气候变化领域集成服务门户(CCPortal): Nonparametric coalescent inference of mutation spectrum history and demography

CCPortal

DOI	10.1073/pnas.2013798118
	Nonparametric coalescent inference of mutation spectrum history and demography
	DeWitt W.S.; Harris K.D.; Ragsdale A.P.; Harris K.
发表日期	2021
ISSN	0027-8424
卷号	118 期号:21
英文摘要	As populations boom and bust, the accumulation of genetic diversity is modulated, encoding histories of living populations in present-day variation. Many methods exist to decode these histories, and all must make strong model assumptions. It is typical to assume that mutations accumulate uniformly across the genome at a constant rate that does not vary between closely related populations. However, recent work shows that mutational processes in human and great ape populations vary across genomic regions and evolve over time. This perturbs the mutation spectrum (relative mutation rates in different local nucleotide contexts). Here, we develop theoretical tools in the framework of Kingman’s coalescent to accommodate mutation spectrum dynamics. We present mutation spectrum history inference (mushi), a method to perform nonparametric inference of demographic and mutation spectrum histories from allele frequency data. We use mushi to reconstruct trajectories of effective population size and mutation spectrum divergence between human populations, identify mutation signatures and their dynamics in different human populations, and calibrate the timing of a previously reported mutational pulse in the ancestors of Europeans. We show that mutation spectrum histories can be placed in a well-studied theoretical setting and rigorously inferred from genomic variation data, like other features of evolutionary history. © 2021 National Academy of Sciences. All rights reserved.
英文关键词	Coalescent theory; Demographic inference; Inverse problems; Mutation spectrum; Sample frequency spectrum
语种	英语
scopus关键词	Article; calibration; conceptual framework; demography; gene frequency; gene mutation; genetic variation; history; human genetics; molecular dynamics; molecular evolution; mutation spectrum history; mutational analysis; nonparametric test; population genetics; population size; priority journal
来源期刊	Proceedings of the National Academy of Sciences of the United States of America
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/238912
作者单位	Department of Genome Sciences, University of Washington, Seattle, WA 98195, United States; Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, United States; Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA 98195, United States; Department of Biology, University of Washington, Seattle, WA 98195, United States; National Laboratory of Genomics for Biodiversity, Unit of Advanced Genomics, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Irapuato, 36821, Mexico
推荐引用方式 GB/T 7714	DeWitt W.S.,Harris K.D.,Ragsdale A.P.,et al. Nonparametric coalescent inference of mutation spectrum history and demography[J],2021,118(21).
APA	DeWitt W.S.,Harris K.D.,Ragsdale A.P.,&Harris K..(2021).Nonparametric coalescent inference of mutation spectrum history and demography.Proceedings of the National Academy of Sciences of the United States of America,118(21).
MLA	DeWitt W.S.,et al."Nonparametric coalescent inference of mutation spectrum history and demography".Proceedings of the National Academy of Sciences of the United States of America 118.21(2021).