Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease.

Long non-coding RNA (lncRNA) genes have well-established and important impacts on molecular and cellular functions. However, among the thousands of lncRNA genes, it is still a major challenge to identify the subset with disease or trait relevance. To systematically characterize these lncRNA genes, we used Genotype Tissue Expression (GTEx) project v8 genetic and multi-tissue transcriptomic data to profile the expression, genetic regulation, cellular contexts, and trait associations of 14,100 lncRNA genes across 49 tissues for 101 distinct complex genetic traits. Using these approaches, we identified 1,432 lncRNA gene-trait associations, 800 of which were not explained by stronger effects of neighboring protein-coding genes. This included associations between lncRNA quantitative trait loci and inflammatory bowel disease, type 1 and type 2 diabetes, and coronary artery disease, as well as rare variant associations to body mass index.

Transcriptional Architecture of Synaptic Communication Delineates GABAergic Neuron Identity.

Understanding the organizational logic of neural circuits requires deciphering the biological basis of neuronal diversity and identity, but there is no consensus on how neuron types should be defined. We analyzed single-cell transcriptomes of a set of anatomically and physiologically characterized cortical GABAergic neurons and conducted a computational genomic screen for transcriptional profiles that distinguish them from one another. We discovered that cardinal GABAergic neuron types are delineated by a transcriptional architecture that encodes their synaptic communication patterns. This architecture comprises 6 categories of ∼40 gene families, including cell-adhesion molecules, transmitter-modulator receptors, ion channels, signaling proteins, neuropeptides and vesicular release components, and transcription factors. Combinatorial expression of select members across families shapes a multi-layered molecular scaffold along the cell membrane that may customize synaptic connectivity patterns and input-output signaling properties. This molecular genetic framework of neuronal identity integrates cell phenotypes along multiple axes and provides a foundation for discovering and classifying neuron types.

EpMYB2 positively regulates chicoric acid biosynthesis by activating both primary and specialized metabolic genes in purple coneflower.

Chicoric acid is the major active ingredient of the world-popular medicinal plant purple coneflower (Echinacea purpurea (L.) Menoch). It is recognized as the quality index of commercial hot-selling Echinacea products. While the biosynthetic pathway of chicoric acid in purple coneflower has been elucidated recently, its regulatory network remains elusive. Through co-expression and phylogenetic analysis, we found EpMYB2, a typical R2R3-type MYB transcription factor (TF) responsive to methyl jasmonate (MeJA) simulation, is a positive regulator of chicoric acid biosynthesis. In addition to directly regulating chicoric acid biosynthetic genes, EpMYB2 positively regulates genes of the upstream shikimate pathway. We also found that EpMYC2 could activate the expression of EpMYB2 by binding to its G-box site, and the EpMYC2-EpMYB2 module is involved in the MeJA-induced chicoric acid biosynthesis. Overall, we identified an MYB TF that positively regulates the biosynthesis of chicoric acid by activating both primary and specialized metabolic genes. EpMYB2 links the gap between the JA signaling pathway and chicoric acid biosynthesis. This work opens a new direction toward engineering purple coneflower with higher medicinal qualities.

Demographic confounders distort inference of gene regulatory and gene co-expression networks in cancer.

Gene regulatory networks (GRNs) and gene co-expression networks (GCNs) allow genome-wide exploration of molecular regulation patterns in health and disease. The standard approach for obtaining GRNs and GCNs is to infer them from gene expression data, using computational network inference methods. However, since network inference methods are usually applied on aggregate data, distortion of the networks by demographic confounders might remain undetected, especially because gene expression patterns are known to vary between different demographic groups. In this paper, we present a computational framework to systematically evaluate the influence of demographic confounders on network inference from gene expression data. Our framework compares similarities between networks inferred for different demographic groups with similarity distributions obtained for random splits of the expression data. Moreover, it allows to quantify to which extent demographic groups are represented by networks inferred from the aggregate data in a confounder-agnostic way. We apply our framework to test four widely used GRN and GCN inference methods as to their robustness w. r. t. confounding by age, ethnicity and sex in cancer. Our findings based on more than $ {44000}$ inferred networks indicate that age and sex confounders play an important role in network inference for certain cancer types, emphasizing the importance of incorporating an assessment of the effect of demographic confounders into network inference workflows. Our framework is available as a Python package on GitHub: https://github.com/bionetslab/grn-confounders.

Exploring the role of transcriptional and post-transcriptional processes in mRNA co-expression.

Co-expression of two or more genes at the single-cell level is usually associated with functional co-regulation. While mRNA co-expression-measured as the correlation in mRNA levels-can be influenced by both transcriptional and post-transcriptional events, transcriptional regulation is typically considered dominant. We review and connect the literature describing transcriptional and post-transcriptional regulation of co-expression. To enhance our understanding, we integrate four datasets spanning single-cell gene expression data, single-cell promoter activity data and individual transcript half-lives. Confirming expectations, we find that positive co-expression necessitates promoter coordination and similar mRNA half-lives. Surprisingly, negative co-expression is favored by differences in mRNA half-lives, contrary to initial predictions from stochastic simulations. Notably, this association manifests specifically within clusters of genes. We further observe a striking compensation between promoter coordination and mRNA half-lives, which additional stochastic simulations suggest might give rise to the observed co-expression patterns. These findings raise intriguing questions about the functional advantages conferred by this compensation between distal kinetic steps.

Integrated gene co-expression network analysis and experimental validation revealed potential targets of human urine extract CDA-II in treating chronic myeloid leukemia.

BACKGROUND: Cell differentiation agent II (CDA-II) exhibits potent anti-proliferative and apoptosis-inducing properties against a variety of cancer cells. However, its mechanism of action in chronic myeloid leukemia (CML) remains unclear. METHODS: Cell counting Kit 8 (CCK-8) and flow cytometry were used to investigate the effects of CDA-II on the biological characteristics of K562 cells. Gene (mRNA and lncRNA) expression profiles were analyzed by bioinformatics to screen differentially expressed genes and to perform enrichment analysis. The Pearson correlation coefficients of lncRNAs and mRNAs were calculated using gene expression values, and a lncRNA/mRNA co-expression network was constructed. The MCODE and cytoHubba plugins were used to analyze the co-expression network. RESULTS: The Results, derived from CCK-8 and flow cytometry, indicated that CDA-II exerts dual effects on K562 cells: it inhibits their proliferation and induces apoptosis. From bioinformatics analysis, we identified 316 mRNAs and 32 lncRNAs. These mRNAs were predominantly related to the meiotic cell cycle, DNA methylation, transporter complex and peptidase regulator activity, complement and coagulation cascades, protein digestion and absorption, and cell adhesion molecule signaling pathways. The co-expression network comprised of 163 lncRNA/mRNA interaction pairs. Notably, our analysis results implicated clustered histone gene families and five lncRNAs in the biological effects of CDA-II on K562 cells. CONCLUSION: This study highlights the hub gene and lncRNA/mRNA co-expression network as crucial elements in the context of CDA-II treatment of CML. This insight not only enriches our understanding of CDA-II's mechanism of action but also might provide valuable clues for subsequent experimental studies of CDA-II, and potentially contribute to the discovery of new therapeutic targets for CML.

SGCP: a spectral self-learning method for clustering genes in co-expression networks.

BACKGROUND: A widely used approach for extracting information from gene expression data employs the construction of a gene co-expression network and the subsequent computational detection of gene clusters, called modules. WGCNA and related methods are the de facto standard for module detection. The purpose of this work is to investigate the applicability of more sophisticated algorithms toward the design of an alternative method with enhanced potential for extracting biologically meaningful modules. RESULTS: We present self-learning gene clustering pipeline (SGCP), a spectral method for detecting modules in gene co-expression networks. SGCP incorporates multiple features that differentiate it from previous work, including a novel step that leverages gene ontology (GO) information in a self-leaning step. Compared with widely used existing frameworks on 12 real gene expression datasets, we show that SGCP yields modules with higher GO enrichment. Moreover, SGCP assigns highest statistical importance to GO terms that are mostly different from those reported by the baselines. CONCLUSION: Existing frameworks for discovering clusters of genes in gene co-expression networks are based on relatively simple algorithmic components. SGCP relies on newer algorithmic techniques that enable the computation of highly enriched modules with distinctive characteristics, thus contributing a novel alternative tool for gene co-expression analysis.

Contribution of FOS in neutrophils to venous thromboembolism via miR-144 based on bioinformatic prediction and validation.

The Finkel-Biskis-Jinkins Osteosarcoma (c-Fos; encoded by FOS) plays an important role in several cardiovascular diseases, including atherosclerosis and stroke. However, the relationship between FOS and venous thromboembolism (VTE) remains unknown. We identified differentially expressed genes in Gene Expression Omnibus dataset, GSE48000, comprising VTE patients and healthy individuals, and analysed them using CIBERSORT and weighted co-expression network analysis (WGCNA). FOS and CD46 expressions were significantly downregulated (FOS p = 2.26E-05, CD64 p = 8.83E-05) and strongly linked to neutrophil activity in VTE. We used GSE19151 and performed PCR to confirm that FOS and CD46 had diagnostic potential for VTE; however, only FOS showed differential expression by PCR and ELISA in whole blood samples. Moreover, we found that hsa-miR-144 which regulates FOS expression was significantly upregulated in VTE. Furthermore, FOS expression was significantly downregulated in neutrophils of VTE patients (p = 0.03). RNA sequencing performed on whole blood samples of VTE patients showed that FOS exerted its effects in VTE via the leptin-mediated adipokine signalling pathway. Our results suggest that FOS and related genes or proteins can outperform traditional clinical markers and may be used as diagnostic biomarkers for VTE.

Core cellular and tissue-specific mechanisms enable desiccation tolerance in Craterostigma.

Resurrection plants can survive prolonged life without water (anhydrobiosis) in regions with seasonal drying. This desiccation tolerance requires the coordination of numerous cellular processes across space and time, and individual plant tissues face unique constraints related to their function. Here, we analyzed the complex, octoploid genome of the model resurrection plant Craterostigma (C. plantagineum), and surveyed spatial and temporal expression dynamics to identify genetic elements underlying desiccation tolerance. Homeologous genes within the Craterostigma genome have divergent expression profiles, suggesting the subgenomes contribute differently to desiccation tolerance traits. The Craterostigma genome contains almost 200 tandemly duplicated early light-induced proteins, a hallmark trait of desiccation tolerance, with massive upregulation under water deficit. We identified a core network of desiccation-responsive genes across all tissues, but observed almost entirely unique expression dynamics in each tissue during recovery. Roots and leaves have differential responses related to light and photoprotection, autophagy and nutrient transport, reflecting their divergent functions. Our findings highlight a universal set of likely ancestral desiccation tolerance mechanisms to protect cellular macromolecules under anhydrobiosis, with secondary adaptations related to tissue function.

Time of day and genotype sensitivity adjust molecular responses to temperature stress in sorghum.

Sorghum is one of the four major C4 crops that are considered to be tolerant to environmental extremes. Sorghum shows distinct growth responses to temperature stress depending on the sensitivity of the genetic background. About half of the transcripts in sorghum exhibit diurnal rhythmic expressions emphasizing significant coordination with the environment. However, an understanding of how molecular dynamics contribute to genotype-specific stress responses in the context of the time of day is not known. We examined whether temperature stress and the time of day impact the gene expression dynamics in thermo-sensitive and thermo-tolerant sorghum genotypes. We found that time of day is highly influencing the temperature stress responses, which can be explained by the rhythmic expression of most thermo-responsive genes. This effect is more pronounced in thermo-tolerant genotypes, suggesting a stronger regulation of gene expression by the time of day and/or by the circadian clock. Genotypic differences were mostly observed on average gene expression levels, which may be responsible for contrasting sensitivities to temperature stress in tolerant versus susceptible sorghum varieties. We also identified groups of genes altered by temperature stress in a time-of-day and genotype-specific manner. These include transcriptional regulators and several members of the Ca2+ -binding EF-hand protein family. We hypothesize that expression variation of these genes between genotypes along with time-of-day independent regulation may contribute to genotype-specific fine-tuning of thermo-responsive pathways. These findings offer a new opportunity to selectively target specific genes in efforts to develop climate-resilient crops based on their time-of-day and genotype variation responses to temperature stress.

Ectomycorrhizal symbiosis prepares its host locally and systemically for abiotic cue signaling.

Tree growth and survival are dependent on their ability to perceive signals, integrate them, and trigger timely and fitted molecular and growth responses. While ectomycorrhizal symbiosis is a predominant tree-microbe interaction in forest ecosystems, little is known about how and to what extent it helps trees cope with environmental changes. We hypothesized that the presence of Laccaria bicolor influences abiotic cue perception by Populus trichocarpa and the ensuing signaling cascade. We submitted ectomycorrhizal or non-ectomycorrhizal P. trichocarpa cuttings to short-term cessation of watering or ozone fumigation to focus on signaling networks before the onset of any physiological damage. Poplar gene expression, metabolite levels, and hormone levels were measured in several organs (roots, leaves, mycorrhizas) and integrated into networks. We discriminated the signal responses modified or maintained by ectomycorrhization. Ectomycorrhizas buffered hormonal changes in response to short-term environmental variations systemically prepared the root system for further fungal colonization and alleviated part of the root abscisic acid (ABA) signaling. The presence of ectomycorrhizas in the roots also modified the leaf multi-omics landscape and ozone responses, most likely through rewiring of the molecular drivers of photosynthesis and the calcium signaling pathway. In conclusion, P. trichocarpa-L. bicolor symbiosis results in a systemic remodeling of the host's signaling networks in response to abiotic changes. In addition, ectomycorrhizal, hormonal, metabolic, and transcriptomic blueprints are maintained in response to abiotic cues, suggesting that ectomycorrhizas are less responsive than non-mycorrhizal roots to abiotic challenges.

Organ-enriched gene expression during floral morphogenesis in wild barley.

Floral morphology varies considerably between dicots and monocots. The ABCDE model explaining how floral organ development is controlled was formulated using core eudicots and applied to grass crops. Barley (Hordeum. vulgare) has unique floral morphogenesis. Wild barley (H. vulgare ssp. spontaneum), which is the immediate ancestor of cultivated barley (H. vulgare ssp. vulgare), contains a rich reservoir of genetic diversity. However, the wild barley genes involved in floral organ development are still relatively uncharacterized. In this study, we generated an organ-specific transcriptome atlas for wild barley floral organs. Genome-wide transcription profiles indicated that 22 838 protein-coding genes were expressed in at least one organ. These genes were grouped into seven clusters according to the similarities in their expression patterns. Moreover, 5619 genes exhibited organ-enriched expression, 677 of which were members of 47 transcription factor families. Gene ontology analyses suggested that the functions of the genes with organ-enriched expression influence the biological processes in floral organs. The co-expression regulatory network showed that the expression of 690 genes targeted by MADS-box proteins was highly positively correlated with the expression of ABCDE model genes during floral morphogenesis. Furthermore, the expression of 138 genes was specific to the wild barley OUH602 genome and not the Morex genome; most of these genes were highly expressed in the glume, awn, lemma, and palea. This study revealed the global gene expression patterns underlying floral morphogenesis in wild barley. On the basis of the study findings, a molecular mechanism controlling floral morphology in barley was proposed.

Gene expression and expression quantitative trait loci analyses uncover natural variations underlying the improvement of important agronomic traits during modern maize breeding.

Maize (Zea mays L.) is a major staple crop worldwide, and during modern maize breeding, cultivars with increased tolerance to high-density planting and higher yield per plant have contributed significantly to the increased yield per unit land area. Systematically identifying key agronomic traits and their associated genomic changes during modern maize breeding remains a significant challenge because of the complexity of genetic regulation and the interactions of the various agronomic traits, with most of them being controlled by numerous small-effect quantitative trait loci (QTLs). Here, we performed phenotypic and gene expression analyses for a set of 137 elite inbred lines of maize from different breeding eras in China. We found four yield-related traits are significantly improved during modern maize breeding. Through gene-clustering analyses, we identified four groups of expressed genes with distinct trends of expression pattern change across the historical breeding eras. In combination with weighted gene co-expression network analysis, we identified several candidate genes regulating various plant architecture- and yield-related agronomic traits, such as ZmARF16, ZmARF34, ZmTCP40, ZmPIN7, ZmPYL10, ZmJMJ10, ZmARF1, ZmSWEET15b, ZmGLN6 and Zm00001d019150. Further, by combining expression quantitative trait loci (eQTLs) analyses, correlation coefficient analyses and population genetics, we identified a set of candidate genes that might have been under selection and contributed to the genetic improvement of various agronomic traits during modern maize breeding, including a number of known key regulators of plant architecture, flowering time and yield-related traits, such as ZmPIF3.3, ZAG1, ZFL2 and ZmBES1. Lastly, we validated the functional variations in GL15, ZmPHYB2 and ZmPYL10 that influence kernel row number, flowering time, plant height and ear height, respectively. Our results demonstrates the effectiveness of our combined approaches for uncovering key candidate regulatory genes and functional variation underlying the improvement of important agronomic traits during modern maize breeding, and provide a valuable genetic resource for the molecular breeding of maize cultivars with tolerance for high-density planting.

An across breed, diet and tissue analysis reveals the transcription factor NR1H3 as a key mediator of residual feed intake in beef cattle.

BACKGROUND: Provision of feed is a major determinant of overall profitability in beef production systems, accounting for up to 75% of the variable costs. Thus, improving cattle feed efficiency, by way of determining the underlying genomic control and subsequently selecting for feed efficient cattle, provides a method through which feed input costs may be reduced. The objective of this study was to undertake gene co-expression network analysis using RNA-Sequence data generated from Longissimus dorsi and liver tissue samples collected from steers of two contrasting breeds (Charolais and Holstein-Friesian) divergent for residual feed intake (RFI), across two consecutive distinct dietary phases (zero-grazed grass and high-concentrate). Categories including differentially expressed genes (DEGs) based on the contrasts of RFI phenotype, breed and dietary source, as well as key transcription factors and proteins secreted in plasma were utilised as nodes of the gene co-expression network. RESULTS: Of the 2,929 DEGs within the network analysis, 1,604 were reported to have statistically significant correlations (≥ 0.80), resulting in a total of 43,876 significant connections between genes. Pathway analysis of clusters of co-expressed genes revealed enrichment of processes related to lipid metabolism (fatty acid biosynthesis, fatty acid ß-oxidation, cholesterol biosynthesis), immune function, (complement cascade, coagulation system, acute phase response signalling), and energy production (oxidative phosphorylation, mitochondrial L-carnitine shuttle pathway) based on genes related to RFI, breed and dietary source contrasts. CONCLUSIONS: Although similar biological processes were evident across the three factors examined, no one gene node was evident across RFI, breed and diet contrasts in both liver and muscle tissues. However within the liver tissue, the IRX4, NR1H3, HOXA13 and ZNF648 gene nodes, which all encode transcription factors displayed significant connections across the RFI, diet and breed comparisons, indicating a role for these transcription factors towards the RFI phenotype irrespective of diet and breed. Moreover, the NR1H3 gene encodes a protein secreted into plasma from the hepatocytes of the liver, highlighting the potential for this gene to be explored as a robust biomarker for the RFI trait in beef cattle.

Integrated analysis of transcriptomics and defense-related phytohormones to discover hub genes conferring maize Gibberella ear rot caused by Fusarium Graminearum.

BACKGROUND: Gibberella ear rot (GER) is one of the most devastating diseases in maize growing areas, which directly reduces grain yield and quality. However, the underlying defense response of maize to pathogens infection is largely unknown. RESULTS: To gain a comprehensive understanding of the defense response in GER resistance, two contrasting inbred lines 'Nov-82' and 'H10' were used to explore transcriptomic profiles and defense-related phytohormonal alterations during Fusarium graminearum infection. Transcriptomic analysis revealed 4,417 and 4,313 differentially expressed genes (DEGs) from the Nov-82 and H10, respectively, and 647 common DEGs between the two lines. More DEGs were obviously enriched in phenylpropanoid biosynthesis, secondary metabolites biosynthesis, metabolic process and defense-related pathways. In addition, the concentration of the defense-related phytohormones, jasmonates (JAs) and salicylates (SAs), was greatly induced after the pathogen infection. The level of JAs in H10 was more higher than in Nov-82, whereas an opposite pattern for the SA between the both lines. Integrated analysis of the DEGs and the phytohormones revealed five vital modules based on co-expression network analysis according to their correlation. A total of 12 hub genes encoding fatty acid desaturase, subtilisin-like protease, ethylene-responsive transcription factor, 1-aminocyclopropane-1-carboxylate oxidase, and sugar transport protein were captured from the key modules, indicating that these genes might play unique roles in response to pathogen infection, CONCLUSIONS: Overall, our results indicate that large number DEGs related to plant disease resistance and different alteration of defensive phytohormones were activated during F. graminearum infection, providing new insight into the defense response against pathogen invasion, in addition to the identified hub genes that can be further investigated for enhancing maize GER resistance.

LncRNA and mRNA expression characteristic and bioinformatic analysis in myocardium of diabetic cardiomyopathy mice.

BACKGROUND: Diabetic cardiomyopathy (DCM) is becoming a very well-known clinical entity and leads to increased heart failure in diabetic patients. Long non-coding RNAs (LncRNAs) play an important role in the pathogenesis of DCM. In the present study, the expression profiles of lncRNAs and mRNAs were illuminated in myocardium from DCM mice, with purpose of exploring probable pathological processes of DCM involved by differentially expressed genes in order to provide a new direction for the future researches of DCM. RESULTS: The results showed that a total of 93 differentially expressed lncRNA transcripts and 881 mRNA transcripts were aberrantly expressed in db/db mice compared with the controls. The top 6 differentially expressed lncRNAs like up-regulated Hmga1b, Gm8909, Gm50252 and down-regulated Msantd4, 4933413J09Rik, Gm41414 have not yet been reported in DCM. The lncRNAs-mRNAs co-expression network analysis showed that LncRNA 2610507I01Rik, 2310015A16Rik, Gm10503, A930015D03Rik and Gm48483 were the most relevant to differentially expressed mRNAs. CONCLUSION: Our results showed that db/db DCM mice exist differentially expressed lncRNAs and mRNAs in hearts. These differentially expressed lncRNAs may be involved in the pathological process of cardiomyocyte apoptosis and fibrosis in DCM.

Exploring the gene expression network involved in the heat stress response of a thermotolerant tomato genotype.

BACKGROUND: The increase in temperatures due to the current climate change dramatically affects crop cultivation, resulting in yield losses and altered fruit quality. Tomato is one of the most extensively grown and consumed horticultural products, and although it can withstand a wide range of climatic conditions, heat stress can affect plant growth and development specially on the reproductive stage, severely influencing the final yield. In the present work, the heat stress response mechanisms of one thermotolerant genotype (E42) were investigated by exploring its regulatory gene network. This was achieved through a promoter analysis based on the identification of the heat stress elements (HSEs) mapping in the promoters, combined with a gene co-expression network analysis aimed at identifying interactions among heat-related genes. RESULTS: Results highlighted 82 genes presenting HSEs in the promoter and belonging to one of the 52 gene networks obtained by the GCN analysis; 61 of these also interact with heat shock factors (Hsfs). Finally, a list of 13 candidate genes including two Hsfs, nine heat shock proteins (Hsps) and two GDSL esterase/lipase (GELPs) were retrieved by focusing on those E42 genes exhibiting HSEs in the promoters, interacting with Hsfs and showing variants, compared to Heinz reference genome, with HIGH and/or MODERATE impact on the translated protein. Among these, the Gene Ontology annotation analysis evidenced that only LeHsp100 (Solyc02g088610) belongs to a network specifically involved in the response to heat stress. CONCLUSIONS: As a whole, the combination of bioinformatic analyses carried out on genomic and trascriptomic data available for tomato, together with polymorphisms detected in HS-related genes of the thermotolerant E42 allowed to determine a subset of candidate genes involved in the HS response in tomato. This study provides a novel approach in the investigation of abiotic stress response mechanisms and further studies will be conducted to validate the role of the highlighted genes.

Cell-type brain-region specific changes in prefrontal cortex of a mouse model of alcohol dependence.

The prefrontal cortex is a crucial regulator of alcohol drinking, and dependence, and other behavioral phenotypes associated with AUD. Comprehensive identification of cell-type specific transcriptomic changes in alcohol dependence will improve our understanding of mechanisms underlying the excessive alcohol use associated with alcohol dependence and will refine targets for therapeutic development. We performed single nucleus RNA sequencing (snRNA-seq) and Visium spatial gene expression profiling on the medial prefrontal cortex (mPFC) obtained from C57BL/6 J mice exposed to the two-bottle choice-chronic intermittent ethanol (CIE) vapor exposure (2BC-CIE, defined as dependent group) paradigm which models phenotypes of alcohol dependence including escalation of alcohol drinking. Gene co-expression network analysis and differential expression analysis identified highly dysregulated co-expression networks in multiple cell types. Dysregulated modules and their hub genes suggest novel understudied targets for studying molecular mechanisms contributing to the alcohol dependence state. A subtype of inhibitory neurons was the most alcohol-sensitive cell type and contained a downregulated gene co-expression module; the hub gene for this module is Cpa6, a gene previously identified by GWAS to be associated with excessive alcohol consumption. We identified an astrocytic Gpc5 module significantly upregulated in the alcohol-dependent group. To our knowledge, there are no studies linking Cpa6 and Gpc5 to the alcohol-dependent phenotype. We also identified neuroinflammation related gene expression changes in multiple cell types, specifically enriched in microglia, further implicating neuroinflammation in the escalation of alcohol drinking. Here, we present a comprehensive atlas of cell-type specific alcohol dependence mediated gene expression changes in the mPFC and identify novel cell type-specific targets implicated in alcohol dependence.

PTBP1-mediated repression of neuron-specific CDC42 splicing constitutes a genomic alteration-independent, developmentally conserved vulnerability in IDH-wildtype glioblastoma.

Gene co-expression networks may encode hitherto inadequately recognized vulnerabilities for adult gliomas. By identifying evolutionally conserved gene co-expression modules around EGFR (EM) or PDGFRA (PM), we recently proposed an EM/PM classification scheme, which assigns IDH-wildtype glioblastomas (GBM) into the EM subtype committed in neural stem cell compartment, IDH-mutant astrocytomas and oligodendrogliomas into the PM subtype committed in early oligodendrocyte lineage. Here, we report the identification of EM/PM subtype-specific gene co-expression networks and the characterization of hub gene polypyrimidine tract-binding protein 1 (PTBP1) as a genomic alteration-independent vulnerability in IDH-wildtype GBM. Supervised by the EM/PM classification scheme, we applied weighted gene co-expression network analysis to identify subtype-specific global gene co-expression modules. These gene co-expression modules were characterized for their clinical relevance, cellular origin and conserved expression pattern during brain development. Using lentiviral vector-mediated constitutive or inducible knockdown, we characterized the effects of PTBP1 on the survival of IDH-wildtype GBM cells, which was complemented with the analysis of PTBP1-depedent splicing pattern and overexpression of splicing target neuron-specific CDC42 (CDC42-N) isoform.  Transcriptomes of adult gliomas can be robustly assigned into 4 large gene co-expression modules that are prognostically relevant and are derived from either malignant cells of the EM/PM subtypes or tumor microenvironment. The EM subtype is associated with a malignant cell-intrinsic gene module involved in pre-mRNA splicing, DNA replication and damage response, and chromosome segregation, and a microenvironment-derived gene module predominantly involved in extracellular matrix organization and infiltrating immune cells. The PM subtype is associated with two malignant cell-intrinsic gene modules predominantly involved in transcriptional regulation and mRNA translation, respectively. Expression levels of these gene modules are independent prognostic factors and malignant cell-intrinsic gene modules are conserved during brain development. Focusing on the EM subtype, we identified PTBP1 as the most significant hub for the malignant cell-intrinsic gene module. PTBP1 is not altered in most glioma genomes. PTBP1 represses the conserved splicing of CDC42-N. PTBP1 knockdown or CDC42-N overexpression disrupts actin cytoskeleton dynamics, causing accumulation of reactive oxygen species and cell apoptosis. PTBP1-mediated repression of CDC42-N splicing represents a potential genomic alteration-independent, developmentally conserved vulnerability in IDH-wildtype GBM.

Comparative physiology and transcriptome response patterns in cold-tolerant and cold-sensitive varieties of Solanum melongena.

BACKGROUND: Climate change has led to severe cold events, adversely impacting global crop production. Eggplant (Solanum melongena L.), a significant economic crop, is highly susceptible to cold damage, affecting both yield and quality. Unraveling the molecular mechanisms governing cold resistance, including the identification of key genes and comprehensive transcriptional regulatory pathways, is crucial for developing new varieties with enhanced tolerance. RESULTS: In this study, we conducted a comparative analysis of leaf physiological indices and transcriptome sequencing results. The orthogonal partial least squares discriminant analysis (OPLS-DA) highlighted peroxidase (POD) activity and soluble protein as crucial physiological indicators for both varieties. RNA-seq data analysis revealed that a total of 7024 and 6209 differentially expressed genes (DEGs) were identified from variety "A" and variety "B", respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of DEGs demonstrated that the significant roles of starch and sucrose metabolism, glutathione metabolism, terpenoid synthesis, and energy metabolism (sucrose and starch metabolism) were the key pathways in eggplant. Weighted gene co-expression network analysis (WGCNA) shown that the enrichment of numerous cold-responsive genes, pathways, and soluble proteins in the MEgrep60 modules. Core hub genes identified in the co-expression network included POD, membrane transporter-related gene MDR1, abscisic acid-related genes, growth factor enrichment gene DELLA, core components of the biological clock PRR7, and five transcription factors. Among these, the core transcription factor MYB demonstrated co-expression with signal transduction, plant hormone, biosynthesis, and metabolism-related genes, suggesting a pivotal role in the cold response network. CONCLUSION: This study integrates physiological indicators and transcriptomics to unveil the molecular mechanisms responsible for the differences in cold tolerance between the eggplant cold-tolerant variety "A" and the cold-sensitive variety "B". These mechanisms include modulation of reactive oxygen species (ROS), elevation in osmotic carbohydrate and free proline content, and the expression of terpenoid synthesis genes. This comprehensive understanding contributes valuable insights into the molecular underpinnings of cold stress tolerance, ultimately aiding in the improvement of crop cold tolerance.