Observing the living genome

Current Opinion in Genetics and Development

Volumn 9, Issue 6, 1999, Pages 715-722

  Ferea, Tracy L ^a   Brown, Patrick O ^a  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DNA;

EVOLUTION; GENE EXPRESSION; GENE MAPPING; GENOME; PRIORITY JOURNAL; REVIEW;

EID: 0032784730     PISSN: 0959437X     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0959-437X(99)00033-7     Document Type: Review

References (45)

1. Velculescu V.E., Zhang L., Zhou W., Vogelstein J., Basrai M.A., Bassett D.E. Jr., Hieter P., Vogelstein B., Kinzler K.W. Characterization of the yeast transcriptome. Cell. 88:1997;243-251.
2. Carulli J.P., Artinger M., Swain P.M., Root C.D., Chee L., Tulig C., Guerin J., Osborne M., Stein G., Lian J., Lomedico P.T. High throughput analysis of differential gene expression. J Cell Biochem Suppl. 31:1998;286-296.
3. Lipshutz R.J., Fodor S.P., Gingeras T.R., Lockhart D.J. High density synthetic oligonucleotide arrays. Nat Genet. 21:1999;20-24.
4. Brown P.O., Botstein D. Exploring the new world of the genome with DNA microarrays. Nat Genet. 21:1999;33-37.
5. Vente A., Korn B., Zehetner G., Poustka A., Lehrach H. Distribution and early development of microarray technology in Europe. Nat Genet. 22:1999;22.
6. Bowtell D.D. Options available - from start to finish - for obtaining expression data by microarray. Nat Genet. 21:1999;25-32.
7. Cheung V.G., Morley M., Aguilar F., Massimi A., Kucherlapati R., Childs G. Making and reading microarrays. Nat Genet. 21:1999;15-19.
8. DeRisi 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.
9. 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.
10. 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.
11. Bryant Z., Subrahmanyan L., Tworoger M., LaTray L., Liu C.R., Li M.J., van den Engh G., Ruohola-Baker H. Characterization of differentially expressed genes in purified Drosophila follicle cells: toward a general strategy for cell type-specific developmental analysis. Proc Natl Acad Sci USA. 96:1999;5559-5564.
12. Lee C.K., Klopp R.G., Weindruch R., Prolla T.A. Gene expression profile of aging and its retardation by caloric restriction. Science. 285:1999;1390-1393. Gene expression profiles of aging mice are analyzed using oligonucleotide arrays representing over 6000 genes.
13. Ruan Y., Gilmore J., Conner T. Towards Arabidopsis genome analysis: monitoring expression profiles of 1400 genes using cDNA microarrays. Plant J. 15:1998;821-833.
14. Richmond C.S., Glasner J.D., Mau R., Jin H., Blattner F.R. Genome-wide expression profiling in Escherichia coli K-12. Nucleic Acids Res. 27:1999;3821-3835. The first report of microarrays representing the complete E. coli genome, which are applied to defining differential gene expression in response to both heat shock and treatment with IPTG.
15. Cho R.J., Campbell M.J., Winzeler E.A., Steinmetz L., Conway A., Wodicka L., Wolfsberg T.G., Gabrielian A.E., Landsman D., Lockhart D.J., Davis R.W. A genome-wide transcriptional analysis of the mitotic cell cycle. Mol Cell. 2:1998;65-73. A detailed analysis of the genomic expression program during the mitotic cell cycle in yeast, analyzed using oligonucleotide arrays.
16. 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 genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol Biol Cell. 9:1998;3273-3297. A comprehensive analysis of the genomic expression program during the yeast cell cycle, identifying and characterizing the expression of 800 genes that are determined to be periodically expressed during the cell cycle. Groups of genes with distinctive patterns of expression were identified using a Fourier analysis, as well as hierarchical clustering methods, and characteristic promoter elements are defined.
17. 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. The first comprehensive report of the genomic expression program in a developmental process. This paper includes a systematic analysis of the targets and activity of a key transcriptional regulator in the program.
18. Iyer V.R., Eisen M.B., Ross D.T., Schuler G., Moore T., Lee J.C.F., Trent J.M., Staudt L.M., Hudson J. Jr., Boguski M.S.et al. The transcriptional program in the response of human fibroblasts to serum. Science. 283:1999;83-87. Genomic expression patterns paint a picture of a physiological process. Experiments designed to look at the proliferation response of fibroblasts to serum reveal that the serum response is an unexpectedly complex physiological response to a wound signal.
19. Alizadeh A., Eisen M., Botstein D., Brown P.O., Staudt L.M. Probing lymphocyte biology by genomic-scale gene expression analysis. J Clin Immunol. 18:1998;373-379.
20. Johannes G., Carter M.S., Eisen M.B., Brown P.O., Sarnow P. Identification of eurkayotic mRNAs that can be translated in the abscence of intact cap binding protein complex eIf4F using a cDNA microarray. Proc Natl Acad Sci USA. 96:1999;13118-13123.
21. 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 USA. 95:1998;14470-14475.
22. 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.
23. Cole K.A., Krizman D.B., Emmert-Buck M.R. The genetics of cancer - a 3D model. Nat Genet. 21:1999;38-41.
24. 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 hemato-poietic differentiation. Proc Natl Acad Sci USA. 96:1999;2907-2912. A self-organizing map algorithm is applied to recognize patterns in expression data from both cell-cycle experiments and a model of hematopoietic differentiation.
25. 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. This paper describes a clustering algorithm that can be used to classify genes on the basis of their expression patterns, and to group tumors and tissues according to their overall similarity in gene expression pattern. The method is applied to gene expression data from oligonucleotide array analysis of human colon tumors and normal colon tissue. The authors provide a web site where the data set and algorithm can be downloaded ( http:www.molbio.princeton.edu/colondata ).
26. 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. A hierarchical clustering method and data visualization tools for large-scale gene expression data sets are described. The authors illustrate the power of these methods in organizing, visualizing and extracting biological insights from genomic expression studies. The software described is available at http://rana.stanford.edu/clustering.
27. 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. A detailed description of the utility of available computer algorithms to characterize regulatory networks that emerge from the analysis of gene expression data.
28. Ferea T.L., Botstein D., Brown P.O., Rosenzweig R.F. Systematic changes in gene expression patterns following adaptive evolution in yeast. Proc Natl Acad Sci USA. 96:1999;9721-9726. DNA microarray analysis reveals global changes in gene expression patterns that appear to account for much of the improvement in fitness observed in a laboratory model of evolution under long-term selection.
29. Luttik M.A., Overkamp K.M., Kotter P., de Vries S., van Dijken J.P., Pronk J.T. The Saccharomyces cerevisiae NDE1 and NDE2 genes encode separate mitochondrial NADH dehydrogenases catalyzing the oxidation of cytosolic NADH. J Biol Chem. 273:1998;24529-24534.
30. Boyle G.M., Roucou X., Nagley P., Devenish R.J., Prescott M. Identification of subunit g of yeast mitochondrial F1F0-ATP synthase, a protein required for maximal activity of cytochrome c oxidase. Eur J Biochem. 262:1999;315-323.
31. Fambrough D., McClure K., Kazlauskas A., Lander E.S. Diverse signaling pathways activated by growth factor receptors induce broadly overlapping, rather than independent, sets of genes. Cell. 97:1999;727-741. Wild-type and mutated receptors are used to dissect the roles of downstream pathways in the transcriptional responses of fibroblasts to signaling through growth factor receptors.
32. Pearce D.A., Ferea T., Nosel S.A., Das B., Sherman F. Action of BTN1, the yeast orthologue of the gene mutated in Batten disease. Nat Genet. 22:1999;55-58.
33. Holstege F.C., 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. A genomic approach to mapping regulatory networks. Oligonucleotide arrays are applied to systematic identification of the genes whose regulation is affected by disruption of specific components of the transcriptional regulatory apparatus in yeast.
34. Bulyk M.L., Gentalen E., Lockhart D.J., Church G.M. Quantifying DNA-protein interactions by double-stranded DNA arrays. Nat Biotechnol. 17:1999;573-577. A promising method to analyze DNA-protein interactions on a genomic scale using oligonucleotide arrays.
35. Halushka M.K., Fan J.B., Bentley K., Hsie L., Shen N., Weder A., Cooper R., Lipshutz R., Chakravarti A. Patterns of single-nucleotide polymorphisms in candidate genes for blood-pressure homeostasis. Nat Genet. 22:1999;239-247.
36. Cargill M., Altshuler D., Ireland J., Sklar P., Ardlie K., Patil N., Lane C.R., Lim E.P., Kalayanaraman N., Nemesh J.et al. Characterization of single-nucleotide polymorphisms in coding regions of human genes. Nat Genet. 22:1999;231-238.
37. Kononen J., Bubendorf L., Kallioniemi A., Barlund M., Schraml P., Leighton S., Torhorst J., Mihatsch M.J., Sauter G., Kallioniemi O.P. Tissue microarrays for high-throughput molecular profiling of tumor specimens. Nat Med. 4:1998;844-847.
38. Lee S.B., Huang K., Palmer R., Truong V.B., Herzlinger D., Kolquist K.A., Wong J., Paulding C., Yoon S.K., Gerald W.et al. The Wilms tumor suppressor WT1 encodes a transcriptional activator of amphiregulin. Cell. 98:1999;663-673.
39. Perou C.M., Jeffrey S.S., van de Rijn M., Rees C.A., Eisen M.B., Ross D.T., Pergamenschikov A., Williams C.F., Zhu S.X., Lee J.C.et al. Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc Natl Acad Sci USA. 96:1999;9212-9217. Cluster analysis of gene expression patterns allows the recognition of specific features of histological and physiological variation in histologically complex breast tumor samples.
40. Ugolini F., Adelaide J., Charafe-Jauffret E., Nguyen C., Jacquemier J., Jordan B., Birnbaum D., Pebusque M.J. Differential expression assay of chromosome arm 8p genes identifies Frizzled-related (FRP1/FRZB) and Fibroblast Growth Factor Receptor 1 (FGFR1) as candidate breast cancer genes. Oncogene. 18:1999;903-1910.
41. Debouck C., Goodfellow P.N. DNA microarrays in drug discovery and development. Nat Genet. 21:1999;48-50.
42. Marton M.J., DeRisi J.L., Bennett H.A., Iyer V.R., Meyer M.R., Roberts C.J., Stoughton R., Burchard J., Slade D., Dai H.et al. Drug target validation and identification of secondary drug target effects using DNA microarrays. Nat Med. 4:1998;1293-1301. The application of DNA microarray analysis in drug development. By using DNA microarrays to define the global gene expression pattern resulting from deletion of genes encoding intended drug targets, the target specificity of a candidate inhibitor can be assayed, and off-target effects recognized.
43. Gray N.S., Wodicka L., Thunnissen A.M., 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. A combination of high-throughput technologies are used to increase drug potency. The global effects of the drugs are then monitored in vivo using microarrays.
44. Pollack J.R., Perou C.M., Alizadeh A.A., Eisen M.B., Pergamenschikov A., Williams C.F., Jeffrey S.S., Botstein D., Brown P.O. Genome-wide analysis of DNA copy-number changes using cDNA microarrays. Nat Genet. 23:1999;41-46.
45. Pinkel D., Segraves R., Sudar D., Clark S., Poole I., Kowbel D., Collins C., Kuo W.L., Chen C., Zhai Y.et al. High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat Genet. 20:1998;207-211.