A hybrid genome assembly reveals key pathogenicity signatures in a virulent Ustilaginoidea virens isolate from India

Abstract

Ustilaginoidea virens, responsible for rice false smut, is an emerging pathogen that adversely affects crop yield and grain quality. Despite its growing importance, the molecular basis of pathogenicity in U. virens remains largely unexplored. We report a high-quality whole genome assembly and annotation of a highly virulent isolate, Uv2_4G, using a hybrid sequencing approach combining Nanopore and Illumina platforms. The assembled genome (∼35.9 Mb; 49% GC content, 89 scaffolds) revealed 7444 protein-coding genes. Comparative genome analysis identified genetic variation, including 3,55,173 SNPs, 8,03,524 INDELs, and 7390 SSRs. CAZyme profiling showed enrichment of glycosyl hydrolases (35%), glycosyl transferases (32%), and carbohydrate-binding modules (20%), essential for host colonization. In contrast, the relatively low abundance of auxiliary activities, carbohydrate esterases and polysaccharide lyases implies a limited reliance on extensive cell wall breakdown and lignin degradation, supports the biotrophic or hemibiotrophic lifestyle of U. virens. Additionally, the isolate possessed 6 unique gene clusters enriched in biological processes. Furthermore, 2708 pathogenicity-related genes associated with signal transduction, transcriptional and epigenetic regulation, stress tolerance, iron acquisition, metabolic adaptation, circadian regulation, membrane transport, and host–pathogen interactions were identified. Secretome analysis of the predicted proteome identified 71 putative effectors. Further, qPCR-based validation confirmed high expression of small cysteine rich effectors (SCRE2A and SCRE2B) during early infection stages suggesting SCREs could be a potential effector which can be utilised for disease management strategies under Indian conditions. These findings provide new insights into the molecular basis of U. virens pathogenicity and establish a framework for subsequent functional genomic analyses and improved disease management approaches.