Literature DB >> 15520296

A novel, high-performance random array platform for quantitative gene expression profiling.

Kenneth Kuhn1, Shawn C Baker, Eugene Chudin, Minh-Ha Lieu, Steffen Oeser, Holly Bennett, Philippe Rigault, David Barker, Timothy K McDaniel, Mark S Chee.   

Abstract

We have developed a new microarray technology for quantitative gene-expression profiling on the basis of randomly assembled arrays of beads. Each bead carries a gene-specific probe sequence. There are multiple copies of each sequence-specific bead in an array, which contributes to measurement precision and reliability. We optimized the system for specific and sensitive analysis of mammalian RNA, and using RNA controls of defined concentration, obtained the following estimates of system performance: specificity of 1:250,000 in mammalian poly(A(+)) mRNA; limit of detection 0.13 pM; dynamic range 3.2 logs; and sufficient precision to detect 1.3-fold differences with 95% confidence within the dynamic range. Measurements of expression differences between human brain and liver were validated by concordance with quantitative real-time PCR (R(2) = 0.98 for log-transformed ratios, and slope of the best-fit line = 1.04, for 20 genes). Quantitative performance was further verified using a mouse B- and T-cell model system. We found published reports of B- or T-cell-specific expression for 42 of 59 genes that showed the greatest differential expression between B- and T-cells in our system. All of the literature observations were concordant with our results. Our experiments were carried out on a 96-array matrix system that requires only 100 ng of input RNA and uses standard microtiter plates to process samples in parallel. Our technology has advantages for analyzing multiple samples, is scalable to all known genes in a genome, and is flexible, allowing the use of standard or custom probes in an array.

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Year:  2004        PMID: 15520296      PMCID: PMC525694          DOI: 10.1101/gr.2739104

Source DB:  PubMed          Journal:  Genome Res        ISSN: 1088-9051            Impact factor:   9.043


  35 in total

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Journal:  Nature       Date:  2000-06-15       Impact factor: 49.962

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3.  Profiling alternative splicing on fiber-optic arrays.

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4.  High-density fiber-optic genosensor microsphere array capable of zeptomole detection limits.

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5.  Integrated genomic and proteomic analyses of a systematically perturbed metabolic network.

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Journal:  Science       Date:  2001-05-04       Impact factor: 47.728

6.  Automatic registration of microarray images. II. Hexagonal grid.

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Journal:  Bioinformatics       Date:  2003-09-22       Impact factor: 6.937

7.  Analysis of gene expression in single live neurons.

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Review 9.  Protein kinase C(theta) in T cell activation.

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  81 in total

1.  Multi-level mixed effects models for bead arrays.

Authors:  Ryung S Kim; Juan Lin
Journal:  Bioinformatics       Date:  2010-12-17       Impact factor: 6.937

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Review 5.  Integrating global gene expression analysis and genetics.

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8.  Population genomics of human gene expression.

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