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Computational identification of the selenocysteine tRNA (tRNA(Sec)) in genomes
Selenocysteine (Sec) is known as the 21st amino acid, a cysteine analogue with selenium replacing sulphur. Sec is inserted co-translationally in a small fraction of proteins called selenoproteins. In selenoprotein genes, the Sec specific tRNA (tRNA(Sec)) drives the recoding of highly specific UGA co...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5330540/ https://www.ncbi.nlm.nih.gov/pubmed/28192430 http://dx.doi.org/10.1371/journal.pcbi.1005383 |
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author | Santesmasses, Didac Mariotti, Marco Guigó, Roderic |
author_facet | Santesmasses, Didac Mariotti, Marco Guigó, Roderic |
author_sort | Santesmasses, Didac |
collection | PubMed |
description | Selenocysteine (Sec) is known as the 21st amino acid, a cysteine analogue with selenium replacing sulphur. Sec is inserted co-translationally in a small fraction of proteins called selenoproteins. In selenoprotein genes, the Sec specific tRNA (tRNA(Sec)) drives the recoding of highly specific UGA codons from stop signals to Sec. Although found in organisms from the three domains of life, Sec is not universal. Many species are completely devoid of selenoprotein genes and lack the ability to synthesize Sec. Since tRNA(Sec) is a key component in selenoprotein biosynthesis, its efficient identification in genomes is instrumental to characterize the utilization of Sec across lineages. Available tRNA prediction methods fail to accurately predict tRNA(Sec), due to its unusual structural fold. Here, we present Secmarker, a method based on manually curated covariance models capturing the specific tRNA(Sec) structure in archaea, bacteria and eukaryotes. We exploited the non-universality of Sec to build a proper benchmark set for tRNA(Sec) predictions, which is not possible for the predictions of other tRNAs. We show that Secmarker greatly improves the accuracy of previously existing methods constituting a valuable tool to identify tRNA(Sec) genes, and to efficiently determine whether a genome contains selenoproteins. We used Secmarker to analyze a large set of fully sequenced genomes, and the results revealed new insights in the biology of tRNA(Sec), led to the discovery of a novel bacterial selenoprotein family, and shed additional light on the phylogenetic distribution of selenoprotein containing genomes. Secmarker is freely accessible for download, or online analysis through a web server at http://secmarker.crg.cat. |
format | Online Article Text |
id | pubmed-5330540 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-53305402017-03-10 Computational identification of the selenocysteine tRNA (tRNA(Sec)) in genomes Santesmasses, Didac Mariotti, Marco Guigó, Roderic PLoS Comput Biol Research Article Selenocysteine (Sec) is known as the 21st amino acid, a cysteine analogue with selenium replacing sulphur. Sec is inserted co-translationally in a small fraction of proteins called selenoproteins. In selenoprotein genes, the Sec specific tRNA (tRNA(Sec)) drives the recoding of highly specific UGA codons from stop signals to Sec. Although found in organisms from the three domains of life, Sec is not universal. Many species are completely devoid of selenoprotein genes and lack the ability to synthesize Sec. Since tRNA(Sec) is a key component in selenoprotein biosynthesis, its efficient identification in genomes is instrumental to characterize the utilization of Sec across lineages. Available tRNA prediction methods fail to accurately predict tRNA(Sec), due to its unusual structural fold. Here, we present Secmarker, a method based on manually curated covariance models capturing the specific tRNA(Sec) structure in archaea, bacteria and eukaryotes. We exploited the non-universality of Sec to build a proper benchmark set for tRNA(Sec) predictions, which is not possible for the predictions of other tRNAs. We show that Secmarker greatly improves the accuracy of previously existing methods constituting a valuable tool to identify tRNA(Sec) genes, and to efficiently determine whether a genome contains selenoproteins. We used Secmarker to analyze a large set of fully sequenced genomes, and the results revealed new insights in the biology of tRNA(Sec), led to the discovery of a novel bacterial selenoprotein family, and shed additional light on the phylogenetic distribution of selenoprotein containing genomes. Secmarker is freely accessible for download, or online analysis through a web server at http://secmarker.crg.cat. Public Library of Science 2017-02-13 /pmc/articles/PMC5330540/ /pubmed/28192430 http://dx.doi.org/10.1371/journal.pcbi.1005383 Text en © 2017 Santesmasses et al 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, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Santesmasses, Didac Mariotti, Marco Guigó, Roderic Computational identification of the selenocysteine tRNA (tRNA(Sec)) in genomes |
title | Computational identification of the selenocysteine tRNA (tRNA(Sec)) in genomes |
title_full | Computational identification of the selenocysteine tRNA (tRNA(Sec)) in genomes |
title_fullStr | Computational identification of the selenocysteine tRNA (tRNA(Sec)) in genomes |
title_full_unstemmed | Computational identification of the selenocysteine tRNA (tRNA(Sec)) in genomes |
title_short | Computational identification of the selenocysteine tRNA (tRNA(Sec)) in genomes |
title_sort | computational identification of the selenocysteine trna (trna(sec)) in genomes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5330540/ https://www.ncbi.nlm.nih.gov/pubmed/28192430 http://dx.doi.org/10.1371/journal.pcbi.1005383 |
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