DELIMITING SPECIES USING MULTILOCUS DATA: DIAGNOSING CRYPTIC DIVERSITY IN THE SOUTHERN CAVEFISH,<i>TYPHLICHTHYS SUBTERRANEUS</i>(TELEOSTEI: AMBLYOPSIDAE)

Niemiller, Matthew L.; Near, Thomas J.; Fitzpatrick, Benjamin M.

doi:10.1111/j.1558-5646.2011.01480.x

Cited by 152 publications

(176 citation statements)

References 93 publications

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“…As shown by Hedin et al (2015), groups characterized by strong population structure present some of the most challenging systems for delimitation, especially when inferences are limited to genetic data. In such cases, methods for delineating formal groups (that is, species, conservation units) may 'over-split' major genetic groups, and factors such as sample size can play an important role in the inference of whether such groups are recognized or not (see Niemiller et al, 2012 for an empirical example). As demonstrated by Chiucchi and Gibbs (2010), S. catenatus exhibits characteristics such as strong population structure and small population sizes that may make these snakes susceptible to potential 'over-splitting' in lineage delimitation studies.…”

Section: Identifying Significant Phylogenetic Lineagesmentioning

confidence: 99%

Origin of a cryptic lineage in a threatened reptile through isolation and historical hybridization

2016

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Identifying phylogenetically distinct lineages and understanding the evolutionary processes by which they have arisen are important goals of phylogeography. This information can also help define conservation units in endangered species. Such analyses are being transformed by the availability of genomic-scale data sets and novel analytical approaches for statistically comparing different historical scenarios as causes of phylogeographic patterns. Here, we use genomic-scale restriction-site-associated DNA sequencing (RADseq) data to test for distinct lineages in the endangered Eastern Massasauga Rattlesnake (Sistrurus catenatus). We then use coalescent-based modeling techniques to identify the evolutionary mechanisms responsible for the origin of the lineages in this species. We find equivocal evidence for distinct phylogenetic lineages within S. catenatus east of the Mississippi River, but strong support for a previously unrecognized lineage on the western edge of the range of this snake, represented by populations from Iowa, USA. Snakes from these populations show patterns of genetic admixture with a nearby non-threatened sister species (Sistrurus tergeminus). Tests of historical demographic models support the hypothesis that the genetic distinctiveness of Iowa snakes is due to a combination of isolation and historical introgression between S. catenatus and S. tergeminus. Our work provides an example of how model-based analysis of genomic-scale data can help identify conservation units in rare species.

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Section: Identifying Significant Phylogenetic Lineagesmentioning

confidence: 99%

Origin of a cryptic lineage in a threatened reptile through isolation and historical hybridization

2016

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“…Camargo et al, 2012;Harrington and Near, 2012;Niemiller et al, 2012), but loci which are likely to be under active selection pressure may produce misleading signals of lineage divergence. Third, separate gene trees need to be constructed for each locus.…”

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confidence: 99%

Phylogenetic Pattern, Evolutionary Processes and Species Delimitation in the Genus Echinococcus

Lymbery

2017

Advances in Parasitology

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“…The second data set we analyze consists of 22 individuals of a cavefish (Typhlichthys subterraneus) sequenced at five nuclear gene loci (with one allele for each individual at each locus), published by Niemiller et al (2012). T. subterraneus is a teleost fish widely distributed in Eastern North America.…”

Section: The Cavefish Data Setmentioning

confidence: 99%

“…Genetic data thus constitute a valuable source of information for species delimitation in such organisms. Niemiller et al (2012) sequenced multiple loci to delimit species in T. subterraneus. They used the method of O'Meara (2010) to assign individuals to populations/species and then *BEAST (Heled and Drummond 2010) to infer the species tree.…”

Section: The Cavefish Data Setmentioning

confidence: 99%

Improved Reversible Jump Algorithms for Bayesian Species Delimitation

2013

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Several computational methods have recently been proposed for delimiting species using multilocus sequence data. Among them, the Bayesian method of Yang and Rannala uses the multispecies coalescent model in the likelihood framework to calculate the posterior probabilities for the different species-delimitation models. It has a sound statistical basis and is found to have nice statistical properties in simulation studies, such as low error rates of undersplitting and oversplitting. However, the method suffers from poor mixing of the reversible-jump Markov chain Monte Carlo (rjMCMC) algorithms. Here, we describe several modifications to the algorithms. We propose a flexible prior that allows the user to specify the probability that each node on the guide tree represents a true speciation event. We also introduce modifications to the rjMCMC algorithms that remove the constraint on the new species divergence time when splitting and alter the gene trees to remove incompatibilities. The new algorithms are found to improve mixing of the Markov chain for both simulated and empirical data sets. SPECIES delimitation using genetic data has become a popular objective in recent years (Knowles and Carstens 2007). Several likelihood and Bayesian methods have been developed in the coalescent framework that accounts for lineage sorting and species-tree vs. gene-tree conflicts but they vary in the adequacy of their treatment of statistical uncertainty. The methods of O'Meara (2010) and Ence and Carstens (2011) attempt to infer both species trees and delimitations but assume that gene trees are known without error. O'Meara (2010) also uses several heuristics to avoid difficult numerical analyses-the statistical performance of his method is therefore not predictable from standard asymptotic theory. Most populations for which species delimitation will be applied will not be greatly differentiated and the gene trees will be very uncertain due to few mutations and a consequent lack of information in the sequence data. A recent Bayesian-delimitation method (Yang and Rannala 2010) averages over uncertainties in the gene trees and should perform better for such data. From a statistical perspective, species delimitation can be viewed as a model choice problem. Each possible delimitation corresponds to a distinct statistical model with parameters that are not strictly comparable. This is similar to the problem of phylogenetic inference in which parameters such as branch lengths have different interpretations in different topologies (see Yang 2006), but the delimitation problem is more complex because the number of parameters (model dimension) also changes across delimitations (Yang and Rannala 2010).The Bayesian method of Yang and Rannala (2010) uses reversible-jump Markov chain Monte Carlo (rjMCMC) to calculate the posterior probabilities of species delimitations, allowing for changes of dimension between models. The algorithms involve a split step (which increases the number of species by one) and a join step (which decreases th...

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DELIMITING SPECIES USING MULTILOCUS DATA: DIAGNOSING CRYPTIC DIVERSITY IN THE SOUTHERN CAVEFISH,TYPHLICHTHYS SUBTERRANEUS(TELEOSTEI: AMBLYOPSIDAE)

Cited by 152 publications

References 93 publications

Origin of a cryptic lineage in a threatened reptile through isolation and historical hybridization

Origin of a cryptic lineage in a threatened reptile through isolation and historical hybridization

Phylogenetic Pattern, Evolutionary Processes and Species Delimitation in the Genus Echinococcus

Improved Reversible Jump Algorithms for Bayesian Species Delimitation

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