Genetic analysis of late-maturity α-amylase in twelve wheat populations

MAIN CONCLUSION

Genetic loci, particularly those with an effect in the independent panel, could be utilised to further reduce LMA expression when used with favourable combinations of genes known to affect LMA. Late maturity α-amylase (LMA) is a grain quality defect involving elevated α-amylase within the aleurone of wheat (Triticum aestivum L.) grains. The genes known to affect expression are the reduced height genes Rht-B1 (chromosome 4B) and Rht-D1 (chromosome 4D), and an ent-copalyl diphosphate synthase gene (LMA-1) on chromosome 7B. Other minor effect loci have been reported, but these are poorly characterised and further genetic understanding is needed. In this study, twelve F4-derived populations were created through single seed descent, genotyped and evaluated for LMA. LMA-1 haplotype C and the Rht-D1b allele substantially reduced LMA expression. The alternative dwarfing genes Rht13 and Rht18 had no significant effect on LMA expression. Additional quantitative trait loci (QTL) were mapped at 16 positions in the wheat genome. Effects on LMA expression were detected for four of these QTL in a large independent panel of Australian wheat lines. The QTL detected in mapping populations and confirmed in the large independent panel provide further opportunity for selection against LMA, especially if combined with Rht-D1b and/or favourable haplotypes of LMA-1.

A multi-environment framework to evaluate the adaptation of wheat (Triticum aestivum) to heat stress

Assessing adaptation to abiotic stresses such as high temperature conditions across multiple environments presents opportunities for breeders to target selection for broad adaptation and specific adaptation. Adaptation of wheat to heat stress is an important component of adaptation in variable climates such as the cereal producing areas of Australia. However, in variable climates stress conditions may not be present in every season or are present to varying degrees, at different times during the season. Such conditions complicate plant breeders' ability to select for adaptation to abiotic stress. This study presents a framework for the assessment of the genetic basis of adaptation to heat stress conditions with improved relevance to breeders' selection objectives. The framework was applied here with the evaluation of 1225 doubled haploid lines from five populations across six environments (three environments selected for contrasting temperature stress conditions during anthesis and grain fill periods, over two consecutive seasons), using regionally best practice planting times to evaluate the role of heat stress conditions in genotype adaptation. Temperature co-variates were determined for each genotype, in each environment, for the anthesis and grain fill periods. Genome-wide QTL analysis identified performance QTL for stable effects across all environments, and QTL that illustrated responsiveness to heat stress conditions across the sampled environments. A total of 199 QTL were identified, including 60 performance QTL, and 139 responsiveness QTL. Of the identified QTL, 99 occurred independent of the 21 anthesis date QTL identified. Assessing adaptation to heat stress conditions as the combination of performance and responsiveness offers breeders opportunities to select for grain yield stability across a range of environments, as well as genotypes with higher relative yield in stress conditions.

Plant Variety Selection Using Interaction Classes Derived From Factor Analytic Linear Mixed Models: Models With Independent Variety Effects

A major challenge in the analysis of plant breeding multi-environment datasets is the provision of meaningful and concise information for variety selection in the presence of variety by environment interaction (VEI). This is addressed in the current paper by fitting a factor analytic linear mixed model (FALMM) then using the fundamental factor analytic parameters to define groups of environments in the dataset within which there is minimal crossover VEI, but between which there may be substantial crossover VEI. These groups are consequently called interaction classes (iClasses). Given that the environments within an iClass exhibit minimal crossover VEI, it is then valid to obtain predictions of overall variety performance (across environments) for each iClass. These predictions can then be used not only to select the best varieties within each iClass but also to match varieties in terms of their patterns of VEI across iClasses. The latter is aided with the use of a new graphical tool called an iClass Interaction Plot. The ideas are introduced in this paper within the framework of FALMMs in which the genetic effects for different varieties are assumed independent. The application to FALMMs which include information on genetic relatedness is the subject of a subsequent paper.

Genetic analysis of wheat (Triticum aestivum) adaptation to heat stress

Adaptation to abiotic stresses such as high-temperature conditions should be considered as its independent components of total performance and responsiveness. Understanding and identifying improved adaptation to abiotic stresses such as heat stress has been the focus of a number of studies in recent decades. However, confusing and potentially misleading terminology has made progress difficult and hard to apply within breeding programs selecting for improved adaption to heat stress conditions. This study proposes that adaption to heat stress (and other abiotic stresses) be considered as the combination of total performance and responsiveness to heat stress. In this study, 1413 doubled haploid lines from seven populations were screened through a controlled environment assay, subjecting plants to three consecutive eight hour days of an air temperature of 36 °C and a wind speed of 40 km h^-1, 10 days after the end of anthesis. QTL mapping identified a total of 96 QTL for grain yield determining traits and anthesis date with nine correlating to responsiveness, 72 for total performance and 15 for anthesis date. Responsiveness QTL were found both collocated with other performance QTL as well as independently. A sound understanding of genomic regions associated with total performance and responsiveness will be important for breeders. Genomic regions of total performance, those that show higher performance that is stable under both stressed and non-stressed conditions, potentially offer significant opportunities to breeders. We propose this as a definition and selection target that has not previously been defined for heat stress adaptation.

Estimating Biomass and Canopy Height With LiDAR for Field Crop Breeding

Above-ground biomass (AGB) is a trait with much potential for exploitation within wheat breeding programs and is linked closely to canopy height (CH). However, collecting phenotypic data for AGB and CH within breeding programs is labor intensive, and in the case of AGB, destructive and prone to assessment error. As a result, measuring these traits is seldom a priority for breeders, especially at the early stages of a selection program. LiDAR has been demonstrated as a sensor capable of collecting three-dimensional data from wheat field trials, and potentially suitable for providing objective, non-destructive, high-throughput estimates of AGB and CH for use by wheat breeders. The current study investigates the deployment of a LiDAR system on a ground-based high-throughput phenotyping platform in eight wheat field trials across southern Australia, for the non-destructive estimate of AGB and CH. LiDAR-derived measurements were compared to manual measurements of AGB and CH collected at each site and assessed for their suitability of application within a breeding program. Correlations between AGB and LiDAR Projected Volume (LPV) were generally strong (up to r = 0.86), as were correlations between CH and LiDAR Canopy Height (LCH) (up to r = 0.94). Heritability (H2) of LPV (H2 = 0.32-0.90) was observed to be greater than, or similar to, the heritability of AGB (H2 = 0.12-0.78) for the majority of measurements. A similar level of heritability was observed for LCH (H2 = 0.41-0.98) and CH (H2 = 0.49-0.98). Further to this, measurements of LPV and LCH were shown to be highly repeatable when collected from either the same or opposite direction of travel. LiDAR scans were collected at a rate of 2,400 plots per hour, with the potential to further increase throughput to 7,400 plots per hour. This research demonstrates the capability of LiDAR sensors to collect high-quality, non-destructive, repeatable measurements of AGB and CH suitable for use within both breeding and research programs.

High-Throughput Field Imaging and Basic Image Analysis in a Wheat Breeding Programme

Visual assessment of colour-based traits plays a key role within field-crop breeding programmes, though the process is subjective and time-consuming. Digital image analysis has previously been investigated as an objective alternative to visual assessment for a limited number of traits, showing suitability and slight improvement to throughput over visual assessment. However, easily adoptable, field-based high-throughput methods are still lacking. The aim of the current study was to produce a high-throughput digital imaging and analysis pipeline for the assessment of colour-based traits within a wheat breeding programme. This was achieved through the steps of (i) a proof-of-concept study demonstrating basic image analysis methods in a greenhouse, (ii) application of these methods to field trials using hand-held imaging, and (iii) developing a field-based high-throughput imaging infrastructure for data collection. The proof of concept study showed a strong correlation (r = 0.95) between visual and digital assessments of wheat physiological yellowing (PY) in a greenhouse environment, with both scores having similar heritability (H2 = 0.85 and 0.76, respectively). Digital assessment of hand-held field images showed strong correlations to visual scores for PY (r = 0.61 and 0.78), senescence (r = 0.74 and 0.75) and Septoria tritici blotch (STB; r = 0.76), with greater heritability of digital scores, excluding STB. Development of the high-throughput imaging infrastructure allowed for images of field plots to be collected at a rate of 7,400 plots per hour. Images of an advanced breeding trial collected with this system were analysed for canopy cover at two time-points, with digital scores correlating strongly to visual scores (r = 0.88 and 0.86) and having similar or greater heritability. This study details how high-throughput digital phenotyping can be applied to colour-based traits within field trials of a wheat breeding programme. It discusses the logistics of implementing such systems with minimal disruption to the programme, provides a detailed methodology for the basic image analysis methods utilized, and has potential for application to other field-crop breeding or research programmes.

High-Throughput Field Imaging and Basic Image Analysis in a Wheat Breeding Programme

Visual assessment of colour-based traits plays a key role within field-crop breeding programmes, though the process is subjective and time-consuming. Digital image analysis has previously been investigated as an objective alternative to visual assessment for a limited number of traits, showing suitability and slight improvement to throughput over visual assessment. However, easily adoptable, field-based high-throughput methods are still lacking. The aim of the current study was to produce a high-throughput digital imaging and analysis pipeline for the assessment of colour-based traits within a wheat breeding programme. This was achieved through the steps of (i) a proof-of-concept study demonstrating basic image analysis methods in a greenhouse, (ii) application of these methods to field trials using hand-held imaging, and (iii) developing a field-based high-throughput imaging infrastructure for data collection. The proof of concept study showed a strong correlation (r = 0.95) between visual and digital assessments of wheat physiological yellowing (PY) in a greenhouse environment, with both scores having similar heritability (H² = 0.85 and 0.76, respectively). Digital assessment of hand-held field images showed strong correlations to visual scores for PY (r = 0.61 and 0.78), senescence (r = 0.74 and 0.75) and Septoria tritici blotch (STB; r = 0.76), with greater heritability of digital scores, excluding STB. Development of the high-throughput imaging infrastructure allowed for images of field plots to be collected at a rate of 7,400 plots per hour. Images of an advanced breeding trial collected with this system were analysed for canopy cover at two time-points, with digital scores correlating strongly to visual scores (r = 0.88 and 0.86) and having similar or greater heritability. This study details how high-throughput digital phenotyping can be applied to colour-based traits within field trials of a wheat breeding programme. It discusses the logistics of implementing such systems with minimal disruption to the programme, provides a detailed methodology for the basic image analysis methods utilized, and has potential for application to other field-crop breeding or research programmes.

Increased genomic prediction accuracy in wheat breeding using a large Australian panel

KEY MESSAGE

Genomic prediction accuracy within a large panel was found to be substantially higher than that previously observed in smaller populations, and also higher than QTL-based prediction. In recent years, genomic selection for wheat breeding has been widely studied, but this has typically been restricted to population sizes under 1000 individuals. To assess its efficacy in germplasm representative of commercial breeding programmes, we used a panel of 10,375 Australian wheat breeding lines to investigate the accuracy of genomic prediction for grain yield, physical grain quality and other physiological traits. To achieve this, the complete panel was phenotyped in a dedicated field trial and genotyped using a custom AxiomTM Affymetrix SNP array. A high-quality consensus map was also constructed, allowing the linkage disequilibrium present in the germplasm to be investigated. Using the complete SNP array, genomic prediction accuracies were found to be substantially higher than those previously observed in smaller populations and also more accurate compared to prediction approaches using a finite number of selected quantitative trait loci. Multi-trait genetic correlations were also assessed at an additive and residual genetic level, identifying a negative genetic correlation between grain yield and protein as well as a positive genetic correlation between grain size and test weight.

Genetic Basis for Variation in Wheat Grain Yield in Response to Varying Nitrogen Application

Nitrogen (N) is a major nutrient needed to attain optimal grain yield (GY) in all environments. Nitrogen fertilisers represent a significant production cost, in both monetary and environmental terms. Developing genotypes capable of taking up N early during development while limiting biomass production after establishment and showing high N-use efficiency (NUE) would be economically beneficial. Genetic variation in NUE has been shown previously. Here we describe the genetic characterisation of NUE and identify genetic loci underlying N response under different N fertiliser regimes in a bread wheat population of doubled-haploid lines derived from a cross between two Australian genotypes (RAC875 × Kukri) bred for a similar production environment. NUE field trials were carried out at four sites in South Australia and two in Western Australia across three seasons. There was genotype-by-environment-by-treatment interaction across the sites and also good transgressive segregation for yield under different N supply in the population. We detected some significant Quantitative Trait Loci (QTL) associated with NUE and N response at different rates of N application across the sites and years. It was also possible to identify lines showing positive N response based on the rankings of their Best Linear Unbiased Predictions (BLUPs) within a trial. Dissecting the complexity of the N effect on yield through QTL analysis is a key step towards elucidating the molecular and physiological basis of NUE in wheat.

The Genetic Control of Grain Protein Content under Variable Nitrogen Supply in an Australian Wheat Mapping Population

Genetic variation has been observed in both protein concentration in wheat grain and total protein content (protein yield). Here we describe the genetic analysis of variation for grain protein in response to nitrogen (N) supply and locate significant genomic regions controlling grain protein components in a spring wheat population. In total, six N use efficiency (NUE) field trials were carried out for the target traits in a sub-population of doubled haploid lines derived from a cross between two Australian varieties, RAC875 and Kukri, in Southern and Western Australia from 2011 to 2013. Twenty-four putative Quantitative Trait Loci (QTL) for protein-related traits were identified at high and low N supply and ten QTL were identified for the response to N for the traits studied. These loci accounted for a significant proportion of the overall effect of N supply. Several of the regions were co-localised with grain yield QTL and are promising targets for further investigation and selection in breeding programs.

Factor analytic mixed models for the provision of grower information from national crop variety testing programs

Factor analytic mixed models for national crop variety testing programs have the potential to improve industry productivity through appropriate modelling and reporting to growers of variety by environment interaction. Crop variety testing programs are conducted in many countries world-wide. Within each program, data are combined across locations and seasons, and analysed in order to provide information to assist growers in choosing the best varieties for their conditions. Despite major advances in the statistical analysis of multi-environment trial data, such methodology has not been adopted within national variety testing programs. The most commonly used approach involves a variance component model that includes variety and environment main effects, and variety by environment (V × E) interaction effects. The variety predictions obtained from such an analysis, and subsequently reported to growers, are typically on a long-term regional basis. In Australia, the variance component model has been found to be inadequate in terms of modelling V × E interaction, and the reporting of information at a regional level often masks important local V × E interaction. In contrast, the factor analytic mixed model approach that is widely used in Australian plant breeding programs, has regularly been found to provide a parsimonious and informative model for V × E effects, and accurate predictions. In this paper we develop an approach for the analysis of crop variety evaluation data that is based on a factor analytic mixed model. The information obtained from such an analysis may well be superior, but will only enhance industry productivity if mechanisms exist for successful technology transfer. With this in mind, we offer a suggested reporting format that is user-friendly and contains far greater local information for individual growers than is currently the case.

Genetic control of grain yield and grain physical characteristics in a bread wheat population grown under a range of environmental conditions

Genetic analysis of the yield and physical quality of wheat revealed complex genetic control, including strong effects of photoperiod-sensitivity loci. Environmental conditions such as moisture deficit and high temperatures during the growing period affect the grain yield and grain characteristics of bread wheat (Triticum aestivum L.). The aim of this study was to map quantitative trait loci (QTL) for grain yield and grain quality traits using a Drysdale/Gladius bread wheat mapping population grown under a range of environmental conditions in Australia and Mexico. In general, yield and grain quality were reduced in environments exposed to drought and/or heat stress. Despite large effects of known photoperiod-sensitivity loci (Ppd-B1 and Ppd-D1) on crop development, grain yield and grain quality traits, it was possible to detect QTL elsewhere in the genome. Some of these QTL were detected consistently across environments. A locus on chromosome 6A (TaGW2) that is known to be associated with grain development was associated with grain width, thickness and roundness. The grain hardness (Ha) locus on chromosome 5D was associated with particle size index and flour extraction and a region on chromosome 3B was associated with grain width, thickness, thousand grain weight and yield. The genetic control of grain length appeared to be largely independent of the genetic control of the other grain dimensions. As expected, effects on grain yield were detected at loci that also affected yield components. Some QTL displayed QTL-by-environment interactions, with some having effects only in environments subject to water limitation and/or heat stress.

Genetic mapping and marker development for resistance of wheat against the root lesion nematode Pratylenchus neglectus

BACKGROUND

The Rlnn1 locus, which resides on chromosome 7A of bread wheat (Triticum aestivum L.) confers moderate resistance against the root lesion nematode Pratylenchus neglectus. Prior to this research, the exact linkage relationships of Rlnn1 with other loci on chromosome 7A were not clear and there were no simple codominant markers available for selection of Rlnn1 in wheat breeding. The objectives of the research reported here were to (1) develop an improved genetic map of the Rlnn1 region of chromosome 7A and (2) develop molecular markers that could be used in marker-assisted selection to improve resistance of wheat against P. neglectus.

RESULTS

A large-effect quantitative trait locus (QTL) for resistance against P. neglectus was genetically mapped using a population of Excalibur/Kukri doubled haploid lines. This QTL coincides in position with the rust resistance gene(s) Lr20/Sr15, the phytoene synthase gene Psy-A1 and 10 molecular markers, including five new markers designed using wheat-rice comparative genomics and wheat expressed sequence tags. Two of the new markers are suitable for use as molecular diagnostic tools to distinguish plants that carry Rlnn1 and Lr20/Sr15 from those that do not carry these resistance genes.

CONCLUSIONS

The genomic location of Rlnn1 was confirmed to be in the terminal region of the long arm of chromosome 7A. Molecular markers were developed that provide simple alternatives to costly phenotypic assessment of resistance against P. neglectus in wheat breeding. In Excalibur, genetic recombination seems to be completely suppressed in the Rlnn1 region.

A DNA-based method for studying root responses to drought in field-grown wheat genotypes

Root systems are critical for water and nutrient acquisition by crops. Current methods measuring root biomass and length are slow and labour-intensive for studying root responses to environmental stresses in the field. Here, we report the development of a method that measures changes in the root DNA concentration in soil and detects root responses to drought in controlled environment and field trials. To allow comparison of soil DNA concentrations from different wheat genotypes, we also developed a procedure for correcting genotypic differences in the copy number of the target DNA sequence. The new method eliminates the need for separation of roots from soil and permits large-scale phenotyping of root responses to drought or other environmental and disease stresses in the field.

Quantification of the effects of VRN1 and Ppd-D1 to predict spring wheat (Triticum aestivum) heading time across diverse environments

Heading time is a major determinant of the adaptation of wheat to different environments, and is critical in minimizing risks of frost, heat, and drought on reproductive development. Given that major developmental genes are known in wheat, a process-based model, APSIM, was modified to incorporate gene effects into estimation of heading time, while minimizing degradation in the predictive capability of the model. Model parameters describing environment responses were replaced with functions of the number of winter and photoperiod (PPD)-sensitive alleles at the three VRN1 loci and the Ppd-D1 locus, respectively. Two years of vernalization and PPD trials of 210 lines (spring wheats) at a single location were used to estimate the effects of the VRN1 and Ppd-D1 alleles, with validation against 190 trials (~4400 observations) across the Australian wheatbelt. Compared with spring genotypes, winter genotypes for Vrn-A1 (i.e. with two winter alleles) had a delay of 76.8 degree days (°Cd) in time to heading, which was double the effect of the Vrn-B1 or Vrn-D1 winter genotypes. Of the three VRN1 loci, winter alleles at Vrn-B1 had the strongest interaction with PPD, delaying heading time by 99.0 °Cd under long days. The gene-based model had root mean square error of 3.2 and 4.3 d for calibration and validation datasets, respectively. Virtual genotypes were created to examine heading time in comparison with frost and heat events and showed that new longer-season varieties could be heading later (with potential increased yield) when sown early in season. This gene-based model allows breeders to consider how to target gene combinations to current and future production environments using parameters determined from a small set of phenotyping treatments.

Detection of two major grain yield QTL in bread wheat (Triticum aestivum L.) under heat, drought and high yield potential environments

A large proportion of the worlds' wheat growing regions suffers water and/or heat stress at some stage during the crop growth cycle. With few exceptions, there has been no utilisation of managed environments to screen mapping populations under repeatable abiotic stress conditions, such as the facilities developed by the International Wheat and Maize Improvement Centre (CIMMYT). Through careful management of irrigation and sowing date over three consecutive seasons, repeatable heat, drought and high yield potential conditions were imposed on the RAC875/Kukri doubled haploid population to identify genetic loci for grain yield, yield components and key morpho-physiological traits under these conditions. Two of the detected quantitative trait loci (QTL) were located on chromosome 3B and had a large effect on canopy temperature and grain yield, accounting for up to 22 % of the variance for these traits. The locus on chromosome arm 3BL was detected under all three treatments but had its largest effect under the heat stress conditions, with the RAC875 allele increasing grain yield by 131 kg ha(-1) (or phenotypically, 7 % of treatment average). Only two of the eight yield QTL detected in the current study (including linkage groups 3A, 3D, 4D 5B and 7A) were previously detected in the RAC875/Kukri doubled haploid population; and there were also different yield components driving grain yield. A number of discussion points are raised to understand differences between the Mexican and southern Australian production environments and explain the lack of correlation between the datasets. The two key QTL detected on chromosome 3B in the present study are candidates for further genetic dissection and development of molecular markers.

Genetic dissection of grain yield and physical grain quality in bread wheat (Triticum aestivum L.) under water-limited environments

In the water-limited bread wheat production environment of southern Australia, large advances in grain yield have previously been achieved through the introduction and improved understanding of agronomic traits controlled by major genes, such as the semi-dwarf plant stature and photoperiod insensitivity. However, more recent yield increases have been achieved through incremental genetic advances, of which, breeders and researchers do not fully understand the underlying mechanism(s). A doubled haploid population was utilised, derived from a cross between RAC875, a relatively drought-tolerant breeders' line and Kukri, a locally adapted variety more intolerant of drought. Experiments were performed in 16 environments over four seasons in southern Australia, to physiologically dissect grain yield and to detect quantitative trait loci (QTL) for these traits. Two stage multi-environment trial analysis identified three main clusters of experiments (forming distinctive environments, ENVs), each with a distinctive growing season rainfall patterns. Kernels per square metre were positively correlated with grain yield and influenced by kernels per spikelet, a measure of fertility. QTL analysis detected nine loci for grain yield across these ENVs, individually accounting for between 3 and 18% of genetic variance within their respective ENVs, with the RAC875 allele conferring increased grain yield at seven of these loci. These loci were partially dissected by the detection of co-located QTL for other traits, namely kernels per square metre. While most loci for grain yield have previously been reported, their deployment and effect within local germplasm are now better understood. A number of novel loci can be further exploited to aid breeders' efforts in improving grain yield in the southern Australian environment.

Identification of novel quantitative trait loci for days to ear emergence and flag leaf glaucousness in a bread wheat (Triticum aestivum L.) population adapted to southern Australian conditions

In southern Australia, where the climate is predominantly Mediterranean, achieving the correct flowering time in bread wheat minimizes the impact of in-season cyclical and terminal drought. Flag leaf glaucousness has been hypothesized as an important component of drought tolerance but its value and genetic basis in locally adapted germplasm is unknown. From a cross between Kukri and RAC875, a doubled-haploid (DH) population was developed. A genetic linkage map consisting of 456 DArT and SSR markers was used to detect QTL affecting time to ear emergence and Zadoks growth score in seven field experiments. While ear emergence time was similar between the parents, there was significant transgressive segregation in the population. This was the result of segregation for the previously characterized Ppd-D1a and Ppd-B1 photoperiod responsive alleles. QTL of smaller effect were also detected on chromosomes 1A, 4A, 4B, 5A, 5B, 7A and 7B. A novel QTL for flag leaf glaucousness of large, repeatable effect was detected in six field experiments, on chromosome 3A (QW.aww-3A) and accounted for up to 52 percent of genetic variance for this trait. QW.aww-3A was validated under glasshouse conditions in a recombinant inbred line population from the same cross. The genetic basis of time to ear emergence in this population will aid breeders' understanding of phenological adaptation to the local environment. Novel loci identified for flag leaf glaucousness and the wide phenotypic variation within the DH population offers considerable scope to investigate the impact and value of this trait for bread wheat production in southern Australia.

Genetic dissection of grain yield and physical grain quality in bread wheat (Triticum aestivum L.) under water-limited environments

In the water-limited bread wheat production environment of southern Australia, large advances in grain yield have previously been achieved through the introduction and improved understanding of agronomic traits controlled by major genes, such as the semi-dwarf plant stature and photoperiod insensitivity. However, more recent yield increases have been achieved through incremental genetic advances, of which, breeders and researchers do not fully understand the underlying mechanism(s). A doubled haploid population was utilised, derived from a cross between RAC875, a relatively drought-tolerant breeders' line and Kukri, a locally adapted variety more intolerant of drought. Experiments were performed in 16 environments over four seasons in southern Australia, to physiologically dissect grain yield and to detect quantitative trait loci (QTL) for these traits. Two stage multi-environment trial analysis identified three main clusters of experiments (forming distinctive environments, ENVs), each with a distinctive growing season rainfall patterns. Kernels per square metre were positively correlated with grain yield and influenced by kernels per spikelet, a measure of fertility. QTL analysis detected nine loci for grain yield across these ENVs, individually accounting for between 3 and 18% of genetic variance within their respective ENVs, with the RAC875 allele conferring increased grain yield at seven of these loci. These loci were partially dissected by the detection of co-located QTL for other traits, namely kernels per square metre. While most loci for grain yield have previously been reported, their deployment and effect within local germplasm are now better understood. A number of novel loci can be further exploited to aid breeders' efforts in improving grain yield in the southern Australian environment.

Identification of novel quantitative trait loci for days to ear emergence and flag leaf glaucousness in a bread wheat (Triticum aestivum L.) population adapted to southern Australian conditions

In southern Australia, where the climate is predominantly Mediterranean, achieving the correct flowering time in bread wheat minimizes the impact of in-season cyclical and terminal drought. Flag leaf glaucousness has been hypothesized as an important component of drought tolerance but its value and genetic basis in locally adapted germplasm is unknown. From a cross between Kukri and RAC875, a doubled-haploid (DH) population was developed. A genetic linkage map consisting of 456 DArT and SSR markers was used to detect QTL affecting time to ear emergence and Zadoks growth score in seven field experiments. While ear emergence time was similar between the parents, there was significant transgressive segregation in the population. This was the result of segregation for the previously characterized Ppd-D1a and Ppd-B1 photoperiod responsive alleles. QTL of smaller effect were also detected on chromosomes 1A, 4A, 4B, 5A, 5B, 7A and 7B. A novel QTL for flag leaf glaucousness of large, repeatable effect was detected in six field experiments, on chromosome 3A (QW.aww-3A) and accounted for up to 52 percent of genetic variance for this trait. QW.aww-3A was validated under glasshouse conditions in a recombinant inbred line population from the same cross. The genetic basis of time to ear emergence in this population will aid breeders' understanding of phenological adaptation to the local environment. Novel loci identified for flag leaf glaucousness and the wide phenotypic variation within the DH population offers considerable scope to investigate the impact and value of this trait for bread wheat production in southern Australia.

Genetic and genomic tools to improve drought tolerance in wheat

Tolerance to drought is a quantitative trait, with a complex phenotype, often confounded by plant phenology. Breeding for drought tolerance is further complicated since several types of abiotic stress, such as high temperatures, high irradiance, and nutrient toxicities or deficiencies can challenge crop plants simultaneously. Although marker-assisted selection is now widely deployed in wheat, it has not contributed significantly to cultivar improvement for adaptation to low-yielding environments and breeding has relied largely on direct phenotypic selection for improved performance in these difficult environments. The limited success of the physiological and molecular breeding approaches now suggests that a careful rethink is needed of our strategies in order to understand better and breed for drought tolerance. A research programme for increasing drought tolerance of wheat should tackle the problem in a multi-disciplinary approach, considering interaction between multiple stresses and plant phenology, and integrating the physiological dissection of drought-tolerance traits and the genetic and genomics tools, such as quantitative trait loci (QTL), microarrays, and transgenic crops. In this paper, recent advances in the genetics and genomics of drought tolerance in wheat and barley are reviewed and used as a base for revisiting approaches to analyse drought tolerance in wheat. A strategy is then described where a specific environment is targeted and appropriate germplasm adapted to the chosen environment is selected, based on extensive definition of the morpho-physiological and molecular mechanisms of tolerance of the parents. This information was used to create structured populations and develop models for QTL analysis and positional cloning.

The effects on grain quality traits of a grain serpin protein and the VPM1 segment in southern Australian wheat breeding

Production of wheat of sufficient quality to meet market demands is an ongoing agricultural challenge. Identification and evaluation of alleles of genes affecting quality parameters enables breeders to improve their germplasm by active selection towards specific allele combinations. Using a large dataset obtained from southern Australian wheat breeding programs, and including a relationship matrix in the analysis to minimise bias, we re-evaluated the effects of high- and low-molecular-weight glutenin alleles and puroindoline alleles on the grain quality parameters Rmax, dough extensibility, dough development time, flour water absorption, and milling yield and found that estimated effects were in close agreement with those from earlier analyses without a relationship matrix. We also evaluated, for the first time, the effects on the same quality parameters of 2 alleles (wild-type and null) of a defence grain protein, a serpin located on chromosome 5B. In addition, we assessed the effect of the VPM1 alien segment. The serpin null allele significantly reduced milling yield by ~0.4 g of flour per 100 g of grain milled across different germplasm sources and flour protein levels. In Australian germplasm, the origin of this allele was traced to a 19th Century introduction from India by William Farrer; however other sources, of significance in international breeding programs, were also identified. Our analysis of the effect of the VPM1 segment on quality traits revealed no detrimental effects of its presence on the traits we measured.

Genetic dissection of grain yield in bread wheat. I. QTL analysis

Grain yield forms one of the key economic drivers behind a successful wheat (Triticum aestivum L.) cropping enterprise and is consequently a major target for wheat breeding programmes. However, due to its complex nature, little is known regarding the genetic control of grain yield. A doubled-haploid population, comprising 182 individuals, produced from a cross between two cultivars 'Trident' and 'Molineux', was used to construct a linkage map based largely on microsatellite molecular makers. 'Trident' represents a lineage of wheat varieties from southern Australia that has achieved consistently high relative grain yield across a range of environments. In comparison, 'Molineux' would be rated as a variety with low to moderate grain yield. The doubled-haploid population was grown from 2002 to 2005 in replicated field experiments at a range of environments across the southern Australian wheat belt. In total, grain yield data were recorded for the population at 18 site-year combinations. Grain yield components were also measured at three of these environments. Many loci previously found to be involved in the control of plant height, rust resistance and ear-emergence were found to influence grain yield and grain yield components in this population. An additional nine QTL, apparently unrelated to these traits, were also associated with grain yield. A QTL associated with grain yield on chromosome 1B, with no significant relationship with plant height, ear-emergence or rust resistance, was detected (LOD > or =2) at eight of the 18 environments. The mean yield, across 18 environments, of individuals carrying the 'Molineux' allele at the 1B locus was 4.8% higher than the mean grain yield of those lines carrying the 'Trident' allele at this locus. Another QTL identified on chromosome 4D was also associated with overall gain yield at six of the 18 environments. Of the nine grain yield QTL not shown to be associated with plant height, phenology or rust resistance, two were located near QTL associated with grain yield components. A third QTL, associated with grain yield components at each of the environments used for testing, was located on chromosome 7D. However, this QTL was not associated with grain yield at any of the environments. The implications of these findings on marker-assisted selection for grain yield are discussed.

Genetic dissection of grain yield in bread wheat. II. QTL-by-environment interaction

The grain yield of wheat is influenced by genotype, environment and genotype-by-environment interaction. A mapping population consisting of 182 doubled haploid progeny derived from a cross between the southern Australian varieties 'Trident' and 'Molineux', was used to characterise the interaction of previously mapped grain yield quantitative trait locus (QTL) with specific environmental covariables. Environments (17) used for grain yield assessment were characterised for latitude, rainfall, various temperature-based variables and stripe rust infection severity. The number of days in the growing season in which the maximum temperature exceeded 30 degrees C was identified as the variable with the largest effect on site mean grain yield. However, the greatest QTL-by-environmental covariable interactions were observed with the severity of stripe rust infection. The rust resistance allele at the Lr37/Sr38/Yr17 locus had the greatest positive effect on grain yield when an environment experienced a combination of high-stripe rust infection and cool days. The grain yield QTL, QGyld.agt-4D, showed a very similar QTL-by-environment covariable interaction pattern to the Lr37/Sr38/Yr17 locus, suggesting a possible role in rust resistance or tolerance. Another putative grain yield per se QTL, QGyld.agt-1B, displayed interactions with the quantity of winter and spring rainfall, the number of days in which the maximum temperature exceeded 30 degrees C, and the number of days with a minimum temperature below 10 degrees C. However, no cross-over interaction effect was observed for this locus, and the 'Molineux' allele remained associated with higher grain yield in response to all environmental covariables. The results presented here confirm that QGyld.agt-1B may be a prime candidate for marker-assisted selection for improved grain yield and wide adaptation in wheat. The benefit of analysing the interaction of QTL and environmental covariables, such as employed here, is discussed.

Genetic dissection of grain yield in bread wheat. I. QTL analysis

Grain yield forms one of the key economic drivers behind a successful wheat (Triticum aestivum L.) cropping enterprise and is consequently a major target for wheat breeding programmes. However, due to its complex nature, little is known regarding the genetic control of grain yield. A doubled-haploid population, comprising 182 individuals, produced from a cross between two cultivars 'Trident' and 'Molineux', was used to construct a linkage map based largely on microsatellite molecular makers. 'Trident' represents a lineage of wheat varieties from southern Australia that has achieved consistently high relative grain yield across a range of environments. In comparison, 'Molineux' would be rated as a variety with low to moderate grain yield. The doubled-haploid population was grown from 2002 to 2005 in replicated field experiments at a range of environments across the southern Australian wheat belt. In total, grain yield data were recorded for the population at 18 site-year combinations. Grain yield components were also measured at three of these environments. Many loci previously found to be involved in the control of plant height, rust resistance and ear-emergence were found to influence grain yield and grain yield components in this population. An additional nine QTL, apparently unrelated to these traits, were also associated with grain yield. A QTL associated with grain yield on chromosome 1B, with no significant relationship with plant height, ear-emergence or rust resistance, was detected (LOD > or =2) at eight of the 18 environments. The mean yield, across 18 environments, of individuals carrying the 'Molineux' allele at the 1B locus was 4.8% higher than the mean grain yield of those lines carrying the 'Trident' allele at this locus. Another QTL identified on chromosome 4D was also associated with overall gain yield at six of the 18 environments. Of the nine grain yield QTL not shown to be associated with plant height, phenology or rust resistance, two were located near QTL associated with grain yield components. A third QTL, associated with grain yield components at each of the environments used for testing, was located on chromosome 7D. However, this QTL was not associated with grain yield at any of the environments. The implications of these findings on marker-assisted selection for grain yield are discussed.

Diversity arrays technology (DArT) for high-throughput profiling of the hexaploid wheat genome

Despite a substantial investment in the development of panels of single nucleotide polymorphism (SNP) markers, the simple sequence repeat (SSR) technology with a limited multiplexing capability remains a standard, even for applications requiring whole-genome information. Diversity arrays technology (DArT) types hundreds to thousands of genomic loci in parallel, as previously demonstrated in a number diploid plant species. Here we show that DArT performs similarly well for the hexaploid genome of bread wheat (Triticum aestivum L.). The methodology previously used to generate DArT fingerprints of barley also generated a large number of high-quality markers in wheat (99.8% allele-calling concordance and approximately 95% call rate). The genetic relationships among bread wheat cultivars revealed by DArT coincided with knowledge generated with other methods, and even closely related cultivars could be distinguished. To verify the Mendelian behaviour of DArT markers, we typed a set of 90 Cranbrook x Halberd doubled haploid lines for which a framework (FW) map comprising a total of 339 SSR, restriction fragment length polymorphism (RFLP) and amplified fragment length polymorphism (AFLP) markers was available. We added an equal number of DArT markers to this data set and also incorporated 71 sequence tagged microsatellite (STM) markers. A comparison of logarithm of the odds (LOD) scores, call rates and the degree of genome coverage indicated that the quality and information content of the DArT data set was comparable to that of the combined SSR/RFLP/AFLP data set of the FW map.

Identification of genetic loci associated with ear-emergence in bread wheat

A doubled haploid population constructed from a cross between the South Australian wheat cultivars 'Trident' and 'Molineux' was grown under winter field conditions, under field conditions over summer and under artificial light both with and without vernalisation. The duration from planting to ear-emergence was recorded and QTL associated with heading date were detected using a previously constructed genetic linkage map. Associations were shown with chromosomal regions syntenous to previously identified photoperiod (Ppd-B1) and vernalisation (Vrn-A1) sensitive loci. Additional QTL associated with time to heading were also identified on chromosomes 1A, 2A, 2B, 6D, 7A and 7B. Comparisons between the genetic associations observed under the different growing conditions allowed the majority of these loci to be classified as having either photoperiod-sensitive, vernalisation-sensitive or earliness per se actions. The identification of a photoperiod-sensitive QTL on chromosome 1A provides evidence for a wheat gene possibly homoeologous to Ppd-H2 previously identified on chromosome 1H of barley. The occurrence of a putative major gene for photoperiod sensitivity observed on chromosome 7A is presented. The combined additive effects at these loci accounted for more than half the phenotypic variance in the duration from planting to ear-emergence in this population. The possible role of these loci on the adaptation of wheat in Australia is discussed.

Joint modeling of additive and non-additive genetic line effects in single field trials

A statistical approach is presented for selection of best performing lines for commercial release and best parents for future breeding programs from standard agronomic trials. The method involves the partitioning of the genetic effect of a line into additive and non-additive effects using pedigree based inter-line relationships, in a similar manner to that used in animal breeding. A difference is the ability to estimate non-additive effects. Line performance can be assessed by an overall genetic line effect with greater accuracy than when ignoring pedigree information and the additive effects are predicted breeding values. A generalized definition of heritability is developed to account for the complex models presented.

Mapping of a novel QTL for resistance to cereal cyst nematode in wheat

Cereal cyst nematode (CCN; Heterodera avenae Woll.) is a root pathogen of cereals that can cause severe yield losses in intolerant wheat cultivars. Loci for resistance to CCN, measured by a seedling bioassay, were identified by creating a genetic map based on a Trident/Molineux doubled haploid population of 182 lines. A novel locus accounting for up to 14% of the resistance to CCN was mapped to chromosome 1B of Molineux by association with microsatellite marker loci Xwmc719 and Xgwm140. This locus acts additively with the previously identified CCN resistance loci identified on chromosomes 6B (Cre8) and 2A (Cre5 on the VPM1 segment) in this population to explain 44% of the genetic variance for this major wheat pathogen.

The genetic control of milling yield, dough rheology and baking quality of wheat

Improving the end-use quality of wheat is a key target for many breeding programmes. With the exception of the relationship between glutenin alleles and some dough rheological characters, knowledge concerning the genetic control of wheat quality traits is somewhat limited. A doubled haploid population produced from a cross between two Australian cultivars 'Trident' and 'Molineux' has been used to construct a linkage map based largely on microsatellite molecular makers. 'Molineux' is superior to 'Trident' for a number of milling, dough rheology and baking quality characteristics, although by international standards 'Trident' would still be regarded as possessing moderately good end-use quality. This population was therefore deemed useful for investigation of wheat end-use quality. A number of significant QTL identified for dough rheological traits mapped to HMW and LMW glutenin loci on chromosomes 1A and 1B. However, QTL associated with dough strength and loaf volume were also identified on chromosome 2A and a significant QTL associated with loaf volume and crumb quality was identified on chromosome 3A. A QTL for flour protein content and milling yield was identified on chromosome 6A and a QTL associated with flour colour reported previously on chromosome 7B was confirmed in this population. The detection of loci affecting dough strength, loaf volume and flour protein content may provide fresh opportunities for the application of marker-assisted selection to improve bread-making quality.

Contributions of glutenin and puroindoline genes to grain quality traits in southern Australian wheat breeding programs

Glutenin genes were known to influence maximum dough resistance (Rmax), dough extensibility (extensibility), and dough development time, whereas puroindoline genes were known to influence grain hardness, flour water absorption (water absorption), and milling yield. These are important determinants of grain quality of wheat in Australia. This study was conducted to investigate the combined effect of these genes on Rmax, extensibility, dough development time, water absorption, and milling yield in a large dataset assembled from the breeding programs based at Horsham, Victoria; Roseworthy, South Australia; and Wagga Wagga, New South Wales; for at least 10 seasons. The effect of the glutenin genes on Rmax, extensibility, and dough development time was confirmed, as was the effect of the puroindoline genes on water absorption and milling yield. In addition, puroindoline genes were shown to significantly affect extensibility and dough development time. The Pina-D1a/Pinb-D1b genotype increased extensibility, dough development time, and milling yield relative to the Pina-D1b/Pinb-D1a genotype. Both of these genotypes are present in cultivars classified as hard-grained in southern Australia. Therefore, the allelic composition of both glutenin and puroindoline genes is required to predict the grain quality of hard wheat in southern Australian breeding programs. The glutenin and puroindoline genes in combination accounted for more than 50% of the genotypic variance for these traits, except for milling yield, but a substantial proportion of the genotypic variation could not be attributed to these genes, indicating that other genes affecting the traits were present in the populations of these wheat-breeding programs.

Sequence tagged microsatellites for the Xgwm533 locus provide new diagnostic markers to select for the presence of stem rust resistance gene Sr2 in bread wheat ( Triticum aestivum L.)

The stem rust resistance gene Sr2 has provided durable broad-spectrum, adult-plant resistance to the fungal pathogen Puccinia graminis Pers. f. sp. tritici throughout wheat-growing regions of the world for more than 50 years. The ability to select for Sr2 in wheat breeding programs was recently improved by the identification of a tightly linked microsatellite marker gwm533. This marker typically amplifies a 120-bp polymerase chain reaction fragment from wheat lines carrying Sr2. In instances where the 120-bp fragment is not associated with the presence of Sr2, DNA sequence analysis has shown that a second allele was amplified, differing in the structure of the microsatellite repeat. To discriminate this allelic homoplasy (alleles identical in size, but not identical by descent), sequence-tagged microsatellites (STM) markers were developed for the Xgwm533 locus. These markers were shown to be diagnostic for the presence of Sr2 in a wide range of germplasm, representative of all major wheat varieties historically grown in Australia. The STMs will be particularly useful for marker-assisted selection in Southern Australian breeding programs, where the use of the marker gwm533 is often precluded by the presence of the non- Sr2-associated 120-bp allele in the pedigree of current breeding germplasm. The STMs also revealed a high incidence of previously undetected allelic homoplasy at the Xgwm533 locus and may have broader utility in genetic research and breeding, as this locus is also reported to be strongly associated with a major gene conferring resistance to Fusarium head blight.

Differences in delta9 desaturase activity between Jersey- and Limousin-sired cattle

An experiment examined delta9 desaturase activity and FA composition in subcutaneous adipose tissue in two differing breeds of cattle. Jersey-sired cattle had significantly higher rates of desaturase activity than Limousin-sired cattle (1.55 vs. 0.75 nmol/mg protein/min). This difference was also demonstrated by a lower concentration of individual (e.g., 18:0) and total saturated FA (38.3 vs. 45.1 wt%), and a higher concentration of individual (e.g., 16:1) and total monounsaturated FA (58.2 vs. 52.7 wt%) in the Jersey animals. Other indices of desaturation calculated from the FA composition showed this same difference. The slip point of adipose tissue of Jersey cattle (36.8 degrees C) was significantly lower than that of Limousin cattle (39.2 degrees C), but Jersey adipose tissue had a greater content of beta-carotene. The positive relationship between adipose tissue beta-carotene and desaturation opposes the negative relationship between dietary beta-carotene and desaturation determined elsewhere. These results, however, lead to the hypothesis that some cattle have a reduced capacity to metabolize beta-carotene to various forms of vitamin A, a compound that can reduce delta9 desaturase enzyme activity. In addition, the higher level of intramuscular fat in Jersey cattle (6.97 vs. 3.82%) is possibly related to a lack of inhibition of the adipocyte differentiation genes by vitamin A.

Mapping of a QTL contributing to cereal cyst nematode tolerance and resistance in wheat

Cereal cyst nematode (CCN; Heterodera avenae Woll.) is a root pathogen of cereals that can cause severe yield losses in intolerant wheat cultivars. Tolerance to CCN, measured as early vigour in CCN-infested plots, was mapped in a Trident/Molineux doubled-haploid (DH) population. A locus accounting for a significant proportion of the tolerance to CCN was mapped to chromosome 6B of Molineux by association with RFLP loci Xcdo347-6B and Xbcd1 and also by nullisomic/tetrasomic substitution line analysis, and has been designated Cre8. The linkage of CCN tolerance with Xcdo347-6B was validated using a Barunga/Suneca DH population. The Cre8 locus also contributed to CCN resistance in the Trident/Molineux population. The RFLP locus Xbcd175, which is diagnostic for the Aegilops ventricosa segment VPM1 of Trident, explained up to 18% of the variation for early vigour in CCN-infested soils in the Trident/Molineux population. However, the Trident/Molineux population also segregated for early vigour in the absence of CCN, with Xbcd175 explaining up to 7% of the variation for this trait. The VPM1 segment of Trident therefore provides early vigour that may contribute to CCN tolerance in this cultivar.