Leveraging consanguinity and homozygosity to identify novel recessive variants

项目概要/摘要 全基因组关联研究（GWAS）传统上假设一个加性模型， 基因遗传，其中杂合基因型的遗传效应正好是 两种纯合基因型的遗传效应的中间。但我们知道 许多等位基因以显性或隐性方式起作用。检测表型 罕见的，隐性变异的影响是特别具有挑战性的，由于罕见的， 纯合子基因型在这里，我们建议使用来自96，000人的数据， 巴基斯坦基因组资源（PGR），以量化罕见的，隐性变异的影响， 广泛的表型特征和常见的复杂疾病。我们的研究利用了 PGR内的近亲繁殖率高（这增加了稀有， 纯合子基因型），以及广泛的生活方式，家族史和遗传数据， 所有参与者。我们的项目的具体目标是（1）阶段和归属变量到 超过96，000个PCR基因组，使用包括6，200个高- 覆盖范围基因组序列从南亚;（2）测试之间的关联广泛 表型和基因型的范围，使用标准的单变量测试的组合 和新的纯合性作图方法;和（3）推断历史模型， PGR内的血缘关系，使用纯合性的长期分布（导致 通过近亲结婚）在个体内部和个体之间。

PROJECT SUMMARY/ABSTRACT Genome-wide association studies (GWAS) traditionally assume an additive model of genetic inheritance, where the genetic effect of a heterozygous genotype is exactly intermediate to the genetic effects of the two homozygous genotypes. However, we know that many alleles act in either a dominant or recessive fashion. Detecting the phenotypic effects of rare, recessive variants is especially challenging, due to the scarcity of rare, homozygous genotypes. Here, we propose to use data from 96,000 individuals from the Pakistan Genomic Resource (PGR) to quantify the effects of rare, recessive variants on a wide range of phenotypic traits and common, complex diseases. Our study leverages the high rates of inbreeding within the PGR (which increases the frequency of rare, homozygous genotypes), as well as extensive lifestyle, family history and genetic data from all participants. The specific aims for our project are (1) Phase and impute variants into more than 96,000 PGR genomes using a reference panel that includes 6,200 high- coverage genome sequences from South Asia; (2) Test for associations between a wide range of phenotypes and genotype, using a combination of standard single-variant tests and novel homozygosity-mapping approaches; and (3) Infer historical models of consanguinity within the PGR, using the distributions of long runs of homozygosity (caused by consanguineous marriages) both within and between individuals.