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

Current Progress and Future Prospect of Wheat Genetics Research towards an Enhanced Nitrogen Use Efficiency

To improve the yield and quality of wheat is of great importance for food security worldwide. One of the most effective and significant approaches to achieve this goal is to enhance the nitrogen use efficiency (NUE) in wheat. In this review, a comprehensive understanding of the factors involved in the process of the wheat nitrogen uptake, assimilation and remobilization of nitrogen in wheat were introduced. An appropriate definition of NUE is vital prior to its precise evaluation for the following gene identification and breeding process. Apart from grain yield (GY) and grain protein content (GPC), the commonly recognized major indicators of NUE, grain protein deviation (GPD) could also be considered as a potential trait for NUE evaluation. As a complex quantitative trait, NUE is affected by transporter proteins, kinases, transcription factors (TFs) and micro RNAs (miRNAs), which participate in the nitrogen uptake process, as well as key enzymes, circadian regulators, cross-talks between carbon metabolism, which are associated with nitrogen assimilation and remobilization. A series of quantitative genetic loci (QTLs) and linking markers were compiled in the hope to help discover more efficient and useful genetic resources for breeding program. For future NUE improvement, an exploration for other criteria during selection process that incorporates morphological, physiological and biochemical traits is needed. Applying new technologies from phenomics will allow high-throughput NUE phenotyping and accelerate the breeding process. A combination of multi-omics techniques and the previously verified QTLs and molecular markers will facilitate the NUE QTL-mapping and novel gene identification.

A genome-wide association study (GWAS) identifies multiple loci linked with the natural variation for Al3+ resistance in Brassica napus

Acid soils limit yields of many important crops including canola (Brassica napus ), Australia's third largest crop. Aluminium (Al3+ ) stress is the main cause of this limitation primarily because the toxic Al3+ present inhibits root growth. Breeding programmes do not target acid-soil tolerance in B. napus because genetic variation and convincing quantitative trait loci have not been reported. We conducted a genome-wide association study (GWAS) using the BnASSYST diversity panel of B. napus genotyped with 35 729 high-quality DArTseq markers. We screened 352 B. napus accessions in hydroponics with and without a toxic concentration of AlCl3 (12μM, pH 4.3) for 12days and measured shoot biomass, root biomass, and root length. By accounting for both population structure and kinship matrices, five significant quantitative trait loci for different measures of resistance were identified using incremental Al3+ resistance indices. Within these quantitative trait locus regions of B. napus , 40 Arabidopsis thaliana gene orthologues were identified, including some previously linked with Al3+ resistance. GWAS analysis indicated that multiple genes are responsible for the natural variation in Al3+ resistance in B. napus . The results provide new genetic resources and markers to enhance that Al3+ resistance of B. napus germplasm via genomic and marker-assisted selection.

Capturing Wheat Phenotypes at the Genome Level

Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.

QTL Mapping and GWAS Reveal the Genetic Mechanism Controlling Soluble Solids Content in Brassica napus Shoots

Oilseed-vegetable-dual-purpose (OVDP) rapeseed can effectively alleviate the land contradiction between crops and it supplements vegetable supplies in winter or spring. The soluble solids content (SSC) is an important index that is used to evaluate the quality and sugar content of fruits and vegetables. However, the genetic architecture underlying the SSC in Brassica napus shoots is still unclear. Here, quantitative trait loci (QTLs) for the SSC in B. napus shoots were investigated by performing linkage mapping using a recombinant inbred line population containing 189 lines. A germplasm set comprising 302 accessions was also used to conduct a genome-wide association study (GWAS). The QTL mapping revealed six QTLs located on chromosomes A01, A04, A08, and A09 in two experiments. Among them, two major QTLs, qSSC/21GY.A04-1 and qSSC/21NJ.A08-1, accounted for 12.92% and 10.18% of the phenotypic variance, respectively. In addition, eight single-nucleotide polymorphisms with phenotypic variances between 5.62% and 10.18% were identified by the GWAS method. However, no locus was simultaneously identified by QTL mapping and GWAS. We identified AH174 (7.55 °Brix and 7.9 °Brix), L166 (8.9 °Brix and 8.38 °Brix), and L380 (8.9 °Brix and 7.74 °Brix) accessions can be used as superior parents. These results provide valuable information that increases our understanding of the genetic control of SSC and will facilitate the breeding of high-SSC B. napus shoots.

From Genetic Maps to QTL Cloning: An Overview for Durum Wheat

Durum wheat is one of the most important cultivated cereal crops, providing nutrients to humans and domestic animals. Durum breeding programs prioritize the improvement of its main agronomic traits; however, the majority of these traits involve complex characteristics with a quantitative inheritance (quantitative trait loci, QTL). This can be solved with the use of genetic maps, new molecular markers, phenotyping data of segregating populations, and increased accessibility to sequences from next-generation sequencing (NGS) technologies. This allows for high-density genetic maps to be developed for localizing candidate loci within a few Kb in a complex genome, such as durum wheat. Here, we review the identified QTL, fine mapping, and cloning of QTL or candidate genes involved in the main traits regarding the quality and biotic and abiotic stresses of durum wheat. The current knowledge on the used molecular markers, sequence data, and how they changed the development of genetic maps and the characterization of QTL is summarized. A deeper understanding of the trait architecture useful in accelerating durum wheat breeding programs is envisioned.

Multi-Locus GWAS of Quality Traits in Bread Wheat: Mining More Candidate Genes and Possible Regulatory Network

In wheat breeding, improved quality traits, including grain quality and dough rheological properties, have long been a critical goal. To understand the genetic basis of key quality traits of wheat, two single-locus and five multi-locus GWAS models were performed for six grain quality traits and three dough rheological properties based on 19, 254 SNPs in 267 bread wheat accessions. As a result, 299 quantitative trait nucleotides (QTNs) within 105 regions were identified to be associated with these quality traits in four environments. Of which, 40 core QTN regions were stably detected in at least three environments, 19 of which were novel. Compared with the previous studies, these novel QTN regions explained smaller phenotypic variation, which verified the advantages of the multi-locus GWAS models in detecting important small effect QTNs associated with complex traits. After characterization of the function and expression in-depth, 67 core candidate genes involved in protein/sugar synthesis, histone modification and the regulation of transcription factor were observed to be associated with the formation of grain quality, which showed that multi-level regulations influenced wheat grain quality. Finally, a preliminary network of gene regulation that may affect wheat quality formation was inferred. This study verified the power and reliability of multi-locus GWAS methods in wheat quality trait research, and increased the understanding of wheat quality formation mechanisms. The detected QTN regions and candidate genes in this study could be further used for gene cloning and marker-assisted selection in high-quality breeding of bread wheat.

Quantitative Trait Locus (QTLs) Mapping for Quality Traits of Wheat Based on High Density Genetic Map Combined With Bulked Segregant Analysis RNA-seq (BSR-Seq) Indicates That the Basic 7S Globulin Gene Is Related to Falling Number

Numerous quantitative trait loci (QTLs) have been identified for wheat quality; however, most are confined to low-density genetic maps. In this study, based on specific-locus amplified fragment sequencing (SLAF-seq), a high-density genetic map was constructed with 193 recombinant inbred lines derived from Chuanmai 42 and Chuanmai 39. In total, 30 QTLs with phenotypic variance explained (PVE) up to 47.99% were identified for falling number (FN), grain protein content (GPC), grain hardness (GH), and starch pasting properties across three environments. Five NAM genes closely adjacent to QGPC.cib-4A probably have effects on GPC. QGH.cib-5D was the only one detected for GH with high PVE of 33.31-47.99% across the three environments and was assumed to be related to the nearest pina-D1 and pinb-D1genes. Three QTLs were identified for FN in at least two environments, of which QFN.cib-3D had relatively higher PVE of 16.58-25.74%. The positive effect of QFN.cib-3D for high FN was verified in a double-haploid population derived from Chuanmai 42 × Kechengmai 4. The combination of these QTLs has a considerable effect on increasing FN. The transcript levels of Basic 7S globulin and Basic 7S globulin 2 in QFN.cib-3D were significantly different between low FN and high FN bulks, as observed through bulk segregant RNA-seq (BSR). These QTLs and candidate genes based on the high-density genetic map would be beneficial for further understanding of the genetic mechanism of quality traits and molecular breeding of wheat.

Simultaneous improvement of grain yield and protein content in durum wheat by different phenotypic indices and genomic selection

Simultaneous improvement of protein content and grain yield by index selection is possible but its efficiency largely depends on the weighting of the single traits. The genetic architecture of these indices is similar to that of the primary traits. Grain yield and protein content are of major importance in durum wheat breeding, but their negative correlation has hampered their simultaneous improvement. To account for this in wheat breeding, the grain protein deviation (GPD) and the protein yield were proposed as targets for selection. The aim of this work was to investigate the potential of different indices to simultaneously improve grain yield and protein content in durum wheat and to evaluate their genetic architecture towards genomics-assisted breeding. To this end, we investigated two different durum wheat panels comprising 159 and 189 genotypes, which were tested in multiple field locations across Europe and genotyped by a genotyping-by-sequencing approach. The phenotypic analyses revealed significant genetic variances for all traits and heritabilities of the phenotypic indices that were in a similar range as those of grain yield and protein content. The GPD showed a high and positive correlation with protein content, whereas protein yield was highly and positively correlated with grain yield. Thus, selecting for a high GPD would mainly increase the protein content whereas a selection based on protein yield would mainly improve grain yield, but a combination of both indices allows to balance this selection. The genome-wide association mapping revealed a complex genetic architecture for all traits with most QTL having small effects and being detected only in one germplasm set, thus limiting the potential of marker-assisted selection for trait improvement. By contrast, genome-wide prediction appeared promising but its performance strongly depends on the relatedness between training and prediction sets.

Quality and Safety Aspects of Cereals (Wheat) and Their Products

Cereals and, most specifically, wheat are described in this chapter highlighting on their safety and quality aspects. Moreover, wheat quality aspects are adequately addressed since they are used to characterize dough properties and baking quality. Determination of dough properties is also mentioned and pasta quality is also described in this chapter. Chemometrics-multivariate analysis is one of the analyses carried out. Regarding production weighing/mixing of flours, kneading, extruded wheat flours, and sodium chloride are important processing steps/raw materials used in the manufacturing of pastry products. Staling of cereal-based products is also taken into account. Finally, safety aspects of cereal-based products are well documented with special emphasis on mycotoxins, acrylamide, and near infrared methodology.

Genome-Wide Association Study Dissecting the Genetic Architecture Underlying the Branch Angle Trait in Rapeseed (Brassica napus L.)

The rapeseed branch angle is an important morphological trait because an adequate branch angle enables more efficient light capture under high planting densities. Here, we report that the average angle of the five top branches provides a reliable representation of the average angle of all branches. Statistical analyses revealed a significantly positive correlation between the branch angle and multiple plant-type and yield-related traits. The 60 K Brassica Infinium^® single nucleotide polymorphism (SNP) array was utilized to genotype an association panel with 520 diverse accessions. A genome-wide association study was performed to determine the genetic architecture of branch angle, and 56 loci were identified as being significantly associated with the branch angle trait via three models, including a robust, novel, nonparametric Anderson-Darling (A-D) test. Moreover, these loci explained 51.1% of the phenotypic variation when a simple additive model was applied. Within the linkage disequilibrium (LD) decay ranges of 53 loci, we observed plausible candidates orthologous to documented Arabidopsis genes, such as LAZY1, SGR2, SGR4, SGR8, SGR9, PIN3, PIN7, CRK5, TIR1, and APD7. These results provide insight into the genetic basis of the branch angle trait in rapeseed and might facilitate marker-based breeding for improvements in plant architecture.

Quantitative Trait Loci Associated with Phenological Development, Low-Temperature Tolerance, Grain Quality, and Agronomic Characters in Wheat (Triticum aestivum L.)

Plants must respond to environmental cues and schedule their development in order to react to periods of abiotic stress and commit fully to growth and reproduction under favorable conditions. This study was initiated to identify SNP markers for characters expressed from the seedling stage to plant maturity in spring and winter wheat (Triticum aestivum L.) genotypes adapted to western Canada. Three doubled haploid populations with the winter cultivar ‘Norstar’ as a common parent were developed and genotyped with a 90K Illumina iSelect SNP assay and a 2,998.9 cM consensus map with 17,541 markers constructed. High heritability’s reflected large differences among the parents and relatively low genotype by environment interactions for all characters considered. Significant QTL were detected for the 15 traits examined. However, different QTL for days to heading in controlled environments and the field provided a strong reminder that growth and development are being orchestrated by environmental cues and caution should be exercised when extrapolating conclusions from different experiments. A QTL on chromosome 6A for minimum final leaf number, which determines the rate of phenological development in the seedling stage, was closely linked to QTL for low-temperature tolerance, grain quality, and agronomic characters expressed up to the time of maturity. This suggests phenological development plays a critical role in programming subsequent outcomes for many traits. Transgressive segregation was observed for the lines in each population and QTL with additive effects were identified suggesting that genes for desirable traits could be stacked using Marker Assisted Selection. QTL were identified for characters that could be transferred between the largely isolated western Canadian spring and winter wheat gene pools demonstrating the opportunities offered by Marker Assisted Selection to act as bridges in the identification and transfer of useful genes among related genetic islands while minimizing the drag created by less desirable genes.

Dynamic and comparative QTL analysis for plant height in different developmental stages of Brassica napus L

This report describes a dynamic QTL analysis for plant height at various stages using a large doubled haploid population and performs a QTL comparison between different populations in Brassica napus. Plant height (PH) not only plays an important role in determining plant architecture, but is also an important character related to yield. The process of determining PH occurs through a series of steps; however, no studies have focused on developmental behavior factors affecting PH in Brassica napus. In the present study, KN DH, a large doubled haploid population containing 348 lines was used for a dynamic quantitative trait locus (QTL) analysis for PH in six experiments. In all, 20 QTLs were identified at maturity, whereas 50 QTLs were detected by conditional m apping method and the same number was identified by unconditional mapping strategies. Interestingly, five unconditional QTLs ucPH.A2-2, ucPH.A3-2, ucPH.C5-1, ucPH.C6-2 and ucPH.C6-3 were identified that were consistent over the all growth stages of one or two particular experiments, and one conditional QTL cPH.A2-3 was expressed throughout the entire growth process in one experiment. A total of 70 QTLs were obtained after combining QTLs identified at maturity, by conditional and unconditional mapping strategies, in which 25 showed opposite genetic effects in different periods/stages and experiments. A consensus map containing 1357 markers was constructed to compare QTLs identified in the KN population with five previously mapped populations. Alignment of the QTLs detected in different populations onto the consensus map showed that 27 were repeatedly detected in different genetic backgrounds. These findings will enhance our understanding of the genetic control of PH regulation in B. napus, and will be useful for rapeseed genetic manipulation through molecular marker-assisted selection.

New QTL alleles for quality-related traits in spring wheat revealed by RIL population derived from supernumerary × non-supernumerary spikelet genotypes

A population developed from an exotic line with supernumerary spikelets was genetically dissected for eight quality traits, discovering new genes/alleles with potential use in wheat breeding programs. Identifying new QTLs and alleles in exotic germplasm is paramount for further improvement of quality traits in wheat. In the present study, an RIL population developed from a cross of an elite wheat line (WCB414) and an exotic genotype with supernumerary spikelets (SS) was used to identify QTLs and new alleles for eight quality traits. Composite interval mapping for 1,000 kernels weight (TKW), kernel volume weight (KVW), grain protein content (GPC), percent of flour extraction (FE) and four mixograph-related traits identified a total of 69 QTLs including 19 stable QTLs. These QTLs were located on 18 different chromosomes (except 4D, 5D, and 6D). Thirteen of these QTLs explained more than 15% of phenotypic variation (PV) and were considered as major QTLs. In this study, we identified 11 QTLs for TKW (R (2) = 7.2-17.1 %), 10 for KVW (R (2) = 6.7-22.5%), 11 for GPC (R (2) = 4.7-16.9%), 6 for FE (R (2) = 4.8-19%) and 31 for mixograph-related traits (R (2) = 3.2-41.2%). In this population, several previously identified QTLs for SS, nine spike-related and ten agronomic traits were co-located with the quality QTLs, suggesting pleiotropic effects or close linkage among loci. The traits GPC and mixogram-related traits were positively correlated with SS. Indeed, several loci for quality traits were co-located with QTL for SS. The exotic parent contributed positive alleles that increased PV of the traits at 56% of loci demonstrating the suitability of germplasm with SS to improve quality traits in wheat.

Structural-functional dissection and characterization of yield-contributing traits originating from a group 7 chromosome of the wheatgrass species Thinopyrum ponticum after transfer into durum wheat

For the first time, using chromosome engineering of durum wheat, the underlying genetic determinants of a yield-improving segment from Thinopyrum ponticum (7AgL) were dissected. Three durum wheat-Th. ponticum near-isogenic recombinant lines (NIRLs), with distal portions of their 7AL arm (fractional lengths 0.77, 0.72, and 0.60) replaced by alien chromatin, were field-tested for two seasons under rainfed conditions. Yield traits and other agronomic characteristics of the main shoot and whole plant were measured. Loci for seed number per ear and per spikelet were detected in the proximal 7AgL segment (0.60-0.72). Loci determining considerable increases of flag leaf width and area, productive tiller number per plant, biomass per plant, and grain yield per plant were located in the distally adjacent 0.72-0.77 7AgL segment, while in the most distal portion (0.77-1.00) genetic effects on spikelet number per ear were identified. Contrary to previous reports, trials with the bread wheat T4 translocation line, carrying on 7DL a sizeable 7AgL segment of which those present in the durum wheat-Th. ponticum NIRLs represent fractions, gave no yield advantage. The hypothesis that ABA might be a factor contributing to the 7AgL effects was tested by analysing endogenous ABA contents of the NIRLs and their responses to exogenous ABA application. The 7AgL yield-related loci were shown to be ABA-independent. This study highlights the value of wheat-alien recombinant lines for dissecting the genetic and physiological basis of complex traits present in wild germplasm, and provides a basis for their targeted exploitation in wheat breeding.

A consensus map of rapeseed (Brassica napus L.) based on diversity array technology markers: applications in genetic dissection of qualitative and quantitative traits

Background

Dense consensus genetic maps based on high-throughput genotyping platforms are valuable for making genetic gains in Brassica napus through quantitative trait locus identification, efficient predictive molecular breeding, and map-based gene cloning. This report describes the construction of the first B. napus consensus map consisting of a 1,359 anchored array based genotyping platform; Diversity Arrays Technology (DArT), and non-DArT markers from six populations originating from Australia, Canada, China and Europe. We aligned the B. napus DArT sequences with genomic scaffolds from Brassica rapa and Brassica oleracea, and identified DArT loci that showed linkage with qualitative and quantitative loci associated with agronomic traits.

Results

The integrated consensus map covered a total of 1,987.2 cM and represented all 19 chromosomes of the A and C genomes, with an average map density of one marker per 1.46 cM, corresponding to approximately 0.88 Mbp of the haploid genome. Through in silico physical mapping 2,457 out of 3,072 (80%) DArT clones were assigned to the genomic scaffolds of B. rapa (A genome) and B. oleracea (C genome). These were used to orientate the genetic consensus map with the chromosomal sequences. The DArT markers showed linkage with previously identified non-DArT markers associated with qualitative and quantitative trait loci for plant architecture, phenological components, seed and oil quality attributes, boron efficiency, sucrose transport, male sterility, and race-specific resistance to blackleg disease.

Conclusions

The DArT markers provide increased marker density across the B. napus genome. Most of the DArT markers represented on the current array were sequenced and aligned with the B. rapa and B. oleracea genomes, providing insight into the Brassica A and C genomes. This information can be utilised for comparative genomics and genomic evolution studies. In summary, this consensus map can be used to (i) integrate new generation markers such as SNP arrays and next generation sequencing data; (ii) anchor physical maps to facilitate assembly of B. napus genome sequences; and (iii) identify candidate genes underlying natural genetic variation for traits of interest.

Genetic and physical mapping of flowering time loci in canola (Brassica napus L.)

We identified quantitative trait loci (QTL) underlying variation for flowering time in a doubled haploid (DH) population of vernalisation-responsive canola (Brassica napus L.) cultivars Skipton and Ag-Spectrum and aligned them with physical map positions of predicted flowering genes from the Brassica rapa genome. Significant genetic variation in flowering time and response to vernalisation were observed among the DH lines from Skipton/Ag-Spectrum. A molecular linkage map was generated comprising 674 simple sequence repeat, sequence-related amplified polymorphism, sequence characterised amplified region, Diversity Array Technology, and candidate gene based markers loci. QTL analysis indicated that flowering time is a complex trait and is controlled by at least 20 loci, localised on ten different chromosomes. These loci each accounted for between 2.4 and 28.6% of the total genotypic variation for first flowering and response to vernalisation. However, identification of consistent QTL was found to be dependant upon growing environments. We compared the locations of QTL with the physical positions of predicted flowering time genes located on the sequenced genome of B. rapa. Some QTL associated with flowering time on A02, A03, A07, and C06 may represent homologues of known flowering time genes in Arabidopsis; VERNALISATION INSENSITIVE 3, APETALA1, CAULIFLOWER, FLOWERING LOCUS C, FLOWERING LOCUS T, CURLY LEAF, SHORT VEGETATIVE PHASE, GA3 OXIDASE, and LEAFY. Identification of the chromosomal location and effect of the genes influencing flowering time may hasten the development of canola varieties having an optimal time for flowering in target environments such as for low rainfall areas, via marker-assisted selection.

Molecular mapping of qualitative and quantitative loci for resistance to Leptosphaeria maculans causing blackleg disease in canola (Brassica napus L.)

Blackleg, caused by Leptosphaeria maculans, is one of the most important diseases of oilseed and vegetable crucifiers worldwide. The present study describes (1) the construction of a genetic linkage map, comprising 255 markers, based upon simple sequence repeats (SSR), sequence-related amplified polymorphism, sequence tagged sites, and EST-SSRs and (2) the localization of qualitative (race-specific) and quantitative (race non-specific) trait loci controlling blackleg resistance in a doubled-haploid population derived from the Australian canola (Brassica napus L.) cultivars Skipton and Ag-Spectrum using the whole-genome average interval mapping approach. Marker regression analyses revealed that at least 14 genomic regions with LOD ≥ 2.0 were associated with qualitative and quantitative blackleg resistance, explaining 4.6-88.9 % of genotypic variation. A major qualitative locus, designated RlmSkipton (Rlm4), was mapped on chromosome A7, within 0.8 cM of the SSR marker Xbrms075. Alignment of the molecular markers underlying this QTL region with the genome sequence data of B. rapa L. suggests that RlmSkipton is located approximately 80 kb from the Xbrms075 locus. Molecular marker-RlmSkipton linkage was further validated in an F(2) population from Skipton/Ag-Spectrum. Our results show that SSR markers linked to consistent genomic regions are suitable for enrichment of favourable alleles for blackleg resistance in canola breeding programs.

Diversity array technology markers: genetic diversity analyses and linkage map construction in rapeseed (Brassica napus L.)

We developed Diversity Array Technology (DArT) markers for application in genetic studies of Brassica napus and other Brassica species with A or C genomes. Genomic representation from 107 diverse genotypes of B. napus L. var. oleifera (rapeseed, AACC genomes) and B. rapa (AA genome) was used to develop a DArT array comprising 11 520 clones generated using PstI/BanII and PstI/BstN1 complexity reduction methods. In total, 1547 polymorphic DArT markers of high technical quality were identified and used to assess molecular diversity among 89 accessions of B. napus, B. rapa, B. juncea, and B. carinata collected from different parts of the world. Hierarchical cluster and principal component analyses based on genetic distance matrices identified distinct populations clustering mainly according to their origin/pedigrees. DArT markers were also mapped in a new doubled haploid population comprising 131 lines from a cross between spring rapeseed lines ‘Lynx-037DH’ and ‘Monty-028DH’. Linkage groups were assigned on the basis of previously mapped simple sequence repeat (SSRs), intron polymorphism (IP), and gene-based markers. The map consisted of 437 DArT, 135 SSR, 6 IP, and 6 gene-based markers and spanned 2288 cM. Our results demonstrate that DArT markers are suitable for genetic diversity analysis and linkage map construction in rapeseed.

Genome-wide association analyses of common wheat (Triticum aestivum L.) germplasm identifies multiple loci for aluminium resistance

Aluminium (Al3+) toxicity restricts productivity and profitability of wheat (Triticum aestivum L.) crops grown on acid soils worldwide. Continued gains will be obtained by identifying superior alleles and novel Al3+ resistance loci that can be incorporated into breeding programs. We used association mapping to identify genomic regions associated with Al3+ resistance using 1055 accessions of common wheat from different geographic regions of the world and 178 polymorphic diversity arrays technology (DArT) markers. Bayesian analyses based on genetic distance matrices classified these accessions into 12 subgroups. Genome-wide association analyses detected markers that were significantly associated with Al3+ resistance on chromosomes 1A, 1B, 2A, 2B, 2D, 3A, 3B, 4A, 4B, 4D, 5B, 6A, 6B, 7A, and 7B. Some of these genomic regions correspond to previously identified loci for Al3+ resistance, whereas others appear to be novel. Among the markers targeting TaALMT1 (the major Al3+-resistance gene located on chromosome 4D), those that detected alleles in the promoter explained most of the phenotypic variance for Al3+ resistance, which is consistent with this region controlling the level of TaALMT1 expression. These results demonstrate that genome-wide association mapping cannot only confirm known Al3+-resistance loci, such as those on chromosomes 4D and 4B, but they also highlight the utility of this technique in identifying novel resistance loci.

Quantitative trait loci influencing endosperm texture, dough-mixing strength, and bread-making properties of the hard red spring wheat breeding lines

Wheat end product quality is determined by a complex group of traits including dough viscoelastic characteristics and bread-making properties. Quantitative trait loci (QTL) mapping and analysis were conducted for endosperm texture, dough-mixing strength, and bread-making properties in a population of 139 (MN99394 × MN98550) recombinant inbred lines that were evaluated at three environments in 2006. Based on the genetic map of 534 loci, six QTL were identified for endosperm texture, with the main QTL on chromosomes 1A (R2 = 6.6%–17.3%), 5A (R2 = 6.1%–17.1%), and 5D (R2 = 15.8%–22%). Thirty-four QTL were identified for eight dough-mixing strength and bread-making properties. Major QTL clusters were associated with the low-molecular weight glutenin gene Glu-A3, the two high-molecular weight glutenin genes Glu-B1 and Glu-D1, and two regions on chromosome 6D. Alleles at these QTL clusters have previously been proven useful for wheat quality, except one of the QTL clusters on chromosome 6D. A QTL cluster on chromosome 6D is one of the novel chromosome regions influencing dough-mixing strength and bread-making properties. The QTL for endosperm texture on chromosomes 1A, 5A, and 5B also influenced flour ash content (12.4%–23.3%), flour protein content (10.5%–12.5%), and flour colour (7.7%–13.5%), respectively.

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.