Research On Animal Production

Extended Abstract
Introduction and Objective: Climate change and the increase in greenhouse gases are among the most important environmental challenges of the present century, to which the agricultural sector, especially animal husbandry, has a significant contribution. Methane emission through anaerobic fermentation processes in the rumen of ruminants, as one of the main sources of this gas, has attracted the attention of researchers. Reducing methane emissions not only helps improving environmental conditions, but can also increase production efficiency and feed use efficiency in livestock. With the advancement of genetic and molecular technologies, livestock genetic improvement has been proposed as a long-term and sustainable solution to reduce greenhouse gas emissions. This approach, by utilizing the genetic diversity existing in livestock populations, enables the selection and breeding of animals with desirable environmental and production traits. However, the success of genetic improvement depends on the accurate understanding of the genetic structure of the desired traits and the determination of relevant genomic regions. In this context, genome-wide association studies (GWAS) have been recognized as an efficient tool for discovering associations between broad genetic markers and complex traits. By simultaneously examining thousands of SNPs across the genome, this method allows the identification of genetic loci affecting traits of multigenic origin. Despite the widespread use of GWAS in genetic studies of dairy cattle for traits such as milk production and disease resistance, its application to traits related to methane emission and rumen parameters has not yet been fully investigated. The main objective of this research was to investigate genomic association and identify regions affecting methane emission per kilogram of milk protein and rumen pH in Holstein cattle. The results of this study can help to develop breeding programs that simultaneously increase productivity and reduce the environmental impacts of livestock farming.
 Materials and Methods: Hair and rumen fluid samples of 150 Holstein cows based on the two-way milk yield trait breeding values were collected to investigate methane emission per kg of milk protein and rumen pH. Ruminal fluid sampling was performed using an esophageal tube; the tube was inserted into the rumen through the esophagus and approximately 5 mL of rumen fluid was collected in the tube by creating a vacuum. After sampling, the concentration of volatile fatty acids in the rumen fluid was measured, and used as an indicator for estimating methane emission per animal. The rumen fluid pH was also measured directly. DNA extracted from hair samples was genotyped using a 4v LD-GGP SNP chip containing 30108 single nucleotide polymorphism (SNP) markers. GWAS was performed using the PLINK 2.0 package. Finally, the cattle QTLdb database (https://www.animalgenome.org/cgi-bin/QTLdb/BT/index) was used to determine the quantitative trait loci (QTL) associated with the significant SNPs. This search was performed within a one megabase region around the SNPs passing the Bonferroni correction threshold for each chromosome to identify genomic regions associated with the target traits.
Results: Least squares analysis of variance using the GLM procedure showed that the effect of breeding season and animal age on the predicted methane emission trait was significant (P<0.05). In this study, two significant SNPs were identified. One SNP with the identifier BovineHD1900001716 was associated with the methane emission trait per kilogram of milk protein on chromosome 19, and the SNP with the identifier BovineHD1700012101 was associated with the rumen pH trait on chromosome 17. Also, using genomic annotation, QTL regions associated with milk production traits and their components, body weight, residual feed intake, pregnancy rate, dystocia, and stillbirth were identified around these SNPs.
Conclusion: The results of this research showed that some of identified genes and QTLs simultaneously affect environmental traits such as methane emission, economic traits such as body weight and milk production, as well as physiological characteristics related to the lactation and parturition periods. Based on the performed genomic analyses, some traits were identified that play a role in controlling production performance and reducing greenhouse gas emissions simultaneously. These findings double the importance of using genetic and genomic information in breeding programs and livestock management. The results of this research also indicate that targeted genetic selection can be used as a sustainable and long-term approach to reduce methane emission rates in each animal. Therefore, the livestock genetic improvement not only helps to improve production and reproductive traits by creating cumulative and permanent changes in performance, but also simultaneously reduces the environmental impacts of livestock production systems, including greenhouse gas emissions. Utilizing this approach can create a more sustainable future for the livestock industry.