ArticleBMC genomics2004
A comparative analysis of data generated using two different target preparation methods for hybridization to high-density oligonucleotide microarrays.
Article in BMC genomics, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Evaluating whole transcriptome amplification for gene profiling experiments using RNA-Seq.BMC biotechnology · 2015Article
- Cardiomyocyte PDGFR-beta signaling is an essential component of the mouse cardiac response to load-induced stress.The Journal of clinical investigation · 2010Article
- Evaluation of methods for amplification of picogram amounts of total RNA for whole genome expression profiling.BMC genomics · 2009Article
- Technical analysis of cDNA microarrays.PloS one · 2009Article
- Impact of smoking cessation on global gene expression in the bronchial epithelium of chronic smokers.Cancer prevention research (Philadelphia, Pa.) · 2008Article
- Interlaboratory performance of a microarray-based gene expression test to determine tissue of origin in poorly differentiated and undifferentiated cancers.The Journal of molecular diagnostics : JMD · 2008Article
- Review of the literature examining the correlation among DNA microarray technologies.Environmental and molecular mutagenesis · 2007Review
- Effect of sirolimus treatment on gene expression in renal transplant patients.World journal of surgery · 2007Article
- Reliability and reproducibility issues in DNA microarray measurements.Trends in genetics : TIG · 2006Review
- Options available for profiling small samples: a review of sample amplification technology when combined with microarray profiling.Nucleic acids research · 2006Review
- Limitations of mRNA amplification from small-size cell samples.BMC genomics · 2005Article
- Biological validation of differentially expressed genes in chronic lymphocytic leukemia identified by applying multiple statistical methods to oligonucleotide microarrays.The Journal of molecular diagnostics : JMD · 2005Article
- RNA amplification for successful gene profiling analysis.Journal of translational medicine · 2005Article
- Redefinition of Affymetrix probe sets by sequence overlap with cDNA microarray probes reduces cross-platform inconsistencies in cancer-associated gene expression measurements.BMC bioinformatics · 2005Article
- Increased DNA microarray hybridization specificity using sscDNA targets.BMC genomics · 2005Article
- A robust method for the amplification of RNA in the sense orientation.BMC genomics · 2005Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundTo generate specific transcript profiles, one must isolate homogenous cell populations using techniques that often yield small amounts of RNA, requiring researchers to employ RNA amplification methods. The data generated by using these methods must be extensively evaluated to determine any technique dependent distortion of the expression profiles.
resultsHigh-density oligonucleotide microarrays were used to perform experiments for comparing data generated by using two protocols, an in vitro transcription (IVT) protocol that requires 5 microg of total RNA and a double in vitro transcription (dIVT) protocol that requires 200 ng of total RNA for target preparation from RNA samples extracted from a normal and a cancer cell line. In both cell lines, about 10% more genes were detected with IVT than with dIVT. Genes were filtered to exclude those that were undetected on all arrays. Hierarchical clustering using the 9,482 genes that passed the filter showed that the variation attributable to biological differences between samples was greater than that introduced by differences in the protocols. We analyzed the behavior of these genes separately for each protocol by using a statistical model to estimate the posterior probability of various levels of fold change. At each level, more differentially expressed genes were detected with IVT than with dIVT. When we checked for genes that had a posterior probability greater than 99% of fold change greater than 2, in data generated by IVT but not dIVT, more than 60% of these genes had posterior probabilities greater than 90% in data generated by dIVT. Both protocols identified the same functional gene categories to be differentially expressed. Differential expression of selected genes was confirmed using quantitative real-time PCR.
conclusionUsing nanogram quantities on total RNA, the usage of dIVT protocol identified differentially expressed genes and functional categories consistent with those detected by the IVT protocol. There was a loss in sensitivity of about 10% when detecting differentially expressed genes using the dIVT protocol. However, the lower amount of RNA required for this protocol, as compared to the IVT protocol, renders this methodology a highly desirable one for biological systems where sample amounts are limiting.
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