Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics.

Single-cell and single-nucleus RNA-sequencing technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality data sets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation and to make the data readily available to the community in this fast-developing field of research.

BREEDIT: a multiplex genome editing strategy to improve complex quantitative traits in maize.

Ensuring food security for an ever-growing global population while adapting to climate change is the main challenge for agriculture in the 21st century. Although new technologies are being applied to tackle this problem, we are approaching a plateau in crop improvement using conventional breeding. Recent advances in CRISPR/Cas9-mediated gene engineering have paved the way to accelerate plant breeding to meet this increasing demand. However, many traits are governed by multiple small-effect genes operating in complex interactive networks. Here, we present the gene discovery pipeline BREEDIT, which combines multiplex genome editing of whole gene families with crossing schemes to improve complex traits such as yield and drought tolerance. We induced gene knockouts in 48 growth-related genes into maize (Zea mays) using CRISPR/Cas9 and generated a collection of over 1,000 gene-edited plants. The edited populations displayed (on average) 5%-10% increases in leaf length and up to 20% increases in leaf width compared with the controls. For each gene family, edits in subsets of genes could be associated with enhanced traits, allowing us to reduce the gene space to be considered for trait improvement. BREEDIT could be rapidly applied to generate a diverse collection of mutants to identify promising gene modifications for later use in breeding programs.

Burning questions for a warming and changing world: 15 unknowns in plant abiotic stress.

We present unresolved questions in plant abiotic stress biology as posed by 15 research groups with expertise spanning eco-physiology to cell and molecular biology. Common themes of these questions include the need to better understand how plants detect water availability, temperature, salinity, and rising carbon dioxide (CO2) levels; how environmental signals interface with endogenous signaling and development (e.g. circadian clock and flowering time); and how this integrated signaling controls downstream responses (e.g. stomatal regulation, proline metabolism, and growth versus defense balance). The plasma membrane comes up frequently as a site of key signaling and transport events (e.g. mechanosensing and lipid-derived signaling, aquaporins). Adaptation to water extremes and rising CO2 affects hydraulic architecture and transpiration, as well as root and shoot growth and morphology, in ways not fully understood. Environmental adaptation involves tradeoffs that limit ecological distribution and crop resilience in the face of changing and increasingly unpredictable environments. Exploration of plant diversity within and among species can help us know which of these tradeoffs represent fundamental limits and which ones can be circumvented by bringing new trait combinations together. Better defining what constitutes beneficial stress resistance in different contexts and making connections between genes and phenotypes, and between laboratory and field observations, are overarching challenges.

MINI-AC: inference of plant gene regulatory networks using bulk or single-cell accessible chromatin profiles.

Gene regulatory networks (GRNs) represent the interactions between transcription factors (TF) and their target genes. Plant GRNs control transcriptional programs involved in growth, development, and stress responses, ultimately affecting diverse agricultural traits. While recent developments in accessible chromatin (AC) profiling technologies make it possible to identify context-specific regulatory DNA, learning the underlying GRNs remains a major challenge. We developed MINI-AC (Motif-Informed Network Inference based on Accessible Chromatin), a method that combines AC data from bulk or single-cell experiments with TF binding site (TFBS) information to learn GRNs in plants. We benchmarked MINI-AC using bulk AC datasets from different Arabidopsis thaliana tissues and showed that it outperforms other methods to identify correct TFBS. In maize, a crop with a complex genome and abundant distal AC regions, MINI-AC successfully inferred leaf GRNs with experimentally confirmed, both proximal and distal, TF-target gene interactions. Furthermore, we showed that both AC regions and footprints are valid alternatives to infer AC-based GRNs with MINI-AC. Finally, we combined MINI-AC predictions from bulk and single-cell AC datasets to identify general and cell-type specific maize leaf regulators. Focusing on C4 metabolism, we identified diverse regulatory interactions in specialized cell types for this photosynthetic pathway. MINI-AC represents a powerful tool for inferring accurate AC-derived GRNs in plants and identifying known and novel candidate regulators, improving our understanding of gene regulation in plants.

Modeling reveals posttranscriptional regulation of GA metabolism enzymes in response to drought and cold.

The hormone gibberellin (GA) controls plant growth and regulates growth responses to environmental stress. In monocotyledonous leaves, GA controls growth by regulating division-zone size. We used a systems approach to investigate the establishment of the GA distribution in the maize leaf growth zone to understand how drought and cold alter leaf growth. By developing and parameterizing a multiscale computational model that includes cell movement, growth-induced dilution, and metabolic activities, we revealed that the GA distribution is predominantly determined by variations in GA metabolism. Considering wild-type and UBI::GA20-OX-1 leaves, the model predicted the peak in GA concentration, which has been shown to determine division-zone size. Drought and cold modified enzyme transcript levels, although the model revealed that this did not explain the observed GA distributions. Instead, the model predicted that GA distributions are also mediated by posttranscriptional modifications increasing the activity of GA 20-oxidase in drought and of GA 2-oxidase in cold, which we confirmed by enzyme activity measurements. This work provides a mechanistic understanding of the role of GA metabolism in plant growth regulation.

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.

Increasing yield on dry fields: molecular pathways with growing potential.

Drought stress constitutes one of the major constraints to agriculture all over the world, and its devastating effect is only expected to increase in the following years due to climate change. Concurrently, the increasing food demand in a steadily growing population requires a proportional increase in yield and crop production. In the past, research aimed to increase plant resilience to severe drought stress. However, this often resulted in stunted growth and reduced yield under favorable conditions or moderate drought. Nowadays, drought tolerance research aims to maintain plant growth and yield under drought conditions. Overall, recently deployed strategies to engineer drought tolerance in the lab can be classified into a 'growth-centered' strategy, which focuses on keeping growth unaffected by the drought stress, and a 'drought resilience without growth penalty' strategy, in which the main aim is still to boost drought resilience, while limiting the side effects on plant growth. In this review, we put the scope on these two strategies and some molecular players that were successfully engineered to generate drought-tolerant plants: abscisic acid, brassinosteroids, cytokinins, ethylene, ROS scavenging genes, strigolactones, and aquaporins. We discuss how these pathways participate in growth and stress response regulation under drought. Finally, we present an overview of the current insights and future perspectives in the development of new strategies to improve drought tolerance in the field.

Combining multiplex gene editing and doubled haploid technology in maize.

A major advantage of using CRISPR/Cas9 for gene editing is multiplexing, that is, the simultaneous targeting of many genes. However, primary transformants typically contain hetero-allelic mutations or are genetic mosaic, while genetically stable lines that are homozygous are desired for functional analysis. Currently, a dedicated and labor-intensive effort is required to obtain such higher-order mutants through several generations of genetic crosses and genotyping. We describe the design and validation of a rapid and efficient strategy to produce lines of genetically identical plants carrying various combinations of homozygous edits, suitable for replicated analysis of phenotypical differences. This approach was achieved by combining highly multiplex gene editing in Zea mays (maize) with in vivo haploid induction and efficient in vitro generation of doubled haploid plants using embryo rescue doubling. By combining three CRISPR/Cas9 constructs that target in total 36 genes potentially involved in leaf growth, we generated an array of homozygous lines with various combinations of edits within three generations. Several genotypes show a reproducible 10% increase in leaf size, including a septuple mutant combination. We anticipate that our strategy will facilitate the study of gene families via multiplex CRISPR mutagenesis and the identification of allele combinations to improve quantitative crop traits.

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.

An in situ sequencing approach maps PLASTOCHRON1 at the boundary between indeterminate and determinate cells.

The plant shoot apex houses the shoot apical meristem, a highly organized and active stem-cell tissue where molecular signaling in discrete cells determines when and where leaves are initiated. We optimized a spatial transcriptomics approach, in situ sequencing (ISS), to colocalize the transcripts of 90 genes simultaneously on the same section of tissue from the maize (Zea mays) shoot apex. The RNA ISS technology reported expression profiles that were highly comparable with those obtained by in situ hybridizations (ISHs) and allowed the discrimination between tissue domains. Furthermore, the application of spatial transcriptomics to the shoot apex, which inherently comprised phytomers that are in gradual developmental stages, provided a spatiotemporal sequence of transcriptional events. We illustrate the power of the technology through PLASTOCHRON1 (PLA1), which was specifically expressed at the boundary between indeterminate and determinate cells and partially overlapped with ROUGH SHEATH1 and OUTER CELL LAYER4 transcripts. Also, in the inflorescence, PLA1 transcripts localized in cells subtending the lateral primordia or bordering the newly established meristematic region, suggesting a more general role of PLA1 in signaling between indeterminate and determinate cells during the formation of lateral organs. Spatial transcriptomics builds on RNA ISH, which assays relatively few transcripts at a time and provides a powerful complement to single-cell transcriptomics that inherently removes cells from their native spatial context. Further improvements in resolution and sensitivity will greatly advance research in plant developmental biology.

Identification of growth regulators using cross-species network analysis in plants.

With the need to increase plant productivity, one of the challenges plant scientists are facing is to identify genes that play a role in beneficial plant traits. Moreover, even when such genes are found, it is generally not trivial to transfer this knowledge about gene function across species to identify functional orthologs. Here, we focused on the leaf to study plant growth. First, we built leaf growth transcriptional networks in Arabidopsis (Arabidopsis thaliana), maize (Zea mays), and aspen (Populus tremula). Next, known growth regulators, here defined as genes that when mutated or ectopically expressed alter plant growth, together with cross-species conserved networks, were used as guides to predict novel Arabidopsis growth regulators. Using an in-depth literature screening, 34 out of 100 top predicted growth regulators were confirmed to affect leaf phenotype when mutated or overexpressed and thus represent novel potential growth regulators. Globally, these growth regulators were involved in cell cycle, plant defense responses, gibberellin, auxin, and brassinosteroid signaling. Phenotypic characterization of loss-of-function lines confirmed two predicted growth regulators to be involved in leaf growth (NPF6.4 and LATE MERISTEM IDENTITY2). In conclusion, the presented network approach offers an integrative cross-species strategy to identify genes involved in plant growth and development.

A forward genetics approach integrating genome-wide association study and expression quantitative trait locus mapping to dissect leaf development in maize (Zea mays).

The characterization of the genetic basis of maize (Zea mays) leaf development may support breeding efforts to obtain plants with higher vigor and productivity. In this study, a mapping panel of 197 biparental and multiparental maize recombinant inbred lines (RILs) was analyzed for multiple leaf traits at the seedling stage. RNA sequencing was used to estimate the transcription levels of 29 573 gene models in RILs and to derive 373 769 single nucleotide polymorphisms (SNPs), and a forward genetics approach combining these data was used to pinpoint candidate genes involved in leaf development. First, leaf traits were correlated with gene expression levels to identify transcript-trait correlations. Then, leaf traits were associated with SNPs in a genome-wide association (GWA) study. An expression quantitative trait locus mapping approach was followed to associate SNPs with gene expression levels, prioritizing candidate genes identified based on transcript-trait correlations and GWAs. Finally, a network analysis was conducted to cluster all transcripts in 38 co-expression modules. By integrating forward genetics approaches, we identified 25 candidate genes highly enriched for specific functional categories, providing evidence supporting the role of vacuolar proton pumps, cell wall effectors, and vesicular traffic controllers in leaf growth. These results tackle the complexity of leaf trait determination and may support precision breeding in maize.

The translatability of genetic networks from model to crop species: lessons from the past and perspectives for the future.

Comparative analyses of growth-regulatory mechanisms between Arabidopsis and maize revealed that even when the gene space is conserved, the translation of knowledge from model species to crops is not trivial. Based on these insights, we formulate future opportunities to improve the interpretation of curiosity-driven research towards crop improvement.

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.

Root engineering in maize by increasing cytokinin degradation causes enhanced root growth and leaf mineral enrichment.

KEY MESSAGE: Root-specific expression of a cytokinin-degrading CKX gene in maize roots causes formation of a larger root system leading to higher element content in shoot organs. The size and architecture of the root system is functionally relevant for the access to water and soil nutrients. A great number of mostly unknown genes are involved in regulating root architecture complicating targeted breeding of plants with a larger root system. Here, we have explored whether root-specific degradation of the hormone cytokinin, which is a negative regulator of root growth, can be used to genetically engineer maize (Zea mays L.) plants with a larger root system. Root-specific expression of a CYTOKININ OXIDASE/DEHYDROGENASE (CKX) gene of Arabidopsis caused the formation of up to 46% more root dry weight while shoot growth of these transgenic lines was similar as in non-transgenic control plants. The concentration of several elements, in particular of those with low soil mobility (K, P, Mo, Zn), was increased in leaves of transgenic lines. In kernels, the changes in concentration of most elements were less pronounced, but the concentrations of Cu, Mn and Zn were significantly increased in at least one of the three independent lines. Our data illustrate the potential of an increased root system as part of efforts towards achieving biofortification. Taken together, this work has shown that root-specific expression of a CKX gene can be used to engineer the root system of maize and alter shoot element composition.

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.

Modification of the Expression of the Aquaporin ZmPIP2;5 Affects Water Relations and Plant Growth.

The plasma membrane intrinsic protein PIP2;5 is the most highly expressed aquaporin in maize (Zea mays) roots. Here, we investigated how deregulation of PIP2;5 expression affects water relations and growth using maize overexpression (OE; B104 inbred) or knockout (KO; W22 inbred) lines. The hydraulic conductivity of the cortex cells of roots grown hydroponically was higher in PIP2;5 OE and lower in pip2;5 KO lines compared with the corresponding wild-type plants. While whole-root conductivity decreased in the KO lines compared to the wild type, no difference was observed in OE plants. This paradox was interpreted using the MECHA hydraulic model, which computes the radial flow of water within root sections. The model hints that the plasma membrane permeability of the cells is not radially uniform but that PIP2;5 may be saturated in cell layers with apoplastic barriers, i.e. the endodermis and exodermis, suggesting the presence of posttranslational mechanisms controlling the abundance of PIP in the plasma membrane in these cells. At the leaf level, where the PIP2;5 gene is weakly expressed in wild-type plants, the hydraulic conductance was higher in the PIP2;5 OE lines compared with the wild-type plants, whereas no difference was observed in the pip2;5 KO lines. The temporal trend of leaf elongation rate, used as a proxy for that of xylem water potential, was faster in PIP2;5 OE plants upon mild stress, but not in well-watered conditions, demonstrating that PIP2;5 may play a beneficial role in plant growth under specific conditions.

Turgor-time controls grass leaf elongation rate and duration under drought stress.

The process of leaf elongation in grasses is characterized by the creation and transformation of distinct cell zones. The prevailing turgor pressure within these cells is one of the key drivers for the rate at which these cells divide, expand and differentiate, processes that are heavily impacted by drought stress. In this article, a turgor-driven growth model for grass leaf elongation is presented, which combines mechanistic growth from the basis of turgor pressure with the ontogeny of the leaf. Drought-induced reductions in leaf turgor pressure result in a simultaneous inhibition of both cell expansion and differentiation, lowering elongation rate but increasing elongation duration due to the slower transitioning of cells from the dividing and elongating zone to mature cells. Leaf elongation is, therefore, governed by the magnitude of, and time spent under, growth-enabling turgor pressure, a metric which we introduce as turgor-time. Turgor-time is able to normalize growth patterns in terms of varying water availability, similar to how thermal time is used to do so under varying temperatures. Moreover, additional inclusion of temperature dependencies within our model pioneers a novel concept enabling the general expression of growth regardless of water availability or temperature.

Comparative transcriptomics enables the identification of functional orthologous genes involved in early leaf growth.

Leaf growth is a complex trait for which many similarities exist in different plant species, suggesting functional conservation of the underlying pathways. However, a global view of orthologous genes involved in leaf growth showing conserved expression in dicots and monocots is currently missing. Here, we present a genome-wide comparative transcriptome analysis between Arabidopsis and maize, identifying conserved biological processes and gene functions active during leaf growth. Despite the orthology complexity between these distantly related plants, 926 orthologous gene groups including 2829 Arabidopsis and 2974 maize genes with similar expression during leaf growth were found, indicating conservation of the underlying molecular networks. We found 65% of these genes to be involved in one-to-one orthology, whereas only 28.7% of the groups with divergent expression had one-to-one orthology. Within the pool of genes with conserved expression, 19 transcription factor families were identified, demonstrating expression conservation of regulators active during leaf growth. Additionally, 25 Arabidopsis and 25 maize putative targets of the TCP transcription factors with conserved expression were determined based on the presence of enriched transcription factor binding sites. Based on large-scale phenotypic data, we observed that genes with conserved expression have a higher probability to be involved in leaf growth and that leaf-related phenotypes are more frequently present for genes having orthologues between dicots and monocots than clade-specific genes. This study shows the power of integrating transcriptomic with orthology data to identify or select candidates for functional studies during leaf development in flowering plants.

How grass keeps growing: an integrated analysis of hormonal crosstalk in the maize leaf growth zone.

We studied the maize leaf to understand how long-distance signals, auxin and cytokinin, control leaf growth dynamics. We constructed a mathematical model describing the transport of these hormones along the leaf growth zone and their interaction with the local gibberellin (GA) metabolism in the control of cell division. Assuming gradually declining auxin and cytokinin supply at the leaf base, the model generated spatiotemporal hormone distribution and growth patterns that matched experimental data. At the cellular level, the model predicted a basal leaf growth as a result of cell division driven by auxin and cytokinin. Superimposed on this, GA synthesis regulated growth through the control of the size of the region of active cell division. The predicted hormone and cell length distributions closely matched experimental data. To correctly predict the leaf growth profiles and final organ size of lines with reduced or elevated GA production, the model required a signal proportional to the size of the emerged part of the leaf that inhibited the basal leaf growth driven by auxin and cytokinin. Excision and shading of the emerged part of the growing leaf allowed us to demonstrate that this signal exists and depends on the perception of light intensity.