Kunpu Zhang

Detection of quantitative trait loci for heading date based on the doubled haploid progeny of two elite Chinese wheat cultivars

Quantitative trait loci (QTLs) with epistatic and QTL × environment (QE) interaction for heading date were studied using a doubled haploid (DH) population containing 168 progeny lines derived from a cross between two elite Chinese wheat cultivars Huapei 3 × Yumai 57 (Triticum aestivum L.). A genetic map was constructed based on 305 marker loci, consisting of 283 SSR loci and 22 EST-SSR markers, which covered a total length of 2141.7 cM with an average distance of 7.02 cM between adjacent markers in the genome. QTL analyses were performed using a mixed linear model approach. Two main-effect QTLs and two pairs of digenic epistatic effects were detected for heading date on chromosomes 1B, 2B, 5D, 6D, 7A, and 7D at three different environments in 2005 and 2006 cropping seasons. A highly significant QTL with an F-value 148.96, designated as Qhd5D, was observed within the Xbarc320-Xwmc215 interval on chromosome 5DL, accounting for 53.19% of the phenotypic variance and reducing days-to-heading by 2.77 days. The Qhd5D closely links with a PCR marker Xwmc215 with the genetic distance 2.1 cM, which can be used in molecular marker-assisted selection (MAS) in wheat breeding programs. Moreover, the Qhd5D was located on the similar position of well-characterised vernalization sensitivity gene Vrn-D1. We are also spending more efforts to develop near-isogenic lines to finely map the Qhd5D and clone the gene Vrn-D1 through map-based cloning. The Qhd1B with additive effect on heading date has not been reported in previous linkage mapping studies, which might be a photoperiod-sensitive gene homoeologous to the Ppd-H2 gene on chromosome 1B. No main-effect QTLs for heading date were involved in epistatic effects.

A Genetic Map Constructed Using a Doubled Haploid Population Derived from Two Elite Chinese Common Wheat Varieties

Genetic mapping provides a powerful tool for the analysis of quantitative trait loci (QTLs) at the genomic level. Herein, we report a new genetic linkage map developed from an F(1)-derived doubled haploid (DH) population of 168 lines, which was generated from the cross between two elite Chinese common wheat (Triticum aestivum L.) varieties, Huapei 3 and Yumai 57. The map contained 305 loci, represented by 283 simple sequence repeat (SSR) and 22 expressed sequence tag (EST)-SSR markers, which covered a total length of 2141.7 cM with an average distance of 7.02 cM between adjacent markers on the map. The chromosomal locations and map positions of 22 new SSR markers were determined, and were found to distribute on 14 linkage groups. Twenty SSR loci showed different chromosomal locations from those reported in other maps. Therefore, this map offers new information on the SSR markers of wheat. This genetic map provides new opportunities to detect and map QTLs controlling agronomically important traits. The unique features of this map are discussed.

Conditional QTL Mapping of Sedimentation Volume on Seven Quality Traits in Common Wheat

Abstract To evaluate the possible genetic interrelationships between flour components and the sedimentation volume (SD), a doubled haploid (DH) population comprising 168 lines were used to identify the conditional quantitative trait loci (QTLs) for SD in three environments. Ten additive QTLs and 15 pairs of epistatic QTLs were detected for SD through unconditional and conditional QTL mapping. Three major additive QTLs were detected for SD conditioned on the seven quality traits. Two additive QTLs were found to be independent of these traits. Three additive QTLs were suppressed by three of the seven traits because of non-detection in unconditional mapping. Three pairs of epistatic QTLs were completely affected by the seven traits because of detection in unconditional mapping but no-detection in conditional mapping. Twelve pairs of epistatic QTLs were detected in conditional mapping. Our results indicated that conditional mapping could contribute to a better understanding of the interdependence of different and closely correlated traits at the QTL molecular level, especially some minor QTLs were found. The conditional mapping approach provides new insights that will make it possible to avoid the disadvantages of different traits by breeding through molecular design.

Detection of QTLs with Additive Effects, Epistatic Effects, and QTL × Environment Interactions for Zeleny Sedimentation Value Using a Doubled Haploid Population in Cultivated Wheat

In order to understand the genetic basis for Zeleny sedimentation value (ZSV) of wheat, a doubled haploid (DH) population Huapei 3 × Yumai 57 (Yumai 57 is superior to Huapei 3 for ZSV), and a linkage map consisting of 323 marker loci were used to search QTLs for ZSV. This program was based on mixed linear models and allowed simultaneous mapping of additive effect QTLs, epistatic QTLs, and QTL × environment interactions (QEs). The DH population and the parents were evaluated for ZSV in three field trials. Mapping analysis produced a total of 8 QTLs and 2 QEs for ZSV with a single QTL explaining 0.64-14.39% of phenotypic variations. Four additive QTLs, 4 pairs of epistatic QTLs, and two QEs collectively explained 46.11% of the phenotypic variation (PVE). This study provided a precise location of ZSV gene within the Xwmc 93 and GluD1 interval, which was designated as Qzsv-1D. The information obtained in this study should be useful for manipulating the QTLs for ZSV by marker assisted selection (MAS) in wheat breeding programs.

Genetic Detection of Main Yield Traits in Wheat

Yield and related traits controlled by multiple genes are the most important goal of wheat breeding. In this chapter, QTL mapping was used to detect yield and related traits, such as thousand-grain weight and spike-related traits (spike length, grain number per spike, spikelets per spike, fertile spikelets per spike, sterile spikelets per spike, compactness, and spike weight). The QTL results may facilitate yield improvement through molecular marker-assisted selection.

Genetic Detection of Main Quality Traits in Wheat

Wheat quality is one of the important breeding objectives for wheat breeders, but most of the major genes controlling these traits are unclear. So in this chapter, grain quality traits, nutritional quality traits, flour quality traits, dough quality traits, and processing quality traits were genetically dissected by QTL mapping. Of which, grain quality included grain weight, grain length, diameter, and hardness; nutritional quality presented protein content, beneficial mineral elements, amino acid content and components, and carotenoid pigments; flour quality contained gluten content and index, flour whiteness and color, PPO activity, sedimentation volume, paste viscosity parameters, falling number, starch content and components; for dough quality, farinograph, mixograph and alveograph parameters were involved; and processing quality mainly discussed Chinese noodle and steamed bread quality. Some major QTLs identified for wheat quality traits provided important genetic and molecular information for marker-assisted selection breeding.

Genetic Analysis of Main Physiological and Morphological Traits

Wheat physiological and morphological traits are the most important traits for wheat (Triticum aestivum L.) yield. In this chapter, quantitative trait loci (QTL) mapping for physiological traits including photosynthetic Characters, microdissection characteristics of Stem, heading date and cell membrane permeability of leaf, and for morphological traits of containing root-related traits and leaf-related traits were analyzed in different environments using the DH population, RIL population or natural population. Photosynthesis related traits of wheat were mapped under field and phytotron environments, respectively. Eight additive QTLs and three pairs of epistatic QTLs for chlorophyll were detected in field environments and 17 additive QTLs for conferring photosynthesis and its related traits were identified in phytotron environments. Furthermore, 18 additive loci for dry matter production (DMA) and Fv/Fm were detected. For microdissection characteristics of wheat stem, a total of 12 QTLs controlling anatomical traits of second basal internode on chromosomes 1B, 4D, 5B, 5D, 6A and 7D, and 20 additive QTLs for anatomical traits of the uppermost internode on chromosomes 1A, 1B, 2A, 2D, 3D, 4D, 5D, 6A, 6D and 7D were detected based on DH population. Two additive QTLs on chromosomes 1B and 5D in DH population, five additive QTLs on chromosomes 3B, 5B, 6A, 6B and 7D in RIL population derived from the cross of Nuomai 1 × Gaocheng 8901 and 12 additive QTLs on chromosomes 1A, 1B, 4B, 6A and 6B based on a RIL population derived from the cross of Shannong 01-35 × Gaocheng 9411 were identified for heading date. For cell membrane permeability of leaf, a total of 21 additive QTLs were detected on chromosomes 1B, 2A, 3A, 3B, 5B, 6A, 6B, 6D, 7B and 7D, respectively in three different environments based on a DH population. Seven additive QTLs and 12 pairs of epistatic QTLs for root-related traits were mapped on chromosomes 1A, 1D, 2A, 2B, 2D, 3A, 3B, 5D, 6D and 7D using IF2 population derived from Huapei 3 × Yumai 57.31 additive QTLs and 22 pairs of epistatic QTLs conferring leaf morphology were detected based on a DH population. Finally, by genome-wide association analysis with a natural population derived from the founder parent Aimengniu and its progenies, 61 marker-trait associations (MTAs) involving 46 DArT markers distributed on 14 chromosomes (1B, 1D, 2A, 2B, 2D, 3A, 3B, 4A, 5B, 6A, 6B, 6D, 7A and 7B) for leaf-related traits were identified and the R2 ranges from 0.1 to 16.4 %. These results provide a better understanding of the genetic factors for wheat physiological and morphological traits and facilitate marker-assisted selection strategy in wheat breeding.

Genetic Dissection of Stress-Tolerance Traits in Wheat

Wheat (Triticumaestivum L.) growth and its productivity were always affected by abiotic or biotic stress. Especially, drought, salinity, waterlogging and disease often cause severe reductions in wheat yield. Therefore, it is greatly important to discover resistant genes in wheat. In this chapter, drought resistance, heavy metals resistance (cadmium and chromium stress), pre-harvest sprouting resistance, disease resistance (adult-plant resistance to powdery mildew, fusarium head blight resistance), salt resistance and potassium resistance were genetically dissected by QTL mapping. Some major QTLs identified in this chapter could provide important genetic and molecular information for marker-assisted selection breeding in wheat.

The Concept and Research Progress of Quantitative Traits

Quantitative traits are very common in nature; most agronomical important traits in crops are quantitative. In this chapter, the history and concept of molecular quantitative genetics, tools and methods to study quantitative traits, application of molecular markers, and progress and prospect of QTL mapping were introduced.

Construction of Molecular Genetic Map of Wheat

Molecular genetic map not only provides a powerful tool for the analysis of quantitative trait loci (QTLs) and marker-assisted selection (MAS) at the genomic level, but also lays a foundation for fine mapping and cloning important genes. In this chapter, the unique characteristics and breeding values of the six molecular genetic maps (1 DH, 3 RIL, and 2 natural populations) constructed by SSR, DarT, and SNP markers were illustrated. The parents for each genetic map have some distinguishing features, such as agronomic traits, yield, and/or quality traits. The average distances between adjacent markers in the wheat maps were appropriate (0.44–9.77 cM), thus meeting the recommended requirement for genome-wide QTL scanning. The molecular genetic maps have been used to QTL mapping for some agronomic traits, yield and quality traits, and the good results have been achieved.