利用GenBank中大量葡萄EST序列分离有效基因的电子表达分析平台

 【目的】充分利用GenBank上的大量葡萄EST序列，建立本地化基因电子表达分析平台，实现基因表达模式的大规模快速分析。【方法】利用生物信息学方法对GenBank上的362 193条葡萄EST序列进行本地化及后续处理，建立电子分析平台，并通过RT-PCR技术对其电子分析准确性进行验证。【结果】建立了包含叶、花等11个组织类别和GA3等5个胁迫类型的基因电子表达分析平台。通过VvAG、VvCHS、VvF3H、VvLDOX等4个葡萄基因的RT-PCR和电子表达分析结果比较发现，平台预测效率较高，在预测EST来源数较多的果实、花序、花组织的表达效果较好，而对叶等EST来源较少的组织的预测效果需结合试验判断。随着dbEST库中源于葡萄各组织EST序列数量的大量增加，平台的预测效果将更加符合基因表达的实际情况。【结论】葡萄基因电子表达分析平台预测效率较高，为葡萄基因大规模快速表达分析以及重要相关信息的挖掘提供了很好的分析工具。

Isolation of Effective Genes with Digital Northern Platform of NCBI Grapevine (Vitis vinifera L.) EST Sequences

【Objective】The objective of the study is to take full advantage of mass grapevine (Vitis vinifera L.) expression sequence tags (ESTs) from NCBI database, establish localization digital platform for grapevine genes, and achieve the purpose of rapid large-scale gene expression analysis.【Method】A total of 362 193 grapevine ESTs were downloaded from GenBank, processed further by bioinformatics methods, and used to build the digital Northern platform. The verification of the accuracy of the electronic analysis was done by quantitative RT-PCR technique.【Result】The digital northern platform for eleven tissues and those under five stress conditions were effectively established. The comparison of the results from qRT-PCR of four grape genes (VvAG, VvCHS, VvF3H, VvLDOX) and the corresponding electronic expression analysis data indicated that the predictive efficiency of this platform was high. The efficiency of expression prediction in the organs and tissues (berry, inflorescense, and flower) with more ESTs from them available was good, and the prediction in the tissues which has less ESTs deposited needs more experimental analysis. The predictive result will be closer to the true gene expression situation with more ESTs from various tissues are sequenced and deposited in the NCBI database.【Conclusion】The grape gene digital Northern platform has relatively high efficiency of predicting result, and can provide a useful analysis tool for rapid large-scale analysis of the grapevine gene expression and mining of the related important data.