Optimization of minuscule samples for use with cDNA microarrays

Susan McLean Hunter , Fiona C. Mansergh , Martin J. Evans
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引用次数: 12

Abstract

The recent advent of microarray technology and RNA amplification allows us to compare the expression profiles of thousands of genes from small amounts of tissue or cells. We have compared and contrasted various methods of RNA preparation, RNA amplification, target labelling and array analysis in order to achieve a streamlined protocol for microarraying small samples. We have concluded that usage of the NIA 15K cDNA array set, in combination with RNA extraction using the Mini RNA Isolation kit (Zymo), amplification with the RiboAmp kit (Arcturus), followed by indirect labelling via the Atlas™ PowerScript™ Fluorescent Labelling kit (using a modified protocol), is optimal with a material derived from either very early stage mouse embryos or individually picked embryonic stem cell colonies. Normalisation using the analysis package Limma (Bioconductor) with data normalisation by print tip Loess, using the “normexp” function with an offset of 50 for background adjustment, and incorporating A-quantile between array normalisation was best with our results. Furthermore, RT-PCR confirmation of array results is achievable without amplification, thereby controlling for amplification bias. These methods will be of great utility in mapping the transcriptome of embryonic and other small samples.

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用于cDNA微阵列的微小样品的优化
最近出现的微阵列技术和RNA扩增使我们能够比较来自少量组织或细胞的数千个基因的表达谱。我们比较和对比了RNA制备、RNA扩增、靶标标记和阵列分析的各种方法,以实现小样本微阵列的简化方案。我们得出的结论是,使用NIA 15K cDNA阵列,结合使用Mini RNA分离试剂盒(Zymo)提取RNA,使用RiboAmp试剂盒(Arcturus)扩增,然后使用Atlas™PowerScript™荧光标记试剂盒(使用改进的方案)间接标记,对于来自非常早期小鼠胚胎或单独挑选的胚胎干细胞菌群的材料是最佳的。使用分析包Limma (Bioconductor)进行归一化,使用打印尖黄土进行数据归一化,使用偏移量为50的“normexp”函数进行背景调整,并在阵列归一化之间合并a分位数,这与我们的结果最吻合。此外,阵列结果的RT-PCR确认无需扩增,从而控制了扩增偏倚。这些方法将在绘制胚胎和其他小样本的转录组图谱方面发挥重要作用。
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