bioRxivEvolutionary BiologyPreprint
Conservation Genomics of Urban Populations of Streamside Salamander (Ambystoma barbouri)
Abstract
In Tennessee, populations of the state endangered Streamside Salamander (Ambystoma barbouri) are in decline as their distribution lies mostly within rapidly developing areas in the Nashville Basin. Information regarding the partitioning of genetic variation among populations of A. barbouri, and the taxonomic status of these populations relative to northern populations and their congener, the smallmouth salamander (A. texanum), have important implications for management and conservation of this species. Here we combined mitochondrial sequencing and genome-wide single nucleotide polymorphism (SNP) data generated using Genotyping-by-Sequencing (GBS) to investigate patterns of genetic variation within Tennessee populations of A. barbouri, to assess their relationship to populations in Kentucky, and to examine their phylogenetic relationship to the closely related A. texanum. Results from phylogenetic reconstructions reveal a complex history of Tennessee A. barbouri populations with regards to northern populations, unisexual A. barbouri, and A. texanum. Patterns of mitochondrial sequence variation suggest that A. barbouri may have originated within Tennessee and expanded north multiple times into Kentucky, Ohio, Indiana and West Virginia. Phylogenetic reconstructions based on genome-wide SNP data contradict results based on mitochondrial DNA and correspond to geographic and taxonomic boundaries. Variation in allele frequencies at SNP genotypes, as identified by multivariate analyses and Bayesian assignment tests, identified three evolutionary significant units (ESUs) for A. barbouri within the state of Tennessee. Collectively, these results emphasize the need for prioritizing conservation needs of Tennessee populations of A. barbouri to ensure the long-term persistence of this species.
- organism: mouse
- assay: DNA methylation
- research focus: phylogenetics / evolution
- approach: statistical model
- approach: Bayesian inference
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