Ferroptosis is a form of regulated cell death driven by the accumulation of lipid hydroperoxides. Regulation of ferroptosis might be beneficial to cancer treatment. Non-coding RNAs (ncRNAs) are a class of RNA transcripts that generally cannot encode proteins and have been demonstrated to play critical roles in regulating ferroptosis. Herein, we developed ncFO, the ncRNA-ferroptosis association database, to document the manually curated and predicted ncRNAs that are associated with ferroptosis. Collectively, ncFO contains 90 experimentally verified entries, including 46 microRNAs (miRNAs), 21 long non-coding RNAs (lncRNAs), and 17 circular RNAs (circRNAs). In addition, ncFO also incorporates two online prediction tools based on the regulation and co-expression of ncRNA and ferroptosis genes. Using default parameters, we obtained 3260 predicted entries, including 598 miRNAs and 178 lncRNAs, by regulation, as well as 2,592,661 predicted entries, including 967 miRNAs and 9632 lncRNAs, by ncRNA-ferroptosis gene co-expression in more than 8000 samples across 20 cancer types. The detailed information of each entry includes ncRNA name, disease, species, tissue, target, regulation, publication time, and PubMed identifier. ncFO also provides survival analysis and differential expression analysis for ncRNAs. In summary, ncFO offers a user-friendly platform to search and predict ferroptosis-associated ncRNAs, which might facilitate research on ferroptosis and discover potential targets for cancer treatment. ncFO can be accessed at http://www.jianglab.cn/ncFO/. <<<

In the evolutionary model of dosage compensation, per-allele expression level of the X chromosome has been proposed to have twofold up-regulation to compensate its dose reduction in males (XY) compared to females (XX). However, the expression regulation of X-linked genes is still controversial, and comprehensive evaluations are still lacking. By integrating multi-omics datasets in mammals, we investigated the expression ratios including X to autosomes (X:AA ratio) and X to orthologs (X:XX ratio) at the transcriptome, translatome, and proteome levels. We revealed a dynamic spatial-temporal X:AA ratio during development in humans and mice. Meanwhile, by tracing the evolution of orthologous gene expression in chickens, platypuses, and opossums, we found a stable expression ratio of X-linked genes in humans to their autosomal orthologs in other species (X:XX ≈ 1) across tissues and developmental stages, demonstrating stable dosage compensation in mammals. We also found that different epigenetic regulations contributed to the high tissue specificity and stage specificity of X-linked gene expression, thus affecting X:AA ratios. It could be concluded that the dynamics of X:AA ratios were attributed to the different gene contents and expression preferences of the X chromosome, rather than the stable dosage compensation. <<<

N-methyladenine (mA) is the most abundant RNA modification in mammalian messenger RNAs (mRNAs), which participates in and regulates many important biological activities, such as tissue development and stem cell differentiation. Due to an improved understanding of mA, researchers have discovered that the biological function of mA can be linked to many stages of mRNA metabolism and that mA can regulate a variety of complex biological processes. In addition to its location on mammalian mRNAs, mA has been identified on viral transcripts. mA also plays important roles in the life cycle of many viruses and in viral replication in host cells. In this review, we briefly introduce the detection methods of mA, the mA-related proteins, and the functions of mA. We also summarize the effects of mA-related proteins on viral replication and infection. We hope that this review provides researchers with some insights for elucidating the complex mechanisms of the epitranscriptome related to viruses, and provides information for further study of the mechanisms of other modified nucleobases acting on processes such as viral replication. We also anticipate that this review can stimulate collaborative research from different fields, such as chemistry, biology, and medicine, and promote the development of antiviral drugs and vaccines. <<<

Jacqueline Rehner, Georges Pierre Schmartz, Laura Groeger, Jan Dastbaz, Nicole Ludwig, Matthias Hannig, Stefan Rupf, Berthold Seitz, Elias Flockerzi, Tim Berger, Matthias Christian Reichert, Marcin Krawczyk, Eckart Meese, Christian Herr, Robert Bals, Sören L Becker, Andreas Keller, Rolf Müller, IMAGINE Consortium <<<

High-quality DNA extraction is a crucial step in metagenomic studies. Bias by different isolation kits impairs the comparison across datasets. A trending topic is, however, the analysis of multiple metagenomes from the same patients to draw a holistic picture of microbiota associated with diseases. We thus collected bile, stool, saliva, plaque, sputum, and conjunctival swab samples and performed DNA extraction with three commercial kits. For each combination of the specimen type and DNA extraction kit, 20-gigabase (Gb) metagenomic data were generated using short-read sequencing. While profiles of the specimen types showed close proximity to each other, we observed notable differences in the alpha diversity and composition of the microbiota depending on the DNA extraction kits. No kit outperformed all selected kits on every specimen. We reached consistently good results using the Qiagen QiAamp DNA Microbiome Kit. Depending on the specimen, our data indicate that over 10 Gb of sequencing data are required to achieve sufficient resolution, but DNA-based identification is superior to identification by mass spectrometry. Finally, long-read nanopore sequencing confirmed the results (correlation coefficient > 0.98). Our results thus suggest using a strategy with only one kit for studies aiming for a direct comparison of multiple microbiotas from the same patients. <<<