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3,818 results for “Differential Expression”
Fig 2 in Colossoma macropomum (Characiformes: Serrasalmidae) adapted to new climate regime: differential gene expression from farmed tambaqui juveniles raised in subtropical and tropical regions
Fig 2: Heatmap of relative expression in Balbina (BA) and Brumado (BRU) populations. The colour scale ranges from blue (low transcript levels) to red (high transcript levels).
Figure 4 in Differential gene expression pattern and plasma sex steroids during testicular development in Genyatremus luteus (Perciforme: Haemulidae) (Bloch, 1790)
Figure 4. Principal component analysis (PCA) used to classify the influence of lhr and er gene expression, plasma steroids (11-KT, 17- OHP and E2), ichthyological parameters and GSI on male G. luteus individuals. Legend: LHR = LH receptor; ER = estrogen receptor; KT = 11-ketotestosterone; E2 = 17β-estradiol; OHP = 17-α-hydroxyprogesterone; TW = total weight; TL = total length; GW = gonad weight; GSI = gonadosomatic index.
Figure 1 in Differential gene expression pattern and plasma sex steroids during testicular development in Genyatremus luteus (Perciforme: Haemulidae) (Bloch, 1790)
Figure 1. Photomicrographs of germ cell and testes development stages of Genyatremus luteus. Stages were determined as (A) Immature, (B) Maturing, (C) Mature. Abbreviations are as follows: SPG, spermatogonia; SPC, spermatocyte; SPZ, spermatozoa. All panels were at 60x magnification.
Figure 2 in Differential gene expression pattern and plasma sex steroids during testicular development in Genyatremus luteus (Perciforme: Haemulidae) (Bloch, 1790)
Figure 2. Steroid concentrations in the blood plasma of male Genyatremus luteus individuals during their reproductive cycle. (A) 11-ketotestosterone. (B) 17 α-hidroxy progesterone. (C) 17β-estradiol. Data are represented as mean ± SEM. abc: indicates statistically significant difference (p<0.05).
Pelagomonas calceolata gene expression levels in different nitrogen conditions and differential expression analysis.
<p>These files contains the expression levels and DESeq2 results of <em>Pelagomonas calceolata</em> genes cultivated with different nitrate conditions. Two strains of <em>P. calceolata </em>(RCC100 and RCC697) were cultivated and their RNAs reads were aligned on the predicted genes of <em>P. calceolata</em> RCC100 genome: <a href="https://www.ncbi.nlm.nih.gov/Traces/wgs/CAKKNE01?display=download" rel="nofollow">https://www.ncbi.nlm.nih.gov/Traces/wgs/CAKKNE01?display=download</a></p> <p>The following culture conditions were analysed :</p> <p>882 µM of Nitrate (RCC100 and RCC697) </p> <p>441 µM of Nitrate (RCC100)</p> <p>220 µM of Nitrate (RCC100 and RCC697)</p> <p>50 µM of Nitrate (RCC697)</p> <p>882 µM Cyanate (RCC100)</p> <p>882 µM Ammonia (RCC100)</p> <p>441 µM Urea (RCC100)</p> <p><a href="../api/records/12582059/draft/files/20230427_RCC100-Nitrate_transcriptomes_rawcounts.tsv/content" target="_blank" rel="noopener noreferrer">20230427_RCC100-Nitrate_transcriptomes_rawcounts.tsv</a> : the file contains the raw read counts of RCC100 in 6 culture conditions in triplicate + the gene names = 19 columns.</p> <p><a href="../api/records/12582059/draft/files/20230427_RCC100-Nitrate_transcriptomes_TPM.tsv/content" target="_blank" rel="noopener noreferrer">20230427_RCC100-Nitrate_transcriptomes_TPM.tsv</a> : same data normalized in transcript per kb per million mapped reads (TPM).</p> <p><a href="../api/records/12582059/draft/files/20230427_RCC100-Nitrate_transcriptomes_rawcounts.tsv/content" target="_blank" rel="noopener noreferrer">20230427_RCC697-Nitrate_transcriptomes_rawcounts.tsv</a> : the file contains the raw read counts of RCC697 of 3 culture conditions in triplicate + the gene names = 10 columns.</p> <p><a href="../api/records/12582059/draft/files/20230427_RCC100-Nitrate_transcriptomes_TPM.tsv/content" target="_blank" rel="noopener noreferrer">20230427_RCC697-Nitrate_transcriptomes_TPM.tsv</a> : same data normalized in transcript per kb per million mapped reads (TPM).</p> <p><span>Differential expression analysis (DESeq2) was performed by pairwise comparisons between the standard condition (882 µM nitrate) and low-nitrate conditions (50, 220 or 441 µM nitrate) or changing nitrogen sources (882 µM ammonium, 882 µM cyanate and 441 µM urea). Each DESeq-results_RCCxxx_xxx.tsv file contains 6 columns : <em>P.calceolata </em>gene name, base Mean, log2 Fold Change, standard error value (lfcSE), pvalue and adjusted pvalue (padj).<br></span></p>
Human-specific tandem repeat expansion and differential gene expression during primate evolution
<p>THIS DATASET IS PART OF THE FOLLOWING STUDY:<br> <a href="https://www.pnas.org/content/early/2019/10/22/1912175116">https://www.pnas.org/content/early/2019/10/22/1912175116</a></p> <p> </p> <p>THE RAW SEQUENCING 10x GENOMICS READS CAN BE DOWNLOADED FROM SRA:<br> <a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA593056">https://www.ncbi.nlm.nih.gov/bioproject/PRJNA593056</a></p> <p><br> ORIGINAL UPLOAD: 09/06/2019</p> <p>UPDATES: 10/28/2019; 01/27/2020</p> <p>DESCRIPTION: Contigs were assembled using Phased-SV (<a href="https://www.nature.com/articles/s41467-018-08148-z">Chaisson et al, Nature Communications 2019</a>) on six human haplotypes (i.e., H0 and H1 in NA19240, HG00514, and HG00733), and six nonhuman haplotypes (this study, H0 and H1 in Clint the chimpanzee, Kamilah the gorilla, and Susie the orangutan). The long read data (PacBio CLR) from NHPs were phased into haplotypes H0 and H1 using linked reads from 10X Genomics prior to assembly, whenever possible. If not possible (e.g., in the case of long runs of homozygosity regions), long reads from both haplotypes were used to generate a "squished assembly". Using human haplotype data, we identified 21,442 polymorphic STRs/VNTRs, followed by a targetted phasing of these regions in the three NHPs. All of the human and nonhuman primate contigs were padded by 2 kbp both upstream and downstream, followed by mapping against the human reference (GRCh38). We did the same for "squished assemblies" from a Yoruban individual, CHM13, and three NHPs as described in <a href="https://science.sciencemag.org/content/360/6393/eaar6343">Kronenberg et al, Science 2018</a>. The BAM and BAI files in this dataset contain the alignment of all these contigs against GRCh38.</p>
Figure 2 in Identification and expression of Dmrt1 and Sox9 during the gonadal differentiation of Rana chensinensis
Figure 2. Nucleotides and deduced amino acids of rcDmrt1. The DM domain is boxed in shaded rectangles, while the male-specific motifs and P/S-rich element are underlined with a solid and dotted line, respectively. Cysteines and histidines that coordinate Zn2+ are aligned as two intertwined binding sites: site I (circles) and site II (boxes). The stop codon is marked by an asterisk.
Figure 1 in Identification and expression of Dmrt1 and Sox9 during the gonadal differentiation of Rana chensinensis
Figure 1. Images of undifferentiated gonads and differentiated testes and ovaries of R. Chensinensis tadpoles. A, Stage 28; B, stage 46, testis; C, stage 46, ovary. Wd, Wolffian duct; Gmc, gonad-mesonephros complex; Pe, perisome; Ki, kidney; Te, testis; Ov, ovary.
Figure 6. rcDmrt1 and rcSox9 in Identification and expression of Dmrt1 and Sox9 during the gonadal differentiation of Rana chensinensis
Figure 6. rcDmrt1 and rcSox9 expression in various tissues of adult R. chensinensis. Upper two panels, RT-PCR using rcDmrt1 and rcSox9 gene-specific primers, respectively; lower panel, control RT-PCR using rpl8 gene-specific primers.
Figure 4 in Identification and expression of Dmrt1 and Sox9 during the gonadal differentiation of Rana chensinensis
Figure 4. The neighbor-joining phylogenetic trees of Dmrt1 and Sox9. Phylogenetic tree was constructed on the basis of alignment of the amino acid sequences of Dmrt1 and Sox9 homologs, showing the evolutionary relationship of rcDmrt1 (A) and rcSox9 (B) with other species of the Dmrt1 and Sox9 family. Numbers at branch nodes are percentages of bootstrap confidence values derived from 2000 replications. GenBank Accession Nos. of various species are shown in Table 2.
Figure 3 in Identification and expression of Dmrt1 and Sox9 during the gonadal differentiation of Rana chensinensis
Figure 3. Nucleotides and deduced amino acids of rcSox9. The HMG-box domain is boxed in shaded rectangles, while the Sox-N domain and PQA-rich element are underlined with a solid and dotted line, respectively. The stop codon is marked by an asterisk.
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.
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>
Limma-voom differential expression results for GTEx CVD and MD analyses
<p>Supplementary File 5 for the paper entitled "Exploring the Impact of Cerebrovascular Disease and Major Depression on Non-diseased Human Tissue Transcriptomes" (doi: 10.3389/fgene.2021.696836).</p>
Extended data tables to Haering and Habermann, F1000Res, RNfuzzyApp: an R shiny RNA-seq data analysis app for visualisation, differential expression analysis, time-series clustering and enrichment analysis
<p><b>Background</b> </p> <p>RNA-seq is a widely adopted affordable method for large scale gene expression profiling. However, user-friendly and versatile tools for wet-lab biologists to analyse RNA-seq data beyond standard analyses such as differential expression, are rare. Especially, the analysis of time-series data is difficult for wet-lab biologists lacking advanced computational training. Furthermore, most meta-analysis tools are tailored for model organisms and not easily adaptable to other species.</p> <p><b>Results</b></p> <p>With RNfuzzyApp, we provide a user-friendly, web-based R-shiny app for differential expression analysis, as well as time-series analysis of RNA-seq data. RNfuzzyApp offers several methods for normalization and differential expression analysis of RNA-seq data, providing easy-to-use toolboxes, interactive plots and downloadable results. For time-series analysis, RNfuzzyApp presents the first web-based, automated pipeline for soft clustering with the Mfuzz R package, including methods to aid in cluster number selection, Mfuzz loop computations, cluster overlap analysis, as well as cluster enrichments.</p> <p><b>Conclusion</b></p> <p>RNfuzzyApp is an intuitive, easy to use and interactive R shiny app for RNA-seq differential expression and time-series analysis, offering a rich selection of interactive plots, providing a quick overview of raw data and generating rapid analysis results. Furthermore, its orthology assignment, enrichment analysis, as well as ID conversion functions are accessible to non-model organisms.</p>
RNA-seq data of "Transcriptome analyses of leaves reveal that hexanoic acid priming differentially regulate gene expression in contrasting Coffea arabica cultivars"
<p>This dataset represent FASTQ gziped files from the study "Transcriptome analyses of leaves reveal that hexanoic acid priming differentially regulate gene expression in contrasting <em>Coffea arabica</em> cultivars" (<a href="https://doi.org/10.3389/fsufs.2021.735893">https://doi.org/10.3389/fsufs.2021.735893</a>). Sequencing was done using an Illumina Novaseq 6000 instrument, paired-sequencing (2 X150 bp). Sample details are also available at https://www.ebi.ac.uk/ena/browser/view/ERA6282544.</p> <p> </p> <p>All filenames have the following naming scheme:</p> <p>LCS7609_DS_AAA_leafBBB_(R1 or R2).fq.gz</p> <p>AAA stands for the abbreviations:</p> <p>- CC (Coffea arabica cv Catuai control)</p> <p>- CHx (Coffea arabica cv Catuai exposed to Hexanoic acid)</p> <p>- OC (Coffea arabica cv Obatã control)</p> <p>- OHx (Coffea arabica cv Obatã exposed to Hexanoic acid)</p> <p>BBB stands for the number of biological replicate (1, 2 or 3).</p> <p> </p> <p> </p> <p> </p>
RNAseq data: Analysis of circRNA expression in human neuronal differentiation
<p>This dataset contains sequencing read count data related to samples from differentiating human neuroepithelial stem cells (NES) collected at days zero (NES), five (D5) and 28 (D28) of differentiation. Details on how samples were collected and how data was generated and processed are described below.</p> <p> </p> <p><em>Sample preparation</em></p> <p>NES were seeded on tissue culture flasks coated with 20 μg/ml poly-L-ornithine (Sigma-Aldrich P3655), and 1 μg/ml laminin (Sigma-Aldrich L2020). Cells were grown in DMEM/F12+GlutaMAX medium (ThermoFisher 31331093) supplemented with 0.05X B27 (ThermoFisher 17504044), 1X N2 (ThermoFisher 17502001), 10 ng/ml bFGF (fisher scientific CTP0261), 10 ng/ml EGF (PeproTech AF-100-15) and 10 U/ml penicillin/streptomycin (ThermoFisher 15140122). Medium was exchanged 50% daily and cells maintained in 5% CO2 at 37ºC, passaging once 100% confluent and seeding at a density of 5x104 cells/cm2. Neural differentiation was induced by growth factor withdrawal the day after plating with media B27 concentration increased to 0.5X. Media was exchanged 50% every second day up until D15, after which media was supplemented with 0.4 ug/ml laminin and exchanged 50% every three days. </p> <p> </p> <p><em>RNA extraction and sequencing</em></p> <p>Cells were lysed in TRIzol reagent (ThermoFischer 15596026) before separating with chloroform and mixing the aqueous phase with isopropanol as per manufacturer directions. RNA was then isolated from the isopropanol/chloroform solution using the ReliaPrep RNA Cell Miniprep kit (Promega Z6010). Libraries were prepared with Illumina Truseq Stranded total RNA RiboZero GOLD kit and sequenced on the NovaSeq6000 platform with a 2x151 setup using NovaSeqXp workflow in S4 mode flowcell.</p> <p> </p> <p><em>Data generation</em></p> <p>Raw reads were processed using cutadapt v3.2 to trim adaptor sequences and low-quality base pairs and discard short reads (options: -m 20 -e 0.1 -q 20 -O 1). The GRCh37 genome assembly was used for all alignment, annotation, and downstream analysis steps. Trimmed read weres alignment to the GRCh37 genome assembly using TopHat v2.0.9 tophat_fusion (with Bowtie v1.1.2 and Samtools v0.1.19) with –fusion-min-dist 200. BAM files have been anonymised by removal of potentially identifiable genetic variant information using BAMboozle v0.5.0 (Ziegenhain & Sandberg, 2021) with default settings. This BAM files and corresponding index (.bai) files are provided here with naming convention "<em>label.</em>bam" Information on sample labels and corresponding conditions is provided in the file 'metadata.txt'.</p> <p><br> </p>
Results of the differential gene expression analysis in SIV infection in Chlorocebus sabaeus and Macaca mulatta
<p>Results of differential gene expression analysis in SIV infection in Chlorocebus sabaeus and Macaca mulatta.</p> <p>From the transcriptome data repository MACE (http://mace.ihes.fr)</p>
Differentially-expressed genes in blood in response to lipopolysaccharide in three rodent species
<p>Infection tolerance in rodents was examined by injecting single-dose lipopolysaccharide (LPS) to induce inflammation in <span><em>Peromyscus</em> <em>leucopus</em></span><span> (LL stock), the white-footed deermouse also reservoir for Lyme disease and </span><span><em>Mus</em> <em>musculus</em></span><span> (outbred CD-1 breed), the house mouse, and </span><span><em>Rattus</em> <em>norvegicus</em></span><span>, the brown rat (Fischer strain). Reaction to LPS was analyzed in the blood of challenged rodents and compared to control animals. As natural reservoirs of zoonoses deermice show significant anti-inflammatory response as described in "An Infection-Tolerant Mammalian Reservoir for Several Zoonotic Agents Broadly Counters the Inflammatory Effects of Endotoxin" (</span><a href="https://doi.org/10.1128/mBio.00588-21)" rel="noopener"><span>https://doi.org/10.1128/mBio.00588-21)</span></a><span>. The project and the description of the samples are described under the following NCBI BioProjects: PRJNA975149 (</span><a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA975149" rel="noopener"><span>https://www.ncbi.nlm.nih.gov/bioproject/PRJNA975149)</span></a><span> for mouse and deermouse and PRJNA973677 (</span><a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA973677)" rel="noopener"><span>https://www.ncbi.nlm.nih.gov/bioproject/PRJNA973677)</span></a><span>. This project is a follow-up project focusing on the transcriptomic analysis of the whole blood bulk RNA-seq and further analysis of differentially expressed genes (DEG) between the treatment arm and controls. Complete fold change and false discovery rate for all three rodent species used for the current Dryad set are previously published (<a href="https://doi.org/10.7280/D1470Z">https://doi.org/10.7280/D1470Z</a>). Here we report that deermice tolerance to infection is partly due to lower expression of interferon-gamma in comparison to mice and rats. <br></span></p>
The raw microarray data and the differential expression analysis results from "Manipulating the growth environment through co-culture to enhance stress tolerance and viability of probiotic strains in the gastrointestinal tract".
<p>The signal data for each spot were subsequently quantified by using Feature Extraction software (Agilent Technologies).M1.txt to M5.txt: monoculture; C1.txt to C5.txt: co-culture; P1.txt to P5.txt: pH-controlled monoculture. The differential expression analysis results were obtained by using limma.</p>
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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.