巨桉叶绿体基因组密码子偏好性分析

Analysis of codon bias of chloroplast genome in Eucalyptus grandis

该文针对巨桉叶绿体基因组序列,选取其中长于300 nt且以AUG为起始密码子的43个非重复基因作为研究对象,采用CodonW1.4.2软件分析巨桉叶绿体基因组的密码子使用偏好性。结果表明:第3位密码子的平均GC含量为27.97%;ENC的变化范围为39.49~61.00,平均为47.04;RSCU>1的密码子有31个,其中29个以A/U结尾;中性分析显示,GC12与GC3无显著相关;回归分析未达到显著性水平;ENC-plot分析发现,大部分基因落在曲线上或附近;对应分析表明第1轴的贡献率为17.68%,第2轴的贡献率为11.49%,第3轴、第4轴的贡献率分别为8.00%和5.76%,前4轴累计贡献率达42.93%,第1轴与GC、ENC、CAI达到极显著相关。上述分析结果表明,巨桉叶绿体基因组的密码子偏好较弱,密码子第3位偏好以A或U结尾,选择和突变在巨桉叶绿体基因组密码子偏好中起相对均衡的作用,最终确定UUG、CUU、GUU、UCC、UCA、ACA、UAU、UAA、CAU、AAU、AGA和GGA 12个高频高表达密码子为最优密码子。这为转化叶绿体基因密码子优化,提高表达效率和改良巨桉目标性状奠定了坚实基础。

In this study,analysis of codon bias was carried out using CodonW 1.4.2 software,with chloroplast genome of Eucalyptus grandis as material and 43 non-repeated genes beginning with AUG as objects.The results showed that the average GC content in the 3rd position was 27.97%;ENC ranged from 39.49 to 61.00 with an average of 47.04;there were 31 codons whose RSCU were more than 1.00 in the chloroplast genome;of which,29 codons ended with A/U;neutral plot analysis showed correction and regression analysis between GC12 and GC3 were not significant;ENC-plot revealed most genes were located along or near the standard curve;correspondence analysis indicated the 1st axis accounted for 17.68%contribution,the 2nd axis 11.49%,the rest axes accounted for 8.00%and 5.76%and the first four axes accounted for 42.93%in total;the correction between the 1st axis and the parameters such as GC,ENC and CAI was extremely significant.The results mentioned above revealed that the codon bias level was low in the chloroplast genome and the 3 rd codons always end with A/U and codon bias might be determined by both mutation and selection nearly equally.Finally,twelve codons that were not only highly expressed but frequently were determined as the optimal codons including UUG,CUU,GUU,UCC,UCA,ACA,UAU,UAA,CAU,AAU,AGA and GGA.This study will provide a solid foundation for codon optimization of the genes transformed into chloroplast genome and future increasing the expression efficiency for improvement of important traits.