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From pairwise to multiple spliced alignment

Authors :
Safa Jammali
Abigaïl Djossou
Wend-Yam D D Ouédraogo
Yannis Nevers
Ibrahim Chegrane
Aïda Ouangraoua
Source :
Bioinformatics Advances. 2
Publication Year :
2022
Publisher :
Oxford University Press (OUP), 2022.

Abstract

Motivation Alternative splicing is a ubiquitous process in eukaryotes that allows distinct transcripts to be produced from the same gene. Yet, the study of transcript evolution within a gene family is still in its infancy. One prerequisite for this study is the availability of methods to compare sets of transcripts while accounting for their splicing structure. In this context, we generalize the concept of pairwise spliced alignments (PSpAs) to multiple spliced alignments (MSpAs). MSpAs have several important purposes in addition to empowering the study of the evolution of transcripts. For instance, it is a key to improving the prediction of gene models, which is important to solve the growing problem of genome annotation. Despite its essentialness, a formal definition of the concept and methods to compute MSpAs are still lacking. Results We introduce the MSpA problem and the SplicedFamAlignMulti (SFAM) method, to compute the MSpA of a gene family. Like most multiple sequence alignment (MSA) methods that are generally greedy heuristic methods assembling pairwise alignments, SFAM combines all PSpAs of coding DNA sequences and gene sequences of a gene family into an MSpA. It produces a single structure that represents the superstructure and models of the gene family. Using real vertebrate and simulated gene family data, we illustrate the utility of SFAM for computing accurate gene family superstructures, MSAs, inferring splicing orthologous groups and improving gene-model annotations. Availability and implementation The supporting data and implementation of SFAM are freely available at https://github.com/UdeS-CoBIUS/SpliceFamAlignMulti. Supplementary information Supplementary data are available at Bioinformatics Advances online.

Subjects

Subjects :
General Medicine

Details

ISSN :
26350041
Volume :
2
Database :
OpenAIRE
Journal :
Bioinformatics Advances
Accession number :
edsair.doi...........228e1a5f3319d24e5d45ad6f2bf1de7e
Full Text :
https://doi.org/10.1093/bioadv/vbab044