Improved database searches for orthologous sequences by conditioning on outgroup sequences

Abstract

Motivation: Searches of biological sequence databases are usually focussed on distinguishing significant from random matches. However, the increasing abundance of related sequences on databases present a second challenge: to distinguish the evolutionarily most closely related sequences (often orthologues) from more distantly related homologues. This is particularly important when searching a database of partial sequences, where short orthologous sequences from a non-conserved region will score much more poorly than non-orthologous (outgroup) sequences from a conserved region. Results: Such inferences are shown to be improved by conditioning the search results on the scores of an outgroup sequence. The log-odds score for each target sequence identified on the database has the log-odds score of the outgroup sequence subtracted from it. A test group of Caenorhabditis elegans kinase sequences and their identified C.elegans outgroups were searched against a test database of human Expressed Sequence Tag (EST) sequences, where the sets of true target sequences were known in advance. The outgroup conditioned method was shown to identify 58% more true positives ahead of the first false positive, compared to the straightforward search without an outgroup. A test dataset of 151 proteins drawn from the C.elegans genome, where the putative 'outgroup' was assigned automatically, similarly found 50% more true positives using outgroup conditioning. Thus, outgroup conditioning provides a means to improve the results of database searching with little increase in the search computation time.