DOI: 10.5061/dryad.cfxpnvxh7
title: Data from: A tale of two tails: Untangling the phylogeography and demographic history of extant species of mulgara (<em>Dasycercus</em> spp.) in the Australian arid zone

description: Australia’s arid and semi-arid zones cover approximately 70% of the
 continent, yet the biogeography of these extensive and diverse landscapes
 remains poorly understood. Mulgara (Dasycercus spp.; Marsupialia:
 Dasyuridae) are widely distributed across these regions and provide an
 opportunity to investigate patterns of population structure that have
 previously been obscured by taxonomic uncertainty. Using contemporary and
 museum tissue samples, we generated next-generation sequencing data for
 311 individuals and retained 4,360 single-nucleotide polymorphisms for
 population genomic analyses. We found that the two extant species, the
 brush-tailed mulgara (Dasycercus blythi) and the crest-tailed mulgara (D.
 hillieri), are clearly delineated and correspond well with their currently
 recognised distributions. Population genomic analyses of the brush-tailed
 mulgara (212 individuals, 2,740 SNPs) revealed substructure that aligns
 primarily with major drainage divisions. Historical demographic inference
 suggested largely stable population sizes over the past 1,000 years,
 although declines following European colonisation in some populations
 cannot be excluded. The Pilbara population was the most genetically
 differentiated and showed stronger isolation-by-distance than other
 populations, yet levels of observed heterozygosity were similar across all
 populations (Ho = 0.078–0.090). These results suggest that stable
 population dynamics, high dispersal potential, and ecological
 characteristics of mulgara contribute to consistent genetic diversity
 across much of the species’ range, while geographic features such as major
 drainage divisions shape contemporary population structure. Further
 targeted sampling in under-represented regions will improve estimates of
 genomic diversity, population structure, and genetic health across the
 full distribution of the species.
description: # A tale of two tails: Untangling mulgara (Dasycercus spp.) species
 identity and phylogeography in the Australian arid zone
 [https://doi.org/10.5061/dryad.cfxpnvxh7](https://doi.org/10.5061/dryad.cfxpnvxh7) ## Description of the data and file structure Single-nucleotide polymorphism data were obtained from commercial library preparation and sequencing of extracted genomic DNA provided to Diversity Arrays Pty Ltd. Two Rdata files (DasycercusALL_MANUSCRIPT_filtered_v4.rdata and DasycercusBLYTHI_MANUSCRIPT_filtered_v4.rdata)  are provided that represent the filtered SNP datasets used in analyses in the manuscript, one containing all *Dasycercus blythi* and *D. hillieri* samples and the other containing only *D. blythi* samples, that was used for population genomic analyses. Samples in the latter file cover the distribution of Dasycercus blythi across the Australian arid zone and are grouped into four regional populations, Central East, Central Australia, Murchison, and Pilbara. The DArTseq SNP x sample matrix file was converted to genlight format in R, and quality filterwere s applied primarily in the dartR R package. The sample metadata indicating population of origin is also provided in the ind. metrics slot of each genlight file. This dataset contains SNP genotypes obtained from DArTseq analysis of tissue samples from the brush-tailed mulgara and the crest-tailed mulgara. Raw SNP genotypes were quality filtered on read depth, reproducibility, call rate by locus and individual samples, multiple SNP loci found on the same contig (retaining only a single locus with the best repeatability), and minor allele count. In addition, loci that showed significant departure from Hardy-Weinberg equilibrium across both species or all *a priori* populations. The SNPs were also pruned based on linkage disequilibrium*.* Metadata relating to the sample population of origin and other characteristics is also provided.  ## Code/software The SNP genotype files are provided as R data files and can be loaded into R using load(). The file is in genlight format and is manipulated primarily using functions in the dartR package v2.9.5.