search for this author in: * NPG journals * PubMed * Google Scholar * Peadar N Kirke28 Search for this author in: * NPG journals * PubMed * Google Scholar * James M Scott27 Search for this author in: * NPG journals * PubMed * Google Scholar * Mauricio Arcos-Burgos29 Search for this author in: * NPG journals * PubMed * Google Scholar * Alan F Scott6 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:525–529Year published:(2010)DOI:doi:10.1038/ng.580Received17 December 2009Accepted06 April 2010Published online02 May 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Case-parent trios were used in a genome-wide association study of cleft lip with and without cleft palate. SNPs near two genes not previously associated with cleft lip with and without cleft palate (MAFB, most significant SNP rs13041247, with odds ratio (OR) per minor allele = 0.704, 95% CI 0.635–0.778, P = 1.44 × 10−11; and ABCA4, most significant SNP rs560426, with OR = 1.432, 95% CI 1.292–1.587, P = 5.01 × 10−12) and two previously identified regions (at chromosome 8q24 and IRF6) attained genome-wide significance. Stratifying trios into European and Asian ancestry groups revealed differences in statistical significance, although estimated effect sizes remained similar. Replication studies from several populations showed confirming evidence, with families of European ancestry giving stronger evidence for markers in 8q24, whereas Asian families showed stronger evidence for association with MAFB and ABCA4. Expression studies support a role for MAFB in palatal devel! opment. View full text Figures at a glance * Figure 1: Manhattan plots of −log10(P values) from TDT for autosomal SNPs on CL/P case-parent trios (omitting SNPs flagged by quality control). (–) Results based on all 1,908 CL/P trios (), results based on 825 CL/P case-parent trios of European ancestry () and results based on 1,038 CL/P case-parent trios of Asian ancestry (). * Figure 2: Significance and effect size for SNPs near MAFB based on all CL/P trios. (–) The −log10(P value) for allelic TDT for 17 SNPs near MAFB on chromosome 20q11 (), the estimated OR (case) from a conditional logistic regression and the corresponding 95% CIs under an additive model () and the physical position of tested SNPs and the single exon of MAFB (). * Figure 3: Significance and effect size for SNPs in and near ABCA4 based on all CL/P trios. (–) The −log10(P value) for allelic TDT for 98 SNPs in or near ABCA4 on chromosome 1p22.1 (), the estimated OR(case) from a conditional logistic regression and the corresponding 95% CIs under an additive model fit to 1,908 CL/P case-parent trios () and the physical position of tested SNPs and combined exons of ABCA4 (). * Figure 4: Mafb, and not Abca4, is expressed during the development of the secondary palate in the mouse. (–) In situ hybridization for Mafb on whole-mount E13.5 embryos () shows expression in craniofacial ectoderm, vibrissae and neural crest–derived mesoderm. A signal was also detected in the elevated palatal shelves (, view of the roof of the mouth). (–) Immunofluorescence staining for Mafb (red) on E13.5 palatal sections shows Mafb localized in the epithelium of the palatal shelves () and in the medial edge epithelium during palatal fusion on E14.5 tissue sections (,). Expression is also detected in the epithelium at the base of the nasal septum and on the tongue epithelium (). Note the absence of signal in the sense probe control (,) and in the no primary antibody control (). (,) Immunofluorescence staining for Abca4 (green) on adult murine retina () and E14.5 palatal sections () shows the presence of Abca4 in the rim of rods photoreceptor cells of the retina and its absence in orofacial structures. Nuclei were counterstained with DAPI (blue). v, vibrissae; p, palatal ! shelf; t, tongue; ns, nasal septum. Scale bars: –,, 100 μm; , 50 μm. Author information * Author information * Supplementary information Affiliations * Johns Hopkins University, School of Public Health, Baltimore, Maryland, USA. * Terri H Beaty, * Ingo Ruczinski, * Jacqueline B Hetmanski, * Kung Yee Liang, * Tao Wu, * Tanda Murray, * M Daniele Fallin, * Holger Schwender & * Sheng-Chih Jin * Department of Pediatrics, University of Iowa, Iowa City, Iowa, USA. * Jeffrey C Murray, * Martine Dunnwald, * Maria A Mansilla, * Elizabeth Leslie & * Aline Petrin * University of Pittsburgh, School of Dental Medicine, Pittsburgh, Pennsylvania, USA. * Mary L Marazita, * Margaret E Cooper, * Renato Menezes & * Alexandre R Vieira * Utah State University, Logan, Utah, USA. * Ronald G Munger * Peking University Health Science Center, Beijing, China. * Tao Wu * Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA. * Richard A Redett, * Gerald Raymond, * Ethylin W Jabs, * Hong Wang & * Alan F Scott * Department of Orthodontics, University of Iowa, Iowa City, Iowa, USA. * Stephen Bullard, * Andrew C Lidral & * Lina M Moreno * National Institute of Environmental Health Science, National Institutes of Health (NIH), Durham, North Carolina, USA. * Allen J Wilcox * University of Bergen, Bergen, Norway. * Rolv T Lie * Mt. Sinai Medical School, New York, New York, USA. * Ethylin W Jabs & * Xiaoqian Ye * Chang Gung Memorial Hospital, Taoyuan, Taiwan. * Yah Huei Wu-Chou & * Philip K Chen * Wuhan University, Wuhan, China. * Xiaoqian Ye * Peking Union Medical College, Beijing, China. * Shangzhi Huang * KK Women's and Children's Hospital, Singapore. * Vincent Yeow * National University of Singapore, Singapore. * Samuel S Chong * Epidemiology and Health Promotion, Yonsei University, Seoul, Korea. * Sun Ha Jee * West China School of Stomatology, Sichuan University, Chengdu, China. * Bing Shi * University of Southern Denmark, Odense, Denmark. * Kaare Christensen * Statens Serum Institute, Copenhagen, Denmark. * Mads Melbye * Center for Inherited Disease Research, Johns Hopkins University, Baltimore, Maryland, USA. * Kimberly F Doheny, * Elizabeth W Pugh & * Hua Ling * Department of Genetics, Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro, Brazil. * Eduardo E Castilla * Foundation for the Community Control of Hereditary Diseases, Budapest, Hungary. * Andrew E Czeizel * School of Stomatology, Beijing University, Beijing, China. * Lian Ma * Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada. * L Leigh Field * National Human Genome Research Institute, NIH, Bethesda, Maryland, USA. * Lawrence Brody & * Faith Pangilinan * National Institute of Child Health and Human Development, NIH, Bethesda, Maryland, USA. * James L Mills * Trinity College Dublin, Dublin, Ireland. * Anne M Molloy & * James M Scott * Health Research Board, Dublin, Ireland. * Peadar N Kirke * University of Miami, Miller School of Medicine, Miami, Florida, USA. * Mauricio Arcos-Burgos Contributions T.H.B. and J.B.H. contributed to data collection for the original consortium study, data analysis and writing the manuscript. J.C.M. and M.L.M. contributed to data collection for the original consortium study and replication samples, data analysis and writing of the manuscript. R.G.M. and A.J.W. contributed to data collection for the original consortium study and to manuscript writing. I.R. and K.Y.L. contributed to data analysis and manuscript writing. T.W. and T.M. contributed to data collection, management and analysis. M.D.F. contributed to manuscript writing. R.A.R., G.R., R.T.L., E.W.J., Y.H.W.-C., P.K.C., H.W., X.Y., S.H., V.Y., S.S.C., S.H.J. and B.S. contributed to data collection for the original consortium study. H.S. and S.-C.J. contributed to data analysis. M.E.C. contributed to the analysis of replication samples. M.A.M. contributed to data collection, genotyping and laboratory studies. M.D., A.P., E.L. and S.B. contributed to laboratory studies. A.C.L. and L.M! .M. contributed to collection of replication samples and laboratory studies. A.R.V., A.E.C., E.E.C., K.C., L.M., L.L.F., M.M., L.C.B., F.P., J.L.M., A.M.M., P.N.K., J.M.S., R.M. and M.A.-B. contributed to collection of replication samples. K.F.D. contributed to genotyping and manuscript writing. E.W.P. and H.L. contributed to genotyping and analysis. A.F.S. contributed to genotyping, data analysis, laboratory studies and manuscript writing. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Terri H Beaty (tbeaty@jhsph.edu) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Note, Supplementary Tables 1–7 and Supplementary Figures 1–7 Additional data
• Deletion of the protein tyrosine phosphatase gene PTPN2 in T-cell acute lymphoblastic leukemia
  - Nat Genet 42(6):530-535 (2010)
  Nature Genetics | Letter Deletion of the protein tyrosine phosphatase gene PTPN2 in T-cell acute lymphoblastic leukemia * Maria Kleppe1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Idoya Lahortiga1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Tiama El Chaar3 Search for this author in: * NPG journals * PubMed * Google Scholar * Kim De Keersmaecker1, 2, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Nicole Mentens1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Carlos Graux5 Search for this author in: * NPG journals * PubMed * Google Scholar * Katrien Van Roosbroeck1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Adolfo A Ferrando4, 6, 7 Search for this author in: * NPG journals * PubMed * Google Scholar * Anton W Langerak8 Search for this author in: * NPG journals * PubMed * Google Scholar * Jules P P Meijerink9 Search for this author in: * NPG journals * PubMed * Google Scholar * François Sigaux3 Search for this author in: * NPG journals * PubMed * Google Scholar * Torsten Haferlach10 Search for this author in: * NPG journals * PubMed * Google Scholar * Iwona Wlodarska2 Search for this author in: * NPG journals * PubMed * Google Scholar * Peter Vandenberghe2 Search for this author in: * NPG journals * PubMed * Google Scholar * Jean Soulier3 Search for this author in: * NPG journals * PubMed * Google Scholar * Jan Cools1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume:42,Pages:530–535Year published:(2010)DOI:doi:10.1038/ng.587Received22 December 2009Accepted19 April 2010Published online16 May 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg PTPN2 (protein tyrosine phosphatase non-receptor type 2, also known as TC-PTP) is a cytosolic tyrosine phosphatase that functions as a negative regulator of a variety of tyrosine kinases and other signaling proteins1, 2, 3. In agreement with its role in the regulation of the immune system, PTPN2 was identified as a susceptibility locus for autoimmune diseases4, 5. In this work, we describe the identification of focal deletions of PTPN2 in human T-cell acute lymphoblastic leukemia (T-ALL). Deletion of PTPN2 was specifically found in T-ALLs with aberrant expression of the TLX1 transcription factor oncogene6, including four cases also expressing the NUP214-ABL1 tyrosine kinase7. Knockdown of PTPN2 increased the proliferation and cytokine sensitivity of T-ALL cells. In addition, PTPN2 was identified as a negative regulator of NUP214-ABL1 kinase activity. Our study provides genetic and functional evidence for a tumor suppressor role of PTPN2 and suggests that expression of PTPN2 ! may modulate response to treatment. View full text Figures at a glance * Figure 1: Comprehensive analysis of T-ALL individuals featuring PTPN2 deletion. () Agilent array CGH and Affymetrix SNP array data for 13 T-ALL individuals indicating biallelic deletion of PTPN2 in individuals 1 to 7, and monoallelic deletion of PTPN2 in individuals 18, 20 and 22. *Blast cell content for individual 5 was only 50%. () Interphase FISH confirmed the presence of PTPN2 deletion in >90% of the cells for individuals 1 (biallelic deletion) and 20 (monoallelic deletion). () Quantitative PCR analysis on genomic DNA isolated from diagnosis, remission and relapse samples of individual 1 confirmed that the deletion was acquired at diagnosis, and again present at relapse. A primer set for CDH2 (18q12) was used for normalization. () PTPN2 expression was analyzed in a set from individuals with T-ALL (n = 90) using Affymetrix gene expression arrays (probe set 213136_at) and categorized according to oncogenic T-ALL subtypes (x axis). y axis displays PTPN2 expression as a logarithmic scale. n indicates number of affected individuals analyzed. () Quantitat! ive real-time PCR analysis of individuals with T-ALL detects lower expression for T-ALL cases with loss of PTPN2 as compared with affected individuals with no deletion. Expression values were normalized for HPRT gene expression and blotted at the y axis in logarithmic scale. Samples derived from bone marrow or peripheral blood were analyzed separately. Closed rectangles, no deletion (n = 8); open triangles, monoallelic deletion (n = 5); open circle, biallelic deletion (individual 1). The individual with an additional mutation in PTPN2 is shown in red. * Figure 2: Knockdown of PTPN2 causes higher sensitivity of T-cell lines to cytokine stimulation. () Protein blot analysis of whole-cell lysates showing higher sensitivity of JURKAT cells to cytokine stimulation (IFN-γ) due to decreased PTPN2 expression. Stimulated cells expressing reduced amounts of PTPN2 displayed an increased and prolonged phosphorylation of STAT1 as well as JAK1. Results of two independent experiments are shown. ERK1/2 was used as loading control. Open bars, siRNA PTPN2; closed bars, siRNA control. Bars show average ± s.e.m., n = 3; error bars represent s.e.m. *P < 0.005. () HPB-ALL cells expressing reduced (siRNA PTPN2) or normal amounts (siRNA control) of PTPN2 were stimulated with different concentrations of IL-7 for indicated time points and whole-cell lysates were analyzed for activation of STAT5 and JAK1 by protein blot. Quantification of protein blot experiments showed that knockdown of PTPN2 resulted in stronger activation of JAK1 and STAT5. Normalized quantification values calculated as relative change compared to unstimulated cells are sh! own below respective immunoblots. ERK1/2 was used as loading control. * Figure 3: Mouse T-ALL cells display altered cytokine receptor signaling in correlation with Ptpn2 expression. () Knockdown of Ptpn2 enhanced responsiveness of the IL-7 receptor pathway to ligand stimulation as displayed by increased strength and duration of the phosphorylation status of JAK1 and downstream protein STAT5 when compared with control cells. Open arrow points at the protein band corresponding to JAK1. Black arrow indicates time point of cytokine removal. STAT5 was used as loading control. () Protein blot analysis of whole-cell lysates showed increased sensitivity of primary mouse T-ALL cells to IL-2 stimulation due to decreased Ptpn2 expression as analyzed by phosphorylation level of STAT5. STAT5 is shown as loading control. () Cytokine-depleted cells were exposed to IFN-γ for indicated time periods and subsequently analyzed for activation of STAT1 by protein blot. Quantification of protein blot experiments showed that reduction of Ptpn2 protein resulted in stronger activation of STAT1. STAT1 was assayed to ensure equal protein loading. () Primary T-ALL cells were depri! ved of cytokines for 24 h before restimulation with either IL-7 alone or a combination of IL-2 and IL-7. Under both conditions, knockdown of Ptpn2 provided cells with a significant proliferative advantage in response to cytokine readdition. Open bars, shRNA Ptpn2; closed bars, shRNA Alk (control). Bars show average ± s.e.m. Error bars represent s.e.m. *P < 0.05. Efficient knockdown of Ptpn2 was confirmed using antibody to Ptpn2 (3E2). Differences in phosphorylation signal intensity were quantified for JAK1 and STAT proteins, and corresponding values are shown below blots. * Figure 4: Identification of NUP214-ABL1 oncogene as a new substrate of PTPN2. () Desphosphorylation of NUP214-ABL1 was observed upon overexpression of wild-type PTPN2 (PTPN2-WT). Immune precipitation (IP) of the catalytic mutant PTPN2-D182A resulted in coprecipitation of NUP214-ABL1. DD, destabilization domain; GFP, green fluorescent protein; WCL, whole-cell lysates. () Viable cell numbers determined 3 d after electroporation with small interfering RNAs (siRNAs). Decrease in PTPN2 resulted in proliferative advantage of ALL-SIL cells. () Cells were exposed to imatinib at time of maximal PTPN2 knockdown. Protein blot showed differential activation status of STAT family members downstream of NUP214-ABL1. ERK1/2 and an SRC-family kinase were constitutively active in ALL-SIL cells, and knockdown of PTPN2 caused an augmented phosphorylation, which stayed unchanged upon imatinib treatment. Loading control was ERK1/2. () IP experiments of ALL-SIL cells after electroporation with siRNAs showed an enhancing effect on JAK3 kinase activation (upper) and identifie! d the differentially activated SRC-family kinase as LCK. Phosphorylation of JAK3 and LCK were detected with a phosphotyrosine (pTyr) or phospho-SRC family antibody, respectively. JAK3 or LCK were used as loading controls. () Ba/F3 cells carrying indicated constructs were grown in the absence of IL-3, and mean growth ± s.e.m. was recorded in triplicate for 8 d. No s.e.m. is shown in case of values below 0.03. () Protein blot of NUP214-ABL1-dependent Ba/F3 cells demonstrated stronger constitutive activation of NUP214-ABL1 and STAT5 in case of concomitant shRNA-mediated knockdown of Ptpn2. Loading controls were c-ABL, STAT5. () Induced overexpression of PTPN2-WT in Ba/F3 cells carrying the NUP214-ABL fusion results in dephosphorylation of the oncogenic kinase and its downstream mediator STAT5. c-ABL is shown as loading control. Values below immunoblots represent normalized (for loading control) quantitative values. Open bars, siRNA PTPN2; closed bars, siRNA control. Bars show! average ± s.e.m. Error bars represent s.e.m. *P < 0.05, **P ! < 0.005. * Figure 5: Reduction of PTPN2 expression affects treatment response of NUP214-ABL1–dependent cells to the kinase inhibitor imatinib. () Follow-up of survival of ALL-SIL cells treated with imatinib (500 nM) demonstrated decreased sensitivity due to alteration of PTPN2 expression. y axis displays cell viability (%). Open bars, siRNA PTPN2; closed bars, control siRNA. () Small interfering RNA (siRNA)-mediated knockdown of PTPN2 in ALL-SIL cells reduced activity of imatinib as depicted by an increased IC50 value (126 nM) as compared with control cells (73 nM). Untreated cells were set to 100%. Graph displays relative cell growth (%) as a function of concentrations (nM, logarithmic scale). Open circles, siRNA PTPN2; closed rectangles, siRNA control. () Protein blot analysis of ALL-SIL cells exposed to increasing concentrations of imatinib showed a stronger activation of NUP214-ABL downstream target STAT5 in knockdown cells (left panel). Bar graph displays calculated differences in STAT5 activation due to alterations in PTPN2 expression (right panel). Loading control, c-ABL; open bars, siRNA PTPN2; closed bars,! control siRNA. All values represent the average ± s.e.m. of three determinations. Significant differences compared with those of control siRNA are indicated. *P < 0.05 and **P < 0.005. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Entrez Nucleotide * NM_002828 * NM_080422 * NM_080423 * NM_008977 Author information * Accession codes * Author information * Supplementary information Affiliations * Department of Molecular and Developmental Genetics, VIB, Leuven, Belgium. * Maria Kleppe, * Idoya Lahortiga, * Kim De Keersmaecker, * Nicole Mentens, * Katrien Van Roosbroeck & * Jan Cools * Center for Human Genetics, K.U. Leuven, Leuven, Belgium. * Maria Kleppe, * Idoya Lahortiga, * Kim De Keersmaecker, * Nicole Mentens, * Katrien Van Roosbroeck, * Iwona Wlodarska, * Peter Vandenberghe & * Jan Cools * INSERM U944 and Hematology Laboratory, Hôpital Saint-Louis, Institut Universitaire d′Hématologie, Paris, France. * Tiama El Chaar, * François Sigaux & * Jean Soulier * Institute for Cancer Genetics, Columbia University Medical Center, New York, New York, USA. * Kim De Keersmaecker & * Adolfo A Ferrando * Cliniques universitaires de Mont-Godinne, Yvoir, Belgium. * Carlos Graux * Department of Pathology, Columbia University Medical Center, New York, New York, USA. * Adolfo A Ferrando * Department of Pediatrics, Columbia University Medical Center, New York, New York, USA. * Adolfo A Ferrando * Department of Immunology, Erasmus Medical Center, Rotterdam, The Netherlands. * Anton W Langerak * Department of Pediatrics, Erasmus Medical Center–Sophia, Rotterdam, The Netherlands. * Jules P P Meijerink * Munich Leukemia Laboratory, Munich, Germany. * Torsten Haferlach Contributions All authors contributed to the text; M.K. designed and carried out experiments and analyzed data; I.L., T.E.C., K.D.K., N.M., C.G., K.V.R. and I.W. carried out experiments and analyzed data; A.A.F., A.W.L., J.P.P.M., F.S., T.H. and P.V. collected samples, carried out experiments and analyzed data; J.S. and J.C. supervised the project and analyzed data. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Jean Soulier (jean.soulier@sls.aphp.fr) or * Jan Cools (jan.cools@cme.vib-kuleuven.be) Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (904K) Supplementary Figures 1–8 and Supplementary Tables 1–4 Additional data
• Substitutions in woolly mammoth hemoglobin confer biochemical properties adaptive for cold tolerance
  Campbell KL Roberts JE Watson LN Stetefeld J Sloan AM Signore AV Howatt JW Tame JR Rohland N Shen TJ Austin JJ Hofreiter M Ho C Weber RE Cooper A - Nat Genet 42(6):536-540 (2010)
  Nature Genetics | Letter Substitutions in woolly mammoth hemoglobin confer biochemical properties adaptive for cold tolerance * Kevin L Campbell1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jason E E Roberts1 Search for this author in: * NPG journals * PubMed * Google Scholar * Laura N Watson2 Search for this author in: * NPG journals * PubMed * Google Scholar * Jörg Stetefeld3 Search for this author in: * NPG journals * PubMed * Google Scholar * Angela M Sloan1 Search for this author in: * NPG journals * PubMed * Google Scholar * Anthony V Signore1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jesse W Howatt1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jeremy R H Tame4 Search for this author in: * NPG journals * PubMed * Google Scholar * Nadin Rohland5, 8 Search for this author in: * NPG journals * PubMed * Google Scholar * Tong-Jian Shen6 Search for this author in: * NPG journals * PubMed * Google Scholar * Jeremy J Austin2 Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Hofreiter5, 9 Search for this author in: * NPG journals * PubMed * Google Scholar * Chien Ho6 Search for this author in: * NPG journals * PubMed * Google Scholar * Roy E Weber7, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Alan Cooper2, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume:42,Pages:536–540Year published:(2010)DOI:doi:10.1038/ng.574Received18 December 2009Accepted31 March 2010Published online02 May 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We have genetically retrieved, resurrected and performed detailed structure-function analyses on authentic woolly mammoth hemoglobin to reveal for the first time both the evolutionary origins and the structural underpinnings of a key adaptive physiochemical trait in an extinct species. Hemoglobin binds and carries O2; however, its ability to offload O2 to respiring cells is hampered at low temperatures, as heme deoxygenation is inherently endothermic (that is, hemoglobin-O2 affinity increases as temperature decreases). We identify amino acid substitutions with large phenotypic effect on the chimeric β/δ-globin subunit of mammoth hemoglobin that provide a unique solution to this problem and thereby minimize energetically costly heat loss. This biochemical specialization may have been involved in the exploitation of high-latitude environments by this African-derived elephantid lineage during the Pleistocene period. This powerful new approach to directly analyze the genetic a! nd structural basis of physiological adaptations in an extinct species adds an important new dimension to the study of natural selection. View full text Figures at a glance * Figure 1: Evolution of the genes encoding the single adult-expressed hemoglobin component of three members of the Elephantidae family. The position of nucleotide and amino acid changes are shown within the three coding regions (exons) of the HBA-T2 and HBB/HBD globin genes (shown as open horizontal boxes along each branch) superimposed on the Elephantidae phylogeny4. Branch lengths are not proportional to geologic time. Ancestral nucleotide and amino acid residues are shown above, and derived nucleotide and amino acid residues are shown below the exons. The numbers above and the letters to the right of the vertical lines denote the amino acid residue, whereas the numbers below and the letters to the left of each vertical line indicate nucleotide position relative to the ATG initiation codon. Thick vertical lines with bold characters indicate nonsynonymous substitutions, and thin vertical lines represent synonymous substitutions, with red, green and blue characters and bars representing replacements at codon positions 1, 2 and 3, respectively. We employed the α-globin and β-globin chain sequences of other ! afrotherian mammals (Echinops telfairi (GenBank P24291, P24292), Procavia habessinica (P01957, P02086) and Trichechus inunguis (P07414, P07415)) to deduce the direction of amino acid substitutions. * Figure 2: Surface model of a chimeric Asian elephant (left) and mammoth (right) deoxyhemoglobin molecule bound to 2,3-bisphosphoglycerate (BPG). The locations of the three mammoth-specific amino acid substitutions are highlighted in blue, and the positions of each heme group are denoted by ball-and-stick diagrams. Regions highlighted in yellow denote positively charged residues (Lys82 of the β/δ-chain (hereafter denoted β/δ82 Lys), β/δ143 His and the amino group of β/δ1 Val) implicated in the binding of BPG to elephant deoxyhemoglobin11, 12, 14. Note that because the polar hydroxyl side chain of β/δ12 Thr of Asian elephant deoxyhemoglobin (and human hemoglobin25) forms a hydrogen bond with the carbonyl group of β/δ8 Lys (green), the negatively charged side chain of β/δ79 Asp (red) is free to project into the BPG binding pocket, where it would tend to repel this anion. Conversely, the methyl side chain of β/δ12 Ala in mammoth hemoglobin cannot bond with β/δ8 Lys, allowing the lysyl side chain to form an ionic interaction with β/δ79 Asp of the E helix and neutralizing its charge (light red). The mam! moth-specific β/δ101 Gln residue is spatially distant from this charged cluster and cannot contribute to BPG binding15, 16, 17. However, this central cavity residue alters electrostatic interactions at the sliding interface of the molecule that both destabilizes the low-affinity deoxy-state protein and creates additional proton-linked chloride binding sites in mammoth hemoglobin (see main text for details). * Figure 3: Oxygen equilibrium curves of woolly mammoth (blue) and Asian elephant hemoglobin (red) at 37 °C and pH 7.0. In the absence of allosteric effectors (solid lines), the mammoth β/δ-chain E101Q substitution destabilizes the tense-state (deoxy) conformation, leading to a protein phenotype with an intrinsic affinity nearly two times higher (curve is shifted to the left). This radical increase in O2 affinity (which would drastically impair tissue O2 offloading) is almost precisely compensated by enhanced H+, Cl− and 2,3-BPG binding to mammoth hemoglobin that right-shifts the curve more strongly than in Asian elephant hemoglobin. As a result, the overall O2 affinity of mammoth hemoglobin in the presence of red cell effectors is nearly identical to that of Asian elephants at 37 °C (red dashed line). However, the increased effector binding to mammoth hemoglobin lowers the effect of temperature on O2 affinity, facilitating the release of O2 at cold temperatures in relation to Asian elephant hemoglobin. * Figure 4: Mean enthalpy of oxygenation (ΔH; kJ mol−1 O2) values of woolly mammoth (blue columns) and Asian elephant (red columns) hemoglobin in the absence and presence of effector molecules. Error bars for each treatment ('stripped', 0.1 M Cl−, and 0.1 M Cl− plus saturating levels of 2,3-bisphosphoglycerate (Cl− + BPG)) are ± s.e.m. of four calculated ΔH values: one from O2 equilibria measured at 10 °C and 25 °C at pH 7.0; one from measurements at 25 °C and 37 °C at pH 7.0; one from measurements at 10 °C and 25 °C at pH 7.4; and one from measurements at 25 °C and 37 °C at pH 7.4. The temperature dependence of the oxygenation process is governed by the associated overall ΔH of this reaction19, where numerically low ΔH values correspond to small effects of temperature on hemoglobin-O2 affinity. Student's unpaired t-tests (α = 0.05, n = 4) illustrate that the intrinsic thermal sensitivity of mammoth hemoglobin is not different from that of Asian elephant hemoglobin (P = 0.9174). Conversely, as denoted by asterisks, the endothermic dissociation of Cl− (P = 0.0198) and BPG (P = 0.0168) each independently lower the oxygenation enthalpy of mammoth ! hemoglobin to significantly greater degrees than for Asian elephant hemoglobin, as predicted by the E101Q and T12A substitutions on the mammoth β/δ-globin chain, respectively (see text for details). The ΔH of mammoth hemoglobin was independent of pH under all conditions employed here, illustrating that the binding of Bohr protons does not directly contribute to lowering the ΔH value. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Entrez Nucleotide * FJ716079 * FJ716094 Author information * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Roy E Weber & * Alan Cooper Affiliations * Department of Biological Sciences, University of Manitoba, Winnipeg, Canada. * Kevin L Campbell, * Jason E E Roberts, * Angela M Sloan, * Anthony V Signore & * Jesse W Howatt * Australian Centre for Ancient DNA, School of Earth and Environmental Sciences, University of Adelaide, Adelaide, Australia. * Laura N Watson, * Jeremy J Austin & * Alan Cooper * Department of Chemistry, University of Manitoba, Winnipeg, Canada. * Jörg Stetefeld * Protein Design Laboratory, Yokohama City University, Yokohama, Japan. * Jeremy R H Tame * Junior Research Group Molecular Ecology, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany. * Nadin Rohland & * Michael Hofreiter * Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA. * Tong-Jian Shen & * Chien Ho * Zoophysiology, Institute of Biological Sciences, University of Aarhus, Aarhus, Denmark. * Roy E Weber * Present address: Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA. * Nadin Rohland * Present address: Department of Biology, University of York, York, UK. * Michael Hofreiter Contributions K.L.C. conceived the research. K.L.C., J.S., M.H., J.J.A., T.-J.S., C.H., R.E.W. and A.C. designed the experiments. K.L.C., J.E.E.R., L.N.W., A.M.S., A.V.S., J.W.H., N.R., T.-J.S., R.E.W. and J.J.A. conducted the experiments. K.L.C., J.S., A.V.S., J.R.H.T., R.E.W. and A.C. analyzed the data. K.L.C. and A.C. drafted the manuscript, and K.L.C., M.H., J.R.H.T., C.H., R.E.W. and A.C. contributed to the final manuscript writing and its revisions. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Kevin L Campbell (campbelk@cc.umanitoba.ca) or * Alan Cooper (alan.cooper@adelaide.edu.au) Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Note, Supplementary Figures 1–12 and Supplementary Tables 1–4 Additional data
• Regulation of OsSPL14 by OsmiR156 defines ideal plant architecture in rice
  - Nat Genet 42(6):541-544 (2010)
  Nature Genetics | Letter Regulation of OsSPL14 by OsmiR156 defines ideal plant architecture in rice * Yongqing Jiao1, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Yonghong Wang1, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Dawei Xue2, 3, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Jing Wang1 Search for this author in: * NPG journals * PubMed * Google Scholar * Meixian Yan2 Search for this author in: * NPG journals * PubMed * Google Scholar * Guifu Liu1 Search for this author in: * NPG journals * PubMed * Google Scholar * Guojun Dong2 Search for this author in: * NPG journals * PubMed * Google Scholar * Dali Zeng2 Search for this author in: * NPG journals * PubMed * Google Scholar * Zefu Lu1 Search for this author in: * NPG journals * PubMed * Google Scholar * Xudong Zhu2 Search for this author in: * NPG journals * PubMed * Google Scholar * Qian Qian2 Search for this author in: * NPG journals * PubMed * Google Scholar * Jiayang Li1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature GeneticsVolume:42,Pages:541–544Year published:(2010)DOI:doi:10.1038/ng.591Received11 February 2010Accepted21 April 2010Published online23 May 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Increasing crop yield is a major challenge for modern agriculture. The development of new plant types, which is known as ideal plant architecture (IPA), has been proposed as a means to enhance rice yield potential over that of existing high-yield varieties1, 2. Here, we report the cloning and characterization of a semidominant quantitative trait locus, IPA1 (Ideal Plant Architecture 1), which profoundly changes rice plant architecture and substantially enhances rice grain yield. The IPA1 quantitative trait locus encodes OsSPL14 (SOUAMOSA PROMOTER BINDING PROTEIN-LIKE 14) and is regulated by microRNA (miRNA) OsmiR156 in vivo. We demonstrate that a point mutation in OsSPL14 perturbs OsmiR156-directed regulation of OsSPL14, generating an 'ideal' rice plant with a reduced tiller number, increased lodging resistance and enhanced grain yield. Our study suggests that OsSPL14 may help improve rice grain yield by facilitating the breeding of new elite rice varieties. View full text Figures at a glance * Figure 1: Map-based cloning of the IPA1 QTL and subcellular localization of the OsSPL14-GFP fusion protein. () The plant architecture of SNJ and TN1. Scale bars, 10 cm. () Location of IPA1 on rice chromosome 8. () Coarse linkage map of IPA1. () High-resolution linkage map of IPA1. The number of recombinants between the molecular marker and IPA1 is indicated. () Annotation of the candidate region surrounding IPA1 on BAC AP006049. Arrows indicate the putative genes predicted in the Rice Genome Annotation Database. () OsSPL14 structure and the mutation site in SNJ. The white boxes represent the 5′ and 3′ untranslated regions, the black boxes represent the coding sequences and lines between boxes represent introns. The red asterisk indicates the OsmiR156 target site. () Subcellular localization of OsSPL14-GFP in rice root cells. Scale bars, 10 μm. * Figure 2: Expression pattern of OsSPL14 and confirmation of OsmiR156-directed regulation on OsSPL14. (–) OsSPL14 expression patterns revealed by mRNA in situ hybridization. Scale bars, 200 μm. () OsmiR156 cleavage sites in OsSPL14 mRNAs determined by RNA ligase-mediated 5′ RACE. The vertical lines represent the nucleotides that base-pair with OsmiR156 and dots show the mismatched nucleotide. The numbers above the sequence indicate the location of the nucleotide in the OsSPL14 coding sequence. The positions corresponding to the 5′ ends of the cleaved OsSPL14 mRNAs determined by 5′ RACE and the frequency of 5′ RACE clones corresponding to each site are indicated by arrows. () IPA1 transcript levels in various organs, including shoot apexes of seedlings (SA), culms (C), leaves (L), leaf sheaths (LS), panicles after heading (P) and seedling roots (R). Values in are means and s.d. of three independent experiments. () Expression pattern of OsmiR156. OsmiR156 transcript levels were determined by RNA blot analysis in various organs. * Figure 3: Effects of the point mutation in OsSPL14ipa1 on the OsmiR156-directed regulation of OsSPL14. () Chromatogram of intact OsSPL14IPA1/ipa1 mRNAs recovered from RT-PCR with primers flanking the cleavage site. Arrows indicate the different nucleotides in OsSPL14IPA1 and OsSPL14ipa1 cDNAs. () Phenotypes of OsSPL14IPA1-GFP, OsSPL14ipa1-GFP and OsSPL14IPA17m-GFP transgenic plants. Scale bar, 10 cm. The blue letter indicates the mutation site in the OsSPL14ipa1 mRNA. The asterisks and red letters indicate the mutation sites and mutant nucleotides introduced into the OsmiR156 target site in the OsSPL14IPA17m-GFP transgene, which interrupts the OsmiR156 target site without changing the amino acid residues. () Protein levels of IPA1 in Nipponbare (NP), gOsSPL14IPA1-2, gOsSPL14IPA1-3 and gOsSPL14ipa1-1 transgenic plants. Above, protein blot with the antibody to IPA1; below, Ponceau S staining showing equal loading of proteins. () Transcript levels of IPA1 revealed by real-time PCR in Nipponbare (NP), gOsSPL14IPA1-2, gOsSPL14IPA1-3 and gOsSPL14ipa1-1 transgenic plants. Values are! means and s.d. of three independent experiments. * Figure 4: Phenotypic characterization of NIL OsSPL14ipa1 plants. () Gross morphologies of NIL OsSPL14IPA1 and NIL OsSPL14ipa1 plants at maturity. Scale bar, 10 cm. () Panicles of NIL OsSPL14IPA1 and NIL OsSPL14ipa1. Scale bar, 10 cm. () Culms of NIL OsSPL14IPA1 and NIL OsSPL14ipa1. Scale bar, 5 cm. () Cross-sections of culms of NIL OsSPL14IPA1 and NIL OsSPL14ipa1 plants. The middle and right panels are magnifications of indicated square and circle regions in the left panel, respectively. BV, big vascular bundles; SV, small vascular bundles; SC, sclerenchyma cells. Bars, 100 μm. () Comparison of the maximum bending force on third internodes between NIL OsSPL14IPA1 and NIL OsSPL14ipa1. () Comparison of primary branch number per main panicle between NIL OsSPL14IPA1 and NIL OsSPL14ipa1. () Comparison of secondary branch number per main panicle between NIL OsSPL14IPA1 and NIL OsSPL14ipa1. () Comparison of grain number per main panicle between NIL OsSPL14IPA1 and NIL OsSPL14ipa1. () Comparison of 1,000-grain weight between NIL OsSPL14IPA1 and ! NIL OsSPL14ipa1. () Comparison of the grain yield per main panicle between NIL OsSPL14IPA1 and NIL OsSPL14ipa1. Values in – are means ± s.d. (–,, n = 12 plants; , n = 3 replicates). The double asterisks represent significance difference determined by the Student's t-test at P < 0.01. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions GenBank * GU136674 Author information * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Yongqing Jiao, * Yonghong Wang & * Dawei Xue Affiliations * State Key Laboratory of Plant Genomics and National Center for Plant Gene Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China. * Yongqing Jiao, * Yonghong Wang, * Jing Wang, * Guifu Liu, * Zefu Lu & * Jiayang Li * State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China. * Dawei Xue, * Meixian Yan, * Guojun Dong, * Dali Zeng, * Xudong Zhu & * Qian Qian * Present address: College of Life and Environment Sciences, Hangzhou Normal University, Hangzhou, China. * Dawei Xue Contributions Y.J. and Y.W. designed the research, performed experiments, analyzed data and wrote the paper. D.X. performed experiments and analyzed data. J.W., M.Y., G.L., G.D., D.Z., Z.L and X.Z. performed the experiments. Q.Q. designed the research and analyzed the data. J.L. supervised the project, designed research, analyzed data and wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Jiayang Li (jyli@genetics.ac.cn) or * Qian Qian (qianqian188@hotmail.com) Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Tables 1 and 2 and Supplementary Figures 1–11. Additional data
• OsSPL14 promotes panicle branching and higher grain productivity in rice
  - Nat Genet 42(6):545-549 (2010)
  Nature Genetics | Letter OsSPL14 promotes panicle branching and higher grain productivity in rice * Kotaro Miura1 Search for this author in: * NPG journals * PubMed * Google Scholar * Mayuko Ikeda1 Search for this author in: * NPG journals * PubMed * Google Scholar * Atsushi Matsubara1 Search for this author in: * NPG journals * PubMed * Google Scholar * Xian-Jun Song1 Search for this author in: * NPG journals * PubMed * Google Scholar * Midori Ito1 Search for this author in: * NPG journals * PubMed * Google Scholar * Kenji Asano1 Search for this author in: * NPG journals * PubMed * Google Scholar * Makoto Matsuoka1 Search for this author in: * NPG journals * PubMed * Google Scholar * Hidemi Kitano1 Search for this author in: * NPG journals * PubMed * Google Scholar * Motoyuki Ashikari1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature GeneticsVolume:42,Pages:545–549Year published:(2010)DOI:doi:10.1038/ng.592Received01 March 2010Accepted21 April 2010Published online23 May 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Identification of alleles that improve crop production and lead to higher-yielding varieties are needed for food security. Here we show that the quantitative trait locus WFP (WEALTHY FARMER'S PANICLE) encodes OsSPL14 (SQUAMOSA PROMOTER BINDING PROTEIN-LIKE 14, also known as IPA1). Higher expression of OsSPL14 in the reproductive stage promotes panicle branching and higher grain yield in rice. OsSPL14 controls shoot branching in the vegetative stage and is affected by microRNA excision. We also demonstrate the feasibility of using the OsSLP14WFP allele to increase rice crop yield. Introduction of the high-yielding OsSPL14WFP allele into the standard rice variety Nipponbare resulted in increased rice production. View full text Figures at a glance * Figure 1: Characterization and cloning of the WFP QTL. () The gross morphologies of Nipponbare and ST-12. Scale bar, 20 cm. () The panicle morphologies of Nipponbare and ST-12. Arrowheads indicate primary branches. Scale bar, 5 cm. () Comparison of grain number per main panicle between Nipponbare and ST-12. () Comparison of primary branch number per main panicle between Nipponbare and ST-12. () The WFP locus was detected between RM223 and RM264 on chromosome 8. Positional cloning narrowed the WFP locus to a 66-kb region between dCAPS825 and CAPS311, and six genes are predicted to be located in this region by RAP-DB. Further analysis used 14 recombinant plants to narrow the candidate region to 2.6 kb. Numbers on the map indicate the number of recombinants. Predicted open reading frames and sequence differences between Nipponbare and ST-12 around the WFP candidate region are shown. Values are means, with bars showing s.d. (n = 40 plants in ,). * Figure 2: Expression analysis and transgenic analysis of OsSPL14. () Expression analysis of OsSPL14 in shoots, roots, shoot apices and young panicles. Relative expression levels are calibrated based on shoot expression in Nipponbare. () Expression analysis of OsSPL14 in shoots and the 1–2-mm, 2–5-mm, 5–10-mm and 10–50-mm stages of young panicle growth. Relative expression levels are calibrated based on the 1–2-mm panicle stage of Nipponbare. (–) In situ hybridization of OsSPL14 during panicle development in Nipponbare (–) and ST-12 (–). and are just after the phase change from vegetative to reproductive stage in Nipponbare and ST-12, respectively. and are at the stage of primary branch meristem differentiation in Nipponbare and ST-12, respectively. and are at the stage of formation of primary branch primordia in Nipponbare and ST-12, respectively. and are sense probes in Nipponbare and ST-12, respectively, at the stage of primary branch meristem differentiation. () Panicle morphologies of transgenic plants. OsSPL14 driv! en by the Nipponbare and ST-12 promoter, indicated as pNipOsSPL14 and pST-12OsSPL14, respectively. Vector, the TAC7 vector control. Scale bar, 5 cm. () Comparison of primary branch number per main panicle of transgenic plants. Values are means, with bars showing s.d. (n = 3 times in ,; n = 40 plants in ). Scale bars in – indicate 200 μm. **Significant at 1% level; *significant at 5% level; n.s., not significant. * Figure 3: Effect of microRNA excision on OsSPL14 expression. (–) Expression of GUS-fused OsSPL14 without or with a mutation in the microRNA-targeted site driven by the Nipponbare promoter. (–) The expression of unmutated OsSPL14-GUS and mutated mOsSPL14-GUS in leaves (,) and in the shoot base (,). (,) Gross morphology of unmutated (pNipOsSPL14) and mutated (pNipmOsSPL14) transgenic plants with OsSPL14 driven under the Nipponbare promoter at the vegetative stage. () Comparison of tiller number among transgenic plants of the OsSPL14 Nipponbare allele (pNip OsSPL14), mutated OsSPL14 (pNipmOsSPL14) and OsSPL14 Aikawa 1 allele (pNipOsSPL14Aikawa1). () Nucleotide change in Aikawa 1 from C to A at the OsmiR156-targeted site in OsSPL14. (–) Gross morphologies of Nipponbare, ST-12 and Aikawa 1 plants. () Comparison of tiller number per plant among Nipponbare, ST-12 and Aikawa 1. () Relative expression of OsSPL14 in shoots of Nipponbare, ST-12 and Aikawa 1. () RNA hybridization of OsmiR156. U6 RNA was used as a control probe and ethidium ! bromide was used as the loading control. Arrowhead indicates 20-nucleotide (nt) signal of OsmiR156. () Number of primary branches per panicle for Nipponbare, ST-12 and Aikawa 1. () Relative expression of OsSPL14 in the 2–5-mm stage of young panicles of Nipponbare, ST-12 and Aikawa 1. Scale bars: –, 1 cm; ,,–, 20 cm. Values are means and bars are s.d. (n = 40 plants in ,,; n = 3 times in ,). * Figure 4: Effect of OsSPL14WFP on grain yield. () Graphical genotypes of BC2F2 plants derived from a cross between Nipponbare and ST-12. Blue and yellow bars indicate chromosomes of Nipponbare and ST-12, respectively. Gray bars indicate chromosomes of undetermined genotypes. Red circles on ST-12 indicate the positions of QTLs controlling the number of primary branches. () Comparison of primary branch number per main panicle among the four BC2F2 genotypes. () Comparison of grain number per main panicle among the four BC2F2 genotypes. () Comparison of grain number per plant among the four BC2F2 genotypes. The Nipponbare and ST-12 genotypes in – are indicated as Nip and ST-12 on the x axes, respectively. Values in – are means, with bars showing s.d. (n = 40 plants). Author information * Author information * Supplementary information Affiliations * Bioscience and Biotechnology Center, Nagoya University, Nagoya, Japan. * Kotaro Miura, * Mayuko Ikeda, * Atsushi Matsubara, * Xian-Jun Song, * Midori Ito, * Kenji Asano, * Makoto Matsuoka, * Hidemi Kitano & * Motoyuki Ashikari Contributions H.K., M.M. and M.A. designed the research. K.M., M.I., A.M., X.-J.S., M.I. and K.A. conducted the research. K.M., X.-J.S., H.K. and M.A. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Motoyuki Ashikari (ashi@agr.nagoya-u.ac.jp) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Note, Supplementary Figures 1–11 and Supplementary Tables 1 and 2. Additional data