Investigating the genetic control of plant development in spring barley under speed breeding conditions.

KEY MESSAGE: This study found that the genes, PPD-H1 and ELF3, control the acceleration of plant development under speed breeding, with important implications for optimizing the delivery of climate-resilient crops. Speed breeding is a tool to accelerate breeding and research programmes. Despite its success and growing popularity with breeders, the genetic basis of plant development under speed breeding remains unknown. This study explored the developmental advancements of barley genotypes under different photoperiod regimes. A subset of the HEB-25 Nested Association Mapping population was evaluated for days to heading and maturity under two contrasting photoperiod conditions: (1) Speed breeding (SB) consisting of 22 h of light and 2 h of darkness, and (2) normal breeding (NB) consisting of 16 h of light and 8 h of darkness. GWAS revealed that developmental responses under both conditions were largely controlled by two loci: PPDH-1 and ELF3. Allelic variants at these genes determine whether plants display early flowering and maturity under both conditions. At key QTL regions, domesticated alleles were associated with late flowering and maturity in NB and early flowering and maturity in SB, whereas wild alleles were associated with early flowering under both conditions. We hypothesize that this is related to the dark-dependent repression of PPD-H1 by ELF3 which might be more prominent in NB conditions. Furthermore, by comparing development under two photoperiod regimes, we derived an estimate of plasticity for the two traits. Interestingly, plasticity in development was largely attributed to allelic variation at ELF3. Our results have important implications for our understanding and optimization of speed breeding protocols particularly for introgression breeding and the design of breeding programmes to support the delivery of climate-resilient crops.

Evaluating the impact of a national geriatric mental health ECHO educational program on healthcare providers' practice.

Project Extension for Community Healthcare Outcomes (ECHO) enables healthcare providers to share knowledge and best practices via telementoring. The ECHO model builds provider capacity and improves care for patients with a variety of health conditions. This study describes a Canada-wide National ECHO pilot project in the area of geriatric mental health and reports on the program's impact on providers' care practices. A mixed-methods approach was used to analyze surveys completed by participating healthcare providers. Program evaluation measured satisfaction, achievement of learning objectives, awareness of issues related to geriatric mental health, and comfort and self-efficacy working with older adults. The program led to a statistically significant increase in participants' awareness of issues related to support for older adults with mental illness and comfort and self-efficacy in managing these patients in their own practice. The National ECHO pilot project was successful in building healthcare providers' capacity to care for older adults with mental health issues and positively impacting their practice. These findings support using the ECHO model to provide ongoing geriatric mental health education for clinicians from across Canada and beyond.

Mutations causing premature termination codons discriminate and generate cellular and clinical variability in HHT.

ABSTRACT: For monogenic diseases caused by pathogenic loss-of-function DNA variants, attention focuses on dysregulated gene-specific pathways, usually considering molecular subtypes together within causal genes. To better understand phenotypic variability in hereditary hemorrhagic telangiectasia (HHT), we subcategorized pathogenic DNA variants in ENG/endoglin, ACVRL1/ALK1, and SMAD4 if they generated premature termination codons (PTCs) subject to nonsense-mediated decay. In 3 patient cohorts, a PTC-based classification system explained some previously puzzling hemorrhage variability. In blood outgrowth endothelial cells (BOECs) derived from patients with ACVRL1+/PTC, ENG+/PTC, and SMAD4+/PTC genotypes, PTC-containing RNA transcripts persisted at low levels (8%-23% expected, varying between replicate cultures); genes differentially expressed to Bonferroni P < .05 in HHT+/PTC BOECs clustered significantly only to generic protein terms (isopeptide-bond/ubiquitin-like conjugation) and pulse-chase experiments detected subtle protein maturation differences but no evidence for PTC-truncated protein. BOECs displaying highest PTC persistence were discriminated in unsupervised hierarchical clustering of near-invariant housekeeper genes, with patterns compatible with higher cellular stress in BOECs with >11% PTC persistence. To test directionality, we used a HeLa reporter system to detect induction of activating transcription factor 4 (ATF4), which controls expression of stress-adaptive genes, and showed that ENG Q436X but not ENG R93X directly induced ATF4. AlphaFold accurately modeled relevant ENG domains, with AlphaMissense suggesting that readthrough substitutions would be benign for ENG R93X and other less rare ENG nonsense variants but more damaging for Q436X. We conclude that PTCs should be distinguished from other loss-of-function variants, PTC transcript levels increase in stressed cells, and readthrough proteins and mechanisms provide promising research avenues.

Medical Emergency Team call within 24 h of medical admission with a focus on sepsis: a retrospective review.

BACKGROUND AND AIMS: Clinical deterioration within the first 24 h of patient admission triggering a Medical Emergency Team (MET) call is a common occurrence. A greater understanding of these events, with a focus on the recognition and management of sepsis, could lead to quality improvement interventions. METHODS: A retrospective observational review of general and subspecialty medical admissions triggering a MET call within 24 h of admission at a quaternary Australian hospital. RESULTS: 2648 MET calls occurred (47.9/1000 admissions), 527 (20% of total MET events, 9.5/1000 admissions) within 24 h of admission, with the trigger more likely to be hypotension (odds ratio: 1.5, P = 0.0013). There were 263 MET calls to 217 individual medical patients within 24 h of admission, of which 84 (38.7%) were admitted with suspected infection, 69% of which fulfilled sepsis criteria. Of these, 36.2% received antimicrobial therapy within the recommended timeframe and 39.6% received antibiotics in line with hospital guidelines. Sepsis was initially missed in 11% of patients. Afferent limb failure occurred in 29% of patients with 40.5% experiencing a failure of the ward-based response to deterioration prior to MET call. Median hospital length of stay was increased in patients admitted with suspected infection (7 vs 5 days, P = 0.015) and in those with sepsis not receiving antimicrobial therapy within guideline timeframes (9 vs 4 days, P = 0.017). CONCLUSION: There is a significant opportunity to improve care for patients who trigger a MET within 24 h of admission. This study supports the implementation of a hospital sepsis management guideline.

Evaluation of Illumina® COVIDSeq™ as a tool for Omicron SARS-CoV-2 characterisation.

The continued emergence and transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants requires ongoing genetic surveillance to support public health responses. The expansion of reliable next generation sequence (NGS) platforms has enabled the rapid characterisation of the constant emergence of new SARS-CoV-2 variants using nasopharyngeal swab specimens. Several studies have assessed the ability of COVIDSeq to type earlier SARS-CoV-2 strains (pre-Delta) rapidly and successfully, however, there is limited data showing suitability against Omicron variants. In the present study, we evaluated the performance of the Illumina COVIDSeq Assay as a streamlined amplicon-based NGS platform for detection and typing of Omicron variants. Our results demonstrate the high performance of SARS-CoV-2 sequencing using the COVIDSeq approach, with good repeatability, reproducibility and sensitivity for samples approaching CT 31. The COVIDSeq approach was 100% concordant with samples previously characterized by sequencing methods. The quick library preparation process and high throughput kit made it ideal for reflex testing, with a total time required for sequencing and analysis of approximately two days. This study demonstrates the effectiveness and versatility of the amplicon-based NGS characterisation method for SARS-CoV-2, providing a foundation for further research and development of custom-designed amplicon panels targeting different microorganisms.

Wetting Characteristics of Laser-Ablated Hierarchical Textures Replicated by Micro Injection Molding.

Texturing can be used to functionalize the surface of plastic parts and, in particular, to modify the interaction with fluids. Wetting functionalization can be used for microfluidics, medical devices, scaffolds, and more. In this research, hierarchical textures were generated on steel mold inserts using femtosecond laser ablation to transfer on plastic parts surface via injection molding. Different textures were designed to study the effects of various hierarchical geometries on the wetting behavior. The textures are designed to create wetting functionalization while avoiding high aspect ratio features, which are complex to replicate and difficult to manufacture at scale. Nano-scale ripples were generated over the micro-scale texture by creating laser-induced periodic surface structures. The textured molds were then replicated by micro-injection molding using polypropylene and poly(methyl methacrylate). The static wetting behavior was investigated on steel inserts and molded parts and compared to the theoretical values obtained from the Cassie-Baxter and Wenzel models. The experimental results showed correlations between texture design, injection molding replication, and wetting properties. The wetting behavior on the polypropylene parts followed the Cassie-Baxter model, while for PMMA, a composite wetting state of Cassie-Baxter and Wenzel was observed.

Phenomic and genomic prediction of yield on multiple locations in winter wheat.

Genomic selection has recently become an established part of breeding strategies in cereals. However, a limitation of linear genomic prediction models for complex traits such as yield is that these are unable to accommodate Genotype by Environment effects, which are commonly observed over trials on multiple locations. In this study, we investigated how this environmental variation can be captured by the collection of a large number of phenomic markers using high-throughput field phenotyping and whether it can increase GS prediction accuracy. For this purpose, 44 winter wheat (Triticum aestivum L.) elite populations, comprising 2,994 lines, were grown on two sites over 2 years, to approximate the size of trials in a practical breeding programme. At various growth stages, remote sensing data from multi- and hyperspectral cameras, as well as traditional ground-based visual crop assessment scores, were collected with approximately 100 different data variables collected per plot. The predictive power for grain yield was tested for the various data types, with or without genome-wide marker data sets. Models using phenomic traits alone had a greater predictive value (R2 = 0.39-0.47) than genomic data (approximately R2 = 0.1). The average improvement in predictive power by combining trait and marker data was 6%-12% over the best phenomic-only model, and performed best when data from one full location was used to predict the yield on an entire second location. The results suggest that genetic gain in breeding programmes can be increased by utilisation of large numbers of phenotypic variables using remote sensing in field trials, although at what stage of the breeding cycle phenomic selection could be most profitably applied remains to be answered.

COVID-19 (Omicron strain) hospital admissions from a virtual ward - who required further care?

BACKGROUND: The COVID-19 virtual ward was created to provide care for people at home with COVID-19. Given this was a new model of care, little was known about the clinical characteristics and outcomes of patients requiring admission to hospital from the virtual ward platform. The aims were to characterise hospital admission volume, patient epidemiology, clinical characteristics, and outcome from a virtual ward in the setting of an Omicron (BA.1, BA.2) outbreak. METHODS: A retrospective observational study was performed for all virtual ward patients admitted from 1st January 2022 to 25th March 2022 (over 16 years old). Epidemiological, clinical and laboratory data was reviewed on all patients who required hospital admission. RESULTS: A total of 7021 patients were cared for on the virtual ward over the study period with 473 referred to hospital for assessment. Twenty-six (0.4%) patients were admitted to hospital during their care on the ward. Twenty-two (84.6%) admissions were COVID-19 related. Fifty three percent of the hospitalised patients were fully vaccinated and 11 had received prior therapeutics for COVID-19. Shortness of breath was the most common reason for escalation to hospital. Chest pain was the second most common reason and the most common diagnosis after investigation was non-cardiac chest pain. CONCLUSIONS: Few patients required admission from the virtual ward in the setting of the Omicron variant (BA.1, BA.2) as a direct result of COVID-19 disease and virtual ward care. Shortness of breath and chest pain were the most common symptoms driving further clinical care.

SARS-CoV-2 RT-PCR to Screen for B.1.617.2 (Delta) Variant of Concern.

The continuous transmission and evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has required that diagnostic capabilities be constantly monitored and updated as new variants emerge and prior variants disappear. Although whole genome sequencing provides full characterisation of SARS-CoV-2 directly from patient samples, this has limited throughput and requires sufficient resources. To enhance screening for circulating variants, we designed a rapid in-house RT-PCR assay to target a spike mutation (D950N) in Delta variants, which is not detected in the remaining variants of concern (VOCs). Assay sensitivity for detecting Delta variants was 93% and specificity was 100% using a sequenced sample bank of several lineages. As the D950N mutation is prevalent in >95% of the global Delta variant sequences deposited in GISAID, this assay has the potential to provide rapid results to determine if the samples are presumptively Delta variants and can support clinicians in timely clinical decision-making for effective treatments and surveillance.

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.

Analysis of historical selection in winter wheat.

KEY MESSAGE: Modeling of the distribution of allele frequency over year of variety release identifies major loci involved in historical breeding of winter wheat. Winter wheat is a major crop with a rich selection history in the modern era of crop breeding. Genetic gains across economically important traits like yield have been well characterized and are the major force driving its production. Winter wheat is also an excellent model for analyzing historical genetic selection. As a proof of concept, we analyze two major collections of winter wheat varieties that were bred in Western Europe from 1916 to 2010, namely the Triticeae Genome (TG) and WAGTAIL panels, which include 333 and 403 varieties, respectively. We develop and apply a selection mapping approach, Regression of Alleles on Years (RALLY), in these panels, as well as in simulated populations. RALLY maps loci under sustained historical selection by using a simple logistic model to regress allele counts on years of variety release. To control for drift-induced allele frequency change, we develop a hybrid approach of genomic control and delta control. Within the TG panel, we identify 22 significant RALLY quantitative selection loci (QSLs) and estimate the local heritabilities for 12 traits across these QSLs. By correlating predicted marker effects with RALLY regression estimates, we show that alleles whose frequencies have increased over time are heavily biased toward conferring positive yield effect, but negative effects in flowering time, lodging, plant height and grain protein content. Altogether, our results (1) demonstrate the use of RALLY to identify selected genomic regions while controlling for drift, and (2) reveal key patterns in the historical selection in winter wheat and guide its future breeding.

Risk taking propensity: Nurse, surgeon and patient preferences for diverting ileostomy.

AIM: The decision-making process to defunction a pelvic colorectal anastomosis involves complex heuristics and is framed by surgeon personality factors. Risk taking propensity may be an important factor in these decisions and patient preferences have not been evaluated alongside surgeons and nurses. METHODS: A prospective cross-sectional study involving a one-off interview and questionnaire assessing how risk taking propensity affects nurse, surgeon and patient preferences for a temporary defunctioning ileostomy (TDI) was performed. The risk taking index (RTI) was employed to evaluate risk taking propensity and the validated prospective measures of preference instruments to evaluate preferences for stoma avoidance in several scenarios by asking the individual to consider trading or gambling years of remaining life expectancy. RESULTS: One hundred and fifty participants met the inclusion criteria, which included 30 (20.0%) surgical nurses, 20 (13.3%) colorectal surgeons and 100 (66.7%) patients. Surgeons had a significantly higher RTI (mean ± SD: 26.8 ± 6.7) than patients (mean ± SD: 20.0 ± 9.8) and nurses (mean ± SD: 23.0 ± 6.6) p = 0.002. Surgeons would consider that it would be in a patient's best interest to have a TDI at an AL rate of 15% or greater, whereas nurses and patients would do so at 28% and 25%, respectively (p = 0.007). CONCLUSION: Surgeons were shown to have a higher risk taking propensity than patients and nurses but a significantly lower threshold of AL where they would consider a TDI is in the best interest of the patient.

Identification of a novel stripe rust resistance gene from the European winter wheat cultivar 'Acienda': A step towards rust proofing wheat cultivation.

All stage resistance to stripe rust races prevalent in India was investigated in the European winter wheat cultivar 'Acienda'. In order to dissect the genetic basis of the resistance, a backcross population was developed between 'Acienda' and the stripe rust susceptible Indian spring wheat cultivar 'HD 2967'. Inheritance studies revealed segregation for a dominant resistant gene. High density SNP genotyping was used to map stripe rust resistance and marker regression analysis located stripe rust resistance to the distal end of wheat chromosome 1A. Interval mapping located this region between the SNP markers AX-95162217 and AX-94540853, at a LOD score of 15.83 with a phenotypic contribution of 60%. This major stripe rust resistance locus from 'Acienda' has been temporarily designated as Yraci. A candidate gene search in the 2.76 Mb region carrying Yraci on chromosome 1A identified 18 NBS-LRR genes based on wheat RefSeqv1.0 annotations. Our results indicate that as there is no major gene reported in the Yraci chromosome region, it is likely to be a novel stripe rust resistance locus and offers potential for deployment, using the identified markers, to confer all stage stripe rust resistance.

Wheat genetic loci conferring resistance to stripe rust in the face of genetically diverse races of the fungus Puccinia striiformis f. sp. tritici.

KEY MESSAGE: Analysis of a wheat multi-founder population identified 14 yellow rust resistance QTL. For three of the four most significant QTL, haplotype analysis indicated resistance alleles were rare in European wheat. Stripe rust, or yellow rust (YR), is a major fungal disease of wheat (Triticum aestivum) caused by Puccinia striiformis Westend f. sp. tritici (Pst). Since 2011, the historically clonal European Pst races have been superseded by the rapid incursion of genetically diverse lineages, reducing the resistance of varieties previously showing durable resistance. Identification of sources of genetic resistance to such races is a high priority for wheat breeding. Here we use a wheat eight-founder multi-parent population genotyped with a 90,000 feature single nucleotide polymorphism array to genetically map YR resistance to such new Pst races. Genetic analysis of five field trials at three UK sites identified 14 quantitative trait loci (QTL) conferring resistance. Of these, four highly significant loci were consistently identified across all test environments, located on chromosomes 1A (QYr.niab-1A.1), 2A (QYr.niab-2A.1), 2B (QYr.niab-2B.1) and 2D (QYr.niab-2D.1), together explaining ~ 50% of the phenotypic variation. Analysis of these four QTL in two-way and three-way combinations showed combinations conferred greater resistance than single QTL, and genetic markers were developed that distinguished resistant and susceptible alleles. Haplotype analysis in a collection of wheat varieties found that the haplotypes associated with YR resistance at three of these four major loci were rare (≤ 7%) in European wheat, highlighting their potential utility for future targeted improvement of disease resistance. Notably, the physical interval for QTL QYr.niab-2B.1 contained five nucleotide-binding leucine-rich repeat candidate genes with integrated BED domains, of which two corresponded to the cloned resistance genes Yr7 and Yr5/YrSp.

Trends of genetic changes uncovered by Env- and Eigen-GWAS in wheat and barley.

KEY MESSAGE: Variety age and population structure detect novel QTL for yield and adaptation in wheat and barley without the need to phenotype. The process of crop breeding over the last century has delivered new varieties with increased genetic gains, resulting in higher crop performance and yield. However, in many cases, the alleles and genomic regions underpinning this success remain unknown. This is partly due to the difficulty of generating sufficient phenotypic data on large numbers of historical varieties to enable such analyses. Here we demonstrate the ability to circumvent such bottlenecks by identifying genomic regions selected over 100 years of crop breeding using age of a variety as a surrogate for yield. Rather than collecting phenotype data, we deployed 'environmental genome-wide association scans' (EnvGWAS) based on variety age in two of the world's most important crops, wheat and barley, and detected strong signals of selection across both genomes. EnvGWAS identified 16 genomic regions in barley and 10 in wheat with contrasting patterns between spring and winter types of the two crops. To further examine changes in genome structure, we used the genomic relationship matrix of the genotypic data to derive eigenvectors for analysis in EigenGWAS. This detected seven major chromosomal introgressions that contributed to adaptation in wheat. EigenGWAS and EnvGWAS based on variety age avoid costly phenotyping and facilitate the identification of genomic tracts that have been under selection during breeding. Our results demonstrate the potential of using historical cultivar collections coupled with genomic data to identify chromosomal regions under selection and may help guide future plant breeding strategies to maximise the rate of genetic gain and adaptation.

The evolving battle between yellow rust and wheat: implications for global food security.

Wheat (Triticum aestivum L.) is a global commodity, and its production is a key component underpinning worldwide food security. Yellow rust, also known as stripe rust, is a wheat disease caused by the fungus Puccinia striiformis Westend f. sp. tritici (Pst), and results in yield losses in most wheat growing areas. Recently, the rapid global spread of genetically diverse sexually derived Pst races, which have now largely replaced the previous clonally propagated slowly evolving endemic populations, has resulted in further challenges for the protection of global wheat yields. However, advances in the application of genomics approaches, in both the host and pathogen, combined with classical genetic approaches, pathogen and disease monitoring, provide resources to help increase the rate of genetic gain for yellow rust resistance via wheat breeding while reducing the carbon footprint of the crop. Here we review key elements in the evolving battle between the pathogen and host, with a focus on solutions to help protect future wheat production from this globally important disease.

Crafting for a better MAGIC: systematic design and test for Multiparental Advanced Generation Inter-Cross population.

Multiparental Advanced Generation Inter-Cross (MAGIC) populations are valuable crop resources with a wide array of research uses including genetic mapping of complex traits, management of genetic resources and breeding of new varieties. Multiple founders are crossed to create a rich mosaic of highly recombined founder genomes in the MAGIC recombinant inbred lines (RILs). Many variations of MAGIC population designs exist; however, a large proportion of the currently available populations have been created empirically and based on similar designs. In our evaluations of five MAGIC populations, we found that the choice of designs has a large impact on the recombination landscape in the RILs. The most popular design used in many MAGIC populations has been shown to have a bias in recombinant haplotypes and low level of unique recombinant haplotypes, and therefore is not recommended. To address this problem and provide a remedy for the future, we have developed the "magicdesign" R package for creating and testing any MAGIC population design via simulation. A Shiny app version of the package is available as well. Our "magicdesign" package provides a unifying tool and a framework for creativity and innovation in MAGIC population designs. For example, using this package, we demonstrate that MAGIC population designs can be found which are very effective in creating haplotype diversity without the requirement for very large crossing programs. Furthermore, we show that interspersing cycles of crossing with cycles of selfing is effective in increasing haplotype diversity. These approaches are applicable in species that are hard to cross or in which resources are limited.

Unraveling regulatory divergence, heterotic malleability, and allelic imbalance switching in rice due to drought stress.

The indica ecotypes, IR64, an elite drought-susceptible variety adapted to irrigated ecosystem, and Apo (IR55423-01 or NSIC RC9), a moderate drought-tolerant upland genotype together with their hybrid (IR64 × Apo) were exposed to non- and water-stress conditions. By sequencing (RNA-seq) these genotypes, we were able to map genes diverging in cis and/or trans factors. Under non-stress condition, cis dominantly explains (11.2%) regulatory differences, followed by trans (8.9%). Further analysis showed that water-limiting condition largely affects trans and cis + trans factors. On the molecular level, cis and/or trans regulatory divergence explains their genotypic differences and differential drought response. Between the two parental genotypes, Apo appears to exhibit more photosynthetic efficiency even under water-limiting condition and is ascribed to trans. Statistical analyses showed that regulatory divergence is significantly influenced by environmental conditions. Likewise, the mode of parental expression inheritance which drives heterosis (HET) is significantly affected by environmental conditions indicating the malleability of heterosis to external factors. Further analysis revealed that the HET class, dominance, was significantly enriched under water-stress condition. We also identified allelic imbalance switching in which several genes prefer IR64- (or Apo-) specific allele under non-stress condition but switched to Apo- (or IR64-) specific allele when exposed to water-stress condition.

Limited haplotype diversity underlies polygenic trait architecture across 70 years of wheat breeding.

BACKGROUND: Selection has dramatically shaped genetic and phenotypic variation in bread wheat. We can assess the genomic basis of historical phenotypic changes, and the potential for future improvement, using experimental populations that attempt to undo selection through the randomizing effects of recombination. RESULTS: We bred the NIAB Diverse MAGIC multi-parent population comprising over 500 recombinant inbred lines, descended from sixteen historical UK bread wheat varieties released between 1935 and 2004. We sequence the founders' genes and promoters by capture, and the MAGIC population by low-coverage whole-genome sequencing. We impute 1.1 M high-quality SNPs that are over 99% concordant with array genotypes. Imputation accuracy only marginally improves when including the founders' genomes as a haplotype reference panel. Despite capturing 73% of global wheat genetic polymorphism, 83% of genes cluster into no more than three haplotypes. We phenotype 47 agronomic traits over 2 years and map 136 genome-wide significant associations, concentrated at 42 genetic loci with large and often pleiotropic effects. Around half of these overlap known quantitative trait loci. Most traits exhibit extensive polygenicity, as revealed by multi-locus shrinkage modelling. CONCLUSIONS: Our results are consistent with a gene pool of low haplotypic diversity, containing few novel loci of large effect. Most past, and projected future, phenotypic changes arising from existing variation involve fine-scale shuffling of a few haplotypes to recombine dozens of polygenic alleles of small effect. Moreover, extensive pleiotropy means selection on one trait will have unintended consequences, exemplified by the negative trade-off between yield and protein content, unless selection and recombination can break unfavorable trait-trait associations.