Mapping of novel salt tolerance QTL in an Excalibur × Kukri doubled haploid wheat population.

KEY MESSAGE: Novel QTL for salinity tolerance traits have been detected using non-destructive and destructive phenotyping in bread wheat and were shown to be linked to improvements in yield in saline fields. Soil salinity is a major limitation to cereal production. Breeding new salt-tolerant cultivars has the potential to improve cereal crop yields. In this study, a doubled haploid bread wheat mapping population, derived from the bi-parental cross of Excalibur × Kukri, was grown in a glasshouse under control and salinity treatments and evaluated using high-throughput non-destructive imaging technology. Quantitative trait locus (QTL) analysis of this population detected multiple QTL under salt and control treatments. Of these, six QTL were detected in the salt treatment including one for maintenance of shoot growth under salinity (QG(1-5).asl-7A), one for leaf Na+ exclusion (QNa.asl-7A) and four for leaf K+ accumulation (QK.asl-2B.1, QK.asl-2B.2, QK.asl-5A and QK:Na.asl-6A). The beneficial allele for QG(1-5).asl-7A (the maintenance of shoot growth under salinity) was present in six out of 44 mainly Australian bread and durum wheat cultivars. The effect of each QTL allele on grain yield was tested in a range of salinity concentrations at three field sites across 2 years. In six out of nine field trials with different levels of salinity stress, lines with alleles for Na+ exclusion and/or K+ maintenance at three QTL (QNa.asl-7A, QK.asl-2B.2 and QK:Na.asl-6A) excluded more Na+ or accumulated more K+ compared to lines without these alleles. Importantly, the QK.asl-2B.2 allele for higher K+ accumulation was found to be associated with higher grain yield at all field sites. Several alleles at other QTL were associated with higher grain yields at selected field sites.

Variation in shoot tolerance mechanisms not related to ion toxicity in barley.

Soil salinity can severely reduce crop growth and yield. Many studies have investigated salinity tolerance mechanisms in cereals using phenotypes that are relatively easy to measure. The majority of these studies measured the accumulation of shoot Na+ and the effect this has on plant growth. However, plant growth is reduced immediately after exposure to NaCl before Na+ accumulates to toxic concentrations in the shoot. In this study, nondestructive and destructive measurements are used to evaluate the responses of 24 predominately Australian barley (Hordeum vulgare L.) lines at 0, 150 and 250mM NaCl. Considerable variation for shoot tolerance mechanisms not related to ion toxicity (shoot ion-independent tolerance) was found, with some lines being able to maintain substantial growth rates under salt stress, whereas others stopped growing. Hordeum vulgare spp. spontaneum accessions and barley landraces predominantly had the best shoot ion independent tolerance, although two commercial cultivars, Fathom and Skiff, also had high tolerance. The tolerance of cv. Fathom may be caused by a recent introgression from H. vulgare L. spp. spontaneum. This study shows that the most salt-tolerant barley lines are those that contain both shoot ion-independent tolerance and the ability to exclude Na+ from the shoot (and thus maintain high K+:Na+ ratios).

A QTL on the short arm of wheat (Triticum aestivum L.) chromosome 3B affects the stability of grain weight in plants exposed to a brief heat shock early in grain filling.

BACKGROUND: Molecular markers and knowledge of traits associated with heat tolerance are likely to provide breeders with a more efficient means of selecting wheat varieties able to maintain grain size after heat waves during early grain filling. RESULTS: A population of 144 doubled haploids derived from a cross between the Australian wheat varieties Drysdale and Waagan was mapped using the wheat Illumina iSelect 9,000 feature single nucleotide polymorphism marker array and used to detect quantitative trait loci for heat tolerance of final single grain weight and related traits. Plants were subjected to a 3 d heat treatment (37 °C/27 °C day/night) in a growth chamber at 10 d after anthesis and trait responses calculated by comparison to untreated control plants. A locus for single grain weight stability was detected on the short arm of chromosome 3B in both winter- and autumn-sown experiments, determining up to 2.5 mg difference in heat-induced single grain weight loss. In one of the experiments, a locus with a weaker effect on grain weight stability was detected on chromosome 6B. Among the traits measured, the rate of flag leaf chlorophyll loss over the course of the heat treatment and reduction in shoot weight due to heat were indicators of loci with significant grain weight tolerance effects, with alleles for grain weight stability also conferring stability of chlorophyll ('stay-green') and shoot weight. Chlorophyll loss during the treatment, requiring only two non-destructive readings to be taken, directly before and after a heat event, may prove convenient for identifying heat tolerant germplasm. These results were consistent with grain filling being limited by assimilate supply from the heat-damaged photosynthetic apparatus, or alternatively, accelerated maturation in the grains that was correlated with leaf senescence responses merely due to common genetic control of senescence responses in the two organs. There was no evidence for a role of mobilized stem reserves (water soluble carbohydrates) in determining grain weight responses. CONCLUSIONS: Molecular markers for the 3B or 6B loci, or the facile measurement of chlorophyll loss over the heat treatment, could be used to assist identification of heat tolerant genotypes for breeding.

Variation for N Uptake System in Maize: Genotypic Response to N Supply.

An understanding of the adaptations made by plants in their nitrogen (N) uptake systems in response to reduced N supply is important to the development of cereals with enhanced N uptake efficiency (NUpE). Twenty seven diverse genotypes of maize (Zea mays, L.) were grown in hydroponics for 3 weeks with limiting or adequate N supply. Genotypic response to N was assessed on the basis of biomass characteristics and the activities of the nitrate ([Formula: see text]) and ammonium ([Formula: see text]) high-affinity transport systems. Genotypes differed greatly for the ability to maintain biomass with reduced N. Although, the N response in underlying biomass and N transport related characteristics was less than that for biomass, there were clear relationships, most importantly, lines that maintained biomass at reduced N maintained net N uptake with no change in size of the root relative to the shoot. The root uptake capacity for both [Formula: see text] and [Formula: see text] increased with reduced N. Transcript levels of putative [Formula: see text] and [Formula: see text] transporter genes in the root tissue of a subset of the genotypes revealed that predominately ZmNRT2 transcript levels responded to N treatments. The correlation between the ratio of transcripts of ZmNRT2.2 between the two N levels and a genotype's ability to maintain biomass with reduced N suggests a role for these transporters in enhancing NUpE. The observed variation in the ability to capture N at low N provides scope for both improving NUpE in maize and also to better understand the N uptake system in cereals.

Combining field performance with controlled environment plant imaging to identify the genetic control of growth and transpiration underlying yield response to water-deficit stress in wheat.

Crop yield in low-rainfall environments is a complex trait under multigenic control that shows significant genotype×environment (G×E) interaction. One way to understand and track this trait is to link physiological studies to genetics by using imaging platforms to phenotype large segregating populations. A wheat population developed from parental lines contrasting in their mechanisms of yield maintenance under water deficit was studied in both an imaging platform and in the field. We combined phenotyping methods in a common analysis pipeline to estimate biomass and leaf area from images and then inferred growth and relative growth rate, transpiration, and water-use efficiency, and applied these to genetic analysis. From the 20 quantitative trait loci (QTLs) found for several traits in the platform, some showed strong effects, accounting for between 26 and 43% of the variation on chromosomes 1A and 1B, indicating that the G×E interaction could be reduced in a controlled environment and by using dynamic variables. Co-location of QTLs identified in the platform and in the field showed a possible common genetic basis at some loci. Co-located QTLs were found for average growth rate, leaf expansion rate, transpiration rate, and water-use efficiency from the platform with yield, spike number, grain weight, grain number, and harvest index in the field. These results demonstrated that imaging platforms are a suitable alternative to field-based screening and may be used to phenotype recombinant lines for positional cloning.

Accounting for variation in designing greenhouse experiments with special reference to greenhouses containing plants on conveyor systems.

BACKGROUND: There are a number of unresolved issues in the design of experiments in greenhouses. They include whether statistical designs should be used and, if so, which designs should be used. Also, are there thigmomorphogenic or other effects arising from the movement of plants on conveyor belts within a greenhouse? A two-phase, single-line wheat experiment involving four tactics was conducted in a conventional greenhouse and a fully-automated phenotyping greenhouse (Smarthouse) to investigate these issues. RESULTS AND DISCUSSION: Analyses of our experiment show that there was a small east-west trend in total area of the plants in the Smarthouse. Analyses of the data from three multiline experiments reveal a large north-south trend. In the single-line experiment, there was no evidence of differences between trios of lanes, nor of movement effects. Swapping plant positions during the trial was found to decrease the east-west trend, but at the cost of increased error variance. The movement of plants in a north-south direction, through a shaded area for an equal amount of time, nullified the north-south trend. An investigation of alternative experimental designs for equally-replicated experiments revealed that generally designs with smaller blocks performed best, but that (nearly) trend-free designs can be effective when blocks are larger. CONCLUSIONS: To account for variation in microclimate in a greenhouse, using statistical design and analysis is better than rearranging the position of plants during the experiment. For the relocation of plants to be successful requires that plants spend an equal amount of time in each microclimate, preferably during comparable growth stages. Even then, there is no evidence that this will be any more precise than statistical design and analysis of the experiment, and the risk is that it will not be successful at all. As for statistical design and analysis, it is best to use either (i) smaller blocks, (ii) (nearly) trend-free arrangement of treatments with a linear trend term included in the analysis, or, as a last resort, (iii) blocks of several complete rows with trend terms in the analysis. Also, we recommend that the greenhouse arrangement parallel that in the Smarthouse, but with randomization where appropriate.

A simulation study to assess a variable selection method for selecting single nucleotide polymorphisms associated with disease.

In genome-wide association studies, where hundreds of thousands of single nucleotide polymorphisms (SNPs) are genotyped, the potential for false positives is high and methods for selecting models with only a few SNPs are required. Methods for variable selection giving sets of SNPs associated with disease have been developed, but are still less common than evaluation of individual SNPs one at a time. To assess the potential improvement available from multi-SNP approaches, we examined the performance of the software GeneRaVE as a variable selection method when applied to SNP data in case-control studies. The method was assessed via simulations, in which a haplotype identified by three SNPs was taken to be associated with the disease. Simulated data sets reflecting different levels and patterns of genetic association with the disease were generated. In order to have a baseline level of performance to assess the method against, we used a generalized linear model using only the three disease susceptibility SNPs to provide an upper bound on the possible performance of the selection methods. To investigate the advantage of using variable selection method as a multivariate method over a single SNP approach, we used chi-squared tests for each of the disease susceptibility (DS) SNPs with correction for multiple testing. Simulation results showed that GeneRaVE performed well and outperformed single SNP analysis using the chi-squared method in identifying disease-related SNPs. In application to a large dataset, it identified SNPs known to be associated with disease that were not identified by single SNP methods.