Gene set enrichment analysis (GSEA) is a widely used computational method for determining whether predefined sets of genes show statistically significant concordant differences between two biological states. Despite its popularity, effective visualization of GSEA results remains challenging particularly for users seeking to extract meaningful insights without extensive programming knowledge. Although several tools are available for visualizing GSEA results, many lack the flexibility and customization options necessary for a comprehensive exploration of the data. For instance, the desktop GSEA software generates basic plots that are not publication ready and offer limited options for editing or modification. Users often encounter difficulties adjusting graphical parameters to achieve the desired level of customization or visual quality. Furthermore, traditional tools often fail to meet the demands of emerging analytical needs. For instance, they will lack the capability to effectively compare pathway activity levels across multiple experimental conditions. To bridge this gap, we introduce GseaVis, a user‐friendly R package specifically designed to simplify and enhance the visualization of GSEA results. GseaVis provides a variety of highly customizable and publication‐ready plots including enrichment plots, ranked gene heatmaps, and other forms of graphic visualizations of enriched gene sets. With its simple interface and flexibility, our tool significantly lowers the barrier for biologists and bioinformaticians to explore and present their GSEA data clearly and effectively. The GseaVis package is available on GitHub and is integrated with well‐established R libraries, allowing easy data manipulation and seamless integration into existing bioinformatics workflows. The GseaVis is publicly available via GitHub (https://github.com/junjunlab/GseaVis) for users’ access. A complete description of the usages can be found on the manuscript’s GitHub page (https://junjunlab.github.io/gseavis‐manual/).

N⁶-methyladenosine (m⁶A) plays crucial roles in regulating RNA metabolisms. METTL16 identified as a single-component methyltransferase catalyzes m⁶A formation in the nucleus; whether it regulates cytoplasmic RNA fate remains unknown. Here, we detected the dual localization of METTL16 in the nucleus and cytoplasm. METTL16 depletion attenuates protein synthesis, but the methyltransferase activity is not required for its translation-promoting function. Mechanistically, we identified an interactor of METTL16, eIF4E2, which represses translation by acting as a competitor of eIF4E. The METTL16-eIF4E2 interaction impedes the recruitment of eIF4E2 to 5' cap structure, promoting the cap recognition by eIF4E and selective protein synthesis. Depletion of METTL16 suppresses lung tumorigenesis by downregulating the translation of key oncogenes. Collectively, our study reports a role of METTL16 in modulating translation and provides a therapeutic target for lung cancer treatment.

N⁶-methyladenosine (m⁶A) has emerged as a crucial epitranscriptomic mark which regulates a broad spectrum of physiological processes including stem cell differentiation. m⁶A-binding YTHDF proteins have recently been proposed to mediate differentiation of leukemia cell in a redundant manner. However, whether these proteins play semblable roles in pluripotent stem cell remain largely unknown. Here, we showed the differential functions of YTHDF1 and YTHDF3 in controlling the differentiation of embryonic stem cells (ESCs). Depletion of YTHDF3 in ESCs resulted in loss of pluripotency with accelerated expressions of marker genes involved in formation of three germ layers. Phenotypic and transcriptomic analyses revealed that loss of YTHDF1 led to dramatic impairment of cardiomyocytes (CMs) differentiation, accompanied by downregulated CM-specific genes. While, knockdown of YTHDF3 accelerated differentiation through facilitating the expressions of CM-specific gene. Notably, YTHDF3 appears to modulate cellular differentiation partially through suppression of YTHDF1, supporting the distinguishable but interrelated roles of YTHDF1 and YTHDF3 in cell fate determination.

Single-cell RNA sequencing as well as bulk RNA sequencing data provide valuable insights into both physiological and pathological processes. The effective interpretation of these data relies on the availability of sophisticated analysis and visualization tools. Here, we introduce ClusterGVis, an advanced bioinformatics software specifically designed to simplify the analysis and visualization of gene expression data. ClusterGVis provides a user-friendly interface that allows researchers to perform fuzzy c-means and k-means clustering on transcriptomic datasets. It enables researchers to uncover patterns and relationships within complex gene expression profiles effectively. The integrated heatmap visualization features support intuitive exploration of co-expression networks and the identification of differentially expressed genes across diverse experimental conditions. ClusterGVis serves a dual purpose by aiding in the identification of potential biomarkers and enriching the understanding of gene function and regulatory mechanisms. The tutorials, manual, source code, and demo data of ClusterGVis are publicly available at https://github.com/junjunlab/ClusterGVis and https://bioconductor.org/packages/ClusterGVis. The ClusterGVis Shiny App has been deployed on shinyapps.io and is accessible at https://laojunjun.shinyapps.io/clustergvis_app_v0/. The Shiny App source code is hosted on GitHub at https://github.com/junjunlab/ClusterGvis-app.

Adipogenesis is mediated by the complex gene expression networks involving the posttranscriptional modifications. The natural compound rhein has been linked to the regulation of adipogenesis, but the underlying regulatory mechanisms remain elusive. Herein, we systematically analyzed the effects of rhein on adipogenesis at both the transcriptional and posttranscriptional levels. Rhein remarkably suppresses adipogenesis in the stage-specific and dose-dependent manners. Rhein has been identified to inhibit fat mass and obesity-associated (FTO) demethylase activity. Surprisingly, side-by-side comparison analysis revealed that the rhein treatment and Fto knockdown triggered the differential gene regulatory patterns, resulting in impaired adipocyte formation. Specifically, rhein treatment mildly altered the transcriptome with hundreds of genes dysregulated. N⁶-methyladenosine (m⁶A) methylome profile showed that, although the supply of rhein induced increased m⁶A levels on a small subset of messenger RNAs (mRNAs), few of them showed dramatic transcriptional response to this compound. Moreover, the specific rhein-responsive mRNAs, which are linked to mitotic pathway, are barely methylated or contain m⁶A peaks without dramatic response to rhein, suggesting separate regulation of global m⁶A pattern and adipogenesis mediated by rhein. Further identification of m⁶A-independent pathways revealed a positive regulator, receptor expressing-enhancing protein 3 (REEP3), in guidance of adipogenesis. Hence, this study provides the mechanistic view of the cellular actions of rhein in the modulation of adipogenesis and identifies a potential novel target for obesity therapeutic research.

Translation occurring on cytoplasmic mRNA is precisely governed at three consecutive stages, including initiation, elongation and termination. A growing body of evidence has revealed that an emerging epitranscriptomic code N⁶-methyladenosine (m⁶A), asymmetrically present in a large subset of coding and non-coding transcripts, is crucially required for mediating the translatomic stability. Through recruiting translation machinery proteins, serving as a physical barrier, or directing RNA structural rearrangement and mRNA looping formation, m⁶A has been decoded to modulate translational dynamics through potentially influencing the progress of different stages, thereby forming an additional layer of complexity to the regulation of translation. In this review, we summarize the current understanding of how m⁶A guides mRNA translation under normal and stress conditions, highlighting the divergent molecular mechanisms of multifarious regulation of m⁶A-mediated translation.