Investigating genetic markers using novel sequencing technology to improve the selection for feed efficiency in beef cattle

The importance of selecting for feed efficiency in the beef industry

Improving the selection for production traits, such as feed efficiency, may bring economic and environmental benefits for beef production. Currently, one of the major challenges in the beef industry includes high feed costs, which can represent approximately 70% of total production costs. Due to this, the selection pressure for feed efficiency in cattle has been increasing. Improved feed efficiency can reduce feed conversion ratio and production expenses, resulting in economic benefits for the beef industry. In addition, cattle with higher feed efficiency are expected to use metabolic energy more efficiently, which can lead to reduced enteric methane production and lower greenhouse gas emissions from beef systems. However, measuring feed efficiency is often cost-inefficient and impractical at the farm level. The most commonly used measure to calculate feed efficiency is residual feed intake (RFI; expressed as kg/d), which is the difference between expected and actual feed intake. Currently, this method, among others, is costly, time consuming, and labor demanding. This emphasizes the importance to investigate alternative ways to improve feed efficiency of the herd using genomics.

One way to improve the efficiency of feed use is to incorporate selection for feed efficiency in breeding programs. Conducting functional genomics studies comparing cattle with high and low feed efficiency is an effective strategy to identify genetic markers (mutations or 'SNPs' found in the genome associated with a trait of interest) related to feed efficiency. These genetic markers can be incorporated into commercial breeding programs. Our research aims to detect genetic markers found within differentially expressed genes related to feed efficiency and improve the understanding of the biology and metabolic pathways underlying genetic markers and key regulator genes that may influence the function and regulation of feed efficiency in beef cattle.

The importance of improving feed efficiency for beef production system profitability and environmental sustainability.

Figure 1. The importance of improving feed efficiency for beef production system profitability and environmental sustainability.

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Current Research using genomics and novel sequencing technologies

Innovative scientific technologies are continuously being developed and improved to advance research methods in the field of livestock genetic studies. Among them, a new technology available is high-throughput transcriptome sequencing analysis, known as RNA-Sequencing (RNA-Seq). RNA-Seq is used to measure gene expression in the entire genome of the animal (approximately 24,000 genes in the beef cattle genome). In addition, this technology could be used to detect genetic variants and markers, such as SNPs (single nucleotide polymorphisms). Recently, this tool has been critical in the identification of functional genetic markers associated with economically relevant traits in livestock, which has helped provide a more in depth understanding of the genetic architecture of important production traits such as feed efficiency, health, fertility, and meat quality traits in beef cattle.

In this study, we used RNA-Seq analysis to identify genetic markers within genes that are expressed in different tissues related with feed efficiency (ie. muscle and liver) of high and low feed efficient beef steers.

Workflow diagram to identify genetic markers related to genes and metabolic pathways involved with feed efficiency in beef cattle.

Figure 2. Workflow diagram to identify genetic markers related to genes and metabolic pathways involved with feed efficiency in beef cattle.

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Key Regulatory Genes and Candidate Markers (SNPs)

The liver and muscle are important target tissues used to study the genetic architecture regulating feed efficiency. Studies have found that protein coding genes related to striated muscle contraction are differentially expressed between high and low feed efficiency groups, suggesting the involvement of muscle function in the efficiency of energy use in cattle. Liver tissue function is associated with the regulation of metabolic energy and nutrient supply and previous studies have found that liver metabolite concentrations are associated with feed efficiency. In addition, the liver is known to be involved with circadian control of gene expression which regulates nutrient uptake and organ function alignment. Much evidence exists supporting the many differentially expressed genes found in muscle and liver tissue due to the importance of these key target tissues to study feed efficiency.

In total, 180 differentially expressed genes in liver and muscle tissue were identified and involved with regulating feed efficiency in beef cattle. Of the 180 identified genes, 68 were differentially expressed in muscle tissue and 112 genes in liver tissue, with 5 being the same between both muscle and liver tissue. This is reasonable, as these tissues are biologically involved in different metabolic processes such as energy metabolism (liver tissue) and efficiency of energy use (muscle tissue).

The five genes that were regulating gene expression in both liver and muscle tissue are interesting, as this may suggest that these genes function in multiple tissues to regulate feed efficiency. One of the genes included early growth response protein 1 (EGR1 gene). EGR1 is involved with the regulation of circadian patterns of genes expressed in metabolic pathways such as growth response pathways and cell differentiation. These metabolic pathways may play a key role in the efficiency of energy use for animal growth and biological functions of tissues and cells.

Using RNA-Seq analysis, we also identified genetic markers associated with high or low feed efficiency and determined how many markers are located within the five genes found differentially expressed in both liver and muscle tissue, for both high and low feed efficiency groups. A total of 26 markers (SNPs) were identified in the low group, and 18 markers (SNPs) were identified in the high group within those genes. For example, one marker from the low feed efficiency group was associated with the EGR1 gene, which may serve as a candidate marker that is influencing low or high feed efficiency in an animal. The markers found exclusively in the more efficient animals may be contributing to the regulation of feed efficiency, allowing for higher accuracy in the selection for more feed efficient animals.

Implications and Conclusions

This study revealed interesting preliminary results regarding the potential regulatory genes and genetic markers associated with feed efficiency in beef steers. From this, further investigation will be performed including validation of genetic markers across purebred and crossbred beef cattle and different management systems. This information can be further evaluated and potentially applied to genomic selection strategies by including markers in genotyping platforms for commercial herds and in selection protocols, leading to improved production efficiency and environmental sustainability of the beef industry.

Acknowledgements

The authors gratefully acknowledge the financial support from the Ontario Ministry of Agriculture, Food, and Rural Affairs (OMAFRA), Ontario Ministry of Research and Innovation, Agriculture and Agri-Food Canada (AAFC), Genome Canada, Beef Farmers of Ontario (BFO), Beef Cattle Research Council (BCRC), AgSights, and the national and international institutions collaborating on this project (University of Alberta (Canada), Teagasc (Ireland), and American Angus Association/Angus Genetics Inc. (Missouri, USA)). The authors would also like to recognize the financial contributions of sponsors to the Livestock Research Innovation Centre - Elora Beef Facility. This leading-edge research facility will enable the advancement of beef cattle genetic research in Ontario.

Article Author Information:

Authors: Stephanie Lam1, Aroa Suárez-Vega1, Pablo Fonseca1,2, Angela Cánovas1

Affiliations:

1 Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario, N1G 2W1, Canada.

2 Universidade Federal de Minas Gerais, Departamento de Biologia Geral, Belo Horizonte, Minas Gerais, 31270-901, Brazil.


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