Recent advances in -omics technologies such as transcriptomics, metabolomics, and proteomics along with genotypic profiling have permitted dissection of the genetics of complex traits represented by molecular phenotypes in nonmodel species. To identify the genetic factors underlying variation in primary metabolism in potato (Solanum tuberosum), we have profiled primary metabolite content in a diploid potato mapping population, derived from crosses between S. tuberosum and wild relatives, using gas chromatography-time of flight-mass spectrometry. In total, 139 polar metabolites were detected, of which we identified metabolite quantitative trait loci for approximately 72% of the detected compounds. In order to obtain an insight into the relationships between metabolic traits and classical phenotypic traits, we also analyzed statistical associations between them. The combined analysis of genetic information through quantitative trait locus coincidence and the application of statistical learning methods provide information on putative indicators associated with the alterations in metabolic networks that affect complex phenotypic traits.The variation observed in phenotypic trait values in plants is often of quantitative nature, and it remains challenging to unravel the genetic basis of these traits. Quantitative trait locus (QTL) mapping is currently the most commonly used approach to dissect the genetic factors underlying complex traits. The goal of QTL mapping is to identify genomic regions associated with a specific complex phenotype by statistical analysis of the associations between genetic markers and phenotypic variation (Doerge, 2002). Recently, advances in highthroughput analysis and analytical detection methods have facilitated more integrated approaches to measure global phenotypic variation at the molecular level. Metabolite profiling is a rapidly evolving technology that has significantly increased the possibilities of performing high-throughput analysis of hundreds to thousands of compounds in a range of plants, including complex crop species. Metabolite composition is of great importance in crop plants, as a number of important traits such as biotic and abiotic stress resistance, postharvest processing, and nutritional value are largely dependent on the metabolic content (Fernie and Schauer, 2009).In potato (Solanum tuberosum) breeding, metabolomic studies have progressively increased in importance, as many potato tuber traits such as content and quality of starch, chipping quality, flesh color, taste, and glycoalkaloid content have been shown to be linked to a wide range of metabolites (Coffin et al., 1987;Dobson et al., 2008). As a result, tuber quality can be assessed by assaying a range of metabolites. Gas chromatography-time of flight-mass spectrometry (GC-TOF-MS) has been shown to be useful for the rapid and highly sensitive detection of a large fraction of plant metabolites covering the central pathways of primary metabolism (Roessner et al., 2000;Lisec et al., 2006). In potato, untargeted metab...