Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Functional analysis of KAI1

ABSTRACT: We sequenced mRNA from mouse EML cell line under Kai1 knockdown or Kai1 overexpressing condition. KAI1 belongs to tetraspanin superfamily and is known as suppressor of tumor metastasis. Examination of mRNA levels in wildtype (WT) and KAI1 knockdown EML cells were generated by deep sequencing, in duplicate, using Illumina GAIIx. Examination of mRNA levels in wildtype (WT) and KAI1 overexpressing EML cells were also generated in single set.

ORGANISM(S): Mus musculus

SUBMITTER: Tae-Young Roh

PROVIDER: E-GEOD-56867 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

CD82/KAI1 Maintains the Dormancy of Long-Term Hematopoietic Stem Cells through Interaction with DARC-Expressing Macrophages.

Hur Jin J Choi Jae-Il JI Lee Hwan H Nham Pniel P Kim Tae-Won TW Chae Cheong-Whan CW Yun Ji-Yeon JY Kang Jin-A JA Kang Jeehoon J Lee Sang Eun SE Yoon Chang-Hwan CH Boo Kyungjin K Ham Seokjin S Roh Tae-Young TY Jun Jong Kwan JK Lee Ho H Baek Sung Hee SH Kim Hyo-Soo HS

Cell stem cell 20160317 4

Hematopoiesis is regulated by crosstalk between long-term repopulating hematopoietic stem cells (LT-HSCs) and supporting niche cells in the bone marrow (BM). Here, we examine the role of CD82/KAI1 in niche-mediated LT-HSC maintenance. We found that CD82/KAI1 is expressed predominantly on LT-HSCs and rarely on other hematopoietic stem-progenitor cells (HSPCs). In Cd82(-/-) mice, LT-HSCs were selectively lost as they exited from quiescence and differentiated. Mechanistically, CD82-based TGF-β1/Sma ...[more]

PMID: 26996598

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Project description:Most adult patients have a D816V mutation in phosphotransferase domain (PTD), we have described that half of the children carry mutations in extracellular domain (ECD). KIT-ECD versus IT-PTD-mutants were introduced into rodent Ba/F3, EML, Rat2 and human TF1 cells to investigate their biological effect. ECD- and PTD-mutants also displayed distinct whole-genome transcriptional profiles in EML cells. We observed differences in their signaling properties: they both activated STAT pathways, whereas AKT pathway was only activated by ECD-mutants. Consistently, AKT inhibitor suppressed ECD-mutant-dependent proliferation, clonogenicity and erythroid differentiation. Expression of myristoylated AKT restored erythroid differentiation in EMLPTD cells, suggesting the differential role of AKT in those mutants. Overall, our study implied different pathogenesis of pediatric versus adult mastocytosis, which might explain their diverse phenotypes. Each EML cell line (Del417-419insY mutant and D816V mutant) was cultured with or without 250 ng/mL SCF for 48h. Gene expression profile analysis was performed using whole-genome microarrays. RNA expression profiling of cell lines was done with Affymetrix M430 2.0 mouse oligonucleotide microarrays containing 45.101 probe sets, representing 21.408 transcripts and variants including 17.482 well-characterized mouse genes. Preparation of cRNA, hybridizations, washes, detection and quantification were done as recommended by the supplier. For each sample, synthesis of the first-strand cDNA was done from 3 μg total RNA by T7-oligo(dT) priming, followed by second-strand cDNA synthesis. After purification, in vitro transcription associated with amplification generated cRNA-containing biotinylated pseudouridine. Biotinylated cRNA was purified, quantified and chemically fragmented (95°C for 35 min), then hybridized to microarrays in 200 μL hybridization buffer at 45°C for 16 h. Automated washes and staining with streptavidin-phycoerythrin were done as recommended. Signal amplification was done by biotinylated antistreptavidin antibody with goat-IgG blocking antibody. Scanning was done with Affymetrix GeneArray scanner and quantification with Affymetrix GCOS software.

Project description:During commitment of a multipotent stem or progenitor cell to a particular lineage, a large number of genes alter their expression in a coordinated manner orchestrated by the gene regulatory network (GRN). The constraints imposed by the GRN govern how cells move in the high-dimensional gene expression state space and can be understood as a dynamical system in which phenotypic cell states (cell types) are attractors that stabilize the cell-type characteristic gene expression pattern against molecular noise. Despite insights from various theoretical models, it remains elusive how multipotent cells, when committing to a specific lineage, exit their attractor and enter a new distinct attractor. Here we show, using single-cell resolution monitoring of transcript patterns by qPCR that commitment of multipotent blood progenitor cells to either the erythroid or the myeloid lineage is preceded by a destabilization of the progenitorsâ?? attractor state and a slowing-down of relaxation of cells from outlier states, indicating a critical state transition (â??tipping pointâ??). The high-dimensionality of the system (many genes) and availability of individual trajectories of a large ensemble of systems (many cells) affords a novel signature for critical transition which can be predicted from theory: Decrease of correlation between cells and concomitant increase of correlation between genes as the cell population approaches the tipping point. Consistent with a destabilizing bifurcation that simultaneously opens access to the erythroid and myeloid attractors, differentiation signal for either lineage caused some cells to commit to the â??wrongâ?? fate; moreover providing conflicting signals resulted in a delayed decision at the bifurcation point that however was ultimately resolved by commitment to one fate. These results suggest that the theoretical framework of â??early-warning signsâ?? and critical transitions can be applied to ensembles of high-dimensional systems, offering a formal tool for analyzing single-cell omics data beyond current descriptive computational pattern recognition. Mouse blood progenitor cells (EML cell line) was exposed to EPO, IL-3/GM-CSF or a mixture of both cytokines and gene expression change was measured in sorted subpopulations wrt Sca1 progenitor surface marker expression. In total, there was 4 conditions (including control), three time points (including d0) and 20 samples (10 samples in duplicates) were analyzed. Two independent experiments were performed for each condition. The untreated progenitor cell population was used as control.

Dataset Information

Functional analysis of KAI1

Publications

CD82/KAI1 Maintains the Dormancy of Long-Term Hematopoietic Stem Cells through Interaction with DARC-Expressing Macrophages.

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