DNA hybridization to mismatched templates: a chip study

High-density oligonucleotide arrays are among the most rapidly expanding technologies in biology today. In the {\sl GeneChip} system, the reconstruction of the target concentration depends upon the differential signal generated from hybridizing the target RNA to two nearly identical templates: a perfect match (PM) and a single mismatch (MM) probe. It has been observed that a large fraction of MM probes repeatably bind targets better than the PMs, against the usual expectation from sequence-specific hybridization; this is difficult to interpret in terms of the underlying physics. We examine this problem via a statistical analysis of a large set of microarray experiments. We classify the probes according to their signal to noise ($S/N$) ratio, defined as the eccentricity of a (PM, MM) pair's `trajectory' across many experiments. Of those probes having large $S/N$ ($>3$) only a fraction behave consistently with the commonly assumed hybridization model. Our results imply that the physics of DNA hybridization in microarrays is more complex than expected, and they suggest new ways of constructing estimators for the target RNA concentration.Comment: 3 figures 1 tabl

Solid‐Phase Supports for Oligonucleotide Synthesis

This unit begins with a discussion of the advantages and disadvantages of oligonucleotide synthesis using solid supports. The physical and chemical properties of solid‐phase supports are discussed in terms of their suitability for oligonucleotide synthesis. In addition, the unit outlines the properties of linkers used for transient or permanent attachment of properly protected nucleosides to the derivatized support, as well as strategies for coupling nucleosides to linkers and conditions for the release of synthetic oligonucleotides from specific supports.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143613/1/cpnc0301.pd

Solving the riddle of the bright mismatches: hybridization in oligonucleotide arrays

HDONA technology is predicated on two ideas. First, the differential between high-affinity (perfect match, PM) and lower-affinity (mismatch, MM) probes is used to minimize cross-hybridization. Second, several short probes along the transcript are combined, introducing redundancy. Both ideas have shown problems in practice: MMs are often brighter than PMs, and it is hard to combine the pairs because their brightness often spans decades. Previous analysis suggested these problems were sequence-related; publication of the probe sequences has permitted us an in-depth study of this issue. Our results suggest that fluorescently labeling the nucleotides interferes with mRNA binding, causing a catch-22 since, to be detected, the target mRNA must both glow and stick to its probe: without labels it cannot be seen even if bound, while with too many it won't bind. We show that this conflict causes much of the complexity of HDONA raw data, suggesting that an accurate physical understanding of hybridization by incorporating sequence information is necessary to perfect microarray analysis.Comment: 4 figure

Nanoliter high-throughput RT-qPCR: a statistical analysis and assessment

Biomarkers discovered from gene expression profiles using hybridization microarrays have made great inroads in the diagnosis and development of safer and efficacious drugs. The candidate gene set is biologically validated by quantitative measurement with reverse transcriptase quantitative PCR (RT-qPCR) and is an effective strategy when implemented with microplates if the number of candidate genes and samples is small. With the trend toward informative candidate gene panels increasing from tens to hundreds of genes and sample cohorts exceeding several hundred, an alternative fluidic approach is needed that preserves the intrinsic analytical precision, large dynamic range, and high sensitivity of RT-qPCR, yet is scalable to high throughputs. We have evaluated the performance of a nanoliter fluidic system that enables up to 3072 nanoliter RT-qPCR assays simultaneously in a high-density array format. We measured the transcription from two different adult human tissues to assess measurement reproducibility across replicates, measurement accuracy, precision, specificity, and sensitivity; determined the false positive rate (FPR) and false negative rate (FNR) of the expressed transcript copies; and determined differences in kinase gene expression reflecting tissue and dosage differences. Using our methodology, we confirm the potential of this technology in advancing pharmaceutical research and development