Animal Molecular Breeding 2024, Vol.14, No.5, 307-317 http://animalscipublisher.com/index.php/amb 307 Research Insight Open Access Genome-Wide Association Studies for Milk Production in Dairy Cattle QinengSi Biotechnology Reseach Center, Cuixi Academy of Biotechnology, Zhuji, 311800, Zhejiang, China Corresponding email: qineng.si@cuixi.org Animal Molecular Breeding, 2024, Vol.14, No.5 doi: 10.5376/amb.2024.14.0032 Received: 28 Jul., 2024 Accepted: 06 Sep., 2024 Published: 20 Sep., 2024 Copyright © 2024 Si, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Si Q.N., 2024, Genome-wide association studies for milk production in dairy cattle, Animal Molecular Breeding, 14(5): 307-317 (doi: 10.5376/amb.2024.14.0032) Abstract This study synthesizes findings from multiple GWAS, highlighting key genomic regions and candidate genes associated with milk yield, fat percentage, protein percentage, and somatic cell score (SCS). Notable genes such as DGAT1, ABCG2, and MGST1 are consistently implicated, along with novel candidates like CCSER1and CUX2. By integrating high-density SNP chips and whole-genome sequencing, these studies have enhanced the detection of quantitative trait loci (QTLs) and refined genomic selection strategies. The findings underscore the polygenic nature of milk production traits and the utility of GWAS in improving breeding accuracy. Future prospects include the integration of machine learning, epigenomics, and metabolomics to further enhance genetic predictions, optimize breeding programs, and ensure sustainable dairy farming practices. Keywords Genome-wide association studies (GWAS); Milk production; Quantitative trait loci (QTL); Genomic selection; Dairy cattle 1 Introduction Milk production is a critical economic trait in dairy cattle, significantly influencing the profitability and sustainability of dairy farming. The efficiency and volume of milk production are determined by a complex interplay of genetic, environmental, and management factors. Over the years, selective breeding has been employed to enhance milk yield and quality, focusing on traits such as milk fat, protein content, and overall milk volume (Pryce et al., 2010; Buaban et al., 2021; Taherkhani et al., 2022). The advent of genomic technologies has revolutionized the ability to identify and select for these traits, providing a more precise and efficient approach to dairy cattle breeding. Understanding the genetic basis of milk production traits is essential for several reasons. Firstly, it allows for the identification of specific genes and genomic regions that influence milk yield and composition, which can be targeted in breeding programs to improve these traits (Mai et al., 2010; Dadousis et al., 2017a; Teng et al., 2023). Secondly, it provides insights into the biological mechanisms underlying milk production, which can lead to the development of new strategies for enhancing milk yield and quality (Chen et al., 2018; Otto et al., 2020). Genome-wide association studies (GWAS) have been particularly instrumental in this regard, enabling the discovery of quantitative trait loci (QTL) and candidate genes associated with milk production traits across different cattle breeds (Bolormaa et al., 2010; Jiang et al., 2010). This study aims to synthesize current knowledge on the genetic factors influencing milk production in dairy cattle, particularly based on findings from genome-wide association studies (GWAS). It seeks to identify key genomic regions and candidate genes associated with milk production traits, discuss the comparison of different GWAS approaches and their effectiveness in identifying relevant genetic markers, and explore the implications of these genetic structures for dairy cattle breeding and milk production improvement. The study aspires to provide a comprehensive overview of the genetic information on milk production in dairy cattle and highlight potential research directions for future studies and applications in genomic selection programs. 2 Overview of Genome-Wide Association Studies (GWAS) 2.1 Introduction to GWAS Genome-Wide Association Studies (GWAS) are a powerful tool used to identify genetic variants associated with specific traits by scanning the entire genome. This approach involves comparing the DNA of individuals with
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