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accession-icon GSE31703
Ecological success of a group of Saccharomyces cerevisiae / Saccharomyces kudriavzevii hybrids in the Northern European wine making environment.
  • organism-icon Saccharomyces cerevisiae x saccharomyces kudriavzevii, Saccharomyces cerevisiae
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

The aim of this project was to evaluate the ploidy of a S. cerevisiae *S. kudriavzevii hybrid in comparison to the lab strain S288C. Other wine yeast have been icluded in the project for the global analysis.

Publication Title

Ecological success of a group of Saccharomyces cerevisiae/Saccharomyces kudriavzevii hybrids in the northern european wine-making environment.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE57775
Masseter muscle gene expression in human malocclusion subjects with and without posterior facial asymmetry
  • organism-icon Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

Non-syndromic facial asymmetry is commonly found in dentofacial deformity populations with skeletal malocclusions. Asymmetry of this type may result from imbalanced growth and function of both the jaw and associated muscles. Among the multiple genes that interact to affect the craniofacial musculoskeletal complex during pre and postnatal growth and development, NODAL signaling pathwy (NSP) genes are active in adult skeletal muscle and may be key factors in development, growth and maintenance of facial asymmetry. It is of interest to determine whether expression of NODAL pathway genes might differ in masseter muscles between individuals with malocclusion that have facial asymmetry and normal symmetry.

Publication Title

Nodal pathway genes are down-regulated in facial asymmetry.

Sample Metadata Fields

Sex, Age, Specimen part, Race, Subject

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accession-icon GSE55513
Transcriptome Analysis Predicts Clinical Outcome and Sensitivity to Anticancer Drugs of patients with a Pancreatic Adenocarcinoma
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

A major impediment to the effective treatment of patients with PDAC (Pancreatic Ductal Adenocarcinoma) is the molecular heterogeneity of the disease, which is reflected in an equally diverse pattern of clinical responses to therapy. We developed an efficient strategy in which PDAC samples from 17 consecutively patients were obtained by EUS-FNA or surgery, their cells maintained as a primary culture and tumors as breathing tumors by xenografting in immunosuppressed mice. For these patients a clinical follow up was obtained. On the breathing tumors we studied the RNA expression profile by an Affymetrix approach. We observed a significant heterogeneity in their RNA expression profile, however, the transcriptome was able to discriminate patients with long- or short-time survival which correspond to moderately- or poorly-differentiated PDAC tumors respectively. Cells allowed us the possibility to analyze their relative sensitivity to several anticancer drugs in vitro by developing a chimiogram, like an antibiogram for microorganisms, with several anticancer drugs for obtaining an individual profile of drug sensitivity and as expected, the response was patient-dependent. Interestingly, using this approach, we also found that the transcriptome analysis could predict the sensitivity to some anticancer drugs of patients with a PDAC. In conclusion, using this approach, we found that the transcriptome analysis could predict the sensitivity to some anticancer drugs and the clinical outcome of patients with a PDAC.

Publication Title

Transcriptomic analysis predicts survival and sensitivity to anticancer drugs of patients with a pancreatic adenocarcinoma.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE89792
Gene Expression Profiling of Patient-Derived Pancreatic Cancer Xenografts predicts sensitivity to the BET bromodomain inhibitor JQ1: Implications to individualized medicine efforts
  • organism-icon Homo sapiens
  • sample-icon 40 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

c-Myc controls more than 15% of genes responsible for proliferation, differentiation, and cellular metabolism in pancreatic as well as other cancers making this transcription factor a prime target for treating patients. The transcriptome of 55 patient derived xenografts show that 30% of them share an exacerbated expression profile of MYC transcriptional targets (MYC-high). This cohort is characterized by a high level of Ki67 staining, a lower differentiation state and a shorter survival time compared to the MYC-low subgroup. To define classifier expression signature, we selected a group of 10 MYC targets transcripts which expression is increased in the MYC-high group and 6 transcripts increased in the MYC-low group. We validated the ability of these markers panel to identify MYC-high patient-derived xenografts from both: discovery and validation cohorts as well as primary cells cultures from the same patients. We then showed that cells from MYC-high patients are more sensitive to JQ1 treatment compared to MYC-low cells, in both monolayer and 3D cultured spheroids, due to cell cycle arrest followed by apoptosis. Therefore, these results provide new markers and potentially novel therapeutic modalities for distinct subgroups of pancreatic tumors and may find application to the future management of these patients within the setting of individualized medicine clinics.

Publication Title

Gene expression profiling of patient-derived pancreatic cancer xenografts predicts sensitivity to the BET bromodomain inhibitor JQ1: implications for individualized medicine efforts.

Sample Metadata Fields

Disease

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accession-icon GSE26900
Effect of Tet1-knockdown on gene expression in mouse ES cells cultured in ES and TS cell culture conditions
  • organism-icon Mus musculus
  • sample-icon 27 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

TET-family enzymes convert 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) in DNA. Tet1 and Tet2 are Oct4-regulated enzymes that together sustain 5hmC in mouse embryonic stem (ES) cells. ES cells depleted of Tet1 by RNAi show diminished expression of the Nodal antagonist Lefty1, and display hyperactive Nodal signalling and skewed differentiation into the endoderm-mesoderm lineage in embryoid bodies in vitro. In Fgf4- and heparin-supplemented culture conditions that favor derivation of trophoblast stem (TS) cells, Tet1-depleted ES cells activate the trophoblast stem cell lineage determinant Elf5 and can colonize the placenta in mid-gestation embryo chimeras. Consistent with these findings, Tet1-depleted ES cells form aggressive hemorrhagic teratomas with increased endoderm, reduced neuroectoderm and ectopic appearance of trophoblastic giant cells. Thus Tet1 functions to regulate the lineage differentiation potential of ES cells. Here, we performed whole-genome transcriptome profiling of ES cells stably depleted of Tet1 by shRNA knockdown (Tet1-kd) cultured in either standard ES cell or in TS cell culture conditions. Gene expression changes in Tet1-kd ES cells were fairly modest compared to control (GFP-kd) cells, although gene ontology (GO) analysis of differentially expressed genes yielded many terms related to embryonic development and cell cycle regulation. In TS cell culture conditions, a core set of genes defining trophectodermal cell differentiation, including Cdx2, Eomes and Tead4, was enriched in Tet1-kd compared to GFP-kd cells.

Publication Title

Tet1 and Tet2 regulate 5-hydroxymethylcytosine production and cell lineage specification in mouse embryonic stem cells.

Sample Metadata Fields

Specimen part

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accession-icon SRP069872
Uncoupling X chromosome number from sex determination separates contribution of sex and X dose to sex-biased gene expression in C. elegans
  • organism-icon Caenorhabditis elegans
  • sample-icon 15 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

The difference in X chromosome copy number creates a potential difference in X chromosomal gene expression between males and females. In many animals, dosage compensation mechanisms equalize X chromosome expression between sexes. Yet, X chromosome is also enriched for sex-biased genes due to differences in the evolutionary history of the X and autosomes. The manner in which dosage compensation and sex-biased gene expression exist on the X chromosome remains an open question. Most studies compare gene expression between two sexes, which combines expression differences due to X chromosome number (dose) and sex. Here, we uncoupled the effects of sex and X dose in C. elegans and determined how each process affects expression of the X chromosome compared to autosomes. We found that in the soma, sex-biased expression on the X chromosome is almost entirely due to sex because the dosage compensation complex (DCC) effectively compensates for the X dose difference between sexes. In the germline where the DCC is not present, X chromosome copy number contributes to hermaphrodite-biased gene expression. These results suggest that X dose contributes to sex-biased gene expression based on the level of dosage compensation in different tissues and developmental stages. Overall design: RNA-Seq profiles of C. elegans XO hermaphrodite and XX male L3 larvae and adults

Publication Title

Untangling the Contributions of Sex-Specific Gene Regulation and X-Chromosome Dosage to Sex-Biased Gene Expression in Caenorhabditis elegans.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE19355
Silencing of mrhl non coding RNA in mouse spermatoginial cells GC1-Spg
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Mrhl is a non coding RNA identified from mouse chromosome 8. It is a 2.4kb poly adenylated, nuclear restricted RNA expressed in multiple tissues. The 2.4 kb RNA also undergoes a nuclear processing event mediated through Drosha that generates an 80nt intermediate RNA. This study was aimed at understanding the functiion of mrhl by silencing the mrhl RNA in the mouse spermatogonial cells using a pool of siRNAs targeted against the mrhl and analyse the global gene expression change using Affymetrix mouse expression array. The mRNAs that showed significant change in expression in mrhl siRNA treated cells against control were studied further for their biological significance with respect to mrhl silencing.

Publication Title

mrhl RNA, a long noncoding RNA, negatively regulates Wnt signaling through its protein partner Ddx5/p68 in mouse spermatogonial cells.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE5130
Accurate and precise transcriptional profiles from 50 pg of total RNA or 100 flow-sorted primary lymphocytes
  • organism-icon Mus musculus
  • sample-icon 103 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

We have developed a total RNA amplification and labeling strategy for use with Affymetrix GeneChips. Our protocol, which we denote BIIB, employs two rounds of linear T7 amplification followed by Klenow labeling to generate a biotinylated cDNA. In benchmarking studies using a titration of mouse universal total RNA, BIIB outperformed commercially available kits in terms of sensitivity, accuracy, and amplified target length, while providing equivalent results for technical reproducibility. BIIB maintained 50 and 44% present calls from 100 and 50 pg of total RNA, respectively. Inter- and intrasample precision studies indicated that BIIB produces an unbiased and complete expression profile within a range of 5 ng to 50 pg of starting total RNA. From a panel of spiked exogenous transcripts, we established the BIIB linear detection limit to be 20 absolute copies. Additionally, we demonstrate that BIIB is sensitive enough to detect the stochastic events inherent in a highly diluted sample. Using RNA isolated from whole tissues, we further validated BIIB accuracy and precision by comparison of 224 expression ratios generated by quantitative real-time PCR. The utility of our method is ultimately illustrated by the detection of biologically expected trends in a T cell/B cell titration of 100 primary cells flow sorted from a healthy mouse spleen.

Publication Title

Accurate and precise transcriptional profiles from 50 pg of total RNA or 100 flow-sorted primary lymphocytes.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE18892
Silencing of AEBP1 in U87MG glial cells and Chip-chIP with AEBP1 antibody
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

AEBP1 has been identified as a transcriptional repressor playing a

Publication Title

Identification of genomic targets of transcription factor AEBP1 and its role in survival of glioma cells.

Sample Metadata Fields

Cell line

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accession-icon GSE76652
Silencing of ASCL1 in U87MG glioma cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

ASCL1 is known to act as transcriptional activator of notch signaling pathway. We have found that ASCL1 is over expressed in secondary glioblastoma.

Publication Title

System analysis identifies distinct and common functional networks governed by transcription factor ASCL1, in glioma and small cell lung cancer.

Sample Metadata Fields

Cell line

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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)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

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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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