Rarely Common: Uncovering the dominant role of rare variants in the genetic architecture of complex human traits.

罕见：揭示罕见变异在复杂人类特征的遗传结构中的主导作用。

• 批准号: 10531261
• 负责人: Ryan D. Hernandez
• 金额: $ 54.57万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10531261
• 关键词: Alleles; Bioinformatics; Biological; Biological Assay; Biology; Communities; Complex; DNA; Data; Development; Disease; Enhancers; Exclusion; Exhibits; Feedback; Frequencies; Gene Expression; Gene Expression Profile; Gene Frequency; Genetic; Genetic Models; Genetic Risk; Genetic Variation; Genetic study; Genome; Genome engineering; Genomics; Genotype-Tissue Expression Project; Goals; Growth; Heritability; Human; Human Genetics; Human body; Iceberg; Learning; Mendelian disorder; Methods; Minor; Minority Groups; Modeling; Mutation; Phenotype; Play; Population; Population Genetics; Population Heterogeneity; Recording of previous events; Reporter; Research; Research Personnel; Role; Sampling; Science; Shapes; Statistical Models; Technology; Testing; Time; Tissues; Trans-Omics for Precision Medicine; Transcriptional Regulation; Validation; Variant; Work; bioinformatics tool; causal variant; environmental change; exome; experience; genetic architecture; genome sequencing; genome wide association study; human disease; human tissue; improved; insight; large datasets; pathogen; precision medicine; rare variant; reproductive; success; tool; trait; transcriptome sequencing; whole genome

ABSTRACT: The vast majority of human mutations have minor allele frequencies (MAF) under 1%, with the plurality observed only once (i.e., “singletons”). While Mendelian diseases are predominantly caused by rare alleles, the cumulative contribution of rare variants to complex phenotypes remains hotly debated. In our recent work, we demonstrated that ultrarare variants (MAF<0.01%) make a substantial contribution to the genetic architecture of human transcriptional regulation (an intermediate between genetic variation and complex disease)1, and low frequency variants constitute nearly half the heritability of several complex traits (on average)2. In this study, we will functionally validate the role that ultrarare variants play in human gene expression using massively parallel reporter assays (MPRAs). MPRA have revolutionized the way enhancers can be assayed for activity. We will utilize MPRAs to functionally validate our finding that ultrarare variants dominate the genetic architecture of human gene expression. We will use insights from this technology to drive statistical and bioinformatic improvements in the way genetic variation data are analyzed. We will then expand our analysis to quantify the genetic architecture of gene expression across tissues. All tissues in the human body derive from essentially the same DNA but exhibit remarkably different patterns of gene expression. We will extend our Haseman-Elston (HE) regression approach for modeling the genetic architecture of gene expression to multiple traits to uncover cross-tissue and tissue-specific genetic effects using WGS and multi-tissue RNA-sequencing data from the GTEx project5. Finally, we will improve genomic-based precision medicine efforts for all by characterizing the population-specific genetic architecture of complex traits. Every human population has experienced a different evolutionary history in the recent past (different pathogens, different limits on reproductive growth, etc). Each population therefore has a different distribution of genetic variation. As a consequence, different populations likely have different genetic architectures for complex traits. Further, many understudied populations are admixed (with ancestry deriving from multiple populations). We will extend our HE regression approach to model shared and population-specific genetic effects using >140 thousand samples from multiple populations with whole genome sequencing data and complex trait data from the TOPMed Project6.

抽象的： 绝大多数人类突变的次要等位基因频率 (MAF) 低于 1%，其中 仅观察到一次（即“单例”），而孟德尔疾病主要是由罕见等位基因引起的， 罕见变异对复杂表型的累积贡献仍然是我们最近的热门争论。 工作中，我们证明了极其罕见的变异（MAF<0.01%）对遗传做出了重大贡献 人类转录调控的结构（遗传变异和复杂的中间体） 疾病）1，低频变异构成了几个复杂性状遗传力的近一半（关于 平均）2。在这项研究中，我们将从功能上验证超罕见变异在人类基因中的作用。 使用大规模并行检测报告基因 (MPRA) 进行表达彻底改变了表达方式。 我们将利用 MPRA 来功能性验证我们的发现。 我们将利用来自超罕见变异的见解来主导人类基因表达的遗传结构。 该技术可推动遗传变异数据的统计和生物信息改进 然后我们将扩展我们的分析以量化基因表达的遗传结构。 人体的所有组织本质上都源自相同的 DNA，但表现出惊人的不同。 我们将扩展我们的 Haseman-Elston (HE) 回归方法进行建模。 基因表达的遗传结构对多种性状的揭示，以揭示跨组织和组织特异性 最后，我们将使用来自 GTEx 项目的 WGS 和多组织 RNA 测序数据来研究遗传效应。 通过表征特定人群的遗传特征，改善所有人的基于基因组的精准医学工作 每个人类群体都经历了不同的进化历史。 最近的过去（不同的病原体，不同的生殖生长限制等）。 具有不同的遗传变异分布，因此不同的人群可能具有不同的遗传变异。 此外，许多未被研究的人群是混合的（有血统）。 来自多个群体）我们将扩展我们的 HE 回归方法来模型共享和 使用来自多个群体的超过 14 万个样本进行群体特异性遗传效应 来自 TOPMed 项目的基因组测序数据和复杂性状数据6。