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Domainoid: domain-oriented orthology inference

BACKGROUND: Orthology inference is normally based on full-length protein sequences. However, most proteins contain independently folding and recurring regions, domains. The domain architecture of a protein is vital for its function, and recombination events mean individual domains can have different...

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Autores principales: Persson, Emma, Kaduk, Mateusz, Forslund, Sofia K., Sonnhammer, Erik L. L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6816169/
https://www.ncbi.nlm.nih.gov/pubmed/31660857
http://dx.doi.org/10.1186/s12859-019-3137-2
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author Persson, Emma
Kaduk, Mateusz
Forslund, Sofia K.
Sonnhammer, Erik L. L.
author_facet Persson, Emma
Kaduk, Mateusz
Forslund, Sofia K.
Sonnhammer, Erik L. L.
author_sort Persson, Emma
collection PubMed
description BACKGROUND: Orthology inference is normally based on full-length protein sequences. However, most proteins contain independently folding and recurring regions, domains. The domain architecture of a protein is vital for its function, and recombination events mean individual domains can have different evolutionary histories. It has previously been shown that orthologous proteins may differ in domain architecture, creating challenges for orthology inference methods operating on full-length sequences. We have developed Domainoid, a new tool aiming to overcome these challenges faced by full-length orthology methods by inferring orthology on the domain level. It employs the InParanoid algorithm on single domains separately, to infer groups of orthologous domains. RESULTS: This domain-oriented approach allows detection of discordant domain orthologs, cases where different domains on the same protein have different evolutionary histories. In addition to domain level analysis, protein level orthology based on the fraction of domains that are orthologous can be inferred. Domainoid orthology assignments were compared to those yielded by the conventional full-length approach InParanoid, and were validated in a standard benchmark. CONCLUSIONS: Our results show that domain-based orthology inference can reveal many orthologous relationships that are not found by full-length sequence approaches. AVAILABILITY: https://bitbucket.org/sonnhammergroup/domainoid/
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spelling pubmed-68161692019-10-31 Domainoid: domain-oriented orthology inference Persson, Emma Kaduk, Mateusz Forslund, Sofia K. Sonnhammer, Erik L. L. BMC Bioinformatics Research Article BACKGROUND: Orthology inference is normally based on full-length protein sequences. However, most proteins contain independently folding and recurring regions, domains. The domain architecture of a protein is vital for its function, and recombination events mean individual domains can have different evolutionary histories. It has previously been shown that orthologous proteins may differ in domain architecture, creating challenges for orthology inference methods operating on full-length sequences. We have developed Domainoid, a new tool aiming to overcome these challenges faced by full-length orthology methods by inferring orthology on the domain level. It employs the InParanoid algorithm on single domains separately, to infer groups of orthologous domains. RESULTS: This domain-oriented approach allows detection of discordant domain orthologs, cases where different domains on the same protein have different evolutionary histories. In addition to domain level analysis, protein level orthology based on the fraction of domains that are orthologous can be inferred. Domainoid orthology assignments were compared to those yielded by the conventional full-length approach InParanoid, and were validated in a standard benchmark. CONCLUSIONS: Our results show that domain-based orthology inference can reveal many orthologous relationships that are not found by full-length sequence approaches. AVAILABILITY: https://bitbucket.org/sonnhammergroup/domainoid/ BioMed Central 2019-10-28 /pmc/articles/PMC6816169/ /pubmed/31660857 http://dx.doi.org/10.1186/s12859-019-3137-2 Text en © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Persson, Emma
Kaduk, Mateusz
Forslund, Sofia K.
Sonnhammer, Erik L. L.
Domainoid: domain-oriented orthology inference
title Domainoid: domain-oriented orthology inference
title_full Domainoid: domain-oriented orthology inference
title_fullStr Domainoid: domain-oriented orthology inference
title_full_unstemmed Domainoid: domain-oriented orthology inference
title_short Domainoid: domain-oriented orthology inference
title_sort domainoid: domain-oriented orthology inference
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6816169/
https://www.ncbi.nlm.nih.gov/pubmed/31660857
http://dx.doi.org/10.1186/s12859-019-3137-2
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