Genome-Wide Association Mapping for Tolerance to Preharvest Sprouting and Low Falling Numbers in Wheat

Preharvest Sprouting in Quinoa: A New Screening Method Adapted to Panicles and GWAS Components

The introduction of quinoa into new growing regions and environments is of interest to farmers, consumers, and stakeholders around the world. Many plant breeding programs have already started to adapt quinoa to the environmental and agronomic conditions of their local fields. Formal quinoa breeding efforts in Washington State started in 2010, led by Professor Kevin Murphy out of Washington State University. Preharvest sprouting appeared as the primary obstacle to increased production in the coastal regions of the Pacific Northwest. Preharvest sprouting (PHS) is the undesirable sprouting of seeds that occurs before harvest, is triggered by rain or humid conditions, and is responsible for yield losses and lower nutrition in cereal grains. PHS has been extensively studied in wheat, barley, and rice, but there are limited reports for quinoa, partly because it has only recently emerged as a problem. This study aimed to better understand PHS in quinoa by adapting a PHS screening method commonly used in cereals. This involved carrying out panicle-wetting tests and developing a scoring scale specific for panicles to quantify sprouting. Assessment of the trait was performed in a diversity panel (N = 336), and the resulting phenotypes were used to create PHS tolerance rankings and undertake a GWAS analysis (n = 279). Our findings indicate that PHS occurred at varying degrees across a subset of the quinoa germplasm tested and that it is possible to access PHS tolerance from natural sources. Ultimately, these genotypes can be used as parental lines in future breeding programs aiming to incorporate tolerance to PHS.

Genome-wide association mapping for pre-harvest sprouting in European winter wheat detects novel resistance QTL, pleiotropic effects, and structural variation in multiple genomes

Pre-harvest sprouting (PHS), germination of seeds before harvest, is a major problem in global wheat (Triticum aestivum L.) production, and leads to reduced bread-making quality in affected grain. Breeding for PHS resistance can prevent losses under adverse conditions. Selecting resistant lines in years lacking pre-harvest rain, requires challenging of plants in the field or in the laboratory or using genetic markers. Despite the availability of a wheat reference and pan-genome, linking markers, genes, allelic, and structural variation, a complete understanding of the mechanisms underlying various sources of PHS resistance is still lacking. Therefore, we challenged a population of European wheat varieties and breeding lines with PHS conditions and phenotyped them for PHS traits, grain quality, phenological and agronomic traits to conduct genome-wide association mapping. Furthermore, we compared these marker-trait associations to previously reported PHS loci and evaluated their usefulness for breeding. We found markers associated with PHS on all chromosomes, with strong evidence for novel quantitative trait locus/loci (QTL) on chromosome 1A and 5B. The QTL on chromosome 1A lacks pleiotropic effect, for the QTL on 5B we detected pleiotropic effects on phenology and grain quality. Multiple peaks on chromosome 4A co-located with the major resistance locus Phs-A1, for which two causal genes, TaPM19 and TaMKK3, have been proposed. Mapping markers and genes to the pan-genome and chromosomal alignments provide evidence for structural variation around this major PHS-resistance locus. Although PHS is controlled by many loci distributed across the wheat genome, Phs-A1 on chromosome 4A seems to be the most effective and widely deployed source of resistance, in European wheat varieties.

Genetic analysis of late-maturity α-amylase in twelve wheat populations

MAIN CONCLUSION

Genetic loci, particularly those with an effect in the independent panel, could be utilised to further reduce LMA expression when used with favourable combinations of genes known to affect LMA. Late maturity α-amylase (LMA) is a grain quality defect involving elevated α-amylase within the aleurone of wheat (Triticum aestivum L.) grains. The genes known to affect expression are the reduced height genes Rht-B1 (chromosome 4B) and Rht-D1 (chromosome 4D), and an ent-copalyl diphosphate synthase gene (LMA-1) on chromosome 7B. Other minor effect loci have been reported, but these are poorly characterised and further genetic understanding is needed. In this study, twelve F4-derived populations were created through single seed descent, genotyped and evaluated for LMA. LMA-1 haplotype C and the Rht-D1b allele substantially reduced LMA expression. The alternative dwarfing genes Rht13 and Rht18 had no significant effect on LMA expression. Additional quantitative trait loci (QTL) were mapped at 16 positions in the wheat genome. Effects on LMA expression were detected for four of these QTL in a large independent panel of Australian wheat lines. The QTL detected in mapping populations and confirmed in the large independent panel provide further opportunity for selection against LMA, especially if combined with Rht-D1b and/or favourable haplotypes of LMA-1.

Identification and validation of seed dormancy loci and candidate genes and construction of regulatory networks by WGCNA in maize introgression lines

KEY MESSAGE

Seventeen PHS-QTLs and candidate genes were obtained, including eleven major loci, three under multiple environments and two with co-localization by the other mapping methods; The functions of three candidate genes were validated using mutants; nine target proteins and five networks were filtered by joint analysis of GWAS and WGCNA. Seed dormancy (SD) and pre-harvest sprouting (PHS) affect yield, as well as grain and hybrid quality in seed production. Therefore, identification of genetic and regulatory pathways underlying PHS and SD is key to gene function analysis, allelic variation mining and genetic improvement. In this study, 78,360 SNPs by SLAF-seq of 230 maize chromosome segment introgression lines (ILs), PHS under five environments were used to conduct GWAS (genome wide association study) (a threshold of 1/n), and seventeen unreported PHS QTLs were obtained, including eleven QTLs with PVE > 10% and three QTLs under multiple environments. Two QTL loci were co-located between the other two genetic mapping methods. Using differential gene expression analyses at two stages of grain development, gene functional analysis of Arabidopsis mutants, and gene functional analysis in the QTL region, seventeen PHS QTL-linked candidate genes were identified, and their five molecular regulatory networks constructed. Based on the Arabidopsis T-DNA mutations, three candidate genes were shown to regulate for SD and PHS. Meanwhile, using RNA-seq of grain development, the weighted correlation network analysis (WGCNA) was performed, deducing five regulatory pathways and target genes that regulate PHS and SD. Based on the conjoint analysis of GWAS and WGCNA, four pathways, nine target proteins and target genes were revealed, most of which regulate cell wall metabolism, cell proliferation and seed dehydration tolerance. This has important theoretical and practical significance for elucidating the genetic basis of maize PHS and SD, as well as mining of genetic resources and genetic improvement of traits.

Genome-wide association and targeted transcriptomic analyses reveal loci and candidate genes regulating preharvest sprouting in barley

KEY MESSAGE

Genome-wide association study of diverse barley genotypes identified loci, single nucleotide polymorphisms and candidate genes that control seed dormancy and therefore enhance resistance to preharvest sprouting. Preharvest sprouting (PHS) causes significant yield and quality loss in barley and it is strongly associated with the level of seed dormancy. This study performed genome-wide association study using a collection of 255 diverse barley genotypes grown over four environments to identify loci controlling dormancy/PHS. Our phenotypic analysis revealed substantial variation in germination index/dormancy levels among the barley genotypes. Marker-trait association and linkage disequilibrium (LD) decay analyses identified 16 single nucleotide polymorphisms (SNPs) and two QTLs associated with dormancy/PHS, respectively, on chromosome 3H and 5H explaining 6.9% to 11.1% of the phenotypic variation. QTL.5H consist of 14 SNPs of which 12 SNPs satisfy the FDR threshold of α = 0.05, and it may represent the SD2 locus. The QTL on 3H consists of one SNP that doesn't satisfy FDR (α = 0.05). Genes harbouring the significant SNPs were analyzed for their expression pattern in the seeds of selected dormant and non-dormant genotypes. Of these genes, HvRCD1, HvPSRP1 and HvF3H exhibited differential expression between the dormant and non-dormant seed samples, suggesting their role in controlling seed dormancy/PHS. Three SNPs located within the differentially expressed genes residing in QTL.5H explained considerable phenotypic variation (≥ 8.6%), suggesting their importance in regulating PHS resistance. Analysis of the SNP marker data in QTL.5H identified a haplotype for PHS resistance. Overall, the study identified loci, SNPs and candidate genes that control dormancy and therefore play important roles in enhancing PHS resistance in barley through marker-assisted breeding.

Genome-Wide Association Study Discovers Novel Germplasm Resources and Genetic Loci with Resistance to Gibberella Ear Rot Caused by Fusarium graminearum

Gibberella ear rot (GER) in maize caused by Fusarium graminearum is one of the most devastating maize diseases reducing grain yield and quality worldwide. The genetic bases of maize GER resistance remain largely unknown. Using artificial inoculation across multiple environments, the GER severity of an association panel consisting of 316 diverse inbred lines was observed with wide phenotypic variation. In the association panel, a genome-wide association study using a general linear model identified 69 single-nucleotide polymorphisms (SNPs) significantly associated with GER resistance at the threshold of 2.04 × 10-5, and the average phenotypic variation explained (PVE) of these SNPs was 5.09%. We also conducted a genome-wide association study analysis using a mixed linear model at a threshold of 1.0 × 10-4, and 16 significantly associated SNPs with an average PVE of 4.73% were detected. A combined general linear model and mixed linear model method obtained 10 co-localized significantly associated SNPs linked to GER resistance, including the most significant SNP (PZE-105079915) with the greatest PVE value, 9.07%, at bin 5.05 following 10 candidate genes. These findings are significant for the exploration of the complicated genetic variations in maize GER resistance. The regions and genes identified herein provide a list of candidate targets for further investigation, in addition to the elite germplasm resources that can be used for breeding GER resistance in maize.

LMA or vivipary? Wheat grain can germinate precociously during grain maturation under the cool conditions used to induce late maturity alpha-amylase (LMA)

Introduction

This study found that wheat (Triticum aestivum) grain can germinate precociously during the maturation phase of grain development, a phenomenon called vivipary that was associated with alpha-amylase induction. Farmers receive severe discounts for grain with low falling number (FN), an indicator that grain contains sufficiently elevated levels of the starch-digesting enzyme alpha-amylase to pose a risk to end-product quality. High grain alpha-amylase can result from: preharvest sprouting (PHS)/germination when mature wheat is rained on before harvest, or from late maturity alpha-amylase (LMA) when grain experiences cool temperatures during the soft dough stage of grain maturation (Zadoks growth stage 85). An initial LMA-induction experiment found that low FN was associated with premature visible germination, suggesting that cool and humid conditions caused vivipary.

Methods

To examine whether LMA and vivipary are related, controlled environment experiments examined the conditions that induce vivipary, whether LMA could be induced without vivipary, and whether the pattern of alpha-amylase expression during vivipary better resembled PHS or LMA.

Results

Vivipary was induced in the soft to hard dough stages of grain development (Zadok's stages 83-87) both on agar and after misting of the mother plant. This premature germination was associated with elevated alpha-amylase activity. Vivipary was more strongly induced under the cooler conditions used for LMA-induction (18°C day/7.5°C night) than warmer conditions (25°C day/18°C night). Cool temperatures could induce LMA with little or no visible germination when low humidity was maintained, and susceptibility to vivipary was not always associated with LMA susceptibility in a panel of 8 varieties. Mature grain preharvest sprouting results in much higher alpha-amylase levels at the embryo-end of the kernel. In contrast, vivipary resulted in a more even distribution of alpha-amylase that was reminiscent of LMA.

Discussion

Vivipary can occur in susceptible varieties under moist, cool conditions, and the resulting alpha-amylase activity may result in low FN problems when a farm experiences cool, rainy conditions before the crop is mature. While there are genotypic differences in LMA and vivipary susceptibility, overlapping mechanisms are likely involved since they are similarly controlled by temperature and growth stage, and result in similar patterns of alpha-amylase expression.

Genetics of a diverse soft winter wheat population for pre-harvest sprouting, agronomic, and flour quality traits

Soft winter wheat has been adapted to the north-central, north-western, and south-central United States over hundreds of years for optimal yield, height, heading date, and pathogen and pest resistance. Environmental factors like weather affect abiotic traits such as pre-harvest sprouting resistance. However, pre-harvest sprouting has rarely been a target for breeding. Owing to changing weather patterns from climate change, pre-harvest sprouting resistance is needed to prevent significant crop losses not only in the United States, but worldwide. Twenty-two traits including age of breeding line as well as agronomic, flour quality, and pre-harvest sprouting traits were studied in a population of 188 lines representing genetic diversity over 200 years of soft winter wheat breeding. Some traits were correlated with one another by principal components analysis and Pearson's correlations. A genome-wide association study using 1,978 markers uncovered a total of 102 regions encompassing 226 quantitative trait nucleotides. Twenty-six regions overlapped multiple traits with common significant markers. Many of these traits were also found to be correlated by Pearson's correlation and principal components analyses. Most pre-harvest sprouting regions were not co-located with agronomic traits and thus useful for crop improvement against climate change without affecting crop performance. Six different genome-wide association statistical models (GLM, MLM, MLMM, FarmCPU, BLINK, and SUPER) were utilized to search for reasonable models to analyze soft winter wheat populations with increased markers and/or breeding lines going forward. Some flour quality and agronomic traits seem to have been selected over time, but not pre-harvest sprouting. It appears possible to select for pre-harvest sprouting resistance without impacting flour quality or the agronomic value of soft winter wheat.

Genetic analysis of global faba bean diversity, agronomic traits and selection signatures

KEY MESSAGE

We identified marker-trait associations for key faba bean agronomic traits and genomic signatures of selection within a global germplasm collection. Faba bean (Vicia faba L.) is a high-protein grain legume crop with great potential for sustainable protein production. However, little is known about the genetics underlying trait diversity. In this study, we used 21,345 high-quality SNP markers to genetically characterize 2678 faba bean genotypes. We performed genome-wide association studies of key agronomic traits using a seven-parent-MAGIC population and detected 238 significant marker-trait associations linked to 12 traits of agronomic importance. Sixty-five of these were stable across multiple environments. Using a non-redundant diversity panel of 685 accessions from 52 countries, we identified three subpopulations differentiated by geographical origin and 33 genomic regions subjected to strong diversifying selection between subpopulations. We found that SNP markers associated with the differentiation of northern and southern accessions explained a significant proportion of agronomic trait variance in the seven-parent-MAGIC population, suggesting that some of these traits were targets of selection during breeding. Our findings point to genomic regions associated with important agronomic traits and selection, facilitating faba bean genomics-based breeding.

GWAS and genomic prediction for pre-harvest sprouting tolerance involving sprouting score and two other related traits in spring wheat

In wheat, a genome-wide association study (GWAS) and genomic prediction (GP) analysis were conducted for pre-harvest sprouting (PHS) tolerance and two of its related traits. For this purpose, an association panel of 190 accessions was phenotyped for PHS (using sprouting score), falling number, and grain color over two years and genotyped with 9904 DArTseq based SNP markers. GWAS for main-effect quantitative trait nucleotides (M-QTNs) using three different models (CMLM, SUPER, and FarmCPU) and epistatic QTNs (E-QTNs) using PLINK were performed. A total of 171 M-QTNs (CMLM, 47; SUPER, 70; FarmCPU, 54) for all three traits, and 15 E-QTNs involved in 20 first-order epistatic interactions were identified. Some of the above QTNs overlapped the previously reported QTLs, MTAs, and cloned genes, allowing delineating 26 PHS-responsive genomic regions that spread over 16 wheat chromosomes. As many as 20 definitive and stable QTNs were considered important for use in marker-assisted recurrent selection (MARS). The gene, TaPHS1, for PHS tolerance (PHST) associated with one of the QTNs was also validated using the KASP assay. Some of the M-QTNs were shown to have a key role in the abscisic acid pathway involved in PHST. Genomic prediction accuracies (based on the cross-validation approach) using three different models ranged from 0.41 to 0.55, which are comparable to the results of previous studies. In summary, the results of the present study improved our understanding of the genetic architecture of PHST and its related traits in wheat and provided novel genomic resources for wheat breeding based on MARS and GP.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01357-5.

Pyramiding wheat pre-harvest sprouting resistance genes in triticale breeding

Pre -harvest sprouting (PHS) is an important problem in cereal production reducing yield and grain quality. After decades of improvement, triticale remains particularly susceptible to PHS but no resistance genes or QTLs were identified so far in this species. As wheat shares the A and B genomes with triticale, wheat PHS resistance genes can be introgressed into triticale genome by recombination after interspecific crosses. In this project, three PHS resistance genes have been transferred from wheat to triticale by marker-assisted interspecific crosses, followed by four backcrosses. The gene TaPHS1 from the 3AS chromosome of cultivar Zenkoujikomugi (Zen) and the TaMKK3 and TaQsd1, respectively located on the 4AL and 5BL chromosomes derived both from cultivar Aus1408, were pyramided in the triticale cultivar Cosinus. Only the TaPHS1 gene increases consistently the PHS resistance in triticale. The lack of efficacy of the other two genes, especially TaQsd1, could be the result of an imperfect linkage between the marker and the gene of interest. The introduction of PHS resistance genes did not alter agronomic nor disease resistance performances of triticale. This approach leads to two new, agronomically performant and PHS-resistant triticale cultivars. Today, two breeding triticale lines are ready to enter the official registration process.

Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding

In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.

Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding

In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.

Genome-wide association mapping of Hagberg falling number, protein content, test weight, and grain yield in U.K. wheat

Association mapping using crop cultivars allows identification of genetic loci of direct relevance to breeding. Here, 150 U.K. wheat (Triticum aestivum L.) cultivars genotyped with 23,288 single nucleotide polymorphisms (SNPs) were used for genome-wide association studies (GWAS) using historical phenotypic data for grain protein content, Hagberg falling number (HFN), test weight, and grain yield. Power calculations indicated experimental design would enable detection of quantitative trait loci (QTL) explaining ≥20% of the variation (PVE) at a relatively high power of >80%, falling to 40% for detection of a SNP with an R² ≥ .5 with the same QTL. Genome-wide association studies identified marker-trait associations for all four traits. For HFN (h ² = .89), six QTL were identified, including a major locus on chromosome 7B explaining 49% PVE and reducing HFN by 44 s. For protein content (h ² = 0.86), 10 QTL were found on chromosomes 1A, 2A, 2B, 3A, 3B, and 6B, together explaining 48.9% PVE. For test weight, five QTL were identified (one on 1B and four on 3B; 26.3% PVE). Finally, 14 loci were identified for grain yield (h ² = 0.95) on eight chromosomes (1A, 2A, 2B, 2D, 3A, 5B, 6A, 6B; 68.1% PVE), of which five were located within 16 Mbp of genetic regions previously identified as under breeder selection in European wheat. Our study demonstrates the utility of exploiting historical crop datasets, identifying genomic targets for independent validation, and ultimately for wheat genetic improvement.

As the number falls, alternatives to the Hagberg-Perten falling number method: A review

This review examines the application, limitations, and potential alternatives to the Hagberg-Perten falling number (FN) method used in the global wheat industry for detecting the risk of poor end-product quality mainly due to starch degradation by the enzyme α-amylase. By viscometry, the FN test indirectly detects the presence of α-amylase, the primary enzyme that digests starch. Elevated α-amylase results in low FN and damages wheat product quality resulting in cakes that fall, and sticky bread and noodles. Low FN can occur from preharvest sprouting (PHS) and late maturity α-amylase (LMA). Moist or rainy conditions before harvest cause PHS on the mother plant. Continuously cool or fluctuating temperatures during the grain filling stage cause LMA. Due to the expression of additional hydrolytic enzymes, PHS has a stronger negative impact than LMA. Wheat grain with low FN/high α-amylase results in serious losses for farmers, traders, millers, and bakers worldwide. Although blending of low FN grain with sound wheat may be used as a means of moving affected grain through the marketplace, care must be taken to avoid grain lots from falling below contract-specified FN. A large amount of sound wheat can be ruined if mixed with a small amount of sprouted wheat. The FN method is widely employed to detect α-amylase after harvest. However, it has several limitations, including sampling variability, high cost, labor intensiveness, the destructive nature of the test, and an inability to differentiate between LMA and PHS. Faster, cheaper, and more accurate alternatives could improve breeding for resistance to PHS and LMA and could preserve the value of wheat grain by avoiding inadvertent mixing of high- and low-FN grain by enabling testing at more stages of the value stream including at harvest, delivery, transport, storage, and milling. Alternatives to the FN method explored here include the Rapid Visco Analyzer, enzyme assays, immunoassays, near-infrared spectroscopy, and hyperspectral imaging.

Interpretation of Manhattan Plots and Other Outputs of Genome-Wide Association Studies

With increasing marker density, estimation of recombination rate between a marker and a causal mutation using linkage analysis becomes less important. Instead, linkage disequilibrium (LD) becomes the major indicator for gene mapping through genome-wide association studies (GWAS). In addition to the linkage between the marker and the causal mutation, many other factors may contribute to the LD, including population structure and cryptic relationships among individuals. As statistical methods and software evolve to improve statistical power and computing speed in GWAS, the corresponding outputs must also evolve to facilitate the interpretation of input data, the analytical process, and final association results. In this chapter, our descriptions focus on (1) considerations in creating a Manhattan plot displaying the strength of LD and locations of markers across a genome; (2) criteria for genome-wide significance threshold and the different appearance of Manhattan plots in single-locus and multiple-locus models; (3) exploration of population structure and kinship among individuals; (4) quantile-quantile (QQ) plot; (5) LD decay across the genome and LD between the associated markers and their neighbors; (6) exploration of individual and marker information on Manhattan and QQ plots via interactive visualization using HTML. The ultimate objective of this chapter is to help users to connect input data to GWAS outputs to balance power and false positives, and connect GWAS outputs to the selection of candidate genes using LD extent.

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.

Over-Expression of a Wheat Late Maturity Alpha-Amylase Type 1 Impact on Starch Properties During Grain Development and Germination

The hydrolysis of starch is a complex process that requires synergistic action of multiple hydrolytic enzymes, including α-amylases. Wheat over-expression of TaAmy1, driven by seed specific promoter, resulted in a 20- to 230-fold total α-amylase activity in mature grains. Ectopic expression of TaAmy1 showed a significant elevated α-amylase activity in stem and leaf without consequences on transitory starch. In mature grain, overexpressed TaAMY1 was mainly located in the endosperm with high expression of TaAmy1. This is due to early developing grains having effect on starch granules from 18 days post-anthesis (DPA) and on soluble sugar accumulation from 30 DPA. While accumulation of TaAMY1 led to a high degree of damaged starch in grain, the dramatic alterations of starch visco-properties caused by the elevated levels of α-amylase essentially occurred during processing, thus suggesting a very small impact of related starch damage on grain properties. Abnormal accumulation of soluble sugar (α-gluco-oligosaccharide and sucrose) by TaAMY1 over-expression reduced the grain dormancy and enhanced abscisic acid (ABA) resistance. Germination study in the presence of α-amylase inhibitor suggested a very limited role of TaAMY1 in the early germination process and starch conversion into soluble sugars.

Phenotypic Evaluation and Genetic Analysis of Seedling Emergence in a Global Collection of Wheat Genotypes (Triticum aestivum L.) Under Limited Water Availability

The challenge in establishing an early-sown wheat crop in southern Australia is the need for consistently high seedling emergence when sowing deep in subsoil moisture (>10 cm) or into dry top-soil (4 cm). However, the latter is strongly reliant on a minimum soil water availability to ensure successful seedling emergence. This study aimed to: (1) evaluate 233 Australian and selected international wheat genotypes for consistently high seedling emergence under limited soil water availability when sown in 4 cm of top-soil in field and glasshouse (GH) studies; (2) ascertain genetic loci associated with phenotypic variation using a genome-wide association study (GWAS); and (3) compare across loci for traits controlling coleoptile characteristics, germination, dormancy, and pre-harvest sprouting. Despite significant (P < 0.001) environment and genotype-by-environment interactions within and between field and GH experiments, eight genotypes that included five cultivars, two landraces, and one inbred line had consistently high seedling emergence (mean value > 85%) across nine environments. Moreover, 21 environment-specific quantitative trait loci (QTL) were detected in GWAS analysis on chromosomes 1B, 1D, 2B, 3A, 3B, 4A, 4B, 5B, 5D, and 7D, indicating complex genetic inheritance controlling seedling emergence. We aligned QTL for known traits and individual genes onto the reference genome of wheat and identified 16 QTL for seedling emergence in linkage disequilibrium with coleoptile length, width, and cross-sectional area, pre-harvest sprouting and dormancy, germination, seed longevity, and anthocyanin development. Therefore, it appears that seedling emergence is controlled by multifaceted networks of interrelated genes and traits regulated by different environmental cues.

Late-maturity α-amylase (LMA): exploring the underlying mechanisms and end-use quality effects in wheat

MAIN CONCLUSION

A comprehensive understanding of LMA from the underlying molecular aspects to the end-use quality effects will greatly benefit the global wheat industry and those whose livelihoods depend upon it. Late-maturity α-amylase (LMA) leads to the expression and protein accumulation of high pI α-amylases during late grain development. This α-amylase is maintained through harvest and leads to an unacceptable low falling number (FN), the wheat industry's standard measure for predicting end-use quality. Unfortunately, low FN leads to significant financial losses for growers. As a result, wheat researchers are working to understand and eliminate LMA from wheat breeding programs, with research aims that include unraveling the genetic, biochemical, and physiological mechanisms that lead to LMA expression. In addition, cereal chemists and quality scientists are working to determine if and how LMA-affected grain impacts end-use quality. This review is a comprehensive overview of studies focused on LMA and includes open questions and future directions.

Physical mapping of QTL associated with agronomic and end-use quality traits in spring wheat under conventional and organic management systems

Using phenotypic data of four biparental spring wheat populations evaluated at multiple environments under two management systems, we discovered 152 QTL and 22 QTL hotspots, of which two QTL accounted for up to 37% and 58% of the phenotypic variance, consistently detected in all environments, and fell within genomic regions harboring known genes. Identification of the physical positions of quantitative trait loci (QTL) would be highly useful for developing functional markers and comparing QTL results across multiple independent studies. The objectives of the present study were to map and characterize QTL associated with nine agronomic and end-use quality traits (tillering ability, plant height, lodging, grain yield, grain protein content, thousand kernel weight, test weight, sedimentation volume, and falling number) in hard red spring wheat recombinant inbred lines (RILs) using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map. We evaluated a total of 698 RILs from four populations derived from crosses involving seven parents at 3-8 conventionally (high N) and organically (low N) managed field environments. Using the phenotypic data combined across all environments per management, and the physical map between 1058 and 6526 markers per population, we identified 152 QTL associated with the nine traits, of which 29 had moderate and 2 with major effects. Forty-nine of the 152 QTL mapped across 22 QTL hotspot regions with each region coincident to 2-6 traits. Some of the QTL hotspots were physically located close to known genes. QSv.dms-1A and QPht.dms-4B.1 individually explained up to 37% and 58% of the variation in sedimentation volume and plant height, respectively, and had very large LOD scores that varied from 19.0 to 35.7 and from 16.7 to 55.9, respectively. We consistently detected both QTL in the combined and all individual environments, laying solid ground for further characterization and possibly for cloning.

Integrating GWAS and transcriptomics to identify genes involved in seed dormancy in rice

Several QTLs and genes responsible for seed dormancy were detected and SNP candidates were shown to cause changes in seed germination. Seed dormancy is a key agricultural trait to prevent pre-harvest sprouting in crop plants such as rice (Oryza sativa L.), wheat (Triticum aestivum), and barley (Hordeum vulgare L.). However, our knowledge of seed dormancy is hampered by the complexities of studying a trait that changes over time after seed harvest, and is complicated by interactions between phytohormones, seed coat components and the environment. Here, we have conducted a genome-wide association study using a panel of 311 natural accessions of cultivated rice, examining a total of 519,158 single nucleotide polymorphisms (SNPs). Eight quantitative trait loci (QTLs) were found to associate with seed dormancy in the whole panel and five in the Japonica and Indica subpanel; expression of candidate genes within 100 kb of each QTL was examined in two published, germination-specific transcriptomic datasets. Ten candidate genes, differentially expressed within the first four days post-imbibition, were identified. Five of these genes had previously been associated with awn length, heading date, yield, and spikelet length phenotypes. Two candidates were validated using Quantitative Reverse Transcription (qRT)-PCR. In addition, previously identified genes involved in hormone signaling during germination were found to be differentially expressed between a japonica and an indica line; SNPs in the promoter of Os9BGlu33 were associated with germination index, with qRT-PCR validation. Collectively, our results are useful for future characterization of seed dormancy mechanism and crop improvement, and suggest haplotypes for further analysis that may be of use to boost PHS resistance in rice.

Development of a Raspberry Pi-Based Sensor System for Automated In-Field Monitoring to Support Crop Breeding Programs

Sensor applications for plant phenotyping can advance and strengthen crop breeding programs. One of the powerful sensing options is the automated sensor system, which can be customized and applied for plant science research. The system can provide high spatial and temporal resolution data to delineate crop interaction with weather changes in a diverse environment. Such a system can be integrated with the internet to enable the internet of things (IoT)-based sensor system development for real-time crop monitoring and management. In this study, the Raspberry Pi-based sensor (imaging) system was fabricated and integrated with a microclimate sensor to evaluate crop growth in a spring wheat breeding trial for automated phenotyping applications. Such an in-field sensor system will increase the reproducibility of measurements and improve the selection efficiency by investigating dynamic crop responses as well as identifying key growth stages (e.g., heading), assisting in the development of high-performing crop varieties. In the low-cost system developed here-in, a Raspberry Pi computer and multiple cameras (RGB and multispectral) were the main components. The system was programmed to automatically capture and manage the crop image data at user-defined time points throughout the season. The acquired images were suitable for extracting quantifiable plant traits, and the images were automatically processed through a Python script (an open-source programming language) to extract vegetation indices, representing crop growth and overall health. Ongoing efforts are conducted towards integrating the sensor system for real-time data monitoring via the internet that will allow plant breeders to monitor multiple trials for timely crop management and decision making.

Identification of QTLs and a Candidate Gene for Reducing Pre-Harvest Sprouting in Aegilops tauschii-Triticum aestivum Chromosome Segment Substitution Lines

Wheat pre-harvest sprouting (PHS) causes serious losses in wheat yield. In this study, precise mapping was carried out in the chromosome segment substitution lines (CSSL) F₂ population generated by a direct cross of Zhoumai 18 (PHS-sensitive) and Aegilops tauschii accession T093 (highly PHS-resistant). Three Ae. tauschii-derived quantitative trait loci (QTLs), QDor.3D.1, QDor.3D.2, and QDor.3D.3, were detected on chromosome 3DL using four simple sequence repeats (SSR) markers and 10 developed Kompetitive allele-specific PCR (KASP) markers. Alongside these QTL results, the RNA-Seq and qRT-PCR analysis revealed expression levels of TraesCS3D01G466100 in the QDor.3D.2 region that were significantly higher in CSSLs 495 than in Zhoumai 18 during the seed imbibition treatment. The cDNA sequencing results of TraesCS3D01G466100 showed two single nucleotide polymorphisms (SNPs), resulting in two changed amino acid substitutions between Zhoumai 18 and line 495, and the 148 nt amino acid substitution of TraesCS3D01G466100, derived from Ae. tauschii T093, which may play an important role in the functioning of ubiquitin ligase enzymes 3 (E3) according to the homology protein analysis, which could lead to differential PHS-resistance phenotypes. Taken together, our results may foster a better understanding of the mechanism of PHS resistance and are potentially valuable for marker-assisted selection in practical wheat breeding efforts.

Seed Dormancy and Preharvest Sprouting in Quinoa (Chenopodium quinoa Willd.)

Quinoa (Chenopodium quinoa Willd.) is a culturally significant staple food source that has been grown for thousands of years in South America. Due to its natural drought and salinity tolerance, quinoa has emerged as an agronomically important crop for production in marginal soils, in highly variable climates, and as part of diverse crop rotations. Primary areas of quinoa research have focused on improving resistance to abiotic stresses and disease, improving yields, and increasing nutrition. However, an evolving issue impacting quinoa seed end-use quality is preharvest sprouting (PHS), which is when seeds with little to no dormancy experience a rain event prior to harvest and sprout on the panicle. Far less is understood about the mechanisms that regulate quinoa seed dormancy and seed viability. This review will cover topics including seed dormancy, orthodox and unorthodox dormancy programs, desiccation sensitivity, environmental and hormonal mechanisms that regulate seed dormancy, and breeding and non-breeding strategies for enhancing resistance to PHS in quinoa.

A Major Locus on Wheat Chromosome 7B Associated With Late-Maturity α-Amylase Encodes a Putative ent-Copalyl Diphosphate Synthase

Many wheat varieties have the potential to develop unacceptably high levels of α-amylase in the grains if exposed to a cool temperature shock or simply cool temperature during the early to middle stages of grain filling. This phenomenon is referred to as late maturity α-amylase (LMA). The enzyme persists in the grain until harvest and may result in wheat with a low Falling Number that does not meet receival and export specifications. Resistance to LMA is therefore a valuable target for wheat breeders and wheat industries in general. Genetic evidence implicating a locus on the long arm of chromosome 7B in variation in LMA phenotype was confirmed in this investigation. Through intensive fine-mapping an ent-copalyl diphosphate synthase (CPS), hitherto named LMA-1, was identified as the likely candidate gene associated with variation in LMA phenotype. Single Nucleotide Polymorphisms (SNPs) within the LMA-1 coding sequence of Chinese Spring, Maringa and Halberd result in either prematurely terminated or functionally altered proteins that are associated with useful levels of resistance to LMA. LMA-1 transcripts detected in de-embryonated grain tissue from around 15 days after anthesis, several days before the synthesis of α-amylase, were low in the resistant varieties Chinese Spring and Maringa compared with LMA susceptible genotype Spica. This was associated with a dramatic reduction in the concentrations of intermediates in the gibberellin biosynthesis pathway such as GA₁₉, evidence that LMA-1 was functioning as CPS in the gibberellin biosynthesis pathway. A survey of a large collection of Australian and international wheat varieties distinguished 9 major haplotypes at the LMA-1 locus. Generally, within classes, there was notable variation for LMA phenotype and evidence for genotypes whose resistance is presumed to be due to genetic loci located elsewhere on the wheat genome. Further investigation is required to characterize the sequence of steps between LMA-1 and α-amylase synthesis as well as to gain a better understanding of the role and potential impact of other genetic loci. Diagnostic markers for sources of resistance and SNP variation reported in this study should assist breeders to deploy resistance associated with LMA-1 variants in breeding programs.

Genome-Wide Linkage Mapping for Preharvest Sprouting Resistance in Wheat Using 15K Single-Nucleotide Polymorphism Arrays

Preharvest sprouting (PHS) significantly reduces grain yield and quality. Identification of genetic loci for PHS resistance will facilitate breeding sprouting-resistant wheat cultivars. In this study, we constructed a genetic map comprising 1,702 non-redundant markers in a recombinant inbred line (RIL) population derived from cross Yangxiaomai/Zhongyou9507 using the wheat 15K single-nucleotide polymorphism (SNP) assay. Four quantitative trait loci (QTL) for germination index (GI), a major indicator of PHS, were identified, explaining 4.6-18.5% of the phenotypic variances. Resistance alleles of Qphs.caas-3AL, Qphs.caas-3DL, and Qphs.caas-7BL were from Yangxiaomai, and Zhongyou9507 contributed a resistance allele in Qphs.caas-4AL. No epistatic effects were detected among the QTL, and combined resistance alleles significantly increased PHS resistance. Sequencing and linkage mapping showed that Qphs.caas-3AL and Qphs.caas-3DL corresponded to grain color genes Tamyb10-A and Tamyb10-D, respectively, whereas Qphs.caas-4AL and Qphs.caas-7BL were probably new QTL for PHS. We further developed cost-effective, high-throughput kompetitive allele-specific PCR (KASP) markers tightly linked to Qphs.caas-4AL and Qphs.caas-7BL and validated their association with GI in a test panel of cultivars. The resistance alleles at the Qphs.caas-4AL and Qphs.caas-7BL loci were present in 72.2 and 16.5% cultivars, respectively, suggesting that the former might be subjected to positive selection in wheat breeding. The findings provide not only genetic resources for PHS resistance but also breeding tools for marker-assisted selection.

Artificial selection in breeding extensively enriched a functional allelic variation in TaPHS1 for pre-harvest sprouting resistance in wheat

Pre-harvest sprouting (PHS) causes significant losses in wheat yield and quality worldwide. Previously, we cloned a PHS resistance gene, TaPHS1, and identified two causal mutations for reduced seed dormancy (SD) and increased PHS susceptibility. Here we identified a novel allelic variation of C to T transition in 3'-UTR of TaPHS1, which associated with reduced SD and PHS resistance. The T allele occurred in wild wheat progenitors and was likely the earliest functional mutation in TaPHS1 for PHS susceptibility. Allele frequency analysis revealed low frequency of the T allele in wild diploid and tetraploid wheat progenitors, but very high frequency in modern wheat cultivars and breeding lines, indicating that artificial selection quickly enriched the T allele during modern breeding. The T allele was significantly associated with short SD in both T. aestivum and T. durum, the two most cultivated species of wheat. This variation together with previously reported functional sequence variations co-regulated TaPHS1 expression levels and PHS resistance in different germplasms. Haplotype analysis of the four functional variations identified the best PHS resistance haplotype of TaPHS1. The resistance haplotype can be used in marker-assisted selection to transfer TaPHS1 to new wheat cultivars.

Exome sequencing of bulked segregants identified a novel TaMKK3-A allele linked to the wheat ERA8 ABA-hypersensitive germination phenotype

Using bulked segregant analysis of exome sequence, we fine-mapped the ABA-hypersensitive mutant ERA8 in a wheat backcross population to the TaMKK3-A locus of chromosome 4A. Preharvest sprouting (PHS) is the germination of mature grain on the mother plant when it rains before harvest. The ENHANCED RESPONSE TO ABA8 (ERA8) mutant increases seed dormancy and, consequently, PHS tolerance in soft white wheat 'Zak.' ERA8 was mapped to chromosome 4A in a Zak/'ZakERA8' backcross population using bulked segregant analysis of exome sequenced DNA (BSA-exome-seq). ERA8 was fine-mapped relative to mutagen-induced SNPs to a 4.6 Mb region containing 70 genes. In the backcross population, the ERA8 ABA-hypersensitive phenotype was strongly linked to a missense mutation in TaMKK3-A-G1093A (LOD 16.5), a gene associated with natural PHS tolerance in barley and wheat. The map position of ERA8 was confirmed in an 'Otis'/ZakERA8 but not in a 'Louise'/ZakERA8 mapping population. This is likely because Otis carries the same natural PHS susceptible MKK3-A-A660^S allele as Zak, whereas Louise carries the PHS-tolerant MKK3-A-C660^R allele. Thus, the variation for grain dormancy and PHS tolerance in the Louise/ZakERA8 population likely resulted from segregation of other loci rather than segregation for PHS tolerance at the MKK3 locus. This inadvertent complementation test suggests that the MKK3-A-G1093A mutation causes the ERA8 phenotype. Moreover, MKK3 was a known ABA signaling gene in the 70-gene 4.6 Mb ERA8 interval. None of these 70 genes showed the differential regulation in wild-type Zak versus ERA8 expected of a promoter mutation. Thus, the working model is that the ERA8 phenotype results from the MKK3-A-G1093A mutation.

Late-maturity α-amylase expression in wheat is influenced by genotype, temperature and stage of grain development

Late-maturity α-amylase (LMA) expression in wheat grains can be induced by either a cool temperature shock close to physiological maturity or continuous cool maximum temperatures during grain development. Late-maturity α-amylase (LMA) is a genetic trait in wheat (Triticum aestivum L.) involving the production of α-amylase during grain development, which can result in an unacceptably low Falling Number (FN) in mature grain and consequent grain downgrading. Comparison of the FN test, an α-amylase activity assay and a high pI α-amylase-specific ELISA on the same meal samples gave equivalent results; ELISA was used for further experiments because of its isoform specificity. A cool temperature shock during the middle stages of grain development is known to induce LMA and is used for phenotypic screening. It was determined that a cool temperature treatment of seven days was required to reliably induce LMA. Glasshouse studies performed in summer and winter demonstrated that temperature affected the timing of sensitivity to cool-shock by altering the rate and duration of grain development, but that the sensitive grain developmental stage was unchanged at 35-45% moisture content. Wheat varieties with Rht-B1b or Rht-D1b dwarfing genes responded to a cool-shock only from mid grain filling until physiological maturity, whilst genotypes with Rht8c or without a dwarfing gene expressed LMA in response to a cool-shock during a wider developmental range. A continuous cool maximum temperature regimen (23 °C/15 °C day/night) during grain development also resulted in LMA expression and showed a stronger association with field expression than the cool-shock treatment. These results clarify how genotype, temperature and grain developmental stage determine LMA expression, and allow for the improvement of LMA phenotypic screening methods.

Strong temporal dynamics of QTL action on plant growth progression revealed through high-throughput phenotyping in canola

A major challenge of plant biology is to unravel the genetic basis of complex traits. We took advantage of recent technical advances in high-throughput phenotyping in conjunction with genome-wide association studies to elucidate genotype-phenotype relationships at high temporal resolution. A diverse Brassica napus population from a commercial breeding programme was analysed by automated non-invasive phenotyping. Time-resolved data for early growth-related traits, including estimated biovolume, projected leaf area, early plant height and colour uniformity, were established and complemented by fresh and dry weight biomass. Genome-wide SNP array data provided the framework for genome-wide association analyses. Using time point data and relative growth rates, multiple robust main effect marker-trait associations for biomass and related traits were detected. Candidate genes involved in meristem development, cell wall modification and transcriptional regulation were detected. Our results demonstrate that early plant growth is a highly complex trait governed by several medium and many small effect loci, most of which act only during short phases. These observations highlight the importance of taking the temporal patterns of QTL/allele actions into account and emphasize the need for detailed time-resolved analyses to effectively unravel the complex and stage-specific contributions of genes affecting growth processes that operate at different developmental phases.

Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping

Kernel size-related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P < 2.25 × 10^-6 ) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P < 1 × 10^-3 ) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable-effect SNPs and the co-localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co-localized SNPs, of which zma-miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1, CUC2 and NAC6 in vitro. Overexpression of zma-miR164e resulted in the down-regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker-assisted selection (MAS) for high-yield breeding in maize.

Potential Effects of Awn Length Variation on Seed Yield and Components, Seed Dispersal and Germination Performance in Siberian Wildrye (Elymus sibiricus L.)

: Awns, needle-like structures formed on the distal of the lemmas in the florets, are of interest because of their essential roles in seed dispersal, germination and photosynthesis. Previous research has reported the potential benefits of awns in major cereal grasses, yet reports on the agronomic and economic implications of awn length variation in forage grasses remain scarce. This study investigated the variation of awn length among 20 Siberian wildrye populations and the effect of awn length on seed yield and yield components. This work then studied the impact of awn length on seed dispersal and germination. The analyses indicated a high level of awn length variation among populations. Awn length showed a significant influence on harvested seed yield per plant (p < 0.05) mostly driven by interactions between awn length and the majority of seed yield components. Principal component analysis clearly revealed that the final impact of awn length on seed yield depends on the balance of its positive and negative effects on traits determining seed yield. Furthermore, awn length tended to increase seed dispersal distance, although little diversity in the nature of this progression was observed in some populations. Awn length exhibited a significant relationship (p < 0.05) with germination percentage. It also tended to shorten germination duration, although this interaction was not statistically significant. Collectively, these results provide vital information for breeding and agronomic programs aiming to maintain yield in grasses. This is the first report to demonstrate in Siberian wildrye the agronomic impacts of awn length variation.

Genome-wide association study of pre-harvest sprouting tolerance using a 90K SNP array in common wheat (Triticum aestivum L.)

Three major loci for pre-harvest sprouting tolerance (PHST) were mapped on chromosomes 1AL, 3BS, and 6BL, and two CAPS and one dCAPS markers were validated. Sixteen lines with favorable alleles and increased PHST were identified. Pre-harvest sprouting (PHS) significantly affects wheat grain yield and quality. In the present study, the PHS tolerance (PHST) of 192 wheat varieties (lines) was evaluated by assessment of field sprouting, seed germination index, and period of dormancy in different environments. A high-density Illumina iSelect 90K SNP array was used to genotype the panel. A genome-wide association study (GWAS) based on single- and multi-locus mixed linear models was used to detect loci for PHST. The single-locus model identified 23 loci for PHST (P < 0.0001) and explained 6.0-18.9% of the phenotypic variance. Twenty loci were consistent with known quantitative trait loci (QTLs). Three single-nucleotide polymorphism markers closely linked with three major loci (Qphs.ahau-1A, Qphs.ahau-3B, and Qphs.ahau-6B) on chromosomes 1AL, 3BS, and 6BL, respectively, were converted to two cleaved amplified polymorphic sequences (CAPS) and one derived-CAPS markers, and validated in 374 wheat varieties (lines). The CAPS marker EX06323 for Qphs.ahau-6B co-segregated with a novel major QTL underlying PHST in a recombinant inbred line population raised from the cross Jing 411 × Wanxianbaimaizi. Linear regression showed a clear dependence of PHST on the number of favorable alleles. Sixteen varieties showing an elevated degree of PHST were identified and harbored more than 16 favorable alleles. The multi-locus model detected 39 marker-trait associations for PHST (P < 0.0001), of which five may be novel. Six loci common to the two models were identified. The combination of the two GWAS methods contributes to efficient dissection of the complex genetic mechanism of PHST.

A genome-wide association study identified loci for yield component traits in sugarcane (Saccharum spp.)

Sugarcane (Saccharum spp.) has a complex genome with variable ploidy and frequent aneuploidy, which hampers the understanding of phenotype and genotype relations. Despite this complexity, genome-wide association studies (GWAS) may be used to identify favorable alleles for target traits in core collections and then assist breeders in better managing crosses and selecting superior genotypes in breeding populations. Therefore, in the present study, we used a diversity panel of sugarcane, called the Brazilian Panel of Sugarcane Genotypes (BPSG), with the following objectives: (i) estimate, through a mixed model, the adjusted means and genetic parameters of the five yield traits evaluated over two harvest years; (ii) detect population structure, linkage disequilibrium (LD) and genetic diversity using simple sequence repeat (SSR) markers; (iii) perform GWAS analysis to identify marker-trait associations (MTAs); and iv) annotate the sequences giving rise to SSR markers that had fragments associated with target traits to search for putative candidate genes. The phenotypic data analysis showed that the broad-sense heritability values were above 0.48 and 0.49 for the first and second harvests, respectively. The set of 100 SSR markers produced 1,483 fragments, of which 99.5% were polymorphic. These SSR fragments were useful to estimate the most likely number of subpopulations, found to be four, and the LD in BPSG, which was stronger in the first 15 cM and present to a large extension (65 cM). Genetic diversity analysis showed that, in general, the clustering of accessions within the subpopulations was in accordance with the pedigree information. GWAS performed through a multilocus mixed model revealed 23 MTAs, six, three, seven, four and three for soluble solid content, stalk height, stalk number, stalk weight and cane yield traits, respectively. These MTAs may be validated in other populations to support sugarcane breeding programs with introgression of favorable alleles and marker-assisted selection.

Genome-wide association study and quantitative trait loci mapping of seed dormancy in common wheat (Triticum aestivum L.)

Totally, 23 and 26 loci for the first count germination ratio and the final germination ratio were detected by quantitative trait loci (QTL) mapping and association mapping, respectively, which could be used to facilitate wheat pre-harvest sprouting breeding. Weak dormancy can cause pre-harvest sprouting in seeds of common wheat which significantly reduces grain yield. In this study, both quantitative trait loci (QTL) mapping and genome-wide association study (GWAS) were used to identify loci controlling seed dormancy. The analyses were based on a recombinant inbred line population derived from Zhou 8425B/Chinese Spring cross and 166 common wheat accessions. Inclusive composite interval mapping detected 8 QTL, while 45 loci were identified in the 166 wheat accessions by GWAS. Among these, four loci (Q_bifcgr.cas-3AS/Qfcgr.cas-3AS, Q_bifcgr.cas-6AL.1/Qfcgr.cas-6AL.1, Q_bifcgr.cas-7BL.2/Qfcgr.cas-7BL.2, and Q_bigr.cas-3DL/Qgr.cas-3DL) were detected in both QTL mapping and GWAS. In addition, 41 loci co-located with QTL reported previously, whereas 8 loci (Qfcgr.cas-5AL, Qfcgr.cas-6DS, Qfcgr.cas-7AS, Qgr.cas-3DS.1, Qgr.cas-3DS.2, Q_bigr.cas-3DL/Qgr.cas-3DL, Qgr.cas-4B, and Qgr.cas-5A) were likely to be new. Linear regression showed the first count germination ratio or the final germination ratio reduced while multiple favorable alleles increased. It is suggested that QTL pyramiding was effective to reduce pre-harvest sprouting risk. This study could enrich the research on pre-harvest sprouting and provide valuable information of marker exploration for wheat breeding programs.

Genetic Dissection of Snow Mold Tolerance in US Pacific Northwest Winter Wheat Through Genome-Wide Association Study and Genomic Selection

Snow mold is a yield-limiting disease of wheat in the Pacific Northwest (PNW) region of the US, where there is prolonged snow cover. The objectives of this study were to identify genomic regions associated with snow mold tolerance in a diverse panel of PNW winter wheat lines in a genome-wide association study (GWAS) and to evaluate the usefulness of genomic selection (GS) for snow mold tolerance. An association mapping panel (AMP; N = 458 lines) was planted in Mansfield and Waterville, WA in 2017 and 2018 and genotyped using the Illumina^® 90K single nucleotide polymorphism (SNP) array. GWAS identified 100 significant markers across 17 chromosomes, where SNPs on chromosomes 5A and 5B coincided with major freezing tolerance and vernalization loci. Increased number of favorable alleles was related to improved snow mold tolerance. Independent predictions using the AMP as a training population (TP) to predict snow mold tolerance of breeding lines evaluated between 2015 and 2018 resulted in a mean accuracy of 0.36 across models and marker sets. Modeling nonadditive effects improved accuracy even in the absence of a close genetic relatedness between the TP and selection candidates. Selecting lines based on genomic estimated breeding values and tolerance scores resulted in a 24% increase in tolerance. The identified genomic regions associated with snow mold tolerance demonstrated the genetic complexity of this trait and the difficulty in selecting tolerant lines using markers. GS was validated and showed potential for use in PNW winter wheat for selecting on complex traits such tolerance to snow mold.

Does Late Maturity Alpha-Amylase Impact Wheat Baking Quality?

Late maturity α-amylase (LMA) and pre-harvest sprouting (PHS) are both recognized as environmentally induced grain quality defects resulting from abnormally high levels of α-amylase. LMA is a more recently identified quality issue that is now receiving increasing attention worldwide and whose prevalence is now seen as impeding the development of superior quality wheat varieties. LMA is a genetic defect present in specific wheat genotypes and is characterized by elevated levels of the high pI TaAMY1 α-amylase, triggered by environmental stress during wheat grain development. TaAMY1 remains present in the aleurone through the harvest, lowering Falling Number (FN) at receival, causing a down-grading of the grain, often to feed grade, thus reducing the farmers' income. This downgrading is based on the assumption within the grain industry that, as for PHS, a low FN represents poor quality grain. Consequently any wheat line possessing low FN or high α-amylase levels is automatically considered a poor bread wheat despite there being no published evidence to date, to show that LMA is detrimental to end product quality. To evaluate the validity of this assumption a comprehensive evaluation of baking properties was performed from LMA prone lines using a subset of tall non-Rht lines from a multi-parent advanced generation inter-cross (MAGIC) wheat population grown at three different sites. LMA levels were determined along with quality parameters including end product functionality such as oven spring, bread loaf volume and weight, slice area and brightness, gas cell number and crumb firmness. No consistent or significant phenotypic correlation was found between LMA related FN and any of the quality traits. This manuscript provides for the first time, compelling evidence that LMA has limited impact on bread baking end product functionality.