DISSECT: an assignment-free Bayesian discovery method for species delimitation under the multispecies coalescent

Jones, Graham; Aydın, Zeynep Gökçe Gayretli; Oxelman, Bengt

doi:10.1093/bioinformatics/btu770

Cited by 191 publications

(171 citation statements)

References 34 publications

(28 reference statements)

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“…These methods address different research questions (Casiraghi et al , 2010); thus, the user needs to assess several factors before choosing the most appropriate method for a particular study. The “species-tree” approaches rely on multiple genetic loci (Jones et al , 2015; Yang and Rannala, 2014) and account for potential species-tree/gene-tree incongruence (Maddison, 1997). Such methods are the most appropriate when the goal is to perform taxonomic revisions.…”

Section: Introductionmentioning

confidence: 99%

Multi-rate Poisson tree processes for single-locus species delimitation under maximum likelihood and Markov chain Monte Carlo

et al. 2017

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MotivationIn recent years, molecular species delimitation has become a routine approach for quantifying and classifying biodiversity. Barcoding methods are of particular importance in large-scale surveys as they promote fast species discovery and biodiversity estimates. Among those, distance-based methods are the most common choice as they scale well with large datasets; however, they are sensitive to similarity threshold parameters and they ignore evolutionary relationships. The recently introduced “Poisson Tree Processes” (PTP) method is a phylogeny-aware approach that does not rely on such thresholds. Yet, two weaknesses of PTP impact its accuracy and practicality when applied to large datasets; it does not account for divergent intraspecific variation and is slow for a large number of sequences.ResultsWe introduce the multi-rate PTP (mPTP), an improved method that alleviates the theoretical and technical shortcomings of PTP. It incorporates different levels of intraspecific genetic diversity deriving from differences in either the evolutionary history or sampling of each species. Results on empirical data suggest that mPTP is superior to PTP and popular distance-based methods as it, consistently yields more accurate delimitations with respect to the taxonomy (i.e., identifies more taxonomic species, infers species numbers closer to the taxonomy). Moreover, mPTP does not require any similarity threshold as input. The novel dynamic programming algorithm attains a speedup of at least five orders of magnitude compared to PTP, allowing it to delimit species in large (meta-) barcoding data. In addition, Markov Chain Monte Carlo sampling provides a comprehensive evaluation of the inferred delimitation in just a few seconds for millions of steps, independently of tree size.Availability and ImplementationmPTP is implemented in C and is available for download at http://github.com/Pas-Kapli/mptp under the GNU Affero 3 license. A web-service is available at http://mptp.h-its.org.Supplementary information Supplementary data are available at Bioinformatics online.

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Section: Introductionmentioning

confidence: 99%

Multi-rate Poisson tree processes for single-locus species delimitation under maximum likelihood and Markov chain Monte Carlo

et al. 2017

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“…The difference was particularly apparent in the time to 'burn-in' in cases where there was little incomplete lineage sorting and many loci in Test-I. Although these are the cases where signal is strongest, DISSECT can take a very long time to converge, as reported in Jones et al (2014) for the case of 27 loci. With regard to the Test-II data, Giarla and Esselstyn Giarla and Esselstyn (2015) report that 'we observed little sign of convergence in analyses of more than 50 loci in *BEAST, even after billions of MCMC generations.'…”

Section: Discussionmentioning

confidence: 97%

“…However, in many empirical data sets the difficulties due to coalescent variation will be compounded with large amounts of mutational variation. The simulations used in Jones et al (2014) were much harder in terms of the mutational variation: the sequences were 500 bp, there was only one sequence per individual, and the shortest branch lengths were 0.001, so that the expected number of substitutions along the shortest branches is only 0.5 instead of 8. The results of that paper may be a better guide to to the accuracy of the approach on many empirical data sets.…”

Section: Discussionmentioning

confidence: 99%

“…It accounts for incomplete lineage sorting, a ubiquitous source of discord between gene trees. More recently, it has been used for species delimitation, in BPP (Yang and Rannala 2010;Rannala and Yang 2013;Yang and Rannala 2014) and DISSECT (Jones et al 2014). More details and discussion of alternative approaches can be found in Jones et al (2014), Olave et al (2014), and Zhang et al (2014).…”

Section: Previous Workmentioning

confidence: 99%

“…The first 1 million discarded as burnin. Samples were taken every 1000 generations, so there were 4000, 6000, or 9000 SMC-trees on which to base the species delimitations using SpeciesDelimitationAnalyser (Jones et al 2014).…”

Section: Tests On Simulated Datamentioning

confidence: 99%

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Algorithmic improvements to species delimitation and phylogeny estimation under the multispecies coalescent

2016

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The focus of this article is a Bayesian method for inferring both species delimitations and species trees under the multispecies coalescent model using molecular sequences from multiple loci. The species delimitation requires no a priori assignment of individuals to species, and no guide tree. The method is implemented in a package called STACEY for BEAST2, and is a extension of the author's DISSECT package. Here we demonstrate considerable efficiency improvements by using three new operators for sampling from the posterior using the Markov chain Monte Carlo algorithm, and by using a model for the population size parameters along the branches of the species tree which allows these parameters to be integrated out. The correctness of the moves is demonstrated by tests of the implementation. The practice of using a pipeline approach to species delimitation under the multispecies coalescent, has been shown to have major problems on simulated data (Olave et al. in Syst Biol 63:263-271. doi: 10.1093/sysbio/syt106 , 2014). The same simulated data set is used to demonstrate the accuracy and improved convergence of the present method. We also compare performance with *BEAST for a fixed delimitation analysis on a large data set, and again show improved convergence.

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Coalescent‐based species delimitation in North American pinyon pines using low‐copy nuclear genes and plastomes

Montes

Peláez

Moreno‐Letelier

et al. 2022

American J of Botany

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Premise: Accurate species delimitation is essential for evolutionary biology, conservation, and biodiversity management. We studied species delimitation in North American pinyon pines, Pinus subsection Cembroides, a natural group with high levels of incomplete lineage sorting. Methods: We used coalescent-based methods and multivariate analyses of low-copy number nuclear genes and nearly complete high-copy number plastomes generated with the Hyb-Seq method. The three coalescent-based species delimitation methods evaluated were the Generalized Mixed Yule Coalescent (GMYC), Poisson Tree Process (PTP), and Trinomial Distribution of Triplets (Tr2). We also measured admixture in populations with possible introgression. Results: Our results show inconsistencies among GMYC, PTP, and Tr2. The singlelocus based GMYC analysis of plastid DNA recovered a higher number of species (up to 24 entities, including singleton lineages and clusters) than PTP and the multilocus coalescent approach. The PTP analysis identified 10 species whereas Tr2 recovered 13, which agreed closely with taxonomic treatments. Conclusions: We found that PTP and GMYC identified species with low levels of ILS and high morphological divergence (P. maximartinezii, P. pinceana, and P. rzedowskii). However, GMYC method oversplit species by identification of more divergent samples as singletons. Moreover, both PTP and GMYC were incapable of identifying some species that are readily identified morphologically. We suggest that the divergence times between lineages within North American pinyon pines are so disparate that GMYC results are unreliable. Results of the Tr2 method coincided well with previous delimitations based on morphology, DNA, geography, and secondary chemistry.

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DISSECT: an assignment-free Bayesian discovery method for species delimitation under the multispecies coalescent

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 191 publications

References 34 publications

Multi-rate Poisson tree processes for single-locus species delimitation under maximum likelihood and Markov chain Monte Carlo

Multi-rate Poisson tree processes for single-locus species delimitation under maximum likelihood and Markov chain Monte Carlo

Algorithmic improvements to species delimitation and phylogeny estimation under the multispecies coalescent

Coalescent‐based species delimitation in North American pinyon pines using low‐copy nuclear genes and plastomes

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