Abstract
Increasing grain yield is the ultimate goal for maize breeding. High resolution quantitative trait loci (QTL) mapping can help us understand the molecular basis of phenotypic variation of yield and thus facilitate marker assisted breeding. The aim of this study is to use genotyping-by-sequencing (GBS) for large-scale SNP discovery and simultaneous genotyping of all F2 individuals from a cross between two varieties of maize that are in clear contrast in yield and related traits. A set of 199 F2 progeny derived from the cross of varieties SG-5 and SG-7 were generated and genotyped by GBS. A total of 1,046,524,604 reads with an average of 5,258,918 reads per F2 individual were generated. This number of reads represents an approximately 0.36-fold coverage of the maize reference genome Zea_mays.AGPv3.29 for each F2 individual. A total of 68,882 raw SNPs were discovered in the F2 population, which, after stringent filtering, led to a total of 29,927 high quality SNPs. Comparative analysis using these physically mapped marker loci revealed a higher degree of synteny with the reference genome. The SNP genotype data were utilized to construct an intra-specific genetic linkage map of maize consisting of 3,305 bins on 10 linkage groups spanning 2,236.66 cM at an average distance of 0.68 cM between consecutive markers. From this map, we identified 28 QTLs associated with yield traits (100-kernel weight, ear length, ear diameter, cob diameter, kernel row number, corn grains per row, ear weight, and grain weight per plant) using the composite interval mapping (CIM) method and 29 QTLs using the least absolute shrinkage selection operator (LASSO) method. QTLs identified by the CIM method account for 6.4% to 19.7% of the phenotypic variation. Small intervals of three QTLs (qCGR-1, qKW-2, and qGWP-4) contain several genes, including one gene (GRMZM2G139872) encoding the F-box protein, three genes (GRMZM2G180811, GRMZM5G828139, and GRMZM5G873194) encoding the WD40-repeat protein, and one gene (GRMZM2G019183) encoding the UDP-Glycosyltransferase. The work will not only help to understand the mechanisms that control yield traits of maize, but also provide a basis for marker-assisted selection and map-based cloning in further studies.
Highlights
Maize (Zea mays) is one of the most important cereal and forage crops of the world
In one of our previous studies, a small-effect quantitative trait loci (QTL) Flwdt7 conferring flowering time of soybean was mapped on LG C2 and it only contributed 11.0% of the phenotypic variance in the BC1F3 genetic background while in the advanced residual heterozygous line (RHL) populations the contribution increased to 36.8% (Su et al, 2010)
Because least absolute shrinkage selection operator (LASSO) deals with a multiple marker model where all marker effects are estimated simultaneously, the result should be more reliable than the composite interval mapping (CIM) method
Summary
High grain yield is a constant topic and pursuing direction of maize breeders. Most yield related traits are quantitative in nature and are often controlled by multiple genes. Quantitative trait loci (QTL) mapping has been successfully applied to maize and with this technology people have identified many loci relevant to yield and yield component traits (Beavis et al, 1994; Veldboom et al, 1994; Austin and Lee, 1996; Lima et al, 2006; Messmer et al, 2009). The high complexity of crop genomes and the low-coverage of genetic markers across chromosomes have posed great challenges for dissection of quantitative genetic variation by QTL analysis, especially for detecting small-effect QTL (Wenzl et al, 2006; Yu et al, 2011)
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