Literature DB >> 28281309

Bayesian species identification under the multispecies coalescent provides significant improvements to DNA barcoding analyses.

Ziheng Yang1,2, Bruce Rannala2,3.   

Abstract

DNA barcoding methods use a single locus (usually the mitochondrial COI gene) to assign unidentified specimens to known species in a library based on a genetic distance threshold that distinguishes between-species divergence from within-species diversity. Recently developed species delimitation methods based on the multispecies coalescent (MSC) model offer an alternative approach to individual assignment using either single-locus or multiloci sequence data. Here, we use simulations to demonstrate three features of an MSC method implemented in the program bpp. First, we show that with one locus, MSC can accurately assign individuals to species without the need for arbitrarily determined distance thresholds (as required for barcoding methods). We provide an example in which no single threshold or barcoding gap exists that can be used to assign all specimens without incurring high error rates. Second, we show that bpp can identify cryptic species that may be misidentified as a single species within the library, potentially improving the accuracy of barcoding libraries. Third, we show that taxon rarity does not present any particular problems for species assignments using bpp and that accurate assignments can be achieved even when only one or a few loci are available. Thus, concerns that have been raised that MSC methods may have problems analysing rare taxa (singletons) are unfounded. Currently, barcoding methods enjoy a huge computational advantage over MSC methods and may be the only approach feasible for massively large data sets, but MSC methods may offer a more stringent test for species that are tentatively assigned by barcoding.
© 2017 John Wiley & Sons Ltd.

Entities:  

Keywords:  zzm321990bppzzm321990; DNA barcoding; coalescent; species delimitation; species identification

Mesh:

Year:  2017        PMID: 28281309     DOI: 10.1111/mec.14093

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


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