Just as variety is the spice of life, it’s also a key focus for those behind the “Efficient Dairy Genome Project”. As they seek to apply genomics in breeding dairy cattle that are more feed efficient and produce less methane, scientists know that genetic variance could be the difference between success and failure.
“We’re examining the transcriptome (RNA) and genome (DNA) of dairy cattle to improve feed efficiency and reduce methane emissions,” said Stephanie Lam, a PhD student working with Dr. Angela Cánovas and Dr. Filippo Miglior at the University of Guelph.
Can you spot the difference?
Using public data available from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO), Lam and her colleagues developed a methodology for accurately detecting structural changes or variations in dairy cattle DNA. They then applied the method to another dairy cattle population from the center consisting of Holstein and Jersey cows. The goal was to find genetic variance in the genome – such as insertion, deletion or duplication of base pairs - of animals with high feed efficiency.
“Essentially we are seeking genetic clues to help us determine what makes certain animals more feed efficient than others. When we see structural changes in DNA between two extreme groups of animals with high and low feed efficiency, it’s possible that these changes in the high efficiency group are behind their improved metabolic performance.”
Through their research, the team found about 14,000 SNP’s that were unique to either the high or low group. A SNP or single nucleotide polymorphism is a variation at a single DNA site, and is the most frequent type of variation in the genome.
Of course, not all variations will necessarily have a functional impact on metabolic pathways or biological processes, so the next step was determining which SNP’s or genetic markers were causal. Using specially designed software, the team found 400 – 500 SNP’s that may have a functional impact on feed efficiency.
“We then took the 400 – 500 SNP’s and, using the same software, found that the genes containing these SNP’s were mainly associated with metabolic pathways related to fat metabolism and protein digestion and absorption. That suggests that these markers may play a role in regulating feed efficiency and helping cows perform more effectively when it comes to milk production.”
Though the work itself is highly complex, the possible implications for the dairy industry are both easy to understand and exciting to ponder.
“Once we identify these key markers, we can incorporate them into SNP panels or even make custom panels to specifically select for feed efficiency in a herd. By evaluating two different cow populations, we are confirming genetic information and narrowing our focus to what is most important. In doing so, we can provide producers and industry with applicable results that have more functional data and reliability.”
Lam is pleased with the progress thus far. At the same time, she is encourage by how the work to date could fuel further research and possible breakthroughs.
“These results help us decide what we can do in our next studies. For example, we have a lot of genes associated with fatty acid metabolism and protein digestion, so we may want to look at more specific target tissues related to those pathways. When we find common genes across breeds, it can assist future studies in deciding what genes to focus on regarding genetic markers that relate to feed efficiency.”