Project description:RNA is emerging as a key regulator of a plethora of biological processes. While its study has remained elusive for decades, the recent advent of high-throughput sequencing technologies provided the unique opportunity to develop novel techniques for the study of RNA structure and post-transcriptional modifications. Nonetheless, most of the required downstream bioinformatics analyses steps are not easily reproducible, thus making the application of these techniques a prerogative of few laboratories. Here we introduce RNA Framework, an all-in-one toolkit for the analysis of most NGS-based RNA structure probing and post-transcriptional modifications mapping experiments. To prove the extreme versatility of RNA Framework, we applied it to both an in-house generated DMS-MaPseq dataset, and to a series of literature available experiments. Notably, when starting from publicly available datasets, our software easily allows replicating authors' findings. Collectively, RNA Framework provides the most complete and versatile toolkit to date for a rapid and streamlined analysis of the RNA epistructurome. RNA Framework is available for download at: http://www.rnaframework.com.
Project description:Kethoxal-assisted ssDNA sequencing (KAS-seq) is gaining popularity as a robust and effective approach to study the dynamics of transcriptionally engaged RNA polymerases through profiling of genome-wide single-stranded DNA (ssDNA). Its latest variant, spKAS-seq, a strand-specific version of KAS-seq, has been developed to map genome-wide R-loop structures by detecting imbalances of ssDNA on two strands. However, user-friendly, open-source, and specific bioinformatic analyzer for KAS-seq data are still lacking. Here we present KAS-Analyzer as a flexible and integrated toolkit to facilitate the analysis and interpretation of KAS-seq data. KAS-Analyzer can perform standard analyses such as quality control, read alignment, and differential RNA polymerase activity analysis. In addition, KAS-Analyzer introduces many novel features, including, but not limited to: calculation of transcriptional indexes, identification of single-stranded transcribing enhancers, and high-resolution mapping of R-loops. We use benchmark datasets to demonstrate that KAS-Analyzer provides a powerful framework to study transient transcriptional regulatory programs. KAS-Analyzer is available at https://github.com/Ruitulyu/KAS-Analyzer.
Project description:The dynamic behavior of RNA underlies fundamental biological processes. RNA function is controlled by post-transcriptional modifications that are spatiotemporally regulated, but characterizing the distribution of modified RNA transcripts with subcellular resolution is a major challenge. Here we present APEX-RNA-MS, which combines APEX2 proximity labeling with LC-MS quantification of modified ribonucleotides. We use APEX-RNA-MS to characterize RNA modifications proximal to RNA-binding proteins enriched in non-membrane bound cellular structures. We measure changes in protein-proximal RNA modification levels upon induction of DNA damage foci and stress granules, consistent with previous studies using antibody-based imaging and biochemical fractionation. Further, we show that tRNA-specific modifications are proximal to G3BP1 and use RNA sequencing and RNA FISH to demonstrate the accumulation of multiple tRNAs in stress granules. Taken together, our work provides a general approach for characterizing the subcellular distribution of RNA modifications and reveals new insights into the composition and function of cellular condensates.
Project description:Cells express distinct splicing isoforms in normal physiology and disease. Long-read single-cell RNA-sequencing (LR-scRNAseq) enables isoform quantification at single-cell resolution. However, methods to assess isoform complexity between cell populations are lacking. To address this, we present Hypatia, a toolkit for analyzing isoform usage shifts, diversity, and expression. Using simulated data, we establish a framework for comparative analysis. Using three LR-scRNAseq data sets, we identify widespread transcript-level heterogeneities across cells.
Project description:We developed hictk, a toolkit that can transparently operate on .hic and .cool files with excellent performance. The toolkit is written in C++ and consists of a C++ library with Python bindings as well as CLI tools to perform common operations directly from the shell, including converting between .hic and .mcool formats. We benchmark the performance of hictk and compare it with other popular tools and libraries. We conclude that hictk significantly outperforms existing tools while providing the flexibility of natively working with both file formats without code duplication.