Bridging Genomics and Clinical Medicine: RSVrecon Enhances RSV Surveillance with Automated Genotyping and Clinically-important Mutation Reporting

Abstract

BackgroundRespiratory Syncytial Virus (RSV) causes significant respiratory infections, particularly in young children and elderly adults. Genetic variations in the fusion (F) protein can reduce the efficacy of vaccination and monoclonal antibody treatments, emphasizing the need for genomic surveillance of this virus. MotivationCurrent pipelines for RSV genome assembly focus on sequence reconstruction but often lack features for detecting genotypes, clinically relevant mutations, or presenting results in formats that are suitable for clinical researchers. ResultsWe introduce RSVrecon, an advanced bioinformatics pipeline for comprehensive RSV genome assembly and phylogenetic analysis. RSVrecon processes raw FASTQ files into annotated variant reports and delivers results in multiple formats (CSV, PDF, HTML) tailored to diverse end users. A key innovation of RSVrecon is not only its integrated detection of clinically critical features--including genotype classification and F protein mutation calling, capabilities absent in most analytical pipelines--but also its presentation of these results to clinicians via an integrated, graphical, and user-friendly interface. Its modular design, powered by Nextflows modern framework, ensures a scalable and robust workflow, while user-friendly reports enable seamless translation of genomic data into actionable clinical insights. Benchmarking against existing pipelines using clinical datasets revealed that RSVrecon achieves comparable genomic assembly accuracy while excelling in three key dimensions: (1) expanded functional capabilities, (2) intuitive biological interpretation of the results, and (3) superior user experience and accessibility. By seamlessly translating RSV genomic data into clinically meaningful information, RSVrecon empowers research breakthroughs, guides clinical care decisions, and strengthens surveillance systems. With these features, RSVrecon offers an enhanced approach to RSV surveillance and research. The tool is freely available at https://github.com/stjudecab/rsvrecon and https://github.com/stjudecab/RSVreconPy. Key PointsO_LIRSVrecon enables comprehensive clinical detection for RSV such as identifying genotypes and F protein mutations. C_LIO_LIRSVrecon delivers results through an integrated, graphical, and user-friendly interface for clinicians. C_LIO_LIRSVrecons Nextflow-based design ensures robust, scalable, and consistent performance. C_LIO_LIRSVrecon matches assembly accuracy while excelling in functionality, interpretation, and accessibility during benchmarking. C_LI