Incorporating geography into statistical methods for analysis of population genomic DNA
将地理学纳入群体基因组 DNA 分析的统计方法
基本信息
- 批准号:10737747
- 负责人:
- 金额:$ 37.51万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-01 至 2025-04-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Project Summary
In humans, genetic variation is distributed geographically, reflecting the history of human movements across
the continents. Understanding these spatial patterns is crucial for many fields in human population genomics,
including the study of human evolutionary history and linking genotypes and phenotypes. Historically, limi-
tations in the size and scope of empirical datasets have allowed researchers to employ models that ignore
geography, but modern genomic datasets demand population genetic methods that incorporate geographic
space. The proposed research will generate novel statistical methods that incorporate geography into the
study of population genetic structure, admixture, demography, and natural selection. These methods will be
developed and implemented as open-source software, validated using state-of-the-art forward-time simula-
tions, and applied to publicly available human genomic datasets.
We will develop tests for population admixture that explicitly account for geographic patterns due to isolation
by distance. These tests will be used to analyze densely sampled Eurasian human genomic datasets to
identify admixed samples, and will also be applied in sliding windows along the genome to highlight genomic
regions that may have been transferred between populations via adaptive introgression. We will also develop
a spatiotemporal population clustering method that can jointly analyze ancient and modern samples. Neutral
genetic processes are expected to generate population differentiation between samples separated in space or
time, so this clustering method will account for both when determining whether two samples share ancestry in
the same discrete population. This method will be extended to detect selection on polygenic traits by testing for
an aggregate increase in the frequency of alleles involved in a particular trait relative to the neutral expectation.
We will apply this method to test for selection through time on human height across Eurasia. Finally, we will
model the lengths of shared genomic segments between individuals, which are informative about genealogical
overlap at different points in the past, to learn about how population density and dispersal patterns have
changed across geographic space through time.
The proposed work represents advances in a number of fields in statistical population genetics, including the
detection of population admixture, adaptive introgression, population replacement and the joint analysis of
DNA from ancient and modern samples, detecting selection on polygenic traits, and modeling heterogeneity
in demographic processes through time. Taken together, this work will offer empirical researchers a valuable
toolkit for the analysis of modern genomic datasets, which require spatially explicit methods, and will shed light
on both human evolutionary history and the mechanisms by which humans have adapted to their environment
across space and time.
项目总结
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Gideon Bradburd其他文献
Gideon Bradburd的其他文献
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{{ truncateString('Gideon Bradburd', 18)}}的其他基金
Incorporating geography into statistical methods for analysis of population genomic DNA
将地理学纳入群体基因组 DNA 分析的统计方法
- 批准号:
10615605 - 财政年份:2022
- 资助金额:
$ 37.51万 - 项目类别:
Incorporating geography into statistical methods for analysis of population genomic DNA
将地理学纳入群体基因组 DNA 分析的统计方法
- 批准号:
10027142 - 财政年份:2020
- 资助金额:
$ 37.51万 - 项目类别:
Incorporating geography into statistical methods for analysis of population genomic DNA
将地理学纳入群体基因组 DNA 分析的统计方法
- 批准号:
10200099 - 财政年份:2020
- 资助金额:
$ 37.51万 - 项目类别:
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