GLASSgo – Automated and Reliable Detection of sRNA Homologs From a Single Input Sequence

• Main Authors: Steffen C. Lott, Richard A. Schäfer, Martin Mann, Rolf Backofen, Wolfgang R. Hess, Björn Voß, Jens Georg
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2018-04-01
• Series: Frontiers in Genetics
• Subjects: sRNA; prediction; homology search; ncRNA; bacteria; Rfam
• Online Access: http://journal.frontiersin.org/article/10.3389/fgene.2018.00124/full

Bacterial small RNAs (sRNAs) are important post-transcriptional regulators of gene expression. The functional and evolutionary characterization of sRNAs requires the identification of homologs, which is frequently challenging due to their heterogeneity, short length and partly, little sequence conservation. We developed the GLobal Automatic Small RNA Search go (GLASSgo) algorithm to identify sRNA homologs in complex genomic databases starting from a single sequence. GLASSgo combines an iterative BLAST strategy with pairwise identity filtering and a graph-based clustering method that utilizes RNA secondary structure information. We tested the specificity, sensitivity and runtime of GLASSgo, BLAST and the combination RNAlien/cmsearch in a typical use case scenario on 40 bacterial sRNA families. The sensitivity of the tested methods was similar, while the specificity of GLASSgo and RNAlien/cmsearch was significantly higher than that of BLAST. GLASSgo was on average ∼87 times faster than RNAlien/cmsearch, and only ∼7.5 times slower than BLAST, which shows that GLASSgo optimizes the trade-off between speed and accuracy in the task of finding sRNA homologs. GLASSgo is fully automated, whereas BLAST often recovers only parts of homologs and RNAlien/cmsearch requires extensive additional bioinformatic work to get a comprehensive set of homologs. GLASSgo is available as an easy-to-use web server to find homologous sRNAs in large databases.