Spurley William J, Payseur Bret A
Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, USA.
Genome Biol Evol. 2025 Mar 6;17(3). doi: 10.1093/gbe/evaf035.
In many populations, unequal numbers of females and males reproduce each generation. This imbalance in the breeding sex ratio shapes patterns of genetic variation on the sex chromosomes and the autosomes in distinct ways. Despite recognition of this phenomenon, effects of the breeding sex ratio on some aspects of variation remain unclear, especially for populations with nonequilibrium demographic histories. To address this gap in the field, we used coalescent simulations to examine relative patterns of variation at X-linked loci and autosomal loci in populations spanning the range of breeding sex ratio with historical changes in population size. Shifts in breeding sex ratio away from 1:1 reduce nucleotide diversity and the number of unique haplotypes and increase linkage disequilibrium and the frequency of the most common haplotype, with contrasting effects on X-linked loci and autosomal loci. Strong population bottlenecks transform relationships among the breeding sex ratio, the site frequency spectrum, and linkage disequilibrium, while relationships among the breeding sex ratio, nucleotide diversity, and haplotype characteristics are broadly conserved. Our findings indicate that evolutionary interpretations of variation on the X chromosome should consider the combined effects of the breeding sex ratio and demographic history. The genomic signatures we report could be used to reconstruct these fundamental population parameters from genomic data in natural populations.
在许多种群中,每一代参与繁殖的雌性和雄性数量并不相等。这种繁殖性别比的失衡以不同方式塑造了性染色体和常染色体上的遗传变异模式。尽管人们已经认识到这一现象,但繁殖性别比对某些变异方面的影响仍不明确,尤其是对于具有非平衡种群历史的种群。为了填补该领域的这一空白,我们使用溯祖模拟来研究在种群数量随历史变化且繁殖性别比范围不同的情况下,X连锁基因座和常染色体基因座上的相对变异模式。繁殖性别比偏离1:1会降低核苷酸多样性和独特单倍型的数量,并增加连锁不平衡和最常见单倍型的频率,对X连锁基因座和常染色体基因座有不同影响。强烈的种群瓶颈会改变繁殖性别比、位点频率谱和连锁不平衡之间的关系,而繁殖性别比、核苷酸多样性和单倍型特征之间的关系则大致保持不变。我们的研究结果表明,对X染色体变异的进化解释应考虑繁殖性别比和种群历史的综合影响。我们报告的基因组特征可用于从自然种群的基因组数据中重建这些基本的种群参数。