Summary of Study ST000870
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000603. The data can be accessed directly via it's Project DOI: 10.21228/M8QQ3S This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
| Study ID | ST000870 |
| Study Title | Untargeted metabolomic profile of Saccharomyces cerevisiae (F2) hybrids (part II) |
| Study Summary | Metabolomic profiles were compiled from oak and wine yeast parents, and their F2 hybrids. Included in this study are extraction controls. |
| Institute | Washington University in St. Louis |
| Last Name | Swain Lenz |
| First Name | Devjanee |
| Address | 4515 McKinley Avenue, Saint Louis, Missouri, 63110, USA |
| devjanee.swain.lenz@duke.edu | |
| Phone | 314-362-3679 |
| Submit Date | 2017-08-22 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Thermo) |
| Analysis Type Detail | API-MS |
| Release Date | 2017-11-20 |
| Release Version | 1 |
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Project:
| Project ID: | PR000603 |
| Project DOI: | doi: 10.21228/M8QQ3S |
| Project Title: | Causal genetic variation underlying metabolome differences |
| Project Summary: | A goal of biology is to predict the phenotypes of individuals, such as side effects to drugs, from their genotypes. Genetic variants that cause disease can change an individual’s total metabolite profile, or metabolome. Understanding the function of these genetic variants may help predict novel phenotypes. We used an unbiased method in yeast to show that genetic differences in two genes change the levels of several urea cycle metabolites. Leveraging knowledge of the urea cycle, we then predicted and validated the sensitivity of yeast strains to a particular drug. The interpretability of our results demonstrates the promise of using genetic variants underlying differences in the metabolome to predict novel phenotypes from genotype. |
| Institute: | Washington University in St. Louis |
| Last Name: | Swain Lenz |
| First Name: | Devjanee |
| Address: | 4515 McKinley Avenue, Saint Louis, Missouri, 63110, USA |
| Email: | devjanee.swain.lenz@duke.edu |
| Phone: | 314-362-3679 |
