Using clusterProfiler to characterize multiomics data.

With the advent of multiomics, software capable of multidimensional enrichment analysis has become increasingly crucial for uncovering gene set variations in biological processes and disease pathways. This is essential for elucidating disease mechanisms and identifying potential therapeutic targets. clusterProfiler stands out for its comprehensive utilization of databases and advanced visualization features. Importantly, clusterProfiler supports various biological knowledge, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, through performing over-representation and gene set enrichment analyses. A key feature is that clusterProfiler allows users to choose from various graphical outputs to visualize results, enhancing interpretability. This protocol describes innovative ways in which clusterProfiler has been used for integrating metabolomics and metagenomics analyses, identifying and characterizing transcription factors under stress conditions, and annotating cells in single-cell studies. In all cases, the computational steps can be completed within ~2 min. clusterProfiler is released through the Bioconductor project and can be accessed via https://bioconductor.org/packages/clusterProfiler/ .

Reducing language barriers, promoting information absorption, and communication using fanyi.

ABSTRACT: Interpreting genes of interest is essential for identifying molecular mechanisms, but acquiring such information typically involves tedious manual retrieval. To streamline this process, the fanyi package offers tools to retrieve gene information from sources like National Center for Biotechnology Information (NCBI), significantly enhancing accessibility. Additionally, understanding the latest research advancements and sharing achievements are crucial for junior researchers. However, language barriers often restrict knowledge absorption and career development. To address these challenges, we developed the fanyi package, which leverages artificial intelligence (AI)-driven online translation services to accurately translate among multiple languages. This dual functionality allows researchers to quickly capture and comprehend information, promotes a multilingual environment, and fosters innovation in academic community. Meanwhile, the translation functions are versatile and applicable beyond biomedicine research to other domains as well. The fanyi package is freely available at https://github.com/YuLab-SMU/fanyi .

OsLCD3 interacts with OsSAMS1 to regulate grain size via ethylene/polyamine homeostasis control.

A fundamental question in developmental biology is how to regulate grain size to improve crop yields. Despite this, little is still known about the genetics and molecular mechanisms regulating grain size in crops. Here, we provide evidence that a putative protein kinase-like (OsLCD3) interacts with the S-adenosyl-L-methionine synthetase 1 (OsSAMS1) and determines the size and weight of grains. OsLCD3 mutation (lcd3) significantly increased grain size and weight by promoting cell expansion in spikelet hull, whereas its overexpression caused negative effects, suggesting that grain size was negatively regulated by OsLCD3. Importantly, lcd3 and OsSAMS1 overexpression (SAM1OE) led to large and heavy grains, with increased ethylene and decreased polyamines production. Based on genetic analyses, it appears that OsLCD3 and OsSAMS1 control rice grain size in part by ethylene/polyamine homeostasis. The results of this study provide a genetic and molecular understanding of how the OsLCD3-OsSAMS1 regulatory module regulates grain size, suggesting that ethylene/polyamine homeostasis is an appropriate target for improving grain size and weight.

RNA modification-related EIF4G2 is an immunotherapy determinant in osteosarcoma: A single-cell sequencing analysis.

The clinical outcomes of osteosarcoma are relatively dismal. As immunotherapy has revolutionized treatment for solid tumors, exploring novel immunotherapy-related therapeutic targets for osteosarcoma is important. In this study, we aimed to establish the connection between RNA modification and immunotherapy in osteosarcoma to identify novel therapeutic targets. An RNA modification-related signature was first developed using weight gene correlation network analysis and a machine-learning algorithm, random forest. The signature's prognostic value, drug prediction, and immune characteristics were analyzed. EIF4G2 from the signature was next identified as a critical immunotherapy determinant. EIF4G2 could also promote tumor proliferation, migration, and M2 macrophage migration by single-cell sequencing analysis and in vitro validation. Our signature and EIF4G2 are expected to provide valuable insights into the clinical management of osteosarcoma.

shinyTempSignal: an R shiny application for exploring temporal and other phylogenetic signals.

The molecular clock model is fundamental for inferring species divergence times from molecular sequences. However, its direct application may introduce significant biases due to sequencing errors, recombination events, and inaccurately labeled sampling times. Improving accuracy necessitates rigorous quality control measures to identify and remove potentially erroneous sequences. Furthermore, while not all branches of a phylogenetic tree may exhibit a clear temporal signal, specific branches may still adhere to the assumptions, with varying evolutionary rates. Supporting a relaxed molecular clock model better aligns with the complexities of evolution. The root-to-tip regression method has been widely used to analyze the temporal signal in phylogenetic studies and can be generalized for detecting other phylogenetic signals. Despite its utility, there remains a lack of corresponding software implementations for broader applications. To address this gap, we present shinyTempSignal, an interactive web application implemented with the shiny framework, available as an R package and publicly accessible at https://github.com/YuLab-SMU/shinyTempSignal. This tool facilitates the analysis of temporal and other phylogenetic signals under both strict and relaxed models. By extending the root-to-tip regression method to diverse signals, shinyTempSignal helps in the detection of evolving features or traits, thereby laying the foundation for deeper insights and subsequent analyses.

Enhancement of de novo lipogenesis by the IDH1 and IDH2-dependent reverse TCA cycle maintains the growth and angiogenic capacity of bone marrow-derived endothelial progenitor cells under hypoxia.

BACKGROUND: Bone marrow-derived endothelial progenitor cells (EPCs) play a dynamic role in maintaining the structure and function of blood vessels. But how these cells maintain their growth and angiogenic capacity under bone marrow hypoxic niche is still unclear. This study aims to explore the mechanisms from a perspective of cellular metabolism. METHODS: XFe96 Extracellular Flux Analyzer was used to analyze the metabolic status of EPCs. Gas Chromatography-Mass Spectrometry (GC-MS) was used to trace the carbon movement of 13C-labeled glucose and glutamine under 1 % O2 (hypoxia) and ∼20 % O2 (normoxia). Moreover, RNA interference, targeting isocitrate dehydrogenase-1 (IDH1) and IDH2, was used to inhibit the reverse tricarboxylic acid (TCA) cycle and analyze metabolic changes via isotope tracing as well as changes in cell growth and angiogenic potential under hypoxia. The therapeutic potential of EPCs under hypoxia was investigated in the ischemic hindlimb model. RESULTS: Compared with normoxic cells, hypoxic cells showed increased glycolysis and decreased mitochondrial respiration. Isotope metabolic tracing revealed that under hypoxia, the forward TCA cycle was decreased and the reverse TCA cycle was enhanced, mediating the conversion of α-ketoglutarate (α-KG) into isocitrate/citrate, and de novo lipid synthesis was promoted. Downregulation of IDH1 or IDH2 under hypoxia suppressed the reverse TCA cycle, attenuated de novo lipid synthesis (DNL), elevated α-KG levels, and decreased the expression of hypoxia inducible factor-1α (HIF-1α) and vascular endothelial growth factor A (VEGFA), eventually inhibiting the growth and angiogenic capacity of EPCs. Importantly, the transplantation of hypoxia-cultured EPCs in a mouse model of limb ischemia promoted new blood vessel regeneration and blood supply recovery in the ischemic area better than the transplantation of normoxia-cultured EPCs. CONCLUSIONS: Under hypoxia, the IDH1- and IDH2-mediated reverse TCA cycle promotes glutamine-derived de novo lipogenesis and stabilizes the expression of α-KG and HIF-1α, thereby enhancing the growth and angiogenic capacity of EPCs.