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Codon usage bias and phylogenetic analysis of chloroplast genome in 36 gracilariaceae species
Functional & Integrative Genomics ( IF 2.9 ) Pub Date : 2024-03-01 , DOI: 10.1007/s10142-024-01316-z
Tingting Li , Zheng Ma , Tiemei Ding , Yanxin Yang , Fei Wang , Xinjing Wan , Fangyun Liang , Xi Chen , Huipeng Yao

Gracilariaceae is a group of marine large red algae and main source of agar with important economic and ecological value. The codon usage patterns of chloroplast genomes in 36 species from Graciliaceae show that GC range from 0.284 to 0.335, the average GC3 range from 0.135 to 0.243 and the value of ENC range from 35.098 to 42.327, which indicates these genomes are rich in AT and prefer to use codons ending with AT in these species. Nc plot, PR2 plot, neutrality plot analyses and correlation analysis indicate that these biases may be caused by multiple factors, such as natural selection and mutation pressure, but prolonged natural selection is the main driving force influencing codon usage preference. The cluster analysis and phylogenetic analysis show that the differentiation relationship of them is different and indicate that codons with weak or unbiased preferences may also play an irreplaceable role in these species’ evolution. In addition, we identified 26 common high-frequency codons and 8–18 optimal codons all ending in A/U in these 36 species. Our results will not only contribute to carrying out transgenic work in Gracilariaceae species to maximize the protein yield in the future, but also lay a theoretical foundation for further exploring systematic classification of them.



中文翻译:

36个江蓠科植物叶绿体基因组密码子使用偏倚及系统发育分析

江蓠科是一类海洋大型红藻类,是琼脂的主要来源,具有重要的经济和生态价值。江蓠科 36 个物种叶绿体基因组密码子使用模式显示,GC 范围为 0.284 至 0.335,平均 GC3 范围为 0.135 至 0.243,ENC 值范围为 35.098 至 42.327,这表明这些基因组富含 AT,并且更喜欢使用密码子。在这些物种中使用以 AT 结尾的密码子。Nc图、PR2图、中性图分析和相关分析表明这些偏差可能是由自然选择和突变压力等多种因素引起的,但长期自然选择是影响密码子使用偏好的主要驱动力。聚类分析和系统发育分析表明它们的分化关系不同,表明具有弱偏好或无偏偏好的密码子也可能在这些物种的进化中发挥不可替代的作用。此外,我们还确定了这 36 个物种中的 26 个常见高频密码子和 8-18 个最佳密码子,全部以 A/U 结尾。我们的研究结果不仅有助于未来在江蓠科物种中开展转基因工作以最大限度地提高蛋白质产量,而且为进一步探索其系统分类奠定理论基础。

更新日期:2024-03-03
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