An Integrative Genetic Strategy for Identifying Causal Genes at Quantitative Trait Loci in Chickens

Background: Identifying causal genes underlying quantitative trait loci (QTLs) remains challenging due to small effect sizes and the prevalence of non-coding variants. Although multi-omics integration frameworks such as eQTL- and epigenomic-based approaches and TWAS have advanced gene prioritization, their application in poultry and livestock is often constrained by limited reference panels and tissue resources. This review introduces a cost-effective F2-based integrative framework and compares it with existing multi-omics strategies. Methods: The proposed framework combines QTL remapping, transcriptome analysis, haplotype frequency comparison, association analysis, and conditional correlation analysis within a single workflow. Causal analysis and quantitative complementation tests using knockout birds are incorporated to identify causal genes. Results: By reusing the original F2 population employed for QTL mapping, this approach enables hypothesis-independent gene prioritization without requiring additional fine-mapping crosses. Its effectiveness is demonstrated through comparison with conventional multi-omics methods, and the integration of causal analysis and quantitative complementation testing provides robust genetic evidence for pinpointing causal genes. Conclusions: This F2-based framework efficiently prioritizes and verifies causal gene candidates directly within the mapping population, offering a cost-effective alternative to multi-omics approaches that require large-scale resources. It is broadly applicable to diverse chicken crosses and readily transferable to other small livestock species and model organisms.