The use of non-amplified RNA samples for gene expression analysis by sensitive microarray.
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE30945 | GEO | 2011/07/28
SECONDARY ACCESSION(S): PRJNA146251
REPOSITORIES: GEO
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Project description:Gene expression profiles were compared based on the rounds of sample RNA amplification procedure. The intra- and inter-method reproducibility was shown by comparing gene expression profiles from two micoarray data. For the repeatability, CVs calculated from multiple microarray data were compared between different amplification methods. The accuracy of each method was estimated from the correlation with RT-PCR results when the same samples were assayed. The range of differential expression was shown using the brain RNA samples derived from an Alzheimer and non-Alzheimer donors.
2011-07-27 | E-GEOD-30945 | biostudies-arrayexpress
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2010-05-20 | GSE21389 | GEO
Project description:Demand for high quality gene expression data has driven the development of revolutionary microarray technologies. The quality of the data is affected by the performance of the microarray platform as well as how the nucleic acid targets are prepared. The most common method for target nucleic acid preparation includes in vitro transcription amplification of the sample RNA. Although this method requires a small amount of starting material and is reported to have high reproducibility, there are also technical disadvantages such as amplification bias and the long, laborious protocol. Using RNA derived from human brain, breast and colon, we demonstrate that a non-amplification method, which was previously shown to be inferior, could be transformed to a highly quantitative method with a dynamic range of five orders of magnitude. Furthermore, the correlation coefficient calculated by comparing microarray assays using non-amplified samples with qRT-PCR assays was approximately 0.9, a value much higher than when samples were prepared using amplification methods. Our results were also compared with data from various microarray platforms studied in the MicroArray Quality Control (MAQC) project. In combination with micro-columnar 3D-Gene™ microarray, this non-amplification method is applicable to a variety of genetic analyses, including biomarker screening and diagnostic tests for cancer.
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Project description:In order to assess the impact of three rounds of linear amplification on the technical reproducibility of gene expression measurements, we performed twelve microarray experiments. We analysed mouse RNA from cortex, cerebellum and liver from one individual. One RNA sample of 5µg from each of the three different tissues was processed according to the standard Affymetrix protocol and hybridized onto mouse gene expression arrays MG_U74Av2. Three additional samples from each tissue of 1ng were processed according to a modified procedure that involves three linear amplifications before hybridization onto the microarray chips. One mouse was analysed. One RNA sample of 5µg from each of liver, cortex, and cerebellum were processed according to the standard Affymetrix protocol and hybridized onto mouse gene expression arrays MG_U74Av2. Three additional samples (technical replicates) from each tissue of 1ng were processed according to a modified procedure that involves three linear amplifications before hybridization onto the microarray chips, resulting in 12 microarray experiments.
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Project description:The goals of the study were to assess array platform performance and analysis algorithm performance. The most widely used method for detecting genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and "spike-ins" comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. Keywords: ChIP-chip, competition, artificial DNA For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf DNA samples had spike-in DNA added to simulate peaks in ChIP-chip experiments. Same DNA samples used in the arrays in this Series; these are technical array replicates.
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