Natural variation in a glucuronosyltransferase modulates propionate sensitivity in a C. elegans propionic acidemia model

Abstract

Mutations in human metabolic genes can lead to rare diseases known as inborn errors of human metabolism. For instance, patients with loss-of-function mutations in either subunit of propionyl-CoA carboxylase suffer from propionic acidemia because they cannot catabolize propionate, leading to its harmful accumulation. Both the penetrance and expressivity of metabolic disorders can be modulated by genetic background. However, modifiers of these diseases are difficult to identify because of the lack of statistical power for rare diseases in human genetics. Here, we use a model of propionic acidemia in the nematode Caenorhabditis elegans to identify genetic modifiers of propionate sensitivity. Using genome-wide association (GWA) mapping across wild strains, we identify several genomic regions correlated with reduced propionate sensitivity. We find that natural variation in the putative glucuronosyltransferase GLCT-3, a homolog of human B3GAT, partly explains differences in propionate sensitivity in one of these genomic intervals. We demonstrate that loss-of-function alleles in glct-3 render the animals less sensitive to propionate. Additionally, we find that C. elegans has an expansion of the glct gene family, suggesting that the number of members of this family could influence sensitivity to excess propionate. Our findings demonstrate that natural variation in genes that are not directly associated with propionate breakdown can modulate propionate sensitivity. Our study provides a framework for using C. elegans to characterize the contributions of genetic background in models of human inborn errors in metabolism.

From QTL to gene: C. elegans facilitates discoveries of the genetic mechanisms underlying natural variation

“…This result supports the duplication-divergence model, where new genes come from copies of pre-existing genes [132]. In one example, researchers mapped variation in propionate sensitivity to a putative glucuronosyltransferase that is part of an expanded gene family specific to C. elegans [74]. Importantly, new results show that hyper-divergent regions of the C. elegans genome contain environmentalresponse genes that are genes not found in the N2 reference genome and members of C. elegans specific expanded gene families [10].…”

“…Of these 11 QTVs, three were identified using GWA mapping alone, four using linkage mapping alone, and four using both mapping methods. For example, multiple common alleles have been correlated with toxin response differences [6,65,[74][75][76]101]. This result suggests that these alleles have been maintained over many generations and the predicted fitness costs of harboring such alleles are likely to be small.…”

“…One explanation for this discrepancy can be explained by nonadditive effects, including epistasis. For C. elegans, only five studies have estimated both broad-and narrow-sense heritability [15,39,69,74,76] and most trait variation is additive, as observed in yeast [139]. To more broadly impact our understanding of quantitative trait variation, these estimates should be calculated for every quantitative trait mapping and the data organized in a central repository.…”

Two novel loci underlie natural differences in Caenorhabditis elegans abamectin responses

“…Therefore, we hypothesized that variation in these genes might not be specific to the abamectin response. We compared our three abamectin-response QTL on chromosome V to previously mapped QTL in responses to several benzimidazoles [ 20 , 21 ] as well as numerous other toxin-response QTL [ 28 – 33 , 41 , 44 , 45 ]. We found several cases of overlapping QTL between toxins.…”

Natural variation in fecundity is correlated with species-wide levels of divergence in Caenorhabditis elegans

“…Genotype data for each of the 121 isotypes were acquired from the hard-filtered isotype VCF (20200815 CeNDR release). We performed the mapping using the pipeline cegwas2-nf ( https://github.com/AndersenLab/cegwas2-nf ) as previously described ( Zdraljevic et al 2019 ; Na et al 2020 ). Briefly, we used BCFtools ( Li 2011 ) to filter variants that had any missing genotype calls and variants that were below the 5% minor allele frequency.…”