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Analysis of codon usage patterns in 48 Aconitum species.

Authors :
Yang, Meihua
Liu, Jiahao
Yang, Wanqing
Li, Zhen
Hai, Yonglin
Duan, Baozhong
Zhang, Haizhu
Yang, Xiaoli
Xia, Conglong
Source :
BMC Genomics. 8/16/2023, Vol. 24 Issue 1, p1-13. 13p.
Publication Year :
2023

Abstract

Background: The Aconitum genus is a crucial member of the Ranunculaceae family. There are 350 Aconitum species worldwide, with about 170 species found in China. These species are known for their various pharmacological effects and are commonly used to treat joint pain, cold abdominal pain, and other ailments. Codon usage bias (CUB) analysis contributes to evolutionary relationships and phylogeny. Based on protein-coding sequences (PCGs), we selected 48 species of Aconitum for CUB analysis. Results: The results revealed that Aconitum species had less than 50% GC content. Furthermore, the distribution of GC content was irregular and followed a trend of GC1 > GC2 > GC3, indicating a bias towards A/T bases. The relative synonymous codon usage (RSCU) heat map revealed the presence of conservative codons with slight variations within the genus. The effective number of codons (ENC)-Plot and the parity rule 2 (PR2)-bias plot analysis indicate that natural selection is the primary factor influencing the variation in codon usage. As a result, we screened various optimal codons and found that A/T bases were preferred as the last codon. Furthermore, our Maximum Likelihood (ML) analysis based on PCGs among 48 Aconitum species yielded results consistent with those obtained from complete chloroplast (cp.) genome data. This suggests that analyzing mutation in PCGs is an efficient method for demonstrating the phylogeny of species at the genus level. Conclusions: The CUB analysis of 48 species of Aconitum was mainly influenced by natural selection. This study reveals the CUB pattern of Aconitum and lays the foundation for future genetic modification and phylogenetic analyses. [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 :
173840008
Full Text :
https://doi.org/10.1186/s12864-023-09650-5