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dHPLC 效率对半自动化 cDNA-AFLP 分析和片段收集在苹果黑星病抗性基因模型中的应用。

dHPLC efficiency for semi-automated cDNA-AFLP analyses and fragment collection in the apple scab-resistance gene model.

机构信息

Department of Fruit Tree and Woody Plant Science, University of Bologna, viale Fanin 46, 40127, Bologna, Italy.

出版信息

Planta. 2012 May;235(5):1065-80. doi: 10.1007/s00425-012-1589-y. Epub 2012 Jan 21.

Abstract

cDNA-AFLP analysis for transcript profiling has been successfully applied to study many plant biological systems, particularly plant-microbe interactions. However, the separation of cDNA-AFLP fragments by gel electrophoresis is reported to be labor-intensive with only limited potential for automation, and the collection of differential bands for gene identification is even more cumbersome. In this work, we present the use of dHPLC (denaturing high performance liquid chromatography) and automated DNA fragment collection using the WAVE(®) System to analyze and recover cDNA-AFLP fragments. The method is successfully applied to the Malus-Venturia inaequalis interaction, making it possible to collect 66 different transcript-derived fragments for apple genes putatively involved in the defense response activated by the HcrVf2 resistance gene. The results, validated by real time quantitative RT-PCR, were consistent with the plant-pathogen interaction under investigation and this further supports the suitability of dHPLC for cDNA-AFLP transcript profiling. Features and advantages of this new approach are discussed, evincing that it is an almost fully automatable and cost-effective solution for processing large numbers of samples and collecting differential genes involved in other biological processes and non-model plants.

摘要

cDNA-AFLP 分析已成功应用于研究许多植物生物学系统,特别是植物-微生物相互作用。然而,据报道,cDNA-AFLP 片段的凝胶电泳分离劳动强度大,自动化程度有限,并且基因鉴定的差异带的收集甚至更加繁琐。在这项工作中,我们提出使用 dHPLC(变性高效液相色谱)和 WAVE(®)系统自动收集 DNA 片段来分析和回收 cDNA-AFLP 片段。该方法成功应用于苹果与梨火疫病菌的相互作用,使得有可能收集 66 个不同的转录衍生片段,用于鉴定苹果中可能参与 HcrVf2 抗性基因激活的防御反应的基因。通过实时定量 RT-PCR 验证的结果与所研究的植物-病原体相互作用一致,这进一步支持 dHPLC 用于 cDNA-AFLP 转录谱分析的适用性。讨论了这种新方法的特点和优势,证明它是一种几乎完全自动化且具有成本效益的解决方案,可用于处理大量样本和收集参与其他生物学过程和非模式植物的差异基因。

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