中文摘要：

在学习 mRNA 表示的一个关键假设是它在蛋白质表示的预言是增进知识的。然而，仅仅有限的研究在酵母探索了 mRNA 蛋白质表示关联或人的纸巾和结果是相对不一致的。我们从 30 个无关的女人在刚孤立的人的传播单核白血球在 mRNA 蛋白质表情上执行了关联分析。为 71 基因的表示蛋白质被确定并且由结合的 2-D 电气泳动识别了集体 spectrometry。相应 mRNA 表达式被 Affymetrix 基因芯片确定。重要关联(r=0.235， P < 0.0001 ) 包括所有学习基因和所有样品为整个数据集被观察。关联在基因本体论的不同生物范畴变化了。例如，最高的关联以细胞的部件为细胞外的区域的基因被完成(r=0.643， P < 0.0001 ) 并且最低关联为规定的基因被获得(r=0.099， P=0.213 ) 以生物过程。在染色体，样品的一半证明为 71 基因的重要积极关联和重要关联在所有样品在平均 mRNA 和平均蛋白质表示层次之间被发现(r=0.296， P < 0.01 ) 。在学习组水平，然而，仅仅五学习基因越过所有样品有重要积极关联。我们的结果显示出在 mRNA 和蛋白质表示层次之间的全面积极关联。然而，中等、变化的关联建议那 mRNA 表情可能有时是有用的，但是远非当然在预言蛋白质表示层次完善。

英文摘要：

A key assumption in studying mRNA expression is that it is informative in the prediction of protein expression. However, only limited studies have explored the mRNA-protein expression correlation in yeast or human tissues and the results have been relatively inconsistent. We carried out correlation analyses on mRNA-protein expressions in freshly isolated human circulating monocytes from 30 unrelated women. The expressed proteins for 71 genes were quantified and identified by 2-D electrophoresis coupled with mass spectrometry. The corresponding mRNA expressions were quantified by Affymetrix gene chips. Significant correlation （r=0.235, P〈0.0001） was observed for the whole dataset including all studied genes and all samples. The correlations varied in different biological categories of gene ontology. For example, the highest correlation was achieved for genes of the extracellular region in terms of cellular component （r=0.643, P〈0.0001） and the lowest correlation was obtained for genes of regulation （r=0.099, P=0.213） in terms of biological process. In the genome, haffof the samples showed significant positive correlation for the 71 genes and significant correlation was found between the average mRNA and the average protein expression levels in all samples （r=0.296, P〈0.01）. However, at the study group level, only five studied genes had significant positive correlation across all the samples. Our results showed an overall positive correlation between mRNA and protein expression levels. However, the moderate and varied correlations suggest that mRNA expression might be sometimes useful, but certainly far from perfect, in predicting protein expression levels.