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cRegions—a tool for detecting conserved cis-elements in multiple sequence alignment of diverged coding sequences

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 pro...

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Detalles Bibliográficos
Autores principales: Puustusmaa, Mikk, Abroi, Aare
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6330207/
https://www.ncbi.nlm.nih.gov/pubmed/30647994
http://dx.doi.org/10.7717/peerj.6176
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author Puustusmaa, Mikk
Abroi, Aare
author_facet Puustusmaa, Mikk
Abroi, Aare
author_sort Puustusmaa, Mikk
collection PubMed
description 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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spelling pubmed-63302072019-01-15 cRegions—a tool for detecting conserved cis-elements in multiple sequence alignment of diverged coding sequences Puustusmaa, Mikk Abroi, Aare PeerJ Bioinformatics 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/. PeerJ Inc. 2019-01-10 /pmc/articles/PMC6330207/ /pubmed/30647994 http://dx.doi.org/10.7717/peerj.6176 Text en © 2019 Puustusmaa and Abroi http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Puustusmaa, Mikk
Abroi, Aare
cRegions—a tool for detecting conserved cis-elements in multiple sequence alignment of diverged coding sequences
title cRegions—a tool for detecting conserved cis-elements in multiple sequence alignment of diverged coding sequences
title_full cRegions—a tool for detecting conserved cis-elements in multiple sequence alignment of diverged coding sequences
title_fullStr cRegions—a tool for detecting conserved cis-elements in multiple sequence alignment of diverged coding sequences
title_full_unstemmed cRegions—a tool for detecting conserved cis-elements in multiple sequence alignment of diverged coding sequences
title_short cRegions—a tool for detecting conserved cis-elements in multiple sequence alignment of diverged coding sequences
title_sort cregions—a tool for detecting conserved cis-elements in multiple sequence alignment of diverged coding sequences
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6330207/
https://www.ncbi.nlm.nih.gov/pubmed/30647994
http://dx.doi.org/10.7717/peerj.6176
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