Immune Variation Project (ImmVar) [CD14]
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE56034 | GEO | 2014/05/02
SECONDARY ACCESSION(S): PRJNA242430
REPOSITORIES: GEO
Similar Datasets
Project description:Gene expression profiling of Monocytes (CD14+CD16-) from human peripheral blood mononuclear cells (PBMCs). PBMCs were isolated from healthy individuals from the Boston area. Over the course of 18 months, fresh blood samples from healthy participants were collected following a rigorous, standardized set of procedures (SOP). 15ml of blood was collected and used to isolate peripheral blood mononuclear cells (PBMCs). From the PBMCS, cell population of interest, CD14+CD16-, underwent a two-step sorting strategy in order to achieve cell purity >99%. mRNAs from these cells were profiled on Affymetrix GeneChip Human Gene ST 1.0 microarrays. Raw data CEL files were processed using the Robust Multichip Average (RMA) algorithm in Affymetrix PowerTools. To account for non-genetic factors such as batch effects, age, gender, and technical artifacts in gene expression data, we used Principal Component Analysis (PCA). PCs were estimated separately from the gene expression matrix for each population. The optimal numbers of PCs for association analysis were determined based on the PC that resulted in maximum number of cis-eQTLs. This procedure identified 20, 10, and 14 PCs in EU, EA and AA monocytes, respectively. GSE56034_GSM.ImmVarCD14.*.PC*.txt supplementary files: For each population EU, AA, and EA, individual PC-corrected matrices for samples that have passed both Expression QC and Genotyping QC. These are the same expression matrices that were used for the eQTL association analysis.
2014-05-02 | E-GEOD-56034 | biostudies-arrayexpress
Project description:Gene expression profiling of CD4 T-Cells (CD4+CD62L+) from human peripheral blood mononuclear cells (PBMCs). PBMCs were isolated from healthy individuals from the Boston area.
2014-05-02 | GSE56033 | GEO
Project description:In this study gene expression of human blood classical monocytes (CD14++CD16-), CD16 positive monocytes (consisting of non-classical CD14+16++ and intermediate CD14++CD16+ monocytes) and CD1c+ CD19- dendritic cells from healthy subjects were investigated. Keywords: expression profiling by array
2011-12-17 | GSE34515 | GEO
Project description:Human and mouse monocytes can be divided into 2 different sub-populations, using CD14-CD16 and Ly6C-CX3CR1 respectively. We investigated the pig monocytes sub-populations and found that all porcine monocyte express CD16 and CD172M-NM-1 but can be divided into 2 subpopulation using CD14 and the scavenger receptor CD163. The CD14hi-CD163low population resemble to the inflammatory monocytes whereas the CD14low-CD163hi display more a resident monocyte type. Pig monocyte can be differentiated into macrophages when cultured with rhCSF-1 and show an increase in size, granularity and autofluorescence, and express the common macrophage markers CD14, CD16 and CD172M-NM-1. Gene expression in these 2 sub-populations was profiled using the newly-developed and annotated pig whole genome snowball microarray, showing a distinct pattern between inflammatory and resident monocytes but this difference would be more a maturation process instead of two separate subsets. Furthermore, the expression of certain genes such as CD36, CLEC4E or TREM-1 proved to share the same pattern as human monocytes, quite different from mouse monocytes. These results emphasize the potential role of the pigs as a model for human inflammatory disease and will improved our knowledge on the mononuclear phagocyte system development. Porcine PBMCs were isolated from the blood of three seperate pigs, FACS sorted on expression of CD14 and CD163 and RNA isolated from each sample, a total of 6 microarrays were hybridised
2013-02-14 | E-GEOD-43898 | biostudies-arrayexpress
Project description:Monocytes are a heterogeneous cell population with subset-specific functions and phenotypes. The differential expression of CD14 and CD16 distinguishes classical CD14++CD16-, intermediate CD14++CD16+ and non-classical CD14+CD16++ monocytes. However, CD14++CD16+ monocytes remain the most poorly characterized subset so far. Therefore we analyzed the transcriptomes of the three monocyte subsets using SuperSAGE in combination with high-throughput sequencing. Analysis of 5,487,603 tags revealed unique identifiers of CD14++CD16+ monocytes, delineating these cells from the two other monocyte subsets. CD14++CD16+ monocytes were linked to antigen processing and presentation (e.g. CD74, HLA-DR, IFI30, CTSB), to inflammation and monocyte activation (e.g. TGFB1, AIF1, PTPN6), and to angiogenesis (e.g. TIE2, CD105). Therefore we provide genetic evidence for a distinct role of CD14++CD16+ monocytes in human immunity. Human monocyte subsets (CD14++CD16-, CD14++CD16+, CD14+CD16++) were isolated from 12 healthy volunteers based on MACS technology. Total RNA from monocyte subsets was isolated and same aliquots from each donor and monocyte subset were matched for SuperSAGE. Three SuperSAGE libraries (CD14++CD16-, CD14++CD16+ and CD14+CD16++) were generated.
2011-07-24 | E-GEOD-30811 | biostudies-arrayexpress
Project description:Monocytes are a heterogeneous cell population with subset-specific functions and phenotypes. The differential expression of CD14 and CD16 distinguishes classical CD14++CD16-, intermediate CD14++CD16+ and non-classical CD14+CD16++ monocytes. However, CD14++CD16+ monocytes remain the most poorly characterized subset so far. Therefore we analyzed the transcriptomes of the three monocyte subsets using SuperSAGE in combination with high-throughput sequencing. Analysis of 5,487,603 tags revealed unique identifiers of CD14++CD16+ monocytes, delineating these cells from the two other monocyte subsets. CD14++CD16+ monocytes were linked to antigen processing and presentation (e.g. CD74, HLA-DR, IFI30, CTSB), to inflammation and monocyte activation (e.g. TGFB1, AIF1, PTPN6), and to angiogenesis (e.g. TIE2, CD105). Therefore we provide genetic evidence for a distinct role of CD14++CD16+ monocytes in human immunity.
2011-07-24 | GSE30811 | GEO
Project description:Identification of genes differentially expressed between human CD14+CD16- and CD16+ monocyte-derived macrophages generated in the presence of either GM-CSF (termed GM14 and GM16, respectively) or M-CSF (termed M14 and M16, respectively) Human peripheral CD14+CD16- and CD16+ blood monocytes from three independent healthy donors (D1, D2 and D3) were isolated by positive selection from peripheral blood mononuclear cells (PBMC) using magnetic separation systems (MACS, Miltenyi Biotec). Briefly, PBMC were first incubated with MACS anti-CD56 antibody conjugated to paramagnetic microbeads in order to eliminate the NK (CD16+) cell fraction. NK-depleted PBMC were further incubated with MACS anti-CD16 antibody to isolate CD16+ monocytes. CD56-CD16- PBMC were finally incubated with MACS anti-CD14 antibody to obtain the CD14+CD16- monocyte fraction. Monocytes were cultured for 7 days in medium containing either GM-CSF or M-CSF. Total RNA from each condition was extracted using the RNeasy kit (Qiagen) and hybridized to an Agilent Human Whole Genome (4x44) Oligo Microarray. All experimental procedures were performed following manufacturer instructions.
2015-04-21 | E-GEOD-68061 | biostudies-arrayexpress
Project description:The new official nomenclature subdivides human monocytes into three subsets, classical (CD14++CD16-), intermediate (CD14++CD16+) and nonclassical (CD14+CD16+). Here, we comprehensively define relationships and unique characteristics of the three human monocyte subsets using microarray and flow cytometry analysis. Our analysis revealed that the intermediate and nonclassical monocyte subsets were most closely related. For the intermediate subset, majority of genes and surface markers were expressed at an intermediary level between the classical and nonclassical subset. There features therefore indicate a close and direct lineage relationship between the intermediate and nonclassical subset. From gene expression profiles, we define unique characteristics for each monocyte subset. Classical monocytes were functionally versatile, due to the expression of a wide range of sensing receptors and several members of the AP-1 transcription factor family. The intermediate subset was distinguished by high expression of MHC class II associated genes. The nonclassical subset were most highly differentiated and defined by genes involved in cytoskeleton rearrangement that explains their highly motile patrolling behavior in vivo. Additionally, we identify unique surface markers, CLEC4D, IL-13RA1 for classical, GFRA2, CLEC10A for intermediate and GPR44 for nonclassical. Our study hence defines the fundamental features of monocyte subsets necessary for future research on monocyte heterogeneity. Three human monocyte subsets, the CD14++CD16- classical, the CD14++CD16+ intermediate and CD14+CD16+ nonclassical subsets were purified using fluorescence activated cell sorting from peripheral blood mononuclear cells. RNA was processed from the three monocyte subsets from 4 individual donors in duplicates, giving a total of 24 samples.
2011-05-01 | E-GEOD-25913 | biostudies-arrayexpress
Project description:Gene expression profiling of CD4 T-Cells (CD4+CD62L+) from human peripheral blood mononuclear cells (PBMCs). PBMCs were isolated from healthy individuals from the Boston area. Over the course of 18 months, fresh blood samples from healthy participants were collected following a rigorous, standardized set of procedures (SOP). 15ml of blood was collected and used to isolate peripheral blood mononuclear cells (PBMCs). From the PBMCS, cell population of interest, CD4+CD62L+, underwent a two-step sorting strategy in order to achieve cell purity >99%. mRNAs from these cells were profiled on Affymetrix GeneChip Human Gene ST 1.0 microarrays. Raw data CEL files were processed using the Robust Multichip Average (RMA) algorithm in Affymetrix PowerTools. To account for non-genetic factors such as batch effects, age, gender, and technical artifacts in gene expression data, we used Principal Component Analysis (PCA). PCs were estimated separately from the gene expression matrix for each population and cell type. The optimal numbers of PCs for association analysis were determined based on the PC that resulted in maximum number of cis-eQTLs. This procedure identified 20, 12 and 12 PCs in EU, EA and AA CD4+ T-cells, respectively. GSE56033_GSM.ImmVarCD4.*.PC*.txt supplementary files: For each population EU, AA, and EA, individual PC-corrected matrices for samples that have passed both Expression QC and Genotyping QC. These are the same expression matrices that were used for the eQTL association analysis.
2014-05-02 | E-GEOD-56033 | biostudies-arrayexpress
Project description:Serum-free Fibrocytes, Serum-containing Fibrocytes, CD14++CD16- Monocytes, CD14++CD16+ Monocytes, CD14+CD16++ Monocytes, Macrophages were all generated from up to 3 biological replicates from each of 3 separate donors. RNA was extracted (Ambion RNAqueous), labelled with cy3, mixed with cy5 labelled human reference (Stratagene), and hybridised to slides printed with Human AROS v4.0 oligonucleotides (Operon). Slides were scanned using a Perkin Elmer GX plus, and the data then normalised with GEPAS v4.0 and collated. Final data analysis was carried out using TMEV 4.0. SAM was performed using a 0.1% FDR. PCA were plotted from this list, and interrogation carried out using DAVID to determine pathway enrichment.
2011-01-01 | E-MEXP-2811 | biostudies-arrayexpress