GSE132025
Rinf regulates pluripotency network and Tet enzymes in embryonic stem cells (ESCs)
In this study: (1) We have mapped the genome wide binding distribution and enrichment of Rinf/CXXC5 at genes and regulatory regions in mouse ESCs by ChIP-seq using a specific antibody against Rinf. (2) We have examined the role of Rinf in regulation of ESC gene expression programs by performing transcriptomic analysis of Rinf wild type and knockout ESCs by RNA-seq to identify differentially expressed genes. (3) We have investigated the role of Rinf in differentiation and lineage specification programs of ESCs by analyzing the transcriptomic profile of wild type and Rinf–/– ESCs during differentiation to embroyoid bodies (EBs) at three time points (day 0, 3, 6). Overall design: Rinf ChIP-seq: It was performed on two independent wild type V6.5 mESC lines and one Rinf–/– ESC line (negative control) as previously described (Johnson et al., 2007). To ensure the specificity of the antibody, we also performed ChIP-seq in a Rinf–/– ESC line as a negative control. Briefly, ESCs were cultured on gelatin, harvested, crosslinked, lysed, sonicated and subjected to ChIP using an anti-Rinf/CXXC5 antibody (Cat#84546S, CST). 100bp paired end sequencing was performed at the Einstein Epigenomics core following their established protocols using Illumina HiSeq 2500 platform. Reads were mapped to the mouse genome (mm10) using the software Bowtie2 (VN: 2.2.3) with default (Langmead and Salzberg, 2012). The Rinf binding peaks were called with the software MACS2 using the input as controls and default parameters (Yong Zhang et al., 2008), with the final peaks called from the merged reads of the two biological replicates. Details of ChIP-seq and data analysis are described in the methods sections of the manuscript. The ChIP-seq analysis identified a total of 2,342 Rinf peaks that were mapped to promoters and gene bodies as well as distal regulatory elements and intergenic regions. We examined the role of Rinf in regulation of ESC gene expression programs by performing transcriptomic analysis of Rinf wild type and knockout ESCs by RNA-seq to identify differentially expressed genes.  RNA-Seq of ESCs: Two independent ESC of each genotype (Wild type and Rinf KO) were cultured on feeders then pre-plated to remove feeders and seeded on gelatin overnight. Total RNA was extracted (Omega E.Z.N.A Total RNA kit), barcoded and used to prepare libraries. ERCC spike in controls were included. The libraries were subjected to 150 bp paired-end sequencing using Illumina Next Seq 500 platform at the Einstein Epigenomics core following their protocols. We generated ~25 million reads per sample. The reads were trimmed using trim galore (v 0.4.1, https://github.com/FelixKrueger/TrimGalore) to remove adapters and then mapped to mouse genome (mm10) by tophat software (v 2.0.13) with default parameters (D. Kim et al., 2013). Details of RNA-seq and data analysis are described in the methods sections of the manuscript. RNA-seq of EBs: Two independent ESC line of each genotype (Wild type and Rinf KO) were differentiated to EBs following standard hanging drop methods (described in manuscript) and total RNA was isolated (Omega E.Z.N.A Total RNA kit) at three time points (day 0, 3, 6) of differentiation (total of 12 RNA samples). Samples were barcoded and used to prepare libraries. ERCC spike in controls were included. Libraries were subjected to 75bp single-end sequencing using Illumina Next-Seq 500 platform at Einstein Epigenomics core following their protocols. We generated ~30 million reads per sample.  The reads were trimmed using trim galore (v 0.4.1, https://github.com/FelixKrueger/TrimGalore) to remove adapters and then mapped to mouse genome (mm10) by tophat software (v 2.0.13) with default parameters (D. Kim et al., 2013). Data analysis and identification of DEGs between the two genotypes for each time point are explained in detail in the manuscript methods section. Details of RNA-seq and data analysis are described in the methods sections of the manuscript.