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

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

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.

The effects of probe binding affinity differences on gene expression measurements and how to deal with them

MOTIVATION

When comparing gene expression levels between species or strains using microarrays, sequence differences between the groups can cause false identification of expression differences. Our simulated dataset shows that a sequence divergence of only 1% between species can lead to falsely reported expression differences for >50% of the transcripts-similar levels of effect have been reported previously in comparisons of human and chimpanzee expression. We propose a method for identifying probes that cause such false readings, using only the microarray data, so that problematic probes can be excluded from analysis. We then test the power of the method to detect sequence differences and to correct for falsely reported expression differences. Our method can detect 70% of the probes with sequence differences using human and chimpanzee data, while removing only 18% of probes with no sequence differences. Although only 70% of the probes with sequence differences are detected, the effect of removing probes on falsely reported expression differences is more dramatic: the method can remove 98% of the falsely reported expression differences from a simulated dataset. We argue that the method should be used even when sequence data are available.

CONTACT

lachmann@eva.mpg.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Real-time DNA microarrays: reality check

DNA microarrays are plagued with inconsistent quantifications and false-positive results. Using established mechanisms of surface reactions, we argue that these problems are inherent to the current technology. In particular, the problem of multiplex non-equilibrium reactions cannot be resolved within the framework of the existing paradigm. We discuss the advantages and limitations of changing the paradigm to real-time data acquisition similar to real-time PCR methodology. Our analysis suggests that the fundamental problem of multiplex reactions is not resolved by the real-time approach itself. However, by introducing new detection chemistries and analysis approaches, it is possible to extract target-specific quantitative information from real-time microarray data. The possible scope of applications for real-time microarrays is discussed.