Steak fans may soon reap the benefits of the genomics revolution. A new project will help scientists create bovine breeds genetically selected to produce bountiful supplies of perfectly marbled steaks.
Scientists at several U.S. and Canadian research institutes are collaborating with Illumina, based in San Diego, CA, to develop a bovine gene chip, similar to those used to study the genetics of human disease. The DNA chips, expected to be on the market early next year, will dramatically speed the search for the genetic variants that underlie desired traits, such as the level of marbling in a cut of meat or the efficiency of a dairy cow’s milk production.
“This opens a whole new scale of gene identification in cattle,” says Jerry Taylor, professor of animal genomics at the University of Missouri-Columbia and one of the researchers on the project. “We’ll be able to tackle genetics of all of these traits–reproductive capability, milk production, milk composition, and quality of meat–in ways we never before envisioned.”
The sequence of the cow genome was released last year, but scientists have made little progress in identifying genes associated with desirable bovine traits, for the same reasons that have slowed human studies of complex genetic diseases: vast amounts of genetic data are needed to narrow down the gene variants linked to a particular trait.
Now scientists are planning to pool data from revised drafts of the bovine genome and other studies to create this genetic tool–a tiny glass chip coated with thousands of short sequences of DNA that can detect sites in the genome that frequently differ among individuals. Researchers at the U.S. Department of Agriculture, University of Missouri-Columbia, and University of Alberta are now choosing the specific sequences that will be included on the chip.
The chips will allow scientists to quickly and cheaply gather genetic data on huge numbers of cattle. Scientists can take a DNA sample from an animal and use the chip to simultaneously detect thousands of genetic variations, giving a detailed profile of that animal’s genome. Thousands of individual profiles are then analyzed in conjunction with data on each animal’s phenotype (its observable, physical characteristics) to determine the variations associated with a particular characteristic, such as growth rate.
Breeders of dairy cows are particularly excited about the gene chips. Currently, they can’t tell if a bull produces high-quality progeny–meaning cows that make lots of milk–until the bull’s female calves grow up. If scientists can find a genetic pattern that quickly and cheaply identifies desirable bulls, the breeding process would be much more efficient. “We’re looking at changing the costs from tens of thousands to under one thousand dollars,” says Curt Van Tassell, a geneticist at the U.S. Department of Agriculture in Beltsville, MD, and a collaborator on the chip project. Van Tassell and the team plan to start such an analysis as soon as they finish designing the chip. “We hope to have genetic prediction machinery within a year of having collected data, with a higher-resolution model in two years,” he says.
The chip could also shed light on how breeding has shaped the bovine genome. Missouri-Columbia’s Taylor plans to characterize the genetic variation in different breeds of cattle, creating a bovine map that’s much like the human HapMap released last year, which mapped the genetic diversity of people from all over the world (see “A New Map for Health”). The researchers also plan to look at related species, such as bison, water buffalo, and the now-extinct auroch, an ancestor of modern cattle.
Early results of the bovine genetic testing suggest that breeding for particular qualities, such as high milk production, hasn’t selected for two or three specific variants associated with that trait. Rather, years of breeding have produced selection pressure across the genome in a complex pattern. “Small differences in many genes leads to big differences in underlying phenotype,” says Taylor. “It’s much more subtle than you might think.”
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