Project description:Total RNA was extracted from WT or KO liver tumor tissues. RNA samples were analyzed by RNA sequencing based on the manufacturer’s protocols. Briefly, Illumina HiSeq 2500 platform was used to sequence the RNA samples for the subsequent generation of raw data. KEGG pathway and GSEA enrichment analysis were used for functional pathway analysis.
Project description:Purpose: The goal of this study is to identify the differential cardiac transcriptome profiling between WT and Smyd1 null (Smyd1-KO) hearts at E9.5 using RNA-seq. Methods: mRNA profiles of E9.5 WT and Smyd1-KO mouse hearts were generated by deep sequencing, n=3 for each genotype, using Illumina HiSeq2500. The sequence reads were aligned to the mm10 reference genome using STAR via the bcbio-nextgen RNA-sequencing pipeline. Differential gene expression was determined by DEseq2. Results: 1756 genes were differentially expressed between WT and Smyd1-KO hearts [adjusted P value <0.05, |log2(Fold Change)| > 0.5], with 1130 upregulated and 626 downregulated in E9.5 Smyd1-KO hearts.
Project description:Purpose: This study aimed at exploring the deregulated genes in setd2 knockout mESCs compared with wt, more particularly to find the mechanism controlled by setd2,which was required for endoderm differentiation. Methods: Setd2 wt and ko mESCs were generated by deep sequencing, using Illumina GAIIx. Using Avadis NGS (version:1.3) software to analyze the sequence reads that passed quality filter to acquire the expression level of all genes. qRT–PCR validation was performed usingSYBR Green assays. Results: Using an optimized data analysis workflow, we mapped about 80 million sequence reads per sample to the mouse genome (build mm9) and identified 17,827 transcripts in the sted2 wt and ko mESCs. About 2,516 genes were deregulated in setd2 ko mESCs, more than 10 genes were validated using qRT-PCR. Conclusions: Through RNA-seq,we noticed that a subset of genes that related to MAPK signaling pathways were down-regulated in ko mESCs. This provided a bridge to connect setd2 and mESCs endoderm differentiation. One wt and one ko mESCs were generated by deep sequencing, using Illumina GAIIx.
Project description:Naïve T cells were obtained by StemCell CD4+ T cell isolation kit of spleen from Mettl3 KO and WT mice followed by FACS sorting (CD4+CD25-CD45RB-Hi). Raw sequencing reads were aligned to the mouse genome (mm10) with Tophat, and gene expression levels were measured by Cufflinks.
Project description:Our goal was to identify early genetic changes in the development of autoimmune dysfunction. WT and IL-2-KO CD8 T cells were sorted from the lymph node and spleen of 12-day old mice. Total RNA was isolated by Expression Analysis Inc. using Illumina TrueSeq Stranded Total RNA Sample Preparation Kit. Eight samples were sequenced (four biological replicates of IL-2-KO and WT/HET mice), producing 2X50 paired-end reads using the Illumine HiSeq 2500 platform. Raw reads were provided by Expression Analysis. We identified several genetic signatures within the bulk data including a cytolyic pattern and a novel gene expression pattern indicating a helper-like function.
Project description:Purpose: This study aimed at exploring the deregulated genes in setd2 knockout mESCs compared with wt, more particularly to find the mechanism controlled by setd2,which was required for endoderm differentiation. Methods: Setd2 wt and ko mESCs were generated by deep sequencing, using Illumina GAIIx. Using Avadis NGS (version:1.3) software to analyze the sequence reads that passed quality filter to acquire the expression level of all genes. qRT–PCR validation was performed usingSYBR Green assays. Results: Using an optimized data analysis workflow, we mapped about 80 million sequence reads per sample to the mouse genome (build mm9) and identified 17,827 transcripts in the sted2 wt and ko mESCs. About 2,516 genes were deregulated in setd2 ko mESCs, more than 10 genes were validated using qRT-PCR. Conclusions: Through RNA-seq,we noticed that a subset of genes that related to MAPK signaling pathways were down-regulated in ko mESCs. This provided a bridge to connect setd2 and mESCs endoderm differentiation.
Project description:The experiment was designed to compare transcriptomic differences between WT and Ccr6 KO Tregs during activation. WT and Ccr6 KO Tregs, cells were isolated from mice and cultured in vitro for 3 days with activation using anti-CD3/CD28 beads. Total RNA was extracted using the Trizol method. Quantity and quality were assessed using a Thermo Scientific™ NanoDrop™ 2000/2000c Spectrophotometer. Novogene Corporation Inc prepared the RNA-seq 250-300 bp insert cDNA library. Illumina HiSeq platform PE150 sequencing was used for sequencing, yielding 20M raw reads/sample. Mus Musculus mm39 was used as the reference genome for alignment.
Project description:mRNAseq and proteomic data set of one week old WT (Chop wt/wt CkmmCre wt/wt Dars2 fl/fl), Chop KO (Chop ko/ko CkmmCre wt/wt Dars2 fl/fl), Dars2 KO (Chop wt/wt CkmmCre tg/wt Dars2 fl/fl) and DKO (Chop ko/ko CkmmCre tg/wt Dars2 fl/fl) mice
