Summary Naïve and primed pluripotency is characterized by distinct signaling requirements, transcriptomes and developmental properties, but both cellular states share key transcriptional regulators, Oct4, Sox2 and Nanog. Here we demonstrate that transition between these two pluripotent states is associated with widespread Oct4 relocalization, mirrored by global rearrangement of enhancer chromatin landscapes. Our genomic and biochemical analyses identified candidate mediators of primed state-specific Oct4 binding, including Otx2 and Zic2/3. Even when differentiation cues are blocked, premature Otx2 overexpression is sufficient to exit the naïve state, induce transcription of a substantial subset of primed pluripotency-associated genes and redirect Oct4 to previously inaccessible enhancer sites. However, ability of Otx2 to engage new enhancer regions is determined by its levels, cis-encoded properties of the sites and signaling environment. Our results illuminate regulatory mechanisms underlying pluripotency and suggest that capacity of transcription factors such as Otx2 and Oct4 to pioneer new enhancer sites is highly context-dependent.

Summary Cis-regulatory changes play a central role in morphological divergence, yet the regulatory principles underlying emergence of human traits remain poorly understood. Here we use epigenomic profiling from human and chimpanzee cranial neural crest cells to systematically and quantitatively annotate divergence of craniofacial cis-regulatory landscapes. Epigenomic divergence is attributable to genetic variation within TF motifs at orthologous enhancers, with a novel motif being most predictive of activity biases. We explore properties of this cis-regulatory change, revealing the role of particular retroelements, uncovering broad clusters of species-biased enhancers near genes associated with human facial variation, and demonstrating that cis-regulatory divergence is linked to quantitative expression differences of crucial neural crest regulators. Our work provides a wealth of candidates for future evolutionary studies and demonstrates the value of ‘cellular anthropology’, a strategy of using in vitro-derived embryonic cell types to elucidate both fundamental and evolving mechanisms underlying morphological variation in higher primates.

Oligodendrocyte development and myelination rely on an unusual membrane-associated transcription factor that shares functional domains with bacteriophage proteins.

Author contributions L.X. and A.M contributed equally to this study. S.M., E.M. and A.B. planned the study, with input from M.P.S. and J.W. S.M. and E.M. performed the reprogramming experiments, and analysed and interpreted data. S.M., E.M. and L.X. wrote the manuscript with the help of A.B. S.M. generated, processed and analysed bulk and single-cell RNA-seq datasets, analysed the metabolomics data, and performed most THY1-related and conditioned medium experiments. E.M. generated and propagated transgene-free iPS cell lines. All other studies were done by both E.M and S.M., unless otherwise noted. A.M. and S.M. performed wound healing experiments under the supervision of M.T.L. L.X. helped with reprogramming, FACS, and immunofluorescence experiments. F.J. generated the in vitro single-cell RNA-seq data under the supervision of M.P.S. R.S. generated the ChIP-seq libraries under the supervision of J.W. K.H. helped with statistics and PAGODA analysis. X.L. performed metabolomics experiments and helped with metabolomics data analysis and validation under the supervision of M.P.S. K.D. helped with reprogramming and western blotting experiments. L.P. helped with reprogramming and RT-qPCR experiments. C.E.A. and Y.S. performed the induced neuron reprogramming experiment under the supervision of M.W. B.A.B. helped with analysis of the epigenomic data. A.L.S.C. identified and collected the human samples. All authors discussed the results and commented on the manuscript. Data availabilityAll raw sequencing reads for population RNA-seq, ChIP-seq and single-cell RNA-seq data can be found under BioProject PRJNA316110. The command and configuration files, in addition to a list of all versioned dependencies present in the running environment, are available on the Github repository for this paper (https://github.com/brunetlab/Mahmoudi_et_al_2018) (except for the code for the processing of metabolomics data, which is available upon request).