P1046 Deciphering chicken fatness trait with integrative genetic and genomic approaches. (1st September 2016)

• Record Type: Journal Article
• Authors: Khoo, C. K.; Gheyas, A.; Kuo, R.; Eory, L.; Hocking, P. M.; Burt, D.
• Is Part Of: Journal of animal science. Volume 94(2016)Supplement 4
• Page Start: 36
• Page End: 37
• Publication Date: 2016-09-01
• Subjects: fatness -- genetic variants -- VLDL; Livestock -- Periodicals; Livestock; Electronic journals; Periodicals; 636.005
• DOI: 10.2527/jas2016.94supplement436b
• Languages: English
• ISSNs: 0021-8812

Abstract

Abstract: Understanding the functional mechanism of genetic variants that underlie complex traits remains a formidable endeavor, albeit significant efforts have been made toward providing the tools for dissecting the genotype-phenotype interaction. The limited efficiency and accuracy of QTL mapping often results in large intervals harboring many candidate genes, thereby limiting the ability to identify the causative variants. Nevertheless, the advances in genome sequence information and bioinformatics have enabled molecular phenotyping of organisms quickly at an affordable cost. Through integration of genetic and genomic approaches, we dissected the chromosomal regions involved in regulating fatness traits in broiler chickens. Using 2 broiler lines, divergently selected for plasma very low density lipoprotein (VLDL), we attempted to identify and characterize the genomic regions and genetic variants responsible for regulating this fatness trait. We identified 3 significant QTLs for plasma VLDL and 9 significant QTLs for abdominal fat pad weight, which are both important metrics of fatness. Further incorporation of signatures of selection, using millions of SNPs generated from whole genome resequencing, narrowed the QTL intervals, reflecting the potential of integrative approaches to complement conventional QTL mapping. We found that non-coding regions were enriched in selection signatures, suggesting the underlying variants could be regulatory in nature and further strengthening the regulatory relevance of non-coding loci. Incorporating evolutionary constraint elements previously identified from the multiple genome alignment of 49 sauropods and PacBio transcriptome analysis, this study provided further information for non-coding regions. Adipogenesis pathway and acetate conversion to acetyl-CoA pathway, which are both associated with lipid metabolism, were among the canonical pathways enriched. Our study demonstrated that the integration of analysis of selection signatures with functional annotation of variants enabled refinement and further characterization of the QTL and selection signature regions. Combining quantitative and population genetics with the knowledge of selection history, our integrated approach identified plausible candidate genes and nucleotides, and further elucidated the potential interplay among genes and biological pathways involved in regulating fatness traits in selection lines of broiler chickens.