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Next Generation Sequencing Facilitates Quantitative Analysis of young nand aged control and Acsl6-/- Transcriptomes

ABSTRACT: Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived cerebellar transcriptome profiling (RNA-seq) to determine age-relatined impact of acsl6 deficiency on brain transcriptome profiles. Methods: Cerebellar mRNA profiles of 2-month and 18-month control and long-chain acyl-coa synthetase 6-knockout (Acsl6) mice were generated and sent to Genewiz for RNAseq analysis Results: Using an optimized data analysis workflow, we mapped about 3,451,694,754 sequence reads total and ~25-45 million reads per sample of which ~98% were mapped to the mouse genome. Conclusions: Our study represents the first detailed analysis of cerebellar transcriptomes of Acsl6 knockout mice, compated to controls, at young and old ages.

ORGANISM(S): Mus musculus

PROVIDER: GSE175571 | GEO | 2021/05/27

REPOSITORIES: GEO

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Project description:To examine the role of platelets in mouse monocyte function, we administered anti-GPIba antibody to deplete platelets or IgG as a control to 48 mice. After 12 hours, mice were either exposed to LPS or PBS (as a sham control) for 3 hours. Peripheral blood mononuclear cells (PBMCs) were collected, and monocytes were sorted into QIAzol lysis buffer. The experimental setup included 4 conditions, with each condition repeated 3 times. In each experiment, the blood from 4 mice was pooled to generate biological replicates of 12 mice, distributed into 4 groups: Sham mice (IgG) treated with PBS (n = 3) Sham mice (IgG) treated with LPS (n = 3) Platelet-depleted mice (anti-GPIba) treated with PBS (n = 3) Platelet-depleted mice (anti-GPIba) treated with LPS (n = 3) After these treatments, mouse Ly6G− IA/IE− CD45+ CD11b+ CD115+ monocytes were FACS-sorted directly into Quiazol for RNA extraction. The lysed samples were sent to GENEWIZ for RNA isolation and bulk RNA-seq analysis. RNA extraction and library preparation were conducted according to the GENEWIZ (Azenta Life Sciences) pipeline. Ultra-low input RNA-Seq was performed on Illumina HiSeq PE 2x150 bp with approximately 350M reads. Subsequently, reads were mapped to the Mus musculus GRCm38 reference genome (ENSEMBL) using the STAR aligner v.2.5.2b, and unique gene hit counts were generated with featureCounts from the Subread package v.1.5.2. Standard analysis was performed by GENEWIZ, including differential gene expression analysis using DESeq2. p-values and log2 fold changes were calculated using the Wald test, with genes meeting criteria of adjusted p-value < 0.05 and absolute fold change > 2 considered significantly differentially expressed genes (DEGs). Gene ontology (GO) analysis of significant DEGs was conducted by GENEWIZ (Azenta Life Sciences) using the Fisher exact test.\\" *Our goal is to assess the alternations on transcription levels (mRNA-Seq) between the different groups. Twelve samples contain 500 - 10000 mouse monocytes that were directly sorted into 1 ml QIAzol. **Experimental setting: samples were generated from three independent experiments (biological replicates N1, N2 and N3), each on a different day. Each experiment consisted of 4 different groups: Group 1: treated with IgG + PBS Group 2: treated with IgG + LPS challenge Group 3: treated with AntiGPIb + PBS Group 4: treated with AntiGPIb + LPS challenge First run with biological replicates Nr. 1 (indicated as \\"N1\\") contained samples 1 - 4. Second run with biological replicates Nr. 2 (indicated as \\"N2\\") contained samples 5 - 8. Third run with biological replicates Nr. 3 (indicated as \\"N3\\") contained samples 9 - 12. Experimental questions/analysis: 1) what is the effect of AntiGPIb treatment w.o LPS challenge? i.e. \\"Group 3 (Treatment) vs. Group 1(Ctrl)\\" 2) what is the effect of LPS in \\"Group 2 (Treatment) vs. Group 1 (Ctrl)\\" as well as \\"Group 4 (Treatment) vs. Group 3 (Ctrl)\".

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Next Generation Sequencing Facilitates Quantitative Analysis of young nand aged control and Acsl6-/- Transcriptomes

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