Validating regulatory predictions from diverse bacteria with mutant fitness data.

ABSTRACT: Although transcriptional regulation is fundamental to understanding bacterial physiology, the targets of most bacterial transcription factors are not known. Comparative genomics has been used to identify likely targets of some of these transcription factors, but these predictions typically lack experimental support. Here, we used mutant fitness data, which measures the importance of each gene for a bacterium's growth across many conditions, to test regulatory predictions from RegPrecise, a curated collection of comparative genomics predictions. Because characterized transcription factors often have correlated fitness with one of their targets (either positively or negatively), correlated fitness patterns provide support for the comparative genomics predictions. At a false discovery rate of

SUBMITTER: Sagawa S 

PROVIDER: S-EPMC5443562 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature