Single-character insertion–deletion model preserves long indels in ancestral sequence reconstruction

Insertions and deletions (indels) play a significant role in genome evolution across species. Realistic modelling of indel evolution is challenging and is still an open research question. Several attempts have been made to explicitly model multi-character (long) indels, such as TKF92, by relaxing the site independence assumption and introducing fragments. However, these methods are computationally expensive. On the other hand, the Poisson Indel Process (PIP) assumes site independence but allows one to infer single-character indels on the phylogenetic tree, distinguishing insertions from deletions. PIP's marginal likelihood computation has linear time complexity, enabling ancestral sequence reconstruction (ASR) with indels in linear time. Recently, we developed ARPIP, an ASR method using PIP, capable of inferring indel events with explicit evolutionary interpretations. Here, we investigate the effect of the single-character indel assumption on reconstructed ancestral sequences on mammalian protein orthologs and on simulated data. We show that ARPIP's ancestral estimates preserve the gap length distribution observed in the input alignment. In mammalian proteins the lengths of inserted segments appear to be substantially longer compared to deleted segments. Further, we confirm the well-established deletion bias observed in real data. To date, ARPIP is the only ancestral reconstruction method that explicitly models insertion and deletion events over time. Given a good quality input alignment, it can capture ancestral long indel events on the phylogeny.

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Publication Details

Journal
BMC Bioinformatics
Published
2024-12-01
DOI
https://doi.org/10.1186/s12859-024-05986-1
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Single-character insertion–deletion model preserves long indels in ancestral sequence reconstruction

Jeļena Pečerska, Gholamhossein Jowkar, Maria Anisimova, Manuel Gil
BMC Bioinformatics
Genomics and Phylogenetic Studies
article

Single-character insertion–deletion model preserves long indels in ancestral sequence reconstruction

Jeļena Pečerska, Gholamhossein Jowkar, Maria Anisimova, Manuel Gil
article en

Abstract

Insertions and deletions (indels) play a significant role in genome evolution across species. Realistic modelling of indel evolution is challenging and is still an open research question. Several attempts have been made to explicitly model multi-character (long) indels, such as TKF92, by relaxing the site independence assumption and introducing fragments. However, these methods are computationally expensive. On the other hand, the Poisson Indel Process (PIP) assumes site independence but allows one to infer single-character indels on the phylogenetic tree, distinguishing insertions from deletions. PIP's marginal likelihood computation has linear time complexity, enabling ancestral sequence reconstruction (ASR) with indels in linear time. Recently, we developed ARPIP, an ASR method using PIP, capable of inferring indel events with explicit evolutionary interpretations. Here, we investigate the effect of the single-character indel assumption on reconstructed ancestral sequences on mammalian protein orthologs and on simulated data. We show that ARPIP's ancestral estimates preserve the gap length distribution observed in the input alignment. In mammalian proteins the lengths of inserted segments appear to be substantially longer compared to deleted segments. Further, we confirm the well-established deletion bias observed in real data. To date, ARPIP is the only ancestral reconstruction method that explicitly models insertion and deletion events over time. Given a good quality input alignment, it can capture ancestral long indel events on the phylogeny.

BMC BioinformaticsVol. 25(1)
SIB Swiss Institute of Bioinformatics (CH), ZHAW Zurich University of Applied Sciences (CH), University of Neuchâtel (CH)
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Life in Land
Openalex Percentile: Top 81%
Genomics and Phylogenetic Studies
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