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accession-icon GSE66256
Frequent derepression of the mesenchymal transcription factor gene in acute myeloid leukemia
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Frequent Derepression of the Mesenchymal Transcription Factor Gene FOXC1 in Acute Myeloid Leukemia.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE66254
Frequent derepression of the mesenchymal transcription factor gene in acute myeloid leukemia (human)
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

Bone marrow samples from normal adult male donors were collected into EDTA. Red cells were removed by ammonium chloride lysis. Leukocytes were washed in SM buffer and CD34+ cells were separated from CD34- cells using an AutoMACS device and anti-CD34 immunomagnetic beads (Miltenyi Biotec), according to manufacturers instructions. For mature cell populations, CD34- cells were FACS purified according to the following immunophenotypes, with 7-AAD used to exclude dead cells: Neutrophils: side scatter high CD15+ CD16+. Monocytes: side scatter low-intermediate CD14+ CD16- CD15-. See also Huang et al., 2014.

Publication Title

Frequent Derepression of the Mesenchymal Transcription Factor Gene FOXC1 in Acute Myeloid Leukemia.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE54309
A targeted knockdown screen of genes coding for phosphoinositide modulators identifies PIP4K2A as required for acute myeloid leukemia cell proliferation and survival
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Given the importance of deregulated phosphoinositide (PI) signaling in leukemic hematopoiesis, genes coding for proteins that regulate PI metabolism may have significant and as yet unappreciated roles in leukemia. We performed a targeted knockdown screen of PI modulator genes in human AML cells and identified candidates required to sustain proliferation or prevent apoptosis. One of these, the lipid kinase phosphatidylinositol-5-phosphate 4-kinase, type II, alpha (PIP4K2A) regulates cellular levels of phosphatidylinositol-5-phosphate (PtsIns5P) and phosphatidylinositol 4,5-bisphosphate (PtdIns(4,5)P2). We found PIP4K2A to be essential for the clonogenic and leukemia-initiating potential of human AML cells, and for the clonogenic potential of murine MLL-AF9 AML cells. Importantly, PIP4K2A is also required for the clonogenic potential of primary human AML cells. Its knockdown results in accumulation of the cyclin-dependent kinase inhibitors CDKN1A and CDKN1B, G1 cell cycle arrest and apoptosis. Both CDKN1A accumulation and apoptosis were partially dependent upon activation of the mTOR pathway. Critically, however, PIP4K2A knockdown in normal hematopoietic stem and progenitor cells, both murine and human, did not adversely impact either clonogenic or multilineage differentiation potential, indicating a selective dependency which we suggest may be the consequence of the regulation of different transcriptional programmes in normal versus malignant cells. Thus, PIP4K2A is a novel candidate therapeutic target in myeloid malignancy.

Publication Title

A targeted knockdown screen of genes coding for phosphoinositide modulators identifies PIP4K2A as required for acute myeloid leukemia cell proliferation and survival.

Sample Metadata Fields

Specimen part, Time

View Samples
accession-icon GSE4935
wheat expression level polymorphism study 39 genotypes 2 biological reps
  • organism-icon Triticum aestivum
  • sample-icon 77 Downloadable Samples
  • Technology Badge Icon Affymetrix Wheat Genome Array (wheat)

Description

The use of statistical tools established for the genetic analysis of quantitative traits can be applied to gene expression data. Quantitative trait loci (QTL) analysis can associate expression of genes or groups of genes with particular genomic regions and thereby identify regions that play a role in the regulation of gene expression. A segregating population of 41 doubled haploid (DH) lines from the hard red spring wheat cross RL4452 x AC Domain was used. This population had previously been mapped with microsatellites and includes a full QTL analysis for agronomic and seed quality traits. Expression analysis from 5 day post anthesis developing seed was conducted on 39 of the 41 DH lines using the Affymetrix wheat array. Expression analysis of developing seeds from field grown material identified 1,327 sequences represented by Affymetrix probe sets whose expression varied significantly between genotypes of the population. A sub-set of 378 transcripts were identified that each mapped to a single chromosome interval illustrating that major expression QTLs can be found in wheat. Genomic regions corresponding to multiple expression QTLs were identified that were coincident with previous identified seed quality trait QTL. These regions may be important regulatory regions governing economically important traits. Comparison of expression mapping data with physical mapping for a sub-set of sequences showed that both cis and trans acting expression QTLs were present.

Publication Title

Identifying regions of the wheat genome controlling seed development by mapping expression quantitative trait loci.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE5942
Wheat expression level polymorphism study parentals and progenies from SB location
  • organism-icon Triticum aestivum
  • sample-icon 76 Downloadable Samples
  • Technology Badge Icon Affymetrix Wheat Genome Array (wheat)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Identifying regions of the wheat genome controlling seed development by mapping expression quantitative trait loci.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE5939
Wheat expression level polymorphism study 36 genotypes 2 biological reps from SB location
  • organism-icon Triticum aestivum
  • sample-icon 72 Downloadable Samples
  • Technology Badge Icon Affymetrix Wheat Genome Array (wheat)

Description

The use of statistical tools established for the genetic analysis of quantitative traits can be applied to gene expression data. Quantitative trait loci (QTL) analysis can associate expression of genes or groups of genes with particular genomic regions and thereby identify regions that play a role in the regulation of gene expression. A segregating population of 41 doubled haploid (DH) lines from the hard red spring wheat cross RL4452 x AC Domain was used. This population had previously been mapped with microsatellites and includes a full QTL analysis for agronomic and seed quality traits. Expression analysis from 5 day post anthesis developing seed was conducted on 36 of the 41 DH lines using the Affymetrix wheat array. Expression analysis of developing seeds from field grown material in location 2 identified 10,280 sequences represented by Affymetrix probe sets whose expression varied significantly between genotypes of the population. Of these 1,455 were identified in the point location as well. A sub-set of 542 transcripts were identified that each mapped to a single chromosome interval illustrating that major expression QTLs can be found in wheat. Genomic regions corresponding to multiple expression QTLs were identified that were coincident with previous identified seed quality trait QTL. These regions may be important regulatory regions governing economically important traits. Comparison of expression mapping data with physical mapping for a sub-set of sequences showed that both cis and trans acting expression QTLs were present.

Publication Title

Identifying regions of the wheat genome controlling seed development by mapping expression quantitative trait loci.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE4929
wheat expression level polymorphism study parental genotypes 2 biological reps
  • organism-icon Triticum aestivum
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Wheat Genome Array (wheat)

Description

The use of statistical tools established for the genetic analysis of quantitative traits can be applied to gene expression data. Quantitative trait loci (QTL) analysis can associate expression of genes or groups of genes with particular genomic regions and thereby identify regions that play a role in the regulation of gene expression. A segregating population of 41 doubled haploid (DH) lines from the hard red spring wheat cross RL4452 x AC Domain was used. This population had previously been mapped with microsatellites and includes a full QTL analysis for agronomic and seed quality traits. Expression analysis from 5 day post anthesis developing seed was conducted on 39 of the 41 DH lines using the Affymetrix wheat array. Expression analysis of developing seeds from field grown material identified 1,327 sequences represented by Affymetrix probe sets whose expression varied significantly between genotypes of the population. A sub-set of 378 transcripts were identified that each mapped to a single chromosome interval illustrating that major expression QTLs can be found in wheat. Genomic regions corresponding to multiple expression QTLs were identified that were coincident with previous identified seed quality trait QTL. These regions may be important regulatory regions governing economically important traits. Comparison of expression mapping data with physical mapping for a sub-set of sequences showed that both cis and trans acting expression QTLs were present.

Publication Title

Identifying regions of the wheat genome controlling seed development by mapping expression quantitative trait loci.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE5937
Wheat expression level polymorphism study parental genotypes 2 biological reps from SB location
  • organism-icon Triticum aestivum
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Wheat Genome Array (wheat)

Description

The use of statistical tools established for the genetic analysis of quantitative traits can be applied to gene expression data. Quantitative trait loci (QTL) analysis can associate expression of genes or groups of genes with particular genomic regions and thereby identify regions that play a role in the regulation of gene expression. A segregating population of 41 doubled haploid (DH) lines from the hard red spring wheat cross RL4452 x AC Domain was used. This population had previously been mapped with microsatellites and includes a full QTL analysis for agronomic and seed quality traits. Expression analysis from 5 day post anthesis developing seed was conducted on 36 of the 41 DH lines using the Affymetrix wheat array. Expression analysis of developing seeds from field grown material in location 2 identified 10,280 sequences represented by Affymetrix probe sets whose expression varied significantly between genotypes of the population. Of these 1,455 were identified in the point location as well. A sub-set of 542 transcripts were identified that each mapped to a single chromosome interval illustrating that major expression QTLs can be found in wheat. Genomic regions corresponding to multiple expression QTLs were identified that were coincident with previous identified seed quality trait QTL. These regions may be important regulatory regions governing economically important traits. Comparison of expression mapping data with physical mapping for a sub-set of sequences showed that both cis and trans acting expression QTLs were present.

Publication Title

Identifying regions of the wheat genome controlling seed development by mapping expression quantitative trait loci.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP103126
Frequent derepression of the Iroquois homeobox gene IRX3 in human acute leukemia
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

The Iroquois homeodomain transcription factor gene IRX3 is highly expressed in the developing nervous system, limb buds and heart. In adults, expression levels specify risk of obesity. We now report a significant functional role for IRX3 in human acute leukemia. While transcript levels are very low in normal human bone marrow cell populations, high level IRX3 expression is observed in ~30% of patients with acute myeloid leukemia (AML), ~50% of patients with T-acute lymphoblastic leukemia and ~20% of patients with B-acute lymphoblastic leukemia, typically in association with high levels of HOXA9. Expression of IRX3 alone was sufficient to immortalise murine bone marrow stem and progenitor cells, and induce T- and B-lineage leukemias in vivo with incomplete penetrance. IRX3 knockdown induced terminal differentiation of AML cells. Combined IRX3 and Hoxa9 expression in murine bone marrow stem and progenitor cells substantially enhanced the morphologic and phenotypic differentiation block of the resulting AMLs by comparison with Hoxa9-only leukemias, through suppression of a myelomonocytic program. Likewise, in cases of primary human AML, high IRX3 expression is associated with reduced myelomonocytic differentiation. Thus, tissue-inappropriate derepression of IRX3 modulates the cellular consequences of HOX gene expression to enhance differentiation block in human AML. Overall design: Murine acute myeloid leukemias - 3 samples from separate mice with AML initiated by HOXA9 and 3 samples from separate mice with AML initiated by HOXA9 and IRX3 coexpression

Publication Title

Derepression of the Iroquois Homeodomain Transcription Factor Gene IRX3 Confers Differentiation Block in Acute Leukemia.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP033466
Transcriptome analysis of Jurkat T cells expressing MALT1 or its mutants MALT1-R149A and MALT1-C464A or the MALT1-R149A-C464A double mutant.
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Purpose: study the role of MALT1 auto-proteolysis in T cell receptor mediated activation of NF-kB. Methods: Jurkat cells were generated that express wild type MALT1, the auto-cleavage deficient MALT1-R149A mutant, the catalytic inactive MALT1-C464A mutant or the R149A-C464A double mutant (RACA). Expression of endogenous MALT1 was inactivated using TALEN technology for the Jurkat cells expressing MALT1-R149A (JDM-RA) and MALT1-C464A (JDM-CA). Illumina HISeq 2000 deep sequencing was performed to determine the mRNA profiles for MALT1, JDM-RA, JDM-CA and RACA cells in unstimulated conditions or after treatment with 75ng/ml PMA and 150 ng/ml ionomycin for 3 or 18 hrs. Results: PMA ionomycin stimulation of the MALT1 auto-cleavage defective JDM-RA cells fails to activate NF-kB-dependent transcription like for the MALT1 catalytic inactive JDM-CA cells and the double RACA mutant cells. Conclusion: MALT1 autoproteolysis is essential for transcription of NF-kB target genes Overall design: mRNA profiles of Jurkat expressing MALT1, MALT1-R149A, MALT1-C464A and MALT1-R149A-C464A after 0, 3 and 18 hours of stimulation with PMA and Ionomycin were generated by deep sequencing, in duplicate, using Illumina HISeq 2000

Publication Title

MALT1 auto-proteolysis is essential for NF-κB-dependent gene transcription in activated lymphocytes.

Sample Metadata Fields

No sample metadata fields

View Samples
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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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