Contrasting demographic history and mutational load in three threatened whitebark pines (Pinus subsect. Gerardianae): implications for conservation

濒危物种 濒危物种 生物 人口历史 人口 生态学 进化生物学 有效人口规模 环境生态位模型 鳞片 适应(眼睛) 生态位 动物 遗传变异 遗传学 人口学 栖息地 基因 神经科学 社会学
作者
Yixuan Kou,Mili Liu,Jordi López‐Pujol,Qijing Zhang,Zhiyong Zhang,Zhong‐Hu Li
出处
期刊:Plant Journal [Wiley]
卷期号:119 (6): 2967-2981
标识
DOI:10.1111/tpj.16965
摘要

SUMMARY Demographic history and mutational load are of paramount importance for the adaptation of the endangered species. However, the effects of population evolutionary history and genetic load on the adaptive potential in endangered conifers remain unclear. Here, using population transcriptome sequencing, whole chloroplast genomes and mitochondrial DNA markers, combined with niche analysis, we determined the demographic history and mutational load for three threatened whitebark pines having different endangered statuses, Pinus bungeana , P. gerardiana and P. squamata . Demographic inference indicated that severe bottlenecks occurred in all three pines at different times, coinciding with periods of major climate and geological changes; in contrast, while P. bungeana experienced a recent population expansion, P. gerardiana and P. squamata maintained small population sizes after bottlenecking. Abundant homozygous‐derived variants accumulated in the three pines, particularly in P. squamata , while the species with most heterozygous variants was P. gerardiana . Abundant moderately and few highly deleterious variants accumulated in the pine species that have experienced the most severe demographic bottlenecks ( P. gerardiana and P. squamata ), most likely because of purging effects. Finally, niche modeling showed that the distribution of P. bungeana might experience a significant expansion in the future, and the species' identified genetic clusters are also supported by differences in the ecological niche. The integration of genomic, demographic and niche data has allowed us to prove that the three threatened pines have contrasting patterns of demographic history and mutational load, which may have important implications in their adaptive potential and thus are also key for informing conservation planning.
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