Genome-wide SNP analysis unveils genetic structure and phylogeographic history of snow sheep () populations inhabiting the Verkhoyansk Mountains and Momsky Ridge (northeastern Siberia).

Insights into the genetic characteristics of a species provide important information for wildlife conservation programs. Here, we used the OvineSNP50 BeadChip developed for domestic sheep to examine population structure and evaluate genetic diversity of snow sheep () inhabiting Verkhoyansk Range and Momsky Ridge. A total of 1,121 polymorphic SNPs were used to test 80 specimens representing five populations, including four populations of the Verkhoyansk Mountain chain: Kharaulakh Ridge-Tiksi Bay (TIK, =22), Orulgan Ridge (ORU, =22), the central part of Verkhoyansk Range (VER, =15), Suntar-Khayata Ridge (SKH, =13), and Momsky Ridge (MOM, =8). We showed that the studied populations were genetically structured according to a geographic pattern. Pairwise values ranged from 0.044 to 0.205. Admixture analysis identified =2 as the most likely number of ancestral populations. A Neighbor-Net tree showed that TIK was an isolated group related to the main network through ORU. TreeMix analysis revealed that TIK and MOM originated from two different ancestral populations and detected gene flow from MOM to ORU. This was supported by the f3 statistic, which showed that ORU is an admixed population with TIK and MOM/SKH heritage. Genetic diversity in the studied groups was increasing southward. Minimum values of observed (Ho) and expected (He) heterozygosity and allelic richness (Ar) were observed in the most northern population-TIK, and maximum values were observed in the most southern population-SKH. Thus, our results revealed clear genetic structure in the studied populations of snow sheep and showed that TIK has a different origin from MOM, SKH, and VER even though they are conventionally considered a single subspecies known as Yakut snow sheep (). Most likely, TIK was an isolated group during the Late Pleistocene glaciations of Verkhoyansk Range.