转录组
计算生物学
DNA微阵列
基因表达谱
拟南芥
生物
标签
协议(科学)
计算机科学
仿形(计算机编程)
RNA序列
微阵列分析技术
微阵列
基因
基因表达
数据挖掘
遗传学
医学
生物化学
替代医学
病理
突变体
操作系统
作者
Tara J. Holman,Michael Wilson,Kim Kenobi,Ian L. Dryden,Charlie Hodgman,Andrew T. A. Wood,Michael J. Holdsworth
出处
期刊:Plant Methods
[BioMed Central]
日期:2010-01-01
卷期号:6 (1): 9-9
被引量:14
标识
DOI:10.1186/1746-4811-6-9
摘要
BACKGROUND: Microarrays are a powerful tool used for the determination of global RNA expression. There is an increasing requirement to focus on profiling gene expression in tissues where it is difficult to obtain large quantities of material, for example individual tissues within organs such as the root, or individual isolated cells. From such samples, it is difficult to produce the amount of RNA required for labelling and hybridisation in microarray experiments, thus a process of amplification is usually adopted. Despite the increasing use of two-cycle amplification for transcriptomic analyses on the Affymetrix ATH1 array, there has been no report investigating any potential bias in gene representation that may occur as a result. RESULTS: Here we compare transcriptomic data generated using Affymetrix one-cycle (standard labelling protocol), two-cycle (small-sample protocol) and IVT-Express protocols with the Affymetrix ATH1 array using Arabidopsis root samples. Results obtained with each protocol are broadly similar. However, we show that there are 35 probe sets (of a total of 22810) that are misrepresented in the two-cycle data sets. Of these, 33 probe sets were classed as mis-amplified when comparisons of two independent publicly available data sets were undertaken. CONCLUSIONS: Given the unreliable nature of the highlighted probes, we caution against using data associated with the corresponding genes in analyses involving transcriptomic data generated with two-cycle amplification protocols. We have shown that the Affymetrix IVT-E labelling protocol produces data with less associated bias than the two-cycle protocol, and as such, would recommend this kit for new experiments that involve small samples.
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