Dataset Information

A general species delimitation method with applications to phylogenetic placements.

ABSTRACT: MOTIVATION: Sequence-based methods to delimit species are central to DNA taxonomy, microbial community surveys and DNA metabarcoding studies. Current approaches either rely on simple sequence similarity thresholds (OTU-picking) or on complex and compute-intensive evolutionary models. The OTU-picking methods scale well on large datasets, but the results are highly sensitive to the similarity threshold. Coalescent-based species delimitation approaches often rely on Bayesian statistics and Markov Chain Monte Carlo sampling, and can therefore only be applied to small datasets. RESULTS: We introduce the Poisson tree processes (PTP) model to infer putative species boundaries on a given phylogenetic input tree. We also integrate PTP with our evolutionary placement algorithm (EPA-PTP) to count the number of species in phylogenetic placements. We compare our approaches with popular OTU-picking methods and the General Mixed Yule Coalescent (GMYC) model. For de novo species delimitation, the stand-alone PTP model generally outperforms GYMC as well as OTU-picking methods when evolutionary distances between species are small. PTP neither requires an ultrametric input tree nor a sequence similarity threshold as input. In the open reference species delimitation approach, EPA-PTP yields more accurate results than de novo species delimitation methods. Finally, EPA-PTP scales on large datasets because it relies on the parallel implementations of the EPA and RAxML, thereby allowing to delimit species in high-throughput sequencing data. AVAILABILITY AND IMPLEMENTATION: The code is freely available at www.exelixis-lab.org/software.html. .

SUBMITTER: Zhang J

PROVIDER: S-EPMC3810850 | biostudies-other | 2013 Nov

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

A general species delimitation method with applications to phylogenetic placements.

Zhang Jiajie J Kapli Paschalia P Pavlidis Pavlos P Stamatakis Alexandros A

Bioinformatics (Oxford, England) 20130829 22

<h4>Motivation</h4>Sequence-based methods to delimit species are central to DNA taxonomy, microbial community surveys and DNA metabarcoding studies. Current approaches either rely on simple sequence similarity thresholds (OTU-picking) or on complex and compute-intensive evolutionary models. The OTU-picking methods scale well on large datasets, but the results are highly sensitive to the similarity threshold. Coalescent-based species delimitation approaches often rely on Bayesian statistics and M ...[more]

PMID: 23990417

Similar Datasets

Project description:Molecular genetic approaches are playing an increasing role in conservation science by identifying biodiversity that may not be evident by morphology-based taxonomy and systematics. So-called cryptic species are particularly prevalent in freshwater environments, where isolation of dispersal-limited species, such as crayfishes, within dendritic river networks often gives rise to high intra- and inter-specific genetic divergence. We apply here a multi-gene molecular approach to investigate relationships among extant species of the crayfish genus Pacifastacus, representing the first comprehensive phylogenetic study of this taxonomic group. Importantly, Pacifastacus includes both the widely invasive signal crayfish Pacifastacus leniusculus, as well as several species of conservation concern like the Shasta crayfish Pacifastacus fortis. Our analysis used 83 individuals sampled across the four extant Pacifastacus species (omitting the extinct Pacifastacus nigrescens), representing the known taxonomic diversity and geographic distributions within this genus as comprehensively as possible. We reconstructed phylogenetic trees from mitochondrial (16S, COI) and nuclear genes (GAPDH), both separately and using a combined or concatenated dataset, and performed several species delimitation analyses (PTP, ABGD, GMYC) on the COI phylogeny to propose Primary Species Hypotheses (PSHs) within the genus. All phylogenies recovered the genus Pacifastacus as monophyletic, within which we identified a range of six to 21 PSHs; more abundant PSHs delimitations from GMYC and ABGD were always nested within PSHs delimited by the more conservative PTP method. Pacifastacus leniusculus included the majority of PSHs and was not monophyletic relative to the other Pacifastacus species considered. Several of these highly distinct P. leniusculus PSHs likely require urgent conservation attention. Our results identify research needs and conservation priorities for Pacifastacus crayfishes in western North America, and may inform better understanding and management of P. leniusculus in regions where it is invasive, such as Europe and Japan.

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

A general species delimitation method with applications to phylogenetic placements.

Publications

A general species delimitation method with applications to phylogenetic placements.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets