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.

Interspecies co-expression analysis of lateral root development using inducible systems in rice, Medicago, and Arabidopsis.

Lateral roots are crucial for plant growth and development, making them an important target for research aiming to improve crop yields and food security. However, their endogenous ontogeny and, as it were, stochastic appearance challenge their study. Lateral Root Inducible Systems (LRIS) can be used to overcome these challenges by inducing lateral roots massively and synchronously. The combination of LRISs with transcriptomic approaches significantly advanced our insights in the molecular control of lateral root formation, in particular for Arabidopsis. Despite this success, LRISs have been underutilized for other plant species or for lateral root developmental stages later than the initiation. In this study, we developed and/or adapted LRISs in rice, Medicago, and Arabidopsis to perform RNA-sequencing during time courses that cover different developmental stages of lateral root formation and primordium development. As such, our study provides three extensive datasets of gene expression profiles during lateral root development in three different plant species. The three LRISs are highly effective but timing and spatial distribution of lateral root induction vary among the species. Detailed characterization of the stages in time and space in the respective species enabled an interspecies co-expression analysis to identify conserved players involved in lateral root development, as illustrated for the AUX/IAA and LBD gene families. Overall, our results provide a valuable resource to identify potentially conserved regulatory mechanisms in lateral root development, and as such will contribute to a better understanding of the complex regulatory network underlying lateral root development.

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.

SMAP design: a multiplex PCR amplicon and gRNA design tool to screen for natural and CRISPR-induced genetic variation.

Multiplex amplicon sequencing is a versatile method to identify genetic variation in natural or mutagenized populations through eco-tilling or multiplex CRISPR screens. Such genotyping screens require reliable and specific primer designs, combined with simultaneous gRNA design for CRISPR screens. Unfortunately, current tools are unable to combine multiplex gRNA and primer design in a high-throughput and easy-to-use manner with high design flexibility. Here, we report the development of a bioinformatics tool called SMAP design to overcome these limitations. We tested SMAP design on several plant and non-plant genomes and obtained designs for more than 80-90% of the target genes, depending on the genome and gene family. We validated the designs with Illumina multiplex amplicon sequencing and Sanger sequencing in Arabidopsis, soybean, and maize. We also used SMAP design to perform eco-tilling by tilling PCR amplicons across nine candidate genes putatively associated with haploid induction in Cichorium intybus. We screened 60 accessions of chicory and witloof and identified thirteen knockout haplotypes and their carriers. SMAP design is an easy-to-use command-line tool that generates highly specific gRNA and/or primer designs for any number of loci for CRISPR or natural variation screens and is compatible with other SMAP modules for seamless downstream analysis.

Spatial Regression Models for Field Trials: A Comparative Study and New Ideas.

Naturally occurring variability within a study region harbors valuable information on relationships between biological variables. Yet, spatial patterns within these study areas, e.g., in field trials, violate the assumption of independence of observations, setting particular challenges in terms of hypothesis testing, parameter estimation, feature selection, and model evaluation. We evaluate a number of spatial regression methods in a simulation study, including more realistic spatial effects than employed so far. Based on our results, we recommend generalized least squares (GLS) estimation for experimental as well as for observational setups and demonstrate how it can be incorporated into popular regression models for high-dimensional data such as regularized least squares. This new method is available in the BioConductor R-package pengls. Inclusion of a spatial error structure improves parameter estimation and predictive model performance in low-dimensional settings and also improves feature selection in high-dimensional settings by reducing "red-shift": the preferential selection of features with spatial structure. In addition, we argue that the absence of spatial autocorrelation (SAC) in the model residuals should not be taken as a sign of a good fit, since it may result from overfitting the spatial trend. Finally, we confirm our findings in a case study on the prediction of winter wheat yield based on multispectral measurements.

ksrates: positioning whole-genome duplications relative to speciation events in KS distributions.

SUMMARY: We present ksrates, a user-friendly command-line tool to position ancient whole-genome duplication events with respect to speciation events in a phylogeny by comparing paralog and ortholog KS distributions derived from genomic or transcriptomic sequences, while adjusting for substitution rate differences among the lineages involved. AVAILABILITY AND IMPLEMENTATION: ksrates is implemented in Python 3 and as a Nextflow pipeline. The source code, Singularity and Docker containers, documentation and tutorial are available via https://github.com/VIB-PSB/ksrates. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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.

Vascular transcription factors guide plant epidermal responses to limiting phosphate conditions.

Optimal plant growth is hampered by deficiency of the essential macronutrient phosphate in most soils. Plant roots can, however, increase their root hair density to efficiently forage the soil for this immobile nutrient. By generating and exploiting a high-resolution single-cell gene expression atlas of Arabidopsis roots, we show an enrichment of TARGET OF MONOPTEROS 5/LONESOME HIGHWAY (TMO5/LHW) target gene responses in root hair cells. The TMO5/LHW heterodimer triggers biosynthesis of mobile cytokinin in vascular cells and increases root hair density during low-phosphate conditions by modifying both the length and cell fate of epidermal cells. Moreover, root hair responses in phosphate-deprived conditions are TMO5- and cytokinin-dependent. Cytokinin signaling links root hair responses in the epidermis to perception of phosphate depletion in vascular cells.

Interspecific hybridization facilitates niche adaptation in beer yeast.

Hybridization between species often leads to non-viable or infertile offspring, yet examples of evolutionarily successful interspecific hybrids have been reported in all kingdoms of life. However, many questions on the ecological circumstances and evolutionary aftermath of interspecific hybridization remain unanswered. In this study, we sequenced and phenotyped a large set of interspecific yeast hybrids isolated from brewing environments to uncover the influence of interspecific hybridization in yeast adaptation and domestication. Our analyses demonstrate that several hybrids between Saccharomyces species originated and diversified in industrial environments by combining key traits of each parental species. Furthermore, posthybridization evolution within each hybrid lineage reflects subspecialization and adaptation to specific beer styles, a process that was accompanied by extensive chimerization between subgenomes. Our results reveal how interspecific hybridization provides an important evolutionary route that allows swift adaptation to novel environments.

Endoreplication as a potential driver of cell wall modifications.

Endoreplication represents a variant of the mitotic cell cycle during which cells replicate their DNA without mitosis and/or cytokinesis, resulting in an increase in the cells' ploidy level. This process is especially prominent in higher plants, where it has been correlated with cell differentiation, metabolic output and rapid cell growth. However, different reports argue against a ploidy-dependent contribution to cell growth. Here, we review accumulating data suggesting that endocycle onset might exert an effect on cell growth through transcriptional control of cell wall-modifying genes to drive cell wall changes required to accommodate turgor-driven rapid cell expansion, consistent with the idea that vacuolar expansion rather than a ploidy-driven increase in cellular volume represents the major force driving cell growth.

A Spatiotemporal DNA Endoploidy Map of the Arabidopsis Root Reveals Roles for the Endocycle in Root Development and Stress Adaptation.

Somatic polyploidy caused by endoreplication is observed in arthropods, molluscs, and vertebrates but is especially prominent in higher plants, where it has been postulated to be essential for cell growth and fate maintenance. However, a comprehensive understanding of the physiological significance of plant endopolyploidy has remained elusive. Here, we modeled and experimentally verified a high-resolution DNA endoploidy map of the developing Arabidopsis thaliana root, revealing a remarkable spatiotemporal control of DNA endoploidy levels across tissues. Fitting of a simplified model to publicly available data sets profiling root gene expression under various environmental stress conditions suggested that this root endoploidy patterning may be stress-responsive. Furthermore, cellular and transcriptomic analyses revealed that inhibition of endoreplication onset alters the nuclear-to-cellular volume ratio and the expression of cell wall-modifying genes, in correlation with the appearance of cell structural changes. Our data indicate that endopolyploidy might serve to coordinate cell expansion with structural stability and that spatiotemporal endoreplication pattern changes may buffer for stress conditions, which may explain the widespread occurrence of the endocycle in plant species growing in extreme or variable environments.

Fern genomes elucidate land plant evolution and cyanobacterial symbioses.

Ferns are the closest sister group to all seed plants, yet little is known about their genomes other than that they are generally colossal. Here, we report on the genomes of Azolla filiculoides and Salvinia cucullata (Salviniales) and present evidence for episodic whole-genome duplication in ferns-one at the base of 'core leptosporangiates' and one specific to Azolla. One fern-specific gene that we identified, recently shown to confer high insect resistance, seems to have been derived from bacteria through horizontal gene transfer. Azolla coexists in a unique symbiosis with N2-fixing cyanobacteria, and we demonstrate a clear pattern of cospeciation between the two partners. Furthermore, the Azolla genome lacks genes that are common to arbuscular mycorrhizal and root nodule symbioses, and we identify several putative transporter genes specific to Azolla-cyanobacterial symbiosis. These genomic resources will help in exploring the biotechnological potential of Azolla and address fundamental questions in the evolution of plant life.

The Apicomplexa-specific glucosamine-6-phosphate N-acetyltransferase gene family encodes a key enzyme for glycoconjugate synthesis with potential as therapeutic target.

Apicomplexa form a phylum of obligate parasitic protozoa of great clinical and veterinary importance. These parasites synthesize glycoconjugates for their survival and infectivity, but the enzymatic steps required to generate the glycosylation precursors are not completely characterized. In particular, glucosamine-phosphate N-acetyltransferase (GNA1) activity, needed to produce the essential UDP-N-acetylglucosamine (UDP-GlcNAc) donor, has not been identified in any Apicomplexa. We scanned the genomes of Plasmodium falciparum and representatives from six additional main lineages of the phylum for proteins containing the Gcn5-related N-acetyltransferase (GNAT) domain. One family of GNAT-domain containing proteins, composed by a P. falciparum sequence and its six apicomplexan orthologs, rescued the growth of a yeast temperature-sensitive GNA1 mutant. Heterologous expression and in vitro assays confirmed the GNA1 enzymatic activity in all lineages. Sequence, phylogenetic and synteny analyses suggest an independent origin of the Apicomplexa-specific GNA1 family, parallel to the evolution of a different GNA1 family in other eukaryotes. The inability to disrupt an otherwise modifiable gene target suggests that the enzyme is essential for P. falciparum growth. The relevance of UDP-GlcNAc for parasite viability, together with the independent evolution and unique sequence features of Apicomplexa GNA1, highlights the potential of this enzyme as a selective therapeutic target against apicomplexans.

Origins, evolution, domestication and diversity of Saccharomyces beer yeasts.

Yeasts have been used for food and beverage fermentations for thousands of years. Today, numerous different strains are available for each specific fermentation process. However, the nature and extent of the phenotypic and genetic diversity and specific adaptations to industrial niches have only begun to be elucidated recently. In Saccharomyces, domestication is most pronounced in beer strains, likely because they continuously live in their industrial niche, allowing only limited genetic admixture with wild stocks and minimal contact with natural environments. As a result, beer yeast genomes show complex patterns of domestication and divergence, making both ale (S. cerevisiae) and lager (S. pastorianus) producing strains ideal models to study domestication and, more generally, genetic mechanisms underlying swift adaptation to new niches.

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.

Reciprocally Retained Genes in the Angiosperm Lineage Show the Hallmarks of Dosage Balance Sensitivity.

In several organisms, particular functional categories of genes, such as regulatory and complex-forming genes, are preferentially retained after whole-genome multiplications but rarely duplicate through small-scale duplication, a pattern referred to as reciprocal retention. This peculiar duplication behavior is hypothesized to stem from constraints on the dosage balance between the genes concerned and their interaction context. However, the evidence for a relationship between reciprocal retention and dosage balance sensitivity remains fragmentary. Here, we identified which gene families are most strongly reciprocally retained in the angiosperm lineage and studied their functional and evolutionary characteristics. Reciprocally retained gene families exhibit stronger sequence divergence constraints and lower rates of functional and expression divergence than other gene families, suggesting that dosage balance sensitivity is a general characteristic of reciprocally retained genes. Gene families functioning in regulatory and signaling processes are much more strongly represented at the top of the reciprocal retention ranking than those functioning in multiprotein complexes, suggesting that regulatory imbalances may lead to stronger fitness effects than classical stoichiometric protein complex imbalances. Finally, reciprocally retained duplicates are often subject to dosage balance constraints for prolonged evolutionary times, which may have repercussions for the ease with which genome multiplications can engender evolutionary innovation.

Evolutionary Context Improves Regulatory Network Predictions.

A novel algorithm harnesses phylogenetic information and facilitates a better understanding of the evolutionary divergence of gene regulation between species.