Genetic interactions between polymorphisms that affect gene expression in yeast

Abstract

Interactions between polymorphisms at different quantitative trait loci (QTLs) are thought to contribute to the genetics of many traits, and can markedly affect the power of genetic studies to detect QTLs. Interacting loci have been identified in many organisms. However, the prevalence of interactions, and the nucleotide changes underlying them, are largely unknown. Here we search for naturally occurring genetic interactions in a large set of quantitative phenotypes--the levels of all transcripts in a cross between two strains of Saccharomyces cerevisiae. For each transcript, we searched for secondary loci interacting with primary QTLs detected by their individual effects. Such locus pairs were estimated to be involved in the inheritance of 57% of transcripts; statistically significant pairs were identified for 225 transcripts. Among these, 67% of secondary loci had individual effects too small to be significant in a genome-wide scan. Engineered polymorphisms in isogenic strains confirmed an interaction between the mating-type locus MAT and the pheromone response gene GPA1. Our results indicate that genetic interactions are widespread in the genetics of transcript levels, and that many QTLs will be missed by single-locus tests but can be detected by two-stage tests that allow for interactions.

Figure 1

Genome distribution of QTL pairs detected by the two-stage linkage search. On each axis the genome is divided into 611 bins of 20 kb each, shown in chromosomal order. The set of transcripts mapping to QTLs in each pair of bins in the two-stage analysis is represented as a circle, with the width proportional to the number of such co-linking transcripts; circles are centered on the corresponding bins. The largest circle represents the MAT-GPA1 locus pair.

Figure 2

Example transcripts showing genetic interaction between MAT and GPA1. Each panel represents one transcript. “Locus 1” denotes MAT and “locus 2” denotes GPA1; RM is MATa and BY is MATα. Each red point represents the mean expression level over segregants with the indicated genotype, normalized by the mean over segregants inheriting the BY allele at both loci; red error bars represent standard deviations among segregants with the indicated genotype. Each green point represents the expression level in the indicated engineered strain, normalized by the level in the engineered strain with the BY allele at both loci.