N6-methyladenosine (m6A) has been increasingly recognized as a new and important regulator of gene expression. To date, transcriptome-wide m6A detection primarily relies on well-established methods using next-generation sequencing (NGS) platform. However, direct RNA sequencing (DRS) using the Oxford Nanopore Technologies (ONT) platform has recently emerged as a promising alternative method to study m6A. While multiple computational tools are being developed to facilitate the direct detection of nucleotide modifications, little is known about the capabilities and limitations of these tools. Here, we systematically compare ten tools used for mapping m6A from ONT DRS data. We find that most tools present a trade-off between precision and recall, and integrating results from multiple tools greatly improve performance. Using a negative control could improve precision by subtracting certain intrinsic bias. We also observed variation in detection capabilities and quantitative information among motifs, and identified sequencing depth and m6A stoichiometry as potential factors affecting performance. Our study provides insight into the computational tools currently used for mapping m6A based on ONT DRS data and highlights the potential for further improving these tools, which may serve as the basis for future research.
Sleep is essential for maintaining health. Indeed, sleep loss is closely associated with multiple health problems, including gastrointestinal disorders. However, it is not yet clear whether sleep loss affects the function of intestinal stem cells (ISCs). Mechanical sleep deprivation and sss mutant flies were used to generate the sleep loss model. qRT‐PCR was used to measure the relative mRNA expression. Gene knock‐in flies were used to observe protein localization and expression patterns. Immunofluorescence staining was used to determine the intestinal phenotype. The shift in gut microbiota was observed using 16S rRNA sequencing and analysis. Sleep loss caused by mechanical sleep deprivation and sss mutants disturbs ISC proliferation and intestinal epithelial repair through the brain–gut axis. In addition, disruption of SSS causes gut microbiota dysbiosis in Drosophila. As regards the mechanism, gut microbiota and the GABA signalling pathway both partially played a role in the sss regulation of ISC proliferation and gut function. The research shows that sleep loss disturbed ISC proliferation, gut microbiota, and gut function. Therefore, our results offer a stem cell perspective on brain–gut communication, with details on the effect of the environment on ISCs.
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