ArticlePeerJ2019
cRegions-a tool for detecting conserved cis-elements in multiple sequence alignment of diverged coding sequences.
Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Computational methods for inferring location and genealogy of overlapping genes in virus genomes: approaches and applications.Current opinion in virology · 2022Review
- Article
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2 authors.
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Abstract
Identifying cis-acting elements and understanding regulatory mechanisms of a gene is crucial to fully understand the molecular biology of an organism. In general, it is difficult to identify previously uncharacterised cis-acting elements with an unknown consensus sequence. The task is especially problematic with viruses containing regions of limited or no similarity to other previously characterised sequences. Fortunately, the fast increase in the number of sequenced genomes allows us to detect some of these elusive cis-elements. In this work, we introduce a web-based tool called cRegions. It was developed to identify regions within a protein-coding sequence where the conservation in the amino acid sequence is caused by the conservation in the nucleotide sequence. The cRegion can be the first step in discovering novel cis-acting sequences from diverged protein-coding genes. The results can be used as a basis for future experimental analysis. We applied cRegions on the non-structural and structural polyproteins of alphaviruses as an example and successfully detected all known cis-acting elements. In this publication and in previous work, we have shown that cRegions is able to detect a wide variety of functional elements in DNA and RNA viruses. These functional elements include splice sites, stem-loops, overlapping reading frames, internal promoters, ribosome frameshifting signals and other embedded elements with yet unknown function. The cRegions web tool is available at http://bioinfo.ut.ee/cRegions/.
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