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25,372 results for “Transcriptomics”
Fig. 5 in Comparative transcriptome analysis of three Bactrocera dorsalis (Diptera: Tephritidae) organs to identify functional genes in the male accessory glands and ejaculatory duct
Fig. 5. Six examples of the tissue expression profiling of predicted distinct unigenes (>500 bp) expressed highly in male accessory glands and ejaculatory duct tissue of Bactrocera dorsalis. Relative expression levels were determined by qRT-PCR in head (HE), thorax (TH), abdomen (AB), midgut (MG), fat body (FB), Malpighian tubules (MT), testes (TE), and male accessory glands and ejaculatory duct (MAG) samples from B. dorsalis males. Relative expression levels were calculated based on the value in head, which was ascribed an arbitrary value of 1. Different letters above the bars indicate significant differences based on Tukey's test (P ≤ 0.05).
Fig. 3 in Comparative transcriptome analysis of three Bactrocera dorsalis (Diptera: Tephritidae) organs to identify functional genes in the male accessory glands and ejaculatory duct
Fig. 3. Gene ontology (GO) classification of unigenes expressed highly in male accessory glands and ejaculatory duct tissue of Bactrocera dorsalis.
Supplemental Results for Assembly, Annotation, and Analysis from HiFi reads of Gulf Toadfish Genome and Transcriptome fOpsBet2.1
<p>This repository contains gzipped tarballs of the results of the various assembly, annotation, and analysis steps performed during the assembly of the fOpsBet2.1 genome assembly for Opsanus beta at the University of Miami Rosenstiel School of Marine, Atmospheric, and Earth Science for the McDonald Toadfish Lab. These results are too numerous to include as supplemental data for a journal publication and so are available here for review. In this repository you will find results for:</p><p>Scripts:</p><p>-all bash and LSF scheduler job scripts used as part of the analysis, both exploratory and final. </p><p>QC:</p><p>-GenomeScope2 estimation of genome metrics from HiFi Reads</p><p>-QUAST genome statistics for each assembly step</p><p>-BUSCO completeness assessments for each assembly step </p><p>-inspector logs for polishing of initial assembly</p><p>-logs from Kraken2 contaminant screen</p><p>Assembly and Scaffolding:</p><p>-ntLINKS logs and intermediates for initial scaffolding</p><p>-ragtag logs and metrics for super-scaffolding to the ThaAma1.1 T. amazonica reference assembly</p><p>-mitoHIFI results for mitogenome assembly from HiFi reads, primary assembly, and purged alternate assembly</p><p>Annotation:</p><p>-PASA directory with full input and output for SQLite PASA assembly of transcriptome for gene predictors</p><p>-Results folder for Funannotate::annotate for gene models, annotations, and CDS/mRNA/protein fastas</p><p>-InterProSCan5 results for protein annotation used as input into Funannotate</p><p>-ghostKOALA KEGG assignment results for predicted proteins from funannotate results</p><p>Repetitive Elements:</p><p>-tidk telomere repeat analysis results</p><p>-TRAH satellite DNA analysis with subsequent analysis with HiCAT and StainedGlass</p><p>-RepeatModeler results for de novo TE prediction</p><p>-repclassifier results for TE curation</p><p>Comparative Analysis:</p><p>-OrthoFinder ortholog search for O. beta to several other vertebrates</p><p>-CAFE5 gene family expansion and contraction of Orthogroups from OrthoFinder results</p><p> </p>
Updated spiny mouse transcriptome assembly (now includes embryo-specific transcripts)
<p><strong>Summary</strong></p> <p>Updated spiny mouse transcriptome. Embryo-specific contigs generated from BioProject PRJNA436818 were added to the Trinity_v2.3.2 spiny mouse <em>de novo </em>transcriptome assembly (https://doi.org/10.5281/zenodo.808870).</p> <p> </p> <p><strong>Methods</strong></p> <p>Embryos were collected from female spiny mice (n=12) in accordance with the Australian Code of Practice for the Care and Use of Animals for Scientific Purposes with approval from the Monash Medical Centre Animal Ethics Committee. Female dams were staged from delivery of their previous litter (spiny mice conceive their next litter approximately 12h postpartum) and culled at specific time-points for embryo retrieval at the required stage: 2-cell at 48h postpartum (n=4), 4-cell at 52h postpartum ('early' 4-cell; n=2) or at 68h postpartum ('late 4-cell'; n=2), and 8-cell at 72h postpartum (n=4). Embryos were snap frozen in cell lysis solution per the Nugen SoLo protocol (version M01406v3; available from NuGEN). After ligation of cDNA, qPCR was performed on all samples to determine the number of amplification cycles required to ensure that amplification was in the linear range. Based on these results, each sample was amplified using 24 cycles. Final libraries were quantitated by Qubit and size profile determined by the Agilent Bioanalyzer. All libraries were in the expected size range (~320-360 bp). Custom 'AnyDeplete' rRNA depletion probes were designed and produced by NuGEN Technologies, Inc (San Carlos, CA, USA) using rRNA sequences from our reference transcriptome (Mamrot et al., 2017; https://doi.org/10.5281/zenodo.808870). Prior to use, efficacy and off-target effects of the rRNA depletion probes were examined <em>in silico</em> by NuGEN. Samples were loaded using c-Bot (200pM per library pool) and run on 2 lanes of an Illumina HiSeq 3000 8-lane flow-cell. PhiX spike-in was not used directly due to incompatibility with the custom rRNA depletion probes, however it was incorporated into other lanes of the same HiSeq 3000 run. RNA-Seq data (100bp, paired-end reads) are available from the NCBI as Bioproject PRJNA436818.</p> <p>The quality of RNA-Seq reads was assessed using FastQC v0.11.6 (<a href="https://github.com/s-andrews/FastQC">https://github.com/s-andrews/FastQC</a>; 50f0c26), with MultiQC v1.4 (<a href="https://github.com/ewels/MultiQC">https://github.com/ewels/MultiQC</a>; baefc2e) reports available from Github (<a href="https://github.com/jpmam1">https://github.com/jpmam1</a>) (Ewels et al., 2016). Adapter sequences were trimmed from the reads using trim-galore v0.4.2 (<a href="https://github.com/FelixKrueger/TrimGalore">https://github.com/FelixKrueger/TrimGalore</a>; d6b586e), implementing cutadapt v1.12 (<a href="https://github.com/marcelm/cutadapt">https://github.com/marcelm/cutadapt</a>; 98f0e2f). Reads with a quality scores lower than 20 and read pairs in which either forward or reverse reads were trimmed to fewer than 35 nucleotides were discarded. Further trimming of poor quality reads was conducted using Trimmomatic v0.36 (<a href="http://www.usadellab.org/cms/index.php?page=trimmomatic">http://www.usadellab.org/cms/index.php?page=trimmomatic</a>) with settings "LEADING:3 TRAILING:3 SLIDINGWINDOW:4:20 AVGQUAL:25 MINLEN:35" (Bolger et al., 2014). Nucleotides with quality scores lower than 3 were trimmed from the 3’ and 5’ read ends. Reads with an average quality score lower than 25 or with a length of fewer than 35 nucleotides after trimming were removed. Error correction of reads was performed using Rcorrector v1.0.2 (<a href="https://github.com/mourisl/Rcorrector">https://github.com/mourisl/Rcorrector</a>; 144602f) (Song et al., 2015). FastQC was used to assess the improvement in read quality after trimming adapter removal; MultiQC reports are available from Github (<a href="https://github.com/jpmam1">https://github.com/jpmam1</a>).</p> <p>Error corrected reads were assembled using Trinity v2.4.0 (<a href="https://github.com/trinityrnaseq/trinityrnaseq">https://github.com/trinityrnaseq/trinityrnaseq</a>; 1603d80) with settings "--max_memory 400G, --CPU 32 and --full_cleanup" (Haas et al., 2013). Assembly statistics were computed using the TrinityStats.pl from the Trinity package, and summary statistics are provided in Table S1. All reads were aligned to this transcriptome assembly using Bowtie2 v2.2.5 (<a href="https://github.com/BenLangmead/bowtie2">https://github.com/BenLangmead/bowtie2</a>; e718c6f) with settings: "--end-to-end, --score-min L,-0.1,-0.1, --no-mixed, --no-discordant, -k 100, -X 1000, --time, -p 24" (Langmead & Salzberg, 2012).</p> <p>Read-supported contigs were identified within the embryo-specific Trinity <em>de novo </em>transcriptome assembly using samtools "idxstats" v1.5 (contigs with >=1 reads aligning were retained) (<a href="https://github.com/samtools/samtools">https://github.com/samtools/samtools</a>; f510fb1) (Li et al., 2009). The read-supported contigs from the embryo-specific assembly (n=54,660) were added to the reference spiny mouse transcriptome assembly previously described (Mamrot, J., Legaie, R., Ellery, S.J., Wilson, T., Seemann, T., Powell, D.R., Gardner, D.K., Walker, D.W., Temple-Smith, P., Papenfuss, A.T. and Dickinson, H., 2017. De novo transcriptome assembly for the spiny mouse (Acomys cahirinus). Scientific Reports, 7(1), p.8996).</p> <p>The updated transcriptome is comprised of 2,274,638 transcripts in total.</p>
De novo transcriptome of Dryopteris affinis ssp. affinis
<p>Supplementary data for </p> <p><em>Differential gene expression profiling of one- and two-dimensional apogamous gametophytes of the fern Dryopteris affinis ssp. affinis</em></p> <p> </p> <ul> <li>Transcript sequence in FASTA format (166'191 transcripts)</li> </ul>
Data File for Manuscript "Comprehensive Molecular Simulation on Triple Negative Breast Cancer Transcriptomics Features of mir-145 and 3' UTR of ARF6 mRNA"
<p>This is a data file for the manuscript "Comprehensive Molecular Simulation on Triple Negative Breast Cancer Transcriptomics Features of mir-145 and 3’ UTR of ARF6 mRNA". It comprises of molecular docking (AUTODOCK VINA 4) and dynamics data (NAMD and VMD).</p>
De novo transcriptome assembly from the killifish, Fundulus rathbuni (gill epithelium)
<p>De novo transcriptome assembly from the killifish, Fundulus rathbuni. Fish were acclimated to either brackish or fresh water then exposed to an acute brackish water challenge. Transcriptome data from gill epithelium tissue were collected. A reference transcriptome assembly was generated from all individuals then used to analyze transcriptional responses to salinity.</p>
Shared and distinct genetic risk factors for childhood-onset and adult-onset asthma: genome-wide and transcriptome-wide studies
<p>GWAS summary results from the paper</p> <p>The Lancet Respiratory Medicine: http://dx.doi.org/10.1016/S2213-2600(19)30055-4</p> <p>Preprint: https://doi.org/10.1101/427427</p>
IsoSeq transcriptome of C. laxum, D. oligosanthes and H. amplexicaulis
<p>IsoSeq leaf transcriptome dataset of three grass species (Chasmanthium laxum, Dichanthelium oligosanthes and Hymenachne amplexicaulis). Mature leaves were used.</p>
Transcriptome assemblies of Thalassiosira hyalina and Nitzschia frigida
<p>Transcriptome assemblies of Thalassiosira hyalina and Nitzschia frigida originating from a time course experiment, in which these two species were exposed to high light stress and monitored over 120h under low and high pCO2. The corresponding Sequencing data is deposited at the EBI ArrayExpress database under accession number E-MTAB-6999. Contigs were created with Trinity Assembler.</p> <p>The according publication is currently in review (8/6/2019): Higher sensitivity towards light stress and ocean acidification in an Arctic sympagic compared to a pelagic diatom;</p> <p>Author team: Ane C. Kvernvik, Sebastian D. Rokitta, Eva Leu, Lars Harms, Tove M. Gabrielsen, Björn Rost and Clara J. M. Hoppe</p> <p>Do not hesitate to contact the authors if you like more information!</p>
Tentacle transcriptomes of the speckled anemone (Actiniaria: Actiniidae: Oulactis sp.): venom-related components and their domain structure
<p>This data set pertains to the transcriptome and proteomic analysis conducted on the tentacles of the speckled anemone (<em>Oulactis</em> sp. - yet to be formally described) from Australia. The aim of the study was to mine for novel peptide and proteins related to the venom in the tentacles of the speckled anemone. These sequences could then be used in structure, function and evolution studies in the search for sequences with potential therapeutic use.</p> <p>The data set includes the quant.sf for each individual (1, 2 and 3) and the Trinotate annotation reports for each individual and their assembly annotation.</p>
Proteo-transcriptomic characterization of the venom from the endoparasitoid wasp Pimpla turionellae with aspects on its biology and evolution
<p>Within mega-diverse Hymenoptera non-aculeate parasitic wasps represent 75 % of all hymenopteran species. Their ovipositor dual-functionally injects venom and employs eggs into (endoparasitoids) or onto (ectoparasitoids) diverse host species. Few endoparasitoid wasps such as <em>Pimpla turionellae</em> paralyze the host and suppress its immune responses, such as encapsulation and melanization, to guarantee their offspring’s survival. In our proteo-transcriptomic analysis we shed new light on the venom biology of the endoparasitoid <em>Pimpla turionealle</em>.</p> <p>All additional data is made available here, such as the transcriptome assembly file, CDS prediction and all proteome data files including the raw data. All alignments to train HMMsearch and JACKHMMERsearch are stored here as well and the alignments of identified venom proteins (known and novel).</p> <p>The readme file gives further explanation/information.</p>
Fig. 2 in All the better to see you with: a review of odonate color vision with transcriptomic insight into the odonate eye
Fig. 2 Image representing the body and wing coloration of damselflies (a-e). (a) Platycyphya caligata courtesy of J. Abbott. (b) Calopteryx maculata courtesy of J. Abbott. (c) An andromrophic mating wheel of Ischnura ramburii with male on top and andromorph female on the bottom. Courtesy of S. Coleman. (d) Megaloprepus coerulatus courtesy of T. Davenport. (e) An gynomrophic mating wheel of Ischnura ramburii with male on top and gynomorph female on bottom. Courtesy of S. Coleman
Fig. 1 in All the better to see you with: a review of odonate color vision with transcriptomic insight into the odonate eye
Fig. 1 Diagram of the ventral ommatidium of Sympetrum (redrawn from Armett-Kibel and Menertzhagen 1983)
Fig. 2 in Subtle transcriptomic response of Eurasian perch (Perca fluviatilis) associated with Triaenophorus nodulosus plerocercoid infection
Fig. 2. MA and volcano plots comparing infected and uninfected spleen samples (a & b) and liver samples (c & d). In the MA plots (a & c), the log counts and the log fold change are represented on the x- and y-axis, respectively. For each volcano plot (b & d), log fold change is represented on the x-axis and the –log10 p-value on the y-axis, respectively. Positive fold change corresponds to upregulated genes in infected individuals.
Fig. 1. Differentially expressed genes between infected and uninfected P in Subtle transcriptomic response of Eurasian perch (Perca fluviatilis) associated with Triaenophorus nodulosus plerocercoid infection
Fig. 1. Differentially expressed genes between infected and uninfected P. fluviatilis in a) spleen and b) liver tissues. Filled-in and empty boxes on the top of each plot represent infected and uninfected individuals, respectively. N/A indicates unknown protein.
Dataset of single-cell transcriptomic matrix of 10 human glioblastoma tissue
<p>Dataset of single-cell transcriptomic matrix of 10 human glioblastoma tissue. <span>scRNA-seq was performed using the droplet-based 10x Genomics platform</span><span> </span><span>(10x Genomics, Pleasanton, CA, USA)<span>. <span>GBM tissues for single-cell RNA sequencing (<a name="_Hlk147870629"></a>scRNA-seq)</span> were collected from patients admitted to Xiangya Hospital, Central South University.</span></span></p>
Single-cell and spatial transcriptomics delineate molecular traits and immunosuppressive landscape during histological progression of lung adenocarcinoma
<p>Two specimens of lung adenocarcinoma, each corresponding to the lepidic and solid histologic patterns as confirmed through histologic scrutiny, were procured in accordance with standard surgical protocols. These specimens underwent a process of formalin fixation and were subsequently encapsulated within paraffin-embedded tissue blocks. The specimens were then sectioned and subjected to hematoxylin and eosin (H&E) staining to facilitate subsequent imaging at a resolution of 40x (equivalent to 0.25 micron/pixel) via the use of Aperio GT450 scanners. The tissue slides were then conveyed to the Genomics core, where following the decoverslipping of the tissue, the Visium CytAssist device was employed to transfer transcriptomic probes from the original glass slides to capture areas on Visium slides measuring 11mm x 11mm. Comprehensive transcriptomic profiling was achieved post mRNA permeabilization, through poly(A) capture and probe hybridization. The resultant libraries were sequenced utilizing the Illumina Novaseq 6000, using paired-end sequencing with a read length of 150 base pairs.</p>
Práctica de transcriptómica: expresión diferencial de genes aplicado a la producción de alimentos / Practical Transcriptomics: Differential gene expression applied to food production
<p>Data for the eLearning tutorial Practical Transcriptomics: Differential gene expression applied to food production</p> <p>Datos para el tutorial eLearning Práctica de transcriptómica: expresión diferencial de genes aplicado a la producción de alimentos</p>
Transcriptomic changes in OIR vs Normoxia microglia
<table> <tbody> <tr> <td>File Name</td> <td>Condition</td> </tr> <tr> <td>L135597_Track-180078_R2.fastq.gz</td> <td>Normoxia</td> </tr> <tr> <td>L135597_Track-180078_R1.fastq.gz</td> <td>Normoxia</td> </tr> <tr> <td>L135598_Track-180079_R1.fastq.gz</td> <td>Normoxia</td> </tr> <tr> <td>L135598_Track-180079_R2.fastq.gz</td> <td>Normoxia</td> </tr> <tr> <td>L135599_Track-180080_R2.fastq.gz</td> <td>Normoxia</td> </tr> <tr> <td>L135599_Track-180080_R1.fastq.gz</td> <td>Normoxia</td> </tr> <tr> <td>L135600_Track-180081_R2.fastq.gz</td> <td>OIR-model</td> </tr> <tr> <td>L135600_Track-180081_R1.fastq.gz</td> <td>OIR-model</td> </tr> <tr> <td>L135601_Track-180082_R1.fastq.gz</td> <td>OIR-model</td> </tr> <tr> <td>L135601_Track-180082_R2.fastq.gz</td> <td>OIR-model</td> </tr> <tr> <td>L135602_Track-180083_R2.fastq.gz</td> <td>OIR-model</td> </tr> <tr> <td>L135602_Track-180083_R1.fastq.gz</td> <td>OIR-model</td> </tr> </tbody> </table>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.