Location: Vegetable Crops Research2013 Annual Report
1a. Objectives (from AD-416):
1. Develop and characterize cucumber and melon populations segregating for fruit size. A set of segregating populations from cucumber will be analyzed for fruit size phenotype. 2. Combine genomic tools, segregating populations, and phenotypic characterization to identify loci associated with fruit size. Genetic analysis using the SNP arrays developed in this project and segregating populations for fruit size will identify QTL associated with fruit size.
1b. Approach (from AD-416):
Three mapping populations will be used for phenotyping of fruit size (RIL and F2:3 families). Phenotypic data will be collected from field trials in three years (2011, 2012, and 2013) at both greenhouse and field conditions. Whole genome scan of different population segregating for fruit size will be conducted for QTL analysis to establish marker-fruit size trait associations.
3. Progress Report:
This project was renumbered from 3655-21000-048-28A to 3655-21000-062-09A. This is the final report, project terminated 06/30/2013. Development of populations for fruit size quantitative trait loci (QTL) mapping in cucumber. We developed three populations segregating for fruit size and other traits for this project. The first population included 150 recombinant inbred lines (RIL)s, (F7, F8, or F9) from the cross between Gy14 (North American pickling type) and 9930 (North China fresh market type). The second population includes 69 RILs (F8) and 500 F2 plants from the cross between Gy14 and the wild cucumber (C. sativus var. hardwickii) plant introduction line (PI) 183967. The third population consisted of 175 F2:3 families and 432 F2 plants of XSBN-3 x PI 249561. These populations are being used for mapping QTL of multiple traits that important in cucumber production of cucumber evolution. Phenotypic data collection. In the 2011 field season, replicated trials were conducted in three locations (Hancock, Wisconsin; Raleigh, North Carolina; and East Lansing, Michigan) to collect data for fruit size (length and diameter) from the Gy14 x 9930 RIL populations. In the 2012 and 2013 field season, two more trials were conducted in Hancock, Wisconsin on this RIL population. Fruit size data have been, or will be used in QTL mapping to identify fruit size QTL in cucumber with molecular marker data. We also grew 175 F3 families and 432 F2 plants of XSBN x PI 249561 cross, as well RIL and F2 plants of GY14 x hardwickii cross at the Hancock Research Station. We have collected data for the following traits in these populations: flowering time, fruit length and diameter, fruit number and weight, and flesh color. We sequenced the Gy14 cucumber genome at 20x genome coverage. We also re-sequenced the 9930 cucumber genome with the Illumina HiSeq 2000 platform (30x genome coverage). These sequences were sent to our collaborators in Israel for single nucleotide polymorphism (SNP) discovery and SNP array development. In total, 97,015 high quality SNPs were identified, and nearly 50% were spotted into a customized SNP array, which were used for hybridization with deoxyribonucleic acid (DNA) samples of 119 Gy14 x 9930 RILs for QTL mapping of fruit sizes in cucumber. Data analysis is underway, and we expect at least two manuscripts from the above-mentioned work. QTL mapping and fruit size QTL validation in other mapping populations. We are developing microsatellite or simple sequence repeat (SSR)-based linkage maps using the XSBN x PI 249561 and Gy14 x HARD populations, which will be used in QTL mapping of fruit size and other traits. At this time, ~200 SSR marker loci have been placed on each map. With average marker interval of ~3 cM, phenotypic data are being collected from the field trials which will be used to identify major QTLs for fruit length and diameter, flowering time, and fruit number in cucumber. We anticipate two manuscripts from this part of research. This research relates to objectives 1 and 2 through the development of populations for fruit size QTL mapping in cucumber, phenotypic data collection, genotyping, and the development of linkage maps.