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21,239 results for “RNA-Seq”
Influence of RNA-Seq library construction, sampling methods, and tissue harvesting time on gene expression estimation
<p>RNA sequencing (RNA-Seq) is popular for measuring gene expression in non-model organisms, including wild populations. While RNA-Seq can detect gene expression variation among wild-caught individuals and yield important insights into biological function, sampling methods may influence gene expression estimates. We examined the influence of multiple technical variables on estimated gene expression in a non-model fish, the westslope cutthroat trout (<em>Oncorhynchus clarkii lewisi</em>), using two RNA-Seq library types: 3' RNA-Seq (QuantSeq) and whole mRNA-Seq (NEB). We evaluated effects of dip netting versus electrofishing, and of harvesting tissue immediately versus 5 minutes after euthanasia on estimated gene expression in blood, gill, and muscle. We found no significant differences in gene expression between sampling methods or tissue collection times with either library type. When library types were compared using the same blood samples, 58% of genes detected by both NEB and QuantSeq showed significantly different expression between library types, and NEB detected 31% more genes than QuantSeq. Although QuantSeq and NEB recovered different numbers of genes and expression levels, there were no differences in gene expression between sampling methods and tissue harvesting time for either library type. Our study suggests that researchers can safely rely on different fish sampling strategies in the field. In addition, while QuantSeq is more cost-effective, NEB detects more expressed genes. Therefore, when it is crucial to detect as many genes as possible (especially low expressed genes), when alternative splicing is of interest, or when working with an organism lacking good genomic resources, whole mRNA-Seq is more powerful.</p>
Single-cell RNA-seq count data used in differential expression benchmark study
<p>Count matrices and meta data tables from simulated and real world immune cell single-cell RNA-seq experiments.</p> <p>All files are in Rds format and can be read by R using "readRDS()". </p> <ul> <li>10k_*: These files contain a filtered version of the 10k Human PBMCs, 3' v3.1 data <a href="https://www.10xgenomics.com/resources/datasets/10k-human-pbmcs-3-v3-1-chromium-controller-3-1-high">published</a> by 10x Genomics</li> <li>blueprint_data.Rds: This file contains the bulk RNA-seq data downloaded from <a href="http://dcc.blueprint-epigenome.eu">BLUEPRINT</a></li> <li>blueprint_immune_comparisons.Rds: Results from running three bulk RNA-seq differential expression methods</li> <li>sim_data*: These files contain the count matrices and meta data tables for the simulated data. Every file contains a list of 13 replicates.</li> </ul> <p> </p>
RNA-seq and RT-qPCR data showing MDF role in RNA splicing and gene expression control in Arabidopsis
<p>Plants respond to environmental stresses through controlled stem cell maintenance and meristem activity. One level of transcriptional control is RNA alternative splicing. However the mechanistic link between stress, meristem function and RNA splicing is poorly understood. The MERISTEM-DEFECTIVE (MDF)/DEFECTIVELY ORGANIZED TRIBUTARIES (DOT2) gene of Arabidopsis encodes a SR-related family protein, required for meristem function and leaf vascularization, and is the likely orthologue of the human SART1 and yeast snu66 splicing factors. MDF is required for the correct splicing and expression of key transcripts associated with root meristem function. We identified RSZ33 and ACC1, both known to regulate cell patterning, as splicing targets required for MDF function in the meristem. MDF expression is modulated by osmotic and cold stress, associated with differential splicing and specific isoform accumulation and shuttling between nucleus and cytosol, and acts in part via a splicing target SR34. We propose a model in which MDF controls splicing in the root meristem to promote stemness and repress stress response and cell differentiation pathways.</p>
Flnc: Machine Learning Improves the Identification of Novel Long Noncoding RNAs from Stand-Alone RNA-Seq Data
<p>Flnc is software that can accurately identify full-length long noncoding RNAs (lncRNAs) from human RNA-seq data. lncRNAs are linear transcripts of more than 200 nucleotides that do not encode proteins. The most common approach for identifying lncRNAs from RNA-seq data which examines the coding abilities of assembled transcripts will result in a very high false-positive rate (30%-75%) of lncRNA identification. The falsely discovered lncRNAs lack transcriptional start sites and most of them are RNA fragments or result from transcriptional noise. Unlike the false-positive lncRNAs, true lncRNAs are full-length lncRNA transcripts that include transcriptional start sites (TSSs). To exclude these false lncRNAs, H3K4me3 chromatin immunoprecipitation sequencing (ChIP-seq) data had been used to examine transcriptional start sites of putative lncRNAs, which are transcripts without coding abilities. However, because of cost, time, and the limited availability of sample materials for generating H3K4me3 ChIP-seq data, most samples (especially clinical biospecimens) may have available RNA-seq data but lack matched H3K4me3 ChIP-seq data. This Flnc method solves the problem of lacking transcriptional initiation profiles when identifying lncRNAs.</p> <p>Flnc integrates seven machine-learning algorithms built with four genomic features. Flnc achieves state-of-the-art prediction power with a AUROC score over 0.92. Flnc significantly improves the prediction accuracy from less than 50% using the common approach to over 85% on five independent datasets without requiring matched H3K4me3 ChIP-seq data. In addition to the stranded polyA-selected RNA-seq data, Flnc can also be applied to identify lncRNAs from stranded RNA-seq data of ribosomal RNA depleted samples or unstranded RNA-seq data of polyA-selected samples.</p>
TCGA RNA-Seq normalized rsem data, TCGA clinical data and mutational signature profiles
<p>Normalized rsem RNA-Seq data for each of the 33 TCGA tumor types named as "<em>tumortype</em>rnaSeq.tar", a file containing TCGA clinical data ("cliDat_tcga_18.tar") and a text file with single base substitution mutational signatures for each sample from COSMIC (https://cancer.sanger.ac.uk/cosmic, “signatureProfileSample.txt.zip”).</p>
Jagodinsky et al 2024 bulk RNA-seq counts
<p>On day 3 following BT, tumors were collected and tissue samples were taken from the high, moderate, and low dose regions. The samples were homogenized in Trizol reagent (ThermoFisher) using a Bead Ruptor Elite (OMNI). RNA was isolated using Qiagen’s RNeasy Mini Kit according to the manufacturer’s instructions. 1 µg of RNA was used for library preparation (Illumina) with UD indexing (Illumina) according to manufacturer’s instructions. The prepared libraries were sequenced on an Illumina NOVAseq 6000. Skewer was used to trim adapter sequences from reads and to remove low quality bases from read 3’ ends before aligning to GRCm38.p6 using STAR.<br> <br> RSEM was used to calculate expected gene counts from aligned reads. Principal component analysis and Pearson correlation between vectors of gene counts that belong to biological replicates was employed to detect outlier libraries. Any samples with inter-replicate Pearson correlation less than 0.9 or which did not cluster with replicates by PCA were dropped from downstream analyses.</p>
RNA-seq data showing PLS role in gene expression control in Arabidopsis
<p class="MsoNormal">The vital plant ethylene receptor (ETR1) contains an essential Cu(I) ion, and as for other vesicular cupro-proteins, the final step of Cu(I) maturation at the endoplasmic reticulum (ER) is undefined. We previously discovered that mutants in the <em>Arabidopsis</em>gene <em>POLARIS</em> (<em>PLS</em>), encoding a 36 amino acid peptide, exhibit constitutive ethylene signalling responses. Here we report a 1:2 thiol-dependent Cu(I):PLS<sub>2</sub> complex, with an affinity of 3.79 (±1.5) x10<sup>19</sup> M<sup>-2</sup>. We demonstrate interactions with the transmembrane domain of ETR1, the Cu(I) chaperones ATX1 and CCH, and Cu(I)-transporting P<sub>1B</sub>-type ATPase RAN1 at the ER. Formation of Cu(I)-dependent PLS-cuproprotein adducts at the ER provides a mechanism to modulate the metalation of ETR1, thereby regulating its activity and representing a distinct mechanism for plant hormone receptor regulation.</p>
Data for: RNA-Seq dataset of RBL-2H3 (RPKM)
<p><span>The coordination between actin and microtubule network is crucial, yet our understanding of the underlying mechanisms remains limited. In this study, </span><span>we used travelling waves in the cell cortex to characterize the collective dynamics of cytoskeletal networks. Our findings show that Cdc42 and </span><span>F-BAR</span><span>-dependent actin waves in mast cells are mainly driven by formin-mediated actin polymerization, with the microtubule-binding formin FH2 domain-containing protein 1 (FHDC1) as an early regulator. </span><span>FHDC1, as well as its interaction with microtubule is required for actin waves. In addition, </span><span>the phase of microtubule depolymerization coincides with the nucleation of actin waves and microtubule stabilization inhibit actin waves, leading us to propose that microtubule shrinking and </span><span>the concurrent release of FHDC1 locally regulate actin nucleation. Lastly, we show that FHDC1 is crucial for multiple cellular processes such as cell division and migration. </span><span>Our data provided molecular insights into the nucleation mechanisms of actin waves and uncover an antagonistic interplay between microtubule and actin polymerization in their collective dynamics.</span></p>
Supporting data for "Software pipelines for RNA-Seq, ChIP-Seq and Germline Variant calling analyses in Common Workflow Language (CWL)"
<p>Datasets produced during the validation of CWL-based pipelines, designed for the analysis of data from RNA-Seq, ChIP-Seq and germline variant calling experiments. Specifically, the workflows were tested using publicly available High-throughput (HTS) data from published studies on Chronic Lymphocytic Leukemia (CLL) (accession numbers: E-MTAB-6962, GSE115772) and Genome in a Bottle (GIAB) project samples (accession numbers: SRR6794144, SRR22476789, SRR22476790, SRR22476791).</p> <p>The supporting data include:</p> <ul> <li>Differential transcript and gene expression results produced during the analysis with the CWL-based RNA-Seq pipeline</li> <li>Bigwig and narrowPeak files, differential binding results, table of consensus peaks and read counts of EZH2 and H3K27me3, produced during the analysis with the CWL-based ChIP-Seq pipeline</li> <li>VCF files containing the detected and filtered variants, along with the respective hap.py () results regarding comparisons against the GIAB golden standard truth sets for both CWL-based germline variant calling pipelines</li> </ul>
Data from: Single cell RNA-seq data of E18 fetal thymocytes from HEB Vav-iCre and Id3-KO mice and their wild type littermate counterparts
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RNA-seq of green hydra strains' ( Hydra viridissima) response to the removal or exchange of symbionts
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RNA-seq and label-free quantitative proteomics data from: KDM4A serves as an α-tubulin demethylase regulating microtubule polymerization and cell mitosis
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RNA-seq data for LS180 and NCI-H358 Cancer cell lines
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Integrative genomics of the mammalian alveolar macrophage response to intracellular mycobacteria: RNA-seq statistics and results
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Data for: RNA-Seq dataset of RBL-2H3 (RPKM)
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A novel method for using RNA-seq data to identify imprinted genes in social Hymenoptera with multiply mated queens
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RNA-seq data for embryonic chicken wings series treated with sonidegib
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RNA-seq and RT-qPCR data showing MDF role in RNA splicing and gene expression control in Arabidopsis
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RNA-seq and CUT&Tag-seq datasets for MDA-MB-231 and MCF-10A cells from: Sp1 mechanotransduction regulates breast cancer cell invasion in engineered viscoelastic extracellular matrices
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RNA-seq data for an embryonic chicken digit tissue time-series, treated in vivo with smoothened agonist to induce ectopic feathers
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.