Golgi-Resident Gαo Promotes Protrusive Membrane Dynamics.

To form protrusions like neurites, cells must coordinate their induction and growth. The first requires cytoskeletal rearrangements at the plasma membrane (PM), the second requires directed material delivery from cell's insides. We find that the Gαo-subunit of heterotrimeric G proteins localizes dually to PM and Golgi across phyla and cell types. The PM pool of Gαo induces, and the Golgi pool feeds, the growing protrusions by stimulated trafficking. Golgi-residing KDELR binds and activates monomeric Gαo, atypically for G protein-coupled receptors that normally act on heterotrimeric G proteins. Through multidimensional screenings identifying > 250 Gαo interactors, we pinpoint several basic cellular activities, including vesicular trafficking, as being regulated by Gαo. We further find small Golgi-residing GTPases Rab1 and Rab3 as direct effectors of Gαo. This KDELR → Gαo → Rab1/3 signaling axis is conserved from insects to mammals and controls material delivery from Golgi to PM in various cells and tissues.

SPINT2 mutations in the Kunitz domain 2 found in SCSD patients inactivate HAI-2 as prostasin inhibitor via abnormal protein folding and N-glycosylation.

Mutations in the Kunitz-type serine protease inhibitor HAI-2, encoded by SPINT2, are responsible for the pathogenesis of syndromic congenital sodium diarrhea (SCSD), an intractable secretory diarrhea of infancy. Some of the mutations cause defects in the functionally required Kunitz domain 1 and/or subcellular targeting signals. Almost all SCSD patients, however, harbor SPINT2 missense mutations that affect the functionally less important Kunitz domain 2. How theses single amino acid substitutions inactivate HAI-2 was, here, investigated by the doxycycline-inducible expression of three of these mutants in HAI-2-knockout Caco-2 human colorectal adenocarcinoma cells. Examining protein expressed from these HAI-2 mutants reveals that roughly 50% of the protein is synthesized as disulfide-linked oligomers that lose protease inhibitory activity due to the distortion of the Kunitz domains by disarrayed disulfide bonding. Although the remaining protein is synthesized as monomers, its glycosylation status suggests that the HAI-2 monomer remains in the immature, lightly glycosylated form, and is not converted to the heavily glycosylated mature form. Heavily glycosylated HAI-2 possesses full anti-protease activity and appropriate subcellular targeting signals, including the one embedded in the complex-type N-glycan. As predicted, these HAI-2 mutants cannot suppress the excessive prostasin proteolysis caused by HAI-2 deletion. The oligomerization and glycosylation defects have also been observed in a colorectal adenocarcinoma line that harbors one of these SPINT2 missense mutations. Our study reveals that the abnormal protein folding and N-glycosylation can cause widespread HAI-2 inactivation in SCSD patents.

Epilepsies of presumed genetic etiology show enrichment of rare variants that occur in the general population.

Previous studies suggested that severe epilepsies, e.g., developmental and epileptic encephalopathies (DEEs), are mainly caused by ultra-rare de novo genetic variants. For milder disease, rare genetic variants could contribute to the phenotype. To determine the importance of rare variants for different epilepsy types, we analyzed a whole-exome sequencing cohort of 9,170 epilepsy-affected individuals and 8,436 control individuals. Here, we separately analyzed three different groups of epilepsies: severe DEEs, genetic generalized epilepsy (GGE), and non-acquired focal epilepsy (NAFE). We required qualifying rare variants (QRVs) to occur in control individuals with an allele count ≥ 1 and a minor allele frequency ≤ 1:1,000, to be predicted as deleterious (CADD ≥ 20), and to have an odds ratio in individuals with epilepsy ≥ 2. We identified genes enriched with QRVs primarily in NAFE (n = 72), followed by GGE (n = 32) and DEE (n = 21). This suggests that rare variants may play a more important role for causality of NAFE than for DEE. Moreover, we found that genes harboring QRVs, e.g., HSGP2, FLNA, or TNC, encode proteins that are involved in structuring the brain extracellular matrix. The present study confirms an involvement of rare variants for NAFE that occur also in the general population, while in DEE and GGE, the contribution of such variants appears more limited.

VirGrapher: a graph-based viral identifier for long sequences from metagenomes.

Viruses are the most abundant biological entities on earth and are important components of microbial communities. A metagenome contains all microorganisms from an environmental sample. Correctly identifying viruses from these mixed sequences is critical in viral analyses. It is common to identify long viral sequences, which has already been passed thought pipelines of assembly and binning. Existing deep learning-based methods divide these long sequences into short subsequences and identify them separately. This makes the relationships between them be omitted, leading to poor performance on identifying long viral sequences. In this paper, VirGrapher is proposed to improve the identification performance of long viral sequences by constructing relationships among short subsequences from long ones. VirGrapher see a long sequence as a graph and uses a Graph Convolutional Network (GCN) model to learn multilayer connections between nodes from sequences after a GCN-based node embedding model. VirGrapher achieves a better AUC value and accuracy on validation set, which is better than three benchmark methods.

A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases.

Finding disease-relevant tissues and cell types can facilitate the identification and investigation of functional genes and variants. In particular, cell type proportions can serve as potential disease predictive biomarkers. In this manuscript, we introduce a novel statistical framework, cell-type Wide Association Study (cWAS), that integrates genetic data with transcriptomics data to identify cell types whose genetically regulated proportions (GRPs) are disease/trait-associated. On simulated and real GWAS data, cWAS showed good statistical power with newly identified significant GRP associations in disease-associated tissues. More specifically, GRPs of endothelial and myofibroblasts in lung tissue were associated with Idiopathic Pulmonary Fibrosis and Chronic Obstructive Pulmonary Disease, respectively. For breast cancer, the GRP of blood CD8+ T cells was negatively associated with breast cancer (BC) risk as well as survival. Overall, cWAS is a powerful tool to reveal cell types associated with complex diseases mediated by GRPs.

Single-molecule RNA in situ detection in clinical FFPE tissue sections by vsmCISH.

Although RNA plays a vital role in gene expression, it is less used as an in situ biomarker for clinical diagnostics than DNA and protein. This is mainly due to technical challenges caused by the low expression level and easy degradation of RNA molecules. To tackle this issue, methods that are sensitive and specific are needed. Here, we present an RNA single-molecule chromogenic in situ hybridization assay based on DNA probe proximity ligation and rolling circle amplification. When the DNA probes hybridize into close proximity to the RNA molecules, they form a V-shape structure and mediate the circularization of circle probes. Thus, our method was termed vsmCISH. We successfully applied our method to assess HER2 mRNA expression status in invasive breast cancer tissue and investigated the utility of albumin mRNA ISH for differentiating primary from metastatic liver cancer. The promising results on clinical samples indicate that our method has great potential for application in diagnosing diseases using RNA biomarkers.

Semaphorin 1a-mediated dendritic wiring of the Drosophila mushroom body extrinsic neurons.

SignificanceThe adult Drosophila mushroom body (MB) is one of the most extensively studied neural circuits. However, how its circuit organization is established during development is unclear. In this study, we provide an initial characterization of the assembly process of the extrinsic neurons (dopaminergic neurons and MB output neurons) that target the vertical MB lobes. We probe the cellular mechanisms guiding the neurite targeting of these extrinsic neurons and demonstrate that Semaphorin 1a is required in several MB output neurons for their dendritic innervations to three specific MB lobe zones. Our study reveals several intriguing molecular and cellular principles governing assembly of the MB circuit.

Toward Controlled Synthesis of 2D Crystals by CVD: Learning from the Real-Time Crystal Morphology Evolutions.

The rich morphology of 2D materials grown through chemical vapor deposition (CVD), is a distinctive feature. However, understanding the complex growth of 2D crystals under practical CVD conditions remains a challenge due to various intertwined factors. Real-time monitoring is crucial to providing essential data and enabling the use of advanced tools like machine learning for unraveling these complexities. In this study, we present a custom-built miniaturized CVD system capable of observing and recording 2D MoS2 crystal growth in real time. Image processing converts the real-time footage into digital data, and machine learning algorithms (ML) unveil the significant factors influencing growth. The machine learning model successfully predicts CVD growth parameters for synthesizing ultralarge monolayer MoS2 crystals. It also demonstrates the potential to reverse engineer CVD growth parameters by analyzing the as-grown 2D crystal morphology. This interdisciplinary approach can be integrated to enhance our understanding of controlled 2D crystal synthesis through CVD.

Substrate Specificities of Variants of Barley (1,3)- and (1,3;1,4)-ß-d-Glucanases Resulting from Mutagenesis and Segment Hybridization.

Barley (1,3;1,4)-ß-d-glucanase is believed to have evolved from an ancestral monocotyledon (1,3)-ß-d-glucanase, enabling the hydrolysis of (1,3;1,4)-ß-d-glucans in the cell walls of leaves and germinating grains. In the present study, we investigated the substrate specificities of variants of the barley enzymes (1,3;1,4)-ß-d-glucan endohydrolase [(1,3;1,4)-ß-d-glucanase] isoenzyme EII (HvEII) and (1,3)-ß-d-glucan endohydrolase [(1,3)-ß-d-glucanase] isoenzyme GII (HvGII) obtained by protein segment hybridization and site-directed mutagenesis. Using protein segment hybridization, we obtained three variants of HvEII in which the substrate specificity was that of a (1,3)-ß-d-glucanase and one variant that hydrolyzed both (1,3)-ß-d-glucans and (1,3;1,4)-ß-d-glucans; the wild-type enzyme hydrolyzed only (1,3;1,4)-ß-d-glucans. Using substitutions of specific amino acid residues, we obtained one variant of HvEII that hydrolyzed both substrates. However, neither protein segment hybridization nor substitutions of specific amino acid residues gave variants of HvGII that could hydrolyze (1,3;1,4)-ß-d-glucans; the wild-type enzyme hydrolyzed only (1,3)-ß-d-glucans. Other HvEII and HvGII variants showed changes in specific activity and their ability to degrade the (1,3;1,4)-ß-d-glucans or (1,3)-ß-d-glucans to larger oligosaccharides. We also used molecular dynamics simulations to identify amino-acid residues or structural regions of wild-type HvEII and HvGII that interact with (1,3;1,4)-ß-d-glucans and (1,3)-ß-d-glucans, respectively, and may be responsible for the substrate specificities of the two enzymes.

Combined Treatment of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes and Endothelial Cells Regenerate the Infarcted Heart in Mice and Non-Human Primates.

BACKGROUND: Remuscularization of the mammalian heart can be achieved after cell transplantation of human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CMs). However, several hurdles remain before implementation into clinical practice. Poor survival of the implanted cells is related to insufficient vascularization, and the potential for fatal arrhythmogenesis is associated with the fetal cell-like nature of immature CMs. METHODS: We generated 3 lines of hiPSC-derived endothelial cells (ECs) and hiPSC-CMs from 3 independent donors and tested hiPSC-CM sarcomeric length, gap junction protein, and calcium-handling ability in coculture with ECs. Next, we examined the therapeutic effect of the cotransplantation of hiPSC-ECs and hiPSC-CMs in nonobese diabetic-severe combined immunodeficiency (NOD-SCID) mice undergoing myocardial infarction (n≥4). Cardiac function was assessed by echocardiography, whereas arrhythmic events were recorded using 3-lead ECGs. We further used healthy non-human primates (n=4) with cell injection to study the cell engraftment, maturation, and integration of transplanted hiPSC-CMs, alone or along with hiPSC-ECs, by histological analysis. Last, we tested the cell therapy in ischemic reperfusion injury in non-human primates (n=4, 3, and 4 for EC+CM, CM, and control, respectively). Cardiac function was evaluated by echocardiography and cardiac MRI, whereas arrhythmic events were monitored by telemetric ECG recorders. Cell engraftment, angiogenesis, and host-graft integration of human grafts were also investigated. RESULTS: We demonstrated that human iPSC-ECs promote the maturity and function of hiPSC-CMs in vitro and in vivo. When cocultured with ECs, CMs showed more mature phenotypes in cellular structure and function. In the mouse model, cotransplantation augmented the EC-accompanied vascularization in the grafts, promoted the maturity of CMs at the infarct area, and improved cardiac function after myocardial infarction. Furthermore, in non-human primates, transplantation of ECs and CMs significantly enhanced graft size and vasculature and improved cardiac function after ischemic reperfusion. CONCLUSIONS: These results demonstrate the synergistic effect of combining iPSC-derived ECs and CMs for therapy in the postmyocardial infarction heart, enabling a promising strategy toward clinical translation.

Association of Posttraumatic Stress Disorder and Race on Readmissions After Stroke.

BACKGROUND: There is limited research on outcomes of patients with posttraumatic stress disorder (PTSD) who also develop stroke, particularly regarding racial disparities. Our goal was to determine whether PTSD is associated with the risk of hospital readmission after stroke and whether racial disparities existed. METHODS: The analytical sample consisted of all veterans receiving care in the Veterans Health Administration who were identified as having a new stroke requiring inpatient admission based on the International Classification of Diseases codes. PTSD and comorbidities were identified using the International Classification of Diseases codes and given the date of first occurrence. The retrospective cohort data were obtained from the Veterans Affairs Corporate Data Warehouse. The main outcome was any readmission to Veterans Health Administration with a stroke diagnosis. The hypothesis that PTSD is associated with readmission after stroke was tested using Cox regression adjusted for patient characteristics including age, sex, race, PTSD, smoking status, alcohol use, and comorbidities treated as time-varying covariates. RESULTS: Our final cohort consisted of 93 651 patients with inpatient stroke diagnosis and no prior Veterans Health Administration codes for stroke starting from 1999 with follow-up through August 6, 2022. Of these patients, 12 916 (13.8%) had comorbid PTSD. Of the final cohort, 16 896 patients (18.0%) with stroke were readmitted. Our fully adjusted model for readmission found an interaction between African American veterans and PTSD with a hazard ratio of 1.09 ([95% CI, 1.00-1.20] P=0.047). In stratified models, PTSD has a significant hazard ratio of 1.10 ([95% CI, 1.02-1.18] P=0.01) for African American but not White veterans (1.05 [95% CI, 0.99-1.11]; P=0.10). CONCLUSIONS: Among African American veterans who experienced stroke, preexisting PTSD was associated with increased risk of readmission, which was not significant among White veterans. This study highlights the need to focus on high-risk groups to reduce readmissions after stroke.

Investigation of the association between the Toll-like receptor 1 rs4833095 variation and gastric adenocarcinoma recurrence.

BACKGROUND: Toll-like receptors (TLRs) are a family of transmembrane receptors that play key roles in identifying invading pathogens and activating innate immunity. TLR1 has been reported to be associated with the risk of gastric cancer (GC) but that was based on only a simple statistical analysis. METHODS: We genotyped the TLR1 in 526 GC patients to investigate the association between the variation and gastric cancer survival by the multiplex polymerase chain reaction and sequencing method. The rs4833095 variation (chr4:38798089 [GRCh38. p14], T > C) in the TLR1 gene was genotyped in 526 patients who underwent GC resection. The associations between genotype, survival, and recurrence were investigated. The potential role of TLR1 in stomach cancer was investigated using clinical data from formalin-fixed, paraffin-embedded tissue samples. RESULTS: Patients with the T/C and C/C genotypes of rs4833095 had a lower risk of recurrence than those with the T/T genotype. Recurrence-free periods were substantially longer in patients with the T/C or C/C genotypes (22.6 and 22.3 months, respectively) than in those with the T/T genotype (20.7 months). Patients with the T/C or C/C genotype, low expression levels of VEGF1, high expression levels of ERBB2 and ERCC1, the absence of cancer nodules, a tumor size of less than 5 cm, and poor differentiation had a considerably reduced risk of recurrence. CONCLUSIONS: TLR1 rs4833095 was correlated with the postresection prognosis of patients with gastric cancer, suggesting that TLR1 may have a role in the onset or progression of gastric cancer.

Concurrent Atezolizumab Plus Bevacizumab and High-Dose External Beam Radiotherapy for Highly Advanced Hepatocellular Carcinoma.

BACKGROUND: Atezolizumab plus bevacizumab (atezo-bev) has been recommended for advanced hepatocellular carcinoma (HCC). High-dose external beam radiotherapy (RT) is recognized for its excellent local tumor control. The efficacy and safety of concurrent atezo-bev with RT for highly advanced HCC has been minimally explored. METHODS: In this preliminary retrospective study, we assessed patients with highly advanced HCC, characterized by Vp4 portal vein thrombosis or tumors exceeding 50% of liver volume, who received concurrent atezo-bev and RT (group A). Group A included 13 patients who received proton radiation at a dose of 72.6 GyE in 22 fractions, and one patient who received photon radiation at a dose of 54 Gy in 18 fractions. This group was compared with 34 similar patients treated atezo-bev alone as a control (group B). The primary objectives were to evaluate the objective response rate (ORR), overall survival (OS), and safety. RESULTS: Baseline characteristics were similar between groups, except for a higher incidence of Vp4 portal vein thrombosis in group A (78.6% vs. 21.4%, P = .05). Group A achieved a higher ORR (50.0% vs. 11.8%, P < .01) and a longer OS (not reached vs. 5.5 months, P = .01) after a median follow-up of 5.2 months. Multivariate analysis indicated that concurrent RT independently favored longer OS (hazard ratio: 0.18; 95% CI, 0.05-0.63, P < .01). Group A did not increase any grade adverse events (78.6% vs. 58.8%, P = .19) or severe adverse events of grade ≥ 3 (14.3% vs. 14.7%, P = .97) compared to group B. CONCLUSIONS: The concurrent high-dose external beam radiotherapy appears to safely enhance the effectiveness of atezolizumab plus bevacizumab for highly advanced patients with HCC. Further studies are warranted to confirm these findings.

Combined amplification-based single-molecule fluorescence in situ hybridization with immunofluorescence for simultaneous in situ detection of RNAs and proteins.

We present a combined amplification-based single-molecule fluorescence in situ hybridization and immunofluorescence (asmFISH-IF) method for the detection of multiple RNAs and proteins simultaneously in cells and formaldehyde-fixed and paraffin-embedded tissue sections. We showed that performing asmFISH before immunofluorescence gives a better IF signal than the opposite. Our asmFISH-IF method could help study the interplay of RNA and protein, helping to understand their functions.

Application of bulk segregant RNA-Seq (BSR-Seq) and allele-specific primers to study soybean powdery mildew resistance.

BACKGROUND: Powdery mildew (PM) is one of the important soybean diseases, and host resistance could practically contribute to soybean PM management. To date, only the Rmd locus on chromosome (Chr) 16 was identified through traditional QTL mapping and GWAS, and it remains unclear if the bulk segregant RNA-Seq (BSR-Seq) methodology is feasible to explore additional PM resistance that might exist in other varieties. RESULTS: BSR-Seq was applied to contrast genotypes and gene expressions between the resistant bulk (R bulk) and the susceptible bulk (S bulk), as well as the parents. The ∆(SNP-index) and G' value identified several QTL and significant SNPs/Indels on Chr06, Chr15, and Chr16. Differentially expressed genes (DEGs) located within these QTL were identified using HISAT2 and Kallisto, and allele-specific primers (AS-primers) were designed to validate the accuracy of phenotypic prediction. While the AS-primers on Chr06 or Chr15 cannot distinguish the resistant and susceptible phenotypes, AS-primers on Chr16 exhibited 82% accuracy prediction with an additive effect, similar to the SSR marker Satt431. CONCLUSIONS: Evaluation of additional AS-primers in the linkage disequilibrium (LD) block on Chr16 further confirmed the resistant locus, derived from the resistant parental variety 'Kaohsiung 11' ('KS11'), not only overlaps with the Rmd locus with unique up-regulated LRR genes (Glyma.16G213700 and Glyma.16G215100), but also harbors a down-regulated MLO gene (Glyma.16G145600). Accordingly, this study exemplified the feasibility of BSR-Seq in studying biotrophic disease resistance in soybean, and showed the genetic makeup of soybean variety 'KS11' comprising the Rmd locus and one MLO gene.

A comparison of deep learning-based pre-processing and clustering approaches for single-cell RNA sequencing data.

The emergence of single cell RNA sequencing has facilitated the studied of genomes, transcriptomes and proteomes. As available single-cell RNA-seq datasets are released continuously, one of the major challenges facing traditional RNA analysis tools is the high-dimensional, high-sparsity, high-noise and large-scale characteristics of single-cell RNA-seq data. Deep learning technologies match the characteristics of single-cell RNA-seq data perfectly and offer unprecedented promise. Here, we give a systematic review for most popular single-cell RNA-seq analysis methods and tools based on deep learning models, involving the procedures of data preprocessing (quality control, normalization, data correction, dimensionality reduction and data visualization) and clustering task for downstream analysis. We further evaluate the deep model-based analysis methods of data correction and clustering quantitatively on 11 gold standard datasets. Moreover, we discuss the data preferences of these methods and their limitations, and give some suggestions and guidance for users to select appropriate methods and tools.

Characterizing viral circRNAs and their application in identifying circRNAs in viruses.

Circular RNAs (circRNAs) are non-coding RNAs with a special circular structure produced formed by the reverse splicing mechanism, which play an important role in a variety of biological activities. Viruses can encode circRNA, and viral circRNAs have been found in multiple single-stranded and double-stranded viruses. However, the characteristics and functions of viral circRNAs remain unknown. Sequence alignment showed that viral circRNAs are less conserved than circRNAs in animal, indicating that the viral circRNAs may evolve rapidly. Through the analysis of the sequence characteristics of viral circRNAs and circRNAs in animal, it was found that viral circRNAs and animals circRNAs are similar in nucleic acid composition, but have obvious differences in secondary structure and autocorrelation characteristics. Based on these characteristics of viral circRNAs, machine learning algorithms were employed to construct a prediction model to identify viral circRNA. Additionally, analysis of the interaction between viral circRNA and miRNAs showed that viral circRNA is expected to interact with 518 human miRNAs, and preliminary analysis of the role of viral circRNA. And it has been also found that viral circRNAs may be involved in many KEGG pathways related to nervous system and cancer. We curated an online server, and the data and code are available: http://server.malab.cn/viral-CircRNA/.

Optimization of drug-target affinity prediction methods through feature processing schemes.

MOTIVATION: Numerous high-accuracy drug-target affinity (DTA) prediction models, whose performance is heavily reliant on the drug and target feature information, are developed at the expense of complexity and interpretability. Feature extraction and optimization constitute a critical step that significantly influences the enhancement of model performance, robustness, and interpretability. Many existing studies aim to comprehensively characterize drugs and targets by extracting features from multiple perspectives; however, this approach has drawbacks: (i) an abundance of redundant or noisy features; and (ii) the feature sets often suffer from high dimensionality. RESULTS: In this study, to obtain a model with high accuracy and strong interpretability, we utilize various traditional and cutting-edge feature selection and dimensionality reduction techniques to process self-associated features and adjacent associated features. These optimized features are then fed into learning to rank to achieve efficient DTA prediction. Extensive experimental results on two commonly used datasets indicate that, among various feature optimization methods, the regression tree-based feature selection method is most beneficial for constructing models with good performance and strong robustness. Then, by utilizing Shapley Additive Explanations values and the incremental feature selection approach, we obtain that the high-quality feature subset consists of the top 150D features and the top 20D features have a breakthrough impact on the DTA prediction. In conclusion, our study thoroughly validates the importance of feature optimization in DTA prediction and serves as inspiration for constructing high-performance and high-interpretable models. AVAILABILITY AND IMPLEMENTATION: https://github.com/RUXIAOQING964914140/FS_DTA.

COP1-ERF1-SCE1 regulatory module fine-tunes stress response under light-dark cycle in Arabidopsis.

ETHYLENE RESPONSE FACTOR 1 (ERF1) plays an important role in integrating hormone crosstalk and stress responses. Previous studies have shown that ERF1 is unstable in the dark and its degradation is mediated by UBIQUITIN-CONJUGATING ENZYME 18. However, whether there are other enzymes regulating ERF1's stability remains unclear. Here, we use various in vitro and in vivo biochemical, genetic and stress-tolerance tests to demonstrate that both CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1) and SUMO-CONJUGATING ENZYME 1 (SCE1) regulate the stability of ERF1. We also performed transcriptomic analyses to understand their common regulatory pathways. We show that COP1 mediates ERF1 ubiquitination in the dark while SCE1 mediates ERF1 sumoylation in the light. ERF1 stability is positively regulated by SCE1 and negatively regulated by COP1. Upon abiotic stress, SCE1 plays a positive role in stress defence by regulating the expression of ERF1's downstream stress-responsive genes, whereas COP1 plays a negative role in stress response. Moreover, ERF1 also promotes photomorphogenesis and the expression of light-responsive genes. Our study reveals the molecular mechanism of how COP1 and SCE1 counteract to regulate ERF1's stability and light-stress signalling crosstalk.