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Germplasm collections hold valuable allelic diversity for crop improvement and genetic mapping of complex traits. To gain access to the genetic diversity within the USDA National Small Grain Collection (NSGC), we developed the Barley Recombinant Inbred Diverse Germplasm Population (BRIDG6), a six-row spring barley multiparent population (MPP) with 88 cultivated accessions crossed to a common parent (Rasmusson). The parents were randomly selected from a core subset of the NSGC that represents the genetic diversity of landrace and breeding accessions. In total, we generated 6160 F5 recombinant inbred lines (RILs), with an average of 69 and a range of 37-168 RILs per family, that were genotyped with 7773 SNPs, with an average of 3889 SNPs segregating per family. We detected 23 quantitative trait loci (QTL) associated with flowering time with five QTL found coincident with previously described flowering time genes. A major QTL was detected near the flowering time gene, HvPpd-H1 which affects photoperiod. Haplotype-based analysis of HvPpd-H1 identified private alleles to families of Asian origin conferring both positive and negative effects, providing the first observation of flowering time-related alleles private to Asian accessions. We evaluated several subsampling strategies to determine the effect of sample size on the power of QTL detection, and found that, for flowering time in barley, a sample size >50 families or 3000 individuals results in the highest power for QTL detection. This MPP will be useful for uncovering large and small effect QTL for traits of interest, and identifying and utilizing valuable alleles from the NSGC for barley improvement.

The modeling of genotype × environment interactions (GEI) is important to understand how new crops perform in different environments and management systems. Naked barley (Hordeum vulgare L.) is a type of barley where the hull threshes freely from the grain and can be used for multiple end uses, including food, malt, and animal feed. We examined the performance of a winter naked barley trial grown in organic conditions across three regions and 3 years in northern latitude regions of the United States. We recorded yield, test weight, heading date, plant height, threshability, winter survival, barley stripe rust (Puccinia striiformis f. sp. hordei Westend), barley scald (Rhynchosporium commune Zaffarano, McDonald and Linde sp. nov), and spot blotch (Cochliobolus sativus, anamorph Bipolaris sorokiniana (S. Ito & Kurib.). Barley stripe rust, plant height, heading date, preharvest sprouting, and threshability had high heritability and low GEI. Grain yield, test weight, scald, and winter survival had high GEI and were analyzed using the additive main effect and multiplicative interaction (AMMI) model, genotype plus GEI biplot (GGE), and Finlay–Wilkinson (FW) stability analysis. The environmental patterns explained by the AMMI and GGE models indicated that selection for high GEI traits should occur within target environments and across multiple years within the target environments. Environmental groups were separated by Oregon as the first group and Wisconsin and New York as the second group. Core Ideas: Barley stripe rust, plant height, heading date, preharvest sprouting, and threshability had high heritability and low genotype × environment interactions.Grain yield, test weight, scald, and winter survival had high genotype × environment interaction effects.Environmental groupings were separated into OR as the first group and NY and WI as the second group. [ABSTRACT FROM AUTHOR]

Fusarium head blight (FHB) or scab is a devastating disease of barley that severely reduces the yield and quality of the grain. Additionally, mycotoxins produced by the causal Fusarium species can contaminate harvested grain, resulting in food safety concerns and further economic losses. In the Upper Midwest region of the United States, Fusarium graminearum is the primary causal agent, and deoxynivalenol (DON) is the main mycotoxin associated with Fusarium infection. Deployment of resistant cultivars is an important component of an integrated strategy to manage this disease. Unfortunately, few good sources of FHB resistance have been identified from the evaluation of large collections of Hordeum germplasm. Over the past 25 years, many barley mapping populations have been developed with selected resistance sources to identify the number, chromosomal position and allelic effect of quantitative trait loci (QTL) contributing to FHB resistance and DON accumulation. To consolidate the genetic data generated from 14 mapping studies that included 22 bi‐ or tri‐parental mapping populations and three genome‐wide association (GWAS) mapping panels, a consensus map was constructed that includes 4145 SNP, SSR, RFLP and AFLP markers. A meta‐analysis based on this consensus map revealed 96 QTL for FHB resistance and 57 for DON accumulation scattered across the barley genome. Many of the QTL explained a low percentage (<10%) of variation for the traits and were often found significant in only one or a few environments in multi‐year/multi‐location field trials. Moreover, many of the FHB/DON QTL mapped to chromosomal positions coincided with various agro‐morphological traits that could influence the level of disease (e.g. heading date, height, spike density, and spike angle), raising the important question of whether the former are true resistance factors or are simply the result of pleiotropy with the latter. Considering the magnitude of effect, consistency of detection across environments and independence from agro‐morphological traits, only three of 96 QTL for FHB and five of 57 QTL for DON were considered priority targets for marker‐assisted selection (MAS). In spite of the challenge for having a limited number of useful QTL for breeding, genomic selection holds promise for increasing the efficiency of developing FHB‐resistant barley cultivars, an essential component of the overall management strategy for the disease. [ABSTRACT FROM AUTHOR]

Threshability, defined here as the propensity of grains to lose their hull after harvest, is a key trait in naked barley (Hordeum vulgare L.). While threshability is a defining characteristic of naked grains and has been found to be associated with grain size and shape, its genetic architecture is poorly described. The goals of this study were to identify quantitative trait loci associated with threshability and evaluate their utility as covariates in genomic prediction models. A genome‐wide association study identified two loci on chromosomes 2H and 3H associated with threshability. The locus on chromosome 2H accounted for 9.9% of the phenotypic variance explained (PVE). The locus on chromosomes 3H accounted for 7.8% of the PVE. With effects on threshability of 0.18 and 0.29 for each marker, respectively, these markers could have a limited impact when implemented in marker‐assisted selection. Predictive ability for threshability was 0.842 using a structured genomic best linear unbiased prediction model. Incorporation of the markers with significant associations as covariates in the model did not improve predictive ability. Predictive ability was improved by the use of a multi‐trait model including grain test weight. The high predictive ability for threshability overall indicate that genomic selection would be useful in selection for threshability in naked barley. Core Ideas: Two markers were identified with significant associations to threshability.Predictive ability for threshability was 0.842 using a structured gBLUP model.Predictive ability was not increased by inclusion of identified QTL as covariates.Predictive ability was increased using a multi‐trait prediction model. [ABSTRACT FROM AUTHOR]

SUMMARY: The distribution of recombination events along large cereal chromosomes is uneven and is generally restricted to gene‐rich telomeric ends. To understand how the lack of recombination affects diversity in the large pericentromeric regions, we analysed deep exome capture data from a final panel of 815 Hordeum vulgare (barley) cultivars, landraces and wild barleys, sampled from across their eco‐geographical ranges. We defined and compared variant data across the pericentromeric and non‐pericentromeric regions, observing a clear partitioning of diversity both within and between chromosomes and germplasm groups. Dramatically reduced diversity was found in the pericentromeres of both cultivars and landraces when compared with wild barley. We observed a mixture of completely and partially differentiated single‐nucleotide polymorphisms (SNPs) between domesticated and wild gene pools, suggesting that domesticated gene pools were derived from multiple wild ancestors. Patterns of genome‐wide linkage disequilibrium, haplotype block size and number, and variant frequency within blocks showed clear contrasts among individual chromosomes and between cultivars and wild barleys. Although most cultivar chromosomes shared a single major pericentromeric haplotype, chromosome 7H clearly differentiated the two‐row and six‐row types associated with different geographical origins. Within the pericentromeric regions we identified 22 387 non‐synonymous SNPs, 92 of which were fixed for alternative alleles in cultivar versus wild accessions. Surprisingly, only 29 SNPs found exclusively in the cultivars were predicted to be 'highly deleterious'. Overall, our data reveal an unconventional pericentromeric genetic landscape among distinct barley gene pools, with different evolutionary processes driving domestication and diversification. Significance Statement: We have explored genetic variation in regions of the genome that have been genetically inaccessible, comparing wild progenitors with domesticated barleys. This study provides a more nuanced understanding to help in the future exploitation of breeding improvement. [ABSTRACT FROM AUTHOR]

Predicting the performance of new plant genotypes under new environmental conditions could accelerate the development of locally adapted and climate resilient cultivars. Enabling these predictions may rely on extending the genomewide prediction framework to include environmental covariates (EC), but such models have generally been tested under limited, less breeding‐realistic contexts. Using a barley (Hordeum vulgare L.) multi‐environment dataset, our objectives were to compare multi‐environment prediction models and scenarios that target genotypes from different breeding generations, use different levels and timescales of ECs, and are applied to different agronomic and quality traits. When predicting the phenotypes of previously tested genotypes in untested environments, models that included the interaction of genomewide markers and pre‐selected in‐season ECs resulted in more accurate predictions (rMG or rMP) within (rMG = 0.56–0.94) and across (rMP = 0.63–0.87) environments; similar accuracy was achieved within (rMP = 0.46–0.89) and across (rMP = 0.87–0.95) locations when using only ECs from realistically available historical climate data. Shifting the prediction target to a distinct, untested offspring population slightly reduced model performance within environments or locations, but rMP across environments (rMP = 0.60–0.86) or locations (rMP = 0.87–0.94) remained very high. Though we achieved moderately high rMP for most traits in the challenging scenario of predicting the offspring population in holdout environments, the similarity between training and target environments, like that between populations, will be a limiting factor for enabling accurate predictions of new genotypes under new growing conditions. Core Ideas: Genomewide prediction with select environmental covariates led to accurate whole‐phenotype predictions.Historical climate data enabled a more breeding‐realistic framework for predicting phenotypes in new locations.Predictive ability was improved for both tested genotypes and untested offspring across new environments.Genetic and environmental similarity may have limited accuracy of untested offspring in holdout environments. [ABSTRACT FROM AUTHOR]

Winter survival is a major yield-limiting factor in winter barley grown in the Upper Midwest, where winter temperatures regularly reach-20°C or lower. Here, we tested the hypothesis that improved freezing survival is associated with smaller xylem vessel diameters as a mechanism that minimizes physical damage arising from intracellular ice formation, using leaf vasculature as a proxy trait. A second goal was to test whether such anatomical differences could be captured non-destructively via gas exchange measurements. We first identified a group of 11 winter barley genotypes that exhibited differential field winter survival. We then conducted xylem diameter measurements on the first three leaves on all genotypes in two independent experiments based on 1,188 images, in addition to leaf gas exchange measurements. Freezing-tolerant genotypes consistently exhibited significantly smaller metaxylem vessel diameters irrespective of leaf rank, and this difference was not influenced by hardening, indicating that this trait is heritable. Additionally, genotypes with smaller vasculature tended to exhibit lower stomatal conductance and transpiration rates. Our data indicate that genotypes with leaf xylem diameters smaller than 30 µm are prime donor parents and could be identified using gas exchange measurements, pointing to new phenotyping approaches to accelerate breeding for freezing survival. [ABSTRACT FROM AUTHOR]

Naked barley (Hordeum vulgare L.) grain threshes freely from its hull during harvesting and cleaning. Much of the available naked barley germplasm is unadapted to U.S. barley growing regions, and few genotypes have been selected to thrive under organic systems. The goal of this research was to characterize a set of spring naked barley genotypes for agronomic traits in the northern United States under organic conditions and estimate the degree of genotype × environment interaction (GEI). To achieve this goal, a multienvironment trial was conducted over 3 yr. Experiments were grown under organic conditions where traits including grain yield, test weight, plant height, heading date, and threshability were evaluated. Contributions of environment, genotype, and GEI to the phenotypic variance were calculated. In the tested germplasm, test weight, plant height, heading date, and threshability were found to have higher variance attributed to genotypic effects compared to GEI. Grain yield variance attributed to GEI was five times greater than that of genotype alone. Genotype + GEI (GGE) and location‐grouping (LG) biplots showed two sets of environments where naked barley genotypes performed similarly. Sensitivity analysis by Finlay–Wilkinson regression found that grain yield was highly sensitive to changes in environment mean yield. These results show that selection for grain yield should be conducted within mega‐environments to leverage GEI patterns. Heading date, plant height, test weight, and threshability can be selected across mega‐environments. Core Ideas: There is five‐times greater genotype × environment interaction (GEI) than genetic variance for grain yield. Biplots define two mega‐environments in the northern United States for naked barley grain yield. Other assessed agronomic traits and threshability are more affected by genotype than GEI. [ABSTRACT FROM AUTHOR]

Plant breeding programs expend significant resources on multilocation testing to evaluate genotypes for advancement or potential cultivar release. The selection of genotype entries for these trials is typically based on previous phenotypic data or predictions; yet locations, important contributors to nongenetic variation, are often chosen in a less data‐driven manner. Using agronomic and quality trait data from two long‐term regional barley (Hordeum vulgare L.) nurseries, our objectives were (a) to measure the precision, repeatability, and representativeness of test locations based on multitrait data and (b) to optimize the selection of test locations for use in future trials. When considering traits individually, ideal locations could be identified simply, but a combined analysis of 11 traits indicated that very few locations were broadly favorable, and considerable tradeoffs are necessary. We developed a flexible optimization procedure to select the locations based on their precision, repeatability, and representativeness for multiple traits while simultaneously constraining the total number of locations. Optimization led to a 58–75% reduction in the number of locations, and therefore phenotyping costs, with little loss in data utility. Importantly, our approach allowed locations to be selected for phenotyping different sets of traits (e.g., either agronomic or both agronomic and malting quality), mimicking the often nested structure of trait data collection. This approach may be useful for individual plant breeding programs or collaborations wishing to increase the resource efficiency of these important regional evaluation trials. Core Ideas: Test locations in regional barley breeding nurseries were evaluated for multiple traits.No single location was ever superior for genotypic evaluation of many traits.Optimization identified a reduced set of locations with little loss in phenotypic data utility. [ABSTRACT FROM AUTHOR]

Climate changes leading to higher summer temperatures can adversely affect cool season crops like spring barley. In the Upper Midwest region of the United States, one option for escaping this stress factor is to plant winter or facultative type cultivars in the autumn and then harvest in early summer before the onset of high-temperature stress. However, the major challenge in breeding such cultivars is incorporating sufficient winter hardiness to survive the extremely low temperatures that commonly occur in this production region. To broaden the genetic base for winter hardiness in the University of Minnesota breeding program, 2,214 accessions from the N. I. Vavilov Institute of Plant Industry (VIR) were evaluated for winter survival (WS) in St. Paul, Minnesota. From this field trial, 267 (>12%) accessions survived [designated as the VIR-low-temperature tolerant (LTT) panel] and were subsequently evaluated for WS across six northern and central Great Plains states. The VIR-LTT panel was genotyped with the Illumina 9K SNP chip, and then a genome-wide association study was performed on seven WS datasets. Twelve significant associations for WS were identified, including the previously reported frost resistance gene FR-H2 as well as several novel ones. Multi-allelic haplotype analysis revealed the most favorable alleles for WS in the VIR-LTT panel as well as another recently studied panel (CAP-LTT). Seventy-eight accessions from the VIR-LTT panel exhibited a high and consistent level of WS and select ones are being used in winter barley breeding programs in the United States and in a multiparent population. [ABSTRACT FROM AUTHOR]

Summary: Circadian clock rhythms are shown to be intertwined with crop adaptation. To realize the adaptive value of changes in these rhythms under crop domestication and improvement, there is a need to compare the genetics of clock and yield traits.We compared circadian clock rhythmicity based on Chl leaf fluorescence and transcriptomics among wild ancestors, landraces, and breeding lines of barley under optimal and high temperatures. We conducted a genome scan to identify pleiotropic loci regulating the clock and field phenotypes. We also compared the allelic diversity in wild and cultivated barley to test for selective sweeps.We found significant loss of thermal plasticity in circadian rhythms under domestication. However, transcriptome analysis indicated that this loss was only for output genes and that temperature compensation in the core clock machinery was maintained. Drivers of the circadian clock (DOC) loci were identified via genome‐wide association study. Notably, these loci also modified growth and reproductive outputs in the field. Diversity analysis indicated selective sweep in these pleiotropic DOC loci.These results indicate a selection against thermal clock plasticity under barley domestication and improvement and highlight the importance of identifying genes underlying for understanding the biochemical basis of crop adaptation to changing environments. [ABSTRACT FROM AUTHOR]

In plant breeding, the goal of genomewide selection is to predict the merit of unobserved individuals, particularly those in the next breeding generation. Predictions of these individuals in unobserved or future environments would be of additional use to a breeder. For many of the complex traits targeted in breeding, this may require management of genotype × environment interactions by, for example, using data from homogeneous groups of environments. Our objectives were to assess the accuracy of genomewide predictions in unobserved environments both within and between breeding generations; we aimed to compare training sets that included data from all possible environments with those that included data from (a) decreasingly similar environments or (b) discrete clusters of similar environments. A 183‐line spring barley (Hordeum vulgare L.) training population and 50‐line offspring test population were phenotyped in 29 location–year environments for grain yield, heading date, and plant height. Environmental similarities were measured using phenotypic data, geographic distance, or environmental covariables. When using training data from more, but decreasingly similar environments, prediction accuracy increased, but marginal gains declined; in some cases, accuracy declined with additional data. Clusters of environments informed by phenotypes (i.e., phenotypic correlations or multiplicative models) typically improved prediction accuracy within a generation, but not between generations (offspring population). Our study suggests that, as an alternative to using data from all available environments, informative subsets may be advantageous for genomewide predictions within a single breeding generation, but not between generations. [ABSTRACT FROM AUTHOR]

Featured Application: The featured application of this work is the optimization of breeding techniques for plants susceptible to being damaged by wind. Stem lodging is the bending or breakage of stems in the wind that result in negative economic impacts to producers and processors of small grain crops. To address this issue, plant breeders attempt to quantify lodging using proxy traits such as stem structure and biomechanics. Stem lodging is a function of both stem strength and elasticity. In this paper, we explore the biomechanics of stems approaching the lodging, or permanent bending, condition. Oat, wheat, and two types of barley varying in lodging resistance were exposed to standard growing conditions over the course of a season. Their capability of returning from a bent to unbent state was characterized using a push force meter that measured resistant force and displacement over time. Changes in stem energy and power were then calculated using displacement and force measurements. Lodging susceptibility could be differentiated by stem strength, displacement and change in power measurements depending on small grain species without damaging the plant. These measurements could be used by small cereal grain breeding programs as proxy traits to determine lodging susceptibility without destructively testing or waiting for storm events, thus saving time and resources. [ABSTRACT FROM AUTHOR]

One option to achieving greater resiliency for barley production in the face of climate change is to explore the potential of winter and facultative growth habits: for both types, low temperature tolerance (LTT) and vernalization sensitivity are key traits. Sensitivity to short-day photoperiod is a desirable attribute for facultative types. In order to broaden our understanding of the genetics of these phenotypes, we mapped quantitative trait loci (QTLs) and identified candidate genes using a genome-wide association studies (GWAS) panel composed of 882 barley accessions that was genotyped with the Illumina 9K single-nucleotide polymorphism (SNP) chip. Fifteen loci including 5 known and 10 novel QTL/genes were identified for LTT—assessed as winter survival in 10 field tests and mapped using a GWAS meta-analysis. FR-H1 , FR-H2 , and FR-H3 were major drivers of LTT, and candidate genes were identified for FR-H3. The principal determinants of vernalization sensitivity were VRN-H1 , VRN-H2 , and PPD-H1. VRN-H2 deletions conferred insensitive or intermediate sensitivity to vernalization. A subset of accessions with maximum LTT were identified as a resource for allele mining and further characterization. Facultative types comprised a small portion of the GWAS panel but may be useful for developing germplasm with this growth habit. [ABSTRACT FROM AUTHOR]

In barley (Hordeum vulgare L.), lateral branches called tillers contribute to grain yield and define shoot architecture, but genetic control of tiller number and developmental rate are not well characterized. The primary objectives of this work were to examine relationships between tiller number and other agronomic and morphological traits and identify natural genetic variation associated with tiller number and rate, and related traits. We grew 768 lines from the USDA National Small Grain Collection in the field and collected data over two years for tiller number and rate, and agronomic and morphological traits. Our results confirmed that spike row-type and days to heading are correlated with tiller number, and as much as 28% of tiller number variance was associated with these traits. In addition, negative correlations between tiller number and leaf width and stem diameter were observed, indicating trade-offs between tiller development and other vegetative growth. Thirty-three quantitative trait loci (QTL) were associated with tiller number or rate. Of these, 40% overlapped QTL associated with days to heading and 22% overlapped QTL associated with spike row-type, further supporting that tiller development is associated with these traits. Some QTL associated with tiller number or rate, including the major QTL on chromosome 3H, were not associated with other traits, suggesting that some QTL may be directly related to rate of tiller development or axillary bud number. These results enhance our knowledge of the genetic control of tiller development in barley, which is important for optimizing tiller number and rate for yield improvement. [ABSTRACT FROM AUTHOR]

Key message: Association mapping study conducted in a population of 3490 elite barley breeding lines from ten barley breeding programs of the USA identified 12 QTLs for resistance/susceptibility to net form of net blotch. Breeding resistant varieties is the best management strategy for net form of net blotch (NFNB) in barley (Hordeum vulgare L.) caused by Pyrenophora teres f. teres (Ptt). Several resistance QTL have been previously identified in barley via linkage mapping and genome-wide association studies (GWAS). A GWAS conducted in a collection of advanced breeding lines (n = 3490) representing elite germplasm from ten barley breeding programs of the USA identified 42 unique marker-trait associations (MTA) for NFNB resistance. The lines were genotyped with 3072 SNP markers and phenotyped with four Ptt isolates in controlled environment. The lines were used to construct 13 different GWAS panels. Efficient mixed model association method with principal components and kinship was used for GWAS. Significance threshold for MTA was set at a false discovery rate of 0.05. Two, eight, six, one and 25 MTA were identified in chromosomes 1H, 3H, 4H, 5H and 6H, respectively. Based on genetic positions and linkage disequilibrium, these MTA's correspond to two, three, two, one and four QTLs in chromosome 1H, 3H, 4H, 5H and 6H, respectively. A comparison with previous linkage and GWAS studies revealed several previously identified and novel QTLs. Moreover, different genomic regions were found to be responsible for NFNB resistance in two-row versus six-row germplasm. The germplasm-specific SNP markers with additive effects and allelic distribution is reported to facilitate breeders in selection of markers for MAS to introgress novel net blotch resistance. [ABSTRACT FROM AUTHOR]

In the current study, 248 two‐rowed and another 253 six‐rowed spring barley (Hordeum vulgare L.) breeding lines from several US barley breeding programs were evaluated in multiple locations in Egypt to select for potentially adapted lines. The introduced plant materials were planted in two locations during three growing seasons (2015, 2016, and 2017). The focus of the first growing season was to increase available seeds and collect preliminary observations. During the second and third growing seasons, the advanced plant materials and local check cultivars were planted in an incomplete block design in two replicates within three locations. Grain yield, leaf rust, number of days to flowering, and plant height were measured. Based on grain yield production, the top 94 lines from the two‐rowed and 100 from the six‐rowed barley lines were selected and advanced for further evaluation in 2017. The introduced materials contained several lines that consistently outperformed the check cultivars. Therefore, these lines could be used as parents to improve barley production and enhance genetic diversity or be directly released as cultivars after appropriate testing in Egypt. [ABSTRACT FROM AUTHOR]

Predicting the genetic variance among progeny from a cross—prior to making said cross—would be a valuable metric for plant breeders to discriminate among possible parent combinations. The use of genomewide markers and simulated populations is one proposed method for making such predictions. Our objective was to assess the predictive ability of this method for three relevant quantitative traits within a breeding program regularly using genomewide selection. Using a training population of two‐row barley (Hordeum vulgare L.) lines, we predicted the mean (μ), genetic variance (VG), and superior progeny mean (μSP, mean of the best 10% of lines) of 330,078 possible parent combinations for Fusarium head blight (FHB) severity, heading date, and plant height. Twenty‐seven of these combinations were chosen to develop biparental populations, which were subsequently phenotyped for the same traits. We found that the predictive abilities (rMP) for μ and μSP were moderate to high (rMP = 0.46–0.69), whereas those for VG were lower (rMP = 0.01–0.48). Unsurprisingly, predictive ability was likely a function of trait heritability, as rMP estimates for heading date (the most heritable trait) were highest, and rMP estimates for FHB severity (the least heritable trait) were lowest. We observed strong negative bias when predicting VG (on average −83 to −96%), but the relative consistency of this bias across validation families indicates that it may have little impact when selecting crosses. We concluded that accurate predictions of VG and μSP are feasible, but as with any implementation of genomewide selection, reliable phenotypic data are critical. [ABSTRACT FROM AUTHOR]

Fusarium head blight (FHB) is an important fungal disease affecting the yield and quality of barley and other small grains. Developing and deploying resistant barley cultivars is an essential component of an integrated strategy for reducing the adverse effects of FHB. Genetic mapping studies have revealed that resistance to FHB and the accumulation of pathogen-produced mycotoxins are controlled by many quantitative trait loci (QTL) with minor effects and are highly influenced by plant morphological traits and environmental conditions. Some prior studies aimed at mapping FHB resistance have used populations derived from crossing a Swiss landrace Chevron with elite breeding lines/cultivars. Both Chevron and Peatland, a sib-line of Chevron, were used as founders in the University of Minnesota barley breeding program. To understand the native resistance that might be present in the Minnesota breeding materials, a cross of an elite cultivar with a susceptible unadapted genotype is required. Here, a mapping population of 93 recombinant inbred lines (RILs) was developed from a cross between a moderately susceptible elite cultivar ‘Rasmusson’ and a highly susceptible Japanese landrace PI 383933. This population was evaluated for FHB severity, deoxynivalenol (DON) accumulation and various agromorphological traits. Genotyping of the population was performed with the barley iSelect 9K SNP chip and 1,394 SNPs were used to develop a genetic map. FHB severity and DON accumulation were negatively correlated with plant height (HT) and spike length (SL), and positively correlated with spike density (SD). QTL analysis using composite interval mapping (CIM) identified the largest effect QTL associated with FHB and DON on the centromeric region of chromosome 7H, which was also associated with HT, SL, and SD. A minor FHB QTL and a minor DON QTL were detected on chromosome 6H and chromosome 3H, respectively, and the Rasmusson alleles contributed to resistance. The 3H DON QTL likely represents native resistance in elite germplasm as the marker haplotype of Rasmusson at this QTL is distinct from that of Chevron. This study highlights the relationship between FHB resistance/susceptibility and morphological traits and the need for breeders to account for morphology when developing FHB resistant genotypes. [ABSTRACT FROM AUTHOR]

Bacterial leaf streak (BLS), caused chiefly by the pathogen Xanthomonas translucens pv. translucens, is becoming an increasingly important foliar disease of barley in the Upper Midwest. The deployment of resistant cultivars is the most economical and practical method of control. To identify sources of BLS resistance, we evaluated two panels of breeding lines from the University of Minnesota (UMN) and Anheuser-Busch InBev (ABI) barley improvement programs for reaction to strain CIX95 in the field at St. Paul and Crookston, MN, in 2020 and 2021. The percentage of resistant lines in the UMN and ABI panels with mid-season maturity was 1.8% (6 of 333 lines) and 5.2% (13 of 251 lines), respectively. Both panels were genotyped with the barley 50K iSelect SNP array, and then a genome-wide association study was performed. A single, highly significant association was identified for BLS resistance on chromosome 6H in the UMN panel. This association was also identified in the ABI panel. Seven other significant associations were detected in the ABI panel: two each on chromosomes 1H, 2H, and 3H and one on chromosome 5H. Of the eight associations identified in the panels, five were novel. The discovery of resistance in elite breeding lines will hasten the time needed to develop and release a BLS-resistant cultivar. [ABSTRACT FROM AUTHOR]

Background: Fusarium graminearum causes Fusarium head blight (FHB), a major disease problem worldwide. Resistance to FHB is controlled by quantitative trait loci (QTL) of which two are located on barley chromosomes 2H bin8 and 6H bin7. The mechanisms of resistance mediated by FHB QTL are poorly defined. Results: Near-isogenic lines (NILs) carrying Chevron-derived resistant alleles for the two QTL were developed and exhibited FHB resistance in field trials. To understand the molecular responses associated with resistance, transcriptomes of the NILs and recurrent parents (M69 and Lacey) were investigated with RNA sequencing (RNA-Seq) after F. graminearum or mock inoculation. A total of 2083 FHB-responsive transcripts were detected and provide a gene expression atlas for the barley-F. graminearum interaction. Comparative analysis of the 2Hb8 resistant (R) NIL and M69 revealed that the 2Hb8 R NIL exhibited an elevated defense response in the absence of fungal infection and responded quicker than M69 upon fungal infection. The 6Hb7 R NIL displayed a more rapid induction of a set of defense genes than Lacey during the early stage of fungal infection. Overlap of differentially accumulated genes were identified between the two R NILs, suggesting that certain responses may represent basal resistance to F. graminearum and/or general biotic stress response and were expressed by both resistant genotypes. Long noncoding RNAs (lncRNAs) have emerged as potential key regulators of transcription. A total of 12,366 lncRNAs were identified, of which 604 were FHB responsive. Conclusions: The current transcriptomic analysis revealed differential responses conferred by two QTL during F. graminearum infection and identified genes and lncRNAs that were associated with FHB resistance. [ABSTRACT FROM AUTHOR]

Fusarium head blight (FHB) and its associated mycotoxin, deoxynivalenol (DON), are the major biotic factors limiting cereal production in many parts of the world. A recent association mapping (AM) study of US six-row spring barley identified several modest effect quantitative trait loci (QTL) for DON and FHB. To date, few studies have attempted to verify the results of association analyses, particularly for complex traits such as DON and FHB resistance in barley. While AM methods use measures to control for the effects of population structure and multiple testing, false positive associations may still occur. A previous AM study used elite breeding germplasm to identify QTL for FHB and DON. To verify the results of that study, we evaluated the effects of the nine DON QTL using near-isogenic lines (NILs). We created families of contrasting homozygous haplotypes from lines in the original AM populations that were heterozygous for the DON QTL. Seventeen NIL families were evaluated for FHB and DON in three field experiments. Significant differences between contrasting NIL haplotypes were detected for three QTL across environments and/or genetic backgrounds, thereby confirming QTL from the original AM study. Several explanations for those QTL that were not confirmed are discussed, including the effect of genetic background and incomplete sampling of relevant haplotypes. [ABSTRACT FROM AUTHOR]

Over the past two decades many quantitative trait loci (QTL) have been detected; however, very few have been incorporated into breeding programs. The recent development of genome-wide association studies (GWAS) in plants provides the opportunity to detect QTL in germplasm collections such as unstructured populations from breeding programs. The overall goal of the barley Coordinated Agricultural Project was to conduct GWAS with the intent to couple QTL detection and breeding. The basic idea is that breeding programs generate a vast amount of phenotypic data and combined with cheap genotyping it should be possible to use GWAS to detect QTL that would be immediately accessible and used by breeding programs. There are several constraints to using breeding program-derived phenotype data for conducting GWAS namely: limited population size and unbalanced data sets. We chose the highly heritable trait heading date to study these two variables. We examined 766 spring barley breeding lines (panel #1) grown in balanced trials and a subset of 384 spring barley breeding lines (panel #2) grown in balanced and unbalanced trials. In panel #1, we detected three major QTL for heading date that have been detected in previous bi-parental mapping studies. Simulation studies showed that population sizes greater than 384 individuals are required to consistently detect QTL. We also showed that unbalanced data sets from panel #2 can be used to detect the three major QTL. However, unbalanced data sets resulted in an increase in the false-positive rate. Interestingly, one-step analysis performed better than two-step analysis in reducing the false-positive rate. The results of this work show that it is possible to use phenotypic data from breeding programs to detect QTL, but that careful consideration of population size and experimental design are required. [ABSTRACT FROM AUTHOR]

Background: Considerations in applying association mapping (AM) to plant breeding are population structure and size: not accounting for structure and/or using small populations can lead to elevated false-positive rates. The principal determinants of population structure in cultivated barley are growth habit and inflorescence type. Both are under complex genetic control: growth habit is controlled by the epistatic interactions of several genes. For inflorescence type, multiple loss-of-function alleles in one gene lead to the same phenotype. We used these two traits as models for assessing the effectiveness of AM. This research was initiated using the CAP Core germplasm array (n = 102) assembled at the start of the Barley Coordinated Agricultural Project (CAP). This array was genotyped with 4,608 SNPs and we re-sequenced genes involved in morphology, growth and development. Larger arrays of breeding germplasm were subsequently genotyped and phenotyped under the auspices of the CAP project. This provided sets of 247 accessions phenotyped for growth habit and 2,473 accessions phenotyped for inflorescence type. Each of the larger populations was genotyped with 3,072 SNPs derived from the original set of 4,608. Results: Significant associations with SNPs located in the vicinity of the loci involved in growth habit and inflorescence type were found in the CAP Core. Differentiation of true and spurious associations was not possible without a priori knowledge of the candidate genes, based on re-sequencing. The re-sequencing data were used to define allele types of the determinant genes based on functional polymorphisms. In a second round of association mapping, these synthetic markers based on allele types gave the most significant associations. When the synthetic markers were used as anchor points for analysis of interactions, we detected other known-function genes and candidate loci involved in the control of growth habit and inflorescence type. We then conducted association analyses - with SNP data only - in the larger germplasm arrays. For both vernalization sensitivity and inflorescence type, the most significant associations in the larger data sets were found with SNPs coincident with the synthetic markers used in the CAP Core and with SNPs detected via interaction analysis in the CAP Core. Conclusions: Small and highly structured collections of germplasm, such as the CAP Core, are cost-effectively phenotyped and genotyped with high-throughput markers. They are also useful for characterizing allelic diversity at loci in germplasm of interest. Our results suggest that discovery-oriented exercises in AM in such small arrays may generate a large number of false-positives. However, if haplotypes in candidate genes are available, they may be used as anchors in an analysis of interactions to identify other candidate regions harboring genes determining target traits. Using larger germplasm arrays, genome regions where the principal genes determining vernalization sensitivity and row type are located were identified. [ABSTRACT FROM AUTHOR]

Previous studies have shown that there is considerable population structure in cultivated barley (Hordeum vu/gare L.), with the strongest structure corresponding to differences in row number and growth habit. U.S. barley breeding programs include six-row and two-row types and winter and spring types in all combinations. To facilitate mapping of complex traits in breeding germplasm, 1816 barley lines from 10 U.S. breeding programs were scored with 1536 single nucleotide polymorphism (SNP) genotyping assays. The number of SNPs segregating within breeding programs varied from 854 to 1398. Model-based analysis of population structure showed the expected clustering by row type and growth habit; however, there was additional structure, some of which corresponded to the breeding programs. The model that fit the data best had seven populations: three two-row spring, two six-row spring, and two six-row winter. Average linkage disequilibrium (LD) within populations decayed over a distance of 20 to 30 cM, but some populations showed long-range LD suggestive of admixture. Genetic distance (allele-sharing) between populations varied from 0.11 (six-row spring vs. six-row spring) to 0.45 (two-row spring vs. six-row spring). Analyses of pairwise LD revealed that the phase of allelic associations was not well correlated between populations, particularly when their allele-sharing distance was >0.2. These results suggest that pooling divergent barley populations for purposes of association mapping may be inadvisable. [ABSTRACT FROM AUTHOR]

Background: Considerations in applying association mapping (AM) to plant breeding are population structure and size: not accounting for structure and/or using small populations can lead to elevated false-positive rates. The principal determinants of population structure in cultivated barley are growth habit and inflorescence type. Both are under complex genetic control: growth habit is controlled by the epistatic interactions of several genes. For inflorescence type, multiple loss-of-function alleles in one gene lead to the same phenotype. We used these two traits as models for assessing the effectiveness of AM. This research was initiated using the CAP Core germplasm array (n = 102) assembled at the start of the Barley Coordinated Agricultural Project (CAP). This array was genotyped with 4,608 SNPs and we re-sequenced genes involved in morphology, growth and development. Larger arrays of breeding germplasm were subsequently genotyped and phenotyped under the auspices of the CAP project. This provided sets of 247 accessions phenotyped for growth habit and 2,473 accessions phenotyped for inflorescence type. Each of the larger populations was genotyped with 3,072 SNPs derived from the original set of 4,608. Results: Significant associations with SNPs located in the vicinity of the loci involved in growth habit and inflorescence type were found in the CAP Core. Differentiation of true and spurious associations was not possible without a priori knowledge of the candidate genes, based on re-sequencing. The re-sequencing data were used to define allele types of the determinant genes based on functional polymorphisms. In a second round of association mapping, these synthetic markers based on allele types gave the most significant associations. When the synthetic markers were used as anchor points for analysis of interactions, we detected other known-function genes and candidate loci involved in the control of growth habit and inflorescence type. We then conducted association analyses - with SNP data only - in the larger germplasm arrays. For both vernalization sensitivity and inflorescence type, the most significant associations in the larger data sets were found with SNPs coincident with the synthetic markers used in the CAP Core and with SNPs detected via interaction analysis in the CAP Core. Conclusions: Small and highly structured collections of germplasm, such as the CAP Core, are cost-effectively phenotyped and genotyped with high-throughput markers. They are also useful for characterizing allelic diversity at loci in germplasm of interest. Our results suggest that discovery-oriented exercises in AM in such small arrays may generate a large number of false-positives. However, if haplotypes in candidate genes are available, they may be used as anchors in an analysis of interactions to identify other candidate regions harboring genes determining target traits. Using larger germplasm arrays, genome regions where the principal genes determining vernalization sensitivity and row type are located were identified. [ABSTRACT FROM AUTHOR]

Background: Advanced cycle breeding utilizes crosses among elite lines and is a successful method to develop new inbreds. However, it results in a reduction in genetic diversity within the breeding population. The development of malting barley varieties requires the adherence to a narrow malting quality profile and thus the use of advanced cycle breeding strategies. Although attention has been focused on diversity in gene expression and its association with genetic diversity, there are no studies performed in a single breeding program examining the implications that consecutive cycles of breeding have on gene expression variation and identifying the variability still available for future improvement. Results: Fifteen lines representing the historically important six-rowed malting barley breeding program of the University of Minnesota were genotyped with 1,524 SNPs, phenotypically examined for six malting quality traits, and analyzed for transcript accumulation during germination using the Barley1 GeneChip array. Significant correlation was detected between genetic and transcript-level variation. We observed a reduction in both genetic and gene expression diversity through the breeding process, although the expression of many genes have not been fixed. A high number of quality-related genes whose expression was fixed during the breeding process was identified, indicating that much of the diversity reduction was associated with the improvement of the complex phenotype "malting quality", the main goal of the University of Minnesota breeding program. We also identified 49 differentially expressed genes between the most recent lines of the program that were correlated with one or more of the six primary malting quality traits. These genes constitute potential targets for the improvement of malting quality within the breeding program. Conclusions: The present study shows the repercussion of advanced cycle breeding on gene expression diversity within an important barley breeding program. A reduction in gene expression diversity was detected, although there is diversity still present after forty years of breeding that can exploited for future crop improvement. In addition, the identification of candidate genes for enhancing malting quality may be used to optimize the selection of targets for further improvements in this economically important phenotype. [ABSTRACT FROM AUTHOR]

Background: Molecular marker technologies are undergoing a transition from largely serial assays measuring DNA fragment sizes to hybridization-based technologies with high multiplexing levels. Diversity Arrays Technology (DArT) is a hybridization-based technology that is increasingly being adopted by barley researchers. There is a need to integrate the information generated by DArT with previous data produced with gel-based marker technologies. The goal of this study was to build a high-density consensus linkage map from the combined datasets of ten populations, most of which were simultaneously typed with DArT and Simple Sequence Repeat (SSR), Restriction Enzyme Fragment Polymorphism (RFLP) and/or Sequence Tagged Site (STS) markers. Results: The consensus map, built using a combination of JoinMap 3.0 software and several purpose-built perl scripts, comprised 2,935 loci (2,085 DArT, 850 other loci) and spanned 1,161 cM. It contained a total of 1,629 'bins' (unique loci), with an average inter-bin distance of 0.7 ± 1.0 cM (median = 0.3 cM). More than 98% of the map could be covered with a single DArT assay. The arrangement of loci was very similar to, and almost as optimal as, the arrangement of loci in component maps built for individual populations. The locus order of a synthetic map derived from merging the component maps without considering the segregation data was only slightly inferior. The distribution of loci along chromosomes indicated centromeric suppression of recombination in all chromosomes except 5H. DArT markers appeared to have a moderate tendency toward hypomethylated, gene-rich regions in distal chromosome areas. On the average, 14 ± 9 DArT loci were identified within 5 cM on either side of SSR, RFLP or STS loci previously identified as linked to agricultural traits. Conclusion: Our barley consensus map provides a framework for transferring genetic information between different marker systems and for deploying DArT markers in molecular breeding schemes. The study also highlights the need for improved software for building consensus maps from high-density segregation data of multiple populations. [ABSTRACT FROM AUTHOR]

Kernel color and grain protein concentration (GPC) are two of the most important attributes of barley (Hordeum vulgate L.) grain intended for use in malting and brewing. Grain with protein levels that are too low or high or that have dark kernel color, which may result from the disease complex of kernel discoloration (KD), is unacceptable for the malting and brewing industries. The purpose of this study was to use molecular markers to map quantitative trait loci (QTLs) for KD and GPC in two recombinant inbred line (RIL) populations. One population was created by means of the high GPC and KD resistant cultivar Chevron. The other population was created from a KD resistant cultivar MNBrite that was derived from Chevron through eight generations of crossing and selection for bright kernels. The traits KD and GPC were evaluated in four and three environments, respectively, using the Chevron population and six environments using the MNBrite population. GPC and KD score were negatively correlated in both populations. A revised genetic map for the Chevron/M69 population, with an additional 45 simple sequence repeat (SSR) markers, was used to identify nine QTLs associated with KD on chromosomes 1(7H), 2(2H), 4(4H), 6(6H), and 7(5H), including two major QTLs on chromosome 6(6H). A single QTL for GPC identified in the Chevron mapping population, accounting for over 55% of the phenotypic variation, was located on chromosome 6(6H) and was coincident with one of the two major QTLs for KD. In this region, the Chevron allele increased GPC and decreased KD score. In the MNBrite mapping population, the same region of chromosome 6(6H) was mapped with SSR markers, and QTL analysis verified that this region was associated with both KD and GPC, indicating that MNBrite inherited this region of chromosome 6(6H) from Chevron. The results of this study suggest that if GPC and KD are controlled by tightly linked genes, then it should be possible to use SSR markers to identify recombinants in this region of chromosome 6(6H) and break the linkage to allow selection for KD resistance without high GPC. Alternatively, if GPC and KD are conditioned by the same gene, then it should be possible to select for KD resistance from Chevron by means of SSR markers and to use phenotypic selection to introgress other genes to reduce GPC to acceptable levels. [ABSTRACT FROM AUTHOR]

Due to the stringent quality requirements imposed by the US malting barley industry, barley breeders have been reluctant to introduce exotic germplasm into cultivar development programs. To determine whether wild barley (Hordeum vulgare ssp. spontaneum) contains favorable alleles for yield and malting quality characteristics, we mapped quantitative trait loci (QTL) for heading date, height, lodging, yield, and nine malting parameters important to the malting and brewing industry. Traits were mapped in a wild x cultivated barley BC2-derived advanced backcross mapping population. Harrington, the recurrent parent, is a North American two-rowed malting barley cultivar, and OUH602, the donor parent, is a wild barley accession that exhibits resistance to multiple barley diseases. The 98 derived lines were grown in replicated field trials at St. Paul and Crookston, MN in 2009–2011. One to four QTL were identified for each trait, for a total of 36 QTL. Trangressive segregants for increased yield were identified and four lines had higher yield than Harrington across all environments; however, for yield QTL the OUH602 alleles decreased the trait value. Wild barley alleles had both positive and negative effects on the malting traits of diastatic power, free amino nitrogen, and soluble protein. Combined with the previously identified QTL associated with resistance to fungal diseases, this population represents a rich resource for barley breeding. To facilitate future breeding and genetics studies with this population, a set of pre-introgression lines composed of 28 BC2-derived and 6 BC3-derived lines were identified that collectively contain introgressions across the entire OUH602 genome. [ABSTRACT FROM AUTHOR]

The many quantitative traits of interest to plant breeders are often genetically correlated, which can complicate progress from selection. Improving multiple traits may be enhanced by identifying parent combinations - an important breeding step - that will deliver more favorable genetic correlations (rG). Modeling the segregation of genomewide markers with estimated effects may be one method of predicting rG in a cross, but this approach remains untested. Our objectives were to: (i) use simulations to assess the accuracy of genomewide predictions of rG and the long-term response to selection when selecting crosses on the basis of such predictions; and (ii) empirically measure the ability to predict genetic correlations using data from a barley (Hordeum vulgare L.) breeding program. Using simulations, we found that the accuracy to predict rG was generally moderate and influenced by trait heritability, population size, and genetic correlation architecture (i.e., pleiotropy or linkage disequilibrium). Among 26 barley breeding populations, the empirical prediction accuracy of rG was low (-0.012) to moderate (0.42), depending on trait complexity. Within a simulated plant breeding program employing indirect selection, choosing crosses based on predicted rG increased multi-trait genetic gain by 11-27% compared to selection on the predicted cross mean. Importantly, when the starting genetic correlation was negative, such cross selection mitigated or prevented an unfavorable response in the trait under indirect selection. Prioritizing crosses based on predicted genetic correlation can be a feasible and effective method of improving unfavorably correlated traits in breeding programs. [ABSTRACT FROM AUTHOR]

Targeted identification and purging of deleterious genetic variants has been proposed as a novel approach to animal and plant breeding. This strategy is motivated, in part, by the observation that demographic events and strong selection associated with cultivated species pose a "cost of domestication." This includes an increase in the proportion of genetic variants that are likely to reduce fitness. Recent advances in DNA resequencing and sequence constraint-based approaches to predict the functional impact of a mutation permit the identification of putatively deleterious SNPs (dSNPs) on a genome-wide scale. Using exome capture resequencing of 21 barley lines, we identified 3855 dSNPs among 497,754 total SNPs. We generated whole-genome resequencing data of Hordeum murinum ssp. glaucum as a phylogenetic outgroup to polarize SNPs as ancestral vs. derived. We also observed a higher proportion of dSNPs per synonymous SNPs (sSNPs) in low-recombination regions of the genome. Using 5215 progeny from a genomic prediction experiment, we examined the fate of dSNPs over three breeding cycles. Adjusting for initial frequency, derived alleles at dSNPs reduced in frequency or were lost more often than other classes of SNPs. The highest-yielding lines in the experiment, as chosen by standard genomic prediction approaches, carried fewer homozygous dSNPs than randomly sampled lines from the same progeny cycle. In the final cycle of the experiment, progeny selected by genomic prediction had a mean of 5.6% fewer homozygous dSNPs relative to randomly chosen progeny from the same cycle. [ABSTRACT FROM AUTHOR]

Genomewide selection is hailed for its ability to facilitate greater genetic gains per unit time. Over breeding cycles, the requisite linkage disequilibrium (LD) between quantitative trait loci and markers is expected to change as a result of recombination, selection, and drift, leading to a decay in prediction accuracy. Previous research has identified the need to update the training population using data that may capture new LD generated over breeding cycles; however, optimal methods of updating have not been explored. In a barley (Hordeum vulgare L.) breeding simulation experiment, we examined prediction accuracy and response to selection when updating the training population each cycle with the best predicted lines, the worst predicted lines, both the best and worst predicted lines, random lines, criterion-selected lines, or no lines. In the short term, we found that updating with the best predicted lines or the best and worst predicted lines resulted in high prediction accuracy and genetic gain, but in the long term, all methods (besides not updating) performed similarly. We also examined the impact of including all data in the training population or only the most recent data. Though patterns among update methods were similar, using a smaller but more recent training population provided a slight advantage in prediction accuracy and genetic gain. In an actual breeding program, a breeder might desire to gather phenotypic data on lines predicted to be the best, perhaps to evaluate possible cultivars. Therefore, our results suggest that an optimal method of updating the training population is also very practical. [ABSTRACT FROM AUTHOR]

Continental cropping systems are increasingly exposed to extreme and opposing trends of temperatures over the same growing season. This situation is epitomized by winter barley grown in the Upper Midwest, which is subject to temperatures that can be as low as −30 °C during the winter and over 30 °C during summer. This interaction severely limits the potential of this emerging crop, by threatening the winter survival of the crown which is often exposed to lethal freezing stress and by exposing reproductive organs to high temperature (HT) stress, to which this cool-season grass is highly sensitive. This poses a unique challenge that requires the discovery and capture of well-defined sets of traits enabling adaptation to extreme tail ends of a stressor, with limited trade-offs, while minimizing costs. Here, based on a critical literature review, we propose a framework integrating i) environmental characterization (envirotyping), ii) envirotype-relevant scouting of genetic resources, iii) ecophysiology-informed trait identification and phenotyping and iv) breeding pipelines. We outline propositions and guidelines for implementing these steps and discuss their feasibility, with an emphasis on i) identifying novel genetic resources and eco-physiological traits relevant to this problem, ii) navigating their physiological trade-offs and iii) leveraging this information to develop ad hoc phenotyping methods for deployment in breeding programs. Our review indicates that the eco-physiological and genetic bases for improving tolerance to both stresses in the same organism likely exists based on evidence from crop relatives and extremophile species, with smaller vasculature (freezing tolerance) and transpirational cooling (HT tolerance) being prime examples. Our findings indicate that such traits could be captured with minimal trade-offs, and that is possible to use similar phenotyping concepts (thermal imaging) and infrastructure (cold/heat tents) to screen for these traits and accelerate breeding to enhance adaptation to temperature extremes. • Temperature extremes limit winter barley yields grown in the Upper Midwest. • Freezing stress limits crown survival and heat stress limits reproductive development. • A trans-disciplinary framework is proposed to improve adaptation to both stressors. • Physiological/ genetic bases for adaptation to both stresses likely exists. • Possibility to use similar phenotyping infrastructure for promising traits. [ABSTRACT FROM AUTHOR]

The ability to access alleles from unadapted germplasm collections is a long-standing problem for geneticists and breeders. Here we developed, characterized, and demonstrated the utility of a wild barley advanced backcross-nested association mapping (ABNAM) population. We developed this population by backcrossing 25 wild barley accessions to the six-rowed malting barley cultivar Rasmusson. The 25 wild barley parents were selected from the 318 accession Wild Barley Diversity Collection (WBDC) to maximize allelic diversity. The resulting 796 BC2F4:6 lines were genotyped with 384 SNP markers, and an additional 4022 SNPs and 263,531 sequence variants were imputed onto the population using 9K iSelect SNP genotypes and exome capture sequence of the parents, respectively. On average, 96% of each wild parent was introgressed into the Rasmusson background, and the population exhibited low population structure. While linkage disequilibrium (LD) decay (r² = 0.2) was lowest in the WBDC (0.36 cM), the AB-NAM (9.2 cM) exhibited more rapid LD decay than comparable advanced backcross (28.6 cM) and recombinant inbred line (32.3 cM) populations. Three qualitative traits: glossy spike, glossy sheath, and black hull color were mapped with high resolution to loci corresponding to known barley mutants for these traits. Additionally, a total of 10 QTL were identified for grain protein content. The combination of low LD, negligible population structure, and high diversity in an adapted background make the AB-NAM an important tool for highresolution gene mapping and discovery of novel allelic variation using wild barley germplasm. [ABSTRACT FROM AUTHOR]