Estimating the temporal and spatial extent of gene flow among sympatric lizard populations (genusSceloporus) in the southern Mexican highlands

Abstract

1Interspecific gene flow is pervasive throughout the tree of life. Although detecting 2 gene flow between populations has been facilitated by new analytical approaches, 3 determining the timing and geography of hybridization has remained difficult, 4 particularly for historical gene flow. A geographically explicit phylogenetic 5 approach is needed to determine the ancestral population overlap. In this study, 6 we performed population genetic analyses, species delimitation, simulations, and a 7 recently developed approach of species tree diffusion to infer the phylogeographic 8 history, timing and geographic extent of gene flow in lizards of the Sceloporus 9 spinosus group. The two species in this group, S. spinosus and S. horridus, are 10 distributed in eastern and western portions of Mexico, respectively, but 11 populations of these species are sympatric in the southern Mexican highlands. We 12 generated data consisting of three mitochondrial genes and eight nuclear loci for 13 148 and 68 individuals, respectively. We delimited six lineages in this group, but 14 found strong evidence of mito-nuclear discordance in sympatric populations of S. 15 spinosus and S. horridus owing to mitochondrial introgression. We used 16 coalescent simulations to differentiate ancestral gene flow from secondary contact, 17 but found mixed support for these two models. Bayesian phylogeography 18 indicated more than 60% range overlap between ancestral S. spinosus and S. 19 horridus populations since the time of their divergence. Isolation-migration 20 analyses, however, revealed near-zero levels of gene flow between these ancestral 21 populations. Interpreting results from both simulations and empirical data 22 indicate that despite a long history of sympatry among these two species, gene 23 flow in this group has only recently occurred.24

Genetic structuring and secondary contact in the white‐chestedAmaziliahummingbird species complex

“…Under scenario 5, the basal split (t2) was dated to 23 200 kya and the merger of lineages due to gene flow was dated at 3640 kya (Table 6). However, microsatellite data tends to underestimate timing of events, specifically ancient events (Cornuet et al ), and so, these results should be treated with caution.…”

“…Samples from 95 hummingbirds were genotyped at ten polymorphic, unlinked, nuclear microsatellite (nSSR) loci designed for Amazilia cyanocephala (A1‐3‐5, A1‐4‐1, A2‐13‐8, A1‐10‐9 and A2‐5‐3; Molecular Ecology Resources Primer Development Consortium et al 2013), Campylopterus curvipennis (Cacu13‐7; Molecular Ecology Resources Primer Development Consortium et al ) and Selasphorus platycercus (HumB1, HumB2, HumB3, HumB9; Oyler‐McCance et al 2011). Amplification, PCR conditions and fragment sizing of microsatellite loci are fully described elsewhere (Molecular Ecology Resources Primer Development Consortium et al , 2013, Oyler‐McCance et al 2011). For each PCR we used control samples and for some of the samples we conducted repeats to check for errors or allelic dropouts.…”

“…These samples were not included in the analyses. Five tissue samples from UNAM collection included heart and liver tissue and preserved very well in the buffer solution since collection in . Fluorescently labelled PCR fragments were read in a 310 or 3730 automated DNA sequencer (Applied Biosystems, Foster City, CA, USA) at the Inst.…”

“…Expected ( He ) and observed heterozygosity ( Ho ) and mean number of alleles ( Na ) per locus were calculated using GENEPOP and Arlequin ver. 3.5 (Excoffier and Lischer ). To investigate population genetic structure, we calculated pairwise comparisons of F ST values between populations based on the infinite alleles mutation model (IAM) and R ST based on the stepwise mutation model (SMM) using Arlequin with 10 000 permutations.…”

Phylogeographic model selection leads to insight into the evolutionary history of four-eyed frogs

“…Simulation-based techniques are also commonly applied to empirical systems, either to test competing hypotheses such as introgression and lineage sorting (e.g., refs. [12][13][14] or to test phylogeographic hypotheses against a null model (e.g., refs. [15][16][17].…”