Improved gene mapping for whole genome data

改进全基因组数据的基因图谱

• 批准号: 8133536
• 负责人: BRIAN LEE BROWNING
• 金额: $ 45.58万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-25 至 2013-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8133536
• 关键词: Affect; Cardiovascular Diseases; Chromosome Mapping; Complex; Computer software; Computing Methodologies; DNA Sequence; Data; Data Analyses; Data Set; Detection; Diabetes Mellitus; Diagnosis; Disease; Family; Frequencies; Genetic; Genetic Markers; Genetic Materials; Genetic Variation; Genome; Genotype; Haplotypes; Heart Diseases; Individual; Inherited; Methodology; Methods; Modeling; Parents; Participant; Phase; Population; Prevention; Research; Resolution; Sampling; Statistical Methods; United States; Variant; Work; density; disorder risk; genetic linkage analysis; genetic pedigree; genetic variant; genome-wide; human disease; improved; population based; public health relevance

DESCRIPTION (provided by applicant): One of the most fundamental problems in genetics is the problem of identifying genetic variants that are shared identical by descent (IBD) from a recent common ancestor. Usually the concept of IBD is applied to data from families, but it can be applied to unrelated individuals because such individuals are related, even if only very distantly. This project will develop methods to detect and utilize IBD information from genome- wide data in related and unrelated individuals. These methods will make it possible to detect additional genes and variants that are involved in human disease, including common, complex diseases such as heart disease and diabetes The detected IBD information will be useful for determining regions where affected individuals in a pedigree share genetic material (linkage analysis). Current methods for linkage analysis are limited to relatively small families and to low-density panels of genetic markers. This work will enable linkage analysis to be performed on much larger families, and even on whole populations, particularly when these populations are small and isolated. This work will also enable linkage analysis to be performed with very high density genetic information, even to the level of DNA sequence data. The detected IBD will also be useful for obtaining highly accurate estimates of variants that were inherited together from each parent (the haplotype phase), and for imputing ungenotyped variation. Association studies, which correlate genotypic or haplotypic variation with disease status, do not directly use IBD information, but will have increased power due to these improved estimates obtained using IBD. PUBLIC HEALTH RELEVANCE: Heritable genetic variants contribute to many common diseases, such as cardiovascular disease and diabetes. This research will develop new statistical and computational methods for genetic data analysis that will improve our ability to identify genetic variants that increase risk of disease. These methods will contribute to the prevention, diagnosis, and treatment of heritable diseases in the United States and throughout the world.

描述（由申请人提供）：遗传学中最基本的问题之一是鉴定来自最近共同祖先的遗传变异的问题。IBD的概念通常适用于来自家庭的数据，但它也可以适用于不相关的个体，因为这些个体是相关的，即使只是非常遥远。该项目将开发从相关和不相关个体的全基因组数据中检测和利用IBD信息的方法。这些方法将使检测涉及人类疾病的其他基因和变异成为可能，包括常见的复杂疾病，如心脏病和糖尿病。检测到的IBD信息将有助于确定谱系中受影响个体共享遗传物质的区域（连锁分析）。目前的连锁分析方法仅限于相对较小的家族和低密度的遗传标记组。这项工作将使连锁分析能够在大得多的家庭，甚至整个人口，特别是当这些人口是小和孤立的。这项工作还将使连锁分析能够用非常高密度的遗传信息进行，甚至达到DNA序列数据的水平。检测到的IBD还将用于获得从每个亲本一起遗传的变体的高度准确的估计值（单倍型阶段），以及用于插补未基因分型的变异。关联研究将基因型或单倍型变异与疾病状态相关联，不直接使用IBD信息，但由于使用IBD获得的这些改进的估计值，因此具有增加的功效。 公共卫生相关性：遗传性遗传变异导致许多常见疾病，如心血管疾病和糖尿病。这项研究将为遗传数据分析开发新的统计和计算方法，这将提高我们识别增加疾病风险的遗传变异的能力。这些方法将有助于美国和全世界遗传性疾病的预防、诊断和治疗。