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SNP Chips Driving Revolution in Dairy Cow Breeding


NEW YORK (GenomeWeb) – In the early 2000s, the US dairy industry realized it had a problem: while important economic traits in its cows such as milk production and fat content had been greatly increased using genetic breeding techniques, fertility had been steadily falling for decades.

"The Holstein breed had been bleeding fertility out of its cows," Curt Van Tassel, a researcher at the US Department of Agriculture's Agricultural Research Service, told GenomeWeb. Partly it was due to oversight. Fertility, measured by the likelihood a cow would become pregnant after artificial insemination, had largely been ignored. Taking it into consideration helped the problem from getting worse, but because fertility is a lowly heritable trait it seemed a major challenge to reverse the trend and get fertility metrics on the rise.

But at the same time as fertility was bottoming out, another trend began to rise in the industry: breeding using a strategy called genomic selection, which applies data from high-density, chip-based SNP genotyping. The 50,400-SNP bovine BeadChip was borne out of a 2006 deal between the USDA and Illumina and by 2008, the USDA began releasing data from these genotyping projects for use in breeding. Because of low levels of genomic recombination in the Holstein cattle breed, flanking SNPs can offer a lot of information on what's in between, even if the SNPs themselves have nothing to do with the biology of the trait they offer information on. It's a kind of black box approach where the results speak for themselves.

Less than a decade into the genomic selection era of dairy cow breeding, the results are extremely positive, according to a new study led by Van Tassel, which was published today in the Proceedings of the National Academy of Sciences.

"Everybody's anxious to document what the impact has been and we concluded that it was far enough along that we could at least make some sense of the change in the industry," he said.

Data presented in the study suggest that fertility metrics are on the rise again. "It's looking like we're recovering ground rapidly using genomics," Van Tassel said. And the effect on fertility is just one example of the ways genomic selection is helping breeders.

Genetic gain and metrics for valuable milk production traits are on the rise while the speed at which traits are being incorporated into the population is approaching biologically defined limits.

"These results clearly demonstrate the positive impact of genomic selection in US dairy cattle, even though this technology has only been in use for a short time," the authors wrote in PNAS, adding that "It is unlikely that a state of equilibrium has been reached, and these estimates may not reflect the full impact of genomic selection."

There's still room for improvement and it could well be reached, as the dairy industry is genotyping tens of thousands of animals every month and that figure could continue to grow exponentially, Van Tassel said.

"Genetic selection in dairy cattle took off around the 1950s with advent of artificial insemination," Kurt Weigel, an expert on genomic selection at the University of Wisconsin-Madison, told GenomeWeb. It allowed much higher selection intensity on male animals. "Instead of a bull on every farm you could have a few to serve the entire country," he said.

But assessing which bulls carried the best genes for improving milk production was challenging. "Males don't give any milk so anything interesting is measured in females," Weigel said.

To get any information about a bull's contribution to milk production would take at least two years, when the bull's daughters would have their first calves and begin lactating. "By then he's five years old, which is a tremendous time lag," Weigel said.

Progeny testing driving genetic selection was the most advanced way to breed animals for decades, but in 2001 things started to change after Norwegian bioinformatician Theodorus Meuwissen and Australian animal geneticist Michael Goddard published their seminal paper on genomic selection.

"They proposed taking dense marker data to predict genetic values," Van Tassel said. "The dairy industries around the world had been predicting genetic values using a combination of pedigree and performance data for almost a hundred years. The novelty was that genomic data could speed up the process.

"The idea is that we use the linkage and linkage disequilibrium between the markers and the causative effects, so that we find the gene combinations that are most advantageous without having to identify them," Van Tassel said. "It's not critical that one understands the biology in making this system run. It's certainly in one's interest to understand the biology of what one is doing, but it's not strictly necessary to make the system crank."

But without SNP chips, it was a system that couldn't be implemented.

Following his work on the bovine genome project and the bovine HapMap project, Van Tassel recognized that it was time to create a high-density SNP chip. He helped put together a grant to fund development of the Illumina bovine BeadChip, which contained more than 50,000 SNPs, what was considered high-density at the time.

Today, 50,000-SNP chips are the workhorse of the dairy breeding industry and are considered medium density, running at approximately $100. High-density chips made by Illumina and primarily used for research and on elite bulls contain almost 800,000 SNPs and cost $250. Low-density chips containing 10,000 to 20,000 SNPs are also available for approximately $40, primarily used by regular farmers.

Illumina and Thermo Fisher Scientific subsidiary Affymetrix offer several bovine SNP genotyping products.

"The challenge is you don't gain much as you go from the medium to high-density," Weigel, the UW-Madison scientist, said. "You don't gain selection accuracy because there's no new information coming. You get more SNPs telling you the same thing you already knew."

Prior to genomic selection, a breeder might spend $50,000 to test each bull. Now high-density genotyping only costs about $250. "That's why it's so much more useful, because status quo was this expensive, time-consuming process of weighing and measuring performance," Weigel said.

In the case of fertility, genomic selection allowed researchers to find markers for regions that might cause genetic defects in a homozygous recessive pattern that led to embryonic death. 

"We were able to uncover very quickly a dozen genetic defects in the main dairy breeds that way," Weigel said. "And it was possible only because of the SNP chips."

In addition to fertility, generational interval is another metric demonstrating the success of the genomic selection program. The age of the bull when his son is born has dropped from about 7 years to under 3, meaning useful genes are selected for much more rapidly. "We're approaching biologic limits on puberty," Van Tassel said.

That has a particular effect on those operating in the niche area of dairy cow artificial insemination, he said. "If you are at the top of the heap, it will take very little time for the competitor to get to that same model very quickly." The Holstein Association keeps a list of elite bulls, ranking them by genetic value. "Before genomics there was a bull mentioned that was sitting at the top of the bull list for six or eight years," Van Tassel said. "Today's top bulls may survive at the top for six or eight months."

While genomic selection has been rapidly adopted in the dairy industry, it hasn't been as widely adopted by beef cattle breeders. "There are legitimate reasons for that," Van Tassel said. Artificial insemination isn't as widespread, it isn't as dominated by one breed like Holsteins dominate diary, and early economic indicators like birth weight can be measured in bulls. But that doesn't mean genomics isn't being applied in that industry.

"You can't measure meat quality until the animal is dead," Van Tassel said. "That's an area where they could benefit. Traits measured late in life are the ones for which it'd be nice to know the information sooner."

Meanwhile, genotyping in dairy cattle continues to grow. Van Tassel estimated that the US is genotyping 10 to twenty times the number of cattle as it was just a decade ago.

And with all that data, more specific studies into that actual biology behind the SNPs could help improve animal health and, eventually, milk production.

Weigel said the best estimates are that hundreds of genes affect milk production.
"Are we going to be able to figure out where each is and what's the mutation? Not tomorrow but maybe in ten to twenty years," he said.

"We spent 20 years hunting [for quantitative trait loci] and only found a few," Weigel said. Genomic selection has helped breeders spread beneficial gene regions without knowing exactly how they worked. But Weigel said eventually dairy cattle genomics will come back to finding specific genes. "You do actually need to know what's going on," he said.