Cargando…
Operon-based approach for the inference of rRNA and tRNA evolutionary histories in bacteria
BACKGROUND: In bacterial genomes, rRNA and tRNA genes are often organized into operons, i.e. segments of closely located genes that share a single promoter and are transcribed as a single unit. Analyzing how these genes and operons evolve can help us understand what are the most common evolutionary...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7160887/ https://www.ncbi.nlm.nih.gov/pubmed/32299351 http://dx.doi.org/10.1186/s12864-020-6612-2 |
_version_ | 1783522841427181568 |
---|---|
author | Pawliszak, Tomasz Chua, Meghan Leung, Carson K. Tremblay-Savard, Olivier |
author_facet | Pawliszak, Tomasz Chua, Meghan Leung, Carson K. Tremblay-Savard, Olivier |
author_sort | Pawliszak, Tomasz |
collection | PubMed |
description | BACKGROUND: In bacterial genomes, rRNA and tRNA genes are often organized into operons, i.e. segments of closely located genes that share a single promoter and are transcribed as a single unit. Analyzing how these genes and operons evolve can help us understand what are the most common evolutionary events affecting them and give us a better picture of ancestral codon usage and protein synthesis. RESULTS: We introduce BOPAL, a new approach for the inference of evolutionary histories of rRNA and tRNA genes in bacteria, which is based on the identification of orthologous operons. Since operons can move around in the genome but are rarely transformed (e.g. rarely broken into different parts), this approach allows for a better inference of orthologous genes in genomes that have been affected by many rearrangements, which in turn helps with the inference of more realistic evolutionary scenarios and ancestors. CONCLUSIONS: From our comparisons of BOPAL with other gene order alignment programs using simulated data, we have found that BOPAL infers evolutionary events and ancestral gene orders more accurately than other methods based on alignments. An analysis of 12 Bacillus genomes also showed that BOPAL performs just as well as other programs at building ancestral histories in a minimal amount of events. |
format | Online Article Text |
id | pubmed-7160887 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-71608872020-04-21 Operon-based approach for the inference of rRNA and tRNA evolutionary histories in bacteria Pawliszak, Tomasz Chua, Meghan Leung, Carson K. Tremblay-Savard, Olivier BMC Genomics Research BACKGROUND: In bacterial genomes, rRNA and tRNA genes are often organized into operons, i.e. segments of closely located genes that share a single promoter and are transcribed as a single unit. Analyzing how these genes and operons evolve can help us understand what are the most common evolutionary events affecting them and give us a better picture of ancestral codon usage and protein synthesis. RESULTS: We introduce BOPAL, a new approach for the inference of evolutionary histories of rRNA and tRNA genes in bacteria, which is based on the identification of orthologous operons. Since operons can move around in the genome but are rarely transformed (e.g. rarely broken into different parts), this approach allows for a better inference of orthologous genes in genomes that have been affected by many rearrangements, which in turn helps with the inference of more realistic evolutionary scenarios and ancestors. CONCLUSIONS: From our comparisons of BOPAL with other gene order alignment programs using simulated data, we have found that BOPAL infers evolutionary events and ancestral gene orders more accurately than other methods based on alignments. An analysis of 12 Bacillus genomes also showed that BOPAL performs just as well as other programs at building ancestral histories in a minimal amount of events. BioMed Central 2020-04-16 /pmc/articles/PMC7160887/ /pubmed/32299351 http://dx.doi.org/10.1186/s12864-020-6612-2 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Pawliszak, Tomasz Chua, Meghan Leung, Carson K. Tremblay-Savard, Olivier Operon-based approach for the inference of rRNA and tRNA evolutionary histories in bacteria |
title | Operon-based approach for the inference of rRNA and tRNA evolutionary histories in bacteria |
title_full | Operon-based approach for the inference of rRNA and tRNA evolutionary histories in bacteria |
title_fullStr | Operon-based approach for the inference of rRNA and tRNA evolutionary histories in bacteria |
title_full_unstemmed | Operon-based approach for the inference of rRNA and tRNA evolutionary histories in bacteria |
title_short | Operon-based approach for the inference of rRNA and tRNA evolutionary histories in bacteria |
title_sort | operon-based approach for the inference of rrna and trna evolutionary histories in bacteria |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7160887/ https://www.ncbi.nlm.nih.gov/pubmed/32299351 http://dx.doi.org/10.1186/s12864-020-6612-2 |
work_keys_str_mv | AT pawliszaktomasz operonbasedapproachfortheinferenceofrrnaandtrnaevolutionaryhistoriesinbacteria AT chuameghan operonbasedapproachfortheinferenceofrrnaandtrnaevolutionaryhistoriesinbacteria AT leungcarsonk operonbasedapproachfortheinferenceofrrnaandtrnaevolutionaryhistoriesinbacteria AT tremblaysavardolivier operonbasedapproachfortheinferenceofrrnaandtrnaevolutionaryhistoriesinbacteria |