Digital quantitative measurements of gene expression

One of the primary goals of functional genomics is to provide a quantitative understanding of gene function. However, the success of this enterprise is dependent on the accuracy and precision of the functional genomic data. A novel approach, digital analysis of gene expression (DAGE) described herein, is an accurate and precise technology for measuring digital gene expression on a relative or absolute scale by simply counting the number of transcripts of a gene being expressed at a given time. The result is a greatly improved technology sensitive enough for identifying and quantifying small (but biologically important and statistically relevant) changes in gene expression. Fourteen genes involved in galactose metabolism in Saccharomyces cerevisiae were analyzed for their expression levels in glucose and galactose minimal media. The quantitative expression results were characterized in terms of distributional and accuracy attributes; they were also in general agreement (in terms of direction of change) with corresponding results obtained using microarray technology. DAGE is likely to have profound implications in the field of functional genomics because the gene expression measurements are digital in nature and therefore more accurate than any other technologies. © 2004 Wiley Periodicals, Inc.

[1]  George M Church,et al.  Parallel competition analysis of Saccharomyces cerevisiae strains differing by a single base using polymerase colonies. , 2003, Nucleic acids research.

[2]  David M. Rocke,et al.  A Model for Measurement Error for Gene Expression Arrays , 2001, J. Comput. Biol..

[3]  S. Fields The future is function , 1997, Nature Genetics.

[4]  Christina Kendziorski,et al.  On Differential Variability of Expression Ratios: Improving Statistical Inference about Gene Expression Changes from Microarray Data , 2001, J. Comput. Biol..

[5]  Jean-Michel Claverie,et al.  Detection of Eukaryotic Promoters Using Markov Transition Matrices , 1997, Comput. Chem..

[6]  Michael L. Bittner,et al.  Ratio statistics of gene expression levels and applications to microarray data analysis , 2002, Bioinform..

[7]  John Aach,et al.  Measuring absolute expression with microarrays with a calibrated reference sample and an extended signal intensity range , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[8]  M D Adams Serial analysis of gene expression: ESTs get smaller. , 1996, BioEssays : news and reviews in molecular, cellular and developmental biology.

[9]  Paola Sebastiani,et al.  Statistical Challenges in Functional Genomics , 2003 .

[10]  David E. Housman,et al.  Digital genotyping and haplotyping with polymerase colonies , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[11]  R. Narayanan,et al.  Microarray-based expression profiling in prostate tumors. , 2000, In vivo.

[12]  K. Kinzler,et al.  Serial Analysis of Gene Expression , 1995, Science.

[13]  Adam B. Olshen,et al.  Deriving quantitative conclusions from microarray expression data , 2002, Bioinform..

[14]  G. Church,et al.  In situ localized amplification and contact replication of many individual DNA molecules. , 1999, Nucleic acids research.

[15]  R. Nadon,et al.  Statistical issues with microarrays: processing and analysis. , 2002, Trends in genetics : TIG.

[16]  J. Ibrahim,et al.  Bayesian Models for Gene Expression With DNA Microarray Data , 2002 .

[17]  Eric Wickstrom,et al.  Characterization of mutations and loss of heterozygosity of p53 and K-ras2 in pancreatic cancer cell lines by immobilized polymerase chain reaction , 2003, BMC biotechnology.

[18]  R Fislage,et al.  Differential display approach to quantitation of environmental stimuli on bacterial gene expression (minireview) , 1998, Electrophoresis.

[19]  S. Sealfon,et al.  Accuracy and calibration of commercial oligonucleotide and custom cDNA microarrays. , 2002, Nucleic acids research.

[20]  M. Boguski,et al.  Functional genomics: it's all how you read it. , 1997, Science.

[21]  G. Ramsay DNA chips: State-of-the art , 1998, Nature Biotechnology.

[22]  Rithy K. Roth,et al.  Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays , 2000, Nature Biotechnology.

[23]  D E Koshland,et al.  The Era of Pathway Quantification , 1998, Science.