Dataset Information

Next Generation Sequencing of Batf-knock out pDC Transcriptomes in a longitudinal activation study (CpG 0h, 2h, 6h, 12)

ABSTRACT: Next Generation Sequencing of Batf-knock out pDC Transcriptomes in a longitudinal activation study (CpG 0h, 2h, 6h, 12)

PROVIDER: PRJNA736103 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	SRR14882963.fastq.gz	Fastqsanger.gz
	SRR14882964.fastq.gz	Fastqsanger.gz
	SRR14882965.fastq.gz	Fastqsanger.gz
	SRR14882966.fastq.gz	Fastqsanger.gz
	SRR14882967.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 12

Similar Datasets

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.

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.

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.

Dataset Information

Next Generation Sequencing of Batf-knock out pDC Transcriptomes in a longitudinal activation study (CpG 0h, 2h, 6h, 12)

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets