eSMC : a statistical model to infer admixture events from individual genomics data

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

  • Yonghui Wang
  • Yinan Wang
  • Xiaobo Qian
  • Changfa Wang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number827
Journal / PublicationBMC Genomics
Volume23
Issue numberSupplement 4
Online published14 Dec 2022
Publication statusPublished - 2022

Link(s)

Abstract

Background: Inferring historical population admixture events yield essential insights in understanding a species demographic history. Methods are available to infer admixture events in demographic history with extant genetic data from multiple sources. Due to the deficiency in ancient population genetic data, there lacks a method for admixture inference from a single source. Pairwise Sequentially Markovian Coalescent (PSMC) estimates the historical effective population size from lineage genomes of a single individual, based on the distribution of the most recent common ancestor between the diploid’s alleles. However, PSMC does not infer the admixture event.

Results: Here, we proposed eSMC, an extended PSMC model for admixture inference from a single source. We evaluated our model’s performance on both in silico data and real data. We simulated population admixture events at an admixture time range from 5 kya to 100 kya (5 years/generation) with population admix ratio at 1:1, 2:1, 3:1, and 4:1, respectively. The root means the square error is ± 7.61 kya for all experiments. Then we implemented our method to infer the historical admixture events in human, donkey and goat populations. The estimated admixture time for both Han and Tibetan individuals range from 60 kya to 80 kya (25 years/generation), while the estimated admixture time for the domesticated donkeys and the goats ranged from 40 kya to 60 kya (8 years/generation) and 40 kya to 100 kya (6 years/generation), respectively. The estimated admixture times were concordance to the time that domestication occurred in human history.

Conclusion: Our eSMC effectively infers the time of the most recent admixture event in history from a single individual’s genomics data. The source code of eSMC is hosted at https://github.com/zachary-zzc/eSMC.

Research Area(s)

  • Demographic History, Domestication, Population Admixture, PSMC, TMRCA

Citation Format(s)

eSMC: a statistical model to infer admixture events from individual genomics data. / Wang, Yonghui; Zhao, Zicheng; Miao, Xinyao et al.
In: BMC Genomics, Vol. 23, No. Supplement 4, 827, 2022.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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