Structurally complex genome loci in human populations and human phenotypes

摘要/摘要 结构复杂基因座(SCLS)是基因组研究的热点，其与人类表型的关系 变异是未知的。SCL有多个重复的DNA序列片段，可以包含或侧翼 基因、外显子或调控元件；这些重复序列彼此重组以产生新的 等位基因通过非等位基因同源重组和基因转换，产生了许多功能截然不同的基因 具有不同基因剂量和/或蛋白质结构的等位基因。 人类遗传学还不知道大多数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。SCLS的遗传变异倾向于由许多等位基因引起，很难组装，并且 与附近的SNPs和SNP单倍型有复杂的关系。然而，SCL提供了一个真正的机会来联系 功能等位基因系列的表型对基因剂量或蛋白结构域有可解释的影响 结构。 在这项工作中，我们将开发一些方法来确定基因组中各个基因座的scl是如何由等位基因组成的。 系列，并与一组不同的人类表型有关。为此，我们将组合来自多种形式的数据 基因组分析--确定的长读数据(n~102且还在增长)、全基因组和全外显子组序列 数据(104-105)和SNP阵列数据(105-107)以及伴随的表型数据。 在目标1中，我们将开发方法来揭示SCLS的全部变化范围。我们将(A)确定变量 DNA特征以及这些特征的变化方式和共同分布在成千上万的 不同的祖先，以及(B)找到解释这种种群规模的潜在等位基因和等位基因频率 变种。 在目标2中，我们将启用强大的基因-表型分析，利用大量现有的SNP数据集；我们 将通过创建SCL等位基因和周围SNP的参考单倍型的大面板来实现这一点，以及 将SCL等位基因输入SNP数据的改进方法。 在目标3中，我们将提出在SCLS进行遗传关联分析和精细定位的方法，并探索 SCLS对数量性状和疾病风险的功能后果。 我们希望能够更多地发现复杂基因座上的等位基因序列是如何形成的。 人类的表型。

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.