Using transcriptome profiling to characterize QTL regions on chicken chromosome 5.

Area of Science:

• Animal Genetics
• Genomics
• Quantitative Trait Loci (QTL) Analysis

Background:

• Wide confidence intervals in livestock QTL mapping hinder causative mutation identification.
• Microarray data's utility in enhancing QTL detection requires investigation.
• A specific quantitative trait loci (QTL) for abdominal fatness (AF) on chicken chromosome 5 (GGA5) was previously identified.

Purpose of the Study:

• To evaluate the contribution of microarray data to quantitative trait loci (QTL) detection in livestock.
• To improve the characterization of a chicken abdominal fatness (AF) QTL region on GGA5 using three complementary approaches.

Main Methods:

• Obtained hepatic transcriptome profiles from 45 chicken offspring using a 20K chicken oligochip.
• Correlated mRNA levels of 660 genes with the abdominal fatness (AF) trait.
• Employed three strategies: phenotype dissection via transcript profiles, targeted gene analysis, and transcriptome-based QTL prediction.

Main Results:

• Dissecting the AF phenotype revealed a new QTL and increased the significance of the distal GGA5 AF QTL.
• Identified five candidate genes, including HMGCS1 involved in lipid metabolism, regulated by the AF QTL.
• Refined the GGA5 AF QTL confidence interval from 31 cM to 7 cM, localizing it to 12 genes.

Conclusions:

• Demonstrated the feasibility and efficacy of using microarray data for QTL detection and refinement in chickens.
• Identified HMGCS1 as a potential functional gene related to abdominal fatness (AF) within the refined QTL region.
• Significantly narrowed the confidence interval of a chicken GGA5 AF QTL, facilitating causative mutation identification.