Sweet corn story begins in UW-Madison lab
This week, scientists are revealing the genetic instructions inside corn, one of the big three cereal crops. Corn, or maize, has one of the most complex sequences of DNA ever analyzed, says University of Wisconsin–Madison genomicist David Schwartz, who was one of more than 100 authors in the article in the journal Science.
“The maize genome is a true maze — full of confusing repeats and dead-ends that have troubled would-be sequencers for years,” says Schwartz.
Publication of the genome is expected to advance knowledge of corn’s ancestry, and also guide breeders trying to extract even more productivity from a crop that is expected to produce more than 200 million tons of grain from more than 87 million acres in the United States this year.
Producing the genome sequence required input from a unique optical mapping facility in the Laboratory for Molecular and Computational Genomics at UW–Madison.
Unlike traditional gene sequencers, who examine DNA letter by letter, the optical mapping system looks at bigger pieces, and that has positioned the lab’s research as a key complementary component for working with the data produced by gene sequencers.
The first step in optical mapping system is to stretch out long, string-like DNA molecules and stick them to electrically charged glass plates. These molecules are sliced up into a series of consecutive chunks, marking them in the same way as a grocery bar code, and then painted with a fluorescent dye.
When the bar-coded molecules are exposed to a blue laser, the amount of fluorescent light they emit reveals the length of each bar-code feature. The microscopes in the optical mapping system are fully automated, so millions of bar-coded molecules can be pieced together to reveal the structure of a genome.
The optical map supplies a scaffold, or big-picture view, of the structure of the DNA under study, says Schwartz. “Traditional sequencing must work on small chunks at a time, but the maize genome is incredibly complex, full of repeats, and that’s confusing. It’s like buying a 10,000-piece jigsaw puzzle; from looking at one piece, it’s hard to know if you are looking at the dwarf’s foot, or Snow White’s face. Our optical maps, just like the box cover, give the big picture that allows the sequencers to link up their smaller pieces into a complete genome.”
Shiguo Zhou, Schwartz’s colleague who did much of the heavy lifting in the optical map of maize, says the optical mapping system was “incredibly cost-effective and invaluable in dissecting the infamously complex maize genome.”
Zhou and Schwartz were the principal authors of a companion article in PLoS Genetics, which explained how they made the optical map of corn.
At the center of the Schwartz system is a series of automated microscopes that run 24 hours a day, seven days a week. “For the maize genome, we looked at about 2 million molecules. If you had to do that by hand, hunched over a microscope, you would grow dizzy from boredom,” says Schwartz.
Once the optical information is obtained, it is correlated with the letter-by-letter information coming from the gene sequencers. That statistic-intensive process is handled by hundreds of networked computers, running software that were created by Schwartz’s collaborators Michael Waterman and his student, John Nguyen, and enabled to run on Miron Livny’s computer cluster in the department of computer sciences.
“The maize optical map is by far the most complex example of genome analysis via single molecules,” says Schwartz, who with Zhou recently mapped the plant disease that caused the deadly Irish potato blight, and continues to affect potato and tomato farmers today. “It was created using completely new techniques which greatly surpass conventional sequencing and all available next-generation sequencing methods and platforms in terms of completeness, speed, accuracy and cost.”
Scientists say the speed-ups and cost reductions now affecting DNA analysis are akin to those once seen in the computer industry, and it is only a matter of time before it’s routine to analyze an individual case of cancer. Because cancer has so many genetic variations, such analyses will likely lead to a period of “personalized medicine” in which the treatment is matched to the genetic makeup of a particular tumor, not by the averaged response gathered from broad-based studies.
“The maps we make tell us a lot about us, touch the food we eat, and the organisms that can make you sick,” says Schwartz. “I believe this system is going to help deliver cost-effective personal genomics, and that will allow more effective diagnosis, earlier detection of cancer, and unclog the pipelines for new drugs. This work points the way toward new tools for exploring personal genomics.”
