A KDELR-mediated ER-retrieval system modulates mitochondrial functions via the unfolded protein response in fission yeast.

KDELR (Erd2 [ER retention defective 2] in yeasts) is a receptor protein that retrieves endoplasmic reticulum (ER)-resident proteins from the Golgi apparatus. However, the role of the KDELR-mediated ER-retrieval system in regulating cellular homeostasis remains elusive. Here, we show that the absence of Erd2 triggers the unfolded protein response (UPR) and enhances mitochondrial respiration and reactive oxygen species in an UPR-dependent manner in the fission yeast Schizosaccharomyces pombe. Moreover, we perform transcriptomic analysis and find that the expression of genes related to mitochondrial respiration and the tricarboxylic acid cycle is upregulated in a UPR-dependent manner in cells lacking Erd2. The increased mitochondrial respiration and reactive oxygen species production is required for cell survival in the absence of Erd2. Therefore, our findings reveal a novel role of the KDELR-Erd2-mediated ER-retrieval system in modulating mitochondrial functions and highlight its importance for cellular homeostasis in the fission yeast.

Rice co-expression network analysis identifies gene modules associated with agronomic traits.

Identifying trait-associated genes is critical for rice (Oryza sativa) improvement, which usually relies on map-based cloning, quantitative trait locus analysis, or genome-wide association studies. Here we show that trait-associated genes tend to form modules within rice gene co-expression networks, a feature that can be exploited to discover additional trait-associated genes using reverse genetics. We constructed a rice gene co-expression network based on the graphical Gaussian model using 8,456 RNA-seq transcriptomes, which assembled into 1,286 gene co-expression modules functioning in diverse pathways. A number of the modules were enriched with genes associated with agronomic traits, such as grain size, grain number, tiller number, grain quality, leaf angle, stem strength, and anthocyanin content, and these modules are considered to be trait-associated gene modules. These trait-associated gene modules can be used to dissect the genetic basis of rice agronomic traits and to facilitate the identification of trait genes. As an example, we identified a candidate gene, OCTOPUS-LIKE 1 (OsOPL1), a homolog of the Arabidopsis (Arabidopsis thaliana) OCTOPUS gene, from a grain size module and verified it as a regulator of grain size via functional studies. Thus, our network represents a valuable resource for studying trait-associated genes in rice.

An Arabidopsis expression predictor enables inference of transcriptional regulators for gene modules.

The regulation of gene expression by transcription factors (TFs) has been studied for a long time, but no model that can accurately predict transcriptome profiles based on TF activities currently exists. Here, we developed a computational approach, named EXPLICIT (Expression Prediction via Log-linear Combination of Transcription Factors), to construct a universal predictor for Arabidopsis to predict the expression of 29 182 non-TF genes using 1678 TFs. When applied to RNA-Seq samples from diverse tissues, EXPLICIT generated accurate predicted transcriptomes correlating well with actual expression, with an average correlation coefficient of 0.986. After recapitulating the quantitative relationships between TFs and their target genes, EXPLICIT enabled downstream inference of TF regulators for genes and gene modules functioning in diverse plant pathways, including those involved in suberin, flavonoid, glucosinolate metabolism, lateral root, xylem, secondary cell wall development or endoplasmic reticulum stress response. Our approach showed a better ability to recover the correct TF regulators when compared with existing plant tools, and provides an innovative way to study transcriptional regulation.

EXPLICIT-Kinase: A gene expression predictor for dissecting the functions of the Arabidopsis kinome.

Protein kinases regulate virtually all cellular processes, but it remains challenging to determine the functions of all protein kinases, collectively called the "kinome", in any species. We developed a computational approach called EXPLICIT-Kinase to predict the functions of the Arabidopsis kinome. Because the activities of many kinases can be regulated transcriptionally, their gene expression patterns provide clues to their functions. A universal gene expression predictor for Arabidopsis was constructed to predict the expression of 30,172 non-kinase genes based on the expression of 994 kinases. The model reconstituted highly accurate transcriptomes for diverse Arabidopsis samples. It identified the significant kinases as predictor kinases for predicting the expression of Arabidopsis genes and pathways. Strikingly, these predictor kinases were often regulators of related pathways, as exemplified by those involved in cytokinesis, tissue development, and stress responses. Comparative analyses revealed that portions of these predictor kinases are shared and conserved between Arabidopsis and maize. As an example, we identified a conserved predictor kinase, RAF6, from a stomatal movement module. We verified that RAF6 regulates stomatal closure. It can directly interact with SLAC1, a key anion channel for stomatal closure, and modulate its channel activity. Our approach enables a systematic dissection of the functions of the Arabidopsis kinome.

Arabidopsis MADS-box factor AGL16 is a negative regulator of plant response to salt stress by downregulating salt-responsive genes.

Sessile plants constantly experience environmental stresses in nature. They must have evolved effective mechanisms to balance growth with stress response. Here we report the MADS-box transcription factor AGL16 acting as a negative regulator in stress response in Arabidopsis. Loss-of-AGL16 confers resistance to salt stress in seed germination, root elongation and soil-grown plants, while elevated AGL16 expression confers the opposite phenotypes compared with wild-type. However, the sensitivity to abscisic acid (ABA) in seed germination is inversely correlated with AGL16 expression levels. Transcriptomic comparison revealed that the improved salt resistance of agl16 mutants was largely attributed to enhanced expression of stress-responsive transcriptional factors and the genes involved in ABA signalling and ion homeostasis. We further demonstrated that AGL16 directly binds to the CArG motifs in the promoter of HKT1;1, HsfA6a and MYB102 and represses their expression. Genetic analyses with double mutants also support that HsfA6a and MYB102 are target genes of AGL16. Taken together, our results show that AGL16 acts as a negative regulator transcriptionally suppressing key components in the stress response and may play a role in balancing stress response with growth.

PARylation of the forkhead-associated domain protein DAWDLE regulates plant immunity.

Protein poly(ADP-ribosyl)ation (PARylation) primarily catalyzed by poly(ADP-ribose) polymerases (PARPs) plays a crucial role in controlling various cellular responses. However, PARylation targets and their functions remain largely elusive. Here, we deployed an Arabidopsis protein microarray coupled with in vitro PARylation assays to globally identify PARylation targets in plants. Consistent with the essential role of PARylation in plant immunity, the forkhead-associated (FHA) domain protein DAWDLE (DDL), one of PARP2 targets, positively regulates plant defense to both adapted and non-adapted pathogens. Arabidopsis PARP2 interacts with and PARylates DDL, which was enhanced upon treatment of bacterial flagellin. Mass spectrometry and mutagenesis analysis identified multiple PARylation sites of DDL by PARP2. Genetic complementation assays indicate that DDL PARylation is required for its function in plant immunity. In contrast, DDL PARylation appears to be dispensable for its previously reported function in plant development partially mediated by the regulation of microRNA biogenesis. Our study uncovers many previously unknown PARylation targets and points to the distinct functions of DDL in plant immunity and development mediated by protein PARylation and small RNA biogenesis, respectively.

Maize network analysis revealed gene modules involved in development, nutrients utilization, metabolism, and stress response.

BACKGROUND: The advent of big data in biology offers opportunities while poses challenges to derive biological insights. For maize, a large amount of publicly available transcriptome datasets have been generated but a comprehensive analysis is lacking. RESULTS: We constructed a maize gene co-expression network based on the graphical Gaussian model, using massive RNA-seq data. The network, containing 20,269 genes, assembles into 964 gene modules that function in a variety of plant processes, such as cell organization, the development of inflorescences, ligules and kernels, the uptake and utilization of nutrients (e.g. nitrogen and phosphate), the metabolism of benzoxazionids, oxylipins, flavonoids, and wax, and the response to stresses. Among them, the inflorescences development module is enriched with domestication genes (like ra1, ba1, gt1, tb1, tga1) that control plant architecture and kernel structure, while multiple other modules relate to diverse agronomic traits. Contained within these modules are transcription factors acting as known or potential expression regulators for the genes within the same modules, suggesting them as candidate regulators for related biological processes. A comparison with an established Arabidopsis network revealed conserved gene association patterns for specific modules involved in cell organization, nutrients uptake & utilization, and metabolism. The analysis also identified significant divergences between the two species for modules that orchestrate developmental pathways. CONCLUSIONS: This network sheds light on how gene modules are organized between different species in the context of evolutionary divergence and highlights modules whose structure and gene content can provide important resources for maize gene functional studies with application potential.

The plastidial retrograde signal methyl erythritol cyclopyrophosphate is a regulator of salicylic acid and jasmonic acid crosstalk.

The exquisite harmony between hormones and their corresponding signaling pathways is central to prioritizing plant responses to simultaneous and/or successive environmental trepidations. The crosstalk between jasmonic acid (JA) and salicylic acid (SA) is an established effective mechanism that optimizes and tailors plant adaptive responses. However, the underlying regulatory modules of this crosstalk are largely unknown. Global transcriptomic analyses of mutant plants (ceh1) with elevated levels of the stress-induced plastidial retrograde signaling metabolite 2-C-methyl-D-erythritol cyclopyrophosphate (MEcPP) revealed robustly induced JA marker genes, expected to be suppressed by the presence of constitutively high SA levels in the mutant background. Analyses of a range of genotypes with varying SA and MEcPP levels established the selective role of MEcPP-mediated signal(s) in induction of JA-responsive genes in the presence of elevated SA. Metabolic profiling revealed the presence of high levels of the JA precursor 12-oxo-phytodienoic acid (OPDA), but near wild type levels of JA in the ceh1 mutant plants. Analyses of coronatine-insensitive 1 (coi1)/ceh1 double mutant plants confirmed that the MEcPP-mediated induction is JA receptor COI1 dependent, potentially through elevated OPDA. These findings identify MEcPP as a previously unrecognized central regulatory module that induces JA-responsive genes in the presence of high SA, thereby staging a multifaceted plant response within the environmental context.

Incorporating motif analysis into gene co-expression networks reveals novel modular expression pattern and new signaling pathways.

Understanding of gene regulatory networks requires discovery of expression modules within gene co-expression networks and identification of promoter motifs and corresponding transcription factors that regulate their expression. A commonly used method for this purpose is a top-down approach based on clustering the network into a range of densely connected segments, treating these segments as expression modules, and extracting promoter motifs from these modules. Here, we describe a novel bottom-up approach to identify gene expression modules driven by known cis-regulatory motifs in the gene promoters. For a specific motif, genes in the co-expression network are ranked according to their probability of belonging to an expression module regulated by that motif. The ranking is conducted via motif enrichment or motif position bias analysis. Our results indicate that motif position bias analysis is an effective tool for genome-wide motif analysis. Sub-networks containing the top ranked genes are extracted and analyzed for inherent gene expression modules. This approach identified novel expression modules for the G-box, W-box, site II, and MYB motifs from an Arabidopsis thaliana gene co-expression network based on the graphical Gaussian model. The novel expression modules include those involved in house-keeping functions, primary and secondary metabolism, and abiotic and biotic stress responses. In addition to confirmation of previously described modules, we identified modules that include new signaling pathways. To associate transcription factors that regulate genes in these co-expression modules, we developed a novel reporter system. Using this approach, we evaluated MYB transcription factor-promoter interactions within MYB motif modules.

Novel positive regulatory role for the SPL6 transcription factor in the N TIR-NB-LRR receptor-mediated plant innate immunity.

Following the recognition of pathogen-encoded effectors, plant TIR-NB-LRR immune receptors induce defense signaling by a largely unknown mechanism. We identify a novel and conserved role for the SQUAMOSA PROMOTER BINDING PROTEIN (SBP)-domain transcription factor SPL6 in enabling the activation of the defense transcriptome following its association with a nuclear-localized immune receptor. During an active immune response, the Nicotiana TIR-NB-LRR N immune receptor associates with NbSPL6 within distinct nuclear compartments. NbSPL6 is essential for the N-mediated resistance to Tobacco mosaic virus. Similarly, the presumed Arabidopsis ortholog AtSPL6 is required for the resistance mediated by the TIR-NB-LRR RPS4 against Pseudomonas syringae carrying the avrRps4 effector. Transcriptome analysis indicates that AtSPL6 positively regulates a subset of defense genes. A pathogen-activated nuclear-localized TIR-NB-LRR like N can therefore regulate defense genes through SPL6 in a mechanism analogous to the induction of MHC genes by mammalian immune receptors like CIITA and NLRC5.

Arabidopsis RTNLB1 and RTNLB2 Reticulon-like proteins regulate intracellular trafficking and activity of the FLS2 immune receptor.

Receptors localized at the plasma membrane are critical for the recognition of pathogens. The molecular determinants that regulate receptor transport to the plasma membrane are poorly understood. In a screen for proteins that interact with the FLAGELIN-SENSITIVE2 (FLS2) receptor using Arabidopsis thaliana protein microarrays, we identified the reticulon-like protein RTNLB1. We showed that FLS2 interacts in vivo with both RTNLB1 and its homolog RTNLB2 and that a Ser-rich region in the N-terminal tail of RTNLB1 is critical for the interaction with FLS2. Transgenic plants that lack RTNLB1 and RTNLB2 (rtnlb1 rtnlb2) or overexpress RTNLB1 (RTNLB1ox) exhibit reduced activation of FLS2-dependent signaling and increased susceptibility to pathogens. In both rtnlb1 rtnlb2 and RTNLB1ox, FLS2 accumulation at the plasma membrane was significantly affected compared with the wild type. Transient overexpression of RTNLB1 led to FLS2 retention in the endoplasmic reticulum (ER) and affected FLS2 glycosylation but not FLS2 stability. Removal of the critical N-terminal Ser-rich region or either of the two Tyr-dependent sorting motifs from RTNLB1 causes partial reversion of the negative effects of excess RTNLB1 on FLS2 transport out of the ER and accumulation at the membrane. The results are consistent with a model whereby RTNLB1 and RTNLB2 regulate the transport of newly synthesized FLS2 to the plasma membrane.

SingleCellGGM enables gene expression program identification from single-cell transcriptomes and facilitates universal cell label transfer.

Gene co-expression analysis of single-cell transcriptomes, aiming to define functional relationships between genes, is challenging due to excessive dropout values. Here, we developed a single-cell graphical Gaussian model (SingleCellGGM) algorithm to conduct single-cell gene co-expression network analysis. When applied to mouse single-cell datasets, SingleCellGGM constructed networks from which gene co-expression modules with highly significant functional enrichment were identified. We considered the modules as gene expression programs (GEPs). These GEPs enable direct cell-type annotation of individual cells without cell clustering, and they are enriched with genes required for the functions of the corresponding cells, sometimes at levels greater than 10-fold. The GEPs are conserved across datasets and enable universal cell-type label transfer across different studies. We also proposed a dimension-reduction method through averaging by GEPs for single-cell analysis, enhancing the interpretability of results. Thus, SingleCellGGM offers a unique GEP-based perspective to analyze single-cell transcriptomes and reveals biological insights shared by different single-cell datasets.

Single-cell network analysis reveals gene expression programs for Arabidopsis root development and metabolism.

Single-cell RNA-sequencing datasets of Arabidopsis roots have been generated, but related comprehensive gene co-expression network analyses are lacking. We conducted a single-cell gene co-expression network analysis with publicly available scRNA-seq datasets of Arabidopsis roots using a SingleCellGGM algorithm. The analysis identified 149 gene co-expression modules, which we considered to be gene expression programs (GEPs). By examining their spatiotemporal expression, we identified GEPs specifically expressed in major root cell types along their developmental trajectories. These GEPs define gene programs regulating root cell development at different stages and are enriched with relevant developmental regulators. As examples, a GEP specific for the quiescent center (QC) contains 20 genes regulating QC and stem cell niche homeostasis, and four GEPs are expressed in sieve elements (SEs) from early to late developmental stages, with the early-stage GEP containing 17 known SE developmental regulators. We also identified GEPs for metabolic pathways with cell-type-specific expression, suggesting the existence of cell-type-specific metabolism in roots. Using the GEPs, we discovered and verified a columella-specific gene, NRL27, as a regulator of the auxin-related root gravitropism response. Our analysis thus systematically reveals GEPs that regulate Arabidopsis root development and metabolism and provides ample resources for root biology studies.

Stomatal maturomics: hunting genes regulating guard cell maturation and function formation from single-cell transcriptomes.

Stomata play critical roles in gas exchange and immunity to pathogens. While many genes regulating early stomatal development up to the production of young guard cells (GCs) have been identified in Arabidopsis, much less is known about how young GCs develop into mature functional stomata. Here we perform a maturomics study on stomata, with "maturomics" defined as omics analysis of the maturation process of a tissue or organ. We develop an integrative scheme to analyze three public stomata-related single-cell RNA-seq datasets and identify a list of 586 genes that are specifically up-regulated in all three datasets during stomatal maturation and function formation. The list, termed sc_586, is enriched with known regulators of stomatal maturation and functions. To validate the reliability of the dataset, we selected two candidate G2-like transcription factor genes, MYS1 and MYS2, to investigate their roles in stomata. These two genes redundantly regulate the size and hoop rigidity of mature GCs, and the mys1 mys2 double mutants cause mature GCs with severe defects in regulating their stomatal apertures. Taken together, our results provide a valuable list of genes for studying GC maturation and function formation.

6-Phosphogluconate dehydrogenase 2 bridges the OPP and shikimate pathways to enhance aromatic amino acid production in plants.

The oxidative pentose phosphate (OPP) pathway provides metabolic intermediates for the shikimate pathway and directs carbon flow to the biosynthesis of aromatic amino acids (AAAs), which serve as basic protein building blocks and precursors of numerous metabolites essential for plant growth. However, genetic evidence linking the two pathways is largely unclear. In this study, we identified 6-phosphogluconate dehydrogenase 2 (PGD2), the rate-limiting enzyme of the cytosolic OPP pathway, through suppressor screening of arogenate dehydrogenase 2 (adh2) in Arabidopsis. Our data indicated that a single amino acid substitution at position 63 (glutamic acid to lysine) of PGD2 enhanced its enzyme activity by facilitating the dissociation of products from the active site of PGD2, thus increasing the accumulation of AAAs and partially restoring the defective phenotype of adh2. Phylogenetic analysis indicated that the point mutation occurred in a well-conserved amino acid residue. Plants with different amino acids at this conserved site of PGDs confer diverse catalytic activities, thus exhibiting distinct AAAs producing capability. These findings uncover the genetic link between the OPP pathway and AAAs biosynthesis through PGD2. The gain-of-function point mutation of PGD2 identified here could be considered as a potential engineering target to alter the metabolic flux for the production of AAAs and downstream compounds.

Decoding transcriptional regulation via a human gene expression predictor.

Transcription factors (TFs) regulate cellular activities by controlling gene expression, but a predictive model describing how TFs quantitatively modulate human transcriptomes is lacking. We construct a universal human gene expression predictor named EXPLICIT-Human and utilize it to decode transcriptional regulation. Using the expression of 1613 TFs, the predictor reconstitutes highly accurate transcriptomes for samples derived from a wide range of tissues and conditions. The broad applicability of the predictor indicates that it recapitulates the quantitative relationships between TFs and target genes ubiquitous across tissues. Significant interacting TF-target gene pairs are extracted from the predictor and enable downstream inference of TF regulators for diverse pathways involved in development, immunity, metabolism, and stress response. A detailed analysis of the hematopoiesis process reveals an atlas of key TFs regulating the development of different hematopoietic cell lineages, and a portion of these TFs are conserved between humans and mice. The results demonstrate that our method is capable of delineating the TFs responsible for fate determination. Compared to other existing tools, EXPLICIT-Human shows a better performance in recovering the correct TF regulators.

SIZ1 regulation of phosphate starvation-induced root architecture remodeling involves the control of auxin accumulation.

Phosphate (Pi) limitation causes plants to modulate the architecture of their root systems to facilitate the acquisition of Pi. Previously, we reported that the Arabidopsis (Arabidopsis thaliana) SUMO E3 ligase SIZ1 regulates root architecture remodeling in response to Pi limitation; namely, the siz1 mutations cause the inhibition of primary root (PR) elongation and the promotion of lateral root (LR) formation. Here, we present evidence that SIZ1 is involved in the negative regulation of auxin patterning to modulate root system architecture in response to Pi starvation. The siz1 mutations caused greater PR growth inhibition and LR development of seedlings in response to Pi limitation. Similar root phenotypes occurred if Pi-deficient wild-type seedlings were supplemented with auxin. N-1-Naphthylphthalamic acid, an inhibitor of auxin efflux activity, reduced the Pi starvation-induced LR root formation of siz1 seedlings to a level equivalent to that seen in the wild type. Monitoring of the auxin-responsive reporter DR5::uidA indicated that auxin accumulates in PR tips at early stages of the Pi starvation response. Subsequently, DR5::uidA expression was observed in the LR primordia, which was associated with LR elongation. The time-sequential patterning of DR5::uidA expression occurred earlier in the roots of siz1 as compared with the wild type. In addition, microarray analysis revealed that several other auxin-responsive genes, including genes involved in cell wall loosening and biosynthesis, were up-regulated in siz1 relative to wild-type seedlings in response to Pi starvation. Together, these results suggest that SIZ1 negatively regulates Pi starvation-induced root architecture remodeling through the control of auxin patterning.

Regulation of reactive oxygen species during plant immunity through phosphorylation and ubiquitination of RBOHD.

Production of reactive oxygen species (ROS) is critical for successful activation of immune responses against pathogen infection. The plant NADPH oxidase RBOHD is a primary player in ROS production during innate immunity. However, how RBOHD is negatively regulated remains elusive. Here we show that RBOHD is regulated by C-terminal phosphorylation and ubiquitination. Genetic and biochemical analyses reveal that the PBL13 receptor-like cytoplasmic kinase phosphorylates RBOHD's C-terminus and two phosphorylated residues (S862 and T912) affect RBOHD activity and stability, respectively. Using protein array technology, we identified an E3 ubiquitin ligase PIRE (PBL13 interacting RING domain E3 ligase) that interacts with both PBL13 and RBOHD. Mimicking phosphorylation of RBOHD (T912D) results in enhanced ubiquitination and decreased protein abundance. PIRE and PBL13 mutants display higher RBOHD protein accumulation, increased ROS production, and are more resistant to bacterial infection. Thus, our study reveals an intricate post-translational network that negatively regulates the abundance of a conserved NADPH oxidase.

Static magnetic field regulates Arabidopsis root growth via auxin signaling.

Static magnetic field (SMF) plays important roles in biological processes of many living organisms. In plants, however, biological significance of SMF and molecular mechanisms underlying SMF action remain largely unknown. To address these questions, we treated Arabidopsis young seedlings with different SMF intensities and directions. Magnetic direction from the north to south pole was adjusted in parallel (N0) with, opposite (N180) and perpendicular to the gravity vector. We discovered that root growth is significantly inhanced by 600 mT treatments except for N180, but not by any 300 mT treatments. N0 treatments lead to more active cell division of the meristem, and higher auxin content that is regulated by coordinated expression of PIN3 and AUX1 in root tips. Consistently, N0-promoted root growth disappears in pin3 and aux1 mutants. Transcriptomic and gene ontology analyses revealed that in roots 85% of the total genes significantly down-regulated by N0 compared to untreatment are enriched in plastid biological processes, such as metabolism and chloroplast development. Lastly, no difference in root length is observed between N0-treated and untreated roots of the double cryptochrome mutant cry1 cry2. Taken together, our data suggest that SMF-regulated root growth is mediated by CRY and auxin signaling pathways in Arabidopsis.