SimSpliceEvol: alternative splicing-aware simulation of biological sequence evolution

• Published in: BMC bioinformatics Vol. 20; no. Suppl 20; pp. 640 - 13
• Main Authors: Kuitche, Esaie, Jammali, Safa, Ouangraoua, Aïda
• Format: Journal Article
• Language: English
• Published: London BioMed Central 17.12.2019; BioMed Central Ltd; Springer Nature B.V; BMC
• Subjects: Algorithms; Alignment; Alternative splicing; Alternative Splicing - genetics; Analysis; Animals; Base Sequence; Bioinformatics; Biological evolution; Biomedical and Life Sciences; Branches; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Computer Simulation; DNA, Complementary - genetics; Evolution; Evolution, Molecular; Evolutionary genetics; Exon-intron structure; Exons; Exons - genetics; Genes; Genetic research; Humans; Inference; Introns - genetics; Life Sciences; Markov Chains; Microarrays; Nucleotide sequence; Orthology; Phylogeny; Probability; Proteins; Ribonucleic acid; RNA; RNA, Messenger - genetics; RNA, Messenger - metabolism; Simulation; Software; Source code; Splicing; Test procedures; Transcription; Alternative splicing; Evolution; Simulation; Exon-intron structure
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-019-3207-5

Background It is now well established that eukaryotic coding genes have the ability to produce more than one type of transcript thanks to the mechanisms of alternative splicing and alternative transcription. Because of the lack of gold standard real data on alternative splicing, simulated data constitute a good option for evaluating the accuracy and the efficiency of methods developed for splice-aware sequence analysis. However, existing sequence evolution simulation methods do not model alternative splicing, and so they can not be used to test spliced sequence analysis methods. Results We propose a new method called SimSpliceEvol for simulating the evolution of sets of alternative transcripts along the branches of an input gene tree. In addition to traditional sequence evolution events, the simulation also includes gene exon-intron structure evolution events and alternative splicing events that modify the sets of transcripts produced from genes. SimSpliceEvol was implemented in Python. The source code is freely available at https://github.com/UdeS-CoBIUS/SimSpliceEvol . Conclusions Data generated using SimSpliceEvol are useful for testing spliced RNA sequence analysis methods such as methods for spliced alignment of cDNA and genomic sequences, multiple cDNA alignment, orthologous exons identification, splicing orthology inference, transcript phylogeny inference, which requires to know the real evolutionary relationships between the sequences.