Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

RNA Sequencing Analysis of Gene Expression Profiles in WT and CIC-deficient DP Thymocytes

ABSTRACT: Purpose : The goal of this study is to compare the gene expression profiles between wild-type (WT) and CIC-deficient DP thymocytes to understand the molecular mechanisms of CIC regulation of T cell development, especially in DP thymocytes. Methods : DP thymocytes (lin-CD4+CD8+TCRlo (Lineage : CD11b, CD11c, CD19, NK1.1, Gr-1, γδTCR, and TER119)) from thymus were sorted by a MoFlo-XDP (Beckman Coulter). Total RNA was extracted using RiboEX (GeneAll) according to the manufacturer's instructions. The library for mRNA sequencing was generated using the TruSeq Stranded Total RNA LT Sample Prep Kit (Illumina) and sequencing was performed with NovaSeq 6000 (Illumina). Results : Trimmed reads were mapped to the mouse reference genome (mm10 RefSeq) with HISAT2, and the transcripts were assembled using StringTie. A total of 482 differentially expressed genes (DEGs; fold change > 2 and P-value < 0.05) were generated using edgeR. The 263 upregulated genes included known CIC target genes such as Etv1, Etv4, Etv5, Spry4, Spred1, Dusp4, and Dusp6. Conclusions : Our study represents the first comparative analysis of DP thymocytes from WT and hematopoietic lineage cell-specific Cic deficient mice. We concluded that CIC deficiency leads to impaired positive and negative selection, and TCR signaling in DP cells. The attenuation of TCR signaling is caused by derepression of CIC target genes involved in dephosphorylation of ERK.

ORGANISM(S): Mus musculus

PROVIDER: GSE173909 | GEO | 2021/05/06

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

RNA Sequencing Analysis of Gene Expression Profiles in Cic-null B-1a and Follicular B (Fo B) cells

Project description:Purpose: The goal of this study is to compare and examine the transcriptional profiles in control versus Cic-deficient B cells, specifically splenic B-1a and Fo B cells, by mRNA sequencing. Methods: Splenic B-1a (IgM+, CD19+, CD5+, CD43+) and Fo B (B220+, CD93-, CD23+, CD21lo-mid) cells were sorted by a MoFlo-XDP (Beckman Coulter). Total RNA was extracted using TRIzol Reagent (GeneAll), according to the manufacturer’s instructions. The DNA library for mRNA sequencing was generated using SMART-seq v4 Ultra Input RNA Kit (Clontech, for B-1a cells) and TruSeq RNA Sample Prep Kit v2 (Illumina, for Fo B cells). DNA libraries were multiplexed and pooled for sequencing on the Illumina Hiseq 4000 platform. Results: Trimmed reads were mapped to mouse reference genome (mm10 RefSeq) with HISAT2, a splice-aware aligner, and transcripts were assembled by StringTie with aligned reads, for known transcripts, novel transcripts, and alternatively spliced transcripts. A total of 712 genes were differentially expressed in Cic-null B-1a cells (325 upregulated and 387 downregulated), while 357 genes were differentially expressed in Cic-deficient Fo B cells (180 upregulated and 178 downregulated) when compared with their respective control cells (fold change >1.2 and P < 0.05). Several known CIC target genes, including Etv1, Etv4, Etv5, Spry4, Spred1, Spred2, Dusp4, Dusp6, and Per2, were included in the list of the upregulated differentially expressed genes (DEGs) in either Cic-null B-1a or Fo B cells or both, validating the reliability of RNA sequencing results. Conclusions: Our study presents the first comparative gene expression analysis of B-1a and Fo B cells from control and B cell-specific Cic-deficient mice. We concluded that CIC deficiency promotes B-1a cell development through enhancing the BCR signaling pathway. The data reported here also provide references for the gene expression profiles of murine B-1a and Fo B cells.

2021-12-16 | GSE163455 | GEO

RNA Sequencing Analysis of T Cell Receptor Alpha and Beta Chain in Thymic WT versus CIC-deficient CD4+ SP Non-Treg and Treg Cells.

Project description:Purpose : The goal of this study is to compare the repertoire of T cell receptor (TCR) alpha and beta chain between WT and CIC-deficient thymic CD4+ single positive (SP) T cells, in both non-Treg and Treg populations, to confirm the effect of CIC deficiency on T cell development in the aspect of TCR repertoire. Methods : Treg (CD4+CD8-CD25+GFP+) and non-Treg (CD4+CD8-GFP-) cells from Foxp3-GFP;Cicf/f and Foxp3-GFP;Cicf/f;Vav1-Cre mice were sorted by MoFlo-XDP (Beckman Coulter). Total RNA was extracted using RiboEX (GeneAll) according to the manufacturer's instructions. RNA was then amplified using a commercially available multiplex primer mix covering the TCR alpha and beta chains in two separate PCR reactions. Reverse transcription and subsequent PCR amplification (RT-PCR1) were performed using the Qiagen OneStep RT PCR mix (Qiagen). The cDNA was selected and unused primers were removed by SPRIselect bead selection (Beckman Coulter) followed by a second round of amplification performed with a pair of primers specific for communal sites engineered onto the 5ʹ end of the C- and V- primers used during RT-PCR1. After library preparation, paired-end sequencing was performed using the Illumina Miseq v3 600-cycle Reagent Kit (Illumina). Results : We observed increased frequency of TCRs with long CDR3 length in CIC-deficient non-Treg and Treg cells. We also found significant alterations in the TCR repertoire of TCR beta chain in CIC-deficient Treg cells compared to WT cells, including altered frequency of V and J chain usage. Conclusions : Our study represents the first comparative analysis of TCR repertoire of thymic CD4 SP cells from WT and hematopoietic lineage cell-specific Cic deficient mice. We concluded that CIC deficiency leads to alterations in TCR repertoire of thymic Treg cells.

2021-05-07 | GSE173996 | GEO

BCR repertoire analysis of wild-type and Cic-null B-1a cells

Project description:Purpose: B-1a cells have a distinct BCR repertoire compared with that of B-2 cells. To examine whether CIC loss affects the BCR repertoire in B-1a cells, we analyzed mRNA sequences of immunoglobulin heavy (Igh) and light (Igk and Igl) chain genes in B-1a cells from 12-week-old control and Cicf/f;Cd19-Cre mice. Methods: Peritoneal cavity B-1a cells (IgM+, CD19+, CD5+, CD43+) were sorted by a MoFlo-XDP (Beckman Coulter). Total RNA was extracted using TRIzol Reagent (GeneAll), according to the manufacturer’s instructions. Long Read iR-Profile Reagent System (iRepertoire) was used to generate NGS libraries covering BCR chains including Igh, Igk, and Igl. Briefly, nested inside and outside primers selectively amplified all V- and C- regions and incorporated communal adaptors. Following clean up, only target amplicons, which contain 5’ and 3’ communal adaptors, were exponentially amplified. Amplified libraries were multiplexed for sequencing on the Illumina Miseq platform. Sequence reads were de-multiplexed according to the barcode sequences. Results: Trimmed reads were mapped to germline V, D and J reference sequences downloaded from the IMGT database. IgH diversity and the usage of variable (V) segments in heavy (Ighv) chain and light (Igkv and Iglv) chain genes were comparable between control and Cic-null B-1a cells. Analysis of non-templated (N)-nucleotide addition at V(D)J junctions revealed that Cic-null B-1a cells have a higher proportion of zero to two N-nucleotides-containing-BCRs than control cells. Conclusions: Our study presents the first comparative BCR repertoire analysis of wild-type and Cic-null B-1a cells. We concluded that CIC deficiency does not dramatically alter the BCR repertoire in B-1a cells.

2021-12-16 | GSE164147 | GEO

RNA sequencing analysis of gene expresssion profiles in Cic-null MZB cells

Project description:Purpose: The goal of this study is to compare and examine the transcriptional profiles in Cd19-Cre (control) versus Cicf/f;Cd19-Cre (Cic-null) MZB cells,by mRNA sequencing. Methods: MZB cells (CD19+CD93-CD21+CD23-) were sorted by a MoFlo-Astrios (Beckman Coulter). Total RNA was extracted using TRIzol Reagent (GeneAll), according to the manufacturer’s instructions. . A library for mRNA sequencing was prepared using the Truseq Stranded mRNA/Total Library Prep Kit (Illumina) according to the manufacturer’s instructions. Sequencing was performed with Novaseq 6000 (Illumina). Results: Tophat (v2.0.13) was used to map reads for each sample to the mm10 RefSeq reference genome. The aligned results were then added to Cuffdiff (v2.2.0) to identify the differentially expressed genes (DEGs). In total, 775 genes were differentially expressed in Cic-null MZB cells (505 upregulated and 270 downregulated) compared to control cells (Log2 fold-change > 0.5 and P < 0.01). Conclusions: Our study presents the first comparative gene expression analysis of MZB cells from control and B cell-specific Cic-deficient mice. We concluded that CIC deficiency attenuates MZB cell development through downregulation of the NOTCH signaling pathway. The data reported here also provide references for the gene expression profiles of murine MZB cells through TPM.

2024-04-29 | GSE264654 | GEO

Expression data from developing thymocytes of N15TCR transgenic Rag2 deficient mice

Project description:T cell development relies on the precise developmental control of various cellular functions for appropriate positive and negative selection. Previously, gene expression profiling of peptide-driven negative selection events in the N15 TCR class I MHC-restricted mouse and D011.10 TCR class II MHC-restricted mouse has offered insights into the coordinate engagement of biological processes affecting thymocyte development. However, there has been little comparable detailed in vivo global genome expression analysis reported for positive selection. We used microarrays to identify the genes differentially expressed during CD8 single positive T cell development in N15 TCR transgenic Rag2 deficient mice. We have analyzed gene expression in the individual populations as development proceeds from DP, intermediate (Int), to SP subsets. To this end, we sorted the individual populations from six age and sex matched 5-6 week old N15 TCR tg+/+ RAG-2-/- H-2b mice for two independent experiments. For sorting subpopulations, cells were stained with anti-CD4 (L3T4) and anti-CD8 (Ly-2) antibodies (Pharmingen, San Diego, CA USA) and DP, Int and SP thymocytes were sorted on a MoFlo (Cytomation, Fort Collins, CO USA).

2009-03-31 | E-GEOD-13493 | biostudies-arrayexpress

Chromatin organizer SATB1 controls the cell identity of CD4+ CD8+ double-positive thymocytes by compacting super-enhancers

Project description:CD4+ and CD8+ double-positive (DP) thymocytes are at a critical stage during the T cell development in thymus. DP cells rearrange the T cell receptor gene Tcra to generate T cell receptors with TCR. Then DP cells differentiate into CD4 or CD8 single-positive (SP) thymocytes, Regulatory T cells, or invariant nature kill T cells (iNKT) according to the TCR signal. Chromatin organizer SATB1 is highly expressed in DP cells and plays an essential role in regulating Tcra rearrangement and differentiation of DP cells. Here we explored the mechanism of SATB1 orchestrating gene expression in DP cells. Single-cell RNA sequencing assay of SATB1-deficient thymocytes showed that the cell identity of DP thymocytes was changed, and the genes specifically highly expressed in DP cells were down-regulated. ChIP-seq and ATAC-seq data showed the similar tendency. The super-enhancers regulate the expressions of the DP-specific genes, and the SATB1 deficiency reduced the super-enhancer activity. Hi-C data showed that interactions in super-enhancers and between super-enhancers and promoters decreased in SATB1 deficient thymocytes. We further explored the regulation mechanism of two SATB1-regulating genes, ETS2 and Bcl6, in DP cells and found that the knockout of the super-enhancers of these two genes impaired the development of DP cells. Our research reveals that SATB1 globally regulates super-enhancers of DP cells and promotes the establishment of DP cell identity, which helps understand the role of SATB1 in thymocyte development.

2021-09-02 | GSE182995 | GEO

Gene expression analysis of CD4+ CD8+ thymocytes [Affymetrix]

Project description:We performed ChIP-Seq for hallmark TFs (Ets1, Runx1), histone modification marks (H3K4me1, H3K4me2, H3K4me3, H3K27me3, H3K36me3), total RNA Pol II, short RNA-Seq as well as nucleosome mapping mainly in murine Rag2 -/- thymocytes. We also performed ChIP-Seq for E47 as well as nucleosome mapping, gene expression microarray analysis in CD4+ CD8+ DP thymocytes. Overall, we find a key role for the transcription factor Ets1, contributing towards alpha beta T cell lineage commitment via differential transactivation of stage-specific genes orchestrated by dynamic, co-association -mediated chromatin remodeling, as well as transcription dependent generation of a specialized chromatin structure at the TCR beta locus. Genome-wide analysis via ChIP-Seq for Ets1, Runx1, total RNA Pol II binding, H3K4me1, H3K4me2, H3K4me3, H3K27me3, H3K36me3, short RNA-Seq, Mnase-Seq in murine Rag2 -/- thymocytes, ChIP-Seq for E47, Mnase-Seq and gene expression microarray analysis in DP thymocytes

2014-04-01 | GSE56357 | GEO

Gene expression analysis of CD4+ CD8+ thymocytes [Affymetrix]

2014-04-01 | E-GEOD-56357 | biostudies-arrayexpress

Gene expression analysis of Ets1-/- CD4+ CD8+ thymocytes

Project description:We performed ChIP-Seq for hallmark TFs (Ets1, Runx1), histone modification marks (H3K4me1, H3K4me2, H3K4me3, H3K27me3, H3K36me3), total RNA Pol II, short RNA-Seq as well as nucleosome mapping mainly in murine Rag2 -/- thymocytes. We also performed ChIP-Seq for E47 as well as nucleosome mapping, gene expression microarray analysis in CD4+ CD8+ WT and Ets1-/- DP thymocytes. Overall, we find a key role for the transcription factor Ets1, contributing towards alpha beta T cell lineage commitment via differential transactivation of stage-specific genes orchestrated by dynamic, co-association -mediated chromatin remodeling, as well as transcription dependent generation of a specialized chromatin structure at the TCR beta locus. Genome-wide analysis via ChIP-Seq for Ets1, Runx1, total RNA Pol II binding, H3K4me1, H3K4me2, H3K4me3, H3K27me3, H3K36me3, short RNA-Seq, Mnase-Seq in murine Rag2 -/- thymocytes, ChIP-Seq for E47, Mnase-Seq and gene expression microarray analysis in DP thymocytes Gene expression analysis of Ets1-/- CD4+ CD8+ thymocytes

2015-12-19 | E-GEOD-73849 | biostudies-arrayexpress

Impact of Jmjd3 and Utx histone demethylases on Histone H3 lysine 27 trimethylation (H3K27Me3) in mature CD4 SP thymocytes

Project description:While histone H3 lysine 27 trimethylation (H3K27Me3) is associated with gene silencing, whether H3K27Me3 demethylation affects transcription and cell differentiation in vivo has remained elusive. To investigate this, we conditionally inactivated the two H3K27Me3 demethylases, Jmjd3 and Utx, in non-dividing intrathymic CD4+ T cell precursors. We show that both enzymes redundantly promote H3K27Me3 removal at, and expression of, a specific subset of genes involved in terminal thymocyte differentiation, especially S1pr1, encoding a sphingosine-phosphate receptor required for thymocyte egress. Floxed alleles of the genes encoding Utx and Jmjd3 (Kdm6a and Kdm6b, respectively) were deleted in double positive (DP) thymocytes carrying a CD4 Cre transgene. Genome-wide H3K27Me3 ChipSeq was performed on (i) pre-selection (CD69lo) DP thymocytes from wild-type mice carrying an endogenous polyclonal TCR repertoire, (ii) mature (TCRhi CD24lo) CD4 SP thymocytes from wild type (Wt), Jmjd3KO, UtxKO and dKO mice carrying an endogenous polyclonal TCR repertoire and (iii) mature (Va2hi CD24lo) CD4 SP thymocytes from wild type and dKO mice carrying the OTII TCR transgene.

2015-09-02 | E-GEOD-70795 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data