Digital quantitative measurements of gene expression

被引:17
作者
Mikkilineni, V
Mitra, RD
Merritt, J
DiTonno, JR
Church, GM
Ogunnaike, B
Edwards, JS [1 ]
机构
[1] Univ Delaware, Dept Chem Engn, Newark, DE 19716 USA
[2] Washington Univ, Dept Genet, St Louis, MO 63110 USA
[3] Harvard Univ, Dept Genet, Sch Med, Boston, MA 02115 USA
关键词
yeast; gene expression; genomics; metabolism; polonies; bioinformatics;
D O I
10.1002/bit.20048
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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. (C) 2004 Wiley Periodicals, Inc.
引用
收藏
页码:117 / 124
页数:8
相关论文
共 25 条
[1]   Serial analysis of gene expression: ESTs get smaller [J].
Adams, MD .
BIOESSAYS, 1996, 18 (04) :261-262
[2]   Detection of eukaryotic promoters using Markov transition matrices [J].
Audic, S ;
Claverie, JM .
COMPUTERS & CHEMISTRY, 1997, 21 (04) :223-227
[3]   Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays [J].
Brenner, S ;
Johnson, M ;
Bridgham, J ;
Golda, G ;
Lloyd, DH ;
Johnson, D ;
Luo, SJ ;
McCurdy, S ;
Foy, M ;
Ewan, M ;
Roth, R ;
George, D ;
Eletr, S ;
Albrecht, G ;
Vermaas, E ;
Williams, SR ;
Moon, K ;
Burcham, T ;
Pallas, M ;
DuBridge, RB ;
Kirchner, J ;
Fearon, K ;
Mao, J ;
Corcoran, K .
NATURE BIOTECHNOLOGY, 2000, 18 (06) :630-634
[4]   Exploring the new world of the genome with DNA microarrays [J].
Brown, PO ;
Botstein, D .
NATURE GENETICS, 1999, 21 (Suppl 1) :33-37
[5]  
Brown PO, 1998, MOL BIOL CELL, V9, p2A
[6]   Characterization of mutations and loss of heterozygosity of p53 and K-ras2 in pancreatic cancer cell lines by immobilized polymerase chain reaction -: art. no. 11 [J].
Butz, J ;
Wickstrom, E ;
Edwards, J .
BMC BIOTECHNOLOGY, 2003, 3 (1)
[7]   Ratio statistics of gene expression levels and applications to microarray data analysis [J].
Chen, YD ;
Kamat, V ;
Dougherty, ER ;
Bittner, ML ;
Meltzer, PS ;
Trent, JM .
BIOINFORMATICS, 2002, 18 (09) :1207-1215
[8]   Measuring absolute expression with microarrays with a calibrated reference sample and an extended signal intensity range [J].
Dudley, AM ;
Aach, J ;
Steffen, MA ;
Church, GM .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2002, 99 (11) :7554-7559
[9]  
Elek J, 2000, IN VIVO, V14, P173
[10]   The future is function [J].
Fields, S .
NATURE GENETICS, 1997, 15 (04) :325-327