Use of hidden correlations in short oligonucleotide array data are insufficient for accurate quantification of nucleic acid targets in complex target mixtures

Rule, Rebecca A.; Pozhitkov, Alex; Noble, Peter A.

doi:10.1016/j.mimet.2008.10.011

Cited by 6 publications

(4 citation statements)

References 23 publications

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“…Although prokaryotic tRNAs differ in terms of their nucleotide composition, they are uniform in terms of their size (74–95 nucleotides). As our study will show (below), the prokaryotic tRNA sequences were ideal for investigating the interactions of immobilized probes with nontarget sequences because the tRNAs did cross-hybridize with probes, which is consistent with another study that showed cross-hybridization of nontargets to immobilized probes cannot be predicted (23). …”

Section: Resultssupporting

confidence: 89%

Beyond Affymetrix arrays: expanding the set of known hybridization isotherms and observing pre-wash signal intensities

Pozhitkov

Boube

Brouwer

et al. 2009

Nucleic Acids Research

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Microarray hybridization studies have attributed the nonlinearity of hybridization isotherms to probe saturation and post-hybridization washing. Both processes are thought to distort ‘true’ target abundance because immobilized probes are saturated with excess target and stringent washing removes loosely bound targets. Yet the paucity of studies aimed at understanding hybridization and dissociation makes it difficult to align physicochemical theory to microarray results. To fill the void, we first examined hybridization isotherms generated on different microarray platforms using a ribosomal RNA target and then investigated hybridization signals at equilibrium and after stringent wash. Hybridization signal at equilibrium was achieved by treating the microarray with isopropanol, which prevents nucleic acids from dissolving into solution. Our results suggest that (i) the shape of hybridization isotherms varied by microarray platform with some being hyperbolic or linear, and others following a power-law; (ii) at equilibrium, fluorescent signal of different probes hybridized to the same target were not similar even with excess of target and (iii) the amount of target removed by stringent washing depended upon the hybridization time, the probe sequence and the presence/absence of nonspecific targets. Possible physicochemical interpretations of the results and future studies are discussed.

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Section: Resultssupporting

confidence: 89%

Beyond Affymetrix arrays: expanding the set of known hybridization isotherms and observing pre-wash signal intensities

Pozhitkov

Boube

Brouwer

et al. 2009

Nucleic Acids Research

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“…23 of these genes showed different probe rankings on different arrays and were therefore excluded from further analysis. There are many more effects other than mRNA-degradation that influence the measured probe-transcript hybridization strength, which are not yet fully understood (Rule et al, 2009). However, it is known that the GC-content of a probe influences the strength of the hybridization and thus the expression value.…”

Section: Data Filteringmentioning

confidence: 99%

Clustering approach to detect mRNA-degradation patterns from DNA–microarray gene-expression data

Motameny

Wünschiers

2012

BIT-journal

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DNA-microarray based gene-expression analysis is based on hybridization events between messenger RNA (mRNA) and single stranded DNA probes. In oligo nucleotide DNA-microarrays the probes consist of approximately 20 to 80 nucleotides long DNA-molecules. Consequently, several unique probes perfectly matching each single open reading frame (ORF) of mono-or polycistronic mRNA are usually used. If these probes are distributed over the whole length of the mRNA molecule, information about mRNA-degradation patterns can be gathered with data clustering methods. Here we report analysis of expression of 1107 open reading frames from the cyanobacterium Nostoc PCC 7120. Each open reading frame was covered by 10 unique 25 nucleotides long probes and analyzed by 4 independent DNA-microarray experiments. Both the positional information and the absolute expression value for each probe were used to infer clusters of transcripts that show similar expression patterns. Hierarchical and fuzzy k-means clustering yielded comparable results. Our results suggest that several different mRNA-degradation mechanisms, specific for certain transcripts, work in concert.

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“…Lastly, many microarray studies involve a tremendous amount of data manipulation (e.g. ad hoc criteria) that is not based on physicochemical principles, as shown previously (103,104,106,(109)(110)(111)(112)(113)122).…”

Section: Evaluation Of High-throughput Microarraysmentioning

confidence: 99%

High‐throughput methods for analysis of the human oral microbiome

Pozhitkov

Beikler²,

Flemmig³

et al. 2010

Periodontology 2000

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Use of hidden correlations in short oligonucleotide array data are insufficient for accurate quantification of nucleic acid targets in complex target mixtures

Cited by 6 publications

References 23 publications

Beyond Affymetrix arrays: expanding the set of known hybridization isotherms and observing pre-wash signal intensities

Beyond Affymetrix arrays: expanding the set of known hybridization isotherms and observing pre-wash signal intensities

Clustering approach to detect mRNA-degradation patterns from DNA–microarray gene-expression data

High‐throughput methods for analysis of the human oral microbiome

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