Next Generation Sequencing of Wild Type pDC Transcriptomes in a longitudinal activation study (CpG 0h, 2h, 6h, 12)
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PROVIDER: PRJNA717967 | ENA |
REPOSITORIES: ENA
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Project description:Purpose: The goals of this study are to compare NGS-derived pDC transcriptome profiling (RNA-seq) normalized counts and differential expression of genes between different pDC states (steady state, or TLR9 activated for 2h, 6h, or 12h with CpG) in Batf presence and absence. Methods: mRNA profiles of Bone marrow-derived Flt3-L cultured FACS purified pDCs from wild-type and Batf-knockout mice that were left naive or stimulated with TLR9 agonist CpG for 2h, 6h r 12h were generated by deep sequencing, in triplicate, using the Illumina HiSeq3000 platform. DNase digested total RNA samples used for transcriptome analyses were quantified (Qubit RNA HS Assay, Thermo Fisher Scientific) and quality measured by capillary electrophoresis using the Fragment Analyzer and the ‘Total RNA Standard Sensitivity Assay’ (Agilent Technologies, Inc. Santa Clara, USA). All samples in this study showed high quality RNA Quality Numbers (RQN; mean = 9.9). The library preparation was performed according to the manufacturer’s protocol using the Illumina® ‘TruSeq Stranded mRNA Library Prep Kit’. Briefly, 200 ng total RNA were used for mRNA capturing, fragmentation, the synthesis of cDNA, adapter ligation and library amplification. Bead purified libraries were normalized and finally sequenced on the HiSeq 3000/4000 system (Illumina Inc. San Diego, USA) with a read setup of SR 1x150 bp. The bcl2fastq tool was used to convert the bcl files to fastq files as well for adapter trimming and demultiplexing. Results: Data analyses on fastq files were conducted with CLC Genomics Workbench (version 11.0.1, QIAGEN, Venlo. NL). The reads of all probes were adapter trimmed (Illumina TruSeq) and quality trimmed (using the default parameters: bases below Q13 were trimmed from the end of the reads, ambiguous nucleotides maximal 2). Mapping was done against the Mus musculus (mm10; GRCm38.86) (March 24, 2017) genome sequence. After grouping of samples (three biological replicates each) according to their respective experimental condition, multi-group comparisons were made and statistically determined using edgeR on usegalaxy.org The Resulting values were corrected for multiple testing by FDR. A value of ≤0.05 was considered significant. Conclusions: Our study represents the first detailed analysis of Batf-dependent gene expression in naive and activated pDC transcriptomes in a longitduinal study. Our results show that Batf absence significantly altered the global gene expression patterns in pDCs, modulating many biological pathways important for cell development and effector function.
2021-04-01 | GSE170750 | GEO
Project description:Purpose: The goals of this study are to compare NGS-derived pDC transcriptome profiling (RNA-seq) normalized counts and differential expression of genes between different pDC states (steady state, or TLR9 activated for 2h, 6h, or 12h with CpG) in Batf presence and absence. Methods: mRNA profiles of Bone marrow-derived Flt3-L cultured FACS purified pDCs from wild-type and Batf-knock out mice that were left naive or stimulated with TLR9 agonist CpG for 2h, 6h r 12h were generated by deep sequencing, in triplicate, using the Illumina HiSeq3000 platform. DNase digested total RNA samples used for transcriptome analyses were quantified (Qubit RNA HS Assay, Thermo Fisher Scientific) and quality measured by capillary electrophoresis using the Fragment Analyzer and the ‘Total RNA Standard Sensitivity Assay’ (Agilent Technologies, Inc. Santa Clara, USA). All samples in this study showed high quality RNA Quality Numbers (RQN; mean = 9.9). The library preparation was performed according to the manufacturer’s protocol using the Illumina® ‘TruSeq Stranded mRNA Library Prep Kit’. Briefly, 200 ng total RNA were used for mRNA capturing, fragmentation, the synthesis of cDNA, adapter ligation and library amplification. Bead purified libraries were normalized and finally sequenced on the HiSeq 3000/4000 system (Illumina Inc. San Diego, USA) with a read setup of SR 1x150 bp. The bcl2fastq tool was used to convert the bcl files to fastq files as well for adapter trimming and demultiplexing. Results: Data analyses on fastq files were conducted with CLC Genomics Workbench (version 11.0.1, QIAGEN, Venlo. NL). The reads of all probes were adapter trimmed (Illumina TruSeq) and quality trimmed (using the default parameters: bases below Q13 were trimmed from the end of the reads, ambiguous nucleotides maximal 2). Mapping was done against the Mus musculus (mm10; GRCm38.86) (March 24, 2017) genome sequence. After grouping of samples (three biological replicates each) according to their respective experimental condition, multi-group comparisons were made and statistically determined using edgeR on usegalaxy.org The Resulting pvalues were corrected for multiple testing by FDR. A pvalue of ≤0.05 was considered significant. Conclusions: Our study represents the first detailed analysis of Batf-dependent gene expression in naive and activated pDC transcriptomes in a longitduinal study. Our results show that Batf absence significantly altered the global gene expression patterns in pDCs, modulating many biological pathways important for cell development and effector function.
2024-01-12 | GSE176419 | GEO
Project description:ATAC-Seq of Wild Type pDC Transcriptomes (CpG 0h, 2h)
| PRJNA718276 | ENA
Project description:We performed RNA-seq of E16.5 mouse cortical neurons depolarized with 55mM KCl for 0h, 2h and 6h.
2022-11-02 | GSE201636 | GEO
Project description:We performed RNA methylation profiling for E16.5 mouse cortical neurons depolarized with 55mM KCl for 0h, 2h and 6h.
2022-11-02 | GSE201635 | GEO
Project description:Next Generation Sequencing of Wild Type and Batf-knock out pDC Transcriptomes in a longitudinal activation study (CpG 0h, 2h, 6h, 12)
| PRJNA736101 | ENA
Project description:Purpose: The goals of this study are to compare the pDC chromatin structure (ATAC-seq) at steady state and at 2h after CpG activation. Methods: Cells were harvested and frozen in culture media containing FBS and 5% DMSO. Cryopreserved cells were sent to Active Motif to perform the ATAC-seq assay. The cells were then thawed in a 37°C water bath, pelleted, washed with cold PBS, and tagmented as previously described (Buenrostro et al., 2013), with some modifications based on (Corces et al., 2017). Briefly, cell pellets were resuspended in lysis buffer, pelleted, and tagmented using the enzyme and buffer provided in the Nextera Library Prep Kit (Illumina). Tagmented DNA was then purified using the MinElute PCR purification kit (Qiagen), amplified with 10 cycles of PCR, and purified using Agencourt AMPure SPRI beads (Beckman Coulter). Resulting material was quantified using the KAPA Library Quantification Kit for Illumina platforms (KAPA Biosystems), and sequenced with PE42 sequencing on the NextSeq 500 sequencer (Illumina). Results: Reads were aligned using the BWA algorithm (mem mode; default settings). Duplicate reads were removed, only reads mapping as matched pairs and only uniquely mapped reads (mapping quality >= 1) were used for further analysis. Alignments were extended in silico at their 3’-ends to a length of 200 bp and assigned to 32-nt bins along the genome. The resulting histograms (genomic “signal maps”) were stored in bigWig files. Peaks were identified using the MACS 2.1.0 algorithm at a cut off of p-value 1e-7, without control file, and with the –nomodel option. Peaks that were on the ENCODE blacklist of known false ChIP-Seq peaks were removed. Signal maps and peak locations were used as input data to Active Motifs proprietary analysis program, which creates Excel tables containing detailed information on sample comparison, peak metrics, peak locations and gene annotations. For differential analysis, reads were counted in all merged peak regions (using Subread), and the replicates for each condition were compared using DESeq2. Conclusions: Our study represents a detailed analysis of naive and activated pDC chromatin that analyzes the global murine TF reservoir as defined by Hu et al. in the AnimalTFdb (Hu et al. , 2019, Nucleic Acids Res 47, D33-D38). Our results show that pDC activation substantially altered the chromatin structure making it more or less accessible to specific TF families.
2021-04-01 | GSE171075 | GEO
Project description:Purpose: The goals of this study are to compare the pDC chromatin structure (ATAC-seq) at steady state and at 2h after CpG activation. Methods: Cells were harvested and frozen in culture media containing FBS and 5% DMSO. Cryopreserved cells were sent to Active Motif to perform the ATAC-seq assay. The cells were then thawed in a 37°C water bath, pelleted, washed with cold PBS, and tagmented as previously described (Buenrostro et al., 2013), with some modifications based on (Corces et al., 2017). Briefly, cell pellets were resuspended in lysis buffer, pelleted, and tagmented using the enzyme and buffer provided in the Nextera Library Prep Kit (Illumina). Tagmented DNA was then purified using the MinElute PCR purification kit (Qiagen), amplified with 10 cycles of PCR, and purified using Agencourt AMPure SPRI beads (Beckman Coulter). Resulting material was quantified using the KAPA Library Quantification Kit for Illumina platforms (KAPA Biosystems), and sequenced with PE42 sequencing on the NextSeq 500 sequencer (Illumina). Results: Reads were aligned using the BWA algorithm (mem mode; default settings). Duplicate reads were removed, only reads mapping as matched pairs and only uniquely mapped reads (mapping quality >= 1) were used for further analysis. Alignments were extended in silico at their 3’-ends to a length of 200 bp and assigned to 32-nt bins along the genome. The resulting histograms (genomic “signal maps”) were stored in bigWig files. Peaks were identified using the MACS 2.1.0 algorithm at a cut off of p-value 1e-7, without control file, and with the –nomodel option. Peaks that were on the ENCODE blacklist of known false ChIP-Seq peaks were removed. Signal maps and peak locations were used as input data to Active Motifs proprietary analysis program, which creates Excel tables containing detailed information on sample comparison, peak metrics, peak locations and gene annotations. For differential analysis, reads were counted in all merged peak regions (using Subread), and the replicates for each condition were compared using DESeq2. Conclusions: Our study represents a detailed analysis of naive and activated pDC chromatin that analyzes the role of the transcription factor BATF for chromatin structure in pDCs.
2024-01-12 | GSE178410 | GEO
Project description:Purpose: The goals of this study are to identify BATF binding sites in purified BM-d Flt3-L cultured pDCs (ChIP-seq) at steady state and at 2h after CpG activation. Methods: Cells were fixed with 1% formaldehyde for 15 min and quenched with 0.125 M glycine, and sent to Active Motif Services (Carlsbad, CA) to be processed for ChIP-Seq. In brief, chromatin was isolated by the addition of lysis buffer, followed by disruption with a Dounce homogenizer. Lysates were sonicated and the DNA sheared to an average length of 300-500 bp. Genomic DNA (Input) was prepared by treating aliquots of chromatin with RNase, proteinase K and heat for de-crosslinking, followed by ethanol precipitation. Pellets were resuspended and the resulting DNA was quantified on a NanoDrop spectrophotometer. Extrapolation to the original chromatin volume allowed quantitation of the total chromatin yield. An aliquot of chromatin (20 µg, spiked-in with 200 ng of Drosophila chromatin) was precleared with protein A agarose beads (Invitrogen). Genomic DNA regions of interest were isolated using 4 ug of antibody against BATF (CST, 8638BF). Antibody against H2Av (0.4 ug) was also present in the reaction to ensure efficient pull-down of the spike-in chromatin (Egan et al., 2016). Complexes were washed, eluted from the beads with SDS buffer, and subjected to RNase and proteinase K treatment. Crosslinks were reversed by incubation overnight at 65 °C, and ChIP DNA was purified by phenol-chloroform extraction and ethanol precipitation. Quantitative PCR (QPCR) reactions were carried out in triplicate on specific genomic regions using SYBR Green Supermix (Bio-Rad). The resulting signals were normalized for primer efficiency by carrying out QPCR for each primer pair using Input DNA. Results: For ChIP Sequencing Illumina sequencing libraries were prepared from the ChIP and Input DNAs by the standard consecutive enzymatic steps of end-polishing, dA-addition, and adaptor ligation. Steps were performed on an automated system (Apollo 342, Wafergen Biosystems/Takara). After a final PCR amplification step, the resulting DNA libraries were quantified and sequenced on Illumina’s NextSeq 500 (75 nt reads, single end). Reads were aligned consecutively to the mouse genome (mm10) and to the Drosophila genome (dm3) using the BWA algorithm (default settings). Duplicate reads were removed and only uniquely mapped reads (mapping quality >= 25) were used for further analysis. The number of mouse alignments used in the analysis was adjusted according to the number of Drosophila alignments that were counted in the samples that were compared. Mouse alignments were extended in silico at their 3’-ends to a length of 200 bp, which is the average genomic fragment length in the size-selected library, and assigned to 32-nt bins along the genome. The resulting histograms (genomic “signal maps”) were stored in bigWig files. Peak locations were determined using the MACS algorithm (v2.1.0) with a cutoff of p-value = 1e-7. Peaks that were on the ENCODE blacklist of known false ChIP-Seq peaks were removed. Signal maps and peak locations were used as input data to Active Motifs proprietary analysis program, which creates Excel tables containing detailed information on sample comparison, peak metrics, peak locations and gene annotations. The results were further visualized using Integrative Genomics Viewer (IGV) (Robinson et al., 2011) and modified with Inkscape. Conclusions: Our study represents a detailed analysis of global BATF binding sites in naive and activated pDCs. Our results show that BATF binds not only to promoter regions of genes but extensively to enhancer elements as well. We identify key role players important for pDC biology that are regulated by BATF binding onto their DNA.
2024-01-12 | GSE171868 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2021-06-08 | GSE176420 | GEO