zol and fai: large-scale targeted detection and evolutionary investigation of gene clusters
Rauf Salamzade, Patricia Q. Tran, Cody Martin, Abigail L. Manson, Michael S. Gilmore, Ashlee M. Earl, Karthik Anantharaman, Lindsay Kalan
Abstract
Many universally and conditionally important genes are genomically aggregated within clusters. Here, we introduce fai and zol, which together enable large-scale comparative analysis of different types of gene clusters and mobile-genetic elements, such as biosynthetic gene clusters (BGCs) or viruses. Fundamentally, they overcome a current bottleneck to reliably perform comprehensive orthology inference at large scale across broad taxonomic contexts and thousands of genomes. First, fai allows the identification of orthologous instances of a query gene cluster of interest amongst a database of target genomes. Subsequently, zol enables reliable, context-specific inference of ortholog groups for individual protein-encoding genes across gene cluster instances. In addition, zol performs functional annotation and computes a variety of evolutionary statistics for each inferred ortholog group. Importantly, in comparison to tools for visual exploration of homologous relationships between gene clusters, zol can scale to handle thousands of gene cluster instances and produce detailed reports that are easy to digest. To showcase fai and zol, we apply them for: (i) longitudinal tracking of a virus in metagenomes, (ii) performing population genetic investigations of BGCs for a fungal species, and (iii) uncovering evolutionary trends for a virulence-associated gene cluster across thousands of genomes from a diverse bacterial genus.