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DNA barcoding evaluation and implications for phylogenetic relationships in Lauraceae from China

First Author: Liu ZF; Ci XQ
Abstract:

Lauraceae are an important component of tropical and subtropical forests and have major ecological and economic significance. Owing to lack of clear-cut morphological differences between genera and species, this family is an ideal case for testing the efficacy of DNA barcoding in the identification and discrimination of species and genera. In this study, we evaluated five widely recommended plant DNA barcode loci matK, rbcL, trnH–psbA, ITS2 and the entire ITS region for 409 individuals representing 133 species, 12 genera from China. We tested the ability of DNA barcoding to distinguish species and as an alternative tool for correcting species misidentification. We also used the rbcL+matK+trnH–psbA+ITS loci to investigate the phylogenetic relationships of the species examined. Among the gene regions and their combinations, ITS was the most efficient for identifying species (57.5%) and genera (70%). DNA barcoding also had a positive role for correcting species misidentification (10.8%). Furthermore, based on the results of the phylogenetic analyses, Chinese Lauraceae species formed three supported monophyletic clades, with the Cryptocarya group strongly supported (PP = 1.00, BS = 100%) and the clade including the Persea group, Laureae and Cinnamomum also receiving strong support (PP = 1.00, BS = 98%), whereas the CaryodaphnopsisNeocinnamomum received only moderate support (PP = 1.00 and BS = 85%). This study indicates that molecular barcoding can assist in screening difficult to identify families like Lauraceae, detecting errors of species identification, as well as helping to reconstruct phylogenetic relationships. DNA barcoding can thus help with large-scale biodiversity inventories and rare species conservation by improving accuracy, as well as reducing time and costs associated with species identification.

Contact the author: Li J
Page Number: e0175788
Issue: 4
Subject:
Impact Factor: 3.057
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PubYear: Apr 2017
Volume: 12
Publication Name: PLoS One
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