Complex Trait Genetics : Beyond Additivity

• Main Author: Forsberg, Simon
• Format: Doctoral Thesis
• Language: English
• Published: Uppsala universitet, Institutionen för medicinsk biokemi och mikrobiologi 2016
• Subjects: genetic interactions; epistasis; additivity; GWAS; vGWAS; Genetic mapping; yeast; Arabidopsis Thaliana; dog
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-307837; http://nbn-resolving.de/urn:isbn:978-91-554-9754-5

The link between the genotype and the phenotype of an organism is immensely complex. Despite this it can, to a great extent, be captured using models that assume that gene variants combine their effects in an additive manner. This thesis explores aspects of genetics that cannot be fully captured using such additive models. Using experimental data from three different model organisms, I study two phenomena that fall outside of the additive paradigm: genetic interactions and genetic variance heterogeneity. Using the model plant Arabidopsis thaliana, we show how important biological insights can be reached by exploring loci that display genetic variance heterogeneity. In the first study, this approach identified alleles in the gene CMT2 associated with the climate at sampling locations, suggesting a role in climate adaption. These alleles affected the genome wide methylation pattern, and a complete knock down of this gene increased the plants heat tolerance. In the second study, we demonstrate how the observed genetic variance heterogeneity was the result of the partial linkage of many functional alleles near the gene MOT1, all contributing to Molybdenum levels in the leaves. Further, we explore genetic interactions using data from dogs and budding yeast (Saccharomyces cerevisiae). In the dog population, two interacting loci were associated with fructosamine levels, a biomarker used to monitor blood glucose. One of the loci displayed the pattern of a selective sweep in some of the studied breeds, suggesting that the interaction is important for the phenotypic breed-differences. In a cross between two strains of yeast, with the advantage of large population size and nearly equal allele frequencies, we identified large epistatic networks. The networks were largely centered on a number of hub-loci and altogether involved hundreds of genetic interactions. Most network hubs had the ability to either suppress or uncover the phenotypic effects of other loci. Many multi-locus allele combinations resulted in phenotypes that deviated significantly from the expectations, had the loci acted in an additive manner. Critically, this thesis demonstrates that non-additive genetic mechanisms often need to be considered in order to fully understand the genetics of complex traits.