Evidence map›Paper›PMID 38842253›Full record

ArticleMolecular biology and evolution2024

Please Mind the Gap: Indel-Aware Parsimony for Fast and Accurate Ancestral Sequence Reconstruction and Multiple Sequence Alignment Including Long Indels.

Clara Iglhaut, Jūlija Pečerska, Manuel Gil, Maria Anisimova

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Article in Molecular biology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

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10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Clara IglhautInstitute of Computational Life Science, Zurich University of Applied Science, Wädenswil, Switzerland.ORCID 0009-0009-8022-3012
Jūlija PečerskaInstitute of Computational Life Science, Zurich University of Applied Science, Wädenswil, Switzerland.ORCID 0000-0002-3499-6200
Manuel GilInstitute of Computational Life Science, Zurich University of Applied Science, Wädenswil, Switzerland.ORCID 0000-0001-7089-6285
Maria AnisimovaInstitute of Computational Life Science, Zurich University of Applied Science, Wädenswil, Switzerland.ORCID 0000-0001-8145-7966

Funding

Swiss National Science Foundation 315230_215379
6 · The paper itself

Abstract

Despite having important biological implications, insertion, and deletion (indel) events are often disregarded or mishandled during phylogenetic inference. In multiple sequence alignment, indels are represented as gaps and are estimated without considering the distinct evolutionary history of insertions and deletions. Consequently, indels are usually excluded from subsequent inference steps, such as ancestral sequence reconstruction and phylogenetic tree search. Here, we introduce indel-aware parsimony (indelMaP), a novel way to treat gaps under the parsimony criterion by considering insertions and deletions as separate evolutionary events and accounting for long indels. By identifying the precise location of an evolutionary event on the tree, we can separate overlapping indel events and use affine gap penalties for long indel modeling. Our indel-aware approach harnesses the phylogenetic signal from indels, including them into all inference stages. Validation and comparison to state-of-the-art inference tools on simulated data show that indelMaP is most suitable for densely sampled datasets with closely to moderately related sequences, where it can reach alignment quality comparable to probabilistic methods and accurately infer ancestral sequences, including indel patterns. Due to its remarkable speed, our method is well suited for epidemiological datasets, eliminating the need for downsampling and enabling the exploitation of the additional information provided by dense taxonomic sampling. Moreover, indelMaP offers new insights into the indel patterns of biologically significant sequences and advances our understanding of genetic variability by considering gaps as crucial evolutionary signals rather than mere artefacts.

Indexed as

INDEL MutationPhylogenySequence AlignmentEvolution, MolecularHumansModels, Geneticancestral sequence reconstructionindel-awarelong indel reconstructionmultiple sequence alignmentparsimony

Identifiers

PMID38842253
PMCPMC11221656

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.