Structurally complex genome loci in human populations and human phenotypes

总结/摘要 结构复杂基因座（structurally complex loci，SCL）是基因组动态研究的热点， 变化是未知的。SCL具有多段重复的DNA序列， 基因、外显子或调控元件;这些重复序列彼此重组，产生新的 通过非等位基因同源重组和基因转换，产生许多功能上不同的等位基因。 具有不同基因剂量和/或蛋白质结构的等位基因。 人类遗传学尚未了解大多数SCL中存在的等位基因，也不知道它们与人类的关系 表型变异SCL的遗传变异往往来自许多等位基因，难以组装， 与邻近的SNP和SNP单倍型有复杂的关系。然而，SCL提供了一个真实的机会， 对基因剂量或蛋白质结构域具有可解释影响的功能等位基因的等位基因系列的表型 结构 在这项工作中，我们将开发方法来确定基因组中基因座上的SCL是如何由等位基因组成的。 系列，并涉及一组不同的人类表型。为此，我们将联合收割机的多种形式的数据结合起来， 基因组分析-确定的长读段数据（n~102和增长），全基因组和全外显子组序列 数据（104 - 105）和SNP阵列数据（105 - 107）与伴随表型数据。 在目标1中，我们将开发方法来揭示SCL的全谱变化。我们将（a）确定变量 DNA特征以及这些特征在成千上万的人中变化和共同分布的方式， 不同的祖先，以及（B）找到解释这种人口规模的潜在等位基因和等位基因频率 变化量 在目标2中，我们将实现强大的基因型-表型分析，利用现有的大量SNP数据集;我们 将通过创建SCL等位基因和周围SNP的参考单倍型的大型面板来实现这一点，并且 推进SCL等位基因到SNP数据中的输入方法。 在目标3中，我们将推进SCL的遗传关联分析和精细定位方法，并探索 SCL对数量性状和疾病风险的功能后果。 我们渴望做出并实现更多关于结构复杂基因座上的等位基因系列如何形成的发现 人类表型

SUMMARY/ABSTRACT Structurally complex loci (SCLs) are hotspots of genome dynamism whose relationship to human phenotypic variation is unknown. SCLs have multiple segments of duplicated DNA sequence which can contain or flank genes, exons, or regulatory elements; these repeated sequences recombine with one another to generate new alleles by non-allelic homologous recombination and gene conversion, creating many functionally distinct alleles with different gene dosages and/or protein structures. Human genetics does not yet know the alleles that are present at most SCLs, nor their relationship to human phenotypic variation. Genetic variation at SCLs tends to arise from many alleles, to be hard to assemble, and to have complex relationships to nearby SNPs and SNP haplotypes. Yet SCLs provide a real opportunity to relate phenotypes to allelic series of functional alleles with interpretable effects on gene dosage or protein domain structure. In this work, we will develop ways to ascertain how SCLs at loci across the genome are comprised of allelic series and relate to a diverse set of human phenotypes. To do this, we will combine data from many forms of genome analysis – definitive long-read data (n ~102 and growing), whole-genome and whole-exome sequence data (104-105) and SNP array data (105-107) with companion phenotype data. In Aim 1, we will develop methods to reveal the full spectrum of variation at SCLs. We will (a) identify variable DNA features and the ways in which these features vary and co-distribute across thousands of people of diverse ancestries, and (b) find the underlying alleles and allele frequencies that explain this population-scale variation. In Aim 2, we will enable powerful genotype-phenotype analyses that leverage vast existing SNP data sets; we will do this by creating large panels of reference haplotypes of SCL alleles and surrounding SNPs, and advancing methods for imputing SCL alleles into SNP data. In Aim 3, we will advance approaches for genetic association analysis and fine-mapping at SCLs, and explore the functional consequences of SCLs on quantitative traits and disease risk. We aspire to make and enable many more discoveries about how allelic series at structurally complex loci shape human phenotypes.