Genome-wide association study of six quality-related traits in common wheat (Triticum aestivum L.) under two sowing conditions

Identification and fine mapping of a QTL-rich region for yield- and quality-related traits on chromosome 4BS in common wheat (Triticum aestivum L.)

Yield and quality are important for plant breeding. To better understand the genetic basis underlying yield- and quality-related traits in wheat (Triticum aestivum L.), we conducted the quantitative trait locus (QTL) analysis using recombinant inbred lines (RILs) and a high-density genetic linkage map with a 90 K array. In this study, a total of 117 QTLs were detected for spike number per area (SNPA), thousand grain weight (TGW), grain number per spike (GNS), plant height (PH), spike length (SL), total spikelet number (TSN), spikelet density (SD), grain protein content (GPC), and grain starch content (GSC). Among these QTLs, 30 environmentally stable QTLs for yield- and quality-related traits were detected. Notably, five QTL-rich regions (Qrr) for yield- and/or quality-related traits were identified, including the QTL-rich region on chromosome 4BS (QQrr.cau-4B) for eight traits (SNPA, GNS, PH, SL, TSN, SD, GPC, and GSC). The stable QTL-rich region QQrr.cau-4B was delimited into a physical interval of approximately 2.47 Mb. Based on the annotation information of the Chinese spring wheat genome v1.0 and parental re-sequencing results, the interval included twelve genes with sequence variations. Taken together, these results contribute to further understanding of the genetic basis of SNPA, GNS, PH, SL, TSN, SD, GPC, and GSC, and fine mapping of QQrr.cau-4B will be beneficial for gene cloning and marker-assisted selection in the genetic improvement of wheat varieties.

Pleiotropic Quantitative Trait Loci (QTL) Mining for Regulating Wheat Processing Quality- and Yield-Related Traits

To investigate the genetic basis of processing quality- and yield-related traits in bread wheat (Triticum aestivum L., AABBDD), a systematic analysis of wheat processing quality- and yield-related traits based on genome-wide association studies (GWASs) of 285 regional test lines of wheat from Hebei province, China, was conducted. A total of 87 quantitative trait loci (QTL), including twenty-one for water absorption (WA), four for wet gluten content, eight for grain protein content, seventeen for dough stability time (DST), thirteen for extension area (EA), twelve for maximum resistance (MR), five for thousand-grain weight (TGW), one for grain length, and six for grain width were identified. These QTL harbored 188 significant single-nucleotide polymorphisms (SNPs). Twenty-five SNPs were simultaneously associated with multiple traits. Notably, the SNP AX-111015470 on chromosome 1A was associated with DST, EA, and MR. SNPs AX-111917292 and AX-109124553 on chromosome 5D were associated with wheat WA and TGW. Most processing quality-related QTL and seven grain yield-related QTL identified in this study were newly discovered. Among the surveyed accessions, 18 rare superior alleles were identified. This study identified significant QTL associated with quality-related and yield-related traits in wheat, and some of them showed pleiotropic effects. This study will facilitate molecular designs that seek to achieve synergistic improvements of wheat quality and yield.

Natural allelic variation confers diversity in the regulation of flag leaf traits in wheat

Flag leaf (FL) dimension has been reported as a key ecophysiological aspect for boosting grain yield in wheat. A worldwide winter wheat panel consisting of 261 accessions was tested to examine the phenotypical variation and identify quantitative trait nucleotides (QTNs) with candidate genes influencing FL morphology. To this end, four FL traits were evaluated during the early milk stage under two growing seasons at the Leibniz Institute of Plant Genetics and Crop Plant Research. The results showed that all leaf traits (Flag leaf length, width, area, and length/width ratio) were significantly influenced by the environments, genotypes, and environments × genotypes interactions. Then, a genome-wide association analysis was performed using 17,093 SNPs that showed 10 novel QTNs that potentially play a role in modulating FL morphology in at least two environments. Further analysis revealed 8 high-confidence candidate genes likely involved in these traits and showing high expression values from flag leaf expansion until its senescence and also during grain development. An important QTN (wsnp_RFL_Contig2177_1500201) was associated with FL width and located inside TraesCS3B02G047300 at chromosome 3B. This gene encodes a major facilitator, sugar transporter-like, and showed the highest expression values among the candidate genes reported, suggesting their positive role in controlling flag leaf and potentially being involved in photosynthetic assimilation. Our study suggests that the detection of novel marker-trait associations and the subsequent elucidation of the genetic mechanism influencing FL morphology would be of interest for improving plant architecture, light capture, and photosynthetic efficiency during grain development.

TaNAM-6A is essential for nitrogen remobilisation and regulates grain protein content in wheat (Triticum aestivum L.)

Grain protein content (GPC) is a crucial quality trait in bread wheat, which is influenced by the key transcription factor TaNAM. However, the regulatory mechanisms of TaNAM have remained largely elusive. In this study, a new role of TaNAM was unveiled in regulating nitrogen remobilisation which impacts GPC. The TaNAM knockout mutants generated by clustered regularly interspaced short palindromic repeats/Cas9 exhibited significantly delayed senescence and lower GPC, while overexpression of TaNAM-6A resulted in premature senility and much higher GPC. Further analysis revealed that TaNAM directly activates the genes TaNRT1.1 and TaNPF5.5s, which are involved in nitrogen remobilisation. This activity aids in the transfer of nitrogen from leaves to grains for protein synthesis. In addition, an elite allele of TaNAM-6A, associated with high GPC, was identified as a candidate gene for breeding high-quality wheat. Overall, our work not only elucidates the potential mechanism of TaNAM-6A affecting bread wheat GPC, but also highlights the significance of nitrogen remobilisation from senescent leaves to grains for protein accumulation. Moreover, our research provides a new target and approach for improving the quality traits of wheat, particularly the GPC.

Dissecting the genetic basis of Fusarium crown rot resistance in wheat by genome wide association study

KEY MESSAGE

A locus conferring Fusarium crown rot resistance was identified on chromosome arm 3DL through genome wide association study and further validated in two recombinant inbred lines populations. Fusarium crown rot (FCR) is a severe soil borne disease in many wheat growing regions of the world. In this study, we attempted to detect loci conferring FCR resistance through a new seedling inoculation assay. A total of 223 wheat accessions from different geography origins were used to assemble an association panel for GWAS analysis. Four genotypes including Heng 4332, Luwanmai, Pingan 998 and Yannong 24 showed stable resistance to FCR. A total of 54 SNPs associated with FCR resistance were identified. Among the 10 putative QTLs represented by these SNPs, seven QTLs on chromosome 2B, 3A, 3D, 4A, 7A and 7B were novel and were consistently detected in at least two of the three trials conducted. Qfcr.cau.3D-3, which was targeted by 38 SNPs clustered within a genomic region of approximately 5.57 Mb (609.12-614.69 Mb) on chromosome arm 3DL, was consistently detected in all the three trials. The effects of Qfcr.cau.3D-3 were further validated in two recombinant inbred line populations. The presence of this locus reduced FCR severity up to 21.55%. Interestingly, the collinear positions of sequences containing the four SNPs associated with two FCR loci (Qfcr.cau.3A and Qfcr.cau.3B) were within the regions of Qfcr.cau.3D-3, suggesting that genes underlying these three loci may be homologous. Our results provide useful information for improving FCR resistance in wheat.

A novel variation of TaGW2-6B increases grain weight without penalty in grain protein content in wheat (Triticum aestivum L.)

Yield and quality are two crucial breeding objects of wheat therein grain weight and grain protein content (GPC) are two key relevant factors correspondingly. Investigations of their genetic mechanisms represent special significance for breeding. In this study, 199 F2 plants and corresponding F2:3 families derived from Nongda3753 (ND3753) and its EMS-generated mutant 564 (M564) were used to investigate the genetic basis of larger grain and higher GPC of M564. QTL analysis identified a total of 33 environmentally stable QTLs related to thousand grain weight (TGW), grain area (GA), grain circle (GC), grain length (GL), grain width (GW), and GPC on chromosomes 1B, 2A, 2B, 4D, 6B, and 7D, respectively, among which QGw.cau-6B.1, QTgw.cau-6B.1, QGa.cau-6B.1, and QGc.cau-6B.1 shared overlap confidence interval on chromosome 6B. This interval contained the TaGW2 gene playing the same role as the QTLs, so TaGW2-6B was cloned and sequenced. Sequence alignment revealed two G/A SNPs between two parents, among which the SNP in the seventh exon led to a premature termination in M564. A KASP marker was developed based on the SNP, and single-marker analysis on biparental populations showed that the mutant allele could significantly increase GW and TGW, but had no effect on GPC. Distribution detection of the mutant allele through KASP marker genotyping and sequence alignment against databases ascertained that no materials harbored this allele within natural populations. This allele was subsequently introduced into three different varieties through molecular marker-assisted backcrossing, and it was revealed that the allele had a significant effect on simultaneously increasing GW, TGW, and even GPC in all of three backgrounds. Summing up the above, it could be concluded that a novel elite allele of TaGW2-6B was artificially created and might play an important role in wheat breeding for high yield and quality.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-024-01455-y.

Deciphering the evolution and complexity of wheat germplasm from a genomic perspective

Bread wheat provides an essential fraction of the daily calorific intake for humanity. Due to its huge and complex genome, progress in studying on the wheat genome is substantially trailed behind those of the other two major crops, rice and maize, for at least a decade. With rapid advances in genome assembling and reduced cost of high-throughput sequencing, emerging de novo genome assemblies of wheat and whole-genome sequencing data are leading to a paradigm shift in wheat research. Here, we review recent progress in dissecting the complex genome and germplasm evolution of wheat since the release of the first high-quality wheat genome. New insights have been gained in the evolution of wheat germplasm during domestication and modern breeding progress, genomic variations at multiple scales contributing to the diversity of wheat germplasm, and complex transcriptional and epigenetic regulations of functional genes in polyploid wheat. Genomics databases and bioinformatics tools meeting the urgent needs of wheat genomics research are also summarized. The ever-increasing omics data, along with advanced tools and well-structured databases, are expected to accelerate deciphering the germplasm and gene resources in wheat for future breeding advances.

Novel Genetic Loci from Triticum timopheevii Associated with Gluten Content Revealed by GWAS in Wheat Breeding Lines

The content and quality of gluten in wheat grain is a distinctive characteristic that determines the final properties of wheat flour. In this study, a genome-wide association study (GWAS) was performed on a wheat panel consisting of bread wheat varieties and the introgression lines (ILs) obtained via hybridization with tetraploid wheat relatives. A total of 17 stable quantitative trait nucleotides (QTNs) located on chromosomes 1D, 2A, 2B, 3D, 5A, 6A, 7B, and 7D that explained up to 21% of the phenotypic variation were identified. Among them, the QTLs on chromosomes 2A and 7B were found to contain three and six linked SNP markers, respectively. Comparative analysis of wheat genotypes according to the composition of haplotypes for the three closely linked SNPs of chromosome 2A indicated that haplotype TT/AA/GG was characteristic of ten ILs containing introgressions from T. timopheevii. The gluten content in the plants with TT/AA/GG haplotype was significantly higher than in the varieties with haplotype GG/GG/AA. Having compared the newly obtained data with the previously reported quantitative trait loci (QTLs) we inferred that the locus on chromosome 2A inherited from T. timopheevii is potentially novel. The introgression lines containing the new locus can be used as sources of genetic factors to improve the quality traits of bread wheat.

Nutritional Genomic Approach for Improving Grain Protein Content in Wheat

Grain protein content (GPC) is a key aspect of grain quality, a major determinant of the flour functional properties and grain nutritional value of bread wheat. Exploiting diverse germplasms to identify genes for improving crop performance and grain nutritional quality is needed to enhance food security. Here, we evaluated GPC in a panel of 255 Triticum aestivum L. accessions from 27 countries. GPC determined in seeds from three consecutive crop seasons varied from 8.6 to 16.4% (11.3% on average). Significant natural phenotypic variation in GPC among genotypes and seasons was detected. The population was evaluated for the presence of the trait-linked single nucleotide polymorphism (SNP) markers via a genome-wide association study (GWAS). GWAS analysis conducted with calculated best linear unbiased estimates (BLUEs) of phenotypic data and 90 K SNP array using the fixed and random model circulating probability unification (FarmCPU) model identified seven significant genomic regions harboring GPC-associated markers on chromosomes 1D, 3A, 3B, 3D, 4B and 5A, of which those on 3A and 3B shared associated SNPs with at least one crop season. The verified SNP-GPC associations provide new promising genomic signals on 3A (SNPs: Excalibur_c13709_2568 and wsnp_Ku_c7811_13387117) and 3B (SNP: BS00062734_51) underlying protein improvement in wheat. Based on the linkage disequilibrium for significant SNPs, the most relevant candidate genes within a 4 Mbp-window included genes encoding a subtilisin-like serine protease; amino acid transporters; transcription factors; proteins with post-translational regulatory functions; metabolic proteins involved in the starch, cellulose and fatty acid biosynthesis; protective and structural proteins, and proteins associated with metal ions transport or homeostasis. The availability of molecular markers within or adjacent to the sequences of the detected candidate genes might assist a breeding strategy based on functional markers to improve genetic gains for GPC and nutritional quality in wheat.

Heat Stress Tolerance 2 confers basal heat stress tolerance in allohexaploid wheat (Triticum aestivum L.)

Heat stress substantially reduces the yield potential of wheat (Triticum aestivum L.), one of the most widely cultivated staple crops, and greatly threatens global food security in the context of global warming. However, few studies have explored the heat stress tolerance (HST)-related genetic resources in wheat. Here, we identified and fine-mapped a wheat HST locus, TaHST2, which is indispensable for HST in both the vegetative and reproductive stages of the wheat life cycle. The studied pair of near isogenic lines (NILs) exhibited diverse morphologies under heat stress, based on which we mapped TaHST2 to a 485 kb interval on chromosome arm 4DS. Under heat stress, TaHST2 confers a superior conversion rate from soluble sugars to starch in wheat grains, resulting in faster grain filling and a higher yield potential. A further exploration of genetic resources indicated that TaHST2 underwent strong artificial selection during wheat domestication, suggesting it is an essential locus for basal HST in wheat. Our findings provide deeper insights into the genetic basis of wheat HST and might be useful for global efforts to breed heat-stress-tolerant cultivars.

Uncovering the genetic basis of gluten aggregation parameters by genome-wide association analysis in wheat (Triticum aestivum L.) using GlutoPeak

BACKGROUND

Numerous studies have shown that gluten aggregation properties directly affect the processing quality of wheat, however, the genetic basis of gluten aggregation properties were rarely reported.

RESULTS

To explore the genetic basis of gluten aggregation properties in wheat, an association population consisted with 207 wheat genotypes were constructed for evaluating nine parameters of aggregation properties on GlutoPeak across three-year planting seasons. A total of 940 significant SNPs were detected for 9 GlutoPeak parameters through genome-wide association analysis (GWAS). Finally, these SNPs were integrated to 68 non-redundant QTL distributed on 20 chromosomes and 54 QTL was assigned as pleiotropic loci which accounting for multiple parameters of gluten aggregation property. Furthermore, the peak SNPs representing 54 QTL domonstrated additive effect on all the traits. There was a significant positive correlation between the number of favorable alleles and the phenotypic values of each parameter. Peak SNPs of two novel QTL, q3AL.2 and q4DL, which contributing to both PMT (peak maximum time) and A3 (area from the first minimum to torque 15 s before the maximum torque) parameters, were selected for KASP (Kompetitive Allele Specific PCR) markers development and the KASP markers can be used for effectively evaluating the quality of gluten aggregation properties in the association population.

CONCLUSION

The rapid and efficient GlutoPeak method for gluten measurement can be used for early selection of wheat breeding. This study revealed the genetic loci related to GlutoPeak parameters in association population, which would be helpful to develop wheat elite lines with improved gluten aggregation through molecular marker-assisted breeding.

Consensus genomic regions associated with grain protein content in hexaploid and tetraploid wheat

A meta-analysis of QTLs associated with grain protein content (GPC) was conducted in hexaploid and tetraploid wheat to identify robust and stable meta-QTLs (MQTLs). For this purpose, as many as 459 GPC-related QTLs retrieved from 48 linkage-based QTL mapping studies were projected onto the newly developed wheat consensus map. The analysis resulted in the prediction of 57 MQTLs and 7 QTL hotspots located on all wheat chromosomes (except chromosomes 1D and 4D) and the average confidence interval reduced 2.71-fold in the MQTLs and QTL hotspots compared to the initial QTLs. The physical regions occupied by the MQTLs ranged from 140 bp to 224.02 Mb with an average of 15.2 Mb, whereas the physical regions occupied by QTL hotspots ranged from 1.81 Mb to 36.03 Mb with a mean of 8.82 Mb. Nineteen MQTLs and two QTL hotspots were also found to be co-localized with 45 significant SNPs identified in 16 previously published genome-wide association studies in wheat. Candidate gene (CG) investigation within some selected MQTLs led to the identification of 705 gene models which also included 96 high-confidence CGs showing significant expressions in different grain-related tissues and having probable roles in GPC regulation. These significantly expressed CGs mainly involved the genes/gene families encoding for the following proteins: aminotransferases, early nodulin 93, glutamine synthetases, invertase/pectin methylesterase inhibitors, protein BIG GRAIN 1-like, cytochrome P450, glycosyl transferases, hexokinases, small GTPases, UDP-glucuronosyl/UDP-glucosyltransferases, and EamA, SANT/Myb, GNAT, thioredoxin, phytocyanin, and homeobox domains containing proteins. Further, eight genes including GPC-B1, Glu-B1-1b, Glu-1By9, TaBiP1, GSr, TaNAC019-A, TaNAC019-D, and bZIP-TF SPA already known to be associated with GPC were also detected within some of the MQTL regions confirming the efficacy of MQTLs predicted during the current study.

Wheat genomic study for genetic improvement of traits in China

Bread wheat (Triticum aestivum L.) is a major crop that feeds 40% of the world's population. Over the past several decades, advances in genomics have led to tremendous achievements in understanding the origin and domestication of wheat, and the genetic basis of agronomically important traits, which promote the breeding of elite varieties. In this review, we focus on progress that has been made in genomic research and genetic improvement of traits such as grain yield, end-use traits, flowering regulation, nutrient use efficiency, and biotic and abiotic stress responses, and various breeding strategies that contributed mainly by Chinese scientists. Functional genomic research in wheat is entering a new era with the availability of multiple reference wheat genome assemblies and the development of cutting-edge technologies such as precise genome editing tools, high-throughput phenotyping platforms, sequencing-based cloning strategies, high-efficiency genetic transformation systems, and speed-breeding facilities. These insights will further extend our understanding of the molecular mechanisms and regulatory networks underlying agronomic traits and facilitate the breeding process, ultimately contributing to more sustainable agriculture in China and throughout the world.

Genome-wide association study of grain hardness and novel Puroindoline alleles in common wheat

Grain hardness (HI) is a key trait for wheat milling and end-use quality. Puroindoline genes (PINs) are the major genes responsible for grain hardness, but other QTLs also contribute to the trait. Therefore, it is essential to identify loci associated with the HI and allelic variations of PINs in wheat. In the present study, 287 accessions from Shanxi province representing 70 years of wheat breeding were grown in one rainfed and two irrigated conditions to study grain hardness. Genome-wide association analysis (GWAS) was performed using the 15 K array, and the variability of PIN alleles was investigated. Among the accessions, hard wheat was most common. The broad-sense heritability (H2) among the three environments was 99.5%, suggesting HI was mainly affected by heredity. GWAS identified nine significant marker-trait associations (MTAs), including that PINs, which explained 7.03% to 17.70% of phenotypic variation. Four MTAs on chromosome 2A, 2B, 5A, and 7A were novel loci. As for diversity of PINs, a total of 11 PINs haplotypes were detected, composed of 12 allelic variations of the PIN gene. The most frequent haplotypes were Pina-D1a/Pinb-D1b (43.9%) and Pina-Dla/Pinb-D1p (18.8%), and both the frequency of Pina-D1a/Pinb-D1b and the HI value increased with breeding years were related to local dietary habits probably. A novel double deletion allele of the PINs haplotype was found in Donghei1206. These results will be useful not only in understanding of the genetics of the HI but also in breeding for improved grain texture.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01303-x.

Dissection of the Genetic Architecture for Quantities of Gliadins Fractions in Wheat (Triticum aestivum L.)

Gliadin is a group of grain storage proteins that confers extensibility/viscosity to the dough and are vital to end-use quality in wheat. Moreover, gliadins are one of the important components for nutritional quality because they contain the nutritional unprofitable epitopes that cause chronic immune-mediated intestinal disorder in genetically susceptible individuals designated celiac disease (CD). The main genetic loci encoding the gliadins were revealed by previous studies; however, the genes related to the content of gliadins and their fractions were less elucidated. To illustrate the genetic basis of the content of gliadins and their fractions comprehensively, a recombinant inbred line (RIL) population that consisted of 196 lines was constructed from the two parents, Luozhen No.1 and Zhengyumai 9987. Quantitative trait loci (QTL) controlling the content of total gliadins and their fractions (ω-, α-, and γ-gliadin) were screened genome-widely under four environments across 2 years. Totally, thirty QTL which explained 1.97-12.83% of the phenotypic variation were detected to be distributed on 17 chromosomes and they were gathered into 12 clusters. One hundred and one pairs of epistatic QTL (E-QTL) were revealed, among which five were involved with the total gliadins and its fractions content QTL located on chromosome 1AS, 1DS, 4DS, 1DL, and 6AS. Three Kompetitive Allele-Specific PCR (KASP) markers were developed from three major QTL clusters located on chromosomes 6A, 6D, and 7D, respectively. The present research not only dissects the genetic loci for improving the content of gliadins and their three fractions, but may also contribute to marker-assisted selection of varieties with appropriate gliadin fractions content for end-use quality and health benefit at the early developmental stages and early breeding generations.

Genome-Wide Association Study Reveals the Genetic Basis of Five Quality Traits in Chinese Wheat

Bread wheat is a highly adaptable food crop grown extensively around the world and its quality genetic improvement has received wide attention. In this study, the genetic loci associated with five quality traits including protein content (PC), gluten content (GC), baking value (BV), grain hardness (HA), and sedimentation value (SV) in a population of 253 Chinese wheat grown in Inner Mongolia were investigated through genome wide association mapping. A total of 103 QTL containing 556 SNPs were significantly related to the five quality traits based on the phenotypic data collected from three environments and BLUP data. Of these QTL, 32 QTL were continuously detected under at least two experiments. Some QTL such as qBV3D.2/qHA3D.2 on 3D, qPC5A.3/qGC5A on 5A, qBV5D/qHA5D on 5D, qBV6B.2/qHA6B.3 on 6B, and qBV6D/qHA6D.1 on 6D were associated with multiple traits. In addition, distribution of favorable alleles of the stable QTL in the association panel and their effects on five quality traits were validated. Analysis of existing transcriptome data revealed that 34 genes were specifically highly expressed in grains during reproductive growth stages. The functions of these genes will be characterized in future experiments. This study provides novel insights into the genetic basis of quality traits in wheat.

Identification of QTLs for Grain Protein Content in Russian Spring Wheat Varieties

Most modern breeding programs aim to develop wheat (T. aestivum L.) varieties with a high grain protein content (GPC) due to its greater milling and cooking quality, and improved grain price. Here, we used a genome-wide association study (GWAS) to map single nucleotide polymorphisms (SNPs) associated with GPC in 93 spring bread wheat varieties developed by eight Russian Breeding Centers. The varieties were evaluated for GPC, grain weight per spike (GWS), and thousand-kernel weight (TKW) at six environments, and genotyped with 9351 polymorphic SNPs and two SNPs associated with the NAM-A1 gene. GPC varied from 9.8 to 20.0%, depending on the genotype and environment. Nearly 52% of the genotypes had a GPC > 14.5%, which is the threshold value for entry into high-class wheat varieties. Broad-sense heritability for GPC was moderate (0.42), which is due to the significant effect of environment and genotype × environment interactions. GWAS performed on mean GPC evaluated across six environments identified eleven significant marker-trait associations, of which nine were physically mapped on chromosome 6A. Screening of wheat varieties for allelic variants of the NAM-A1 gene indicated that 60% of the varieties contained the NAM-A1c allele, followed by 33% for NAM-A1d, and 5% for NAM-A1a alleles. Varieties with the NAM-A1d allele showed significantly (p < 0.01) smaller GPC than those with NAM-A1c and NAM-A1a. However, no significant differences between NAM-A1 alleles were observed for both GWS and TKW.

Understanding Starch Metabolism in Pea Seeds towards Tailoring Functionality for Value-Added Utilization

Starch is the most abundant storage carbohydrate and a major component in pea seeds, accounting for about 50% of dry seed weight. As a by-product of pea protein processing, current uses for pea starch are limited to low-value, commodity markets. The globally growing demand for pea protein poses a great challenge for the pea fractionation industry to develop new markets for starch valorization. However, there exist gaps in our understanding of the genetic mechanism underlying starch metabolism, and its relationship with physicochemical and functional properties, which is a prerequisite for targeted tailoring functionality and innovative applications of starch. This review outlines the understanding of starch metabolism with a particular focus on peas and highlights the knowledge of pea starch granule structure and its relationship with functional properties, and industrial applications. Using the currently available pea genetics and genomics knowledge and breakthroughs in omics technologies, we discuss the perspectives and possible avenues to advance our understanding of starch metabolism in peas at an unprecedented level, to ultimately enable the molecular design of multi-functional native pea starch and to create value-added utilization.

Genetic Basis of Gluten Aggregation Properties in Wheat (Triticum aestivum L.) Dissected by QTL Mapping of GlutoPeak Parameters

Bread wheat is one of the most important crops worldwide, supplying approximately one-fifth of the daily protein and the calories for human consumption. Gluten aggregation properties play important roles in determining the processing quality of wheat (Triticum aestivum L.) products. Nevertheless, the genetic basis of gluten aggregation properties has not been reported so far. In this study, a recombinant inbred line (RIL) population derived from the cross between Luozhen No. 1 and Zhengyumai 9987 was used to identify quantitative trait loci (QTL) underlying gluten aggregation properties with GlutoPeak parameters. A linkage map was constructed based on 8,518 SNPs genotyped by specific length amplified fragment sequencing (SLAF-seq). A total of 33 additive QTLs on 14 chromosomes were detected by genome-wide composite interval mapping (GCIM), four of which accounted for more than 10% of the phenotypic variation across three environments. Two major QTL clusters were identified on chromosomes 1DS and 1DL. A premature termination of codon (PTC) mutation in the candidate gene (TraesCS1D02G009900) of the QTL cluster on 1DS was detected between Luozhen No. 1 and Zhengyumai 9987, which might be responsible for the difference in gluten aggregation properties between the two varieties. Subsequently, two KASP markers were designed based on SNPs in stringent linkage with the two major QTL clusters. Results of this study provide new insights into the genetic architecture of gluten aggregation properties in wheat, which are helpful for future improvement of the processing quality in wheat breeding.