bioRxivEvolutionary Biology
Range stability predicts lineage persistence in a morphologically cryptic ground squirrel species complex
Abstract
The processes responsible for patterns of cytonuclear discordance remain unclear. Here, we employ an exon capture dataset, demographic methods, and species distribution modeling to elucidate the impact of historical demography on patterns of genealogical concordance and discordance in ground squirrel lineages from the Otospermophilus beecheyi species complex. Previous studies in O. beecheyi revealed three morphologically cryptic and highly divergent mitochondrial DNA (mtDNA) lineages (named the Northern, Central, and Southern lineages based on geography) with only the Northern lineage exhibiting concordant divergence in nuclear markers. We show that these mtDNA lineages likely formed in allopatry during the Pleistocene, but responded differentially to climatic changes that occurred since the last interglacial ([~]120,000 years ago). We find that the Northern lineage maintained a stable range throughout this period, correlating with genetic distinctiveness among all genetic markers and low migration rates between the other lineages. In contrast, our results support a scenario where the Southern lineage expanded from Baja California Sur during the Late Pleistocene and hybridized with the Central lineage, eventually driving the Central lineage to extinction. While high intraspecific gene flow among newly colonized populations eroded significant signals of Central ancestry from autosomal markers, male sex-biased dispersal in this system preserved signals of this past hybridization and introgression event in matrilineal-biased X-chromosome and mtDNA markers. Our results highlight the importance of range stability in maintaining the persistence of phylogeographic lineages, whereas unstable range dynamics can increase the tendency for lineages to interact and collapse upon secondary contact.
- organism: mouse
- assay: DNA methylation
- research focus: development & morphogenesis
- approach: statistical model
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