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2,227 results for “Tissue expression”
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>
Figure 1 in Validation of reference genes for quantitative expression analysis by qPCR in various tissues of date mussel (Lithophaga lithophaga)
Figure 1. Distribution of Cq values of candidate reference genes in date mussel (L. lithophaga).
Figure 2 in Validation of reference genes for quantitative expression analysis by qPCR in various tissues of date mussel (Lithophaga lithophaga)
Figure 2. Average expression stability (M-value) of reference genes evaluated by geNorm.
Assessment of changes in circRNA expression based on transcripts of genes encoding ADAMTS proteins in patients with non-small cell lung carcinoma compared to normal tissue
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Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene co-expression networks
<p>Data and Inferred Networks accompanying the manuscript entitled - “Aggregation of recount3 RNA-seq data improves the inference of consensus and context-specific gene co-expression networks” </p> <p>Authors: Prashanthi Ravichandran, Princy Parsana, Rebecca Keener, Kaspar Hansen, Alexis Battle </p> <p>Affiliations: Johns Hopkins University School of Medicine, Johns Hopkins University Department of Computer Science, Johns Hopkins University Bloomberg School of Public Health</p> <p>Description: </p> <p>This folder includes data produced in the analysis contained in the manuscript and inferred consensus and context-specific networks from graphical lasso and WGCNA with varying numbers of edges. Contents include:</p> <ul> <li> <p>all_metadata.rds: File including meta-data columns of study accession ID, sample ID, assigned tissue category, cancer status and disease status obtained through manual curation for the 95,484 RNA-seq samples used in the study. </p> </li> <li> <p>all_counts.rds: log2 transformed RPKM normalized read counts for 5999 genes and 95,484 RNA-seq samples which was utilized for dimensionality reduction and data exploration </p> </li> <li> <p>precision_matrices.zip: Zipped folder including networks inferred by graphical lasso for different experiments presented in the paper using weighted covariance aggregation following PC correction.</p> </li> <ul> <li> <p>The networks can be found as follows. First, select the folder corresponding to the network of interest - for example, Blood, this will then include two or more folders which indicate the data aggregation utilized, select the folder corresponding appropriate level of data aggregation - either all samples/ GTEx for blood-specific networks, this includes precision matrices inferred across a range of penalization parameters. To view the precision matrix inferred for a particular value of the penalization parameter X, select the file labeled lambda_X.rds</p> </li> <li> <p>For select networks, we have included the computed centrality measures which can be accessed at centrality_X.rds for a particular value of the penalization parameter X. </p> </li> <li> <p>We have also included .rds files that list the hub genes from the consensus networks inferred from non-cancerous samples at “normal_hubs.rds”, and the consensus networks inferred from cancerous samples at “cancer_hubs.rds”</p> </li> <li> <p>The file “context_specific_selected_networks.csv” includes the networks that were selected for downstream biological interpretation based on the scale-free criterion which is also summarized in the Supplementary Tables. </p> </li> </ul> <li> <p>WGCNA.zip: A zipped folder containing gene modules inferred from WGCNA for sequentially aggregated GTEx, SRA, and blood studies. Select the data aggregated, and the number of studies based on folder names. For example, blood networks inferred from 20 studies can be accessed at blood/consensus/net_20. The individual networks correspond to distinct cut heights, and include information on the cut height used, the genes that the network was inferred over merged module labels, and merged module colors. </p> </li> </ul>
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>
Data from: Sorghum bicolor TX08001 nodal root tissue development gene expression profiling
<div class="page"> <div class="section"> <div class="layoutArea"> <div class="column"> <p>Bioenergy sorghum's large nodal root system enables deposition of soil organic carbon deep in soil profiles aiding production of low carbon intensity biofuels from this crop. During bioenergy sorghum's long growing season, plants produce ~175 nodal roots In review bearing lateral roots that take up water and nutrients from >2 m deep in soil profiles, and aerial roots that support a complex phyllosphere. In the current study, nodal root bud development, a slow process spanning ~40 days, was characterized using microscopy and transcriptome analysis. A first ring of 10-15 nodal root buds was initiated in the stem pulvinus of phytomer 7 near sub-epidermal vascular bundles. A second ring of buds formed above the first ring much later in phytomer development. Nascent nodal root buds from phytomer 7 exhibited relatively high expression of pericycle marker genes (PFA) and genes involved in auxin transport (ABCB19, PIN4, LAX2), cytokinin signaling (TSO, MYB3R1), and cell proliferation (CYCB2;4, CDKB2;1, REM1).</p> <p>Following initiation, expression of genes involved in cell proliferation and cytokinin-signaling decreased while expression of genes involved in proliferative arrest, ABA-signaling, dormancy and stress tolerance increased. Further bud development was correlated with increased expression of WOX11 and PLT5 followed by PLT2, PLT4 and genes encoding RGF peptides that regulate PLT-expression and bud development. Expression of the ARF7-regulated LBD29, a gene required for nodal root formation, increased in parallel with increasing bud size to a maximum late in NRB development. Appearance of the nodal root bud cap late in development coincided with expression of SMB and FEZ, whereas genes such as WOX5 and two MYB36 family members were expressed at higher levels in outgrowing aerial roots. Genes involved in gibberellin, brassinosteroid, strigolactone, ethylene, jasmonate, salicyclic acid, and eATP signaling showed complex patterns of expression during nodal root bud formation. Overall, this study provides a detailed description of bioenergy sorghum nodal root bud development and transcriptome information useful for molecular analysis of networks that regulate nodal root development.</p> </div> </div> </div> </div>
Expression of Angiogenic Biomarkers During Healing of Intra-Oral Soft Tissue Engineered Grafts
ClinicalTrials.gov study NCT01134081. IPD Sharing: NO. Countries: 1. Publications: 1.
Expression-based machine learning models for predicting plant tissue identity
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Data from: Impact of Z chromosome inversions on gene expression in testes and liver tissues in the zebra finch
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Data from: Ocean acidification induces subtle shifts in gene expression and DNA methylation in mantle tissue of the Eastern oyster (Crassostrea virginica)
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Data from: Short-term sleep loss alters cytokine gene expression in brain and peripheral tissues and increases plasma corticosterone of zebra finch (Taeniopygia guttata)
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Influence of RNA-Seq library construction, sampling methods, and tissue harvesting time on gene expression estimation
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Data from: Sorghum bicolor TX08001 nodal root tissue development gene expression profiling
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Data from: Characterization of the transcriptome and gene expression of four different tissues in the ecologically relevant sea urchin Arbacia lixula using RNA-seq
The sea urchin Arbacia lixula is a keystone species in Mediterranean ecosystems that drive landscape changes in littoral communities. However, genomic information available for the whole order Arbacioida is very limited. Using RNA-seq techniques, we have characterized the transcriptome of four different tissue types in A. lixula: the 'somatic' tissues (coelomocytes and digestive tissue) and the 'reproductive' tissues (ovary and testis), from two replicated cDNA libraries for each sample. Additionally, we performed a de novo assembly to build the 'reference' transcriptome, pooling reads of the four tissues, to analyse the differential expression (DE) in pairwise comparisons between tissues. The complete de novo assembly yielded 186 084 transcripts, with a sequence size limit of 100 nt, being 31% of them spliced isoforms. Approximately 21% of the transcripts had blast hits against proteins of metazoans (E < 10−5), being less than 2.2% functionally annotated. Between coelomocytes and digestive, 30 794 transcripts showed DE (~11.8% of them with blast hit), and 19 567 transcripts did so between testis and ovary (~28.5% of them with blast hit). Major GO-term categories upregulated in somatic tissues were those related to muscle contraction and energy generation in digestive, and lipid metabolism associated with immune response in coelomocytes. Between reproductive tissues, the major upregulated GO categories were related to energy generation in testis, and negative regulation of nucleotide metabolism in ovary. We particularly screened for a collection of target genes in each tissue because of their relevance for further studies on evolution and adaptation of echinoids.
Differential Proteomic Expression of Equine Cardiac and Lamellar Tissue During Insulin-Induced Laminitis
<p><span><span>Endocrinopathic laminitis is pathologically similar to the multi-organ dysfunction and peripheral neuropathy found in human patients with metabolic syndrome. Similarly, endocrinopathic laminitis has been shown to partially result from vascular dysfunction. However, despite extensive research, the pathogenesis of this disease is not well elucidated and laminitis remains without an effective treatment. Here, we sought to identify novel proteins and pathways underlying the development of equine endocrinopathic laminitis. Healthy Standardbred horses (n=4/group) were either given an electrolyte infusion, or a 48-hour euglycemic-hyperinsulinemic clamp. Cardiac and lamellar tissues were analyzed by mass spectrometry (FDR=0.05). All hyperinsulinemic horses developed laminitis despite being previously healthy. We identified 538 and 737 unique proteins in the cardiac and lamellar proteomes, respectively. In the lamellar tissue, we identified 14 proteins which were significantly upregulated and 13 proteins which were significantly downregulated in the hyperinsulinemic group as compared to controls. These results were confirmed via real-time reverse-transcriptase PCR. A STRING analysis of protein-protein interactions revealed that these upregulated proteins were primarily involved in coagulation and complement cascades, platelet activity, and ribosomal function, while downregulated proteins were involved in focal adhesions, spliceosomes, and cell-cell matrices. Novel significant differentially expressed proteins associated with hyperinsulinemia-induced laminitis include talin -1, vinculin, cadherin-13, fibrinogen, alpha-2-macroglobulin, and heat shock protein 90. In contrast, no proteins were found to be significantly differentially expressed in the heart of hyperinsulinemic horses compared to controls. Together,</span> <span>these data indicate that while hyperinsulinemia induced, in part, microvascular damage, complement activation, and ribosomal dysfunction in the lamellae, but a similar effect was not seen in the heart. In brief, this proteomic investigation of a unique equine model of hyperinsulinemia identified novel proteins and signaling pathways, which may lead to the discovery of molecular biomarkers and/or therapeutic targets for endocrinopathic laminitis.</span></span></p>
Data from: Oncogene inference optimization using constraint-based modelling incorporated with protein expression in normal and tumour tissues
Cancer cells are known to exhibit unusual metabolic activity and yet, few metabolic cancer driver genes are known. Genetic alterations and epigenetic modi cations of cancer cells result in the abnormal regulation of cellular metabolic pathways that are different when compared to normal cells. Such a metabolic reprogramming can be simulated using constraint-based modelling approaches towards predicting oncogenes. We introduced the tri-level optimization problem to use the metabolic reprogramming towards inferring oncogenes. The algorithm incorporated Recon 2.2 network with the Human Protein Atlas to reconstruct genome-scale metabolic network models of the tissue-speci fic cells at normal and cancer states, respectively. Such reconstructed models were applied to build the templates of the metabolic reprogramming between normal and cancer cell metabolism. The inference optimization problem was formulated to use the templates as a measure towards predicting oncogenes. The nested hybrid differential evolution algorithm was applied to solve the problem to overcome solving difficulty for transferring the inner optimization problem into the single one. Head and neck squamous cells were applied as a case study to evaluate the algorithm. We detected 13 of the top ranked one-hit dysregulations and 17 of the top ranked two-hit oncogenes with high similarity ratios to the templates. According literature survey, most inferred oncogenes are consistent with the observation in various tissues. Furthermore, the inferred oncogenes were highly connected with the TP53/AKT/IGF/MTOR signalling pathway through PTEN, which is one of the most frequently detected tumour suppressor genes in human cancer.
Data from: Impact of microRNA expression in human atrial tissue in patients with atrial fibrillation undergoing cardiac surgery
Background: Although microRNA (miRNA) regulates initiation and/or progression of atrial fibrillation (AF) in canine AF models, the underlying mechanism in humans remains unclear. We speculated that certain miRNAs in atrial tissue are related to AF, and evaluated the relationship of miRNA expression in human atrial tissue in cardiac surgery patients. Methods: Right atrial tissues from 29 patients undergoing cardiovascular surgery were divided into 3 groups [A: chronic AF or unsuccessful maze, n=6; B: successful maze, n=10; C: sinus rhythm (SR) n=13]. miRNA expression was determined using high density microarrays and with Reverse transcriptase-polymerase chain reaction (RT-PCR). Fibrosis was examined using Masson trichrome staining. Results: miRNA microarray analysis showed elevated miRNA-21, miRNA-23b, miRNA-199b, and miRNA-208b in AF as compared to SR groups. RT-PCR showed elevated miRNA-21 (1.9-fold) and miRNA-208b (4.2-fold) in AF as compared to the SR groups. miRNA-21 expression increased from Group C to A (A: 2.1-fold, B: 1.8-fold, C: 1.0-fold). Fibrosis increased from C to A (A: 43.0±12.9%, B: 21.3±6.1%, C: 11.9±3.1%). Percent fibrosis and miRNA-21 expression were correlated (r=0.508, p<0.05). The plasma levels of miRNA-21 in AF patients was significantly decreased as compared to the healthy volunteers (p<0.05). Conclusion: The expression of miRNA-21 in human atrial tissue was found to be related to atrial fibrosis and might affect AF occurrence, indicating its usefulness as a biomarker for cardiac surgery management.
Data from: De novo transcriptome assembly for the lobster Homarus americanus and characterization of differential gene expression across nervous system tissues
Background: The American lobster, Homarus americanus, is an important species as an economically valuable fishery, a key member in marine ecosystems, and a well-studied model for central pattern generation, the neural networks that control rhythmic motor patterns. Despite multi-faceted scientific interest in this species, currently our genetic resources for the lobster are limited. In this study, we de novo assemble a transcriptome for Homarus americanus using central nervous system (CNS), muscle, and hybrid neurosecretory tissues and compare gene expression across these tissue types. In particular, we focus our analysis on genes relevant to central pattern generation and the identity of the neurons in a neural network, which is defined by combinations of genes distinguishing the neuronal behavior and phenotype, including ion channels, neurotransmitters, neuromodulators, receptors, transcription factors, and other gene products. Results: Using samples from the central nervous system (brain, abdominal ganglia), abdominal muscle, and heart (cardiac ganglia, pericardial organs, muscle), we used RNA-Seq to characterize gene expression patterns across tissues types. We also compared control tissues with those challenged with the neuropeptide proctolin in vivo. Our transcriptome generated 34,813 transcripts with known protein annotations. Of these, 5,000-10,000 of annotated transcripts were significantly differentially expressed (DE) across tissue types. We found 421 transcripts for ion channels and identified receptors and/or proteins for over 20 different neurotransmitters and neuromodulators. Results indicated tissue-specific expression of select neuromodulator (allostatin, myomodulin, octopamine, nitric oxide) and neurotransmitter (glutamate, acetylcholine) pathways. We also identify differential expression of ion channel families, including kainite family glutamate receptors, inward-rectifying K+ (IRK) channels, and transient receptor potential (TRP) A family channels, across central pattern generating tissues. Conclusions: Our transcriptome-wide profiles of the rhythmic pattern generating abdominal and cardiac nervous systems in Homarus americanus reveal candidates for neuronal features that drive the production of motor output in these systems.
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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.