Abstract:
DNA barcoding has been adopted as a global bio-identification system for animals in recent years. DNA barcoding, based on the sequencing of a standardized region of the Cytochrome C Oxidase subunit I (COI) gene, has received considerable attention as an accurate and broadly applicable tool for animal species identification. Mitochondrial DNA (mtDNA) has been used extensively in the last three decades as a tool for inferring in the evolutionary and demographic past of both populations and species. This tool has proven invaluable for the new field of molecular ecology and phylogeography. Hilsa shad (Bangali name: Ilish or Elish) is the largest single fishable species in Bangladesh, present in almost all the major river systems, estuaries and Bay of Bengal. Genetic diversity of Tenualosa ilisha, T. toil and Hilsa kelee in Bangladesh were studied from August 2012 to December 2016. Samples were identified based on its morphological characters. In this study, 650 base-pair region of the COI gene was sequenced from samples collected from different regions. The BLAST analysis confirms the three species. The result from BLAST showed that the sequences have high similarity with the existing COI gene sequences of NCBI GenBank. Sequence alignment of all Hilsa and Tenualosa individuals revealed highly consistent 99% - 100% similarity among the species. High efficiency of species identification was demonstrated in the present study by DNA barcoding. In addition to barcode-based species identification system, a phylogenetic analysis was done using Maximum Parsimony (MP) and Maximum Likelihood (ML) methods. The results showed an identical tree topology with minor differences in bootstrap confidence levels. The evolutionary distances indicated that the mean interspecies distance was 25.52%, while the intraspecies distance was 0.22%. Therefore, the study indicates that there are three sepcies of hilsa, and COI is an ideal genetic marker that can be used to identify and confirm the nature of these species. Further studies can be done with large number of samples in wide geographic regions to deeply understand the population structures of these species.
