From QTL to QTN: candidate gene set approach and a case study in porcine IGF1-FoxO pathway

Abstract

Unraveling the genetic background of economic traits is a major goal in modern animal genetics and breeding. Both candidate gene analysis and QTL mapping have previously been used for identifying genes and chromosome regions related to studied traits. However, most of these studies may be limited in their ability to fully consider how multiple genetic factors may influence a particular phenotype of interest. If possible, taking advantage of the combined effect of multiple genetic factors is expected to be more powerful than analyzing single sites, as the joint action of multiple loci within a gene or across multiple genes acting in the same gene set will likely have a greater influence on phenotypic variation. Thus, we proposed a pipeline of gene set analysis that utilized information from multiple loci to improve statistical power. We assessed the performance of this approach by both simulated and a real IGF1-FoxO pathway data set. The results showed that our new method can identify the association between genetic variation and phenotypic variation with higher statistical power and unravel the mechanisms of complex traits in a point of gene set. Additionally, the proposed pipeline is flexible to be extended to model complex genetic structures that include the interactions between different gene sets and between gene sets and environments.

Figure 1. Statistical powers between CGSA and candidate gene approach under different heritability levels.

The power was examined on a trait simulated from 15 causative mutations (QTNs). A total of 1000 replications were conducted for each method. The heritability of the trait varied from 0 to 0.5. The differences between our CGSA and candidate gene set approach with mid-level and low-level of heritability were greater than the one with high heritability.

Figure 2. An illustration of the IGF1/FoxO pathway genes.

Arrows indicate the direction of signal transduction. The numbers on the left side represent the position of the IGF1/FoxO pathway genes.