Microarray researchers from 15 countries flocked to Seattles Pier 66 last week to discuss applications, analysis, and technological aspects of DNA and protein chips at the second annual Northwest Microarray Conference.
The three-day conference included talks on novel statistical methods for analyzing microarray data, presentations on the results of microrray experiments covering areas as diverse as the effect of cell phone radiation on gene expression and the effect of melanoma on opossums (see p. 5), and talks on novel technologies such as multicolor arrays and protein chips. A selection of conference highlights follows:
Roger Bumgarner, the conference chair and director of the University of Washingtons microarray facility (see p. 8), opened up the conference with the prediction that microarray labs would be using prefabricated arrays within the next couple of years, and that arrayers would only be used for boutique organisms that would not be profitable for private companies to produce.
Wilhelm Ansorge, of the European Molecular Biology Laboratory, discussed his labs work to develop protein chips with a three-dimensional chemistry that he said is comparable to the Harvard chips produced by Gavin MacBeath. The chip, which employs antibodies labeled with Cy3 and Cy5 dyes, also allows you to detect proteins at different times, Ansorge said. He also mentioned that his lab is developing a 76,000 probe human cDNA chip.
Chun Cheng, a biostatistician at the Fred Hutchison Cancer Research Center in Seattle described a new regression modeling approach to identify differentially expressed genes that also accounts for the effect of multiple covariant factors, such as tissue type, gender, or age. This approach, Cheng said, allows you to test specific hypotheses on single genes, as well as allowing adjustment for chip-to-chip variations. The algorithm will be incorporated into software called GenePlus that will also include visualization tools. GenePlus is being developed and spun out into a private company by Luo-Ping Zhao at the Hutchison Center.
During a talk on microarray experiments with yeast, Stephen Oliver of the UKs University of Manchester said, Its very important in the near future that we have access to each others raw data, because different [normalization regimes] can move data in different directions. These different normalization regimes had caused Olivers data to diverge from data produced in a similar experiment by Pat Browns lab at Stanford. The only way to find out why this was the case was to examine the statistical parameters and data analysis methods the two groups had used.
David Galbraith of the University of Arizona said that microarrays enable systematic studies of cross hybridization for p450 genes in Arabidopsis. He said he believed it was essential to know the full sequence of each array alement. He has made his Arabidopsis Cy p450 microarray database freely available to the public at http://genomica.agmarley.arizona.edu/ P450.htm
Kyle Serikawa of the University of Washington discussed Translation State Array Analysis, an experimental method that uses microarrays to determine mRNA expression at different states of translation. Serikawa is collaborating with Ruedi Aebersolds lab at the Institute for Systems Biology in Seattle to study how protein levels correlate to mRNA levels at different points in the translation.
While the current method Serikawa is using examines translation state vs. pre- and post- translation states in yeast, he proposed a new method in which RNA isolated from about 25 different time points in translation would be used as samples to test the way the actual pattern of gene expression moves through time. This new method, however, would potentially require 25 times more arrays than the current method. When an audience member asked where researchers would get the money to buy all these chips, Bumgarner, who collaborated with Serikawa on this research, quipped, some day they will become like potato chips.