Harwood Michelle P, Alves Isabel, Edgington Hilary, Agbessi Mawusse, Bruat Vanessa, Soave David, Lamaze Fabien C, Favé Marie-Julie, Awadalla Philip
Ontario Institute for Cancer Research, Toronto, ON, Canada.
Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
Sci Adv. 2022 May 13;8(19):eabl3819. doi: 10.1126/sciadv.abl3819.
How the genetic composition of a population changes through stochastic processes, such as genetic drift, in combination with deterministic processes, such as selection, is critical to understanding how phenotypes vary in space and time. Here, we show how evolutionary forces affecting selection, including recombination and effective population size, drive genomic patterns of allele-specific expression (ASE). Integrating tissue-specific genotypic and transcriptomic data from 1500 individuals from two different cohorts, we demonstrate that ASE is less often observed in regions of low recombination, and loci in high or normal recombination regions are more efficient at using ASE to underexpress harmful mutations. By tracking genetic ancestry, we discriminate between ASE variability due to past demographic effects, including subsequent bottlenecks, versus local environment. We observe that ASE is not randomly distributed along the genome and that population parameters influencing the efficacy of natural selection alter ASE levels genome wide.
群体的基因组成如何通过随机过程(如遗传漂变)并结合确定性过程(如选择)而发生变化,这对于理解表型如何在空间和时间上变化至关重要。在这里,我们展示了影响选择的进化力量,包括重组和有效群体大小,如何驱动等位基因特异性表达(ASE)的基因组模式。整合来自两个不同队列的1500名个体的组织特异性基因型和转录组数据,我们证明在低重组区域较少观察到ASE,而高重组或正常重组区域的基因座在利用ASE下调有害突变方面更有效。通过追踪遗传谱系,我们区分了由于过去的人口统计学效应(包括随后的瓶颈效应)导致的ASE变异性与局部环境导致的ASE变异性。我们观察到ASE并非沿基因组随机分布,并且影响自然选择效力的群体参数会在全基因组范围内改变ASE水平。