Functional Characterization of a Phf8 Processed Pseudogene in the Mouse Genome

Transcriptomics data integration and analysis to uncover hallmark genes in hypertrophic cardiomyopathy

INTRODUCTION

Hypertrophic cardiomyopathy (HCM) is a heterogeneous disease that mainly affects the myocardium. In the current study, we aim to explore HCM-related hub genes through the analysis of differentially expressed genes (DEGs) between HCM and normal sample groups.

METHODS

The GSE68316 and GSE36961 expression profiles were obtained from the Gene Expression Omnibus (GEO) database for the identification of DEGs, to explore hub genes, and to perform their expression analysis. Clinical HCM and control tissue samples were taken for expression and promoter methylation validation analysis via RNA-sequencing (RNA-seq) and targeted bisulfite sequencing (bisulfite-seq) analyses. Then, other different bioinformatics tools were employed to perform STRING, lncRNA-miRNA-mRNA regulatory networks, gene enrichment, and drug prediction analyses.

RESULTS

In total, the top 20 DEGs, including 10 up-regulated and 10 down-regulated, were obtained from GSE68316. Out of the 20 DEGs, we subsequently identified the 8 most important hub genes including 5 up-regulated genes (EPB42, UQCRH, CA1, PFDN5, and LSM5) and 3 down-regulated genes (RPS24, TNS1, and RPL26). Expression and promoter methylation dysregulation of these genes were further validated on clinical HCM samples paired with controls. Next, we further investigated hub genes' regulatory 6 miRNAs (has-mir-1-3p, has-mir-129-5p, has-mir-16-5p, has-mir-23b-3p, has-mir-27-3p, and has-mir-182-5p) and miRNAs regulatory 4 lncRNAs (NUTMB2-AS1, NEAT1, XIST, and GABPB1-AS1) in this study via the lncRNA-cricRNA-miRNA-mRNA regulatory network. Later on, gene enrichment analysis revealed that hub genes were enriched in various important pathways including Nitrogen metabolism, Ribosome, RNA degradation, Cardiac muscle contraction, and Coronavirus disease, etc. Finally, the drug prediction analysis highlighted different potential candidate drugs for altering the expression of hub genes in the treatment of HCM.

CONCLUSION

In summary, the identification of key hub genes and their enrichment analysis in the current study may shed light on the mechanisms behind the occurrence and development of HCM.

Long-read RNA sequencing identifies region- and sex-specific C57BL/6J mouse brain mRNA isoform expression and usage

Alternative splicing (AS) contributes to the biological heterogeneity between species, sexes, tissues, and cell types. Many diseases are either caused by alterations in AS or by alterations to AS. Therefore, measuring AS accurately and efficiently is critical for assessing molecular phenotypes, including those associated with disease. Long-read sequencing enables more accurate quantification of differentially spliced isoform expression than short-read sequencing approaches, and third-generation platforms facilitate high-throughput experiments. To assess differences in AS across the cerebellum, cortex, hippocampus, and striatum by sex, we generated and analyzed Oxford Nanopore Technologies (ONT) long-read RNA sequencing (lrRNA-Seq) C57BL/6J mouse brain cDNA libraries. From >85 million reads that passed quality control metrics, we calculated differential gene expression (DGE), differential transcript expression (DTE), and differential transcript usage (DTU) across brain regions and by sex. We found significant DGE, DTE, and DTU across brain regions and that the cerebellum had the most differences compared to the other three regions. Additionally, we found region-specific differential splicing between sexes, with the most sex differences in DTU in the cortex and no DTU in the hippocampus. We also report on two distinct patterns of sex DTU we observed, sex-divergent and sex-specific, that could potentially help explain sex differences in the prevalence and prognosis of various neurological and psychiatric disorders in future studies. Finally, we built a Shiny web application for researchers to explore the data further. Our study provides a resource for the community; it underscores the importance of AS in biological heterogeneity and the utility of long-read sequencing to better understand AS in the brain.