During the past decade, the use of natural variation and quantitative trait locus (QTL) analysis has been proven to be very fruitful in identifying genes that play a role in complex multigenic processes. Shortly, naturally occurring accessions (ecotypes), preferably differing for the trait under investigation, are crossed; the resulting progeny is genotypes by molecular markers, and trait(s) are quantified. Then, marker-trait association are studied using appropriate statistical software, resulting in QTL, being genetic region that significantly affect the trait under investigation. As a follow-up the underpinning genes may be identified, and the (nucleotide) polymorphism, responsible for the variation between the parental accessions, can be revealed.
Recently, it was shown that ‘omics’ technologies may be used for large-scale QTL studies, in which gene expression levels, protein levels or metabolite levels are used as quantitative traits. Collectively, these approaches are named ‘genetical genomics’ (Jansen and Nap, 2001). Bulk QTL mappling allows for the construction of correlation networks, which are used to identify novel components of biological processes (e.g. flowering, glucosinolate biosynthesis). We use transcipt QTL mapping to study the process of protein secretion and folding in the ER to map branches of the Unfolded Protein Response in plants.