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Abstract Fusarium head blight (FHB) is an economically and environmentally concerning disease of wheat (Triticum aestivum L). A two‐pronged approach of marker‐assisted selection coupled with genomic selection has been suggested when breeding for FHB resistance. A historical dataset comprised of entries in the Southern Uniform Winter Wheat Scab Nursery (SUWWSN) from 2011 to 2021 was partitioned and used in genomic prediction. Two traits were curated from 2011 to 2021 in the SUWWSN: percent Fusarium damaged kernels (FDK) and deoxynivalenol (DON) content. Heritability was estimated for each trait‐by‐environment combination. A consistent set of check lines was drawn from each year in the SUWWSN, and k‐means clustering was performed across environments to assign environments into clusters. Two clusters were identified as FDK and three for DON. Cross‐validation on SUWWSN data from 2011 to 2019 indicated no outperforming training population in comparison to the combined dataset. Forward validation for FDK on the SUWWSN 2020 and 2021 data indicated a predictive accuracy r≈0.58 and r≈0.53, respectively. Forward validation for DON indicated a predictive accuracy of r≈0.57 and r≈0.45, respectively. Forward validation using environments in cluster one for FDK indicated a predictive accuracy of r≈0.65 and r≈0.60, respectively. Forward validation using environments in cluster one for DON indicated a predictive accuracy of r≈0.67 and r≈0.60, respectively. These results indicated that selecting environments based on check performance may produce higher forward prediction accuracies. This work may be used as a model for utilizing public resources for genomic prediction of FHB resistance traits across public wheat breeding programs.

Abstract Introduction Human immunodeficiency virus (HIV) continues to rise in young people among low‐ and middle‐income countries (LMIC). The US National Institutes of Health (NIH) supports the largest public investment in HIV research globally. Despite advancements in the last decade, adolescents and young adults (AYA) remain underrepresented in research to improve HIV prevention and care. We undertook a programme analysis of NIH grants and conducted a targeted review of linked publications on international AYA research across the HIV prevention and care continuum (HPCC) to inform new initiatives to address the needs of AYA in these settings. Methods NIH‐funded grants from 2012 to 2017, pertaining to AYA in LMIC, and evaluating areas of HIV prevention, care and/or treatment were identified. A systematic review of publications limited to funded grants was performed in two waves: 2012–2017 and 2018–2021. The review included a landscape assessment and an evaluation of NIH‐defined clinical trials, respectively. Data on outcomes across the HPCC were abstracted and analysed. Results Among grant applications, 14% were funded and linked to 103 publications for the analytic database, 76 and 27 from the first and second waves, respectively. Fifteen (15%) wave 1 and 27 (26%) wave 2 publications included an NIH‐defined clinical trial. Among these, 36 (86%) did not target a key population (men who have sex with men, drug users and sex workers) and 37 (88%) were exclusively focused on sub‐Saharan Africa. Thirty (71%) publications addressed at least one HPCC milestone. Specific focus was on milestones in HIV prevention, care or both, for 12 (29%), 13 (31%) and five (12%) of publications, respectively. However, few addressed access to and retention in HIV care (4 [14%]) and none included microbicides or treatment as prevention. More focus is needed in crucial early steps of the HIV care continuum and on biomedical HIV prevention interventions. Discussion and Conclusions Research gaps remain in this portfolio across the AYA HPCC. To address these, NIH launched an initiative entitled Prevention and Treatment through a Comprehensive Care Continuum for HIV‐affected Adolescents in Resource Constrained Settings (PATC3H) to generate needed scientific innovation for effective public health interventions for AYA affected by HIV in LMIC.

The connection between expression variation and phenotypic diversity in the populations of polyploid crops remains elusive. Here, the authors reveal the impact of genetic variants leading to biased expression of homoeologous genes in hexaploid wheat on agronomic traits.

With the rapid generation and preservation of both genomic and phenotypic information for many genotypes within crops and across locations, emerging breeding programs have a valuable opportunity to leverage these resources to 1) establish the most appropriate genetic foundation at program inception and 2) implement robust genomic prediction platforms that can effectively select future breeding lines. Integrating genomics-enabled1 breeding into cultivar development can save costs and allow resources to be reallocated towards advanced (i.e., later) stages of field evaluation, which can facilitate an increased number of testing locations and replicates within locations. In this context, a reestablished winter wheat breeding program was used as a case study to understand best practices to leverage and tailor existing genomic and phenotypic resources to determine optimal genetics for a specific target population of environments. First, historical multi-environment phenotype data, representing 1,285 advanced breeding lines, were compiled from multi-institutional testing as part of the SunGrains cooperative and used to produce GGE biplots and PCA for yield. Locations were clustered based on highly correlated line performance among the target population of environments into 22 subsets. For each of the subsets generated, EMMs and BLUPs were calculated using linear models with the ‘lme4’ R package. Second, for each subset, TPs representative of the new SC breeding lines were determined based on genetic relatedness using the ‘STPGA’ R package. Third, for each TP, phenotypic values and SNP data were incorporated into the ‘rrBLUP’ mixed models for generation of GEBVs of YLD, TW, HD and PH. Using a five-fold cross-validation strategy, an average accuracy of r = 0.42 was obtained for yield between all TPs. The validation performed with 58 SC elite breeding lines resulted in an accuracy of r = 0.62 when the TP included complete historical data. Lastly, QTL-by-environment interaction for 18 major effect genes across three geographic regions was examined. Lines harboring major QTL in the absence of disease could potentially underperform (e.g., Fhb1 R-gene), whereas it is advantageous to express a major QTL under biotic pressure (e.g., stripe rust R-gene). This study highlights the importance of genomics-enabled breeding and multi-institutional partnerships to accelerate cultivar development.

Background MRI interpretation and accurate radiological staging are crucial to the important treatment decisions and a consequent successful patient outcome in rectal cancer.Aims To investigate the effect of intensive training on rectal cancer MRI staging performance of radiologists and the impact of different course elements on learning outcomes.Methods In this prospective intervention study, 17 radiology specialists and 1 radiology registrar participated in a training programme including a 6-hour imaging workshop, a 3-hour session of individual feedback and independent MRI readings of primary rectal cancer cases. Their rectal MRI interpretive performance was evaluated through repeated readings of 30 training cases before and after each course element and a time interval with no educational intervention. A proforma template for MRI staging of primary rectal cancer was used and the results were compared with a reference standard of an expert panel. Participants repeatedly reported on confidence scores and self-assessed learning outcome. Outcomes were analysed using mixed-effects models.Results At baseline the quality of rectal MRI assessment varied significantly, with a higher interpretive performance among participants with shorter radiological experience (10.2 years vs 19.9 years, p=0.02). The ability to perform correct treatment allocation improved from 72% to 82% (adjusted OR=2.36, 95% CI 1.64 to 3.39). The improvement was largely driven by the participants with lower performance at baseline and by prevention of overstaging. Individual feedback had a significant impact on the improved interpretive performance (adjusted OR=1.82, 95% CI 1.27 to 2.63), whereas no significant change was seen after workshop or case readings only. Confidence scores increased significantly during training.Conclusions Targeted and individualised training improves the rectal cancer MRI interpretive performance essential to successful patient treatment, especially among radiology specialists with lower performance at baseline.

Abstract Background Genetic variation in growth over the course of the season is a major source of grain yield variation in wheat, and for this reason variants controlling heading date and plant height are among the best-characterized in wheat genetics. While the major variants for these traits have been cloned, the importance of these variants in contributing to genetic variation for plant growth over time is not fully understood. Here we develop a biparental population segregating for major variants for both plant height and flowering time to characterize the genetic architecture of the traits and identify additional novel QTL. Results We find that additive genetic variation for both traits is almost entirely associated with major and moderate-effect QTL, including four novel heading date QTL and four novel plant height QTL. FT2 and Vrn-A3 are proposed as candidate genes underlying QTL on chromosomes 3A and 7A, while Rht8 is mapped to chromosome 2D. These mapped QTL also underlie genetic variation in a longitudinal analysis of plant growth over time. The oligogenic architecture of these traits is further demonstrated by the superior trait prediction accuracy of QTL-based prediction models compared to polygenic genomic selection models. Conclusions In a population constructed from two modern wheat cultivars adapted to the southeast U.S., almost all additive genetic variation in plant growth traits is associated with known major variants or novel moderate-effect QTL. Major transgressive segregation was observed in this population despite the similar plant height and heading date characters of the parental lines. This segregation is being driven primarily by a small number of mapped QTL, instead of by many small-effect, undetected QTL. As most breeding populations in the southeast U.S. segregate for known QTL for these traits, genetic variation in plant height and heading date in these populations likely emerges from similar combinations of major and moderate effect QTL. We can make more accurate and cost-effective prediction models by targeted genotyping of key SNPs.

Abstract Multi‐trait genomic prediction (MTGP) can improve selection accuracy for economically valuable ‘primary’ traits by incorporating data on correlated secondary traits. Resistance to Fusarium head blight (FHB), a fungal disease of wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.), is evaluated using four genetically correlated traits: incidence (INC), severity (SEV), Fusarium damaged kernels (FDK), and deoxynivalenol content (DON). Both FDK and DON are primary traits; DON evaluation is expensive and usually requires several months for wheat breeders to get results from service laboratories performing the evaluations. We evaluated MTGP for DON using three soft red winter wheat breeding datasets: two diversity panels from the University of Illinois (IL) and Purdue University (PU) and a dataset consisting of 2019–2020 University of Illinois breeding cohorts. For DON, relative to single‐trait (ST) genomic prediction, MTGP including phenotypic data for secondary traits on both validation and training sets, resulted in 23.4 and 10.6% higher predictive abilities in IL and PU panels, respectively. The MTGP models were advantageous only when secondary traits were included in both training and validation sets. In addition, MTGP models were more accurate than ST models only when FDK was included, and once FDK was included in the model, adding additional traits hardly improved accuracy. Evaluation of MTGP models across testing cohorts indicated that MTGP could increase accuracy by more than twofold in the early stages. Overall, we show that MTGP can increase selection accuracy for resistance to DON accumulation in wheat provided FDK is evaluated on the selection candidates.

Plant height has been a major target for selection of high-yielding varieties in wheat. Two height-reducing loci (Rht-B1 and Rht-D1) have been widely used since the Green Revolution. However, these genes also negatively affect other agronomic traits such as kernel weight. Identifying alternative height-reducing loci could benefit wheat improvement. This study focused on the genetics of plant height in 260 historical and contemporary winter wheat accessions via genome-wide association studies using 38,693 single nucleotide polymorphism (SNP) markers generated through genotyping by sequencing, two Kompetitive Allele Specific Polymorphism markers, and phenotypic data recorded in two seasons (2016 and 2018). The 260 accessions showed wide variation in plant height. Most accessions developed after 1960 were shorter than earlier accessions. The broad-sense heritability for plant height was high (H2 = 0.82), which was also supported by a high correlation (r = 0.82, P

Stem rust caused by the fungus Puccinia graminis f.sp. tritici Eriks. & E. Henn. (Pgt) threatens the global production of both durum wheat (Triticum turgidum L. ssp. durum (Desf.) Husnot) and common wheat (Triticum aestivum L.). The objective of this study was to evaluate a durum wheat recombinant inbred line (RIL) population from a cross between a susceptible parent ‘DAKIYE’ and a resistant parent ‘Reichenbachii’ developed by the International Center for the Improvement of Maize and Wheat (CIMMYT) 1) for seedling response to races JRCQC and TTRTF and 2) for field response to a bulk of the current Pgt races prevalent in Ethiopia and Kenya and 3) to map loci associated with seedling and field resistances in this population. A total of 224 RILs along with their parents were evaluated at the seedling stage in the Ethiopian Institute for Agricultural Research greenhouse at Debre Zeit, Ethiopia and in the EIAR and KALRO fields in Ethiopia and Kenya, for two seasons from 2019 to 2020. The lines were genotyped using the genotyping-by-sequencing approach. A total of 843 single nucleotide polymorphism markers for 175 lines were used for quantitative trait locus (QTL) analyses. Composite interval mapping (CIM) identified three QTL on chromosomes 3B, 4B and 7B contributed by the resistant parent. The QTL on chromosome 3B was identified at all growth stages and it explained 11.8%, 6.5%, 6.4% and 15.3% of the phenotypic variation for responses to races JRCQC, TTRTF and in the field trials ETMS19 and KNMS19, respectively. The power to identify additional QTL in this population was limited by the number of high-quality markers, since several markers with segregation distortion were eliminated. A cytological study is needed to understand the presence of chromosomal rearrangements. Future evaluations of additional durum lines and RIL families identification of durable adult plant resistance sources is crucial for breeding stem rust resistance in durum wheat in the future.

In humid and temperate areas, Septoria nodorum blotch (SNB) is a major fungal disease of common wheat (Triticum aestivum L.) in which grain yield is reduced when the pathogen, Parastagonospora nodorum, infects leaves and glumes during grain filling. Foliar SNB susceptibility may be associated with sensitivity to P. nodorum necrotrophic effectors (NEs). Both foliar and glume susceptibility are quantitative, and the underlying genetics are not understood in detail. We genetically mapped resistance quantitative trait loci (QTL) to leaf and glume blotch using a double haploid (DH) population derived from the cross between the moderately susceptible cultivar AGS2033 and the resistant breeding line GA03185-12LE29. The population was evaluated for SNB resistance in the field in four successive years (2018-2021). We identified major heading date (HD) and plant height (PH) variants on chromosomes 2A and 2D, co-located with SNB escape mechanisms. Five QTL with small effects associated with adult plant resistance to SNB leaf and glume blotch were detected on 1A, 1B, and 6B linkage groups. These QTL explained a relatively small proportion of the total phenotypic variation, ranging from 5.6 to 11.8%. The small-effect QTL detected in this study did not overlap with QTL associated with morphological and developmental traits, and thus are sources of resistance to SNB.

Many studies have evaluated the effectiveness of genomic selection (GS) using cross-validation within training populations; however, few have looked at its performance for forward prediction within a breeding program. The objectives for this study were to compare the performance of naïve GS (NGS) models without covariates and multi-trait GS (MTGS) models by predicting two years of F4:7 advanced breeding lines for three Fusarium head blight (FHB) resistance traits, deoxynivalenol (DON) accumulation, Fusarium damaged kernels (FDK), and severity (SEV) in soft red winter wheat and comparing predictions with phenotypic performance over two years of selection based on selection accuracy and response to selection. On average, for DON, the NGS model correctly selected 69.2% of elite genotypes, while the MTGS model correctly selected 70.1% of elite genotypes compared with 33.0% based on phenotypic selection from the advanced generation. During the 2018 breeding cycle, GS models had the greatest response to selection for DON, FDK, and SEV compared with phenotypic selection. The MTGS model performed better than NGS during the 2019 breeding cycle for all three traits, whereas NGS outperformed MTGS during the 2018 breeding cycle for all traits except for SEV. Overall, GS models were comparable, if not better than phenotypic selection for FHB resistance traits. This is particularly helpful when adverse environmental conditions prohibit accurate phenotyping. This study also shows that MTGS models can be effective for forward prediction when there are strong correlations between traits of interest and covariates in both training and validation populations.

Introduction Three-dimensional (3D) reconstruction describes the generation of either virtual or physically printed anatomically accurate 3D models from two-dimensional medical images. Their implementation has revolutionised medical practice. Within surgery, key applications include growing roles in operative planning and procedures, surgical education and training, as well as patient engagement and education. In comparison to other surgical specialties, oesophagogastric surgery has been slow in their adoption of this technology. Herein the authors outline a scoping review protocol that aims to analyse the current role of 3D modelling in oesophagogastric surgery and highlight any unexplored avenues for future research.Methods and analysis The protocol was generated using internationally accepted methodological frameworks. A succinct primary question was devised, and a comprehensive search strategy was developed for key databases (MEDLINE, Embase, Elsevier Scopus and ISI Web of Science). These were searched from their inception to 1 June 2020. Reference lists will be reviewed by hand and grey literature identified using OpenGrey and Grey Literature Report. The protocol was registered to the Open Science Framework (osf.io/ta789).Two independent reviewers will screen titles, abstracts and perform full-text reviews for study selection. There will be no methodological quality assessment to ensure a full thematic analysis is possible. A data charting tool will be created by the investigatory team. Results will be analysed to generate descriptive numerical tabular results and a thematic analysis will be performed.Ethics and dissemination Ethical approval was not required for the collection and analysis of the published data. The scoping review report will be disseminated through a peer-reviewed publication and international conferences.Registration details The scoping review protocol has been registered on the Open Science Framework (https://osf.io/ta789).

Wheat heading time is genetically controlled by phenology genes including vernalization (Vrn), photoperiod (Ppd) and earliness per se (Eps) genes. Characterization of the existing genetic variation in the phenology genes of wheat would provide breeding programs with valuable genetic resources necessary for the development of wheat varieties well-adapted to the local environment and early-maturing traits suitable for double-cropping system. One hundred forty-nine eastern U.S. soft winter (ESW) and 32 Korean winter (KW) wheat genotypes were characterized using molecular markers for Vrn, Ppd, Eps and reduced-height (Rht) genes, and phenotyped for heading date (HD) in the eastern U.S. region. The Ppd-D1 and Rht-D1 genes exhibited the highest genetic diversity in ESW and KW wheat, respectively. The genetic variations for HD of ESW wheat were largely contributed by Ppd-B1, Ppd-D1 and Vrn-D3 genes. The Rht-D1 gene largely contributed to the genetic variation for HD of KW wheat. KW wheat headed on average 14 days earlier than ESW wheat in each crop year, largely due to the presence of the one-copy vrn-A1 allele in the former. The development of early-maturing ESW wheat varieties could be achieved by selecting for the one-copy vrn-A1 and vrn-D3a alleles in combination with Ppd-B1a and Ppd-D1a photoperiod insensitive alleles.

Wheat occupies a special role in global food security since, in addition to providing 20% of our carbohydrates and protein, almost 25% of the global production is traded internationally. The importance of wheat for food security was recognised by the Chief Agricultural Scientists of the G20 group of countries when they endorsed the establishment of the Wheat Initiative in 2011. The Wheat Initiative was tasked with supporting the wheat research community by facilitating collaboration, information and resource sharing and helping to build the capacity to address challenges facing production in an increasingly variable environment. Many countries invest in wheat research. Innovations in wheat breeding and agronomy have delivered enormous gains over the past few decades, with the average global yield increasing from just over 1 tonne per hectare in the early 1960s to around 3.5 tonnes in the past decade. These gains are threatened by climate change, the rapidly rising financial and environmental costs of fertilizer, and pesticides, combined with declines in water availability for irrigation in many regions. The international wheat research community has worked to identify major opportunities to help ensure that global wheat production can meet demand. The outcomes of these discussions are presented in this paper.

Abstract Many of the major stem rust resistance genes deployed in commercial wheat (Triticum spp.) cultivars and breeding lines become ineffective over time because of the continuous emergence of virulent races. A genome‐wide association study (GWAS) was conducted using 26,439 single nucleotide polymorphism (SNP) markers and 280 durum wheat [Triticum turgidum L. subsp. Durum (Desf.) Husnot] lines from CIMMYT to identify genomic regions associated with seedling resistance to races TTKSK, TKTTF, JRCQC, and TTRTF and field resistance to TKTTF and JRCQC. The phenotypic data analysis across environments revealed 61–91 and 59–77% of phenotypic variation was explained by the genotypic component for seedling and adult plant response of lines, respectively. For seedling resistance, mixed linear model (MLM) identified eight novel and nine previously reported quantitative trait loci (QTL) while a fixed and random model circulating probability unification (FarmCPU) detected 12 novel and eight previously reported QTL. For field resistance, MLM identified 12 novel and seven previously reported loci while FarmCPU identified seven novel and nine previously reported loci. The regions of Sr7a, Sr8155B1, Sr11, alleles of Sr13, Sr17, Sr22/Sr25, and Sr49 were identified. Novel loci on chromosomes 3B, 4A, 6A, 6B, 7A, and 7B could be used as sources of resistance to the races virulent on durum wheat. Two large‐effect markers on chromosome 6A could potentially be used to differentiate resistant haplotypes of Sr13 (R1 and R3). Allelism tests for Sr13, breaking the deleterious effect associated with Sr22/Sr25 and retaining the resistance allele at the Sr49 locus, are needed to protect future varieties from emerging races.

Abstract Background Genomic selection has the potential to increase genetic gains by using molecular markers as predictors of breeding values of individuals. This study evaluated the accuracy of predictions for grain yield, heading date, plant height, and yield components in soft red winter wheat under different prediction scenarios. Response to selection for grain yield was also compared across different selection strategies- phenotypic, marker-based, genomic, combination of phenotypic and genomic, and random selections. Results Genomic selection was implemented through a ridge regression best linear unbiased prediction model in two scenarios- cross-validations and independent predictions. Accuracy for cross-validations was assessed using a diverse panel under different marker number, training population size, relatedness between training and validation populations, and inclusion of fixed effect in the model. The population in the first scenario was then trained and used to predict grain yield of biparental populations for independent validations. Using subsets of significant markers from association mapping increased accuracy by 64–70% for grain yield but resulted in lower accuracy for traits with high heritability such as plant height. Increasing size of training population resulted in an increase in accuracy, with maximum values reached when ~ 60% of the lines were used as a training panel. Predictions using related subpopulations also resulted in higher accuracies. Inclusion of major growth habit genes as fixed effect in the model caused increase in grain yield accuracy under a cross-validation procedure. Independent predictions resulted in accuracy ranging between − 0.14 and 0.43, dependent on the grouping of site-year data for the training and validation populations. Genomic selection was “superior” to marker-based selection in terms of response to selection for yield. Supplementing phenotypic with genomic selection resulted in approximately 10% gain in response compared to using phenotypic selection alone. Conclusions Our results showed the effects of different factors on accuracy for yield and agronomic traits. Among the factors studied, training population size and relatedness between training and validation population had the greatest impact on accuracy. Ultimately, combining phenotypic with genomic selection would be relevant for accelerating genetic gains for yield in winter wheat.

Abstract Stripe rust, or yellow rust (Puccinia striiformis Westend. f. sp. tritic), is a disease of wheat (Triticum aestivum L.) historically causing significant economic losses in cooler growing regions. Novel isolates of stripe rust with increased tolerance for high temperatures were detected in the United States circa 2000. This increased heat tolerance puts geographic regions, such as the soft red winter wheat (SRWW) growing region of the southeastern United States, at greater risk of stripe rust induced losses. In order to identify sources of stripe rust resistance in contemporary germplasm, we conducted genome‐wide association (GWA) studies on stripe rust severity measured in two panels. The first consisted of 273 older varieties, landraces, and some modern elite breeding lines and was evaluated in environments in the U.S. Pacific Northwest and the southeastern United States. The second panel consisted of 588 modern, elite SRWW breeding lines and was evaluated in four environments in Arkansas and Georgia. The analyses identified three major resistance loci on chromosomes: 2AS (presumably the 2NS:2AS alien introgression from Aegilops ventricosa Tausch; syn. Ae. caudata L.), 3BS, and 4BL. The 4BL locus explained a greater portion of variance in resistance than either the 2AS or 3BS loci in southeastern environments. However, its effects were unstable across different environments and sets of germplasm, possibly a result of its involvement in epistatic interactions. Relatively few lines carry resistance alleles at all three loci, suggesting that there is a pre‐existing reservoir of enhanced stripe rust resistance that may be further exploited by regional breeding programs.

Stem rust of wheat caused by Puccinia graminis Pers. f.sp. trtici Eriks and E. Henn., is the most damaging fungal disease of both common (Triticum aestivum L.) and durum (Triticum turgidum L., ssp. Durum) wheat. Continuously emerging races virulent to many of the commercially deployed qualitative resistance genes have caused remarkable loss worldwide and threaten global wheat production. The objectives of this study were to evaluate the response of a panel of 283 durum wheat lines assembled by the International Maize and Wheat Improvement Center (CIMMYT) to multiple races of stem rust in East Africa at the adult plant stage and map loci associated with field resistance. The lines were evaluated in Debre Zeit, Ethiopia and Njoro, Kenya from 2018 to 2019 in five environments (year × season). The panel was genotyped using genotyping-by-sequencing. After filtering, 26,439 Single Nucleotide Polymorphism (SNP) markers and 280 lines and three checks were retained for analysis. Population structure was assessed using principal component analysis. Genome-wide association analysis (GWAS) was conducted using Genomic Association and Prediction Integrated Tool (GAPIT). The broad-sense heritability of the phenotype data revealed that 64–83% of the variation in stem rust response explained by the genotypes and lines with multiple race resistance were identified. GWAS analysis detected a total of 160 significant marker trait associations representing 42 quantitative trait loci. Of those, 21 were potentially novel and 21 were mapped to the same regions as previously reported loci. Known stem rust resistance genes/alleles were postulated including Sr8a, Sr8155B1, SrWeb/Sr9h, Sr11, Sr12, Sr13/Sr13 alleles, Sr17, Sr28/Sr16, Sr22, and Sr49. Lines resistant to multiple races in East Africa can be utilized as parents in durum wheat breeding programs. Further studies are needed to determine if there are new alleles at the Sr13 locus and potential markers for the known Sr13 alleles.

Abstract Germplasm collections are rich sources of genetic variation to improve crops for many valuable traits. Nested association mapping (NAM) populations can overcome the limitations of genome‐wide association studies (GWAS) in germplasm collections by reducing the effect of population structure. We exploited the genetic diversity of the USDA‐ARS wheat (Triticum aestivum L.) core collection by developing the Spring Wheat Multiparent Introgression Population (SWMIP). To develop this population, twenty‐five core parents were crossed and backcrossed to the Minnesota spring wheat cultivar RB07. The NAM population and 26 founder parents were genotyped using genotyping‐by‐sequencing and phenotyped for heading date, height, test weight, and grain protein content. After quality control, 20,312 markers with physical map positions were generated for 2,038 recombinant inbred lines (RILs). The number of RILs in each family varied between 58 and 96. Three GWAS models were utilized for quantitative trait loci (QTL) detection and accounted for known family stratification, genetic kinship, and both covariates. GWAS was performed on the whole population and also by bootstrap sampling of an equal number of RILs from each family. Greater power of QTL detection was achieved by treating families equally through bootstrapping. In total 16, 15, 12, and 13 marker‐trait associations (MTAs) were identified for heading date, height, test weight, and grain protein content, respectively. Some of these MTAs were coincident with major genes known to control the traits, but others were novel and contributed by the wheat core parents. The SWMIP will be a valuable source of genetic variation for spring wheat breeding.

Introduction Tumour deposits (TDs) are a poor prognostic marker when seen on pathology, and are worse than lymph node metastases (LNMs). They are now being reported on MRI as discontinuous nodules of extramural venous invasion but this diagnosis has not been validated and it is unclear how it correlates with the diagnosis of TDs on pathology.Methods and analysis This is a prospective interventional clinical trial which aims to directly map the location of TDs on MRI and correlate what is seen on MRI with the pathology findings at each location. All patients with rectal cancer undergoing resectional surgery are eligible (including those undergoing preoperative therapy). The primary outcome is the prevalence of TDs seen on pathology. Secondary outcomes are to assess radiological and pathological interobserver agreement, assess the effect of TDs on prognosis and carry out exploratory work looking at differences between TDs and LNMs. The estimated sample size is 100 to detect a twofold increase in the pathological diagnosis of TD when MRI mapping is used.Ethics and dissemination Ethical approval has been granted from the South Central—Hampshire B Research and Ethics Committee (IRAS 217627). The study will be carried out under standard operative procedures within the Royal Marsden Hospital.Trial registration number NCT03303547.

Previous results from our lab have shown that using an optical sorter to identify Fusarium head blight (FHB) resistant breeding lines was effective at reducing the toxin deoxynivalenol (DON) and FHB-associated kernel damage. In this paper we quantified the proportion of desirable genotypes at FHB resistance QTL in lines from three selection cycles of optical sorting. Breeding lines were genotyped at loci on chromosomes 3BS, 2DL, and 5A using the following DNA markers: TaHRC, CFD233, and GWM304. TaHRC is a KASP marker for Fhb1, a major FHB resistance QTL on chromosome 3BS. CFD233 is an SSR marker for Qfhs.nau-2DL on chromosome 2DL. GWM304 is an SSR marker for Qfhs.ifa-5A on chromosome 5A. Sorter selection was effective at identifying lines that had the resistant genotype at TaHRC; in other words, the sorter was able to identify lines with resistance alleles at Fhb1. The sorter was less effective at selecting for the resistant genotype at CFD233 and GWM304. However, the proportion of lines with resistant genotypes at GWM304 did increase with additional sorter selection, just not to the degree that was observed for the Fhb1-associated marker. The proportion of lines with resistant alleles at CFD233 did not show a consistent trend. In addition to increasing the proportion of lines with Fhb1 and Qfhs.ifa-5A each selection cycle, optical sorter-based mass selection enhanced FHB resistance in different marker genotype combinations evaluated in this study. For example, there were net reductions in DON and kernel damage after two cycles of sorter selection in 15X110601S07002, a line with Fhb1, with Qfhs.nau-2DL, and with Qfhs.ifa-5A; final C3 DON levels were 63% of the resistant check (KY02C-3005-25). Kernel damage was also reduced in 15X110601A08221 a line without Fhb1, without Qfhs.nau-2DL, and without Qfhs.ifa-5A. Our findings suggest the increased resistance observed in different marker genotype combinations was conferred by QTL other than Fhb1, QFhs.nau-2DL, and Qfhs.ifa-5, and validate our previous results that the optical sorter is effective at selecting FHB-resistant breeding material.

Abstract Comprehensive information of a breeding population is a necessity to design promising crosses. This study was conducted to characterize a soft red winter wheat breeding population that was subject of intensive germplasm introductions and introgression from exotic germplasm. We used genome‐wide markers and phenotypic assessment to identify signatures of selection and loci controlling agronomic traits in a soft red winter wheat population. The study of linkage disequilibrium (LD) revealed that the extent of LD and its decay varied among chromosomes with chromosomes 2B and 7D showing the most extended islands of high‐LD with slow rates of decay. Four sub‐populations, two with North American origin and two with Australian and Chinese origins, were identified. Genome‐wide scans for selection signatures using FST and hapFLK identified 13 genomic regions under selection, of which five loci (LT, Fr‐A2, Vrn‐A1, Vrn‐B1, Vrn3) were associated with environmental adaptation and two loci were associated with disease resistance genes (Sr36 and Fhb1). Genome‐wide association studies identified major loci controlling yield and yield related traits. For days to heading and plant height, major loci with effects sizes of 2.2 days and 5 cm were identified on chromosomes 7B and 6A respectively. For test weight, number of spikes per square meter, and number of kernels per square meter, large effect loci were identified on chromosomes 1A, 4B, and 5A, respectively. However, for yield alone, no major loci were detected. A combination of selection for large effect loci for yield components and genomic selection could be a promising approach for yield improvement.

Important advances have been made in understanding the relationship of necrotrophic effectors (NE) and host sensitivity (Snn) genes in the Parastagonospora nodorum-wheat pathosystem. Yet much remains to be learned about the role of these interactions in determining wheat resistance levels in the field, and there is mixed evidence on whether breeding programs have selected against Snn genes due to their role in conferring susceptibility. SNB occurs ubiquitously in the U.S. Atlantic seaboard, and the environment is especially well suited to field studies of resistance to natural P. nodorum populations, as there are no other important wheat leaf blights. Insights into the nature of SNB resistance have been gleaned from multi-year data on phenotypes and markers in cultivars representative of the region’s germplasm. In this perspective article, we review the evidence that in this eastern region of the U.S., wheat cultivars have durable quantitative SNB resistance and Snn–NE interactions are of limited importance. This conclusion is discussed in light of the relevant available information from other parts of the world.

Maintaining winter wheat (Triticum aestivum L.) productivity with more efficient nitrogen (N) management will enable growers to increase profitability and reduce the negative environmental impacts associated with nitrogen loss. Wheat breeders would therefore benefit greatly from the identification and application of genetic markers associated with nitrogen use efficiency (NUE). To investigate the genetics underlying N response, two bi-parental mapping populations were developed and grown in four site-seasons under low and high N rates. The populations were derived from a cross between previously identified high NUE parents (VA05W-151 and VA09W-52) and a shared common low NUE parent, 'Yorktown.' The Yorktown × VA05W-151 population was comprised of 136 recombinant inbred lines while the Yorktown × VA09W-52 population was comprised of 138 doubled haploids. Phenotypic data was collected on parental lines and their progeny for 11 N-related traits and genotypes were sequenced using a genotyping-by-sequencing platform to detect more than 3,100 high quality single nucleotide polymorphisms in each population. A total of 130 quantitative trait loci (QTL) were detected on 20 chromosomes, six of which were associated with NUE and N-related traits in multiple testing environments. Two of the six QTL for NUE were associated with known photoperiod (Ppd-D1 on chromosome 2D) and disease resistance (FHB-4A) genes, two were reported in previous investigations, and one QTL, QNue.151-1D, was novel. The NUE QTL on 1D, 6A, 7A, and 7D had LOD scores ranging from 2.63 to 8.33 and explained up to 18.1% of the phenotypic variation. The QTL identified in this study have potential for marker-assisted breeding for NUE traits in soft red winter wheat.

Abstract There are limited data on circulating, cell-free, tumour (ct)DNA analysis in locally advanced rectal cancer (LARC). Digital droplet (dd)PCR was used to investigate KRAS/BRAF mutations in ctDNA from baseline blood samples of 97 LARC patients who were treated with CAPOX followed by chemoradiotherapy, surgery and adjuvant CAPOX ± cetuximab in a randomised phase II trial. KRAS mutation in G12D, G12V or G13D was detected in the ctDNA of 43% and 35% of patients with tumours that were mutant and wild-type for these hotspot mutations, respectively, according to standard PCR-based analyses on tissue. The detection rate in the ctDNA of 10 patients with less common mutations was 50%. In 26 cases ctDNA analysis revealed KRAS mutations that were not previously found in tissue. Twenty-two of these (84.6%) were detected following repeat tissue testing by ddPCR. Overall, the ctDNA detection rate in the KRAS mutant population was 66%. Detection of KRAS mutation in ctDNA failed to predict prognosis or refine patient selection for cetuximab. While this study confirms the feasibility of ctDNA analysis in LARC and the high sensitivity of ddPCR, larger series are needed to better address the role of ctDNA as a prognostic or predictive tool in this setting.

Stem rust was one of the most devastating diseases of barley in North America. Through the deployment of cultivars with the resistance gene Rpg1, losses to stem rust have been minimal over the past 70 yr. However, there exist both domestic (QCCJB) and foreign (TTKSK aka isolate Ug99) pathotypes with virulence for this important gene. To identify new sources of stem rust resistance for barley, we evaluated the Wild Barley Diversity Collection (WBDC) (314 ecogeographically diverse accessions of Hordeum vulgare subsp. spontaneum) for seedling resistance to four pathotypes (TTKSK, QCCJB, MCCFC, and HKHJC) of the wheat stem rust pathogen (Puccinia graminis f. sp. tritici, Pgt) and one isolate (92-MN-90) of the rye stem rust pathogen (P. graminis f. sp. secalis, Pgs). Based on a coefficient of infection, the frequency of resistance in the WBDC was low ranging from 0.6% with HKHJC to 19.4% with 92-MN-90. None of the accessions was resistant to all five cultures of P. graminis. A genome-wide association study (GWAS) was conducted to map stem rust resistance loci using 50,842 single-nucleotide polymorphic markers generated by genotype-by-sequencing and ordered using the new barley reference genome assembly. After proper accounting for genetic relatedness and structure among accessions, 45 quantitative trait loci were identified for resistance to P. graminis across all seven barley chromosomes. Three novel loci associated with resistance to TTKSK, QCCJB, MCCFC, and 92-MN-90 were identified on chromosomes 5H and 7H, and two novel loci associated with resistance to HKHJC were identified on chromosomes 1H and 3H. These novel alleles will enhance the diversity of resistance available for cultivated barley.

Abstract Background Pre-operative chemoradiotherapy (CRT) for MRI-defined, locally advanced rectal cancer is primarily intended to reduce local recurrence rates by downstaging tumours, enabling an improved likelihood of curative resection. However, in a subset of patients complete tumour regression occurs implying that no viable tumour is present within the surgical specimen. This raises the possibility that surgery may have been avoided. It is also recognised that response to CRT is a key determinant of prognosis. Recent radiological advances enable this response to be assessed pre-operatively using the MRI tumour regression grade (mrTRG). Potentially, this allows modification of the baseline MRI-derived treatment strategy. Hence, in a ‘good’ mrTRG responder, with little or no evidence of tumour, surgery may be deferred. Conversely, a ‘poor response’ identifies an adverse prognostic group which may benefit from additional pre-operative therapy. Methods/design TRIGGER is a multicentre, open, interventional, randomised control feasibility study with an embedded phase III design. Patients with MRI-defined, locally advanced rectal adenocarcinoma deemed to require CRT will be eligible for recruitment. During CRT, patients will be randomised (1:2) between conventional management, according to baseline MRI, versus mrTRG-directed management. The primary endpoint of the feasibility phase is to assess the rate of patient recruitment and randomisation. Secondary endpoints include the rate of unit recruitment, acute drug toxicity, reproducibility of mrTRG reporting, surgical morbidity, pathological circumferential resection margin involvement, pathology regression grade, residual tumour cell density and surgical/specimen quality rates. The phase III trial will focus on long-term safety, regrowth rates, oncological survival analysis, quality of life and health economics analysis. Discussion The TRIGGER trial aims to determine whether patients with locally advanced rectal cancer can be recruited and subsequently randomised into a control trial that offers MRI-directed patient management according to radiological response to CRT (mrTRG). The feasibility study will inform a phase III trial design investigating stratified treatment of good and poor responders according to 3-year disease-free survival, colostomy-free survival as well as an increase in cases managed without a major resection. Trial registration ClinicalTrials.gov, ID: NCT02704520 . Registered on 5 February 2016.

Grain yield is a trait of paramount importance in the breeding of all cereals. In wheat (Triticum aestivum L.), yield has steadily increased since the Green Revolution, though the current rate of increase is not forecasted to keep pace with demand due to growing world population and increasing affluence. While several genome-wide association studies (GWAS) on yield and related component traits have been performed in wheat, the previous lack of a reference genome has made comparisons between studies difficult. In this study, a GWAS for yield and yield-related traits was carried out on a population of 322 soft red winter wheat lines across a total of four rain-fed environments in the state of Virginia using single-nucleotide polymorphism (SNP) marker data generated by a genotyping-by-sequencing (GBS) protocol. Two separate mixed linear models were used to identify significant marker-trait associations (MTAs). The first was a single-locus model utilizing a leave-one-chromosome-out approach to estimating kinship. The second was a sub-setting kinship estimation multi-locus method (FarmCPU). The single-locus model identified nine significant MTAs for various yield-related traits, while the FarmCPU model identified 74 significant MTAs. The availability of the wheat reference genome allowed for the description of MTAs in terms of both genetic and physical positions, and enabled more extensive post-GWAS characterization of significant MTAs. The results indicate a number of promising candidate genes contributing to grain yield, including an ortholog of the rice aberrant panicle organization (APO1) protein and a gibberellin oxidase protein (GA2ox-A1) affecting the trait grains per square meter, an ortholog of the Arabidopsis thaliana mother of flowering time and terminal flowering 1 (MFT) gene affecting the trait seeds per square meter, and a B2 heat stress response protein affecting the trait seeds per head.

Although kernel weight (KW) is a major component of grain yield, its contribution to yield genetic gain during breeding history has been minimal. This highlights an untapped potential for further increases in yield via improving KW. We investigated variation and genetics of KW and kernel length (KL) via genome-wide association studies (GWAS) using a historical and contemporary soft red winter wheat population representing 200 years of selection and breeding history in the United States. The observed changes of KW and KL over time did not show any conclusive trend. The population showed a structure, which was mainly explained by the time and location of germplasm development. Cluster sharing by germplasm from more than one breeding population was suggestive of episodes of germplasm exchange. Using 2 years of field-based phenotyping, we detected 26 quantitative trait loci (QTL) for KW and 27 QTL for KL with –log10(p) > 3.5. The search for candidate genes near the QTL on the wheat genome version IWGSCv1.0 has resulted in over 500 genes. The predicted functions of several of these genes are related to kernel development, photosynthesis, sucrose and starch synthesis, and assimilate remobilization and transport. We also evaluated the effect of allelic polymorphism of genes previously reported for KW and KL by using Kompetitive Allele Specific PCR (KASP) markers. Only TaGW2 showed significant association with KW. Two genes, i.e., TaSus2-2B and TaGS-D1 showed significant association with KL. Further physiological studies are needed to decipher the involvement of these genes in KW and KL development.

Wheat ( L.) spike characteristics determine the number of grains produced on each spike and constitute key components of grain yield. Understanding of the genetic basis of spike characteristics in wheat, however, is limited. In this study, genotyping-by-sequencing (GBS) and the iSelect 9K assay were used on a doubled-haploid (DH) soft red winter wheat population that showed a wide range of phenotypic variation for spike traits. A genetic map spanning 2934.1 cM with an average interval length of 3.4 cM was constructed. Quantitative trait loci (QTL) analysis involving additive effects, epistasis (QQ) and QTL × environment (QE), and epistasis × environment (QQE) interactions detected a total of 109 QTL, 13 QE, and 20 QQ interactions in five environments. Spike characteristics were mainly determined by additive effects and were fine-tuned by QQ, QE, and QQE. Major QTL / explained up to 30.9% of the phenotypic variation for spike length (SL) and fertile spikelet number, .1 explained up to 15.6% of the phenotypic variation of grain number per spikelet, and explained up to 80.2% of the phenotypic variation for spike compactness. Additionally, QTL for correlated spike characteristics formed QTL clusters on chromosomes 1A, 5A, 2B, 3B, 5B, 1D, and 5D. This study expands the understanding of the genetic basis of spike characteristics in hexaploid wheat. A number of stable QTL detected in this study have potential to be used in marker-assisted selection. Additionally, the genetic map generated in this study could be used to study other traits of economic importance.

Fusarium head blight (FHB) is one of the most important wheat ( L.) diseases worldwide, and host resistance displays complex genetic control. A genome-wide association study (GWAS) was performed on 273 winter wheat breeding lines from the midwestern and eastern regions of the United States to identify chromosomal regions associated with FHB resistance. Genotyping-by-sequencing (GBS) was used to identify 19,992 single-nucleotide polymorphisms (SNPs) covering all 21 wheat chromosomes. Marker–trait associations were performed with different statistical models, the most appropriate being a compressed mixed linear model (cMLM) controlling for relatedness and population structure. Ten significant SNP–trait associations were detected on chromosomes 4A, 6A, 7A, 1D, 4D, and 7D, and multiple SNPs were associated with on chromosome 3B. Although combination of favorable alleles of these SNPs resulted in lower levels of severity (SEV), incidence (INC), and deoxynivalenol concentration (DON), lines carrying multiple beneficial alleles were in very low frequency for most traits. These SNPs can now be used for creating new breeding lines with different combinations of favorable alleles. This is one of the first GWAS using genomic resources from the International Wheat Genome Sequencing Consortium (IWGSC).

In wheat (Triticum aestivum L.), time from planting to spike emergence is influenced by genes controlling vernalization requirement and photoperiod response. Characterizing the available genetic diversity of known and novel alleles of VERNALIZATION1 (VRN1) and PHOTOPERIOD1 (PPD1) in winter wheat can inform approaches for breeding climate resilient cultivars. This study identified QTL for heading date (HD) associated with multiple VRN1 and PPD1 loci in a population developed from a cross between two early flowering winter wheat cultivars. When the population was grown in the greenhouse after partial vernalization treatment, major heading date QTLs co-located with the VRN-A1 and VRN-B1 loci. Copy number variation at the VRN-A1 locus influenced HD such that RIL having three copies required longer cold exposure to transition to flowering than RIL having two VRN-A1 copies. Sequencing vrn-B1 winter alleles of the parents revealed multiple polymorphisms in the first intron that were the basis of mapping a major HD QTL coinciding with VRN-B1. A 36 bp deletion in the first intron of VRN-B1 was associated with earlier HD after partial vernalization in lines having either two or three haploid copies of VRN-A1. The VRN1 loci interacted significantly and influenced time to heading in field experiments in Louisiana, Georgia and North Carolina. The PPD1 loci were significant determinants of heading date in the fully vernalized treatment in the greenhouse and in all field environments. Heading date QTL were associated with alleles having large deletions in the upstream regions of PPD-A1 and PPD-D1 and with copy number variants at the PPD-B1 locus. The PPD-D1 locus was determined to have the largest genetic effect, followed by PPD-A1 and PPD-B1. Our results demonstrate that VRN1 and PPD1 alleles of varying strength allow fine tuning of flowering time in diverse winter wheat growing environments.

Heading date in wheat (Triticum aestivum L.) and other small grain cereals is affected by the vernalization and photoperiod pathways. The reduced-height loci also have an effect on growth and development. Heading date, which occurs just prior to anthesis, was evaluated in a population of 299 hard winter wheat entries representative of the U.S. Great Plains region, grown in nine environments during 2011-2012 and 2012-2013. The germplasm was evaluated for candidate genes at vernalization (Vrn-A1, Vrn-B1, and Vrn-D1), photoperiod (Ppd-A1, Ppd-B1 and Ppd-D1), and reduced-height (Rht-B1 and Rht-D1) loci using polymerase chain reaction (PCR) and Kompetitive Allele Specific PCR (KASP) assays. Our objectives were to determine allelic variants known to affect flowering time, assess the effect of allelic variants on heading date, and investigate changes in the geographic and temporal distribution of alleles and haplotypes. Our analyses enhanced understanding of the roles developmental genes have on the timing of heading date in wheat under varying environmental conditions, which could be used by breeding programs to improve breeding strategies under current and future climate scenarios. The significant main effects and two-way interactions between the candidate genes explained an average of 44% of variability in heading date at each environment. Among the loci we evaluated, most of the variation in heading date was explained by Ppd-D1, Ppd-B1, and their interaction. The prevalence of the photoperiod sensitive alleles Ppd-A1b, Ppd-B1b, and Ppd-D1b has gradually decreased in U.S. Great Plains germplasm over the past century. There is also geographic variation for photoperiod sensitive and reduced-height alleles, with germplasm from breeding programs in the northern Great Plains having greater incidences of the photoperiod sensitive alleles and lower incidence of the semi-dwarf alleles than germplasm from breeding programs in the central or southern plains.

Fusarium head blight (FHB) resistance is quantitative and difficult to evaluate. Genomic selection (GS) could accelerate FHB resistance breeding. We used U.S. cooperative FHB wheat nursery data to evaluate GS models for several FHB resistance traits including deoxynivalenol (DON) levels. For all traits we compared the models: ridge regression (RR), Bayesian LASSO (BL), reproducing kernel Hilbert spaces (RKHS) regression, random forest (RF) regression, and multiple linear regression (MLR) (fixed effects). For DON, we evaluated additional prediction methods including bivariate RR models, phenotypes for correlated traits, and RF regression models combining markers and correlated phenotypes as predictors. Additionally, for all traits, we compared different marker sets including genomewide markers, FHB quantitative trait loci (QTL) targeted markers, and both sets combined. Genomic selection accuracies were always higher than MLR accuracies, RF and RKHS regression were often the most accurate methods, and for DON, marker plus trait RF regression was more accurate than all other methods. For all traits except DON, using QTL targeted markers alone led to lower accuracies than using genomewide markers. This study indicates that cooperative FHB nursery data can be useful for GS, and prior information about correlated traits and QTL could be used to improve accuracies in some cases.

The occurrence of epidemics of Fusarium head blight (FHB), caused by Schwabe, in U.S. winter wheat ( L.) during the past two decades led to significant emphasis on development of resistant cultivars. Understanding the genetic diversity, population structure (PS), and linkage disequilibrium (LD) in winter wheat in the eastern United States is important for marker-assisted breeding and association analysis in this germplasm. Lines selected from collaborative FHB screening nurseries were genotyped with simple sequence repeat (SSR), sequence tagged site (STS), and Diversity Array Technology (DArT) markers to assess LD, genetic diversity, and PS. The genomewide average of LD decay to < 0.2 was 9.9 cM and moderate levels of LD ( > 0.2) were generally constrained to markers less than 5 cM apart. Although the lines evaluated were targeted to distinct production zones of the eastern winter wheat region, cluster and principal component analyses did not detect separation of lines into subpopulations. The short, intense breeding history for scab resistance may have localized effects on LD. Lack of subgroups within our population could be due to intercrossing among common resistant parents and indicate frequent admixture and germplasm exchange among U.S. winter wheat programs focused on development of FHB resistant cultivars.

Accelerated wheat development and deployment of high-yielding, climate resilient, and disease resistant cultivars can contribute to enhanced food security and sustainable intensification. To facilitate gene discovery, we assembled an association mapping panel of 528 spring wheat landraces of diverse geographic origin for a genome-wide association study (GWAS). All accessions were genotyped using an Illumina Infinium 9K wheat single nucleotide polymorphism (SNP) chip and 4781 polymorphic SNPs were used for analysis. To identify loci underlying resistance to the major leaf spot diseases and to better understand the genomic patterns, we quantified population structure, allelic diversity, and linkage disequilibrium. Our results showed 32 loci were significantly associated with resistance to the major leaf spot diseases. Further analysis identified QTL effective against major leaf spot diseases of wheat which appeared to be novel and others that were previously identified by association analysis using Diversity Arrays Technology (DArT) and bi-parental mapping. In addition, several identified SNPs co-localized with genes that have been implicated in plant disease resistance. Future work could aim to select the putative novel loci and pyramid them in locally adapted wheat cultivars to develop broad-spectrum resistance to multiple leaf spot diseases of wheat via marker-assisted selection (MAS).

Purpose The benefit of neoadjuvant therapy for tumours above the peritoneal reflection is not clear. The purpose of this study is to demonstrate the feasibility and downstaging of treating locally advanced tumours from high rectum to distal sigmoid with preoperative chemoradiotherapy (CRT). Methods and Materials Seventeen patients with high rectal, recto-sigmoid or distal sigmoid tumours above the peritoneal reflection received neo-adjuvant CRT, selected on MRI findings indicating T4 disease or threatened circumferential resection margin. All patients were administered neoadjuvant chemotherapy, with Oxaliplatin or Mitomycin C and a Fluoropyrimidine. The pelvis received long-course CT-planned conformal RT, 45 Gy in 25 fractions, with a boost of 5.4–9 Gy in 3–5 fractions. Thirteen patients were treated with concomitant oral or intravenous Fluoropyrimidine chemotherapy. Results Median follow-up was 37 months. Overall survival was 82.35% (95% Confidence Interval (CI) 54.7–93.9) and disease free survival 81.25% (95% CI 52.5–93.5). Only 1 patient suffered loco-regional relapse. Chemotherapy regimens were well tolerated, though some patients required dose reductions. Nine patients (52.9%) lowered pathologic disease AJCC stage, i.e. ‘downstaged’. Six patients (35.3%) achieved complete pathological response. Clear margins were attained in all but 1 patient. Three patients were converted from cT4 to ypT3. No patient required a gap during CRT. One patient suffered a grade III acute toxicity, but no grade IV (RTOG). There were 3 grade III and 3 grade IV late toxicities (LENT-SOMA). Conclusions Locally advanced high rectal and recto-sigmoid tumours may be treated with pre-operative CRT with acceptable toxicity, impressive down-staging, and clear surgical margins.

Purpose To investigate the relationship between extramural venous invasion (EMVI) detected at T2-weighted MRI and nodal disease rectal cancer compared with histopathology. Materials and Methods The MR imaging of 79 consecutive patients with rectal cancer who underwent primary rectal surgery without neoadjuvant treatment were reviewed. MR images were scored by an expert radiologist for the presence and degree of EMVI using a five point scale blinded to pathological findings. Receiver operating characteristic curve analyses were performed to determine the sensitivity and specificity of MRI scoring in predicting EMVI and nodal disease at histopathology. Results Compared with histology, an MR score of >2 was found to have 100% sensitivity (95% CI: 77%-100%) and 89% specificity (95% CI: 79%–96%) in identifying EMVI involving veins >3 mm in diameter. An EMVI score of >2 was had a sensitivity of 56% (95% CI: 30%–80%) and specificity of 81% (95% CI: 69%–90%) for identifying patients with stage N2 disease. Conclusions EMVI score of >2 on T2-weighted MR imaging has a high sensitivity and specificity for histopathologically proven extramural venous invasion involving venules ≥3 mm in diameter. However, EMVI scores have only moderate sensitivity in the predicting nodal involvement.