为了验证作者建立的葡萄(Vitis vinifera L.)基因电子表达分析平台在葡萄果实发育相关基因的表达预测及特定序列快速检索等方面的应用效果,利用NCBI上公布的大量葡萄EST序列及半定量PCR和RT-PCR技术,对葡萄不同器官中VvANR、VvCHI、VvCHS2和VvDFR基因的表达分析预测结果进行验证,并对该平台具有的特定序列快速检索功能进行了简介。预测结果表明:葡萄各器官中VvANR、VvCHI、VvCHS2和VvDFR基因的无冗余EST序列数量均较多,分别为33条、36条、55条和46条;4个基因的表达量有一定差异,VvANR在花序和芽中表达量较高,VvCHI在花序、果实和芽中表达量较高,VvCHS2在果实、芽、花序和花中表达量较高,VvDFR在花序、芽、花、果实和根中表达量均较高。半定量PCR和RT-PCR实验结果显示:VvANR主要在花序、花和小果中表达;VvCHI主要在小果、花、茎和花序中表达;VvCHS2主要在茎、花序、花和小果中表达;VvDFR在各组织中表达量从高至低依次排序为花、花序、茎、叶、小果、中果、大果。验证结果表明:采用葡萄基因电子表达分析平台识别表达量较高的组织时,平台的预测结果与实验结果基本一致;而在预测一些表达量较低的组织时效果较差。应用该平台、通过5个步骤,可以简便、快速检索出特定组织或特定状况下的特定cDNA文库信息。

In order to verify the application effect of gene in-silico expression analysis platform. for grape ( Vitis vinifera L．) on expression prediction and rapid retrieval of specific sequences of fruit development genes， the prediction result on expression of four genes including VvANR， VvCHI， VvCHS2 and VvDFR in different tissues of V． vinifera was verified by means of mass ESTs on NCBI and technology of RT-PCR and semi-quantitative PCR． And the brief introduction of the platform. function on rapid retrieval of specific sequences was carried out， too． The prediction results show that numbers of non-redundant ESTs of VvANR， VvCHI， VvCHS2 and VvDFR in different tissues of V． vinifera are all much more with sequences of 33， 36， 55 and 46， respectively． The expression amount of four genes has a certain difference， in which， the expression amount of VvANR is relatively high in inflorescence and bud， that of VvCHI relatively high in inflorescence， fruit and bud， that of VvCHS2 relatively high in fruit， bud， inflorescence and flower， while that of VvDFR relatively high in inflorescence， bud， flower， fruit and root． The results of semi-quantitative PCR and RT-PCR show that VvANR mainly expresses in inflorescence， flower and small-sized fruit， VvCHI predominantly in small-sized fruit， flower， shoot and inflorescence， VvCHS2 primarily in shoot， inflorescence， flower and small-sized fruit， and the order of VvDFR expression from high to low is flower， inflorescence， shoot， leaf， small-sized fruit， medium-sized fruit， big-sized fruit． The verification result indicates that the platform. prediction result is basically in accordance with the experiment result in recognizing tissues with high expression， but it is not quite effective in predicting tissues with low expression． The information of specific cDNA libraries in specific tissues or status can be easily and quickly retrieved through five steps with this platform．