Abstract
Molecular diversity, which reflects variation in species abundance and genetic structure, plays a pivotal role in forensic entomology by enabling the accurate identification of insect evidence through tools such as DNA barcoding. In Pakistan, the absence of trained forensic entomologists and limited research on insect biodiversity hinder the effective use of entomological evidence in criminal investigations. Traditional morphological identification methods are insufficient for resolving complex forensic cases, particularly when dealing with immature insect stages. This highlights the urgent need for molecular approaches, such as DNA barcoding, to enhance species identification and genetic analysis of forensically relevant insects. This study uniquely focuses on evaluating the utility of a 658 bp fragment of the mitochondrial cytochrome oxidase subunit 1 (CO1) gene for identifying dipteran species collected from cadavers in Lahore, Pakistan. The primary goal was to identify forensically relevant insect species, assess their genetic diversity and population structure, and compare these findings with global data to contextualize the results within forensic entomology. Three blow fly species were identified: Chrysomya megacephala (Fabricius, 1794), Chrysomya saffranea (Bigot, 1877), and Chrysomya rufifacies (Macquart, 1843). Low genetic diversity was observed within populations, while significant genetic differentiation among populations was indicated by a high fixation index (FST = 0.83992). These findings suggest unique genetic signatures for blow fly populations in Lahore. This study underscores the importance of molecular tools like DNA barcoding for species identification and highlights the need for further research to establish a comprehensive database of forensically relevant insects in Pakistan, given the limited species diversity and unique genetic profiles observed. By laying the groundwork for future research, this study contributes to advancing forensic entomology in Pakistan by improving species identification, which, when combined with future thermobiological data, can enhance postmortem interval (PMI) estimation and forensic investigations.