Dataset Information

Quantitative Analysis of Wild Type(wt) and Setd2 knockout(ko) mESCs Transcriptomes [RNA-Seq]

ABSTRACT: 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.

ORGANISM(S): Mus musculus

PROVIDER: GSE54932 | GEO | 2014/10/14

SECONDARY ACCESSION(S): PRJNA238051

REPOSITORIES: GEO

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Project description:Purpose: The histone H3 lysine 36 methyltransferase SETD2 is frequently mutated in various cancers, including leukemia. However, there has not been any functional model to show the contribution of SETD2 in hematopoiesis or the causal role of SETD2 mutation in tumorigenesis. In this study, using a conditional Setd2 knock-out (KO) mouse model, we show that Setd2 deficiency skews hematopoietic differentiation and impaired HSC (hematopoietic stem cell) self-renewal. Intriguingly, Setd2-deleted HSCs, through a latency period, can acquire abilities to overcome the growth disadvantage and eventually develop into hematopoietic malignancy characteristic of myelodysplastic syndrome (MDS). This study aimed at finding the mechanism controlled by Setd2, which was required for MDS formation. Methods: Young and old Setd2 WT and KO LSKs (Lin-c-Kit+Sca1+) were generated by deep RNA-seq, using Illumina Hiseq2500. Using Stringtie (version:1.3.0) software to analyze the sequence reads that passed quality filter to acquire the expression level of all genes. qRT–PCR validation was performed using SYBR Green assays. Young Setd2 WT and KO LSKs were also generated by whole genome bisulfite sequencing (WGBS), using Illumina Hiseq2500. Results: Using an optimized data analysis workflow, 246 genes down-regulated and 226 up-regulated, showed significant differential expression (fold change, FC ≤ 0.5 or FC ≥ 2; p < 0.05) between young WT and KO LSKs. Old LSKs displayed about 1112 down-regulated and 777 up-regulated genes between WT and KO. The results of WGBS showed that the Setd2 KO genome carries a much larger number of hypomethylated DMRs (different methylation regions) relative to hypermethylated ones (5,839 versus 1,294). Conclusions: Through RNA-seq, gene expression profile of young Setd2-deleted LSKs partially resembles the Dnmt3a/Tet2 double knock-out. WGBS also indicated that Setd2 deficiency can regulate the distribution of whole genome DNA methylation. Furthermore, young Setd2 deficiency also induces DNA replication stress in HSCs, as reflected by activated E2F gene regulatory network and repressed ribonucleotide reductase subunit Rrm2b. Old Setd2-deleted LSKs displayed a MDS related transcriptional signature.

Dataset Information

Quantitative Analysis of Wild Type(wt) and Setd2 knockout(ko) mESCs Transcriptomes [RNA-Seq]

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