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

Area of Science:

• Genomics
• Quantitative Genetics
• Animal Breeding

Background:

• Identifying causal genes for quantitative trait loci (QTLs) is difficult due to small effect sizes and non-coding variants.
• Existing multi-omics methods (eQTL, epigenomics, TWAS) are limited in poultry and livestock by small reference panels and tissue availability.

Purpose of the Study:

• Introduce a cost-effective F2-based integrative framework for causal gene identification.
• Compare this framework with existing multi-omics strategies.
• Provide a practical solution for gene prioritization in livestock.

Main Methods:

• Integrates QTL remapping, transcriptome analysis, haplotype frequency comparison, association analysis, and conditional correlation analysis.
• Incorporates causal analysis and quantitative complementation tests using knockout birds.
• Utilizes the original F2 population for hypothesis-independent gene prioritization.

Main Results:

• The F2-based framework enables gene prioritization without additional fine-mapping crosses.
• Effectiveness demonstrated through comparison with conventional multi-omics methods.
• Causal analysis and quantitative complementation provide robust evidence for pinpointing causal genes.

Conclusions:

• The F2-based framework efficiently prioritizes and verifies causal gene candidates within the mapping population.
• Offers a cost-effective alternative to resource-intensive multi-omics approaches.
• Broadly applicable to diverse chicken crosses and transferable to other livestock and model organisms.