Genetic characterisation of dough rheological properties in a wheat doubled haploid population: additive genetic effects and epistatic interactions

Genetic dissection of protein and starch during wheat grain development using QTL mapping and GWAS

Protein, starch, and their components are important for wheat grain yield and end-products, which are affected by wheat grain development. Therefore, QTL mapping and a genome-wide association study (GWAS) of grain protein content (GPC), glutenin macropolymer content (GMP), amylopectin content (GApC), and amylose content (GAsC) were performed on wheat grain development at 7, 14, 21, and 28 days after anthesis (DAA) in two environments using a recombinant inbred line (RIL) population of 256 stable lines and a panel of 205 wheat accessions. A total of 29 unconditional QTLs, 13 conditional QTLs, 99 unconditional marker-trait associations (MTAs), and 14 conditional MTAs significantly associated (p < 10^-4) with four quality traits were found to be distributed on 15 chromosomes, with the phenotypic variation explained (PVE) ranging from 5.35% to 39.86%. Among these genomic variations, three major QTLs [QGPC3B, QGPC2A, and QGPC(S3|S2)3B] and SNP clusters on the 3A and 6B chromosomes were detected for GPC, and the SNP TA005876-0602 was stably expressed during the three periods in the natural population. The QGMP3B locus was detected five times in three developmental stages in two environments with 5.89%-33.62% PVE, and SNP clusters for GMP content were found on the 3A and 3B chromosomes. For GApC, the QGApC3B.1 locus had the highest PVE of 25.69%, and SNP clusters were found on chromosomes 4A, 4B, 5B, 6B, and 7B. Four major QTLs of GAsC were detected at 21 and 28 DAA. Most interestingly, both QTL mapping and GWAS analysis indicated that four chromosomes (3B, 4A, 6B, and 7A) were mainly involved in the development of protein, GMP, amylopectin, and amylose synthesis. Of these, the wPt-5870-wPt-3620 marker interval on chromosome 3B seemed to be most important because it played an important role in the synthesis of GMP and amylopectin before 7 DAA, in the synthesis of protein and GMP from 14 to 21 DAA, and in the development of GApC and GAsC from 21 to 28 DAA. Using the annotation information of IWGSC Chinese Spring RefSeq v1.1 genome assembly, we predicted 28 and 69 candidate genes for major loci from QTL mapping and GWAS, respectively. Most of them have multiple effects on protein and starch synthesis during grain development. These results provide new insights and information for the potential regulatory network between grain protein and starch synthesis.

Allelic variation and genetic diversity of HMW glutenin subunits in Chinese wheat (Triticum aestivum L.) landraces and commercial cultivars

Wheat landraces have abundant genetic variation at the Glu-1 loci, which is desirable germplasms for genetic enhancement of modern wheat varieties, especially for quality improvement. In the current study, we analyzed the allelic variations of the Glu-1 loci of 597 landraces and 926 commercial wheat varieties from the four major wheat-growing regions in China using SDS-PAGE. As results, alleles Null, 7+8, and 2+12 were the dominant HMW-GSs in wheat landraces. Compared to landraces, the commercial varieties contain higher frequencies of high-quality alleles, including 1, 7+9, 14+15 and 5+10. The genetic diversity of the four commercial wheat populations (alleles per locus (A) = 7.33, percent polymorphic loci (P) = 1.00, effective number of alleles per locus (Ae) = 2.347 and expected heterozygosity (He) = 0.563) was significantly higher than that of the landraces population, with the highest genetic diversity found in the Southwestern Winter Wheat Region population. The genetic diversity of HMW-GS is mainly present within the landraces and commercial wheat populations instead of between populations. The landraces were rich in rare subunits or alleles may provide germplasm resources for improving the quality of modern wheat.

Spatial distribution of proteins and metabolites in developing wheat grain and their differential regulatory response during the grain filling process

Grain filling and grain development are essential biological processes in the plant's life cycle, eventually contributing to the final seed yield and quality in all cereal crops. Studies of how the different wheat (Triticum aestivum L.) grain components contribute to the overall development of the seed are very scarce. We performed a proteomics and metabolomics analysis in four different developing components of the wheat grain (seed coat, embryo, endosperm, and cavity fluid) to characterize molecular processes during early and late grain development. In-gel shotgun proteomics analysis at 12, 15, 20, and 26 days after anthesis (DAA) revealed 15 484 identified and quantified proteins, out of which 410 differentially expressed proteins were identified in the seed coat, 815 in the embryo, 372 in the endosperm, and 492 in the cavity fluid. The abundance of selected protein candidates revealed spatially and temporally resolved protein functions associated with development and grain filling. Multiple wheat protein isoforms involved in starch synthesis such as sucrose synthases, starch phosphorylase, granule-bound and soluble starch synthase, pyruvate phosphate dikinase, 14-3-3 proteins as well as sugar precursors undergo a major tissue-dependent change in abundance during wheat grain development suggesting an intimate interplay of starch biosynthesis control. Different isoforms of the protein disulfide isomerase family as well as glutamine levels, both involved in the glutenin macropolymer pattern, showed distinct spatial and temporal abundance, revealing their specific role as indicators of wheat gluten quality. Proteins binned into the functional category of cell growth/division and protein synthesis/degradation were more abundant in the early stages (12 and 15 DAA). At the metabolome level all tissues and especially the cavity fluid showed highly distinct metabolite profiles. The tissue-specific data are integrated with biochemical networks to generate a comprehensive map of molecular processes during grain filling and developmental processes.

Composition of low-molecular-weight glutenin subunits in common wheat (Triticum aestivum L.) and their effects on the rheological properties of dough

The main purpose of this research was the identification and characterization of low-molecular-weight glutenin subunit (LMW-GS) composition in common wheat and the determination of the effect of these proteins on the rheological properties of dough. The use of capillary zone electrophoresis and reverse-phase high-performance liquid chromatography has made it possible to identify four alleles in the Glu-A3 and Glu-D3 loci and seven alleles in the Glu-B3 locus, encoding LMW-GSs in 70 varieties and breeding lines of wheat tested. To determine the technological quality of dough, analyses were performed at the microscale using a TA.XT Plus Texture Analyzer. Wheat varieties containing the Glu-3 loci scheme (Glu-A3b, Glu-A3f at the Glu-A3 locus; Glu-B3a, Glu-B3b, Glu-B3d, Glu-B3h at the Glu-B3 locus; Glu-D3a, Glu-D3c at the Glu-D3 locus) determined the most beneficial quality parameters.

Contribution to Breadmaking Performance of Two Different HMW Glutenin 1Ay Alleles Expressed in Hexaploid Wheat

Two expressed alleles of the 1Ay high-molecular-weight glutenin subunit (HMW-GS), 1Ay21* and 1AyT1, previously introduced in durum and bread wheat, were separately introgressed into the Australian bread wheat (Triticum aestivum L.) cv. Livingston. The developed lines had different allelic compositions compared to that of the parental cultivar (1Ax1), having either 1Ax21+1Ay21* or 1Ax1+1AyT1 at the Glu-A1 locus. Since 1Ax21 and 1Ax1 are known to have the same effects on quality, differences observed between the two sets of the developed lines are attributed to the two introgressed Ay genes. Yield and agronomic performance of the lines were evaluated in the field, and the protein, dough, and baking quality attributes were evaluated by large-scale quality testing. Results demonstrated that the subunit 1Ay21* increased unextractable polymeric protein by up to 14.3% and improved bread loaf volume by up to 9.2%. On the other hand, subunit 1AyT1 increased total grain protein by up to 9% along with dough elasticity. Furthermore, milling extraction was higher, and flour ash was lower in the 1Ay21* lines compared to the lines integrating 1AyT1. Both sets of the 1Ay introgression lines reduced dough-mixing time compared to the recurrent parent Livingston. The results also showed that 1Ay21* had a higher potential to improve the baking quality than 1AyT1 under the Livingston genetic background. Both alleles showed the potential to be utilized in breeding programs to improve the breadmaking quality.

Identification of quantitative trait loci for carbon isotope ratio (δ13C) in a recombinant inbred population of soybean

KEY MESSAGE

QTL analysis identified 16 QTLs, grouped in eight loci on seven soybean chromosomes that were associated with carbon isotope ratio (δ13C) in a biparental recombinant inbred population. Drought is a major limitation to soybean yield, and the frequency of drought stress is likely to increase under future climatic scenarios. Water use efficiency (WUE) is associated with drought tolerance, and carbon isotope ratio (δ13C) is positively correlated with WUE. In this study, 196 F6-derived recombinant inbred lines from a cross of PI 416997 (high WUE) × PI 567201D (low WUE) were evaluated in four environments to identify genomic regions associated with δ13C. There were positive correlations of δ13C values between different environments (0.67 ≤ r ≤ 0.78). Genotype, environment, and genotype × environment interactions had significant effects on δ13C. Narrow sense heritability of δ13C was 90% when estimated across environments. There was a total of 16 QTLs on seven chromosomes with individual QTLs explaining between 2.5 and 29.9% of the phenotypic variation and with additive effects ranging from 0.07 to 0.22‰. These 16 QTLs likely identified eight loci based on their overlapping confidence intervals. Of these eight loci, two loci on chromosome 20 (Gm20) were detected in at least three environments and were considered as stable QTLs. Additive QTLs on Gm20 showed epistatic interactions with 10 QTLs present across nine chromosomes. Five QTLs were identified across environments and showed significant QTL × environment interactions. These findings demonstrate that additive QTLs and QTL × QTL interactions play significant roles in genetic control of the δ13C trait. Markers flanking identified QTLs may facilitate marker-assisted selection to accumulate desirable QTLs to improve WUE and drought tolerance in soybean.

Introgression of an expressed HMW 1Ay glutenin subunit allele into bread wheat cv. Lincoln increases grain protein content and breadmaking quality without yield penalty

An expressed HMW glutenin subunit Glu-Ay showed positive impacts on a range of wheat processing quality and yield traits. The grain protein compositions are significantly optimised for baking, resulting in a better breadmaking quality. The unique breadmaking properties of wheat flour are related to the quality and quantity of high-molecular weight glutenin subunits (HMW-GSs) present in the grain. In the current study, the silent 1Ay HMW-GS allele, present in most bread wheat cultivars, was replaced by the expressed 1Ay21* allele, which was introgressed into Australian bread wheat cultivar Lincoln by a backcrossing and selfing scheme. Stability of gene expression and the effect of the introgressed 1Ay21* subunit on protein composition, agronomic traits, flour functionality, and breadmaking quality were studied using BC4F5 grain grown in glasshouse and field. Field phenotyping and grain quality testing showed that the 1Ay21* gene conferred significant improvements to a range of traits, including an increase in grain protein content by up to 9%, UPP% by up to 24%, bread volume by up to 28%. The glasshouse experiment and one of the field trials showed positive 1Ay21* effects on yield, while one field trial showed one significant effects. This indicates that expression of the 1Ay21* gene has the potential of simultaneously increasing protein content and grain yield under certain environment. The qualitative improvements of the grain also led to a reduction of the energy required during the baking process in addition to the significant positive effects on bread quality.

Allelic variation of low molecular weight glutenin subunits composition and the revealed genetic diversity in durum wheat (Triticum turgidum L. ssp. durum (Desf))

Low molecular weight glutenin subunits (LMW-GS) play an important role in determining the bread-making characteristics of dough in the end-use quality of wheat. In this study, A total of 149 worldwide-originated durum wheat were used to analyze the composition of LMW-GS using MALDI-TOF-MS. Based on the allelic variation of glutenin subunits, the genetic diversity was evaluated for the 149 durum wheat. Five types of alleles were identified at the Glu-A3 locus with Glu-A3e, Glu-A3a/c, Glu-A3f, Glu-A3d and Glu-A3b accounting for 43.0%, 16.1%, 12.8%, 10.1% and 7.4 % of the accessions, respectively. Five types of alleles were identified at the Glu-B3 locus: Glu-B3d (60.4%), Glu-B3b (6.0%), Glu-B3c (6.0%), Glu-B3h (2.7%) and Glu-B3f (0.7%). Two novel alleles encoding abnormal subunits 40500 Da and 41260 Da were identified at the Glu-A3 and Glu-B3 loci, respectively. Further studies are needed to match these novel alleles to previously discovered novel alleles. Moreover, the genetic diversity analysis indicated that great genetic variation existed in durum wheat among encoding loci of glutenin subunits, released periods of varieties and different geographical origins. The results provide more important information of potential germplasm for the improvement of durum wheat and common wheat.

Characterization of novel LMW glutenin subunit genes at the Glu-M3 locus from Aegilops comosa

We report the characterization of seven novel low-molecular-weight glutenin subunit (LMW-GS) genes from Aegilops comosa (2n = 2x = 14, MM). We found that all seven LMW-GS genes possessed the same primary structure shared by other known LMW-GSs. Three genes (comosa-M1, comosa-M2, and comosa-M3) encode LMW-m-type subunits, two (comosa-I1 and comosa-I2) encode LWM-i-type subunits, and two (comosa-L1 and comosa-L2) encode LWM-l-type subunits. The comosa-M1 possessed seven cysteine residues, which resulted from a single-nucleotide polymorphism (SNP) of the G-A transition in the fifth position of the N-terminal sequence. Two l-type subunits, comosa-L1 and comosa-L2, contained nine cysteine residues with an extra cysteine residue located in the signal peptide and repetitive domain. In addition, a long insertion of 13 residues (LGQQPQ8/LVQQPQ8) was present in the end of the C-terminal II. Phylogenetic analysis implied that the comosa-L2 may be the intermediate type during the evolution of LMW-l and LMW-i-type genes. Our results demonstrated that the novel LMW-GSs, such as comosa-M1, comosa-L1, and comosa-L2, may have positive effects on dough properties.

Interactions between Glu-1 and Glu-3 loci and associations of selected molecular markers with quality traits in winter wheat (Triticum aestivum L.) DH lines

The quality of wheat depends on a large complex of genes and environmental factors. The objective of this study was to identify quantitative trait loci controlling technological quality traits and their stability across environments, and to assess the impact of interaction between alleles at loci Glu-1 and Glu-3 on grain quality. DH lines were evaluated in field experiments over a period of 4 years, and genotyped using simple sequence repeat markers. Lines were analysed for grain yield (GY), thousand grain weight (TGW), protein content (PC), starch content (SC), wet gluten content (WG), Zeleny sedimentation value (ZS), alveograph parameter W (APW), hectolitre weight (HW), and grain hardness (GH). A number of QTLs for these traits were identified in all chromosome groups. The Glu-D1 locus influenced TGW, PC, SC, WG, ZS, APW, GH, while locus Glu-B1 affected only PC, ZS, and WG. Most important marker-trait associations were found on chromosomes 1D and 5D. Significant effects of interaction between Glu-1 and Glu-3 loci on technological properties were recorded, and in all types of this interaction positive effects of Glu-D1 locus on grain quality were observed, whereas effects of Glu-B1 locus depended on alleles at Glu-3 loci. Effects of Glu-A3 and Glu-D3 loci per se were not significant, while their interaction with alleles present at other loci encoding HMW and LMW were important. These results indicate that selection of wheat genotypes with predicted good bread-making properties should be based on the allelic composition both in Glu-1 and Glu-3 loci, and confirm the predominant effect of Glu-D1d allele on technological properties of wheat grains.

Allelic variation of LMW-GS composition in Chinese wheat landraces of the Yangtze-River region detected by MALDI-TOF-MS

Low molecular weight glutenin subunits are important components of wheat storage proteins, which play an important role in determining end-use quality of common wheat. A newly established matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) procedure was used to analyze 478 landraces of bread wheat collected from the Yangtze-River region in China. Results indicated that 17 alleles at three loci: Glu-A3, Glu-B3 and Glu-D3 were identified, resulting in 87 different allele combinations. Of the 17 alleles detected at all the Glu-3 loci, five belonged to Glu-A3, seven to Glu-B3 and five to Glu-D3 locus. MALDI-TOF-MS indicated Glu-A3a/c was present in 72.8%, Glu-A3b in 8.4%, Glu-A3d in 8.4%, Glu-A3f in 5.2% and Glu-A3e in 3.6% lines. Seven types of alleles were identified at the Glu-B3 locus: Glu-B3d/i (25.5%), Glu-B3b (21.3%), Glu-B3c (16.9%), Glu-B3h (13.8%), Glu-B3f (8.4%), Glu-B3a (8.2%), and Glu-B3g (5.2%). Five types of Glu-D3 alleles were detected: Glu-D3a (58.4%), Glu-D3c (22.6%), Glu-D3d (15.5%), Glu-D3b (3.3%) and Glu-D3f (0.2%). Four new alleles that showed abnormal MALDI-TOF spectrum patterns were identified at the Glu-A3 and Glu-B3 loci. A detailed study is needed to further characterize these alleles and their potential usage for wheat improvement.

Dynamic metabolome profiling reveals significant metabolic changes during grain development of bread wheat (Triticum aestivum L.)

BACKGROUND

Metabolites in wheat grains greatly influence nutritional values. Wheat provides proteins, minerals, B-group vitamins and dietary fiber to humans. These metabolites are important to human health. However, the metabolome of the grain during the development of bread wheat has not been studied so far. In this work the first dynamic metabolome of the developing grain of the elite Chinese bread wheat cultivar Zhongmai 175 was analyzed, using non-targeted gas chromatography/mass spectrometry (GC/MS) for metabolite profiling.

RESULTS

In total, 74 metabolites were identified over the grain developmental stages. Metabolite-metabolite correlation analysis revealed that the metabolism of amino acids, carbohydrates, organic acids, amines and lipids was interrelated. An integrated metabolic map revealed a distinct regulatory profile. The results provide information that can be used by metabolic engineers and molecular breeders to improve wheat grain quality.

CONCLUSION

The present metabolome approach identified dynamic changes in metabolite levels, and correlations among such levels, in developing seeds. The comprehensive metabolic map may be useful when breeding programs seek to improve grain quality. The work highlights the utility of GC/MS-based metabolomics, in conjunction with univariate and multivariate data analysis, when it is sought to understand metabolic changes in developing seeds. © 2015 Society of Chemical Industry.

Allelic variations of α-gliadin genes from species of Aegilops section Sitopsis and insights into evolution of α-gliadin multigene family among Triticum and Aegilops

The α-gliadins account for 15-30 % of the total storage protein in wheat endosperm and play important roles in the dough extensibility and nutritional quality. On the other side, they act as a main source of toxic peptides triggering celiac disease. In this study, 37 α-gliadins were isolated from three species of Aegilops section Sitopsis. Sequence similarity and phylogenetic analyses revealed novel allelic variation at Gli-2 loci of species of Sitopsis and regular organization of motifs in their repetitive domain. Based on the comprehensive analyses of a large number of known sequences of bread wheat and its diploid genome progenitors, the distributions of four T cell epitopes and length variations of two polyglutamine domains are analyzed. Additionally, according to the organization of repeat motifs, we classified the α-gliadins of Triticum and Aegilops into eight types. Their most recent common ancestor and putative divergence patterns were further considered. This study provides new insights into the allelic variations of α-gliadins in Aegilops section Sitopsis, as well as evolution of α-gliadin multigene family among Triticum and Aegilops species.

Comprehensive Identification and Bread-Making Quality Evaluation of Common Wheat Somatic Variation Line AS208 on Glutenin Composition

High molecular weight glutenin subunits (HMW-GSs) are important seed storage proteins in wheat (Triticum aestivum) that determine wheat dough elasticity and processing quality. Clarification of the defined effectiveness of HMW-GSs is very important to breeding efforts aimed at improving wheat quality. To date, there have no report on the expression silencing and quality effects of 1Bx20 and 1By20 at the Glu-B1 locus in wheat. A wheat somatic variation line, AS208, in which both 1Bx20 and 1By20 at Glu-B1 locus were silenced, was developed recently in our laboratory. Evaluation of agronomic traits and seed storage proteins by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and reversed-phase high performance liquid chromatography (RP-HPLC) indicated that AS208 was highly similar to its parental cultivar Lunxuan987 (LX987), with the exception that the composition and expression of HMW-GSs was altered. The 1Bx20 and 1By20 in AS208 were further identified to be missing by polymerase chain reaction (PCR) and quantitative real-time RT-PCR (qRT-PCR) assays. Based on the PCR results for HMW-GS genes and their promoters in AS208 compared with LX987, 1Bx20 and 1By20 were speculated to be deleted in AS208 during in vitro culture. Quality analysis of this line with Mixograph, Farinograph, and Extensograph instruments, as well as analysis of bread-making quality traits, demonstrated that the lack of the genes encoding 1Bx20 and 1By20 caused various negative effects on dough processing and bread-making quality traits, including falling number, dough stability time, mixing tolerance index, crude protein values, wet gluten content, bread size, and internal cell structure. AS208 can potentially be used in the functional dissection of other HMW-GSs as a plant material with desirable genetic background, and in biscuit making industry as a high-quality weak gluten wheat source.

Identification of Low Molecular Weight Glutenin Alleles by Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF-MS) in Common Wheat (Triticum aestivum L.)

Low molecular weight glutenin subunits (LMW-GS) play an important role in determining dough properties and breadmaking quality. However, resolution of the currently used methodologies for analyzing LMW-GS is rather low which prevents an efficient use of genetic variations associated with these alleles in wheat breeding. The aim of the current study is to evaluate and develop a rapid, simple, and accurate method to differentiate LMW-GS alleles using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. A set of standard single LMW-GS allele lines as well as a suite of well documented wheat cultivars were collected from France, CIMMYT, and Canada. Method development and optimization were focused on protein extraction procedures and MALDI-TOF instrument settings to generate reproducible diagnostic spectrum peak profiles for each of the known wheat LMW-GS allele. Results revealed a total of 48 unique allele combinations among the studied genotypes. Characteristic MALDI-TOF peak patterns were obtained for 17 common LMW-GS alleles, including 5 (b, a or c, d, e, f), 7 (a, b, c, d or i, f, g, h) and 5 (a, b, c, d, f) patterns or alleles for the Glu-A3, Glu-B3, and Glu-D3 loci, respectively. In addition, some reproducible MALDI-TOF peak patterns were also obtained that did not match with any known alleles. The results demonstrated a high resolution and throughput nature of MALDI-TOF technology in analyzing LMW-GS alleles, which is suitable for application in wheat breeding programs in processing a large number of wheat lines with high accuracy in limited time. It also suggested that the variation of LMW-GS alleles is more abundant than what has been defined by the current nomenclature system that is mainly based on SDS-PAGE system. The MALDI-TOF technology is useful to differentiate these variations. An international joint effort may be needed to assign allele symbols to these newly identified alleles and determine their effects on end-product quality attributes.

An improved MALDI-TOF mass spectrometry procedure and a novel DNA marker for identifying over-expressed Bx7 glutenin protein subunit in wheat

Wheat bread-making quality is mainly determined by glutenin proteins in the grain, which exist in a wide range of variable alleles with differential influence on processing attributes. A recently identified allele, Bx7 over-expression (Bx7(oe) ), has been showing highly significant positive effects on wheat dough strength over the normally expressed Bx7 allele. SDS-PAGE and normal RP-HPLC procedures failed to separate the two alleles. In the current study, an extensively optimised MALDI-TOF based procedure and a refined DNA based marker for efficiently differentiating Bx7(oe) from normal Bx7 allele were established. Results indicated that the MALDI-TOF procedure is cost effective, high throughput, and proven reliable, while the refined PCR marker only amplifies Bx7(oe) allele, a clear advantage over the previously developed codominant marker.

The trafficking pathway of a wheat storage protein in transgenic rice endosperm

BACKGROUND AND AIMS

The trafficking of proteins in the endoplasmic reticulum (ER) of plant cells is a topic of considerable interest since this organelle serves as an entry point for proteins destined for other organelles, as well as for the ER itself. In the current work, transgenic rice was used to study the pattern and pathway of deposition of the wheat high molecular weight (HMW) glutenin sub-unit (GS) 1Dx5 within the rice endosperm using specific antibodies to determine whether it is deposited in the same or different protein bodies from the rice storage proteins, and whether it is located in the same or separate phases within these.

METHODS

The protein distribution and the expression pattern of HMW sub-unit 1Dx5 in transgenic rice endosperm at different stages of development were determined using light and electron microscopy after labelling with antibodies.

KEY RESULTS

The use of HMW-GS-specific antibodies showed that sub-unit 1Dx5 was expressed mainly in the sub-aleurone cells of the endosperm and that it was deposited in both types of protein body present in the rice endosperm: derived from the ER and containing prolamins, and derived from the vacuole and containing glutelins. In addition, new types of protein bodies were also formed within the endosperm cells.

CONCLUSIONS

The results suggest that the HMW 1Dx5 protein could be trafficked by either the ER or vacuolar pathway, possibly depending on the stage of development, and that its accumulation in the rice endosperm could compromise the structural integrity of protein bodies and their segregation into two distinct populations in the mature endosperm.

Identification of QTLs for seed and pod traits in soybean and analysis for additive effects and epistatic effects of QTLs among multiple environments

Soybean seed and pod traits are important yield components. Selection for high yield style in seed and pod along with agronomic traits is a goal of many soybean breeders. The intention of this study was to identify quantitative trait loci (QTL) underlying seed and pod traits in soybean among eleven environments in China. 147 recombinant inbred lines were advanced through single-seed-descent method. The population was derived from a cross between Charleston (an American high yield soybean cultivar) and DongNong594 (a Chinese high yield soybean cultivar). A total of 157 polymorphic simple sequence repeat markers were used to construct a genetic linkage map. The phenotypic data of seed and pod traits [number of one-seed pod, number of two-seed pod, number of three-seed pod, number of four-seed pod, number of (two plus three)-seed pod, number of (three plus four)-seed pod, seed weight per plant, number of pod per plant] were recorded in eleven environments. In the analysis of single environment, fourteen main effect QTLs were identified. In the conjoint analysis of multiple environments, twenty-four additive QTLs were identified, and additive QTLs by environments interactions (AE) were evaluated and analyzed at the same time among eleven environments; twenty-three pairs of epistatic QTLs were identified, and epistasis (additive by additive) by environments interactions (AAE) were also analyzed and evaluated among eleven environments. Comparing the results of identification between single environment mapping and multiple environments conjoint mapping, three main effect QTLs with positive additive values and another three main effect QTLs with negative additive values, had no interactions with all environments, supported that these QTLs could be used in molecular assistant breeding in the future. These different effect QTLs could supply a good foundation to the gene clone and molecular asisstant breeding of soybean seed and pod traits.

Effect of Glu-B3 allelic variation on sodium dodecyl sulfate sedimentation volume in common wheat (Triticum aestivum L.)

Sodium dodecyl sulfate (SDS) sedimentation volume has long been used to characterize wheat flours and meals with the aim of predicting processing and end-product qualities. In order to survey the influence of low-molecular-weight glutenin subunits (LMW-GSs) at Glu-B3 locus on wheat SDS sedimentation volume, a total of 283 wheat (Triticum aestivum L.) varieties including landraces and improved and introduced cultivars were analyzed using 10 allele-specific PCR markers at the Glu-B3 locus. The highest allele frequency observed in the tested varieties was Glu-B3i with 21.9% in all varieties, 21.1% in landraces, 25.5% in improved cultivars, and 12% in introduced cultivars. Glu-B3 locus represented 8.6% of the variance in wheat SDS sedimentation volume, and Glu-B3b, Glu-B3g, and Glu-B3h significantly heightened the SDS sedimentation volume, but Glu-B3a, Glu-B3c, and Glu-B3j significantly lowered the SDS sedimentation volume. For the bread-making quality, the most desirable alleles Glu-B3b and Glu-B3g become more and more popular and the least desirable alleles Glu-B3a and Glu-B3c got less and less in modern improved cultivars, suggesting that wheat grain quality in China has been significantly improved through breeding effort.

Molecular mechanisms of HMW glutenin subunits from 1S(l) genome of Aegilops longissima positively affecting wheat breadmaking quality

A wheat cultivar “Chinese Spring” chromosome substitution line CS-1S^l(1B), in which the 1B chromosome was substituted by 1S^l from Aegilops longissima, was developed and found to possess superior dough and breadmaking quality. The molecular mechanism of its super quality conformation is studied in the aspects of high molecular glutenin genes, protein accumulation patterns, glutenin polymeric proteins, protein bodies, starch granules, and protein disulfide isomerase (PDI) and PDI-like protein expressions. Results showed that the introduced HMW-GS 1S^l×2.3* and 1S^ly16* in the substitution line possesses long repetitive domain, making both be larger than any known x- and y-type subunits from B genome. The introduced subunit genes were also found to have a higher level of mRNA expressions during grain development, resulting in more HMW-GS accumulation in the mature grains. A higher abundance of PDI and PDI-like proteins was observed which possess a known function of assisting disulfide bond formation. Larger HMW-GS deposited in protein bodies were also found in the substitution line. The CS substitution line is expected to be highly valuable in wheat quality improvement since the novel HMW-GS are located on chromosome 1S^l, making it possible to combine with the known superior D×5+Dy10 subunits encoded by Glu-D1 for developing high quality bread wheat.

Composition and functional analysis of low-molecular-weight glutenin alleles with Aroona near-isogenic lines of bread wheat

BACKGROUND

Low-molecular-weight glutenin subunits (LMW-GS) strongly influence the bread-making quality of bread wheat. These proteins are encoded by a multi-gene family located at the Glu-A3, Glu-B3 and Glu-D3 loci on the short arms of homoeologous group 1 chromosomes, and show high allelic variation. To characterize the genetic and protein compositions of LMW-GS alleles, we investigated 16 Aroona near-isogenic lines (NILs) using SDS-PAGE, 2D-PAGE and the LMW-GS gene marker system. Moreover, the composition of glutenin macro-polymers, dough properties and pan bread quality parameters were determined for functional analysis of LMW-GS alleles in the NILs.

RESULTS

Using the LMW-GS gene marker system, 14-20 LMW-GS genes were identified in individual NILs. At the Glu-A3 locus, two m-type and 2-4 i-type genes were identified and their allelic variants showed high polymorphisms in length and nucleotide sequences. The Glu-A3d allele possessed three active genes, the highest number among Glu-A3 alleles. At the Glu-B3 locus, 2-3 m-type and 1-3 s-type genes were identified from individual NILs. Based on the different compositions of s-type genes, Glu-B3 alleles were divided into two groups, one containing Glu-B3a, B3b, B3f and B3g, and the other comprising Glu-B3c, B3d, B3h and B3i. Eight conserved genes were identified among Glu-D3 alleles, except for Glu-D3f. The protein products of the unique active genes in each NIL were detected using protein electrophoresis. Among Glu-3 alleles, the Glu-A3e genotype without i-type LMW-GS performed worst in almost all quality properties. Glu-B3b, B3g and B3i showed better quality parameters than the other Glu-B3 alleles, whereas the Glu-B3c allele containing s-type genes with low expression levels had an inferior effect on bread-making quality. Due to the conserved genes at Glu-D3 locus, Glu-D3 alleles showed no significant differences in effects on all quality parameters.

CONCLUSIONS

This work provided new insights into the composition and function of 18 LMW-GS alleles in bread wheat. The variation of i-type genes mainly contributed to the high diversity of Glu-A3 alleles, and the differences among Glu-B3 alleles were mainly derived from the high polymorphism of s-type genes. Among LMW-GS alleles, Glu-A3e and Glu-B3c represented inferior alleles for bread-making quality, whereas Glu-A3d, Glu-B3b, Glu-B3g and Glu-B3i were correlated with superior bread-making quality. Glu-D3 alleles played minor roles in determining quality variation in bread wheat. Thus, LMW-GS alleles not only affect dough extensibility but greatly contribute to the dough resistance, glutenin macro-polymers and bread quality.

A comparison of two methods to estimate additive-by-additive interaction of QTL effects by a simulation study

Additive-by-additive epistasis plays an important role in the genetic architecture of complex traits. The parameter connected with the additive-by-additive interaction can influence decisions concerning usefulness of the breeding material for the generation of new genotypes with characteristics improved over the parental forms. This study presents comparisons of two estimation methods of additive-by-additive interactions of QTL effects by the Monte Carlo simulation study. In the first method we assume that we observed only the plant phenotype, while in the second method we have additional information from the molecular marker observations. The obtained results show that the additive-by-additive interaction effect calculated on the basis of the marker observations is always smaller than the total additive-by-additive interaction effect obtained from phenotypic observations only. The lack of influence of the distance between markers and the number of linkage groups on the estimation of effects of additive-by-additive epistasis interaction genes by the two methods shows that both these methods may be used for different genetic maps and for different plant species.

Comparative proteome analysis of glutenin synthesis and accumulation in developing grains between superior and poor quality bread wheat cultivars

BACKGROUND

Wheat glutenins are the major determinants of wheat quality. In this study, grains at the development stage from three wheat cultivars (Jimai 20, Jin 411 and Zhoumai 16) with different bread-making quality were harvested based on thermal times from 150 °C(d) to 750 °C(d) , and were used to investigate glutenin accumulation patterns and their relationships with wheat quality.

RESULTS

High and low molecular weight glutenin subunits (HMW-GSs and LMW-GSs) were synthesised concurrently. No obvious correlations between HMW/LMW glutenin ratios and dough property were observed. Accumulation levels of HMW-GSs and LMW-GSs as well as 1Bx13 + 1By16 and 1Dx4 + 1Dy12 subunits were higher in superior gluten quality cultivar Jimain 20 than in poor quality cultivar Jing 411 and Zhoumai 16. According to the results of two-dimensional gel electrophoresis, six types of accumulation patterns in LMW-GSs were identified and classified. The possible relationships between individual LMW-GSs and gluten quality were established.

CONCLUSION

The high accumulation level of HMW-GSs and LMW-GSs as well as 1Bx13 + 1By16 and 1Dx4 + 1Dy12 subunits contributed to the superior gluten quality of Jimai 20. Two highly expressed and 16 specifically expressed LMW glutenin subunits in Jimain 20 had positive effects on dough quality, while 17 specifically expressed subunits in Zhoumai 16 and Jing 411 appeared to have negative effects on gluten quality.

Phylogenetic relationship of a new class of LMW-GS genes in the M genome of Aegilops comosa

A new class of low molecular weight glutenin subunit (LMW-GS) genes was isolated and characterized from Aegilops comosa (2n = 2x = 14, MM). Although their DNA structure displayed high similarity to LMW-i type genes, there are some key differences. The deduced amino acid sequences of their mature proteins showed that the first amino acid residue of each gene was leucine and therefore they were designated as LMW-l type subunits. An extra cysteine residue was present in the signal peptide and the first cysteine residue of mature proteins located at the end of repetitive domain. Additionally, a long insertion of 10-22 residues (LGQQPQ(5-17)) occurred in the end of the C-terminal II. Comparative analysis demonstrated that LMW-l type glutenin genes possessed a great number of single-nucleotide polymorphisms and insertions/deletions. A new classification system was proposed according to the gene structure and phylogenetic analysis. In this new system, LMW-GS is classified into two major classes, LMW-M and LMW-I, with each including two subclasses. The former included LMW-m and LMW-s types while the latter contained LMW-l and LMW-i types. Analysis of their evolutionary origin showed that the LMW-l genes diverged from the group 2 of LMW-m type genes at about 12-14 million years ago (MYA) while LMW-i type evolved from LMW-l type at approximately 8-12 MYA. The LMW-s type was a variant form of group 1 of LMW-m type and their divergence occurred about 4-6 MYA. In addition to homologous recombination, non-homologous illegitimate recombination could be an important molecular mechanism for the origin and evolution of LMW-GS gene family. The secondary structure prediction suggested that the novel LMW-l type subunits, such as AcLMW-L1 and AcLMW-L2, may have positive effects on dough properties.

QTL mapping for quantities of protein fractions in bread wheat (Triticum aestivum L.)

One of the key targets of breeding programs in bread wheat is to improve the end-use quality. The relationships between quantities of protein fractions and dough rheological characters have been well established, but there is little information on the genetic control of quantities of protein fractions. Two hundred and forty F(6) recombinant inbred lines derived from a cross between two Chinese wheat cultivars, PH82-2 and Neixiang 188, were sown at Jiaozuo in Henan province in the 2005-2006 and 2006-2007 cropping seasons, and inclusive composite interval mapping was used to dissect main effect quantitative trait loci (M-QTLs) and digenic epistatic QTLs (E-QTLs) for quantities of protein fractions. A total of 55 M-QTLs and 77 pairs of E-QTLs affecting the quantities of protein fractions including GLU-A1 (QGA1), GLU-B1 (QGB1), GLU-D1 (QGD1), HMW-GS (QHMW), GLU-A3 (QGA3), GLU-B3 (QGB3), LMW-GS (QLMW), glutenin (QGLU) and the ratio of the quantity of glutenin to those of gliadin were identified, with M-QTLs contributing 39.3-95.6% of the phenotypic variance explained (PVE), and E-QTLs accounting for 1.4-33.5% of the PVE. Among the M-QTLs, 33 were consistent in two seasons and in the mean value of two seasons with similar effects in both magnitude and direction, including major genes on HMW and LMW glutenin loci linked to Sec1 and Glu-B1c, Glu-D1d, Glu-A3a, and grain hardness locus Ha, indicating that these genes were the most important determinants of gluten strength, and they might have significant effects on dough properties not only through effects on allelic composition, but also by influencing quantities of protein fractions. The effects of E-QTLs were more influenced by environments, compared with those of M-QTLs, with only two pairs of E-QTLs consistent in two seasons and in the mean value of two seasons. The M-QTLs were detected in 12 marker intervals, all of which involved E-QTLs on quantities of protein fractions, whereas only 40 of 77 pairs of E-QTLs involved intervals in which M-QTLs were detected. The results indicated that besides main effects, epistatic effects were also important factors in determining quantities of protein fractions in wheat.

Association mapping for quality traits in soft winter wheat

Improvement of end-use quality in bread wheat (Triticum aestivum L.) depends on a thorough understanding of the genetic basis of important quality traits. The main goal of our study was to investigate the genetic basis of 1,000-kernel weight, protein content, sedimentation volume, test weight, and starch concentration using an association mapping approach. We fingerprinted 207 diverse European elite soft winter wheat lines with 115 SSR markers and evaluated the genotypes in multi-environment trials. The principal coordinate analysis revealed absence of a clear population but presence of a family structure. Therefore, we used linear mixed models and marker-based kinship matrices to correct for family structure. In genome-wide scans, we detected main effect QTL for all five traits. In contrast, epistatic QTL were only observed for sedimentation volume and test weight explaining a small proportion of the genotypic variation. Consequently, our findings suggested that integrating epistasis in marker-assisted breeding will not lead to substantially increased selection gain for quality traits in soft winter wheat.

Molecular characterization of the celiac disease epitope domains in α-gliadin genes in Aegilops tauschii and hexaploid wheats (Triticum aestivum L.)

Nineteen novel full-ORF α-gliadin genes and 32 pseudogenes containing at least one stop codon were cloned and sequenced from three Aegilops tauschii accessions (T15, T43 and T26) and two bread wheat cultivars (Gaocheng 8901 and Zhongyou 9507). Analysis of three typical α-gliadin genes (Gli-At4, Gli-G1 and Gli-Z4) revealed some InDels and a considerable number of SNPs among them. Most of the pseudogenes were resulted from C to T change, leading to the generation of TAG or TAA in-frame stop codon. The putative proteins of both Gli-At3 and Gli-Z7 genes contained an extra cysteine residue in the unique domain II. Analysis of toxic epitodes among 19 deduced α-gliadins demonstrated that 14 of these contained 1-5 T cell stimulatory toxic epitopes while the other 5 did not contain any toxic epitopes. The glutamine residues in two specific ployglutamine domains ranged from 7 to 27, indicating a high variation in length. According to the numbers of 4 T cell stimulatory toxic epitopes and glutamine residues in the two ployglutamine domains among the 19 α-gliadin genes, 2 were assigned to chromosome 6A, 5 to chromosome 6B and 12 to chromosome 6D. These results were consistent with those from wheat cv. Chinese Spring nulli-tetrasomic and phylogenetic analysis. Secondary structure prediction showed that all α-gliadins had high content of β-strands and most of the α-helixes and β-strands were present in two unique domains. Phylogenetic analysis demonstrated that α-gliadin genes had a high homology with γ-gliadin, B-hordein, and LMW-GS genes and they diverged at approximate 39 MYA. Finally, the five α-gliadin genes were successfully expressed in E. coli, and their expression amount reached to the maximum after 4 h induced by IPTG, indicating that the α-gliadin genes can express in a high level under the control of T(7) promoter.

New insights into the organization, recombination, expression and functional mechanism of low molecular weight glutenin subunit genes in bread wheat

The bread-making quality of wheat is strongly influenced by multiple low molecular weight glutenin subunit (LMW-GS) proteins expressed in the seeds. However, the organization, recombination and expression of LMW-GS genes and their functional mechanism in bread-making are not well understood. Here we report a systematic molecular analysis of LMW-GS genes located at the orthologous Glu-3 loci (Glu-A3, B3 and D3) of bread wheat using complementary approaches (genome wide characterization of gene members, expression profiling, proteomic analysis). Fourteen unique LMW-GS genes were identified for Xiaoyan 54 (with superior bread-making quality). Molecular mapping and recombination analyses revealed that the three Glu-3 loci of Xiaoyan 54 harbored dissimilar numbers of LMW-GS genes and covered different genetic distances. The number of expressed LMW-GS in the seeds was higher in Xiaoyan 54 than in Jing 411 (with relatively poor bread-making quality). This correlated with the finding of higher numbers of active LMW-GS genes at the A3 and D3 loci in Xiaoyan 54. Association analysis using recombinant inbred lines suggested that positive interactions, conferred by genetic combinations of the Glu-3 locus alleles with more numerous active LMW-GS genes, were generally important for the recombinant progenies to attain high Zeleny sedimentation value (ZSV), an important indicator of bread-making quality. A higher number of active LMW-GS genes tended to lead to a more elevated ZSV, although this tendency was influenced by genetic background. This work provides substantial new insights into the genomic organization and expression of LMW-GS genes, and molecular genetic evidence suggesting that these genes contribute quantitatively to bread-making quality in hexaploid wheat. Our analysis also indicates that selection for high numbers of active LMW-GS genes can be used for improvement of bread-making quality in wheat breeding.

Gene networks in the synthesis and deposition of protein polymers during grain development of wheat

As the amino acid storing organelle, the protein bodies provide nutrients for embryo development, seed germination and early seedling growth through storage proteolysis in cereal plants, such as wheat and rice. In protein bodies, the monomeric and polymeric prolamins, i.e. gliadins and glutenins, form gluten and play a key role in determining dough functionality and end-product quality of wheat. The formation of intra- and intermolecular bonds, including disulphide and tyrosine bonds, in and between prolamins confers cohesivity, viscosity, elasticity and extensibility to wheat dough during mixing and processing. In this review, we summarize recent progress in wheat gluten research with a focus on the fundamental molecular biological aspects, including transcriptional regulation on genes coding for prolamin components, biosynthesis, deposition and secretion of protein polymers, formation of protein bodies, genetic control of seed storage proteins, the transportation of the protein bodies and key enzymes for determining the formation of disulphide bonds of prolamin polymers.

Localisation of quantitative trait loci for quality attributes in a doubled haploid population of wheat (Triticum aestivum L.)

Selection of wheat germplasm for a range of quality traits has been a challenging exercise because of the cost of testing, the variation within testing data, and a poor understanding of the underlying genetics. The objective of this study was to identify quantitative trait loci (QTLs) underlying quality traits in wheat. A doubled haploid population comprising 190 lines from Chara/WW2449 was grown in two different environments and evaluated for various quality traits. A molecular map comprising 362 markers based upon simple sequence repeat, sequence tagged microsatellite, glutenin, and DArT loci was constructed and subsequently exploited to identify QTLs using a whole-genome approach. Fifteen QTLs that were consistent in the two different environments were identified for thousand kernel mass, grain protein content, milling yield, flour protein content, flour colour, flour water absorption, dough development time, dough strength (extensograph height and resistance at 5 cm), and dough extensibility (extensograph length) using the whole genome average interval mapping approach. The amount of genetic variation explained by individual QTLs ranged from 3% to 49%. A number of QTLs associated with dough strength, dough extensibility, dough development time, and flour water absorption were located close to the glutenin Glu-B1 locus on chromosome 1B. Identification of the chromosomal location and effect of the QTLs influencing wheat quality may hasten the development of superior wheats for target markets via marker-assisted selection.

Genetic control of wheat quality: interactions between chromosomal regions determining protein content and composition, dough rheology, and sponge and dough baking properties

While the genetic control of wheat processing characteristics such as dough rheology is well understood, limited information is available concerning the genetic control of baking parameters, particularly sponge and dough (S&D) baking. In this study, a quantitative trait loci (QTL) analysis was performed using a population of doubled haploid lines derived from a cross between Australian cultivars Kukri x Janz grown at sites across different Australian wheat production zones (Queensland in 2001 and 2002 and Southern and Northern New South Wales in 2003) in order to examine the genetic control of protein content, protein expression, dough rheology and sponge and dough baking performance. The study highlighted the inconsistent genetic control of protein content across the test sites, with only two loci (3A and 7A) showing QTL at three of the five sites. Dough rheology QTL were highly consistent across the 5 sites, with major effects associated with the Glu-B1 and Glu-D1 loci. The Glu-D1 5 + 10 allele had consistent effects on S&D properties across sites; however, there was no evidence for a positive effect of the high dough strength Glu-B1-al allele at Glu-B1. A second locus on 5D had positive effects on S&D baking at three of five sites. This study demonstrated that dough rheology measurements were poor predictors of S&D quality. In the absence of robust predictive tests, high heritability values for S&D demonstrate that direct selection is the current best option for achieving genetic gain in this product category.

Characterization of novel LMW-GS genes at Glu-D3 locus on chromosome 1D in Aegilops tauschii

The objectives of this study were to clarify the relationship between LMW-GS Glu-D3 gene of Ae. tauschii registered in GenBank and the six Glu-D3 genes including 12 allelic variants of common wheat characterized in our previous studies, and identify novel Glu-D3 genes and haplotypes from Ae. tauschii using gene specific PCR amplification. By searching the NCBI database, 13 LMW-GS genes/pseudogenes of Ae. tauschii were retrieved and classified into five gene families based on their nucleotide similarity with the six Glu-D3 genes of common wheat. Of them, four Ae. tauschii genes, AY585350, AY585354, AY585355 and AY585356 matched GluD3-4, GluD3-5, GluD3-1 and GluD3-2 of common wheat, respectively, and one pseudogene AY585351 matched to GluD3-6, but none of them matched to GluD3-3. In order to identify the Glu-D3 genes from Ae. tauschii corresponding to GluD3-3 and GluD3-6 of common wheat, gene specific primers were developed to amplify 8-18 Ae. tauschii entries. As a result, two novel Glu-D3 genes, designated as GluDt3-3 and GluDt3-6, were identified. GluDt3-3 showed seven allelic variants or haplotypes at the DNA level in eight Ae. tauschii entries, designated as GluDt3-31, GluDt3-32, GluDt3-33, GluDt3-34, GluDt3-35, GluDt3-36 and GluDt3-37, respectively. Two to eight SNPs were found among the seven haplotypes and 1-4 amino acid substitutions among the deduced peptides. Multiple sequence alignments showed that the DNA similarity was 99.6-99.9% among the seven GluDt3-3 haplotypes, and 99.4-99.7% between these haplotypes and those of common wheat GluD3-3 gene. GluDt3-6 presented seven haplotypes in 18 Ae. tauschii entries, designated as GluDt3-61, GluDt3-62, GluDt3-63, GluDt3-64, GluDt3-65, GluDt3-66 and GluDt3-67, respectively. GluDt3-61 from Ae. tauschii entry Ae38 was the only one haplotype with complete coding sequence, and the other six were all pseudogenes. Compared with GluD3-6 gene of common wheat, GluDt3-61 exhibited a 3-bp insertion, a 42-bp deletion and 11 base substitutions, leading to a glutamine insertion in position 52, 14 amino acid deletion in position 84-97 and 10 amino acid mutations in its deduced peptide; GluDt3-62 and GluDt3-63 showed a 6-bp insertion, a 24-bp deletion and 15-21 base substitutions in coding region, of which a nonsense mutation from C to T at position 622 resulted in pseudogenes; GluDt3-64 had five base substitution, including a nonsense mutation at the position 742. GluDt3-65, GluDt3-66 and GluDt3-67 all had a base deletion at position 247, as well as 7-8 base substitutions, which resulted in frameshift mutations in the three haplotypes. The results indicated that Ae. tauschii also contains six Glu-D3 genes and their allelic variants are even richer than those in common wheat.

A novel chimeric low-molecular-weight glutenin subunit gene from the wild relatives of wheat Aegilops kotschyi and Ae. juvenalis: evolution at the Glu-3 loci

Four LMW-m and one novel chimeric (between LMW-i and LMW-m types) low-molecular-weight glutenin subunit (LMW-GS) genes from Aegilops neglecta (UUMM), Ae. kotschyi (UUSS), and Ae. juvenalis (DDMMUU) were isolated and characterized. Sequence structures showed that the 4 LMW-m-type genes, assigned to the M genome of Ae. neglecta, displayed a high homology with those from hexaploid common wheat. The novel chimeric gene, designed as AjkLMW-i, was isolated from both Ae. kotschyi and Ae. juvenalis and shown to be located on the U genome. Phylogentic analysis demonstrated that it had higher identity to the LMW-m-type than the LMW-i-type genes. A total of 20 single nucleotide polymorphisms (SNPs) were detected among the 4 LMW-m genes, with 13 of these being nonsynonymous SNPs that resulted in amino acid substitutions in the deduced mature proteins. Phylogenetic analysis demonstrated that it had higher identity to the LMW-m-type than the LMW-i-type genes. The divergence time estimation showed that the M and D genomes were closely related and diverged at 5.42 million years ago (MYA) while the differentiation between the U and A genomes was 6.82 MYA. We propose that, in addition to homologous recombination, an illegitimate recombination event on the U genome may have occurred 6.38 MYA and resulted in the generation of the chimeric gene AjkLMW-i, which may be an important genetic mechanism for the origin and evolution of LMW-GS Glu-3 alleles as well as other prolamin genes.

Molecular cloning and characterization of four novel LMW glutenin subunit genes from Aegilops longissima, Triticum dicoccoides and T. zhukovskyi

This paper reports cloning and characterisation of four novel low-molecular-weight glutenin subunit (LMW-GS) genes (designated as TzLMW-m2, TzLMW-m1, TdLMW-m1 and AlLMW-m2) from the genomic DNA of Triticum dicoccoides, T. zhukovskyi and Aegilops longissima. The coding regions of TzLMW-m2, TzLMW-m1, TdLMW-m1 and AlLMW-m2 were 1056 bp, 903 bp, 1056 bp and 1050 bp in length, encoding 350, 300, 350 and 348 amino acid residues, respectively. The deduced amino acid sequences showed that the four novel genes were classified as LMW-m types and the comparison results indicated that the four genes had a more similar structure and a higher level of homology with the LMW-m genes than the LMW-s and -i types genes. However, the first cysteine residue's positions of TzLMW-m2, TdLMW-m1 and AlLMW-m2 were different from the others. Moreover, AlLMW-m2, TdLMW-m1 and TzLMW-m2 all possessed a longer repetitive domain, which was considered to be associated with good quality of wheat. The secondary structure prediction revealed that the content of beta-strand in AlLMW-m2 and TdLMW-m1 exceeded the positive control, suggesting that AlLMW-m2 and TdLMW-m1 should be considered as candidate genes that may have positive effect on dough quality. In order to investigate the evolutionary relationship of the novel genes with the other LMW-GSs, a phylogenetic tree was constructed. The results lead to a speculation that AlLMW-m2, TdLMW-m1 and TzLMW-m2 may be the middle types during the evolution of LMW-m and LMW-s.