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Next Generation Sequencing Facilitates Single Cell Analysis of Wild Type and Monocyte-Depleted Brain Transcriptomes

ABSTRACT: Next Generation Sequencing Facilitates Single Cell Analysis of Wild Type and Monocyte-Depleted Brain Transcriptomes

PROVIDER: PRJNA785260 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR17085563.fastq.gz	Fastqsanger.gz
	SRR17085564.fastq.gz	Fastqsanger.gz
	SRR17085565.fastq.gz	Fastqsanger.gz
	SRR17085566.fastq.gz	Fastqsanger.gz
	SRR17085567.fastq.gz	Fastqsanger.gz

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Next-Generation Sequencing Facilitates Quantitative Analysis of Wild Type and Monocyte-Depleted Brain Transcriptomes

Project description:Next-Generation Sequencing Facilitates Quantitative Analysis of Wild Type and Monocyte-Depleted Brain Transcriptomes

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Next-Generation Sequencing Facilitates Quantitative Analysis of Wild Type and Monocyte-Depleted Brain Transcriptomes

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived brain transcriptome profiling (RNA-seq) to reveal the difference of cellular pathways in adult brains of wild type (WT) and monocyte-depleted (CCR2-DTR) mice 8 days post infection of Trichinella spiralis. Methods: Illumina compatible RNAseq library was prepared using NEB next ultra RNAseq library preparation kit. The sequencing of the cDNA libraries was performed on the Illumina NextSeq platform (Illumina, San Diego, CA) using the high output 1X75 cycles configuration. CLC Genomics Workbench 11.0.1 version (http://www.clcbio.com/products/clc-genomics-workbench/ ; Qiagen) was used for RNA-seq analysis. De-multiplexed fastq files from RNA-Seq libraries are imported into the CLC software. Bases with low quality were trimmed and reads are mapped to reference genome Mus musculus genome GRCm38. The reference genome sequence and annotation files were downloaded from ENSEMBLE, release.92 (Mus_musculus.GRCm38.92.fa, and Mus_musculus.GRCm38.92.gtf). The aligned reads were obtained using the RNA-Seq Analysis Tool of CLC Genomics Workbench. Statistical analysis of differentially expressed genes is carried out based on a negative binomial model using a tool in CLC Genomic Workbench. The reference genome sequence and annotation files were downloaded from ENSEMBL, release.92 (Mus_musculus.GRCm38.92.fa, and Mus_musculus.GRCm38.92.gtf). The aligned reads were obtained using the RNA-Seq Analysis Tool of CLC Genomics Workbench. Results: Using an optimized data analysis workflow, we mapped over 50 million sequence reads per sample to the mouse genome (GRCm38) and found that Trichinella-infected mice depleted of monocytes presented with significantly increased expression of proinflammatory genes compared to controls.

2022-08-25 | GSE190493 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Transcriptomes in Tbx2 depleted melanoma cells

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of Transcriptomes in Tbx2 depleted melanoma cells

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Next Generation Sequencing Facilitates Single Cell Analysis of Wild Type and Monocyte-Depleted Brain Transcriptomes

Project description:Methods: Cells isolated from the whole brains of naive wild type, infected wild type, and infected CCR2-DTR mice were sort-purified on live CD45hi cells from five biological replicates and pooled. Sort-purified cells were then processed using the 10X Genomics Chromium Controller. Cell suspensions were loaded onto the Chromium Single Cell A Chip for cell lysis and barcoding. RNA from individual cells was reverse transcribed and sequencing libraries prepared using the Chromium Single Cell 3’ Library Kit v2 following the manufacturers protocol. Samples were sequenced using an Illumina NextSeq 550 with standard 10X Genomics Configuration (26 bp x 98 bp). After sequencing, raw bcl files were processed using the cellranger mkfastq command for sample demultiplexing and conversion to .fastq files, followed by cellranger count for cell barcode and UMI deconvolution as well as mapping to the respective reference genome. Processed digital gene expression matrices were imported into R studio for analysis using the Seurat package. Samples were aligned along common sources of variation and compared using canonical correlation analysis to identify unique clusters of cells within the samples. Marker genes for each sample and cluster were identified and used for generation of downstream plots within the Seurat package. All packages are maintained to be best in class and are regularly updated to their most recent release. Results: 10 distinct cell clusters were identified and we found that two populations were found at increased proportions post-infection but were substantially reduced in the monocyte-depleted animals (CCR2-DTR). We confirmed that these populations to be monocytes and monocyte-derived cells, and valicated their immunoregulatory molecules by RT-qPCR analysis.

2022-08-25 | GSE189957 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Solanum lycopersicum bud and flower Transcriptomes

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Next Generation Sequencing Facilitates Quantitative Analysis of IBP Transcriptomes

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