Does Gene Expression Noise Play a Functional Role in Plants?

A dose-dependent bimodal switch by homologous Aux/IAA transcriptional repressors

Combinatorial interactions between different regulators diversify and enrich the chance of transcriptional regulation in eukaryotic cells. However, a dose-dependent functional switch of homologous transcriptional repressors has rarely been reported. Here, we show that SHY2, an auxin/indole-3-acetic acid (Aux/IAA) repressor, exhibits a dose-dependent bimodal role in auxin-sensitive root-hair growth and gene transcription in Arabidopsis, whereas other Aux/IAA homologs consistently repress the auxin responses. The co-repressor (TOPLESS [TPL])-binding affinity of a bimodal Aux/IAA was lower than that of a consistently repressing Aux/IAA. The switch of a single amino acid residue in the TPL-binding motif between the bimodal form and the consistently repressing form switched their TPL-binding affinity and transcriptional and biological roles in auxin responses. Based on these data, we propose a model whereby competition between homologous repressors with different co-repressor-binding affinities could generate a bimodal output at the transcriptional and developmental levels.

Bet-hedging and variability in plant development: seed germination and beyond

When future conditions are unpredictable, bet-hedging strategies can be advantageous. This can involve isogenic individuals producing different phenotypes, under the same environmental conditions. Ecological studies provide evidence that variability in seed germination time has been selected for as a bet-hedging strategy. We demonstrate how variability in germination time found in Arabidopsis could function as a bet-hedging strategy in the face of unpredictable lethal stresses. Despite a body of knowledge on how the degree of seed dormancy versus germination is controlled, relatively little is known about how differences between isogenic seeds in a batch are generated. We review proposed mechanisms for generating variability in germination time and the current limitations and new possibilities for testing the model predictions. We then look beyond germination to the role of variability in seedling and adult plant growth and review new technologies for quantification of noisy gene expression dynamics. We discuss evidence for phenotypic variability in plant traits beyond germination being under genetic control and propose that variability in stress response gene expression could function as a bet-hedging strategy. We discuss open questions about how noisy gene expression could lead to between-plant heterogeneity in gene expression and phenotypes. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

Suppression of pyrrolidine ring biosynthesis and its effects on gene expression and subsequent accumulation of anatabine in leaves of tobacco (N. tabacum L.)

BACKGROUND

Anatabine, although being one of four major tobacco alkaloids, is never accumulated in high quantity in any of the naturally occurring species from the Nicotiana genus. Previous studies therefore focused on transgenic approaches to synthetize anatabine, most notably by generating transgenic lines with suppressed putrescine methyltransferase (PMT) activity. This led to promising results, but the global gene expression of plants with such distinct metabolism has not been analyzed. In the current study, we describe how these plants respond to topping and the downstream effects on alkaloid biosynthesis.

RESULTS

The surge in anatabine accumulation in PMT transgenic lines after topping treatment and its effects on gene expression changes were analyzed. The results revealed increases in expression of isoflavone reductase-like (A622) and berberine bridge-like enzymes (BBLs) oxidoreductase genes, previously shown to be crucial for the final steps of nicotine biosynthesis. We also observed significantly higher methylputrescine oxidase (MPO) expression in all plants subjected to topping treatment. In order to investigate if MPO suppression would have the same effects as that of PMT, we generated transgenic plants. These plants with suppressed MPO expression showed an almost complete drop in leaf nicotine content, whereas leaf anatabine was observed to increase by a factor of ~ 1.6X.

CONCLUSION

Our results are the first concrete evidence that suppression of MPO leads to decreased nicotine in favor of anatabine in tobacco roots and that this anatabine is successfully transported to tobacco leaves. Alkaloid transport in plants remains to be investigated to higher detail due to high variation of its efficiency among Nicotiana species and varieties of tobacco. Our research adds important step to better understand pyrrolidine ring biosynthesis and its effects on gene expression and subsequent accumulation of anatabine.

Large-scale analysis and computer modeling reveal hidden regularities behind variability of cell division patterns in Arabidopsis thaliana embryogenesis

Noise plays a major role in cellular processes and in the development of tissues and organs. Several studies have examined the origin, the integration or the accommodation of noise in gene expression, cell growth and elaboration of organ shape. By contrast, much less is known about variability in cell division plane positioning, its origin and links with cell geometry, and its impact on tissue organization. Taking advantage of the first-stereotyped-then-variable division patterns in the embryo of the model plant Arabidopsis thaliana, we combined 3D imaging and quantitative cell shape and cell lineage analysis together with mathematical and computer modeling to perform a large-scale, systematic analysis of variability in division plane orientation. Our results reveal that, paradoxically, variability in cell division patterns of Arabidopsis embryos is accompanied by a progressive reduction of heterogeneity in cell shape topology. The paradox is solved by showing that variability operates within a reduced repertoire of possible division plane orientations that is related to cell geometry. We show that in several domains of the embryo, a recently proposed geometrical division rule recapitulates observed variable patterns, suggesting that variable patterns emerge from deterministic principles operating in a variable geometrical context. Our work highlights the importance of emerging patterns in the plant embryo under iterated division principles, but also reveal domains where deviations between rule predictions and experimental observations point to additional regulatory mechanisms.

Transcriptional noise adjusted for expression levels reveals genes with high transcriptional noise that are highly expressed, functionally related, and co-regulated in yeast

Understanding the relationship between variability in single-cell and non-single-cell gene expression studies will aid in understanding the role of and mechanisms that lead to variability in biological systems. Studies on the variation of gene expression levels in yeast normally focus on single cells and use the coefficient of variance (CV) as a measure of noise. The CV is typically negatively correlated with gene expression levels, so most of the studies using yeast find that genes with high transcriptional noise are lowly expressed. We find adjusting noise for expression levels using linear/natural log polynomial, and local fits and analyzing many non-single-cell RNA-seq sets identifies genes with high median transcriptional noise that are different than those that have high median CVs. Interestingly, these genes are heavily regulated by transcription factors that are related to variability and stochastic processes based on single-cell studies, including Msn2p, Msn4p, Hsf1p, and Crz1p but are not associated with genes with high median CVs based on non-single-cell gene expression data. In addition, adjusting noise for expression levels in a single-cell RNA-seq data set adds value by finding genes that have noisy gene expression levels and their associated transcription factors that are not found to be associated with genes with high CVs in the single-cell expression data or a comparable non-single-cell gene expression data. Lastly, S. cerevisiae genes with noisy expression tend to have orthologs with noisy gene expression in C. albicans, indicating transcriptional noise is evolutionarily conserved.

Organizing your space: The potential for integrating spatial transcriptomics and 3D imaging data in plants

Plant cells communicate information for the regulation of development and responses to external stresses. A key form of this communication is transcriptional regulation, accomplished via complex gene networks operating both locally and systemically. To fully understand how genes are regulated across plant tissues and organs, high resolution, multi-dimensional spatial transcriptional data must be acquired and placed within a cellular and organismal context. Spatial transcriptomics (ST) typically provides a two-dimensional spatial analysis of gene expression of tissue sections that can be stacked to render three-dimensional data. For example, X-ray and light-sheet microscopy provide sub-micron scale volumetric imaging of cellular morphology of tissues, organs, or potentially entire organisms. Linking these technologies could substantially advance transcriptomics in plant biology and other fields. Here, we review advances in ST and 3D microscopy approaches and describe how these technologies could be combined to provide high resolution, spatially organized plant tissue transcript mapping.

Biotinylated subunit of 3-methylcrotonyl-CoA carboxylase encoding gene (AtMCCA) participating in Arabidopsis resistance to carbonate Stress by transcriptome analysis

Soil salinization is a major factor impacting modern agricultural production, and alkaline soils contain large amounts of NaHCO₃. Therefore, understanding plant tolerance to high levels of NaHCO₃ is essential. In this study, a transcriptome analysis of shoot and root tissues of wild-type Arabidopsis thaliana was conducted at 0, 4, 12, 24 and 48 h after exposure to a 3 mM NaHCO₃ stress. We focused on differentially expressed genes (DEGs) in roots identified in the early stages (4 h and 12 h) of the NaHCO₃ stress response that were enriched in GO term, carboxylic acid metabolic process, and utilize HCO₃^-. Six genes were identified that exhibited similar expression patterns in both the RNA-seq and qRT-PCR data. We also characterized the phenotypic response of AtMCCA-overexpressing plants to carbonate stress, and found that the ability of AtMCCA-overexpressing plants to tolerate carbonate stress was enhanced by the addition of biotin to the growth medium.

Noise-induced quasiperiod and period switching

We employ a typical genetic circuit model to explore how noise can influence dynamic structure. With the increase of a key interactive parameter, the model will deterministically go through two bifurcations and three dynamic structure regions. We find that a quasiperiodic component, which is not allowed by deterministic dynamics, will be generated by noise inducing in the first two regions, and this quasiperiod will be more and more stable along with the increase in noise. In particular, in the second region the quasiperiod will compete with a stable limit cycle and perform a new transient rhythm. Furthermore, we ascertain the entropy production rate and the heat dissipation rate, and discover a minimal value with theoretical elucidation. In the end, we unveil the mechanism of the formation of quasiperiods, and show a practical biological example. We expect this work to be helpful in solving some biological or ecological problems, such as the genetic origin of periodical cicadas and population dynamics with fluctuation.

Plant RNA-mediated gene regulatory network

Not all transcribed RNAs are protein-coding RNAs. Many of them are non-protein-coding RNAs in diverse eukaryotes. However, some of them seem to be non-functional and are resulted from spurious transcription. A lot of non-protein-coding transcripts have a significant function in the translation process. Gene expressions depend on complex networks of diverse gene regulatory pathways. Several non-protein-coding RNAs regulate gene expression in a sequence-specific system either at the transcriptional level or post-transcriptional level. They include a significant part of the gene expression regulatory network. RNA-mediated gene regulation machinery is evolutionarily ancient. They well-evolved during the evolutionary time and are becoming much more complex than had been expected. In this review, we are trying to summarizing the current knowledge in the field of RNA-mediated gene silencing.

Plant Cell Identity in the Era of Single-Cell Transcriptomics

High-throughput single-cell transcriptomic approaches have revolutionized our view of gene expression at the level of individual cells, providing new insights into their heterogeneity, identities, and functions. Recently, technical challenges to the application of single-cell transcriptomics to plants have been overcome, and many plant organs and tissues have now been subjected to analyses at single-cell resolution. In this review, we describe these studies and their impact on our understanding of the diversity, differentiation, and activities of plant cells. We particularly highlight their impact on plant cell identity, including unprecedented views of cell transitions and definitions of rare and novel cell types. We also point out current challenges and future opportunities for the application and analyses of single-cell transcriptomics in plants. Expected final online publication date for the Annual Review of Genetics, Volume 55 is November 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Potential Markers for Selecting Self-Eliminating Apple Genotypes

The heavy blooming of apple trees results in the inefficient usage of energy and nutritional material, and additional expenditure on fruitlet thinning is required to maintain fruit quality. A possible solution for controlling the fruit load on trees is the development of new cultivars that self-eliminate excess fruitlets, thus controlling yield. The aim of our study was to identify biological differences in apple cultivars in terms of blooming intensity and fruitlet load self-regulation. In total, 19 apple cultivars were studied in the years 2015–2017. The dynamics of fruitlet self-elimination, seed development in fruitlets and fruits, photosynthetic parameters, carbohydrates, and plant hormones were evaluated. We established that apple cultivars self-eliminating a small number of fruitlets need a lower number of well-developed seeds in fruit, and their number of leaves and area per fruit on a bearing branch are larger, compared to cultivars, self-eliminating large numbers of fruitlets. A higher carbohydrate amount in the leaves may be related to smaller fruitlet self-elimination. The amount of auxin and a high indole-3-acetic acid/zeatin ratio between leaves of cultivar groups with heavy blooming were higher than in cultivars with moderate blooming. A lower amount of abscisic acid was found in heavy-blooming cultivars during drought stress. All these parameters may be used as markers for the selection of different apple genotypes that self-eliminate fruitlets.

Quantitative imaging of RNA polymerase II activity in plants reveals the single-cell basis of tissue-wide transcriptional dynamics

The responses of plants to their environment are often dependent on the spatiotemporal dynamics of transcriptional regulation. While live-imaging tools have been used extensively to quantitatively capture rapid transcriptional dynamics in living animal cells, the lack of implementation of these technologies in plants has limited concomitant quantitative studies in this kingdom. Here, we applied the PP7 and MS2 RNA-labelling technologies for the quantitative imaging of RNA polymerase II activity dynamics in single cells of living plants as they respond to experimental treatments. Using this technology, we counted nascent RNA transcripts in real time in Nicotiana benthamiana (tobacco) and Arabidopsis thaliana. Examination of heat shock reporters revealed that plant tissues respond to external signals by modulating the proportion of cells that switch from an undetectable basal state to a high-transcription state, instead of modulating the rate of transcription across all cells in a graded fashion. This switch-like behaviour, combined with cell-to-cell variability in transcription rate, results in mRNA production variability spanning three orders of magnitude. We determined that cellular heterogeneity stems mainly from stochasticity intrinsic to individual alleles instead of variability in cellular composition. Together, our results demonstrate that it is now possible to quantitatively study the dynamics of transcriptional programs in single cells of living plants.

Time Will Tell: Intercellular Communication in the Plant Clock

Multicellular organisms have evolved local and long-distance signaling mechanisms to synchronize development and response to stimuli among a complex network of cells, tissues, and organs. Biological timekeeping is one such activity that is suggested to be coordinated within an organism to anticipate and respond to daily and seasonal patterns in the environment. New research into the plant clock suggests circadian rhythms are communicated between cells and across long distances. However, further clarity is required on the nature of the signaling molecules and the mechanisms underlying signal translocation. Here we summarize the roles and properties of tissue-specific circadian rhythms, discuss the evidence for local and long-distance clock communication, and evaluate the potential signaling molecules and transport mechanisms involved in this system.

The Arabidopsis thaliana E3 Ubiquitin Ligase BRIZ Functions in Abscisic Acid Response

The ubiquitin system is essential for multiple hormone signaling pathways in plants. Here, we show that the Arabidopsis thaliana E3 ligase BRIZ, a heteromeric ligase that consists minimally of BRIZ1 and BRIZ2 proteins, functions in abscisic acid (ABA) signaling or response. briz1 and briz2 homozygous mutants either fail to germinate or emerge later than wild-type seedlings, with little cotyledon expansion or root elongation and no visible greening. Viability staining indicates that briz1 and briz2 embryos are alive but growth-arrested. Germination of briz mutants is improved by addition of the carotenoid biosynthetic inhibitor fluridone or gibberellic acid (GA3), and briz mutants have improved development in backgrounds deficient in ABA synthesis (gin1-3/aba2) or signaling (abi5-7). Endogenous ABA is not higher in briz2 seeds compared to wild-type seeds, and exogenous ABA does not affect BRIZ mRNAs in imbibed seeds. These results indicate that briz embryos are hypersensitive to ABA and that under normal growth conditions, BRIZ acts to suppress ABA signaling or response. ABA signaling and sugar signaling are linked, and we found that briz1 and briz2 mutants excised from seed coats are hypersensitive to sucrose. Although briz single mutants do not grow to maturity, we were able to generate mature briz2-3 abi5-7 double mutant plants that produced seeds. These seeds are more sensitive to exogenous sugar and are larger than seeds from sibling abi5-7 BRIZ2/briz2-3 plants, suggesting that BRIZ has a parental effect on seed development. From these data, we propose a model in which the BRIZ E3 ligase suppresses ABA responses during seed maturation and germination and early seedling establishment.

Co-expression Networks From Gene Expression Variability Between Genetically Identical Seedlings Can Reveal Novel Regulatory Relationships

Co-expression networks are a powerful tool to understand gene regulation. They have been used to identify new regulation and function of genes involved in plant development and their response to the environment. Up to now, co-expression networks have been inferred using transcriptomes generated on plants experiencing genetic or environmental perturbation, or from expression time series. We propose a new approach by showing that co-expression networks can be constructed in the absence of genetic and environmental perturbation, for plants at the same developmental stage. For this, we used transcriptomes that were generated from genetically identical individual plants that were grown under the same conditions and for the same amount of time. Twelve time points were used to cover the 24-h light/dark cycle. We used variability in gene expression between individual plants of the same time point to infer a co-expression network. We show that this network is biologically relevant and use it to suggest new gene functions and to identify new targets for the transcriptional regulators GI, PIF4, and PRR5. Moreover, we find different co-regulation in this network based on changes in expression between individual plants, compared to the usual approach requiring environmental perturbation. Our work shows that gene co-expression networks can be identified using variability in gene expression between individual plants, without the need for genetic or environmental perturbations. It will allow further exploration of gene regulation in contexts with subtle differences between plants, which could be closer to what individual plants in a population might face in the wild.

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.