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Key message: Malt for craft “all-malt” brewing can have high quality, PHS resistance, and malted in normal timeframes. Canadian style adjunct malt is associated with PHS susceptibility. Expansion of malting barley production into non-traditional growing regions and erratic weather has increased the demand for preharvest sprouting (PHS) resistant, high quality malting barley cultivars. This is hindered by the relatively unknown relationships between PHS resistance and malting quality. Here we present a three-year study of malting quality and germination at different after-ripening durations post physiological maturity. Malting quality traits alpha amylase (AA) and free amino nitrogen (FAN) and germination rate at six days post PM shared a common association with a SNP in HvMKK3 on chromosome 5H in the Seed Dormancy 2 (SD2) region responsible for PHS susceptibility. Soluble protein (SP) and soluble over total protein (S/T) both shared a common association with a marker in the SD2 region. Significant genetic correlations between PHS resistance and the malting quality traits AA, FAN, SP, S/T were detected across and within HvMKK3 allele groups. High adjunct malt quality was related to PHS susceptibility. Selection for PHS resistance led to a correlated response in malting quality traits. Results strongly suggest pleiotropy of HvMKK3 on malting quality traits and that the classic “Canadian-style” malt is caused by a PHS susceptible allele of HvMKK3. PHS susceptibility appears to benefit the production of malt intended for adjunct brewing, while PHS resistance is compatible with all-malt brewing specifications. Here we present our analysis on the effect of combining complexly inherited and correlated traits with contrasting goals to inform breeding practice in malting barley, the general principles of which can be extended to other breeding programs. [ABSTRACT FROM AUTHOR]

There is an increased demand for food-grade grains grown sustainably. Hard red winter wheat has comparative advantages for organic farm rotations due to fall soil cover, weed competition, and grain yields. However, limitations of currently available cultivars such as poor disease resistance, winter hardiness, and baking quality, challenges its adoption and use. Our goal was to develop a participatory hard red winter wheat breeding program for the US Upper Midwest involving farmers, millers, and bakers. Specifically, our goals include (1) an evaluation of genotype-by-environment interaction (GEI) and genotypic stability for both agronomic and quality traits, and (2) the development of on-farm trials as well as baking and sensory evaluations of genotypes to include farmers, millers, and bakers' perspectives in the breeding process. Selection in early generations for diseases and protein content was followed by multi-environment evaluations for agronomic, disease, and quality traits in three locations during five years, on-farm evaluations, baking trials, and sensory evaluations. GEI was substantial for most traits, but no repeatable environmental conditions were significant contributors to GEI making selection for stability a critical trait. Breeding lines had similar performance in on-station and on-farm trials compared to commercial checks, but some breeding lines were more stable than the checks for agronomic, quality traits, and baking performance. These results suggest that stable lines can be developed using a participatory breeding approach under organic management. Crop improvement explicitly targeting sustainable agriculture practices for selection with farm to table participatory perspectives are critical to achieve long-term sustainable crop production. Key message: We describe a hard red winter wheat breeding program focused on developing genotypes adapted to organic systems in the US Upper Midwest for high-end artisan baking quality using participatory approaches. [ABSTRACT FROM AUTHOR]

Key message: HvMKK3 alleles are temperature sensitive and are major contributors to environmental stability of preharvest sprouting in barley. Preharvest sprouting (PHS) can severely damage barley (Hordeum vulgare L.) malting quality, but PHS resistance is often negatively correlated with malting quality. Seed dormancy is closely related to PHS. Increased temperature during grain fill can decrease seed dormancy in barley, but genetic components of seed dormancy temperature sensitivity are poorly understood. Six years of PHS data were used to fit quantitative trait locus (QTL) x environment mixed models incorporating marker data from seed dormancy genes HvAlaAT1, HvGA20ox1, and HvMKK3 and weather covariates in spring and winter two-row malting barley. Variation in winter barley PHS was best modeled by average temperature range during grain fill and spring barley PHS by total precipitation during grain fill. Average high temperature during grain fill also accurately modeled PHS for both datasets. A highly non-dormant HvMKK3 allele determined baseline PHS susceptibility and HvAlaAT1 interactions with multiple HvMKK3 alleles conferred environmental sensitivity. Polygenic variation for PHS within haplotype was detected. Residual genotype and QTL by environment interaction variance indicated additional environmental and genetic factors involved in PHS. These models provide insight into genotype and environmental regulation of barley seed dormancy, a method for PHS forecasting, and a tool for breeders to improve PHS resistance. [ABSTRACT FROM AUTHOR]

Key message: GWAS identified eight yield-related, peak starch type of waxy and wild-type starch and 21 starch pasting property-related traits (QTLs). Prediction ability of eight GS models resulted in low to high predictability, depending on trait, heritability, and genetic architecture. Cassava is both a food and an industrial crop in Africa, South America, and Asia, but knowledge of the genes that control yield and starch pasting properties remains limited. We carried out a genome-wide association study to clarify the molecular mechanisms underlying these traits and to explore marker-based breeding approaches. We estimated the predictive ability of genomic selection (GS) using parametric, semi-parametric, and nonparametric GS models with a panel of 276 cassava genotypes from Thai Tapioca Development Institute, International Center for Tropical Agriculture, International Institute of Tropical Agriculture, and other breeding programs. The cassava panel was genotyped via genotyping-by-sequencing, and 89,934 single-nucleotide polymorphism (SNP) markers were identified. A total of 31 SNPs associated with yield, starch type, and starch properties traits were detected by the fixed and random model circulating probability unification (FarmCPU), Bayesian-information and linkage-disequilibrium iteratively nested keyway and compressed mixed linear model, respectively. GS models were developed, and forward predictabilities using all the prediction methods resulted in values of − 0.001–0.71 for the four yield-related traits and 0.33–0.82 for the seven starch pasting property traits. This study provides additional insight into the genetic architecture of these important traits for the development of markers that could be used in cassava breeding programs. [ABSTRACT FROM AUTHOR]

Key message: Integration of multi-omics data improved prediction accuracies of oat agronomic and seed nutritional traits in multi-environment trials and distantly related populations in addition to the single-environment prediction. Multi-omics prediction has been shown to be superior to genomic prediction with genome-wide DNA-based genetic markers (G) for predicting phenotypes. However, most of the existing studies were based on historical datasets from one environment; therefore, they were unable to evaluate the efficiency of multi-omics prediction in multi-environment trials and distantly related populations. To fill those gaps, we designed a systematic experiment to collect omics data and evaluate 17 traits in two oat breeding populations planted in single and multiple environments. In the single-environment trial, transcriptomic BLUP (T), metabolomic BLUP (M), G + T, G + M, and G + T + M models showed greater prediction accuracy than GBLUP for 5, 10, 11, 17, and 17 traits, respectively, and metabolites generally performed better than transcripts when combined with SNPs. In the multi-environment trial, multi-trait models with omics data outperformed both counterpart multi-trait GBLUP models and single-environment omics models, and the highest prediction accuracy was achieved when modeling genetic covariance as an unstructured covariance model. We also demonstrated that omics data can be used to prioritize loci from one population with omics data to improve genomic prediction in a distantly related population using a two-kernel linear model that accommodated both likely casual loci with large-effect and loci that explain little or no phenotypic variance. We propose that the two-kernel linear model is superior to most genomic prediction models that assume each variant is equally likely to affect the trait and can be used to improve prediction accuracy for any trait with prior knowledge of genetic architecture. [ABSTRACT FROM AUTHOR]

Genomic selection (GS) models have been validated for many quantitative traits in wheat (Triticum aestivum L.) breeding. However, those models are mostly constrained within the same growing cycle and the extension of GS to the case of across cycles has been a challenge, mainly due to the low predictive accuracy resulting from two factors: reduced genetic relationships between different families and augmented environmental variances between cycles. Using the data collected from diverse field conditions at the International Wheat and Maize Improvement Center, we evaluated GS for grain yield in three elite yield trials across three wheat growing cycles. The objective of this project was to employ the secondary traits, canopy temperature, and green normalized difference vegetation index, which are closely associated with grain yield from high-throughput phenotyping platforms, to improve prediction accuracy for grain yield. The ability to predict grain yield was evaluated reciprocally across three cycles with or without secondary traits. Our results indicate that prediction accuracy increased by an average of 146% for grain yield across cycles with secondary traits. In addition, our results suggest that secondary traits phenotyped during wheat heading and early grain filling stages were optimal for enhancing the prediction accuracy for grain yield. [ABSTRACT FROM AUTHOR]

Key message: Genome-wide association mapping in conjunction with population sequencing map and Ensembl plants was used to identify markers/candidate genes linked to leaf rust, stripe rust and tan spot resistance in wheat.Abstract: Leaf rust (LR), stripe rust (YR) and tan spot (TS) are some of the important foliar diseases in wheat (Triticum aestivum L.). To identify candidate resistance genes for these diseases in CIMMYT’s (International Maize and Wheat Improvement Center) International bread wheat screening nurseries, we used genome-wide association studies (GWAS) in conjunction with information from the population sequencing map and Ensembl plants. Wheat entries were genotyped using genotyping-by-sequencing and phenotyped in replicated trials. Using a mixed linear model, we observed that seedling resistance to LR was associated with 12 markers on chromosomes 1DS, 2AS, 2BL, 3B, 4AL, 6AS and 6AL, and seedling resistance to TS was associated with 14 markers on chromosomes 1AS, 2AL, 2BL, 3AS, 3AL, 3B, 6AS and 6AL. Seedling and adult plant resistance (APR) to YR were associated with several markers at the distal end of chromosome 2AS. In addition, YR APR was also associated with markers on chromosomes 2DL, 3B and 7DS. The potential candidate genes for these diseases included several resistance genes, receptor-like serine/threonine-protein kinases and defense-related enzymes. However, extensive LD in wheat that decays at about 5 × 107 bps, poses a huge challenge for delineating candidate gene intervals and candidates should be further mapped, functionally characterized and validated. We also explored a segment on chromosome 2AS associated with multiple disease resistance and identified seventeen disease resistance linked genes. We conclude that identifying candidate genes linked to significant markers in GWAS is feasible in wheat, thus creating opportunities for accelerating molecular breeding. [ABSTRACT FROM AUTHOR]

Wheat stem rust, caused by Puccinia graminis f. sp. tritici, is one of the most destructive diseases of wheat. A new race of the pathogen named TTKSK (syn. Ug99) and its derivatives detected in East Africa are virulent to many designated and undesignated stem rust resistance genes. The emergence and spread of those races pose an imminent threat to wheat production worldwide. Genes Sr25 and Sr26 transferred into wheat from Thinopyrum ponticum are effective against these new races. DNA markers for Sr25 and Sr26 are needed to pyramid both genes into adapted germplasm. The previously published dominant markers Gb for Sr25 and Sr26#43 for Sr26 were validated with eight wheat lines with or without Sr25 or Sr26. We tested six published STS (sequence tagged site) markers amplifying diagnostic bands of Th. ponticum. Marker BF145935 consistently amplified well and can be used as a co-dominant marker for Sr25. Among 16 STS markers developed from wheat ESTs mapped to deletion bin 6AL8-0.90-1.00, none was co-dominant for tagging Sr26. However, five 6A-specific markers were identified. Multiplex PCR with marker Sr26#43 and 6A-specific marker BE518379 can be used as a co-dominant marker for Sr26. The co-dominant markers for Sr25 and Sr26 were validated with 37 lines with known stem rust resistance genes. A diverse set of germplasm consisting 170 lines from CIMMYT, China, USA and other counties were screened with the co-dominant markers for Sr25 and Sr26. Five lines with the diagnostic fragment for Sr25 were identified, and they all have ‘Wheatear’ in their pedigrees, which is known to carry Sr25. None of the 170 lines tested had Sr26, as expected. [ABSTRACT FROM AUTHOR]

The premature germination of seeds before harvest, known as preharvest sprouting (PHS), is a serious problem in all wheat growing regions of the world. In order to determine genetic control of PHS resistance in white wheat from the relatively uncharacterized North American germplasm, a doubled haploid population consisting of 209 lines from a cross between the PHS resistant variety Cayuga and the PHS susceptible variety Caledonia was used for QTL mapping. A total of 16 environments were used to detect 15 different PHS QTL including a major QTL, QPhs.cnl-2B.1, that was significant in all environments tested and explained from 5 to 31% of the trait variation in a given environment. Three other QTL QPhs.cnl-2D.1, QPhs.cnl-3D.1, and QPhs.cnl-6D.1 were detected in six, four, and ten environments, respectively. The potentially related traits of heading date (HD), plant height (HT), seed dormancy (DOR), and rate of germination (ROG) were also recorded in a limited number of environments. HD was found to be significantly negatively correlated with PHS score in most environments, likely due to a major HD QTL, QHd.cnl-2B.1, found to be tightly linked to the PHS QTL QPhs.cnl-2B.1. Using greenhouse grown material no overlap was found between seed dormancy and the four most consistent PHS QTL, suggesting that greenhouse environments are not representative of field environments. This study provides valuable information for marker-assisted breeding for PHS resistance, future haplotyping studies, and research into seed dormancy. [ABSTRACT FROM AUTHOR]

Powdery mildew is a severe foliar disease for wheat and could cause great yield loss in epidemic years. To explore new powdery mildew resistance genes, two einkorn accessions including TA2033 and M80, both resistant to this disease, were studied for the inheritance of resistance. Each accession possessed a single but different dominant resistance gene that was designated as Mlm2033 and Mlm80, respectively. Marker mapping indicated that they are both linked to Xgwm344 on the long arm of chromosome 7A. To establish their genetic relationship with Pm1 on 7AL, five RFLP markers previously reported to co-segregate with Pm1a were converted to STS markers. Three of them detected polymorphism between the mapping parents and were mapped close to Mlm2033 or Mlm80 or both. Xmag2185, the locus determined by the STS marker derived from PSR680, one of the RFLP markers, was placed less than 2 cM away from them. The allelism test indicated that Mlm2033 and Mlm80 are likely allelic to each other. In addition, through comparative and EST mapping, more markers linked to these two genes were identified. The high density mapping of Mlm2033 and Mlm80 will contribute to map-based cloning of the Pm1 locus. The markers for both genes will also facilitate their transfer to wheat. [ABSTRACT FROM AUTHOR]

Tef [ Eragrostis tef (Zucc.) Trotter] is the major cereal crop in Ethiopia. Tef is an allotetraploid with a base chromosome number of 10 (2 n = 4 x = 40) and a genome size of 730 Mbp. Ninety-four F9 recombinant inbred lines (RIL) derived from the interspecific cross, Eragrostis tef cv. Kaye Murri × Eragrostis pilosa (accession 30-5), were mapped using restriction fragment length polymorphisms (RFLP), simple sequence repeats derived from expressed sequence tags (EST–SSR), single nucleotide polymorphism/insertion and deletion (SNP/INDEL), intron fragment length polymorphism (IFLP) and inter-simple sequence repeat amplification (ISSR). A total of 156 loci from 121 markers was grouped into 21 linkage groups at LOD 4, and the map covered 2,081.5 cM with a mean density of 12.3 cM per locus. Three putative homoeologous groups were identified based on multi-locus markers. Sixteen percent of the loci deviated from normal segregation with a predominance of E. tef alleles, and a majority of the distorted loci were clustered on three linkage groups. This map will be useful for further genetic studies in tef including mapping of loci controlling quantitative traits (QTL), and comparative analysis with other cereal crops. [ABSTRACT FROM AUTHOR]

Drought limits cereal yields in several regions of the world and plant water status plays an important role in tolerance to drought. To investigate and understand the genetic and physiological basis of drought tolerance in barley, differentially expressed sequence tags (dESTs) and candidate genes for the drought response were mapped in a population of 167 F8 recombinant inbred lines derived from a cross between “Tadmor” (drought tolerant) and “Er/Apm” (adapted only to specific dry environments). One hundred sequenced probes from two cDNA libraries previously constructed from drought-stressed barley (Hordeum vulgareL., var. Tokak) plants and 12 candidate genes were surveyed for polymorphism, and 33 loci were added to a previously published map. Composite interval mapping was used to identify quantitative trait loci (QTL) associated with drought tolerance including leaf relative water content, leaf osmotic potential, osmotic potential at full turgor, water-soluble carbohydrate concentration, osmotic adjustment, and carbon isotope discrimination. A total of 68 QTLs with a limit of detection score =2.5 were detected for the traits evaluated under two water treatments and the two traits calculated from both treatments. The number of QTLs identified for each trait varied from one to 12, indicating that the genome contains multiple genes affecting different traits. Two candidate genes and ten differentially expressed sequences were associated with QTLs for drought tolerance traits. [ABSTRACT FROM AUTHOR]