Genotype‐by‐environment interactions in beef and dairy cattle populations: A review of methodologies and perspectives on research and applications

生物 肉牛 牲畜 生物技术 奶牛 动物福利 动物育种 基因组选择 牧群 生产(经济) 选择(遗传算法) 动物科学 基因型 生态学 遗传学 单核苷酸多态性 人工智能 经济 宏观经济学 基因 计算机科学
作者
João Barbosa da Silva Neto,Lúcio Flávio Macêdo Mota,Marisol Londoño‐Gil,Patrícia Iana Schmidt,Gustavo Roberto Dias Rodrigues,Viviane Andrade Ligori,Leonardo Machestropa Arikawa,C. de U. Magnabosco,Luiz F. Brito,Fernando Sebastian Baldi
出处
期刊:Animal Genetics [Wiley]
卷期号:55 (6): 871-892 被引量:60
标识
DOI:10.1111/age.13483
摘要

Modern livestock production systems are characterized by a greater focus on intensification, involving managing larger numbers of animals to achieve higher productive efficiency and animal health and welfare within herds. Therefore, animal breeding programs need to be strategically designed to select animals that can effectively enhance production performance and animal welfare across a range of environmental conditions. Thus, this review summarizes the main methodologies used for assessing the levels of genotype-by-environment interaction (G × E) in cattle populations. In addition, we explored the importance of integrating genomic and phenotypic information to quantify and account for G × E in breeding programs. An overview of the structure of cattle breeding programs is provided to give insights into the potential outcomes and challenges faced when considering G × E to optimize genetic gains in breeding programs. The role of nutrigenomics and its impact on gene expression related to metabolism in cattle are also discussed, along with an examination of current research findings and their potential implications for future research and practical applications. Out of the 116 studies examined, 60 and 56 focused on beef and dairy cattle, respectively. A total of 83.62% of these studies reported genetic correlations across environmental gradients below 0.80, indicating the presence of G × E. For beef cattle, 69.33%, 24%, 2.67%, 2.67%, and 1.33% of the studies evaluated growth, reproduction, carcass and meat quality, survival, and feed efficiency traits, respectively. By contrast, G × E research in dairy cattle populations predominantly focused on milk yield and milk composition (79.36% of the studies), followed by reproduction and fertility (19.05%), and survival (1.59%) traits. The importance of G × E becomes particularly evident when considering complex traits such as heat tolerance, disease resistance, reproductive performance, and feed efficiency, as highlighted in this review. Genomic models provide a valuable avenue for studying these traits in greater depth, allowing for the identification of candidate genes and metabolic pathways associated with animal fitness, adaptation, and environmental efficiency. Nutrigenetics and nutrigenomics are emerging fields that require extensive investigation to maximize our understanding of gene-nutrient interactions. By studying various transcription factors, we can potentially improve animal metabolism, improving performance, health, and quality of products such as meat and milk.
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