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Novel population-genetic methods for localizing targets of natural selection in diverse human genomes

Novel population-genetic methods for localizing targets of natural selection in diverse human genomes
用于在不同人类基因组中定位自然选择目标的新群体遗传学方法
批准号:
10538648
负责人:
Sohini Ramachandran
金额:
$37.45万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-01-01 至 2025-12-31

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英文摘要
PROJECT SUMMARY. The PI's research program in population genetics focuses on the coalescent-based inference of population his- tories from whole genomes, and the determination of genetic basis of adaptation and disease at multiple biolog- ical scales—from mutations to genes to gene subnetworks. In the genomic era, computational and statistical methods are essential for identifying candidate adaptive and disease-associated mutations in humans, in whom mapping via linkage studies is challenging and costly. State-of-the-art approaches that scan genome-wide for signatures of selection or association with phenotype state are routinely applied to samples from one homoge- neous ancestry, rely on arbitrary thresholds for interpreting results, and produce results at genomic scales that can be difficult to connect to biological mechanism (for example, analyzing linkage blocks or sliding genomic windows). Thus, despite the enormous investments made by the NIH and biobanks around the world to generate large-scale genomic datasets from diverse individuals, methods for analyzing such datasets are lagging behind. This application describes a series of projects motivated by answering three fundamental questions in human population genetics: (1) what role has balancing selection played in human adaptation? (2) to what extent has adaptive evolution versus non-adaptive processes shaped human genomes? (3) to what extent do the genetic architectures of human traits vary by ancestry? The overall strategy for future research plans draws on the PI's expertise in coalescent theory, Bayesian inference, population genetics, and statistical genetics to produce new frameworks for analyzing patterns in and evolutionary processes underlying multiethnic genomic datasets. The outcomes of the research described in this MIRA application will give new insight into the interaction between selection and dynamic population histories in generating human genetic diversity, while determining the different modes of selection shaping human phenotypes and diseases.
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Novel population-genetic methods for localizing targets of natural selection in diverse human genomes
  • 批准号:
    10321900
  • 项目类别:
  • 资助金额:
    $37.4万
  • 财政年份:
    2021
  • 负责人:
    Sohini Ramachandran
  • 依托单位:
Predoctoral Training Program in Biological Data Science at Brown University
  • 批准号:
    10405983
  • 项目类别:
  • 资助金额:
    $8.64万
  • 财政年份:
    2018
  • 负责人:
    Sohini Ramachandran
  • 依托单位:
Predoctoral Training Program in Biological Data Science at Brown University
  • 批准号:
    10197955
  • 项目类别:
  • 资助金额:
    $29.26万
  • 财政年份:
    2018
  • 负责人:
    Sohini Ramachandran
  • 依托单位:
Predoctoral Training Program in Biological Data Science at Brown University
  • 批准号:
    10447019
  • 项目类别:
  • 资助金额:
    $31.09万
  • 财政年份:
    2018
  • 负责人:
    Sohini Ramachandran
  • 依托单位:
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