Overview

Dr. Kenny Beckman is Assistant Scientist and Director of the Functional Genomics Core at CHORI. From a doctoral background in plant biochemistry (he studied the host-pathogen interaction between potato and the blight fungus Phytophthora infestans as a graduate student at the University of Cambridge in England), Dr. Beckman followed an interest in oxidative stress to research on aging at U.C. Berkeley in the laboratory of Bruce Ames.

During his postdoctoral studies, Dr. Beckman developed methods for measuring trace oxidative damage to DNA, and applied these methods to studies of vertebrate aging. Most recently, he took a two-year sabbatical from academia as co-founder of Gorilla Genomics, a research reagent company in Alameda, CA. Since mid-2002, Dr. Beckman has been developing the Functional Genomics Core at CHORI, while establishing an independent research program surrounding the genomic response to oxidative stresses, the role of nutrient-gene interactions in cellular homeostasis, and the overall transcriptional control of cellular defenses and repair.

Functional Genomics
During the past decade, there has been a technological revolution in the way that the life sciences are conducted, commonly referred to as the “genomics” revolution. Initially, this label was applied to large-scale sequencing projects, such as the global Human Genome Project and similar efforts dedicated to organisms such as E. coli, yeast, the fruit fly, the round-worm C. elegans, and the laboratory mouse. In recent years, however, as the technologies developed in support of these large-scale efforts have spilled over into the rest of biomedical research, the term “genomics” has come to mean much more. By now, “genomics” refers to research which is driven by primary genomic sequence information, and in which hundreds to tens of thousands of genes are analyzed simultaneously.

The principle factors driving genomics have been: 1) the complete sequencing of the human genome—and dozens of other genomes—during the past five years; 2) the development and commercialization of robots and other devices capable of handling tens of thousands of samples, which is required in parallel studies of all of the genes in a genome; 3) developments in computing which now provide any researcher who has a few thousand dollars with an extremely powerful personal computer capable of dealing with large data sets; 4) developments in the related field of “bioinformatics,” which have resulted in software for manipulating and analyzing millions of data points from tens of thousands of genes and thousands of samples.

Perhaps most significantly, the adoption of genomics has been driven by an evolution in the mind-set of research scientists, who have now embraced a “discovery-based” model for research that differs from and is complementary to “hypothesis-driven” approaches. Traditionally, most biomedical research has been driven by hypotheses about specific molecules, structures, genes, and so on. Most experiments, in other words, have been pursued in order to test out a specific model about how a known molecule, cell, organ, or organism works. The sequencing of the human genome, of course, made it evident that scientists were studying no more than 10% of identifiable genes. Genomics, in essence, permits scientists to try to discover the identities and functions of the remaining 90% of genes. In other words, many genomic experiments have no explicit hypothesis about a known gene, as they are focused on unearthing different kinds of information, such as the functional identities of uncharacterized genes, or previously unknown associations between disparate genes and gene families.