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Analysis of codon usage patterns in citrus based on coding sequence data
BACKGROUND: Codon usage is an important determinant of gene expression levels that can help us understand codon biology, evolution and mRNA translation of species. The majority of previous codon usage studies have focused on single species analysis, although few studies have focused on the species w...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7739459/ https://www.ncbi.nlm.nih.gov/pubmed/33327935 http://dx.doi.org/10.1186/s12864-020-6641-x |
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author | Shen, Zenan Gan, Zhimeng Zhang, Fa Yi, Xinyao Zhang, Jinzhi Wan, Xiaohua |
author_facet | Shen, Zenan Gan, Zhimeng Zhang, Fa Yi, Xinyao Zhang, Jinzhi Wan, Xiaohua |
author_sort | Shen, Zenan |
collection | PubMed |
description | BACKGROUND: Codon usage is an important determinant of gene expression levels that can help us understand codon biology, evolution and mRNA translation of species. The majority of previous codon usage studies have focused on single species analysis, although few studies have focused on the species within the same genus. In this study, we proposed a multispecies codon usage analysis workflow to reveal the genetic features and correlation in citrus. RESULTS: Our codon usage analysis workflow was based on the GC content, GC plot, and relative synonymous codon usage value of each codon in 8 citrus species. This approach allows for the comparison of codon usage bias of different citrus species. Next, we performed cluster analysis and obtained an overview of the relationship in citrus. However, traditional methods cannot conduct quantitative analysis of the correlation. To further estimate the correlation among the citrus species, we used the frequency profile to construct feature vectors of each species. The Pearson correlation coefficient was used to quantitatively analyze the distance among the citrus species. This result was consistent with the cluster analysis. CONCLUSIONS: Our findings showed that the citrus species are conserved at the genetic level and demonstrated the existing genetic evolutionary relationship in citrus. This work provides new insights into codon biology and the evolution of citrus and other plant species. |
format | Online Article Text |
id | pubmed-7739459 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-77394592020-12-17 Analysis of codon usage patterns in citrus based on coding sequence data Shen, Zenan Gan, Zhimeng Zhang, Fa Yi, Xinyao Zhang, Jinzhi Wan, Xiaohua BMC Genomics Research BACKGROUND: Codon usage is an important determinant of gene expression levels that can help us understand codon biology, evolution and mRNA translation of species. The majority of previous codon usage studies have focused on single species analysis, although few studies have focused on the species within the same genus. In this study, we proposed a multispecies codon usage analysis workflow to reveal the genetic features and correlation in citrus. RESULTS: Our codon usage analysis workflow was based on the GC content, GC plot, and relative synonymous codon usage value of each codon in 8 citrus species. This approach allows for the comparison of codon usage bias of different citrus species. Next, we performed cluster analysis and obtained an overview of the relationship in citrus. However, traditional methods cannot conduct quantitative analysis of the correlation. To further estimate the correlation among the citrus species, we used the frequency profile to construct feature vectors of each species. The Pearson correlation coefficient was used to quantitatively analyze the distance among the citrus species. This result was consistent with the cluster analysis. CONCLUSIONS: Our findings showed that the citrus species are conserved at the genetic level and demonstrated the existing genetic evolutionary relationship in citrus. This work provides new insights into codon biology and the evolution of citrus and other plant species. BioMed Central 2020-12-16 /pmc/articles/PMC7739459/ /pubmed/33327935 http://dx.doi.org/10.1186/s12864-020-6641-x 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 Shen, Zenan Gan, Zhimeng Zhang, Fa Yi, Xinyao Zhang, Jinzhi Wan, Xiaohua Analysis of codon usage patterns in citrus based on coding sequence data |
title | Analysis of codon usage patterns in citrus based on coding sequence data |
title_full | Analysis of codon usage patterns in citrus based on coding sequence data |
title_fullStr | Analysis of codon usage patterns in citrus based on coding sequence data |
title_full_unstemmed | Analysis of codon usage patterns in citrus based on coding sequence data |
title_short | Analysis of codon usage patterns in citrus based on coding sequence data |
title_sort | analysis of codon usage patterns in citrus based on coding sequence data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7739459/ https://www.ncbi.nlm.nih.gov/pubmed/33327935 http://dx.doi.org/10.1186/s12864-020-6641-x |
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