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The American Society of Human Genetics 60th Annual Meeting November 2-6, 2010 Washington, DC PLATFORM ABSTRACTS Abstract/ Abstract/ Program Program Numbers Numbers Concurrent Platform Sessions I (10-17) Concurrent Platform Session II (28-35) Wednesday, November 3, 10:30 am - 1:00 pm Thursday, November 4, 10:30 am - 1:00 pm SESSION 10 – Lessons from High-Throughput Sequencing 1-10 SESSION 28 – Structural Variation in Neuropsychiatric Disorders 87-96 SESSION 11 – Intervention and Treatment of Genetic Disorders11-20 SESSION 29 – Advances in Epigenetics: Technologies, 97-106 SESSION 12 – Evolutionary and Population Genetics 21-30 Mechanisms, and Genetic Disorders SESSION 13 – Cancer GWAS and Beyond 31-40 SESSION 30 – Cardiovascular Genetics and Genomics 107-116 SESSION 14 – Detection, Interpretation and Functional 41-50 SESSION 31 – Transcriptome Characterization and 117-126 Consequences of CNVs Functional Analysis SESSION 15 – The Long and Short of Skeletogenesis 51-60 SESSION 32 – Statistical Analysis of Human Sequence Variation127-136 SESSION 16 – Genetic Epidemiology in Multifactorial Traits 61-70 SESSION 33 – Craniofacial & Skeletal Disorders 137-146 SESSION 17 – Gene Identification in Neuropsychiatric Disease71-80 SESSION 34 – Genetic Counseling and Clinical Testing 147-156 SESSION 35 – Pharmacogenetics 157-166 Session 19 – Plenary Session – Wednesday, 2:30 pm – 5:00 pm 81-85 Concurrent Platform Session III (41-48) Concurrent Platform Session IV (49-56) Friday, November 5, 8:00 am – 10:30 am Friday, November 5, 1:30 pm – 4:00 pm SESSION 41 – The Cilia, The Better 167-176 SESSION 49 – Breast Cancer Susceptibility 247-256 SESSION 42 – Sequencing and Strategies: Rare Variants in 177-186 SESSION 50 – Evolutionary Genetics and Adaptation 257-266 Polygenic Traits SESSION 51 – Polygenic Traits: GWAS Methods and Results 267-276 SESSION 43 – Genetic Analysis of Gene Expression 187-196 SESSION 52 – Diabetes, Obesity and Metabolic Traits 277-286 SESSION 44 – Cancer Syndromes and Cancer Genomes 197-206 SESSION 53 – Genetic Architecture of Neurological Diseases 287-296 SESSION 45 – Mechanisms and Treatment of 207-216 SESSION 54 – From Gene Discovery to Function 297-306 Metabolic Disease SESSION 55 – Influence of Polymorphisms on Disease 307-316 SESSION 46 – Genome-wide Association Studies 217-226 Risks and Traits and Imputation SESSION 56 – Diverse Approaches Uncover Mendelian 317-326 SESSION 47 – Reproductive Genetics: Meosis to Menopause 227-236 Disorders SESSION 48 – Neurologic Disorders: Proteins, 237-246 Carbohydrates and Metals Concurrent Platform Session V (57-64) Friday, November 5, 4:30 pm – 7:00 pm SESSION 57 – Biological Insights of Genomic Studies 327-336 SESSION 58 – Rare Variation and Cardiovascular Genetics 337-346 SESSION 59 – Neurogenetics and Brain Development 347-356 SESSION 60 – New Findings in Known Clinical Disorders 357-366 SESSION 61 – Methods in Statistical Genetics 367-376 SESSION 62 – Autoimmunity and Infection 377-386 SESSION 63 – Ethical, Legal, Education and Policy Issues 387-396 SESSION 64 – Mechanisms of Chromosomal 397-406 Rearrangement and Implications for Cancer Copyright © 2010 The American Society of Human Genetics. All rights reserved. T : 24720$COV2 09-16-10 13:55:37 Layout: 24720X : Start Odd Page 1 Platform Session 10: Lessons from High-Throughput Sequencing 1 1 3 The 1000 Genomes Project: A comprehensive map of common and low Approaches for Discovering Structural Variation in the 1000 Genomes frequency human genetic variation. G.R. Abecasis, The 1000 Genomes Project. J. Korbel1, R. Mills2, C. Stewart3, the Structural Variation Analysis Project. Center for Statistical Genetics and Department of Biostatistics, Uni- Group of the 1000 Genomes Project. 1) Genome Biology, EMBL, Heidelberg, versity of Michigan, Ann Arbor, MI. Germany; 2) Molecular Genetic Research Unit, Brigham and Women’s Hos- We present a map of common human genetic variation obtained by whole pital, Harvard Medical School, Boston, MA; 3) Department of Biology, Boston genome-sequencing on a population scale. We describe the location, allele College, Chestnut Hill, MA. frequency and local haplotype structure of over 20 million SNPs, 1 million The discovery of genomic structural variants (SVs) from next-generation short insertion-deletion polymorphisms and thousands of structural variants, sequencing data (NGS) is a relatively novel problem with implications for many of them novel. In addition, we show that sequence data from many personal genomics. In the course of the 1000 Genomes Project (1000GP) individuals can be used to discover segregating sequences that are absent pilot phase, a number of different SV discovery approaches have been from the current genome assembly, that are polymorhpic between individuals developed, which underlie four different rationales: read-depth analysis, and that vary in frequency across populations. As of May 2010 >500 paired-end analysis, split-read analysis, and sequence assembly. Groups genomes have been sequenced, and we estimate that the 1000 Genome contributing to the 1000GP have generated approximately 30 SV discovery resource will ultimately contain ~95% of accessible variants with a minor callsets using variations of these four rationales. Based on these, a set allele frequency of 1% in each of five continental groups. Our results show encompassing thousands of SVs is being released, the majority of which that low-coverage sequencing of many individuals can highly accurate indi- have already been successfully validated by PCR, microarray, and sequence vidual genotypes at shared sites. By examing two deeply sequenced nuclear assembly based approaches. We have comprehensively analyzed this high families, we estimate the rate of de novo germ-line point mutation to be 10- confidence SV set with a focus on deletions (i.e., SVs that can be identified 8 per base pair per generation and characterise factors influencing the rate by all four rationales) to assess differences in SV ascertainment between of structural mutation. We identify many novel fixed differences of strong approaches along with influences of other factors, such as NGS library functional candidacy between populations and show that the hitch-hiking choice. Our analysis revealed that SV discovery approaches are partially effect has a marked effect on genetic variation around genes. Project data complementary in terms of the types of SVs they detect (SV-mechanism, are already being used in a large number of other studies and we show repeat/SD-content, SV-size, SV-type, and proximity/overlap with other that the resource can be used for accurate imputation of common variants genetic variants), with regard to how they can be experimentally validated, into existing association studies. and with regard to their sensitivity and FDR - with each approach having unique benefits. In our presentation we will cover limitations of current approaches and discuss possible solutions to overcome these. We will further describe a conceptual pipeline for SV discovery in NGS data and 2 comprehensively describe the processes the 1000GP SV analysis group Population genomics in the Americas: sub-continental ancestry and 1 2 has developed to go from raw individual sequencing data to a highly confident its implications for medical genomics. A. Moreno Estrada ,M.Via,C. SV discovery set. This pipeline includes a framework for merging and com- Gignoux2, B. Henn1, V. Acuña Alonzo3, K. Bryc4, H. Rangel Villalobos5,S. 6 7 2 1 bining information across different SV discovery-sets into a coherent high- Cañizales Quinteros , A. Ruiz Linares , E.G. Burchard , C.D. Bustamante . confidence SV set. We will show that applying SV genotyping with this SV 1) Department of Genetics, Stanford University, Stanford, CA; 2) Institute set enables filling in missing data from genomes sequenced at low coverage for Human Genetics, University of California at San Francisco, San Fran- and facilitates the removal of sample outliers. Finally, we will discuss how cisco, CA; 3) Molecular Genetics Laboratory, Escuela Nacional de Antropo- the SV set released by the 1000GP may be used to leverage future NGS logía e Historia (ENAH), Mexico City, Mexico; 4) Department of Biological based association studies. Statistics and Computational Biology, Cornell University, Ithaca, NY; 5) Molecular Genetics Research Institute, Universidad de Guadalajara, Ocot- lan, Mexico; 6) Molecular Biology and Genomic Medicine, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán (INCMNSZ), Universidad 4 Nacional Autónoma de México (UNAM), Mexico City, Mexico; 7) Department Characterizing the regulatory landscape of obesity-associated FTO. of Genetics, Evolution and Environment, University College London, Lon- N.F. Wasserman, J. Westlund, M.A. Nobrega. Human Gen, Univ Chicago, don, UK. Chicago, IL. Human populations from the Americas are often of admixed origin, with Genome-wide association studies (GWAS) routinely implicate non-coding significant genetic contributions from Native American and European popula- DNA variants in the etiology of common complex disease. Such findings tions (primarily involving local indigenous populations and migrants from imply that many of these associated regions may harbor functional non- the Iberian peninsula and Southern Europe) as well as West Africans brought coding variants capable of altering the activity of long-range cis-regulatory to the Americas through the trans-Atlantic slave trade. As a result present- elements - such as enhancers - that control the tissue
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