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Natural Genetic Variation Influences Protein Abundances in C. elegans Developmental Signalling Pathways

ABSTRACT: 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 Bristol N2 and Hawaii CB4856 to enable quantitative trait loci (QTL) mapping. Variation in gene expression was greater in the RILs than in the parental lines, at the proteome as well as at the transcriptome levels. We detected a trans-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.

ORGANISM(S): Caenorhabditis elegans

PROVIDER: GSE77905 | GEO | 2016/02/16

SECONDARY ACCESSION(S): PRJNA311992

REPOSITORIES: GEO

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Project description:The nutritional environments that organisms experience are inherently variable, requiring tight coordination of how resources are allocated to different functions relative to the total amount of resources available. A growing body of evidence supports the hypothesis that key endocrine pathways play a fundamental role in this coordination. In particular, the insulin/insulin-like growth factor signaling (IIS) and target of rapamycin (TOR) pathways have been implicated in nutrition-dependent changes in metabolism and nutrient allocation, however little is known about the genetic basis of standing variation in the pathways. To characterize natural genetic variation in the IIS/TOR pathway, we used over 250 recombinant inbred lines (RILs) derived from a multiparental mapping population, the Drosophila Synthetic Population Resource (DSPR), to map QTL for transcript levels of the genes encoding 52 of the core components of the IIS/TOR pathway in three different nutritional environments (dietary restriction, control, and high sugar). In addition, we assayed lifespan for 80 RILs in both dietary restriction and control diets. We identified cis (i.e., local) QTL for six transcripts, all of which are significant in multiple nutrient environments. Further, we identified trans (i.e., distant) QTL for two transcripts, specific to a single nutrient environment, and one “plasticity” QTL that influences the change in gene expression between the control and high sugar diet. Nearly all transcripts, 85%, were significantly differentially expressed between diets. A discriminant function analysis for the control and dietary restriction treatments identified which transcripts best predict the diet treatment. The resulting composite discriminant function scores are correlated with median lifespan (r = 0.45) and mapping these scores revealed a significant QTL within the dietary restriction diet. Our results corroborate the association between the IIS/TOR pathway and the increase in lifespan under dietary restriction in a natural population and identify new locations in the genome involved in regulating the IIS/TOR pathway.

Project description:Analyses of QTLs for expression levels (eQTLs) of the genes reveal genetic relationship between expression variation and the regulator, thus unlocking the information for identifying the regulatory network. Oligo-nucleotide expression microarrays hybridized with RNA can simultaneously provide data for molecular markers and transcript abundance. In this study, we used Affymetrix GeneChip Rice Genome Array to analyze eQTLs in rice shoots at 72 h after germination from 110 recombinant inbred lines (RILs) derived from a cross between Zhenshan 97 and Minghui 63. Totally 1,632 single feature polymorphisms (SFPs) plus 23 PCR markers were identified and placed into 601 recombinant bins, spanning 1,459 cM in length, which were used as markers to genotype the RILs. We obtained 16,372 expression traits (e-traits) each with at least one eQTL, resulting in 26,051 eQTLs in total, including both cis- and trans-eQTLs. We also identified 171 eQTL hotspots among rice genome, each of which controls transcript variations of many e-traits. Gene Ontology analysis revealed enrichment of certain functional categories of genes in some of the eQTL hotspots. In particular, eQTLs for e-traits involving DNA metabolic process was significantly enriched in several eQTL hotspots on chromosomes 3, 5 and 10. Several transcription factors colocalizing with cis-eQTLs showed significant correlations with hundreds of e-traits, indicating possible co-regulation. We also detected correlations between the QTLs for shoot dry weight and eQTLs, revealing possible candidate genes for the trait. These results provided the clues for identification and characterization of regulatory network in the whole genome at the transcriptional level. To dissect the genetic variation between the two rice indica varieties Minghui 63 and Zhenshan 97, a total of 110 RILs from Minghui 63 and Zhenshan 97 and parents were sampled. And the Affymetrix Genechip rice Genome Array was used to investigate their dynamic transcript levels. Two independent biological replicates were sampled from each RIL, and three replicates for each parent.resulting in a dataset of 226 microarrays.

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Natural Genetic Variation Influences Protein Abundances in C. elegans Developmental Signalling Pathways

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