Abstract
BackgroundAlthough many QTL for various traits have been mapped in livestock, location confidence intervals remain wide that makes difficult the identification of causative mutations. The aim of this study was to test the contribution of microarray data to QTL detection in livestock species. Three different but complementary approaches are proposed to improve characterization of a chicken QTL region for abdominal fatness (AF) previously detected on chromosome 5 (GGA5).ResultsHepatic transcriptome profiles for 45 offspring of a sire known to be heterozygous for the distal GGA5 AF QTL were obtained using a 20 K chicken oligochip. mRNA levels of 660 genes were correlated with the AF trait. The first approach was to dissect the AF phenotype by identifying animal subgroups according to their 660 transcript profiles. Linkage analysis using some of these subgroups revealed another QTL in the middle of GGA5 and increased the significance of the distal GGA5 AF QTL, thereby refining its localization. The second approach targeted the genes correlated with the AF trait and regulated by the GGA5 AF QTL region. Five of the 660 genes were considered as being controlled either by the AF QTL mutation itself or by a mutation close to it; one having a function related to lipid metabolism (HMGCS1). In addition, a QTL analysis with a multiple trait model combining this 5 gene-set and AF allowed us to refine the QTL region. The third approach was to use these 5 transcriptome profiles to predict the paternal Q versus q AF QTL mutation for each recombinant offspring and then refine the localization of the QTL from 31 cM (100 genes) at a most probable location confidence interval of 7 cM (12 genes) after determining the recombination breakpoints, an interval consistent with the reductions obtained by the two other approaches.ConclusionThe results showed the feasibility and efficacy of the three strategies used, the first revealing a QTL undetected using the whole population, the second providing functional information about a QTL region through genes related to the trait and controlled by this region (HMGCS1), the third could drastically refine a QTL region.
Highlights
Many QTL for various traits have been mapped in livestock, location confidence intervals remain wide that makes difficult the identification of causative mutations
Approach 2: refining distal GGA5 abdominal fatness (AF) QTL by Expression Quantitative Trait Locus (eQTL) mapping Selection of genes correlated with the AF trait and having an eQTL colocalizing with GGA5 AF QTL Out of the previously selected 660 genes, we identified 46 genes (6.9%) that had an eQTL (p-value < 0.1) that colocalized with the location confidence interval of the GGA5 AF QTL (156-187 cM)
Our results showed the value of using "Genetical Genomics (GG)" to characterize QTL responsible for complex trait variability in livestock
Summary
Many QTL for various traits have been mapped in livestock, location confidence intervals remain wide that makes difficult the identification of causative mutations. In spite of success in QTL research for complex traits in livestock species in the last twenty years, location confidence intervals of many QTL are wide, possibly harboring hundreds of genes This is the major obstacle to finding causative mutations underlying any QTL identified. Fine mapping techniques and positional cloning to reduce the location confidence interval of the initial QTL are time-consuming, especially for livestock species compared to plant and animal models This is mainly due to a lack of inbred lines, long generation intervals, the cost of maintaining each animal and the difficulty of producing transgenic or "knock-out" individuals to confirm the causative nature of the mutation of the trait of interest. Very little is known of the molecular nature of cis-acting and (even more so) trans-acting eQTL regions
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