Feed conversion ratio (FCR) is one of the most critical indicators of biological efficiency and economic profitability in poultry production. Improving feed efficiency has become a strategic priority for the poultry industry due to increasing feed costs, limited natural resources, and growing concerns regarding environmental sustainability. Although conventional breeding and nutritional management have contributed substantially to genetic improvement, feed conversion ratio is a complex trait regulated by numerous interacting genetic, epigenetic, metabolic, microbial, and environmental factors. In recent years, multi-omics technologies have emerged as powerful approaches for unraveling the molecular mechanisms underlying feed efficiency and accelerating the development of precision breeding and nutritional strategies.
Multi-omics integrates complementary high-throughput platforms, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and microbiomics, to provide a comprehensive understanding of biological systems. These technologies enable the identification of genes, regulatory pathways, proteins, metabolites, microbial communities, and epigenetic modifications that collectively influence nutrient digestion, energy metabolism, muscle development, intestinal integrity, immune function, oxidative stress, and growth performance. Genome-wide association studies (GWAS), RNA sequencing, quantitative proteomics, metabolite profiling, and microbiome analyses have identified numerous molecular signatures associated with superior feed efficiency in commercial poultry populations.
The integration of multi-omics datasets has significantly enhanced the discovery of predictive biomarkers and candidate genes involved in feed conversion ratio. Advanced bioinformatics, systems biology, artificial intelligence, and machine learning algorithms facilitate the analysis of complex biological networks and improve the prediction of economically important traits. Furthermore, combining multi-omics with genomic selection and precision nutrition enables the development of individualized feeding programs based on genetic background, physiological status, and metabolic responses, thereby improving nutrient utilization, reducing feed costs, minimizing nitrogen and phosphorus excretion, and enhancing animal health and welfare.
Despite its considerable potential, several challenges remain for the large-scale implementation of multi-omics in poultry production. High analytical costs, limited availability of integrated reference datasets, computational complexity, data standardization issues, and the need for functional validation of identified biomarkers continue to restrict commercial applications. Future research should emphasize integrated multi-omics analyses, host–microbiome interactions, nutrigenomics, single-cell omics, and explainable artificial intelligence to establish robust predictive models for feed efficiency. Overall, multi-omics technologies provide an unprecedented opportunity to understand the biological complexity of feed conversion ratio and represent a cornerstone for the development of sustainable, data-driven, and precision poultry production systems.