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  • Comparison between p‐distance and single‐locus species delimitation models for delineating reproductively tested strains of pennate diatoms (Bacillariophyceae) using cox 1, rbcL and ITS
Title: Comparison between p‐distance and single‐locus species delimitation models for delineating reproductively tested strains of pennate diatoms (Bacillariophyceae) using cox 1, rbcL and ITS
Abstract Several automated molecular methods have emerged for distinguishing eukaryote species based on DNA sequence data. However, there are knowledge gaps around which of these single‐locus methods is more accurate for the identification of microalgal species, such as the highly diverse and ecologically relevant diatoms. We applied genetic divergence, Automatic Barcode Gap Discovery for primary species delimitation (ABGD), Assemble Species by Automatic Partitioning (ASAP), Statistical Parsimony Network Analysis (SPNA), Generalized Mixed Yule Coalescent (GMYC) and Poisson Tree Processes (PTP) using partialcox1,rbcL,5.8S + ITS2,ITS1 + 5.8S + ITS2 markers to delineate species and compare to published polyphasic identification data (morphological features, phylogeny and sexual reproductive isolation) to test the resolution of these methods. ASAP, ABGD, SPNA and PTP models resolved species ofEunotia,Seminavis, Nitzschia, SellaphoraandPseudo‐nitzschiacorresponding to previous polyphasic identification, including reproductive isolation studies. In most cases, these models identified diatom species in similar ways, regardless of sequence fragment length. GMYC model presented smallest number of results that agreed with previous published identification. Following the recommendations for proper use of each model presented in the present study, these models can be useful tools to identify cryptic or closely related species of diatoms, even when the datasets have relatively few sequences.  more » « less
Award ID(s):
2015674
PAR ID:
10493908
Author(s) / Creator(s):
; ;
Publisher / Repository:
Wiley
Date Published:
Journal Name:
Journal of Eukaryotic Microbiology
Volume:
70
Issue:
5
ISSN:
1066-5234
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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