浙江农林大学学报2024，Vol.41Issue(4)：696-705,10.DOI:10.11833/j.issn.2095-0756.20230498
梁山慈竹叶绿体基因组密码子偏好性分析
Analysis of codon preference in chloroplast genome of Dendrocalamus farinosus
摘要
Abstract
[Objective]The objective is to explore the preferred usage patterns of chloroplast genome codon in Dendrocalamus farinosus,analyze the main reasons affecting the codon usage preference of D.farinosus,and determine the optimal codon,so as to provide reference for chloroplast genomics research in Bambusoideae plants.[Method]According to the GenBank login number MZ681865.156,85 chloroplast gene sequences of D.farinosus were downloaded from National Center for Biotechnology Information(NCBI)database in the United States.CodonW,CUSP and R language software were used to analyze the effective number of codons(ENC),adaptation index(CAI)and relative synonymous codon usage(RSCU).Correspondence analysis of RSCU was performed and the codons were sorted based on ENC and RSCU values.[Result]The average ratio of guanine(G)and cytosine(C)in the chloroplast genome codon(GC ratio)was 39.48％,with GC1(47.69％)＞GC2(39.70％)＞GC3(31.05％),and the last codon base preferred to end in A/U.The majority of ENC value was above 35,and CAI value was 0.167,so the codon preference was weak.Neutral plot analysis,ENC-plot and PR2-plot analysis showed that natural selection was the main factor affecting the codon preference of the chloroplast genome of D.farinosus.A total of 18 codons,including GCA,GCU,UUC,and GGU,were identified as the optimal codons for the chloroplast genome of D.farinosus.[Conclusion]Natural selection is the main factor contributing to the codon preference of the chloroplast genome in D.farinosus,and 18 optimal codons such as GCU,GAU,and GGU are screened for the chloroplast genome of D.farinosus.[Ch,5 fig.5 tab.30 ref.]关键词
梁山慈竹/密码子偏好性/叶绿体基因组/最优密码子Key words
Dendrocalamus farinosus/codon preference/chloroplast genome/optimal codons分类
农业科技引用本文复制引用
魏亚楠,龚明贵,白娜,苏佳杰,姜霞..梁山慈竹叶绿体基因组密码子偏好性分析[J].浙江农林大学学报,2024,41(4):696-705,10.基金项目
贵州省林业局资助项目(黔林科合[2019]06号) （黔林科合[2019]06号）
国家自然科学基金资助项目(31860178) （31860178）
