bioRxivBioinformaticsPreprint
Pleistocene Mammal Population Fluctuation Patterns Inferred by Their Genomes
Yulu LiuiD, Biao LiuiD, Xingxin PaniD, Qiong ShiiD, Zhoujian XiaoiD, Shengbin LiiD, Shuai Cheng LiiD
Abstract
Paleoclimate fluctuations critically affect paleoecological systems and influence mammal populations, even resulting in population differentiation [1]. Historical effective population size (Ne) can reflect these influences [2, 3]. Dozens of recent studies have investigated the relationship between variations in Ne values of one or a small number of mammalian species, inferred from genomic data, and fluctuations in paleoclimate [4-7]. However, there lacks an integrated and comprehensive study on the relationship between the fluctuations in paleoclimate and variations in Ne values inferred from genome sequencing data of a wide range of mammals. To investigate patterns in mammalian Ne values during the the Pleistocene, we gathered whole genome sequencing data of 60 mammals from 35 species distributed across Afro-Eurasia and the Americas, then inferred their Ne curves using the Pairwise Sequentially Markovian Coalescent (PSMC) method; 30 mammalian Ne curves almost simultaneously started to contract at the turning point of the Middle Pleistocene Transition (MPT); then the population of seven mammals started to expand at the turning point of the Middle Brunhes Event (MBE), while the contraction of other mammals populations was prolonged to the later different time periods. Eight mammals experienced a severe population contraction around the Last Glaciation Maximum, as some aves did [8], while four potential ruminant beneficiaries showed an expanding population. Sus scrofa and Bos taurus experienced an internal population differentiation in the MPT. To conclude, the phenomenon that critical paleoclimate events facilitated contemporaneous animal population fluctuations in the paleoecological system is showed by our Ne curve analysis.
- organism: multiple species
- assay: whole-genome sequencing
- research focus: variant calling
- approach: statistical model
- Citations
- 0
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