Feed conversion ratio (FCR) is one of the most economically important traits in modern poultry production because it directly influences production costs, profitability, environmental sustainability, and resource utilization. Continuous genetic improvement combined with advances in nutritional management has substantially enhanced feed efficiency in commercial poultry; however, conventional breeding approaches remain limited by the complex genetic architecture of feed conversion traits. Recent developments in genomics and genomic selection have revolutionized poultry breeding by enabling the identification of genomic regions, candidate genes, and molecular markers associated with feed efficiency. These technologies provide opportunities to accelerate genetic gain through more accurate selection decisions while reducing generation intervals and improving breeding efficiency.
High-throughput sequencing technologies, genome-wide association studies (GWAS), whole-genome sequencing, single nucleotide polymorphism (SNP) arrays, and genomic prediction models have substantially improved the understanding of the biological mechanisms underlying feed conversion ratio. Numerous genes involved in energy metabolism, nutrient digestion, appetite regulation, muscle development, mitochondrial function, immune responses, and intestinal health have been identified as important contributors to feed efficiency. Moreover, transcriptomic and epigenomic studies have demonstrated that differential gene expression and epigenetic regulation significantly influence nutrient utilization and metabolic efficiency in poultry populations.
Genomic selection integrates dense genome-wide marker information into breeding programs, allowing the estimation of genomic breeding values with greater accuracy than traditional pedigree-based methods. This approach is particularly beneficial for low-heritability or difficult-to-measure traits such as feed efficiency, where direct phenotypic measurements are costly and time-consuming. The incorporation of genomic information into breeding strategies has resulted in measurable improvements in feed conversion ratio while maintaining growth performance, carcass quality, reproductive traits, and animal health. Furthermore, integrating genomic data with phenomics, precision livestock farming, artificial intelligence, and machine learning has enabled more comprehensive prediction models capable of identifying superior breeding candidates under diverse environmental conditions.
Despite these remarkable advances, several challenges remain, including the high cost of genomic technologies, the need for larger reference populations, genotype-by-environment interactions, computational complexity, and ethical considerations regarding data management. Future research should focus on integrating multi-omics approaches, microbiome profiling, nutrigenomics, and advanced computational methods to better understand the biological pathways regulating feed efficiency. Such multidisciplinary approaches will facilitate the development of sustainable breeding programs that maximize genetic progress while minimizing feed costs and environmental impacts. Overall, genomics and genomic selection represent transformative tools for improving feed conversion ratio and ensuring the long-term sustainability, profitability, and competitiveness of the global poultry industry.