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accession-icon GSE27648
Expression profile of Maize (Zea mays L.) Embryonic Axes During Germination: Regulation of Ribosomal Protein mRNAs.
  • organism-icon Zea mays
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Maize Genome Array (maize)

Description

Seed germination is a critical developmental process in plant propagation. Knowledge of the gene expression patterns in this critical process is important in order to understand the main biochemical reactions involved in successful germination, specially for economically relevant plants such as Maize.

Publication Title

Expression profile of maize (Zea mays L.) embryonic axes during germination: translational regulation of ribosomal protein mRNAs.

Sample Metadata Fields

Treatment, Time

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accession-icon SRP064952
Transcriptomics of adult human small bowel grafts
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

Objective: the objective of this work was to determine different gene expression patterns in small bowel grafts biopsies with “minimal changes” histology that could identify patients with high rejection risk Methods: 24 samples (17 stable and 7 non stable grafts) from 8 adult patients with small bowel transplantation were included for RNA-Sequencing.Total RNA extracted from intestinal biopsies was used with the TruSeq RNA Sample Preparation v2 Kit to construct index-tagged cDNA libraries. Libraries were sequenced on the Genome Analyzer IIx following the standard RNA sequencing protocol with the TruSeq SBS Kit v5. Fastq files containing reads for each library were extracted and demultiplexed using Casava v1.8.2 pipeline. Sequencing adapter contaminations were removed from reads using Cutadapt software v1.6 and the resulting reads were aligned to the reference human genome (Ensembl gene-build GRCh37.75) using TopHat2 v2.0.13. Gene expression values were calculated as counts using HTSeq v0.6.1. Only genes with at least 1 count per million in all samples were considered for statistical analysis. Data were then normalized and differential expression tested using the R Bioconductor package edgeR. We selected all biopsies from 4 of the patients (18 biopsies, 11 stable and 7 non stable) as the discovery set. The other 6 biopsies from 4 patients (all stable) were used as the test set. Differences in the discovery set were tested by generalized linear model analysis,and results were considered significant when the Benjamini-Hochberg adjusted p-value was < 0,05. Results: We obtained 816 differentially expressed genes (DEGs) between stable and non stable biopsies in the discovery set: 369 upregulated and 447 downregulated in the non stable group. The classification and prediction with the Nearest Shrunken Centroids method identified 5 genes (ADH1C, CYP4F2, PDZK1, SLC39A4 and OPTN) from the 816 DEGs that could classify both groups with an error rate of 11% and classified correctly all samples from the test set. These results were confirmed by Supoprted Vector Machine (SVM), bagSVM and Random Forest methods, showing high accuracy, sensitivity and specificity. Conclusions: We identified 5 genes from the DEGs as possible biomarkers to classify patients with normal histology that could be however in a higher risk of rejection. In this way, gene expression assays are powerful tools with high sensitivity that allow more accurate diagnosis. Overall design: The study included 24 samples from 8 adult patients with small bowel transplantation. Samples correspond to RNA extracted from intestinal biopsies obtained at different post-transplantation time. All biopsies have an histological diagnosis of "minimal changes" and they were classified in two groups according their immunological stability (stable and non stable). Stable group comprised biopsies of patients that never rejected and biopsies obtained at least 15 days after rejection if no other rejection episode occurred in at least the next six months. Non stable group included biopsies obtained between rejection episodes (separated less than six months) and also those biopsies collected within the 15 days before the first rejection episode.

Publication Title

5-gene differential expression predicts stability of human intestinal allografts.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP160510
Transcription-dependent control of stem cell self-renewal and differentiation by the splicing factor U2AF1
  • organism-icon Homo sapiens
  • sample-icon 66 Downloadable Samples
  • Technology Badge Icon

Description

Purpose: Here we describe the modulation of a gene expression program involved in cell fate. Methods: We depleted U2AF1 in human induced pluripotent stem cells (hiPSCs) to the level found in differentiated cells using an inducible shRNA system, followed by high-throughput RNAseq, revealing a gene expression program involved in cell fate determination. Results: Approximately 85% of the total raw reads were mapped to the human genome sequence (GRCh37), giving an average of 200 million human reads per sample for total RNA and 15 million human reads per sample for small RNA libraries. Conclusions: Our results show that transcriptional control of gene expression in hiPSCs can be set by the CSF U2AF1, establishing a direct link between transcription and AS during cell fate determination. Overall design: hiPSCs were differentiated into the three germ layers following the described protocol in the study (Gifford et al., 2013).

Publication Title

The core spliceosomal factor U2AF1 controls cell-fate determination via the modulation of transcriptional networks.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE34027
EWS TC-71 cell lines: IGF-1R resistant
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Ewing's Sarcoma cell lines were made resistant to different IGF-1R drugs to investigate mechanisms and pathways modulated by the resistance.

Publication Title

Identification of common and distinctive mechanisms of resistance to different anti-IGF-IR agents in Ewing's sarcoma.

Sample Metadata Fields

Cell line

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accession-icon GSE31415
Comparison of WAT CD34+ vs LAF CD34+
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

A catalytic role has been proposed in neoplastic angiogenesis and cancer progression for bone marrow-derived endothelial progenitor cells (EPCs). However, in preclinical and clinical studies the quantitative role of marrow-derived EPCs in cancer vascularization was found to be extremely variable. Adipose tissue represents an attractive source of autologous adult stem cells due to its abundance and surgical accessibility. CD34+cells from Lipotransfer aspirates (LAs) of patients undergoing breast reconstruction after breast cancer surgery were compared with CD34+ cells from Leucapheresis of normal subjects.

Publication Title

The white adipose tissue used in lipotransfer procedures is a rich reservoir of CD34+ progenitors able to promote cancer progression.

Sample Metadata Fields

Sex

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accession-icon GSE48027
Host directed activity of Pyrazinamide in Mycobacterium tuberculosis infection
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Pyrazinamide (PZA) is one of the first line antibiotics used for the treatment of tuberculosis (TB). we have used human monocyte and a mouse model of pulmonary TB to investigate whether treatment with PZA, in addition to its known anti-mycobacterial properties, modulate the host immune response during Mycobacterium tuberculosis (Mtb) infection.

Publication Title

Host targeted activity of pyrazinamide in Mycobacterium tuberculosis infection.

Sample Metadata Fields

Specimen part, Treatment, Time

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accession-icon GSE73330
AMP18 Dual Effects
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

AMP-18 inhibits growth of cancer cells, but stimulates growth of normal cell lines. Microarray assay was performed to identify gene expression profiles between a head/neck cancer.

Publication Title

A Novel Peptide for Simultaneously Enhanced Treatment of Head and Neck Cancer and Mitigation of Oral Mucositis.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE28996
Xenograft model systems of adenoid cystic carcinoma
  • organism-icon Homo sapiens
  • sample-icon 22 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Adenoid cystic carcinoma (ACC) is one of the most common malignancies that arise in the salivary glands, with an incidence of 4.5 per 1,000,000. It can also arise in glandular tissue closely related to salivary glands in the lacrimal gland, nasal passages and tracheobronchial tree, as well as in glands of the breast and vulva. At all of these sites, it is characterized by a distinctive histology of basaloid epithelial cells arranged in cribriform or tubular patterns, usually demonstrating abundant hyaline extracellular matrix secretion and some degree of myoepithelial differentiation. ACC is generally a slow-growing tumor characterized by a protracted clinical course, usually well over 5 years in duration, marked by regional recurrence, distant metastasis and/or spread along peripheral nerves. A recurrent chromosomal translocation, t(6;9)(q23;p21), has been identified in ACC, and recently it has been discovered that in a majority of ACC the MYB gene on chromosome 6 is fused to the 3 terminus of the NFIB gene on chromosome 9, creating a fusion gene product resulting in increased MYB-related transcriptional activation. Recently it has been determined that most cell lines with attribution of ACC derivation are either contaminants of other cell lines or do not have the characteristic MYB-NFIB translocation. Also, there are no animal models of this histologically and genetically defined tumor type. To address the paucity of experimental and pre-clinical models systems of ACC, we have for several years been establishing xenograft tumor lines from clinical samples of ACC. We describe our experience with these models and their characterization here.

Publication Title

Development and characterization of xenograft model systems for adenoid cystic carcinoma.

Sample Metadata Fields

Specimen part

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accession-icon SRP061774
The SWI/SNF chromatin remodeling complex is required for lineage specific enhancer activity [MEF_RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Genes encoding subunits of SWI/SNF (BAF) chromatin remodeling complexes are collectively altered in over 20% of all human malignancies, but the mechanisms by which these complexes alter chromatin to modulate transcription and control cell fate are poorly understood. Utilizing both loss-of-function and gain-of-function approaches, here we show that SWI/SNF complexes are preferentially targeted to distal enhancers and interact with p300 to regulate transcription via modulation of histone H3 lysine 27 acetylation. We identify a greater requirement for SWI/SNF at typical enhancers than at most super-enhancers and at enhancers in untranscribed regions than in transcribed regions. Our data further demonstrate that SWI/SNF-dependent distal enhancers are essential for controlling expression of genes linked to developmental processes. Our findings thus establish SWI/SNF complexes as regulators of the enhancer landscape and provide insight into the roles of SWI/SNF in cellular fate control. Overall design: RNA-seq in Mouse Embryonic Fibroblasts in WT condition and for knockouts of different SWI/SNF complex subunits.

Publication Title

The SWI/SNF chromatin remodelling complex is required for maintenance of lineage specific enhancers.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE31043
Transgenerational epigenetic inheritance of longevity in Caenorhabditis elegans
  • organism-icon Caenorhabditis elegans
  • sample-icon 35 Downloadable Samples
  • Technology Badge Icon Affymetrix C. elegans Genome Array (celegans)

Description

Chromatin modifiers regulate lifespan in several organisms, raising the question of whether changes in chromatin states in the parental generation could be incompletely reprogrammed in the next generation and thereby affect the lifespan of descendents. The histone H3 lysine 4 trimethylation (H3K4me3) complex composed of ASH-2, WDR-5, and the histone methyltransferase SET-2 regulates C. elegans lifespan. Here we show that deficiencies in the H3K4me3 chromatin modifiers ASH-2, WDR-5, or SET-2 in the parental generation extend the lifespan of descendents up until the third generation. The transgenerational inheritance of lifespan extension by members of the ASH-2 complex is dependent on the H3K4me3 demethylase RBR-2, and requires the presence of a functioning germline in the descendents. Transgenerational inheritance of lifespan is specific for the H3K4me3 methylation complex and is associated with epigenetic changes in gene expression. Thus, manipulation of specific chromatin modifiers only in parents can induce an epigenetic memory of longevity in descendents.

Publication Title

Transgenerational epigenetic inheritance of longevity in Caenorhabditis elegans.

Sample Metadata Fields

No sample metadata fields

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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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