The Center for Genomic Science Innovation is a center in the UW-Madison Office of the Vice Chancellor for Research and Graduate Education (OVCRGE). The mission of the CGSI is to advance genomic science by creating new methods of genome-enabled biological measurement, new computational approaches to analyze those data, and new ways of integrating approaches to answer questions in biology. CGSI also maintains a strong commitment to education, administering two training grants that support graduate and postdoctoral trainees to become the genomic leaders of tomorrow.
CGSI is a sister center to the UW-Madison Biotechnology Center (UWBC), whose mission is to provide cutting-edge technologies through fee-for-service facilities. CGSI and UWBC maintain a close relationship to facilitate the delivery of new genomic approaches developed in CGSI through UWBC resources.
Information for the public on the field of genomics and the history of CGSI are found below. We welcome you to explore our pages to find out more about our research, educational activities, and commitment to collaborative genomics.
Genomics studies how information in an organism’s DNA blueprint is encoded and enacted to create living creatures.
Scientists have technology to “read” the complete DNA sequence of an organism, called the genome. The order of four chemical compounds called nucleotides specifies information that cells can read; yet our ability to interpret the genome sequence remains limited. The field of genomics is developing new technologies to study genome sequence, genome structure, biological processes encoded in genome sequences, and how changes in DNA relate to changes in organismal form and function.
Genomic science is uncovering new information about how biology works.
A better understanding of how cells and organisms function enables scientists to use that information to better the world around us. A better understanding of how genomes function reveals how organisms may change in response to mutation, disease, or environmental changes. This knowledge translates into direct benefits to society.
Genomic science benefits society:
Personalized Medicine: a person’s genome will eventually influence preventative care, treatment plans, and paths to better health.
Agriculture: genomic science enhances selective breeding for crop and animal traits, including disease resistance and productivity.
Conservation biology: genomics in wild populations helps track, predict, and ideally combat the effects of environmental change.
Industry: genomics fosters the development of better industrial microbes and biologics.
Basic scientific discovery: Genomics provides a new view into biology and how it works.
History of the CGSI
The Genomics Revolution of the late 1990s presented a new world of biological discovery, by ushering in the age of genome sequencing. Technological advances in reading the base-pair sequence of DNA (invented by CGSI member Lloyd Smith) enabled reading an organism’s complete DNA blueprint for the first time, fostering new questions into how information is stored, read, transmitted, and in some cases, disabled in individual organisms. This development was synergized by Pulsed Field Gel Electrophoresis (invented by CGSI member David Schwartz), which enfranchised megabase-sized DNAs as workable substrates and helped set the stage for the Human Genome Initiative. Sequencing of budding yeast and E. coli genomes (the latter by emeritus faculty Fred Blattner and contributed to by CGSI member Nicole Perna) led the way, followed by drafts of the first human genome sequences in 2000. These large-scale, multi-billion dollar sequencing and mapping efforts were instrumental in pushing major advances in biology. With representative genomes in hand, for the first time researchers could catalog genes regulatory elements, repetitive sequences, and replication mechanisms; understand how genic and intergenic content was organized across chromosomes; and begin to address what makes living creatures tick.
The Genomics Revolution truly transformed how scientists explore the living world. Beyond sequencing representative genomes, it became feasible to sequence and compare many genomes within and across species. The resulting catalog of sequence differences could then be associated statistically with phenotypic differences across individuals, including those linked to plant and animal diseases. These efforts also supported large-scale mutagenesis studies in which every single gene identified in representative genomes could be deleted and the resulting mutant phenotypes dissected. Accessible sequencing and available genomes spun off other technologies, including methods to identify all RNAs, proteins, and protein-nucleic acid associations in the cell and follow their dynamic changes during development, in response to environmental changes, and across life cycles. The emergence of each new technology was often followed by new computational methods to manage data and extract biological insights.
But with decreasing sequencing costs and increased accessibility of sequencing technologies over the last two decades, the Genomics Revolution has undergone its own evolution. Genome sequencing is now a ‘no-brainer’ starting point for biological investigation, and genomic applications like RNA and chromatin sequencing are part of the standard toolkit of molecular analysis. Off-the-shelf analysis methods enable many labs to incorporate existing genomic methods into their research programs. However, a critical gap that emerged in the wake of the genome ‘reading’ revolution is our ability to interpret genome sequences to predict how a DNA blueprint produces a living organism. We have little functional understanding of how the parts list encoded in a genome produces a complex biological system with emergent properties that vastly exceed the sum of those parts. In turn, predicting how genetic variation impacts phenotype is a significant hurdle. For example, while sequencing technologies enabled genome-wide associations that link genetic variants to disease, in most cases we have no idea why variants cause dysfunction and thus little predictive power to address it. This is especially true for non-Mendelian, multi-genic traits including many plant and animal diseases. Predicting complex cellular phenotypes, and in particular variations in those phenotypes from genomic sequence, remains a critical Grand Challenge in biology.
Tackling this Grand Challenge requires highly collaborative science that integrates new ways of interrogating biological systems, new methods of gleaning insights from the data those methods produce, and new approaches for integrating information to answer biological questions that could not be addressed before. Reaching this goal also requires interdisciplinary collaboration to nimbly respond to new research opportunities. It is in this light that the Center for Genomic Science Innovation (CGSI) was formed.