Literature DB >> 15464596

A diffusion-reaction model for DNA microarray assays.

Chetan Gadgil1, Andrew Yeckel, Jeffrey J Derby, Wei-Shou Hu.   

Abstract

DNA microarrays are extensively used for the quantification of the degree of differential mRNA expression. The assay involves hybridization of mobile DNA strands with immobilized complementary DNA strands to form duplexes. The overall duplex formation rate depends on the rate of transport of strands in solution to the corresponding spot on the surface, and the rate of the hybridization reaction. We present a theoretical model that incorporates both kinetics of the reversible hybridization reaction and diffusional transport of the labeled strands, and analyze DNA microarray hybridization using this model. Simulations are carried out in a geometrically realistic domain for labeled DNA concentrations corresponding to rare and abundant transcripts for typical assay conditions. The rate of strand diffusion in solution is shown to strongly affect the overall hybridization rate. We compute the minimum inter-spot spacing for replicate spots to enhance sensitivity. We also determine the hybridization time for which reliable estimates of the relative mRNA abundance of two species can be obtained using total fluorescence intensities. An analytical solution for the concentration distribution of mobile strands at intermediate hybridization times provides a convenient tool to calculate the mobile strand concentration profiles. This model provides a framework for the process analysis of all microarray assays currently used for genomic transcriptional analysis.

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Year:  2004        PMID: 15464596     DOI: 10.1016/j.jbiotec.2004.05.008

Source DB:  PubMed          Journal:  J Biotechnol        ISSN: 0168-1656            Impact factor:   3.307


  14 in total

1.  Diffusion, mixing, and associated dye effects in DNA-microarray hybridizations.

Authors:  Jacob R Borden; Carlos J Paredes; Eleftherios Terry Papoutsakis
Journal:  Biophys J       Date:  2005-08-12       Impact factor: 4.033

Review 2.  Expression profiles as detailed snapshots of biological states.

Authors:  Fumiaki Katagiri; Masanao Sato
Journal:  Transgenic Res       Date:  2007-06-05       Impact factor: 2.788

3.  Array feature size influences nucleic acid surface capture in DNA microarrays.

Authors:  David S Dandy; Peng Wu; David W Grainger
Journal:  Proc Natl Acad Sci U S A       Date:  2007-05-07       Impact factor: 11.205

4.  Real-time fluorescent image analysis of DNA spot hybridization kinetics to assess microarray spot heterogeneity.

Authors:  Archana N Rao; Christopher K Rodesch; David W Grainger
Journal:  Anal Chem       Date:  2012-10-29       Impact factor: 6.986

5.  Optimization of encoded hydrogel particles for nucleic acid quantification.

Authors:  Daniel C Pregibon; Patrick S Doyle
Journal:  Anal Chem       Date:  2009-06-15       Impact factor: 6.986

6.  Systematic spatial bias in DNA microarray hybridization is caused by probe spot position-dependent variability in lateral diffusion.

Authors:  Doris Steger; David Berry; Susanne Haider; Matthias Horn; Michael Wagner; Roman Stocker; Alexander Loy
Journal:  PLoS One       Date:  2011-08-17       Impact factor: 3.240

7.  Relationship between gene expression and observed intensities in DNA microarrays--a modeling study.

Authors:  G A Held; G Grinstein; Y Tu
Journal:  Nucleic Acids Res       Date:  2006-05-24       Impact factor: 16.971

8.  An analysis of the use of genomic DNA as a universal reference in two channel DNA microarrays.

Authors:  Mugdha Gadgil; Wei Lian; Chetan Gadgil; Vivek Kapur; Wei-Shou Hu
Journal:  BMC Genomics       Date:  2005-05-08       Impact factor: 3.969

9.  An efficient algorithm for the stochastic simulation of the hybridization of DNA to microarrays.

Authors:  Erdem Arslan; Ian J Laurenzi
Journal:  BMC Bioinformatics       Date:  2009-12-10       Impact factor: 3.169

10.  Signal oscillation is another reason for variability in microarray-based gene expression quantification.

Authors:  Raghvendra Singh
Journal:  PLoS One       Date:  2013-01-21       Impact factor: 3.240

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