Pluto Bioinformatics

GSE156118: RNA-sequencing of QKI proficient and deficient microglia

Bulk RNA sequencing

Purpose:RNA_sequencing analysis defined a novel role for the QKI in microglia; Methods: microglia mRNA profiles of 4-6 weeks-old wild-type (QKIfl/fl) and microglia specific knockout (QKIfl/fl; cx3r1cre-ert2) mice were generated by Illumina HiSeq 4000 in triplicate. The sequence reads that passed quality filters were trimmed with Trimmomatic v0.39. STAR v2.7.1a was then used to align the reads to the mouse genome (mm10/GRCm38). Gene expression was quantified across all samples with HOMER v4.11.1, and the normalization was carried out through the regularized logarithm (rlog) transformation of DESeq2 v1.26.0. Differential expression between the WT and knockout samples were calculated through DESeq2 v1.26.0, and the gene expression was considered significantly different if the absolute value of the log-fold-change (LFC) was higher than 2, the base means larger than 10 and the false discovery rate (FDR) less than 0.05.; Results: RNA-seq data revealed the up-regulation of 326 genes and down-regulation of 294 genes in knockout microglia compare to wt (2-fold change at FDR of 0.05, base mean>10). In particular qkICx3cr1-KO microglia exhibited higher expression of genes that are known to encode proteins related to inflammation (Il-6, Apoe, Cxcl-10, Il-1b, Il-12b, and Tnf). In line with this, functional annotation by DAVID, Reactome and, GO analysis showed enrichment of cell cycle and inflammation-related pathways in the up-regulated transcripts in qkICx3cr1-KO mice. Up-regulated transcripts were further validated using qRT-PCR.; Conclusions: Our study represents the first detailed analysis of microglia transcriptomes without QKI expression, with biologic replicates, generated by RNA-seq technology. The data should provide how QKI modulates the microglia gene expression profiles in genome-wide detail. SOURCE: Stephane Richard McGill University

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