Genome-wide association analysis of stem water-soluble carbohydrate content in bread wheat

Identification of candidate genes and genomic prediction of soybean fatty acid components in two soybean populations

Soybean, a source of plant-derived lipids, contains an array of fatty acids essential for health. A comprehensive understanding of the fatty acid profiles in soybean is crucial for enhancing soybean cultivars and augmenting their qualitative attributes. Here, 180 F10 generation recombinant inbred lines (RILs), derived from the cross-breeding of the cultivated soybean variety 'Jidou 12' and the wild soybean 'Y9,' were used as primary experimental subjects. Using inclusive composite interval mapping (ICIM), this study undertook a quantitative trait locus (QTL) analysis on five distinct fatty acid components in the RIL population from 2019 to 2021. Concurrently, a genome-wide association study (GWAS) was conducted on 290 samples from a genetically diverse natural population to scrutinize the five fatty acid components during the same timeframe, thereby aiming to identify loci closely associated with fatty acid profiles. In addition, haplotype analysis and the Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed to predict candidate genes. The QTL analysis elucidated 23 stable QTLs intricately associated with the five fatty acid components, exhibiting phenotypic contribution rates ranging from 2.78% to 25.37%. In addition, GWAS of the natural population unveiled 102 significant loci associated with these fatty acid components. The haplotype analysis of the colocalized loci revealed that Glyma.06G221400 on chromosome 6 exhibited a significant correlation with stearic acid content, with Hap1 showing a markedly elevated stearic acid level compared with Hap2 and Hap3. Similarly, Glyma.12G075100 on chromosome 12 was significantly associated with the contents of oleic, linoleic, and linolenic acids, suggesting its involvement in fatty acid biosynthesis. In the natural population, candidate genes associated with the contents of palmitic and linolenic acids were predominantly from the fatty acid metabolic pathway, indicating their potential role as pivotal genes in the critical steps of fatty acid metabolism. Furthermore, genomic selection (GS) for fatty acid components was conducted using ridge regression best linear unbiased prediction based on both random single nucleotide polymorphisms (SNPs) and SNPs significantly associated with fatty acid components identified by GWAS. GS accuracy was contingent upon the SNP set used. Notably, GS efficiency was enhanced when using SNPs derived from QTL mapping analysis and GWAS compared with random SNPs, and reached a plateau when the number of SNP markers exceeded 3,000. This study thus indicates that Glyma.06G221400 and Glyma.12G075100 are genes integral to the synthesis and regulatory mechanisms of fatty acids. It provides insights into the complex biosynthesis and regulation of fatty acids, with significant implications for the directed improvement of soybean oil quality and the selection of superior soybean varieties. The SNP markers delineated in this study can be instrumental in establishing an efficacious pipeline for marker-assisted selection and GS aimed at improving soybean fatty acid components.

Stem traits promote wheat climate-resilience

Introduction

Wheat grain filling processes under post-anthesis stress scenarios depend mainly on stem traits and remobilization of stem water-soluble carbohydrates (WSC).

Methods

A diverse panel of advanced semi-dwarf spring wheat lines, representing a natural variation in stem traits (WSC content, stem diameter, peduncle length, and stem wall width), was used to identify specific traits that reliably reflect the relationship between WSC and grain yield. The panel was phenotyped under various environmental conditions: well-watered, water-limited, and heat stress in Mexico, and terminal-drought in Israel.

Results

Environmental stresses reduced grain yield (from 626 g m-2 under well-watered to 213 g m-2 under heat), lower internode diameter, and peduncle length. However, stem-WSC generally peaked 3-4 weeks after heading under all environmental conditions except heat (where it peaked earlier) and expressed the highest values under water-limited and terminal-drought environments. Increased investment in internode diameter and peduncle length was associated with a higher accumulation of stem WSC, which showed a positive association with yield and kernel weight. Across all environments, there were no apparent trade-offs between increased crop investment in internode diameter, peduncle length, and grain yield.

Discussion

Our results showed that selecting for genotypes with higher resource investment in stem structural biomass, WSC accumulation, and remobilization could be a valuable strategy to ameliorate grain size reduction under stress without compromising grain yield potential. Furthermore, easy-to-measure proxies for WSC (stem diameter at specific internodes and length of the last internode, i.e., the peduncle) could significantly increase throughput, potentially at the breeding scale.

Variations in phenological, physiological, plant architectural and yield-related traits, their associations with grain yield and genetic basis

BACKGROUND AND AIMS

Physiological and morphological traits play essential roles in wheat (Triticum aestivum) growth and development. In particular, photosynthesis is a limitation to yield. Increasing photosynthesis in wheat has been identified as an important strategy to increase yield. However, the genotypic variations and the genomic regions governing morphological, architectural and photosynthesis traits remain unexplored.

METHODS

Here, we conducted a large-scale investigation of the phenological, physiological, plant architectural and yield-related traits, involving 32 traits for 166 wheat lines during 2018-2020 in four environments, and performed a genome-wide association study with wheat 90K and 660K single nucleotide polymorphism (SNP) arrays.

KEY RESULTS

These traits exhibited considerable genotypic variations in the wheat diversity panel. Higher yield was associated with higher net photosynthetic rate (r = 0.41, P < 0.01), thousand-grain weight (r = 0.36, P < 0.01) and truncated and lanceolate shape, but shorter plant height (r = -0.63, P < 0.01), flag leaf angle (r = -0.49, P < 0.01) and spike number per square metre (r = -0.22, P < 0.01). Genome-wide association mapping discovered 1236 significant stable loci detected in the four environments among the 32 traits using SNP markers. Trait values have a cumulative effect as the number of the favourable alleles increases, and significant progress has been made in determining phenotypic values and favourable alleles over the years. Eleven elite cultivars and 14 traits associated with grain yield per plot (GY) were identified as potential parental lines and as target traits to develop high-yielding cultivars.

CONCLUSIONS

This study provides new insights into the phenotypic and genetic elucidation of physiological and morphological traits in wheat and their associations with GY, paving the way for discovering their underlying gene control and for developing enhanced ideotypes in wheat breeding.

GWAS scans of cereal cyst nematode (Heterodera avenae) resistance in Indian wheat germplasm

Significant yield losses in major cereal-growing regions around the world have been linked to cereal cyst nematodes (Heterodera spp.). Identifying and deploying natural sources of resistance is of utmost importance due to increasing concerns associated with chemical methods over the years. We screened 141 diverse wheat genotypes collected from pan-Indian wheat cultivation states for nematode resistance over two years, alongside two resistant (Raj MR1, W7984 (M6)) and two susceptible (WH147, Opata M85) checks. We performed genome-wide association analysis using four single-locus models (GLM, MLM, CMLM, and ECMLM) and three multi-locus models (Blink, FarmCPU, and MLMM). Single locus models identified nine significant MTAs (-log10 (P) > 3.0) on chromosomes 2A, 3B, and 4B whereas, multi-locus models identified 11 significant MTAs on chromosomes 1B, 2A, 3B, 3D and 4B. Single and multi-locus models identified nine common significant MTAs. Candidate gene analysis identified 33 genes like F-box-like domain superfamily, Cytochrome P450 superfamily, Leucine-rich repeat, cysteine-containing subtype Zinc finger RING/FYVE/PHD-type, etc., having a putative role in disease resistance. Such genetic resources can help to reduce the impact of this disease on wheat production. Additionally, these results can be used to design new strategies for controlling the spread of H. avenae, such as the development of resistant varieties or the use of resistant cultivars. Finally, the obtained results can also be used to identify new sources of resistance to this pathogen and develop novel control methods.

Linking genetic markers with an eco-physiological model to pyramid favourable alleles and design wheat ideotypes

Genetic markers can be linked with eco-physiological crop models to accurately predict genotype performance and individual markers' contributions in target environments, exploring interactions between genotype and environment. Here, wheat (Triticum aestivum L.) yield was dissected into seven traits corresponding to cultivar genetic coefficients in an eco-physiological model. Loci for these traits were discovered through the genome-wide association studies (GWAS). The cultivar genetic coefficients were derived from the loci using multiple linear regression or random forest, building a marker-based eco-physiological model. It is then applied to simulate wheat yields and design virtual ideotypes. The results indicated that the loci identified through GWAS explained 46%-75% variations in cultivar genetic coefficients. Using the marker-based model, the normalized root mean square error (nRMSE) between the simulated yield and observed yield was 13.95% by multiple linear regression and 13.62% by random forest. The nRMSE between the simulated and observed maturity dates was 1.24% by multiple linear regression and 1.11% by random forest, respectively. Structural equation modelling indicated that variations in grain yield could be well explained by cultivar genetic coefficients and phenological data. In addition, 24 pleiotropic loci in this study were detected on 15 chromosomes. More significant loci were detected by the model-based dissection method than considering yield per se. Ideotypes were identified by higher yield and more favourable alleles of cultivar genetic traits. This study proposes a genotype-to-phenotype approach and demonstrates novel ideas and tools to support the effective breeding of new cultivars with high yield through pyramiding favourable alleles and designing crop ideotypes.

A 'wiring diagram' for source strength traits impacting wheat yield potential

Source traits are currently of great interest for the enhancement of yield potential; for example, much effort is being expended to find ways of modifying photosynthesis. However, photosynthesis is but one component of crop regulation, so sink activities and the coordination of diverse processes throughout the crop must be considered in an integrated, systems approach. A set of 'wiring diagrams' has been devised as a visual tool to integrate the interactions of component processes at different stages of wheat development. They enable the roles of chloroplast, leaf, and whole-canopy processes to be seen in the context of sink development and crop growth as a whole. In this review, we dissect source traits both anatomically (foliar and non-foliar) and temporally (pre- and post-anthesis), and consider the evidence for their regulation at local and whole-plant/crop levels. We consider how the formation of a canopy creates challenges (self-occlusion) and opportunities (dynamic photosynthesis) for components of photosynthesis. Lastly, we discuss the regulation of source activity by feedback regulation. The review is written in the framework of the wiring diagrams which, as integrated descriptors of traits underpinning grain yield, are designed to provide a potential workspace for breeders and other crop scientists that, along with high-throughput and precision phenotyping data, genetics, and bioinformatics, will help build future dynamic models of trait and gene interactions to achieve yield gains in wheat and other field crops.

Wheat traits and the associated loci conferring radiation use efficiency

Wheat (Triticum aestivum L.) radiation use efficiency (RUE) must be raised through crop breeding to further increase the yield potential, as the harvest index is now close to its theoretical limit. Field experiments including 209 wheat cultivars which have been widely cultivated in China since the 1940s were conducted in two growing seasons (2018-2019 and 2019-2020) to evaluate the variations of phenological, physiological, plant architectural, and yield-related traits and their contributions to RUE and to identify limiting factors for wheat yield potential. The average annual genetic gain in grain yield was 0.60% (or 45.32 kg ha^-1  year^-1 ; R²  = 0.44, P < 0.01), mainly attributed to the gain in RUE (r = 0.85, P < 0.01). The net photosynthetic rates were positively and closely correlated with grain RUE and grain yield, suggesting source as a limiting factor to future yield gains. Thirty-four cultivars were identified, exhibiting not only high RUE, but also traits contributing to high RUE and 11 other critical traits - of known genetic basis - as potential parents for breeding to improve yield and RUE. Our findings reveal wheat traits and the associated loci conferring RUE, which are valuable for facilitating marker-assisted breeding to improve wheat RUE and yield potential.

QTL mapping and KASP marker development for seed vigor related traits in common wheat

Seed vigor is an important parameter of seed quality, and identification of seed vigor related genes can provide an important basis for highly efficient molecular breeding in wheat. In the present study, a doubled haploid (DH) population with 174 lines derived from a cross between Yangmai16 and Zhongmai 895 was used to evaluate 10 seed vigor related traits in Luoyang during the 2018-2019 cropping season and in Mengjin and Luoning Counties during 2019-2020 cropping season for three environments. Quantitative trait locus (QTL) mapping of 10 seed vigor related traits in the DH population resulted in the discovery/identification of 28 QTLs on chromosomes 2B, 3D, 4B, 4D, 5A, 5B, 6A, 6B, 6D, 7A and 7D, explaining 3.6-23.7% of the phenotypic variances. Among them, one QTL cluster for shoot length, root length and vigor index was mapped between AX-89421921 and Rht-D1_SNP on chromosome 4D in the physical intervals of 18.78-19.29 Mb (0.51 Mb), explaining 9.2-20.5% of the phenotypic variances. Another QTL for these traits was identified at the physical position 185.74 Mb on chromosome 5B, which was flanked by AX-111465230 and AX-109519938 and accounted for 8.0-13.3% of the phenotypic variances. Two QTLs for shoot length, shoot fresh weight and shoot dry weight were identified in the marker intervals of AX-109384026-AX-111120402 and AX-111651800-AX-94443918 on chromosomes 6A and 6B, explaining 8.2-11.7% and 3.6-10.3% of the phenotypic variance, respectively; both alleles for increasing phenotypic values were derived from Yangmai 16. We also developed the KASP markers for the QTL cluster QVI.haust-4D.1/QSL.haust-4D/QRL.haust-4D, and validated in an international panel of 135 wheat accessions. The germplasm, genes and KASP markers were developed for breeders to improve wheat varieties with seed vigor related traits.

Genes Impacting Grain Weight and Number in Wheat (Triticum aestivum L. ssp. aestivum)

The primary goal of common wheat (T. aestivum) breeding is increasing yield without negatively impacting the agronomic traits or product quality. Genetic approaches to improve the yield increasingly target genes that impact the grain weight and number. An energetic trade-off exists between the grain weight and grain number, the result of which is that most genes that increase the grain weight also decrease the grain number. QTL associated with grain weight and number have been identified throughout the hexaploid wheat genome, leading to the discovery of numerous genes that impact these traits. Genes that have been shown to impact these traits will be discussed in this review, including TaGNI, TaGW2, TaCKX6, TaGS5, TaDA1, WAPO1, and TaRht1. As more genes impacting the grain weight and number are characterized, the opportunity is increasingly available to improve common wheat agronomic yield by stacking the beneficial alleles. This review provides a synopsis of the genes that impact grain weight and number, and the most beneficial alleles of those genes with respect to increasing the yield in dryland and irrigated conditions. It also provides insight into some of the genetic mechanisms underpinning the trade-off between grain weight and number and their relationship to the source-to-sink pathway. These mechanisms include the plant size, the water soluble carbohydrate levels in plant tissue, the size and number of pericarp cells, the cytokinin and expansin levels in developing reproductive tissue, floral architecture and floral fertility.

GWAS to Identify Novel QTNs for WSCs Accumulation in Wheat Peduncle Under Different Water Regimes

Water-soluble carbohydrates (WSCs) play a vital role in water stress avoidance and buffering wheat grain yield. However, the genetic architecture of stem WSCs' accumulation is partially understood, and few candidate genes are known. This study utilizes the compressed mixed linear model-based genome wide association study (GWAS) and heuristic post GWAS analyses to identify causative quantitative trait nucleotides (QTNs) and candidate genes for stem WSCs' content at 15 days after anthesis under different water regimes (irrigated, rainfed, and drought). Glucose, fructose, sucrose, fructans, total non-structural carbohydrates (the sum of individual sugars), total WSCs (anthrone based) quantified in the peduncle of 301 bread wheat genotypes under multiple environments (E01-E08) pertaining different water regimes, and 14,571 SNPs from "35K Axiom Wheat Breeders" Array were used for analysis. As a result, 570 significant nucleotide trait associations were identified on all chromosomes except for 4D, of which 163 were considered stable. A total of 112 quantitative trait nucleotide regions (QNRs) were identified of which 47 were presumable novel. QNRs qWSC-3B.2 and qWSC-7A.2 were identified as the hotspots. Post GWAS integration of multiple data resources prioritized 208 putative candidate genes delimited into 64 QNRs, which can be critical in understanding the genetic architecture of stem WSCs accumulation in wheat under optimum and water-stressed environments. At least 19 stable QTNs were found associated with 24 prioritized candidate genes. Clusters of fructans metabolic genes reported in the QNRs qWSC-4A.2 and qWSC-7A.2. These genes can be utilized to bring an optimum combination of various fructans metabolic genes to improve the accumulation and remobilization of stem WSCs and water stress tolerance. These results will further strengthen wheat breeding programs targeting sustainable wheat production under limited water conditions.

Comprehensive evaluation of mapping complex traits in wheat using genome-wide association studies

Genome-wide association studies (GWAS) are effectively applied to detect the marker trait associations (MTAs) using whole genome-wide variants for complex quantitative traits in different crop species. GWAS has been applied in wheat for different quality, biotic and abiotic stresses, and agronomic and yield-related traits. Predictions for marker-trait associations are controlled with the development of better statistical models taking population structure and familial relatedness into account. In this review, we have provided a detailed overview of the importance of association mapping, population design, high-throughput genotyping and phenotyping platforms, advancements in statistical models and multiple threshold comparisons, and recent GWA studies conducted in wheat. The information about MTAs utilized for gene characterization and adopted in breeding programs is also provided. In the literature that we surveyed, as many as 86,122 wheat lines have been studied under various GWA studies reporting 46,940 loci. However, further utilization of these is largely limited. The future breakthroughs in area of genomic selection, multi-omics-based approaches, machine, and deep learning models in wheat breeding after exploring the complex genetic structure with the GWAS are also discussed. This is a most comprehensive study of a large number of reports on wheat GWAS and gives a comparison and timeline of technological developments in this area. This will be useful to new researchers or groups who wish to invest in GWAS.

High Resolution Genome Wide Association Studies Reveal Rich Genetic Architectures of Grain Zinc and Iron in Common Wheat (Triticum aestivum L.)

Biofortification is a sustainable strategy to alleviate micronutrient deficiency in humans. It is necessary to improve grain zinc (GZnC) and iron concentrations (GFeC) in wheat based on genetic knowledge. However, the precise dissection of the genetic architecture underlying GZnC and GFeC remains challenging. In this study, high-resolution genome-wide association studies were conducted for GZnC and GFeC by three different models using 166 wheat cultivars and 373,106 polymorphic markers from the wheat 660K and 90K single nucleotide polymorphism (SNP) arrays. Totally, 25 and 16 stable loci were detected for GZnC and GFeC, respectively. Among them, 17 loci for GZnC and 8 for GFeC are likely to be new quantitative trait locus/loci (QTL). Based on gene annotations and expression profiles, 28 promising candidate genes were identified for Zn/Fe uptake (8), transport (11), storage (3), and regulations (6). Of them, 11 genes were putative wheat orthologs of known Arabidopsis and rice genes related to Zn/Fe homeostasis. A brief model, such as genes related to Zn/Fe homeostasis from root uptake, xylem transport to the final seed storage was proposed in wheat. Kompetitive allele-specific PCR (KASP) markers were successfully developed for two major QTL of GZnC on chromosome arms 3AL and 7AL, respectively, which were independent of thousand kernel weight and plant height. The 3AL QTL was further validated in a bi-parental population under multi-environments. A wheat multidrug and toxic compound extrusion (MATE) transporter TraesCS3A01G499300, the ortholog of rice gene OsPEZ2, was identified as a potential candidate gene. This study has advanced our knowledge of the genetic basis underlying GZnC and GFeC in wheat and provides valuable markers and candidate genes for wheat biofortification.

Identification of genomic regions affecting grain peroxidase activity in bread wheat using genome-wide association study

BACKGROUND

Peroxidase (POD) activity plays an important role in flour-based product quality, which is mainly associated with browning and bleaching effects of flour. Here, we performed a genome-wide association study (GWAS) on POD activity using an association population consisted with 207 wheat world-wide collected varieties. Our study also provide basis for the genetic improvement of flour color-based quality in wheat.

RESULTS

Twenty quantitative trait loci (QTLs) were detected associated with POD activity, explaining 5.59-12.67% of phenotypic variation. Superior alleles were positively correlated with POD activity. In addition, two SNPs were successfully developed to KASP (Kompetitive Allele-Specific PCR) markers. Two POD genes, TraesCS2B02G615700 and TraesCS2D02G583000, were aligned near the QTLs flanking genomic regions, but only TraesCS2D02G583000 displayed significant divergent expression levels (P < 0.001) between high and low POD activity varieties in the investigated association population. Therefore, it was deduced to be a candidate gene. The expression level of TraesCS2D02G583000 was assigned as a phenotype for expression GWAS (eGWAS) to screen regulatory elements. In total, 505 significant SNPs on 20 chromosomes (excluding 4D) were detected, and 9 of them located within 1 Mb interval of TraesCS2D02G583000.

CONCLUSIONS

To identify genetic loci affecting POD activity in wheat grain, we conducted GWAS on POD activity and the candidate gene TraesCS2D02G583000 expression. Finally, 20 QTLs were detected for POD activity, whereas two QTLs associated SNPs were converted to KASP markers that could be used for marker-assisted breeding. Both cis- and trans-acting elements were revealed by eGWAS of TraesCS2D02G583000 expression. The present study provides genetic loci for improving POD activity across wide genetic backgrounds and largely improved the selection efficiency for breeding in wheat.

The potential of resilient carbon dynamics for stabilizing crop reproductive development and productivity during heat stress

Impaired carbon metabolism and reproductive development constrain crop productivity during heat stress. Reproductive development is energy intensive, and its requirement for respiratory substrates rises as associated metabolism increases with temperature. Understanding how these processes are integrated and the extent to which they contribute to the maintenance of yield during and following periods of elevated temperatures is important for developing climate-resilient crops. Recent studies are beginning to demonstrate links between processes underlying carbon dynamics and reproduction during heat stress, consequently a summation of research that has been reported thus far and an evaluation of purported associations are needed to guide and stimulate future research. To this end, we review recent studies relating to source-sink dynamics, non-foliar photosynthesis and net carbon gain as pivotal in understanding how to improve reproductive development and crop productivity during heat stress. Rapid and precise phenotyping during narrow phenological windows will be important for understanding mechanisms underlying these processes, thus we discuss the development of relevant high-throughput phenotyping approaches that will allow for more informed decision-making regarding future crop improvement.

Genome-Wide Association Study of Kernel Traits in Aegilops tauschii

Aegilops tauschii is the diploid progenitor of the D subgenome of hexaploid wheat (Triticum aestivum L.). Here, the phenotypic data of kernel length (KL), kernel width (KW), kernel volume (KV), kernel surface area (KSA), kernel width to length ratio (KWL), and hundred-kernel weight (HKW) for 223 A. tauschii accessions were gathered across three continuous years. Based on population structure analysis, 223 A. tauschii were divided into two subpopulations, namely T-group (mainly included A. tauschii ssp. tauschii accessions) and S-group (mainly included A. tauschii ssp. strangulata). Classifications based on cluster analysis were highly consistent with the population structure results. Meanwhile, the extent of linkage disequilibrium decay distance (r² = 0.5) was about 110 kb and 290 kb for T-group and S-group, respectively. Furthermore, a genome-wide association analysis was performed on these kernel traits using 6,723 single nucleotide polymorphism (SNP) markers. Sixty-six significant markers, distributed on all seven chromosomes, were identified using a mixed linear model explaining 4.82–13.36% of the phenotypic variations. Among them, 15, 28, 22, 14, 21, and 13 SNPs were identified for KL, KW, KV, KSA, KWL, and HKW, respectively. Moreover, six candidate genes that may control kernel traits were identified (AET2Gv20774800, AET4Gv20799000, AET5Gv20005900, AET5Gv20084100, AET7Gv20644900, and AET5Gv21111700). The transfer of beneficial genes from A. tauschii to wheat using marker-assisted selection will broaden the wheat D subgenome improve the efficiency of breeding.

Genome-Wide Association of Stem Carbohydrate Accumulation and Remobilization during Grain Growth in Bread Wheat (Triticum aestivum L.) in Mediterranean Environments

Water deficit represents an important challenge for wheat production in many regions of the world. Accumulation and remobilization of water-soluble carbohydrates (WSCs) in stems are part of the physiological responses regulated by plants to cope with water stress and, in turn, determine grain yield (GY). The genetic mechanisms underlying the variation in WSC are only partially understood. In this study, we aimed to identify Single Nucleotide Polymorphism (SNP) markers that account for variation in a suite of WSC and GY, evaluated in 225 cultivars and advanced lines of spring wheat. These genotypes were established in two sites in the Mediterranean region of Central Chile, under water-limited and full irrigation conditions, and assessed in two growing seasons, namely anthesis and maturity growth periods. A genome-wide association study (GWAS) was performed by using 3243 SNP markers. Genetic variance accounted for 5 to 52% of phenotypic variation of the assessed traits. A rapid linkage disequilibrium decay was observed across chromosomes (r² ≤ 0.2 at 2.52 kbp). Marker-trait association tests identified 96 SNPs related to stem weight (SW), WSCs, and GY, among other traits, at the different sites, growing seasons, and growth periods. The percentage of SNPs that were part of the gene-coding regions was 34%. Most of these genes are involved in the defensive response to drought and biotic stress. A complimentary analysis detected significant effects of different haplotypes on WSC and SW, in anthesis and maturity. Our results evidence both genetic and environmental influence on WSC dynamics in spring wheat. At the same time, they provide a series of markers suitable for supporting assisted selection approaches and functional characterization of genes.

Toward the Genetic Basis and Multiple QTLs of Kernel Hardness in Wheat

Kernel hardness is one of the most important single traits of wheat seed. It classifies wheat cultivars, determines milling quality and affects many end-use qualities. Starch granule surfaces, polar lipids, storage protein matrices and Puroindolines potentially form a four-way interaction that controls wheat kernel hardness. As a genetic factor, Puroindoline polymorphism explains over 60% of the variation in kernel hardness. However, genetic factors other than Puroindolines remain to be exploited. Over the past two decades, efforts using population genetics have been increasing, and numerous kernel hardness-associated quantitative trait loci (QTLs) have been identified on almost every chromosome in wheat. Here, we summarize the state of the art for mapping kernel hardness. We emphasize that these steps in progress have benefitted from (1) the standardized methods for measuring kernel hardness, (2) the use of the appropriate germplasm and mapping population, and (3) the improvements in genotyping methods. Recently, abundant genomic resources have become available in wheat and related Triticeae species, including the high-quality reference genomes and advanced genotyping technologies. Finally, we provide perspectives on future research directions that will enhance our understanding of kernel hardness through the identification of multiple QTLs and will address challenges involved in fine-tuning kernel hardness and, consequently, food properties.