Next Generation Sequencing Facilitates Quantitative Analysis of peritoneal macrophages Transcriptomes of Dnmt3a macrophage conditional knockout mouse
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE74750 | GEO | 2016/05/30
SECONDARY ACCESSION(S): PRJNA301402
REPOSITORIES: GEO
Similar Datasets
Project description:Purpose:The purpose of this study is to measure the gene expression profile in Dnmt3a conditional knockout macrophages. Methods:Dnmt3a conditional knockout macrophages mRNA profiles were generated by deep sequencing,using Illumina. Results: We mapped about 20 million sequence reads per sample to the mouse genome, identified hundreds of genes with significant mRNA variation during Dnmt3a conditional knockout in macrophages. Dnmt3a conditional knockout mRNA profiles were generated by deep sequencing
2016-05-30 | E-GEOD-74750 | biostudies-arrayexpress
Project description:Purpose: Epigenetic regulation contributes to pathogenesis of neurondegenerative disease. We found that dis-regulation of a 242-gene subnetwork related to DNA methylation regulated neuronal differentiation are common in AD and HD. There are two DNA methyltransferases, DNMT1 and DNMT3A, in the subnetwork. DNMT1 is one of top hub genes in the network and likely to play a key regulatory role in the subnetwork. To validate that DNMT1 is a key regulator for the subnetwork, and DNMT3A not as one, we constructed two brain-specific conditional knockout mice. Methods: Cortices were dissected from Dnmt1 conditional knockout (CKO), Dnmt3a CKO, and respective littermate control mice at 18 weeks. RNA was isolated from three biological replicates for each genotype using TRIzol (Invitrogen) extraction and isopropanol precipitation. RNA samples were resuspended in water and further purified with RNeasy columns with on-column DNase treatment (Qiagen). RNA purity was assessed by measuring the A260/A280 ratio using a NanoDrop and RNA quality checked using an Agilent 2100 Bioanalyzer (Agilent Technologies). Approximately 250 ng of total RNA per sample were used for library construction by the TruSeq RNA Sample Prep Kit (Illumina) and sequenced using the Illumina HiSeq 2500 instrument according to the manufacturer's instructions. Sequence reads were aligned to mouse genome assembly mm10 and quantified using Cufflinks. Results: Genes differentially expressed in CKO mice compared to littermate control mice, or the Dnmt1 CKO signature, including GSN (the genes with the largest number of connection in the subnetwork) and SOX10 (a key transcription factor of myelination), significantly overlaps with the subnetwork. Broadly, the Dnmt1 CKO signature is enriched for genes involved in GO biological processes immune response, lipid metabolism, endocytosis, glial cell differentiation, and nerve ensheatment, consistent with biological function of the subnetwork. Moreover, the Dnmt1 CKO mice show increased predilection to seizures, an incidence also increased in patients with AD (Amatniek et al, 2006) as well as juvenile form of HD (Cloud et al, 2012). In contrast, the Dnmt3a CKO signature does not overlap with the subnetwork (p=0.07) and is not enriched for any GO biological process. Conclusions: These results suggest the Dnmt1 regulates common genes related with AD and HD while Dnmt3a has little effect. All of the mice used in this study were handled in accordance with IACUC-approved protocols. Dnmt1flox/flox (Fan et al, 2001; Jackson-Grusby et al, 2001) and Dnmt3aflox/flox (Nguyen et al, 2007) mice were backcrossed onto a C57BL/6 background and crossed with Olig1-cre mice to generate Dnmt1 conditional knockout (Olig1cre/+;Dnmt1flox/flox) and littermate control (Olig1+/+;Dnmt1flox/flox) mice, and Dnmt3a conditional knockout (Olig1cre/+;Dnmt3aflox/flox) and littermate control (Olig1+/+;Dnmt3aflox/flox) mice.
2014-07-31 | E-GEOD-58261 | biostudies-arrayexpress
Project description:Purpose: Epigenetic regulation contributes to pathogenesis of neurondegenerative disease. We found that dis-regulation of a 242-gene subnetwork related to DNA methylation regulated neuronal differentiation are common in AD and HD. There are two DNA methyltransferases, DNMT1 and DNMT3A, in the subnetwork. DNMT1 is one of top hub genes in the network and likely to play a key regulatory role in the subnetwork. To validate that DNMT1 is a key regulator for the subnetwork, and DNMT3A not as one, we constructed two brain-specific conditional knockout mice. Methods: Cortices were dissected from Dnmt1 conditional knockout (CKO), Dnmt3a CKO, and respective littermate control mice at 18 weeks. RNA was isolated from three biological replicates for each genotype using TRIzol (Invitrogen) extraction and isopropanol precipitation. RNA samples were resuspended in water and further purified with RNeasy columns with on-column DNase treatment (Qiagen). RNA purity was assessed by measuring the A260/A280 ratio using a NanoDrop and RNA quality checked using an Agilent 2100 Bioanalyzer (Agilent Technologies). Approximately 250 ng of total RNA per sample were used for library construction by the TruSeq RNA Sample Prep Kit (Illumina) and sequenced using the Illumina HiSeq 2500 instrument according to the manufacturer's instructions. Sequence reads were aligned to mouse genome assembly mm10 and quantified using Cufflinks. Results: Genes differentially expressed in CKO mice compared to littermate control mice, or the Dnmt1 CKO signature, including GSN (the genes with the largest number of connection in the subnetwork) and SOX10 (a key transcription factor of myelination), significantly overlaps with the subnetwork. Broadly, the Dnmt1 CKO signature is enriched for genes involved in GO biological processes immune response, lipid metabolism, endocytosis, glial cell differentiation, and nerve ensheatment, consistent with biological function of the subnetwork. Moreover, the Dnmt1 CKO mice show increased predilection to seizures, an incidence also increased in patients with AD (Amatniek et al, 2006) as well as juvenile form of HD (Cloud et al, 2012). In contrast, the Dnmt3a CKO signature does not overlap with the subnetwork (p=0.07) and is not enriched for any GO biological process. Conclusions: These results suggest the Dnmt1 regulates common genes related with AD and HD while Dnmt3a has little effect.
2014-07-31 | GSE58261 | GEO
Project description:Gains and losses in DNA methylation are prominent genomic features of all mammalian cell types. To gain insight into mechanisms that could promote shifts in DNA methylation patterns and thus contribute to cell fate, including malignant transformation, we performed genome-wide mapping of 5-methylcytosine in purified wild type and Dnmt3a conditional knockout hematopoietic stem cells (HSCs). We generated 1,121 million (control HSCs), and 1,213 million (Dnmt3a knockout HSCs) raw reads; about 81.4% and 88.7%, respectively, were successfully aligned to either strand of the reference genome (mm9), obtainig an average CG coverage of 39.5-fold (wild type) and 47.0-fold (Dnmt3a kockout). Whole genome bisulfite sequencing of secondarily-transplanted wild-type and Dnmt3a conditional knockout hematopoietic stem cells using Illumina HiSeq 2000
2013-11-17 | E-GEOD-49714 | biostudies-arrayexpress
Project description:Gains and losses in DNA methylation are prominent genomic features of all mammalian cell types. To gain insight into mechanisms that could promote shifts in DNA 5-hydroxymethylation (5hmc) patterns and thus contribute to cell fate, including malignant transformation, we performed genome-wide mapping of 5hmc in purified wild type and Dnmt3a conditional knockout hematopoietic stem cells (HSCs) using cytosine-5-methylenesulphonate sequencing (CMS-seq). Comparing anti-CMS pulldown to input control, we identified 107,549 and 175,682 peaks of 5hmc enrichment in control and Dnmt3a knockout HSCs, respectively. Whole genome CMS-enriched bisulfite sequencing of secondarily-transplanted wild-type and Dnmt3a conditional knockout hematopoietic stem cells using Illumina HiSeq 2000
2014-01-22 | E-GEOD-53742 | biostudies-arrayexpress
Project description:Transcriptomic and epigenetic disruptions in excitatory neurons in Dnmt3a conditional knockout mouse
| PRJNA594019 | ENA
Project description:We created a mouse line in which deletion of exon 19 of Dnmt3a is driven by the Neurod6 promoter (also known as Nex-Cre line). In this conditional knockout (cKO), Dnmt3a is functionally ablated in excitatory neurons in the neocortex and hippocampus starting in mid/late gestation (~E13-15). With an affinity purification approach to isolate tagged nuclei in mice (similar to INTACT; [Deal R.B. and Henikoff S. A simple method for gene expression and chromatin profiling of individual cell types within a tissue. Dev. Cell 18,1030-1040. (2010)]), we characterized the genome-wide patterns of transcription, DNA methylation, and histone modifications in excitatory pyramidal neurons of the frontal cortex from the Dnmt3a cKO and control mice. Our data provide a detailed assessment of the molecular basis of the accompanying changes of neurophysiological and behavioral phenotypes in the cKO mice, and suggest a complex interaction between DNA methylation and Polycomb-mediated repression in the epigenetic regulation in developing brain cells.
2022-05-23 | GSE141587 | GEO
Project description:Purpose:The purpose of this study is to detect activated or silenced genes during KAT8-deficient peritoneal macrophages and the control cells. Gene expression differences between two samples could be found using transcriptome profiling (RNA-seq) analysis. Methods:Mouse peritoenal macrophages were harvested from mice 3 days after thioglycollate (Merck) injection. Macrophages RNA profiles were generated by deep sequencing,using Illumina. Results: We mapped about 10 million sequence reads per sample to the mouse genome, identified hundreds of genes with significant mRNA variation between KAT8-deficient macrophages and the control cells.
2019-01-03 | GSE124551 | GEO
Project description:Conditional DICER1 knockout hESCs
| PRJNA450977 | ENA
Project description:Purpose: The purpose of this study is to detect activated or silenced genes during Kdm2b-deficient peritoneal macrophages and the control cells. Gene expression differences between two samples could be found using transcriptome profiling (RNA-seq) analysis. Methods: Mouse peritoneal macrophages were harvested from mice 4 days after thioglycollate (BD, Sparks, MD) injection. Macrophages RNA profiles were generated by deep sequencing, using Illumina. Results: We mapped about 10 million sequence reads per sample to the mouse genome, identified hundreds of genes with significant mRNA variation between Kdm2b-deficient macrophages and the control cells.
2019-12-31 | GSE120651 | GEO