Understanding the metabolic content of plants and its genetic basis is important to determine the most appropriate breeding strategies for traits such as yield, fruit quality, nutritional content, tolerance to disease factors, adaptation to various environmental conditions, and tolerance to abiotic and biotic stresses. Recently, post-genomic studies such as metabolomics, proteomics and transcriptomics are attracting attention and being used in conjunction with genomic studies. These studies help to speed research progress with crops as well as model plants. Tomato (Solanum lycopersicum) is an important crop which is cultivated widely in the world and in our country, and is also important for our daily diet. Although there is growing attention to studies on tomato day by day, there are limited studies that identify the quantitative trait locus (QTL) regions responsible for important agronomic, economic, nutritional and health related traits by correlation of metabolomics and genomics data. In this study, an interspecific IBL (inbred backcross line) population derived from the cross S. lycopersicum cv. Tueza x S. pimpinellifolium (LA1589) was both genotyped via genotyping by sequencing (GBS) and quantified for primary and secondary metabolites affecting yield, quality and nutritional value of the fruit to determine QTL regions for the targeted metabolites. In total, 187 QTLs were identified for 143 important traits. The data obtained from this study will help to shed light on the genetic control of plant metabolism and to develop high yield and nutrient-rich cultivars with improved agronomic traits by breeding strategies.