Ruihua Ren

Development of highly polymorphic SNP markers from the complexity reduced portion of maize [Zea mays L.] genome for use in marker-assisted breeding

The duplicated and the highly repetitive nature of the maize genome has historically impeded the development of true single nucleotide polymorphism (SNP) markers in this crop. Recent advances in genome complexity reduction methods coupled with sequencing-by-synthesis technologies permit the implementation of efficient genome-wide SNP discovery in maize. In this study, we have applied Complexity Reduction of Polymorphic Sequences technology (Keygene N.V., Wageningen, The Netherlands) for the identification of informative SNPs between two genetically distinct maize inbred lines of North and South American origins. This approach resulted in the discovery of 1,123 putative SNPs representing low and single copy loci. In silico and experimental (Illumina GoldenGate (GG) assay) validation of putative SNPs resulted in mapping of 604 markers, out of which 188 SNPs represented 43 haplotype blocks distributed across all ten chromosomes. We have determined and clearly stated a specific combination of stringent criteria (>0.3 minor allele frequency, >0.8 GenTrainScore and >0.5 Chi_test100 score) necessary for the identification of highly polymorphic and genetically stable SNP markers. Due to these criteria, we identified a subset of 120 high-quality SNP markers to leverage in GG assay-based marker-assisted selection projects. A total of 32 high-quality SNPs represented 21 haplotypes out of 43 identified in this study. The information on the selection criteria of highly polymorphic SNPs in a complex genome such as maize and the public availability of these SNP assays will be of great value for the maize molecular genetics and breeding community.

Combining powers of linkage and association mapping for precise dissection of QTL controlling resistance to gray leaf spot disease in maize ( Zea mays L.)

BackgroundGray Leaf Spot (GLS causal agents Cercospora zeae-maydis and Cercospora zeina) is one of the most important foliar diseases of maize in all areas where the crop is being cultivated. Although in the USA the situation with GLS severity is not as critical as in sub-Saharan Africa or Brazil, the evidence of climate change, increasing corn monoculture as well as the narrow genetic base of North American resistant germplasm can turn the disease into a serious threat to US corn production. The development of GLS resistant cultivars is one way to control the disease. In this study we combined the high QTL detection power of genetic linkage mapping with the high resolution power of genome-wide association study (GWAS) to precisely dissect QTL controlling GLS resistance and identify closely linked molecular markers for robust marker-assisted selection and trait introgression.ResultsUsing genetic linkage analysis with a small bi-parental mapping population, we identified four GLS resistance QTL on chromosomes 1, 6, 7, and 8, which were validated by GWAS. GWAS enabled us to dramatically increase the resolution within the confidence intervals of the above-mentioned QTL. Particularly, GWAS revealed that QTLGLSchr8, detected by genetic linkage mapping as a locus with major effect, was likely represented by two QTL with smaller effects. Conducted in parallel, GWAS of days-to-silking demonstrated the co-localization of flowering time QTL with GLS resistance QTL on chromosome 7 indicating that either QTLGLSchr7 is a flowering time QTL or it is a GLS resistance QTL that co-segregates with the latter. As a result, this genetic linkage – GWAS hybrid mapping system enabled us to identify one novel GLS resistance QTL (QTLGLSchr8a) and confirm with more refined positions four more previously mapped QTL (QTLGLSchr1, QTLGLSchr6, QTLGLSchr7, and QTLGLSchr8b). Through the novel Single Donor vs. Elite Panel method we were able to identify within QTL confidence intervals SNP markers that would be suitable for marker-assisted selection of gray leaf spot resistant genotypes containing the above-mentioned GLS resistance QTL.ConclusionThe application of a genetic linkage – GWAS hybrid mapping system enabled us to dramatically increase the resolution within the confidence interval of GLS resistance QTL by-passing labor- and time-intensive fine mapping. This method appears to have a great potential to accelerate the pace of QTL mapping projects. It is universal and can be used in the QTL mapping projects in any crops.