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Data for: A structure-based mechanism for displacement of the HEXIM adapter from 7SK small nuclear RNA
<p><span>Productive transcriptional elongation of many cellular and viral mRNAs requires transcriptional factors to extract pTEFb from the 7SK snRNP by modulating the association between the HEXIM protein and the 7SK snRNA. Here we report the structure of the HEXIM arginine-rich motif in complex with the apical stemloop-1 of 7SK (7SK-SL1<sup>apical</sup>) and detail how the HIV transcriptional regulator Tat from various subtypes overcome the structural constraints required to displace HEXIM. While most interactions between 7SK and HEXIM and Tat are similar, critical differences exist that guide function. First, the conformational plasticity of 7SK enables the formation of three different base pair configurations at a critical remodeling site, which allows for the modulation required for HEXIM binding and its subsequent displacement by Tat. Furthermore, the specific sequence variations observed in various Tat subtypes all converge on remodeling 7SK at this region. Second, we show that HEXIM primes its own displacement by causing specific local destabilization upon binding </span>— <span>a feature that is then exploited by Tat to bind 7SK more efficiently. Overall, our study details the molecular environment presented by HEXIM and uncovers a destabilization-driven displacement strategy that increases the conformational sampling of 7SK-snRNP, which may allow diverse transcriptional factors to competitively regulate pTEFb.</span></p>
RNA 3D structure modeling by fragment assembly with Small Angle X-ray Scattering restraints
<p>Structure determination is a key step in the functional characterization of many non-coding RNA molecules. High-resolution RNA 3D structure determination efforts, however, are not keeping up with the pace of discovery of new non-coding RNA sequences. This increases the importance of computational approaches and low-resolution experimental data, such as from the Small Angle X-ray Scattering experiments. We present RNA Masonry, a computer program and a web service for a fully automated modeling of RNA 3D structures. It assemblies RNA fragments into geometrically plausible models that meet user-provided secondary structure constraints, restraints on tertiary contacts and Small Angle X-ray Scattering data. We illustrate the method description with detailed benchmarks and its application to structural studies of viral RNAs with SAXS restraints.</p>
Small RNA sequencing
<p>The innovation of large-scale, next-generation sequencing has exponentially increased knowledge of RNA biology, with regard to the diversity, abundance, and function of various RNA molecules. <a href="https://rna.cd-genomics.com/small-rna-sequencing.html">Small RNA-seq</a> is a powerful tool for analyzing small RNAs such as miRNAs, siRNAs, and piRNAs in a single sequencing run, allowing the evaluation and discovery of novel small RNA molecules and the prediction of their functions. These RNA-seq methods have provided an even more complete characterization of small RNA and promised further applications.<br><br>Our technologies at single-base resolution allow for small RNA detection from very small amounts of cellular materials, which can help you detect pre-known small RNA, discover new small RNA, and examine all small RNA for differential expression in any sample. We generate small RNA sequencing libraries directly from total RNA and Capture the complete range of small RNAs, to understand the roles they play. this will provide you with a comprehensive and efficient approach to understand post-transcriptional regulation and discovering novel biomarkers.</p>
Data for: A structure-based mechanism for displacement of the HEXIM adapter from 7SK small nuclear RNA
Open the record for dataset details and reuse information.
G-quadruplex-forming small RNA inhibits coronavirus and influenza A virus replication
Open the record for dataset details and reuse information.
A histone methyltransferase-independent function of PRC2 controls small RNA dynamics during programmed DNA elimination in Paramecium
<p><span lang="EN-US">To limit transposable element (TE) mobilization, most eukaryotes have evolved small RNAs to silence TE activity via homology-dependent mechanisms. Small RNAs, 20-30 nucleotides in length, bind to PIWI proteins and guide them to nascent transcripts by sequence complementarity, triggering the recruitment of histone methyltransferase enzymes on chromatin to repress the transcriptional activity of TEs and other repeats. In<span> the ciliate <em>Paramecium tetraurelia</em>,</span> 25-nt scnRNAs corresponding to TEs recruit Polycomb Repressive Complex 2 (PRC2), and trigger their elimination during the formation of the somatic nucleus. Here, we sequenced sRNAs during the entire sexual cycle with unprecedented resolution. Our data confirmed that scnRNAs are produced from the entire germline genome, from TEs and non-TE sequences, during meiosis. Non-TE scnRNAs are selectively degraded, which results in the specific selection of TE-scnRNAs. We demonstrate that PRC2 is essential for the selective degradation of non-TE-scnRNAs, independently of its histone methyltransferase activity. We further show that the PRC2 cofactor Rf4 mediates the physical interaction between the scnRNA-binding protein Ptiwi09 and the zinc finger protein Gtsf1, pointing to an architectural role of PRC2 in scnRNA degradation.</span></p>
HTLV-1 and HTLV-2 Infections Significantly Alter Small RNA Expression in Asymptomatic Carriers: A Pilot Study
<p><span>Small RNA NGS sequences from asymptomatic HTLV-2 infected individuals</span></p>
Atypical epigenetic and small RNA control of degenerated transposons and their fragments in clonally reproducing Spirodela polyrhiza.
<p><span>The dataset contains all the original raw files for images, including protein and RNA blots, DNA and protein sequences used for phylogenetic trees, do plots…, and any other type of source data, sorted by figure and figure panel. Plasmids generated for this study have been deposited in Addgene. They are listed below together with previously existing plasmids obtained from Addgene and used in this study. NGS data has been deposited on NCBI SRA, accession numbers of datasets used in each figure are listed accordingly in this document. Ready-to-visualize using IGV software files of all NGS datasets together with the S. polyrhiza 9509 gene and TE annotations are also provided. The content of each file is:</span></p> <p><span> </span></p> <p><strong><span>FIGURE 3:</span></strong></p> <p><span>- </span><strong><span>3A</span></strong><span>: Picture of Spirodela polyrhiza (used as well in S19A, S26B, D).</span></p> <p><span> </span></p> <p><strong><span>FIGURE 5:</span></strong></p> <p><span>- </span><strong><span>5A:</span></strong><span> Western blot raw TIFF image files for the detection of H3K9me1, H3K9me2 and H3 in Arabidopsis and Spirodela.</span></p> <p><span> </span></p> <p><strong><span>FIGURE 7:</span></strong></p> <p><span>- </span><strong><span>7A:</span></strong><span> Western blot and Coomassie raw TIFF image files for the detection of FHA-AtAGO4_gDNA and FHA-SpAGO4a_cDNA in input and IP fractions from transient expression in <em>N. benthamiana</em>.</span></p> <p><span>- </span><strong><span>7D:</span></strong><span> Raw scan image files of <em>N. benthamiana</em> leaves infiltrated with RUBY or Scarlet hairpin (hpScarlet) and Northern blots raw TIFF image files for the detection of siRNAs produced by RUBY and hpScarlet transiently expressed in <em>N. benthamiana</em>.</span></p> <p><span>- </span><strong><span>7E:</span></strong><span> Raw scan image files of Spirodela cultures in dishes infiltrated with RUBY or Scarlet hairpin (hpScarlet) and Northern blots raw TIFF image files for the detection of siRNAs produced by RUBY and hpScarlet transiently expressed in Spirodela.</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S6:</span></strong></p> <p><span>- </span><span>Protein sequences, and their alignment, of several angiosperm DRB proteins, including those identified in the <em>S. polyrhiza</em>9509 genome, used to build phylogenetic tree in fasta (.fa) format. Machine readable tree file is also provided in Nexus format (.nxs).</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S7:</span></strong></p> <p><span>- </span><span>Protein sequences, and their alignment, of several angiosperm RDR proteins, including those identified in the <em>S. polyrhiza</em>9509 genome, used to build phylogenetic tree in fasta (.fa) format. Machine readable tree file is also provided in Nexus format (.nxs).</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S8:</span></strong></p> <p><span>- </span><span>Protein sequences, and their alignment, of several angiosperm DCL proteins, including those identified in the <em>S. polyrhiza</em>9509 genome, used to build phylogenetic tree in fasta (.fa) format. Machine readable tree file is also provided in Nexus format (.nxs).</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S9:</span></strong></p> <p><span>- </span><span>Protein sequences, and their alignment, of several angiosperm AGO proteins, including those identified in the <em>S. polyrhiza</em>9509 genome, used to build phylogenetic tree in fasta (.fa) format. Machine readable tree file is also provided in Nexus format (.nxs).</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S10:</span></strong></p> <p><span>- </span><span>DNA sequence of the Spirodela (Sp9509) Chromosome 7 fragment containing the AGO5 cluster.</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S11:</span></strong></p> <p><span>- </span><span>Protein sequences, and their alignment, of several angiosperm SHH proteins, including those identified in the <em>S. polyrhiza</em>9509 genome, used to build phylogenetic tree in fasta (.fa) format. Machine readable tree file is also provided in Nexus format (.nxs).</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S12:</span></strong></p> <p><span>- </span><span>Protein sequences, and their alignment, of several angiosperm Snf2 remodelers proteins, including those identified in the <em>S. polyrhiza</em> 9509 genome, used to build phylogenetic tree in fasta (.fa) format. Machine readable tree file is also provided in Nexus format (.nxs).</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S13:</span></strong></p> <p><span>- </span><span>Protein sequences, and their alignment, of several angiosperm Class V SET-domain containing proteins, including those identified in the <em>S. polyrhiza</em> 9509 genome, used to build phylogenetic tree in fasta (.fa) format. Machine readable tree file is also provided in Nexus format (.nxs).</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S14:</span></strong></p> <p><span>- </span><span>Protein sequences, and their alignment, of several angiosperm DNA methyltransferase proteins, including those identified in the <em>S. polyrhiza</em> 9509 genome, used to build phylogenetic tree in fasta (.fa) format. Machine readable tree file is also provided in Nexus format (.nxs).</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S15:</span></strong></p> <p><span>- </span><span>Protein sequences, and their alignment, of several angiosperm RNA pol large subunit proteins, including those identified in the <em>S. polyrhiza</em> 9509 genome, used to build phylogenetic tree in fasta (.fa) format. Machine readable tree file is also provided in Nexus format (.nxs).</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S16:</span></strong></p> <p><span>- </span><span>Protein sequences, and their alignment, of several angiosperm SPT5 and SPT5L proteins, including those identified in the <em>S. polyrhiza</em> 9509 genome, used to build phylogenetic tree in fasta (.fa) format. Machine readable tree file is also provided in Nexus format (.nxs).</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S17:</span></strong></p> <p><span>- </span><span>Protein sequences, and their alignment, of several animal and plant Uhrf/VIM proteins, including those identified in the <em>S. polyrhiza</em> 9509 genome, used to build phylogenetic tree in fasta (.fa) format. Machine readable tree file is also provided in Nexus format (.nxs).</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S18:</span></strong></p> <p><span>- </span><strong><span>S18A_B:</span></strong><span> Protein sequences, and their alignment, of several angiosperm SUVH4 and SUVH5/6 proteins, including those identified in the <em>S. polyrhiza</em> 9509 genome, used to build phylogenetic tree in fasta (.fa) format. Machine readable tree file is also provided in Nexus format (.nxs).</span></p> <p><span>- </span><strong><span>S18C_D:</span></strong><span> Protein sequences, and their alignment, of several angiosperm ASI1 proteins, including those identified in the <em>S. polyrhiza</em> 9509 genome, used to build phylogenetic tree in fasta (.fa) format. Machine readable tree file is also provided in Nexus format (.nxs).</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S19:</span></strong></p> <p><span>- </span><span>Picture of Arabidopsis (used as well in S26 A,C).</span></p> <p><strong><span> </span></strong></p> <p><strong><span>SUPPLEMENTAL FIGURE S24:</span></strong></p> <p><span>- </span><strong><span>S24C:</span></strong> <span>Raw TIFF image files of the coomassie staining of histone acid-extraction protein samples run on SDS-PAGE gel.</span></p> <p><span>- </span><strong><span>S24D:</span></strong><span> Excel files with mass-spectrometry data used for quantification of histone modifications in Arabidopsis and Spirodela.</span></p> <p><span> </span></p> <p><strong><span>SUPPLEMENTAL FIGURE S27:</span></strong></p> <p><span>- </span><strong><span>S27A:</span></strong> <span>Raw czi and TIFF image files of Arabidopsis interphase nuclei stained with DAPI.</span></p> <p><span>- </span><strong><span>S27B:</span></strong> <span>Raw czi and TIFF image files of Spirodela interphase nuclei stained with DAPI.</span></p> <p><span> </span></p> <p><strong><span>SUPPLEMENTAL FIGURE S34:</span></strong></p> <p><span>- </span><span>DNA sequence files (fasta) of TEs used to generate dot plots</span><span>.</span></p> <p><span> </span></p> <p><strong><span>SUPPLEMENTAL FIGURE S35:</span></strong></p> <p><span>- </span><strong><span>S35A:</span></strong> <span>Western blot and Coomassie raw TIFF image files for the detection of FHA-AtAGO4_gDNA and FHA-SpAGO4a_gDNA in input and IP fractions from transient expression in <em>N. benthamiana</em>.</span></p> <p><span>- </span><strong><span>S35B:</span></strong> <span>Intron-annotated genomic DNA sequences of At<em>AGO4 </em>and Sp<em>AGO4a</em> in GenBank (.gbk) format.</span></p> <p><span>- </span><strong><span>S35C:</span></strong><span> Raw image file of EtBr staining of agarose gel electrophoresis of 5’OH-RACE prior to gel excision and cloning.</span></p> <p><span>- </span><strong><span>S35D:</span></strong> <span>Western blot and Coomassie raw TIFF image files for the detection of FHA-AtAGO4_gDNA and FHA-SpAGO4a_cDNA in input and IP fractions from transient expression in <em>N. benthamiana</em>.</span></p> <p><span> </span></p> <p><strong><span>SUPPLEMENTAL FIGURE S36:</span></strong></p> <p><span>- </span><span>DNA sequence files (fasta) of TEs used to generate dot plots</span><span>.</span></p> <p><span> </span></p> <p><strong><span>SUPPLEMENTAL FIGURE S38:</span></strong></p> <p><span>- </span><span>Pictures of Spirodela during pretreatment, manual and vacuum agroinfiltration and RUBY transient expression</span><span>.</span></p> <p><span> </span></p> <p><strong><span>GENOME BROWSER TRACKS:</span></strong></p> <p><span>- </span><span>The following Integrative Genomics Viewer browser (</span><a href="https://igv.org/"><span>https://igv.org</span></a><span>) tracks are provided:</span></p> <p><span>SPIRODELA</span></p> <p><span>· </span><span>Spirodela 9509 genome (this study)</span></p> <p><span>· </span><span>Spirodela gene annotations (V3.0)</span></p> <p><span>· </span><span>Spirodela TE annotations (this study)</span></p> <p><span>· </span><span>Spirodela H3K9me1 as log2[H3K9me1/H3] (this study)</span></p> <p><span>· </span><span>Spirodela H3K9me2 as log2[H3K9me2/H3] (this study)</span></p> <p><span>· </span><span>Spirodela H3K27me3 as log2[H3K27me3/H3] (this study)</span></p> <p><span>· </span><span>Spirodela H3K4me3 as log2[H3K4me3/H3] (this study)</span></p> <p><span>· </span><span>Spirodela H3K9me1 as log2[H3K9me1/H3] for H3K27me1 (this study)</span></p> <p><span>· </span><span>Spirodela H3K9me2 as log2[H3K9me2/H3] ] for H3K27me1 (this study)</span></p> <p><span>· </span><span>Spirodela H3K27me3 as log2[H3K27me3/H3] ] for H3K27me1 (this study)</span></p> <p><span>· </span><span>Spirodela TraPR purified 21-nt small RNAs (+ strand) (this study)</span></p> <p><span>· </span><span>Spirodela TraPR purified 21-nt small RNAs (- strand) (this study)</span></p> <p><span>· </span><span>Spirodela TraPR purified 22-nt small RNAs (+ strand) (this study)</span></p> <p><span>· </span><span>Spirodela TraPR purified 22-nt small RNAs (- strand) (this study)</span></p> <p><span>· </span><span>Spirodela TraPR purified 24-nt small RNAs (+ strand) (this study)</span></p> <p><span>· </span><span>Spirodela TraPR purified 24-nt small RNAs (- strand) (this study)</span></p> <p><span>· </span><span>Spirodela Illumina RNA seq coverage (this study)</span></p> <p><span>· </span><span>Spirodela Illumina RNA seq reads (this study)</span></p> <p><span>· </span><span>Spirodela PacBio Iso-seq coverage (this study)</span></p> <p><span>· </span><span>Spirodela PacBio Iso-seq reads (this study)</span></p> <p><span> </span></p> <p><span>ARABIDOPSIS</span></p> <p><span>· </span><span>Arabidopsis Col-0 genome (TAIR10)</span></p> <p><span>· </span><span>Arabidopsis gene annotations (TAIR10)</span></p> <p><span>· </span><span>Arabidopsis TE annotations (TAIR10)</span></p> <p><span>· </span><span>Arabidopsis seedlings H3K9me1 as log2[H3K9me1/H3] (this study)</span></p> <p><span>· </span><span>Arabidopsis seedlings H3K9me2 as log2[H3K9me2/H3] (this study)</span></p> <p><span>· </span><span>Arabidopsis seedlings H3K27me3 as log2[H3K27me3/H3] (this study)</span></p> <p><span>· </span><span>Arabidopsis seedlings H3K4me3 as log2[H3K4me3/H3] (this study)</span></p> <p><span>· </span><span>Arabidopsis seedlings TraPR purified 21-nt small RNAs (+ strand) (this study)</span></p> <p><span>· </span><span>Arabidopsis seedlings TraPR purified 21-nt small RNAs (- strand) (this study)</span></p> <p><span>· </span><span>Arabidopsis seedlings TraPR purified 22-nt small RNAs (+ strand) (this study)</span></p> <p><span>· </span><span>Arabidopsis seedlings TraPR purified 22-nt small RNAs (- strand) (this study)</span></p> <p><span>· </span><span>Arabidopsis seedlings TraPR purified 24-nt small RNAs (+ strand) (this study)</span></p> <p><span>· </span><span>Arabidopsis seedlings TraPR purified 24-nt small RNAs (- strand) (this study)</span></p> <p><span> </span></p> <p><strong><span>NGS DATASETS:</span></strong></p> <p><span> </span></p> <p><span>All the NGS data generated for this study can be found under the SRA BioProject ID PRJNA1164696. The data was used to generate the following figure panels:</span></p> <p><span>- </span><span>Figures: 1A-H, 2A-F, 3A-E, 4A-H, 5D-J, 6A-G, 7B, 7F-H</span></p> <p><span>- </span><span>Supplemental Figures: S1, S3, S4, S19, S20, S22, S23, S26, S28, S29, S30, S31, S32, S33, S35, S36, S37, S38.</span></p> <p><span> </span></p> <p><span>Publicly available sequencing data (from indicated datasets) was used to generate the following figures:</span></p> <p><span>- </span><span>Figure 2A-F (Arabidopsis gene expression): GSM6892968</span></p> <p><span> </span></p> <p><strong><span>MASS SPECTROMETRY DATA:</span></strong></p> <p><span> </span></p> <p><span>The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD050443. Data was used to generate:</span></p> <p><span>- </span><span>Supplemental Figure 24D</span></p> <p><span> </span></p> <p><strong><span>PLASMIDS:</span></strong></p> <p><span> </span></p> <p><span>The following plasmids generated in this study can be retrieved from Addgene under the following ID#:</span></p> <p><span>- </span><span>p35S:FHA-AtAGO4_gDNA: #216838</span></p> <p><span>- </span><span>p35S:FHA-SpAGO4a_gDNA: #216841</span></p> <p><span>- </span><span>p35S::FHA-SpAGO4a_cDNA: #216842</span></p> <p><span> </span></p> <p><span>The following plasmids used in this study were retrieved from Addgene under the following ID#:</span></p> <p><span>- </span><span>p35S:RUBY: #160908</span></p> <p><span>- </span><span>pZmUbq:RUBY: #160909</span></p> <p><span>- </span><span>p35S:GFP-GUS: #167122</span></p> <p><span> </span></p> <p><span>The following plasmids were a gift from Dr. Marco Incarbone (Max Planck Institute of Molecular Plant Physiology, Potsdam Science Park, Potsdam 14476, Germany).</span></p> <p><span>- </span><span>pAtUBQ:hpScarlet</span></p>
Chronic nicotine exposure alters sperm small RNA content in a C57BL/6J mouse model: Implications for epigenetic inheritance
<p>Raw small RNA sequencing data files to accompany manuscript</p>
NEBNext Small RNA Validation
<p>Data supporting the release of the NEBNext Small RNA kit (E7300, E7330, E7580, E7560).</p>
Immunotherapy of Melanoma With Tumor Antigen RNA and Small Inhibitory RNA Transfected Autologous Dendritic Cells
ClinicalTrials.gov study NCT00672542. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Exploring the potential of small RNA subunit and ITS sequences for resolving phylogenetic relationships within the phylum Ctenophora
Ctenophores are a phylum of non-bilaterian marine (mostly planktonic) animals, characterised by several unique synapomorphies (e.g. comb rows, apical organ). Relationships between and within the nine recognised ctenophore orders are far from understood, notably due to a paucity of phylogenetically-informative anatomical characters. Previous attempts to address ctenophore phylogeny using molecular data (18S rRNA) led to poorly resolved trees but demonstrated the paraphyly of the order Cydippida. Here we compiled an updated 18S rRNA data set, notably including a few newly-sequenced species representing previously unsampled families (Lampeidae, Euryhamphaeidae), and we built up an additional more rapidly-evolving ITS1+5.8SrRNA+ITS2 alignment. These data sets have been analysed separately and in combination under a probabilistic framework, using different methods (Maximum Likelihood, Bayesian inference) and models (e.g. doublet model to accommodate secondary structure; data partitioning). An important lesson from our exploration of these datasets is that the fast-evolving ITS regions are useful markers for reconstructing high-level relationships within ctenophores. Our results confirm the paraphyly of the order Cydippida (and thus a "cyddipid-like" ctenophore common ancestor) and suggest that the family Mertensiidae could be the sister-group of all other ctenophores. The family Lampeidae (also part of the former "Cydippida") is probably the sister-group of the order Platyctenida (benthic ctenophores). The order Beroida might not be monophyletic, due to the position of Beroe abyssicola outside of a clade grouping the other Beroe species and members of the "Cydippida" family Haeckeliidae. Many relationships (i.e. between Pleurobrachiidae, Beroida, Cestida, Lobata, Thalassocalycida) remain unresolved. Future progress in understanding ctenophore phylogeny will come from the use of additional rapidly-evolving markers and improvement of taxonomic sampling.
Data from: miR-122, small RNA annealing and sequence mutations alter the predicted structure of the Hepatitis C virus 5′ UTR RNA to stabilize and promote viral RNA accumulation
Annealing of the liver-specific microRNA, miR-122, to the Hepatitis C virus (HCV) 5′ UTR is required for efficient virus replication. By using siRNAs to pressure escape mutations, 30 replication-competent HCV genomes having nucleotide changes in the conserved 5′ untranslated region (UTR) were identified. In silico analysis predicted that miR-122 annealing induces canonical HCV genomic 5′ UTR RNA folding, and mutant 5′ UTR sequences that promoted miR-122-independent HCV replication favored the formation of the canonical RNA structure, even in the absence of miR-122. Additionally, some mutant viruses adapted to use the siRNA as a miR-122-mimic. We further demonstrate that small RNAs that anneal with perfect complementarity to the 5′ UTR stabilize and promote HCV genome accumulation. Thus, HCV genome stabilization and life-cycle promotion does not require the specific annealing pattern demonstrated for miR-122 nor 5′ end annealing or 3′ overhanging nucleotides. Replication promotion by perfect-match siRNAs was observed in Ago2 knockout cells revealing that other Ago isoforms can support HCV replication. At last, we present a model for miR-122 promotion of the HCV life cycle in which miRNA annealing to the 5′ UTR, in conjunction with any Ago isoform, modifies the 5′ UTR structure to stabilize the viral genome and promote HCV RNA accumulation.
Data from: Comprehensive experimental fitness landscape and evolutionary network for small RNA
The origin of life is believed to have progressed through an RNA world, in which RNA acted as both genetic material and functional molecules. The structure of the evolutionary fitness landscape of RNA would determine natural selection for the first functional sequences. Fitness landscapes are the subject of much speculation, but their structure is essentially unknown. Here we describe a comprehensive map of a fitness landscape, exploring nearly all of sequence space, for short RNAs surviving selection in vitro. With the exception of a small evolutionary network, we find that fitness peaks are largely isolated from one another, highlighting the importance of historical contingency and indicating that natural selection would be constrained to local exploration in the RNA world.
Guppy brain small RNA library prep
<p>Library preparation data</p>
Augmented base pairing networks encode RNA-small molecule binding preferences
<p>Dataset used to train and validate the RNAmigos model from "Augmented base pairing networks encode RNA-small molecule binding preferences".</p> <p> </p> <p>This will give you a cleaned up version of the data used to train the RNAmigos 1.0 models.</p> <p> </p> <p>If you run `python make_nice.py` you will generate a CSV file `rnamigos1_dataset.csv` which contains all the info you need.</p> <p>The script will also use DecoyFinder to generate the decoys for each pocket.</p> <p> </p> <p> </p> <p>### Pockets</p> <p> </p> <p>The CSV has one row for each binding pocket.</p> <p> </p> <p>The columns are:</p> <p> </p> <p>* pdbid: the PDBID this pocket belongs to</p> <p>* model_num: the model number inside the PDB we took</p> <p>* chain: the chain the pocket belongs to</p> <p>* ligand_id: the 3-letter code of the ligand (e.g. ATP) which you can look up on RCSB.org</p> <p>* ligand_resnum: the residue number of the ligand in the PDB</p> <p>* nodelist: a list of nodes separated by ';' in the pocket as a string in the format `<node1 pdbid>.<node1 chain>.<node1 position>-<nucleotide type>;<node2 pdbid>...`</p> <p>* edgelist: a list of edges separated by ';' in the pocket as a string in the format nodes are in the same format as above, and connected by a '-' char, with an additional label field. e.g. of a two edge list `1aju.A.1-1aju.A.5-CWW;1aju.A.1-1aju.A.2-B53`</p> <p>* fp_native_maccs: bit string of the MACCS for the native ligand</p> <p>* split_{k}_train: one col for all the splits we ran (k \in {0-9}) contains True if this pocket was in the train set for this split</p> <p>* split_{k}_test: one col for all the splits we ran (k \in {0-9}) contains True if this pocket was in the test set for this split</p> <p> </p> <p>### Decoys</p> <p> </p> <p>The folder `decoy_db/` has the following structure:</p> <p> </p> <p>```</p> <p>decoy_db</p> <p> <pdbid>_<chain>_{ligand_id}_{ligand_position}</p> <p> decoyfinder</p> <p> actives.txt</p> <p> decoys.txt</p> <p> pdb</p> <p> actives.txt</p> <p> decoys.txt</p> <p> </p> <p> </p> <p>Each `actives.txt` and `decoys.txt` is a file with one SMILES per line. </p> <p> </p> <p>`decoyfinder/` has decoys computed by DecoyFinder and the acvtives are just the native ligands.</p> <p>`pdb/` has decoys taken from other pockets in the PDB and actives are just the native ligands.</p>
A Study Using Intravitreal Injections of a Small Interfering RNA in Patients With Age-Related Macular Degeneration
ClinicalTrials.gov study NCT00395057. IPD Sharing: Not stated. Countries: 3. Publications: 0.
A First-in-Human Safety and Efficacy Study of ALN-CFB, a Small Interfering RNA (siRNA) Targeting Complement Factor B, in Adult Participants With Paroxysmal Nocturnal Hemoglobinuria With Persistent Ane
ClinicalTrials.gov study NCT07187401. IPD Sharing: YES. Countries: 2. Publications: 0.
Effect of Small Interfering RNA Inclisiran on Carotid Plaques As Assessed by Carotid Ultrasound
ClinicalTrials.gov study NCT06586684. IPD Sharing: NO. Countries: 0. Publications: 11.
Data from: miR-122, small RNA annealing and sequence mutations alter the predicted structure of the Hepatitis C virus 5′ UTR RNA to stabilize and promote viral RNA accumulation
Open the record for dataset details and reuse information.
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