Corrigendum: Proximal hyperspectral imaging detects diurnal and drought-induced changes in maize physiology.

[This corrects the article DOI: 10.3389/fpls.2021.640914.].

Monitoring of drought stress and transpiration rate using proximal thermal and hyperspectral imaging in an indoor automated plant phenotyping platform.

BACKGROUND: Thermography is a popular tool to assess plant water-use behavior, as plant temperature is influenced by transpiration rate, and is commonly used in field experiments to detect plant water deficit. Its application in indoor automated phenotyping platforms is still limited and mainly focuses on differences in plant temperature between genotypes or treatments, instead of estimating stomatal conductance or transpiration rate. In this study, the transferability of commonly used thermography analysis protocols from the field to greenhouse phenotyping platforms was evaluated. In addition, the added value of combining thermal infrared (TIR) with hyperspectral imaging to monitor drought effects on plant transpiration rate (E) was evaluated. RESULTS: The sensitivity of commonly used TIR indices to detect drought-induced and genotypic differences in water status was investigated in eight maize inbred lines in the automated phenotyping platform PHENOVISION. Indices that normalized plant temperature for vapor pressure deficit and/or air temperature at the time of imaging were most sensitive to drought and could detect genotypic differences in the plants' water-use behavior. However, these indices were not strongly correlated to stomatal conductance and E. The canopy temperature depression index, the crop water stress index and the simplified stomatal conductance index were more suitable to monitor these traits, and were consequently used to develop empirical E prediction models by combining them with hyperspectral indices and/or environmental variables. Different modeling strategies were evaluated, including single index-based, machine learning and mechanistic models. Model comparison showed that combining multiple TIR indices in a random forest model can improve E prediction accuracy, and that the contribution of the hyperspectral data is limited when multiple indices are used. However, the empirical models trained on one genotype were not transferable to all eight inbred lines. CONCLUSION: Overall, this study demonstrates that existing TIR indices can be used to monitor drought stress and develop E prediction models in an indoor setup, as long as the indices normalize plant temperature for ambient air temperature or relative humidity.

Predicting yield of individual field-grown rapeseed plants from rosette-stage leaf gene expression.

In the plant sciences, results of laboratory studies often do not translate well to the field. To help close this lab-field gap, we developed a strategy for studying the wiring of plant traits directly in the field, based on molecular profiling and phenotyping of individual plants. Here, we use this single-plant omics strategy on winter-type Brassica napus (rapeseed). We investigate to what extent early and late phenotypes of field-grown rapeseed plants can be predicted from their autumnal leaf gene expression, and find that autumnal leaf gene expression not only has substantial predictive power for autumnal leaf phenotypes but also for final yield phenotypes in spring. Many of the top predictor genes are linked to developmental processes known to occur in autumn in winter-type B. napus accessions, such as the juvenile-to-adult and vegetative-to-reproductive phase transitions, indicating that the yield potential of winter-type B. napus is influenced by autumnal development. Our results show that single-plant omics can be used to identify genes and processes influencing crop yield in the field.

Modulation of the DA1 pathway in maize shows that translatability of information from Arabidopsis to crops is complex.

Modern agriculture is struggling to meet the increasing food, silage and raw material demands due to the rapid growth of population and climate change. In Arabidopsis, DA1 and DAR1 are proteases that negatively regulate cell proliferation and control organ size. DA1 and DAR1 are activated by ubiquitination catalyzed by the E3 ligase BIG BROTHER (BB). Here, we characterized the DA1, DAR1 and BB gene families in maize and analyzed whether perturbation of these genes regulates organ size similar to what was observed in Arabidopsis. We generated da1_dar1a_dar1b triple CRISPR maize mutants and bb1_bb2 double mutants. Detailed phenotypic analysis showed that the size of leaf, stem, cob, and seed was not consistently enlarged in these mutants. Also overexpression of a dominant-negative DA1R333K allele, resembling the da1-1 allele of Arabidopsis which has larger leaves and seeds, did not alter the maize phenotype. The mild negative effects on plant height of the DA1R333K_bb1_bb2 mutant indicate that the genes in the DA1 pathway may control organ size in maize, albeit less obvious than in Arabidopsis.

SAMBA controls cell division rate during maize development.

SAMBA has been identified as a plant-specific regulator of the anaphase-promoting complex/cyclosome (APC/C) that controls unidirectional cell cycle progression in Arabidopsis (Arabidopsis thaliana), but so far its role has not been studied in monocots. Here, we show the association of SAMBA with the APC/C is conserved in maize (Zea mays). Two samba genome edited mutants showed growth defects, such as reduced internode length, shortened upper leaves with erect leaf architecture, and reduced leaf size due to an altered cell division rate and cell expansion, which aggravated with plant age. The two mutants differed in the severity and developmental onset of the phenotypes, because samba-1 represented a knockout allele, while translation re-initiation in samba-3 resulted in a truncated protein that was still able to interact with the APC/C and regulate its function, albeit with altered APC/C activity and efficiency. Our data are consistent with a dosage-dependent role for SAMBA to control developmental processes for which a change in growth rate is pivotal.

Drought affects the rate and duration of organ growth but not inter-organ growth coordination.

Drought at flowering and grain filling greatly reduces maize (Zea mays) yield. Climate change is causing earlier and longer-lasting periods of drought, which affect the growth of multiple maize organs throughout development. To study how long periods of water deficit impact the dynamic nature of growth, and to determine how these relate to reproductive drought, we employed a high-throughput phenotyping platform featuring precise irrigation, imaging systems, and image-based biomass estimations. Prolonged drought resulted in a reduction of growth rate of individual organs-though an extension of growth duration partially compensated for this-culminating in lower biomass and delayed flowering. However, long periods of drought did not affect the highly organized succession of maximal growth rates of the distinct organs, i.e. leaves, stems, and ears. Two drought treatments negatively affected distinct seed yield components: Prolonged drought mainly reduced the number of spikelets, and drought during the reproductive period increased the anthesis-silking interval. The identification of these divergent biomass and yield components, which were affected by the shift in duration and intensity of drought, will facilitate trait-specific breeding toward future climate-resilient crops.

Proximal Hyperspectral Imaging Detects Diurnal and Drought-Induced Changes in Maize Physiology.

Hyperspectral imaging is a promising tool for non-destructive phenotyping of plant physiological traits, which has been transferred from remote to proximal sensing applications, and from manual laboratory setups to automated plant phenotyping platforms. Due to the higher resolution in proximal sensing, illumination variation and plant geometry result in increased non-biological variation in plant spectra that may mask subtle biological differences. Here, a better understanding of spectral measurements for proximal sensing and their application to study drought, developmental and diurnal responses was acquired in a drought case study of maize grown in a greenhouse phenotyping platform with a hyperspectral imaging setup. The use of brightness classification to reduce the illumination-induced non-biological variation is demonstrated, and allowed the detection of diurnal, developmental and early drought-induced changes in maize reflectance and physiology. Diurnal changes in transpiration rate and vapor pressure deficit were significantly correlated with red and red-edge reflectance. Drought-induced changes in effective quantum yield and water potential were accurately predicted using partial least squares regression and the newly developed Water Potential Index 2, respectively. The prediction accuracy of hyperspectral indices and partial least squares regression were similar, as long as a strong relationship between the physiological trait and reflectance was present. This demonstrates that current hyperspectral processing approaches can be used in automated plant phenotyping platforms to monitor physiological traits with a high temporal resolution.

Using single-plant-omics in the field to link maize genes to functions and phenotypes.

Most of our current knowledge on plant molecular biology is based on experiments in controlled laboratory environments. However, translating this knowledge from the laboratory to the field is often not straightforward, in part because field growth conditions are very different from laboratory conditions. Here, we test a new experimental design to unravel the molecular wiring of plants and study gene-phenotype relationships directly in the field. We molecularly profiled a set of individual maize plants of the same inbred background grown in the same field and used the resulting data to predict the phenotypes of individual plants and the function of maize genes. We show that the field transcriptomes of individual plants contain as much information on maize gene function as traditional laboratory-generated transcriptomes of pooled plant samples subject to controlled perturbations. Moreover, we show that field-generated transcriptome and metabolome data can be used to quantitatively predict individual plant phenotypes. Our results show that profiling individual plants in the field is a promising experimental design that could help narrow the lab-field gap.

Growth rate rather than growth duration drives growth heterosis in maize B104 hybrids.

Research in maize is often performed using inbred lines that can be readily transformed, such as B104. However, because the B104 line flowers late, the kernels do not always mature before the end of the growing season, hampering routine seed yield evaluations of biotech traits introduced in B104 at many geographical locations. Therefore, we generated five hybrids by crossing B104 with the early-flowering inbred lines CML91, F7, H99, Mo17, and W153R and showed in three consecutive years that the hybrid lines proved to be suitable to evaluate seed yield under field conditions in a temperate climate. By assessing the two main processes driving maize leaf growth, being rate of growth (leaf elongation rate or LER) and the duration of growth (leaf elongation duration or LED) in this panel of hybrids, we showed that leaf growth heterosis was mainly the result of increased LER and not or to a lesser extent of LED. Ectopic expression of the transgenes GA20-oxidase (GA20-OX) and PLASTOCHRON1 (PLA1), known to stimulate the LER and LED, respectively, in the hybrids showed that leaf length heterosis can be stimulated by increased LER, but not by LED, indicating that LER rather than LED is the target for enhancing leaf growth heterosis.

The reduction in maize leaf growth under mild drought affects the transition between cell division and cell expansion and cannot be restored by elevated gibberellic acid levels.

Growth is characterized by the interplay between cell division and cell expansion, two processes that occur separated along the growth zone at the maize leaf. To gain further insight into the transition between cell division and cell expansion, conditions were investigated in which the position of this transition zone was positively or negatively affected. High levels of gibberellic acid (GA) in plants overexpressing the GA biosynthesis gene GA20-OXIDASE (GA20OX-1OE ) shifted the transition zone more distally, whereas mild drought, which is associated with lowered GA biosynthesis, resulted in a more basal positioning. However, the increased levels of GA in the GA20OX-1OE line were insufficient to convey tolerance to the mild drought treatment, indicating that another mechanism in addition to lowered GA levels is restricting growth during drought. Transcriptome analysis with high spatial resolution indicated that mild drought specifically induces a reprogramming of transcriptional regulation in the division zone. 'Leaf Growth Viewer' was developed as an online searchable tool containing the high-resolution data.

Altered expression of maize PLASTOCHRON1 enhances biomass and seed yield by extending cell division duration.

Maize is the highest yielding cereal crop grown worldwide for grain or silage. Here, we show that modulating the expression of the maize PLASTOCHRON1 (ZmPLA1) gene, encoding a cytochrome P450 (CYP78A1), results in increased organ growth, seedling vigour, stover biomass and seed yield. The engineered trait is robust as it improves yield in an inbred as well as in a panel of hybrids, at several locations and over multiple seasons in the field. Transcriptome studies, hormone measurements and the expression of the auxin responsive DR5rev:mRFPer marker suggest that PLA1 may function through an increase in auxin. Detailed analysis of growth over time demonstrates that PLA1 stimulates the duration of leaf elongation by maintaining dividing cells in a proliferative, undifferentiated state for a longer period of time. The prolonged duration of growth also compensates for growth rate reduction caused by abiotic stresses.

F-Box Protein FBX92 Affects Leaf Size in Arabidopsis thaliana.

F-box proteins are part of one of the largest families of regulatory proteins that play important roles in protein degradation. In plants, F-box proteins are functionally very diverse, and only a small subset has been characterized in detail. Here, we identified a novel F-box protein FBX92 as a repressor of leaf growth in Arabidopsis. Overexpression of AtFBX92 resulted in plants with smaller leaves than the wild type, whereas plants with reduced levels of AtFBX92 showed, in contrast, increased leaf growth by stimulating cell proliferation. Detailed cellular analysis suggested that AtFBX92 specifically affects the rate of cell division during early leaf development. This is supported by the increased expression levels of several cell cycle genes in plants with reduced AtFBX92 levels. Surprisingly, overexpression of the maize homologous gene ZmFBX92 in maize had no effect on plant growth, whereas ectopic expression in Arabidopsis increased leaf growth. Expression of a truncated form of AtFBX92 showed that the contrasting effects of ZmFBX92 and AtFBX92 gain of function in Arabidopsis are due to the absence of the F-box-associated domain in the ZmFBX92 gene. Our work reveals an additional player in the complex network that determines leaf size and lays the foundation for identifying putative substrates.

Combined Large-Scale Phenotyping and Transcriptomics in Maize Reveals a Robust Growth Regulatory Network.

Leaves are vital organs for biomass and seed production because of their role in the generation of metabolic energy and organic compounds. A better understanding of the molecular networks underlying leaf development is crucial to sustain global requirements for food and renewable energy. Here, we combined transcriptome profiling of proliferative leaf tissue with in-depth phenotyping of the fourth leaf at later stages of development in 197 recombinant inbred lines of two different maize (Zea mays) populations. Previously, correlation analysis in a classical biparental mapping population identified 1,740 genes correlated with at least one of 14 traits. Here, we extended these results with data from a multiparent advanced generation intercross population. As expected, the phenotypic variability was found to be larger in the latter population than in the biparental population, although general conclusions on the correlations among the traits are comparable. Data integration from the two diverse populations allowed us to identify a set of 226 genes that are robustly associated with diverse leaf traits. This set of genes is enriched for transcriptional regulators and genes involved in protein synthesis and cell wall metabolism. In order to investigate the molecular network context of the candidate gene set, we integrated our data with publicly available functional genomics data and identified a growth regulatory network of 185 genes. Our results illustrate the power of combining in-depth phenotyping with transcriptomics in mapping populations to dissect the genetic control of complex traits and present a set of candidate genes for use in biomass improvement.

Correlation analysis of the transcriptome of growing leaves with mature leaf parameters in a maize RIL population.

BACKGROUND: To sustain the global requirements for food and renewable resources, unraveling the molecular networks underlying plant growth is becoming pivotal. Although several approaches to identify genes and networks involved in final organ size have been proven successful, our understanding remains fragmentary. RESULTS: Here, we assessed variation in 103 lines of the Zea mays B73xH99 RIL population for a set of final leaf size and whole shoot traits at the seedling stage, complemented with measurements capturing growth dynamics, and cellular measurements. Most traits correlated well with the size of the division zone, implying that the molecular basis of final leaf size is already defined in dividing cells of growing leaves. Therefore, we searched for association between the transcriptional variation in dividing cells of the growing leaf and final leaf size and seedling biomass, allowing us to identify genes and processes correlated with the specific traits. A number of these genes have a known function in leaf development. Additionally, we illustrated that two independent mechanisms contribute to final leaf size, maximal growth rate and the duration of growth. CONCLUSIONS: Untangling complex traits such as leaf size by applying in-depth phenotyping allows us to define the relative contributions of the components and their mutual associations, facilitating dissection of the biological processes and regulatory networks underneath.

Dynamic Changes in ANGUSTIFOLIA3 Complex Composition Reveal a Growth Regulatory Mechanism in the Maize Leaf.

Most molecular processes during plant development occur with a particular spatio-temporal specificity. Thus far, it has remained technically challenging to capture dynamic protein-protein interactions within a growing organ, where the interplay between cell division and cell expansion is instrumental. Here, we combined high-resolution sampling of the growing maize (Zea mays) leaf with tandem affinity purification followed by mass spectrometry. Our results indicate that the growth-regulating SWI/SNF chromatin remodeling complex associated with ANGUSTIFOLIA3 (AN3) was conserved within growing organs and between dicots and monocots. Moreover, we were able to demonstrate the dynamics of the AN3-interacting proteins within the growing leaf, since copurified GROWTH-REGULATING FACTORs (GRFs) varied throughout the growing leaf. Indeed, GRF1, GRF6, GRF7, GRF12, GRF15, and GRF17 were significantly enriched in the division zone of the growing leaf, while GRF4 and GRF10 levels were comparable between division zone and expansion zone in the growing leaf. These dynamics were also reflected at the mRNA and protein levels, indicating tight developmental regulation of the AN3-associated chromatin remodeling complex. In addition, the phenotypes of maize plants overexpressing miRNA396a-resistant GRF1 support a model proposing that distinct associations of the chromatin remodeling complex with specific GRFs tightly regulate the transition between cell division and cell expansion. Together, our data demonstrate that advancing from static to dynamic protein-protein interaction analysis in a growing organ adds insights in how developmental switches are regulated.