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SRP126295
Mus musculus
24 Downloadable Samples
Illumina HiSeq 1000
Description
We introduce an in vivo imaging approach that allows us to temporally and spatially resolve the evolution of iNOS and Arginase-positive phagocyte phenotypes in a murine MS model. We show that the polarization of individual phagocytes is established after CNS entry, is dependent on the CNS compartment and can be adapted as inflammatory lesions move from expansion to resolution. Our study thus provides a first real-time analysis of phagocyte specification in the intact CNS. Overall design: Cells were isolated from the Blood and CNS of Arginase-YFP X iNOS-Tomato-Cre mice at clinical onset of Experimental Autoimmune Encephalomyelitis. CD11b_high, CD45_low microglia cells and CD45_positive, CD115_positive, Ly6c_high monocytes were FACS sorted respectively. Total RNA was extracted from the separated populations.
Publication Title
Mononuclear phagocytes locally specify and adapt their phenotype in a multiple sclerosis model.
Sample Metadata Fields
Specimen part, Subject
View Samples- Mus musculus
- 55 Downloadable Samples
- Illumina HiSeq 3000
Description
The innate immune cell compartment is highly diverse in the healthy central nervous system (CNS) including parenchymal and non-parenchymal macrophages. However, this complexity is increased in inflammatory settings by the recruitment of circulating myeloid cells. It is unclear which disease-specific myeloid subsets exist and what their transcriptional profiles and dynamics during CNS pathology are. By combining deep single-cell transcriptome analysis, fate mapping, in vivo imaging, clonal analysis, and transgenic lines, we comprehensively characterized unappreciated myeloid subsets in several CNS compartments during neuroinflammation. During inflammation, CNS macrophage subsets undergo self-renewal, and random proliferation shifted towards clonal expansion. Finally, functional studies demonstrated that endogenous CNS tissue macrophages are redundant for antigen presentation. Our results highlight myeloid cell diversity and provide insights into the brain's innate immune system. Overall design: CD45+ cells isolated from different CNS compartments (including leptomeninges, perivascular space and parenchyma, and choroid plexus) and Ly6Chigh and Ly6Clow monocytes from blood were FACS-sorted in 384-well plates and used for scRNAseq. All myeloid cells were sorted from C57BL/6N mice with 8-10 weeks of age at naive stage or at different stages of Experimental Autoimmune Encephalomyelitis (preclinical, onset and peak of the disease). Data are representative of 16-18 mice from three independent experiments. mCEL-Seq2 protocol was used for single cell sequencing (Hashimshony et al. 2016, Herman et al. 2018).
Publication Title
Single-cell profiling identifies myeloid cell subsets with distinct fates during neuroinflammation.
Sample Metadata Fields
Age, Specimen part, Disease, Disease stage, Cell line, Subject
View Samples- Mus musculus
- 81 Downloadable Samples
Affymetrix Mouse Gene 2.1 ST Array (mogene21st)
Description
Recent studies have shown that tissue macrophages (MF) arise from embryonic progenitors of the yolk sac (YS) and fetal liver and colonize the tissues before birth. Further studies have proposed that developmentally distinct tissue MF can be identified based on the differential expression of F4/80 and CD11b, but whether a characteristic transcriptional profile exists is largely unknown. Here, we established an inducible fate mapping system that facilitated the identification of A2 progenitors of the YS as source of F4/80hi but not CD11bhi MF. Large-scale transcriptional profiling of MF precursors from the YS until adulthood allowed the description of a complex MF pedigree. We further identified a distinct molecular signature of F4/80hi and CD11bhi MF and found that Irf8 was vital for MF maturation and the innate immune response. Our data provide new cellular and molecular insights into the origin and developmental pathways of tissue MF.
Publication Title
Transcriptome-based profiling of yolk sac-derived macrophages reveals a role for Irf8 in macrophage maturation.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 24 Downloadable Samples
- Illumina HiSeq 2500, Illumina HiSeq 2000
Description
RNA-seq analysis was performed using RNA isolated from three tumor models (GL261 glioma, LLC Lewis lung carcinoma, B16F10 melanoma) implanted subcutaneousy in C57BL/6 mice, or in ICR scid mice. Mice were untreated or were treated with cyclophosphamide (CPA) given on a 6-day repeating metronomic schedule (CPA/6d), except as noted. Results from these global transcriptome analysis indicated substantial elevation of basal GL261 immune infiltration and strong activation by CPA/6d treatment of GL261 immune stimulatory pathways and their upstream regulators, but without preferential depletion of negative immune regulators compared to LLC and B16F10 tumors. In LLC tumors, where CPA/6d treatment was found to be anti-angiogenic, CPA/6d suppressed VEGFA target genes and down regulated cell adhesion and leukocyte transendothelial migration genes. In GL261 tumors implanted in adaptive immune-deficient scid mice, where CPA/6d-induced GL261 regression is incomplete and late tumor growth rebound can occur, T cell receptor signaling and certain cytokine-cytokine receptor responses seen in B6 mice were deficient. Extending the CPA treatment interval from 6 to 9 days (CPA/9d) - which results in a strong but transient natural killer cell response followed by early tumor growth rebound - induced fewer cytokines and increased expression of drug metabolism genes. Taken together, these findings elucidate molecular response pathways activated by intermittent metronomic CPA treatment and identify deficiencies that characterize immune-unresponsive tumor models and drug schedules. Overall design: RNA isolated from various tumor cell lines implanted s.c in C57BL/6 mice or scid mice, untreated or treated with cyclophosphamide (CPA) given on a metronomic schedule, were prepared and used for stranded or unstranded RNA-seq.
Publication Title
Metronomic cyclophosphamide activation of anti-tumor immunity: tumor model, mouse host, and drug schedule dependence of gene responses and their upstream regulators.
Sample Metadata Fields
No sample metadata fields
View Samples- 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- Homo sapiens
- 24 Downloadable Samples
- Illumina humanRef-8 v2.0 expression beadchip
Description
At least six histone H1 variants exist in mammalian somatic cells that bind to the linker DNA and stabilize the nucleosome particle contributing to higher order chromatin compaction. In addition, H1 seems to be involved in the active regulation of gene expression. It is not well known whether the different variants have specific roles or regulate specific promoters. We have explored this by inducible shRNA-mediated knock-down of each of the H1 variants in a human breast cancer cell line. A different subset of genes is altered in each H1 knock-down.
Publication Title
Depletion of human histone H1 variants uncovers specific roles in gene expression and cell growth.
Sample Metadata Fields
No sample metadata fields
View Samples