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Codon usage pattern of the ancestor of green plants revealed through Rhodophyta.

Authors :
Yao, Huipeng
Li, Tingting
Ma, Zheng
Wang, Xiyuan
Xu, Lixiao
Zhang, Yuxin
Cai, Yi
Tang, Zizhong
Source :
BMC Genomics. 9/11/2023, Vol. 24 Issue 1, p1-12. 12p.
Publication Year :
2023

Abstract

Rhodophyta are among the closest known relatives of green plants. Studying the codons of their genomes can help us understand the codon usage pattern and characteristics of the ancestor of green plants. By studying the codon usage pattern of all available red algae, it was found that although there are some differences among species, high-bias genes in most red algae prefer codons ending with GC. Correlation analysis, Nc-GC3s plots, parity rule 2 plots, neutrality plot analysis, differential protein region analysis and comparison of the nucleotide content of introns and flanking sequences showed that the bias phenomenon is likely to be influenced by local mutation pressure and natural selection, the latter of which is the dominant factor in terms of translation accuracy and efficiency. It is worth noting that selection on translation accuracy could even be detected in the low-bias genes of individual species. In addition, we identified 15 common optimal codons in seven red algae except for G. sulphuraria for the first time, most of which were found to be complementary and bound to the tRNA genes with the highest copy number. Interestingly, tRNA modification was found for the highly degenerate amino acids of all multicellular red algae and individual unicellular red algae, which indicates that highly biased genes tend to use modified tRNA in translation. Our research not only lays a foundation for exploring the characteristics of codon usage of the red algae as green plant ancestors, but will also facilitate the design and performance of transgenic work in some economic red algae in the future. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14712164
Volume :
24
Issue :
1
Database :
Academic Search Index
Journal :
BMC Genomics
Publication Type :
Academic Journal
Accession number :
171883079
Full Text :
https://doi.org/10.1186/s12864-023-09586-w