Integrating Quantitative Genetic and Genomic Approaches to Dissect Fatness Traits in Divergently Selected Broiler Chickens

Dissecting the functional mechanisms underlying genetic variations associated with complex traits is a formidable endeavour. This is complicated by the large confidence intervals of the quantitative trait loci (QTL) harbouring many candidate genes. In this study we describe the integration of genetic/genomic approaches - viz. QTL analysis, whole-genome sequencing to identify a comprehensive list of genetic variants, analysis of signatures of selection and functional annotations of genetic variants using different tools - to detect and characterise the chromosomal regions that are involved in controlling fatness traits in two divergently selected broiler chicken lines. By analyzing these lines, we have identified 3 significant QTLs for plasma VLDL (Very Low Density Lipoprotein) and 9 significant QTLs for abdominal fat pad weight, which are important metrics of fatness. Integrating results from analysis of signatures of selection based on F_ST approach using millions of SNPs markedly narrowed down the QTL intervals. We further refined and characterized the variants within selection-signature regions by filtering for opposite genotypes and performing functional annotation using different methods including intersecting the variants with evolutionary constraint elements. Results show that most of the potentially functional variants lie within non-coding regions, suggesting their possible regulatory roles on expression instead of having major effects through change in protein structure and function. Our study shows that integrative approach effectively reduces the QTL interval for fatness traits, thereby facilitating the prioritization of candidate genes/variants. Most importantly, this study highlights ACSL1, AKT1 and VGLL2 genes as potential candidates for VLDL trait in broilers.