SNP barcoding based on decision tree algorithm: A new tool for identification of mosquito species with special reference to Anopheles

Abstract

Molecular taxonomy based identification of species in the form of DNA barcodes are extensively used in evolutionary systematics. Almost all the DNA barcodes contain detailed information of the barcoding gene along with uninformative sequences of a particular species. Therefore, a technique is highly essential to remove or to reduce the number of uninformative sequences and ought to create species-specific barcodes for differentiation. The actual variation in genetic sequences, called single nucleotide polymorphism (SNP) genotyping, can be utilized to develop a new tool for rapid, reliable, and high-throughput assay to distinguish the known species. SNPs act as important hereditary markers for uncovering the evolutionary history and normal genetic polymorphisms. Keeping in mind, we propose a decision tree-based barcoding (DTB) algorithm for generating SNP barcodes from the DNA barcoding sequence of several evolutionarily related species to accurately identify a single species. To address this issue, we analyzed mitochondrial COI gene sequences of 64 species of Anopheles mosquitoes. After alignment and truncating, 32 SNPs were discovered in COI gene sequences of Anopheles mosquitoes and then computed to set up the decision rule for constructing the decision tree. The decision tree based barcoding algorithm generates 126 nodes and 32 loci for discriminating 64 Anopheles mosquito species. Finally, we concluded that the DTB method is useful and effective for generating sequence tags for Anopheles mosquito species identification.