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Mus musculus
10 Downloadable Samples
Illumina Genome Analyzer II
Description
To fully understand cell type identity and function in the nervous system there is a need to understand neuronal gene expression at the level of isoform diversity. Here we applied Next Generation Sequencing of the transcriptome (RNA-Seq) to purified sensory neurons and cerebellar granular neurons (CGNs) grown on an axonal growth permissive substrate. The goal of the analysis was to uncover neuronal type specific isoforms as a prelude to understanding patterns of gene expression underlying their intrinsic growth abilities. Global gene expression patterns were comparable to those found for other cell types, in that a vast majority of genes were expressed at low abundance. Nearly 18% of gene loci produced more than one transcript. More than 8000 isoforms were differentially expressed, either to different degrees in different neuronal types or uniquely expressed in one or the other. Sensory neurons expressed a larger number of genes and gene isoforms than did CGNs. To begin to understand the mechanisms responsible for the differential gene/isoform expression we identified transcription factor binding sites present specifically in the upstream genomic sequences of differentially expressed isoforms, and analyzed the 3’ untranslated regions (3’ UTRs) for microRNA (miRNA) target sites. Our analysis defines isoform diversity for two neuronal types with diverse axon growth capabilities and begins to illuminate the complex transcriptional landscape in two neuronal populations. Overall design: RNA was sequenced from cultured peripheral neurons of the dorsal root ganglia (DRG neurons) and cerebellar granular neurons (CGNs) of the central nervous system
Publication Title
Isoform diversity and regulation in peripheral and central neurons revealed through RNA-Seq.
Sample Metadata Fields
Specimen part, Cell line, Subject
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SRP044619- Mus musculus
- 18 Downloadable Samples
- Illumina HiSeq 2000
Description
To identify isoform differential expression underlying peripheral nerve regeneration we performed RNA-Sequencing on DRG neurons after axotomy. Overall design: RNA was sequenced from peripheral Dorsal Root Ganglia (DRG) neurons from adult male mice 7 days after a conditioning lesion at the level of the sciatic nerve (Crushed samples) or after a sham surgery (Controls surgery).
Publication Title
Identification of miRNAs involved in DRG neurite outgrowth and their putative targets.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 6 Downloadable Samples
Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)
Description
Cerebellum from post-natal day 11 L1 knockout mice on the 129Sv background were compared to wild type littermates. The original goal of the study was to determine if there was compensation from other L1 family members or alterations in cell survival or apoptosis. Interestingly no major changes were detected in those families or pathways.
Publication Title
A modifier locus on chromosome 5 contributes to L1 cell adhesion molecule X-linked hydrocephalus in mice.
Sample Metadata Fields
Sex
View Samples- Mus musculus
- 36 Downloadable Samples
- NextSeq 500
Description
We developed a UPPL (Upk3a-CreERT2;p53f/f;Ptenf/f;Rosa26LSL-Luc) mouse model of bladder cancer and compared it with the existing BBN (N-butyl-N-(4-hydroxybutyl)nitrosamine) mouse model of blader cancer. We cultured UPPL and BBN primary tumor cells as cell lines along with MB49 cancer cell lines and KT immortalized normal urothelial cell lines and implanted them back into mice as cell-line derived tumors. Overall design: RNASeq analysis was performed on 9 UPPL primary tumors, 11 BBN primary tumors, 1 UPPL cell line, 1 BBN cell line, 1 MB49 cell line, 3 KT cell lines, 4 UPPL cell-line derived tumors, 2 BBN cell-line derived tumors, and 4 MB49 cell-line derived tumors
Publication Title
Molecular Subtype-Specific Immunocompetent Models of High-Grade Urothelial Carcinoma Reveal Differential Neoantigen Expression and Response to Immunotherapy.
Sample Metadata Fields
Disease, Treatment, Subject
View Samples- Mus musculus
- 86 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Dynamic regulatory network controlling TH17 cell differentiation.
Sample Metadata Fields
Specimen part, Treatment
View Samples- Mus musculus
- 61 Downloadable Samples
- Illumina Genome Analyzer
Description
Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. Overall design: RNA-seq of knockdown of 12 genes in Th17 cell differentiation
Publication Title
Dynamic regulatory network controlling TH17 cell differentiation.
Sample Metadata Fields
Specimen part, Cell line, Treatment, Subject
View Samples- Mus musculus
- 58 Downloadable Samples
Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells.
Publication Title
Dynamic regulatory network controlling TH17 cell differentiation.
Sample Metadata Fields
Specimen part, Treatment
View Samples- Mus musculus
- 20 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells.
Publication Title
Dynamic regulatory network controlling TH17 cell differentiation.
Sample Metadata Fields
Specimen part, Treatment
View Samples- Homo sapiens
- 6 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
Chromosomal translocations affecting Mixed Lineage Leukemia (MLL) gene result in acute leukemias resistant to therapy. The leukemogenic activity of MLL fusion proteins is dependent on their interaction with menin, providing basis for therapeutic intervention. Here we report development of novel, highly potent and orally bioavailable small molecule inhibitors of the menin-MLL interaction, MI-463 and MI-503, show their profound effects in MLL leukemia cells and substantial survival benefit in mice models of MLL leukemia. Finally, we demonstrate efficacy of these compounds in primary samples derived from MLL leukemia patients. Overall, we demonstrate for the first time that pharmacologic inhibition of the menin-MLL interaction represents an effective treatment for MLL leukemias in vivo and provide advanced molecular scaffold for clinical lead identification.
Publication Title
Pharmacologic inhibition of the Menin-MLL interaction blocks progression of MLL leukemia in vivo.
Sample Metadata Fields
Cell line, Treatment
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