Complex traits, including common disease-related traits, are affected by many different genes that function in multiple pathways and networks. The apoptosis, MAPK, Notch, and Wnt signalling pathways play important roles in development and disease progression. At the moment we have a poor understanding of how allelic variation affects gene expression in these pathways at the level of translation. Here we report the effect of natural genetic variation on transcript and protein abundance involved in developmental signalling pathways in Caenorhabditis elegans. We used selected reaction monitoring to analyse proteins from the abovementioned four pathways in a set of recombinant inbred lines (RILs) generated from the wild-type strains N2 (Bristol) and CB4856 (Hawaii) to enable quantitative trait locus (QTL) mapping. About half of the cases from the 44 genes tested showed a statistically significant change in protein abundance between various strains, most of these were however very weak (below 1.3-fold change). We detected a distant QTL on the left arm of chromosome II that affected protein abundance of the phosphatidylserine receptor protein PSR-1, and two separate QTLs that influenced embryonic and ionizing radiation-induced apoptosis on chromosome IV. Our results demonstrate that natural variation in C. elegans is sufficient to cause significant changes in signalling pathways both at the gene expression (transcript and protein abundance) and phenotypic levels.

Natural genetic variation is the raw material of evolution and influences disease development and progression. An important question is how this genetic variation translates into variation in protein abundance. To analyze the effects of the genetic background on gene and protein expression in the nematode Caenorhabditis elegans, we quantitatively compared the two genetically highly divergent wild-type strains N2 and CB4856. Gene expression was analyzed by microarray assays, and proteins were quantified using stable isotope labeling by amino acids in cell culture. Among all transcribed genes, we found 1,532 genes to be differentially transcribed between the two wild types. Of the total 3,238 quantified proteins, 129 proteins were significantly differentially expressed between N2 and CB4856. The differentially expressed proteins were enriched for genes that function in insulin-signaling and stress-response pathways, underlining strong divergence of these pathways in nematodes. The protein abundance of the two wild-type strains correlates more strongly than protein abundance versus transcript abundance within each wild type. Our findings indicate that in C. elegans only a fraction of the changes in protein abundance can be explained by the changes in mRNA abundance. These findings corroborate with the observations made across species. Molecular & Cellular Proteomics 15: 10.1074/mcp.M115.052548, 1670-1680, 2016.Natural genetic variation in gene expression shapes the diversity in phenotypic traits and is the raw material for evolutionary processes (1). Variation in gene expression can be very extensive across individuals with different genotypes. The additive effects (narrow-sense heritability) of independent loci on gene expression variation can reach 35% in humans (2). The broad-sense heritable variation in gene expression has been estimated to be up to 70% in the nematode Caenorhabditis elegans (3, 4) and up to 80% in yeast (5). This high heritability and the ability to construct genetically segregating populations facilitate mapping of gene expression regulation and subsequent detection of expression quantitative trait loci (eQTL) 1 (5-11). eQTLs are genomic regions containing a polymorphism associated with variation in transcript abundance between genotypes (12). eQTL analysis provides insight into the underlying genetic architecture of complex traits and is valuable for the identification of pathways and gene networks (10,(13)(14)(15). A key question is whether gene expression variation is translated into variation at the proteome level and whether it affects functionally relevant proteins. Genetic model species provide an ideal platform to explore the relationship between gene expression variation and variation at the proteome level due to their tractability. Although it is well established that there is a correlation between transcript and protein abundances, the relationship between natural variation in gene expression and variation in protein abundance is less well understood. The proteome provides informat...

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