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 mutatants 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.

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

Single-cell RNA-seq (scRNA-seq) 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 gene expression programs (GEPs). By checking their spatiotemporal expression, we identified GEPs specifically expressed in major root cell types along their developmental trajectories. These GEPs defined gene programs regulating root cell development at different stages and are enriched with relevant developmental regulators. As examples, a GEP specific for quiescent center (QC) contains 20 genes regulating QC and stem cell niche homeostasis, and five 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 auxin-related root gravitropism response. Our analysis thus systematically revealed GEPs regulating Arabidopsis root development and metabolism and provided candidate genes for root biology studies.

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.

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.

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.

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.

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.

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.

Aurora A Inhibition Eliminates Myeloid Cell-Mediated Immunosuppression and Enhances the Efficacy of Anti-PD-L1 Therapy in Breast Cancer.

The Aurora A inhibitor alisertib shows encouraging activities in clinical trials against advanced breast cancer. However, it remains unclear whether and how the inflammatory microenvironment is involved in its efficacy. Here, we demonstrated that inhibition of Aurora A directly reshaped the immune microenvironment through removal of tumor-promoting myeloid cells and enrichment of anticancer T lymphocytes, which established a tumor-suppressive microenvironment and significantly contributed to the regression of murine mammary tumors. Mechanistically, alisertib treatment triggered apoptosis in myeloid-derived suppressor cells (MDSC) and macrophages, resulting in their elimination from tumors. Furthermore, alisertib treatment disrupted the immunosuppressive functions of MDSC by inhibiting Stat3-mediated ROS production. These alterations led to significant increases of active CD8+ and CD4+ T lymphocytes, which efficiently inhibited the proliferation of tumor cells. Intriguingly, alisertib combined with PD-L1 blockade showed synergistic efficacy in the treatment of mammary tumors. These results detail the effects of Aurora A inhibition on the immune microenvironment and provide a novel chemo-immunotherapy strategy for advanced breast cancers. SIGNIFICANCE: These findings show that inhibition of Aurora A facilitates an anticancer immune microenvironment, which can suppress tumor progression and enhance anti-PD-L1 therapy in breast cancer.See related commentary by Rivoltini et al., p. 3169.

The MAP4 Kinase SIK1 Ensures Robust Extracellular ROS Burst and Antibacterial Immunity in Plants.

Microbial patterns are recognized by cell-surface receptors to initiate pattern-triggered immunity (PTI) in plants. Receptor-like cytoplasmic kinases (RLCKs), such as BIK1, and calcium-dependent protein kinases (CPKs) are engaged during PTI to activate the NADPH oxidase RBOHD for reactive oxygen species (ROS) production. It is unknown whether protein kinases besides CPKs and RLCKs participate in RBOHD regulation. We screened mutants in all ten Arabidopsis MAP4 kinases (MAP4Ks) and identified the conserved MAP4K SIK1 as a positive regulator of PTI. sik1 mutants were compromised in their ability to elicit the ROS burst in response to microbial features and exhibited compromised PTI to bacterial infection. SIK1 directly interacts with, phosphorylates, and stabilizes BIK1 in a kinase activity-dependent manner. Furthermore, SIK1 directly interacts with and phosphorylates RBOHD upon flagellin perception. Thus, SIK1 positively regulates immunity by stabilizing BIK1 and activating RBOHD to promote the extracellular ROS burst.

De novo assembly of a Chinese soybean genome.

Soybean was domesticated in China and has become one of the most important oilseed crops. Due to bottlenecks in their introduction and dissemination, soybeans from different geographic areas exhibit extensive genetic diversity. Asia is the largest soybean market; therefore, a high-quality soybean reference genome from this area is critical for soybean research and breeding. Here, we report the de novo assembly and sequence analysis of a Chinese soybean genome for "Zhonghuang 13" by a combination of SMRT, Hi-C and optical mapping data. The assembled genome size is 1.025 Gb with a contig N50 of 3.46 Mb and a scaffold N50 of 51.87 Mb. Comparisons between this genome and the previously reported reference genome (cv. Williams 82) uncovered more than 250,000 structure variations. A total of 52,051 protein coding genes and 36,429 transposable elements were annotated for this genome, and a gene co-expression network including 39,967 genes was also established. This high quality Chinese soybean genome and its sequence analysis will provide valuable information for soybean improvement in the future.

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.

Discovery of Novel Human Gene Regulatory Modules from Gene Co-expression and Promoter Motif Analysis.

Deciphering gene regulatory networks requires identification of gene expression modules. We describe a novel bottom-up approach to identify gene modules regulated by cis-regulatory motifs from a human gene co-expression network. Target genes of a cis-regulatory motif were identified from the network via the motif's enrichment or biased distribution towards transcription start sites in the promoters of co-expressed genes. A gene sub-network containing the target genes was extracted and used to derive gene modules. The analysis revealed known and novel gene modules regulated by the NF-Y motif. The binding of NF-Y proteins to these modules' gene promoters were verified using ENCODE ChIP-Seq data. The analyses also identified 8,048 Sp1 motif target genes, interestingly many of which were not detected by ENCODE ChIP-Seq. These target genes assemble into house-keeping, tissues-specific developmental, and immune response modules. Integration of Sp1 modules with genomic and epigenomic data indicates epigenetic control of Sp1 targets' expression in a cell/tissue specific manner. Finally, known and novel target genes and modules regulated by the YY1, RFX1, IRF1, and 34 other motifs were also identified. The study described here provides a valuable resource to understand transcriptional regulation of various human developmental, disease, or immunity pathways.

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.

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.

Plant protein kinase substrates identification using protein microarrays.

Protein kinases regulate signaling pathways by phosphorylating their targets. They play critical roles in plant signaling networks. Although many important protein kinases have been identified in plants, their substrates are largely unknown. We have developed and produced plant protein microarrays with more than 15,000 purified plant proteins. Here, we describe a detailed protocol to use these microarrays to identify plant protein kinase substrates via in vitro phosphorylation assays on these arrays.

AtGGM2014, an Arabidopsis gene co-expression network for functional studies.

Gene co-expression networks provide an important tool for systems biology studies. Using microarray data from the ArrayExpress database, we constructed an Arabidopsis gene co-expression network, termed AtGGM2014, based on the graphical Gaussian model, which contains 102,644 co-expression gene pairs among 18,068 genes. The network was grouped into 622 gene co-expression modules. These modules function in diverse house-keeping, cell cycle, development, hormone response, metabolism, and stress response pathways. We developed a tool to facilitate easy visualization of the expression patterns of these modules either in a tissue context or their regulation under different treatment conditions. The results indicate that at least six modules with tissue-specific expression pattern failed to record modular regulation under various stress conditions. This discrepancy could be best explained by the fact that experiments to study plant stress responses focused mainly on leaves and less on roots, and thus failed to recover specific regulation pattern in other tissues. Overall, the modular structures revealed by our network provide extensive information to generate testable hypotheses about diverse plant signaling pathways. AtGGM2014 offers a constructive tool for plant systems biology studies.