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Use of a three-color cDNA microarray platform to measure and control support-bound probe for improved data quality and reproducibility
Author(s) -
Martin J. Hessner
Publication year - 2003
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gng059
Subject(s) - replicate , complementary dna , biology , dna microarray , reproducibility , computational biology , biological system , microarray , fluorescein , molecular probe , hybridization probe , computer science , fluorescence , genetics , gene expression , optics , gene , mathematics , chromatography , chemistry , statistics , physics
Construction methodologies for cDNA microarrays lack the ability to determine array integrity prior to hybridization, leaving the array itself a source of uncontrolled experimental variation. We solved this problem through development of a three-color cDNA array platform whereby printed probes are tagged with fluorescein and are compatible with Cy3 and Cy5 target labeling dyes when using con- focal laser scanners possessing narrow band- widths. Here we use this approach to: (i) develop a tracking system to monitor the printing of probe plates at predicted coordinates; (ii) define the quan- tity of immobilized probe necessary for quality hybridized array data to establish pre-hybridization array selection criteria; (iii) investigate factors that influence probe availability for hybridization; and (iv) explore the feasibility of hybridized data filtering using element fluorescein intensity. A direct and significant relationship (R 2 = 0.73, P < 0.001) between pre-hybridization average fluorescein intensity and subsequent hybridized replicate con- sistency was observed, illustrating that data quality can be improved by selecting arrays that meet defined pre-hybridization criteria. Furthermore, we demonstrate that our three-color approach provides a means to filter spots possessing insufficient bound probe from hybridized data sets to further improve data quality. Collectively, this strategy will improve microarray data and increase its utility as a sensitive screening tool.

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