Kok Esther J, Franssen-van Hal Nicole L W, Winnubst Lies N W, Kramer Evelien H M, Dijksma Wilko T P, Kuiper Harry A, Keijer Jaap
RIKILT Institute for Food Safety, Bornsesteeg 45, 6700 AE Wageningen, The Netherlands.
J Plant Physiol. 2007 Mar;164(3):337-49. doi: 10.1016/j.jplph.2006.02.013. Epub 2006 Apr 21.
Microarray technology makes it feasible to analyse the expression of thousands of different gene elements in a single experiment. Most informative are 'whole genome' arrays, where all gene expression products of a single species or variety are represented. Such arrays are now available for a limited number of model species. However, for other, less well-documented species other routes are still necessary to obtain informative arrays. This includes the use of cDNA libraries. To enhance the amount of information that can be obtained from cDNA libraries, redundancy needs to be minimised, and the number of cDNAs relevant for the conditions of interest needs to be increased. Here, we used representational difference analysis (RDA), a mRNA subtraction procedure, as a tool to enhance the efficiency of cDNA libraries to be used to generate microarrays. Tomato was chosen as a model system for a less well-documented species. cDNA libraries for two distinct physiological conditions of tomato fruits, red and green, were made. The libraries were characterized by sequencing and hybridisation analysis. The RDA procedure was shown to be effective in selecting for genes of relevance for the physiological conditions under investigation, and against constitutively expressed genes. At the same time, redundancy was reduced, but complete normalisation was not obtained, and subsequent sequence analysis will be required to obtain non-redundant arrays. Further, known and putative ripening-related cDNAs were identified in hybridisation experiments on the basis of RNA populations as isolated from the green and red stage of ripening.
微阵列技术使得在单个实验中分析数千种不同基因元件的表达成为可能。最具信息量的是“全基因组”阵列,其中代表了单个物种或品种的所有基因表达产物。目前,此类阵列仅适用于少数模式物种。然而,对于其他记录较少的物种,仍需要其他途径来获得信息量丰富的阵列。这包括使用cDNA文库。为了增加从cDNA文库中可获得的信息量,需要尽量减少冗余,并增加与感兴趣条件相关的cDNA数量。在此,我们使用代表性差异分析(RDA),一种mRNA扣除程序,作为提高用于生成微阵列的cDNA文库效率的工具。番茄被选为一个记录较少物种的模型系统。构建了番茄果实两种不同生理状态(红色和绿色)的cDNA文库。通过测序和杂交分析对文库进行了表征。结果表明,RDA程序在选择与所研究生理条件相关的基因以及排除组成型表达基因方面是有效的。同时,冗余减少了,但未实现完全标准化,需要后续进行序列分析以获得非冗余阵列。此外,在基于从绿色和红色成熟阶段分离的RNA群体进行的杂交实验中,鉴定出了已知的和假定的与成熟相关的cDNA。