Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants

Artificial intelligence in plant breeding

Harnessing cutting-edge technologies to enhance crop productivity is a pivotal goal in modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data analysis and pattern recognition, and is revolutionizing numerous scientific domains including plant breeding. We explore the wider potential of AI tools in various facets of breeding, including data collection, unlocking genetic diversity within genebanks, and bridging the genotype-phenotype gap to facilitate crop breeding. This will enable the development of crop cultivars tailored to the projected future environments. Moreover, AI tools also hold promise for refining crop traits by improving the precision of gene-editing systems and predicting the potential effects of gene variants on plant phenotypes. Leveraging AI-enabled precision breeding can augment the efficiency of breeding programs and holds promise for optimizing cropping systems at the grassroots level. This entails identifying optimal inter-cropping and crop-rotation models to enhance agricultural sustainability and productivity in the field.

Rewiring gene circuitry for plant improvement

Aspirations for high crop growth and yield, nutritional quality and bioproduction of materials are challenged by climate change and limited adoption of new technologies. Here, we review recent advances in approaches to profile and model gene regulatory activity over developmental and response time in specific cells, which have revealed the basis of variation in plant phenotypes: both redeployment of key regulators to new contexts and their repurposing to control different slates of genes. New synthetic biology tools allow tunable, spatiotemporal regulation of transgenes, while recent gene-editing technologies enable manipulation of the regulation of native genes. Ultimately, understanding how gene circuitry is wired to control form and function across varied plant species, combined with advanced technology to rewire that circuitry, will unlock solutions to our greatest challenges in agriculture, energy and the environment.

Characterization and stress-responsive regulation of CmPHT1 genes involved in phosphate uptake and transport in Melon (Cucumis melo L.)

BACKGROUND

Phosphorus (P) deficiency, a major nutrient stress, greatly hinders plant growth. Phosphate (Pi) uptake in plant roots relies on PHT1 family transporters. However, melon (Cucumis melo L.) lacks comprehensive identification and characterization of PHT1 genes, particularly their response patterns under diverse stresses.

RESULTS

This study identified and analyzed seven putative CmPHT1 genes on chromosomes 3, 4, 5, 6, and 7 using the melon genome. Phylogenetic analysis revealed shared motifs, domain compositions, and evolutionary relationships among genes with close histories. Exon number varied from 1 to 3. Collinearity analysis suggested segmental and tandem duplications as the primary mechanisms for CmPHT1 gene family expansion. CmPHT1;4 and CmPHT1;5 emerged as a tandemly duplicated pair. Analysis of cis-elements in CmPHT1 promoters identified 14 functional categories, including putative PHR1-binding sites (P1BS) in CmPHT1;4, CmPHT1;6, and CmPHT1;7. We identified that three WRKY transcription factors regulated CmPHT1;5 expression by binding to its W-box element. Notably, CmPHT1 promoters harbored cis-elements responsive to hormones and abiotic factors. Different stresses regulated CmPHT1 expression differently, suggesting that the adjusted expression patterns might contribute to plant adaptation.

CONCLUSIONS

This study unveils the characteristics, evolutionary diversity, and stress responsiveness of CmPHT1 genes in melon. These findings lay the foundation for in-depth investigations into their functional mechanisms in Cucurbitaceae crops.

Recent advances in local and systemic nitrate signaling in Arabidopsisthaliana

Nitrate is the most abundant form of inorganic nitrogen in aerobic soils, serving both as a nutrient and a signaling molecule. Central to nitrate signaling in higher plants is the intricate balance between local and systemic signaling and response pathways. The interplay between local and systemic responses allows plants to regulate their global gene expression, metabolism, physiology, growth, and development under fluctuating nitrate availability. This review offers an overview of recent discoveries regarding new players on nitrate sensing and signaling, in local and systemic contexts in Arabidopsis thaliana. Additionally, it addresses unanswered questions that warrant further investigation for a better understanding of nitrate signaling and responses in plants.

Dynamic changes in mRNA nucleocytoplasmic localization in the nitrate response of Arabidopsis roots

Nitrate is a nutrient and signal that regulates gene expression. The nitrate response has been extensively characterized at the organism, organ, and cell-type-specific levels, but intracellular mRNA dynamics remain unexplored. To characterize nuclear and cytoplasmic transcriptome dynamics in response to nitrate, we performed a time-course expression analysis after nitrate treatment in isolated nuclei, cytoplasm, and whole roots. We identified 402 differentially localized transcripts (DLTs) in response to nitrate treatment. Induced DLT genes showed rapid and transient recruitment of the RNA polymerase II, together with an increase in the mRNA turnover rates. DLTs code for genes involved in metabolic processes, localization, and response to stimulus indicating DLTs include genes with relevant functions for the nitrate response that have not been previously identified. Using single-molecule RNA FISH, we observed early nuclear accumulation of the NITRATE REDUCTASE 1 (NIA1) transcripts in their transcription sites. We found that transcription of NIA1, a gene showing delayed cytoplasmic accumulation, is rapidly and transiently activated; however, its transcripts become unstable when they reach the cytoplasm. Our study reveals the dynamic localization of mRNAs between the nucleus and cytoplasm as an emerging feature in the temporal control of gene expression in response to nitrate treatment in Arabidopsis roots.

Optimizing data integration improves gene regulatory network inference in Arabidopsis thaliana

MOTIVATIONS

Gene regulatory networks (GRNs) are traditionally inferred from gene expression profiles monitoring a specific condition or treatment. In the last decade, integrative strategies have successfully emerged to guide GRN inference from gene expression with complementary prior data. However, datasets used as prior information and validation gold standards are often related and limited to a subset of genes. This lack of complete and independent evaluation calls for new criteria to robustly estimate the optimal intensity of prior data integration in the inference process.

RESULTS

We address this issue for two regression-based GRN inference models, a weighted random forest (weigthedRF) and a generalized linear model estimated under a weighted LASSO penalty with stability selection (weightedLASSO). These approaches are applied to data from the root response to nitrate induction in Arabidopsis thaliana. For each gene, we measure how the integration of transcription factor binding motifs influences model prediction. We propose a new approach, DIOgene, that uses model prediction error and a simulated null hypothesis in order to optimize data integration strength in a hypothesis-driven, gene-specific manner. This integration scheme reveals a strong diversity of optimal integration intensities between genes, and offers good performance in minimizing prediction error as well as retrieving experimental interactions. Experimental results show that DIOgene compares favorably against state-of-the-art approaches and allows to recover master regulators of nitrate induction.

AVAILABILITY AND IMPLEMENTATION

The R code and notebooks demonstrating the use of the proposed approaches are available in the repository https://github.com/OceaneCsn/integrative_GRN_N_induction.

Recent advances in exploring transcriptional regulatory landscape of crops

Crop breeding entails developing and selecting plant varieties with improved agronomic traits. Modern molecular techniques, such as genome editing, enable more efficient manipulation of plant phenotype by altering the expression of particular regulatory or functional genes. Hence, it is essential to thoroughly comprehend the transcriptional regulatory mechanisms that underpin these traits. In the multi-omics era, a large amount of omics data has been generated for diverse crop species, including genomics, epigenomics, transcriptomics, proteomics, and single-cell omics. The abundant data resources and the emergence of advanced computational tools offer unprecedented opportunities for obtaining a holistic view and profound understanding of the regulatory processes linked to desirable traits. This review focuses on integrated network approaches that utilize multi-omics data to investigate gene expression regulation. Various types of regulatory networks and their inference methods are discussed, focusing on recent advancements in crop plants. The integration of multi-omics data has been proven to be crucial for the construction of high-confidence regulatory networks. With the refinement of these methodologies, they will significantly enhance crop breeding efforts and contribute to global food security.

Dof1.7 and NIGT1 transcription factors mediate multilayered transcriptional regulation for different expression patterns of NITRATE TRANSPORTER2 genes under nitrogen deficiency stress

Elucidating the mechanisms regulating nitrogen (N) deficiency responses in plants is of great agricultural importance. Previous studies revealed that decreased expression of NITRATE-INDUCIBLE GARP-TYPE TRANSCRIPTIONAL REPRESSOR1 (NIGT1) transcriptional repressor genes upon N deficiency is involved in N deficiency-inducible gene expression in Arabidopsis thaliana. However, our knowledge of the mechanisms controlling N deficiency-induced changes in gene expression is still limited. Through the identification of Dof1.7 as a direct target of NIGT1 repressors and a novel N deficiency response-related transcriptional activator gene, we here show that NIGT1 and Dof1.7 transcription factors (TFs) differentially regulate N deficiency-inducible expression of three high-affinity nitrate transporter genes, NRT2.1, NRT2.4, and NRT2.5, which are responsible for most of the soil nitrate uptake activity of Arabidopsis plants under N-deficient conditions. Unlike NIGT1 repressors, which directly suppress NRT2.1, NRT2.4, and NRT2.5 under N-sufficient conditions, Dof1.7 directly activated only NRT2.5 but indirectly and moderately activated NRT2.1 and NRT2.4 under N-deficient conditions, probably by indirectly decreasing NIGT1 expression. Thus, Dof1.7 converted passive transcriptional activation into active and potent transcriptional activation, further differentially enhancing the expression of NRT2 genes. These findings clarify the mechanism underlying different expression patterns of NRT2 genes upon N deficiency, suggesting that time-dependent multilayered transcriptional regulation generates complicated expression patterns of N deficiency-inducible genes.

Bipartite networks represent causality better than simple networks: evidence, algorithms, and applications

A network, whose nodes are genes and whose directed edges represent positive or negative influences of a regulatory gene and its targets, is often used as a representation of causality. To infer a network, researchers often develop a machine learning model and then evaluate the model based on its match with experimentally verified "gold standard" edges. The desired result of such a model is a network that may extend the gold standard edges. Since networks are a form of visual representation, one can compare their utility with architectural or machine blueprints. Blueprints are clearly useful because they provide precise guidance to builders in construction. If the primary role of gene regulatory networks is to characterize causality, then such networks should be good tools of prediction because prediction is the actionable benefit of knowing causality. But are they? In this paper, we compare prediction quality based on "gold standard" regulatory edges from previous experimental work with non-linear models inferred from time series data across four different species. We show that the same non-linear machine learning models have better predictive performance, with improvements from 5.3% to 25.3% in terms of the reduction in the root mean square error (RMSE) compared with the same models based on the gold standard edges. Having established that networks fail to characterize causality properly, we suggest that causality research should focus on four goals: (i) predictive accuracy; (ii) a parsimonious enumeration of predictive regulatory genes for each target gene g; (iii) the identification of disjoint sets of predictive regulatory genes for each target g of roughly equal accuracy; and (iv) the construction of a bipartite network (whose node types are genes and models) representation of causality. We provide algorithms for all goals.

Nitrogen sensing and regulatory networks: it's about time and space

A plant's response to external and internal nitrogen signals/status relies on sensing and signaling mechanisms that operate across spatial and temporal dimensions. From a comprehensive systems biology perspective, this involves integrating nitrogen responses in different cell types and over long distances to ensure organ coordination in real time and yield practical applications. In this prospective review, we focus on novel aspects of nitrogen (N) sensing/signaling uncovered using temporal and spatial systems biology approaches, largely in the model Arabidopsis. The temporal aspects span: transcriptional responses to N-dose mediated by Michaelis-Menten kinetics, the role of the master NLP7 transcription factor as a nitrate sensor, its nitrate-dependent TF nuclear retention, its "hit-and-run" mode of target gene regulation, and temporal transcriptional cascade identified by "network walking." Spatial aspects of N-sensing/signaling have been uncovered in cell type-specific studies in roots and in root-to-shoot communication. We explore new approaches using single-cell sequencing data, trajectory inference, and pseudotime analysis as well as machine learning and artificial intelligence approaches. Finally, unveiling the mechanisms underlying the spatial dynamics of nitrogen sensing/signaling networks across species from model to crop could pave the way for translational studies to improve nitrogen-use efficiency in crops. Such outcomes could potentially reduce the detrimental effects of excessive fertilizer usage on groundwater pollution and greenhouse gas emissions.

Organ-delimited gene regulatory networks provide high accuracy in candidate transcription factor selection across diverse processes

Organ-specific gene expression datasets that include hundreds to thousands of experiments allow the reconstruction of organ-level gene regulatory networks (GRNs). However, creating such datasets is greatly hampered by the requirements of extensive and tedious manual curation. Here, we trained a supervised classification model that can accurately classify the organ-of-origin for a plant transcriptome. This K-Nearest Neighbor-based multiclass classifier was used to create organ-specific gene expression datasets for the leaf, root, shoot, flower, and seed in Arabidopsis thaliana. A GRN inference approach was used to determine the: i. influential transcription factors (TFs) in each organ and, ii. most influential TFs for specific biological processes in that organ. These genome-wide, organ-delimited GRNs (OD-GRNs), recalled many known regulators of organ development and processes operating in those organs. Importantly, many previously unknown TF regulators were uncovered as potential regulators of these processes. As a proof-of-concept, we focused on experimentally validating the predicted TF regulators of lipid biosynthesis in seeds, an important food and biofuel trait. Of the top 20 predicted TFs, eight are known regulators of seed oil content, e.g., WRI1, LEC1, FUS3. Importantly, we validated our prediction of MybS2, TGA4, SPL12, AGL18, and DiV2 as regulators of seed lipid biosynthesis. We elucidated the molecular mechanism of MybS2 and show that it induces purple acid phosphatase family genes and lipid synthesis genes to enhance seed lipid content. This general approach has the potential to be extended to any species with sufficiently large gene expression datasets to find unique regulators of any trait-of-interest.

TaLBD41 interacts with TaNAC2 to regulate nitrogen uptake and metabolism in response to nitrate availability

Nitrate is the main source of nitrogen (N) available to plants and also is a signal that triggers complex regulation of transcriptional networks to modulate a wide variety of physiological and developmental responses in plants. How plants adapt to soil nitrate fluctuations is a complex process involving a fine-tuned response to nitrate provision and N starvation, the molecular mechanisms of which remain largely uncharted. Here, we report that the wheat transcription factor TaLBD41 interacts with the nitrate-inducible transcription factor TaNAC2 and is repressed by nitrate provision. Electrophoretic mobility shift assay and dual-luciferase system show that the TaLBD41-NAC2 interaction confers homeostatic coordination of nitrate uptake, reduction, and assimilation by competitively binding to TaNRT2.1, TaNR1.2, and TaNADH-GOGAT. Knockdown of TaLBD41 expression enhances N uptake and assimilation, increases spike number, grain yield, and nitrogen harvest index under different N supply conditions. We also identified an elite haplotype of TaLBD41-2B associated with increased spike number and grain yield. Our study uncovers a novel mechanism underlying the interaction between two transcription factors in mediating wheat adaptation to nitrate availability by antagonistically regulating nitrate uptake and assimilation, providing a potential target for designing varieties with efficient N use in wheat (Triticum aestivum).

Recent advances in unraveling the mystery of combined nutrient stress in plants

Efficiently regulating growth to adapt to varying resource availability is crucial for organisms, including plants. In particular, the acquisition of essential nutrients is vital for plant development, as a shortage of just one nutrient can significantly decrease crop yield. However, plants constantly experience fluctuations in the presence of multiple essential mineral nutrients, leading to combined nutrient stress conditions. Unfortunately, our understanding of how plants perceive and respond to these multiple stresses remains limited. Unlocking this mystery could provide valuable insights and help enhance plant nutrition strategies. This review focuses specifically on the regulation of phosphorous homeostasis in plants, with a primary emphasis on recent studies that have shed light on the intricate interactions between phosphorous and other essential elements, such as nitrogen, iron, and zinc, as well as non-essential elements like aluminum and sodium. By summarizing and consolidating these findings, this review aims to contribute to a better understanding of how plants respond to and cope with combined nutrient stress.

Function of hormone signaling in regulating nitrogen-use efficiency in plants

Nitrogen (N) is one of the most important nutrients for crop plant performance, however, the excessive application of nitrogenous fertilizers in agriculture significantly increases production costs and causes severe environmental problems. Therefore, comprehensively understanding the molecular mechanisms of N-use efficiency (NUE) with the aim of developing new crop varieties that combine high yields with improved NUE is an urgent goal for achieving more sustainable agriculture. Plant NUE is a complex trait that is affected by multiple factors, of which hormones are known to play pivotal roles. In this review, we focus on the interaction between the biosynthesis and signaling pathways of plant hormones with N metabolism, and summarize recent studies on the interplay between hormones and N, including how N regulates multiple hormone biosynthesis, transport and signaling and how hormones modulate root system architecture (RSA) in response to external N sources. Finally, we explore potential strategies for promoting crop NUE by modulating hormone synthesis, transport and signaling. This provides insights for future breeding of N-efficient crop varieties and the advancement of sustainable agriculture.

The MYB-CC Transcription Factor PHOSPHATE STARVATION RESPONSE-LIKE 7 (PHL7) Functions in Phosphate Homeostasis and Affects Salt Stress Tolerance in Rice

Inorganic phosphate (Pi) homeostasis plays an important role in plant growth and abiotic stress tolerance. Several MYB-CC transcription factors involved in Pi homeostasis have been identified in rice (Oryza sativa). PHOSPHATE STARVATION RESPONSE-LIKE 7 (PHL7) is a class II MYC-CC protein, in which the MYC-CC domain is located at the N terminus. In this study, we established that OsPHL7 is localized to the nucleus and that the encoding gene is induced by Pi deficiency. The Pi-responsive genes and Pi transporter genes are positively regulated by OsPHL7. The overexpression of OsPHL7 enhanced the tolerance of rice plants to Pi starvation, whereas the RNA interference-based knockdown of this gene resulted in increased sensitivity to Pi deficiency. Transgenic rice plants overexpressing OsPHL7 produced more roots than wild-type plants under both Pi-sufficient and Pi-deficient conditions and accumulated more Pi in the shoots and roots. In addition, the overexpression of OsPHL7 enhanced rice tolerance to salt stress. Together, these results demonstrate that OsPHL7 is involved in the maintenance of Pi homeostasis and enhances tolerance to Pi deficiency and salt stress in rice.

Organ-specific characteristics govern the relationship between histone code dynamics and transcriptional reprogramming during nitrogen response in tomato

Environmental stimuli trigger rapid transcriptional reprogramming of gene networks. These responses occur in the context of the local chromatin landscape, but the contribution of organ-specific dynamic chromatin modifications in responses to external signals remains largely unexplored. We treated tomato seedlings with a supply of nitrate and measured the genome-wide changes of four histone marks, the permissive marks H3K27ac, H3K4me3, and H3K36me3 and repressive mark H3K27me3, in shoots and roots separately, as well as H3K9me2 in shoots. Dynamic and organ-specific histone acetylation and methylation were observed at functionally relevant gene loci. Integration of transcriptomic and epigenomic datasets generated from the same organ revealed largely syngenetic relations between changes in transcript levels and histone modifications, with the exception of H3K27me3 in shoots, where an increased level of this repressive mark is observed at genes activated by nitrate. Application of a machine learning approach revealed organ-specific rules regarding the importance of individual histone marks, as H3K36me3 is the most successful mark in predicting gene regulation events in shoots, while H3K4me3 is the strongest individual predictor in roots. Our integrated study substantiates a view that during plant environmental responses, the relationships between histone code dynamics and gene regulation are highly dependent on organ-specific contexts.

Involvement of plant signaling network and cell metabolic homeostasis in nitrogen deficiency-induced early leaf senescence

Nitrogen (N) is a basic building block that plays an essential role in the maintenance of normal plant growth and its metabolic functions through complex regulatory networks. Such the N metabolic network comprises a series of transcription factors (TFs), with the coordinated actions of phytohormone and sugar signaling to sustain cell homeostasis. The fluctuating N concentration in plant tissues alters the sensitivity of several signaling pathways to stressful environments and regulates the senescent-associated changes in cellular structure and metabolic process. Here, we review recent advances in the interaction between N assimilation and carbon metabolism in response to N deficiency and its regulation to the nutrient remobilization from source to sink during leaf senescence. The regulatory networks of N and sugar signaling for N deficiency-induced leaf senescence is further discussed to explain the effects of N deficiency on chloroplast disassembly, reactive oxygen species (ROS) burst, asparagine metabolism, sugar transport, autophagy process, Ca2+ signaling, circadian clock response, brassinazole-resistant 1 (BZRI), and other stress cell signaling. A comprehensive understanding for the metabolic mechanism and regulatory network underlying N deficiency-induced leaf senescence may provide a theoretical guide to optimize the source-sink relationship during grain filling for the achievement of high yield by a selection of crop cultivars with the properly prolonged lifespan of functional leaves and/or by appropriate agronomic managements.

Epicuticular wax accumulation and regulation of wax pathway gene expression during bioenergy Sorghum stem development

Bioenergy sorghum is a drought-tolerant high-biomass C4 grass targeted for production on annual cropland marginal for food crops due primarily to abiotic constraints. To better understand the overall contribution of stem wax to bioenergy sorghum's resilience, the current study characterized sorghum stem cuticular wax loads, composition, morphometrics, wax pathway gene expression and regulation using vegetative phase Wray, R07020, and TX08001 genotypes. Wax loads on sorghum stems (~103-215 µg/cm2) were much higher than Arabidopsis stem and leaf wax loads. Wax on developing sorghum stem internodes was enriched in C28/30 primary alcohols (~65%) while stem wax on fully developed stems was enriched in C28/30 aldehydes (~80%). Scanning Electron Microscopy showed minimal wax on internodes prior to the onset of elongation and that wax tubules first appear associated with cork-silica cell complexes when internode cell elongation is complete. Sorghum homologs of genes involved in wax biosynthesis/transport were differentially expressed in the stem epidermis. Expression of many wax pathway genes (i.e., SbKCS6, SbCER3-1, SbWSD1, SbABCG12, SbABCG11) is low in immature apical internodes then increases at the onset of stem wax accumulation. SbCER4 is expressed relatively early in stem development consistent with accumulation of C28/30 primary alcohols on developing apical internodes. High expression of two SbCER3 homologs in fully elongated internodes is consistent with a role in production of C28/30 aldehydes. Gene regulatory network analysis aided the identification of sorghum homologs of transcription factors that regulate wax biosynthesis (i.e., SbSHN1, SbWRI1/3, SbMYB94/96/30/60, MYS1) and other transcription factors that could regulate and specify expression of the wax pathway in epidermal cells during cuticle development.

Metabolic and Molecular Rearrangements of Sauvignon Blanc (Vitis vinifera L.) Berries in Response to Foliar Applications of Specific Dry Yeast

Dry yeast extracts (DYE) are applied to vineyards to improve aromatic and secondary metabolic compound content and wine quality; however, systematic information on the underpinning molecular mechanisms is lacking. This work aimed to unravel, through a systematic approach, the metabolic and molecular responses of Sauvignon Blanc berries to DYE treatments. To accomplish this, DYE spraying was performed in a commercial vineyard for two consecutive years. Berries were sampled at several time points after the treatment, and grapes were analyzed for sugars, acidity, free and bound aroma precursors, amino acids, and targeted and untargeted RNA-Seq transcriptional profiles. The results obtained indicated that the DYE treatment did not interfere with the technological ripening parameters of sugars and acidity. Some aroma precursors, including cys-3MH and GSH-3MH, responsible for the typical aromatic nuances of Sauvignon Blanc, were stimulated by the treatment during both vintages. The levels of amino acids and the global RNA-seq transcriptional profiles indicated that DYE spraying upregulated ROS homeostatic and thermotolerance genes, as well as ethylene and jasmonic acid biosynthetic genes, and activated abiotic and biotic stress responses. Overall, the data suggested that the DYE reduced berry oxidative stress through the regulation of specific subsets of metabolic and hormonal pathways.

Finding Balance in Adversity: Nitrate Signaling as the Key to Plant Growth, Resilience, and Stress Response

To effectively adapt to changing environments, plants must maintain a delicate balance between growth and resistance or tolerance to various stresses. Nitrate, a significant inorganic nitrogen source in soils, not only acts as an essential nutrient but also functions as a critical signaling molecule that regulates multiple aspects of plant growth and development. In recent years, substantial advancements have been made in understanding nitrate sensing, calcium-dependent nitrate signal transmission, and nitrate-induced transcriptional cascades. Mounting evidence suggests that the primary response to nitrate is influenced by environmental conditions, while nitrate availability plays a pivotal role in stress tolerance responses. Therefore, this review aims to provide an overview of the transcriptional and post-transcriptional regulation of key components in the nitrate signaling pathway, namely, NRT1.1, NLP7, and CIPK23, under abiotic stresses. Additionally, we discuss the specificity of nitrate sensing and signaling as well as the involvement of epigenetic regulators. A comprehensive understanding of the integration between nitrate signaling transduction and abiotic stress responses is crucial for developing future crops with enhanced nitrogen-use efficiency and heightened resilience.

Chilling stress drives organ-specific transcriptional cascades and dampens diurnal oscillation in tomato

Improving chilling tolerance in cold-sensitive crops, e.g. tomato, requires knowledge of the early molecular response to low temperature in these under-studied species. To elucidate early responding processes and regulators, we captured the transcriptional response at 30 minutes and 3 hours in the shoots and at 3 hours in the roots of tomato post-chilling from 24°C to 4°C. We used a pre-treatment control and a concurrent ambient temperature control to reveal that majority of the differential expression between cold and ambient conditions is due to severely compressed oscillation of a large set of diurnally regulated genes in both the shoots and roots. This compression happens within 30 minutes of chilling, lasts for the duration of cold treatment, and is relieved within 3 hours of return to ambient temperatures. Our study also shows that the canonical ICE1/CAMTA-to-CBF cold response pathway is active in the shoots, but not in the roots. Chilling stress induces synthesis of known cryoprotectants (trehalose and polyamines), in a CBF-independent manner, and induction of multiple genes encoding proteins of photosystems I and II. This study provides nuanced insights into the organ-specific response in a chilling sensitive plant, as well as the genes influenced by an interaction of chilling response and the circadian clock.

Epigenetic Regulation of Nitrogen Signaling and Adaptation in Plants

Nitrogen (N) is a crucial nutrient that plays a significant role in enhancing crop yield. Its availability, including both supply and deficiency, serves as a crucial signal for plant development. However, excessive N use in agriculture leads to environmental and economic issues. Enhancing nitrogen use efficiency (NUE) is, therefore, essential to minimize negative impacts. Prior studies have investigated the genetic factors involved in N responses and the process of low-nitrogen (LN) adaptation. In this review, we discuss recent advances in understanding how epigenetic modifications, including DNA methylation, histone modification, and small RNA, participate in the regulation of N response and LN adaptation. We highlight the importance of decoding the epigenome at various levels to accelerate the functional study of how plants respond to N availability. Understanding the epigenetic control of N signaling and adaptation can lead to new strategies to improve NUE and enhance crop productivity sustainably.

Gene regulatory network inference in soybean upon infection by Phytophthora sojae

Phytophthora sojae is a soil-borne oomycete and the causal agent of Phytophthora root and stem rot (PRR) in soybean (Glycine max [L.] Merrill). Yield losses attributed to P. sojae are devastating in disease-conducive environments, with global estimates surpassing 1.1 million tonnes annually. Historically, management of PRR has entailed host genetic resistance (both vertical and horizontal) complemented by disease-suppressive cultural practices (e.g., oomicide application). However, the vast expansion of complex and/or diverse P. sojae pathotypes necessitates developing novel technologies to attenuate PRR in field environments. Therefore, the objective of the present study was to couple high-throughput sequencing data and deep learning to elucidate molecular features in soybean following infection by P. sojae. In doing so, we generated transcriptomes to identify differentially expressed genes (DEGs) during compatible and incompatible interactions with P. sojae and a mock inoculation. The expression data were then used to select two defense-related transcription factors (TFs) belonging to WRKY and RAV families. DNA Affinity Purification and sequencing (DAP-seq) data were obtained for each TF, providing putative DNA binding sites in the soybean genome. These bound sites were used to train Deep Neural Networks with convolutional and recurrent layers to predict new target sites of WRKY and RAV family members in the DEG set. Moreover, we leveraged publicly available Arabidopsis (Arabidopsis thaliana) DAP-seq data for five TF families enriched in our transcriptome analysis to train similar models. These Arabidopsis data-based models were used for cross-species TF binding site prediction on soybean. Finally, we created a gene regulatory network depicting TF-target gene interactions that orchestrate an immune response against P. sojae. Information herein provides novel insight into molecular plant-pathogen interaction and may prove useful in developing soybean cultivars with more durable resistance to P. sojae.

The trans-regulatory landscape of gene networks in plants

The transcriptional effector domains of transcription factors play a key role in controlling gene expression; however, their functional nature is poorly understood, hampering our ability to explore this fundamental dimension of gene regulatory networks. To map the trans-regulatory landscape in a complex eukaryote, we systematically characterized the putative transcriptional effector domains of over 400 Arabidopsis thaliana transcription factors for their capacity to modulate transcription. We demonstrate that transcriptional effector activity can be integrated into gene regulatory networks capable of elucidating the functional dynamics underlying gene expression patterns. We further show how our characterized domains can enhance genome engineering efforts and reveal how plant transcriptional activators share regulatory features conserved across distantly related eukaryotes. Our results provide a framework to systematically characterize the regulatory role of transcription factors at a genome-scale in order to understand the transcriptional wiring of biological systems.

Nitrate, Auxin and Cytokinin-A Trio to Tango

Nitrogen is an important macronutrient required for plant growth and development, thus directly impacting agricultural productivity. In recent years, numerous studies have shown that nitrogen-driven growth depends on pathways that control nitrate/nitrogen homeostasis and hormonal networks that act both locally and systemically to coordinate growth and development of plant organs. In this review, we will focus on recent advances in understanding the role of the plant hormones auxin and cytokinin and their crosstalk in nitrate-regulated growth and discuss the significance of novel findings and possible missing links.

Integrated transcriptomic analysis identifies coordinated responses to nitrogen and phosphate deficiency in rice

Nitrogen (N) and phosphorus (P) are two primary components of fertilizers for crop production. Coordinated acquisition and utilization of N and P are crucial for plants to achieve nutrient balance and optimal growth in a changing rhizospheric nutrient environment. However, little is known about how N and P signaling pathways are integrated. We performed transcriptomic analyses and physiological experiments to explore gene expression profiles and physiological homeostasis in the response of rice (Oryza sativa) to N and P deficiency. We revealed that N and P shortage inhibit rice growth and uptake of other nutrients. Gene Ontology (GO) analysis of differentially expressed genes (DEGs) suggested that N and Pi deficiency stimulate specific different physiological reactions and also some same physiological processes in rice. We established the transcriptional regulatory network between N and P signaling pathways based on all DEGs. We determined that the transcript levels of 763 core genes changed under both N or P starvation conditions. Among these core genes, we focused on the transcription factor gene NITRATE-INDUCIBLE, GARP-TYPE TRANSCRIPTIONAL REPRESSOR 1 (NIGT1) and show that its encoded protein is a positive regulator of P homeostasis and a negative regulator of N acquisition in rice. NIGT1 promoted Pi uptake but inhibited N absorption, induced the expression of Pi responsive genes PT2 and SPX1 and repressed the N responsive genes NLP1 and NRT2.1. These results provide new clues about the mechanisms underlying the interaction between plant N and P starvation responses.

The Arabidopsis transcription factor NLP2 regulates early nitrate responses and integrates nitrate assimilation with energy and carbon skeleton supply

Nitrate signaling improves plant growth under limited nitrate availability and, hence, optimal resource use for crop production. Whereas several transcriptional regulators of nitrate signaling have been identified, including the Arabidopsis thaliana transcription factor NIN-LIKE PROTEIN7 (NLP7), additional regulators are expected to fine-tune this pivotal physiological response. Here, we characterized Arabidopsis NLP2 as a top-tier transcriptional regulator of the early nitrate response gene regulatory network. NLP2 interacts with NLP7 in vivo and shares key molecular features such as nitrate-dependent nuclear localization, DNA-binding motif, and some target genes with NLP7. Genetic, genomic, and metabolic approaches revealed a specific role for NLP2 in the nitrate-dependent regulation of carbon and energy-related processes that likely influence plant growth under distinct nitrogen environments. Our findings highlight the complementarity and specificity of NLP2 and NLP7 in orchestrating a multitiered nitrate regulatory network that links nitrate assimilation with carbon and energy metabolism for efficient nitrogen use and biomass production.

EnsInfer: a simple ensemble approach to network inference outperforms any single method

This study evaluates both a variety of existing base causal inference methods and a variety of ensemble methods. We show that: (i) base network inference methods vary in their performance across different datasets, so a method that works poorly on one dataset may work well on another; (ii) a non-homogeneous ensemble method in the form of a Naive Bayes classifier leads overall to as good or better results than using the best single base method or any other ensemble method; (iii) for the best results, the ensemble method should integrate all methods that satisfy a statistical test of normality on training data. The resulting ensemble model EnsInfer easily integrates all kinds of RNA-seq data as well as new and existing inference methods. The paper categorizes and reviews state-of-the-art underlying methods, describes the EnsInfer ensemble approach in detail, and presents experimental results. The source code and data used will be made available to the community upon publication.

Short-term transcriptomic analysis at organ scale reveals candidate genes involved in low N responses in NUE-contrasting tomato genotypes

BACKGROUND

Understanding the complex regulatory network underlying plant nitrogen (N) responses associated with high Nitrogen Use Efficiency (NUE) is one of the main challenges for sustainable cropping systems. Nitrate (NO₃ ^-), acting as both an N source and a signal molecule, provokes very fast transcriptome reprogramming, allowing plants to adapt to its availability. These changes are genotype- and tissue-specific; thus, the comparison between contrasting genotypes is crucial to uncovering high NUE mechanisms.

METHODS

Here, we compared, for the first time, the spatio-temporal transcriptome changes in both root and shoot of two NUE contrasting tomato genotypes, Regina Ostuni (high-NUE) and UC82 (low-NUE), in response to short-term (within 24 h) low (LN) and high (HN) NO₃ ^- resupply.

RESULTS

Using time-series transcriptome data (0, 8, and 24 h), we identified 395 and 482 N-responsive genes differentially expressed (DEGs) between RO and UC82 in shoot and root, respectively. Protein kinase signaling plant hormone signal transduction, and phenylpropanoid biosynthesis were the main enriched metabolic pathways in shoot and root, respectively, and were upregulated in RO compared to UC82. Interestingly, several N transporters belonging to NRT and NPF families, such as NRT2.3, NRT2.4, NPF1.2, and NPF8.3, were found differentially expressed between RO and UC82 genotypes, which might explain the contrasting NUE performances. Transcription factors (TFs) belonging to several families, such as ERF, LOB, GLK, NFYB, ARF, Zinc-finger, and MYB, were differentially expressed between genotypes in response to LN. A complementary Weighted Gene Co-expression Network Analysis (WGCNA) allowed the identification of LN-responsive co-expression modules in RO shoot and root. The regulatory network analysis revealed candidate genes that might have key functions in short-term LN regulation. In particular, an asparagine synthetase (ASNS), a CBL-interacting serine/threonine-protein kinase 1 (CIPK1), a cytokinin riboside 5'-monophosphate phosphoribohydrolase (LOG8), a glycosyltransferase (UGT73C4), and an ERF2 were identified in the shoot, while an LRR receptor-like serine/threonine-protein kinase (FEI1) and two TFs NF-YB5 and LOB37 were identified in the root.

DISCUSSION

Our results revealed potential candidate genes that independently and/or concurrently may regulate short-term low-N response, suggesting a key role played by cytokinin and ROS balancing in early LN regulation mechanisms adopted by the N-use efficient genotype RO.

Ectopic expression of the AtCDF1 transcription factor in potato enhances tuber starch and amino acid contents and yield under open field conditions

INTRODUCTION

Cycling Dof transcription factors (CDFs) have been involved in different aspects of plant growth and development. In Arabidopsis and tomato, one member of this family (CDF1) has recently been associated with the regulation of primary metabolism and abiotic stress responses, but their roles in crop production under open field conditions remain unknown.

METHODS

In this study, we compared the growth, and tuber yield and composition of plants ectopically expressing the CDF1 gene from Arabidopsis under the control of the 35S promoter with wild-type (WT) potato plants cultured in growth chamber and open field conditions.

RESULTS

In growth chambers, the 35S::AtCDF1 plants showed a greater tuber yield than the WT by increasing the biomass partition for tuber development. Under field conditions, the ectopic expression of CDF1 also promoted the sink strength of the tubers, since 35S::AtCDF1 plants exhibited significant increases in tuber size and weight resulting in higher tuber yield. A metabolomic analysis revealed that tubers of 35S::AtCDF1 plants cultured under open field conditions accumulated higher levels of glucose, starch and amino acids than WT tubers. A comparative proteomic analysis of tubers of 35S::AtCDF1 and WT plants cultured under open field conditions revealed that these changes can be accounted for changes in the expression of proteins involved in energy production and different aspects of C and N metabolism.

DISCUSSION

The results from this study advance our collective understanding of the role of CDFs and are of great interest for the purposes of improving the yield and breeding of crop plants.

Signaling pathways underlying nitrogen transport and metabolism in plants

Nitrogen (N) is an essential macronutrient required for plant growth and crop production. However, N in soil is usually insufficient for plant growth. Thus, chemical N fertilizer has been extensively used to increase crop production. Due to negative effects of N rich fertilizer on the environment, improving N usage has been a major issue in the field of plant science to achieve sustainable production of crops. For that reason, many efforts have been made to elucidate how plants regulate N uptake and utilization according to their surrounding habitat over the last 30 years. Here, we provide recent advances focusing on regulation of N uptake, allocation of N by N transporting system, and signaling pathway controlling N responses in plants. [BMB Reports 2023; 56(2): 56-64].

Building High-Confidence Gene Regulatory Networks by Integrating Validated TF-Target Gene Interactions Using ConnecTF

Many methods are now available to identify or predict the target genes of transcription factors (TFs) in plants. These include experimental approaches such as in vivo or in vitro TF-target gene-binding assays and various methods for identifying regulated targets in mutants, transgenics, or isolated plant cells. In addition, computational approaches are used to infer TF-target gene interactions from the regulatory elements or gene expression changes across treatments. While each of these approaches has now been applied to a large number of TFs from many species, each method has its own limitations which necessitates that multiple data types are integrated to build the most accurate representation of the gene regulatory networks operating in plants. To make the analyses of TF-target interaction datasets available to the broader research community, we have developed the ConnecTF web platform ( https://connectf.org/ ). In this chapter, we describe how ConnecTF can be used to integrate validated and predicted TF-target gene interactions in order to dissect the regulatory role of TFs in developmental and stress response pathways. Using as our examples KN1 and RA1, two well-characterized maize TFs involved in developing floral tissue, we demonstrate how ConnecTF can be used to (1) compare the target genes between TFs, (2) identify direct vs. indirect targets by combining TF-binding and TF-regulation datasets, (3) chart and visualize network paths between TFs and their downstream targets, and (4) prune inferred user networks for high-confidence predicted interactions using validated TF-target gene data. Finally, we provide instructions for setting up a private version of ConnecTF that enables research groups to store and analyze their own TF-target gene interaction datasets.

The TARGET System: Rapid Identification of Direct Targets of Transcription Factors by Gene Regulation in Plant Cells

The TARGET system allows for the rapid identification of direct regulated gene targets of transcription factors (TFs). It employs the transient transformation of plant protoplasts with inducible nuclear entry of the TF and subsequent transcriptomic and/or ChIP-seq analysis. The ability to separate direct TF-target gene regulatory interactions from indirect downstream responses and the significantly shorter amount of time required to perform the assay, compared to the generation of transgenics, make this plant cell-based approach a valuable tool for a higher throughput approach to identify the genome-wide targets of multiple TFs, to build validated transcriptional networks in plants. Here, we describe the use of the TARGET system in Arabidopsis seedling root protoplasts to map the gene regulatory network downstream of transcription factors-of-interest.

Genetic variation underlying differential ammonium and nitrate responses in Arabidopsis thaliana

Nitrogen is an essential element required for plant growth and productivity. Understanding the mechanisms and natural genetic variation underlying nitrogen use in plants will facilitate the engineering of plant nitrogen use to maximize crop productivity while minimizing environmental costs. To understand the scope of natural variation that may influence nitrogen use, we grew 1,135 Arabidopsis thaliana natural genotypes on two nitrogen sources, nitrate and ammonium, and measured both developmental and defense metabolite traits. By using different environments and focusing on multiple traits, we identified a wide array of different nitrogen responses. These responses are associated with numerous genes, most of which were not previously associated with nitrogen responses. Only a small portion of these genes appear to be shared between environments or traits, while most are predominantly specific to a developmental or defense trait under a specific nitrogen source. Finally, by using a large population, we were able to identify unique nitrogen responses, such as preferring ammonium or nitrate, which appear to be generated by combinations of loci rather than a few large-effect loci. This suggests that it may be possible to obtain novel phenotypes in complex nitrogen responses by manipulating sets of genes with small effects rather than solely focusing on large-effect single gene manipulations.

MINI-EX: Integrative inference of single-cell gene regulatory networks in plants

Multicellular organisms, such as plants, are characterized by highly specialized and tightly regulated cell populations, establishing specific morphological structures and executing distinct functions. Gene regulatory networks (GRNs) describe condition-specific interactions of transcription factors (TFs) regulating the expression of target genes, underpinning these specific functions. As efficient and validated methods to identify cell-type-specific GRNs from single-cell data in plants are lacking, limiting our understanding of the organization of specific cell types in both model species and crops, we developed MINI-EX (Motif-Informed Network Inference based on single-cell EXpression data), an integrative approach to infer cell-type-specific networks in plants. MINI-EX uses single-cell transcriptomic data to define expression-based networks and integrates TF motif information to filter the inferred regulons, resulting in networks with increased accuracy. Next, regulons are assigned to different cell types, leveraging cell-specific expression, and candidate regulators are prioritized using network centrality measures, functional annotations, and expression specificity. This embedded prioritization strategy offers a unique and efficient means to unravel signaling cascades in specific cell types controlling a biological process of interest. We demonstrate the stability of MINI-EX toward input data sets with low number of cells and its robustness toward missing data, and show that it infers state-of-the-art networks with a better performance compared with other related single-cell network tools. MINI-EX successfully identifies key regulators controlling root development in Arabidopsis and rice, leaf development in Arabidopsis, and ear development in maize, enhancing our understanding of cell-type-specific regulation and unraveling the roles of different regulators controlling the development of specific cell types in plants.

Bacillus amyloliquefaciens GB03 augmented tall fescue growth by regulating phytohormone and nutrient homeostasis under nitrogen deficiency

Nitrogen is an important nutrient for plant growth and development. Soil microorganisms have been used to curb the imbalance between the limited content of natural environmental nitrogen and the pollution caused by increasing nitrogen fertilizer use in ecologically fragile areas. Bacillus amyloliquefaciens GB03 has been shown to confer growth promotion and abiotic stress tolerance in Arabidopsis thaliana. This study provided a new insight into the role of the plant growth-promoting rhizobacterium B. amyloliquefaciens GB03 as an initiator of defense against nitrogen deficiency in non-leguminous grass tall fescue (Festuca arundinacea). Two-week-old seedlings of tall fescue were grown with or without GB03 for 4 weeks under total nitrogen (3.75 mM NO₃ ^-) or low nitrogen (0.25 mM NO₃ ^-) treatment. Growth parameters, chlorophyll content, endogenous total nitrogen, total phosphorus content, and phytohormone content, including those of auxin indole-3-acetic acid, cytokinin, gibberellic acid, and abscisic acid, were determined at the time of harvest. Tall fescue grown in GB03-inoculated soil was more robust than the non-inoculated controls with respect to plant height, root length, plant biomass, chlorophyll concentration, and nutrient (total nitrogen and total phosphorus) contents under total nitrogen treatment. GB03 increased indole acetic acid content by 24.7%, whereas decreased cytokinin and abscisic acid contents by 28.4% and 26.9%, respectively, under a total nitrogen level. Remarkably, GB03 increased indole acetic acid content by more than 80% and inhibited abscisic acid production by nearly 70% under a low nitrogen level. These results showed, for the first time, that GB03 played a crucial role in mediating NO₃ ^-dependent regulation of tall fescue growth and development, especially revealing the mechanism of soil bacteria improve resistance to nitrogen deficiency stress in non-nitrogen-fixing species.

Bioenergy sorghum stem growth regulation: intercalary meristem localization, development, and gene regulatory network analysis

Bioenergy sorghum is a highly productive drought tolerant C₄ grass that accumulates 80% of its harvestable biomass in approximately 4 m length stems. Stem internode growth is regulated by development, shading, and hormones that modulate cell proliferation in intercalary meristems (IMs). In this study, sorghum stem IMs were localized above the pulvinus at the base of elongating internodes using magnetic resonance imaging, microscopy, and transcriptome analysis. A change in cell morphology/organization occurred at the junction between the pulvinus and internode where LATERAL ORGAN BOUNDARIES (SbLOB), a boundary layer gene, was expressed. Inactivation of an AGCVIII kinase in DDYM (dw2) resulted in decreased SbLOB expression, disrupted IM localization, and reduced internode cell proliferation. Transcriptome analysis identified approximately 1000 genes involved in cell proliferation, hormone signaling, and other functions selectively upregulated in the IM compared with a non-meristematic stem tissue. This cohort of genes is expressed in apical dome stem tissues before localization of the IM at the base of elongating internodes. Gene regulatory network analysis identified connections between genes involved in hormone signaling and cell proliferation. The results indicate that gibberellic acid induces accumulation of growth regulatory factors (GRFs) known to interact with ANGUSTIFOLIA (SbAN3), a master regulator of cell proliferation. GRF:AN3 was predicted to induce SbARF3/ETT expression and regulate SbAN3 expression in an auxin-dependent manner. GRFs and ARFs regulate genes involved in cytokinin and brassinosteroid signaling and cell proliferation. The results provide a molecular framework for understanding how hormone signaling regulates the expression of genes involved in cell proliferation in the stem IM.

Time-series RNA-Seq transcriptome profiling reveals novel insights about cold acclimation and de-acclimation processes in an evergreen shrub of high altitude

The high-altitude alpine regions are characterized by highly variable and harsh environmental conditions. However, relatively little is known about the diverse mechanisms adopted by alpine plants to adapt to these stressful conditions. Here, we studied variation in transcriptome and physiological adjustments occurring across the year at high elevation environments in the leaf tissue of Rhododendron anthopogon, an evergreen shrub of Himalaya. The samples were collected at 12 different time-points, from August until snowfall in November 2017, and then from June to September 2018. It was observed that with a drop in both ambient air temperature and photoperiod towards onset of winter, the freezing resistance of plants increased, resulting in 'cold acclimation'. Further, 'de-acclimation' was associated with a decrease in freezing resistance and increase in photosynthetic efficiency of leaves during spring. A considerable amount of variation was observed in the transcriptome in a time-dependent sequential manner, with a total of 9,881 differentially expressed genes. Based on gene expression profiles, the time-points could be segregated into four clusters directly correlating with the distinct phases of acclimation: non-acclimation (22-August-2017, 14-August-2018, 31-August-2018), early cold acclimation (12-September-2017, 29-September-2017), late cold acclimation (11-October-2017, 23-October-2017, 04-November-2017, 18-September-2018) and de-acclimation (15-June-2018, 28-June-2018, 14-July-2018). Cold acclimation was a gradual process, as indicated by presence of an intermediate stage (early acclimation). However, the plants can by-pass this stage when sudden decrease in temperature is encountered. The maximum variation in expression levels of genes occurred during the transition to de-acclimation, hence was 'transcriptionally' the most active phase. The similar or higher expression levels of genes during de-acclimation in comparison to non-acclimation suggested that molecular functionality is re-initiated after passing through the harsh winter conditions.

A Koshihikari X Oryza rufipogon Introgression Line with a High Capacity to Take up Nitrogen to Maintain Growth and Panicle Development under Low Nitrogen Conditions

Nitrogen (N) is an important macronutrient for plant growth and development. Currently, N fertilizers are required for the efficient production of modern crops such as rice due to their limited capacity to take up N when present at low concentrations. Wild rice represents a useful genetic resource for improving crop responses to low nutrient stress. Here, we describe the isolation and characterization of an introgression line, KRIL37, that carries a small region of the Oryza rufipogon genome in the Oryza sativa L. cv Koshihikari (KH) background. This line was found to grow better under low N conditions and have similar or lower C/N ratios in aerial portions compared to those in the parental KH cultivar, suggesting that KRIL37 has a higher capacity to take up and assimilate N when present at low concentrations. KRIL37 performance in the field was also better than that of KH cultivated without N and fertilizer (-F). Transcriptome analyses of 3-week-old seedlings based on RNA-sequencing revealed that KH induced a wider suite of genes than the tolerant line KRIL37 in response to low N conditions. Some ammonium transporters and N assimilation genes were found to be induced under low N in KRIL37, but not in KH. Our findings suggest that the superior growth performance of KRIL37 under limited N conditions could be due to the expression of wild alleles influencing N uptake and assimilation. Our study demonstrates the potential to use wild rice genomes to improve modern crops for low nutrient tolerance.

An APETALA2/ethylene responsive factor transcription factor GmCRF4a regulates plant height and auxin biosynthesis in soybean

Plant height is one of the key agronomic traits affecting soybean yield. The cytokinin response factors (CRFs), as a branch of the APETALA2/ethylene responsive factor (AP2/ERF) super gene family, have been reported to play important roles in regulating plant growth and development. However, their functions in soybean remain unknown. This study characterized a soybean CRF gene named GmCRF4a by comparing the performance of the homozygous Gmcrf4a-1 mutant, GmCRF4a overexpression (OX) and co-silencing (CS) lines. Phenotypic analysis showed that overexpression of GmCRF4a resulted in taller hypocotyls and epicotyls, more main stem nodes, and higher plant height. While down-regulation of GmCRF4a conferred shorter hypocotyls and epicotyls, as well as a reduction in plant height. The histological analysis results demonstrated that GmCRF4a promotes epicotyl elongation primarily by increasing cell length. Furthermore, GmCRF4a is required for the expression of GmYUCs genes to elevate endogenous auxin levels, which may subsequently enhance stem elongation. Taken together, these observations describe a novel regulatory mechanism in soybean, and provide the basis for elucidating the function of GmCRF4a in auxin biosynthesis pathway and plant heigh regulation in plants.

Amino acid transporter gene TaATLa1 from Triticum aestivum L. improves growth under nitrogen sufficiency and is down regulated under nitrogen deficiency

TaATLa1 was identified to respond to nitrogen deprivation through transcriptome analysis of wheat seedlings. TaATLa1 specifically transports Gln, Glu, and Asp, and affects the biomass of Arabidopsis and wheat. Nitrogen is an essential macronutrient and plays a crucial role in wheat production. Amino acids, the major form of organic nitrogen, are remobilized by amino acid transporters (AATs) in plants. AATs are commonly described as central components of essential developmental processes and yield formation via taking up and transporting amino acids in plants. However, few studies have reported the detailed biochemical properties and biological functions of these AATs in wheat. In this study, key genes encoding AATs were screened from transcriptome analysis of wheat seedlings treated with normal nitrogen (NN) and nitrogen deprivation (ND). Among them, 21 AATs were down-regulated and eight AATs were up-regulated under ND treatment. Among the homoeologs, TaATLa1.1-3A, TaATLa1.1-3B, and TaATLa1.1-3D (TaATLa1.1-3A, -3B, and -3D), belonging to amino acid transporter-like a (ATLa) subfamily, were significantly down-regulated in response to ND in wheat, and accordingly were selected for functional analyses. The results demonstrated that TaATLa1.1-3A, -3B, and -3D effectively transported glutamine (Gln), glutamate (Glu), and aspartate (Asp) in yeast. Overexpression of TaAILa1.1-3A, -3B, and -3D in Arabidopsis thaliana L. significantly increased amino acid content in leaves, storage protein content in seeds and the plant biomass under NN. Knockdown of TaATLa1.1-3A, -3B, and -3D in wheat seedlings resulted in a significant block of amino acid remobilization and growth inhibition. Taken together, TaATLa1.1-3A, -3B, and -3D contribute substantially to Arabidopsis and wheat growth. We propose that TaATLa1.1-3A, -3B, and -3D may participate in the source-sink translocation of amino acid, and they may have profound implications for wheat yield improvement.

Integrating speed breeding with artificial intelligence for developing climate-smart crops

INTRODUCTION

In climate change, breeding crop plants with improved productivity, sustainability, and adaptability has become a daunting challenge to ensure global food security for the ever-growing global population. Correspondingly, climate-smart crops are also the need to regulate biomass production, which is imperative for the maintenance of ecosystem services worldwide. Since conventional breeding technologies for crop improvement are limited, time-consuming, and involve laborious selection processes to foster new and improved crop varieties. An urgent need is to accelerate the plant breeding cycle using artificial intelligence (AI) to depict plant responses to environmental perturbations in real-time.

MATERIALS AND METHODS

The review is a collection of authorized information from various sources such as journals, books, book chapters, technical bulletins, conference papers, and verified online contents.

CONCLUSIONS

Speed breeding has emerged as an essential strategy for accelerating the breeding cycles of crop plants by growing them under artificial light and temperature conditions. Furthermore, speed breeding can also integrate marker-assisted selection and cutting-edged gene-editing tools for early selection and manipulation of essential crops with superior agronomic traits. Scientists have recently applied next-generation AI to delve deeper into the complex biological and molecular mechanisms that govern plant functions under environmental cues. In addition, AIs can integrate, assimilate, and analyze complex OMICS data sets, an essential prerequisite for successful speed breeding protocol implementation to breed crop plants with superior yield and adaptability.

Molecular framework integrating nitrate sensing in root and auxin-guided shoot adaptive responses

Mineral nutrition is one of the key environmental factors determining plant development and growth. Nitrate is the major form of macronutrient nitrogen that plants take up from the soil. Fluctuating availability or deficiency of this element severely limits plant growth and negatively affects crop production in the agricultural system. To cope with the heterogeneity of nitrate distribution in soil, plants evolved a complex regulatory mechanism that allows rapid adjustment of physiological and developmental processes to the status of this nutrient. The root, as a major exploitation organ that controls the uptake of nitrate to the plant body, acts as a regulatory hub that, according to nitrate availability, coordinates the growth and development of other plant organs. Here, we identified a regulatory framework, where cytokinin response factors (CRFs) play a central role as a molecular readout of the nitrate status in roots to guide shoot adaptive developmental response. We show that nitrate-driven activation of NLP7, a master regulator of nitrate response in plants, fine tunes biosynthesis of cytokinin in roots and its translocation to shoots where it enhances expression of CRFs. CRFs, through direct transcriptional regulation of PIN auxin transporters, promote the flow of auxin and thereby stimulate the development of shoot organs.

Systems seed biology to understand and manipulate rice grain quality and nutrition

Rice is one of the most essential crops since it meets the calorific needs of 3 billion people around the world. Rice seed development initiates upon fertilization, leading to the establishment of two distinct filial tissues, the endosperm and embryo, which accumulate distinct seed storage products, such as starch, storage proteins, and lipids. A range of systems biology tools deployed in dissecting the spatiotemporal dynamics of transcriptome data, methylation, and small RNA based regulation operative during seed development, influencing the accumulation of storage products was reviewed. Studies of other model systems are also considered due to the limited information on the rice transcriptome. This review highlights key genes identified through a holistic view of systems biology targeted to modify biochemical composition and influence rice grain quality and nutritional value with the target of improving rice as a functional food.

An Integrated Regulatory Network of mRNAs, microRNAs, and lncRNAs Involved in Nitrogen Metabolism of Moso Bamboo

Nitrogen is a key macronutrient essential for plant growth and development, and its availability has a strong influence on biological processes. Nitrogen fertilizer has been widely applied in bamboo forests in recent decades; however, the mechanism of nitrogen metabolism in bamboo is not fully elucidated. Here, we characterized the morphological, physiological, and transcriptome changes of moso bamboo in response to different schemes for nitrogen addition to illuminate the regulation mechanism of nitrogen metabolism. The appropriate addition of nitrogen improved the chlorophyll content and Pn (net photosynthetic rate) of leaves, the nitrogen and ammonium contents of the seedling roots, the biomass of the whole seedling, the number of lateral roots, and the activity of enzymes involved in nitrogen metabolism in the roots. Based on the whole transcriptome data of the roots, a total of 8,632 differentially expressed mRNAs (DEGs) were identified under different nitrogen additions, such as 52 nitrate transporter genes, 6 nitrate reductase genes, 2 nitrite reductase genes, 2 glutamine synthase genes, 2 glutamate synthase genes (GOGAT), 3 glutamate dehydrogenase genes, and 431 TFs belonging to 23 families. Meanwhile, 123 differentially expressed miRNAs (DEMs) and 396 differentially expressed lncRNAs (DELs) were characterized as nitrogen responsive, respectively. Furthermore, 94 DEM-DEG pairs and 23 DEL-DEG pairs involved in nitrogen metabolism were identified. Finally, a predicted regulatory network of nitrogen metabolism was initially constructed, which included 17 nitrogen metabolic pathway genes, 15 TFs, 4 miRNAs, and 10 lncRNAs by conjoint analysis of DEGs, DEMs, and DELs and their regulatory relationships, which was supported by RNA-seq data and qPCR results. The lncRNA-miRNA-mRNA network provides new insights into the regulation mechanism of nitrogen metabolism in bamboo, which facilitates further genetic improvement for bamboo to adapt to the fluctuating nitrogen environment.

Glutamate: A multifunctional amino acid in plants

Glutamate (Glu) is a versatile metabolite and a signaling molecule in plants. Glu biosynthesis is associated with the primary nitrogen assimilation pathway. The conversion between Glu and 2-oxoglutarate connects Glu metabolism to the tricarboxylic acid cycle, carbon metabolism, and energy production. Glu is the predominant amino donor for transamination reactions in the cell. In addition to protein synthesis, Glu is a building block for tetrapyrroles, glutathione, and folate. Glu is the precursor of γ-aminobutyric acid that plays an important role in balancing carbon/nitrogen metabolism and various cellular processes. Glu can conjugate to the major auxin indole 3-acetic acid (IAA), and IAA-Glu is destined for oxidative degradation. Glu also conjugates with isochorismate for the production of salicylic acid. Accumulating evidence indicates that Glu functions as a signaling molecule to regulate plant growth, development, and defense responses. The ligand-gated Glu receptor-like proteins (GLRs) mediate some of these responses. However, many of the Glu signaling events are GLR-independent. The receptor perceiving extracellular Glu as a danger signal is still unknown. In addition to GLRs, Glu may act on receptor-like kinases or receptor-like proteins to trigger immune responses. Glu metabolism and Glu signaling may entwine to regulate growth, development, and defense responses in plants.

Nitrogen Absorption Pattern Detection and Expression Analysis of Nitrate Transporters in Flowering Chinese Cabbage

Nitrate transporters (NRTs) play an important role in nitrate absorption and internal distribution in plant roots and other parts. Experiments were carried out to explore the sequences and expression characteristics of NRT genes, and their correlation with the N uptake in flowering Chinese cabbage. We have isolated three important BcNRTs (BcNRT1.1, BcNRT1.2, and BcNRT2.1) from flowering Chinese cabbage. Spatio-temporal expression analysis found that BcNRT1.1 and BcNRT2.1 were mainly expressed in roots, while BcNRT1.2 was more expressed in roots than in leaves during vegetative growth and was mainly expressed in leaves during reproductive growth. The NO3− uptake rate of the entire growth period was significantly correlated with BcNRT1.1 and BcNRT1.2 expression in roots. In addition, the total N content was increased with the increase in NO3− concentration in flowering Chinese cabbage. The NH4+ uptake was slightly induced by NH4+, but the total N content had no significant difference under the NH4+ concentration of 1–8 mmol/L. We also found that lower concentrations of NH4+ promoted the expression of BcNRT1.1 and BcNRT1.2 while inhibiting the expression of BcNRT2.1 in the roots of flowering Chinese cabbage. The amount of total N uptake in the treatment with 25/75 of NH4+/NO3− was significantly higher than that of the other two treatments (0/100 and 50/50). In the mixture of NH4+ and NO3−, total N uptake was significantly correlated with the BcNRT1.2 expression. We concluded that mixed nutrition with an NH4+/NO3− of 25/75 could significantly increase total nitrogen uptake in flowering Chinese cabbage, in which two members of the NRT1 subfamily (BcNRT1.1 and BcNRT1.2) might play a major regulatory role in it. This study is a beneficial attempt to dig deeper into the NRT genes resources and lays the foundation for the ultimate use of genetic improvement methods to increase the NUE with less nitrogen fertilizer in flowering Chinese cabbage.

Modeling temporal and hormonal regulation of plant transcriptional response to wounding

Plants respond to wounding stress by changing gene expression patterns and inducing the production of hormones including jasmonic acid. This wounding transcriptional response activates specialized metabolism pathways such as the glucosinolate pathways in Arabidopsis thaliana. While the regulatory factors and sequences controlling a subset of wound-response genes are known, it remains unclear how wound response is regulated globally. Here, we how these responses are regulated by incorporating putative cis-regulatory elements, known transcription factor binding sites, in vitro DNA affinity purification sequencing, and DNase I hypersensitive sites to predict genes with different wound-response patterns using machine learning. We observed that regulatory sites and regions of open chromatin differed between genes upregulated at early and late wounding time-points as well as between genes induced by jasmonic acid and those not induced. Expanding on what we currently know, we identified cis-elements that improved model predictions of expression clusters over known binding sites. Using a combination of genome editing, in vitro DNA-binding assays, and transient expression assays using native and mutated cis-regulatory elements, we experimentally validated four of the predicted elements, three of which were not previously known to function in wound-response regulation. Our study provides a global model predictive of wound response and identifies new regulatory sequences important for wounding without requiring prior knowledge of the transcriptional regulators.

The Arabidopsis transcription factors AtPHL1 and AtHB23 act together promoting carbohydrate transport from pedicel-silique nodes to seeds

Carbohydrates are produced in green tissues through photosynthesis and then transported to sink tissues. Carbon partitioning is a strategic process, fine regulated, involving specific sucrose transporters in each connecting tissue. Here we report that a screening of an Arabidopsis transcription factor (TF) library using the homeodomain-leucine zipper I member AtHB23 as bait, allowed identifying the TF AtPHL1 interacting with the former. An independent Y2H assay, and in planta by BiFC, confirmed such interaction. AtHB23 and AtPHL1 coexpressed in the pedicel-silique nodes and the funiculus. Mutant plants (phl1, and amiR23) showed a marked reduction of lipid content in seeds, although lipid composition did not change compared to the wild type. While protein and carbohydrate contents were not significantly different between mutants and control mature seeds, we observed a reduced carbohydrate content in mutant plants young siliques (7 days after pollination). Moreover, using a CFDA probe, we revealed an impaired transport to the seeds, and the gene encoding the carbohydrate transporters SWEET10 and SWEET11, usually expressed in connecting tissues, was repressed in the amiR23 and phl1 mutant plants. Altogether, the results indicated that AtHB23 and AtPHL1 act together, promoting sucrose transport, and the lack of any of them provoked a reduction in seeds lipid content.