Improved multi-trait prediction of wheat end-product quality traits by integrating NIR-predicted phenotypes.

Historically, end-product quality testing has been costly and required large flour samples; therefore, it was generally implemented in the late phases of variety development, imposing a huge cost on the breeding effort and effectiveness. High genetic correlations of end-product quality traits with higher throughput and nondestructive testing technologies, such as near-infrared (NIR), could enable early-stage testing and effective selection of these highly valuable traits in a multi-trait genomic prediction model. We studied the impact on prediction accuracy in genomic best linear unbiased prediction (GBLUP) of adding NIR-predicted secondary traits for six end-product quality traits (crumb yellowness, water absorption, texture hardness, flour yield, grain protein, flour swelling volume). Bread wheat lines (1,400-1,900) were measured across 8 years (2012-2019) for six end-product quality traits with standard laboratory assays and with NIR, which were combined to generate predicted data for approximately 27,000 lines. All lines were genotyped with the Infinium™ Wheat Barley 40K BeadChip and imputed using exome sequence data. End-product and NIR phenotypes were genetically correlated (0.5-0.83, except for flour swelling volume 0.19). Prediction accuracies of end-product traits ranged between 0.28 and 0.64 and increased by 30% through the inclusion of NIR-predicted data compared to single-trait analysis. There was a high correlation between the multi-trait prediction accuracy and genetic correlations between end-product and NIR-predicted data (0.69-0.77). Our forward prediction validation revealed a gradual increase in prediction accuracy when adding more years to the multi-trait model. Overall, we achieved genomic prediction accuracy at a level that enables selection for end-product quality traits early in the breeding cycle.

Advancing understanding of oat phenology for crop adaptation.

Oat (Avena sativa) is an annual cereal grown for forage, fodder and grain. Seasonal flowering behaviour, or phenology, is a key contributor to the success of oat as a crop. As a species, oat is a vernalization-responsive long-day plant that flowers after winter as days lengthen in spring. Variation in both vernalization and daylength requirements broadens adaptation of oat and has been used to breed modern cultivars with seasonal flowering behaviours suited to different regions, sowing dates and farming practices. This review examines the importance of variation in oat phenology for crop adaptation. Strategies to advance understanding of the genetic basis of oat phenology are then outlined. These include the potential to transfer knowledge from related temperate cereals, particularly wheat (Triticum aestivum) and barley (Hordeum vulgare), to provide insights into the potential molecular basis of variation in oat phenology. Approaches that use emerging genomic resources to directly investigate the molecular basis of oat phenology are also described, including application of high-resolution genome-wide diversity surveys to map genes linked to variation in flowering behaviour. The need to resolve the contribution of individual phenology genes to crop performance by developing oat genetic resources, such as near-isogenic lines, is emphasised. Finally, ways that deeper knowledge of oat phenology can be applied to breed improved varieties and to inform on-farm decision-making are outlined.

Benefit of Introgression Depends on Level of Genetic Trait Variation in Cereal Breeding Programmes.

We investigated the benefit from introgression of external lines into a cereal breeding programme and strategies that accelerated introgression of the favourable alleles while minimising linkage drag using stochastic computer simulation. We simulated genomic selection for disease resistance and grain yield in two environments with a high level of genotype-by-environment interaction (G × E) for the latter trait, using genomic data of a historical barley breeding programme as the base generation. Two populations (existing and external) were created from this base population with different allele frequencies for few (N = 10) major and many (N ~ 990) minor simulated disease quantitative trait loci (QTL). The major disease QTL only existed in the external population and lines from the external population were introgressed into the existing population which had minor disease QTL with low, medium and high allele frequencies. The study revealed that the benefit of introgression depended on the level of genetic variation for the target trait in the existing cereal breeding programme. Introgression of external resources into the existing population was beneficial only when the existing population lacked variation in disease resistance or when minor disease QTL were already at medium or high frequency. When minor disease QTL were at low frequencies, no extra genetic gain was achieved from introgression. More benefit in the disease trait was obtained from the introgression if the major disease QTL had larger effect sizes, more selection emphasis was applied on disease resistance, or more external lines were introgressed. While our strategies to increase introgression of major disease QTL were generally successful, most were not able to completely avoid negative impacts on selection for grain yield with the only exception being when major introgression QTL effects were very large. Breeding programmes are advised to carefully consider the level of genetic variation in a trait available in their breeding programme before deciding to introgress germplasms.

Exploiting genotype × management interactions to increase rainfed crop production: a case study from south-eastern Australia.

Crop yield must increase to keep pace with growing global demand. Past increases in crop production have rarely been attributable to an individual innovation but have occurred when technologies and practices combine to form improved farming systems. Inevitably this has involved synergy between genotypic and management improvements. We argue that research focused on developing synergistic systems that overcome clear production constraints will accelerate increases in yield. This offers the opportunity to better focus and multiply the impact of discipline-focused research. Here we use the rainfed grain production systems of south-eastern Australia as a case study of how transformational change in water productivity can be achieved with research focused on genotype × management synergies. In this region, rainfall is low and variable and has declined since 1990. Despite this, growers have maintained yields by implementing synergistic systems combining innovations in (i) soil water conservation, (ii) crop diversity, (iii) earlier sowing, and (iv) matching nitrogen fertilizer to water-limited demand. Further increases are emerging from synergies between genetic improvements to deliver flowering time stability, adjusted sowing times, and potential dual-purpose use. Collaboration between agronomists, physiologists, and crop breeders has led to development of commercial genotypes with stable flowering time that are in early phases of testing and adoption.

Novel Design of Imputation-Enabled SNP Arrays for Breeding and Research Applications Supporting Multi-Species Hybridization.

Array-based single nucleotide polymorphism (SNP) genotyping platforms have low genotype error and missing data rates compared to genotyping-by-sequencing technologies. However, design decisions used to create array-based SNP genotyping assays for both research and breeding applications are critical to their success. We describe a novel approach applicable to any animal or plant species for the design of cost-effective imputation-enabled SNP genotyping arrays with broad utility and demonstrate its application through the development of the Illumina Infinium Wheat Barley 40K SNP array Version 1.0. We show that the approach delivers high quality and high resolution data for wheat and barley, including when samples are jointly hybridised. The new array aims to maximally capture haplotypic diversity in globally diverse wheat and barley germplasm while minimizing ascertainment bias. Comprising mostly biallelic markers that were designed to be species-specific and single-copy, the array permits highly accurate imputation in diverse germplasm to improve the statistical power of genome-wide association studies (GWAS) and genomic selection. The SNP content captures tetraploid wheat (A- and B-genome) and Aegilops tauschii Coss. (D-genome) diversity and delineates synthetic and tetraploid wheat from other wheat, as well as tetraploid species and subgroups. The content includes SNP tagging key trait loci in wheat and barley, as well as direct connections to other genotyping platforms and legacy datasets. The utility of the array is enhanced through the web-based tool, Pretzel (https://plantinformatics.io/) which enables the content of the array to be visualized and interrogated interactively in the context of numerous genetic and genomic resources to be connected more seamlessly to research and breeding. The array is available for use by the international wheat and barley community.

Rhizosheaths on wheat grown in acid soils: phosphorus acquisition efficiency and genetic control.

Rhizosheaths comprise soil bound to roots, and in wheat (Triticum aestivum L.) rhizosheath size correlates with root hair length. The aims of this study were to determine the effect that a large rhizosheath has on the phosphorus (P) acquisition by wheat and to investigate the genetic control of rhizosheath size in wheat grown on acid soil.Near-isogenic wheat lines differing in rhizosheath size were evaluated on two acid soils. The soils were fertilized with mineral nutrients and included treatments with either low or high P. The same soils were treated with CaCO3 to raise the pH and detoxify Al(3+) Genotypic differences in rhizosheath size were apparent only when soil pH was low and Al(3+) was present. On acid soils, a large rhizosheath increased shoot biomass compared with a small rhizosheath regardless of P supply. At low P supply, increased shoot biomass could be attributed to a greater uptake of soil P, but at high P supply the increased biomass was due to some other factor. Generation means analysis indicated that rhizosheath size on acid soil was controlled by multiple, additive loci. Subsequently, a quantitative trait loci (QTL) analysis of an F6 population of recombinant inbred lines identified five major loci contributing to the phenotype together accounting for over 60% of the total genetic variance. One locus on chromosome 1D accounted for 34% of the genotypic variation. Genetic control of rhizosheath size appears to be relatively simple and markers based on the QTL provide valuable tools for marker assisted breeding.

Can citrate efflux from roots improve phosphorus uptake by plants? Testing the hypothesis with near-isogenic lines of wheat.

Phosphorus (P) deficiency in some plant species triggers the release of organic anions such as citrate and malate from roots. These anions are widely suggested to enhance the availability of phosphate for plant uptake by mobilizing sparingly-soluble forms in the soil. Carazinho is an old wheat (Triticum aestivum) cultivar from Brazil, which secretes citrate constitutively from its root apices, and here we show that it also produces relatively more biomass on soils with low P availability than two recent Australian cultivars that lack citrate efflux. To test whether citrate efflux explains this phenotype, we generated two sets of near-isogenic lines that differ in citrate efflux and compared their biomass production in different soil types and with different P treatments in glasshouse experiments and field trials. Citrate efflux improved relative biomass production in two of six glasshouse trials but only at the lowest P treatments where growth was most severely limited by P availability. Furthermore, citrate efflux provided no consistent advantage for biomass production or yield in multiple field trials. Theoretical modeling indicates that the effectiveness of citrate efflux in mobilizing soil P is greater as the volume of soil into which it diffuses increases. As efflux from these wheat plants is restricted to the root apices, the potential for citrate to mobilize sufficient P to increase shoot biomass may be limited. We conclude that Carazinho has other attributes that contribute to its comparatively good performance in low-P soils.

Plot size matters: interference from intergenotypic competition in plant phenotyping studies.

Genetic and physiological studies often comprise genotypes diverse in vigour, size and flowering time. This can make the phenotyping of complex traits challenging, particularly those associated with canopy development, biomass and yield, as the environment of one genotype can be influenced by a neighbouring genotype. Limited seed and space may encourage field assessment in single, spaced rows or in small, unbordered plots, whereas the convenience of a controlled environment or greenhouse makes pot studies tempting. However, the relevance of such growing conditions to commercial field-grown crops is unclear and often doubtful. Competition for water, light and nutrients necessary for canopy growth will be variable where immediate neighbours are genetically different, particularly under stress conditions, where competition for resources and influence on productivity is greatest. Small hills and rod-rows maximise the potential for intergenotypic competition that is not relevant to a crop's performance in monocultures. Response to resource availability will typically vary among diverse genotypes to alter genotype ranking and reduce heritability for all growth-related traits, with the possible exception of harvest index. Validation of pot experiments to performance in canopies in the field is essential, whereas the planting of multirow plots and the simple exclusion of plot borders at harvest will increase experimental precision and confidence in genotype performance in target environments.

Developmental and growth controls of tillering and water-soluble carbohydrate accumulation in contrasting wheat (Triticum aestivum L.) genotypes: can we dissect them?

In wheat, tillering and water-soluble carbohydrates (WSCs) in the stem are potential traits for adaptation to different environments and are of interest as targets for selective breeding. This study investigated the observation that a high stem WSC concentration (WSCc) is often related to low tillering. The proposition tested was that stem WSC accumulation is plant density dependent and could be an emergent property of tillering, whether driven by genotype or by environment. A small subset of recombinant inbred lines (RILs) contrasting for tillering was grown at different plant densities or on different sowing dates in multiple field experiments. Both tillering and WSCc were highly influenced by the environment, with a smaller, distinct genotypic component; the genotype × environment range covered 350-750 stems m(-2) and 25-210 mg g(-1) WSCc. Stem WSCc was inversely related to stem number m(-2), but genotypic rankings for stem WSCc persisted when RILs were compared at similar stem density. Low tillering-high WSCc RILs had similar leaf area index, larger individual leaves, and stems with larger internode cross-section and wall area when compared with high tillering-low WSCc RILs. The maximum number of stems per plant was positively associated with growth and relative growth rate per plant, tillering rate and duration, and also, in some treatments, with leaf appearance rate and final leaf number. A common threshold of the red:far red ratio (0.39-0.44; standard error of the difference=0.055) coincided with the maximum stem number per plant across genotypes and plant densities, and could be effectively used in crop simulation modelling as a 'cut-off' rule for tillering. The relationship between tillering, WSCc, and their component traits, as well as the possible implications for crop simulation and breeding, is discussed.

A multisite managed environment facility for targeted trait and germplasm phenotyping.

Field evaluation of germplasm for performance under water and heat stress is challenging. Field environments are variable and unpredictable, and genotype×environment interactions are difficult to interpret if environments are not well characterised. Numerous traits, genes and quantitative trait loci have been proposed for improving performance but few have been used in variety development. This reflects the limited capacity of commercial breeding companies to screen for these traits and the absence of validation in field environments relevant to breeding companies, and because little is known about the economic benefit of selecting one particular trait over another. The value of the proposed traits or genes is commonly not demonstrated in genetic backgrounds of value to breeding companies. To overcome this disconnection between physiological trait breeding and uptake by breeding companies, three field sites representing the main environment types encountered across the Australian wheatbelt were selected to form a set of managed environment facilities (MEFs). Each MEF manages soil moisture stress through irrigation, and the effects of heat stress through variable sowing dates. Field trials are monitored continuously for weather variables and changes in soil water and canopy temperature in selected probe genotypes, which aids in decisions guiding irrigation scheduling and sampling times. Protocols have been standardised for an essential core set of measurements so that phenotyping yield and other traits are consistent across sites and seasons. MEFs enable assessment of a large number of traits across multiple genetic backgrounds in relevant environments, determine relative trait value, and facilitate delivery of promising germplasm and high value traits into commercial breeding programs.

Genomic regions for canopy temperature and their genetic association with stomatal conductance and grain yield in wheat.

Stomata are the site of CO2 exchange for water in a leaf. Variation in stomatal control offers promise in genetic improvement of transpiration and photosynthetic rates to improve wheat performance. However, techniques for estimating stomatal conductance (SC) are slow, limiting potential for efficient measurement and genetic modification of this trait. Genotypic variation in canopy temperature (CT) and leaf porosity (LP), as surrogates for SC, were assessed in three wheat mapping populations grown under well-watered conditions. The range and resulting genetic variance were large but not always repeatable across days and years for CT and LP alike. Leaf-to-leaf variation was large for LP, reducing heritability to near zero on a single-leaf basis. Replication across dates and years increased line-mean heritability to ~75% for both CT and LP. Across sampling dates and populations, CT showed a large, additive genetic correlation with LP (rg=-0.67 to -0.83) as expected. Genetic increases in pre-flowering CT were associated with reduced final plant height and both increased harvest index and grain yield but were uncorrelated with aerial biomass. In contrast, post-flowering, cooler canopies were associated with greater aerial biomass and increased grain number and yield. A multi-environment QTL analysis identified up to 16 and 15 genomic regions for CT and LP, respectively, across all three populations. Several of the LP and CT QTL co-located with known QTL for plant height and phenological development and intervals for many of the CT and LP quantitative trait loci (QTL) overlapped, supporting a common genetic basis for the two traits. Notably, both Rht-B1b and Rht-D1b dwarfing alleles were paradoxically positive for LP and CT (i.e. semi-dwarfs had higher stomatal conductance but warmer canopies) highlighting the issue of translation from leaf to canopy in screening for greater transpiration. The strong requirement for repeated assessment of SC suggests the more rapid CT assessment may be of greater value for indirect screening of high or low SC among large numbers of early-generation breeding lines. However, account must be taken of variation in development and canopy architecture when interpreting performance and selecting breeding lines on the basis of CT.

Linked gene networks involved in nitrogen and carbon metabolism and levels of water-soluble carbohydrate accumulation in wheat stems.

High levels of water-soluble carbohydrates (WSC) provide an important source of stored assimilate for grain filling in wheat. To better understand the interaction between carbohydrate metabolism and other metabolic processes associated with the WSC trait, a genome-wide expression analysis was performed using eight field-grown lines from the high and low phenotypic tails of a wheat population segregating for WSC and the Affymetrix wheat genome array. The 259 differentially expressed probe sets could be assigned to 26 functional category bins, as defined using MapMan software. There were major differences in the categories to which the differentially expressed probe sets were assigned; for example, probe sets upregulated in high relative to low WSC lines were assigned to category bins such as amino acid metabolism, protein degradation and transport and to be involved in starch synthesis-related processes (carbohydrate metabolism bin), whereas downregulated probe sets were assigned to cell wall-related bins, amino acid synthesis and stress and were involved in sucrose breakdown. Using the set of differentially expressed genes as input, chemical-protein network analyses demonstrated a linkage between starch and N metabolism via pyridoxal phosphate. Twelve C and N metabolism-related genes were selected for analysis of their expression response to varying N and water treatments in the field in the four high and four low WSC progeny lines; the two nitrogen/amino acid metabolism genes demonstrated a consistent negative association between their level of expression and level of WSC. Our results suggest that the assimilation of nitrogen into amino acids is an important factor that influences the levels of WSC in the stems of field-grown wheat.

Molecular detection of genomic regions associated with grain yield and yield-related components in an elite bread wheat cross evaluated under irrigated and rainfed conditions.

Grain yield and grain weight of wheat are often decreased by water-limitation in the north-eastern cropping belt of Australia. Based on knowledge that CIMMYT lines are well-adapted in this region, a recombinant inbred line (RIL) population between two elite CIMMYT bread wheats (Seri M82 and Babax) was evaluated under water-limited environments. Fourteen productivity traits were evaluated in 192 progeny in up to eight trials. For three aggregations of the environments (all, high yield or low yield), multiple quantitative trait loci (QTL) were detected, each explaining <15% of variation. Co-location of multiple trait QTL was greatest on linkage groups 1B-a, 1D-b, 4A-a, 4D-a, 6A-a, 6B-a, 7A-a and an unassigned linkage group. Two putative QTL (LOD > 3) from Seri (6D-b and UA-d) increased grain yield and co-located with a suggestive (2 < LOD < 3) and a putative QTL for increased stem carbohydrate content (WSC), respectively; the latter QTL also co-located with a putative anthesis QTL for earlier flowering. Both QTL were detected only in high yield (>4t ha(-1)) environments. A third increased grain yield QTL (7A-a) from Babax co-located with QTL for increased grain number. Six putative QTL increased grain weight and co-located with QTL for harvest index, grains per spike and spike number. Three putative QTL for increased grains per spike co-located with strong QTL for earlier flowering, increased grain weight and fewer spikes. A group of progeny that exceeded the mean grain yield and grain weight of commercial checks had an increased frequency of QTL for high WSC, large grain size, increased harvest index and greater height, but fewer stems, when compared to low yielding (20% less), low grain weight progeny. These findings were consistent with agronomic analyses of the germplasm and demonstrate that there should be opportunities to independently manipulate grain number and grain size which is typically difficult due to strong negative correlations.