Project Number: 8042-21000-283-10-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 29, 2016
End Date: Sep 28, 2021
Anthracnose fruit rot is one of the most serious diseases affecting the production of tomato (Solanum lycopersicum L.) in the United States and is incited by several species of pathogenic fungi in the genus Colletotrichum. This disease is associated with decay of ripe or ripening fruit and is a threat to profitable crop production. Host resistance is desirable since crop rotation and chemical controls provide incomplete protection from this pathogen. Effective genetic resistance to anthracnose is not present in cultivated forms of tomato but is available in unadapted crop relatives. Resistance is multigenic and difficult to transfer to cultivated forms of the crop using traditional plant breeding practices. Our objective is to identify genes in tomato that influence anthracnose fruit rot resistance and map those loci in a recombinant inbred line population of tomato. Molecular marker tagged genes associated with resistance will improve selection efficiency in breeding programs for development of anthracnose resistant cultivars.
GIFVL developed a population of 250 recombinant inbred lines (RIL) from a cross between an unadapted small-fruited highly resistant tomato accession and a large fruited commercial tomato line susceptible to anthracnose. GIFVL has previously reported on the heritability of anthracnose resistance in this population. This population will be utilized to identify and map genetic factors contributing to host resistance. Tomato genomic DNA will be purified from respective F7 and F8 RILs that comprise this population. A tomato reference genome and large database of mapped SNP and SSR markers that are polymorphic in intra- and interspecific tomato populations are now available for tomato. On average, available markers will allow marker placement at least approximately every 10 cm throughout the genome. Markers that discriminate parental lines will be utilized to identify and map resistance QTL. Interval and single point QTL analysis will be performed using commercially available software such as QGene with LOD 3.0 and P<0.001 as minimum significance levels for QTL detection. The percentage of phenotypic variation explained by the QTL, the degree of dominance and Pearson Correlation coefficients will also be derived using QGene. A selective mapping approach will be considered to map new markers if we are fortunate to identify sufficiently informative lines early in the genotyping phase of the project. QTL that map to low recombination regions, e.g. centromeric regions, will be identified using the tomato physical map. These markers are typically uninformative for fine mapping.