Aakansha Manav, Jitender Singh, Rekha Dixit, Pankaj Kumar, Pushpendra Kumar, Satya Prakash and Ramesh Singh
Abstract
Sweet potato (Ipomoea batatas L.) production is heavily constrained by viral infections, particularly those caused by members of the Poty viridae family, such as Sweet potato feathery mottle virus (SPFMV), Sweet potato virus G (SPVG), and Sweet potato virus C (SPVC). Although extensive high-throughput sequencing (HTS) data are available in public repositories, Indian sweet potato datasets remain underexplored for viral diversity. In this study, a publicly available RNA-Seq dataset (SRR20083564) from Indian sweet potato samples was mined to identify viral genomes using a bioinformatic pipeline built in Galaxy. After quality control, trimming, and assembly with SPAdes, BLASTx analyses revealed three viral contigs exhibiting high similarity to SPFMV (9521 nts, 98% identity), SPVG (8133 nts, 99.1% identity), and SPVC (10,217 nts, 98.7% identity). The sequences were annotated, verified through multiple sequence alignments, and deposited in GenBank (BK071748âBK071750). Pairwise identity matrices indicated high conservation in SPVC and SPVG isolates, while SPFMV displayed greater nucleotide divergence but strong amino acid conservation. Phylogenetic analyses of coat protein sequences confirmed that the Indian isolates clustered with global representatives, including isolates from Africa, South America, and Asia, reflecting their worldwide distribution and possible movement through germplasm exchange. A sequence demarcation tool (SDT)-based heatmap further illustrated genetic clustering and highlighted differential diversity among the three viruses. This work demonstrates the utility of in silico viral mining to extend genomic resources, provides the partial genomic sequences of SPFMV, SPVG, and SPVC from India, and emphasizes the importance of leveraging public datasets for plant virus surveillance, phylogeography, and crop health management.