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Comparative genome-wide analysis of human BM IL3Rα-high precursors show a more MΦ-, DC- and OC committed gene expression profile, as compared to IL3Rα-low precursors

ABSTRACT: To clarify the lineage relationship between IL3Rαhigh- and IL3Rαlow precursor cells and to find potential molecules involved in their differentiation, we compared the IL3Rαhigh- and IL3Rαlow precursor populations from three independent donors by mRNA deep sequencing and used the Ingenuity Pathway Analysis (IPA)- and Multi-experimental Viewer (MeV) to analyze the differentially expressed genes (p<0.001). Analysis of the protein coding genes showed that the samples from IL3Rαhigh precursor cells clustered together, as did the IL3Rαlow samples. This indicated that the gene expression patterns of these cells are likely to be conserved. Further analysis revealed a list of (649) differentially expressed molecules between the two populations. Among these, most notably, genes involved in the differentiation of cell in general, amongst which differentiation of MΦ, OC and antigen presenting cells appeared to be activation increased. Examination of two hematopoietic precursor populations in human BM

ORGANISM(S): Homo sapiens

SUBMITTER: yanling xiao

PROVIDER: E-GEOD-65996 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Comparative genome-wide analysis of human BM IL3Rα-high precursors show a more MΦ-, DC- and OC committed gene expression profile, as compared to IL3Rα-low precursors

Project description:To clarify the lineage relationship between IL3Rαhigh- and IL3Rαlow precursor cells and to find potential molecules involved in their differentiation, we compared the IL3Rαhigh- and IL3Rαlow precursor populations from three independent donors by mRNA deep sequencing and used the Ingenuity Pathway Analysis (IPA)- and Multi-experimental Viewer (MeV) to analyze the differentially expressed genes (p<0.001). Analysis of the protein coding genes showed that the samples from IL3Rαhigh precursor cells clustered together, as did the IL3Rαlow samples. This indicated that the gene expression patterns of these cells are likely to be conserved. Further analysis revealed a list of (649) differentially expressed molecules between the two populations. Among these, most notably, genes involved in the differentiation of cell in general, amongst which differentiation of MΦ, OC and antigen presenting cells appeared to be activation increased.

2015-04-28 | GSE65996 | GEO

Lineage-committed osteoclast precursors circulate in blood and settle down into bone

Project description:Osteoclasts are derived from the monocyte/macrophage lineage, but little is known about osteoclast precursors in circulation. Bone marrow cells were subdivided into three populations; RANKhighFmslow, RANKhighFmshigh and RANKlowFmshigh. GeneChip analysis confirmed that the expression levels of monocyte-macrophage markers such as Emr1 (F4/80), Itgam (CD11b) and Csf1 (c-Fms) were lower in the RANKhighFmslow than RANKlowFmshigh population. In contrast, cells in the RANKhighFmslow population expressed higher levels of osteoclast markers such as Car ll (carbonic anhydrase ll), Mmp9 (matrix metalloproteinase 9), Acp5 (acid phosphatase 5) and Tfrc (transferrin receptor). These results suggest that RANKhighFmslow cells express few of the phenotypes of monocytes, and their differentiation into osteoclasts occurs at a slightly more advanced stage than that of the RANKlowFmshigh population. RANKhighFmslow cells and RANKlowFmshigh cells were isolated from bone marrow in ddY mice by FACS (Fluorescent activated cell sorting). Differential expression levels of mRNA were determined by GeneChip analysis.

2012-01-07 | E-GEOD-26499 | biostudies-arrayexpress

Gene expression profiles of E8.5, E9.5 and E11.5 kidney precursors

Project description:Understanding processes how the early stage kidney precursor gives rise to metanephric mesenchyme, which is a committed progenitor cells of adult kidney is important for the regeneration of kidney in vitro. The combination of fluorescent activated cell sorting (FACS) plus microarray analysis offers a powerful, efficient and effective method for the creation of global gene expression profiles of the developing kidney precursors. Those gene expression data provides insights into not only the stage specific marker genes but also the signals working in each population, which should be informative for the directed differentiation of pluripotent stem cells in vitro. Osr1-GFP knock-in mice were used to isolate kidney precursor cells from embryos at E8.5, E9.5 and E11.5. At E9.5 and E11.5 embryos, to identify the differences between nephron progenitors and surrounding mesenchyme, nephron progenitor populations were further enriched by gating Osr1-GFP positive Integrin alpha8 positive Pdgfr alpha negative population and compared with Osr1-GFP positive cells other than that gate. RNA was isolated from cells and the gene expression profiles were determined by microarrays.

2015-01-13 | E-GEOD-51054 | biostudies-arrayexpress

Lineage-committed osteoclast precursors circulate in blood and settle down into bone

2012-01-07 | GSE26499 | GEO

Multipotent Schwann cell precursors generate steroid-producing cells of the adrenal cortex and chromaffin cells of the adrenal medulla

Project description:Multipotent stem cells are considered as promising biological tools for regenerative medicine, and transcriptome analysis of these cells is fundamental for identifying new factors controlling proliferation versus differentiation. To obtain a comprehensive characterization of adrenal progenitors, we have developed an analytical pipeline relying on flow cytometric sorting of living cells followed by RNA sequencing. This analysis showed that two distinct populations of Nestin-positive progenitors are located in the adrenal cortex and medulla, respectively. Though 1039 genes were differentially regulated, both populations showed Schwann cell precursor properties suggesting both populations to be neural crest-derived.

2023-01-04 | GSE140247 | GEO

Identification of tissue regulatory T cell precursors in lymphoid organs [scRNA]

Project description:Regulatory T (Treg) cells maintain self-tolerance in lymphoid tissues, and specialized Treg cells accumulate and perform homeostasis and regenerative functions in non-lymphoid tissues. A common differentiation pathway of homeostasis-promoting Treg cells in non-lymphoid tissues from a putative precursor remains elusive. By using novel reporter mice and single-cell RNA-sequencing, we identified precursor stages of the IL-33 receptor ST2-expressing non-lymphoid tissue Treg population in spleen and lymph nodes. Molecular profiling of these precursors versus mature tissue Treg cells revealed their sequence of differentiation on a single-cell level. Global chromatin profiling of non-lymphoid tissue Treg cells and progenitor populations revealed a stepwise acquirement of open chromatin accessibility at tissue Treg genes. Mechanistically, we identified and validated the basic leucine zipper transcription factor, ATF-like (Batf) as a driver of the molecular tissue Treg program. Understanding this tissue program will help to harness regenerative properties of tissue Treg cells for therapy.

2020-01-01 | GSE130879 | GEO

Single Cell Transcriptomics Reveals Multi-Dimensional Heterogeneity in Early Hematopoietic Precursors

Project description:Hematopoietic stem cells (HSCs) and multipotent progenitors (MPPs) are at the apex of the hematopoietic hierarchy. The relationship among HSC and MPPs, their heterogeneity and regulation are challenging subjects of continuing study. We performed single-cell RNA-seq on HSC and their immediate progeny MPP1 cells and compared results with bulk RNA-seq data from 18 hematopoietic populations, literature compilations of cell cycle-related genes, lineage specific genes, and putative quiescence genes. HSC and MPP1 were separated into several distinct subsets including actively cycling, quiescent and a putative hibernating subset. The quiescent cells preferentially expressed lymphoid precursor genes, while in actively cycling cells, the relative level of genes specific for individual lineages were differently correlated with stages of cell cycle. Granulocytic/monocytic and megakaryocytic precursor mRNA levels rose in early G1 phase, while erythroid specific expression showed selective augmentation at the G2/M phase. Stimulation of erythropoiesis shifted most HSCs into the active cell fraction without a disproportionate increase in the expression of early erythroid genes. Most transcription factors of the hematopoietic lineages were randomly expressed in a number of the early precursor cells but certain transcription factor mRNAs were detected only in very few cells. The latter genes may act as valves controlling the flow of differentiation. In summary we detect multi-level heterogeneity of the earliest hematopoietic precursor cells, demonstrate novel lineage specific cell cycle effects on the expression of precursor genes, and find that key regulatory genes for stages of differentiation can be identified from their silencing in stem cells.

2016-12-24 | GSE68981 | GEO

Identification of tissue regulatory T cell precursors in lymphoid organs [ATAC-Seq]

2020-01-01 | GSE130825 | GEO

Identification of tissue regulatory T cell precursors in lymphoid organs [scTCR-seq]

2020-01-01 | GSE130875 | GEO

Discrete subsets of myogenic and mesenchymal precursors give rise to soft tissue sarcomas of distinct lineage differentiation

Project description:This work examines sarcoma formation within discrete subsets of KRAS(G12V)-expressing p16p19null myogenic and mesenchymal cells found normally in skeletal muscle. We show that prospectively isolated skeletal muscle precursor cells (SMPs) within the satellite cell pool can serve as cancer cells-of-origin for mouse rhabdomyosarcomas (soft tissue sarcomas with features of myogenic differentiation). Alternatively, non-myogenic progenitors (ScaPCs) induce sarcomas lacking myogenic differentiation markers. We used Affymetrix whole mouse genome 430 2.0 microarrays to gain deeper insights into the molecular underpinnings of the three types of KRAS; p16p19null mouse soft-tissue sarcomas (originating from SMPs, ScaPCs and CD45-MAC1-TER119-Sca1-CXCR4- cells). Four replicates of each type.

2011-11-10 | E-GEOD-22841 | biostudies-arrayexpress

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