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GSE4935
Triticum aestivum
77 Downloadable Samples
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- Triticum aestivum
- 76 Downloadable Samples
- 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- Triticum aestivum
- 72 Downloadable Samples
- 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- Triticum aestivum
- 4 Downloadable Samples
- 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- Triticum aestivum
- 4 Downloadable Samples
- 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- Mus musculus
- 4 Downloadable Samples
Illumina HiSeq 2000
Description
Pancreatic beta-cell dysfunction contributes to onset and progression of type 2 diabetes. In this state beta-cells become metabolically inflexible, losing the ability to select between carbohydrates and lipids as substrates for mitochondrial oxidation. These changes lead to beta-cell dedifferentiation. We have proposed that FoxO proteins are activated through deacetylation-dependent nuclear translocation to forestall the progression of these abnormalities. However, how deacetylated FoxO exert their actions remains unclear. To address this question, we analyzed islet function in mice homozygous for knock-in alleles encoding deacetylated FoxO1 (6KR). Islets expressing 6KR mutant FoxO1 have enhanced insulin secretion in vivo and ex vivo, and decreased fatty acid oxidation ex vivo. Remarkably, the gene expression signature associated with FoxO1 deacetylation differs from wild-type by only ~2% of the > 4,000 genes regulated in response to re-feeding. But this narrow swath includes key genes required for beta-cell identity, lipid metabolism, and mitochondrial fatty acid and solute transport. The data support the notion that deacetylated FoxO1 protects beta-cell function by limiting mitochondrial lipid utilization, and raise the possibility that inhibition of fatty acid oxidation in ß-cells is beneficial to diabetes treatment. Overall design: Examined 2 different feeding state and 2 different genotypes
Publication Title
FoxO1 Deacetylation Decreases Fatty Acid Oxidation in β-Cells and Sustains Insulin Secretion in Diabetes.
Sample Metadata Fields
Cell line, Subject
View Samples- Mus musculus
- 6 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Proprioception relies on two main classes of proprioceptive sensory neurons (pSNs). These neurons innervate two distinct peripheral receptors in muscle, muscle spindles (MSs) or Golgi tendon organs (GTOs), and synapse onto different sets of spinal targets, but the molecular basis of their distinct pSN subtype identity remains unknown.
Publication Title
The PDZ-domain protein Whirlin facilitates mechanosensory signaling in mammalian proprioceptors.
Sample Metadata Fields
Sex, Specimen part
View Samples- Homo sapiens
- 42 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Monitoring genome-wide, cell-specific responses to human disease, although challenging, holds great promise for medicines future. Patients with injury severe enough to develop multiple organ dysfunction syndrome (MODS) are known to have multiple immune derangements, including T-cell apoptosis and anergy combined with depressed monocyte antigen presentation. Genome-wide expression analysis of highly-enriched circulating leukocyte subpopulations, combined with cell-specific pathway analyses, offers a previously unavailable opportunity to discover novel leukocyte regulatory networks in critically injured patients. Severe injury induced significant changes in the T-cell, monocyte, and total leukocyte transcriptome, with only 12% of these genomic changes common to all three cell populations. T-cell-specific pathway analyses identified increased gene expression of several novel inhibitory receptors (PD-1, CD152, NRP-1, Lag3), and concomitant decreases in stimulatory receptors (CD28, CD4, IL-2Ralpha). Functional analysis of T-cells and monocytes confirmed reduced T-cell proliferation and increased cell surface expression of negative signaling receptors paired with decreased monocyte costimulation ligands. Thus, genome-wide expression from highly-enriched cell populations combined with knowledge-based pathway analyses leads to the identification of novel regulatory networks differentially expressed in injured patients. Importantly, application of cell separation, genome-wide expression, and cell specific pathway analyses can be used to discover novel pathway alterations in human disease.
Publication Title
Cell-specific expression and pathway analyses reveal alterations in trauma-related human T cell and monocyte pathways.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 18 Downloadable Samples
- IlluminaHiSeq2000
Description
The development of affinity purification technologies together with mass spectrometric analyses of the purified protein mixtures (AP-MS) has been used both to identify new protein-protein interactions and to define the subunit composition of protein complexes. Transcription factor protein interactions, however, have not been systematically analyzed using these approaches. Here, we have investigated whether ectopic expression of an affinity tagged transcription factor as bait in AP-MS experiments perturbs gene expression in cells resulting in false positive identification of bait associated proteins when typical experimental controls are used. Using quantitative proteomics and RNA-Seq, we determined that the increase in the abundance of a set of proteins caused by overexpression of the transcription factor RelA is not sufficient for these proteins to then copurify non-specifically and be misidentified as bait associated proteins. Therefore typical controls should be sufficient and a number of different baits can be compared with a common set of controls. This is of practical interest when identifying bait interactors from a large number of different baits. As expected, we found several known RelA interactors enriched in our RelA purifications (NFêB1, NFêB2, Rel, RelB, IêBá, IêBâ and IêBå). We also found several proteins not previously described in association with RelA, including the small mitochondrial chaperone Tim13. Using a variety of biochemical approaches, we further investigated the nature of the association between Tim13 and NFêB family transcription factors. The work here therefore provides a conceptual and experimental framework for analyzing transcription faction protein interactions. Overall design: Gene expression profiles were assayed in triplicate from HEK293 cells expressing either Halo-RelA, Halo-NFkB1, or Halo tag alone.
Publication Title
Controlling for gene expression changes in transcription factor protein networks.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 12 Downloadable Samples
- Illumina HiSeq 2500
Description
This experiment analyzes the set of RNAs copurifying with the protein TNIP2 (amino acids 196-346) Overall design: HEK293 cells were transfected with constructs expressing either Halo tag (controls) or Halo-TNIP2 196-346. Total RNA was purified from an aliquot of the whole cell extract (Input samples). Halo-tagged proteins were purified from the remainder of the whole cell extract, and RNA subsequently purified from the Halo purified samples (Pulldown samples).
Publication Title
TNIP2 is a Hub Protein in the NF-κB Network with Both Protein and RNA Mediated Interactions.
Sample Metadata Fields
Cell line, Subject
View Samples