Transcriptional regulatory networks in Arabidopsis thaliana during single and combined stresses

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.

Abiotic stress tolerance in pearl millet: Unraveling molecular mechanisms via transcriptomics

Pearl millet (Pennisetum glaucum (L.)) is a vital cereal crop renowned for its ability to thrive in challenging environmental conditions; however, the molecular mechanisms governing its salt stress tolerance remain poorly understood. To address this gap, next-generation RNA sequencing was conducted to compare gene expression patterns in pearl millet seedlings exposed to salt stress with those grown under normal conditions. Our RNA sequencing analysis focused on shoots from 13-day-old pearl millet plants subjected to either salinity stress (150 mmol of NaCl for 3 days) or thermal stress (50°C for 60 s). Of 36,041 genes examined, 17,271 genes with fold changes ranging from 2.2 to 19.6 were successfully identified. Specifically, 2388 genes were differentially upregulated in response to heat stress, whereas 4327 genes were downregulated. Under salt stress conditions, 2013 genes were upregulated and 4221 genes were downregulated. Transcriptomic analysis revealed four common abiotic KEGG pathways that play crucial roles in the response of pearl millet to salt and heat stress: phenylpropanoid biosynthesis, photosynthesis-antenna proteins, photosynthesis, and plant hormone signal transduction. These metabolic pathways are necessary for pearl millet to withstand and adapt to abiotic stresses caused by salt and heat. Moreover, the pearl millet shoot heat stress group showed specific transcriptomics related to KEEG metabolic pathways such as cytochrome P450, cutin, suberine, and wax biosynthesis, zeatin biosynthesis, crocin biosynthesis, ginsenoside biosynthesis, saponin biosynthesis, and biosynthesis of various plant secondary metabolites. In contrast, pearl millet shoots exposed to salinity stress exhibited transcriptomic changes associated with KEEG metabolic pathways related to carbon fixation in photosynthetic organisms, mismatch repair, and nitrogen metabolism. Our findings underscore the remarkable cross-tolerance of pearl millet to simultaneous salt and heat stress, elucidated through the activation of shared abiotic KEGG pathways. This study emphasizes the pivotal role of transcriptomics analysis in unraveling the molecular responses of pearl millet under abiotic stress conditions.

Gene communities in co-expression networks across different tissues

With the recent availability of tissue-specific gene expression data, e.g., provided by the GTEx Consortium, there is interest in comparing gene co-expression patterns across tissues. One promising approach to this problem is to use a multilayer network analysis framework and perform multilayer community detection. Communities in gene co-expression networks reveal groups of genes similarly expressed across individuals, potentially involved in related biological processes responding to specific environmental stimuli or sharing common regulatory variations. We construct a multilayer network in which each of the four layers is an exocrine gland tissue-specific gene co-expression network. We develop methods for multilayer community detection with correlation matrix input and an appropriate null model. Our correlation matrix input method identifies five groups of genes that are similarly co-expressed in multiple tissues (a community that spans multiple layers, which we call a generalist community) and two groups of genes that are co-expressed in just one tissue (a community that lies primarily within just one layer, which we call a specialist community). We further found gene co-expression communities where the genes physically cluster across the genome significantly more than expected by chance (on chromosomes 1 and 11). This clustering hints at underlying regulatory elements determining similar expression patterns across individuals and cell types. We suggest that KRTAP3-1, KRTAP3-3, and KRTAP3-5 share regulatory elements in skin and pancreas. Furthermore, we find that CELA3A and CELA3B share associated expression quantitative trait loci in the pancreas. The results indicate that our multilayer community detection method for correlation matrix input extracts biologically interesting communities of genes.

Gene communities in co-expression networks across different tissues

With the recent availability of tissue-specific gene expression data, e.g., provided by the GTEx Consortium, there is interest in comparing gene co-expression patterns across tissues. One promising approach to this problem is to use a multilayer network analysis framework and perform multilayer community detection. Communities in gene co-expression networks reveal groups of genes similarly expressed across individuals, potentially involved in related biological processes responding to specific environmental stimuli or sharing common regulatory variations. We construct a multilayer network in which each of the four layers is an exocrine gland tissue-specific gene co-expression network. We develop methods for multilayer community detection with correlation matrix input and an appropriate null model. Our correlation matrix input method identifies five groups of genes that are similarly co-expressed in multiple tissues (a community that spans multiple layers, which we call a generalist community) and two groups of genes that are co-expressed in just one tissue (a community that lies primarily within just one layer, which we call a specialist community). We further found gene co-expression communities where the genes physically cluster across the genome significantly more than expected by chance (on chromosomes 1 and 11). This clustering hints at underlying regulatory elements determining similar expression patterns across individuals and cell types. We suggest that KRTAP3-1, KRTAP3-3, and KRTAP3-5 share regulatory elements in skin and pancreas. Furthermore, we find that CELA3A and CELA3B share associated expression quantitative trait loci in the pancreas. The results indicate that our multilayer community detection method for correlation matrix input extracts biologically interesting communities of genes.

Cellular clarity: a logistic regression approach to identify root epidermal regulators of iron deficiency response

BACKGROUND

Plants respond to stress through highly tuned regulatory networks. While prior works identified master regulators of iron deficiency responses in A. thaliana from whole-root data, identifying regulators that act at the cellular level is critical to a more comprehensive understanding of iron homeostasis. Within the root epidermis complex molecular mechanisms that facilitate iron reduction and uptake from the rhizosphere are known to be regulated by bHLH transcriptional regulators. However, many questions remain about the regulatory mechanisms that control these responses, and how they may integrate with developmental processes within the epidermis. Here, we use transcriptional profiling to gain insight into root epidermis-specific regulatory processes.

RESULTS

Set comparisons of differentially expressed genes (DEGs) between whole root and epidermis transcript measurements identified differences in magnitude and timing of organ-level vs. epidermis-specific responses. Utilizing a unique sampling method combined with a mutual information metric across time-lagged and non-time-lagged windows, we identified relationships between clusters of functionally relevant differentially expressed genes suggesting that developmental regulatory processes may act upstream of well-known Fe-specific responses. By integrating static data (DNA motif information) with time-series transcriptomic data and employing machine learning approaches, specifically logistic regression models with LASSO, we also identified putative motifs that served as crucial features for predicting differentially expressed genes. Twenty-eight transcription factors (TFs) known to bind to these motifs were not differentially expressed, indicating that these TFs may be regulated post-transcriptionally or post-translationally. Notably, many of these TFs also play a role in root development and general stress response.

CONCLUSIONS

This work uncovered key differences in -Fe response identified using whole root data vs. cell-specific root epidermal data. Machine learning approaches combined with additional static data identified putative regulators of -Fe response that would not have been identified solely through transcriptomic profiles and reveal how developmental and general stress responses within the epidermis may act upstream of more specialized -Fe responses for Fe uptake.

Identification of genes associated with abiotic stress tolerance in sweetpotato using weighted gene co-expression network analysis

Sweetpotato, Ipomoea batatas (L.), a key food security crop, is negatively impacted by heat, drought, and salinity stress. The orange-fleshed sweetpotato cultivar "Beauregard" was exposed to heat, salt, and drought treatments for 24 and 48 h to identify genes responding to each stress condition in leaves. Analysis revealed both common (35 up regulated, 259 down regulated genes in the three stress conditions) and unique sets of up regulated (1337 genes by drought, 516 genes by heat, and 97 genes by salt stress) and down regulated (2445 genes by drought, 678 genes by heat, and 204 genes by salt stress) differentially expressed genes (DEGs) suggesting common, yet stress-specific transcriptional responses to these three abiotic stressors. Gene Ontology analysis of down regulated DEGs common to both heat and salt stress revealed enrichment of terms associated with "cell population proliferation" suggestive of an impact on the cell cycle by the two stress conditions. To identify shared and unique gene co-expression networks under multiple abiotic stress conditions, weighted gene co-expression network analysis was performed using gene expression profiles from heat, salt, and drought stress treated 'Beauregard' leaves yielding 18 co-expression modules. One module was enriched for "response to water deprivation," "response to abscisic acid," and "nitrate transport" indicating synergetic crosstalk between nitrogen, water, and phytohormones with genes encoding osmotin, cell expansion, and cell wall modification proteins present as key hub genes in this drought-associated module. This research lays the groundwork for exploring to a further degree, mechanisms for abiotic stress tolerance in sweetpotato.

Transcriptional control of hydrogen peroxide homeostasis regulates ground tissue patterning in the Arabidopsis root

In multicellular organisms, including higher plants, asymmetric cell divisions (ACDs) play a crucial role in generating distinct cell types. The Arabidopsis root ground tissue initially has two layers: endodermis (inside) and cortex (outside). In the mature root, the endodermis undergoes additional ACDs to produce the endodermis itself and the middle cortex (MC), located between the endodermis and the pre-existing cortex. In the Arabidopsis root, gibberellic acid (GA) deficiency and hydrogen peroxide (H2O2) precociously induced more frequent ACDs in the endodermis for MC formation. Thus, these findings suggest that GA and H2O2 play roles in regulating the timing and extent of MC formation. However, details of the molecular interaction between GA signaling and H2O2 homeostasis remain elusive. In this study, we identified the PEROXIDASE 34 (PRX34) gene, which encodes a class III peroxidase, as a molecular link to elucidate the interconnected regulatory network involved in H2O2- and GA-mediated MC formation. Under normal conditions, prx34 showed a reduced frequency of MC formation, whereas the occurrence of MC in prx34 was restored to nearly WT levels in the presence of H2O2. Our results suggest that PRX34 plays a role in H2O2-mediated MC production. Furthermore, we provide evidence that SCARECROW-LIKE 3 (SCL3) regulates H2O2 homeostasis by controlling transcription of PRX34 during root ground tissue maturation. Taken together, our findings provide new insights into how H2O2 homeostasis is achieved by SCL3 to ensure correct radial tissue patterning in the Arabidopsis root.

The PtoTCP20-miR396d-PtoGRF15 module regulates secondary vascular development in Populus

Secondary vascular development is a key biological characteristic of woody plants and the basis of wood formation. Our understanding of gene expression regulation and dynamic changes in microRNAs (miRNAs) during secondary vascular development is still limited. Here we present an integrated analysis of the miRNA and mRNA transcriptome of six phase-specific tissues-the shoot apex, procambium, primary vascular tissue, cambium, secondary phloem, and secondary xylem-in Populus tomentosa. Several novel regulatory modules, including the PtoTCP20-miR396d-PtoGRF15 module, were identified during secondary vascular development in Populus. A series of biochemical and molecular experiments confirmed that PtoTCP20 activated transcription of the miR396d precursor gene and that miR396d targeted PtoGRF15 to downregulate its expression. Plants overexpressing miR396d (35S:miR396d) showed enhanced secondary growth and increased xylem production. Conversely, during the transition from primary to secondary vascular development, plants with downregulated PtoTCP20expression (PtoTCP20-SRDX), downregulated miR396 expression (35S:STTM396), and PtoGRF15 overexpression (35S:PtoGRF15) showed delayed secondary growth. Novel regulatory modules were identified by integrated analysis of the miRNA and mRNA transcriptome, and the regulatory role of the PtoTCP20-miR396d-PtoGRF15 signaling cascade in secondary vascular development was validated in Populus, providing information to support improvements in forest cultivation and wood properties.

Multi-Omics Approaches and Resources for Systems-Level Gene Function Prediction in the Plant Kingdom

In higher plants, the complexity of a system and the components within and among species are rapidly dissected by omics technologies. Multi-omics datasets are integrated to infer and enable a comprehensive understanding of the life processes of organisms of interest. Further, growing open-source datasets coupled with the emergence of high-performance computing and development of computational tools for biological sciences have assisted in silico functional prediction of unknown genes, proteins and metabolites, otherwise known as uncharacterized. The systems biology approach includes data collection and filtration, system modelling, experimentation and the establishment of new hypotheses for experimental validation. Informatics technologies add meaningful sense to the output generated by complex bioinformatics algorithms, which are now freely available in a user-friendly graphical user interface. These resources accentuate gene function prediction at a relatively minimal cost and effort. Herein, we present a comprehensive view of relevant approaches available for system-level gene function prediction in the plant kingdom. Together, the most recent applications and sought-after principles for gene mining are discussed to benefit the plant research community. A realistic tabulation of plant genomic resources is included for a less laborious and accurate candidate gene discovery in basic plant research and improvement strategies.

Time-course transcriptome analysis identifies rewiring patterns of transcriptional regulatory networks in rice under Rhizoctonia solani infection

Sheath Blight (SB) disease in rice is caused by the infection from the fungal pathogen Rhizoctonia solani (R. solani). SB is one of the most severe rice diseases that can cause up to 50% yield losses in rice. Naturally occurring rice varieties resistant to SB have not been reported yet. We have performed a Time-Series RNA-Seq analysis on a widely cultivated rice variety BPT-5204 for identifying transcriptome level response signatures during R. solani infection at 1st, 2nd and 5th day post infection (dpi). In total, 428, 3225 and 1225 genes were differentially expressed in the treated rice plants on 1, 2 and 5 dpi, respectively. GO and KEGG enrichment analysis identified significant processes and pathways differentially altered in the rice plants during the fungal infection. Machine learning and network based integrative approach was used to construct rice Transcriptional Regulatory Networks (TRNs) for the three time points. TRN analysis identified SUB1B, MYB30 and CCA1 as important regulatory hub transcription factors in rice during R. solani infection. Jasmonic acid, salicylic acid, ethylene biogenesis and signaling were induced on infection. SAR was up regulated, while photosynthesis and carbon fixation processes were significantly down regulated. Involvement of MAPK, CYPs, peroxidase, PAL, chitinase genes were also observed in response to the fungal infection. The integrative analysis identified seven putative SB resistance genes differentially regulated in rice during R. solani infection.

A High-Throughput 3'-Tag RNA Sequencing for Large-Scale Time-Series Transcriptome Studies

RNA sequencing (RNA-seq) has proven invaluable for exploring gene expression variation under complex environmental cues. However, the cost of standard RNA-seq (e.g., Illumina TruSeq or NEBNext) remains a barrier for high-throughput applications. 3'-Tag RNA-seq (3'-TagSeq) is a cost-effective solution that permits large-scale experiments. Unlike standard RNA-seq, which generates sequencing libraries for full-length mRNAs, 3'-TagSeq only generates a single fragment from the 3' end of each transcript (a tag read) and quantifies gene expression by tag abundance. Consequently, 3'-TagSeq requires lower sequencing depth (~5 million reads per sample) than standard RNA-seq (~30 million reads per sample), which reduces costs and allows increased technical and biological replication in experiments. Because 3'-TagSeq is considerably cheaper than standard RNA-seq while exhibiting comparable accuracy and reproducibility, researchers focusing on gene expression levels in large or extensive time-series experiments might find 3'-TagSeq to be superior to standard RNA-seq. In this chapter, we describe 3'-TagSeq sequencing library preparation and provide example bioinformatics and statistical analyses of gene expression data.

Transcriptional Regulatory Networks Associate with Early Stages of Potato Virus X Infection of Solanum tuberosum

Potato virus X (PVX) belongs to genus Potexvirus. This study characterizes the cellular transcriptome responses to PVX infection in Russet potato at 2 and 3 days post infection (dpi). Among the 1242 differentially expressed genes (DEGs), 268 genes were upregulated, and 37 genes were downregulated at 2 dpi while 677 genes were upregulated, and 265 genes were downregulated at 3 dpi. DEGs related to signal transduction, stress response, and redox processes. Key stress related transcription factors were identified. Twenty-five pathogen resistance gene analogs linked to effector triggered immunity or pathogen-associated molecular pattern (PAMP)-triggered immunity were identified. Comparative analysis with Arabidopsis unfolded protein response (UPR) induced DEGs revealed genes associated with UPR and plasmodesmata transport that are likely needed to establish infection. In conclusion, this study provides an insight on major transcriptional regulatory networked involved in early response to PVX infection and establishment.

Navigating flower development with a new atlas

In this issue of Developmental Cell, a study presents a 4D atlas integrating live imaging data and expression patterns of 28 regulatory genes in early flower development, which can be used to test gene regulation networks, leading to new hypotheses about the interactions and growth control activities of regulatory genes.

Co-expression network analysis of protein phosphatase 2A (PP2A) genes with stress-responsive genes in Arabidopsis thaliana reveals 13 key regulators

Abiotic and biotic stresses adversely affect plant growth and development and eventually result in less yield and threaten food security worldwide. In plants, several studies have been carried out to understand molecular responses to abiotic and biotic stresses. However, the complete circuitry of stress-responsive genes that plants utilise in response to those environmental stresses are still unknown. The protein phosphatase 2A (PP2A) gene has been known to have a crucial role in abiotic and biotic stresses; but how it regulates the stress response in plants is still not known completely. In this study, we constructed gene co-expression networks of PP2A genes with stress-responsive gene datasets from cold, drought, heat, osmotic, genotoxic, salt, and wounding stresses to unveil their relationships with the PP2A under different conditions of stress. The graph analysis identified 13 hub genes and several influential genes based on closeness centrality score (CCS). Our findings also revealed the count of unique genes present in different settings of stresses and subunits. We also formed clusters of influential genes based on the stress, CCS, and co-expression value. Analysis of cis-regulatory elements (CREs), recurring in promoters of these genes was also performed. Our study has led to the identification of 16 conserved CREs.

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.

Computational solutions for modeling and controlling plant response to abiotic stresses: a review with focus on iron deficiency

Computational solutions enable plant scientists to model protein-mediated stress responses and characterize novel gene functions that coordinate responses to a variety of abiotic stress conditions. Recently, density functional theory was used to study proteins active sites and elucidate enzyme conversion mechanisms involved in iron deficiency responsive signaling pathways. Computational approaches for protein homology modeling and the kinetic modeling of signaling pathways have also resolved the identity and function in proteins involved in iron deficiency signaling pathways. Significant changes in gene relationships under other stress conditions, such as heat or drought stress, have been recently identified using differential network analysis, suggesting that stress tolerance is achieved through asynchronous control. Moreover, the increasing development and use of statistical modeling and systematic modeling of transcriptomic data have provided significant insight into the gene regulatory mechanisms associated with abiotic stress responses. These types of in silico approaches have facilitated the plant science community's future goals of developing multi-scale models of responses to iron deficiency stress and other abiotic stress conditions.

Transcriptome Profiles Reveal the Growth-Promoting Mechanisms of Paenibacillus polymyxa YC0136 on Tobacco (Nicotiana tabacum L.)

Paenibacillus polymyxa is an important member of the plant growth-promoting rhizobacteria. P. polymyxa YC0136 inoculation had beneficial effect on growth promotion and biological control of tobacco (Nicotiana tabacum L.) under field conditions. This study aimed to reveal the growth-promoting mechanisms of strain YC0136. In growth-promotion assays, tobacco plant height was increased by 8.42% and 8.25% at 60 and 90 days, respectively, after inoculation with strain YC0136. Strain YC0136 also promoted the accumulation of tobacco biomass in varying degrees. Following inoculation with strain YC0136, 3,525 and 4,368 tobacco genes were up-regulated and down-regulated, respectively. Strain YC0136 induced the expression of plant hormone-related genes in tobacco, including auxin, cytokinin, and gibberellin, as well as transcription factors related to stress resistance such as WRKY and MYB. In addition, strain YC0136 induced the up-regulation of genes in the phenylpropanoid biosynthesis pathway by 1.51-4.59 times. Interaction with tobacco also induced gene expression changes in strain YC0136, with 286 and 223 genes up-regulated and down-regulated, respectively. Tobacco interaction induced up-regulation of the ilvB gene related to auxin biosynthesis in strain YC0136 by 1.72 times and induced expression of some nutrient transport genes. This study contributes to our understanding of the growth-promoting mechanisms of strain YC0136 on tobacco and provides a theoretical basis for the application of P. polymyxa YC0136 as a biological fertilizer.

Temperature differentially modulates the transcriptome response in Oryza sativa to Xanthomonas oryzae pv. oryzae infection

Bacterial blight is caused by the pathogen Xanthomonas oryzae pv. oryzae (Xoo). Genome scale integrative analysis on the interaction of high and low temperatures on the molecular response signature in rice during the Xoo infection has not been conducted yet. We have analysed a unique RNA-Seq dataset generated on the susceptible rice variety IR24 under combined exposure of Xoo with low 29/21 °C (day/night) and high 35/31 °C (day/night) temperatures. Differentially regulated key genes and pathways in rice plants during both the stress conditions were identified. Differential dynamics of the regulatory network topology showed that WRKY and ERF families of transcription factors play a crucial role during signal crosstalk events in rice plants while responding to combined exposure of Xoo with low temperature vs. Xoo with high temperatures. Our study suggests that upon onset of high temperature, rice plants tend to switch its focus from defence response towards growth and reproduction.

Molecular plant responses to combined abiotic stresses put a spotlight on unknown and abundant genes

Environmental stresses such as drought, heat, and salinity limit plant development and agricultural productivity. While individual stresses have been studied extensively, much less is known about the molecular interaction of responses to multiple stresses. To address this problem, we investigated molecular responses of Arabidopsis to single, double, and triple combinations of salt, osmotic, and heat stresses. A metabolite profiling analysis indicated the production of specific compatible solutes depending on the nature of the stress applied. We found that in combination with other stresses, heat has a dominant effect on global gene expression and metabolite level patterns. Treatments that include heat stress lead to strongly reduced transcription of genes coding for abundant photosynthetic proteins and proteins regulating the cell life cycle, while genes involved in protein degradation are up-regulated. Under combined stress conditions, the plants shifted their metabolism to a survival state characterized by low productivity. Our work provides molecular evidence for the dangers for plant productivity and future world food security posed by heat waves resulting from global warming. We highlight candidate genes, many of which are functionally uncharacterized, for engineering plant abiotic stress tolerance.

Gene Regulatory Network Inference: Connecting Plant Biology and Mathematical Modeling

Plant responses to environmental and intrinsic signals are tightly controlled by multiple transcription factors (TFs). These TFs and their regulatory connections form gene regulatory networks (GRNs), which provide a blueprint of the transcriptional regulations underlying plant development and environmental responses. This review provides examples of experimental methodologies commonly used to identify regulatory interactions and generate GRNs. Additionally, this review describes network inference techniques that leverage gene expression data to predict regulatory interactions. These computational and experimental methodologies yield complex networks that can identify new regulatory interactions, driving novel hypotheses. Biological properties that contribute to the complexity of GRNs are also described in this review. These include network topology, network size, transient binding of TFs to DNA, and competition between multiple upstream regulators. Finally, this review highlights the potential of machine learning approaches to leverage gene expression data to predict phenotypic outputs.

Plant microRNAs: biogenesis, gene silencing, web-based analysis tools and their use as molecular markers

MicroRNAs (miRNAs) are tiny (20-24 nt bp) regulatory non-protein-coding RNA molecules that have been extensively characterized and found important for many physiological and developmental processes. The miss-expression of miRNAs leads to various defects in plants. MicroRNAs repress gene expression by directing mRNA degradation or translational arrest. Several proteins such as PP43A, HYL1, DCL, HST are indispensable role players in promoting miRNA biogenesis in plants. During miRNA biogenesis, lariat RNAs are produced as by-products of pre-mRNA splicing which have a negative role in regulation of miRNA homeostasis. By acting as a decoy and by sequestering to the dicing complex, lariat RNA can prevent the processing of miRNAs. A number of bioinformatic tools with different methodologies are available to identify and validate miRNAs and their targets. Many miRNAs have been reported in different crops for different traits; however, no reports are available on their use in plant breeding. Recently, researchers have developed trait specific miRNA-based molecular markers (miRNA-SSRs/SNP) for many quantitative traits in different plant species. In the future, these molecular markers can be used for plant breeding programs. In this review, a comprehensive up-to-date information is provided on the bioinformatic tools used for analysis of plant miRNAs and their targets, the number of miRNAs, their biogenesis, gene silencing mechanism and miRNA-based molecular markers.

Male Sterility in Maize after Transient Heat Stress during the Tetrad Stage of Pollen Development

Shifts in the duration and intensity of ambient temperature impair plant development and reproduction, particularly male gametogenesis. Stress exposure causes meiotic defects or premature spore abortion in male reproductive organs, leading to male sterility. However, little is known about the mechanisms underlying stress and male sterility. To elucidate these mechanisms, we imposed a moderate transient heat stress on maize (Zea mays) plants at the tetrad stage of pollen development. After completion of pollen development at optimal conditions, stress responses were assessed in mature pollen. Transient heat stress resulted in reduced starch content, decreased enzymatic activity, and reduced pollen germination, resulting in sterility. A transcriptomic comparison pointed toward misregulation of starch, lipid, and energy biosynthesis-related genes. Metabolomic studies showed an increase of Suc and its monosaccharide components, as well as a reduction in pyruvate. Lipidomic analysis showed increased levels of unsaturated fatty acids and decreased levels of saturated fatty acids. In contrast, the majority of genes involved in developmental processes such as those required for auxin and unfolded protein responses, signaling, and cell wall biosynthesis remained unaltered. It is noteworthy that changes in the regulation of transcriptional and metabolic pathway genes, as well as heat stress proteins, remained altered even though pollen could recover during further development at optimal conditions. In conclusion, our findings demonstrate that a short moderate heat stress during the highly susceptible tetrad stage strongly affects basic metabolic pathways and thus generates germination-defective pollen, ultimately leading to severe yield losses in maize.

The plant immune system in heterogeneous environments

The plant immune system inhibits pathogen growth and contributes to shaping a healthy microbial community in the plant body. Plants must appropriately respond to both microbial signals and abiotic factors that are diverse in time and space, and thus, proper integration of these inputs at local and systemic levels is of crucial importance for optimal plant responses and fitness in nature. Here, we review our current knowledge of three properties of the plant immune system, resilience, tunability, and balance, which enable plants to deal with complex cocktails of environmental factors. We also discuss future challenges on the path towards a comprehensive understanding of the interactions between plant immunity and pathogenic, non-pathogenic, and beneficial microbes.

TF2Network: predicting transcription factor regulators and gene regulatory networks in Arabidopsis using publicly available binding site information

A gene regulatory network (GRN) is a collection of regulatory interactions between transcription factors (TFs) and their target genes. GRNs control different biological processes and have been instrumental to understand the organization and complexity of gene regulation. Although various experimental methods have been used to map GRNs in Arabidopsis thaliana, their limited throughput combined with the large number of TFs makes that for many genes our knowledge about regulating TFs is incomplete. We introduce TF2Network, a tool that exploits the vast amount of TF binding site information and enables the delineation of GRNs by detecting potential regulators for a set of co-expressed or functionally related genes. Validation using two experimental benchmarks reveals that TF2Network predicts the correct regulator in 75–92% of the test sets. Furthermore, our tool is robust to noise in the input gene sets, has a low false discovery rate, and shows a better performance to recover correct regulators compared to other plant tools. TF2Network is accessible through a web interface where GRNs are interactively visualized and annotated with various types of experimental functional information. TF2Network was used to perform systematic functional and regulatory gene annotations, identifying new TFs involved in circadian rhythm and stress response.

The histone variant H2A.Z and chromatin remodeler BRAHMA act coordinately and antagonistically to regulate transcription and nucleosome dynamics in Arabidopsis

Plants adapt to environmental changes by regulating transcription and chromatin organization. The histone H2A variant H2A.Z and the SWI2/SNF2 ATPase BRAHMA (BRM) have overlapping roles in positively and negatively regulating environmentally responsive genes in Arabidopsis, but the extent of this overlap was uncharacterized. Both factors have been associated with various changes in nucleosome positioning and stability in different contexts, but their specific roles in transcriptional regulation and chromatin organization need further characterization. We show that H2A.Z and BRM co-localize at thousands of sites, where they interact both cooperatively and antagonistically in transcriptional repression and activation of genes involved in development and responses to environmental stimuli. We identified eight classes of genes that show distinct relationships between H2A.Z and BRM with respect to their roles in transcription. These include activating and silencing transcription both redundantly and antagonistically. We found that H2A.Z contributes to a range of different nucleosome properties, while BRM stabilizes nucleosomes where it binds and destabilizes or repositions flanking nucleosomes. We also found that, at many genes regulated by both BRM and H2A.Z, both factors overlap with binding sites of the light-regulated transcription factor FAR1-Related Sequence 9 (FRS9) and that a subset of these FRS9 binding sites are dependent on H2A.Z and BRM for accessibility. Collectively, we comprehensively characterized the antagonistic and cooperative contributions of H2A.Z and BRM to transcriptional regulation, and illuminated several interrelated roles in chromatin organization. The variability observed in their individual functions implies that both BRM and H2A.Z have more context-dependent roles than previously assumed.

Complex interactions between day length and diurnal patterns of gene expression drive photoperiodic responses in a perennial C4 grass

Photoperiod is a key environmental cue affecting flowering and biomass traits in plants. Key components of the photoperiodic flowering pathway have been identified in many species, but surprisingly few studies have globally examined the diurnal rhythm of gene expression with changes in day length. Using a cost-effective 3'-Tag RNA sequencing strategy, we characterize 9,010 photoperiod responsive genes with strict statistical testing across a diurnal time series in the C₄ perennial grass, Panicum hallii. We show that the vast majority of photoperiod responses are driven by complex interactions between day length and sampling periods. A fine-scale contrast analysis at each sampling time revealed a detailed picture of the temporal reprogramming of cis-regulatory elements and biological processes under short- and long-day conditions. Phase shift analysis reveals quantitative variation among genes with photoperiod-dependent diurnal patterns. In addition, we identify three photoperiod enriched transcription factor families with key genes involved in photoperiod flowering regulatory networks. Finally, coexpression networks analysis of GIGANTEA homolog predicted 1,668 potential coincidence partners, including five well-known GI-interacting proteins. Our results not only provide a resource for understanding the mechanisms of photoperiod regulation in perennial grasses but also lay a foundation to increase biomass yield in biofuel crops.

PropaNet: Time-Varying Condition-Specific Transcriptional Network Construction by Network Propagation

Transcription factor (TF) has a significant influence on the state of a cell by regulating multiple down-stream genes. Thus, experimental and computational biologists have made great efforts to construct TF gene networks for regulatory interactions between TFs and their target genes. Now, an important research question is how to utilize TF networks to investigate the response of a plant to stress at the transcription control level using time-series transcriptome data. In this article, we present a new computational network, PropaNet, to investigate dynamics of TF networks from time-series transcriptome data using two state-of-the-art network analysis techniques, influence maximization and network propagation. PropaNet uses the influence maximization technique to produce a ranked list of TFs, in the order of TF that explains differentially expressed genes (DEGs) better at each time point. Then, a network propagation technique is used to select a group of TFs that explains DEGs best as a whole. For the analysis of Arabidopsis time series datasets from AtGenExpress, we used PlantRegMap as a template TF network and performed PropaNet analysis to investigate transcriptional dynamics of Arabidopsis under cold and heat stress. The time varying TF networks showed that Arabidopsis responded to cold and heat stress quite differently. For cold stress, bHLH and bZIP type TFs were the first responding TFs and the cold signal influenced histone variants, various genes involved in cell architecture, osmosis and restructuring of cells. However, the consequences of plants under heat stress were up-regulation of genes related to accelerating differentiation and starting re-differentiation. In terms of energy metabolism, plants under heat stress show elevated metabolic process and resulting in an exhausted status. We believe that PropaNet will be useful for the construction of condition-specific time-varying TF network for time-series data analysis in response to stress. PropaNet is available at http://biohealth.snu.ac.kr/software/PropaNet.

Abiotic stress induced miRNA-TF-gene regulatory network: A structural perspective

MicroRNAs (miRNAs) and transcription factors (TFs) are the largest families of trans-acting gene regulatory species, which are pivotal players in a complex regulatory network. Recently, extensive research on miRNAs and TFs in agriculture has identified these trans-acting regulatory species, as an effective tool for engineering new crop cultivars to increase yield and quality as well tolerance to environmental stresses but our knowledge of regulatory network is still not sufficient to decipher the exact mechanism. In the current work, stress-specific TF-miRNA-gene network was built for Arabidopsis under drought, cold, salt and waterlogging stress using data from reliable publically available databases; and transcriptome and degradome sequence data analysis by meta-analysis approach. Further network analysis elucidated significantly dense, scale-free, small world and hierarchical backbone of interactions. The various centrality measures highlighted several genes/TF/miRNAs as potential targets for tolerant variety cultivation. This comprehensive regulatory information will accelerate the advancement of current understanding on stress specific transcriptional and post-transcriptional regulatory mechanism and has promising utilizations for experimental biologist who are intended to improve plant crop performance under multiple Abiotic stress environments.

Evolutionary and ecological functional genomics, from lab to the wild

Plant phenotypes are the result of both genetic and environmental forces that act to modulate trait expression. Over the last few years, numerous approaches in functional genomics and systems biology have led to a greater understanding of plant phenotypic variation and plant responses to the environment. These approaches, and the questions that they can address, have been loosely termed evolutionary and ecological functional genomics (EEFG), and have been providing key insights on how plants adapt and evolve. In particular, by bringing these studies from the laboratory to the field, EEFG studies allow us to gain greater knowledge of how plants function in their natural contexts.

Regulatory motifs found in the small heat shock protein (sHSP) gene family in tomato

BACKGROUND

In living organisms, small heat shock proteins (sHSPs) are triggered in response to stress situations. This family of proteins is large in plants and, in the case of tomato (Solanum lycopersicum), 33 genes have been identified, most of them related to heat stress response and to the ripening process. Transcriptomic and proteomic studies have revealed complex patterns of expression for these genes. In this work, we investigate the coregulation of these genes by performing a computational analysis of their promoter architecture to find regulatory motifs known as heat shock elements (HSEs). We leverage the presence of sHSP members that originated from tandem duplication events and analyze the promoter architecture diversity of the whole sHSP family, focusing on the identification of HSEs.

RESULTS

We performed a search for conserved genomic sequences in the promoter regions of the sHSPs of tomato, plus several other proteins (mainly HSPs) that are functionally related to heat stress situations or to ripening. Several computational analyses were performed to build multiple sequence motifs and identify transcription factor binding sites (TFBS) homologous to HSF1AE and HSF21 in Arabidopsis. We also investigated the expression and interaction of these proteins under two heat stress situations in whole tomato plants and in protoplast cells, both in the presence and in the absence of heat shock transcription factor A2 (HsfA2). The results of these analyses indicate that different sHSPs are up-regulated depending on the activation or repression of HsfA2, a key regulator of HSPs. Further, the analysis of protein-protein interaction between the sHSP protein family and other heat shock response proteins (Hsp70, Hsp90 and MBF1c) suggests that several sHSPs are mediating alternative stress response through a regulatory subnetwork that is not dependent on HsfA2.

CONCLUSIONS

Overall, this study identifies two regulatory motifs (HSF1AE and HSF21) associated with the sHSP family in tomato which are considered genomic HSEs. The study also suggests that, despite the apparent redundancy of these proteins, which has been linked to gene duplication, tomato sHSPs showed different up-regulation and different interaction patterns when analyzed under different stress situations.

Principles and characteristics of the Arabidopsis WRKY regulatory network during early MAMP-triggered immunity

During microbe-associated molecular pattern-triggered immunity more than 5000 Arabidopsis genes are significantly altered in their expression, and the question arises, how such an enormous reprogramming of the transcriptome can be regulated in a safe and robust manner? For the WRKY transcription factors (TFs), which are important regulators of numerous defense responses, it appears that they act in a complex regulatory sub-network rather than in a linear fashion, which would be much more vulnerable to gene function loss either by pathogen-derived effectors or by mutations. In this study we employed RNA-seq, mass spectrometry and chromatin immunoprecipitation-seq to find evidence for and uncover principles and characteristics of this network. Upon flg22-treatment, one can distinguish between two sets of WRKY genes: constitutively expressed and induced WRKY genes. Prior to elicitation the induced WRKY genes appear to be maintained in a repressed state mainly by the constitutively expressed WRKY factors, which themselves appear to be regulated by non-WRKY TFs. Upon elicitation, induced WRKYs rapidly bind to induced WRKY gene promoters and by auto- and cross-regulation build up the regulatory network. Maintenance of this flg22-induced network appears highly robust as removal of three key WRKY factors can be physically and functionally compensated for by other WRKY family members.

INDETERMINATE SPIKELET1 Recruits Histone Deacetylase and a Transcriptional Repression Complex to Regulate Rice Salt Tolerance

Perception and transduction of salt stress signals are critical for plant survival, growth, and propagation. Thus, identification of components of the salt stress-signaling pathway is important for rice (Oryza sativa) molecular breeding of salt stress resistance. Here, we report the identification of an apetala2/ethylene response factor transcription factor INDETERMINATE SPIKELET1 (IDS1) and its roles in the regulation of rice salt tolerance. By genetic screening and phenotype analysis, we demonstrated that IDS1 conferred transcriptional repression activity and acted as a negative regulator of salt tolerance in rice. To identify potential downstream target genes regulated by IDS1, we conducted chromatin immunoprecipitation (ChIP) sequencing and ChIP-quantitative PCR assays and found that IDS1 may directly associate with the GCC-box-containing motifs in the promoter regions of abiotic stress-responsive genes, including LEA1 (LATE EMBRYOGENESIS ABUNDANT PROTEIN1) and SOS1 (SALT OVERLY SENSITIVE1), which are key genes regulating rice salt tolerance. IDS1 physically interacted with the transcriptional corepressor topless-related 1 and the histone deacetylase HDA1, contributing to the repression of LEA1 and SOS1 expression. Analyses of histone H3 acetylation status and RNA polymerase II occupation on the promoters of LEA1 and SOS1 further defined the molecular foundation of the transcriptional repression activity of IDS1. Our findings illustrate an epigenetic mechanism by which IDS1 modulates salt stress signaling as well as salt tolerance in rice.

Elucidation and analyses of the regulatory networks of upland and lowland ecotypes of switchgrass in response to drought and salt stresses

Switchgrass is an important bioenergy crop typically grown in marginal lands, where the plants must often deal with abiotic stresses such as drought and salt. Alamo is known to be more tolerant to both stress types than Dacotah, two ecotypes of switchgrass. Understanding of their stress response and adaptation programs can have important implications to engineering more stress tolerant plants. We present here a computational study by analyzing time-course transcriptomic data of the two ecotypes to elucidate and compare their regulatory systems in response to drought and salt stresses. A total of 1,693 genes (target genes or TGs) are found to be differentially expressed and possibly regulated by 143 transcription factors (TFs) in response to drought stress together in the two ecotypes. Similarly, 1,535 TGs regulated by 110 TFs are identified to be involved in response to salt stress. Two regulatory networks are constructed to predict their regulatory relationships. In addition, a time-dependent hidden Markov model is derived for each ecotype responding to each stress type, to provide a dynamic view of how each regulatory network changes its behavior over time. A few new insights about the response mechanisms are predicted from the regulatory networks and the time-dependent models. Comparative analyses between the network models of the two ecotypes reveal key commonalities and main differences between the two regulatory systems. Overall, our results provide new information about the complex regulatory mechanisms of switchgrass responding to drought and salt stresses.

Similar bowtie structures and distinct largest strong components are identified in the transcriptional regulatory networks of Arabidopsis thaliana during photomorphogenesis and heat shock

Photomorphogenesis and heat shock are critical biological processes of plants. A recent research constructed the transcriptional regulatory networks (TRNs) of Arabidopsis thaliana during these processes using DNase-seq. In this study, by strong decomposition, we revealed that each of these TRNs can be represented as a similar bowtie structure with only one non-trivial and distinct strong component. We further identified distinct patterns of variation of a few light-related genes in these bowtie structures during photomorphogenesis. These results suggest that bowtie structure may be a common property of TRNs of plants, and distinct variation patterns of genes in bowtie structures of TRNs during biological processes may reflect distinct functions. Overall, our study provides an insight into the molecular mechanisms underlying photomorphogenesis and heat shock, and emphasizes the necessity to investigate the strong connectivity structures while studying TRNs.

Comparative Proteomic Analysis of Plant Acclimation to Six Different Long-Term Environmental Changes

Plants are constantly challenged in their natural environment by a range of changing conditions. We investigated the acclimation processes and adaptive plant responses to various long-term mild changes and compared them directly within one experimental set-up. Arabidopsis thaliana plants were grown in hydroponic culture for 10 d under controlled abiotic stress (15°C, 25°C, salt and osmotic) and in nutrient deficiency (nitrate and phosphate). Plant growth was monitored and proteomic experiments were performed. Resource allocation between tissues altered during the plants' response. The growth patterns and induced changes of the proteomes indicated that the underlying mechanisms of the adaptation processes are highly specific to the respective environmental condition. Our results indicated differential regulation of response to salt and osmotic treatment, while the proteins in the changed temperature regime showed an inverse, temperature-sensitive control. There was a high correlation of protein level between the nutrient-deficient treatments, but the enriched pathways varied greatly. The proteomic analysis also revealed new insights into the regulation of proteins specific to the shoot and the root. Our investigation revealed unique strategies of plant acclimation to the different applied treatments on a physiological and proteome level, and these strategies are quite distinct in tissues below and above ground.

Chromatin states responsible for the regulation of differentially expressed genes under 60Co~γ ray radiation in rice

Background

The role of histone modifications in the DNA damage response has been extensively studied in non-plant systems, including mammals and yeast. However, there is a lack of detailed evidence showing how chromatin dynamics, either an individual mark or combined chromatin states, participate in regulating differentially expressed genes in the plant DNA damage response.

Results

In this study, we used RNA-seq and ChIP-seq to show that differentially expressed genes (DEGs), in response to ionizing radiation (IR), might be involved in different pathways responsible for the DNA damage response. Moreover, chromatin structures associated with promoters, exons and intergenic regions are significantly affected by IR. Most importantly, either an individual mark or a certain chromatin state was found to be highly correlated with the expression of up-regulated genes. In contrast, only the chromatin states, as opposed to any individual marks tested, are related to the expression of the down-regulated genes.

Conclusions

Our findings demonstrate that IR-related DEGs are modulated by distinct epigenetic mechanisms. Either chromatin states or distinct histone dynamics may act sequentially or in combination in regulating up-regulated genes, but the complex chromatin structure is mainly responsible for the expression of down-regulated genes. Thus, this study provides new insights into how up- and down-regulated genes are epigenetically regulated at the chromatin levels, thereby helping us to understand distinct epigenetic mechanisms that function in the plant DNA damage response.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4172-x) contains supplementary material, which is available to authorized users.

Multilevel Regulation of Abiotic Stress Responses in Plants

The sessile lifestyle of plants requires them to cope with stresses in situ. Plants overcome abiotic stresses by altering structure/morphology, and in some extreme conditions, by compressing the life cycle to survive the stresses in the form of seeds. Genetic and molecular studies have uncovered complex regulatory processes that coordinate stress adaptation and tolerance in plants, which are integrated at various levels. Investigating natural variation in stress responses has provided important insights into the evolutionary processes that shape the integrated regulation of adaptation and tolerance. This review primarily focuses on the current understanding of how transcriptional, post-transcriptional, post-translational, and epigenetic processes along with genetic variation orchestrate stress responses in plants. We also discuss the current and future development of computational tools to identify biologically meaningful factors from high dimensional, genome-scale data and construct the signaling networks consisting of these components.

Alternative splicing complexity contributes to genetic improvement of drought resistance in the rice maintainer HuHan2B

Water-saving and drought-resistantce rice (WDR) breeding practices have greatly increased grain yield and drought resistance. To study the genetic basis of adaptation to drought, transcriptome sequences from the WDR maintainer line HuHan2B and the recurrent parent HanFengB were analyzed for alternative splicing (AS) complexity. Intron retention, the dominant AS type, accounted for 42% of the observed AS events. Differential expression analysis revealed transcripts were preferentially expressed in different varieties and conditions. Based on gene ontology predictions, the biological functions of drought-induced transcripts were significantly enriched in genes involved in transcription regulation, chloroplast components and response to abiotic stimulus in HuHan2B, whereas developmental processes for reproduction were primarily enriched in HanFengB. The regulatory network of transcription factors was driven by cohorts of transcript splicing targets, resulting in more diversified regulatory relationships due to AS complexity than in our previous findings. Moreover, several genes were validated to accumulate novel splicing transcripts in a drought-induced manner. Together, these results suggest that HuHan2B and HanFengB share similar AS features but that a subset of genes with increased levels of AS involved in transcription regulatory networks may contribute an additional level of control for genetic improvement of drought resistance in rice maintainer HuHan2B through breeding.

Differences and commonalities of plant responses to single and combined stresses

In natural or agricultural environments, plants are constantly exposed to a wide range of biotic and abiotic stresses. Given the forecasted global climate changes, plants will cope with heat waves, drought periods and pathogens at the same time or consecutively. Heat and drought cause opposing physiological responses, while pathogens may or may not profit from climate changes depending on their lifestyle. Several studies have been conducted to find stress-specific signatures or stress-independent commonalities. Previously this has been done by comparing different single stress treatments. This approach has been proven difficult since most studies, comparing single and combined stress conditions, have come to the conclusion that each stress treatment results in specific transcriptional changes. Although transcriptional changes at the level of individual genes are highly variable and stress-specific, central metabolic and signaling responses seem to be common, often leading to an overall reduced plant growth. Understanding how specific transcriptional changes are linked to stress adaptations and identifying central hubs controlling this interaction will be the challenge for the coming years. In this review, we will summarize current knowledge on plant responses to different individual and combined stresses and try to find a common thread potentially underlying these responses. We will begin with a brief summary of known physiological, metabolic, transcriptional and hormonal responses to individual stresses, elucidate potential commonalities and conflicts and finally we will describe results obtained during combined stress experiments. Here we will concentrate on simultaneous application of stress conditions but we will also touch consequences of sequential stress treatments.

Predictive Models of Spatial Transcriptional Response to High Salinity

Plants are exposed to a variety of environmental conditions, and their ability to respond to environmental variation depends on the proper regulation of gene expression in an organ-, tissue-, and cell type-specific manner. Although our knowledge of how stress responses are regulated is accumulating, a genome-wide model of how plant transcription factors (TFs) and cis-regulatory elements control spatially specific stress response has yet to emerge. Using Arabidopsis (Arabidopsis thaliana) as a model, we identified a set of 1,894 putative cis-regulatory elements (pCREs) that are associated with high-salinity (salt) up-regulated genes in the root or the shoot. We used these pCREs to develop computational models that can better predict salt up-regulated genes in the root and shoot compared with models based on known TF binding motifs. In addition, we incorporated TF binding sites identified via large-scale in vitro assays, chromatin accessibility, evolutionary conservation, and pCRE combinatorial relationships in machine learning models and found that only consideration of pCRE combinations led to better performance in salt up-regulation prediction in the root and shoot. Our results suggest that the plant organ transcriptional response to high salinity is regulated by a core set of pCREs and provide a genome-wide view of the cis-regulatory code of plant spatial transcriptional responses to environmental stress.

Ancient microRNA families that regulate transcription factors are preferentially preserved during plant radiation

Essential genes are usually less likely to be lost during evolution, whereas dispensable genes are lost more frequently. Integrating sacred lotus and other plant microRNA (miRNA) data, we found different ancient miRNA families that arose before eudicot radiation exhibit different evolutionary trajectories. Those ancient miRNA families with higher copy and target numbers, and older age are more likely to be retained in plant descendants and more conserved in (hairpin-structured) miRNA gene sequences. Interestingly, a large portion of the well conserved miRNA families in plant lineages can target transcription factors (TFs). Also, we found miRNA families that target TFs are preferentially retained after sacred lotus genome duplication. In this article, we provide some points to discuss why miRNA families that regulate TFs are more likely to be preserved in plants.