Natural genetic variation can cause significant differences in gene expression, but little is known about the polymorphisms that affect gene regulation. We analyzed regulatory variation in a cross between laboratory and wild strains of Saccharomyces cerevisiae. Clustering and linkage analysis defined groups of coregulated genes and the loci involved in their regulation. Most expression differences mapped to trans-acting loci. Positional cloning and functional assays showed that polymorphisms in GPA1 and AMN1 affect expression of genes involved in pheromone response and daughter cell separation, respectively. We also asked whether particular classes of genes were more likely to contain trans-regulatory polymorphisms. Notably, transcription factors showed no enrichment, and trans-regulatory variation seems to be broadly dispersed across classes of genes with different molecular functions.

Proper regulation of protein levels is essential for health, and abnormal levels of proteins are hallmarks of many diseases. A number of studies have recently shown that messenger RNA levels vary among individuals of a species and that genetic linkage analysis can be used to identify quantitative trait loci that influence these levels. By contrast, little is known about the genetic basis of variation in protein levels in genetically diverse populations, in large part because techniques for large-scale measurements of protein abundance lag far behind those for measuring transcript abundance. Here we describe a label-free, mass spectrometry-based approach to measuring protein levels in total unfractionated cellular proteins, and we apply this approach to elucidate the genetic basis of variation in protein abundance in a cross between two diverse strains of yeast. Loci that influenced protein abundance differed from those that influenced transcript levels, emphasizing the importance of direct analysis of the proteome.

No abstract

Variation in the levels of co-regulated proteins that function within networks in an outbred yeast population is not driven by variation in the corresponding transcripts.