Short oligonucleotide probes containing G-stacks display abnormal binding affinity on Affymetrix microarrays

    Authors

    C. L. Wu; H. T. Zhao; K. Baggerly; R. Carta;L. Zhang

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Abbreviated Journal Title

    Bioinformatics

    Keywords

    GENE-EXPRESSION; NUCLEIC-ACIDS; ARRAYS; DNA; HYBRIDIZATION; NORMALIZATION; SELECTION; DESIGN; MODEL; BIAS; Biochemical Research Methods; Biotechnology & Applied Microbiology; Computer Science, Interdisciplinary Applications; Mathematical &; Computational Biology; Statistics & Probability

    Abstract

    Motivation: In microarray experiments, probe design is critical to the specific and accurate measurement of target concentrations. Current designs select suitable probes through in silico scanning of transcriptome/genome based on first principles. However, due to lack of tools, the observed microarray data have not been used to assess the performance of individual probes to provide feedback to improve future designs. Result: In this study, we describe a probe performance assessment method based on the concordance of the observed signals from probes that share common targets. Using this method, we found that probes containing multiple guanines in a row (G-stacks) have abnormal binding behavior compared with other probes, both in gene expression assays and genotyping assays using Affymetrix microarrays. These probes are less likely to covary with other probes that interrogate the same genes. Moreover, we found that these probes are much more likely to produce outliers when fitting the observed signals according to the positional dependent nearest neighbor model, which gives reasonable estimates of binding affinity for most other probes. These results suggest that probes containing G-stacks tend to have increased cross hybridization signals and reduced target- specific hybridization signals, presumably due to multiplex binding forming G-quartet structures. Our findings are expected to be useful in microarray design and data analysis.

    Journal Title

    Bioinformatics

    Volume

    23

    Issue/Number

    19

    Publication Date

    1-1-2007

    Document Type

    Article

    Language

    English

    First Page

    2566

    Last Page

    2572

    WOS Identifier

    WOS:000250673800009

    ISSN

    1367-4803

    Share

    COinS