Analysis of Patterns of Structural Variation in the 1000 Genomes Data Set

1000 个基因组数据集中的结构变异模式分析

• 批准号: 8129827
• 负责人: CHARLES LEE
• 金额: $ 84.9万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-18 至 2013-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8129827
• 关键词: Affect; Age; Architecture; Base Sequence; Biological; Cataloging; Catalogs; Categories; Cell physiology; Classification; Cloning; Code; Communities; Custom; DNA Sequence Rearrangement; DNA Transposable Elements; Data; Data Set; Databases; Elements; Event; Evolution; Family; Frequencies; Gene Proteins; Genes; Genetic Variation; Genome; Genomics; Genotype; Goals; Health; Human; Individual; Inheritance Patterns; Inherited; Length; Linkage Disequilibrium; Lymphocyte; Metabolic Pathway; Methodology; Methods; Minisatellite Repeats; Nature; Pattern; Phase; Play; Population; Population Genetics; Population Study; Principal Investigator; Production; Proteins; RNA Splicing; Recording of previous events; Relative (related person); Repetitive Sequence; Research; Role; Sequence Analysis; Signal Pathway; Single Nucleotide Polymorphism; Site; Structure; Transcript; Transcriptional Regulation; Untranslated Regions; Variant; Work; analytical method; base; computerized data processing; design; disease phenotype; genetic analysis; homologous recombination; interest; member; mutant; pressure; promoter; protein complex; research study; structural genomics; tool

DESCRIPTION (provided by applicant): The 1000 Genomes Project is an initiative to sequence the complete genomes of over 1000 individuals and create a reference set of common and uncommon genetic variation among various ethnic populations. This project aims to more comprehensively identify all types of genetic variation, including Single nucleotide polymorphisms (SNPs) and Structural genome variants (SVs) which include regions that have been duplicated, deleted, inverted, or translocated through the course of human evolution. Some of these structural variants have been correlated with many different disease phenotypes and thus play a major role in human health. In the course of the pilot phase of this project, numerous diverse, yet complementary, analytical methods have been developed to detect these types of variation on multiple sequencing platforms. Our research team includes members of the structural genomic variation analysis group for the 1000 genome project who have been conducting analysis from the 1000 genome project over the past year. We now propose to conduct a coordinated analysis of the complete SV dataset from the 1000 genome production project. Our common goal is to enhance the value of the thousand genomes project data by carrying out more detailed characterization of variants in terms (1) structure at the nucleotide sequence-level (2) functional impact on genes and proteins and (3) their distribution in human populations. Our work will take over where the data processing ends, and aim to make the complete 1000 genomes SV call set maximally useful to the biological community.

描述（由申请人提供）： 1000个基因组计划是一项对1000多个个体的完整基因组进行测序的倡议，并在各种族人群中建立一套常见和不常见的遗传变异参考。该项目旨在更全面地识别所有类型的遗传变异，包括单核苷酸多态性（SNP）和结构基因组变异（SV），其中包括在人类进化过程中被复制，删除，倒置或易位的区域。这些结构变异中的一些与许多不同的疾病表型相关，因此在人类健康中起着重要作用。在该项目的试验阶段，已经开发了许多不同但互补的分析方法，以在多个测序平台上检测这些类型的变异。我们的研究团队包括1000基因组计划的结构基因组变异分析小组的成员，他们在过去一年中一直在进行1000基因组计划的分析。我们现在建议对来自1000个基因组生产项目的完整SV数据集进行协调分析。我们的共同目标是通过对变异体进行更详细的表征来提高千人基因组计划数据的价值，这些表征包括：（1）核苷酸序列水平的结构;（2）对基因和蛋白质的功能影响;（3）它们在人群中的分布。我们的工作将接管数据处理结束的地方，并旨在使完整的1000个基因组SV调用集对生物界最大限度地有用。

项目成果

forestSV: structural variant discovery through statistical learning.

• DOI: 10.1038/nmeth.2085
• 发表时间: 2012-07-01
• 期刊: NATURE METHODS
• 影响因子: 48
• 作者: Michaelson, Jacob J.;Sebat, Jonathan
• 通讯作者: Sebat, Jonathan

Whole-genome sequencing in autism identifies hot spots for de novo germline mutation.

• DOI: 10.1016/j.cell.2012.11.019
• 发表时间: 2012-12-21
• 期刊: Cell
• 影响因子: 64.5
• 作者: Michaelson JJ;Shi Y;Gujral M;Zheng H;Malhotra D;Jin X;Jian M;Liu G;Greer D;Bhandari A;Wu W;Corominas R;Peoples A;Koren A;Gore A;Kang S;Lin GN;Estabillo J;Gadomski T;Singh B;Zhang K;Akshoomoff N;Corsello C;McCarroll S;Iakoucheva LM;Li Y;Wang J;Sebat J
• 通讯作者: Sebat J