Biology subjects

Trethowan, R.

Publications and source records attributed to Trethowan, R..

9 recordsLinked to original sources

bioRxiv2026

Developmental stage-dependent decoupling of molecular and phenotypic responses to heat in wheat grain

Heatwaves during flowering and grain development threaten global wheat production, yet the extent to which developmental stage shapes molecular and phenotypic responses remains unclear. Here, we investigated whether heat stress (36/29{degrees}C for 48 h) imposed at closely spaced developmental stages surrounding anthesis generates stage-specific molecular responses that are associated with subsequent effects on grain properties. Heat exposure increased floret abortion most strongly when it was imposed at the trinucleate stage (TN; [~]48%) compared with the binucleate (BN) and early post-anthesis stages. Methylation levels were largely unaffected by prior heat treatments; however, heat induced stage- and locus-specific methylation changes, particularly at BN. Spatial RNA-seq revealed tissue-specific heat responses that were distinctively different in BN and TN. Integrated metabolomic analyses revealed stage-dependent metabolic reprogramming, including shifts towards stress-associated pathways. Despite heat stress at BN generating broader molecular reprogramming in developing grain, exposure at TN produced stronger effects on grain set and composition, revealing a decoupling between the magnitude of responses and phenotypic outcomes. Together, these findings demonstrate that subtle differences in developmental stage influence the complex molecular responses to heat and subsequent grain properties.

plant biology↗

bioRxiv2026

Trait stability of diverse kabuli chickpea germplasm from delayed sowing in a rainfed environment

Structured AbstractO_ST_ABSContext and ObjectiveC_ST_ABSDelayed sowing can expose chickpea crops to stress during the critical period for yield determination, but the effect of yield components and phenology to grain yield variation is not well characterised in diverse germplasm under rainfed conditions. Identifying genetic resources for grain yield improvement requires integration of multi-environment trial and genomic analyses to disentangle direct yield effects from indirect effects of phenology. This study aimed to (1) characterise genotype by environment interaction patterns for grain yield, yield components and phenology across times of sowing and seasons, and (2) identify genomic regions associated with improved grain yield that are present in genebank accessions but absent from current Australian commercial cultivars. MethodsA diversity panel of 141 kabuli chickpea genotypes, including six commercial Australian cultivars and 135 genebank accessions, was evaluated across six rainfed trials at Narrabri, New South Wales over three seasons (2018 to 2020) under typical (MAIN) and delayed (LATE) sowing. Multi-environment trial analyses with factor analytic models partitioned genotype by environment interactions for grain yield, 100-seed weight, seed number, and thermal time to flowering, podding, and maturity. Haplotype block analysis identified high variance blocks associated with seed number, classified by their overlap with high variance thermal time to flowering blocks, to distinguish from effects mediated by phenology. Results and ConclusionsDelayed sowing reduced grain yield by up to 1.04 t ha-{superscript 1}, driven primarily by reductions in seed number rather than 100-seed weight. Accelerated phenology was a key component of adaptation among commercial cultivars. Four haploblocks with high block variance for seed number were identified across all six trials. SignificanceSeed number was the dominant driver of grain yield variation in this diverse kabuli chickpea panel. Targeted introgression of rare superior haplotypes from genebank accessions provides an opportunity to broaden the genetic base of Australian kabuli chickpea and improve yield through higher seed number, with relevance to chickpea production systems facing similar climate variability. HighlightsDelayed sowing reduced grain yield in diverse kabuli chickpea germplasm by up to 1.04 t ha-1 across three years and six trials in northern New South Wales. Seed number, not seed weight, was the dominant driver of grain yield variation, and a shorter phenological duration was associated with higher seed number. Across all six trials, haplotype block analysis identified four genomic regions in high linkage disequilibrium with high variance for seed number and low variance for flowering time. The accession FLIP 94 62C uniquely carried rare superior haplotypes at two chromosome 4 blocks, the haplotype at the 17.0 Mb block was the most superior haplotype in all trials while the haplotype at the 8.5Mb block was most superior only in the most heat stressed environment.

plant biology↗

bioRxiv2026

DeepBioGS: a hybrid framework for integrating crop growth modelling with genomic prediction through neural networks

Ensuring global food security under rapid climate change demands accelerated genetic gain and breeding strategies that address complex Genotype-by-Environment (GxE) interactions. Traditional genomic selection models often fail to account for novel or extreme climates.Furthermore, integrating mechanistic crop growth models (CGMs) using traditional Bayesian frameworks to solve this issue presents severe computational bottlenecks. Here, we introduce DeepBioGS, a novel hybrid framework that integrates genomic selection with biophysical growth modelling via a fully differentiable deep learning architecture. DeepBioGS utilises a parameter-prediction multi-layer perceptron to map high-dimensional genomic markers to latent, highly heritable physiological traits (Genotype-Specific Parameters; GSP). These parameters mechanistically predict crop phenology across diverse environments. Using two multi-environment wheat datasets comprising over 6,000 genotypes, DeepBioGS extracted latent traits with near-perfect SNP-based heritability values (0.95-1.00). Crucially, the framework demonstrated superior or comparable predictive accuracy (up to r2 = 0.77) against standard genomic best linear unbiased prediction (GBLUP) and traditional Bayesian CGM-WGP models. Its architecture drastically improved computational scalability by enabling standard backpropagation, effectively bypassing the stochastic sampling limitations of approximate Bayesian methods. Most importantly for climate adaptation, DeepBioGS allowed accurate forecasting of genotype performance in entirely unobserved environmental conditions. By merging the representational power of deep learning with the structural constraints of biophysics, DeepBioGS provides a highly scalable, interpretable tool to navigate GxE interactions, enabling the assessment of cultivars under future climate scenarios, thus optimising crop breeding for a changing global environment.

plant biology↗

bioRxiv2026

Field-based dissection of stomatal anatomy and conductance reveals stable QTL under drought and heat in wheat

Stomatal traits balance carbon gain with water loss, yet their breeding potential in wheat remains underexploited. This study investigated physiological and anatomical stomatal responses alongside yield across two years of large-scale field trials under water-limitation and delayed sowing-induced heat exposure. Across both seasons, stomatal conductance (gs) declined under stress, reflecting strong environmental constraint on gas-exchange (water-limitation:-26.9%; heat:-13.8%). Partitioning responses by leaf surface and genotype identified the adaxial surface as the dominant contributor to gs variation and the most stress responsive. Despite increases in theoretical anatomical gas-exchange capacity (gsmax), gs-efficiency declined, indicating partial decoupling between structural potential and realised conductance. Drought reduced stomatal size while increasing density whereas heat increased size, suggesting stress-specific anatomical plasticity. Moderate-to-high heritability was observed for anatomical traits (Water-limitation: 0.13-0.57; Heat: 0.42-0.71), contrasting with lower and less stable heritability for gs (water-limitation: 0.13-0.41; heat: 0.13-0.50). Genome-wide-association-mapping identified 169 putative QTLs, predominantly for anatomical traits, including stable and co-localised pleiotropic loci. Fourteen sets of closely positioned markers were detected across seasons or studies, with stable regions on chromosomes 2B, 3B and 7B emerging as key loci. Focusing on stable loci controlling adaxial stomatal anatomy offers a realistic strategy to enhance wheat photosynthetic efficiency and climate resilience. HighlightAdaxial stomatal traits dominate gas exchange responses to heat and drought in wheat, with stable anatomical QTL identified on chromosomes 2B, 3B and 7B. Their stability across environments supports their relevance for crop improvement in water-limited and high temperature systems.

physiology↗

bioRxiv2025

QTL for Heat-Induced Stomatal Anatomy Underpin Gas Exchange Variation in Field-Grown Wheat

Stomata are central to leaf gas exchange, governing carbon uptake, water loss, and ultimately, crop performance. However, the contribution of integrated stomatal anatomy and physiology to wheat heat tolerance remains poorly understood, particularly under realistic field conditions and across divers germplasm. This study explored the role of stomatal anatomical and physiological traits in shaping wheat responses to heat stress. Across two years of multi-environment field trials encompassing 200 genotypes in season 1 and 50 genotypes in season 2, we examined stomatal conductance (g), anatomical traits including stomatal size and density, and the stomatal conductance operating efficiency (gse) across leaf surfaces, along with grain yield. Timely and delayed sowing treatments were used to expose key developmental stages (anthesis) to contrasting temperature regimes. Early sowing supported higher gs and gse, while delayed sowing impaired stomatal function despite similar theoretical anatomical capacity (gsmax), revealing a decoupling of structural potential and physiological performance under stress. The adaxial surface consistently exhibited higher gs, stomatal density, and gsmax than the abaxial surface, highlighting its dominant role in leaf gas exchange. Later sowing induced plastic shifts in anatomy, including smaller, denser stomata, particularly on the adaxial surface, suggesting an adaptive response to thermal stress. Significant genotypic variation was observed for gs, gse, gsmax, and stomatal anatomical traits, with moderate heritability indicating genetic control. 125 putative QTL were identified for multiple stomatal traits across environments, including several stable loci on chromosomes 2B and 5B, and numerous closely clustered QTL for anatomical traits on chromosome 7B, highlighting key genomic regions underlying stomatal anatomy. In contrast, QTL for gs and gse were fewer and season-specific, highlighting the environmentally sensitive nature of physiological stomatal regulation. 42 of the QTL identified were consistent with previously reported QTL for stomatal traits in wheat. Together, these findings elevate the role of stomatal traits, supporting an integrated breeding strategy that combines selection for favourable stomatal anatomy with efficiency physiological regulation. Incorporating traits like gse into selection frameworks may enhance yield stability and resilience in heat-prone environments, advancing the development of climate-resilient wheat ideotypes. ScopeThis manuscript examines how stomatal anatomical and physiological traits integrate to shape wheat responses to heat stress under field conditions, addressing a central challenge in understanding the roles of stomata in a warming climate. Using multi-environment field trials across two growing seasons and encompassing 200 wheat genotypes, we quantify stomatal conductance (gs), anatomical traits, and stomatal operating efficiency (gse), across adaxial and abaxial leaf surfaces, and investigate whether these are under genetic control. The study provides mechanistic insight into the dynamic regulation of stomatal function by demonstrating a decoupling between anatomical capacity and physiological performance under heat stress, alongside plastic shifts in stomatal traits across sowing times. The identification of 125 candidate QTLs, including numerous stable and co-localised QTL across seasons, supports their incorporation into breeding programs aimed at enhancing resilience and yield stability. This work aligns with the Research Topic by elucidating mechanistic underpinnings of stomatal conductance regulation, bridging stomatal biology with applied crop improvement strategies. This work is critical to improving understanding of plant water relations and carbon uptake under future climate scenarios to ensure food security in a changing climate.

plant biology↗

bioRxiv2025

Wheat leaf dark respiration acclimates more strongly at night than in the day when responding to nocturnal warming

Rising night temperatures pose a significant threat to wheat productivity, yet the physiological basis of wheat adaptation to nocturnal warming remains poorly understood. We evaluated leaf photosynthetic and respiratory traits in ten Australian wheat cultivars released between 1901 and 2012 to warm nights under temperature-controlled environments. When exposed to warmer nights, rates of leaf net CO2 assimilation measured at 25 {degrees}C (Anet25) remained stable across cultivar release date despite declines in photosynthetic capacity (Vcmax and J1500) in newer cultivars. In most cultivars leaf respiratory CO2 release in the dark (Rdark) exhibited divergent thermal responses: warm nights suppressed temperature-normalised night Rdark (Rnight) but stimulated or maintained Rdark in the daytime (Rday). The results suggest that century-long, yield-focused selection may have inadvertently maintained Anet25 under warmer nights in modern cultivars through selection for more night-temperature sensitive but efficient photosynthetic capacity (i.e. greater return per protein investment) and overall reduced respiratory demand for maintenance of processes such as Rubisco protein turnover and synthesis. Our findings highlight trait-based targets for enhancing energy efficiency and climate resilience in wheat and opportunities to improve the parameterization of Rdark to warm nights in crop and Earth system models.

plant biology↗

bioRxiv2024

OzWheat: a genome-to-phenome platform to resolve complex traits for wheat pre-breeding and research.

For over a century, Australian wheat breeders have successfully adapted wheat to a broad range of climatic conditions and crop management practices. The OzWheat genome-to-phenome (G2P) platform was established to capture this breeding history and explore traits, genes, and their interactions with the environment to enable ongoing research and deliver targets for wheat improvement. A panel of 285 cultivars and landraces were chosen through knowledge of breeding pedigrees to represent both global diversity and the historic flow of genetic variation over more than 100 years of selective breeding in Australia. Genetic characterisation of the panel included identification of genome-wide sequence variants and gene expression profiling across environments. Important traits for adaptation (flowering time and plant height) were assayed in controlled environments and at multiple field sites and years, with genome-wide association analyses (GWAS) using linear mixed models detecting both known and novel loci. Here, we report establishment of the OzWheat G2P platform as a powerful tool to integrate wheat genomes and phenomes and demonstrate its use to identify candidate genes and understand gene by environment interactions. This provides the wheat research and breeding community a new resource to support future cultivar development.

genomics↗

bioRxiv2021

Wheat photosystem II heat tolerance responds dynamically to short and long-term warming

Heat-induced inhibition of photosynthesis is a key factor in declining wheat performance and yield. Variation in wheat heat tolerance can be characterised using the critical temperature (Tcrit) above which incipient damage to the photosynthetic machinery occurs. We investigated intraspecies variation and plasticity of wheat Tcrit under elevated temperature in field and controlled environment experiments. We also assessed whether intraspecies variation in wheat Tcrit mirrors patterns of global interspecies variation in heat tolerance reported for mostly wild, woody plants. In the field, wheat Tcrit varied through the course of a day, peaking at noon and lowest at sunrise, and increased as plants developed from heading to anthesis and grain filling. Under controlled temperature conditions, heat stress (36{degrees}C) was associated with a rapid rise in wheat Tcrit (i.e. within two hours of heat stress) that peaked after 3-4 days. These peaks in Tcrit indicate a physiological limitation to photosystem II heat tolerance. Analysis of a global dataset (comprising 183 Triticum and wild wheat (Aegilops) species) generated from the current study and a systematic literature review showed that wheat leaf Tcrit varied by up to 20{degrees}C (about two-thirds of reported global plant interspecies variation). However, unlike global patterns of interspecies Tcrit variation which has been linked to latitude of genotype origin, intraspecific variation in wheat Tcrit was unrelated to that. Yet, the observed genotypic variation and plasticity of wheat Tcrit suggests that this trait could be a useful tool for high-throughput phenotyping of wheat photosynthetic heat tolerance.

plant biology↗

bioRxiv2018

Rate of photosynthetic acclimation to fluctuating light varies widely among genotypes of wheat

HighlightSignificant variation exists in the acclimation time of photosynthesis following dark-to-light transitions across wheat genotypes, under field and controlled conditions. Slow acclimation reduced daily carbon assimilation by up to 16%.\n\nAbstractCrop photosynthesis and yield are limited by slow photosynthetic induction in sunflecks. We quantified variation in induction kinetics across diverse genotypes of wheat for the first time. In a preliminary study using penultimate leaves of 58 genotypes grown in the field, we measured induction kinetics for maximum assimilation rate (Amax) after a shift from full darkness to saturating light (1700 mol m-2 s-1) with 1-4 replicates per genotype. We then grew 10 of these genotypes with contrasting responses in a controlled environment and quantified induction kinetics of carboxylation capacity (Vcmax) from dynamic A vs ci curves after a shift from low to high light (50 to 1500 mol m-2 s-1), with 5 replicates per genotype. Within-genotype median time for 95% induction (t95) varied from 8.4 to 23.7 min across genotypes for Amax in field-grown penultimate leaves, and from 6.7 to 10.4 min for Vcmaxin chamber-grown flag leaves. Our simulations suggested that non-instantaneous acclimation reduces daily net carbon gain by up to 16%, and that breeding to speed up Vcmax induction in the slowest genotype to match that in the fastest genotype could increase daily net carbon gain by more than 4%, particularly for leaves that experience predominantly short-duration sunflecks.

physiology↗