Recent advances in the genetics underlying wheat grain protein content and grain protein deviation in hexaploid wheat

Wheat is one of the most important global crops and selection for better performance has been ongoing since ancient times. As a quantitative trait controlled by the interplay of several genomic loci and under the strong influence of the environment, grain protein content (GPC) is of major interest in breeding programs. Here, we review the most recent contributions to the genetics underlying wheat GPC and grain protein deviation (GPD, representing the relationship between grain protein content and yield), together with the performance of genomic prediction models characterizing these traits. A total of 364 significant loci related to GPC and GPD are positioned on the hexaploid wheat genome, highlighting genomic regions where significant independent QTL overlap, with special focus on two regions located on chromosomes 3A and 5A. Some of the corresponding homoeologous sequences co-locate with significant independent QTL reported on the B and D subgenomes. Overlapping independent QTL from different studies are indicative of genomic regions exhibiting stability across environments and genotypes, with promising candidates for improving grain quality.     

Quantitative trait loci for grain yield and adaptation of durum wheat (Triticum durum Desf.) across a wide range of water availability

Grain yield is a major goal for the improvement of durum wheat, particularly in drought-prone areas. In this study, the genetic basis of grain yield (GY), heading date (HD), and plant height (PH) was investigated in a durum wheat population of 249 recombinant inbred lines evaluated in 16 environments (10 rainfed and 6 irrigated) characterized by a broad range of water availability and GY (from 5.6 to 58.8 q ha(-1)). Among the 16 quantitative trait loci (QTL) that affected GY, two major QTL on chromosomes 2BL and 3BS showed significant effects in 8 and 7 environments, with R2 values of 21.5 and 13.8% (mean data of all 16 environments), respectively. In both cases, extensive overlap was observed between the LOD profiles of GY and PH, but not with those for HD. QTL specific for PH were identified on chromosomes 1BS, 3AL, and 7AS. Additionally, three major QTL for HD on chromosomes 2AS, 2BL, and 7BS showed limited or no effects on GY. For both PH and GY, notable epistasis between the chromosome 2BL and 3BS QTL was detected across several environments.     

Genetic analysis of grain protein-content,grain yield and thousand-kernel weight in bread wheat

Grain yield and grain protein content are two very important traits in bread wheat. They are controlled by genetic factors, but environmental conditions considerably affect their expression. The aim of this study was to determine the genetic basis of these two traits by analysis of a segregating population of 194 F(7) recombinant inbred lines derived from a cross between two wheat varieties, grown at six locations in France in 1999. A genetic map of 254 loci was constructed, covering about 75% of the bread wheat genome. QTLs were detected for grain protein-content (GPC), yield and thousand-kernel weight (TKW). 'Stable' QTLs (i.e. detected in at least four of the six locations) were identified for grain protein-content on chromosomes 2A, 3A, 4D and 7D, each explaining about 10% of the phenotypic variation of GPC. For yield, only one important QTL was found on chromosome 7D, explaining up to 15.7% of the phenotypic variation. For TKW, three QTLs were detected on chromosomes 2B, 5B and 7A for all environments. No negative relationships between QTLs for yield and GPC were observed. Factorial Regression on GxE interaction allowed determination of some genetic regions involved in the differential reaction of genotypes to specific climatic factors, such as mean temperature and the number of days with a maximum temperature above 25 degrees C during grain filling.     

Identification and validation of quantitative trait loci for grain protein concentration in adapted Canadian durum wheat populations

Grain protein concentration (GPC) is one of the most important factors influencing pasta-making quality. Durum wheat (Triticum turgidum L. var durum) cultivars with high GPC produce pasta with increased tolerance to overcooking and greater cooked firmness. However, the large environmental effect on expression of GPC and the negative correlation with grain yield have slowed genetic improvement of this important trait. Understanding the genetics and identification of molecular markers associated with high GPC would aid durum wheat breeders in trait selection at earlier generations. The objectives of this study were to identify and validate molecular markers associated with quantitative trait loci (QTL) for elevated GPC in durum wheat. A genetic map was constructed using SSR and DArT^® markers in an F₁-derived doubled haploid (DH) population derived from the cross DT695 × Strongfield. The GPC data were collected from replicated trials grown in six Canadian environments from 2002 to 2005. QTL associated with variation for GPC were identified on the group 1, 2, and 7 chromosomes and on 5B and 6B, but only QGpc.usw-B3 on 2B and QGpc.usw-A3 on 7A were expressed consistently in four and six environments, respectively. Positive alleles for GPC at these loci were contributed by the high-GPC parent Strongfield. The QGpc.usw-A3 QTL was validated in a second DH population, and depending on environment, selection for the Strongfield allele at barc108 resulted in +0.4% to +1.0% increase in GPC, with little effect on yield in most environments. Given the consistent expression pattern in multiple populations and environments, barc108 could be useful for marker-assisted selection for high GPC.     

Molecular genetic analysis of grain protein content and flour whiteness degree using RILs in common wheat

Grain protein content (GPC) and flour whiteness degree (FWD) are important qualitative traits in common wheat. Quantitative trait locus (QTL) mapping for GPC and FWD was conducted using a set of 131 recombinant-inbred lines derived from the cross ‘Chuan 35050 × Shannong 483’ in six environmental conditions. A total of 22 putative QTLs (nine GPC and 13 FWD) were identified on 12 chromosomes with individual QTL explaining 4.5–34.0% phenotypic variation. Nine QTLs (40.9%) were detected in two or more environments. The colocated QTLs were on chromosomes 1B and 4B. Among the QTLs identified for GPC, QGpc.sdau-4A from the parent Shannong 483 represented some important favourable QTL alleles. QGpc.sdau-2A.1 and QFwd.sdau-2A.1 had a significant association with both GPC and FWD. The markers detected on top of QTL regions could be potential targets for marker-assisted selection.     

Relationships between grain protein content and grain yield components through quantitative trait locus analyses in a recombinant inbred line population derived from two elite durum wheat cultivars

Grain protein content (GPC) in durum wheat (Triticum turgidum var. durum) is negatively correlated with grain yield. To evaluate possible genetic interrelationships between GPC and grain yield per spike, thousand-kernel weight and kernel number per spike, quantitative trait loci (QTL) for GPC were mapped using GPC-adjusted data in a covariance analysis on yield components. Phenotypic data were evaluated in a segregating population of 120 recombinant inbred lines derived from crossing the elite cultivars Svevo and Ciccio. The material was tested at five environments in southern Italy. QTL were determined by composite interval mapping based on the Svevo?×?Ciccio linkage map described in Gadaleta et al. (2009) and integrated with DArT markers. The close relationship between GPC and yield components was reflected in the negative correlation between the traits and in the reduction of variance when GPC values were adjusted to yield components. Ten independent genomic regions involved in the expression of GPC were detected, six of which were associated with QTL for one or more grain yield components. QTL alleles with increased GPC effects were associated with QTL alleles with decreased effects on one or more yield component traits, or vice versa (i.e. the allelic effects were in opposite direction). Four QTL for GPC showed always significant effects, and these QTL should represent genes that influence GPC independently from variation in the yield components. Such genes are of special interest in wheat breeding since they would allow an increase in GPC without a concomitant decrease in grain yield.     

QTL analysis for grain protein content using SSR markers and validation studies using NILs in bread wheat

QTL interval mapping for grain protein content (GPC) in bread wheat was conducted for the first time, using a framework map based on a mapping population, which was available in the form of 100 recombinant inbred lines (RILs). The data on GPC for QTL mapping was recorded by growing the RILs in five different environments representing three wheat growing locations from Northern India; one of these locations was repeated for 3 years. Distribution of GPC values followed normal distributions in all the environments, which could be explained by significant g x e interactions observed through analyses of variances, which also gave significant effects due to genotypes and environments. Thirteen (13) QTLs were identified in individual environments following three methods (single-marker analysis or SMA, simple interval mapping or SIM and composite interval mapping or CIM) and using LOD scores that ranged from 2.5 to 6.5. Threshold LOD scores (ranging from 3.05 to 3.57), worked out and used in each case, however, detected only seven of the above 13 QTLs. Only four (QGpc.ccsu-2B.1; QGpc.ccsu-2D.1; QGpc.ccsu-3D.1 and QGpc.ccsu-7A.1) of these QTLs were identified either in more than one location or following one more method other than CIM; another QTL (QGpc.ccsu-3D.2), which was identified using means for all the environments, was also considered to be important. These five QTLs have been recommended for marker-assisted selection (MAS). The QTLs identified as above were also validated using ten NILs derived from three crosses. Five of the ten NILs possessed 38 introgressed segments from 16 chromosomes and carried 42 of the 173 markers that were mapped. All the seven QTLs were associated with one or more of the markers carried by the above introgressed segments, thus validating the corresponding markers. More markers associated with many more QTLs to be identified should become available in the future by effective MAS for GPC improvement.     

Novel and favorable QTL allele clusters for end-use quality revealed by introgression lines derived from synthetic wheat

Wheat quality is an important target trait. Previous studies mainly focus on storage protein, but their contribution to quality is partial, and most loci for quality are still undetected. Wild species of wheat are valuable resources for wheat improvement and introgression lines (ILs) are the ideal materials for detecting quantitative trait loci (QTL). In this study, a set of 82 BC5 F2-6 ILs, carrying a range of introgressed chromosome segments from a synthetic hexaploid wheat Am3 (Triticum carthlicum × Aegilops tauschii), was developed and genotyped with 170 microsatellite markers. QTL analysis was performed for 14 parameters, sodium dodecyl sulfate sedimentation volume, grain protein content (GPC), grain hardness and 11 mixograph parameters, associated with end-use quality of wheat, using the materials harvested in three environments. This led to the detection of 116 QTL, with c. 95% of the positive alleles contributed by Am3. Six important and novel genomic regions for bread-making quality were found on chromosomes 2D, 3A, 4A, 4B, 5A and 6A. These loci for bread-making quality showed pleiotropy and had large positive effects on several quality parameters with no or very weak negative effect on grain yield, thus demonstrating the value of synthetic wheat as a source of useful genetic variation for the improvement of bread wheat quality.     

Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number

Key message

GWAS on multi-environment data identified genomic regions associated with trade-offs for grain weight and grain number.

Abstract

Grain yield (GY) can be dissected into its components thousand grain weight (TGW) and grain number (GN), but little has been achieved in assessing the trade-off between them in spring wheat. In the present study, the Wheat Association Mapping Initiative (WAMI) panel of 287 elite spring bread wheat lines was phenotyped for GY, GN, and TGW in ten environments across different wheat growing regions in Mexico, South Asia, and North Africa. The panel genotyped with the 90 K Illumina Infinitum SNP array resulted in 26,814 SNPs for genome-wide association study (GWAS). Statistical analysis of the multi-environmental data for GY, GN, and TGW observed repeatability estimates of 0.76, 0.62, and 0.95, respectively. GWAS on BLUPs of combined environment analysis identified 38 loci associated with the traits. Among them four loci—6A (85 cM), 5A (98 cM), 3B (99 cM), and 2B (96 cM)—were associated with multiple traits. The study identified two loci that showed positive association between GY and TGW, with allelic substitution effects of 4% (GY) and 1.7% (TGW) for 6A locus and 0.2% (GY) and 7.2% (TGW) for 2B locus. The locus in chromosome 6A (79–85 cM) harbored a gene TaGW2-6A. We also identified that a combination of markers associated with GY, TGW, and GN together explained higher variation for GY (32%), than the markers associated with GY alone (27%). The marker-trait associations from the present study can be used for marker-assisted selection (MAS) and to discover the underlying genes for these traits in spring wheat.

     

Mapping of the quantitative trait loci (QTL) associated with grain quality characteristics of the common wheat grown under different environmental conditions

The quantitative trait loci (QTL) associated with individual characteristics of grain and flour quality in wheat lines grown under contrasting environmental conditions were mapped. Overall, 22 QTL that manifested under contrasting environmental conditions with various significances were detected on 10 chromosomes. Grain hardness and vitreousness were associated with three loci on chromosomes 5D, 6A, and 3A, while the gluten content, with two loci on chromosomes 5B and 7A. Dough extensibility was associated with only one QTL localized in the region of Glu-A1 locus. One of the loci determining flour and dough strengths is located in the region of Gli-B1 and Glu-B3 loci and the rest, in various regions of chromosomes 1B, 5D, and 4B, where no particular genes associated with grain quality have been yet found. The detected QTL can be used in further experiments on genetic control of gluten formation and quality in wheat.     

Molecular mapping in tropical maize (Zea mays L.) using microsatellite markers. 2. Quantitative trait loci (QTL) for grain yield, plant height, ear height and grain moisture

A previous genetic map containing 117 microsatellite loci and 400 F(2) plants was used for quantitative trait loci (QTL) mapping in tropical maize. QTL were characterized in a population of 400 F(2:3) lines, derived from selfing the F(2) plants, and were evaluated with two replications in five environments. QTL determinations were made from the mean of these five environments. Grain yield (GY), plant height (PH), ear height (EH) and grain moisture (GM) were measured. Variance components for genotypes (G), environments (E) and GxE interaction were highly significant for all traits. Heritability was 0.69 for GY, 0.66 for PH, 0.67 for EH and 0.23 for GM. Using composite interval mapping (CIM), a total of 13 distinct QTLs were identified: four for GY, four for PH and five for EH. No QTL was detected for GM. The QTL explained 32.73 % of the phenotypic variance of GY, 24.76 % of PH and 20.91 % of EH. The 13 QTLs displayed mostly partial dominance or overdominance gene action and mapped to chromosomes 1, 2, 7, 8 and 9. Most QTL alleles conferring high values for the traits came from line L-14-4B. Mapping analysis identified genomic regions associated with two or more traits in a manner that was consistent with correlation among traits, supporting either pleiotropy or tight linkage among QTL. The low number of QTLs found, can be due to the great variation that exists among tropical environments.     

Construction of an integrative linkage map and QTL mapping of grain yield-related traits using three related wheat RIL populations

Key message

A novel high-density consensus wheat genetic map was obtained based on three related RIL populations, and the important chromosomal regions affecting yield and related traits were specified.

Abstract

A prerequisite for mapping quantitative trait locus (QTL) is to build a genetic linkage map. In this study, three recombinant inbred line populations (represented by WL, WY, and WJ) sharing one common parental line were used for map construction and subsequently for QTL detection of yield-related traits. PCR-based and diversity arrays technology markers were screened in the three populations. The integrated genetic map contains 1,127 marker loci, which span 2,976.75 cM for the whole genome, 985.93 cM for the A genome, 922.16 cM for the B genome, and 1,068.65 cM for the D genome. Phenotypic values were evaluated in four environments for populations WY and WJ, but three environments for population WL. Individual and combined phenotypic values across environments were used for QTL detection. A total of 165 putative additive QTL were identified, 22 of which showed significant additive-by-environment interaction effects. A total of 65 QTL (51.5 %) were stable across environments, and 23 of these (35.4 %) were common stable QTL that were identified in at least two populations. Notably, QTkw-5B.1, QTkw-6A.2, and QTkw-7B.1 were common major stable QTL in at least two populations, exhibiting 11.28–16.06, 5.64–18.69, and 6.76–21.16 % of the phenotypic variance, respectively. Genetic relationships between kernel dimensions and kernel weight and between yield components and yield were evaluated. Moreover, QTL or regions that commonly interact across genetic backgrounds were discussed by comparing the results of the present study with those of previous similar studies. The present study provides useful information for marker-assisted selection in breeding wheat varieties with high yield.     

Nitrogen application is required to realize wheat yield stimulation by elevated CO2 but will not remove the CO2‐induced reduction in grain protein concentration

Elevated CO₂ (eCO₂) generally promotes increased grain yield (GY) and decreased grain protein concentration (GPC), but the extent to which these effects depend on the magnitude of fertilization remains unclear. We collected data on the eCO₂ responses of GY, GPC and grain protein yield and their relationships with nitrogen (N) application rates across experimental data covering 11 field grown wheat (Triticum aestivum) cultivars studied in eight countries on four continents. The eCO₂‐induced stimulation of GY increased with N application rates up to ~200 kg/ha. At higher N application, stimulation of GY by eCO₂ stagnated or even declined. This was valid both when the yield stimulation was expressed as the total effect and using per ppm CO₂ scaling. GPC was decreased by on average 7% under eCO₂ and the magnitude of this effect did not depend on N application rate. The net effect of responses on GY and protein concentration was that eCO₂ typically increased and decreased grain protein yield at N application rates below and above ~100 kg/ha respectively. We conclude that a negative effect on wheat GPC seems inevitable under eCO₂ and that substantial N application rates may be required to sustain wheat protein yields in a world with rising CO₂.     

Mapping of the quantitative trait loci (QTL) associated with grain quality characteristics of the bread wheat grown under different environmental conditions

The quantitative trait loci (QTL) associated with individual characteristics of grain and flour quality in wheat lines grown under contrasting environmental conditions were mapped. Overall, 22 QTL that manifested under contrasting environmental conditions with various significances were detected on 10 chromosomes. Grain hardness and vitreousness were associated with three loci on chromosomes 5D, 6A, and 3A, while the gluten content, with two loci on chromosomes 5B and 7A. Dough extensibility was associated with only one QTL localized in the region of Glu-A1 locus. One of the loci determining flour and dough strengths is located in the region of Gli-B1 and Glu-B3 loci and the rest, in various regions of chromosomes 1B, 5D, and 4B, where no particular genes associated with grain quality have been yet found. The detected QTL can be used in further experiments on genetic control of gluten formation and quality in wheat.     

Quantifying senescence in bread wheat using multispectral imaging from an unmanned aerial vehicle and QTL mapping

Environmental stresses from climate change can alter source–sink relations during plant maturation, leading to premature senescence and decreased yields. Elucidating the genetic control of natural variations for senescence in wheat (Triticum aestivum) can be accelerated using recent developments in unmanned aerial vehicle (UAV)-based imaging techniques. Here, we describe the use of UAVs to quantify senescence in wheat using vegetative indices (VIs) derived from multispectral images. We detected senescence with high heritability, as well as its impact on grain yield (GY), in a doubled-haploid population and parent cultivars at various growth time points (TPs) after anthesis in the field. Selecting for slow senescence using a combination of different UAV-based VIs was more effective than using a single ground-based vegetation index. We identified 28 quantitative trait loci (QTL) for vegetative growth, senescence, and GY using a 660K single-nucleotide polymorphism array. Seventeen of these new QTL for VIs from UAV-based multispectral imaging were mapped on chromosomes 2B, 3A, 3D, 5A, 5D, 5B, and 6D; these QTL have not been reported previously using conventional phenotyping methods. This integrated approach allowed us to identify an important, previously unreported, senescence-related locus on chromosome 5D that showed high phenotypic variation (up to 18.1%) for all UAV-based VIs at all TPs during grain filling. This QTL was validated for slow senescence by developing kompetitive allele-specific PCR markers in a natural population. Our results suggest that UAV-based high-throughput phenotyping is advantageous for temporal assessment of the genetics underlying for senescence in wheat.

Temporal multispectral imaging from unmanned aerial vehicles can be used to quantify senescence and identify underlying quantitative trait loci in wheat (Triticum aestivum).     

Genetic Analysis of Carbon Isotope Discrimination and its Relation to Yield in a Wheat Doubled Haploid Population

Carbon isotope discrimination (Δ¹³C) is considered a useful indicator for indirect selection of grain yield (GY) in cereals. Therefore, it is important to evaluate the genetic variation in Δ¹³C and its relationship with GY. A doubled haploid (DH) population derived from a cross of two common wheat varieties, Hanxuan 10 (H10) and Lumai 14 (L14), was phenotyped for Δ¹³C in the flag leaf, GY and yield associated traits in two trials contrasted by water availability, specifically, rain‐fed and irrigated. Quantitative trait loci (QTLs) were identified by single locus and two locus QTL analyses. QTLs for Δ¹³C were located on chromosomes 1A, 2B, 3B, 5A, 7A and 7B, and QTLs for other traits on all chromosomes except 1A, 4D, 5A, 5B and 6D. The population selected for high Δ¹³C had an increased frequency of QTL for high Δ¹³C, GY and number of spikes per plant (NSP) when grown under rain‐fed conditions and only for high Δ¹³C and NSP when grown under irrigated conditions, which was consistent with agronomic performance of the corresponding trait values in the high Δ¹³C progeny; that is, significantly greater than that in the low Δ¹³C. Therefore, selection for Δ¹³C was beneficial in increasing grain yield in rain‐fed environments.     

Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers

Key message

We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay.

Abstract

Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai?×?Shi 4185 (D?×?S), Gaocheng 8901?×?Zhoumai 16 (G?×?Z) and Linmai 2?×?Zhong 892 (L?×?Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5–32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

     

Genome-wide association study for agronomic and physiological traits in spring wheat evaluated in a range of heat prone environments

Key message

We identified 27 stable loci associated with agronomic traits in spring wheat using genome-wide association analysis, some of which confirmed previously reported studies. GWAS peaks identified in regions where no QTL for grain yield per se has been mapped to date, provide new opportunities for gene discovery and creation of new cultivars with desirable alleles for improving yield and yield stability in wheat.

Abstract

We undertook large-scale genetic analysis to determine marker-trait associations (MTAs) underlying agronomic and physiological performance in spring wheat using genome-wide association studies (GWAS). Field trials were conducted at seven sites in three countries (Sudan, Egypt, and Syria) over 2–3 years in each country. Twenty-five agronomic and physiological traits were measured on 188 wheat genotypes. After correcting for population structure and relatedness, a total of 245 MTAs distributed over 66 loci were associated with agronomic traits in individual and mean performance across environments respectively; some of which confirmed previously reported loci. Of these, 27 loci were significantly associated with days to heading, thousand kernel weight, grain yield, spike length, and leaf rolling for mean performance across environments. Despite strong QTL by environment interactions, eight of the loci on chromosomes 1A, 1D, 5A, 5D, 6B, 7A, and 7B had pleiotropic effects on days to heading and yield components (TKW, SM^?2, and SNS). The winter-type alleles at the homoeologous VRN1 loci significantly increased days to heading and grain yield in optimal environments, but decreased grain yield in heat prone environments. Top 20 high-yielding genotypes, ranked by additive main effects and multiplicative interaction (AMMI), had low kinship relationship and possessed 4–5 favorable alleles for GY MTAs except two genotypes, Shadi-4 and Qafzah-11/Bashiq-1–2. This indicated different yield stability mechanisms due to potentially favorable rare alleles that are uncharacterized. Our results will enable wheat breeders to effectively introgress several desirable alleles into locally adapted germplasm in developing wheat varieties with high yield stability and enhanced heat tolerance.

     

Genetic dissection of grain beta-glucan and amylose content in barley (Hordeum vulgare L.)

High beta-glucan (BG) barleys (Hordeum vulgare L.) have major potential as food ingredients due to their well-known health benefits. Quantitative trait loci (QTL) associated with BG have been reported in traditional barley varieties with intermediate levels of BG, but no QTL studies have been reported in hull-less barley varieties with high BG levels. In this study, QTL analysis was performed to identify markers linked to high BG and amylose in the hull-less barley varieties Falcon (4–5 % BG) and Azhul (8–9 % BG) using a newly developed recombinant inbred line (RIL) mapping population. The population was grown over 3 years (2007–2009) at sites in Yuma, AZ, USA; Leeston, New Zealand; Aberdeen, ID, USA; and Tetonia, ID, USA. We identified 17 QTL associated with either BG or amylose content. QTL contributing to high BG were located on chromosomes 3H, 4H, 5H, 6H and 7H, while QTL contributing to amylose were located on chromosomes 1H, 5H and 7H. Additionally, we identified QTL affecting both BG and amylose content located on chromosomes 1H and 7H. Transgressive segregation was observed in some of the RILs and exceptions were discovered contradicting an inverse relationship between BG and amylose. This work will provide the basis for gene cloning and marker-assisted selection in combination with traditional field selection to improve barley breeding for high BG content.