A couple of years ago, at TIGR’s Genome Sequencing and Analysis Conference, the microarray was an upstart technology that most speakers ignored because it had little to do with the main topic of discussion — sequencing.
But at this year’s conference, held in Savannah, Ga. (Sept. 21-24), microarrays were almost a given: At least 12 of the 34 speakers wove microarray technology into their talks, more as a taken-for-granted-as-indispensable tool of genomic research than as the object of such research.
In the opening night’s talks, Steffan Jansson of the Umea Plant Science Center in Umea, Sweden, discussed how he and his colleagues are using microarrays in their study of the Populus genus of evergreen trees — aspens and cottonwoods — as a model system for tree genomics. At the end of September, the group released a 25,000-EST Populus array, spotted with cDNAs from over 100,000 ESTs sequenced in 19 cDNA libraries. Jansson and colleagues are now using these arrays to study expression patterns in wood-forming tissues, the xylem of the tree. “We can find the genes expressed during different stages of wood formation,” he explained. Understanding this process has potential economic value, according to Jansson, as the lumber industry is a major part of economies in countries such as Sweden and Canada.
Meanwhile at the theoretical level, Lee Hood, founder of the Institute for Systems Biology, discussed in his plenary speech how systems biology involves studying a system within an organism — a “biomodule,” by perturbing that system at a defined point, then seeing how the system changes —and how microarrays are one tool for detecting these changes. As an example, he cited ISB researcher Andrea Weston’s work to study galactose metabolism in Saccharomyces cerevisae, in which she induced 20 galactose genes, then used microarrays to study the effects of these perturbations on gene expression in the galactose metabolism pathway. By studying the gene expression at different time points, Weston could observe how this biomodule operated in a temporal, dynamic manner, Hood said.
On Monday, Rick Wilson of the Washington University Genome Sequencing Center discussed how his group is using comparative genomic hybridization on microarrays that contain sequence from BAC clones tiled onto the array, to compare genomic DNA from patient and control samples in studies of genetic mutation in prostate cancer, non-small cell lung cancer, AML, and other diseases. These arrays can represent an entire chromosome of interest, he said, and can “reveal regions of a particular chromosome where there may be a disparity of copy number,” or “deletions or amplifications between the two samples.” Nigel Carter of Wellcome Trust Sanger Institute said in another talk that his group is also using CGH for studies of chromosomal disorders and chromosomal mutations in different cancers.
Stephen Chanock of the National Cancer Institute spoke on how microarray data provides a springboard for further study on gene expression, SNPs, and cancer. As part of an interdisciplinary program, the Cancer Genome Anatomy Project, his group has begun resequencing genes that were implicated in a 2000 Nature paper as differentially expressed in different subtypes of breast cancer [See Perou et al, Molecular portraits of human breast tumours, Nature 406, 747-752 (2000)]. “We’ve taken these particular genes which fall out of microarray analysis,” said Chanock, and are resequencing them across the 5’ upstream region, the entire coding region, intronic segments with high similarity to other species such as mouse, and the 3’ region. They resequenced these genes in tumor DNA from 92 Norwegian breast cancer patients, along with 100 controls from the same population, looked at the SNPs to establish linkage disequilibrium and haplotype structure, and are currently comparing this data with expression array data, to get a better picture of the way genetic variation and gene expression interact in breast cancer. “I feel strongly we need to bring the world of haplotypes and SNPs” to expression arrays, he said.
Kam Man Hui of the Cancer Center in Singapore spoke about his group’s use of spotted and Affymetrix arrays in gene expression studies of liver cancer; and Joseph Nevins, of Duke’s department of molecular genetics and microbiology, brought microarray technology from bench to bedside, in detailing how gene expression profiles of breast cancer subtypes derived from microarray experiments are being used in a clinical setting as “clinico-genomic predictors of disease recurrence” to aid in treatment decisions. Nevins said applying genomic data to the clinic is only possible when “the higher ups” see that it is important.