GCVirolens is a lightweight, browser-based tool developed to perform gene-wise GC content analysis of viral genomes. Users simply upload a whole genome FASTA file along with its corresponding GFF annotation file, and the tool automatically extracts each gene sequence and calculates its GC content percentage.
A higher GC content is associated with greater thermal stability, whereas a lower GC content indicates increased susceptibility to mutations. Unlike traditional workflows, GCVirolens eliminates the need for Linux-only tools, pipelines, or multiple software installations. The analysis is executed entirely in the browser, making it fast, platform-independent, and resource-efficient. Results are displayed in an easy-to-read tabular format and can be conveniently downloaded as a CSV file for further analysis and publication.
Kindly upload the complete viral genome sequence along with its corresponding .gff annotation file.
The GC content of a genome is an important indicator of its structural stability and evolutionary behavior. Genes with higher GC content are generally more thermally stable, while those with lower GC content are more prone to mutations and genetic variations. By analyzing GC content at the gene level, researchers can identify which parts of a viral genome are more stable and which regions are more vulnerable to changes. This information is highly valuable in understanding viral adaptation, vaccine design, and drug target identification. The GCVirolens web application makes this process simple, fast, and platform-independent, removing the need for complex bioinformatics pipelines. Beyond human health, such analysis also has applications in agriculture, where understanding viral stability in plant pathogens can support disease resistance breeding, crop protection strategies, and sustainable agricultural practices.
Step 1: Upload Genome (.fasta)
Step 2: Upload Annotation (.gff)
Step 3: Extract Gene Sequences
Step 4: Calculate GC Content (looped for all genes)
Step 5: Download Results (.csv)
To try out GCVirolens, you can download the following sample files of the SARS-CoV-2 genome: