TY - JOUR
T1 - Causal genetic variation underlying metabolome differences
AU - Swain-Lenz, Devjanee
AU - Nikolskiy, Igor
AU - Cheng, Jiye
AU - Sudarsanam, Priya
AU - Nayler, Darcy
AU - Staller, Max V.
AU - Cohen, Barak A.
N1 - Publisher Copyright:
© 2017 by the Genetics Society of America.
PY - 2017
Y1 - 2017
N2 - An ongoing challenge in biology is to predict the phenotypes of individuals from their genotypes. Genetic variants that cause disease often change an individual’s total metabolite profile, or metabolome. In light of our extensive knowledge of metabolic pathways, genetic variants that alter the metabolome may help predict novel phenotypes. To link genetic variants to changes in the metabolome, we studied natural variation in the yeast Saccharomyces cerevisiae. We used an untargeted mass spectrometry method to identify dozens of metabolite Quantitative Trait Loci (mQTL), genomic regions containing genetic variation that control differences in metabolite levels between individuals. We mapped differences in urea cycle metabolites to genetic variation in specific genes known to regulate amino acid biosynthesis. Our functional assays reveal that genetic variation in two genes, AUA1 and ARG81, cause the differences in the abundance of several urea cycle metabolites. Based on knowledge of the urea cycle, we predicted and then validated a new phenotype: sensitivity to a particular class of amino acid isomers. Our results are a proof-of-concept that untargeted mass spectrometry can reveal links between natural genetic variants and metabolome diversity. The interpretability of our results demonstrates the promise of using genetic variants underlying natural differences in the metabolome to predict novel phenotypes from genotype.
AB - An ongoing challenge in biology is to predict the phenotypes of individuals from their genotypes. Genetic variants that cause disease often change an individual’s total metabolite profile, or metabolome. In light of our extensive knowledge of metabolic pathways, genetic variants that alter the metabolome may help predict novel phenotypes. To link genetic variants to changes in the metabolome, we studied natural variation in the yeast Saccharomyces cerevisiae. We used an untargeted mass spectrometry method to identify dozens of metabolite Quantitative Trait Loci (mQTL), genomic regions containing genetic variation that control differences in metabolite levels between individuals. We mapped differences in urea cycle metabolites to genetic variation in specific genes known to regulate amino acid biosynthesis. Our functional assays reveal that genetic variation in two genes, AUA1 and ARG81, cause the differences in the abundance of several urea cycle metabolites. Based on knowledge of the urea cycle, we predicted and then validated a new phenotype: sensitivity to a particular class of amino acid isomers. Our results are a proof-of-concept that untargeted mass spectrometry can reveal links between natural genetic variants and metabolome diversity. The interpretability of our results demonstrates the promise of using genetic variants underlying natural differences in the metabolome to predict novel phenotypes from genotype.
UR - http://www.scopus.com/inward/record.url?scp=85027077575&partnerID=8YFLogxK
U2 - 10.1534/genetics.117.203752
DO - 10.1534/genetics.117.203752
M3 - Article
C2 - 28652377
AN - SCOPUS:85027077575
SN - 0016-6731
VL - 206
SP - 2199
EP - 2206
JO - Genetics
JF - Genetics
IS - 4
ER -