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Can a sex-biased human demography account for the reduced effective population size of chromosome X in non-Africans?

ABSTRACT: Sex-biased demographic events can result in asymmetries in female and male effective population size that can lead to different patterns of genetic variation on chromosome X than are expected based on the patterns on the autosomes. Previous studies point to a period around the time of the dispersal of anatomically modern humans out of Africa when chromosome X experienced a significant reduction in effective population size relative to the autosomes. Here, we explore whether a sex-biased demographic history could explain these observations. We use coalescent simulations to show that a model of primarily male migration during the out-of-Africa dispersal can produce the striking patterns that are observed when comparing patterns of genetic variation on the autosomes and chromosome X. The model involves a history in which after the founder population of non-Africans lost much of its genetic diversity, subsequent mostly male gene flow from an African source brought new diversity into the population. We also explore two additional models, one of sex-biased generation time and one of a substructured population during the dispersal out of Africa with primarily female migration among demes. These latter models cannot account for the magnitude of the observed reduction in chromosome X effective population size, although it is plausible that they played a more minor role in producing the striking chromosome X/autosome patterns.

SUBMITTER: Keinan A

PROVIDER: S-EPMC2944028 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

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Can a sex-biased human demography account for the reduced effective population size of chromosome X in non-Africans?

Keinan Alon A Reich David D

Molecular biology and evolution 20100507 10

Sex-biased demographic events can result in asymmetries in female and male effective population size that can lead to different patterns of genetic variation on chromosome X than are expected based on the patterns on the autosomes. Previous studies point to a period around the time of the dispersal of anatomically modern humans out of Africa when chromosome X experienced a significant reduction in effective population size relative to the autosomes. Here, we explore whether a sex-biased demograp ...[more]

PMID: 20453016

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Project description:Sex-biased demographic events ("sex-bias") involve unequal numbers of females and males. These events are typically inferred from the relative amount of X-chromosomal to autosomal genetic variation and have led to conflicting conclusions about human demographic history. Though population size changes alter the relative amount of X-chromosomal to autosomal genetic diversity even in the absence of sex-bias, this has generally not been accounted for in sex-bias estimators to date. Here, we present a novel method to identify sex-bias from genetic sequence data that models population size changes and estimates the female fraction of the effective population size during each time epoch. Compared to recent sex-bias inference methods, our approach can detect sex-bias that changes on a single population branch without requiring data from an outgroup or knowledge of divergence events. When applied to simulated data, conventional sex-bias estimators are biased by population size changes, especially recent growth or bottlenecks, while our estimator is unbiased. We next apply our method to high-coverage exome data from the 1000 Genomes Project and estimate a male bias in Yorubans (47% female) and Europeans (44%), possibly due to stronger background selection on the X chromosome than on the autosomes. Finally, we apply our method to the 1000 Genomes Project Phase 3 high-coverage Complete Genomics whole-genome data and estimate a female bias in Yorubans (63% female), Europeans (84%), Punjabis (82%), as well as Peruvians (56%), and a male bias in the Southern Han Chinese (45%). Our method additionally identifies a male-biased migration out of Africa based on data from Europeans (20% female). Our results demonstrate that modeling population size change is necessary to estimate sex-bias parameters accurately. Our approach gives insight into signatures of sex-bias in sexual species, and the demographic models it produces can serve as more accurate null models for tests of selection.

Dataset Information

Can a sex-biased human demography account for the reduced effective population size of chromosome X in non-Africans?

Publications

Can a sex-biased human demography account for the reduced effective population size of chromosome X in non-Africans?

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