Kammenga Jan E, Herman Michael A, Ouborg N Joop, Johnson Loretta, Breitling Rainer
Laboratory of Nematology, Wageningen University, Binnenhaven 5, 6709 PD, Wageningen, the Netherlands.
Trends Ecol Evol. 2007 May;22(5):273-9. doi: 10.1016/j.tree.2007.01.013. Epub 2007 Feb 12.
Microarrays are used to measure simultaneously the amount of mRNAs transcribed from many genes. They were originally designed for gene expression profiling in relatively simple biological systems, such as cell lines and model systems under constant laboratory conditions. This poses a challenge to ecologists who increasingly want to use microarrays to unravel the genetic mechanisms underlying complex interactions among organisms and between organisms and their environment. Here, we discuss typical experimental and statistical problems that arise when analyzing genome-wide expression profiles in an ecological context. We show that experimental design and environmental confounders greatly influence the identification of candidate genes in ecological microarray studies, and that following several simple recommendations could facilitate the analysis of microarray data in ecological settings.
微阵列用于同时测量从许多基因转录而来的mRNA的量。它们最初设计用于在相对简单的生物系统中进行基因表达谱分析，例如在恒定实验室条件下的细胞系和模型系统。这给生态学家带来了挑战，他们越来越希望使用微阵列来揭示生物体之间以及生物体与其环境之间复杂相互作用背后的遗传机制。在这里，我们讨论在生态背景下分析全基因组表达谱时出现的典型实验和统计问题。我们表明，实验设计和环境混杂因素在生态微阵列研究中对候选基因的识别有很大影响，遵循一些简单的建议可以促进生态环境中微阵列数据的分析。
