ArticleBMC genomics2008
Amplification biases: possible differences among deviating gene expressions.
Article in BMC genomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- A qualitative transcriptional signature for determining the grade of colorectal adenocarcinoma.Cancer gene therapy · 2020Article
- Evaluation of cross-platform and interlaboratory concordance via consensus modelling of genomic measurements.Bioinformatics (Oxford, England) · 2019Article
- Transcriptome-Stable Isotope Probing Provides Targeted Functional and Taxonomic Insights Into Microaerobic Pollutant-Degrading Aquifer Microbiota.Frontiers in microbiology · 2018Article
- Robust transcriptional signatures for low-input RNA samples based on relative expression orderings.BMC genomics · 2017Article
- A Double-Hybridization Approach for the Transcription- and Amplification-Free Detection of Specific mRNA on a Microarray.Microarrays (Basel, Switzerland) · 2016Article
- Transcriptome analysis of primary bovine extra-embryonic cultured cells.Genomics data · 2015Article
- Microarray experiments and factors which affect their reliability.Biology direct · 2015Review
- Article
- Sources of high variance between probe signals in Affymetrix short oligonucleotide microarrays.Sensors (Basel, Switzerland) · 2013Article
- Gene expression within the extended amygdala of 5 pairs of rat lines selectively bred for high or low ethanol consumption.Alcohol (Fayetteville, N.Y.) · 2013Article
- Amygdala nuclei critical for emotional learning exhibit unique gene expression patterns.Neurobiology of learning and memory · 2013Article
- Adjustment method for microarray data generated using two-cycle RNA labeling protocol.BMC genomics · 2013Article
- Exploiting identifiability and intergene correlation for improved detection of differential expression.ISRN bioinformatics · 2013Article
- Nonlinear dependence in the discovery of differentially expressed genes.ISRN bioinformatics · 2012Article
- Article
- Uncoupled embryonic and extra-embryonic tissues compromise blastocyst development after somatic cell nuclear transfer.PloS one · 2012Article
- An optimized protocol for microarray validation by quantitative PCR using amplified amino allyl labeled RNA.BMC genomics · 2010Article
- Evaluation of methods for amplification of picogram amounts of total RNA for whole genome expression profiling.BMC genomics · 2009Article
- Real-time monitoring of aRNA production during T7 amplification to prevent the loss of sample representation during microarray hybridization sample preparation.Nucleic acids research · 2009Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGene expression profiling has become a tool of choice to study pathological or developmental questions but in most cases the material is scarce and requires sample amplification. Two main procedures have been used: in vitro transcription (IVT) and polymerase chain reaction (PCR), the former known as linear and the latter as exponential. Previous reports identified enzymatic pitfalls in PCR and IVT protocols; however the possible differences between the sequences affected by these amplification defaults were only rarely explored.
resultsScreening a bovine cDNA array dedicated to embryonic stages with embryonic (n = 3) and somatic tissues (n = 2), we proceeded to moderate amplifications starting from 1 mug of total RNA (global PCR or IVT one round). Whatever the tissue, 16% of the probes were involved in deviating gene expressions due to amplification defaults. These distortions were likely due to the molecular features of the affected sequences (position within a gene, GC content, hairpin number) but also to the relative abundance of these transcripts within the tissues. These deviating genes mainly encoded housekeeping genes from physiological or cellular processes (70%) and constituted 2 subsets which did not overlap (molecular features, signal intensities, gene ID). However, the differential expressions identified between embryonic stages were both reliable (minor intersect with biased expressions) and relevant (biologically validated). In addition, the relative expression levels of those genes were biologically similar between amplified and unamplified samples.
conclusionConversely to the most recent reports which challenged the use of intense amplification procedures on minute amounts of RNA, we chose moderate PCR and IVT amplifications for our gene profiling study. Conclusively, it appeared that systematic biases arose even with moderate amplification procedures, independently of (i) the sample used: brain, ovary or embryos, (ii) the enzymatic properties initially inferred (exponential or linear) and (iii) the preliminary optimization of the protocols. Moreover the use of an in-house developed array, small-sized but well suited to the tissues we worked with, was of real interest for the search of differential expressions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.