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      OCT4 and PAX6 determine the dual function of SOX2 in human ESCs as a key pluripotent or neural factor

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          Sox2 is a well-established pluripotent transcription factor that plays an essential role in establishing and maintaining pluripotent stem cells (PSCs). It is also thought to be a linage specifier that governs PSC neural lineage specification upon their exiting the pluripotent state. However, the exact role of SOX2 in human PSCs was still not fully understood. In this study, we studied the role of SOX2 in human embryonic stem cells (hESCs) by gain- and loss-of-function approaches and explored the possible underlying mechanisms.


          We demonstrate that knockdown of SOX2 induced hESC differentiation to endoderm-like cells, whereas overexpression of SOX2 in hESCs enhanced their pluripotency under self-renewing culture conditions but promoted their neural differentiation upon replacing the culture to non-self-renewal conditions. We show that this culture-dependent dual function of SOX2 was probably attributed to its interaction with different transcription factors predisposed by the culture environments. Whilst SOX2 interacts with OCT4 under self-renewal conditions, we found that, upon neural differentiation, PAX6, a key neural transcription factor, is upregulated and shows interaction with SOX2. The SOX2-PAX6 complex has different gene regulation pattern from that of SOX2-OCT4 complex.


          Our work provides direct evidence that SOX2 is necessarily required for hESC pluripotency; however, it can also function as a neural factor, depending on the environmental input. OCT4 and PAX6 might function as key SOX2-interacting partners that determine the function of SOX2 in hESCs.

          Electronic supplementary material

          The online version of this article (10.1186/s13287-019-1228-7) contains supplementary material, which is available to authorized users.

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          Most cited references 34

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          Direct conversion of fibroblasts to functional neurons by defined factors

          Cellular differentiation and lineage commitment are considered robust and irreversible processes during development. Recent work has shown that mouse and human fibroblasts can be reprogrammed to a pluripotent state with a combination of four transcription factors. This raised the question of whether transcription factors could directly induce other defined somatic cell fates, and not only an undifferentiated state. We hypothesized that combinatorial expression of neural lineage-specific transcription factors could directly convert fibroblasts into neurons. Starting from a pool of nineteen candidate genes, we identified a combination of only three factors, Ascl1, Brn2, and Myt1l, that suffice to rapidly and efficiently convert mouse embryonic and postnatal fibroblasts into functional neurons in vitro. These induced neuronal (iN) cells express multiple neuron-specific proteins, generate action potentials, and form functional synapses. Generation of iN cells from non-neural lineages could have important implications for studies of neural development, neurological disease modeling, and regenerative medicine.
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            A unique chromatin signature uncovers early developmental enhancers in humans.

            Cell-fate transitions involve the integration of genomic information encoded by regulatory elements, such as enhancers, with the cellular environment. However, identification of genomic sequences that control human embryonic development represents a formidable challenge. Here we show that in human embryonic stem cells (hESCs), unique chromatin signatures identify two distinct classes of genomic elements, both of which are marked by the presence of chromatin regulators p300 and BRG1, monomethylation of histone H3 at lysine 4 (H3K4me1), and low nucleosomal density. In addition, elements of the first class are distinguished by the acetylation of histone H3 at lysine 27 (H3K27ac), overlap with previously characterized hESC enhancers, and are located proximally to genes expressed in hESCs and the epiblast. In contrast, elements of the second class, which we term 'poised enhancers', are distinguished by the absence of H3K27ac, enrichment of histone H3 lysine 27 trimethylation (H3K27me3), and are linked to genes inactive in hESCs and instead are involved in orchestrating early steps in embryogenesis, such as gastrulation, mesoderm formation and neurulation. Consistent with the poised identity, during differentiation of hESCs to neuroepithelium, a neuroectoderm-specific subset of poised enhancers acquires a chromatin signature associated with active enhancers. When assayed in zebrafish embryos, poised enhancers are able to direct cell-type and stage-specific expression characteristic of their proximal developmental gene, even in the absence of sequence conservation in the fish genome. Our data demonstrate that early developmental enhancers are epigenetically pre-marked in hESCs and indicate an unappreciated role of H3K27me3 at distal regulatory elements. Moreover, the wealth of new regulatory sequences identified here provides an invaluable resource for studies and isolation of transient, rare cell populations representing early stages of human embryogenesis.
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              Identifying ChIP-seq enrichment using MACS.

               Bo Qin,  X. Liu,  Yong Zhang (2012)
              Model-based analysis of ChIP-seq (MACS) is a computational algorithm that identifies genome-wide locations of transcription/chromatin factor binding or histone modification from ChIP-seq data. MACS consists of four steps: removing redundant reads, adjusting read position, calculating peak enrichment and estimating the empirical false discovery rate (FDR). In this protocol, we provide a detailed demonstration of how to install MACS and how to use it to analyze three common types of ChIP-seq data sets with different characteristics: the sequence-specific transcription factor FoxA1, the histone modification mark H3K4me3 with sharp enrichment and the H3K36me3 mark with broad enrichment. We also explain how to interpret and visualize the results of MACS analyses. The algorithm requires ∼3 GB of RAM and 1.5 h of computing time to analyze a ChIP-seq data set containing 30 million reads, an estimate that increases with sequence coverage. MACS is open source and is available from http://liulab.dfci.harvard.edu/MACS/.

                Author and article information

                +44(0)20-75942124 , wei.cui@imperial.ac.uk
                Stem Cell Res Ther
                Stem Cell Res Ther
                Stem Cell Research & Therapy
                BioMed Central (London )
                18 April 2019
                18 April 2019
                : 10
                [1 ]ISNI 0000 0001 2113 8111, GRID grid.7445.2, Institute of Reproductive and Developmental Biology, Department of Surgery and Cancer, Faculty of Medicine, , Imperial College London, ; London, W12 0NN UK
                [2 ]ISNI 0000 0004 0530 8290, GRID grid.22935.3f, Beijing Advanced Innovation Center for Food Nutrition and Human Health, , China Agricultural University, ; Beijing, 100193 China
                [3 ]ISNI 0000 0004 0474 0428, GRID grid.231844.8, Present address: Princess Margaret Cancer Centre, , University Health Network, ; Toronto, M5G1L7 Canada
                © The Author(s). 2019

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Funded by: FundRef http://dx.doi.org/10.13039/100012156, Genesis Research Trust;
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                © The Author(s) 2019

                Molecular medicine

                sox2, oct4, pax6, neural differentiation, human embryonic stem cells


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