Evolutionary Bioinformatics for Pathogen Genomics: Transmission, Adaptation, and Genomic Surveillance

The rapid evolution of pathogens continues to challenge public health, clinical medicine, agriculture, and global surveillance systems. Advances in high-throughput sequencing and bioinformatics have transformed how viral, bacterial, and fungal pathogens are detected, compared, and tracked across populations, hosts, and environments. These approaches now make it possible to reconstruct transmission pathways, identify emerging variants, characterize intra-host diversity, and investigate the genomic basis of virulence, host adaptation, antimicrobial resistance, and immune escape.At the same time, pathogen genomic datasets are becoming larger, more complex, and more heterogeneous. This creates a growing need for robust evolutionary bioinformatics methods that can integrate comparative genomics, phylodynamics, microbial genome-wide association studies, machine learning, and population-level surveillance. While tools such as mGWAS can help link genetic variation to clinically or epidemiologically relevant phenotypes, broader computational frameworks are needed to interpret pathogen evolution across scales, from within-host dynamics to regional and global spread.This Research Topic aims to bring together studies that use evolutionary bioinformatics to understand pathogen transmission, adaptation, and genomic diversity. We welcome contributions that develop, benchmark, or apply computational methods for pathogen genomics, with a particular interest in approaches that translate genomic data into actionable insights for outbreak response, surveillance, and pathogen evolution research.We welcome submissions addressing, but not limited to, the following themes:• Comparative genomics of viral, bacterial, and fungal pathogens• Phylodynamics and transmission reconstruction in infectious disease outbreaks• Intra-host pathogen diversity and within-host evolution• Microbial genome-wide association studies and genotype–phenotype mapping• Machine learning approaches for pathogen classification, prediction, and surveillance• Evolution of antimicrobial resistance, virulence, immune escape, and host adaptation• Bioinformatics pipelines for pathogen genome assembly, annotation, variant calling, and lineage tracking• Population genomics and genomic epidemiology of emerging and re-emerging pathogens• Benchmarking, reproducibility, and methodological challenges in pathogen genomic analysis• Genomic surveillance frameworks for public health, agriculture, and One Health contextsWe welcome Original Research, Review, Methods, Perspective, and Brief Research Report articles. Topic editors: Aquillah M. Kanzi, Dr Elijah Kolawole Oladipo Source: https://www.frontiersin.org/research-topics/84483/evolutionary-bioinformatics-for-pathogen-genomics-transmission-adaptation-and-genomic-surveillance