Genome-Wide Profiling Reveals Alternative Polyadenylation of Innate Immune-Related mRNA in Patients With COVID-19

GutUDB: A comprehensive multiomics database for intestinal diseases

Gut Universe Database (GutUDB) provides a comprehensive, systematic, and practical platform for researchers, and is dedicated to the management, analysis, and visualization of knowledge related to intestinal diseases. Based on this database, eight major categories of omics data analyses are carried out to explore the genotype-phenotype characteristics of a certain intestinal disease. The first tool for comprehensive omics data research on intestinal diseases will help each researcher better understand intestinal diseases.

Whole blood transcriptome signature predicts severe forms of COVID-19: Results from the COVIDeF cohort study

COVID-19 is associated with heterogeneous outcome. Early identification of a severe progression of the disease is essential to properly manage the patients and improve their outcome. Biomarkers reflecting an increased inflammatory response, as well as individual features including advanced age, male gender, and pre-existing comorbidities, are risk factors of severe COVID-19. Yet, these features show limited accuracy for outcome prediction. The aim was to evaluate the prognostic value of whole blood transcriptome at an early stage of the disease. Blood transcriptome of patients with mild pneumonia was profiled. Patients with subsequent severe COVID-19 were compared to those with favourable outcome, and a molecular predictor based on gene expression was built. Unsupervised classification discriminated patients who would later develop a COVID-19-related severe pneumonia. The corresponding gene expression signature reflected the immune response to the viral infection dominated by a prominent type I interferon, with IFI27 among the most over-expressed genes. A 48-genes transcriptome signature predicting the risk of severe COVID-19 was built on a training cohort, then validated on an external independent cohort, showing an accuracy of 81% for predicting severe outcome. These results identify an early transcriptome signature of severe COVID-19 pneumonia, with a possible relevance to improve COVID-19 patient management.

1-L Transcription of SARS-CoV-2 Spike Protein S1 Subunit

The COVID-19 pandemic prompted rapid research on SARS-CoV-2 pathogenicity. Consequently, new data can be used to advance the molecular understanding of SARS-CoV-2 infection. The present bioinformatics study discusses the "spikeopathy" at the molecular level and focuses on the possible post-transcriptional regulation of the SARS-CoV-2 spike protein S1 subunit in the host cell/tissue. A theoretical protein-RNA recognition code was used to check the compatibility of the SARS-CoV-2 spike protein S1 subunit with mRNAs in the human transcriptome (1-L transcription). The principle for this method is elucidated on the defined RNA binding protein GEMIN5 (gem nuclear organelle-associated protein 5) and RNU2-1 (U2 spliceosomal RNA). Using the method described here, it was shown that 45% of the genes/proteins identified by 1-L transcription of the SARS-CoV-2 spike protein S1 subunit are directly linked to COVID-19, 39% are indirectly linked to COVID-19, and 16% cannot currently be associated with COVID-19. The identified genes/proteins are associated with stroke, diabetes, and cardiac injury.

M6A-related bioinformatics analysis indicates that LRPPRC is an immune marker for ischemic stroke

Ischemic stroke (IS) is a common cerebrovascular disease whose pathogenesis involves a variety of immune molecules, immune channels and immune processes. 6-methyladenosine (m6A) modification regulates a variety of immune metabolic and immunopathological processes, but the role of m6A in IS is not yet understood. We downloaded the data set GSE58294 from the GEO database and screened for m6A-regulated differential expression genes. The RF algorithm was selected to screen the m6A key regulatory genes. Clinical prediction models were constructed and validated based on m6A key regulatory genes. IS patients were grouped according to the expression of m6A key regulatory genes, and immune markers of IS were identified based on immune infiltration characteristics and correlation. Finally, we performed functional enrichment, protein interaction network analysis and molecular prediction of the immune biomarkers. We identified a total of 7 differentially expressed genes in the dataset, namely METTL3, WTAP, YWHAG, TRA2A, YTHDF3, LRPPRC and HNRNPA2B1. The random forest algorithm indicated that all 7 genes were m6A key regulatory genes of IS, and the credibility of the above key regulatory genes was verified by constructing a clinical prediction model. Based on the expression of key regulatory genes, we divided IS patients into 2 groups. Based on the expression of the gene LRPPRC and the correlation of immune infiltration under different subgroups, LRPPRC was identified as an immune biomarker for IS. GO enrichment analyses indicate that LRPPRC is associated with a variety of cellular functions. Protein interaction network analysis and molecular prediction indicated that LRPPRC correlates with a variety of immune proteins, and LRPPRC may serve as a target for IS drug therapy. Our findings suggest that LRPPRC is an immune marker for IS. Further analysis based on LRPPRC could elucidate its role in the immune microenvironment of IS.

Alternative Polyadenylation Regulatory Factors Signature for Survival Prediction in Kidney Renal Cell Carcinoma

Background

Alternative polyadenylation (APA) plays a vital regulatory role in various diseases. It is widely accepted that APA is regulated by APA regulatory factors.

Objective

Whether APA regulatory factors affect the prognosis of renal cell carcinoma remains unclear, and this is the main topic of this study.

Methods

We downloaded the transcriptome and clinical data from The Cancer Genome Atlas (TCGA) database. We used the Lasso regression system to construct an APA model for analyzing the relationship between common APA regulatory factors and renal cell carcinoma. We also validated our APA model using independent GEO datasets (GSE29609, GSE76207).

Results

It was found that the expression levels of 5 APA regulatory factors (CPSF1, CPSF2, CSTF2, PABPC1, and PABPC4) were significantly associated with tumor gene mutation burden (TMB) score in renal clear cell carcinoma, and the risk score constructed using the expression level of 5 key APA regulatory factors could be used to predict the outcome of renal clear cell carcinoma. The TMB score is associated with the remodeling of the immune microenvironment.

Conclusions

By identifying key APA regulatory factors in renal cell carcinoma and constructing risk scores for key APA regulatory factors, we showed that key APA regulators affect prognosis of renal clear cell carcinoma patients. In addition, the risk score level is associated with TMB, indicating that APA may affect the efficacy of immunotherapy through immune microenvironment-related genes. This helps us better understand the mRNA processing mechanism of renal clear cell carcinoma.

Single-cell transcriptomic sequencing data reveal aberrant DNA methylation in SMAD3 promoter region in tumor-associated fibroblasts affecting molecular mechanism of radiosensitivity in non-small cell lung cancer

OBJECTIVE

Non-small cell lung cancer (NSCLC) often exhibits resistance to radiotherapy, posing significant treatment challenges. This study investigates the role of SMAD3 in NSCLC, focusing on its potential in influencing radiosensitivity via the ITGA6/PI3K/Akt pathway.

METHODS

The study utilized gene expression data from the GEO database to identify differentially expressed genes related to radiotherapy resistance in NSCLC. Using the GSE37745 dataset, prognostic genes were identified through Cox regression and survival analysis. Functional roles of target genes were explored using Gene Set Enrichment Analysis (GSEA) and co-expression analyses. Gene promoter methylation levels were assessed using databases like UALCAN, DNMIVD, and UCSC Xena, while the TISCH database provided insights into the correlation between target genes and CAFs. Experiments included RT-qPCR, Western blot, and immunohistochemistry on NSCLC patient samples, in vitro studies on isolated CAFs cells, and in vivo nude mouse tumor models.

RESULTS

Fifteen key genes associated with radiotherapy resistance in NSCLC cells were identified. SMAD3 was recognized as an independent prognostic factor for NSCLC, linked to poor patient outcomes. High expression of SMAD3 was correlated with low DNA methylation in its promoter region and was enriched in CAFs. In vitro and in vivo experiments confirmed that SMAD3 promotes radiotherapy resistance by activating the ITGA6/PI3K/Akt signaling pathway.

CONCLUSION

High expression of SMAD3 in NSCLC tissues, cells, and CAFs is closely associated with poor prognosis and increased radiotherapy resistance. SMAD3 is likely to enhance radiotherapy resistance in NSCLC cells by activating the ITGA6/PI3K/Akt signaling pathway.

Variant- and vaccination-specific alternative splicing profiles in SARS-CoV-2 infections

The COVID-19 pandemic, driven by the SARS-CoV-2 virus and its variants, highlights the important role of understanding host-viral molecular interactions influencing infection outcomes. Alternative splicing post-infection can impact both host responses and viral replication. We analyzed RNA splicing patterns in immune cells across various SARS-CoV-2 variants, considering immunization status. Using a dataset of 190 RNA-seq samples from our prior studies, we observed a substantial deactivation of alternative splicing and RNA splicing-related genes in COVID-19 patients. The alterations varied significantly depending on the infecting variant and immunization history. Notably, Alpha or Beta-infected patients differed from controls, while Omicron-infected patients displayed a splicing profile closer to controls. Particularly, vaccinated Omicron-infected individuals showed a distinct dynamic in alternative splicing patterns not widely shared among other groups. Our findings underscore the intricate interplay between SARS-CoV-2 variants, vaccination-induced immunity, and alternative splicing, emphasizing the need for further investigations to deepen understanding and guide therapeutic development.

Multi-omics approaches for drug-response characterization in primary biliary cholangitis and autoimmune hepatitis variant syndrome

BACKGROUND

Primary biliary cholangitis (PBC) and autoimmune hepatitis (AIH) variant syndrome (VS) exhibit a complex overlap of AIH features with PBC, leading to poorer prognoses than those with PBC or AIH alone. The biomarkers associated with drug response and potential molecular mechanisms in this syndrome have not been fully elucidated.

METHODS

Whole-transcriptome sequencing was employed to discern differentially expressed (DE) RNAs within good responders (GR) and poor responders (PR) among patients with PBC/AIH VS. Subsequent gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted for the identified DE RNAs. Plasma metabolomics was employed to delineate the metabolic profiles distinguishing PR and GR groups. The quantification of immune cell profiles and associated cytokines was achieved through flow cytometry and immunoassay technology. Uni- and multivariable logistic regression analyses were conducted to construct a predictive model for insufficient biochemical response. The performance of the model was assessed by computing the area under the receiver operating characteristic (AUC) curve, sensitivity, and specificity.

FINDINGS

The analysis identified 224 differentially expressed (DE) mRNAs, 189 DE long non-coding RNAs, 39 DE circular RNAs, and 63 DE microRNAs. Functional pathway analysis revealed enrichment in lipid metabolic pathways and immune response. Metabolomics disclosed dysregulated lipid metabolism and identified PC (18:2/18:2) and PC (16:0/20:3) as predictors. CD4+ T helper (Th) cells, including Th2 cells and regulatory T cells (Tregs), were upregulated in the GR group. Pro-inflammatory cytokines (IFN-γ, TNF-α, IL-9, and IL-17) were downregulated in the GR group, while anti-inflammatory cytokines (IL-10, IL-4, IL-5, and IL-22) were elevated. Regulatory networks were constructed, identifying CACNA1H and ACAA1 as target genes. A predictive model based on these indicators demonstrated an AUC of 0.986 in the primary cohort and an AUC of 0.940 in the validation cohort for predicting complete biochemical response.

CONCLUSION

A combined model integrating genomic, metabolic, and cytokinomic features demonstrated high accuracy in predicting insufficient biochemical response in patients with PBC/AIH VS. Early recognition of individuals at elevated risk for insufficient response allows for the prompt initiation of additional treatments.

Neutrophil CD64 index as a new early predictive biomarker for infected pancreatic necrosis in acute pancreatitis

OBJECTIVE

Infectious pancreatic necrosis (IPN) is a serious complication of acute pancreatitis, and early recognition and timely intervention are the keys to improving clinical outcomes. The purpose of this study was to investigate the predictive capacity of the neutrophil CD64 index (nCD64 index) on IPN in patients with acute pancreatitis METHODS: This study comprises two independent cohorts: the training cohort consisted of 202 patients from Hunan Provincial People's Hospital, and the validation cohort consisted of 100 patients from Changsha Central Hospital. Peripheral blood samples were collected on the day of admission and on the 3rd, 5th, 7th, and 10th days of hospitalization, and the nCD64 index was detected by flow cytometry. Additionally, relevant clinical characteristics and laboratory biomarkers were collected and analyzed.

RESULTS

We observed that nCD64 index on admission was significantly higher in the IPN group than Non-IPN group (p < 0.001). In the training cohort, a higher occurrence rate of IPN was observed in the high nCD64 index group compared to the moderate and low nCD64 index group (p < 0.001). Further analysis showed that nCD64 index was significant positive correlated with the incidence rate of IPN (p < 0.001, correlation coefficient = 0.972). Furthermore, logistic regression analysis showed that high expression of the nCD64 index on admission was a risk factor for the occurrence of IPN (OR = 2.971, p = 0.038). We further found that the nCD64 index of IPN patients was significantly higher than the Non-IPN patients on the days 1, 3, and 5 after admission, and the nCD64 index of IPN patients before and after the onset (p < 0.05). At the same time, this study revealed that the nCD64 index on admission showed good predictive efficacy for IPN (AUC = 0.859, sensitivity = 80.8%, specificity = 87.5%), which was comparable to APACHE II score. And this finding was further validated in an independent cohort of 100 participants (AUC = 0.919, Sensitivity = 100.0%, Specificity = 76.6%).

CONCLUSION

This study demonstrated the clinical value of nCD64 index in patients with IPN patients for the first time through two independent cohort studies. The nCD64 index can be used as an early prediction and risk assessment tool for the occurrence of IPN, contributing to the improvement of patient outcomes and efficiency of medical resource allocation.

ACACA reduces lipid accumulation through dual regulation of lipid metabolism and mitochondrial function via AMPK- PPARα- CPT1A axis

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is a multifaceted metabolic disorder, whose global prevalence is rapidly increasing. Acetyl CoA carboxylases 1 (ACACA) is the key enzyme that controls the rate of fatty acid synthesis. Hence, it is crucial to investigate the function of ACACA in regulating lipid metabolism during the progress of NAFLD.

METHODS

Firstly, a fatty liver mouse model was established by high-fat diet at 2nd, 12th, and 20th week, respectively. Then, transcriptome analysis was performed on liver samples to investigate the underlying mechanisms and identify the target gene of the occurrence and development of NAFLD. Afterwards, lipid accumulation cell model was induced by palmitic acid and oleic acid (PA ∶ OA molar ratio = 1∶2). Next, we silenced the target gene ACACA using small interfering RNAs (siRNAs) or the CMS-121 inhibitor. Subsequently, experiments were performed comprehensively the effects of inhibiting ACACA on mitochondrial function and lipid metabolism, as well as on AMPK- PPARα- CPT1A pathway.

RESULTS

This data indicated that the pathways significantly affected by high-fat diet include lipid metabolism and mitochondrial function. Then, we focus on the target gene ACACA. In addition, the in vitro results suggested that inhibiting of ACACA in vitro reduces intracellular lipid accumulation, specifically the content of TG and TC. Furthermore, ACACA ameliorated mitochondrial dysfunction and alleviate oxidative stress, including MMP complete, ATP and ROS production, as well as the expression of mitochondria respiratory chain complex (MRC) and AMPK proteins. Meanwhile, ACACA inhibition enhances lipid metabolism through activation of PPARα/CPT1A, leading to a decrease in intracellular lipid accumulation.

CONCLUSION

Targeting ACACA can reduce lipid accumulation by mediating the AMPK- PPARα- CPT1A pathway, which regulates lipid metabolism and alleviates mitochondrial dysfunction.

Downregulation of CPSF6 leads to global mRNA 3' UTR shortening and enhanced antiviral immune responses

Alternative polyadenylation (APA) is a widespread mechanism of gene regulation that generates mRNA isoforms with alternative 3' untranslated regions (3' UTRs). Our previous study has revealed the global 3' UTR shortening of host mRNAs through APA upon viral infection. However, how the dynamic changes in the APA landscape occur upon viral infection remains largely unknown. Here we further found that, the reduced protein abundance of CPSF6, one of the core 3' processing factors, promotes the usage of proximal poly(A) sites (pPASs) of many immune related genes in macrophages and fibroblasts upon viral infection. Shortening of the 3' UTR of these transcripts may improve their mRNA stability and translation efficiency, leading to the promotion of type I IFN (IFN-I) signalling-based antiviral immune responses. In addition, dysregulated expression of CPSF6 is also observed in many immune related physiological and pathological conditions, especially in various infections and cancers. Thus, the global APA dynamics of immune genes regulated by CPSF6, can fine-tune the antiviral response as well as the responses to other cellular stresses to maintain the tissue homeostasis, which may represent a novel regulatory mechanism for antiviral immunity.

Triple Burden: The Incorrigible Threat of Tuberculosis, HIV, and COVID-19

The Coronavirus-19 (COVID-19) hasn't seen the dawn since its emergence, however waxing and waning has resulted in the emergence of deadly variants. The effects of pandemic have not been limited to its virulence, but have rather conferred multiple collateral effects, especially in developing countries; thereby, designating it as a SYNDEMIC. The same culminated in neglect of non-COVID-19 conditions like tuberculosis (TB) and human immunodeficiency virus-acquired immunodeficiency syndrome (HIV/AIDS). Besides being the prognostic factor for severe COVID-19, these infections in hidden pockets served as reservoir for emergence of the deadly Omicron. Another significant impact of this juxtaposition was on the delivery of healthcare services for TB and HIV.

The unanticipated COVID-19 pandemic turned the path of ongoing progress of elimination programs. Direct consequences of the COVID-19 pandemic were pronounced on diagnosis, treatment, and services for patients with TB and HIV. Essential TB services were reallocated to the COVID-19 rapid response task force. However, despite escalating the tribulations, this triple burden has simultaneously taught lessons to escalate the progress of halted programs. The pandemic has catalyzed an unusual level of collaboration among scientists, which can be exploited for TB and HIV. Fast-track diagnostics, digitalization, contact tracing, and vaccine development have enabled world to envision the same for TB/HIV.

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Variant- and Vaccination-Specific Alternative Splicing Profiles in SARS-CoV-2 Infections

The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, and its subsequent variants has underscored the importance of understanding the host-viral molecular interactions to devise effective therapeutic strategies. A significant aspect of these interactions is the role of alternative splicing in modulating host responses and viral replication mechanisms. Our study sought to delineate the patterns of alternative splicing of RNAs from immune cells across different SARS-CoV-2 variants and vaccination statuses, utilizing a robust dataset of 190 RNA-seq samples from our previous studies, encompassing an average of 212 million reads per sample. We identified a dynamic alteration in alternative splicing and genes related to RNA splicing were highly deactivated in COVID-19 patients and showed variant- and vaccination-specific expression profiles. Overall, Omicron-infected patients exhibited a gene expression profile akin to healthy controls, unlike the Alpha or Beta variants. However, significantly, we found identified a subset of infected individuals, most pronounced in vaccinated patients infected with Omicron variant, that exhibited a specific dynamic in their alternative splicing patterns that was not widely shared amongst the other groups. Our findings underscore the complex interplay between SARS-CoV-2 variants, vaccination-induced immune responses, and alternative splicing, emphasizing the necessity for further investigations into these molecular cross-talks to foster deeper understanding and guide strategic therapeutic development.

The role of post-transcriptional regulation in SARS-CoV-2 infection and pathogenicity

The COVID-19 pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has had a significant impact on global social and economic stability. To combat this, researchers have turned to omics approaches, particularly epitranscriptomics, to limit infection and develop effective therapeutic strategies. Multi-omics can provide the host response dynamics during multiple disease phases to reveal the molecular and cellular landscapes. Epitranscriptomics focuses on the mechanisms of gene transcription in cells and tissues and the relationship between genetic material and epigenetic regulation. This review highlights the role of post-transcriptional regulation in SARS-CoV-2, which affect various processes such as virus infection, replication, immunogenicity, and pathogenicity. The review also explains the formation mechanism of post-transcriptional modifications and how they can be regulated to combat viral infection and pathogenicity.

Carbon dioxide and MAPK signalling: towards therapy for inflammation

Inflammation, although necessary to fight infections, becomes a threat when it exceeds the capability of the immune system to control it. In addition, inflammation is a cause and/or symptom of many different disorders, including metabolic, neurodegenerative, autoimmune and cardiovascular diseases. Comorbidities and advanced age are typical predictors of more severe cases of seasonal viral infection, with COVID-19 a clear example. The primary importance of mitogen-activated protein kinases (MAPKs) in the course of COVID-19 is evident in the mechanisms by which cells are infected with SARS-CoV-2; the cytokine storm that profoundly worsens a patient's condition; the pathogenesis of diseases, such as diabetes, obesity, and hypertension, that contribute to a worsened prognosis; and post-COVID-19 complications, such as brain fog and thrombosis. An increasing number of reports have revealed that MAPKs are regulated by carbon dioxide (CO2); hence, we reviewed the literature to identify associations between CO2 and MAPKs and possible therapeutic benefits resulting from the elevation of CO2 levels. CO2 regulates key processes leading to and resulting from inflammation, and the therapeutic effects of CO2 (or bicarbonate, HCO3-) have been documented in all of the abovementioned comorbidities and complications of COVID-19 in which MAPKs play roles. The overlapping MAPK and CO2 signalling pathways in the contexts of allergy, apoptosis and cell survival, pulmonary oedema (alveolar fluid resorption), and mechanical ventilation-induced responses in lungs and related to mitochondria are also discussed. Video Abstract.

MkcDBGAS: a reference-free approach to identify comprehensive alternative splicing events in a transcriptome

Alternative splicing (AS) is an essential post-transcriptional mechanism that regulates many biological processes. However, identifying comprehensive types of AS events without guidance from a reference genome is still a challenge. Here, we proposed a novel method, MkcDBGAS, to identify all seven types of AS events using transcriptome alone, without a reference genome. MkcDBGAS, modeled by full-length transcripts of human and Arabidopsis thaliana, consists of three modules. In the first module, MkcDBGAS, for the first time, uses a colored de Bruijn graph with dynamic- and mixed- kmers to identify bubbles generated by AS with precision higher than 98.17% and detect AS types overlooked by other tools. In the second module, to further classify types of AS, MkcDBGAS added the motifs of exons to construct the feature matrix followed by the XGBoost-based classifier with the accuracy of classification greater than 93.40%, which outperformed other widely used machine learning models and the state-of-the-art methods. Highly scalable, MkcDBGAS performed well when applied to Iso-Seq data of Amborella and transcriptome of mouse. In the third module, MkcDBGAS provides the analysis of differential splicing across multiple biological conditions when RNA-sequencing data is available. MkcDBGAS is the first accurate and scalable method for detecting all seven types of AS events using the transcriptome alone, which will greatly empower the studies of AS in a wider field.

Post-transcriptional control of haemostatic genes: mechanisms and emerging therapeutic concepts in thrombo-inflammatory disorders

The haemostatic system is pivotal to maintaining vascular integrity. Multiple components involved in blood coagulation have central functions in inflammation and immunity. A derailed haemostasis is common in prevalent pathologies such as sepsis, cardiovascular disorders, and lately, COVID-19. Physiological mechanisms limit the deleterious consequences of a hyperactivated haemostatic system through adaptive changes in gene expression. While this is mainly regulated at the level of transcription, co- and posttranscriptional mechanisms are increasingly perceived as central hubs governing multiple facets of the haemostatic system. This layer of regulation modulates the biogenesis of haemostatic components, for example in situations of increased turnover and demand. However, they can also be 'hijacked' in disease processes, thereby perpetuating and even causally entertaining associated pathologies. This review summarizes examples and emerging concepts that illustrate the importance of posttranscriptional mechanisms in haemostatic control and crosstalk with the immune system. It also discusses how such regulatory principles can be used to usher in new therapeutic concepts to combat global medical threats such as sepsis or cardiovascular disorders.

Role of different types of RNA molecules in the severity prediction of SARS-CoV-2 patients

SARS-CoV-2 pandemic is the current threat of the world with enormous number of deceases. As most of the countries have constraints on resources, particularly for intensive care and oxygen, severity prediction with high accuracy is crucial. This prediction will help the medical society in the selection of patients with the need for these constrained resources. Literature shows that using clinical data in this study is the common trend and molecular data is rarely utilized in this prediction. As molecular data carry more disease related information, in this study, three different types of RNA molecules ( lncRNA, miRNA and mRNA) of SARS-COV-2 patients are used to predict the severity stage and treatment stage of those patients. Using seven different machine learning algorithms along with several feature selection techniques shows that in both phenotypes, feature importance selected features provides the best accuracy along with random forest classifier. Further to this, it shows that in the severity stage prediction miRNA and lncRNA give the best performance, and lncRNA data gives the best in treatment stage prediction. As most of the studies related to molecular data uses mRNA data, this is an interesting finding.

CASA: a comprehensive database resource for the COVID-19 Alternative Splicing Atlas

BACKGROUND

As a key process in transcriptional regulatory mechanisms, alternative splicing (AS) plays a crucial role in maintaining the diversity of RNA and protein expression, and mediates the immune response in infectious diseases, especially for the COVID-19. Therefore, urgent data gathering and more research of AS profiles in microbe-infected human cells are needed to improve understanding of COVID-19 and related infectious diseases. Herein, we have created CASA, the COVID-19 Alternative Splicing Atlas to provide a convenient computing platform for studies of AS in COVID-19 and COVID-19-related infectious diseases.

METHODS

In CASA, we reanalyzed thousands of RNA-seq datasets generated from 65 different tissues, organoids and cell lines to systematically obtain quantitative data on AS events under different conditions. A total of 262,994 AS events from various infectious diseases with differing severity were detected and visualized in this database. In order to explore the potential function of dynamics AS events, we performed analysis of functional annotations and drug-target interactions affected by AS in each dataset. RNA-binding proteins (RBPs), which may regulate these dynamic AS events are also provided for users in this database.

RESULTS

CASA displays microbe-induced alterations of the host cell splicing landscape across different virus families and helps users identify condition-specific splicing patterns, as well as their potential regulators. CASA may greatly facilitate the exploration of AS profiles and novel mechanisms of host cell splicing by viral manipulation. CASA is freely available at http://www.splicedb.net/casa/ .

Alternative splicing signatures of congenital heart disease and induced pluripotent stem cell-derived cardiomyocytes from congenital heart disease patients

Congenital heart disease (CHD) is the most serious congenital defect in newborns with higher mortality. Alternative splicing (AS) plays an essential role in numerous heart diseases. However, our understanding of the link between mRNA splicing and CHD in humans is limited. Here, we try to investigate the genome-wide AS events in CHD using bioinformatics methods. We collected available RNA-seq datasets of CHD-induced pluripotent stem cell-cardiomyocytes (iPSC-CMs) (including single ventricle disease [SVD] and tetralogy of Fallot [TOF]) and non-CHD from the Gene Expression Omnibus database. Then, we unprecedentedly performed AS profiles in CHD-iPSC-CMs and non-CHD-iPSC-CMs. The rMAPS was used to generate RNA-maps for the analysis of RNA-binding proteins' (RBPs) binding sites. We used StringTie to identify and quantify the transcripts from aligned RNA-Seq reads. A quantification matrix was generated with respect to different groups by extracting the transcripts per million values from StringTie outputs. Then, this matrix was used for correlation analysis between the expression level of RBP and AS level. Finally, we validated our AS results using RNA-seq data from CHD and non-CHD patient tissue samples. We identified CHD-related AS events using CHD-iPSC-CMs and CHD samples from patients. The results showed that functional enrichment of abnormal AS in SVD and TOF was transcription factor-related. Using rMAPS, RNA-binding proteins which regulated these AS were also determined, and RBP-AS regulatory network was constructed. Overall, we identified abnormal AS in CHD-iPSC-CMs and CHD samples from patients. We predicted AS regulators in SVD and TOF, respectively. At last, we concluded that AS played a key role in the pathogenesis of CHD.

Systematic analysis of clinical relevance and molecular characterization of m6A in COVID-19 patients

The outbreak of coronavirus disease 2019 (COVID-19) has affected more than 200 countries and regions to date. mRNA m⁶A methylation has been reported as a new therapeutic target in COVID-19 patients, and has received widespread attention. However, the effects of m⁶A on COVID-19 clinical features as well as the molecular characterization of m⁶A in real COVID-19 patients are largely unclear. We collected RNA-seq data and clinical data from 100 COVID-19 patients, and sequenced m⁶A-seq from peripheral blood mononuclear cells (PBMCs) of two COVID-19 patients. Using bioinformatics analysis, we found that m⁶A is associated with several clinical features of COVID-19 patients. Furthermore, molecular characterization of m⁶A of COVID-19 patients in vivo rather than cell lines is demonstrated for the first time. Our findings will be valuable for the development of novel treatment strategies for COVID-19 patients.