SINGLE CELL RNA SEQUENCING IDENTIFIES IGFBP5 AND QKI
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ABSTRACT:
PROVIDER: PRJNA704098 | ENA |
REPOSITORIES: ENA
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Project description:Whole lung tissue transcriptomic profiling studies in chronic obstructive pulmonary disease (COPD) have led to the identification of several genes associated with the severity of airflow limitation and/or the presence of emphysema, however, the cell types driving these gene expression signatures remain unidentified. T-distributed stochastic neighbor embedding and clustering of scRNA seq data revealed a total of 17 distinct populations. Among them, the populations with more differentially expressed genes in cases vs. controls (log fold change >|0.4| and FDR=0.05) were monocytes (n=1499); macrophages (n=868) and ciliated epithelial cells (n= 590), respectively. Using GSEA, we found that only ciliated and cytotoxic T cells manifested a trend towards enrichment of the previously reported 127 regional emphysema gene signatures (normalized enrichment score [NES] = 1.28 and =1.33, FDR= 0.085 and =0.092 respectively). Among the significantly altered genes present in ciliated epithelial cells of the COPD lungs, QKI and IGFBP5 protein levels were also found to be altered in the COPD lungs.
2022-02-12 | GSE167295 | GEO
Project description:BackgroundWhole lung tissue transcriptomic profiling studies in chronic obstructive pulmonary disease (COPD) have led to the identification of several genes associated with the severity of airflow limitation and/or the presence of emphysema, however, the cell types driving these gene expression signatures remain unidentified.MethodsTo determine cell specific transcriptomic changes in severe COPD, we conducted single-cell RNA sequencing (scRNA seq) on n = 29,961 cells from the peripheral lung parenchymal tissue of nonsmoking subjects without underlying lung disease (n = 3) and patients with severe COPD (n = 3). The cell type composition and cell specific gene expression signature was assessed. Gene set enrichment analysis (GSEA) was used to identify the specific cell types contributing to the previously reported transcriptomic signatures.ResultsT-distributed stochastic neighbor embedding and clustering of scRNA seq data revealed a total of 17 distinct populations. Among them, the populations with more differentially expressed genes in cases vs. controls (log fold change >|0.4| and FDR = 0.05) were: monocytes (n = 1499); macrophages (n = 868) and ciliated epithelial cells (n = 590), respectively. Using GSEA, we found that only ciliated and cytotoxic T cells manifested a trend towards enrichment of the previously reported 127 regional emphysema gene signatures (normalized enrichment score [NES] = 1.28 and = 1.33, FDR = 0.085 and = 0.092 respectively). Among the significantly altered genes present in ciliated epithelial cells of the COPD lungs, QKI and IGFBP5 protein levels were also found to be altered in the COPD lungs.ConclusionsscRNA seq is useful for identifying transcriptional changes and possibly individual protein levels that may contribute to the development of emphysema in a cell-type specific manner.
| S-EPMC8022543 | biostudies-literature
Project description:Transcriptomic profiling of WT and QKI KO hESC derived cardiomyocyte on Day 6 and 15 via Single cell RNA-seq.
2020-10-19 | GSE144009 | GEO
Project description:Transcription profiling by array of siRNA against Quaking (QKI) transcripts to identify transcripts that are modulated by QKI activity. MiR-155 is an oncogene and we report here that it targets QKI transcripts. Therefore, we believe that QKI acts as a tumor suppressor gene in different leukemias. We ablated the expression of QKI transcripts using siRNAs in order to further elucidate the effects of QKI in leukemogenesis, and how miR-155 and QKI functionally interact with each other.
2016-01-17 | E-MTAB-2375 | biostudies-arrayexpress
Project description:To identify QKI targets, we performed QKI knockdown in BEAS2B cells and analyzed alternative splicing patterns by high-throughput RNA sequencing. The mRNA profiles of control- and QKI-knockdown BEAS2B cells were generated by deep sequencing using Illumina GAIIx sequencer.
2014-04-14 | E-GEOD-55215 | biostudies-arrayexpress
Project description:To assess whether the transcripts identified by PAR-CLIP are regulated by the RNA-binding protein (RBP) Quaking (QKI), we analyzed the mRNA levels of mock-transfected and QKI-specific siRNA-transfected cells with microarrays. Transcripts crosslinked to QKI were significantly upregulated upon siRNA transfection, indicating that QKI negatively regulates bound mRNAs (Figure 3H of PMID 20371350), consistent with previous reports of QKI being a repressor. The RBP QKI was depleted by siRNAs and the expression level was compared to mock-transfected HEK 293 cells.
2010-05-27 | E-GEOD-21574 | biostudies-arrayexpress
Project description:Quaking RNA binding protein(QKI) is essential for oligodendrocyte development as myelination requires MBP mRNA regulation and localization to distal processes by its cytoplasmic isoforms(e.g. QKI-6). QKI-6 is also highly expressed in astrocytes, which we and others recently demonstrated have regulated mRNA localization. Here, we show via CLIPseq that QKI-6 binds 3’UTRs of a subset of astrocytic mRNAs, including many enriched in peripheral processes. Binding is enriched near stop codons, which is mediated partially by QKI binding motifs(QBMs) yet spreads to adjacent sequences. We developed CRISPR TRAPseq: a viral approach for mosaic, cell-type specific gene mutation with simultaneous translational profiling. This enabled study of QKI-6 CLIP targets in QKI-deleted astrocytes in an otherwise normal brain. Astrocyte-targeted QKI deletion altered translation and maturation, while also increasing synaptic density within the astrocyte's territory. Overall, our data indicate QKI is required for astrocyte maturation and demonstrate an approach for a highly targeted translational assessment of gene knockout in specific cell-types in vivo.
2021-01-21 | GSE146935 | GEO
Project description:This study was designed to look for the RNAs that directly bind with QKI
2016-11-10 | GSE84132 | GEO
Project description:Purpose:RNA_sequencing analysis defined a novel role for the QKI in microglia Methods: microglia mRNA profiles of 4-6 weeks-old wild-type (QKIfl/fl) and microglia specific knockout (QKIfl/fl; cx3r1cre-ert2) mice were generated by Illumina HiSeq 4000 in triplicate. The sequence reads that passed quality filters were trimmed with Trimmomatic v0.39. STAR v2.7.1a was then used to align the reads to the mouse genome (mm10/GRCm38). Gene expression was quantified across all samples with HOMER v4.11.1, and the normalization was carried out through the regularized logarithm (rlog) transformation of DESeq2 v1.26.0. Differential expression between the WT and knockout samples were calculated through DESeq2 v1.26.0, and the gene expression was considered significantly different if the absolute value of the log-fold-change (LFC) was higher than 2, the base means larger than 10 and the false discovery rate (FDR) less than 0.05. Results: RNA-seq data revealed the up-regulation of 326 genes and down-regulation of 294 genes in knockout microglia compare to wt (2-fold change at FDR of 0.05, base mean>10). In particular qkICx3cr1-KO microglia exhibited higher expression of genes that are known to encode proteins related to inflammation (Il-6, Apoe, Cxcl-10, Il-1b, Il-12b, and Tnf). In line with this, functional annotation by DAVID, Reactome and, GO analysis showed enrichment of cell cycle and inflammation-related pathways in the up-regulated transcripts in qkICx3cr1-KO mice. Up-regulated transcripts were further validated using qRT-PCR. Conclusions: Our study represents the first detailed analysis of microglia transcriptomes without QKI expression, with biologic replicates, generated by RNA-seq technology. The data should provide how QKI modulates the microglia gene expression profiles in genome-wide detail.
2020-10-30 | GSE156118 | GEO
Project description:QKI is required for myelin formation in the verterbrate brain. It functions by binding RNA and regulating its stability, translation, and/or aternative splicing. We have used Affymetrix exon arrays to assess changes in gene expression in response to QKI knockdown on an exon level in rat CG-4 oligodendrocyte precursor cells. Knockdown cells were compared to control cells. Knockdown groups included QKI siRNA transfection, QKI shRNA stable transfection, and hnRNP A1 transient transfection. Control groups consisted of untransfected, control siRNA transfection, control shRNA stable transfection. Each group was analyzed in triplicate.
2011-01-20 | E-GEOD-26716 | biostudies-arrayexpress