Suppr超能文献

酿酒酵母基因表达转录与翻译控制之间的关系:多元回归分析

Relationships between transcriptional and translational control of gene expression in Saccharomyces cerevisiae: a multiple regression analysis.

作者信息

Pavesi A

机构信息

Department of Evolutionary and Functional Biology, University of Parma, Viale delle Scienze, I-43100 Parma, Italy.

出版信息

J Mol Evol. 1999 Feb;48(2):133-41. doi: 10.1007/pl00006451.

Abstract

Natural selection for an increased translation efficiency has been proposed as the main determinant for the bias in codon usage observed in many genes of Saccharomyces cerevisiae. Recently, the efficiency of transcription of a large number of yeast genes has been determined, based on the cellular content of the respective mRNAs: this provides an additional dimension to the study of the multisep process of gene expression. Using a representative set of yeast genes with a known level of transcription, the relationship between transcriptional and translational steps was evaluated by a multiple linear regression model. This analysis demonstrated a positive correlation between the amount of transcript, given as the number of mRNA copies per cell for each individual gene, and indices evaluating the effects of translational selection on the corresponding codon usage pattern. This finding suggests a close association of the cellular mRNA content, regulated also at the transcriptional level, to its efficiency of translation, mediated by a fine-tuning of codon usage strategy. Moreover, multiple regression analysis demonstrated that the transcription level of a gene can be approximately predicted using indices of bias deriving from its nucleotide sequence. This allowed for an extensive investigation of uncharacterized regions of the complete genome sequence of S. cerevisiae, to detect new potential short protein coding genes that were not considered by previous searching procedures. Several small open reading frames exhibiting a statistically significant coding potential were thus identified as good candidates for functional analysis.

摘要

自然选择导致翻译效率提高,这被认为是酿酒酵母许多基因中观察到的密码子使用偏好的主要决定因素。最近,基于各自mRNA的细胞含量,已经确定了大量酵母基因的转录效率:这为基因表达多步骤过程的研究提供了一个新的维度。使用一组具有已知转录水平的代表性酵母基因,通过多元线性回归模型评估转录步骤与翻译步骤之间的关系。该分析表明,以每个基因每个细胞的mRNA拷贝数表示的转录本数量与评估翻译选择对相应密码子使用模式影响的指标之间存在正相关。这一发现表明,在转录水平也受到调控的细胞mRNA含量与其翻译效率密切相关,这种相关性是由密码子使用策略的微调介导的。此外,多元回归分析表明,可以使用从其核苷酸序列得出的偏好指标大致预测基因的转录水平。这使得能够对酿酒酵母完整基因组序列的未表征区域进行广泛研究,以检测以前的搜索程序未考虑到的新的潜在短蛋白编码基因。因此,几个显示出具有统计学意义编码潜力的小开放阅读框被确定为功能分析的良好候选对象。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验