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Coalescent-based delimitation outperforms distance-based methods for delineating less divergent species: the case of Kurixalus odontotarsus species group.

ABSTRACT: Few empirical studies have compared coalescent-based methods to distance-based methods for delimitation of less divergent species. In this study, we used two coalescent-based (BFD and BPP) and two distance-based barcoding (ABGD and jMOTU) methods to delimit closely related species in the Kurixalus odontotarsus species group. Phylogenetic analyses revealed that the K. odontotarsus species group comprises 11 distinct maternal clades with strong support values. Based on the genetic and morphological evidences, we consider that species diversity in the K. odontotarsus species group was underestimated and the 11 clades represent 11 species, of which six are unnamed. The coalescent-based delimitations decisively supported the scenario of 11-species corresponding to the 11 clades. However, the distance-based ABGD only obtained 3-6 candidate species, which is not consistent with morphological evidence. These results indicate that BFD and BPP are more conservative than ABGD to false negatives (lumping). Method of fixed threshold (jMOTU) may obtain a resolution similar to that inferred by BFD and BPP, but it severely relies on subjective choice of the threshold and lacks statistical support. We consider that coalescent-based BFD and BPP approaches outperform distance-based methods for delineation of less divergent species.

SUBMITTER: Yu G

PROVIDER: S-EPMC5700917 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Coalescent-based delimitation outperforms distance-based methods for delineating less divergent species: the case of Kurixalus odontotarsus species group.

Yu Guohua G Rao Dingqi D Matsui Masafumi M Yang Junxing J

Scientific reports 20171123 1

Few empirical studies have compared coalescent-based methods to distance-based methods for delimitation of less divergent species. In this study, we used two coalescent-based (BFD and BPP) and two distance-based barcoding (ABGD and jMOTU) methods to delimit closely related species in the Kurixalus odontotarsus species group. Phylogenetic analyses revealed that the K. odontotarsus species group comprises 11 distinct maternal clades with strong support values. Based on the genetic and morphologica ...[more]

PMID: 29170403

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Project description:BackgroundFor the last 25 years species delimitation in prokaryotes (Archaea and Bacteria) was to a large extent based on DNA-DNA hybridization (DDH), a tedious lab procedure designed in the early 1970s that served its purpose astonishingly well in the absence of deciphered genome sequences. With the rapid progress in genome sequencing time has come to directly use the now available and easy to generate genome sequences for delimitation of species. GBDP (Genome Blast Distance Phylogeny) infers genome-to-genome distances between pairs of entirely or partially sequenced genomes, a digital, highly reliable estimator for the relatedness of genomes. Its application as an in-silico replacement for DDH was recently introduced. The main challenge in the implementation of such an application is to produce digital DDH values that must mimic the wet-lab DDH values as close as possible to ensure consistency in the Prokaryotic species concept.ResultsCorrelation and regression analyses were used to determine the best-performing methods and the most influential parameters. GBDP was further enriched with a set of new features such as confidence intervals for intergenomic distances obtained via resampling or via the statistical models for DDH prediction and an additional family of distance functions. As in previous analyses, GBDP obtained the highest agreement with wet-lab DDH among all tested methods, but improved models led to a further increase in the accuracy of DDH prediction. Confidence intervals yielded stable results when inferred from the statistical models, whereas those obtained via resampling showed marked differences between the underlying distance functions.ConclusionsDespite the high accuracy of GBDP-based DDH prediction, inferences from limited empirical data are always associated with a certain degree of uncertainty. It is thus crucial to enrich in-silico DDH replacements with confidence-interval estimation, enabling the user to statistically evaluate the outcomes. Such methodological advancements, easily accessible through the web service at http://ggdc.dsmz.de, are crucial steps towards a consistent and truly genome sequence-based classification of microorganisms.

Project description:A statistical framework of model comparison and model validation is essential to resolving the debates over concatenation and coalescent models in phylogenomic data analysis. A set of statistical tests are here applied and developed to evaluate and compare the adequacy of substitution, concatenation, and multispecies coalescent (MSC) models across 47 phylogenomic data sets collected across tree of life. Tests for substitution models and the concatenation assumption of topologically congruent gene trees suggest that a poor fit of substitution models, rejected by 44% of loci, and concatenation models, rejected by 38% of loci, is widespread. Logistic regression shows that the proportions of GC content and informative sites are both negatively correlated with the fit of substitution models across loci. Moreover, a substantial violation of the concatenation assumption of congruent gene trees is consistently observed across six major groups (birds, mammals, fish, insects, reptiles, and others, including other invertebrates). In contrast, among those loci adequately described by a given substitution model, the proportion of loci rejecting the MSC model is 11%, significantly lower than those rejecting the substitution and concatenation models. Although conducted on reduced data sets due to computational constraints, Bayesian model validation and comparison both strongly favor the MSC over concatenation across all data sets; the concatenation assumption of congruent gene trees rarely holds for phylogenomic data sets with more than 10 loci. Thus, for large phylogenomic data sets, model comparisons are expected to consistently and more strongly favor the coalescent model over the concatenation model. We also found that loci rejecting the MSC have little effect on species tree estimation. Our study reveals the value of model validation and comparison in phylogenomic data analysis, as well as the need for further improvements of multilocus models and computational tools for phylogenetic inference. [Bayes factor; Bayesian model validation; coalescent prior; congruent gene trees; independent prior; Metazoa; posterior predictive simulation.].

Project description:BACKGROUND: Species are considered the fundamental unit in many ecological and evolutionary analyses, yet accurate, complete, accessible taxonomic frameworks with which to identify them are often unavailable to researchers. In such cases DNA sequence-based species delimitation has been proposed as a means of estimating species boundaries for further analysis. Several methods have been proposed to accomplish this. Here we present a Bayesian implementation of an evolutionary model-based method, the general mixed Yule-coalescent model (GMYC). Our implementation integrates over the parameters of the model and uncertainty in phylogenetic relationships using the output of widely available phylogenetic models and Markov-Chain Monte Carlo (MCMC) simulation in order to produce marginal probabilities of species identities. RESULTS: We conducted simulations testing the effects of species evolutionary history, levels of intraspecific sampling and number of nucleotides sequenced. We also re-analyze the dataset used to introduce the original GMYC model. We found that the model results are improved with addition of DNA sequence and increased sampling, although these improvements have limits. The most important factor in the success of the model is the underlying phylogenetic history of the species under consideration. Recent and rapid divergences result in higher amounts of uncertainty in the model and eventually cause the model to fail to accurately assess uncertainty in species limits. CONCLUSION: Our results suggest that the GMYC model can be useful under a wide variety of circumstances, particularly in cases where divergences are deeper, or taxon sampling is incomplete, as in many studies of ecological communities, but that, in accordance with expectations from coalescent theory, rapid, recent radiations may yield inaccurate results. Our implementation differs from existing ones in two ways: it allows for the accounting for important sources of uncertainty in the model (phylogenetic and in parameters specific to the model) and in the specification of informative prior distributions that can increase the precision of the model. We have incorporated this model into a user-friendly R package available on the authors' websites.

Dataset Information

Coalescent-based delimitation outperforms distance-based methods for delineating less divergent species: the case of Kurixalus odontotarsus species group.

Publications

Coalescent-based delimitation outperforms distance-based methods for delineating less divergent species: the case of Kurixalus odontotarsus species group.

Similar Datasets

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