Evolutionary Human Genomics: Demography, Natural Selection, and Transcriptional Regulation

进化人类基因组学：人口学、自然选择和转录调控

• 批准号: 10360470
• 负责人: Adam Charles Siepel
• 金额: $ 47.92万
• 依托单位: COLD SPRING HARBOR LABORATORY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-03-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10360470
• 关键词: Address; Architecture; Area; Biochemical; Biological Assay; CRISPR screen; Collaborations; Data; Demography; Detection; Development; Enhancers; Evolution; Genes; Genetic; Genetic Diseases; Genetic Drift; Genetic Recombination; Genetic Transcription; Genetic Variation; Genome; Goals; Graph; Health; Human; Human Biology; Human Genetics; Human Genome; Laboratories; Light; Machine Learning; Maps; Measures; Methods; Modernization; Molecular Evolution; Mutation; Natural Selections; Pattern; Phenotype; Pongidae; Population; Population Genetics; Primates; RNA Stability; Regulatory Element; Reporting; Research; Sample Size; Sampling; Series; Statistical Models; Techniques; Transcription Initiation; Transcriptional Regulation; Untranslated RNA; base; computer science; fitness; genetic variant; genome analysis; genome annotation; genome sequencing; genomic data; human genomics; improved; promoter; reconstruction; statistics

To be fully understood, the human genome must be considered in the context of evolution. The activities that have dominated human genomics for three decades — such as genome sequencing and annotation, interrogation with high-throughput biochemical assays, and the identification of associations between genetic variants and diseases — have been enormously informative, but these descriptive studies must eventually be understood within the theoretical framework of evolutionary genetics. We must continue to press forward from the what? to the why? and how? of human genetics. The goal of my laboratory is to interpret high-throughput genomic data from an evolutionary perspective. Drawing from ideas and techniques in molecular evolution, population genetics, statistics, and computer science, we aim both to understand the evolutionary forces that have shaped human genomes, and to use evolution to shed light on the phenotypic importance of particular sequences. Our recent activities have focused in three major areas: (1) reconstruction of features of human evolution based on genome sequences; (2) prediction of the fitness consequences of human mutations; and (3) the study of transcriptional regulation and its evolution in primates. We have reported major findings in each of these areas, including the existence of gene flow from early modern humans to Eastern Neandertals, a map of fitness consequences for mutations across the human genome, and an analysis showing that the architecture of transcription initiation is highly similar at enhancers and promoters in the human genome. Here we propose to extend our research substantially in each of these areas, working together with a broad range of experimental and theoretical collaborators. Our new goals include the development of improved methods for reconstructing human demography, with a focus on ancient gene flow; extensions of our ancestral recombination graph (ARG) sampling methods to accommodate much larger samples sizes, with applications in association mapping and the detection of natural selection; two complementary machine-learning approaches for improving the prediction of fitness consequences from sequence data; an experimental collaboration to leverage CRISPR-Cas9 screens in characterizing noncoding mutations; a multi-pronged study of the sequence determinants of RNA stability and their implications for the evolution of transcription units; and development of a new probabilistic model for turnover of regulatory elements. Together, these projects will address a wide variety of fundamental questions about the function and evolution of sequences in the human genome.

为了充分了解人类基因组，必须在进化的背景下考虑人类基因组。三十年来主导人类基因组学的活动——如基因组测序和注释、高通量生化分析的拷问、遗传变异和疾病之间关联的识别——已经提供了大量信息，但这些描述性研究最终必须在进化遗传学的理论框架内得到理解。我们必须继续向前推进从什么？为什么？以及如何?人类遗传学。