Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD

Sequence alignments are the foundations of life science research, but most innovation so far focuses on optimal alignments, while information derived from suboptimal solutions is ignored. We argue that one optimal alignment per pairwise sequence comparison is a reasonable approximation when dealing...

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Autores principales: Grigorjew, Andreas, Gynter, Artur, Dias, Fernando H. C., Buchfink, Benjamin, Drost, Hajk-Georg, Tomescu, Alexandru I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10351170/
https://www.ncbi.nlm.nih.gov/pubmed/37461051
http://dx.doi.org/10.1186/s13059-023-03008-6
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author Grigorjew, Andreas
Gynter, Artur
Dias, Fernando H. C.
Buchfink, Benjamin
Drost, Hajk-Georg
Tomescu, Alexandru I.
author_facet Grigorjew, Andreas
Gynter, Artur
Dias, Fernando H. C.
Buchfink, Benjamin
Drost, Hajk-Georg
Tomescu, Alexandru I.
author_sort Grigorjew, Andreas
collection PubMed
description Sequence alignments are the foundations of life science research, but most innovation so far focuses on optimal alignments, while information derived from suboptimal solutions is ignored. We argue that one optimal alignment per pairwise sequence comparison is a reasonable approximation when dealing with very similar sequences but is insufficient when exploring the biodiversity of the protein universe at tree-of-life scale. To overcome this limitation, we introduce pairwise alignment-safety to uncover the amino acid positions robustly shared across all suboptimal solutions. We implement EMERALD, a software library for alignment-safety inference, and apply it to 400k sequences from the SwissProt database. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03008-6.
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spelling pubmed-103511702023-07-18 Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD Grigorjew, Andreas Gynter, Artur Dias, Fernando H. C. Buchfink, Benjamin Drost, Hajk-Georg Tomescu, Alexandru I. Genome Biol Method Sequence alignments are the foundations of life science research, but most innovation so far focuses on optimal alignments, while information derived from suboptimal solutions is ignored. We argue that one optimal alignment per pairwise sequence comparison is a reasonable approximation when dealing with very similar sequences but is insufficient when exploring the biodiversity of the protein universe at tree-of-life scale. To overcome this limitation, we introduce pairwise alignment-safety to uncover the amino acid positions robustly shared across all suboptimal solutions. We implement EMERALD, a software library for alignment-safety inference, and apply it to 400k sequences from the SwissProt database. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03008-6. BioMed Central 2023-07-17 /pmc/articles/PMC10351170/ /pubmed/37461051 http://dx.doi.org/10.1186/s13059-023-03008-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Method
Grigorjew, Andreas
Gynter, Artur
Dias, Fernando H. C.
Buchfink, Benjamin
Drost, Hajk-Georg
Tomescu, Alexandru I.
Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD
title Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD
title_full Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD
title_fullStr Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD
title_full_unstemmed Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD
title_short Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD
title_sort sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using emerald
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10351170/
https://www.ncbi.nlm.nih.gov/pubmed/37461051
http://dx.doi.org/10.1186/s13059-023-03008-6
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