Systematic identification and analysis of frequent gene fusion events in metabolic pathways.

ABSTRACT:

Background

Gene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur.

Results

Here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These sets were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives a

SUBMITTER: Henry CS 

PROVIDER: S-EPMC4921024 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature