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Fusarium head blight (FHB), is one of the destructive fugue diseases of wheat worldwide caused by the Fusarium verticillioides (F.v). In this study, a population consisting of 262 recombinant inbred lines (RILs) derived from Zhongmai 578 and Jimai 22 was used to map Quantitative Trait Locus (QTL) for FHB resistance, with the genotype data using the wheat 50 K single nucleotide polymorphism (SNP) array. The percentage of symptomatic spikelet (PSS) and the weighted average of PSS (PSSW) were collected for each RIL to represent their resistance to wheat head blight caused by F.v. In total, 22 QTL associated with FHB resistance were identified on chromosomes 1D, 2B, 3B, 4A, 5D, 7A, 7B, and 7D, respectively, from which 10 and 12 QTL were detected from PSS and PSSW respectively, explaining 3.82%–10.57% of the phenotypic variances using the inclusive composite interval mapping method. One novel QTL, Qfhb. haust-4A.1, was identified, explaining 10.56% of the phenotypic variation. One stable QTL, Qfhb. haust-1D.1 was detected on chromosome 1D across multiple environments explaining 4.39%–5.70% of the phenotypic variation. Forty-seven candidate genes related to disease resistance were found in the interval of Qfhb. haust-1D.1 and Qfhb. haust-4A.1. Genomic prediction accuracies were estimated from the five-fold cross-validation scheme ranging from 0.34 to 0.40 for PSS, and from 0.34 to 0.39 for PSSW in in-vivo inoculation treatment. This study provided new insight into the genetic analysis of resistance to wheat head blight caused by F.v, and genomic selection (GS) as a potential approach for improving the resistance of wheat head blight.

Seed vigor is an important parameter of seed quality, and identification of seed vigor related genes can provide an important basis for highly efficient molecular breeding in wheat. In the present study, a doubled haploid (DH) population with 174 lines derived from a cross between Yangmai16 and Zhongmai 895 was used to evaluate 10 seed vigor related traits in Luoyang during the 2018-2019 cropping season and in Mengjin and Luoning Counties during 2019-2020 cropping season for three environments. Quantitative trait locus (QTL) mapping of 10 seed vigor related traits in the DH population resulted in the discovery/identification of 28 QTLs on chromosomes 2B, 3D, 4B, 4D, 5A, 5B, 6A, 6B, 6D, 7A and 7D, explaining 3.6-23.7% of the phenotypic variances. Among them, one QTL cluster for shoot length, root length and vigor index was mapped between AX-89421921 and Rht-D1_SNP on chromosome 4D in the physical intervals of 18.78-19.29 Mb (0.51 Mb), explaining 9.2-20.5% of the phenotypic variances. Another QTL for these traits was identified at the physical position 185.74 Mb on chromosome 5B, which was flanked by AX-111465230 and AX-109519938 and accounted for 8.0-13.3% of the phenotypic variances. Two QTLs for shoot length, shoot fresh weight and shoot dry weight were identified in the marker intervals of AX-109384026-AX-111120402 and AX-111651800-AX-94443918 on chromosomes 6A and 6B, explaining 8.2-11.7% and 3.6-10.3% of the phenotypic variance, respectively; both alleles for increasing phenotypic values were derived from Yangmai 16. We also developed the KASP markers for the QTL cluster QVI.haust-4D.1/QSL.haust-4D/QRL.haust-4D, and validated in an international panel of 135 wheat accessions. The germplasm, genes and KASP markers were developed for breeders to improve wheat varieties with seed vigor related traits.

Fructans (fructo-oligosaccharides) is one of the most important carbohydrates in wheat vegetative tissues and plays a vital role in wheat grain development. One hundred and forty 'Avocet'× 'Chilero' wheat (Triticum aestivum L.) recombinant inbred lines (RILs) were phenotyped for grain fructans at Luoyang and Langzhou field sites in the 2015-2016 and 2016-2017 growing seasons and 2090 Diversity Arrays Technology (DArT) molecular marker data were used to determine genomic regions controlling fructan content. Eleven significant quantitative trait loci (QTL) for wheat fructan content were identified on chromosomes 1B, 2A, 2B, 2D, 3D, 4B, 6B, 6D, 7A, and 7B using the inclusive composite interval mapping (ICIM) method, explaining 4.08% to 27.40% of the phenotypic variance, with seven exceeding 10%. The single environment analysis identified QF.haust-6D.1 and QF.haust-7B in Luoyang, QF.haust-1B, QF.haust-2D, QF.haust-3D, and QF.haust-7B in Lanzhou, and QF.haust-1B, QF.haust-7A, and QF.haust-7B in average phenotypic performance. The multi-environment analysis identified QF.haust-2B and QF.haust-7B, which explained 21.01% and 17.39% of the phenotypic variance, respectively. The positive allele of QF.haust-2B and QF.haust-7B were all originated from Chilero. QF.haust-2B was flanked by the 3957031 and SNP1203021 markers; candidate genes for QF.haust-2B were identified by anchoring marker sequences in the IGWSC wheat genome sequence, involving a variety of biological processes, such as the regulation of ribosomes metabolism in wheat. We also constructed the physical map for wheat grain fructan QF.haust-2B and QF.haust-7B, QF.haust-7B with a physical length of 11.47 Mb between marker SNP3026392 and 3954877 and 103 genes within the segment, in which ten were related to glucose metabolism. This study provides a theoretical basis and technical support for wheat grain fructan content-related genes and molecular marker-assisted breeding.