MITOCHONDRIAL COI GENE-BASED MOLECULAR IDENTIFICATION AND PHYLOGENETIC ANALYSIS IN THIRTEEN DRAGONFLIES (ODONATA: LIBELLULIDAE) OF BANGLADESH

Dragonflies serve as essential predators in Integrated Pest Management (IPM). Nevertheless, polymorphism, sexual dimorphism, and body color changes make dragonfly species identification difficult. The application of the mitochondrial cytochrome c oxidase I (COI) gene to identify dragonflies is effective. In the present study, COI gene sequences of thirteen species from the family Libellulidae were generated. The COI gene sequences of twelve dragonfly species were 98% to 99% similar to the gene sequences of their respective species, according to BLAST analysis. Only one species, Brachydiplax farinosa, did not match significantly to any sequences in GenBank. Then, all thirteen sequences were submitted to GenBank, where only B. farinosa's sequence was submitted for the first time. Using MEGA10 and BioEdit, a 569bp COI gene fragment with 369 conserved sites, 200 variable sites, and 167 parsimony-informative sites was identified. The average base composition of the COI sequences was 35.43% T, 17.65 % C, 29.83% A, and 17.07% G. While there was a significant AT bias (65.26%) among dragonfly species. Pairwise distance analysis and phylogenetic tree was used to explore genetic diversity and evolutionary relationships among dragonfly species. The thirteen dragonfly species had 0.119-0.231% interspecific genetic divergence. A phylogenetic tree using the Neighbor-Joining (NJ) algorithm revealed two major clades, A and B, and demonstrated that all dragonfly species shared a common ancestor. These two clades encompass all twelve species, except Tholymis tillarga. Subsequently, a TCS haplotype network unveiled the genetic relatedness of these thirteen dragonflies, with T. tillarga exhibiting the highest number of mutations (49) in the analysis. T. tillarga has experienced significant genetic adaptation over time and could be an excellent model organism to study numerous biological processes. In addition, this work also supports to build a complete DNA barcode database in GenBank and uses DNA barcoding to identify thirteen dragonflies from Bangladesh.