Molecular identification and genetic variations of forensically significant blow flies (Diptera: Calliphoridae) from Eastern India using DNA barcoding

Abstract

Flies, especially those from the Calliphoridae family, play a crucial role in decomposition and are the first to colonize a cadaver. Firstly, accurate species identification is a prerequisite for entomological evidence-based calculation of postmortem interval (PMI). While morphological criteria for identifying the species of adult blow flies exist, there are either absent or inadequate keys for younger stages. In all phases of blow fly development, molecular identification offers a quick and accurate procedure. It is widely known that mitochondrial cytochrome oxidase subunit I has the capacity for molecular identification but is ineffective in certain species. This study was conducted to assess the effectiveness of the cytochrome oxidase 1 gene in the identification of seventeen different species of calliphorid flies involving four genera, Calliphora, Chrysomya, Lucilia, and Hemipyrellia. In West Bengal, 2,977 blow fly specimens were gathered from four distinct geo-climatic zones. COI barcodes were able to confirm morphological identification through low K2P intraspecific genetic divergences (0% to 1%) and moderate to high K2P interspecific genetic divergences (0.39% to 12.29%). The Neighbour-Joining (NJ) analysis demonstrated well-supported reciprocal monophyly among the species. The species grouping was in agreement with morphological and molecular identifications. The four delimitation methods, BIN, ASAP, PTP, and GMYC, used for species identification produced similar results and facilitated the proper identification of species. Therefore, it can be concluded that COI barcodes are a highly successful alternative for the molecular identification of blow flies, facilitating forensic cases and biodiversity research in India.

Fig 1. Map representing the sampling localities of different blow fly species from four different geo-climatic regions of West Bengal, India.

Fig 2. Images of species collected and barcoded for this study.

(a) Chrysomya megacephala (Fabricius, 1794), (b) Chrysomya bezziana Villeneuve, 1914, (c) Chrysomya rufifacies (Macquart, 1844), (d) Chrysomya nigripes Aubertin, 1932, (e) Chrysomya defixa (Walker, 1856), (f) Chrysomya pinguis (Walker, 1858), (g) Hemipyrellia ligurriens (Wiedemann, 1830), (h) Hemipyrellia pulchra (Wiedemann, 1830), (i) Calliphora vomitoria (Linnaeus, 1758), (j) Calliphora pattoni Aubertin, 1931, (k) Calliphora vicina Robineau-Desvoidy, 1830, (l) Lucilia ampullacea Villeneuve, 1922, (m) Lucilia porphyrina (Walker, 1856), (n) Lucilia papuensis Macquart, 1844, (o) Lucilia illustris (Meigen, 1826), (p) Lucilia cuprina (Wiedemann, 1830), and (q) Lucilia sericata (Meigen, 1826).

Fig 3. Neighbour-joining (NJ) tree of 21 calliphorid species with bootstrap support values with the comparison of different species delimitation methods.

Barcode Index Number (BIN) system, Assemble Species by Automatic Partitioning (ASAP), Poisson Tree Processes (PTP), Generalised Mixed Yule Coalescent (GMYC), and FINAL (Final identification).