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opencc-zeroAug 2020View details →

Contrasting signatures of introgression in North American box turtle (Terrapene spp.) contact zones

Hybridization occurs differentially across the genome in a balancing act between selection and migration. With the unprecedented resolution of contemporary sequencing technologies, selection and migration can now be effectively quantified such that researchers can identify genetic elements involved in introgression. Furthermore, genomic patterns can now be associated with ecologically relevant phenotypes, given availability of annotated reference genomes. We do so in North American box turtles (Terrapene) by deciphering how selection affects hybrid zones at the interface of species-boundaries and identifying genetic regions potentially under selection that may relate to thermal adaptations. Such genes may impact physiological pathways involved in temperature-dependent sex determination, immune system functioning, and hypoxia tolerance. We contrasted these patterns across inter- and intra-specific hybrid zones that differ temporally and biogeographically. We demonstrate hybridization is broadly apparent in Terrapene, but with observed genomic cline patterns corresponding to species boundaries at loci potentially associated with thermal adaptation. These loci display signatures of directional introgression within intra-specific boundaries, despite a genome-wide selective trend against intergrades. In contrast, outlier loci for inter-specific comparisons exhibited evidence of being under selection against hybrids. Importantly, adaptations coinciding with species-boundaries in Terrapene overlap with climatic boundaries and highlight the vulnerability of these terrestrial ectotherms to anthropogenic pressures.

opencc-zeroDec 2020View details →

The choices we make and the impacts they have: Machine learning and species delimitation in North American box turtles (Terrapene spp.)

Model-based approaches that attempt to delimit species are hampered by computational limitations as well as the unfortunate tendency by users to disregard algorithmic assumptions. Alternatives are clearly needed, and machine-learning (M-L) is attractive in this regard as it functions without the need to explicitly define a species concept. Unfortunately, its performance will vary according to which (of several) bioinformatic parameters are invoked. Herein, we gauge the effectiveness of M-L-based species-delimitation algorithms by parsing 64 variably-filtered versions of a ddRAD-derived SNP dataset involving North American box turtles (Terrapene spp.). Our filtering strategies included: (A) minor allele frequencies (MAF) of 5%, 3%, 1%, and 0% (=none), and (B) maximum missing data per-individual/per-population at 25%, 50%, 75%, and 100% (=none). We found that species-delimitation via unsupervised M-L impacted the signal-to-noise ratio in our data, as well as the discordance among resolved clades. The latter may also reflect biogeographic history, gene flow, incomplete lineage sorting, or combinations thereof (as corroborated from previously observed patterns of differential introgression). Our results substantiate M-L as a viable species-delimitation method, but also demonstrate how commonly observed patterns of phylogenetic discord can seriously impact M-L-classification.

FIG. 4 in Nest-Site Fidelity and Sex-Biased Dispersal Affect Spatial Genetic Structure of Eastern Box Turtles (Terrapene carolina carolina) at Their Northern Range Edge

FIG. 4. Analysis of global structure along the river corridor from the first principal component of the sPCA represented by (A) interpolation of lagged principal scores showing genetic clines and (B) colors indicating individual scores. Coordinates have been deliberately omitted to deter poachers.

FIG. 3 in Nest-Site Fidelity and Sex-Biased Dispersal Affect Spatial Genetic Structure of Eastern Box Turtles (Terrapene carolina carolina) at Their Northern Range Edge

FIG. 3. Bubble plot showing the results of two-dimensional local spatial autocorrelation analysis for all Eastern Box Turtles (n ¼ 165) sampled in northwestern Michigan. Circles represent individuals and the size of the circle is proportional to the P-values from permutation testing, with large circles representing individuals that are significantly more related to their five nearest neighbors than expected (P, 0.05) based on a random distribution of genotypes. Figure shows the distribution of five genetic ''hotspots'' in relation to known nesting sites (NS) across the study area. Some distantly sampled individuals are omitted for figure clarity.

FIG. 2 in Nest-Site Fidelity and Sex-Biased Dispersal Affect Spatial Genetic Structure of Eastern Box Turtles (Terrapene carolina carolina) at Their Northern Range Edge

FIG. 2. Spatial genetic autocorrelograms of genetic correlation coefficients (r) as a function of distance for Eastern Box Turtles in northwestern Michigan. Plots represent (A) all individuals (n ¼ 165), (B) females only (n ¼ 104), and (C) males only (n ¼ 51). Dashed lines are permuted 95% confidence intervals across all data, and error bars are bootstrapped 95% confidence intervals within each distance class. Tables below graphs represent data for each distance class including the number of pairwise comparisons (n), the correlation coefficients (r), and the P-values (p) associated with bootstrap tests of significance for positive spatial genetic autocorrelation.

FIG. 1 in Nest-Site Fidelity and Sex-Biased Dispersal Affect Spatial Genetic Structure of Eastern Box Turtles (Terrapene carolina carolina) at Their Northern Range Edge

FIG. 1. Scatterplot showing the matrix of pairwise genetic distances and matrix of pairwise geographic distances for box turtles sampled along the river corridor. Warmer colors within the kernel density indicate higher densities of points. The line (slope ¼ 1.074727e–05; R2 ¼ 0.002992) shows the correlation trend.

publicAug 2020View details →

Contrasting signatures of introgression in North American box turtle (Terrapene spp.) contact zones

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