An empirical pipeline for choosing the optimal clustering threshold in RADseq studies.

Genomic data are increasingly used for high resolution population genetic studies including those at the forefront of biological conservation. A key methodological challenge is determining sequence similarity clustering thresholds for RADseq data when no reference genome is available. These thresholds define the maximum permitted divergence among allelic variants and the minimum divergence among putative paralogues and are central to downstream population genomic analyses. Here we develop a novel set of metrics to determine sequence similarity thresholds that maximize the correct separation of paralogous regions and minimize oversplitting naturally occurring allelic variation within loci. These metrics empirically identify the threshold value at which true alleles at opposite ends of several major axes of genetic variation begin to incorrectly separate into distinct clusters, allowing researchers to choose thresholds just below this value. We test our approach on a recently published data set for the protected foothill yellow-legged frog (Rana boylii). The metrics recover a consistent pattern of roughly 96% similarity as a threshold above which genetic divergence and data missingness become increasingly correlated. We provide scripts for assessing different clustering thresholds and discuss how this approach can be applied across a wide range of empirical data sets.

Population genomic data reveal extreme geographic subdivision and novel conservation actions for the declining foothill yellow-legged frog.

Genomic data have the potential to inform high resolution landscape genetic and biological conservation studies that go far beyond recent mitochondrial and microsatellite analyses. We characterize the relationships of populations of the foothill yellow-legged frog, Rana boylii, a declining, "sentinel" species for stream ecosystems throughout its range in California and Oregon. We generated RADseq data and applied phylogenetic methods, hierarchical Bayesian clustering, PCA and population differentiation with admixture analyses to characterize spatial genetic structure across the species range. To facilitate direct comparison with previous analyses, we included many localities and individuals from our earlier work based on mitochondrial DNA. The results are striking, and emphasize the power of our landscape genomic approach. We recovered five extremely differentiated primary clades that indicate that R. boylii may be the most genetically differentiated anuran yet studied. Our results provide better resolution and more spatially consistent patterns than our earlier work, confirming the increased resolving power of genomic data compared to single-locus studies. Genomic structure is not equal across the species distribution. Approximately half the range of R. boylii consists of a single, relatively uniform population, while Sierra Nevada and coastal California clades are deeply, hierarchically substructured with biogeographic breaks observed in other codistributed taxa. Our results indicate that clades should serve as management units for R. boylii rather than previously suggested watershed boundaries, and that the near-extinct population from southwestern California is particularly diverged, exhibits the lowest genetic diversity, and is a critical conservation target for species recovery.

Conservation genetics and genomics of amphibians and reptiles.

Amphibians and reptiles as a group are often secretive, reach their greatest diversity often in remote tropical regions, and contain some of the most endangered groups of organisms on earth. Particularly in the past decade, genetics and genomics have been instrumental in the conservation biology of these cryptic vertebrates, enabling work ranging from the identification of populations subject to trade and exploitation, to the identification of cryptic lineages harboring critical genetic variation, to the analysis of genes controlling key life history traits. In this review, we highlight some of the most important ways that genetic analyses have brought new insights to the conservation of amphibians and reptiles. Although genomics has only recently emerged as part of this conservation tool kit, several large-scale data sources, including full genomes, expressed sequence tags, and transcriptomes, are providing new opportunities to identify key genes, quantify landscape effects, and manage captive breeding stocks of at-risk species.

Multilocus phylogeny of the New-World mud turtles (Kinosternidae) supports the traditional classification of the group.

A goal of modern taxonomy is to develop classifications that reflect current phylogenetic relationships and are as stable as possible given the inherent uncertainties in much of the tree of life. Here, we provide an in-depth phylogenetic analysis, based on 14 nuclear loci comprising 10,305 base pairs of aligned sequence data from all but two species of the turtle family Kinosternidae, to determine whether recent proposed changes to the group's classification are justified and necessary. We conclude that those proposed changes were based on (1) mtDNA gene tree anomalies, (2) preliminary analyses that do not fully capture the breadth of geographic variation necessary to motivate taxonomic changes, and (3) changes in rank that are not motivated by non-monophyletic groups. Our recommendation, for this and other similar cases, is that taxonomic changes be made only when phylogenetic results that are statistically well-supported and corroborated by multiple independent lines of genetic evidence indicate that non-monophyletic groups are currently recognized and need to be corrected. We hope that other members of the phylogenetics community will join us in proposing taxonomic changes only when the strongest phylogenetic data demand such changes, and in so doing that we can move toward stable, phylogenetically informed classifications of lasting value.