Evolutionary rate covariation reveals novel protein networks in Mycobacterium tuberculosis

Proteins that participate together in a function often show covariation in
their relative evolutionary rates, because selective pressures influencing
their evolution affect co-functional proteins as an ensemble. Evolutionary
Rate Covariation (ERC) is a computational comparative genomics tool that
identifies this co-variation using collections of orthologous gene
sequences from several species, providing measures of correlation that can
be used to infer novel functional relationships. Though proven to be
successful at identifying novel functional relationships in eukaryotic
species, ERC’s usefulness in prokaryotes requires further investigation.
In this study, we validate the use of ERC in prokaryotes using 106 species
in the Mycobacterium genus, and provide a useful genome-wide dataset of
functional relationships between 11,638 mycobacterial orthologous gene
groups with Mycobacterium tuberculosis as a focal model organism. To
evaluate the dataset’s utility, we studied genome-wide ERC patterns
between known functionally interacting proteins and operons, as well as
within smaller functional groups such as the recBCD complex, peptidoglycan
synthesis, and multiple transport systems. We use these data to
demonstrate how ERC can be used as a predictor of functional relationships
in prokaryotes and describe three potential novel protein networks for
future study. This repository contains all products and scripts associated
with this study in Mycobacterial species.