Shunhe Cheng

A Combined Association Mapping and Linkage Analysis of Kernel Number Per Spike in Common Wheat (Triticum aestivum L.)

Kernel number per spike (KNPS) in wheat is a key factor that limits yield improvement. In this study, we genotyped a set of 264 cultivars, and a RIL population derived from the cross Yangmai 13/C615 using the 90 K wheat iSelect SNP array. We detected 62 significantly associated signals for KNPS at 47 single nucleotide polymorphism (SNP) loci through genome-wide association analysis of data obtained from multiple environments. These loci were on 19 chromosomes, and the phenotypic variation attributable to each one ranged from 1.53 to 39.52%. Twelve (25.53%) of the loci were also significantly associated with KNPS in the RIL population grown in multiple environments. For example, BS00022896_51-2ATT, BobWhite_c10539_201-2DAA, Excalibur_c73633_120-3BGG, and Kukri_c35508_426-7DTT were significantly associated with KNPS in all environments. Our findings demonstrate the effective integration of association mapping and linkage analysis for KNPS, and underpin KNPS as a target trait for marker-assisted selection and genetic fine mapping.

Association and Validation of Yield-Favored Alleles in Chinese Cultivars of Common Wheat (Triticumaestivum L.).

Common wheat is one of the most important crops in China, which is the largest producer in the world. A set of 230 cultivars was used to identify yield-related loci by association mapping. This set was tested for seven yield-related traits, viz. plant height (PH), spike length (SL), spikelet number per spike (SNPS), kernel number per spike (KNPS), thousand-kernel weight (TKW), kernel weight per spike (KWPS), and sterile spikelet number (SSN) per plant in four environments. A total of 106 simple sequence repeat (SSR) markers distributed on all 21 chromosomes were used to screen the set. Twenty-one and 19 of them were associated with KNPS and TKW, respectively. Association mapping detected 73 significant associations across 50 SSRs, and the phenotypic variation explained (R2) by the associations ranged from 1.54 to 23.93%. The associated loci were distributed on all chromosomes except 4A, 7A, and 7D. Significant and potentially new alleles were present on 8 chromosomes, namely1A, 1D, 2A, 2D, 3D, 4B, 5B, and 6B. Further analysis showed that genetic effects of associated loci were greatly influenced by association panels, and the R2 of crucial loci were lower in modern cultivars than in the mini core collection, probably caused by strong selection in wheat breeding. In order to confirm the results of association analysis, yield-related favorable alleles Xgwm135-1A138, Xgwm337-1D186, Xgwm102-2D144, and Xgwm132-6B128 were evaluated in a double haploid (DH) population derived from Hanxuan10 xLumai14.These favorable alleles that were validated in various populations might be valuable in breeding for high-yield.

Association Analysis of Grain-setting Rates in Apical and Basal Spikelets in Bread Wheat (Triticum aestivum L.)

The rates of grain-setting in apical and basal spikelets in wheat directly affect the kernel number per spike (KNPS). In this study, 220 wheat lines from 18 Chinese provinces and five foreign countries were used as a natural population. Phenotypic analysis showed differences in grain-setting rates between apical and basal spikelets. The broad-sense heritability of grain-setting rate in apical spikelets (18.7–21.0%) was higher than that for basal spikelets (9.4–16.4%). Significant correlations were found between KNPS and grain numbers in apical (R2 = 0.40–0.45, P < 0.01) and basal (R2 = 0.41–0.56, P < 0.01) spikelets. Seventy two of 106 SSR markers were associated with grain setting, 32 for apical spikelets, and 34 for basal spikelets. The SSR loci were located on 17 chromosomes, except 3A, 3D, 4A, and 7D, and explained 3.7–22.9% of the phenotypic variance. Four markers, Xcfa2153-1A202, Xgwm186-5A118, Xgwm156-3B319, and Xgwm537-7B210, showed the largest effects on grain numbers in apical and basal spikelets. High grain numbers in apical and basal spikelets were associated with elite alleles. Ningmai 9, Ning 0569, and Yangmai 18 with high grain-setting rates carried larger numbers of favorable alleles. Comparison of grain numbers in basal and apical spikelets of 35 Yangmai and Ningmai lines indicated that the Ningmai lines had better grain-setting rates (mean 21.4) than the Yangmai lines (16.5).

Development of Near-isogenic Lines with Different Wheat Wx Genes and Their Effects on Amylose Content and Noodle Quality

为明确不同 Wx 基因对小麦直链淀粉含量的影响以及筛选面条品质优异的基因型，以糯小麦品系Caiwx (aabbdd)为3个 Wx 基因隐性突变供体亲本，以扬麦01-2 (AABBDD)为轮回亲本，利用连续回交结合花粉碘染、STS标记和同工酶标记检测方法，创制了8种 Wx 基因纯合基因型的近等基因系，其基因型分别为AABBDD、AABBdd、AAbbDD、AAbbdd、aaBBDD、aaBBdd、aabbDD和aabbdd。利用这些基因型探讨了不同 Wx 基因对直链淀粉含量及面条感官品质的影响。结果表明，各系的直链淀粉含量为0.9%~24.8%，系间差异显著；糯小麦型(aabbdd)直链淀粉含量最低，双缺失型和单缺失型其次，双缺失型中aaBBdd型含量最高，单缺失型中AAbbDD型含量最低，表明 Wx - B1 对直链淀粉的合成作用最大。糯小麦型面条的色泽、表观、软硬度、黏性、韧性得分以及总分显著低于其他类型及轮回亲本扬麦01-2；单缺失型面条的色泽、表观得分、总分显著高于轮回亲本扬麦01-2，其中aaBBDD型面条品质表现突出，与市售优质面条粉“雪花粉”制作的面条得分相当，而其他7种基因型及轮回亲本扬麦01-2的面条评分均显著低于雪花粉。说明可以通过遗传操作 Wx 基因培育优质面条小麦品种。

Genetic Analysis of Fusarium Head Blight Resistance in CIMMYT Bread Wheat Line C615 Using Traditional and Conditional QTL Mapping

Fusarium head blight (FHB) is a destructive wheat disease present throughout the world, and host resistance is an effective and economical strategy used to control FHB. Lack of adequate resistance resource is still a main bottleneck for FHB genetics and wheat breeding research. The synthetic-derived bread wheat line C615, which does not carry the Fhb1 gene, is a promising source of FHB resistance for breeding. A population of 198 recombinant inbred lines (RILs) produced by crossing C615 with the susceptible cultivar Yangmai 13 was evaluated for FHB response using point and spray inoculations. As the disease phenotype is frequently complicated by other agronomic traits, we used both traditional and multivariate conditional QTL mapping approaches to investigate the genetic relationships (at the individual QTL level) between FHB resistance and plant height (PH), spike compactness (SC), and days to flowering (FD). A linkage map was constructed from 3,901 polymorphic SNP markers, which covered 2,549.2 cM. Traditional and conditional QTL mapping analyses found 13 and 22 QTL for FHB, respectively; 10 were identified by both methods. Among these 10, three QTL from C615 were detected in multiple years; these QTL were located on chromosomes 2AL, 2DS, and 2DL. Conditional QTL mapping analysis indicated that, at the QTL level, SC strongly influenced FHB in point inoculation; whereas PH and SC contributed more to FHB than did FD in spray inoculation. The three stable QTL (QFhbs-jaas.2AL, QFhbp-jaas.2DS, and QFhbp-jaas.2DL) for FHB were partly affected by or were independent of the three agronomic traits. The QTL detected in this study improve our understanding of the genetic relationships between FHB response and related traits at the QTL level and provide useful information for marker-assisted selection for the improvement of FHB resistance in breeding.