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accession-icon SRP072417
NextGen Consortium: GENESiPS Study: Identifying the Gene Networks of Insulin Resistance
  • organism-icon Homo sapiens
  • sample-icon 317 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

RNA-seq transcriptome profiling of human induced pluripotent stem cells to characterize gene expression variation across individuals and within multiple iPSC lines from the same individual Overall design: Donor erythroblast or activated T-cells were reprogrammed with a Sendai viral vector coding for reprogramming factors. IPSC lines were propagated for ~9 passages before RNA sequencing

Publication Title

Analysis of Transcriptional Variability in a Large Human iPSC Library Reveals Genetic and Non-genetic Determinants of Heterogeneity.

Sample Metadata Fields

Sex, Age, Race, Subject

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accession-icon SRP066092
Transcriptome Profiling of Testis Tissue from Boars with Good and Bad Sperm DNA Fragmentation Index
  • organism-icon Sus scrofa
  • sample-icon 94 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Chromatin packaging in sperm protects it against DNA fragmentation, and the importance of proper chromatin packaging for boar fertility outcome has become increasingly evident. Little is known however about the molecular mechanisms underlying differences in sperm DNA fragmentation and an understanding of the genes controlling this sperm parameter could help in selecting the best boars for AI use. The aim of this study was to identify differentially expressed genes in testis of Norsvin Landrace and Duroc boars with good and bad sperm DNA fragmentation using transcriptome sequencing and to use the data for polymorphism search. RNA sequence reads were obtained using Illumina technology and mapped by TopHat using the Ensembl pig database. Differentially expressed genes and pathways were analyzed using the R Bioconductor packages edgeR and goseq respectively. Using a false discovery rate of 0.05, 309 and 375 genes were found displaying significant differences in expression level between the good and bad condition in Landrace and Duroc respectively. Of the differentially expressed genes, 72 were found in common for the two breeds. Gene ontology analysis revealed that terms common for the two breeds included extracellular matrix, extracellular region and calcium ion binding. Additionally, different metabolic processes were enriched in Landrace and Duroc, whereas immune response ontologies were found to be important in Landrace. SNP detection in Landrace/Duroc identified 53182/53931 variants in 10924/10748 transcripts and of these, 1573/1827 SNPs occurred in 189/241 unique genes that were also differentially expressed. Possible high impact variants were detected using SnpEff. Transcriptome sequencing identified differentially expressed genes and nucleotide variants related to differences in sperm DNA fragmentation, and functional annotation of the genes pointed towards important biochemical pathways. This study provides insights into the genetic network underlying this trait and is a first step towards using sperm DNA fragmentation for predicting boar fertility. Overall design: Nine Landrace, five low and four high, and eleven Duroc, five low and six high, boars were selected for transcriptome profiling based on their extreme DFI values. The biological replicates within the high and low groups were compared.

Publication Title

RNA sequencing reveals candidate genes and polymorphisms related to sperm DNA integrity in testis tissue from boars.

Sample Metadata Fields

Subject

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accession-icon SRP126289
Impact of regulatory variation across human iPSCs and differentiated cells [RNA-seq]
  • organism-icon Homo sapiens
  • sample-icon 67 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Induced pluripotent stem cells (iPSCs) are an essential tool for studying cellular differentiation and cell types that are otherwise difficult to access. Here we investigate the use of iPSCs and iPSC-derived cells to study the impact of genetic variation across different cell types and as models for the genetics of complex disease. We established a panel of iPSCs from 58 well-studied Yoruba lymphoblastoid cell lines (LCLs); 14 of these lines were further differentiated into cardiomyocytes. We characterized regulatory variation across individuals and cell types by measuring RNA, chromatin accessibility and DNA methylation. Regulatory variation between individuals is lower in iPSCs than in the differentiated cell types, consistent with the intuition that developmental processes are generally canalized. While most cell-type- specific regulatory effects lie in chromatin that is open only in the affected cell-types, we find that 20% of cell-type specific effects are in shared open chromatin. Finally, we developed deep neural network models to predict open chromatin regions in these cell types from DNA sequence alone and were able to use the sequences of segregating haplotypes to predict the effects of common SNPs on tissue-specific chromatin accessibility. Our results provide a framework for using iPSC technology to study regulatory variation in cell types that are otherwise inaccessible. Keywords: Expression profiling by high throughput sequencing Overall design: Immortalized lymphoblastoid cell lines from 58 African individuals were reprogrammed into induced pluripotent stem cells

Publication Title

Impact of regulatory variation across human iPSCs and differentiated cells.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE28582
Gene Copy Number Aberrations are Associated with Survival in Histological Subgroups of Non-Small Cell Lung Cancer
  • organism-icon Homo sapiens
  • sample-icon 100 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Gene copy number aberrations are associated with survival in histologic subgroups of non-small cell lung cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE28571
Gene Copy Number Aberrations are Associated with Survival in Histological Subgroups of Non-Small Cell Lung Cancer (expression data)
  • organism-icon Homo sapiens
  • sample-icon 100 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Hypothesis: Non-small cell lung cancer (NSCLC) is characterized by a multitude of genetic aberrations with unknown clinical impact. In this study, we aimed to identify gene copy number changes that correlate with clinical outcome in NSCLC. To maximize the chance to identify clinically relevant events, we applied a strategy involving two prognostically extreme patient groups.

Publication Title

Gene copy number aberrations are associated with survival in histologic subgroups of non-small cell lung cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE94521
Identification of transcriptome signatures and biomarkers specific for potential developmental toxicants inhibiting human neural crest cell migration
  • organism-icon Homo sapiens
  • sample-icon 57 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The in vitro test battery of the European research consortium ESNATS (novel stem cell-based test systems) has been used to screen for potential human developmental toxicants. As part of this effort, the migration of neural crest (MINC) assay has been used to evaluate chemical effects on neural crest function. It identified some drug-like compounds in addition to known environmental toxicants. The hits included the HSP90 inhibitor geldanamycin, the chemotherapeutic arsenic trioxide, the flame-retardant PBDE-99, the pesticide triadimefon and the histone deacetylase inhibitors valproic acid and trichostatin A. Transcriptome changes triggered by these substances in human neural crest cells were recorded and analysed here to answer three questions: (1) can toxicants be individually identified based on their transcript profile; (2) how can the toxicity pattern reflected by transcript changes be compacted/ dimensionality-reduced for practical regulatory use; (3) how can a reduced set of biomarkers be selected for large-scale follow up? Transcript profiling allowed clear separation of different toxicants and the identification of toxicant types in a blinded test study. We also developed a diagrammatic system to visualize and compare toxicity patterns of a group of chemicals by giving a quantitative overview of altered superordinate biological processes (e.g. activation of KEGG pathways or overrepresentation of gene ontology terms). The transcript data were mined for potential markers of toxicity, and 39 transcripts were selected to either indicate general developmental toxicity or distinguish compounds with different modes-of-action in read-across. In summary, we found inclusion of transcriptome data to largely increase the information from the MINC phenotypic test.

Publication Title

Identification of transcriptome signatures and biomarkers specific for potential developmental toxicants inhibiting human neural crest cell migration.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE36601
Yeast under physiological changes of stress adaptation and stress recovery
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

Background

Publication Title

Distinct roles of the Gcn5 histone acetyltransferase revealed during transient stress-induced reprogramming of the genome.

Sample Metadata Fields

Treatment

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accession-icon GSE8077
Global analyses of gene expression in early experimental knee osteoarthritis
  • organism-icon Rattus norvegicus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

OBJECTIVE: To analyze genome-wide changes in chondrocyte gene expression in a surgically induced model of early osteoarthritis (OA) in rats, to assess the similarity of this model to human OA, and to identify genes and mechanisms leading to OA pathogenesis. METHODS: OA was surgically induced in 5 rats by anterior cruciate ligament transection and partial medial meniscectomy. Sham surgery was performed in 5 additional animals, which were used as controls. Both groups underwent 4 weeks of forced mobilization, 3 times per week. RNA was extracted directly from articular chondrocytes in the OA (operated), contralateral, and sham-operated knees. Affymetrix GeneChip expression arrays were used to assess genome-wide changes in gene expression. Expression patterns of selected dysregulated genes, including Col2a1, Mmp13, Adamts5, Ctsc, Ptges, and Cxcr4, were validated by real-time polymerase chain reaction, immunofluorescence, or immunohistochemistry 2, 4, and 8 weeks after surgery. RESULTS: After normalization, comparison of OA and sham-operated samples showed 1,619 differentially expressed probe sets with changes in their levels of expression >/=1.5-fold, 722 with changes >/=2-fold, 135 with changes >/=4-fold, and 20 with changes of 8-fold. Dysregulated genes known to be involved in human OA included Mmp13, Adamts5, and Ptgs2, among others. Several dysregulated genes (e.g., Reln, Phex, and Ltbp2) had been identified in our earlier microarray study of hypertrophic chondrocyte differentiation. Other genes involved in cytokine and chemokine signaling, including Cxcr4 and Ccl2, were identified. Changes in gene expression were also observed in the contralateral knee, validating the sham operation as the appropriate control. CONCLUSION: Our results demonstrate that the animal model mimics gene expression changes seen in human OA, supporting the relevance of newly identified genes and pathways to early human OA. We propose new avenues for OA pathogenesis research and potential targets for novel OA treatments, including cathepsins and cytokine, chemokine, and growth factor signaling pathways, in addition to factors controlling the progression of chondrocyte differentiation.

Publication Title

Global analyses of gene expression in early experimental osteoarthritis.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE36599
Gene expression profile in yeast under physiological changes of stress adaptation and stress recovery
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

The data provide information expression profile in yeast for 5 different physioloigcal conditions during stress adpatation and stress recovery (normal growth, during stress adaptation, after stress adaptation, under stress recovery, after stress recovery) in yeast. The purpose of the study is to understand how histone acetyltransferase HATs (Gcn5) apply it is function in gene regulation by changing global or local histone acetylation level under different physiological conditions.

Publication Title

Distinct roles of the Gcn5 histone acetyltransferase revealed during transient stress-induced reprogramming of the genome.

Sample Metadata Fields

Treatment

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accession-icon GSE45451
Basal progenitors during cortical neurogenesis
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

MicroRNAs establish robustness and adaptability of a critical gene network to regulate progenitor fate decisions during cortical neurogenesis.

Sample Metadata Fields

Specimen part

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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