Molecular genetic studies on processing traits of wheat flour

Advances in the genetic mapping of wheat, the molecular interpretationof flour processing traits and large-scale sequencing of genes expressed inendosperm tissue are currently converging to define the genes thatunder-pin key quality traits. In order to achieve this, accurate definitions ofa phenotype such as dough extensibility are essential and in this paper amolecular/genetic analysis of this trait is presented. Studies carried out onthe small-scale Mixograph have provided the data to indicate that themixing action in this system develops the dough through multipleelongate-rupture-relax cycles of the flour/water mixture. The measurementcan be used to define a variable we refer to as `M-extensibility', a measurevery closely related to the traditional extensibility measurement and mostlikely a sub-component of this `classical' assessment. Analyses based onmolecular genetic maps have shown that both LMW and HMW gluteninloci most likely account for significant variation in M-extensibility. Inaddition, it is evident that genes on chromosome 2 also contribute andwork is in progress to characterize these genes. The possibility will bediscussed that new seed storage protein genes being discovered from theanalysis of 5000 cDNA's from endosperm tissue (8–12 days post anthesis)have a role to play in M-extensibility.     

QTL mapping of yield-related traits in the wheat germplasm 3228

The new wheat germplasm 3228, a putative derivative of tetraploid Agropyron cristatum Z559 and the common wheat Fukuhokomugi, has superior features in yield-related traits, particularly in spike morphological traits, such as large spike and superior grain number. To identify favorable alleles of these traits in 3228, 237 F_2:3 families were developed from the cross 3228/Jing 4839. A genetic map was constructed using 179 polymorphic SSR and EST-SSR markers. A total of 76 QTL controlling spike number per plant (SNP), spike length (SL), spikelet number per spike (SNS), floret number per spikelet (FNS), grain number per spike (GNS) and thousand-grain weight (TGW) were detected on 16 chromosomes. Each QTL explained 1.24–27.01% of the phenotypic variation, and 9 QTL (28.95%) were detected in two or all environments. Additive effects of 45 QTL were positive with 3228 alleles increasing the QTL effects, 31 QTL had negative effects indicating positive contributions from Jing 4839. Three important clusters involving all traits were located on chromosomes 5A, 6A and 4B, and several co-located QTL were also found. Most of the QTL detected on the three chromosome regions could contribute to the use of 3228 in breeding for grain yield improvement.     

QTL mapping of bio-energy related traits in Sorghum

Plant height (PHT), stem and leaf fresh weight (SLFW), juice weight (JW) and sugar content of stem (Brix) are important traits for biofuel production in sweet Sorghum. QTL analysis of PHT, SLFW, JW and Brix was conducted with composite interval mapping using F₂ and F_2:3 populations derived from the cross between grain Sorghum (Shihong137) × sweet Sorghum (L-Tian). Three QTLs controlling PHT were mapped on SBI-01, SBI-07 and SBI-09 under four different environments. These QTLs could explain 10.16 to 45.29% of the phenotypic variance. Two major effect QTLs on SBI-07 and SBI-09 were consistently detected under four environments. Eight QTLs controlling SLFW were mapped across three environments and accounted for 5.49–25.36% of the phenotypic variance. One major QTL on SBI-09 located between marker Sb5-206 and SbAGE03 was observed under three environments. Four QTLs controlling Brix were identified under two environments and accounted for 11.03–17.65% of the phenotypic variance. Six QTLs controlling JW were detected under two environments, and explained 6.63–23.56% of the phenotypic variance. QTLs for JW on SBI-07 and SBI-09 were consistent in two environments showing higher environmental stability. In addition, two chromosome regions on SBI-07 and SBI-09 were identified in our study having major effect on PHT, SFLW and JW. The results would be useful for the genetic improvement of sweet Sorghum to be used for biofuel production.     

QTL mapping for seedling traits under different nitrogen forms in wheat

The uptake and utilization of nitrogen (N) by plants are affected by the different forms of N in the soil. In this study, eight morphological traits at the seedling stage were investigated using a set of recombinant inbred lines (RILs). Three hydroponic culture experiments were conducted using three different NO₃ ^?/NH₄ ⁺ ratios (T1 at 50/50 %, T2 at 100/0 % and T3 at 0/100 %). The investigated traits in T2 and T1 were significantly higher than T3 in all three experiments, indicating that NO₃ ^? promoted or NH₄ ⁺ suppressed the production of biomass. Comparing T1 with T2, NO₃ ^? significantly increased the values of root fresh weight (RFW), total fresh weight (TFW) and root dry weight (RDW) and significantly decreased shoot dry weight (SDW). A total of 147 quantitative trait loci (QTLs) for the eight traits were detected on 18 chromosomes (except 2A, 3D and 4D). Among them, 16 QTLs (QRfw-1A, QRfw-1D, QSfw-1D, QSfw-2B.1, QTfw-1A, QTfw-1D, QRsfw-2B, QRsfw-3B.1, QRdw-1A.1, QRdw-1A.2, QSdw-6B.1, QSdw-7A.1, QTdw-1A.1, QRsdw-1A.1, QRsdw-5A.1 and QRsdw-7A.1) were detected in more than three of the nine treatment–experiments, and most of the 16 QTLs made large contributions of approximately 15 %. Surprisingly, QRsfw-4A.1 and QRsfw-4A.2 explained as much as 47.9 and 55.5 % of the phenotypic variation, respectively. Thirteen important QTL clusters (C1-C13) with more than four QTLs and involving 66 QTLs (44.9 %) were mapped on chromosomes 1A, 1D, 2B, 2D, 4A, 4B, 5B, 5D, 6B, 7A and 7B.     

QTL analysis of main and epistatic effects for flour color traits in durum wheat

The aim of this work was to map quantitative trait loci (QTLs) associated with flour yellow color (Fb*) and yellow pigment content (YPC) in durum wheat (Triticum turgidum L. var. durum). Additionally, QTLs affecting flour redness (Fa*) and brightness (FL*) color parameters were investigated. A population of 93 RILs (UC1113 × Kofa) was evaluated in three locations of Argentina over 2 years. High heritability values (>94%) were obtained for Fb* and YPC, whereas FL* and Fa* showed intermediate to high values. The main QTLs affecting Fb* and YPC overlapped on chromosome arms 4AL (4AL.2), 6AL (6AL.2), 7AS, 7AL, 7BS (7BS.2) and 7BL (7BL.2). The 7BL.1 QTL included the Psy-B1 locus, but one additional linked QTL was detected. A novel minor QTL located on 7AS affected Fb*, with an epistatic effect on YPC. An epistatic interaction occurred between the 7AL and 7BL.2 QTLs. The 4AL.2 QTL showed a strong effect on Fb* and was involved in two digenic epistatic interactions. The 6AL.2 QTL explained most of the variation for Fb* and YPC. The main QTLs affecting FL* and Fa* were located on 2BS and 7BL, respectively. These results confirm the complex inheritance of flour color traits and open the possibility of developing perfect markers to improve pasta quality in Argentinean breeding programs.     

Identification and characterization of quantitative trait loci related to lodging resistance and associated traits in bread wheat

Lodging is a major constraint to increasing yield in many crops, but is of particular importance in the small‐grained cereals. This study investigated the genetic control of lodging and component traits in wheat through the detection of underlying quantitative trait loci (QTL), The analysis was based on the identification of genomic regions which affect various traits related to lodging resistance in a population of 96‐doubled haploid lines of the cross ‘Milan’בCatbird’, mapped using 126‐microsatellite markers. Although major genes related to plant height (Rht genes) were responsible for increasing lodging resistance in this cross, several other traits independent of plant height were shown to be important such as fool and shoot traits, and various components of plant yield. Yield components such as grain number and weight were shown to be an indicator of plant susceptibility to lodging. QTL for lodging and associated traits were found on chromosomes IB, ID. 2B. 2D. 4B, 4D. 6D and 7D. QTL for yield and associated traits were identified on chromosomes IB, ID. 2A. 2B. 2D. 4D and 6A,     

QTL detection of seven spike-related traits and their genetic correlations in wheat using two related RIL populations

Spike-related traits contribute greatly to grain yield in wheat. To localize wheat chromosomes for factors affecting the seven spike-related traits??i.e., the spike length (SL), the basal sterile spikelet number (BSSN), the top sterile spikelet number (TSSN), the sterile spikelet number in total (SSN), the spikelet number per spike (SPN), the fertile spikelet number (FSN) and the spike density (SD)??two F_8:9 recombinant inbred line (RIL) populations were generated. They were derived from crosses between Weimai 8 and Jimai 20 (WJ) and between Weimai 8 and Yannong 19 (WY), comprising 485 and 229 lines, respectively. Combining the two new linkage maps and the phenotypic data collected from the four environments, we conducted quantitative trait locus (QTL) detection for the seven spike-related traits and evaluated their genetic correlations. Up to 190 putative additive QTL for the seven spike-related traits were detected in WJ and WY, distributing across all the 21 wheat chromosomes. Of these, at least nine pairwise QTL were common to the two populations. In addition, 38 QTL showed significance in at least two of the four different environments, and 18 of these were major stable QTL. Thus, they will be of great value for marker assisted selection (MAS) in breeding programs. Though co-located QTL were universal, every trait owned its unique QTL and even two closely related traits were not excluded. The two related populations with a large/moderate population size made the results authentic and accurate. This study will enhance the understanding of the genetic basis of spike-related traits.     

花生种子大小相关性状QTL定位研究进展

花生是我国重要的油料作物和经济作物,目前国内花生的产量远远不能满足消费者的所需,进一步提高花生单产是解决花生生产供不应求的重要途径。花生种子大小相关性状是花生的重要农艺性状,对提高花生单产至关重要。本文综述了植物种子大小的调控途径以及近年来花生分子标记、遗传图谱构建、种子大小相关性状QTL定位研究中取得的进展,探讨了目前花生种子大小相关性状研究中面临的挑战和机遇,对花生产量遗传改良进行了展望。     

QTL mapping for flour and noodle colour components and yellow pigment content in common wheat

Improvement of flour colour is an important breeding objective for various wheat-based end-products. The objectives of this study were to identify quantitative trait loci (QTL) for flour colour components and yellow pigment content (YPC), using 240 recombinant inbred lines (RILs) derived from a cross between the Chinese wheat cultivars PH82-2 and Neixiang 188. Field trials were performed in a Latinized α-lattice design in Anyang and Jiaozuo, Henan Province and Taian, Shandong, in the 2005–2006 and 2006–2007 cropping seasons providing data for six environments. One hundred and eighty-eight polymorphic SSR markers, rye secalin marker Sec1, STS markers YP7A for a phytoene synthase gene (Psy-A1), and four glutenin subunit markers, were used to genotype the population and construct the linkage map for subsequent QTL analysis. Two major QTL were detected for YPC, associated with 1RS (1B.1R translocation) and the Psy-A1 (7A) gene, explaining 31.9% and 33.9% of the phenotypic variances, respectively. 1RS also had large influences on Fa*, Fb*, KJ, NL*and Nb*, and Psy-A1 genes showed large effects on Fa*, Fb*, Kj, Fci, NL*, Na* and Nb*, explaining from 4.5 to 26.1% and 4.3 to 35.9% of the phenotypic variances, respectively. In addition, QTL for flour colour parameters and yellow pigment content were also detected on chromosomes 1A and 4A, accounting for 1.5–4.1% of the phenotypic variance. The genetic effect of the 1B.1R translocation on flour colour parameters was also discussed.     

甘蓝型油菜耐盐和耐旱相关性状的QTL分析

盐胁迫和干旱胁迫是非生物胁迫中影响作物产量的重要因素,检测与耐盐和耐旱相关的QTL,可为抗逆油菜品种的选育提供理论依据。本研究利用德国冬性甘蓝型油菜Express和中国半冬性甘蓝型油菜SWU07为亲本构建的包含261个株系的双单倍体(doubled haploid, DH)群体,分别以1.2%NaCl溶液和20%PEG-6000溶液作为培养液模拟盐胁迫和干旱胁迫,去离子水为对照,对2个亲本和DH群体进行发芽试验。播种后7 d测定幼苗根长、鲜重及发芽率,计算各性状在盐胁迫和干旱胁迫下的相对值,并作为评价耐盐和耐旱的指标。根据已构建的遗传连锁图谱进行QTL定位。盐胁迫下,在3次重复中共检测到与盐胁迫相关的QTL12个,分布在A02、A03、A05、A09、C01和C09染色体上,单个QTL可解释的表型变异为3.61%～10.59%,其中5个QTL在不同的重复中被检测到。干旱胁迫下,共检测到与干旱胁迫相关的QTL 9个,分布在A01、A02、A03、A05、A09、A10和C03染色体上,单个QTL可解释的表型变异为3.94%～12.90%,其中2个QTL在不同的重复中被检测到。此外,在A0...     

Use of recombinant substitution lines for gene mapping and QTL analysis of bread making quality in wheat

Three populations of 41 to 74 homozygous recombinant substitutionlines (RSLs) were used for RFLP mapping and quantitative trait analysis ofthe following parameters: total proteins (%prot), SDS-sedimentationvolume (SDSsed), bread mixing time (Bmxt) and loaf volume (Blvol). TheRSLs were developed from crosses between disomic substitution linesinvolving chromosomes 1A, 1B, and 1D of the high-quality wheat cv.`Cheyenne' (Cnn) substituted into the genetic background of the poorquality cv. `Chinese Spring' (CS). The QTL analysis indicated regions in thethree chromosomes responsible for the differences between CS and thethree disomic substitution lines. The major effect detected on chromosome1A of Cnn was high SDSsed, Bmxt and Blvol associated with the H-M-WGlutenin subunit locus Glu-A1. In addition a QTL was identifieddistally on the long arm of chromosome 1A for Bmxt and Blvol. Ahigh %prot QTL was mapped on the long arm of chromosome 1B of CSand a high Bmxt QTL was mapped on the long arm of chromosome 1B ofCnn. Additionally, this chromosome enhanced SDSsed, Bmxt and Blvol,which were associated with the region of the gliadin and L-M-W Gluteninsubunit locus Gli-B1/Glu-B3. A second more proximal region on theshort arm of chromosome 1B could be involved in loaf volume. QTLanalyses for% prot, showed a strong clear QTL mapped in the centromericregion (XTri/Centromere linkage group) of chromosome 1D with anapparent positive effect brought by CS. For Blvol we revealed two QTLs inopposite phase: one in the Xtri/Centromere region with a positive effect ofCS allele, one in the Glu-D1 region with a positive effect of Cnnallele. This organization `in repulsion' in the parental lines could explain thesmall difference between them for Blvol and the significant transgressionobserved among the RSLs. No clear candidate gene explained the positiveeffect of the centromeric region of CS on %prot and Blvol. Contrary to thecurrent belief that wheat bread-making quality is determined primarily byvariation at the Glu-1 locus, present results showed that the trait isunder a complex control and the Glu-1 loci was only a component ofthe genetic control of the trait.     

Mapping QTL for stay-green and agronomic traits in wheat under diverse water regimes

Wheat (Triticum aestivum L.) yield is directly proportional to physio-morphological traits. A high-density genetic map consisting of 2575 markers was used for mapping QTL controlling stay-green and agronomic traits in wheat grown under four diverse water regimes. A total of 108 additive QTL were identified in target traits. Among them, 28 QTL for chlorophyll content (CC) were detected on 11 chromosomes, 43 for normalized difference vegetation index (NDVI) on all chromosomes except 5B, 5D, and 7D, five for spikes per plant (NSP) on different chromosomes, nine for plant height (PH) on four chromosomes, and 23 for thousand-kernel weight (TKW) on 11 chromosomes. Considering all traits, the phenotypic variation explained (PVE) ranged from 3.61 to 41.62%. A major QTL, QNDVI.cgb-5A.7, for NDVI with a maximum PVE of 20.21%, was located on chromosome 5A. A stable and major PH QTL was observed on chromosome 4D with a PVE close to 40%. Most distances between QTL and corresponding flanking markers were less than 1 cM, and approximately one-third of the QTL coincided with markers. Each of 16 QTL clusters on 10 chromosomes controlled more than one trait and therefore could be regarded as pleiotropic regions in response to different water regimes. Forty-one epistatic QTL were identified for all traits having PVE of 6.00 to 25.07%. Validated QTL closely linked to flanking markers will be beneficial for marker-assisted selection in improving drought-tolerance in wheat.     

QTL detection of seven quality traits in wheat using two related recombinant inbred line populations

Grain protein content (GPC) and gluten quality are the most important factors determining the end-use quality of wheat for pasta-making. Both GPC and gluten quality are considered to be polygenic traits influenced by environmental factors and other agricultural practices. Two related F_8:9 recombinant inbred line (RIL) populations were generated to localise genetic factors controlling seven quality traits: GPC, wet gluten content (WGC), flour whiteness (FW), kernel hardness (KH), water absorption (Abs), dough development time (DDT) and dough stability time (DST). These lines were derived by crossing Weimai 8 and Jimai 20 (WJ) and by crossing Weimai 8 and Yannong 19 (WY). In total, WJ comprised 485 lines, while WY comprised 229 lines. Data on these seven quality traits were collected from each line in five different environments. Up to 85 putative QTLs for the seven traits were detected in WJ and 65 putative QTLs were detected in WY. Of these QTLs, 31 QTLs (36.47%) were detected in at least two trials in WJ, while 24 QTLs (36.92%) were detected in at least two trials in WY. Three QTLs from WJ and 25 from WY accounted for more than 10% of the phenotypic variance. The total 150 QTLs were spread throughout all 21 wheat chromosomes. Of these, at least thirteen pairwise were common to both populations, accounting for 20.00 and 15.29% of the total QTLs in WJ and WY, respectively. A major QTL for GPC, accounting for 53.04% of the phenotypic variation, was detected on chromosome 5A. A major QTL for WGC also shared this interval, explained more than 36% of the phenotypic variation, and was significant in two environments. Though co-located QTLs were common, every trait had its unique control mechanism, even for two closely related traits. Due to the different sizes of the two line populations, we also assessed the effects of population size on the efficiency and precision of QTL detection. In sum, this study will enhance our understanding of the genetic basis of these seven pivotal quality traits and facilitate the breeding of improved wheat varieties.