Species diversification in the sky islands of southwestern China revealed by genomic, introgression and demographic analyses of Asian shrew moles

The mountains of Southwest China, a global biodiversity hotspot, have a unique “sky island” landscape with high diversity of both ancient and recently formed species. While their distribution patterns offer significant insights into diversification processes, the complex geological and climatic history, combined with dynamic histories of gene flow in endemic taxa, makes unravelling this history challenging. This study focuses on Asian shrew moles (genus Uropsilus), an ancient group endemic to this region with an unresolved taxonomic system. By combining phylogenomic, introgression, and demographic history analyses, we investigated the historical patterns of species diversification in this genus. We detected phylogenetic discordances among rapidly diverged lineages, driven by incomplete lineage sorting, both recent and ancient gene flow, and ghost introgression. The gene flow patterns revealed strong genetic isolation in the Hengduan Mountains region, contrasted by more extensive dispers..., , , # Data from: Phylogenomic and Biogeographic Study of Asian shrew moles

The data includes the input files used in the analysis of the study.

#### The following is the file structure and data description:

\"Uropsilus_filtered_SNP.vcf.gz\"
The whole-genome high-quality biallelic single-nucleotide polymorphisms (SNPs) of 39 samples.

\"raxml_input_SNPs.phy\"
The SNPs file used for constructing the maximum likelihood (ML) tree, converted to .phy format for input into RAxML 8.2.12.

\"NJ_IBS.txt\"
Pairwise estimates of identity-by-state (IBS) scores for all samples obtained by PLINK 1.90, used for constructing a neighbor-joining (NJ) tree with Phylip 3.698.

\"iqtree_input_CDS_4dtv.fas\"
The four-fold degenerate sites obtained from single-copy orthologous genes (CDS-4dtv) of 16 Uropsilus cryptic species and an outgroup Talpa occidentalis, used for constructing a ML tree with IQ-TREE 2.1.4.

\"15_mitochondria_genes_concatenation.phy\"
A concatenated dataset comprising 13 protein-coding genes and two ...,