Co-expression network modeling identifies key long non-coding RNA and mRNA modules in altering molecular phenotype to develop stress-induced depression in rats

Non-coding RNA alterations in occlusal disharmony-induced anxiety-like behaviour

BACKGROUND

Occlusal disharmony (OD) may induce anxiety-like behaviours; however, the underlying mechanism remains unclear. Herein, we explored the expression profiles of non-coding RNAs (ncRNAs), along with their biological function and regulatory network, in anxiety-like behaviour induced by OD.

MATERIALS AND METHODS

Occlusal disharmony was produced by anterior crossbite of C57BL/6 mice. Behavioural tests, corticosterone (CORT) and serotonin (5-HT) levels were used to measure anxiety. In addition, RNA sequencing was used to screen all differentially expressed (DE) ncRNAs. Moreover, the RNA-binding proteins interacting with ncRNAs were predicted by the ENCORI database and confirmed using western blots.

RESULTS

The significant differences in behavioural tests and CORT suggested the successful induction of anxiety-like behaviour by OD. In OD mice, ncRNAs were significantly dysregulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses suggested that the DE ncRNAs were enriched in anxiety-related pathways. CircRNA10039 was upregulated, and PTBP1 was predicted to interact with circRNA10039. In addition, KEGG pathway analysis showed that PTBP1 may be associated with messenger RNA biogenesis and spliceosomes.

CONCLUSION

OD induced by anterior crossbite can lead to the anxiety-like behaviours. During this process, ncRNA also changes. CircRNA10039 and PTBP1 may play a role in OD-induced anxiety-like behaviours.

Epigenetic mechanisms linking early-life adversities and mental health

Early-life adversities, whether prenatal or postnatal exposure, have been linked to adverse mental health outcomes later in life increasing the risk of several psychiatric disorders. Research on its neurobiological consequences demonstrated an association between exposure to adversities and persistent alterations in the structure, function, and connectivity of the brain. Consistent evidence supports the idea that regulation of gene expression through epigenetic mechanisms are involved in embedding the impact of early-life experiences in the genome and mediate between social environments and later behavioral phenotypes. In addition, studies from rodent models and humans suggest that these experiences and the acquired risk factors can be transmitted through epigenetic mechanisms to offspring and the following generations potentially contributing to a cycle of disease or disease risk. However, one of the important aspects of epigenetic mechanisms, unlike genetic sequences that are fixed and unchangeable, is that although the epigenetic markings are long-lasting, they are nevertheless potentially reversible. In this review, we summarize our current understanding of the epigenetic mechanisms involved in the mental health consequences derived from early-life exposure to malnutrition, maltreatment and poverty, adversities with huge and pervasive impact on mental health. We also discuss the evidence about transgenerational epigenetic inheritance in mammals and experimental data suggesting that suitable social and pharmacological interventions could reverse adverse epigenetic modifications induced by early-life negative social experiences. In this regard, these studies must be accompanied by efforts to determine the causes that promote these adversities and that result in health inequity in the population.

Gene-network based analysis of human placental trophoblast subtypes identifies critical genes as potential targets of therapeutic drugs

During early pregnancy, extravillous trophoblasts (EVTs) play a crucial role in modifying the maternal uterine environment. Failures in EVT lineage formation and differentiation can lead to pregnancy complications such as preeclampsia, fetal growth restriction, and pregnancy loss. Despite recent advances, our knowledge on molecular and external factors that control and affect EVT development remains incomplete. Using trophoblast organoid in vitro models, we recently discovered that coordinated manipulation of the transforming growth factor beta (TGFβ) signaling is essential for EVT development. To further investigate gene networks involved in EVT function and development, we performed weighted gene co-expression network analysis (WGCNA) on our RNA-Seq data. We identified 10 modules with a median module membership of over 0.8 and sizes ranging from 1005 (M1) to 72 (M27) network genes associated with TGFβ activation status or in vitro culturing, the latter being indicative for yet undiscovered factors that shape the EVT phenotypes. Lastly, we hypothesized that certain therapeutic drugs might unintentionally interfere with placentation by affecting EVT-specific gene expression. We used the STRING database to map correlations and the Drug-Gene Interaction database to identify drug targets. Our comprehensive dataset of drug-gene interactions provides insights into potential risks associated with certain drugs in early gestation.

Integrative modeling of lncRNA-chromatin interaction maps reveals diverse mechanisms of nuclear retention

BACKGROUND

Many long non-coding RNAs, known to be involved in transcriptional regulation, are enriched in the nucleus and interact with chromatin. However, their mechanisms of chromatin interaction and the served cellular functions are poorly understood. We sought to characterize the mechanisms of lncRNA nuclear retention by systematically mapping the sequence and chromatin features that distinguish lncRNA-interacting genomic segments.

RESULTS

We found DNA 5-mer frequencies to be predictive of chromatin interactions for all lncRNAs, suggesting sequence-specificity as a global theme in the interactome. Sequence features representing protein-DNA and protein-RNA binding motifs revealed potential mechanisms for specific lncRNAs. Complementary to these global themes, transcription-related features and DNA-RNA triplex formation potential were noted to be highly predictive for two mutually exclusive sets of lncRNAs. DNA methylation was also noted to be a significant predictor, but only when combined with other epigenomic features.

CONCLUSIONS

Taken together, our statistical findings suggest that a group of lncRNAs interacts with transcriptionally inactive chromatin through triplex formation, whereas another group interacts with transcriptionally active regions and is involved in DNA Damage Response (DDR) through formation of R-loops. Curiously, we observed a strong pattern of enrichment of 5-mers in four potentially interacting entities: lncRNA-bound DNA tiles, lncRNAs, miRNA seed sequences, and repeat elements. This finding points to a broad sequence-based network of interactions that may underlie regulation of fundamental cellular functions. Overall, this study reveals diverse sequence and chromatin features related to lncRNA-chromatin interactions, suggesting potential mechanisms of nuclear retention and regulatory function.

The 2210408F21Rik/miR-1968-5p/Hras axis regulates synapse-related proteins in a mouse model of depressive-like behaviors through a ceRNA mechanism

Abnormal expression of long non-coding RNAs (lncRNAs) has been correlated with depressive disorders, but limited data are available on the lncRNA-microRNA (miRNA/miR)-messenger RNA (mRNA) competitive endogenous RNA (ceRNA) mechanism in depression. Herein, we address this issue based on transcriptome sequencing and in vitro experiments. Mouse hippocampus tissues were obtained from chronic unpredictable mild stress (CUMS)-induced mice to screen out differentially expressed mRNAs and lncRNAs based on the transcriptome sequencing. Next, the depression-related differentially expressed genes (DEGs) were obtained, followed by Gene Ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) enrichment analysis. A total of 1018 differentially expressed mRNAs, 239 differentially expressed lncRNAs, and 58 DEGs related to depression were acquired. The miRNAs targeting Harvey rat sarcoma virus oncogene (Hras) and miRNAs sponged by Hras-related lncRNA were intersected to identify the ceRNA regulatory network. In addition, the synapse-related genes related to depression were acquired by bioinformatics analysis. Hras was identified as the core gene related to depression, mainly related to neuronal excitation. We also found that 2210408F21Rik competitively bound to miR-1968-5p that targeted Hras. The effects of 2210408F21Rik/miR-1968-5p/Hras axis on neuronal excitation were verified in primary hippocampal neurons. The experimental data indicated that the downregulation of 2210408F21Rik increased the level of miR-1968-5p to diminish Hras expression, thereby affecting neuronal excitation in CUMS mice. In conclusion, the 2210408F21Rik/miR-1968-5p/Hras ceRNA network can potentially affect the expression of synapsia-related proteins and is a promising target for preventing and treating depression.

Identification of novel targets and pathways to distinguish suicide dependent or independent on depression diagnosis

In recent years, postmortem brain studies have revealed that some molecular, cellular, and circuit changes associated with suicide, have an independent or additive effect on depression. The aim of the present study is to identify potential phenotypic, tissue, and sex-specific novel targets and pathways to distinguish depression or suicide from major depressive disorder (MDD) comorbid with suicide. The mRNA expression profiling datasets from two previous independent postmortem brain studies of suicide and depression (GSE102556 and GSE101521) were retrieved from the GEO database. Machine learning analysis was used to differentiate three regrouped gene expression profiles, i.e., MDD with suicide, MDD without suicide, and suicide without depression. Weighted correlation network analysis (WGCNA) was further conducted to identify the key modules and hub genes significantly associated with each of these three sub-phenotypes. TissueEnrich approaches were used to find the essential brain tissues and the difference of tissue enriched genes between depression with or without suicide. Dysregulated gene expression cross two variables, including phenotypes and tissues, were determined by global analysis with Vegan. RRHO analysis was applied to examine the difference in global expression pattern between male and female groups. Using the optimized machine learning model, several ncRNAs and mRNAs with higher AUC and MeanDecreaseGini, including GCNT1P1 and AC092745.1, etc., were identified as potential molecular targets to distinguish suicide with, or without MDD and depression without suicide. WGCNA analysis identified some key modules significantly associated with these three phenotypes, and the gene biological functions of the key modules mainly relate to ncRNA and miRNA processing, as well as oxidoreductase and dehydrogenase activity. Hub genes such as RP11-349A22.5, C20orf196, MAPK8IP3 and RP11-697N18.2 were found in these key modules. TissueEnrich analysis showed that nucleus accumbens and subiculum were significantly changed among the 6 brain regions studied. Global analysis with Vegan and RRHO identified PRS26, ARNT and SYN3 as the most significantly differentially expressed genes across phenotype and tissues, and there was little overlap between the male and female groups. In this study, we have identified novel gene targets, as well as annotated functions of co-expression patterns and hub genes that are significantly distinctive between depression with suicide, depression without suicide, and suicide without depression. Moreover, global analysis across three phenotypes and tissues confirmed the evidence of sex difference in mood disorders.

MicroRNA-124-3p alleviates cerebral ischaemia-induced neuroaxonal damage by enhancing Nrep expression

OBJECTIVE

Ischaemic stroke has a high death rate and frequently results in long-term and severe brain damage in survivors. miRNA-124-3p (miR-124-3p) treatment has been suggested to reduce ischaemia and play a vital function in avoiding neuron death. An investigation of the role of miR-124-3p, in the ischaemia damage repair or protection in the middle cerebral artery occlusion (MCAO) model and oxygen-glucose deprivation/reperfusion (OGD/R) model, was the purpose of this research.

METHODS

The expression of miRNA and mRNA in the MCAO model was predicted using bioinformatics analysis. The OGD/R neuronal model was developed. We examined the influence of a number of compounds on the OGD/R model in vitro using gain- and loss-of-function approaches.

RESULTS

For starters, miR-124-3p and Nrep level in the MCAO model were found to be lower in the model predicted by bioinformatics than in the sham-operated group. And then in the OGD/R model, miR-124-3p treatment reduced OGD/R neuronal damage, increased neuronal survival, and reduced apoptosis in cell lines. Moreover, we further looked at the impact of miR-124-3p on downstream Rnf38 and Nrep using the OGD/R model. Western blot analysis and dual-luciferase reporter assays indicated that miR-124-3p binds and inhibits Rnf38. Finally, although Nrep expression was reduced in the OGD/R model neuronal model, it was shown that miR-124-3p administration reduced apoptosis and increased neuronal activity, particularly with regard to axon regeneration-related proteins.

CONCLUSION

Our studies have shown that miR-124-3p may reduce neuronal injury by preventing Rnf38-mediated effects on the Nrep axis.

The long noncoding RNA FEDORA is a cell type- and sex-specific regulator of depression

Women suffer from depression at twice the rate of men, but the underlying molecular mechanisms are poorly understood. Here, we identify marked baseline sex differences in the expression of long noncoding RNAs (lncRNAs), a class of regulatory transcripts, in human postmortem brain tissue that are profoundly lost in depression. One such human lncRNA, RP11-298D21.1 (which we termed FEDORA), is enriched in oligodendrocytes and neurons and up-regulated in the prefrontal cortex (PFC) of depressed females only. We found that virally expressing FEDORA selectively either in neurons or in oligodendrocytes of PFC promoted depression-like behavioral abnormalities in female mice only, changes associated with cell type-specific regulation of synaptic properties, myelin thickness, and gene expression. We also found that blood FEDORA levels have diagnostic implications for depressed women and are associated with clinical response to ketamine. These findings demonstrate the important role played by lncRNAs, and FEDORA in particular, in shaping the sex-specific landscape of the brain and contributing to sex differences in depression.

Emerging roles of long non-coding RNA in depression

Depression is the second most common psychiatric disorder, affecting more than 340 million people of all ages worldwide. However, the mechanisms underlying the development of depression remain unclear, and existing antidepressants may cause clinical dependence and toxic side effects. Recently, emerging evidence from the fields of neuroscience, genetics, and genomics supports the modulatory role of long non-coding RNA (lncRNA) in depression. LncRNAs may mediate the pathogenesis of depression through multiple pathways, including regulating neurotransmitters and neurotrophic factors, affecting synaptic conduction, and regulating the ventriculo-olfactory neurogenic system. In addition, relying on genome-wide association study and molecular biological experiment, the possibility of lncRNA as a potential biomarker for the differential diagnosis of depression and other mental illnesses, including schizophrenia and anxiety disorders, is gradually being revealed. Thus, it is important to explore whether lncRNAs are potential therapeutic targets and diagnostic biomarkers for depression. Here, we summarize the genesis and function of lncRNAs and discuss the aberrant expression and functional roles of lncRNAs in the development, diagnosis, and therapy of depression, as well as the deficiencies and limitations of these studies. Moreover, we established a lncRNA-miRNA-mRNA-pathway-drug network of depression through bioinformatics analysis methods to deepen our understanding of the relationship between lncRNA and depression, promoting the clinical application of epigenetic research.

The impact of psychosocial defeat stress on the bed nucleus of the stria terminalis transcriptome in adult male mice

The bed nucleus of the stria terminalis (BNST) is a focal point for the convergence of inputs from canonical stress-sensitive structures to fine-tune the response to stress. However, its role in mediating phenotypes of stress resilience or susceptibility is yet to be fully defined. In this study, we carried out unbiased RNA-sequencing to analyse the BNST transcriptomes of adult male mice, which were classified as resilient or susceptible following a 10-day chronic psychosocial defeat stress paradigm. Pairwise comparisons revealed 20 differentially expressed genes in resilience (6) and susceptible (14) mice compared with controls. An in silico validation of our data against an earlier study revealed significant concordance in gene expression profiles associated with resilience to chronic stress. Enrichment analysis revealed that resilience is linked to functions including retinoic acid hydrolase activity, phospholipase inhibitor and tumour necrosis factor (TNF)-receptor activities, whereas susceptibility is linked to alterations in amino acid transporter activity. We also identified differential usage of 134 exons across 103 genes associated with resilience and susceptibility; enrichment analysis for genes with differential exon usage in resilient mice was linked to functions including adrenergic receptor binding mice and oxysterol binding in susceptible mice. Our findings highlight the important and underappreciated role of the BNST in stress resilience and susceptibility and reveal research avenues for follow-up investigations.

Noncoding RNAs in Papillary Thyroid Cancer: Interaction with Cancer-Associated Fibroblasts (CAFs) in the Tumor Microenvironment (TME) and Regulators of Differentiation and Lymph Node Metastasis

A large majority of all thyroid cancers are papillary thyroid carcinomas (PTC), named for the specific papillary architecture observed histologically. Despite the high rate of success with modern diagnostic and therapeutic algorithms, there are significant areas where the management of PTC can be improved. Aggressive PTC subtypes that are refractory to radioactive iodine (RAI) therapy carry a more severe prognosis and account for most of PTC-related deaths. As lymph node metastasis is present in roughly 40% of all adult PTC cases, higher specificity in these tests is a clinical need, especially since lymph node metastases are associated with reduced survival and higher recurrence rates. Additionally, this cancer can progress to more dedifferentiated and aggressive variants, such as poorly differentiated papillary thyroid cancer (PDPTC) and anaplastic thyroid cancer (ATC). Therefore, development of more sensitive and specific detection methods that allow unnecessary surgeries to be avoided is of the utmost importance. The body of large-scale, unbiased gene expression analysis in PTC has focused on the coding transcriptome, specifically mRNAs and microRNAs. However, there have been implications for the potential use of long noncoding RNAs (lncRNAs) in PTC diagnosis, prognosis, and treatment via the utilization of genome-wide studies of patient samples. lncRNAs have diverse regulatory potential in gene expression, alternative splicing, posttranscriptional mRNA modification, and epigenomic alterations. Many lncRNAs have tissue-specific expression and are demonstrated to play key roles in cancer progression and prognosis. However, lncRNAs are not being exploited as biomarkers or therapeutic targets currently, despite their elucidated effects on oncogenesis. These potent biomarkers would be revolutionary in detection at early stages, as this significantly increases the chances of survival. Their aberrant expression in cancer and correlation with steps in tumorigenesis as well as their role in differentiation would allow for a promising role as a prognostic and diagnostic biomarker in thyroid cancer. This would help prevent the more aggressive ATC that derives from dedifferentiation of the less aggressive PTC and FTC. The targeting of the specific lncRNAs could also pose a valuable treatment option via preventing or reversing this dedifferentiation process and making this usually refractory form of thyroid cancer more responsive to standard treatment options.

Identification of the Complex Interplay Between Nematode-Related lncRNAs and Their Target Genes in Glycine max L

Soybean (Glycine max) is a major plant protein source and oilseed crop. However, plant-parasitic nematodes (PPNs) affect its annual yield. In the current study, in order to better understand the regulation of defense mechanism against PPNs in soybean, we investigated the role of long non-coding RNAs (lncRNAs) in response to two nematode species, Heterodera glycines (SCN: soybean cyst nematode) and Rotylenchulus reniformis (reniform). To this end, two publicly available RNA-seq data sets (SCN data set and RAD: reniform-associated data set) were employed to discover the lncRNAome profile of soybean under SCN and reniform infection, respectively. Upon identification of unannotated transcripts in these data sets, a seven-step pipeline was utilized to sieve these transcripts, which ended up in 384 and 283 potential lncRNAs in SCN data set and RAD, respectively. These transcripts were then used to predict cis and trans nematode-related targets in soybean genome. Computational prediction of target genes function, some of which were also among differentially expressed genes, revealed the involvement of putative nematode-responsive genes as well as enrichment of multiple stress responses in both data sets. Finally, 15 and six lncRNAs were proposed to be involved in microRNA-mediated regulation of gene expression in soybean in response to SNC and reniform infection, respectively. Collectively, this study provides a novel insight into the signaling and regulatory network of soybean-pathogen interactions and opens a new window for further research.

The Molecular Basis of Depression: Implications of Sex-Related Differences in Epigenetic Regulation

Major depressive disorder (MDD) is a leading cause of disability worldwide. Although the etiology and pathophysiology of MDD remain poorly understood, aberrant neuroplasticity mediated by the epigenetic dysregulation of gene expression within the brain, which may occur due to genetic and environmental factors, may increase the risk of this disorder. Evidence has also been reported for sex-related differences in the pathophysiology of MDD, with female patients showing a greater severity of symptoms, higher degree of functional impairment, and more atypical depressive symptoms. Males and females also differ in their responsiveness to antidepressants. These clinical findings suggest that sex-dependent molecular and neural mechanisms may underlie the development of depression and the actions of antidepressant medications. This review discusses recent advances regarding the role of epigenetics in stress and depression. The first section presents a brief introduction of the basic mechanisms of epigenetic regulation, including histone modifications, DNA methylation, and non-coding RNAs. The second section reviews their contributions to neural plasticity, the risk of depression, and resilience against depression, with a particular focus on epigenetic modulators that have causal relationships with stress and depression in both clinical and animal studies. The third section highlights studies exploring sex-dependent epigenetic alterations associated with susceptibility to stress and depression. Finally, we discuss future directions to understand the etiology and pathophysiology of MDD, which would contribute to optimized and personalized therapy.

Intersectional analysis of chronic mild stress-induced lncRNA-mRNA interaction networks in rat hippocampus reveals potential anti-depression/anxiety drug targets

Despite studies providing insight into the neurobiology of chronic stress, depression and anxiety, long noncoding RNA (lncRNA)-mediated mechanisms underlying the common and distinct pathophysiology of these stress-induced disorders remain nonconclusive. In a previous study, we used the chronic mild stress paradigm to separate depression-susceptible, anxiety-susceptible and insusceptible rat subpopulations. In the current study, lncRNA and messenger RNA (mRNA) expression was comparatively profiled in the hippocampus of the three stress groups using microarray technology. Groupwise comparisons identified distinct sets of lncRNAs and mRNAs associated with the three different behavioral phenotypes of the stressed rats. To investigate the regulatory roles of the dysregulated lncRNAs upon mRNA expression, correlations between the differential lncRNAs and mRNAs were first analyzed by combined use of weighted gene coexpression network analysis and ceRNA theory-based methods. Subsequent functional analysis of strongly correlated mRNAs indicated that the dysregulated lncRNAs were involved in various biological pathways and processes to specifically induce rat susceptibility or resiliency to depression or anxiety. Further intersectional analysis of phenotype-associated and drug-associated lncRNA-mRNA networks and subnetworks assisted in identifying 16 hub lncRNAs as potential targets of anti-depression/anxiety drugs. Collectively, our study established the molecular basis for understanding the similarities and differences in pathophysiological mechanisms underlying stress-induced depression or anxiety and stress resiliency, revealing several important lncRNAs that represent potentially new therapeutic drug targets for depression and anxiety disorders.

LncRNA Gm14205 induces astrocytic NLRP3 inflammasome activation via inhibiting oxytocin receptor in postpartum depression

Postpartum depression (PPD) is a kind of mental disorder characterized by persistent low emotions in puerperium. The most significant physiological change in postpartum is lactation which is regulated by oxytocin receptor (OXTR). However, whether OXTR is related to pathological process of PPD and the potential mechanism still remain unclear. In the present study, we prepared hormone-simulated pregnancy (HSP)-induced PPD mouse model and found that the protein level of OXTR in hippocampus of PPD model mice was down-regulated and Nod-like receptor protein 3 (NLRP3) inflammasome was activated. We identified five long non-coding RNAs (lncRNAs) related to PPD by transcriptome sequencing, including three up-regulated and two down-regulated. The five lncRNAs were associated with the signaling pathway of OXTR according to the bioinformatics analysis. Furthermore, we focused on one of the five lncRNAs, Gm14205, and found that it targeted OXTR which inhibited astrocytic NLRP3 inflammasome activation in hippocampal primary astrocytes. These findings illustrate that OXTR has protective effects in PPD by inhibiting NLRP3 inflammasome activation and provides a new strategy for targeting lncRNA Gm14205 in the pathogenesis of PPD.

Identification of an immune-based mRNA-lncRNA signature for overall survival in cervical squamous cell carcinoma

Aim: To better predict the survival of cervical squamous cell carcinoma (CESC) patients, we aimed to construct a signature according to different immune infiltration. Methods: We downloaded the RNA sequences of CESC patients from the Cancer Genome Atlas database. By using single-sample gene set enrichment analysis, we separated the samples into high- and low-immunity groups. Then we separated the samples into training and testing datasets and performed the following analyses: univariate, least absolute shrinkage and selection operator analysis, multivariate Cox regression analyses and weighted gene coexpression network analysis using R software. Gene ontology and Kyoto Encyclopedia of Genes and Genomes studies were performed using the Database for Annotation, Visualization and Integrated Discovery website. Results & conclusion: We finally identified a signature with three mRNAs and two lncRNAs: ADGRG5, HSH2D, ZMAT4, RBAKDN and LINC00200. In short, our study constructed an mRNA-lncRNA signature related to immune infiltration to better predict the survival of CESC patients.

DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier

Predicting the phenotypes resulting from molecular perturbations is one of the key challenges in genetics. Both forward and reverse genetic screen are employed to identify the molecular mechanisms underlying phenotypes and disease, and these resulted in a large number of genotype–phenotype association being available for humans and model organisms. Combined with recent advances in machine learning, it may now be possible to predict human phenotypes resulting from particular molecular aberrations. We developed DeepPheno, a neural network based hierarchical multi-class multi-label classification method for predicting the phenotypes resulting from loss-of-function in single genes. DeepPheno uses the functional annotations with gene products to predict the phenotypes resulting from a loss-of-function; additionally, we employ a two-step procedure in which we predict these functions first and then predict phenotypes. Prediction of phenotypes is ontology-based and we propose a novel ontology-based classifier suitable for very large hierarchical classification tasks. These methods allow us to predict phenotypes associated with any known protein-coding gene. We evaluate our approach using evaluation metrics established by the CAFA challenge and compare with top performing CAFA2 methods as well as several state of the art phenotype prediction approaches, demonstrating the improvement of DeepPheno over established methods. Furthermore, we show that predictions generated by DeepPheno are applicable to predicting gene–disease associations based on comparing phenotypes, and that a large number of new predictions made by DeepPheno have recently been added as phenotype databases.

Gene–phenotype associations can help to understand the underlying mechanisms of many genetic diseases. However, experimental identification, often involving animal models, is time consuming and expensive. Computational methods that predict gene–phenotype associations can be used instead. We developed DeepPheno, a novel approach for predicting the phenotypes resulting from a loss of function of a single gene. We use gene functions and gene expression as information to prediction phenotypes. Our method uses a neural network classifier that is able to account for hierarchical dependencies between phenotypes. We extensively evaluate our method and compare it with related approaches, and we show that DeepPheno results in better performance in several evaluations. Furthermore, we found that many of the new predictions made by our method have been added to phenotype association databases released one year later. Overall, DeepPheno simulates some aspects of human physiology and how molecular and physiological alterations lead to abnormal phenotypes.

Geniposide Alleviates Oxidative Stress of Mice With Depression-Like Behaviors by Upregulating Six3os1

Depression is a major cause of disease burden and severely impairs well-being of patients around the globe. Geniposide (GP) has been revealed to play a significant role in depression treatment. Of note, RNA sequencing of this study identified highly expressed long non-coding RNA Six3os1 in response to GP treatment. Thus, we aim to explore how GP affected chronic unpredictable mild stress (CUMS)-induced depression-like behaviors in mice in vivo and in vitro and the downstream molecular mechanism related to Six3os1. The relationship of Six3os1, miR-511-3p and Fezf1 was evaluated by dual-luciferase reporter gene assay, RIP assay, and RNA pulling down assay. Ectopic expression and knockdown experiments were developed in CUMS-induced mice and neurons with or without GP treatment. In vitro experiments and behavioral tests were conducted to examine alteration of CUMS-triggered oxidative stress following different interferences. The experimental data validated that GP treatment resulted in high expression of Six3os1 and Fezf1 and poor expression of miR-511-3p in CUMS-induced neurons. Six3os1 activated the AKT signaling pathway by upregulating miR-511-3p-targeted Fezf1. Either GP treatment or overexpression of Six3os1 or Fezf1 alleviated depression-like behaviors of CUMS-induced mice. GP treatment, miR-511-3p inhibition or overexpression of Six3os1 or Fezf1 not only reduced oxidative stress in CUMS-induced mice and neurons, but also reduced CUMS-induced neuronal apoptosis. Collectively, GP treatment-mediated Six3os1 upregulation ameliorated oxidative stress of mice with depression-like behaviors via the miR-511-3p/Fezf1/AKT axis.

Weighted gene co-expression network analysis identifies FCER1G as a key gene associated with diabetic kidney disease

Background

Diabetic kidney disease (DKD) is the primary cause of end-stage renal disease. However, the pathogenesis of DKD remains unclarified, and there is an urgent need for improved treatments. Recently, many crucial genes closely linked to the molecular mechanism underlying various diseases were discovered using weighted gene co-expression network analysis.

Methods

We used a gene expression omnibus series dataset GSE104948 with 12 renal glomerular DKD tissue samples and 18 control samples obtained from the gene expression omnibus database and performed weighted gene co-expression network analysis. After obtaining the trait-related modules, gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses of the modules were conducted and the key gene associated with DKD was selected from the top two most significant gene ontology terms using the maximal clique centrality method. Finally, we verified the key gene using protein-protein interaction analysis, additional datasets, and explored the relationship between the key gene and DKD renal function using the Nephroseq v5 online database.

Results

Among the 10 gene co-expression modules identified, the darkorange2 and red modules were highly related to DKD and the normal biological process, respectively. Majority of the genes in the darkorange2 module were related to immune and inflammatory responses, and potentially related to the progression of DKD due to their abnormal up-regulation. After performing sub-network analysis of the genes extracted from the top two most significant gene ontology terms and calculating the maximal clique centrality values of each gene, FCER1G, located at the center of the protein-protein interaction network, was identified as a key gene related to DKD. Furthermore, gene expression omnibus validation in additional datasets also showed that FCER1G was overexpressed in DKD compared with normal tissues. Finally, Pearson’s correlation analysis between the expression of FCER1G and DKD renal function revealed that the abnormal upregulation of FCER1G was related to diabetic glomerular lesions.

Conclusions

Our study demonstrated for the first time that FCER1G is a crucial gene associated with the pathogenesis of DKD.

Identification of Hub Genes Associated with Hypertension and Their Interaction with miRNA Based on Weighted Gene Coexpression Network Analysis (WGCNA) Analysis

Background

Hypertension is one of the most widespread health conditions in the world, and the molecular mechanism of it is still unclear. In this study, we identified the hub genes (hub miRNA genes) associated with hypertension and explored the relationship between hypertension miRNA-gene by constructing a mRNA co-expression network and a miRNA co-expression network, which can help to reveal the mechanism and predict the prognosis of hypertension progression.

Material/Methods

Based on gene expression profile data of hypertensive samples from the Gene Expression Omnibus database, WGCNA was used to detect hypertension-related biomarkers and key mRNA and miRNA modules. Then, DAVID was used to perform gene-annotation enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) and miRPath were used for pathway analysis of mRNA and miRNAs genes.

Results

We identified 3 key modules relating to hypertension, 2 mRNA modules named M_saddlebrown and M_greenyellow and 1 miRNA module named M_salmon. In addition, 12 hub genes (RPL21, RPS28, LOC442727/PTGAP10, LOC100129599/RPS29P14, TBXAS1, FCER1G, CFP, FURIN, PECAM1, IGSF6, NCF1C, and LOC285296/UNC93B3) and 7 hub miRNAs (hsa-miR-1268a/b, hsa-miR-513c-3p, hsa-miR-4799-5p, hsa-miR-296-3p, hsa-miR-5195-5p, hsa-miR-219-2-3p, and hsa-miR-548d-5p) relating to hypertension were identified. HIF-1 signaling pathway and insulin signaling pathway were closely related to the 3 key modules. We also discovered 4 miRNAs (hsa-miR-548am-3p, hsa-miR-513c-3p, hsa-miR-182-5p, and hsa-miR-548d-5p) and 6 genes (IGF1R, GSK3B, FOXO1, PRKAR2B, HIF1A, and PIK3R1) were the core nodes in the hypertension-related miRNA-gene network, and hsa-miR-548am-3p was at the center of the network.

Conclusions

These findings will help improve the understanding of the pathogenesis of hypertension, and the discovered genes can serve as signatures for early diagnosis of hypertension.

The Role of Non-coding RNAs in Viral Myocarditis

Viral myocarditis (VMC) is a disease characterized as myocardial parenchyma or interstitium inflammation caused by virus infection, especially Coxsackievirus B3 (CVB3) infection, which has no accurate non-invasive examination for diagnosis and specific drugs for treatment. The mechanism of CVB3-induced VMC may be related to direct myocardial damage of virus infection and extensive damage of abnormal immune response after infection. Non-coding RNA (ncRNA) refers to RNA that is not translated into protein and plays a vital role in many biological processes. There is expanding evidence to reveal that ncRNAs regulate the occurrence and development of VMC, which may provide new treatment or diagnosis targets. In this review, we mainly demonstrate an overview of the potential role of ncRNAs in the pathogenesis, diagnosis and treatment of CVB3-induced VMC.

Sex-Specific Role for the Long Non-coding RNA LINC00473 in Depression

Depression is a common disorder that affects women at twice the rate of men. Here, we report that long non-coding RNAs (lncRNAs), a recently discovered class of regulatory transcripts, represent about one-third of the differentially expressed genes in the brains of depressed humans and display complex region- and sex-specific patterns of regulation. We identified the primate-specific, neuronal-enriched gene LINC00473 as downregulated in prefrontal cortex (PFC) of depressed females but not males. Using viral-mediated gene transfer to express LINC00473 in adult mouse PFC neurons, we mirrored the human sex-specific phenotype by inducing stress resilience solely in female mice. This sex-specific phenotype was accompanied by changes in synaptic function and gene expression selectively in female mice and, along with studies of human neuron-like cells in culture, implicates LINC00473 as a CREB effector. Together, our studies identify LINC00473 as a female-specific driver of stress resilience that is aberrant in female depression.

MicroRNA mediators of early life stress vulnerability to depression and suicidal behavior

Childhood environment can have a profound impact on brain structure and function. Epigenetic mechanisms have been shown to play a critical role in adaptive and maladaptive processes by regulating gene expression without changing the genome. Over the past few years, early life stress (ELS) has been established as a major risk factor for major depression and suicidal behavior along with other psychiatric illnesses in adulthood. In recent years, the emergence of small noncoding RNAs as a mega controller of gene expression has gained attention for their role in various disease processes. Among various noncoding RNAs, microRNAs (miRNAs) are the most studied and well characterized and have emerged as a major regulator of neural plasticity and higher brain functioning. More recently, although limited in number, studies are focusing on how miRNAs can play a role in the maladaptive processes associated with ELS both at adolescent and adult age and whether these processes are critical in developing depression and suicidal behavior. In this review, we critically evaluate how postnatal ELS relates to abnormalities in miRNA expression and functions from both animal and human literature and draw connections from these findings to depression and suicidal behavior later in life.

Circular RNA in Schizophrenia and Depression

Schizophrenia (SZ) and depression (DEP) are two common major psychiatric disorders that are associated with high risk of suicide. These disorders affect not only physical and mental health, but they also affect the social function of the individual. However, diagnoses of SZ and DEP are mainly based on symptomatic changes and the clinical experience of psychiatrists. These rather subjective measures can induce misdiagnoses and missed diagnoses. Therefore, it is necessary to further explore objective indexes for improving the early diagnoses and prognoses of SZ and DEP. Current research indicates that non-coding RNA (ncRNA) may play a role in the occurrence and development of SZ and DEP. Circular RNA (circRNA), as an important component of ncRNA, is associated with many biological functions, especially post-transcriptional regulation. Since circRNA is easily detected in peripheral blood and has a high degree of spatiotemporal tissue specificity and stability, these attributes provide us with a new idea to further explore the potential value for the diagnosis and treatment of SZ and DEP. Here, we summarize the classification, characteristics, and biological functions of circRNA and the most significant results of experimental studies, aiming to highlight the involvement of circRNA in SZ and DEP.

Epigenetic Mechanisms in the Neurodevelopmental Theory of Depression

The genome (genes), epigenome, and environment work together from the earliest stages of human life to produce a phenotype of human health or disease. Epigenetic modifications, including among other things: DNA methylation, modifications of histones and chromatin structure, as well as functions of noncoding RNA, are coresponsible for specific patterns of gene expression. This refers also to mental disorders, including depressive disorders. Early childhood experiences accompanied by severe stressors (considered a risk factor for depression in adult life) are linked with changes in gene expression. They include genes involved in a response to stress (hypothalamic-pituitary-adrenal axis, HPA), associated with autonomic nervous system hyperactivity and with cortical, and subcortical processes of neuroplasticity and neurodegeneration. These are, among others: gene encoding glucocorticoid receptor, FK506 binding protein 5 gene (FKBP5), gene encoding arginine vasopressin and oestrogen receptor alpha, 5-hydroxy-tryptamine transporter gene (SLC6A4), and gene encoding brain-derived neurotrophic factor. How about personality? Can the experiences unique to every human being, the history of his or her development and gene-environment interactions, through epigenetic mechanisms, shape the features of our personality? Can we pass on these features to future generations? Hence, is the risk of depression inherent in our biological nature? Can we change our destiny?

Unraveling the epigenetic landscape of depression: focus on early life stress

Depression is a devastating psychiatric disorder caused by a combination of genetic predisposition and life events, mainly exposure to stress. Early life stress (ELS) in particular is known to "scar" the brain, leading to an increased susceptibility to developing depression later in life via epigenetic mechanisms. Epigenetic processes lead to changes in gene expression that are not due to changes in DNA sequence, but achieved via modulation of chromatin modifications, DNA methylation, and noncoding RNAs. Here we review common epigenetic mechanisms including the enzymes that take part in reading, writing, and erasing specific epigenetic marks. We then describe recent developments in understanding how ELS leads to changes in the epigenome that are manifested in increased susceptibility to depression-like abnormalities in animal models. We conclude with highlighting the need for future studies that will potentially enable the utilisation of the understanding of epigenetic changes linked to ELS for the development of much-needed novel therapeutic strategies and biomarker discovery.
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