Improved gene mapping for whole genome data

描述（由申请人提供）：遗传学中最基本的问题之一是识别来自最近共同祖先的遗传变异（IBD）。通常IBD的概念适用于来自家庭的数据，但它也可以应用于无血缘关系的个体，因为这些个体是有血缘关系的，即使只是非常遥远的关系。该项目将开发从相关和非相关个体的全基因组数据中检测和利用IBD信息的方法。这些方法将使检测与人类疾病有关的其他基因和变异成为可能，包括心脏病和糖尿病等常见复杂疾病。检测到的IBD信息将有助于确定系谱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面板。这项工作将使联系性分析能够在更大的家庭中进行，甚至在整个人口中进行，特别是在这些人口很小和孤立的情况下。这项工作还将使连锁分析能够以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也将有助于获得从每个亲本（单倍型阶段）共同遗传的变异的高度准确估计，并用于输入非基因型变异。关联研究，将基因型或单倍型变异与疾病状态联系起来，不直接使用IBD信息，但由于使用IBD获得的这些改进的估计，将增加效力。

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.