In order to identify novel pluripotency-related oncogenes, an expression screen for oncogenic foci-inducing genes within a retroviral human embryonic stem cell cDNA library was conducted. From this screen, we identified not only known oncogenes but also intriguingly the key pluripotency factor, DPPA4 (developmental pluripotency-associated four) that encodes a DNA binding SAP domain-containing protein. DPPA4 has not been previously identified as an oncogene but is highly expressed in embryonal carcinomas, pluripotent germ cell tumors, and other cancers. DPPA4 is also mutated in some cancers. In direct transformation assays, we validated that DPPA4 is an oncogene in both mouse 3T3 cells and immortalized human dermal fibroblasts. Overexpression of DPPA4 generates oncogenic foci (sarcoma cells) and causes anchorage-independent growth. The in vitro transformed cells also give rise to tumors in immunodeficient mice. Furthermore, functional analyses indicate that both the DNA-binding SAP domain and the histone-binding C-terminal domain are critical for the oncogenic transformation activity of DPPA4. Downregulation of DPPA4 in E14 mouse embryonic stem cells and P19 mouse embryonic carcinoma cells causes decreased cell proliferation in each case. In addition, DPPA4 overexpression induces cell proliferation through genes related to regulation of G1/S transition. Interestingly, we observed similar findings for family member DPPA2. Thus, we have identified a new family of pluripotency-related oncogenes consisting of DPPA2 and DPPA4. Our findings have important implications for stem cell biology and tumorigenesis.

Developmental pluripotency associated factor 4 (Dppa4) is a highly specific marker of pluripotent cells, and is also overexpressed in certain cancers, but its function in either of these contexts is poorly understood. In this study, we use ChIP-Seq to identify Dppa4 binding genome-wide in three distinct cell types: mouse embryonic stem cells (mESC), embryonal carcinoma cells, and 3T3 fibroblasts ectopically expressing Dppa4. We find a core set of Dppa4 binding sites shared across cell types, and also a substantial number of sites unique to each cell type. Across cell types Dppa4 shows a preference for binding to regions with active chromatin signatures, and can influence chromatin modifications at target genes. In 3T3 fibroblasts with enforced Dppa4 expression, Dppa4 represses the cell cycle inhibitor Cdkn2c and activates Ets family transcription factor Etv4, leading to alterations in the cell cycle that likely contribute to the oncogenic phenotype. Dppa4 also directly regulates Etv4 in mESC but represses it in this context, and binds with Oct4 to a set of shared targets that are largely independent of Sox2 and Nanog, indicating that Dppa4 functions independently of the core pluripotency network in stem cells. Together these data provide novel insights into Dppa4 function in both pluripotent and oncogenic contexts.

Induced pluripotent stem cells (iPSCs) are an essential tool for studying cellular differentiation and cell types that are otherwise difficult to access. We investigated the use of iPSCs and iPSC-derived cells to study the impact of genetic variation on gene regulation across different cell types and as models for studies of complex disease. To do so, we established a panel of iPSCs from 58 well-studied Yoruba lymphoblastoid cell lines (LCLs); 14 of these lines were further differentiated into cardiomyocytes. We characterized regulatory variation across individuals and cell types by measuring gene expression levels, chromatin accessibility, and DNA methylation. Our analysis focused on a comparison of inter-individual regulatory variation across cell types. While most cell-type-specific regulatory quantitative trait loci (QTLs) lie in chromatin that is open only in the affected cell types, we found that 20% of cell-type-specific regulatory QTLs are in shared open chromatin. This observation motivated us to develop a deep neural network to predict open chromatin regions from DNA sequence alone. Using this approach, we were able to use the sequences of segregating haplotypes to predict the effects of common SNPs on cell-type-specific chromatin accessibility.