Applying network and genetic analysis to the potato metabolome.

ABSTRACT: Compositional traits in potato [Solanum tuberosum L.] are economically important but genetically complex, often controlled by many loci of small effect; new methods need to be developed to accelerate analysis and improvement of such traits, like chip quality. In this study, we used network analysis to organize hundreds of metabolic features detected by mass spectrometry into groups, as a precursor to genetic analysis. 981 features were condensed into 44 modules; module eigenvalues were used for genetic mapping and correlation analysis with phenotype data collected by the Solanaceae Coordinated Agricultural Project. Half of the modules were associated with at least one SNP according to GWAS; 11 of those modules were also significantly correlated with chip color. Within those modules

SUBMITTER: Levina AV 

PROVIDER: S-EPMC10154602 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature