{"title":"BOPAL 2.0 and a study of tRNA and rRNA gene evolution in <i>Clostridium</i>.","authors":"Meghan Chua, Anthony Tan, Olivier Tremblay-Savard","doi":"10.1142/S0219720021400072","DOIUrl":null,"url":null,"abstract":"<p><p>We present BOPAL 2.0, an improved version of the BOPAL algorithm for the evolutionary history inference of tRNA and rRNA genes in bacterial genomes. Our approach can infer complete evolutionary scenarios and ancestral gene orders on a phylogeny and considers a wide range of events such as duplications, deletions, substitutions, inversions and transpositions. It is based on the fact that tRNA and rRNA genes are often organized in operons/clusters in bacteria, and this information is used to help identify orthologous genes for each genome comparison. BOPAL 2.0 introduces new features, such as a triple-wise alignment step, context-aware singleton matching and a second pass of the algorithm. Evaluation on simulated datasets shows that BOPAL 2.0 outperforms the original BOPAL in terms of the accuracy of inferred events and ancestral genomes. We also present a study of the tRNA/rRNA gene evolution in the <i>Clostridium</i> genus, in which the organization of these genes is very divergent. Our results indicate that tRNA and rRNA genes in <i>Clostridium</i> have evolved through numerous duplications, losses, transpositions and substitutions, but very few inversions were inferred.</p>","PeriodicalId":48910,"journal":{"name":"Journal of Bioinformatics and Computational Biology","volume":"19 6","pages":"2140007"},"PeriodicalIF":0.9000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Bioinformatics and Computational Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1142/S0219720021400072","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/11/13 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 1
Abstract
We present BOPAL 2.0, an improved version of the BOPAL algorithm for the evolutionary history inference of tRNA and rRNA genes in bacterial genomes. Our approach can infer complete evolutionary scenarios and ancestral gene orders on a phylogeny and considers a wide range of events such as duplications, deletions, substitutions, inversions and transpositions. It is based on the fact that tRNA and rRNA genes are often organized in operons/clusters in bacteria, and this information is used to help identify orthologous genes for each genome comparison. BOPAL 2.0 introduces new features, such as a triple-wise alignment step, context-aware singleton matching and a second pass of the algorithm. Evaluation on simulated datasets shows that BOPAL 2.0 outperforms the original BOPAL in terms of the accuracy of inferred events and ancestral genomes. We also present a study of the tRNA/rRNA gene evolution in the Clostridium genus, in which the organization of these genes is very divergent. Our results indicate that tRNA and rRNA genes in Clostridium have evolved through numerous duplications, losses, transpositions and substitutions, but very few inversions were inferred.
期刊介绍:
The Journal of Bioinformatics and Computational Biology aims to publish high quality, original research articles, expository tutorial papers and review papers as well as short, critical comments on technical issues associated with the analysis of cellular information.
The research papers will be technical presentations of new assertions, discoveries and tools, intended for a narrower specialist community. The tutorials, reviews and critical commentary will be targeted at a broader readership of biologists who are interested in using computers but are not knowledgeable about scientific computing, and equally, computer scientists who have an interest in biology but are not familiar with current thrusts nor the language of biology. Such carefully chosen tutorials and articles should greatly accelerate the rate of entry of these new creative scientists into the field.