Phylogeographic analysis of the cornsnake (Elaphe guttata) complex as inferred from maximum likelihood and Bayesian analyses

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Abstract

Most phylogeographic studies have used maximum likelihood or maximum parsimony to infer phylogeny and bootstrap analysis to evaluate support for trees. Recently, Bayesian methods using Marlov chain Monte Carlo to search tree space and simultaneously estimate tree support have become popular due to its fast search speed and ability to create a posterior distribution of parameters of interest. Here, I present a study that utilizes Bayesian methods to infer phylogenetic relationships of the cornsnake (Elaphe guttata) complex using cytochrome b sequences. Examination of the posterior probability distributions confirms the existence of three geographic lineages. Additionally, there is no support for the monophyly of the subspecies of E. guttata. Results suggest the three geographic lineages partially conform to the ranges of previously defined subspecies, although Shimodaira–Hasegawa tests suggest that subspecies-constrained trees produce significantly poorer likelihood estimates than the most likely trees reflecting the evolution of three geographic assemblages. Based on molecular support, these three geographic assemblages are recognized as species using evolutionary species criteria: E. guttata, Elaphe slowinskii, and Elaphe emoryi [phylogeographic, maximum likelihood, maximum parsimony, bootstrap, Bayesian, Markov chain Monte Carlo, cornsnake, Cytochrome b, geographic lineages, E. guttta, E. slowinskii, and E. emoryi].

Introduction

Phylogeographic studies of widely distributed reptile taxa have resulted in the detection of distinct lineages likely to represent species, identified geographical features that reduce gene flow between populations, and allowed the proposal of taxonomies that reflect evolutionary history (Burbrink, 2001; Burbrink et al., 2000; Leache and Reeder, 2002; Rodrı́guez-Robles, 1999; Rodrı́guez-Robles, 2000; Zamudio et al., 1997). A marked genetic break (reflected in phylogenetic history) has been identified for multiple species at the Mississippi and Apalachicola Rivers (Avise, 1996; Burbrink et al., 2000; Leache and Reeder, 2002; Mayden, 1988; Walker et al., 1998; Wiley and Mayden, 1985). These dispersal barriers may also limit genetic interchange for other unstudied taxa with similar distributions and habitat constraints.

The cornsnake (Elaphe guttata) is of particular interest here, as the range of this taxon is continuous across multiple aquatic barriers in the US, including the Mississippi River. It is predicted that a phylogeographic split at the Mississippi River should be noticeable if populations have existed on opposite sides of this River for a long time. Additionally, E. guttata is generally restricted to drier pine and grassland habitats and is often not found in mesic forests. Therefore, the flanking riparian forest along the Mississippi River should also strengthen this river barrier to cornsnake dispersal. As a result of these natural history observations, this makes the cornsnake an ideal candidate to determine if phylogeographic patterns reflect a split at the Mississippi River.

Found throughout the pine forests of the southeastern US and the prairie/semi-desert regions of the Southwest (Fig. 1), the complex of E. guttata is composed of five differently colored subspecies: E. guttata guttata, Elaphe guttata rosacea, Elaphe guttata emoryi, Elaphe guttata intermontanus, and Elaphe guttata meahllmorum (Schultz, 1996) (Fig. 1). The nominate form, E. g. guttata, occurs in the pine forests of the southeastern US and is distinguished by having an orange, reddish-brown, or gray ground color with 25–38 reddish-brown or orange dorsal blotches and lateral blotches bordered in black. This subspecies may have a black and white checker-board pattern or black ventral surface (Schultz, 1996). Similar in appearance to E. g. guttata, E. g. rosacea, of the Florida Keys, is smaller and displays a distinct reduction in dark pigment, and usually posses 35–50 dorsal blotches. The more robust western prarie/semi-desert US subspecies, E. g. emoryi, has a brown or gray ground color, with 27–73 brown, gray, or olive dorsal blotches and similarly colored lateral blotches (Schultz, 1996). The ventral surface may be checkered or spotted. Of questionable taxonomic status are E. g. intermontanus and E. g. meahllmorum. The range of E. g. intermontanus is disjunct from populations of E. g. emoryi and restricted to western Colorado and eastern Utah. This form is slightly smaller than E. g. emoryi (Schultz, 1996). Finally, E. g. meahllmorum, restricted to southern Texas and Mexico, is distinguished as having fewer than 44.5 blotches, whereas, E. g. emoryi usually displays greater than 44.5 blotches (Smith et al., 1994). If any of the subspecies of E. guttata represent distinct evolutionary lineages, then their histories may form distinct partitions in the phylogeny.

Phylogenetic estimates of population relationships of cornsnakes using DNA sequences from the mitochondrial gene cytochrome b were produced with maximum likelihood (ML) analyses. To determine support for these estimates, Bayesian analyses were employed. Typically, computer-intensive non-parametric bootstrap methods using maximum parsimony or ML models have been applied to estimate support for branches (Larget and Simon, 1999). Alternatively, several authors have used Bayesian inference to generate support for phylogenetic relationships (Huelsenbeck and Ronquist, 2001; Larget and Simon, 1999; Mau, 1996; Mau and Newton, 1997; Mau et al., 1999). Markov chain Monte Carlo (MCMC) with the Metropolis–Hastings algorithm was used to sample posterior probability space by these authors. This method has several advantages over traditional bootstrapping methods (Geyer, 1991; Huelsenbeck and Ronquist, 2001; Larget and Simon, 1999; Mau et al., 1999): prior beliefs about the behavior of individual parameters can be incorporated into the model before a search of parameter space, the determination of support for branches using MCMC accompanies tree estimation, and the production of each tree provides a sample for the posterior probability distribution. Finding a single tree is not the goal of Bayesian search, but rather the production of a summary of the parameters of interest (particularly tree topology) as described by their marginal posterior distribution. This is in contrast to estimating uncertainty using the bootstrapping methods of ML and MP, where an optimal tree must first be assembled, bootstrap samples generated from the data, and trees subsequently re-estimated from each bootstrap sample (Hillis and Bull, 1993; Mau et al., 1999). Using the Metropolois-coupled MCMC allows the user to run multiple chains simultaneously. Additionally, these chains can swap states which potentially minimizes the chance of any chain becoming stuck on local optima (Huelsenbeck and Ronquist, 2001). Consequently, these attractive features of Bayesian inference lend themselves to analyzing this molecular data set, which is composed of many closely related samples.

Section snippets

Data collection

Liver or shed skin was used as a source of mitochondrial DNA from 53 specimens of E. guttata and one specimen of each outgroup (Elaphe obsoleta and Elaphe vulpina). Tissues were obtained from across the range (Fig. 1) of E. guttata (Appendix A). Specimens were identified to subspecies by examination of bodies or by locality of capture within the range of a particular subspecies. Tissues were digested in 500 μl of STE (0.1 M NaCl, 0.05 M Tris–HCl, and 0.001 M EDTA pH 7.5) with 25–50 μl of Proteinase

Results

Sequences for all individuals ranged from 560 to 760 bp of the total 1117 bp of the cytochrome b gene for E. guttata. All sequences had an open reading frame with no internal stop codons and no gaps were detected. The amplified fragments likely originated from the mitochondria and were not pseudogenes due to the fact that sequences obtained from the cytochrome b section of the 13.5 kb mitochondrial amplification were identical to the 700+ bp amplifications.

MODELTEST (Posada and Crandall, 1998)

Discussion

Maximum likelihood produced phylogeographic estimates of E. guttata that revealed the presence of three large geographic assemblages: the eastern partition, central partition, and western partition. Support for the assemblages was derived from the posterior probability distribution obtained using Bayesian methods of searching by Metropolis-coupled MCMC without an a priori defined tree. Three separate searches of four million generations each produced a posterior probability distribution of

Acknowledgements

The paper is dedicated to the memory of Joe Slowinski and everyone who feels a void in their life after his passing. I thank J. McGuire and D. Pollock for use of their labs during the data collection stage of the research. The following individuals provided valuable comments on the manuscript: J. Boundy, T. Devitt, J. Faith, A. Leache, J. McGuire, and C. McZealand. I thank F. Sheldon and D. Dittman for use of samples in the Louisiana State University Museum of Natural Science Collection of

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