ࡱ> TJY,yRoot EntryX $X #W h F W `FDataW W X X W xW   X X h WxW W #W 1TableW xW PW 8W W pW xWordDocumentdX dW bX bX =o  !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~     8 !"#$%&'()*+,-./01234567Q9:;<=>?@ABCDEFGHIKLMNOPRSUVW     m* !"#$%&'()+,-./0124XGHKLMNOPQRSTUVWuYZ[\]^_nopqrst'vwxyz{|}~SummaryInformationW X CX C( W X>X @>X DocumentSummaryInformation8 X) X)<CompObjW X (X X X  W W XX H0TableW W W W W !pW Root EntryX $X #W h F W -DataW W X X W xW   X X h WxW W GW 1TableW xW PW 8W W pW xWordDocumentdX dW bX bX = w  !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~some fractionation with DNA array technology and allows identification of translationally regulated genes on a genomic scale. Polysomes are prepared from cell populations and are fractionated on sucrose gradients. The fractions are separated into two pools: poorly-translated (few to no bound ribosomes) and highly translated (several bound ribosomes). The two pools are labeled separately with different dyes and hybridized together to cDNA arrays. For each gene on the array, the ratio of signal between the two fractions (P/H) represents the translation state for that message. Comparison of the translation state for each gene under different experimental treatments allows a genome-level assessment of translational regulation. We have applied this technique to the cell cycle of the budding yeast, Saccharomyces cereviseae. Our initial study focused on G` phase and revealed that over 200 genes appear to be translationally regulated during this part of the cell cycle. Both up-and down-regulation of translation was seen. The message showing increased translation included genes involved in cell polarity, mitochondrial inheritance, phosphate metabolism and DNA replication, among others. Messages undergoing decreased translation included some ribosomal and ribosome assembly proteins, components of the translational apparatus, and some of the histones. To confirm the TSAA results, several genes were chosen for further study. Northern analysis on polysome fractions made from synchronized populations demonstrated that these messages do indeed change in polysome distribution during G1 in the patterns predicted by TSAA. In addition to characterizing translation state, TSAA also estimates transcript levels. As a further assessment of TSAA, the transcript patterns derived from TSAA were compared with those derived from conventional expression array analysis of cell cycle regulated transcription. The two sets of data were found to be in general agreement. TSAA appears to be a useful genomic-level technology for identifying translationally regulated genes. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10:30 - 10:50AM Presenter: M.K. Raghuraman, Dept of Genetics, University of Washington The Topography of Chromosome Replication in Yeast: A Genomic View M. Raghuraman, D. Collingwood1, E. Winzeler1, G. Alvino, S. Hunt, A. Conway2, L. Wodicka3, D. Lockhart3, R. Bumgarner4, R. Davis 5, W. Fangman and B. Brewer. Dept of Genetics, University of Washington, Seattle, WA. 1Dept of Mathematics, University of Washington, Seattle, WA. 2Genomics Institute, Novartis Research Foundation, San Diego, CA. 3Affymetrix, Santa Clara, CA. 4Department of Microbiology, University of Washington, Seattle, WA. 5Department of Biochemistry, Stanford University, Stanford, CA. Genomic DNA microarrays (DNA chips) representing all open reading frames in the yeast Saccharomyces cerevisiae have proven to be a sensitive means of monitoring gene expression across the entire genome. We have tested the utility of such microarrays in mapping the topography of chromosome replication in yeast. Using a modified Meselson-Stahl density transfer experiment, we constructed replication profiles for all chromosomes in yeast, revealing the locations of origins and their activation times. Three lines of evidence support the validity of this method. First, we find a very good match between the chip data and the known locations and activation times of origins on chromosome VI. Second, every predicted origin that we tested on the previously uncharted chromosome X did indeed show origin activity (by 2-D gel analysis) and the replication times (tested by density transfer experiments) matched the predictions as well. Third, a separate experiment done with ORF arrays gave results largely identical to those obtained with oligonucleotide arrays. Analysis of the data for the whole genome has identified 376 putative replication origins - a good agreement with the previous estimate of 400 origins based on electron microscopy and DNA fiber autoradiography. The distance between adjacent origins shows a normal distribution, with a mean separation of ~32 kb. Origin activations occur throughout S phase, from very early to late S, the bulk of the origins being activated just before mid-S phase. These findings are consistent with timing data previously collected on a randomly selected set of origins. We anticipate that this new approach, coupled with the more directed approaches, will provide a powerful means of addressing questions that require large-scale analysis of replication, such as the pattern of replication in mutant strains. Furthermore, the method can be applied in principle to any experimentally tractable organism for which contiguous blocks of sequence are available. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10:50 -11:05AM Break ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 11:05-11:25AM Presenter: Trey Ideker, Molecular Biotechnology, University of Washington. Towards pathway modeling: Gene expression changes in yeast resulting from directed perturbations. T. Ideker1, V. Thorsson1, R. Christmas2, J Buhler3, R Bumgarner4, and L. Hood2. Departments of 1Molecular Biotechnology, 3Computer Science & Engineering, 4Microbiology, University of Washington, 4The Institute for Systems Biology, Seattle. A strategy is presented to successively refine a model of a biochemical pathway through analysis of gene expression profiles recorded over a series of directed pathway perturbations. To explore this strategy, whole-genome microarrays are used to monitor effects of perturbations to the galactose-utilization pathway in yeast. The current model is consistent with many expression-level observations, although unprecedented changes occur both within the pathway and over diverse metabolic processes. Automated search of a physical-interaction database indicates effects likely to be direct. Alternative models are proposed to account for new observations, along with additional perturbations to test these. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 11:25-11:45AM Presenter: Alexander Zrolka, QIAGEN, Valencia, CA, or Markus Ehrat, Zeptosens, Witterswille, Switzerland. Evanescent Field and Planar Waveguide Technology (PWG) in Microarrays for Gene Expression Monitoring. A Abel1, N. Scharer-Hernandez 1, H Schwarz 2, A Zrolka , M Ehrat 1, and A Schafer 2. (1) Zeptosens, Witterswill, Switzerland. (2) QIAGEN, Hilden, Germany. Current microarray technology is limited by its low sensitivity, high signal to noise ratio and low reproducibility. In order to realize the full potential of microarrays the technology must be capable of detecting in the range of <0.1(g of total RNA, <1x103 cells or <1x10-4 mg of tissue. Given the limitations of the currently available microarrays systems these detection levels have been out of reach. QIAGEN and Zeptosens are collaborating on the development of a fully automated microarray system for ultrasensitive detection in gene expression monitoring. By integrating Zeptosens PWG gene chip technology with QIAGENs expertise in sample preparation and instrumentation, extremely high levels of sensitivity and specificity have been achieved. Results will be presented which will illustrate the increased sensitivity and reduced signal to noise ration possible with the QIAGEN/Zeptosens microarray system. We will also report on work in progress to automate sample preparation, microfluidics, hybridization, image acquisition and bioinformatics. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 11:45AM -12:05PM Presenter: Eva Aw, Institute for Systems Biology, Seattle, WA. A Piezoelectric oligo synthesizer and microarrayer. C. Lausted, E. Aw, T. Dahl, S. Lasky and L. Hood. The Institute for Systems Biology, Seattle. A DNA probe arrayer is being developed to synthesize oligomers on solid or membrane supports using piezolectric printing. Individual nucleoside phosphoramidites are delivered by an economical, off-the-shelf, inkjet print head positioned by a precision servo system. As inkjet printing requires the use of a solvent exhibiting both high surface tension and low volatility, alternatives to acetonitrile have been tested for nucleoside coupling efficiency and a suitable candidate chosen. Array spot densities in excess of 5,200 per square centimeter are achieved. Total synthesis time for 27 slides of 5,200 20mer proves is less than eight hours. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12:05 - 12:35PM Presenter: Norman Gerry, Microbiology, Weill Medical College, Cornell University, New York, NY. Development of an Universal DNA Microarray for the Detection of Genetic Alternations N P Gerry, N E Witowski, G Barany, F Barany. Weill Medical College, Cornell University, New York, NY A new type of DNA microchip has been developed which combines polymerase chain reaction/ligase detection reaction (PCR/LDR_ with zip-code hybridization. The microchip is an array of 24-mer oligomucleotides, "zip-codes", having little or no homology to either the target sequence or to other sequences on the genome, covalently coupled to a 3-dimensional gel-matrix. Allele-specific LDR primers with zip-code complements on their 5-ends are used to direct LDR products to specific addresses on the array. By employing zip-codes, hybridization is independent of the genetic sequence of interest, eliminating false signals due to mismatch hybridization. Additionally, the zip-code sequences remain constant and their complements can be appended to any set of LDR primers, making zip-code arrays universal. Using K-ras as a model system, we have been able to correctly identify mutations in tumor and cell line DNA. Examination of the sensitivity of this system has demonstrated its ability to detect mutations present at less than 1 percent in a background of wild-type DNA. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12:35 - 1:50PM Lunch Break All lunches will be served at the South Campus Center - a 5-10 minute walk from Hogness Auditorium.. Exit on the south side of the Health Sciences Center and proceed across the street to the South Campus Center. Signs within the center will guide you to the distribution area for the lunches. You will need to present a lunch ticket to obtain lunch. Feel free to eat anywhere within the South Campus Center, except for the Portage Bay Caf on the lower level. Weather permitting, take your lunch outside and enjoy the view of the water.  Session One: (continued) Wednesday, September 6, 2000 Future Directions in DNA Array Technology, Novel Applications of Arrays ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 1:50 - 2:10PM Presenter: Don Montgomery, CombiMatrix Corporation, Snoqualmie, WA. Multiplexed Immunochemical Assays Using Microelectrode-Array Microchips. K Dill, D Montgomery, W Wang, and J Tsai. CombiMatrix Corporation, Snoqualmie, WA. Arrays of microelectrodes were used to produce biochips containing spatially multiplexed immunochemical assays. The first generation of these devices provide over 1,000 independently addressable assay locations on a footprint of less than one square centimeter. Implementation of diverse assay formats is facile with these devices and both direct capture sandwich assays and competitive assays are described. A wide range of analyte sizes and binding affinities have been explored. Analytes ranging from small peptides, such as saxitoxin, to large moieties, such as Bacillus globigii, can be detected simultaneously out of complex mixtures containing interfering analytes. Dilution series are built into the biochips to provide internal calibration and false positive discrimination. Biochips with arbitrary arrays of immunochemical assays can be produced overnight using fully automated manufacturing equipment. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Session Two: Wednesday, September 6, 2000 Applications(A). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2:10 - 2:30 PM Presenter: Anglique van 't Wout, Microbiology, University of Washington, Seattle, WA. Large Scale Analysis of Gene Expression Affected by HIV-1 Infection Using cDNA Microarrays. Anglique van 't Wout, S Mikheeva, G Geiss, M Katze, R Bumgarner, J Mullins Department of Microbiology, University of Washington, Seattle WA. With a relatively small genome, HIV-1 relies on host cell factors to survive and replicate. In addition, HIV-1 needs to interfere with cellular pathways aimed at destroying viral replication. Multiple cellular pathways are likely to be effected at various times during infection and by different molecular mechanisms. Ideally, one would like to examine all of the biochemical processes in a single experiment, so that the interplay between biochemical pathways can be visualized. An innovative approach that combines standard virology and molecular biology methods with recently developed robotics technology is being employed to determine the overall effect of viral infection on cellular gene expression. Using high density cDNA array technology the expression levels for 15,000 sequence verified unique human cellular cDNAs are being assessed in mock versus HIV-1 infected T cells at different times after infection. Customized software is then used to analyze expression patterns and identify clusters of genes belonging to specific cellular pathways affected by HIV-1. Results of several such analyses will be presented. Identification of cellular pathways affected by HIV-1 infection will likely lead to a better understanding of the pathogenesis of HIV-1 disease. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2:30 - 2:50PM Presenter: Deborah Diamond, Phd, Ciphergen Biosystems, Inc, Palo Alto, CA. mRNA-directed Protein Discovery in M. tuberculosis D Diamond, M Merchant1, N Kitagawa1, T Yip, M Wilson2, Gary Schoolnik2, 1Ciphergen Biosystems, Inc, Palo Alto, CA and Department of Microbiology and Immunology, Stanford University, Palo Alto, CA. Protein discovery initiatives hold the promise of pinpointing important disease targets for drug development. Surface-enhanced laser desorption ionization (SELDI) technology, developed by Ciphergen, is yielding intriguing data from efforts to track the acyl-carrier protein (ACP) of the pathogen, M. tuberculosis. Prompted by mRNA expression data from gene-chip arrays, we have used ProteinChip( analysis in conjunction with SELDI to characterize a protein with the properties expected of ACT, including molecular weight, charge, and increased expression following treatment with isoniazid. Efforts are currently underway to definitively identify this protein as ACP. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2:50 - 3:15PM Presenter: Gary K. Geiss, Dept of Microbiology, University of Washington, Seattle, WA. Microarray Analysis of HeLa cells Infected with Live and Inactivated Influenza Virus Identifies Changes in Host Cell mRNA Levels that are Eitehr Dependent or Independent of Viral Replication. GK Geiss1, M C An2, RE Bumgarner1, E Hammersmark1, D Cunningham2, MG Katze1,2. (1) Department of Microbiology, (2) University of Washington Regional Primate Research Center, University of Washington, Seattle, WA. Influenza virus, the causitive agent of the common flu, remains a world-wide health threat despite nearly seven decades of research. Studies of influenza biology have revealed elaborate mechanisms by which the virus shuts down host cell protein synthesis, evades the innate antiviral response, and facilitates production of progeny virions. Here, we investigated the effect of influenza infection on the biology of the host cell by examining the steady state mRNA levels for approximately 4600 cellular genes using cDNA microarrays. In order to determine if influenza induced changes in cellular gene expression were dependent or independent of viral replication, infections with active and inactivated virus were compared. The data show that at 4 hours post infection cellular mRNA levels were altered in both replication dependent and independent manner. However, as infection proceeds to 8 hours, replication dependent changes in gene expression increased while those signals independent of viral replication dissipated. In general, influenza infection resulted in the downregulation of many genes from diverse cellular pathways that may partially account for virus-induced inhibition of host cell protein synthesis. In contrast, the identity of cellular genes that were upregulated during influenza infection suggest potential roles in the host cells stress response or in the production of viral mRNAs or proteins. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 3:15 - 3:30PM Break ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 3:30 - 3:50PM Presenter: Jeffrey K. Ichikawa, Microbiology and Molecular Genetics, Harvard Medical School, Boston, MA. Application of High-density DNA Arrays to Study the Mechanisms of Pseudomonas aeruginosa Pathogenesis. Jeffrey K. Ichikawa1, M. Gita Bangera1, Matthew Wolfgang1, Roger Bumgarner2 and Stephen Lory1. 1Microbiology and Molecular Genetics, Harvard Medical School, Boston, MA 02115 2Department of Microbiology, University of Washington, Seattle, WA 98195 Pseudomonas aeruginosa, an opportunistic human pathogen, is known to cause acute infections in immunocompromised individuals and is the primary cause of mortality in cystic fibrosis patients. In order to determine the role of specific bacterial pathogenic factors in the disease state of afflicted individuals, we have used high-density DNA microarrays to monitor gene expression in both the bacterium and the host. The Pseudomonas expression arrays, representing each of the 5,570 predicted open reading frames, were used to asses the gene expression patterns of P. aeruginosa during growth conditions that are encountered during host interactions. These conditions include bacteria grown in media with differing calcium concentrations as well as growth in the presence of respiratory mucus. These experiments have identified a number of differentially regulated genes that were previously unknown, some of which may play a role in bacterial colonization of the host. Furthermore, we have used human gene expression microarrays, consisting of 4600 unique human cDNA clones, to monitor relative gene expression levels from human lung cell cultures that have been exposed to wild-type bacteria and isogenic mutants in different virulence factors. We have identified a set of differentially regulated genes that require P. aeruginosa type IV pili mediated adherence and the expression of specific bacterial products. Cluster analysis has been used to organize the genes into groups with similar gene expression. This analysis has identified genes involved in a variety of functions, however, many are involved in immune and inflammatory response signaling pathways and may play a role in the chronic lung disease of CF patients. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 3:50 - 4:10 PM Presenter: Lawrence Adams, Department of Pathology, University of Washington, Seattle, WA. Phenotypic Characterization of the Vulnerable Fibrous Plaque Cap in Atherosclerosis, Lawrence Adams1 Randolph Geary2, Eileen Mulvihill1 and Stephen Schwartz1, 1Department of Pathology, University of Washington, Seattle WA, 2Department of Surgery, Wake Forest University School of Medicine, Winston-Salem, NC. The atherosclerotic plaque is a complex vascular lesion lying luminal to the smooth muscle vessel wall media composed of a luminal facing fibrous cap, underlying areas of necrosis and reorganization frequently adjacent to luminal regions of diffuse smooth muscle rich intimal thickening. The intima is a smooth muscle layer thought to be the site of initial plaque formation and clonal evidence suggests that the fibrous plaque cap is produced by smooth muscle cells originating from the pre-existing intima. The fibrous plaque cap is important for plaque stability and its erosion to a weakened state can lead to plaque rupture and vessel occlusion via thrombosis. We have examined gene expression in fibrous plaque cap, intima and normal vessel media and compared these to whole undisected plaque using Research Genetics cDNA filter arrays containing ~21,000 known genes and ESTs in order to identify differentially expressed genes between each of these tissues layers in the carotid artery. 48 genes were differentially expressed between the intima and the media, 47 of these were higher in the intima including NMMHC-B, a known marker of the intima. 58 genes were differentially expressed between the intima and the fibrous plaque cap, 48 were higher in the intima. Clustering of these expression data showed there were 3 unique markers of the intima, GTP-binding protein GEM, NMMHC-B and Down syndrome candidate region 1-like 1 gene but no unique markers of the media or the fibrous plaque cap. Further clustering identified 3 genes which were expressed higher in both the media and the intima than in the fibrous cap and 1 gene that was more highly expressed in the intima and the fibrous cap than in the media. Finally we compared gene expression in the whole plaque, a complex tissue containing smooth muscle cells, macrophages and lymphocytes, to that of the smooth muscle rich media, intima and fibrous plaque cap. There were 14 genes consistently more highly expressed in the whole plaque than in these tissues, the highest being Catechol-O-methyltransferase and several ESTs. These data suggest that the media, intima and the fibrous plaque cap represent distinct vascular smooth muscle phenotypes. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 4:10 - 4:30 PM Presenter: Michael T. Barrett, Fred Hutchinson Cancer Research Center. Transcriptional analyses of diploid and tetraploid cell populations from primary Barretts esophagus epithelial cultures. MT Barrett1, J Anderson2, C Palanca Wessel2, M J Reid1and P. Rabinovitch1,2. 1Fred Hutchinson Cancer Research Center and 2Department of Pathology, University of Washington, Seattle, WA. The development of increased 4N(G2/tetraploid) fractions in patients with premalignant Barretts epithelium is associated with the loss of p53 function in cycling 2N cells and is a strong prognostic indicator for the development of aneuploidy and esophageal adenocarcinoma. Furthermore, studies in Barretts esophagus and in model systems have suggested that cycling tetraploid cells are unstable intermediates in the development of aneuploidy and cancer. To study the evolution of tetraploid clones, we have developed a series of primary Barretts epithelial cultures from biopsies of patients with early stages of Barretts esophagus. Flow-cytometric analysis at early passage indicated that each culture contained significant proportions (12-25%) of cells with 4N DNA content. Furthermore, approximately 50% of the 4N fraction present in each of the cell cultures consisted of cycling tetraploid cell population. Lesions in p53 (17p LOH and p53 mutation) were detected in 3 of 4 cultures while a fourth had no G1 arrest phenotype after gamma irradiation. In addition these cultures contain genetic lesions, 9pLOH and/or CDKN2/p16 abnormalities (4 of 4 cultures), 5q LOH (1 of 4 cultures) and 18q LOH (1 of 4 cultures) present in vivo. To study the development of tetraploidy in Barretts epithelial cells, 2N and 4N subpopulations of cells from each of the cultures were sorted viably using Hoescht 3342 labeling. Diploid cells were stored for RNA extraction while 4N fractions were returned to culture after sorting, and left undisturbed for several days. Subsequently these samples were resorted to obtain purified tetraploid populations for analyses. Total RNA was prepared from each sample after sorting then used to interrogate Affymetrix FL6800 and Human Cancer G110 Chips to determine the transcriptional profile of each cell strain and their 2N and 4N subpopulations. A small number of genes had a tetraploid-specific increase in their expression pattern. These included genes associated with chromatin structure (e.g. topoisomerase II, mitosin, CENP-A mitotic centromere-associated kinesin, kinesin-like spindle protein HKSP), G2/M phase of the cell cycle (e.g, cyclins A, B and F, CDC2, MPP1, ckshs2, nek-2), and proteolysis (e.g. cyclin-selective ubiquitin carrier protein) as well as some ESTs. In addition, we identified a smaller number of genes (e.g. serpins, G1-related proteins, and transcription factors) that had decreases in expression in the tetraploid cells. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 4:30 - 4:50 PM Presenter: Frank QH Ngo, Insititute of Radiological Sciences, National Yang Ming University, Taipei, Taiwan. The consequences of a repair gene deficiency to the global gene expression pattern: A cDNA microarray study of CHO and XRS-5 cells. F QH Ngo, LK Chen, JJ Wey, J YH Chan, D J. Chen, K. Peck. Institute of Radiological Sciences, National Yang Ming University, Inst. of Biomedical Sciences, Academia Sinica, Taipei, Taiwan and Lawrence Berkeley National Lab, Berkeley, Ca., USA Abstract not available at the time of printing ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Thursday, September 7, 2000 Session Three: DNA Arrays and the Study of Cancer ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 9:00 - 9:25AM Presenter: Kevin Brown, Research Center for Genetic Medicine, Childrens National Medical Center, Washington, DC. Identification of expression changes of prognostic and therapeutic value in metastasizing medulloblastoma. KM Brown, PH Cogen, YW Chen, B Rood, RJ Packer, DDA Stephan, T MacDonald. Research Center for Genetic Medicine, Childrens National Medical Center, Washington, DC. Medulloblastoma is a highly malignant cerebellar tumor of children and, less frequently, of adults, with a tendency of early recurrence and dissemination. Despite recent advances in patient survival, the quality of life for survivors is poor due to neurocognitive, neuroendocrine, and hearing deficits as a direct result of the whole brain and spine radiation required for prevention of metastatic disease. Using global expression profiling, we identified genes prognostic of tumor metastasis that may also serve as new therapeutic targets. An initial expression scan was done using a pooling approach, assuming that genetic heterogeneity would not be a significant confounding factor. We isolated total RNA from six metastasizing and six-non metastatic tumors, made biotinylated cRNA, and pooled samples from the two clinical groups in equimolar amounts. Gene expression profiles were generated using Affymetrix HuGeneFL Gene Chips (5600 genes). Two hundred sixty six genes showed differential expression greater than two-fold. The 58 genes expressed at least five-fold more or less between groups were selected for further analysis. Twenty one out of 30 genes with increased expression in metastatic tumors have been implicated for promoting: invasion/metastasis (14), cell growth (4), and angiogenesis (3). Twelve out of 28 genes with decreased expression in metastatic tumors have been implicated in inhibiting: invasion/metastasis (5), cell differentiation (6), and cell growth (1). Expression of each gene is being characterized via immunostaining (45/58 have available antibodies) and qRT-PCR using 48 frozen and 130 paraffin embedded tumors, and correlated with clinical and pathological data. This study has identified historically valid candidate genes involved in metastatic medulloblastoma, and has shown that a pooling strategy can be utilized effectively to identify candidate genes without complex statistical analysis, as long as validation studies are part of the study design. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 9:25 - 9:50AM Presenter: Peter Nelson, Fred Hutchinson Cancer Research Center, Seattle, WA. Microarray-based Analysis of the Androgen-Regulated Transcriptional Response Program in Human Prostate Cancer Cells. Bioyang Lin, James White, Camari Ferguson, Hugh Arnold, and Peter S. Nelson. Fred Hutchinson Cancer Research Center, Seattle, WA Normal and neoplastic prostate epithelial cells are dependent upon androgens for proliferation and the maintenance of normal secretory function. Genes regulated by androgens via direct or indirect interaction with the androgen receptor (AR) mediate a diverse range of processes in these cells. Our efforts have focused on the characterization of the androgen-response program with the aim of identifying genes and their cognate proteins that could be exploited for diagnostic, prognostic, and therapeutic benefit. Methods employed for comprehensive gene expression analyses center on the use of cDNA microarrays constructed from specialized EST resources derived from normal and neoplastic prostate tissues. We have used these arrays to interrogate the LNCaP androgen-responsive cell line and have identified more than 100 genes that participate in the androgen-response network including several novel genes that are prostate-restricted in their tissue expression profile. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 9:50 - 10:15AM Presenter: Ka Yee Yeung, Department of Computer Science and Engineering, University of Washington, Seattle, WA. Microarray analyses of premalignant Barretts epithelium and surrounding normal gastrointestinal tissues KY Yeung1, MT. Barrett2, J Delrow2, P L. Blount2, B J Reid2 and P S. Rabinovitch3. 1Dept of Computer Science and Engineering, and 3 Dept of Pathology, University of Washington, and 2Fred Hutchinson Cancer Research Center, Seattle WA. Barretts esophagus is a premalignant condition that arises as a result of chronic acid reflux in which the normal squamous epithelium of the esophagus is replaced by a metaplastic columnar epithelium. Patients with Barrett's esophagus typically have symptoms of gastroesophageal reflux, such as heartburn or indigestion and they frequently seek medical attention before they develop cancer. The Barrett's epithelium can be safely visualized and biopsied during upper gastrointestinal endoscopy. At the present time, total removal of Barrett's epithelium requires esophagectomy, a procedure with substantial morbidity and mortality. However, a systematic protocol of endoscopic biopsies can detect early curable cancers arising in Barrett's esophagus. Therefore, the standard of care for many patients includes endoscopic biopsy surveillance for the early detection of cancer. A fundamental question is the distinction between neoplastic Barretts epithelium and the surrounding normal tissues of the upper GI tract. For example, although it arises in the esophagus, Barretts epithelium more closely resembles the epithelium of the duodenum at the cytological level. Therefore we compared the transcriptional profile of BE to those of normal upper GI tissues including gastric epithelium, squamous epithelium of the esophagus and duodenal epithelium. In addition we searched for patterns of gene expression that were specific for each of the normal tissues and the neoplastic Barretts epithelium. Endoscopic biopsies from each tissue were collected from a series of patients during routine surveillance. Poly A+ RNA was prepared from pooled samples (2-4 patients/pool) of Barretts epithelium (n=4 pools), esophageal squamous epithelium (n=4 pools), gastric (n=3 pools) and duodenum (n=3 pools) and used to interrogate Affymetrix HU6800 and FL6800 chips. We investigated the distinction between the neoplastic Barretts tissue samples and the three GI tissue samples using Pearson correlation coefficient on the log-transformed data and Spearmans rank correlation. Although Barretts epithelium is a columnar epithelium that resembles that of the duodenum, we found that the correlation coefficients between Barretts epithelium and duodenum were not significantly different than those between Barretts and gastric, and between Barretts epithelium and squamous epithlium. In order to identify groups of genes with similar expression profiles in the four GI tissues we used the GeneCluster software [Tamayo et al. 1999] to filter out genes that do not vary significantly across the different tissue samples. Then, we compared the performance of several clustering algorithms (including CAST [Ben-Dor et al. 1999], k-means, and several hierarchical algorithms) with the methodology in [Yeung et al. 2000]. The methodology of [Yeung et al. 2000] suggests that the data set consists of approximately 10 clusters, and the best performance were obtained using CAST and k-means. From this analysis, we applied CAST to identify 10 clusters, among which some clusters were specific for squamous epithelium, duodenum, gastric, and Barretts epithelium. Furthermore, we applied a supervised clustering algorithm, which is a modified k-means algorithm with given patterns as initial centroids, to the data set, and identified more tissue-specific clusters. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10:15 - 10:40AM Presenter: Jeff Gregg, Department of Pathology, University of California at Davis, Sacramento, CA. Molecular Profiling Of A Mouse Model For Metastatic Breast Carcinoma. K Jessen, S Liu, L Yong, RD Cardiff1, J Gregg*. Department of Pathology, University of California at Davis, Sacramento, CA. Breast cancer is among the most common human cancers, affecting one in every eight women. One of the significant predictors of prognosis is regional and distant metastasis. As cancer is the consequence of a broad dysregulation or alteration of cell signaling pathways, the ability of cells to metastasize may be due to changes in a limited number of pathways related to invasiveness and metastasis. Our study focuses on gaining a better molecular understanding of these cellular pathways using a mouse model for mammary tumor metastasis. We are working with two transplantable mouse mammary tumor lines with significant differences in metastatic potential. Met-1 tumors develop 100% pulmonary metastases while Db-7 tumors exhibit significantly fewer pulmonary metastases (9%). In order to extract genes differentially expressed in both Met-1 and Db-7, we performed two suppression subtractive hybridization (SSH) experiments. From each of the subtracted libraries, 2600 clones were PCR-amplified and arrayed. By fluorescently labeling the unsubtracted Met-1 and Db-7 libraries and hybridizing them onto the microarray, we were able to demarcate the truly differentially expressed genes. Clones found to be greater than two-fold differentially expressed were then sequenced for identification. Differential expression of each unique gene was verified by RT-PCR, Northern blot, and Western blot. Additionally, RT-PCR was used to determine expression levels of these genes in other mouse tissue (normal mammary, lung, liver, etc.). In order to determine the function of a subset of these genes, anti-sense and sense constructs were introduced into cell lines derived from these tumors. Migration assays were performed and the metastatic potential of each gene was assessed. Using this methodology, we have identified several interesting genes that are both differentially and functionally important for the metastatic phenotype in this model. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10:40 - 10:55AM Break ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10:55 - 11:20AM Presenter: Kwong-Kwok Wong, Molecular Biosciences, Pacific Northwest National Laboratory, Richland, WA. Identification of differentially expressed genes in ovarian cancer by cDNA microarray. Kwong-Kwok Wong*, Rita S. Cheng, and Samuel Mok Pacific Northwest National Laboratory, Richland, WA. Ovarian cancer is the leading cause of death among women from gynecologic malignancies. There is a significant difference in survival rates between early and advanced ovarian cancer. The cure rate with stage I ovarian cancer approaches 90%. Unfortunately, two-thirds of the patients are diagnosed with advanced intraperitoneal metastatic disease, with a five year survival rate of 15 to 20%. Using the MICROMAX cDNA microarray system, we were able to identify genes differentially over-expressed in ovarian cancer. A total of 30 putative genes which differentially over-expressed in ovarian cancer cell lines were identified. The differential expression of some of these genes were further confirmed by real time RT-PCR. Using this strategy, we have identified genes that either overexpress in all cancer cell lines or in only some of the cancer cell lines. Further characterization of these genes will allow them to be exploited in diagnosis, prognosis, anticancer therapy and molecular classification of ovarian cancer. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 11:20 - 11:45 AM Presenter: Michl Schummer, Department of Molecular Biotechnology, University of Washington, Seattle, WA. Finding potential ovarian cancer marker genes through interrogation of a 100,000- clone cDNA array with 32 specimens Michl Schummer, Nancy Kiviat, 1Charles Drescher, Amir Ben-Dor and 2Leroy Hood. Department of Molecular Biotechnology, University of Washington, 1Swedish Medical Center, and 2Institute for Systems Biology, Seattle, USA Ovarian cancer is the forth most important cause of female cancer mortality, in large part because most women present with advanced disease. Current detection methods (CA-125 and TVS) do not have adequate specificity to allow for routine screening. Development of a sensitive, specific and inexpensive serum assay appropriate for use in the general population is therefore an important priority in ovarian cancer control. We used cDNA array technology to screen for one of the characteristics of marker genes: the overexpression in the carcinomas compared to normal tissues. The components of our study were: 1. Thirty-two well characterized tissues (normal ovaries, ovarian carcinomas, white blood cells and liver) obtained through a standardized protocol (for consistent RNA quality and minimizing tissue heterogeneity), associated with an extensive patient questionnaire (to support interpretation of expression patterns), matched with sera from the same patients for downstream analysis of marker specificity and sensitivity. 2. An array of 102,680 clones, derived from 3 unamplified ovarian cDNA libraries (normal ovary, late stage and metastatic cancer), arrayed onto nylon membranes in form of colonies. 3. Algorithms for the analysis of the complex hybridization patterns on a background of high variation due to tissue heterogeneity. We used statistical analysis and the "Bioclust" algorithm. We found 2650 clones representing 883 genes with stronger expression in the tumors, of which 476 represent known genes, 365 matched only to ESTs and 51 were novel genes. Some of the known genes were previously described cancer genes such as CD24, folate binding protein, c-myc, Her2/neu, mucin, metallothionein or c-jun, to name only a few. Detection of these genes demonstrates the power of our approach. Array hybridization is very well suited for the expression analysis of a large number of genes in many tissues, but for a single gene, the transcript values are less accurate, especially for those represented by only a few clones on the array. Therefore, we performed RT-PCR-based expression validation on a subset of the 883 genes based on the result of two separate cluster analyses of the dataset. In the first, we clustered the 2650 clones by their expression patterns in the 32 tissues, resulting in a considerable number of clusters where known tumor marker genes group with unknown genes. In the second approach, we clustered the 32 tissues by the expression of the 2650 clones, resulting in 50 clones of which the expression could discriminate the normal tissues from the tumors. From both approaches, the genes with either no homology to previously described ones or known genes coding for secreted or membrane-bound proteins were selected for validation by RT-PCR. To date, we examined 64 genes in ~150 tissues (among them 32 normal ovaries and more than 60 ovarian tumors and cell lines) of with 35 genes could be confirmed in their overexpression in the tumors. Four of these were also analyzed by Northern blot, further confirming their expression. Characterization by in-situ hybridization shows a expression restricted to tumor cells leaving out the infiltrating lymphocytes or stroma in three cases tested so far. In addition to expanding our in-situ hybridizations (both in number of tissues and genes tested) we are also screening for presence of antibodies and transcripts in patient sera. Finally, we have expressed fusion proteins from three of the candidate markers for the generation of monoclonal antibodies. This will ultimately lead to a serum assay. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 11:45AM - 12:10PM Presenter: Ami Ben-Dor, Chemical and Biological Systems Department, Agilent Technologies, Palo Alto, CA. Computational Methods for analyzing Cancer Gene Expression Data. Amir Ben-Dor(1), Zohar Yakhini1, Nir Friedman2, Michael Bittner3, Yidong Chen3, Jeff Trent3. 1Chemical and Biological Systems Department, Agilent Laboratories, 2Computer Science Department, Hebrew University, 3Cancer Genetics Branch, National Human Genome Research Institute, NIH/ Recent studies in molecular level classification of cancer tissues produced remarkable results, strongly indicating the usability of gene expression assays for cancer diagnosis and treatment assignment. In such studies expression levels of thousands of genes are measured across tens of tissue samples that come from two or more biologically distinct populations (Tumor vs. normal tissues or different types of tumor samples). In this talk we address computational aspects of classifying unknown samples into one of several known tissue types, based on expression data. A key step in the analysis is the gene selection process, in which genes are scored according to their relevance to the distinction between the different tissue types. We present two selection methods, one combinatorially based method, and one informationtheory based method. For both scoring methods we compute p-values, thus enabling statistical assessment of relevance. We will demonstrate software tools and describe analysis results as they apply to a recent study of the molecular classification of cutaneous malignant melanoma. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12:10 1:10PM Lunch - South Campus Center - Don't forget to take your lunch ticket! ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Session Four: Microarray Methods and Technology Development and Keynote Address ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 1:10 - 1:35 PM Presenter: Laurakay Bruhn, Agilent Technologies, Palo Alto, CA. Angiogenic endothelial cell subtracted cDNA microarrays fabricated using thermal ink jets. Laurakay Bruhn*, Doug Amorese, Mike Caren, Scot Collins, Larry Daquino, William Fisher, Diane Ilsley, Samar Lightfoot, George Matcuk1, Tom Quertermous1, Kyle Schleifer, Larry Stanton, Christina Sum, Richard Tella, Cathy Templin, Heidee Villanueva, Peter Webb, Mark Westall, Debra Wiest, and Jay Wolgemuth1, Agilent Technologies, Palo Alto, California, 1Stanford University School of Medicine, Division of Cardiovascular Medicine We have developed a process to print high-density arrays of cDNAs onto modified glass surface by Thermal Ink Jet (TIJ) deposition. To characterize the performance of our system we have executed a series of controlled experiments that were designed to carefully measure the reproducibility, sensitivity, and reliability of expression data. These results show that cDNA microarrays produced by our TIJ deposition system are capable of generating highly reliable gene expression data. Angiogenesis is the process by which blood vessels form from either existing vessels or de novo and is critical to the development of the vasculature, the progression of cancer, arthritis and numerous inflammatory diseases. In a functional test of our complete system, we have generated cDNA microarrays from subtracted libraries derived from tube-forming endothelial cells induced to undergo angiogenesis in vitro. Experimentation with these microarrays are expected to reveal genes that are endothelial cell specific, induced or suppressed during the angiogenic process and operative during angiogenesis in vivo. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 1:35 - 2:00 PM Presenter: Sepp Saljoughi, Operon Technologies, Incorporated, Alameda, CA. Validation of sequence optimized 70 base pair oligonucleotides for use on DNA microarrays. John ten Bosch, Chris Seidel, Sajeev Batra, Hugh Lam, Nico Tuason, Sepehr Saljoughi, and Robert Saul, Operon Technologies, Incorporated, Alameda, CA. In general, current microarray protocols utilize double stranded PCR products spanning the entire open reading frame (ORF) as the DNA targets immobilized onto glass slides. We have synthesized 6,307 70-mers representing each ORF in Saccharomyces cerevisiae for use on arrays designed to monitor gene expression. Each of these sequence optimized oligos was designed to minimize cross hybridization of homologous genes and to allow a Tm normalization of 74C ( 3). We choose a subset of these genes with known function in either the peroxide stimulon, diauxic shift, or heat shock response in order to measure specificity and sensitivity of arrays containing both optimized 70-mer oligos and PCR products spanning entire ORFs. Array results were validated via quantitative RT-PCR Reactions. Whereas ORF targets of genes with a high degree of homology resulted in similar gene expression profiles, optimized oligos were able to differentiate the unique expression profiles for these genes. We believe Operon sequence optimized 70-mers are more specific than longer gene targets, offer a sufficient amount of sensitivity, and are cost effective. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2:00 - 2:25 PM Presenter: Kerrin S. Small, GeneMachines, Inc., San Carlos, CA. Printing Large Scale Custom DNA Microarrays with the GeneMachines OmniGrid"! Microarrayer. Kerrin S. Small, Jeremy T. Dabrowiak, David P. Henninger, Poonam S. Medberry, Joshua E. Kuhl and Jacques Fayet-Faber GeneMachines, San Carlos, CA. As the field of genomics develops, the need for custom arrays has exploded. The role of a flexible, low cost and high throughput microarrayer is critical to meeting the demands of researchers. The OmniGrid microarrayer offers a robust, high-speed and fully integrated solution for creating DNA arrays. Data on the instruments precision, accuracy, flexibility and throughput are discussed. As an example of these parameters, a fully unattended OmniGrid microarrayer is capable of printing 20,000 spots/slide in 7 hours onto 100 slides using 48 pins. The OmniGrid allows for repeated and random access of unique samples within a microtiter plate, as well as inter-plate access among 74 microtiter plates, for construction of entirely customized microarrays. Solutions to minimize the effects of environmental variables on array consistency during extended print runs are presented. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2:25 - 2:40PM Break ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2:40 - 3:00PM - Presenter: Patricia Bresnahan, Molecular Dynamics/APBiotech, Sunnyvale, CA. Integration of an Automated Slide Processor into an Expression Analysis System for cDNA Microarrays. Patricia Bresnahan, Allan Hayle, Hrissi Samartzidou, Roland Howe, Sarah Driver, Anna-Karin Brundin-Storm1, Peter Jones, Phyllida Roe, Tom Houts, Tom Freeman, Brian Munday and Hans Albertsen, Molecular Dynamics/APBiotech, Sunnyvale, CA. Experimental reproducibility is critical for producing consistent and reliable gene expression data from cDNA microarrays. Further, high throughput systems require automation in all aspects of data generation and analysis. The function of the Automated Slide Processor (ASP) is to provide automated pre-treatment, hybridization and washing of microarray slides, while also offering performance advantages over manual hybridization methods. We demonstrate that compared to manual methods the ASP enhances hybridization efficiencies uniformly across the slide, raises signal intensities, and reduces non-specific signal. By minimizing demands on users time, rigorously controlling environmental conditions and reducing variability introduced by manual manipulations the ASP provides a significant contribution to automation of microarray processing. In this report we summarize results using the ASP protocols for several APBiotech slide chemistries. We will also discuss the re-use of hybridized probe, and document the effects of hybridization time and probe concentration on signal strength. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 3:00 - 4:00 PM Keynote Address: Killer Viruses and DNA Microarrays: What can we Learn and How Soon? Michael G. Katze, Professor of Microbiology and Associate Director of the Regional Primate Research Center, University of Washington, Seattle, WA. Dr. Michael Katze, is Professor of Microbiology and Associate Director of Molecular Sciences at the Regional Primate Research Center, at the University of Washington. Katze has long been interested in understanding how viruses evade the host defense interferon system. His laboratory has studied several different virus systems including influenza virus, adenovirus, poliovirus and the primate lentiviruses, HIV-1, HIV-2 and SIV. Recently he received a grant from the National Institutes of Health to focus on understanding the molecular mechanisms by which hepatitis C virus, which infects more than 2 percent of the worlds population, evades the antiviral effects of interferon. He is the author of more than 100 scientific publications and has been instrumental in setting up the Center for Expression Array Analysis, using DNA micro-array technology, in the Department of Microbiology and the Regional Primate Research Center. In 1999 he was named one of two 1999 recipients of the Milstein Award by the International Society of Interferon and Cytokine Research (ISICR). The Milstein Award is given to individuals who have made exceptional contributions to research related to interferons and cytokines in a basic or clinical field. Katze was honored for his work studying virus-host interactions and the evolutionary battle between viruses and the cells they infect. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 4:00 - 7:00 PM Session Five - Attended Poster Session, Wine and Cheese reception and Vendor Exhibition. South Campus Center, Room 316, immediately following our Keynote Speakers presentation. Tickets must be presented at the door to enter the reception. ______________________________________________________________________________________ Wine and Cheese Reception Sponsored by :  Friday, September 8th, 2000 Session 6: Applications(B). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 9:00 - 9:25AM Presenter: Igor Borisevich, German Cancer Research Center, Heidelberg, Germany. Transcription factor CREM dependent expression during mouse spermatogenesis Borisevich I.* , Beissbardt T., Hrlein A., Klewe-Nebenius A., Korn B., Vingron M., Schtz G., German Cancer Research Center, Heidelberg, Germany. CREM belongs to the CREB family of transcription factors. CREMt, a transcriptional activator splice isoform is highly expressed after the meiosis in the round spermatids. Based on the high level and time of expression, CREMt is thought to be the major trigger of expression at the late spermatogenesis. We generated CREM deficient mice by gene targeting. CREM deficient males are sterile due to an arrest of spermatogenesis at stage 2 of round spermatid development. Cells of all further stages including spermatozoa are absent. By the subtractive cloning we cloned the CREM-target messages, i.e. expressed in wild type but not in the CREM deficient mouse testis. 12000 clones were analysed by sequencing and hybridisation. Redundancy of this library has been reduced by high density filter hybridisation with the most abundant clones. 950 clusters of sequences were obtained: 79 known mouse genes, 81 homologies to known genes, 170 different mouse ESTs, 91 ESTs from other spices, 21 homologies to genomic and 139 novel sequences. High density filters were generated by the spotting of the PCR products of non redundant clones. The expression profiling and profile clustering shown the specific expression of cloned messages during spermatogenesis: a - most of the clones are expressed in adult wild-type but down regulated in adult CREM deficient mice; b - the cloned messages are expressed at the same time as CREMt transcription factor. In testis of 9, 17, 19 and 21 day old wild type mice most of the messages are expressed at low level or not at all. At day 23 (second day of high expression of CREMt protein) some more messages are up regulated, and at day 25 the maximum level of expression is reached. At day 27, expression declines (probably due to the suppression of expression by chromatin compaction). Our data comprise extensive new information on gene expression during spermatogenesis, provide a selection of genes as candidates for direct CREM target genes and may be applicable to the diagnosis and treatment of male infertility. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 9:25 - 9:50AM Presenter: David Pritchard, University of Washington, Seattle, WA. Identification of genes differentially expressed during aging in multiple human tissues. D. Pritchard1*, V. Demas2, G. Burmer2, and P. Rabinovitch1; 1University of Washington , 2LifeSpan Biosciences, Seattle WA. Using high density cDNA microarrays containing 6000 genes, we searched for genes differentially expressed between 10 different pairs of young and old human tissues. From these studies we have identified several hundred "aging" genes that are consistently up- or down-regulated during aging in multiple human tissues. Some of these "aging" genes have been previously identified as genes whose expression changes during aging. Many of these "aging" genes are involved in processes such as translation, signal transduction, or energy generation whose function is known to be affected during aging. We have used different clustering techniques (k-means, som, hierarchial) to cluster our expression data. This analysis has indicated that most clusters are differentially expressed during aging in one or more tissues. Furthermore, many of the "aging" genes are clustered with similar expression patterns suggesting that they may function in common biological pathways. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 9:50 - 10:15AM Presenter: Alison Murray, Center for Microbial Ecology, Michigan State University, East Lansing, MI. Application of DNA microarrays to assess relatedness between microorganisms on a gene by gene level. Alison E. Murray*, Doug Lies, Gary Li, Ken H. Nealson Jizhong Zhou, and James M. Tiedje, Center for Microbial Ecology, Michigan State University, East Lansing, MI. Central to the study of microbial evolution and ecology is having an understanding of the relationships between different organisms - in what ways they are functionally similar, and what makes them different. Advances in microbial phylogenetics using the small subunit ribosomal RNA gene have revolutionized the ways of thinking about the relatedness among members of the Archaea and Bacteria. However at the level of closely related species or strains, there are few differences in this gene (e.g. > 95% sequence similarity). Furthermore, though tremendously informative from a phylogenetic standpoint, the SSU rRNA gene provides few clues as to what are the actual relationships between different microorganisms, or what makes phylogenetically related organisms distinct ecological species. Arguably, the species concept is not well defined for microbial species. Microbial genome sequencing and comparative genomics promise to shed light on the relationships between microorganisms. We have undertaken a project to evaluate whether a DNA microarray designed with genes from one organism (Shewanella oneidensis, MR1), can be used to assess homology between the reference strain (MR1) and other species in the Shewanella genus. A pilot microarray was constructed with 192 PCR-amplified genes. Most genes on the array were selected because of homology to genes with roles in energy metabolism and electron transfer. Organisms in the Shewanella genus utilize a diverse repertoire of terminal electron acceptors when respiring, and can be found in a broad range of environments. The results suggest that there is a high correspondence between the relationships predicted from both SSU rRNA and DNA gyrase (gyrB) gene phylogenies and the relatedness predicted from hierarchical cluster analysis of microarray hybridization data between different Shewanella species. The results of parametric and nonparametric methods of data analysis were compared using various data processing and clustering algorithms. Regardless of the algorithm used, both universally conserved and universally heterogeneous gene clusters were consistently identified with the same core genes in each cluster. The results suggest that there are strain specific differences between MR1 and DLM7 in the genes involved in anaerobic respiration such as the genes coding for trimethylamine-N-oxide, and nitrite reductase (nrfD). Among all species investigated, several enzymes with general housekeeping function such as genes coding for ATP synthase, a ribosomal protein, and lysyl-tRNA synthetase were universally conserved. This approach to studying microbial relatedness provides an information-rich level of understanding of the specific genomic content between closely related microorganisms, and should prove to be quite useful from evolutionary, ecological, and taxomonic perspectives ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10:15 - 10:40AM Presenter: Anis H. Khimani, Microarray Applications, PerkinElmer NEN Life Sciences, Boston, MA. Molecular Analysis Of A Developmental Neurological Disorder, Rett Syndrome, Using Microarrays Jonathan Pevsner2 Anis H. Khimani1, Carlo Colantuoni2, Jeffrey B. Killian1, Russell K. Garlick1, and Jonathan Pevsner, 1NEN Life Science Products, Inc., 549 Albany Street, Boston, MA 02118, 2Kennedy Krieger Research Institute, Department of Neuroscience, Johns Hopkins University, 707 North Broadway, Baltimore, MD 21205. The detection of mutations in the methyl-CpG-binding protein 2 (MECP2) gene has suggested the basis of the neuropathology in Rett Syndrome (RS). However, the molecular mechanisms and the genetic interplay leading to this developmental, neurological disorder have remained unknown. We have used microarray technology to identify genes that undergo changes in expression levels in the course of the disease. Age-matched, post-mortem brain samples from RS patients and normal control individuals were compared. The differential expression of these genes was consistent with conventional methods such as RT-PCR, subtractive hybridization, protein analysis, and immunohistochemistry. The microarray analysis revealed dramatic changes in expression of 20 genes, and a subset of these genes are functionally related to MECP2 activity. The changes in expression patterns are also distinctive and consistent with the neuropathology of RS. This is the first study using microarray analysis to understand the molecular events underlying the pathology of a neurological disease such as RS, and the first step to unveil some early diagnostic markers of the disease. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10:40 - 10:50AM Break ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Presenter: Joachim Theilhaber, Aventis Osteoporosis Team Aventis Pharmaceutical, Cambridge, MA. FINDING TARGET GENES IN PATHWAYS RELEVANT TO OSTEOPOROSIS BY NEAREST-NEIGHBOR CLASSIFICATION OF EXPRESSION DATA Joachim Theilhaber, Timothy Connolly, Steven Bushnell and Aventis Osteoporosis Team Cambridge Genomics Center, Aventis Pharmaceuticals We have constructed a classification tool called GENNC (Gene Expression Nearest Neighbor Classifier) that analyzes expression data and assigns genes to a functional pathway by using a training set composed of genes which have been assigned a functional role beforehand, on the basis of expert knowledge. In performing this classification, GENNC uses the so-called ``k nearest-neighbors'' method, in which the preassigned functional class most prevalent in the k nearest neighbors of a given gene is the one that is assigned to the gene. A capital feature of the methodology is that one can estimate error rates in the classification process, a feature which is difficult to implement in the currently prevalent clustering approaches. We have used GENNC to identify potential targets in the treatment of osteoporosis, by analyzing expression data obtained from several murine pluripotent precursor cell-lines grown under conditions that promote or inhibit the pathway to mature osteoblast formation. We focus on the C2C12 cell line under treatment by BMP-2 (bone morphogenetic protein 2), and show how the nearest-neighbor analysis of time-courses yields classifications of genes into the bone, muscle or adipocytic pathways, with concomittant estimates of misclassification errors. We have furthermore conducted biological cross-validation of the genes assigned to the bone pathway, by looking for bone-tissue specificity of the candidate genes in a tissue expression data base, and for correlation with time-courses in bone (calvaria) primary cell cultures derived from newborn mice: both of these cross-validation studies support the putative assignment of these genes to the bone pathway, and suggest additional filtering criteria for choosing drug target candidates. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Presenter: Carl S. Brown/ Paul C. Goodwin, Biotechnology group, Applied Precision, Inc., Issaquah, WA. Gene Expression Resolution and Process Control in the Analysis of Microarrays Carl S. Brown 1, Paul C. Goodwin 1, & Peter K. Sorger 2 1 Biotechnology Group, Applied Precision, Inc., Issaquah, WA 2 Department of Biology, Massachusetts Institute of Technology, Cambridge, MA The ability to finely resolve gene expression levels, relative to a control, is an important goal of cDNA microarray technology. A series of issues involving fabrication, hybridization, scanning, and analysis, however, currently limit expression resolution. Our goal is to eliminate scanner and analysis limitations, and then to enable the refinement of both microarray fabrication and hybridization chemistry. Based on the observation that certain spot quality problems yield systematically incorrect ratios, we have developed eleven process control features for monitoring spot quality. Such spot quality problems are often detectable only with high resolution, high signal-to-noise, and well-aligned images. Even in the case of good quality spots, background subtraction errors can reduce ratio accuracy. To address this problem, we have developed a novel background subtraction technique that more accurately calculates expression ratios. Rather than using preset thresholds to determine whether a given genes expression level is different from the control, our method uses a statistical method of identifying genes whose expression levels are significantly different from the norm. Confidence limits are then used to identify regulated genes, which provides a statistical certainty to the results. Overall, our findings indicate that a scanner with high signal-to-noise, detector linearity, spatial resolution, and sub-pixel wavelength alignment is essential for fine expression resolution and tight process control. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Presenter: Anoop Grewel, Silicon Genetics, Inc., Redwood City, CA. Workbench and Database Solubtions for Gene Expression Analysis Anoop Grewel and Andrew Conway, Silicon Genetics Inc., Redwood City, CA. Gene Expression Arrays are considered one of the foremost tools in the field of Functional Genomics. Equally important, however, are the tools that will maximize the knowledge that can be gleaned from the massive amounts of data generated from use of this technology. To this end, we have developed GeneSpring and GenEx, two solutions for desktop gene expression analysis and enterprise-wide gene expression database management, respectively. We will review the functional features that comprise these two software products; these include tools for clustering, visualization, automated annotation, and data sharing and storage. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Presenter: Hrissi Samartzidou, Molecular Dynamics, Part of Amersham Pharmacia Biotech, Sunnyvale, CA. Microarray ScoreCard: An Integrated Analysis Tool for Evaluating Data Quality in Microarray Experiments Hrissi Samartzidou*, Leah Turner, Tom Houts, Hans Albertsen and Matthew Frome Changes in gene expression profiles can be quantitatively detected using microarrays. However, microarray measurements are often biased by factors that are not well understood. One way to minimize the bias associated with microarray measurements is to utilize a group of control samples of known concentration and ratio as internal references. For this purpose, we have developed the Microarray ScoreCard system to allow the GenIII Spotter user to include predefined targets and probes on individual slides to evaluate the experimental data across multiple experiments. The Microarray ScoreCard system consists of two interdependent components: the control plate, including DNA to be spotted and corresponding labeled probes ("spike mixes"), and the ScoreCard analysis software. The software features quality measurements to allow evaluation of data quality, assessment of the overall microarray system performance, and data normalization within and across individual experiments. In this poster, we show the Microarray ScoreCard system used to analyze several microarray experiments. The experimental data demonstrates that quality measurements from Microarray ScoreCard can be used to help the user differentiate between good and bad results, and reject poor quality experimental data as invalid. In addition, the data presented suggest that Microarray ScoreCard normalization improves overall data quality by improving the accuracy and precision of the measurements. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Lunch ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Presenter: Shishir Shaw, BioDiscovery, Inc., Los Angeles, CA. Automatic Spot Quality and Confidence Inference for Gene Expression Analysis A. Petrov, S. Shah*, B. Hoff, A. Kuklin, and S. Shams Microarrays for gene expression analysis pose a rather serious challenge for statistical inference on the quality of data. This task may be performed by a human operator or by image processing algorithms. Without assessing the reliability of the data, the conclusions drawn from analyzing such data may be misleading. Very often such errors can lead to following a false hypothesis or missing important findings. Spot variation is caused by several problems including mechanical limitations in the spotting process, missing spots, lower-than-measurable expression level, empty wells in the plates used for array fabrication, etc. In addition to the spot position variations, the shape and size of the spots may fluctuate significantly due to variability in concentrations of the DNA and salt, contact space between the tips and the slide surface, etc. This talk will present techniques for quality and confidence assessment based on statistical spot measurements. Information about the array image, including signal, noise, and background quantification, can be used to determine the presence or absence of a spot at each array location. For each spot, we will present procedures for estimating the data confidence based on understanding the signal and shape properties. The methods presented will be illustrated through the use of experimental data. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Presenter: Robert Nadon, Imaging Research, Inc., St Catharines, Ontario, Canada. Outlier detection, statistical inference, and power analysis for gene expression arrays Robert Nadon, Peidi Shi, Erik Woody, Nezar Rghei, Peter Ramm. Gene expression arrays present unique challenges for statistical inference. The typically small number of replicated expression values in array studies make the use of standard parametric statistical tests problematic. Such tests have low sensitivity and return potentially inaccurate probability values. We report novel alternative statistical modeling procedures which circumvent these difficulties by estimating measurement error based upon replicate variability within entire arrays. The procedures, which can be used with both micro- and macro-arrays, include outlier detection, confidence intervals, statistical tests of differences between conditions, and statistical power analysis for determining number of replicates needed to detect between-condition differences of specified magnitude. The methods will be illustrated with experimental data. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Presenter: Bruce Hoff, BioDiscovery, Inc., Los Angeles, CA. Data Mining and Visualization Tools for Gene Expression Analysis B. Hoff*, S. Shah, A. Kuklin, S. Shams Microarray assays produce a large number of quantified gene expression values. Data typically represent thousands or tens of thousands of gene expression levels across multiple experiments or patient samples. The efficient discovery of valuable, non-obvious information from such large collections of data is termed data mining. In other words, data mining is the discovery and application of transformation procedures, which present the data in an intuitively understandable form. One of the typical microarray data analysis goals is to find statistically significantly up or down regulated genes, the so-called outliers or 'interestingly' behaving genes in the data. Another goal is to find functional groupings of genes by discovering similarity or dissimilarity among gene expression profiles, or predicting the biochemical and physiological pathways of previously uncharacterized genes. We discuss the procedures of clustering and principal component analysis (PCA) for analyzing multivariate data. In the microarray application, these techniques aid in the discovery of genes which have unusual behavior or which can be grouped with other similarly behaving genes. We discuss the relative strengths and weaknesses of several clustering algorithms, and the interpretation of the often subtle results of PCA. Another consideration, which is tightly linked with analysis, is the choice of visualization method used for viewing the results of the transformed data. We discuss the judicious use of scatter plots, dendrograms, and time series plots to present data such that our visual system can naturally extract meaningful patterns from the data. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Closing remarks, Roger Bumgarner. 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