Association analysis of loci implied in “buffering” epistasis
The existence of buffering mechanisms is an emerging property of biological networks, and this results in the possible existence of \"buffering\" loci, that would allow buildup of robustness through evolution. So far, there are no explicit methods to find loci implied in buffering mechanisms. However, buffering can be seen as interaction with genetic background. Here we develop this idea into a tractable model for quantitative genetics, in which the buffering effect of one locus with many other loci is condensed into a single (statistical) effect, multiplicative on the total (statistical) additive genetic effect. This allows easier interpretation of the results, and it also simplifies the problem of detecting epistasis from quadratic to linear in the number of loci. Armed with this formulation, we construct a linear model for genome-wide association studies that estimates, and declares significance, of multiplicative epistatic effects at single loci. The model has the form of a variance components, norm reaction model and likelihood ratio tests are used for significance. This model is a generalization and explanation of previous ones. We then test our model using bovine data: Brahman and Tropical Composite animals, phenotyped for body weight at yearling and genotyped up to [~]770,000 Single Nucleotide Polymorphisms (SNP). After association analysis and based on False Discovery Rate rules, we find a number of loci with buffering action in one, the other, or both breeds; these loci do not have significant statistical additive effect. Most of these loci have been reported in previous studies, either with an additive effect, or as footprints of selection. We identify epistatic SNPs present in or near genes encoding for proteins that are functionally enriched for peptide activity and transcription factors reported in the context of signatures of selection in multi-breed cattle population studies. These include loci known to be associated with coat color, fertility and adaptation to tropical environments. In these populations we found loci that have a non-significant statistical additive effect but a significant epistatic effect. We argue that the discovery and study of loci associated with buffering effects allows attacking the difficult problems, among others, of release of maintenance variance in artificial and natural selection, of quick adaptation to the environment, and of opposite signs of marker effects in different backgrounds. We conclude that our method and our results generate promising new perspectives for research in evolutionary and quantitative genetics based on the study of loci that buffer effect of other loci.