Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Interaction of Genetic Variants Activates Latent Metabolic Pathways in Yeast

ABSTRACT:

Genetic interactions are fundamental to the architecture of complex traits, yet the molecular mechanisms by which variant combinations influence cellular pathways remain poorly understood. Here, we answer the question of whether interactions between genetic variants can activate unique pathways and if such pathways can be targeted to modulate phenotypic outcomes. The model organism Saccharomyces cerevisiae was used to dissect how two causal SNPs, MKT1(89G) and TAO3(4477C), interact to modulate metabolic and phenotypic outcomes during sporulation. By integrating time-resolved transcriptomics, absolute proteomics, and targeted metabolomics in isogenic allele replacement yeast strains, we show that the combined presence of these SNPs uniquely activates the arginine biosynthesis pathway and suppresses ribosome biogenesis, reflecting a metabolic trade-off that enhances sporulation efficiency. Functional validation demonstrates that the arginine pathway is essential for mitochondrial activity and efficient sporulation only in the double-SNP background. Our findings show how genetic variant interactions can rewire core metabolic networks, providing a mechanistic framework for understanding polygenic trait regulation and the emergence of additive effects in complex traits.

INSTRUMENT(S): Liquid Chromatography MS - positive - reverse phase

PROVIDER: MTBLS12761 | MetaboLights | 2025-07-22

REPOSITORIES: MetaboLights

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	a_MTBLS12761_LC-MS_positive_reverse-phase_metabolite_profiling.txt	Txt
	i_Investigation.txt	Txt
	m_MTBLS12761_LC-MS_positive_reverse-phase_metabolite_profiling_v2_maf.tsv	Tabular
	s_MTBLS12761.txt	Txt

Items per page:

1 - 4 of 4

Similar Datasets

Interaction of genetic variants activates latent metabolic pathways in yeast

Project description:Genetic interactions are fundamental to the architecture of complex traits, yet the molecular mechanisms by which variant combinations influence cellular pathways remain poorly understood. Here, we answer the question of whether interactions between genetic variants can activate unique pathways and if such pathways can be targeted to modulate phenotypic outcomes. The model organism Saccharomyces cerevisiae was used to dissect how two causal SNPs , MKT189G and TAO34477C, interact to modulate metabolic and phenotypic outcomes during sporulation. By integrating time-resolved transcriptomics, absolute proteomics, and targeted metabolomics in isogenic allele replacement yeast strains, we show that the combined presence of these SNPs uniquely activates the arginine biosynthesis pathway and suppresses ribosome biogenesis, reflecting a metabolic trade-off that enhances sporulation efficiency. Functional validation demonstrates that the arginine pathway is essential for mitochondrial activity and efficient sporulation only in the double-SNP background. Our findings show how genetic variant interactions can rewire core metabolic networks, providing a mechanistic framework for understanding polygenic trait regulation and the emergence of additive effects in complex traits.

2025-07-22 | PXD056947 | Pride

Temporal transcriptomic and proteomic profiling of causal variants in combination uncovers molecular drivers of phenotypic additivity

2025-07-22 | GSE278267 | GEO

Rare and common genetic determinants of metabolic individuality and their effects on human health (INTERVAL study assays)

Project description:Garrod’s concept of “chemical individuality” has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant-metabolite associations (P<1.25x10^-11) within 330 genomic regions, with rare variants (MAF≤1%) explaining 9.4% of associations. Jointly modelling metabolites in each region, we identified 423 regional, co-regulated, variant-metabolite clusters called GIMs (Genetically Influenced Metabotypes). We assigned causal genes for 62.4% of GIMs, providing new insights into fundamental metabolite physiology and their clinical relevance, including metabolite guided discovery of potential adverse drug effects (DPYD, SRD5A2). We show strong enrichment of Inborn Errors of Metabolism (IEM)-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of IEMs. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential aetiological relationships. INTERVAL study assays are reported in the current study MTBLS834EPIC-Norfolk study assays are reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS833' rel='noopener noreferrer' target='_blank'>MTBLS833</a>

2022-09-09 | MTBLS834 | MetaboLights

Stable Polycomb-dependent transgenerational inheritance of chromatin states in Drosophila

Project description:Transgenerational epigenetic inheritance entails transmission of epigenetically determined phenotypic traits through multiple generations. However, very little is known on the principles and the mechanisms governing this type of inheritance. Here, we established stable and isogenic Drosophila epilines by transiently enhancing long-range chromatin interactions. Such epilines display two opposing chromatin states, which depend on differential levels of the H3K27me3 histone mark. Once established, both the active and the repressed epialleles can dominantly be transmitted to naïve flies and can induce paramutation. Importantly, both epilines can be reset to an intermediate naïve state by disrupting chromatin interactions. Finally, we show that the environment can modulate the expressivity of the epialleles and we extend our paradigm to naturally occurring genetic makeups. Our work sheds light on how nuclear organization contributes to epigenetically heritable phenotypic variability and therefore to evolution.

2017-03-14 | GSE76799 | GEO

Genetic Modulation of Protein Expression in Rat Brain

Project description:Genetic linkage analyses in rodents have unveiled numerous genomic loci contributing to a diverse array of traits, such as susceptibility to addictive behaviors and hypertension. To investigate the genetic basis of trait variation in rodents, genetic reference populations, such as the HXB/BXH recombinant inbred (RI) rat panel, have been extensively utilized. The HXB/BXH panel serves as a well-established rat model to dissect genetic variants that modulate metabolic and cardiovascular diseases. The panel has accumulated a wealth of comprehensive genotypic data, transcriptomic profiles, and phenotypic data, enabling integrative analyses to understand the pathway from genomic loci to traits. The parental strains of the HXB/BXH rat panel, SHR/OlaIpcv (SHR) and BN-Lx/Cub (BN-Lx) strains, have been completely sequenced, and sequence variants between them have been well-defined. Integrating genomics, transcriptomics, and proteomics data from these two inbred strains, have successfully identified splice events, genetic variants, and RNA editing. However, there remains a lack of proteome-wide profiling across all 30 HXB/BXH RI strains, and the genetic regulation of protein expression remains largely unexplored.

2024-12-11 | PXD058748 | Pride

Rare and common genetic determinants of metabolic individuality and their effects on human health (EPIC-Norfolk study assays)

Project description:Garrod’s concept of “chemical individuality” has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant-metabolite associations (P<1.25x10^-11) within 330 genomic regions, with rare variants (MAF≤1%) explaining 9.4% of associations. Jointly modelling metabolites in each region, we identified 423 regional, co-regulated, variant-metabolite clusters called GIMs (Genetically Influenced Metabotypes). We assigned causal genes for 62.4% of GIMs, providing new insights into fundamental metabolite physiology and their clinical relevance, including metabolite guided discovery of potential adverse drug effects (DPYD, SRD5A2). We show strong enrichment of Inborn Errors of Metabolism (IEM)-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of IEMs. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential aetiological relationships. EPIC-Norfolk study assays are reported in the current study MTBLS833INTERVAL study assays are reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS834' rel='noopener noreferrer' target='_blank'>MTBLS834</a>

2022-09-09 | MTBLS833 | MetaboLights

Gene Expression Profiles of Sporadic Canine Hemangiosarcoma are Uniquely Associated with Breed

Project description:Abnormal function of genes is at the root of most cancers, but heritable cancer syndromes account for a very small minority of all tumors in humans and domestic animals. The majority of cancers are “sporadic,” that is, they are not heritable in the strictest sense. Instead, sporadic cancers occur due to interactions of unknown intrinsic (heritable) and environmental factors that lead to malignant transformation and uncontrolled growth. Identification of heritable risk factors in sporadic human cancers is difficult because individual genetic backgrounds are very heterogeneous. To this end, individual genetic backgrounds of purebred dogs are more homogeneous, and dog breeds show different predilection to develop specific cancers. Here, we used genomic screens based on gene expression profiling to identify sets of genes that may contribute to the development of canine hemangiosarcoma, a relatively common endothelial sarcoma. Specific genes in a single breed (Golden Retrievers) are modulated by (or with) heritable risk traits, showing functional features that appear to modulate tumor behavior. Our results suggest these methods are suitable to identify genes that will enhance our understanding of how these cancers happen, as well as possible treatment targets that will improve outcomes of both human and canine cancer patients. Keywords: Hemangiosarcoma, microarray, heritability, GSEA, canine 10 samples were analysed. 6 Golden Retrievers with hemangiosarcoma, 3 non-Golden Retrievers with hemangiosarcoma, and 1 mixed breed Golden Retriever with hemangiosarcoma. The experiment was designed to find genes associated with breed and hemangiosarcoma to asses genetic make-up on disease susceptibility and/or progression

2009-03-06 | E-GEOD-15086 | biostudies-arrayexpress

Evolution of genotypic and phenotypic diversity in multispecies biofilms

Project description:Interactions occurring in microbial communities can affect the fitness and adaptability of their individual members when facing changing environmental conditions. This study investigated the impact of interspecies interactions in selecting Bacillus thuringiensis variants emerging in biofilm and planktonic environments. During evolution experiments, a B. thuringiensis distinct phenotypic variant of B. thuringiensis frequently occurred, despite the presence of other species or culture setup. Remarkably, selection of this variant was significantly favored over its ancestor in biofilm settings and when coexisting with other species co-isolated from a wastewater facility, namely Pseudomonas defluvii and Pseudomonas brenneri. Interestingly, the evolved phenotype did not show higher biofilm productivity than its ancestor under any condition, while it was indeed reduced in mixed-species biofilms. Such observation aligned with the reduced abundance of TasA, a major biofilm matrix component in Bacillus species, and SpoVG, a regulator of sporulation, as revealed by matrix proteomics analysis. Furthermore, the variant showed shorter generation time and a lack of sporulation compared to its ancestor, consistent with mutations in key genes for regulating sporulation. Our results indicate that interspecies interactions within biofilms promote B. thuringiensis diversification and alter traits such as biofilm matrix production. Although sporulation is a survival mechanism, this study provides evidence that sporulation does not confer a fitness advantage in in vitro biofilm setting, even within mixed cultures, in the absence of severe stress.

2025-06-19 | PXD046156 | Pride

Intergenerational consequences of gene-environment induced epigenetic dynamics at rDNA in the mouse (RRBS)

Project description:The ability of environmental exposures in one generation to elicit phenotypic outcomes in subsequent generations suggests that DNA is not the sole vehicle of biological heredity. Such non-genetic inheritance has been demonstrated in a variety of non-mammalian species but, to date, has remained controversial and inadequately characterised in mammals. Here, we show that early life protein restriction (PR) in mice alters DNA methylation at specific genetic variants of multi-copy ribosomal DNA (rDNA), to produce a linear correlation with the extent of growth restriction induced by PR. These effects are common to soma and germ-line and are concomitant with changes in the relative abundance of the responsive rDNA genetic variant. Intergenerational pedigree analysis reveals that rDNA genetic correlations are abolished between directly exposed males and their unexposed offspring, and epigenetic correlations are gained. To the best of our knowledge, this is the first direct demonstration in mammals of epigenetic dynamics induced by gene-environment interactions. Our work confirms rDNA as an evolutionarily conserved target of nutritional insults and intergenerational effects in flies, yeast, and now mice.

2016-07-08 | GSE72609 | GEO

Intergenerational consequences of gene-environment induced epigenetic dynamics at rDNA in the mouse (RNA-Seq)

2016-07-08 | GSE72607 | GEO