The biology of time: dynamic responses of cell types to developmental, circadian and environmental cues

Integrative analyses of long and short-read RNA sequencing reveal the spliced isoform regulatory network of seedling growth dynamics in upland cotton

The polyploid genome of cotton has significantly increased the transcript complexity. Recent advances in full-length transcript sequencing are now widely used to characterize the complete landscape of transcriptional events. Such studies in cotton can help us to explore the genetic mechanisms of the cotton seedling growth. Through long-read single-molecule RNA sequencing, this study compared the transcriptomes of three yield contrasting genotypes of upland cotton. Our analysis identified different numbers of spliced isoforms from 31,166, 28,716, and 28,713 genes in SJ48, Z98, and DT8 cotton genotypes, respectively, most of which were novel compared to previous cotton reference transcriptomes, and showed significant differences in the number of exon structures and coding sequence length due to intron retention. Quantification of isoform expression revealed significant differences in expression in the root and leaf of each genotype. An array of key isoform target genes showed protein kinase or phosphorylation functions, and their protein interaction network contained most of the circadian oscillator proteins. Spliced isoforms from the GIGANTEA (GI) protien were differentially regulated in each genotype and might be expected to regulate translational activities, including the sequence and function of target proteins. In addition, these spliced isoforms generate diurnal expression profiles in cotton leaves, which may alter the transcriptional regulatory network of seedling growth. Silencing of the novel spliced GI isoform Gh_A02G0645_N17 significantly affected biomass traits, contributed to variable growth, and increased transcription of the early flowering pathway gene ELF in cotton. Our high-throughput hybrid sequencing results will be useful to dissect functional differences among spliced isoforms in the polyploid cotton genome.

Streamlined spatial and environmental expression signatures characterize the minimalist duckweed Wolffia australiana

Single-cell genomics permits a new resolution in the examination of molecular and cellular dynamics, allowing global, parallel assessments of cell types and cellular behaviors through development and in response to environmental circumstances, such as interaction with water and the light-dark cycle of the Earth. Here, we leverage the smallest, and possibly most structurally reduced, plant, the semiaquatic Wolffia australiana, to understand dynamics of cell expression in these contexts at the whole-plant level. We examined single-cell-resolution RNA-sequencing data and found Wolffia cells divide into four principal clusters representing the above- and below-water-situated parenchyma and epidermis. Although these tissues share transcriptomic similarity with model plants, they display distinct adaptations that Wolffia has made for the aquatic environment. Within this broad classification, discrete subspecializations are evident, with select cells showing unique transcriptomic signatures associated with developmental maturation and specialized physiologies. Assessing this simplified biological system temporally at two key time-of-day (TOD) transitions, we identify additional TOD-responsive genes previously overlooked in whole-plant transcriptomic approaches and demonstrate that the core circadian clock machinery and its downstream responses can vary in cell-specific manners, even in this simplified system. Distinctions between cell types and their responses to submergence and/or TOD are driven by expression changes of unexpectedly few genes, characterizing Wolffia as a highly streamlined organism with the majority of genes dedicated to fundamental cellular processes. Wolffia provides a unique opportunity to apply reductionist biology to elucidate signaling functions at the organismal level, for which this work provides a powerful resource.

The Oryza sativa transcriptome responds spatiotemporally to polystyrene nanoplastic stress

Nanoplastic represents an emerging abiotic stress facing modern agriculture, impacting global crop production. However, the molecular response of crop plants to this stress remains poorly understood at a spatiotemporal resolution. We therefore used RNA sequencing to profile the transcriptome expressed in rice (Oryza sativa) root and leaf organs at 1, 2, 4, and 8 d post exposure with nanoplastic. We revealed a striking similarity between the rice biomass dynamics in aboveground parts to that in belowground parts during nanoplastic stress, but transcriptome did not. At the global transcriptomic level, a total of 2332 differentially expressed genes were identified, with the majority being spatiotemporal specific, reflecting that nanoplastics predominantly regulate three processes in rice seedlings: (1) down-regulation of chlorophyll biosynthesis, photosynthesis, and starch, sucrose and nitrogen metabolism, (2) activation of defense responses such as brassinosteroid biosynthesis and phenylpropanoid biosynthesis, and (3) modulation of jasmonic acid and cytokinin signaling pathways by transcription factors. Notably, the genes involved in plant-pathogen interaction were shown to be successively modulated by both root and leaf organs, particularly plant disease defense genes (OsWRKY24, OsWRKY53, Os4CL3, OsPAL4, and MPK5), possibly indicating that nanoplastics affect rice growth indirectly through other biota. Finally, we associated biomass phenotypes with the temporal reprogramming of rice transcriptome by weighted gene co-expression network analysis, noting a significantly correlation with photosynthesis, carbon metabolism, and phenylpropanoid biosynthesis that may reflect the mechanisms of biomass reduction. Functional analysis further identified PsbY, MYB, cytochrome P450, and AP2/ERF as hub genes governing these pathways. Overall, our work provides the understanding of molecular mechanisms of rice in response to nanoplastics, which in turn suggests how rice might behave in a nanoplastic pollution scenario.

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.

Alternative splicing: An efficient regulatory approach towards plant developmental plasticity

Alternative splicing (AS) is a gene regulatory mechanism that plants adapt to modulate gene expression (GE) in multiple ways. AS generates alternative isoforms of the same gene following various development and environmental stimuli, increasing transcriptome plasticity and proteome complexity. AS controls the expression levels of certain genes and regulates GE networks that shape plant adaptations through nonsense-mediated decay (NMD). This review intends to discuss AS modulation, from interaction with noncoding RNAs to the established roles of splicing factors (SFs) in response to endogenous and exogenous cues. We aim to gather such studies that highlight the magnitude and impact of AS, which are not always clear from individual articles, when AS is increasing in individual genes and at a global level. This work also anticipates making plant researchers know that AS is likely to occur in their investigations and that dynamic changes in AS and their effects must be frequently considered. We also review our understanding of AS-mediated posttranscriptional modulation of plant stress tolerance and discuss its potential application in crop improvement in the future. This article is categorized under: RNA Processing > Splicing Regulation/Alternative Splicing RNA Processing > Splicing Mechanisms RNA-Based Catalysis > RNA Catalysis in Splicing and Translation.

Deciphering Macromolecular Interactions Involved in Abiotic Stress Signaling: A Review of Bioinformatics Analysis

Plant functioning and responses to abiotic stresses largely involve regulations at the transcriptomic level via complex interactions of signal molecules, signaling cascades, and regulators. Nevertheless, all the signaling networks involved in responses to abiotic stresses have not yet been fully established. The in-depth analysis of transcriptomes in stressed plants has become a relevant state-of-the-art methodology to study these regulations and signaling pathways that allow plants to cope with or attempt to survive abiotic stresses. The plant science and molecular biology community has developed databases about genes, proteins, protein-protein interactions, protein-DNA interactions and ontologies, which are valuable sources of knowledge for deciphering such regulatory and signaling networks. The use of these data and the development of bioinformatics tools help to make sense of transcriptomic data in specific contexts, such as that of abiotic stress signaling, using functional biological approaches. The aim of this chapter is to present and assess some of the essential online tools and resources that will allow novices in bioinformatics to decipher transcriptomic data in order to characterize the cellular processes and functions involved in abiotic stress responses and signaling. The analysis of case studies further describes how these tools can be used to conceive signaling networks on the basis of transcriptomic data. In these case studies, particular attention was paid to the characterization of abiotic stress responses and signaling related to chemical and xenobiotic stressors.

Time of Day Analysis over a Field Grown Developmental Time Course in Rice

Plants integrate time of day (TOD) information over an entire season to ensure optimal growth, flowering time, and grain fill. However, most TOD expression studies have focused on a limited number of combinations of daylength and temperature under laboratory conditions. Here, an Oryza sativa (rice) expression study that followed TOD expression in the field over an entire growing season was re-analyzed. Similar to Arabidopsis thaliana, almost all rice genes have a TOD-specific expression over the developmental time course. As has been suggested in other grasses, thermocycles were a stronger cue for TOD expression than the photocycles over the growing season. All the core circadian clock genes display consistent TOD expression over the season with the interesting exception that the two grass paralogs of EARLY FLOWERING 3 (ELF3) display a distinct phasing based on the interaction between thermo- and photo-cycles. The dataset also revealed how specific pathways are modulated to distinct TOD over the season consistent with the changing biology. The data presented here provide a resource for researchers to study how TOD expression changes under natural conditions over a developmental time course, which will guide approaches to engineer more resilient and prolific crops.

Transcriptional regulation of plant innate immunity

Transcriptional reprogramming is an integral part of plant immunity. Tight regulation of the immune transcriptome is essential for a proper response of plants to different types of pathogens. Consequently, transcriptional regulators are proven targets of pathogens to enhance their virulence. The plant immune transcriptome is regulated by many different, interconnected mechanisms that can determine the rate at which genes are transcribed. These include intracellular calcium signaling, modulation of the redox state, post-translational modifications of transcriptional regulators, histone modifications, DNA methylation, modulation of RNA polymerases, alternative transcription inititation, the Mediator complex and regulation by non-coding RNAs. In addition, on their journey from transcription to translation, mRNAs are further modulated through mechanisms such as nuclear RNA retention, storage of mRNA in stress granules and P-bodies, and post-transcriptional gene silencing. In this review, we highlight the latest insights into these mechanisms. Furthermore, we discuss some emerging technologies that promise to greatly enhance our understanding of the regulation of the plant immune transcriptome in the future.