Sterken, M. | bioRxiv Science

bioRxiv2017

Natural genetic variation in C. elegans reveals genomic loci controlling metabolite levels

Metabolic homeostasis is sustained by complex biological networks responding to nutrient availability. Disruption of this equilibrium involving intricate interactions between genetic and environmental factors can lead to metabolic disorders, including obesity and type 2 diabetes. To identify the genetic factors controlling metabolism, we applied a quantitative genetic strategy using a Caenorhabditis elegans population consisting of 199 recombinant inbred lines (RILs) originally derived from crossing parental strains Bristol N2 and Hawaii CB4856. We focused on the genetic factors that control metabolite levels and measured fatty acid (FA) and amino acid (AA) composition in the 199 RILs using targeted metabolomics. For both FA and AA profiles, we observed large variation in metabolite levels with 32-82% heritability between the RILs. We performed metabolite-metabolite correlation analysis and detected strongly co-correlated metabolite clusters. To identify natural genetic variants responsible for the observed metabolite variations, we performed QTL mapping and detected 36 significant metabolite QTL (mQTL). We focused on the mQTL that displayed high significant linkage and heritability, including an mQTL for the FA C14:1 on chromosome I, and another mQTL for the FA C18:2 on chromosome IV. Using introgression lines (ILs) we were able to narrow down both mQTL to a 1.4 Mbp and a 3.6 Mbp region, respectively. Overall, this systems approach provides us with a powerful platform to study the genetic basis of C. elegans metabolism. It also allows us to investigate additional interventions, such as nutrients and stresses that maintain or disturb the regulatory network controlling metabolic homeostasis, and identify gene-by-environment interactions.

genomics↗

bioRxiv2017

Contribution Of Trans Regulatory eQTL To Cryptic Genetic Variation In C. elegans

BackgroundCryptic genetic variation (CGV) is the hidden genetic variation that can be unlocked by perturbing normal conditions. CGV can drive the emergence of novel complex phenotypes through changes in gene expression. Although our theoretical understanding of CGV has thoroughly increased over the past decade, insight into polymorphic gene expression regulation underlying CGV is scarce. Here we investigated the transcriptional architecture of CGV in response to rapid temperature changes in the nematode Caenorhabditis elegans. We analyzed regulatory variation in gene expression (and mapped eQTL) across the course of a heat stress and recovery response in a recombinant inbred population.\n\nResultsWe measured gene expression over three temperature treatments: i) control, ii) heat stress, and iii) recovery from heat stress. Compared to control, exposure to heat stress affected the transcription of 3305 genes, whereas 942 were affected in recovering worms. These affected genes were mainly involved in metabolism and reproduction. The gene expression pattern in recovering worms resembled both the control and the heat stress treatment. We mapped eQTL using the genetic variation of the recombinant inbred population and detected 2626 genes with an eQTL in the heat stress treatment, 1797 in the control, and 1880 in the recovery. The cis-eQTL were highly conserved across treatments. A considerable fraction of the trans-eQTL (40-57%) mapped to 19 treatment specific trans-bands. In contrast to cis-eQTL, trans-eQTL were highly environment specific and thus cryptic. Approximately 67% of the trans-eQTL were only induced in a single treatment, with heat-stress showing the most unique trans-eQTL.\n\nConclusionsThese results illustrate the highly dynamic pattern of CGV across three different environmental conditions that can be evoked by a stress response over a relatively short time-span (2 hours) and that CGV is mainly determined by response related trans regulatory eQTL.

genetics↗