Monitoring gene expression using DNA microarrays

Current Opinion in Microbiology

Volumn 3, Issue 3, 2000, Pages 285-291

  Harrington, Christina A ^a   Rosenow, Carsten ^a   Retief, Jacques ^a  

^a Thermo Fisher Scientific   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

OLIGOMER;

DNA DETERMINATION; GENE EXPRESSION; GENE FUNCTION; GENOTYPE; MICROBIAL GENETICS; NONHUMAN; OPEN READING FRAME; REVIEW; SEQUENCE ANALYSIS; TECHNOLOGY;

EID: 0034044523     PISSN: 13695274     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1369-5274(00)00091-6     Document Type: Review

References (41)

1. Lander E. Array of hope. Suppl Nat Genet. 21:1999;3-4.
2. Brown P.O., Botstein D. Exploring the new world of the genome with DNA microarrays. Suppl Nat Genet. 21:1999;33-37.
3. Case-Green S.C., Mir K.U., Pritchard C.E., Southern E.M. Analysing genetic information with DNA arrays. Curr Opin Chem Biol. 2:1998;404-410.
4. Ferea T.L., Brown P.O. Observing the living genome. Curr Opin Genet Dev. 9:1999;715-722. An overview of array technology with emphasis on spotted arrays. Includes table of web sites for making and using DNA arrays and useful information on pattern recognition and data visualization strategies.
5. Lipshutz R.J., Fodor S.P.A., Gingeras T.R., Lockhart D.J. High density synthetic oligonucleotide arrays. Suppl Nat Genet. 21:1999;20-24. This review includes a summary of the manufacturing process for high-density oligonucleotide arrays and describes how these arrays are being applied, including gene expression monitoring and genotypic analysis.
6. Duggan D.J., Bittner M., Chen Y., Meltzer P., Trent J.M. Expression profiling using cDNA microarrays. Suppl Nat Genet. 21:1999;10-14.
7. Eisen M.B., Brown P.O. DNA arrays for analysis of gene expression. Weissman S.M. Methods in Enzymology: cDNA Preparation and Characterization. vol 303. 1999;179-205 Academic Press.
8. Bowtell D.D.L. Options available-from start to finish-for obtaining expression data by microarray. Suppl Nat Genet. 21:1999;25-32.
9. Winzeler E.A., Schena M., Davis R.W. Fluorescence-based expression monitoring using microarrays. Glorioso J., Schmidt M.C. Methods in Enzymology: Expression of Recominant Genes in Eukaryotic Systems, vol 306. 1999;3-18 Academic Press, London.
10. Schena M., Shalon D., Davis R.W., Brown P.O. Quantitiative monitoring of gene expression patterns with a complementary DNA microarray. Science. 270:1996;467-470.
11. De Risi J.L., Iyer V.R., Brown P.O. Exploring the metabolic and genetic control of gene expression on a genomic scale. Science. 278:1997;680-686.
12. Chee M., Yang R., Hubbell E., Berno A., Huang X.C., Stern D., Winkler J., Lockhart D.J., Morris M.S., Fodor S.P.A. Accessing genomic information with high-density arrays. Science. 274:1996;610-614.
13. Lockhart D.J., Dong H., Byrne M.C., Follettie M.T., Gallo M.V., Chee M.S., Mittmann M., Wang C., Kobayashi M., Horton H., Brown E.L. Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat Biotechnol. 14:1996;1675-1680.
14. Richmond C.S., Glasner J.D., Mau R., Jin H., Blattner F.R. Genome-wide expression in Escherichia coli K-12. Nucleic Acid Res. 27:1999;3821-3835. Changes in RNA levels after exposure of E. coli to heat shock or IPTG are compared using two different methods: hybridization of radioactive cDNA to spot blots on nylon membranes and fluorescence-based hybridization to glass microarrays.
15. Lashkari D.A., DeRisi J.L., McCusker J.H., Namath A.F., Gentile C., Hwang S.Y., Brown P.O., Davis R.W. Yeast microarrays for genome wide parallel genetic and gene expression analysis. Proc Natl Acad Sci USA. 94:1997;13057-13062.
16. Wodicka L., Dong H., Mittmann M., Ho M-H., Lockhart D.J. Genome-wide expression monitoring in Saccharomyces cerevisiae. Nat Biotechnol. 15:1997;1359-1367.
17. Cho R.J., Campbell M.J., Winzeler E.A., Steinmetz L., Conway A., Wodicka L., Wolfsberg T.G., Gabrielian A.E., Landsman, Lockhart D.J., Davis R.W. A genome-wide transcriptional analysis of the mitotic cell cycle. Mol Cell. 2:1998;65-73. [ http://genomics.stanford.edu ] One of the first studies to report genome-wide patterns of expression through a series of cell states. This study measures mRNA transcript levels during the yeast cell cycle using high-density oligonucleotide arrays.
18. Spellman P.T., Sherlock G., Zhang M.Q., Iyer V.R., Anders K., Eisen M.B., Brown P.O., Botstein D., Futcher B. Comprehensive identification of cell cycle-regulated gene of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol Biol Cell. 9:1998;3273-3297. [ http://cellcycle-www.stanford.edu ] Study measuring genome-wide mRNA transcript levels during the yeast cell cycle using spotted DNA microarrays. Promoter elements predictive of cell-cycle regulation were identified.
19. Chu S., DeRisi J., Eisen M., Mulholland J., Botstein D., Brown P.O., Herskowitz I. The transcriptional program of sporulation in budding yeast. Science. 282:1998;699-705. [ http://cmgm.stanford.edu/pbrown/sporulation ] Global patterns of gene expression during a developmental program, sporulation in yeast, are presented. Temporal expression patterns suggest potential functions of many uncharacterized genes.
20. Jelinsky S., Samson L. Global response of Saccharomyces cerevisiae to an alkylating agent. Proc Natl Acad Sci USA. 96:1999;1486-1491. This work demonstrates the ability of global expression profiling to dramatically increase information about specific cellular processes. It also includes a study correlating Northern analyses with microarray results.
21. Holstege F., Jennings E.G., Wyrick J.J., Lee T.I., Hengartner C.J., Green M.R., Golub T.R., Lander E.S., Young R.A. Dissecting the regulatory circuitry of a eukaryotic genome. Cell. 95:1998;717-728.
22. Lelivelt M., Culberston M. Yeast upf proteins required for RNA surveillance affect global expression of the yeast transcriptome. Mol Cell Biol. 19:1999;6710-6719.
23. Madhani H.D., Galitski T., Lander E.S., Fink G.R. Effectors of a developmental mitogen-activated protein kinase cascade revealed by expression signatires of signaling mutants. Proc Natl Acad Sci USA. 96:1998;12530-12535.
24. Marton M.J., DeRisi J.L., Bennet H.A., Iyer V.R., Meyer M.R., Roberts C.J., Stoughton R., Burchard J., Slade D., Dai H.et al. Drug validation and identification of secondary drug target effects using DNA microarrays. Nat Med. 4:1998;1293-1301.
25. Gray N.S., Wodicka L., Thunnissen A.W.H., Norman T.C., Kwon S., Espinoza F.H., Morgan D.O., Barnes G., LeClerc S., Meijer L.et al. Exploiting chemical libraries, structure, and genomics in the search for kinase inhibitors. Science. 281:1998;533-538.
26. Lockhart D.J. Mutant yeast on drugs. Nat Med. 4:1998;1235-1236.
27. Ferea T.L., Botstein D., Brown P.O., Rosenzweig R.F. Systematic changes in gene expression patterns following adaptive evolution. Proc Natl Acad Sci USA. 96:1999;9721-9726.
28. Gingeras T., Rosenow C. High density oligonucleotide arrays and their use in the study of microbial genomes: opportunities unique to prokaryotic genomes. ASM News in press. 2000.
29. De Saizieu A., Certa U., Warrington J., Gray C., Keck W., Mous J. Bacterial transcript imaging by hybridization of total RNA to oligonucleotide arrays. Nat Biotechnol. 16:1998;45-48.
30. Tao H., Bausch C., Richmond C., Blattner F.R., Conway T. Functional genomics: expression analysis of Escherichia coli growing on minimal and rich media. J Bacteriol. 181:1999;6425-6440. Comparison of gene expression profiles using total RNA from E. coli cells grown in rich and minimal medium. A comprehensive analysis of differentially expressed genes is presented.
31. Wilson M., DeRisi J., Kristensen H-H., Imboden P., Rane S., Brown P.O., Schoolnik G.K. Exploring drug-induced alterations in gene expression in Mycobacterium tuberculosis by microarray hybridization. Proc Natl Acad Sci USA. 96:1999;12833-12838. PCR-based microarrays of the entire M. tuberculosis genome were used to study gene induction after treatment of the bacterial cell with the drug isoniazid. Several induced genes were linked to proteins that are relevant to the drug's mode of action.
32. Zhu H., Cong J.P., Mamtora G., Gingeras T., Shenk T. Cellular gene expression altered by human cytomegalovirus: global monitoring with oligonucleotide arrays. Proc Natl Acad Sci. 95:1998;14470-14475. Comprehensive analysis of human genes whose mRNA levels change after infection of primary fibroblast cells with the human cytomegalovirus.
33. Chambers J., Angulo A., Amaratunga D., Guo H., Jiang Y., Wan J.S., Bittner A., Frueh K., Jackson M.R., Peterson P.A.et al. DNA microarrays of the complex human cytomegalovirus genome: profiling kinetic class with drug sensitivity of viral gene expression. J Virol. 73:1999;5757-5766.
34. Bassett D.E., Eisen B., Boguski M.S. Gene expression informatics-it's all in your mine. Suppl Nat Genet. 21:1999;51-55.
35. Eisen M.B., Spellman P.T., Brown P.O., Botstein D. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA. 95:1998;14863-14868.
36. Tamayo P., Slonim D., Mesirov J., Zhu Q., Kitareewan S., Dmitrovsky E., Lander E.S., Golub T.R. Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proc Natl Acad Sci USA. 96:1999;2907-2912.
37. Törönen P., Kolehmainen M., Wong G., Castrën E. Analysis of gene expression data using self-organizing maps. FEBS Lett. 451:1999;142-146.
38. Tavazoie S., Hughes J.D., Campbell M.J., Cho R.J., Church G.M. Systematic determination of genetic network architecture. Nat Genet. 22:1999;281-285.
39. Claverie J.M. Computational methods for the identification of differential and coordinated gene expression. Hum Mol Genet. 8:1999;1821-1832. Review of computational methods used to identify genes that are differentially expressed between normal and pathological samples or coordinately expressed across experimental conditions or through time. Also addresses the clustering of genes with coherent expression features, such as membership in biological pathways.
40. Alon U., Barkai N., Notterman D.A., Gish K., Ybarra S., Mack D., Levine A.J. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. Proc Natl Acad Sci USA. 96:1999;6745-6750. Two-way clustering was applied to microarray data from 40 tumor and 22 normal colon tissue samples. The clustering program separated cancerous from noncancerous tissue even when expression of individual genes varied only slightly between the tissues.
41. Golub T.R., Slonim D.K., Tamayo P., Huard C., Gaasenbeek M., Mesirov J.P., Coller H., Loh M.L., Downing J.R., Caligiuri M.A.et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science. 286:1999;531-537. This paper describes how two types of leukemia can be distinguished through use of an automatically derived predictor.