Reilly Siobhan C, Cossins Andrew R, Quinn John P, Sneddon Lynne U
School of Biological Sciences, University of Liverpool, The BioSciences Building, Liverpool, Merseyside L69 7ZB, United Kingdom.
Brain Res Brain Res Rev. 2004 Oct;46(2):225-33. doi: 10.1016/j.brainresrev.2004.07.001.
The DNA microarray is a powerful, high throughput technique for assessing gene expression on a system-wide genomic scale. It has great potential in pain research for determining the network of gene regulation in different pain conditions, and also for producing detailed gene expression maps in anatomical areas that process nociceptive stimuli. However, for the potential of this high throughput technology to be realised in pain research, microarrays need to be combined with other technologies. Laser capture microdissection is capable of isolating small populations of homogenous cells, allowing distinct areas involved in nociceptive processing to be examined. In combination with sophisticated PCR-based amplification protocols this technique provides sufficient amounts of messenger RNA (mRNA) for application to microarrays. Aside from the technological issues, a difficult task in any microarray study is the analysis of the resulting enormous data set to reveal the key genes, whose regulation is central to the phenotypic changes observed. For this to be achieved, the methods of data analysis, pattern searching and feature recognition, and bioinformatics have to be properly deployed all within the context of an appropriate statistical design. These issues are especially relevant to pain research where interindividual and interpopulation variation is likely to be high, and where polymorphisms can greatly affect nociceptive sensitivity and susceptibility to pain conditions. Methods for assessing the function of new candidate genes identified in microarray screening experiments are also discussed.
DNA微阵列是一种强大的高通量技术,可在全基因组范围内评估基因表达。它在疼痛研究中具有巨大潜力,可用于确定不同疼痛状况下的基因调控网络,还能在处理伤害性刺激的解剖区域绘制详细的基因表达图谱。然而,要在疼痛研究中实现这种高通量技术的潜力,微阵列需要与其他技术相结合。激光捕获显微切割能够分离出少量同质细胞,从而可以检查参与伤害性处理的不同区域。结合基于PCR的复杂扩增方案,该技术可为微阵列分析提供足够量的信使核糖核酸(mRNA)。除了技术问题,在任何微阵列研究中,一项艰巨的任务是分析由此产生的海量数据集,以揭示关键基因,这些基因的调控对于所观察到的表型变化至关重要。要实现这一点,必须在适当的统计设计背景下正确运用数据分析、模式搜索和特征识别方法以及生物信息学。这些问题在疼痛研究中尤为重要,因为个体间和群体间的差异可能很大,而且多态性会极大地影响伤害性敏感性和对疼痛状况的易感性。本文还讨论了评估在微阵列筛选实验中鉴定出的新候选基因功能的方法。