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433 results for “differential gene expression analysis”
Data from "Corset: enabling differential gene expression analysis for de novo assembled transcriptomes"
<p>This dataset contains de novo transcriptome assemblies for three publicly available RNA-seq dataset (SRA055442, SRR453566-SRR453571 and GSE37704 ). For each assembly we also provide a table with the read counts per contig, the output from corset (clusters and counts), and the results from a genome-based analysis. This dataset was used to assess the performance of the corset software. More detail is provided in the paper: Nadia M Davidson and Alicia Oshlack,<strong> </strong>Corset: enabling differential gene expression analysis for de novo assembled transcriptomes, <em>Genome Biology</em> 2014, <strong>15</strong>:410. http://genomebiology.com/2014/15/7/410/abstract</p>
Integrating differential expression and weighted correlation network analysis for identifying genes controlling shoot development in Sorghum bicolor
<p>Supplementery materials of journal article "Integrating differential expression and weighted correlation network analysis for identifying genes controlling shoot development in <em>Sorghum bicolor</em>"</p>
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>
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>
Single cell multiomic analysis identifies key genes differentially expressed in innate lymphoid cells from COVID-19 patients
<p>Innate lymphoid cells (ILCs) are enriched at mucosal surfaces where they respond rapidly to environmental stimuli and contribute to both tissue inflammation and healing. To gain insight into the role of ILCs in the pathology and recovery from COVID-19 infection, we employed a multi-omic approach consisting of Abseq and targeted mRNA sequencing to respectively probe the surface marker expression, transcriptional profile and heterogeneity of ILCs in peripheral blood of patients with COVID-19 compared with healthy controls. We found that the frequency of ILC1 and ILC2 cells was significantly increased in COVID-19 patients. Moreover, all ILC subsets displayed a significantly higher frequency of CD69-expressing cells, indicating a heightened state of activation. ILC2s from COVID-19 patients had the highest number of significantly differentially expressed (DE) genes. The most notable genes DE in COVID-19 vs healthy participants included a) genes associated with responses to virus infections and b) genes that support ILC self-proliferation, activation and homeostasis. In addition, differential gene regulatory network analysis revealed ILC-specific regulons and their interactions driving the differential gene expression in each ILC. Overall, this study provides mechanistic insights into the characteristics of ILC subsets activated during COVID-19 infection.</p>
Table with results of differential gene expression analysis in the controlled environment for fin tissues.
<p>Differences between transcriptomes of three Cottus fish lineages were assessed under controlled, laboratory conditions. Two tissues were investigated: fins and livers. Present table shows results of the differential gene expression analysis performed on fin tissues of Cottus fish. Base-mean, Log-2-fold change. standard error, statistics and associated p-values and FDR-corrected p-values are given for every contrast possible in our experimental design.</p>
Table with results of differential gene expression analysis in the controlled environment for liver tissues.
<p>Differences between transcriptomes of three Cottus fish lineages were assessed under controlled, laboratory conditions. Two tissues were investigated: fins and livers. Present table shows results of the differential gene expression analysis performed on liver tissues of Cottus fish. Base-mean, Log-2-fold change. standard error, statistics and associated p-values and FDR-corrected p-values are given for every contrast possible in our experimental design.</p>
RNA-Seq analysis to identify differentially expressed genes in top and bottom leaves under Alternaria brassicicola infection
<p>The broccoli plants were infected with Alternaria brassicicola and RNA samples were extracted for control and inoculated plants at 10 days post inoculation. </p>
curatedPCaData supplementary data table for differential gene expression analysis
<p>This tab-separated plaintext file contains differential gene expression analyses reported for the curatedPCaData data resource publication.</p>
Single cell multiomic analysis identifies key genes differentially expressed in innate lymphoid cells from COVID-19 patients
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Data from: Differential gene expression analysis of symbiotic and aposymbiotic Exaiptasia anemones under immune challenge with Vibrio coralliilyticus
Anthozoans are a class of Cnidarians that includes scleractinian corals, anemones and their relatives. Despite a global rise in disease epizootics impacting scleractinian corals, little is known about the immune response of this key group of invertebrates. To better characterize the anthozoan immune response, we used the model anemone Exaiptasia pallida to explore the genetic links between the anthozoan-algal symbioses and immunity in a two-factor RNA-Seq experiment using both symbiotic and aposymbiotic(menthol-bleached) Exaiptasia pallida exposed to the bacterial pathogen Vibrio coralliilyticus. Multivariate and univariate analyses of Exaiptasia gene expression demonstrated that exposure to live Vibrio coralliilyticus had strong and significant impacts on transcriptome-wide gene expression for both symbiotic and aposymbiotic anemones, but we did not observe strong interactions between symbiotic state and Vibrio exposure. There were 4,164 significantly differentially expressed (DE) genes for Vibrio exposure, 1,114 DE genes for aposymbiosis, and 472 DE genes for the additive combinations of Vibrio and aposymbiosis. KEGG enrichment analyses identified 11 pathways - involved in immunity (5), transport and catabolism (4) and cell growth and death (2) - that were enriched due to both Vibrio and/or aposymbiosis. Immune pathways showing strongest differential expression included complement, coagulation, nucleotide-binding and oligomerization domain (NOD), and Toll for Vibrio exposure and coagulation and apoptosis for aposymbiosis.
Comparative analysis of differential gene expression indicates divergence in ontogenetic strategies of leaves in two conifer genera
<p><em>Juniperus flaccida</em> (drooping juniper) and <em>Pinus cembroides</em> (pinyon pine) are conifers native to North America, spanning Mexico and the Southwestern region of the United States. Although from two different lineages, both species exhibit heteroblastic growth. Morphologically, their leaves undergo a change between the juvenile and adult life stage. <em>J. flaccida</em> leaves appear needle-like at youth and scale-like at maturity, whereas the <em>P. cembroides</em> will transition from needle-like leaves to brown scale-like leaves. The objective was to perform a comparative transcriptomic analysis to quantify and examine differential expression in juvenile and adult individuals from both species. RNA from twelve samples was sequenced on HiSeq 1500 (100bp PE) and analyzed with available software. Because there are no reference genomes for these species, they were assembled<em> de novo </em>from the RNA-Seq reads. Following assembly, the coding regions were identified and redundant transcripts were removed. Quality filtered reads were aligned to the reference transcriptomes (one for each species), counts were generated from the alignment files, and differential expression analysis was performed with DESeq2 via Kallisto. Up and down-regulated genes (padj<0.1) across both age classes (juvenile vs adult) were observed in each species and compared.</p>
Time-series transcriptome analysis identified differentially expressed genes in broiler chicken infected with mixed Eimeria species
<p>Coccidiosis caused by the <em>Eimeria</em> species is a highly problematic disease in the chicken industry. Here, we used RNA sequencing to observe the time-dependent host responses of <em>Eimeria</em>-infected chickens to examine the genes and biological functions associated with immunity to the parasite. Transcriptome analysis was performed at three time points: 4, 7, and 21 days post-infection (dpi). Based on the changes in gene expression patterns, we defined three groups of genes that showed differential expression. This enabled us to capture evidence of endoplasmic reticulum stress at the initial stage of <em>Eimeria</em> infection. Furthermore, we found that innate immune responses against the parasite were activated at the first exposure; they then showed gradual normalization. Although the cytokine-cytokine receptor interaction pathway was significantly operative at 4 dpi, its downregulation led to an anti-inflammatory effect. Additionally, the construction of gene co-expression networks enabled identification of immunoregulation hub genes and critical pattern recognition receptors after <em>Eimeria</em> infection. Our results provide a detailed understanding of the host-pathogen interaction between chicken and <em>Eimeria</em>. The clusters of genes defined in this study can be utilized to improve chickens for coccidiosis control.</p>
Fig. 5 in Transcriptome profiling of Symbion pandora (phylum Cycliophora): insights from a differential gene expression analysis
Fig. 5 Differential transcript expression analysis. Bar charts represent the enriched molecular functions associated with the upregulated genes in a feeding stages with Prometheus larva(e) and b feeding stages alone
Fig. 4 in Transcriptome profiling of Symbion pandora (phylum Cycliophora): insights from a differential gene expression analysis
Fig. 4 Differential transcript expression analysis. Bar charts represent the enriched biological processes associated with the upregulated genes in a feeding stages with Prometheus larva(e) and b feeding stages alone
Fig. 2 in Transcriptome profiling of Symbion pandora (phylum Cycliophora): insights from a differential gene expression analysis
Fig. 2 Scheme of the methodology employed in this study. In a first approach, the reference transcriptome (workflow in grey) was assembled de novo from three distinct life cycle stages: the feeding stage alone (asexual generation; note that in young feeding stages, the buccal funnel is located inside in the trunk), the feeding stage with Prometheus larva(e) attached to its trunk (sexual generation) and the free-swimming chordoid larva. Secondly, in the differential gene expression analysis (workflow in black), only two different conditions were investigated: feeding stages with Prometheus larva(e) attached to its trunk and feeding stages alone. Finally, sequenced reads were mapped to the reference transcriptome
Fig. 6 in Transcriptome profiling of Symbion pandora (phylum Cycliophora): insights from a differential gene expression analysis
Fig. 6 Differential transcript expression analysis. Bar charts represent the enriched cellular components associated with the upregulated genes in a feeding stages with Prometheus larva(e) and b feeding stages alone
Data from: De novo assembly of a tadpole shrimp (Triops newberryi) transcriptome and preliminary differential gene expression analysis
Next-generation sequencing techniques, such as RNA sequencing, have provided a wealth of genomic information for nonmodel species. Transcriptomic information can be used to quantify the patterns of gene expression, which can identify how environmental differences invoke organismal stress responses and provide a gauge in predicting species adaptability. In our study, we used RNA sequencing to characterize the first transcriptome from a naupliar tadpole shrimp (Triops newberryi) to identify the genes expressed during the early life history stages and which could be important for future genomic studies. RNA was extracted from naupliar T. newberryi that were reared in a laboratory-controlled setting and in two different water types, a native and a non-native condition. A total of six replicates, three per condition, were sequenced with the Illumina Hi-Seq 2000 achieving 365 M 50-nt reads. High-quality reads were produced and de novo assembly was used to construct a T. newberryi transcriptome that was approximately 24.8 M base pairs. More than 10 000 peptides were predicted from the assembly, and genes were sorted into gene ontology categories. The use of different water conditions allowed for a preliminary differential gene expression analysis in order to compare the changes in gene expression between conditions. There were 299 differentially expressed genes between water conditions that might serve as a focal point for future genomic studies of Triops acclimation to different environments. The Triops transcriptome could serve as vital genomic information for additional studies on Branchiopod crustaceans.
Dataset from RNAseq analysis of differential gene expression among developmental stages of two non-marine ostracods
<p>Dataset comprising tree files and alignments used for phylogenetic validation of data, assemblies of reference transcriptomes and draft genomes, annotation of draft genomes, as well as supplementary tables.</p>
Data from: Differential gene expression analysis of symbiotic and aposymbiotic Exaiptasia anemones under immune challenge with Vibrio coralliilyticus
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