Unguided Species Delimitation Using DNA Sequence Data from Multiple Loci

By Ziheng Yang, Bruce Rannala. Molecular biology and evolution, 2014

504 citations recorded by the source corpus.

A method was developed for simultaneous Bayesian inference of species delimitation and species phylogeny using the multispecies coalescent model. The method eliminates the need for a user-specified guide tree in species delimitation and incorporates phylogenetic uncertainty in a Bayesian framework. The nearest-neighbor interchange algorithm was adapted to propose changes to the species tree, with the gene trees for multiple loci altered in the proposal to avoid conflicts with the newly proposed species tree. We also modify our previous scheme for specifying priors for species delimitation models to construct joint priors for models of species delimitation and species phylogeny. As in our earlier method, the modified algorithm integrates over gene trees, taking account of the uncertainty of gene tree topology and branch lengths given the sequence data. We conducted a simulation study to examine the statistical properties of the method using six populations (two sequences each) and a true number of three species, with values of divergence times and ancestral population sizes that are realistic for recently diverged species. The results suggest that the method tends to be conservative with high posterior probabilities being a confident indicator of species status. Simulation results also indicate that the power of the method to delimit species increases with an increase of the divergence times in the species tree, and with an increased number of gene loci. Reanalyses of two data sets of cavefish and coast horned lizards suggest considerable phylogenetic uncertainty even though the data are informative about species delimitation. We discuss the impact of the prior on models of species delimitation and species phylogeny and of the prior on population size parameters (θ) on Bayesian species delimitation.

Subfields: Ecological Modeling, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/58a6245e097e6372d7796522512856791c91edb9

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Citations in the corpus

Multispecies coalescent delimits structure, not species (2017, methodology): “Specifically, we simulate genetic data under a protracted speciation model (21), such that the degree of genetic structure accumulating among lineages differs (7), depending on the duration of speciation (21), and investigate the accuracy of inferences from the popular model-based species delimitati”
Mammals of Italy: an annotated checklist (2019, background): “…species (Fujisawa and Barraclough, 2013; Zhang et al., 2013); (3) use of Bayesian models to understand genealogical processes to identify species (Yang and Rannala, 2014); 4) presence of chromosomal differences, which may be directly involved in the reproductive isolation between populations…”
Species Tree Inference with BPP Using Genomic Sequences and the Multispecies Coalescent (2018, background): “Note that the variance of the estimate of the posterior model probability based on an MCMC sample of size N is P(1 P)/(NE), where P is the true posterior model probability, E is the efficiency of the MCMC sample, and NE is the effective sample size (ESS) (see, e.g., Yang 2014, p. 214).”
The art and science of species delimitation (2015, unknown): “With a new version of BPP now available that jointly infers the phylogeny and delimitation (Yang and Rannala, 2014) one of the major concerns about Bayesian delimitation -- the effect of errors in the guide tree (Leaché and Fujita, 2010; Olave et al.”
The BPP program for species tree estimation and species delimitation (2015, methodology): “Joint species delimitation and species-tree inference or unguided species delimitation (Yang and Rannala, 2014).”
ASAP: assemble species by automatic partitioning (2020, methodology): “In this category, the most popular methods are SpedeSTEM (Ence & Carstens, 2011), BPP (Yang & Rannala, 2014) and BFD (Leaché et al., 2014), reviewed (with other methods) in several articles (Camargo & Sites, 2013; Carstens et al., 2013; Fujita et al., 2012; Leavitt et al., 2015; Rannala, 2015).”
Genetic Diversity and Conservation Units: Dealing With the Species-Population Continuum in the Age of Genomics (2018, background): “merits of these alternatives, it is clear that the technical and analytical tools of population genomics can now robustly identify both components of intraspecific diversity (Funk et al., 2012; Hoban et al., 2013; Whitlock, 2014; Yang and Rannala, 2014).”