Pemanfaatan Marka DNA Barcode untuk Identifikasi Spesies dari Genus Terpilih pada Famili Fabaceae

Abstract

Fabaceae is an invaluable plant family with considerable ecological and economic importances due to its high value and benefits as food sources, soil fertilization agent, and medicinal plants. However, Fabaceae has been overexploited in Indonesia and several species belong to this family are critically endangered. Due to morphological similarity, rapid and accurate identification of Fabaceae species is essential to support its conservation efforts. Nowadays, species identification through DNA barcoding has become an effective taxonomic classification tool. This study was aimed to evaluate the effectiveness of chloroplast markers, matK and rbcL and the combination (matK+rbcL), as DNA barcodes for the identification of seleted genera in Fabaceae. The results showed that the length of the DNA sequences produced from the samples in this study was 568 bp for matK, 479 bp for rbcL, and 1,047 bp for matK+rbcL. Different sequence lengths at each locus are useful as early identification to differentiate species. The highest percentage of varied loci was obtained from the matK (56,69%). The matK+rbcL and matK loci had the highest identification rates (90% and 82,05%) at the species level. In addition, matK has the highest mean of interspecific distance (0,314) and intraspecific distance (0,003). The matK and the matK+rbcL combination have a better ability for species identification or species confirmation up to the species level than the rbcL, so the matK and the matK+rbcL combination are more recommended for Fabaceae plant identification. In the barcoding gap analysis, the average value of the interspecific distance is higher than the intraspecific distance. The mean value of rbcL intraspecific value is smaller than the matK. This is presumably because rbcL, which plays a role in encoding the RuBisCO protein, is thought to have a low mutation rate so that the level of similarity between species is high. In phylogenetic tree reconstruction, the neighbor joining method has a high monophyletic percentage and this method is quite effective for large datasets and is more informative in phylogenetic tree reconstruction.