摘要
Grapevine(Vitis spp.)contains a wealth of phytochemicals that have received considerable attention due to healthpromoting properties and biological activities as phytoalexins.To date,the genetic basis of the quantitative variations for these potentially beneficial compounds has been limited.Here,metabolic quantitative trait locus(mQTL)mapping was conducted using grapevine stems of a segregating F2 population.Metabolic profiling of grapevine stems was performed using liquid chromatography–high-resolution mass spectrometry(LC-HRMS),resulting in the detection of 1317 ions/features.In total,19 of these features matched with literature-reported stilbenoid masses and were genetically mapped using a 1449-SNP linkage map and R/qtl software,resulting in the identification of four mQTLs.Two large-effect mQTLs that corresponded to a stilbenoid dimer and a trimer were mapped on chromosome 18,accounting for phenotypic variances of 29.0%and 38.4%.Functional annotations of these large-effect mQTLs on the VitisNet network database revealed a major hotspot of disease-resistance motifs on chromosome 18.This 2.8-Mbp region contains 48 genes with R-gene motifs,including variants of TIR,NBS,and LRR,that might potentially confer resistance to powdery mildew,downy mildew,or other pathogens.The locus also encompasses genes associated with flavonoid and biosynthetic pathways that are likely involved in the production of secondary metabolites,including phytoalexins.In addition,haplotype dosage effects of the five mQTLs further characterized the genomic regions for differential production of stilbenoids that can be applied in resistance breeding through manipulation of stilbenoid production in planta.
基金
Funding for this research was provided by the USDA-NIFA Specialty Crops Research Initiative(Award Nos 2011-51181-30635 and 2011-51181-30850)through the VitisGen project and the Northern Grapes Project,as well as by the Minnesota Agricultural Experiment Station and the South Dakota Agricultural Experiment Station through the Hatch projects
Funding was also provided by the National Science Foundation IOS(Award No.1238812).
