中国农业科技导报2026，Vol.28Issue(2)：55-62,8.DOI:10.13304/j.nykjdb.2024.0916
石松叶绿体基因组密码子偏好性分析及其与易混品种的分子鉴别
Codon Bias Analysis in Chloroplast Genome of Lycopodium japonicum and Molecular Identification with Its Analogues
摘要
Abstract
To investigate the preferences and influencing factors of codon usage in chloroplast genome of Lycopodium japonicum,and to offer a more scientific,molecular-based method for swiftly and precisely identifying Lycopodium japonicum,31 psbA-trnH sequences from 5 Lycopodium family were obtained from GenBank.Sequence alignment was performed using ClustalW,and MEGA11 was used to calculate intra-and inter-species K2P(kimura2-parameter)genetic distances and construct a phylogenetic tree.Additionally,mEMBOSS,CodonW and SPSS were utilized for neutral plot analysis,ENC-plot analysis,PR2-plot analysis,optimal codon screening and correspondence analysis of the CDS sequences.The results showed that the interspecific genetic distance between Lycopodium japonicum and its analogues was significantly greater than its intraspecific genetic distance.The phylogenetic tree indicated that each species could be independently branched,exhibiting good monophyly.The AU content in the third position of codon in chloroplast genome of Lycopodium japonicum was significantly higher than the GC content.The most of codons with RSCU(relative synonymous codon usage)>1 all ended with A/U,and Lycopodium japonicum had 9 optimal codons.The codon usage bias of chloroplast genome in Lycopodium japonicum was influenced by mutation pressure,natural selection and other factors.The psbA-trnH sequences were capable of accurately distinguishing among the 5 Lycopodium family.Above results provided molecular foundation for the identification of Lycopodium plants and their medicinal counterparts.关键词
石松/psbA-trnH/分子鉴别/密码子偏好性Key words
Lycopodium japonicum/psbA-trnH/molecular identification/codon bias分类
农业科技引用本文复制引用
郑梦迪,马向阳,尹念念,陈斯琪,冯言熙..石松叶绿体基因组密码子偏好性分析及其与易混品种的分子鉴别[J].中国农业科技导报,2026,28(2):55-62,8.基金项目
陕西省自然科学基础研究计划项目(2021JQ-782) （2021JQ-782）
西安医学院2022年度科研能力提升计划项目(2022NLTS084). （2022NLTS084）
