Identification of Butterfly Species on the basis of analysis of MT-COX1 Gene

Abstract (English)

Accurate identification of butterfly species is a fundamental requirement
for biodiversity research, ecological monitoring, and conservation
planning. Traditionally, butterfly taxonomy has relied heavily on
morphological features such as wing coloration, size, and pattern.
However, these characteristics are often insufficient due to
polymorphism, sexual dimorphism, mimicry, and cryptic species, as
commonly observed in species like Papilio polytes. Such limitations
have led to increasing reliance on molecular techniques, especially DNA
barcoding using the mitochondrial cytochrome c oxidase subunit I
(mtCOX1) gene.
This study focuses on identifying butterfly species in the biodiverse
region of Jharkhand, India, through integrative taxonomy combining
classical morphology and molecular genetics. Butterfly samples were
collected from multiple sites, and DNA was extracted and amplified
using standard PCR protocols. The mtCOX1 gene was sequenced and
analyzed using bioinformatics tools such as BLAST, MEGA X, and
ClustalW. The resulting sequences were compared against global
databases (e.g., GenBank), and phylogenetic trees were constructed
using Neighbor-Joining, Maximum Likelihood, and Minimum Evolution
methods.
The molecular data successfully confirmed species identities, even in
morphologically ambiguous or mimetic forms, particularly in Papilio
polytes. Multiple sequence alignment and pairwise distance matrices
showed minimal intraspecific variation, supporting the robustness of mtCOX1 as a molecular marker. The study highlights the significance of
gene-based identification in resolving taxonomic ambiguities and
detecting cryptic diversity, which is often overlooked by morphological
taxonomy alone.
In conclusion, this research demonstrates the efficacy of mtCOX1 gene
sequencing as a reliable, reproducible, and precise tool for butterfly
species identification. It underscores the need for molecular techniques
to complement traditional taxonomy, especially in biodiversity-rich yet
underexplored regions like Jharkhand. The findings contribute to
regional biodiversity documentation and set a foundation for future
conservation and ecological research initiatives.