Identifying splicing regulatory elements with de Bruijn graphs.
Splicing regulatory elements (SREs) are short, degenerate sequences on pre-mRNA molecules that enhance or inhibit the splicing process via the binding of splicing factors, proteins that regulate the functioning of the spliceosome. Existing methods for identifying SREs in a genome are either experimental or computational. Here, we propose a formalism based on de Bruijn graphs that combines genomic structure, word count enrichment analysis, and experimental evidence to identify SREs found in exons. In our approach, SREs are not restricted to a fixed length (i.e., k-mers, for a fixed k). As a result, we identify 2001 putative exonic enhancers and 3080 putative exonic silencers for human genes, with lengths varying from 6 to 15 nucleotides. Many of the predicted SREs overlap with experimentally verified binding sites. Our model provides a novel method to predict variable length putative regulatory elements computationally for further experimental investigation.
Department of Computer Science, Virginia Tech , Blacksburg, Virginia.
Eman
E
Badr
Lenwood S
LS
Heath
D017398:Alternative Splicing / Q000235:genetics*; D001483:Base Sequence; D019295:Computational Biology; D005091:Exons / Q000235:genetics; D016678:Genome; D006801:Humans; D007438:Introns; D012326:RNA Splicing / Q000235:genetics*; D012045:Regulatory Sequences, Nucleic Acid / Q000235:genetics*
algorithms; combinatorics; computational molecular biology; graphs and networks; literature data mining; machine learning; probability; sequences