Abstract
The phylogeny and speciation of subterranean zokors in China are unclear, as previous studies on morphology and limited molecular markers have generated conflicting results. This study unraveled the complex evolutionary history of eight zokor species in China based on de novo assembly at chromosome level and whole-genome sequencing of 23 populations. We found extensive phylogenetic discordances between nuclear and mitochondrial phylogenies, and different coalescent phylogenies, which could be explained by introgression and incomplete lineage sorting (ILS). The recent Qinghai-Tibet Plateau uplift (∼3.60 million y ago; Mya) drove Eospalax to speciate into clade A and clade B (∼3.22 Mya), and discordant phylogenies in this node were mainly attributed to introgression rather than ILS. Clade A rapidly diverged into three lineages due to geographical isolation and glaciation, while glaciation and C4 plant expansion contributed to the speciation of clade B. ILS contributed to the discordances of two rapidly radiated nodes rather than introgression. The effective population sizes (Ne’s) of all the species of Eospalax were affected by three glaciations. Ancient polymorphisms and divergence hitchhiking contribute to genomic islands of all the species pairs. Positively selected genes putatively related to specific inhabitation adaptations were identified, such as heart development, neurogenesis, DNA repair, and immune response. Climate, geological tectonism, and C4 vegetation shaped the adaptation and speciation of zokors in China.
Original language | English |
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Article number | e2121819119 |
Number of pages | 11 |
Journal | Proceedings of the National Academy of Sciences of the United States of America |
Volume | 119 |
Issue number | 19 |
Early online date | 5 May 2022 |
DOIs | |
Publication status | Published - 10 May 2022 |
Keywords
- Myospalacinae
- Population genomics
- Introgression
- Incomplete lineage sorting
- Speciation
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Genomic insights into zokors' phylogeny and speciation in China (dataset)
Zhang, S. (Contributor), NCBI GenBank, 2024
https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA776391
Dataset