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

Andreas Grigorjew; Artur Gynter; Fernando H. C Dias; Benjamin Buchfink; Hajk-Georg Drost; Alexandru I. Tomescu

doi:10.1186/s13059-023-03008-6

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

Andreas Grigorjew, Artur Gynter, Fernando H. C Dias, Benjamin Buchfink, Hajk-Georg Drost (Lead / Corresponding author), Alexandru I. Tomescu (Lead / Corresponding author)

Computational Biology

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Abstract

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.

Original language	English
Article number	168
Number of pages	21
Journal	Genome Biology
Volume	24
DOIs	https://doi.org/10.1186/s13059-023-03008-6
Publication status	Published - 17 Jul 2023

Keywords

Dynamic programming
Needleman-Wunsch algorithm
Protein folding
Sequence alignment
Suboptimal alignments

ASJC Scopus subject areas

Ecology, Evolution, Behavior and Systematics
Genetics
Cell Biology

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10.1186/s13059-023-03008-6Licence: CC BY

Final published versionFinal published version, 3.72 MBLicence: CC BY

Cite this

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title = "Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD",

abstract = "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.",

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AU - Tomescu, Alexandru I.

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AB - 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.

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KW - Needleman-Wunsch algorithm

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

Abstract

Keywords

ASJC Scopus subject areas

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