Differential display in the time of microarrays

References

• Matz MV, Lukyanov SA. Different strategies of differential display: areas of application. Nucleic Acids Res. 26, 5537–5543 (1998).
   PubMed Web of Science ®Google Scholar
• ••A comprehensive, deep review of randomand ordered variants of cDNA differential display.
   Google Scholar
• Green CD, Simons JF, Taillon BE, Lewin DA. Open systems: panoramic views of gene expression. J. Immunot Meth. 250, 67–79 (2001).
   PubMed Web of Science ®Google Scholar
• Breyne P, Zabeau M. Genome-wide expression analysis of plant cell cycle modulated genes. Curr. Opin. Plant Biol. 4, 136–142 (2001).
   Google Scholar
• •A good example of a review of genome-wide expression analysis methods focused on plant genomes.
   Google Scholar
• Lievens S, Goormachtig S, Holsters M. A critical evaluation of differential display as a tool to identify genes involved in legume nodulation: looking back and looking forward. Nucleic Acids. Res. 29, 3459–3468 (2001).
   Google Scholar
• Liang P, Pardee AB. Differential display of eukaryotic messenger RNA by means of the polymerase chain reaction. Science 257, 967–971 (1992).
   PubMed Web of Science ®Google Scholar
• •• A pioneering work on PCR-based mRNA differential display.
   Google Scholar
• Welsh J, McClelland M. Fingerprinting genomes using PCR with arbitrary primers. Nucleic Acids Res. 18, 7213–7218 (1990).
   PubMed Web of Science ®Google Scholar
• Differential display Methods and Protocols. Liang P, Pardee AB (Eds.), Humana Press, Totowa, NJ, USA, (1997).
   Google Scholar
• Analyzing Gene Regulation. Differentially Expressed Genes in Plants: Bench Manual. Hansen E, Harper G, Tayler, Francis (Eds.), (1997).
   Google Scholar
• Deerential Display Leslie RA, Robertson HA (Eds.), Oxford University Press, (2000). toBachem CW, van der Hoeven RS, de Bruijn SM et aL Visualization of differential gene expression using a novel method of RNA fingerprinting based on AFLP: analysis of gene expression during potato tuber development. Plant J. 9, 745–753 (1996).
   Google Scholar
• Matz M, Usman N, Shagin D et aL Ordered differential display: a simple method for systematic comparison of gene expression profiles. Nucleic Acids Res. 25,2541–2542 (1997).
   PubMed Web of Science ®Google Scholar
• VOS P, Hogers R, Bleeker M et al. AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res. 23, 4407–4414 (1995).
   PubMed Web of Science ®Google Scholar
• ••A first paper describing AFLP method.
   Google Scholar
• Siebert PD, Chenchik A, Kellog DE et al. An improved PCR method for walking in uncloned genomic DNA. Nucleic Acids Res. 23, 1087–1088 (1995).
   PubMed Web of Science ®Google Scholar
• ••A first paper describing PCR suppression.
   Google Scholar
• Broude NE, Storm N, Malpel S et al. PCR based targeted genomic and cDNA differential display. Genet. Anal. 15, 51–63 (1999).
   PubMedGoogle Scholar
• Lisitsyn NA. Representational difference analysis: finding the differences between genomes. Trends. Genet.11, 303–307(1995).
   PubMed Web of Science ®Google Scholar
• Ermolaeva OD, Sverdlov ED. Subtractive hybridization, a technique for extraction of DNA sequences distinguishing two closely related genomes: critical analysis. Genet. Anal.13, 49–58 (1996).
   PubMedGoogle Scholar
• Diatchenko L, Lau YE Campbell AP et al. Suppression subtractive hybridization: a method for generating differentially regulated or tissue-specific cDNA probes and libraries. Proc. Natl Acacl Sci. USA 93, 6025–6030 (1996).
   Google Scholar
• ••A fundamental work that describes the useof PCR suppression to develop efficient and simple cDNA subtractive hybridization method.
   Google Scholar
• Diatchenko L, Lukyanov S, Lau YE Siebert PD. Suppression subtractive hybridization: a versatile method for identifying differentially expressed genes. Methods Enzymol 303, 349–380 (1999).
   PubMed Web of Science ®Google Scholar
• Lukyanov K, Gurskaya NG, Bogdanova E„ Lukyanov S. Selective suppression of polymerase chain reaction. Bioorg. Chem. 25, 163–170 (1999).
   Google Scholar
• Broude NE, Mang L, Woodward K et id Multiplex allele-specific target amplification based on PCR suppression. Proc. Natl Acia Sci. USA 98, 206–211(2001).
   PubMed Web of Science ®Google Scholar
• Broude NE, Driscoll K, Cantor CR High- level multiplex PCR Antisense Nucleic Acid Drug Dev. 11, 327–332 (2001).
   Google Scholar
• Velculescu VE, Zhang L, Vogelstein B, Kinzler KW. Serial analysis of gene expression. Science 270,484–487 (1995).
   PubMed Web of Science ®Google Scholar
• ••First paper describing SAGE
   Google Scholar
• Spinella DG, Bernardino AK, Redding AC et al. Tandem arrayed ligation of expressed sequence tags (TALEST): a new method for generating global gene expression profiles. Nucleic Acids Res. 27, e22 (1999).
   Web of Science ®Google Scholar
• Datson NA, van der Perk-de Jong J, van den Berg MP et aL MicroSAGE: a modified procedure for serial analysis of gene expression in limited amounts of tissue. Nucleic Acids Res. 27, 1300–1307 (1999).
   PubMed Web of Science ®Google Scholar
• Brenner S, Williams SR, Vermaas EH et al. In vitro cloning of complex mixtures of DNA on microbeads: physical separation of differentially expressed cDNAs. Proc. Natl Acad. Sci. USA 97, 1665–1670 (2000).
   PubMed Web of Science ®Google Scholar
• ••First publication describing principle andfirst results obtained with massively parallel signature sequencing.
   Google Scholar
• Brenner S, Johnson M, Bridgharn J et al. Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays. Nature Biotechnol. 18, 630–634 (2000).
   PubMed Web of Science ®Google Scholar
• Southern EM. Detection of specific sequences among DNA fragments separated by gel electrophoresis. j Ma Biol 98, 503–517 (1975).
   Google Scholar
• Spellman PT, Sherlock G, Zhang MQ et al. Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mot Biol. Cell 9, 3273–3297 (1998).
   PubMed Web of Science ®Google Scholar
• Iyer VR, Eisen MB, Ross DT et aL The transcriptional program in the response of human fibroblasts to serum. Science 283, 83–87 (1999).
   PubMed Web of Science ®Google Scholar
• Ferea TL, Botstein D, Brown PO, Rosenzweig RF. Systematic changes in gene expression patterns following adaptive evolution in yeast. Proc. Natl Acad. Sci. USA 96, 9721–9726 (1999).
   PubMed Web of Science ®Google Scholar
• Fambrough D, McClure K, Kazlauskas A, Lander ES. Diverse signaling pathways activated by growth factor receptors induce broadly overlapping, rather than independent, sets of genes. Cell 97(6), 727–741 (1999).
   PubMed Web of Science ®Google Scholar
• Tavazoie S, Hughes JD, Campbell et al. Systematic determination of genetic network architecture. Nature Genet. 22, 281–285 (1999).
   PubMed Web of Science ®Google Scholar
• Golub TR, Slonim DK, Tamayo P. et aL Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286, 531–537 (1999).
   PubMed Web of Science ®Google Scholar
• ••A pioneering work demonstrating greatpotential of DNA microarrays for leukemias diagnostics by gene expression monitoring.
   Google Scholar
• Brenton JD, Aparicio SA, Caldas C. Molecular profiling of breast cancer: portraits but not physiognomy. Breast Cancer Res. 3, 77–80 (2001).
   PubMed Web of Science ®Google Scholar
• Alon U, Barkai N, Notterman DA et al. 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, 6745–6750 (1999).
   PubMed Web of Science ®Google Scholar
• Bhattacharjee A, Richards WG, Staunton J. et aZ Classification oh human lung carcinoma by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc. Nad Acad. Sci. USA 98, 13790–13795 (2001).
   Google Scholar
• Shipp MA, Ross KN, Tamayo P et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nature Med 8, 68–74 (2002).
   PubMed Web of Science ®Google Scholar
• Ferea TL, Brown PO. Observing the living genome. Curr. Opin. Genet. Dev. 9, 715–722 (1999).
   PubMed Web of Science ®Google Scholar
• Debouck C, Goodfellow PN. DNA microarrays in drug discovery and development Nature Genet. 21, 48–50 (1999).
   Google Scholar
• Noordewier MO, Warren PV Gene expression microarrays and the integration of biological knowledge. Trends Biotech. 19, 412–415 (2001).
   PubMed Web of Science ®Google Scholar
• von Stein OD, Thies WG, Hofmann M. A high-throughput screening for rarely transcribed differentially expressed genes. Nucleic Acids Res. 25, 2598–2602 (1997).
   PubMed Web of Science ®Google Scholar
• ••A first publication, in which authorscombined suppression subtractive hybridization and microarray techniques.
   Google Scholar
• Akopyants NS, Fradkov A, Diatchenko L et al. PCR-based subtractive hybridization and differences in gene content among strains of Helicobacter pylori. Proc. Natl Acad. Sci. USA 95,13108–13113 (1998).
   PubMed Web of Science ®Google Scholar
• Yang GP, Ross DT, Kuang -WW et at Combining SSH and cDNA microarrays for rapid identification of differentially expressed genes. Nucleic Acids. Res. 27, 1517–1523 (1999).
   PubMed Web of Science ®Google Scholar
• Welford SM, Gregg J, Chen E et al. Detection of differentially expressed genes in primary tumor tissues using representational differences analysis coupled to microarray hybridization. Nucleic Acids Res. 26, 3059–3065 (1998).
   PubMed Web of Science ®Google Scholar
• Martin KJ, Graner E, Li Yet al. High- sensitivity array analysis of gene expression for the early detection of disseminated breast tumor cells in peripheral blood. Proc. Natl Acad. Sci. USA 98, 2646–2651 (2001).
   Google Scholar
• ••A paper showing important practicalimplementation of DD and microarray techniques: their combined application allows early detection of the breast tumor cells in peripheral blood.
   Google Scholar
• Clarke PA, te Poele R, Wooster R, Workman P Gene expression microarray analysis in cancer biology, pharmacology and drug development: progress and potential. Biochem. Pharmacot 62, 1311–1336 (2001).
   PubMed Web of Science ®Google Scholar
• Hamels S, Gala JL, Dufour S et al. Consensus PCR and microarray for diagnosis of the genus Staphylococcus species and methicillin resistance. BioTechniques 31, 1364–1366, 1368, 1370–1372 (2001).
   Google Scholar