Combining PSII photochemistry and hydraulics improves predictions of photosynthesis and water use from mild to lethal drought.

Rising temperatures and increases in drought negatively impact the efficiency and sustainability of both agricultural and forest ecosystems. Although hydraulic limitations on photosynthesis have been extensively studied, a solid understanding of the links between whole plant hydraulics and photosynthetic processes at the cellular level under changing environmental conditions is still missing, hampering our predictive power for plant mortality. Here, we examined plant hydraulic traits and CO2 assimilation rate under progressive water limitation by implementing Photosystem II (PSII) dynamics with a whole plant process model (TREES). The photosynthetic responses to plant water status were parameterized based on measurements of chlorophyll a fluorescence, gas exchange and water potential for Brassica rapa (R500) grown in a greenhouse under fully watered to lethal drought conditions. The updated model significantly improved predictions of photosynthesis, stomatal conductance and leaf water potential. TREES with PSII knowledge predicted a larger hydraulic safety margin and a decrease in percent loss of conductivity. TREES predicted a slower decrease in leaf water potential, which agreed with measurements. Our results highlight the pressing need for incorporating PSII drought photochemistry into current process models to capture cross-scale plant water dynamics from cell to whole plant level.

Current challenges and future of agricultural genomes to phenomes in the USA.

Dramatic improvements in measuring genetic variation across agriculturally relevant populations (genomics) must be matched by improvements in identifying and measuring relevant trait variation in such populations across many environments (phenomics). Identifying the most critical opportunities and challenges in genome to phenome (G2P) research is the focus of this paper. Previously (Genome Biol, 23(1):1-11, 2022), we laid out how Agricultural Genome to Phenome Initiative (AG2PI) will coordinate activities with USA federal government agencies expand public-private partnerships, and engage with external stakeholders to achieve a shared vision of future the AG2PI. Acting on this latter step, AG2PI organized the "Thinking Big: Visualizing the Future of AG2PI" two-day workshop held September 9-10, 2022, in Ames, Iowa, co-hosted with the United State Department of Agriculture's National Institute of Food and Agriculture (USDA NIFA). During the meeting, attendees were asked to use their experience and curiosity to review the current status of agricultural genome to phenome (AG2P) work and envision the future of the AG2P field. The topic summaries composing this paper are distilled from two 1.5-h small group discussions. Challenges and solutions identified across multiple topics at the workshop were explored. We end our discussion with a vision for the future of agricultural progress, identifying two areas of innovation needed: (1) innovate in genetic improvement methods development and evaluation and (2) innovate in agricultural research processes to solve societal problems. To address these needs, we then provide six specific goals that we recommend be implemented immediately in support of advancing AG2P research.

Quantifying physiological trait variation with automated hyperspectral imaging in rice.

Advancements in hyperspectral imaging (HSI) together with the establishment of dedicated plant phenotyping facilities worldwide have enabled high-throughput collection of plant spectral images with the aim of inferring target phenotypes. Here, we test the utility of HSI-derived canopy data, which were collected as part of an automated plant phenotyping system, to predict physiological traits in cultivated Asian rice (Oryza sativa). We evaluated 23 genetically diverse rice accessions from two subpopulations under two contrasting nitrogen conditions and measured 14 leaf- and canopy-level parameters to serve as ground-reference observations. HSI-derived data were used to (1) classify treatment groups across multiple vegetative stages using support vector machines (≥ 83% accuracy) and (2) predict leaf-level nitrogen content (N, %, n=88) and carbon to nitrogen ratio (C:N, n=88) with Partial Least Squares Regression (PLSR) following RReliefF wavelength selection (validation: R 2 = 0.797 and RMSEP = 0.264 for N; R 2 = 0.592 and RMSEP = 1.688 for C:N). Results demonstrated that models developed using training data from one rice subpopulation were able to predict N and C:N in the other subpopulation, while models trained on a single treatment group were not able to predict samples from the other treatment. Finally, optimization of PLSR-RReliefF hyperparameters showed that 300-400 wavelengths generally yielded the best model performance with a minimum calibration sample size of 62. Results support the use of canopy-level hyperspectral imaging data to estimate leaf-level N and C:N across diverse rice, and this work highlights the importance of considering calibration set design prior to data collection as well as hyperparameter optimization for model development in future studies.

Rapid Chlorophyll a Fluorescence Light Response Curves Mechanistically Inform Photosynthesis Modeling.

Crop improvement is crucial to ensuring global food security under climate change, and hence there is a pressing need for phenotypic observations that are both high throughput and improve mechanistic understanding of plant responses to environmental cues and limitations. In this study, chlorophyll a fluorescence light response curves and gas-exchange observations are combined to test the photosynthetic response to moderate drought in four genotypes of Brassica rapa The quantum yield of PSII (ϕ PSII ) is here analyzed as an exponential decline under changing light intensity and soil moisture. Both the maximum ϕ PSII and the rate of ϕ PSII decline across a large range of light intensities (0-1,000 µmol photons m-2 s-1; ß PSII ) are negatively affected by drought. We introduce an alternative photosynthesis model (ß PSII model) incorporating parameters from rapid fluorescence response curves. Specifically, the model uses ß PSII as an input for estimating the photosynthetic electron transport rate, which agrees well with two existing photosynthesis models (Farquhar-von Caemmerer-Berry and Yin). The ß PSII model represents a major improvement in photosynthesis modeling through the integration of high-throughput fluorescence phenotyping data, resulting in gained parameters of high mechanistic value.

Regulation of photoprotection gene expression in Chlamydomonas by a putative E3 ubiquitin ligase complex and a homolog of CONSTANS.

Photosynthetic organisms use nonphotochemical quenching (NPQ) mechanisms to dissipate excess absorbed light energy and protect themselves from photooxidation. In the model green alga Chlamydomonas reinhardtii, the capacity for rapidly reversible NPQ (qE) is induced by high light, blue light, and UV light via increased expression of LHCSR and PSBS genes that are necessary for qE. Here, we used a forward genetics approach to identify SPA1 and CUL4, components of a putative green algal E3 ubiquitin ligase complex, as critical factors in a signaling pathway that controls light-regulated expression of the LHCSR and PSBS genes in C. reinhardtii The spa1 and cul4 mutants accumulate increased levels of LHCSR1 and PSBS proteins in high light, and unlike the wild type, they express LHCSR1 and exhibit qE capacity even when grown in low light. The spa1-1 mutation resulted in constitutively high expression of LHCSR and PSBS RNAs in both low light and high light. The qE and gene expression phenotypes of spa1-1 are blocked by mutation of CrCO, a B-box Zn-finger transcription factor that is a homolog of CONSTANS, which controls flowering time in plants. CONSTANS-like cis-regulatory sequences were identified proximal to the qE genes, consistent with CrCO acting as a direct activator of qE gene expression. We conclude that SPA1 and CUL4 are components of a conserved E3 ubiquitin ligase that acts upstream of CrCO, whose regulatory function is wired differently in C. reinhardtii to control qE capacity via cis-regulatory CrCO-binding sites at key photoprotection genes.

Hydraulic and photosynthetic responses of big sagebrush to the 2017 total solar eclipse.

The total solar eclipse of August 21, 2017 created a path of totality ~115 km in width across the United States. While eclipse observations have shown distinct responses in animal behavior often emulating nocturnal behavior, the influence of eclipses on plant physiology are less understood. We investigated physiological perturbations due to rapid changes of sunlight and air temperature in big sagebrush (Artemisia tridentata ssp. vaseyana), a desert shrub common within the path of eclipse totality. Leaf gas exchange, water potential, and chlorophyll a fluorescence were monitored during the eclipse and compared to responses obtained the day before in absence of the eclipse. On the day of the eclipse, air temperature decreased by 6.4 °C, coupled with a 1.0 kPa drop in vapor pressure deficit having a 9-minute lag following totality. Using chlorophyll a fluorescence measurements, we found photosynthetic efficiency of photosystem II (Fv'/Fm') recovered to near dark acclimated state (i.e., 87%), but the short duration of darkness did not allow for complete recovery. Gas exchange data and a simple light response model were used to estimate a 14% reduction in carbon assimilation for one day over sagebrush dominated areas within the path of totality for the Western United States.

A framework for genomics-informed ecophysiological modeling in plants.

Dynamic process-based plant models capture complex physiological response across time, carrying the potential to extend simulations out to novel environments and lend mechanistic insight to observed phenotypes. Despite the translational opportunities for varietal crop improvement that could be unlocked by linking natural genetic variation to first principles-based modeling, these models are challenging to apply to large populations of related individuals. Here we use a combination of model development, experimental evaluation, and genomic prediction in Brassica rapa L. to set the stage for future large-scale process-based modeling of intraspecific variation. We develop a new canopy growth submodel for B. rapa within the process-based model Terrestrial Regional Ecosystem Exchange Simulator (TREES), test input parameters for feasibility of direct estimation with observed phenotypes across cultivated morphotypes and indirect estimation using genomic prediction on a recombinant inbred line population, and explore model performance on an in silico population under non-stressed and mild water-stressed conditions. We find evidence that the updated whole-plant model has the capacity to distill genotype by environment interaction (G×E) into tractable components. The framework presented offers a means to link genetic variation with environment-modulated plant response and serves as a stepping stone towards large-scale prediction of unphenotyped, genetically related individuals under untested environmental scenarios.

Circadian rhythms are associated with variation in photosystem II function and photoprotective mechanisms.

The circadian clock regulates many aspects of leaf gas supply and biochemical demand for CO2 , and is hypothesized to improve plant performance. Yet the extent to which the clock may regulate the efficiency of photosystem II (PSII) and photoprotective mechanisms such as heat dissipation is less explored. Based on measurements of chlorophyll a fluorescence, we estimated the maximum efficiency of PSII in light (Fv'/Fm') and heat dissipation by nonphotochemical quenching (NPQ). We further dissected total NPQ into its main components, qE (pH-dependent quenching), qT (state-transition quenching), and qI (quenching related to photoinhibition), in clock mutant genotypes of Arabidopsis thaliana, the cognate wild-type genotypes, and a panel of recombinant inbred lines expressing quantitative variation in clock period. Compared with mutants with altered clock function, we observed that wild-type genotypes with clock period lengths of approximately 24 hr had both higher levels of Fv'/Fm', indicative of improved PSII function, and reduced NPQ, suggestive of lower stress on PSII light harvesting complexes. In the recombinant inbred lines, genetic variances were significant for Fv'/Fm' and all 3 components of NPQ, with qE explaining the greatest proportion of NPQ. Bivariate tests of association and structural equation models of hierarchical trait relationships showed that quantitative clock variation was empirically associated with Fv'/Fm' and NPQ, with qE mediating the relationship with gas exchange. The results demonstrate significant segregating variation for all photoprotective components, and suggest the adaptive significance of the clock may partly derive from its regulation of the light reactions of photosynthesis and of photoprotective mechanisms.

Circadian Rhythms and Redox State in Plants: Till Stress Do Us Part.

A growing body of evidence demonstrates a significant relationship between cellular redox state and circadian rhythms. Each day these two vital components of plant biology influence one another, dictating the pace for metabolism and physiology. Diverse environmental stressors can disrupt this condition and, although plant scientists have made significant progress in re-constructing functional networks of plant stress responses, stress impacts on the clock-redox crosstalk is poorly understood. Inter-connected phenomena such as redox state and metabolism, internal and external environments, cellular homeostasis and rhythms can impede predictive understanding of coordinated regulation of plant stress response. The integration of circadian clock effects into predictive network models is likely to increase final yield and better predict plant responses to stress. To achieve such integrated understanding, it is necessary to consider the internal clock not only as a gatekeeper of environmental responses but also as a target of stress syndromes. Using chlorophyll fluorescence as a reliable and high-throughput probe of stress coupled to functional genomics and metabolomics will provide insights on the crosstalk across a wide range of stress severity and duration, including potential insights into oxidative stress response and signaling. We suggest the efficiency of photosystem II in light conditions (Fv'/Fm') to be the most dynamic of the fluorescence variables and therefore the most reliable parameter to follow the stress response from early sensing to mortality.

Circadian Rhythms and Reproductive Phenology Covary in a Natural Plant Population.

The circadian clock is a molecular timekeeper that matches endogenous rhythms in diverse traits with 24-h cycles in the external environment. Although a lack of clock resonance to the environment is detrimental to performance, clock phenotypes in wild populations nevertheless deviate substantially from the predicted optimal cycle length of 24 h, and significant genetic variation exists for circadian parameters. Here, we describe covariation between 2 traits considered to reflect adaptation to different aspects of temporal environmental heterogeneity, circadian rhythms (adaptation to daily environmental cycles) and flowering time (adaptation to seasonal cycles), in a Rocky Mountain population of the mustard Boechera stricta, a North American relative of Arabidopsis thaliana. We found that 18 families that differ in circadian period in leaf movement by 3.5 h expressed genetic diversity in first-year growth, reproductive phenology, vegetative size at reproduction, and starch concentration following vernalization. The families exhibited a large (~90-day) range in mean flowering time, even though the spatial scale of population sampling covered only a few hundred meters. Circadian period covaried with other traits such that longer-period families flowered earlier and at a larger size, a trait combination predicted to yield a fitness benefit in the wild. Circadian clock research in model systems has previously shown that mutations in clock genes influence phenology. Our results widen the scope of this research by illustrating a link between naturally segregating clock variation and reproductive phenology among wild genotypes, suggesting that the causes of genetic diversity in the clock lie partly in adaptation to seasonal environmental heterogeneity.

Dead or Alive? Using Membrane Failure and Chlorophyll a Fluorescence to Predict Plant Mortality from Drought.

Climate models predict widespread increases in both drought intensity and duration in the next decades. Although water deficiency is a significant determinant of plant survival, limited understanding of plant responses to extreme drought impedes forecasts of both forest and crop productivity under increasing aridity. Drought induces a suite of physiological responses; however, we lack an accurate mechanistic description of plant response to lethal drought that would improve predictive understanding of mortality under altered climate conditions. Here, proxies for leaf cellular damage, chlorophyll a fluorescence, and electrolyte leakage were directly associated with failure to recover from drought upon rewatering in Brassicarapa (genotype R500) and thus define the exact timing of drought-induced death. We validated our results using a second genotype (imb211) that differs substantially in life history traits. Our study demonstrates that whereas changes in carbon dynamics and water transport are critical indicators of drought stress, they can be unrelated to visible metrics of mortality, i.e. lack of meristematic activity and regrowth. In contrast, membrane failure at the cellular scale is the most proximate cause of death. This hypothesis was corroborated in two gymnosperms (Picea engelmannii and Pinus contorta) that experienced lethal water stress in the field and in laboratory conditions. We suggest that measurement of chlorophyll a fluorescence can be used to operationally define plant death arising from drought, and improved plant characterization can enhance surface model predictions of drought mortality and its consequences to ecosystem services at a global scale.