CEMiTool: a Bioconductor package for performing comprehensive modular co-expression analyses

Circulating serum miR-362-3p and miR-6721-5p as potential biomarkers for classification patients with adult-type diffuse glioma

According to the fifth edition of the WHO Classification of Tumours of the Central Nervous System (CNS) published in 2021, grade 4 gliomas classification includes IDH-mutant astrocytomas and wild-type IDH glioblastomas. Unfortunately, despite precision oncology development, the prognosis for patients with grade 4 glioma remains poor, indicating an urgent need for better diagnostic and therapeutic strategies. Circulating miRNAs besides being important regulators of cancer development could serve as promising diagnostic biomarkers for patients with grade 4 glioma. Here, we propose a two-miRNA miR-362-3p and miR-6721-5p screening signature for serum for non-invasive classification of identified glioma cases into the highest-grade 4 and lower-grade gliomas. A total of 102 samples were included in this study, comprising 78 grade 4 glioma cases and 24 grade 2-3 glioma subjects. Using the NanoString platform, seven miRNAs were identified as differentially expressed (DE), which was subsequently confirmed via RT-qPCR analysis. Next, numerous combinations of DE miRNAs were employed to develop classification models. The dual panel of miR-362-3p and miR-6721-5p displayed the highest diagnostic value to differentiate grade 4 patients and lower grade cases with an AUC of 0.867. Additionally, this signature also had a high AUC = 0.854 in the verification cohorts by RT-qPCR and an AUC = 0.842 using external data from the GEO public database. The functional annotation analyses of predicted DE miRNA target genes showed their primary involvement in the STAT3 and HIF-1 signalling pathways and the signalling pathway of pluripotency of stem cells and glioblastoma-related pathways. For additional exploration of miRNA expression patterns correlated with glioma, we performed the Weighted Gene-Co Expression Network Analysis (WGCNA). We showed that the modules most associated with glioma grade contained as many as six DE miRNAs. In conclusion, this study presents the first evidence of serum miRNA expression profiling in adult-type diffuse glioma using a classification based on the WHO 2021 guidelines. We expect that the discovered dual miR-362-3p and miR-6721-5p signatures have the potential to be utilised for grading gliomas in clinical applications.

Evolution of chemosensory tissues and cells across ecologically diverse Drosophilids

Chemosensory tissues exhibit significant between-species variability, yet the evolution of gene expression and cell types underlying this diversity remain poorly understood. To address these questions, we conducted transcriptomic analyses of five chemosensory tissues from six Drosophila species and integrated the findings with single-cell datasets. While stabilizing selection predominantly shapes chemosensory transcriptomes, thousands of genes in each tissue have evolved expression differences. Genes that have changed expression in one tissue have often changed in multiple other tissues but at different past epochs and are more likely to be cell type-specific than unchanged genes. Notably, chemosensory-related genes have undergone widespread expression changes, with numerous species-specific gains/losses including novel chemoreceptors expression patterns. Sex differences are also pervasive, including a D. melanogaster-specific excess of male-biased expression in sensory and muscle cells in its forelegs. Together, our analyses provide new insights for understanding evolutionary changes in chemosensory tissues at both global and individual gene levels.

Whole blood RNA sequencing identifies transcriptional differences between primary sclerosing cholangitis and ulcerative colitis

Background & Aims

Genetic and microbiome studies across patients with primary sclerosing cholangitis (PSC) and ulcerative colitis (UC) have indicated that UC in PSC is a separate disease entity to primary UC, but expression studies for PSC are lacking.

Methods

We conducted whole blood RNA sequencing experiments for 495 patients with UC, 220 patients with PSC (including 177 with UC), and 320 healthy controls from Germany and Norway. Differential expression analyses, gene ontology and coexpression analyses and random forest machine learning were performed to identify genes, ontologies and transcriptional features that discriminate diagnoses.

Results

The blood transcriptome in UC and PSC is dominated by neutrophil activation genes (e.g. S100A12). In UC, but not in PSC (neither PSC alone nor patients with an additional diagnosis of UC [PSC/UC]), ribosomal, mitochondrial, and energy metabolism genes are upregulated in conjunction with antibody transcript expression (MZB1, IGJ). In PSC, there is an increase in modules related to apoptosis and expression of genes of interferon-I-related ontologies. Random forest analysis could poorly discriminate PSC alone from PSC/UC (AUROC 0.56), but could discriminate PSC, UC, and controls with high accuracy (AUROC UC vs. controls 0.95, PSC vs. controls 0.88, UC vs. PSC 0.986). The main coexpression modules relevant for distinguishing PSC, UC, and controls are enriched in neutrophil degranulation and antibody production genes.

Conclusions

Supported by machine learning results, PSC and UC appear to be separate entities on a molecular level, while PSC/UC and PSC are indistinguishable.

Impact and implications

Clinical and genetic studies suggest that the colitis-like symptoms in primary sclerosing cholangitis (PSC) represent a different disease entity from primary ulcerative colitis (UC). The present study supports this assumption with transcriptomic data from whole blood and describes notable differences in gene expression between primary UC and PSC, providing insights into the still unclear pathophysiology of both diseases. These findings are of interest to scientists seeking to decipher the molecular pathophysiology of both diseases and provide evidence that a redefinition of the PSC-UC phenotype should be considered. The study practically supports future molecular research by providing a large transcriptomic whole blood reference cohort.

Deciphering head and neck cancer microenvironment: Single-cell and spatial transcriptomics reveals human papillomavirus-associated differences

Human papillomavirus (HPV) is a major causative factor of head and neck squamous cell carcinoma (HNSCC), and the incidence of HPV- associated HNSCC is increasing. The role of tumor microenvironment in viral infection and metastasis needs to be explored further. We studied the molecular characteristics of primary tumors (PTs) and lymph node metastatic tumors (LNMTs) by stratifying them based on their HPV status. Eight samples for single-cell RNA profiling and six samples for spatial transcriptomics (ST), composed of matched primary tumors (PT) and lymph node metastases (LNMT), were collected from both HPV- negative (HPV- ) and HPV-positive (HPV+ ) patients. Using the 10x Genomics Visium platform, integrative analyses with single-cell RNA sequencing were performed. Intracellular and intercellular alterations were analyzed, and the findings were confirmed using experimental validation and publicly available data set. The HPV+ tissues were composed of a substantial amount of lymphoid cells regardless of the presence or absence of metastasis, whereas the HPV- tissue exhibited remarkable changes in the number of macrophages and plasma cells, particularly in the LNMT. From both single-cell RNA and ST data set, we discovered a central gene, pyruvate kinase muscle isoform 1/2 (PKM2), which is closely associated with the stemness of cancer stem cell-like populations in LNMT of HPV- tissue. The consistent expression was observed in HPV- HNSCC cell line and the knockdown of PKM2 weakened spheroid formation ability. Furthermore, we found an ectopic lymphoid structure morphology and clinical effects of the structure in ST slide of the HPV+ patients and verified their presence in tumor tissue using immunohistochemistry. Finally, the ephrin-A (EPHA2) pathway was detected as important signals in angiogenesis for HPV- patients from single-cell RNA and ST profiles, and knockdown of EPHA2 declined the cell migration. Our study described the distinct cellular composition and molecular alterations in primary and metastatic sites in HNSCC patients based on their HPV status. These results provide insights into HNSCC biology in the context of HPV infection and its potential clinical implications.

Comprehensive modular analyses of scar subtypes illuminate underlying molecular mechanisms and potential therapeutic targets

Pathological scarring resulting from traumas and wounds, such as hypertrophic scars and keloids, pose significant aesthetic, functional and psychological challenges. This study provides a comprehensive transcriptomic analysis of these conditions, aiming to illuminate underlying molecular mechanisms and potential therapeutic targets. We employed a co-expression and module analysis tool to identify significant gene clusters associated with distinct pathophysiological processes and mechanisms, notably lipid metabolism, sebum production, cellular energy metabolism and skin barrier function. This examination yielded critical insights into several skin conditions including folliculitis, skin fibrosis, fibrosarcoma and congenital ichthyosis. Particular attention was paid to Module Cluster (MCluster) 3, encompassing genes like BLK, TRPV1 and GABRD, all displaying high expression and potential implications in immune modulation. Preliminary immunohistochemistry validation supported these findings, showing elevated expression of these genes in non-fibrotic samples rich in immune activity. The complex interplay of different cell types in scar formation, such as fibroblasts, myofibroblasts, keratinocytes and mast cells, was also explored, revealing promising therapeutic strategies. This study underscores the promise of targeted gene therapy for pathological scars, paving the way for more personalised therapeutic approaches. The results necessitate further research to fully ascertain the roles of these identified genes and pathways in skin disease pathogenesis and potential therapeutics. Nonetheless, our work forms a strong foundation for a new era of personalised medicine for patients suffering from pathological scarring.

Single-cell transcriptional landscape of long non-coding RNAs orchestrating mouse heart development

Long non-coding RNAs (lncRNAs) comprise the most representative transcriptional units of the mammalian genome. They are associated with organ development linked with the emergence of cardiovascular diseases. We used bioinformatic approaches, machine learning algorithms, systems biology analyses, and statistical techniques to define co-expression modules linked to heart development and cardiovascular diseases. We also uncovered differentially expressed transcripts in subpopulations of cardiomyocytes. Finally, from this work, we were able to identify eight cardiac cell-types; several new coding, lncRNA, and pcRNA markers; two cardiomyocyte subpopulations at four different time points (ventricle E9.5, left ventricle E11.5, right ventricle E14.5 and left atrium P0) that harbored co-expressed gene modules enriched in mitochondrial, heart development and cardiovascular diseases. Our results evidence the role of particular lncRNAs in heart development and highlight the usage of co-expression modular approaches in the cell-type functional definition.

Downregulated NPAS4 in multiple brain regions is associated with major depressive disorder

Major Depressive Disorder (MDD) is a commonly observed psychiatric disorder that affects more than 2% of the world population with a rising trend. However, disease-associated pathways and biomarkers are yet to be fully comprehended. In this study, we analyzed previously generated RNA-seq data across seven different brain regions from three distinct studies to identify differentially and co-expressed genes for patients with MDD. Differential gene expression (DGE) analysis revealed that NPAS4 is the only gene downregulated in three different brain regions. Furthermore, co-expressing gene modules responsible for glutamatergic signaling are negatively enriched in these regions. We used the results of both DGE and co-expression analyses to construct a novel MDD-associated pathway. In our model, we propose that disruption in glutamatergic signaling-related pathways might be associated with the downregulation of NPAS4 and many other immediate-early genes (IEGs) that control synaptic plasticity. In addition to DGE analysis, we identified the relative importance of KEGG pathways in discriminating MDD phenotype using a machine learning-based approach. We anticipate that our study will open doors to developing better therapeutic approaches targeting glutamatergic receptors in the treatment of MDD.

Transcriptional upregulation of galectin-3 in multiple sclerosis

Multiple sclerosis (MS) is an autoimmune, demyelinating disorder of the central nervous system (CNS) affecting approximately 2.5 million people worldwide. The mechanisms underlying the pathogenesis of MS are still only partially elucidated. Galectins are a family of β-galactoside-binding lectins that are involved in the regulation of immune and inflammatory responses and have been shown to exert a role in the maintenance of central nervous system (CNS) homeostasis. There has been an increasing interest in the role of galectin-3 in neuroinflammation and neurodegeneration. In the current study, we have evaluated the expression levels of galectin-3 in different cellular populations involved in the etiopathogenesis of MS. We have observed dramatically higher transcriptomic levels of galectin-3 in encephalitogenic CD4+ T cells in a preclinical model of MS, the MOG-induced experimental allergic encephalomyelitis (EAE). Also, significantly higher levels of galectin-3 were found in microglial cells, astrocytes, and oligodendrocytes isolated from the spinal cord of EAE mice, as well as in human MS-related white matter lesions. Modular co-expression analysis revealed that galectin-3 is co-expressed with genes involved in the regulation of microglia, cytokine production, and chemotaxis. This is the first comprehensive analysis of the expression of galectin-3 in MS, further strengthening its potential pathogenetic role in the etiopathogenesis of this CNS autoimmune disorder.

Identification of serum miR-1246 and miR-150-5p as novel diagnostic biomarkers for high-grade serous ovarian cancer

Epithelial ovarian cancer (EOC) is one of the leading cancers in women, with high-grade serous ovarian cancer (HGSOC) being the most common and lethal subtype of this disease. A vast majority of HGSOC are diagnosed at the late stage of the disease when the treatment and total recovery chances are low. Thus, there is an urgent need for novel, more sensitive and specific methods for early and routine HGSOC clinical diagnosis. In this study, we performed miRNA expression profiling using the NanoString miRNA assay in 34 serum samples from patients with HGSOC and 36 healthy women. We identified 13 miRNAs that were differentially expressed (DE). For additional exploration of expression patterns correlated with HGSOC, we performed weighted gene co-expression network analysis (WGCNA). As a result, we showed that the module most correlated with tumour size, nodule and metastasis contained 8 DE miRNAs. The panel including miR-1246 and miR-150-5p was identified as a signature that could discriminate HGSOC patients with AUCs of 0.98 and 1 for the training and test sets, respectively. Furthermore, the above two-miRNA panel had an AUC = 0.946 in the verification cohorts of RT-qPCR data and an AUC = 0.895 using external data from the GEO public database. Thus, the model we developed has the potential to markedly improve the diagnosis of ovarian cancer.

Multi-layered transcriptomic analysis reveals a pivotal role of FMR1 and other developmental genes in Alzheimer's disease-associated brain ceRNA network

Alzheimer's disease (AD) is an increasingly neurodegenerative disorder that causes progressive cognitive decline and memory impairment. Despite extensive research, the underlying causes of late-onset AD (LOAD) are still in progress. This study aimed to establish a network of competing regulatory interactions involving circular RNAs (circRNAs), microRNAs (miRNAs), RNA-binding proteins (RBPs), and messenger RNAs (mRNAs) connected to LOAD. A systematic analysis of publicly available expression data was conducted to identify integrated differentially expressed genes (DEGs) from the hippocampus of LOAD patients. Subsequently, gene co-expression analysis identified modules comprising highly expressed DEGs that act cooperatively. The competition between co-expressed DEGs and miRNAs/RBPs and the simultaneous interactions between circRNA and miRNA/RBP revealed a complex ceRNA network responsible for post-transcriptional regulation in LOAD. Hippocampal expression data for miRNAs, circRNAs, and RBPs were used to filter relevant relationships for AD. An integrated topological score was used to identify the highly connected hub gene, from which a brain core ceRNA subnetwork was generated. The Fragile X Messenger Ribonucleoprotein 1 (FMR1) coding for the RBP FMRP emerged as the prominent driver gene in this subnetwork. FMRP has been previously related to AD but not in a ceRNA network context. Also, the substantial number of neurodevelopmental genes in the ceRNA subnetwork and their related biological pathways strengthen that AD shares common pathological mechanisms with developmental conditions. Our results enhance the current knowledge about the convergent ceRNA regulatory pathways underlying AD and provide potential targets for identifying early biomarkers and developing novel therapeutic interventions.

HDACi-dependent Microenvironmental Normalization Overcomes Tumor Burden-induced T-cell Exhaustion

PURPOSE

T-cell exhaustion limits immunotherapy for the treatment of solid tumors. Although immune checkpoint blockade and adoptive T-cell therapy (ACT) can mediate tumor regression, their potency is often determined by tumor burden. Here, we identified tumor burden-related pathway changes that are conducive to T-cell exhaustion. We then determined whether microenvironmental reprogramming via epigenetic modulation could reverse T-cell exhaustion and improve immunotherapeutic responsiveness.

EXPERIMENTAL DESIGN

We developed a murine syngeneic tumor model wherein an increased burden ablated therapeutic responsiveness to ACT, which corresponded with systemic induction of T-cell exhaustion. Transcriptome analysis of these large tumors allowed us to characterize changes to immunosuppressive pathway expression during class I histone deacetylase inhibitor MS-275 treatment. We then measured the therapeutic impact of MS-275 during ACT and assessed T-cell exhaustion by transcriptome/phenotypic analysis.

RESULTS

ACT durably regressed small tumors but failed to control large tumors, which were associated with systemic T-cell exhaustion and ablation of T-cell responses. Large tumors were defined by an immunosuppressive pathway signature. MS-275 reversed this pathway signature and promoted durable regression of large tumors during ACT. Prototypical exhaustion marker Tim-3 was selectively upregulated in transferred T cells despite displaying a reduced exhaustion signature. Instead, we observed enhanced activation-dependent signaling correlating with enrichment of the IL2-STAT5 signaling axis. Activated CD8+ T-cell responses were predominantly skewed toward terminal effector cell-like CD44+ Tim-3hi TCF1- CD127- KLRG1+ differentiation.

CONCLUSIONS

Tumor burden-induced pathway changes can be reversed through epigenetic reprogramming, enabling the conversion from T-cell exhaustion to effector lineage differentiation.

Transcriptional Signatures and Network-Based Approaches Identified Master Regulators Transcription Factors Involved in Experimental Periodontitis Pathogenesis

Periodontitis is a chronic inflammatory disease characterized by the progressive and irreversible destruction of the periodontium. Its aetiopathogenesis lies in the constant challenge of the dysbiotic biofilm, which triggers a deregulated immune response responsible for the disease phenotype. Although the molecular mechanisms underlying periodontitis have been extensively studied, the regulatory mechanisms at the transcriptional level remain unclear. To generate transcriptomic data, we performed RNA shotgun sequencing of the oral mucosa of periodontitis-affected mice. Since genes are not expressed in isolation during pathological processes, we disclose here the complete repertoire of differentially expressed genes (DEG) and co-expressed modules to build Gene Regulatory Networks (GRNs) and identify the Master Transcriptional Regulators of periodontitis. The transcriptional changes revealed 366 protein-coding genes and 42 non-coding genes differentially expressed and enriched in the immune response. Furthermore, we found 13 co-expression modules with different representation degrees and gene expression levels. Our GRN comprises genes from 12 gene clusters, 166 nodes, of which 33 encode Transcription Factors, and 201 connections. Finally, using these strategies, 26 master regulators of periodontitis were identified. In conclusion, combining the transcriptomic analyses with the regulatory network construction represents a powerful and efficient strategy for identifying potential periodontitis-therapeutic targets.

IL-12 sensing in neurons induces neuroprotective CNS tissue adaptation and attenuates neuroinflammation in mice

Interleukin-12 (IL-12) is a potent driver of type 1 immunity. Paradoxically, in autoimmune conditions, including of the CNS, IL-12 reduces inflammation. The underlying mechanism behind these opposing properties and the involved cellular players remain elusive. Here we map IL-12 receptor (IL-12R) expression to NK and T cells as well as neurons and oligodendrocytes. Conditionally ablating the IL-12R across these cell types in adult mice and assessing their susceptibility to experimental autoimmune encephalomyelitis revealed that the neuroprotective role of IL-12 is mediated by neuroectoderm-derived cells, specifically neurons, and not immune cells. In human brain tissue from donors with multiple sclerosis, we observe an IL-12R distribution comparable to mice, suggesting similar mechanisms in mice and humans. Combining flow cytometry, bulk and single-nucleus RNA sequencing, we reveal an IL-12-induced neuroprotective tissue adaption preventing early neurodegeneration and sustaining trophic factor release during neuroinflammation, thereby maintaining CNS integrity in mice.

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.

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein co-expression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3.6%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.

Highlights

At the level of individual genes, the abundance of transcripts and proteins is weakly correlated within a species ( ρ = 0.165). While the proteome is not imprinted by population structure, co-expression patterns recapitulate the cellular functional landscapeWild populations exhibit a higher abundance of respiration-related proteins compared to domesticated populationsLoci that influence protein abundance differ from those that impact transcript levels, likely because of protein turnover.

Multi-omic integration of DNA methylation and gene expression data reveals molecular vulnerabilities in glioblastoma

Glioblastoma (GBM) is one of the most aggressive types of cancer and exhibits profound genetic and epigenetic heterogeneity, making the development of an effective treatment a major challenge. The recent incorporation of molecular features into the diagnosis of patients with GBM has led to an improved categorization into various tumour subtypes with different prognoses and disease management. In this work, we have exploited the benefits of genome-wide multi-omic approaches to identify potential molecular vulnerabilities existing in patients with GBM. Integration of gene expression and DNA methylation data from both bulk GBM and patient-derived GBM stem cell lines has revealed the presence of major sources of GBM variability, pinpointing subtype-specific tumour vulnerabilities amenable to pharmacological interventions. In this sense, inhibition of the AP-1, SMAD3 and RUNX1/RUNX2 pathways, in combination or not with the chemotherapeutic agent temozolomide, led to the subtype-specific impairment of tumour growth, particularly in the context of the aggressive, mesenchymal-like subtype. These results emphasize the involvement of these molecular pathways in the development of GBM and have potential implications for the development of personalized therapeutic approaches.

Novel functional atrial fibrillation risk genes and pathways identified from coexpression analyses in human left atria

BACKGROUND

Genomewide association studies have associated >100 genetic loci with atrial fibrillation (AF), but establishing causal genes contributing to AF remains challenging.

OBJECTIVE

The purpose of this study was to determine candidate novel causal genes and mechanistic pathways associated with AF risk loci by incorporating gene expression and coexpression analyses and to provide a resource for functional studies and targeting of AF-associated genes.

METHODS

Cis-expression quantitative trait loci were identified for candidate genes near AF risk variants in human left atrial tissues. Coexpression partners were identified for each candidate gene. Weighted gene coexpression network analysis (WGCNA) identified modules and modules with overrepresentation of candidate AF genes. Ingenuity pathway analysis (IPA) was applied to the coexpression partners of each candidate gene. IPA and gene set over representation analysis were applied to each WGCNA module.

RESULTS

One hundred sixty-six AF-risk single nucleotide polymorphisms were located in 135 loci. Eighty-one novel genes not previously annotated as putative AF risk genes were identified. IPA identified mitochondrial dysfunction, oxidative stress, epithelial adherens junction signaling, and sirtuin signaling as the most frequent significant pathways. WGCNA characterized 64 modules (candidate AF genes overrepresented in 8), represented by cell injury, death, stress, developmental, metabolic/mitochondrial, transcription/translation, and immune activation/inflammation regulatory pathways.

CONCLUSION

Candidate gene coexpression analyses suggest significant roles for cellular stress and remodeling in AF, supporting a dual risk model for AF: Genetic susceptibility to AF may not manifest until later in life, when cellular stressors overwhelm adaptive responses. These analyses also provide a novel resource to guide functional studies on potential causal AF genes.

Endotype Characterization Reveals Mechanistic Differences Across Brain Regions in Sporadic Alzheimer's Disease

Background

While Alzheimer's disease (AD) pathology is associated with altered brain structure, it is not clear whether gene expression changes mirror the onset and evolution of pathology in distinct brain regions. Deciphering the mechanisms which cause the differential manifestation of the disease across different regions has the potential to help early diagnosis.

Objective

We aimed to identify common and unique endotypes and their regulation in tangle-free neurons in sporadic AD (SAD) across six brain regions: entorhinal cortex (EC), hippocampus (HC), medial temporal gyrus (MTG), posterior cingulate (PC), superior frontal gyrus (SFG), and visual cortex (VCX).

Methods

To decipher the states of tangle-free neurons across different brain regions in human subjects afflicted with AD, we performed analysis of the neural transcriptome. We explored changes in differential gene expression, functional and transcription factor target enrichment, and co-expression gene module detection analysis to discern disease-state transcriptomic variances and characterize endotypes. Additionally, we compared our results to tangled AD neuron microarray-based study and the Allen Brain Atlas.

Results

We identified impaired neuron function in EC, MTG, PC, and VCX resulting from REST activation and reversal of mature neurons to a precursor-like state in EC, MTG, and SFG linked to SOX2 activation. Additionally, decreased neuron function and increased dedifferentiation were linked to the activation of SUZ12. Energetic deficit connected to NRF1 inactivation was found in HC, PC, and VCX.

Conclusions

Our findings suggest that SAD manifestation varies in scale and severity in different brain regions. We identify endotypes, such as energetic shortfalls, impaired neuronal function, and dedifferentiation.

Dissection of transcriptomic and epigenetic heterogeneity of grade 4 gliomas: implications for prognosis

BACKGROUND

Grade 4 glioma is the most aggressive and currently incurable brain tumor with a median survival of one year in adult patients. Elucidating novel transcriptomic and epigenetic contributors to the molecular heterogeneity underlying its aggressiveness may lead to improved clinical outcomes.

METHODS

To identify grade 4 glioma -associated 5-hydroxymethylcytosine (5hmC) and transcriptomic features as well as their cross-talks, genome-wide 5hmC and transcriptomic profiles of tissue samples from 61 patients with grade 4 gliomas and 9 normal controls were obtained for differential and co-regulation/co-modification analyses. Prognostic models on overall survival based on transcriptomic features and the 5hmC modifications summarized over genic regions (promoters, gene bodies) and brain-derived histone marks were developed using machine learning algorithms.

RESULTS

Despite global reduction, the majority of differential 5hmC features showed higher modification levels in grade 4 gliomas as compared to normal controls. In addition, the bi-directional correlations between 5hmC modifications over promoter regions or gene bodies and gene expression were greatly disturbed in grade 4 gliomas regardless of IDH1 mutation status. Phenotype-associated co-regulated 5hmC-5hmC modules and 5hmC-mRNA modules not only are enriched with different molecular pathways that are indicative of the pathogenesis of grade 4 gliomas, but also are of prognostic significance comparable to IDH1 mutation status. Lastly, the best-performing 5hmC model can predict patient survival at a much higher accuracy (c-index = 74%) when compared to conventional prognostic factor IDH1 (c-index = 57%), capturing the molecular characteristics of tumors that are independent of IDH1 mutation status and gene expression-based molecular subtypes.

CONCLUSIONS

The 5hmC-based prognostic model could offer a robust tool to predict survival in patients with grade 4 gliomas, potentially outperforming existing prognostic factors such as IDH1 mutations. The crosstalk between 5hmC and gene expression revealed another layer of complexity underlying the molecular heterogeneity in grade 4 gliomas, offering opportunities for identifying novel therapeutic targets.

Mitochondria dysregulation contributes to secondary neurodegeneration progression post-contusion injury in human 3D in vitro triculture brain tissue model

Traumatic Brain injury-induced disturbances in mitochondrial fission-and-fusion dynamics have been linked to the onset and propagation of neuroinflammation and neurodegeneration. However, cell-type-specific contributions and crosstalk between neurons, microglia, and astrocytes in mitochondria-driven neurodegeneration after brain injury remain undefined. We developed a human three-dimensional in vitro triculture tissue model of a contusion injury composed of neurons, microglia, and astrocytes and examined the contributions of mitochondrial dysregulation to neuroinflammation and progression of injury-induced neurodegeneration. Pharmacological studies presented here suggest that fragmented mitochondria released by microglia are a key contributor to secondary neuronal damage progression after contusion injury, a pathway that requires astrocyte-microglia crosstalk. Controlling mitochondrial dysfunction thus offers an exciting option for developing therapies for TBI patients.

Expression of Genes Associated With Epithelial-Mesenchymal Transition in Merkel Cell Polyomavirus-Negative Merkel Cell Carcinoma

Two accepted possible pathways for Merkel cell carcinoma (MCC) pathogenesis include the clonal integration of the Merkel cell polyomavirus (MCPyV) into the neoplastic cells and by UV irradiation. We hypothesize that, in UV etiology, the expression of genes associated with epithelial-mesenchymal transition (EMT) would be higher in MCPyV-negative MCCs. We compared RNA expression in 16 MCPyV-negative with that in 14 MCPyV-positive MCCs in 30 patients using NanoString panel of 760 gene targets as an exploratory method. Subsequently, we confirmed the findings with a publicly available RNA sequencing data set. The NanoString method showed that 29 of 760 genes exhibited significant deregulation. Ten genes (CD44, COL6A3, COL11A1, CXCL8, INHBA, MMP1, NID2, SPP1, THBS1, and THY1) were part of the EMT pathway. The expression of CDH1/E-cadherin, a key EMT gene, and TWIST1, regulator gene of EMT, was higher in MCPyV-negative tumors. To further investigate the expression of EMT genes in MCPyV-negative MCCs, we analyzed publicly available RNA sequencing data of 111 primary MCCs. Differential expression and gene set enrichment analysis of 35 MCPyV-negative versus 76 MCPyV-positive MCCs demonstrated significantly higher expression of EMT-related genes and associated pathways such as Notch signaling, TGF-β signaling, and Hedgehog signaling, and UV response pathway in MCPyV-negative MCCs. The significance of the EMT pathway in MCPyV-negative MCCs was confirmed independently by a coexpression module analysis. One of the modules (M3) was specifically activated in MCPyV-negative MCCs and showed significant enrichment for genes involved in EMT. A network analysis of module M3 revealed that CDH1/E-cadherin was among the most connected genes (hubs). E-cadherin and LEF1 immunostains demonstrated significantly more frequent expression in MCPvV-negative versus MCPyV-positive tumors (P < .0001). In summary, our study showed that the expression of EMT-associated genes is higher in MCPyV-negative MCC. Because EMT-related proteins can be targeted, the identification of EMT pathways in MCPyV-negative MCCs is of potential therapeutic relevance.

Collagen VI sustains cell stemness and chemotherapy resistance in glioblastoma

Microenvironmental factors are known fundamental regulators of the phenotype and aggressiveness of glioblastoma (GBM), the most lethal brain tumor, characterized by fast progression and marked resistance to treatments. In this context, the extracellular matrix (ECM) is known to heavily influence the behavior of cancer cells from several origins, contributing to stem cell niches, influencing tumor invasiveness and response to chemotherapy, mediating survival signaling cascades, and modulating inflammatory cell recruitment. Here, we show that collagen VI (COL6), an ECM protein widely expressed in both normal and pathological tissues, has a distinctive distribution within the GBM mass, strongly correlated with the most aggressive and phenotypically immature cells. Our data demonstrate that COL6 sustains the stem-like properties of GBM cells and supports the maintenance of an aggressive transcriptional program promoting cancer cell proliferation and survival. In particular, we identified a specific subset of COL6-transcriptionally co-regulated genes, required for the response of cells to replicative stress and DNA damage, supporting the concept that COL6 is an essential stimulus for the activation of GBM cell response and resistance to chemotherapy, through the ATM/ATR axis. Altogether, these findings indicate that COL6 plays a pivotal role in GBM tumor biology, exerting a pleiotropic action across different GBM hallmarks, including phenotypic identity and gene transcription, as well as response to treatments, thus providing valuable information for the understanding of the complex microenvironmental cues underlying GBM malignancy.

The Elk-3 target Abhd10 ameliorates hepatotoxic injury and fibrosis in alcoholic liver disease

Alcoholic liver disease (ALD) and other forms of chronic hepatotoxic injury can lead to transforming growth factor β1 (TGFβ1)-induced hepatic fibrosis and compromised liver function, underscoring the need to develop novel treatments for these conditions. Herein, our analyses of liver tissue samples from severe alcoholic hepatitis (SAH) patients and two murine models of ALD reveals that the ALD phenotype was associated with upregulation of the transcription factor ETS domain-containing protein (ELK-3) and ELK-3 signaling activity coupled with downregulation of α/β hydrolase domain containing 10 (ABHD10) and upregulation of deactivating S-palmitoylation of the antioxidant protein Peroxiredoxin 5 (PRDX5). In vitro, we further demonstrate that ELK-3 can directly bind to the ABHD10 promoter to inhibit its transactivation. TGFβ1 and epidermal growth factor (EGF) signaling induce ABHD10 downregulation and PRDX5 S-palmitoylation via ELK-3. This ELK-3-mediated ABHD10 downregulation drives oxidative stress and disrupts mature hepatocyte function via enhancing S-palmitoylation of PRDX5's Cys100 residue. In vivo, ectopic Abhd10 overexpression ameliorates liver damage in ALD model mice. Overall, these data suggest that the therapeutic targeting of the ABHD10-PRDX5 axis may represent a viable approach to treating ALD and other forms of hepatotoxicity.

Integrative analysis reveals marker genes for intestinal mucosa barrier repairing in clinical patients

This study aims to identify biomarkers of intestinal repair and provide potential therapeutic clues for improving functional recovery and prognostic performance after intestinal inflammation or injury. Here, we conducted a large-scale screening of multiple transcriptomic and scRNA-seq datasets of patients with inflammatory bowel disease (IBD), and identified 10 marker genes that potentially contribute to intestinal barrier repairing: AQP8, SULT1A1, HSD17B2, PADI2, SLC26A2, SELENBP1, FAM162A, TNNC2, ACADS, and TST. Analysis of a published scRNA-seq dataset revealed that expression of these healing markers were specific to absorptive cell types in intestinal epithelium. Furthermore, we conducted a clinical study where 11 patients underwent ileum resection demonstrating that upregulation of post-operative AQP8 and SULT1A1 expression were associated with improved recovery of bowel functions after surgery-induced intestinal injury, making them confident biomarkers of intestinal healing as well as potential prognostic markers and therapeutic targets for patients with impaired intestinal barrier functions.

Transcriptional patterns of sexual dimorphism and in host developmental programs in the model parasitic nematode Heligmosomoides bakeri

BACKGROUND

Heligmosomoides bakeri (often mistaken for Heligmosomoides polygyrus) is a promising model for parasitic nematodes with the key advantage of being amenable to study and manipulation within a controlled laboratory environment. While draft genome sequences are available for this worm, which allow for comparative genomic analyses between nematodes, there is a notable lack of information on its gene expression.

METHODS

We generated biologically replicated RNA-seq datasets from samples taken throughout the parasitic life of H. bakeri. RNA from tissue-dwelling and lumen-dwelling worms, collected under a dissection microscope, was sequenced on an Illumina platform.

RESULTS

We find extensive transcriptional sexual dimorphism throughout the fourth larval and adult stages of this parasite and identify alternative splicing, glycosylation, and ubiquitination as particularly important processes for establishing and/or maintaining sex-specific gene expression in this species. We find sex-linked differences in transcription related to aging and oxidative and osmotic stress responses. We observe a starvation-like signature among transcripts whose expression is consistently upregulated in males, which may reflect a higher energy expenditure by male worms. We detect evidence of increased importance for anaerobic respiration among the adult worms, which coincides with the parasite's migration into the physiologically hypoxic environment of the intestinal lumen. Furthermore, we hypothesize that oxygen concentration may be an important driver of the worms encysting in the intestinal mucosa as larvae, which not only fully exposes the worms to their host's immune system but also shapes many of the interactions between the host and parasite. We find stage- and sex-specific variation in the expression of immunomodulatory genes and in anthelmintic targets.

CONCLUSIONS

We examine how different the male and female worms are at the molecular level and describe major developmental events that occur in the worm, which extend our understanding of the interactions between this parasite and its host. In addition to generating new hypotheses for follow-up experiments into the worm's behavior, physiology, and metabolism, our datasets enable future more in-depth comparisons between nematodes to better define the utility of H. bakeri as a model for parasitic nematodes in general.

The fusiform gyrus exhibits differential gene-gene co-expression in Alzheimer's disease

Alzheimer's Disease (AD) is an irreversible neurodegenerative disease clinically characterized by the presence of β-amyloid plaques and tau deposits in various regions of the brain. However, the underlying factors that contribute to the development of AD remain unclear. Recently, the fusiform gyrus has been identified as a critical brain region associated with mild cognitive impairment, which may increase the risk of AD development. In our study, we performed gene co-expression and differential co-expression network analyses, as well as gene-expression-based prediction, using RNA-seq transcriptome data from post-mortem fusiform gyrus tissue samples collected from both cognitively healthy individuals and those with AD. We accessed differential co-expression networks in large cohorts such as ROSMAP, MSBB, and Mayo, and conducted over-representation analyses of gene pathways and gene ontology. Our results comprise four exclusive gene hubs in co-expression modules of Alzheimer's Disease, including FNDC3A, MED23, NRIP1, and PKN2. Further, we identified three genes with differential co-expressed links, namely FAM153B, CYP2C8, and CKMT1B. The differential co-expressed network showed moderate predictive performance for AD, with an area under the curve ranging from 0.71 to 0.76 (+/- 0.07). The over-representation analysis identified enrichment for Toll-Like Receptors Cascades and signaling pathways, such as G protein events, PIP2 hydrolysis and EPH-Epherin mechanism, in the fusiform gyrus. In conclusion, our findings shed new light on the molecular pathophysiology of AD by identifying new genes and biological pathways involved, emphasizing the crucial role of gene regulatory networks in the fusiform gyrus.

Methadone alters transcriptional programs associated with synapse formation in human cortical organoids

Opioid use disorder (OUD) among pregnant women has become an epidemic in the United States. Pharmacological interventions for maternal OUD most commonly involve methadone, a synthetic opioid analgesic that attenuates withdrawal symptoms and behaviors linked with drug addiction. However, evidence of methadone's ability to readily accumulate in neural tissue, and cause long-term neurocognitive sequelae, has led to concerns regarding its effect on prenatal brain development. We utilized human cortical organoid (hCO) technology to probe how this drug impacts the earliest mechanisms of cortico-genesis. Bulk mRNA sequencing of 2-month-old hCOs chronically treated with a clinically relevant dose of 1 μM methadone for 50 days revealed a robust transcriptional response to methadone associated with functional components of the synapse, the underlying extracellular matrix (ECM), and cilia. Co-expression network and predictive protein-protein interaction analyses demonstrated that these changes occurred in concert, centered around a regulatory axis of growth factors, developmental signaling pathways, and matricellular proteins (MCPs). TGFβ1 was identified as an upstream regulator of this network and appeared as part of a highly interconnected cluster of MCPs, of which thrombospondin 1 (TSP1) was most prominently downregulated and exhibited dose-dependent reductions in protein levels. These results demonstrate that methadone exposure during early cortical development alters transcriptional programs associated with synaptogenesis, and that these changes arise by functionally modulating extra-synaptic molecular mechanisms in the ECM and cilia. Our findings provide novel insight into the molecular underpinnings of methadone's putative effect on cognitive and behavioral development and a basis for improving interventions for maternal opioid addiction.

Convolutional neural network for biomarker discovery for triple negative breast cancer with RNA sequencing data

Triple negative breast cancers (TNBCs) are tumors with a poor treatment response and prognosis. In this study, we propose a new approach, candidate extraction from convolutional neural network (CNN) elements (CECE), for discovery of biomarkers for TNBCs. We used the GSE96058 and GSE81538 datasets to build a CNN model to classify TNBCs and non-TNBCs and used the model to make TNBC predictions for two additional datasets, the cancer genome atlas (TCGA) breast cancer RNA sequencing data and the data from Fudan University Shanghai Cancer Center (FUSCC). Using correctly predicted TNBCs from the GSE96058 and TCGA datasets, we calculated saliency maps for these subjects and extracted the genes that the CNN model used to separate TNBCs from non-TNBCs. Among the TNBC signature patterns that the CNN models learned from the training data, we found a set of 21 genes that can classify TNBCs into two major classes, or CECE subtypes, with distinct overall survival rates (P = 0.0074). We replicated this subtype classification in the FUSCC dataset using the same 21 genes, and the two subtypes had similar differential overall survival rates (P = 0.0490). When all TNBCs were combined from the 3 datasets, the CECE II subtype had a hazard ratio of 1.94 (95% CI, 1.25-3.01; P = 0.0032). The results demonstrate that the spatial patterns learned by the CNN models can be utilized to discover interacting biomarkers otherwise unlikely to be identified by traditional approaches.

Voluntary exercise modulates pathways associated with amelioration of retinal degenerative diseases

Background: Exercise has been shown to promote a healthier and longer life and linked to a reduced risk of developing neurodegenerative diseases including retinal degenerations. However, the molecular pathways underpinning exercise-induced cellular protection are not well understood. In this work we aim to profile the molecular changes underlying exercise-induced retinal protection and investigate how exercise-induced inflammatory pathway modulation may slow the progression of retinal degenerations. Methods: Female C57Bl/6J mice at 6 weeks old were given free access to open voluntary running wheels for a period of 28 days and then subjected to 5 days of photo-oxidative damage (PD)-induced retinal degeneration. Following, retinal function (electroretinography; ERG), morphology (optical coherence tomography; OCT) and measures of cell death (TUNEL) and inflammation (IBA1) were analysed and compared to sedentary controls. To decipher global gene expression changes as a result of voluntary exercise, RNA sequencing and pathway and modular gene co-expression analyses were performed on retinal lysates of exercised and sedentary mice that were subjected to PD, as well as healthy dim-reared controls. Results: Following 5 days of PD, exercised mice had significantly preserved retinal function, integrity and reduced levels of retinal cell death and inflammation, compared to sedentary controls. In response to voluntary exercise, inflammatory and extracellular matrix integrity pathways were significantly modulated, with the gene expression profile of exercised mice more closely trending towards that of a healthy dim-reared retina. Conclusion: We suggest that voluntary exercise may mediate retinal protection by influencing key pathways involved in regulating retinal health and shifting the transcriptomic profile to a healthy phenotype.

Transcriptome analysis of aphid-resistant and susceptible near isogenic lines reveals candidate resistance genes in cowpea (Vigna unguiculata)

BACKGROUND

Cowpea (Vigna unguiculata) is a crucial crop for regions of the world that are prone to both heat and drought; however, the phytotoxic cowpea aphid (Aphis craccivora) impairs plant physiology at low population levels. Both antibiotic and antixenotic forms of resistance to the aphid have been mapped to two quantitative trait loci (QTLs) and near isogenic lines (NILs). The molecular mechanism for this resistance response remains unknown.

RESULTS

To understand the genes underlying susceptibility and resistance, two cowpea lines with shared heritage were infested along a time course and characterized for transcriptome variation. Aphids remodeled cowpea development and signaling relative to host plant resistance and the duration of feeding, with resource acquisition and mobilization determining, in part, susceptibility to aphid attack. Major differences between the susceptible and resistant cowpea were identified including two regions of interest housing the most genetic differences between the lines. Candidate genes enabling aphid resistance include both conventional resistance genes (e.g., leucine rich repeat protein kinases) as well as multiple novel genes with no known orthologues.

CONCLUSIONS

Our results demonstrate that feeding by the cowpea aphid globally remodels the transcriptome of cowpea, but how this occurs depends on both the duration of feeding and host-plant resistance. Constitutive expression profiles of the resistant genotype link aphid resistance to a finely-tuned resource management strategy that ultimately reduces damage (e.g., chlorosis) and delays cell turnover, while impeding aphid performance. Thus, aphid resistance in cowpea is a complex, multigene response that involves crosstalk between primary and secondary metabolism.

Co-expression of fibrotic genes in inflammatory bowel disease; A localized event?

INTRODUCTION

Extracellular matrix turnover, a ubiquitous dynamic biological process, can be diverted to fibrosis. The latter can affect the intestine as a serious complication of Inflammatory Bowel Diseases (IBD) and is resistant to current pharmacological interventions. It embosses the need for out-of-the-box approaches to identify and target molecular mechanisms of fibrosis.

METHODS AND RESULTS

In this study, a novel mRNA sequencing dataset of 22 pairs of intestinal biopsies from the terminal ileum (TI) and the sigmoid of 7 patients with Crohn's disease, 6 with ulcerative colitis and 9 control individuals (CI) served as a validation cohort of a core fibrotic transcriptomic signature (FIBSig), This signature, which was identified in publicly available data (839 samples from patients and healthy individuals) of 5 fibrotic disorders affecting different organs (GI tract, lung, skin, liver, kidney), encompasses 241 genes and the functional pathways which derive from their interactome. These genes were used in further bioinformatics co-expression analyses to elucidate the site-specific molecular background of intestinal fibrosis highlighting their involvement, particularly in the terminal ileum. We also confirmed different transcriptomic profiles of the sigmoid and terminal ileum in our validation cohort. Combining the results of these analyses we highlight 21 core hub genes within a larger single co-expression module, highly enriched in the terminal ileum of CD patients. Further pathway analysis revealed known and novel inflammation-regulated, fibrogenic pathways operating in the TI, such as IL-13 signaling and pyroptosis, respectively.

DISCUSSION

These findings provide a rationale for the increased incidence of fibrosis at the terminal ileum of CD patients and highlight operating pathways in intestinal fibrosis for future evaluation with mechanistic and translational studies.

Common Assays in Mammalian Golgi Studies

The Golgi is a complex structure characterized by stacks of tightly aligned flat cisternae. In mammalian cells, Golgi stacks often concentrate in the perinuclear region and link together to form a ribbon. This structure is dynamic to accommodate continuous cargo flow in and out of the Golgi in both directions and undergoes morphological changes under physiological and pathological conditions. The fine, stacked Golgi structure makes it difficult to study by conventional light or even super-resolution microscopy. Furthermore, efforts to understand how Golgi structural dynamics impact cellular processes have been slow because of the knowledge gap in the protein machinery that maintains the complex and dynamic Golgi structure. In this method article, we list the common assays used in our research to help new and established researchers select the most appropriate method to properly address their questions.

Differential Allele-Specific Expression Revealed Functional Variants and Candidate Genes Related to Meat Quality Traits in B. indicus Muscle

Traditional transcriptomics approaches have been used to identify candidate genes affecting economically important livestock traits. Regulatory variants affecting these traits, however, remain under covered. Genomic regions showing allele-specific expression (ASE) are under the effect of cis-regulatory variants, being useful for improving the accuracy of genomic selection models. Taking advantage of the better of these two methods, we investigated single nucleotide polymorphisms (SNPs) in regions showing differential ASE (DASE SNPs) between contrasting groups for beef quality traits. For these analyses, we used RNA sequencing data, imputed genotypes and genomic estimated breeding values of muscle-related traits from 190 Nelore (Bos indicus) steers. We selected 40 contrasting unrelated samples for the analysis (N = 20 animals per contrasting group) and used a beta-binomial model to identify ASE SNPs in only one group (i.e., DASE SNPs). We found 1479 DASE SNPs (FDR ≤ 0.05) associated with 55 beef-quality traits. Most DASE genes were involved with tenderness and muscle homeostasis, presenting a co-expression module enriched for the protein ubiquitination process. The results overlapped with epigenetics and phenotype-associated data, suggesting that DASE SNPs are potentially linked to cis-regulatory variants affecting simultaneously the transcription and phenotype through chromatin state modulation.

3D biocomposite culture enhances differentiation of dopamine-like neurons from SH-SY5Y cells: A model for studying Parkinson's disease phenotypes

Studies of underlying neurodegenerative processes in Parkinson's Disease (PD) have traditionally utilized cell cultures grown on two-dimensional (2D) surfaces. Biomimetic three-dimensional (3D) cell culture platforms have been developed to better emulate features of the brain's natural microenvironment. We here use our bioengineered brain-like tissue model, composed of a silk-hydrogel composite, to study the 3D microenvironment's contributions on the development and performance of dopaminergic-like neurons (DLNs). Compared with 2D culture, SH-SY5Y cells differentiated in 3D microenvironments were enriched for DLNs concomitant with a reduction in proliferative capacity during the neurodevelopmental process. Additionally, the 3D DLN cultures were more sensitive to oxidative stresses elicited by the PD-related neurotoxin 1-methyl-4-phenylpyridinium (MPP). MPP induced transcriptomic profile changes specific to 3D-differentiated DLN cultures, replicating the dysfunction of neuronal signaling pathways and mitochondrial dynamics implicated in PD. Overall, this physiologically-relevant 3D platform resembles a useful tool for studying dopamine neuron biology and interrogating molecular mechanisms underlying neurodegeneration in PD.

Gene Co-Expression Network Modular Analysis Reveals Altered Immune Mechanisms in HIV-HAND

Although the introduction of HAART has completely changed the natural course of HIV infection, the number of chronic forms of HIV-associated neurocognitive disorder (HAND) has risen. It is estimated that up to half of subjects undergoing HAART therapy exhibit mild cognitive impairments. In the current study, we apply the gene co-expression network modular analysis, a well-established system biology approach, to the gene expression profiles of cases from the National NeuroAIDS Tissue Consortium (NNTC). We observed a negative enrichment for genes associated with the control of immune responses and putatively regulated by the transcription factors IRF8 and SPI1 and by both type I and II interferons. Our study provides evidence of altered immune responses, which are likely associated with the occurrence of HAND in the absence of HIV encephalitis (HIVE).

Transcriptomic profiling of sporadic Alzheimer's disease patients

Alzheimer's disease (AD) manifested before age 65 is commonly referred to as early-onset AD (EOAD) (Reitz et al. Neurol Genet. 2020;6:e512). While the majority (> 90%) of EOAD cases are not caused by autosomal-dominant mutations in PSEN1, PSEN2, and APP, they do have a higher heritability (92-100%) than sporadic late-onset AD (LOAD, 70%) (Wingo et al. Arch Neurol. 2012;69:59-64, Fulton-Howard et al. Neurobiol Aging. 2021;99:101.e1-101.e9). Although the endpoint clinicopathological changes, i.e., Aβ plaques, tau tangles, and cognitive decline, are common across EOAD and LOAD, the disease progression is highly heterogeneous (Neff et al. Sci Adv Am Assoc Adv Sci. 2021;7:eabb5398). This heterogeneity, leading to temporally distinct age at onset (AAO) and stages of cognitive decline, may be caused by myriad combinations of distinct disease-associated molecular mechanisms. We and others have used transcriptome profiling in AD patient-derived neuron models of autosomal-dominant EOAD and sporadic LOAD to identify disease endotypes (Caldwell et al. Sci Adv Am Assoc Adv Sci. 2020;6:eaba5933, Mertens et al. Cell Stem Cell. 2021;28:1533-1548.e6, Caldwell et al. Alzheimers Demen. 2022). Further, analyses of large postmortem brain cohorts demonstrate that only one-third of AD patients show hallmark disease endotypes like increased inflammation and decreased synaptic signaling (Neff et al. Sci Adv Am Assoc Adv Sci. 2021;7:eabb5398). Areas of the brain less affected by AD pathology at early disease stages-such as the primary visual cortex-exhibit similar transcriptomic dysregulation as those regions traditionally affected and, therefore, may offer a view into the molecular mechanisms of AD without the associated inflammatory changes and gliosis induced by pathology (Haroutunian et al. Neurobiol Aging. 2009;30:561-73). To this end, we analyzed AD patient samples from the primary visual cortex (19 EOAD, 20 LOAD) using transcriptomic signatures to identify patient clusters and disease endotypes. Interestingly, although the clusters showed distinct combinations and severity of endotypes, each patient cluster contained both EOAD and LOAD cases, suggesting that AAO may not directly correlate with the identity and severity of AD endotypes.

Postnatal developmental trajectory of sex-biased gene expression in the mouse pituitary gland

BACKGROUND

The pituitary gland regulates essential physiological processes such as growth, pubertal onset, stress response, metabolism, reproduction, and lactation. While sex biases in these functions and hormone production have been described, the underlying identity, temporal deployment, and cell-type specificity of sex-biased pituitary gene regulatory networks are not fully understood.

METHODS

To capture sex differences in pituitary gene regulation dynamics during postnatal development, we performed 3' untranslated region sequencing and small RNA sequencing to ascertain gene and microRNA expression, respectively, across five postnatal ages (postnatal days 12, 22, 27, 32, 37) that span the pubertal transition in female and male C57BL/6J mouse pituitaries (n = 5-6 biological replicates for each sex at each age).

RESULTS

We observed over 900 instances of sex-biased gene expression and 17 sex-biased microRNAs, with the majority of sex differences occurring with puberty. Using miRNA-gene target interaction databases, we identified 18 sex-biased genes that were putative targets of 5 sex-biased microRNAs. In addition, by combining our bulk RNA-seq with publicly available male and female mouse pituitary single-nuclei RNA-seq data, we obtained evidence that cell-type proportion sex differences exist prior to puberty and persist post-puberty for three major hormone-producing cell types: somatotropes, lactotropes, and gonadotropes. Finally, we identified sex-biased genes in these three pituitary cell types after accounting for cell-type proportion differences between sexes.

CONCLUSION

Our study reveals the identity and postnatal developmental trajectory of sex-biased gene expression in the mouse pituitary. This work also highlights the importance of considering sex biases in cell-type composition when understanding sex differences in the processes regulated by the pituitary gland.

An Integrated Bioinformatics Approach to Identify Network-Derived Hub Genes in Starving Zebrafish

The present study was aimed at identifying causative hub genes within modules formed by co-expression and protein-protein interaction (PPI) networks, followed by Bayesian network (BN) construction in the liver transcriptome of starved zebrafish. To this end, the GSE11107 and GSE112272 datasets from the GEO databases were downloaded and meta-analyzed using the MetaDE package, an add-on R package. Differentially expressed genes (DEGs) were identified based upon expression intensity N(µ = 0.2, σ² = 0.4). Reconstruction of BNs was performed by the bnlearn R package on genes within modules using STRINGdb and CEMiTool. ndufs5 (shared among PPI, BN and COEX), rps26, rpl10, sdhc (shared between PPI and BN), ndufa6, ndufa10, ndufb8 (shared between PPI and COEX), skp1, atp5h, ndufb10, rpl5b, zgc:193613, zgc:123327, zgc:123178, wu:fc58f10, zgc:111986, wu:fc37b12, taldo1, wu:fb62f08, zgc:64133 and acp5a (shared between COEX and BN) were identified as causative hub genes affecting gene expression in the liver of starving zebrafish. Future work will shed light on using integrative analyses of miRNA and DNA microarrays simultaneously, and performing in silico and experimental validation of these hub-causative (CST) genes affecting starvation in zebrafish.

Mesenchymal and adrenergic cell lineage states in neuroblastoma possess distinct immunogenic phenotypes

Apart from the anti-GD2 antibody, immunotherapy for neuroblastoma has had limited success due to immune evasion mechanisms, coupled with an incomplete understanding of predictors of response. Here, from bulk and single-cell transcriptomic analyses, we identify a subset of neuroblastomas enriched for transcripts associated with immune activation and inhibition and show that these are predominantly characterized by gene expression signatures of the mesenchymal lineage state. By contrast, tumors expressing adrenergic lineage signatures are less immunogenic. The inherent presence or induction of the mesenchymal state through transcriptional reprogramming or therapy resistance is accompanied by innate and adaptive immune gene activation through epigenetic remodeling. Mesenchymal lineage cells promote T cell infiltration by secreting inflammatory cytokines, are efficiently targeted by cytotoxic T and natural killer cells and respond to immune checkpoint blockade. Together, we demonstrate that distinct immunogenic phenotypes define the divergent lineage states of neuroblastoma and highlight the immunogenic potential of the mesenchymal lineage.

Altered activity-regulated H3K9 acetylation at TGF-beta signaling genes during egocentric memory in Huntington's disease

Molecular mechanisms underlying cognitive deficits in Huntington's disease (HD), a striatal neurodegenerative disorder, are unknown. Here, we generated ChIPseq, 4Cseq and RNAseq data on striatal tissue of HD and control mice during striatum-dependent egocentric memory process. Multi-omics analyses showed altered activity-dependent epigenetic gene reprogramming of neuronal and glial genes regulating striatal plasticity in HD mice, which correlated with memory deficit. First, our data reveal that spatial chromatin re-organization and transcriptional induction of BDNF-related markers, regulating neuronal plasticity, were reduced since memory acquisition in the striatum of HD mice. Second, our data show that epigenetic memory implicating H3K9 acetylation, which established during late phase of memory process (e.g. during consolidation/recall) and contributed to glia-mediated, TGFβ-dependent plasticity, was compromised in HD mouse striatum. Specifically, memory-dependent regulation of H3K9 acetylation was impaired at genes controlling extracellular matrix and myelination. Our study investigating the interplay between epigenetics and memory identifies H3K9 acetylation and TGFβ signaling as new targets of striatal plasticity, which might offer innovative leads to improve HD.

A variable gene family encoding nodule-specific cysteine-rich peptides in pea (Pisum sativum L.)

Various legume plants form root nodules in which symbiotic bacteria (rhizobia) fix atmospheric nitrogen after differentiation into a symbiotic form named bacteroids. In some legume species, bacteroid differentiation is promoted by defensin-like nodule-specific cysteine-rich (NCR) peptides. NCR peptides have best been studied in the model legume Medicago truncatula Gaertn., while in many other legumes relevant information is still fragmentary. Here, we characterize the NCR gene family in pea (Pisum sativum L.) using genomic and transcriptomic data. We found 360 genes encoding NCR peptides that are expressed in nodules. The sequences of pea NCR genes and putative peptides are highly variable and differ significantly from NCR sequences of M. truncatula. Indeed, only one pair of orthologs (PsNCR47-MtNCR312) has been identified. The NCR genes in the pea genome are located in clusters, and the expression patterns of NCR genes from one cluster tend to be similar. These data support the idea of independent evolution of NCR genes by duplication and diversification in related legume species. We also described spatiotemporal expression profiles of NCRs and identified specific transcription factor (TF) binding sites in promoters of "early" and "late" NCR genes. Further, we studied the expression of NCR genes in nodules of Fix^- mutants and predicted potential regulators of NCR gene expression, one among them being the TF ERN1 involved in the early steps of nodule organogenesis. In general, this study contributes to understanding the functions of NCRs in legume nodules and contributes to understanding the diversity and potential antibiotic properties of pea nodule-specific antimicrobial molecules.

In vivo tumor immune microenvironment phenotypes correlate with inflammation and vasculature to predict immunotherapy response

Response to immunotherapies can be variable and unpredictable. Pathology-based phenotyping of tumors into ‘hot’ and ‘cold’ is static, relying solely on T-cell infiltration in single-time single-site biopsies, resulting in suboptimal treatment response prediction. Dynamic vascular events (tumor angiogenesis, leukocyte trafficking) within tumor immune microenvironment (TiME) also influence anti-tumor immunity and treatment response. Here, we report dynamic cellular-level TiME phenotyping in vivo that combines inflammation profiles with vascular features through non-invasive reflectance confocal microscopic imaging. In skin cancer patients, we demonstrate three main TiME phenotypes that correlate with gene and protein expression, and response to toll-like receptor agonist immune-therapy. Notably, phenotypes with high inflammation associate with immunostimulatory signatures and those with high vasculature with angiogenic and endothelial anergy signatures. Moreover, phenotypes with high inflammation and low vasculature demonstrate the best treatment response. This non-invasive in vivo phenotyping approach integrating dynamic vasculature with inflammation serves as a reliable predictor of response to topical immune-therapy in patients.

Standard assessment of immune infiltration of biopsies is not sufficient to accurately predict response to immunotherapy. Here, the authors show that reflectance confocal microscopy can be used to quantify dynamic vasculature and inflammatory features to better predict treatment response in skin cancers.

Blood mRNA Expression in Alzheimer's Disease and Dementia With Lewy Bodies

OBJECTIVES

The objective of this study was to investigate the expression of genes in Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), both at the mild cognitive impairment (MCI) and dementia stages, to improve our understanding of disease pathophysiology and investigate the potential for diagnostic and prognostic biomarkers based on mRNA expression.

DESIGN

Cross-sectional observational study.

SETTING

University research center.

PARTICIPANTS

People with MCI with Lewy bodies (MCI-LB, n=55), MCI-AD (n=19), DLB (n=38), AD (n=24) and a cognitively unimpaired comparison group (n=28).

MEASUREMENTS

Ribonucleic acid sequencing of whole blood. Differentially expressed genes (DEGs) were identified and gene set enrichment analysis was carried out.

RESULTS

Compared with the cognitively unimpaired group, there were 22 DEGs in MCI-LB/DLB and 61 DEGs in MCI-AD/AD. DEGS were also identified when comparing the two disease groups. Expression of ANP32A was associated with more rapid cognitive decline in MCI-AD/AD. Gene set enrichment analysis identified downregulation in gene sets including MYC targets and oxidative phosphorylation in MCI-LB/DLB; upregulation of immune and inflammatory responses in MCI-AD/AD; and upregulation of interferon-α and -γ responses in MCI-AD/AD compared with MCI-LB/DLB.

CONCLUSION

This study identified multiple DEGs in MCI-LB/DLB and MCI-AD/AD. One of these DEGs, ANP32A, may be a prognostic marker in AD. Genes related to mitochondrial function were downregulated in MCI-LB/DLB. Previously reported upregulation of genes associated with inflammation and immune responses in MCI-AD/AD was confirmed in this cohort. Differences in interferon responses between MCI-AD/AD and MCI-LB/DLB suggest that there are key differences in peripheral immune responses between these diseases.

hCoCena: Horizontal integration and analysis of transcriptomics datasets

Motivation

Transcriptome-based gene co-expression analysis has become a standard procedure for structured and contextualized understanding and comparison of different conditions and phenotypes. Since large study designs with a broad variety of conditions are costly and laborious, extensive comparisons are hindered when utilizing only a single dataset. Thus, there is an increased need for tools that allow the integration of multiple transcriptomic datasets with subsequent joint analysis, which can provide a more systematic understanding of gene co-expression and co-functionality within and across conditions. To make such an integrative analysis accessible to a wide spectrum of users with differing levels of programming expertise it is essential to provide user-friendliness and customizability as well as thorough documentation.

Results

This article introduces horizontal CoCena (hCoCena: horizontal construction of co-expression networks and analysis), an R-package for network-based co-expression analysis that allows the analysis of a single transcriptomic dataset as well as the joint analysis of multiple datasets. With hCoCena, we provide a freely available, user-friendly and adaptable tool for integrative multi-study or single-study transcriptomics analyses alongside extensive comparisons to other existing tools.

Availability and implementation

The hCoCena R-package is provided together with R Markdowns that implement an exemplary analysis workflow including extensive documentation and detailed descriptions of data structures and objects. Such efforts not only make the tool easy to use but also enable the seamless integration of user-written scripts and functions into the workflow, creating a tool that provides a clear design while remaining flexible and highly customizable. The package and additional information including an extensive Wiki are freely available on GitHub: https://github.com/MarieOestreich/hCoCena. The version at the time of writing has been added to Zenodo under the following link: https://doi.org/10.5281/zenodo.6911782.

Supplementary information

Supplementary data are available at Bioinformatics online.

GPNMB confers risk for Parkinson's disease through interaction with α-synuclein

Many risk loci for Parkinson's disease (PD) have been identified by genome-wide association studies (GWASs), but target genes and mechanisms remain largely unknown. We linked the GWAS-derived chromosome 7 locus (sentinel single-nucleotide polymorphism rs199347) to GPNMB through colocalization analyses of expression quantitative trait locus and PD risk signals, confirmed by allele-specific expression studies in the human brain. In cells, glycoprotein nonmetastatic melanoma protein B (GPNMB) coimmunoprecipitated and colocalized with α-synuclein (aSyn). In induced pluripotent stem cell-derived neurons, loss of GPNMB resulted in loss of ability to internalize aSyn fibrils and develop aSyn pathology. In 731 PD and 59 control biosamples, GPNMB was elevated in PD plasma, associating with disease severity. Thus, GPNMB represents a PD risk gene with potential for biomarker development and therapeutic targeting.

Transcriptional response of a target plant to benzoxazinoid and diterpene allelochemicals highlights commonalities in detoxification

BACKGROUND

Plants growing in proximity to other plants are exposed to a variety of metabolites that these neighbors release into the environment. Some species produce allelochemicals to inhibit growth of neighboring plants, which in turn have evolved ways to detoxify these compounds.

RESULTS

In order to understand how the allelochemical-receiving target plants respond to chemically diverse compounds, we performed whole-genome transcriptome analysis of Arabidopsis thaliana exposed to either the benzoxazinoid derivative 2-amino- 3H-phenoxazin-3-one (APO) or momilactone B. These two allelochemicals belong to two very different compound classes, benzoxazinoids and diterpenes, respectively, produced by different Poaceae crop species.

CONCLUSIONS

Despite their distinct chemical nature, we observed similar molecular responses of A. thaliana to these allelochemicals. In particular, many of the same or closely related genes belonging to the three-phase detoxification pathway were upregulated in both treatments. Further, we observed an overlap between genes upregulated by allelochemicals and those involved in herbicide detoxification. Our findings highlight the overlap in the transcriptional response of a target plant to natural and synthetic phytotoxic compounds and illustrate how herbicide resistance could arise via pathways involved in plant-plant interaction.

Approaches in Gene Coexpression Analysis in Eukaryotes

Simple Summary

Genes whose expression levels rise and fall similarly in a large set of samples, may be considered coexpressed. Gene coexpression analysis refers to the en masse discovery of coexpressed genes from a large variety of transcriptomic experiments. The type of biological networks that studies gene coexpression, known as Gene Coexpression Networks, consist of an undirected graph depicting genes and their coexpression relationships. Coexpressed genes are clustered in smaller subnetworks, the predominant biological roles of which can be determined through enrichment analysis. By studying well-annotated gene partners, the attribution of new roles to genes of unknown function or assumption for participation in common metabolic pathways can be achieved, through a guilt-by-association approach. In this review, we present key issues in gene coexpression analysis, as well as the most popular tools that perform it.

Abstract

Gene coexpression analysis constitutes a widely used practice for gene partner identification and gene function prediction, consisting of many intricate procedures. The analysis begins with the collection of primary transcriptomic data and their preprocessing, continues with the calculation of the similarity between genes based on their expression values in the selected sample dataset and results in the construction and visualisation of a gene coexpression network (GCN) and its evaluation using biological term enrichment analysis. As gene coexpression analysis has been studied extensively, we present most parts of the methodology in a clear manner and the reasoning behind the selection of some of the techniques. In this review, we offer a comprehensive and comprehensible account of the steps required for performing a complete gene coexpression analysis in eukaryotic organisms. We comment on the use of RNA-Seq vs. microarrays, as well as the best practices for GCN construction. Furthermore, we recount the most popular webtools and standalone applications performing gene coexpression analysis, with details on their methods, features and outputs.

Transcriptomics of developing wild sunflower seeds from the extreme ends of a latitudinal gradient differing in seed oil composition

Seed oil composition, an important agronomic trait in cultivated sunflower, varies latitudinally across the native range of its wild progenitor. This pattern is thought to be driven by selection for a higher proportion of saturated fatty acids in southern populations compared with northern populations, likely due to the different temperatures experienced during seed germination. To investigate whether these differences in fatty acid composition between northern and southern populations correspond to transcriptional variation in the expression of genes involved in fatty acid metabolism, we sequenced RNA from developing seeds of sunflowers from Texas, USA, and Saskatchewan, Canada (the extreme ends of sunflower's latitudinal range) grown in a common garden. We found 4,741 genes to be differentially expressed between Texas and Canada, including several genes involved in lipid metabolism. Several differentially expressed lipid metabolism genes also colocalized with known oil quantitative trait loci (QTL). The genes producing stearoyl-ACP-desaturases (SAD) were of particular interest because of their known role in the conversion of fully saturated into unsaturated fatty acids. Two SAD genes were more highly expressed in seeds from Canadian populations, consistent with the observation of increased levels of unsaturated fatty acids in seeds from that region. We also constructed a gene co-expression network to investigate regional variation in network modules. The results of this analysis revealed regional differentiation for eight of 12 modules but no clear relationship with oil biosynthesis. Overall, the differential expression of SAD genes offers a partial explanation for the observed differences in seed oil composition between Texas and Canada, while the expression patterns of other metabolic genes suggest complex regulation of fatty acid production and usage across latitudes.