Exploring natural genetic diversity in a bread wheat multi-founder population: Dual imaging of photosynthesis and stomatal kinetics.

A better understanding of crop phenotype under dynamic environmental conditions will help inform the development of new cultivars with superior adaptation to constantly changing field conditions. Recent research has shown that optimising photosynthetic and stomatal conductance traits holds promise for improved crop performance. However, standard phenotyping tools such as gas-exchange systems are limited by their throughput. In this work, a novel approach based on a bespoke gas-exchange chamber allowing combined measurement of the quantum yield of photosystem II (PSII) with an estimation of stomatal conductance via thermal imaging, was used to phenotype a range of bread wheat (Triticum aestivum L.) genotypes, that were a sub-set of a multi-founder experimental population. Datasets were further supplemented by measurement of photosynthetic capacity and stomatal density. First, we showed that measurement of stomatal traits using our dual imaging system compared to standard IRGA methods showed good agreement between the two methods (R2=0.86) for the rapidity of stomatal opening (Ki), with the dual-imager method resulting in less intra-genotype variation. Using the dual-imaging methods, and traditional approaches we found broad and significant variation in key traits, including photosynthetic CO2 uptake at saturating light and ambient CO2 concentration (Asat), photosynthetic CO2 uptake at saturating light and elevated CO2 concentration (Amax), the maximum velocity of Rubisco for carboxylation (Vcmax), time for stomatal opening (Ki), and leaf evaporative cooling. Anatomical analysis revealed significant variation in flag leaf adaxial stomatal density. Associations between traits highlighted significant relationships between leaf evaporative cooling, leaf stomatal conductance under low (gsmin) and high (gsmax) light intensity, and the operating efficiency of PSII (Fq'/Fm'), highlighting the importance of stomatal conductance and stomatal rapidity in maintaining optimal leaf temperature for photosynthesis in wheat. Additionally, gsmin and gsmax were positively associated, indicating that potential combination of preferable traits (i.e. inherently high gsmax, low Ki and maintained leaf evaporative cooling) are present in wheat. This work highlights for the first time the effectiveness of thermal imaging in screening dynamic stomatal conductance in a large panel of wheat genotypes. The wide phenotypic variation observed suggested the presence of exploitable genetic variability in bread wheat for dynamic stomatal conductance traits and photosynthetic capacity for targeted optimisation within future breeding programs.

Longer epidermal cells underlie a quantitative source of variation in wheat flag leaf size.

The wheat flag leaf is the main contributor of photosynthetic assimilates to developing grains. Understanding how canopy architecture strategies affect source strength and yield will aid improved crop design. We used an eight-founder population to investigate the genetic architecture of flag leaf area, length, width and angle in European wheat. For the strongest genetic locus identified, we subsequently created a near-isogenic line (NIL) pair for more detailed investigation across seven test environments. Genetic control of traits investigated was highly polygenic, with colocalisation of replicated quantitative trait loci (QTL) for one or more traits identifying 24 loci. For QTL QFll.niab-5A.1 (FLL5A), development of a NIL pair found the FLL5A+ allele commonly conferred a c. 7% increase in flag and second leaf length and a more erect leaf angle, resulting in higher flag and/or second leaf area. Increased FLL5A-mediated flag leaf length was associated with: (1) longer pavement cells and (2) larger stomata at lower density, with a trend for decreased maximum stomatal conductance (Gsmax ) per unit leaf area. For FLL5A, cell size rather than number predominantly determined leaf length. The observed trade-offs between leaf size and stomatal morphology highlight the need for future studies to consider these traits at the whole-leaf level.

Disorder in convergent floral nanostructures enhances signalling to bees.

Diverse forms of nanoscale architecture generate structural colour and perform signalling functions within and between species. Structural colour is the result of the interference of light from approximately regular periodic structures; some structural disorder is, however, inevitable in biological organisms. Is this disorder functional and subject to evolutionary selection, or is it simply an unavoidable outcome of biological developmental processes? Here we show that disordered nanostructures enable flowers to produce visual signals that are salient to bees. These disordered nanostructures (identified in most major lineages of angiosperms) have distinct anatomies but convergent optical properties; they all produce angle-dependent scattered light, predominantly at short wavelengths (ultraviolet and blue). We manufactured artificial flowers with nanoscale structures that possessed tailored levels of disorder in order to investigate how foraging bumblebees respond to this optical effect. We conclude that floral nanostructures have evolved, on multiple independent occasions, an effective degree of relative spatial disorder that generates a photonic signature that is highly salient to insect pollinators.

Resolving Recent Plant Radiations: Power and Robustness of Genotyping-by-Sequencing.

Disentangling species boundaries and phylogenetic relationships within recent evolutionary radiations is a challenge due to the poor morphological differentiation and low genetic divergence between species, frequently accompanied by phenotypic convergence, interspecific gene flow and incomplete lineage sorting. Here we employed a genotyping-by-sequencing (GBS) approach, in combination with morphometric analyses, to investigate a small western Mediterranean clade in the flowering plant genus Linaria that radiated in the Quaternary. After confirming the morphological and genetic distinctness of eight species, we evaluated the relative performances of concatenation and coalescent methods to resolve phylogenetic relationships. Specifically, we focused on assessing the robustness of both approaches to variations in the parameter used to estimate sequence homology (clustering threshold). Concatenation analyses suffered from strong systematic bias, as revealed by the high statistical support for multiple alternative topologies depending on clustering threshold values. By contrast, topologies produced by two coalescent-based methods (NJ$_{\mathrm{st}}$, SVDquartets) were robust to variations in the clustering threshold. Reticulate evolution may partly explain incongruences between NJ$_{\mathrm{st}}$, SVDquartets and concatenated trees. Integration of morphometric and coalescent-based phylogenetic results revealed (i) extensive morphological divergence associated with recent splits between geographically close or sympatric sister species and (ii) morphological convergence in geographically disjunct species. These patterns are particularly true for floral traits related to pollinator specialization, including nectar spur length, tube width and corolla color, suggesting pollinator-driven diversification. Given its relatively simple and inexpensive implementation, GBS is a promising technique for the phylogenetic and systematic study of recent radiations, but care must be taken to evaluate the robustness of results to variation of data assembly parameters.

Implementing within-cross genomic prediction to reduce oat breeding costs.

A barrier to the adoption of genomic prediction in small breeding programs is the initial cost of genotyping material. Although decreasing, marker costs are usually higher than field trial costs. In this study we demonstrate the utility of stratifying a narrow-base biparental oat population genotyped with a modest number of markers to employ genomic prediction at early and later generations. We also show that early generation genotyping data can reduce the number of lines for later phenotyping based on selections of siblings to progress. Using sets of small families selected at an early generation could enable the use of genomic prediction for adaptation to multiple target environments at an early stage in the breeding program. In addition, we demonstrate that mixed marker data can be effectively integrated to combine cheap dominant marker data (including legacy data) with more expensive but higher density codominant marker data in order to make within generation and between lineage predictions based on genotypic information. Taken together, our results indicate that small programs can test and initiate genomic predictions using sets of stratified, narrow-base populations and incorporating low density legacy genotyping data. This can then be scaled to include higher density markers and a broadened population base.

Genetic Characterization of a Wheat Association Mapping Panel Relevant to Brazilian Breeding Using a High-Density Single Nucleotide Polymorphism Array.

Bread wheat (Triticum aestivum L.) is one of the world's most important crops. Maintaining wheat yield gains across all of its major production areas is a key target toward underpinning global food security. Brazil is a major wheat producer in South America, generating grain yields of around 6.8 million tons per year. Here, we establish and genotype a wheat association mapping resource relevant to contemporary Brazilian wheat breeding programs. The panel of 558 wheat accessions was genotyped using an Illumina iSelect 90,000 single nucleotide polymorphism array. Following quality control, the final data matrix consisted of 470 accessions and 22,475 polymorphic genetic markers (minor allele frequency ≥5%, missing data <5%). Principal component analysis identified distinct differences between materials bred predominantly for the northern Cerrado region, compared to those bred for southern Brazilian agricultural areas. We augmented the genotypic data with 26 functional Kompetitive Allele-Specific PCR (KASP) markers to identify the allelic combinations at genes with previously known effects on agronomically important traits in the panel. This highlighted breeding targets for immediate consideration - notably, increased Fusarium head blight resistance via the Fhb1 locus. To demonstrate the panel's likely future utility, genome-wide association scans for several phenotypic traits were undertaken. Significant (Bonferroni corrected P < 0.05) marker-trait associations were detected for Fusarium kernel damage (a proxy for type 2 Fusarium resistance), identifying previously known quantitative trait loci in the panel. This association mapping panel represents an important resource for Brazilian wheat breeding, allowing future genetic studies to analyze multiple agronomic traits within a single genetically diverse population.

Assessing European Wheat Sensitivities to Parastagonospora nodorum Necrotrophic Effectors and Fine-Mapping the Snn3-B1 Locus Conferring Sensitivity to the Effector SnTox3.

Parastagonospora nodorum is a necrotrophic fungal pathogen of wheat (Triticum aestivum L.), one of the world's most important crops. P. nodorum mediates host cell death using proteinaceous necrotrophic effectors, presumably liberating nutrients that allow the infection process to continue. The identification of pathogen effectors has allowed host genetic resistance mechanisms to be separated into their constituent parts. In P. nodorum, three proteinaceous effectors have been cloned: SnToxA, SnTox1, and SnTox3. Here, we survey sensitivity to all three effectors in a panel of 480 European wheat varieties, and fine-map the wheat SnTox3 sensitivity locus Snn3-B1 using genome-wide association scans (GWAS) and an eight-founder wheat multi-parent advanced generation inter-cross (MAGIC) population. Using a Bonferroni corrected P ≤ 0.05 significance threshold, GWAS identified 10 significant markers defining a single locus, Snn3-B1, located on the short arm of chromosome 5B explaining 32% of the phenotypic variation [peak single nucleotide polymorphisms (SNPs), Excalibur_c47452_183 and GENE-3324_338, -log10P = 20.44]. Single marker analysis of SnTox3 sensitivity in the MAGIC population located Snn3-B1 via five significant SNPs, defining a 6.2-kb region that included the two peak SNPs identified in the association mapping panel. Accordingly, SNP Excalibur_c47452_183 was converted to the KASP genotyping system, and validated by screening a subset of 95 wheat varieties, providing a valuable resource for marker assisted breeding and for further genetic investigation. In addition, composite interval mapping in the MAGIC population identified six minor SnTox3 sensitivity quantitative trait loci, on chromosomes 2A (QTox3.niab-2A.1, P-value = 9.17-7), 2B (QTox3.niab-2B.1, P = 0.018), 3B (QTox3.niab-3B.1, P = 48.51-4), 4D (QTox3.niab-4D.1, P = 0.028), 6A (QTox3.niab-6A.1, P = 8.51-4), and 7B (QTox3.niab-7B.1, P = 0.020), each accounting for between 3.1 and 6.0 % of the phenotypic variance. Collectively, the outcomes of this study provides breeders with knowledge and resources regarding the sensitivity of European wheat germplasm to P. nodorum effectors, as well as simple diagnostic markers for determining allelic state at Snn3-B1.