Abstract:SUMMARY
Alternative splicing (AS) plays a critical role in cell fate transitions, development, and disease. Recent studies have shown that AS also influences pluripotency and somatic cell reprogramming. We profiled transcriptome-wide AS changes that occur during reprogramming of fibroblasts to pluripotency. This analysis revealed distinct phases of AS, including a splicing program that is unique to transgene-independent induced pluripotent stem cells (iPSCs). Changes in the expression of AS factors Zcchc24, Es… Show more
“…We therefore analysed gene expression during the reprogramming of mouse fibroblasts into iPSCs via OCT4/SOX2/KLF4/MYC from two independent studies (Chen et al, 2016; Cieply et al, 2016). Specifically, we examined genes that required OCT4 for their expression in ESCs (OCT4-dependent) and separated these into genes associated with BRG1-independent or BRG1-dependent OCT4 binding at neighbouring distal regulatory elements in ESCs (see Figure 5).…”
Section: Resultsmentioning
confidence: 99%
“…In contrast, the pre-existing chromatin state at a subset of OCT4 target sites (BRG1-independent) may allow them to be activated more rapidly. Importantly, these observations suggest that chromatin structure likely plays an important role in regulating how OCT4 engages with and functions in the genome not only in mouse ESCs but also during reprogramming and development.10.7554/eLife.22631.017Figure 6.BRG1-dependency reveals distinct modes of OCT4 function of distal regulatory elements during reprogramming and development.( A ) A time course of gene expression changes (log2 fold change) during OKSM-mediated reprogramming of mouse embryonic fibroblasts to iPSCs (Chen et al, 2016; Cieply et al, 2016). The expression changes of OCT4-dependent genes neighbouring the 20% of distal OCT4 targets that were most dependent upon BRG1 for normal OCT4 binding (BRG1-dependent) or the 20% of distal OCT4 targets that were least dependent (BRG1-independent) following BRG1 removal were quantified and visualised as a smoothed trendline ±95% confidence interval.…”
Pioneer transcription factors recognise and bind their target sequences in inaccessible chromatin to establish new transcriptional networks throughout development and cellular reprogramming. During this process, pioneer factors establish an accessible chromatin state to facilitate additional transcription factor binding, yet it remains unclear how different pioneer factors achieve this. Here, we discover that the pluripotency-associated pioneer factor OCT4 binds chromatin to shape accessibility, transcription factor co-binding, and regulatory element function in mouse embryonic stem cells. Chromatin accessibility at OCT4-bound sites requires the chromatin remodeller BRG1, which is recruited to these sites by OCT4 to support additional transcription factor binding and expression of the pluripotency-associated transcriptome. Furthermore, the requirement for BRG1 in shaping OCT4 binding reflects how these target sites are used during cellular reprogramming and early mouse development. Together this reveals a distinct requirement for a chromatin remodeller in promoting the activity of the pioneer factor OCT4 and regulating the pluripotency network.DOI:
http://dx.doi.org/10.7554/eLife.22631.001
“…We therefore analysed gene expression during the reprogramming of mouse fibroblasts into iPSCs via OCT4/SOX2/KLF4/MYC from two independent studies (Chen et al, 2016; Cieply et al, 2016). Specifically, we examined genes that required OCT4 for their expression in ESCs (OCT4-dependent) and separated these into genes associated with BRG1-independent or BRG1-dependent OCT4 binding at neighbouring distal regulatory elements in ESCs (see Figure 5).…”
Section: Resultsmentioning
confidence: 99%
“…In contrast, the pre-existing chromatin state at a subset of OCT4 target sites (BRG1-independent) may allow them to be activated more rapidly. Importantly, these observations suggest that chromatin structure likely plays an important role in regulating how OCT4 engages with and functions in the genome not only in mouse ESCs but also during reprogramming and development.10.7554/eLife.22631.017Figure 6.BRG1-dependency reveals distinct modes of OCT4 function of distal regulatory elements during reprogramming and development.( A ) A time course of gene expression changes (log2 fold change) during OKSM-mediated reprogramming of mouse embryonic fibroblasts to iPSCs (Chen et al, 2016; Cieply et al, 2016). The expression changes of OCT4-dependent genes neighbouring the 20% of distal OCT4 targets that were most dependent upon BRG1 for normal OCT4 binding (BRG1-dependent) or the 20% of distal OCT4 targets that were least dependent (BRG1-independent) following BRG1 removal were quantified and visualised as a smoothed trendline ±95% confidence interval.…”
Pioneer transcription factors recognise and bind their target sequences in inaccessible chromatin to establish new transcriptional networks throughout development and cellular reprogramming. During this process, pioneer factors establish an accessible chromatin state to facilitate additional transcription factor binding, yet it remains unclear how different pioneer factors achieve this. Here, we discover that the pluripotency-associated pioneer factor OCT4 binds chromatin to shape accessibility, transcription factor co-binding, and regulatory element function in mouse embryonic stem cells. Chromatin accessibility at OCT4-bound sites requires the chromatin remodeller BRG1, which is recruited to these sites by OCT4 to support additional transcription factor binding and expression of the pluripotency-associated transcriptome. Furthermore, the requirement for BRG1 in shaping OCT4 binding reflects how these target sites are used during cellular reprogramming and early mouse development. Together this reveals a distinct requirement for a chromatin remodeller in promoting the activity of the pioneer factor OCT4 and regulating the pluripotency network.DOI:
http://dx.doi.org/10.7554/eLife.22631.001
“…CELF2, another RBP that was significantly induced during myofibroblastic differentiation of HSC, has been strongly linked to EMT in other types of stem-like cells, including those involved in hepatocarcinogenesis [24]. Conversely, RBM47, an RBP that was profoundly suppressed in MF-HSC relative to Q-HSC, has been shown to promote mesenchymal-to-epithelial transitions (MET) in pluripotent stem cells derived from mouse embryonic fibroblasts [7,25]. Therefore, our subsequent studies in HSC and injured livers focused on IGF2BP3, CELF2 and RBM47.…”
Section: Rbps Are Differentially Expressed In Quiescent and Myofibrobmentioning
confidence: 99%
“…However, Igf2bp3 is merely one of several RBPs that have been shown to regulate epithelial-to-mesenchymal transitions (EMT) and mesenchymal-to-epithelial transitions (MET) during development and carcinogenesis. Indeed, we discovered that Celf2 and Rbm47, two other RBPs that have been reported to reciprocally regulate EMT/MET in stem-like cells [7,24], are also differentially regulated as HSC become MF. Although relatively little is known about the RBP interactome that controls these complex fate decisions in any cell type, we found that knocking down Igf2bp3 also suppressed accumulation of Celf2 in HSC.…”
Section: Cellular Physiology and Biochemistrymentioning
Background/Aims: Myofibroblasts (MF) derived from quiescent nonfibrogenic hepatic stellate cells (HSC) are the major sources of fibrous matrix in cirrhosis. Because many factors interact to regulate expansion and regression of MF-HSC populations, efforts to prevent cirrhosis by targeting any one factor have had limited success, motivating research to identify mechanisms that integrate these diverse inputs. As key components of RNA regulons, RNA binding proteins (RBPs) may fulfill this function by orchestrating changes in the expression of multiple genes that must be coordinately regulated to affect the complex phenotypic modifications required for HSC transdifferentiation. Methods: We profiled the transcriptomes of quiescent and MF-HSC to identify RBPs that were differentially-expressed during HSC transdifferentiation, manipulated the expression of the most significantly induced RBP, insulin like growth factor 2 binding protein 3 (Igf2bp3), and evaluated transcriptomic and phenotypic effects. Results: Depleting Igf2bp3 changed the expression of thousands of HSC genes, including multiple targets of TGF-β signaling, and caused HSCs to reacquire a less proliferative, less myofibroblastic phenotype. RNA immunoprecipitation assays demonstrated that some of these effects were mediated by direct physical interactions between Igf2bp3 and mRNAs that control proliferative activity and mesenchymal traits. Inhibiting TGF-β receptor-1 signaling revealed a microRNA-dependent mechanism that induces Igf2bp3. Conclusions: The aggregate results indicate that HSC transdifferentiation is ultimately dictated by Igf2bp3-dependent RNA regulons and thus, can be controlled simply by manipulating Igf2bp3.
“…We illustrate these parts of the Procedure by analyzing a published time course of reprogramming to pluripotency using a doxycycline-inducible system in murine cells 23 and the directed differentiation of human induced pluripotent stem cells (iPSC) to hippocampal dentate gyrus granule neurons 24 . We have provided FASTQ files, a metadata table, as well as pre-processed query data so that the user can walk through all of these steps.…”
CellNet is a computational platform designed to assess cell populations engineered via either directed differentiation of pluripotent stem cells or via direct conversion, and to suggest specific hypotheses to improve cell fate engineering protocols. CellNet takes as input gene expression data and compares it to large data sets of normal expression profiles compiled from public sources in terms of the extent to which cell and tissue specific gene regulatory networks are established. CellNet was originally designed to work with human or mouse microarray expression data of 21 cell and tissue types. Here we describe how to apply CellNet to RNA-Seq data and how to build a completely new CellNet platform applicable to, for example, other species or additional cell and tissue types. Once the raw data has been pre-processed, running CellNet only takes several minutes whereas the time required to create a completely new CellNet requires several hours.
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