%A Fei-Fei Wu, Qiu Gao, Fang Liu, Zan Wang, Jian-Li Wang, and Xian-Guo Wang %T DNA barcoding evaluation of Vicia (Fabaceae): Comparative efficacy of six universal barcode loci on abundant species %0 Journal Article %D 2020 %J J Syst Evol %R 10.1111/jse.12474 %P 77-88 %V 58 %N 1 %U {https://www.jse.ac.cn/CN/abstract/article_29539.shtml} %8 2020-01-01 %X

Vicia L. is an invaluable genus with considerable agricultural and economic importance due to its high value as feed, green manure, and medicine. However, most of this genus is not well known and remains underutilized. Due to the imprecise circumscription and delineation of Vicia species, the taxonomic history of this genus is controversial, which has hindered the identification of species with high economic potential. Therefore, rapid and accurate identification of Vicia species is essential. Simultaneously, species identification through DNA barcoding has become an effective taxonomic classification tool. Here, the species‐discrimination abilities of matK, rbcL, trnHpsbA, trnL‐trnF, ITS1, and ITS2 were tested in 161 Vicia species with both sequence similarity (nearest neighbor, best match, and best close match) and tree‐based (maximum likelihood tree) methods. Among the single barcode sites, trnHpsbA had the highest level of polymorphism (52.4% variable sites; nucleotide diversity, 0.1338). Additionally, trnHpsbA had the highest mean interspecific distance (0.1352) and intraspecific distance (0.0071). The combined barcode matK+trnHpsbA had the highest correct identification rate by the sequence similarity method. Both trnHpsbA (75.38%) and matK (70.73%) showed higher species discrimination rates than the other barcodes when using the tree‐based method. Based on overall performance, matK and trnHpsbA, alone or in combination, were the best barcodes for Vicia. Internal transcribed spacer (ITS1) also showed good performance and provided essential information regarding nuclear DNA, so this site is also recommended as a backup barcode for Vicia. These Vicia barcodes can be used to identify species and to evaluate germplasm resource collections.