By Leo Barolo
The rapid development of sequencing technologies has catapulted genomics from research settings to practical applications, including advances in agriculture. Genomic analysis is now used routinely in a variety of ways, from selective animal breeding to trait diagnostics.
But animal science is also emerging as a powerful model to study fundamental questions about how genotype and environment modulate animal phenotypes. With farm animals as research subjects, very large populations coupled with carefully monitored environments and breeding schemes create an incredible system for genomic research.
The UW-Madison Department of Animal and Dairy Sciences is pushing the field of animal genomics forward. As one of the world’s leading research facilities focused on animal nutrition, physiology, management and genetics, the department includes a diverse and collaborative team of experts and exceptional resources. Together, these are producing cutting-edge basic and translational research, spanning the study of fertility, transgenerational inheritance, feeding optimization and more.
Advantages of Domesticated Animals as a Unique Genomic Resource
Farm animals offer unique opportunities to advance genomic applications and genetic research. Large populations of animals with information on molecular markers spanning the whole-genome greatly facilitate genetic analysis. Thanks in part to advances by department chair Kent Weigel, genotype imputation strategies developed in humans, combined with extensive animal pedigree information, has produced a genomic relationship matrix for thousands of animals.
“This works even better in animals because most of these breeds are highly inbred, and so we don’t need as many genetic markers to cover the whole genome”, adds Weigel. This advance led to an eight to tenfold reduction in genetic testing costs, enabling widespread genotyping on farms, in some cases on every calf born.
As such, one of the resources available to the department includes fully genotyped research animals for genetic analysis. This includes 80 cows on the UW campus and a total herd size of about 1500 cows, including heifers and young calves at other UW-affiliated farms such as Arlington and Marshfield.
“That’s twice as much as everybody else and tenfold bigger than some universities,” says Weigel.
In addition to genotype information, climate-controlled environments and measuring strategies produce very detailed phenotypes for individual animals. These include milk production and body weight but also novel traits like feed intake and methane emissions. These traits in turn reflect on animal productivity (and thus farming costs), fertility, and environmental impact.
Innovative analysis of this information helps farmers decide which animals to breed, but also allows researchers to test broader genetic inquiries that influence genomic research as a whole.
Researchers in the Animal and Dairy Sciences Department are using these unique tools to make important advances in applied genomics and basic genetic and genomic understanding at large.
One area is using machine learning for whole-genome based phenotypic prediction, where an individual’s traits can be predicted from the genome analyzed as a whole, rather than by considering individual genes.
Most traits of interest are polygenic, with hundreds of genes contributing to the phenotype. Many traits are also heavily influenced by environmental factors, such that specific genes only explain a fraction of the phenotypic variation. While these features present a challenge in medicine, where the goal is to identify and study individual genes, breeders are most interested in predictive power.
“We don’t necessarily try to find the genes; we have molecular markers or even the full DNA sequences, and we build prediction models,” explains Professor Guilherme Rosa, who collaborates with Weigel on the research. “We predict what we call breeding value of the animal for genetic improvement. We do this using machine learning and artificial intelligence tools.”
Rosa combines genomic information with detailed descriptions of the environment and management in which animals are raised, such as diet, vaccination, and weather variables, to make these predictions. “Any specific animal or genetic background can perform completely differently depending on the environment and management practices they are subjected to.”
He also develops analytical techniques to measure and monitor novel phenotypes using digital tools, so that whole-genome prediction models can help farmers select the best individuals for target traits in different environments. With as little as a hair or blood sample, animals can be genotyped and their future performance predicted, as well as their progeny’s.
Integrative Genomics to Understand Traits
Another area of study is understanding the relationship between genotype, environment and traits of economic or environmental interest.
Assistant Professor Francisco Peñagaricano is studying several of these traits, including fertility, heat stress, feed efficiency, and methane emissions in dairy cows. His work integrates data from whole-genome bisulfite sequencing, transcriptome sequencing, and proteomics along with whole-genome scans and gene-set analysis. Using integrative methods, Peñagaricano is able to pinpoint candidate genes and functional gene sets related to the trait.
Peñagaricano is one of the leading researchers studying male fertility in cattle, instead of female fertility that is typically of focus. He points out that cattle are an excellent model to study environmental impacts on fertility.
“If you are using the same bull in different herds in different parts of the country, you have an optimal design to evaluate sire (the bull used for breeding) conception rate. And with that you can have a better measure of the fertility of the bull,” he explains.
Another important perspective focuses on climate change. In an effort to make the dairy industry more environmentally friendly, Peñagaricano is studying the genetics of feed efficiency and methane emissions. This has important implications since cow digestion produces almost a third of methane greenhouse gas emissions in the US. “It’s a concern of the society and the dairy industry has to address it”, says Peñagaricano.
Researchers are also preparing for what is to come since increased temperature impacts dairy cow performance. Peñagaricano is using marker-assisted breeding as a novel genomic strategy for improving thermotolerance and fertility, understanding candidate genes and functions in the process.
Together, this information helps farmers breed animals that produce more milk or body mass for less feed, increasing profits while minimizing environmental impacts.
Traits of interest also relate to humans and other systems
Peñagaricano hopes that his research reveals insights into human fertility if mechanisms are conserved between bulls and humans. He notes the difficulties of determining the genetics of fertility in humans, who are mostly monogamous and typically produce few offspring, hindering genetic analysis.
Several faculty in the department are studying how different individuals respond to variations in nutrition, an important trait that spans many organisms including humans.
Associate Chair Hasan Khatib is using sheep to investigate how diet-induced epigenetic changes and associated phenotypes are transmitted to subsequent generations.
Using whole-genome bisulfite sequencing, Khatib investigated the effect of paternal diet on sperm DNA methylation across 3 generations of sheep and the phenotypic outcomes of diet exposure. The work suggested over 100 epigenetic marks that were inherited across generations. The work also showed that reproduction and growth traits of an individual were affected by grand-paternal diet, even when that individual was never exposed to dietary changes.
Khatib and Peñagaricano both highlight the value of livestock for controlled studies. In humans, transgenerational epigenetic inheritance is largely inferred from observational data such as the Dutch Hunger Winter. However, animal models allow for system intervention to test hypotheses. Khatib’s lab was able to tease apart the effects of genetics and diet using sheep twins reared in the same conditions except for their diet. This type of environmental manipulation is challenging in human studies.
The collaborative environment within the department, as well as its unique animal resources, offer exciting opportunities for cross-disciplinary collaboration, both within the department and also across campus. Researchers in the Animal and Dairy Sciences Department welcome these opportunities for broader collaboration.