نوع مقاله : مقاله پژوهشی
نویسندگان
1 گروه علوم دامی، دانشکده کشاورزی، دانشکاه فردوسی مشهد
2 گروه علوم دامی، دانشکده کشاورزی؛ دانشگاه فردوسی مشهد
3 گروه علوم دامی، دانشکده کشاورزی، دانشگاه تبریز
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Background and Objectives: Cow's milk is known as one of the primary food sources for humans, offering a broad spectrum of nutritional compounds. Fatty acids are considered as a key component of milk, recognized as essential constituents of the fat present in milk. These components contribute to the creation of a unique fatty acid profile in milk. Genome-wide association studies (GWAS), with high statistical accuracy, play a crucial role in identifying potential causative loci. Numerous GWAS in cattle, particularly in Holstein cows, provide favorable conditions for integrating multiple independent studies. Using advanced techniques such as meta-analysis, the possibility of more precise identification of loci associated with quantitative traits of milk fatty acids in Holstein cows has been facilitated. The main objective of this research is the precise identification of loci associated with quantitative traits of milk fatty acids in Holstein cows. To achieve this goal, techniques such as meta-analysis was employed. This study may improve the accuracy of genetic selections and optimizing fatty acids in Holstein cow milk, through identification of genetic structure of fatty acids.
Materials and Methods: Searching for GWAS studies in Holstein cows, was conducted on Google Scholar using relevant keywords such as Holstein cows, GWAS and milk fatty acids. Single nucleotide polymorphisms (SNPs) derived from Holstein cows (Chinese, Danish, and Dutch) from various countries was available in four independent studies published during 2012 to 2019. A total of 1524 SNPs related to milk fatty acids was avialble from previous GWAS studies. Meta-analysis using a summary statistics approach (i.e., P-values, sample size, allelic effects, etc.) was performed among Holstein cows. In the present study, the METAL software was employed for meta-analysis, utilizing a weighted Z-score model. This method combined and assessed significant SNPs with a P-value less than 0.05.
Results: The most significant SNPs associated with milk fatty acids were identified. For instance, the most meaningful SNPs for the C16:0 trait were rs109421300 and rs137372738, with P-values of 1.05e-102 and 6.62e-23, respectively. These SNPs play a crucial and key role in producing C16:0 fatty acid and may influence the quality of milk production.
Conclusion: Overall, the results of this study demonstrated that based on SNPs with higher significant levels through meta-analysis compared to individual GWAS studies, it is possible to identify SNPs associated with quantitative traits with higher accuracy. Such studies contribute to a better understanding of genomic regions related to quantitative traits for milk fatty acids. Therefore, the identification of SNPs and key genes with high accuracy can play a significant role in genomic assessment and the design of breeding programs for improving fatty acids and the quality of milk production.
کلیدواژه‌ها [English]
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