Oct4:Sox2 binding is essential for establishing but not maintaining active and silent states of dynamically regulated genes in pluripotent cells

Abstract

Much has been learned about the mechanisms of action of pluripotency factors Oct4 and Sox2. However, as with other regulators of cell identity, little is known about the impact of disrupting their binding motifs in a native environment or the characteristics of genes they regulate. By quantitatively examining dynamic ranges of gene expression instead of focusing on conventional measures of differential expression, we found that Oct4 and Sox2 enhancer binding is strongly enriched near genes subject to large dynamic ranges of expression among cell types, with binding sites near these genes usually within superenhancers. Mutagenesis of representative Oct4:Sox2 motifs near such active, dynamically regulated genes revealed critical roles in transcriptional activation during reprogramming, with more limited roles in transcriptional maintenance in the pluripotent state. Furthermore, representative motifs near silent genes were critical for establishing but not maintaining the fully silent state, while genes whose transcript levels varied by smaller magnitudes among cell types were unaffected by nearby Oct4:Sox2 motifs. These results suggest that Oct4 and Sox2 directly establish both active and silent transcriptional states in pluripotent cells at a large number of genes subject to dynamic regulation during mammalian development, but are less important than expected for maintaining transcriptional states.

Keywords: Oct4; Sox2; differentiation; embryonic stem cells; pluripotency; transcription.

Figure 1.

Delineation of ESC-specific, dynamic, and broadly expressed gene classes by deep RNA-seq analysis of nascent transcripts and analysis of ENCODE RNA-seq data sets. (A) Chromatin-associated nascent transcripts from the mouse CCE ESC line (ESC), E14.5 cortical neurons (NEUR), bone marrow-derived macrophages (BMDM), and CD4⁺CD8⁺ double-positive thymocytes (DP) were analyzed by RNA-seq. The smallest fold difference between the ESC RPKM and the RPKMs for the three somatic cells is shown for 3030 ESC-expressed genes (more than five RPKM in ESCs). Six fold difference bins are color-coded, with the number of genes in each bin in parentheses. Only 3% of the genes exhibit a fold difference of >20 for all three somatic cell types. (B) A heat map is shown for genes from the nascent transcript data classified as ESC-specific (91 genes), broadly expressed (1931), and dynamic (248) according to the criteria described in the text. Expression levels are presented as percentiles derived from RPKM, with the highest RPKM among all genes in all cell types defined as 100%. The minimum fold difference in RPKM between ESCs and the three somatic cell types is displayed at the bottom. (C) Nascent transcript levels (RPKM) are shown for representative ESC-specific (Pla2g1b), broadly expressed (Pds5a), and dynamic (Zfp57) genes. (D) The numbers of genes in each of the three classes from an analysis of 13 ENCODE data sets are shown, along with the criteria used to assign genes to each class. The analysis was restricted to genes expressed >4.9 RPKM in ESCs.

Figure 2.

Oct4 and Sox2 binding is enriched near ESC-specific and dynamic gene classes in comparison with broadly expressed genes. (A) The genomic distribution of Oct4 and Sox2 binding peaks is shown, based on ChIP-seq data sets from the mouse ESC line V6.5 (Chronis et al. 2017). (B) The overlap of Oct4 and Sox2 peaks is shown, with a peak summit distance <100 bp required for inclusion as a cobound site. Venn diagrams display overlap when all Oct4 and Sox2 called peaks are analyzed (left), when the analysis is restricted to peaks with peak scores >20 (middle), and when the analysis was further restricted to peaks within 15 kb of a TSS (right). (C) The degree of enrichment is shown for Oct4:Sox2-cobound peaks near ESC-specific and dynamic genes in comparison with broadly expressed genes. The percentage of genes in each class that exhibit nearby (<15 kb from TSS) Oct4:Sox2-cobound peaks (peak scores >20) is also shown. (D) De novo motif discovery at Oct4:Sox2-cobound peaks (peak score >20) near ESC-specific, dynamic, broadly expressed, and silent genes shows strong enrichment of Oct4:Sox2 composite motifs but no large differences at the different gene classes. (E) The distribution of histone H3K27ac ChIP-seq and ATAC-seq signals (RPKM) coinciding with Oct4:Sox2-cobound sites near genes in the ESC-specific, dynamic, broadly expressed, and silent gene classes (from the nascent transcript analysis) is shown. (F) The percentage of Oct4:Sox2-cobound sites that fit the criteria of superenhancers and typical enhancers (Whyte et al. 2013) is shown for cobound sites near each of the four classes of genes identified in the nascent transcript analysis.

Figure 3.

CRISPR-HDR mutagenesis reveals only a moderate role for an Oct4:Sox2 composite motif near the ESC-specific Pla2g1b gene. (A) The bar graph shows the Pla2g1b mRNA profile (RPKM) derived from an analysis of 13 mouse ENCODE RNA-seq data sets. (B) Genome browser snapshots display Oct4 and Sox2 binding, as well as ATAC-seq and histone H3K27ac ChIP-seq peaks, upstream of Pla2g1b. The Oct4:Sox2 composite motif at this location and the mutant sequence introduced by CRISPR-HDR are also shown. (C,D) Oct4 and Sox2 binding at the Pla2g1b upstream region was examined by ChIP-qPCR in wild-type ESCs and in two independent mutant clones. Fold enrichment was calculated as the fold change of percentage of input between the Pla2g1b ChIP-qPCR signal and a negative control region signal (Hbb-b2). IgG was used as a negative control. (E) The normalized expression levels for Pla2g1b mRNA were determined in the two independent clones by qRT-PCR, with BMDM mRNA analyzed as a negative control.

Figure 4.

A tetO-OSKM iPSC line can be used to study gene expression changes during differentiation and secondary reprogramming. (A) The schematic diagram displays the experimental design used to edit the tetO-OSKM iPSC line (by cotransfection with HDR template and Cas9/sgRNA plasmid, as well as selection/genotyping of single-cell colonies). (B) Representative cell culture morphologies are shown for primary iPSCs, EBs, neural progenitors, and secondary iPSCs. (C) The line graph shows mRNA levels monitored by qRT-PCR for seven genes often used to define a pluripotent state. mRNA levels are displayed as a percentage of Gapdh levels. (D) The line graph shows mRNA levels monitored by qRT-PCR for four genes known to be selectively expressed in neural lineage cells.

Figure 5.

Critical role for the Pla2g1b Oct4:Sox2 composite motif in gene activation during secondary reprogramming but not for transcriptional maintenance. (A) Bar graphs show Oct4 and Sox2 binding monitored by ChIP-qPCR at the Pla2g1b enhancer in wild-type and in two independent mutant tetO-OSKM lines in primary iPSCs and day 14 secondary iPSCs. Data are displayed as in Figure 3C. (B) The line graph shows normalized Pla2g1b mRNA levels (by qRT-PCR) in wild-type and two independent mutant tetO-OSKM lines at each stage of differentiation and secondary reprogramming. Values represent means of three independent samples along with standard errors. (C) A genome browser snapshot displays the Oct4 and Sox2 ChIP-seq peaks, ATAC-seq peak, and H3K27ac peak at the Pla2g1b enhancer in ESCs. Blue shades highlight two regions with enriched H3K27ac. At the bottom, bar graphs show H3K27ac ChIP-qPCR levels at the two highlighted regions in wild-type and two independent mutant tetO-OSKM lines at each stage of differentiation and reprogramming. Comparable results were obtained in three independent experiments.

Figure 6.

Critical role for an Oct4:Sox2 composite motif near the dynamic Zfp57 gene in gene activation during secondary reprogramming but not in transcriptional maintenance. (A) The bar graph shows Zfp57 mRNA levels (RPKM from mouse ENCODE RNA-seq data sets) in 13 cell populations. (B) Genome browser snapshots display the Oct4 and Sox2 ChIP-seq, ATAC-seq, and H3K27ac ChIP-seq peaks in ESCs, as well as H3K27ac ChIP-seq peaks in NPCs. Blue shading highlights two genomic regions (E1 and E2) with H3K27ac ChIP-seq peaks flanking the Oct4:Sox2 composite motif. Green shading highlights two additional genomic regions (E3 and E4) with H3K27ac peaks, one of which exhibits a strong H3K27ac peak in NPCs. (C) Bar graphs show Oct4 and Sox2 binding monitored by ChIP-qPCR at the Zfp57 enhancer in wild-type and two independent mutant tetO-OSKM lines in primary iPSCs and day 14 secondary iPSCs. Data are displayed as in Figure 3C. (D) The line graph shows normalized Zfp57 mRNA levels (by qRT-PCR) in wild-type and two independent mutant tetO-OSKM lines at each stage of differentiation and secondary reprogramming. Values represent means of three independent samples along with standard errors. (E) Bar graphs show H3K27ac ChIP-qPCR levels at the Zfp57 E1 and E2 regions in wild-type and mutant tetO-OSKM lines at each stage of differentiation and reprogramming. Comparable results were obtained in three independent experiments. (F) Bar graphs show H3K27ac ChIP-qPCR levels at the Zfp57 E3 and E4 regions in wild-type and mutant tetO-OSKM lines at each stage of differentiation and reprogramming.

Figure 7.

Roles for Oct4:Sox2 composite motifs near the silent Oxgr1 and Gnrhr genes in establishing a silent state during secondary reprogramming but not for maintaining silencing in tetO-OSKM iPSCs. (A) Genome browser snapshots display Oct4 and Sox2 ChIP-seq, ATAC-seq, H3K27ac ChIP-seq, H3K9me3 ChIP-seq, and H3K27me3 ChIP-seq tracks at the silent Oxgr1 locus in mouse ESCs. Yellow shading highlights the region containing the Oct4:Sox2 composite motif. Red shading highlights two other regions (E2 and E3) analyzed here. (B) Bar graphs show Oct4 and Sox2 binding monitored by ChIP-qPCR at the Oxgr1 enhancer in wild-type and two independent mutant tetO-OSKM lines in primary iPSCs and day 14 secondary iPSCs. Data are displayed as in Figure 3C. (C) The line graph shows normalized Oxgr1 mRNA levels (by qRT-PCR) in wild-type and two independent mutant tetO-OSKM lines at each stage of differentiation and secondary reprogramming. Values represent means of three independent samples along with standard errors. (D) Bar graphs show H3K9me3 and H3K27me3 ChIP-qPCR levels at the Oxgr1 E1, E2, and E3 regions in wild-type and mutant tetO-OSKM lines at each stage of differentiation. (E–H) Data analogous to those in A–D are shown for the silent Gnrhr gene.