Two new potential barcodes to discriminate dalbergia species

TitleTwo new potential barcodes to discriminate dalbergia species
Publication TypeJournal Article
Year of Publication2015
AuthorsBhagwat, RM, Dholakia, BB, Kadoo, NY, Balasundaran, M, Gupta, VS
JournalPlos One
Volume10
Issue11
PaginationArticle Number: e0142965
Date PublishedNOV
ISSN1932-6203
Abstract

DNA barcoding enables precise identification of species from analysis of unique DNA sequence of a target gene. The present study was undertaken to develop barcodes for different species of the genus Dalbergia, an economically important timber plant and is widely distributed in the tropics. Ten Dalbergia species selected from the Western Ghats of India were evaluated using three regions in the plastid genome (matK, rbcL, trnH-psbA), a nuclear transcribed spacer (nrITS) and their combinations, in order to discriminate them at species level. Five criteria: (i) inter and intraspecific distances, (ii) Neighbor Joining (NJ) trees, (iii) Best Match (BM) and Best Close Match (BCM), (iv) character based rank test and (v) Wilcoxon signed rank test were used for species discrimination. Among the evaluated loci, rbcL had the highest success rate for amplification and sequencing (97.6%), followed by matK (97.0%), trnH-psbA (94.7%) and nrITS (80.5%). The inter and intraspecific distances, along with Wilcoxon signed rank test, indicated a higher divergence for nrITS. The BM and BCM approaches revealed the highest rate of correct species identification (100%) with matK, matK+rbcL and matK+trnH-psb loci. These three loci, along with nrITS, were further supported by character based identification method. Considering the overall performance of these loci and their ranking with different approaches, we suggest matK and matK+rbcL as the most suitable barcodes to unambiguously differentiate Dalbergia species. These findings will potentially be helpful in delineating the various species of Dalbergia genus, as well as other related genera.

DOI10.1371/journal.pone.0142965
Type of Journal (Indian or Foreign)

Foreign

Impact Factor (IF)3.057
Divison category: 
Biochemical Sciences