The chemical reprogramming of unipotent adult germ cells towards authentic pluripotency and de novo establishment of imprinting.

Although somatic cells can be reprogrammed to pluripotent stem cells (PSCs) with pure chemicals, authentic pluripotency of chemically induced pluripotent stem cells (CiPSCs) has never been achieved through tetraploid complementation assay. Spontaneous reprogramming of spermatogonial stem cells (SSCs) was another non-transgenic way to obtain PSCs, but this process lacks mechanistic explanation. Here, we reconstructed the trajectory of mouse SSC reprogramming and developed a five-chemical combination, boosting the reprogramming efficiency by nearly 80- to 100-folds. More importantly, chemical induced germline-derived PSCs (5C-gPSCs), but not gPSCs and chemical induced pluripotent stem cells, had authentic pluripotency, as determined by tetraploid complementation. Mechanistically, SSCs traversed through an inverted pathway of in vivo germ cell development, exhibiting the expression signatures and DNA methylation dynamics from spermatogonia to primordial germ cells and further to epiblasts. Besides, SSC-specific imprinting control regions switched from biallelic methylated states to monoallelic methylated states by imprinting demethylation and then re-methylation on one of the two alleles in 5C-gPSCs, which was apparently distinct with the imprinting reprogramming in vivo as DNA methylation simultaneously occurred on both alleles. Our work sheds light on the unique regulatory network underpinning SSC reprogramming, providing insights to understand generic mechanisms for cell-fate decision and epigenetic-related disorders in regenerative medicine.

The effects of sequencing depth on the assembly of coding and noncoding transcripts in the human genome.

Investigating the functions and activities of genes requires proper annotation of the transcribed units. However, transcript assembly efforts have produced a surprisingly large variation in the number of transcripts, and especially so for noncoding transcripts. This heterogeneity in assembled transcript sets might be partially explained by sequencing depth. Here, we used real and simulated short-read sequencing data as well as long-read data to systematically investigate the impact of sequencing depths on the accuracy of assembled transcripts. We assembled and analyzed transcripts from 671 human short-read data sets and four long-read data sets. At the first level, there is a positive correlation between the number of reads and the number of recovered transcripts. However, the effect of the sequencing depth varied based on cell or tissue type, the type of read and the nature and expression levels of the transcripts. The detection of coding transcripts saturated rapidly with both short and long-reads, however, there was no sign of early saturation for noncoding transcripts at any sequencing depth. Increasing long-read sequencing depth specifically benefited transcripts containing transposable elements. Finally, we show how single-cell RNA-seq can be guided by transcripts assembled from bulk long-read samples, and demonstrate that noncoding transcripts are expressed at similar levels to coding transcripts but are expressed in fewer cells. This study highlights the impact of sequencing depth on transcript assembly.

MIMIC: an optimization method to identify cell type-specific marker panel for cell sorting.

Multi-omics data allow us to select a small set of informative markers for the discrimination of specific cell types and study of cellular heterogeneity. However, it is often challenging to choose an optimal marker panel from the high-dimensional molecular profiles for a large amount of cell types. Here, we propose a method called Mixed Integer programming Model to Identify Cell type-specific marker panel (MIMIC). MIMIC maintains the hierarchical topology among different cell types and simultaneously maximizes the specificity of a fixed number of selected markers. MIMIC was benchmarked on the mouse ENCODE RNA-seq dataset, with 29 diverse tissues, for 43 surface markers (SMs) and 1345 transcription factors (TFs). MIMIC could select biologically meaningful markers and is robust for different accuracy criteria. It shows advantages over the standard single gene-based approaches and widely used dimensional reduction methods, such as multidimensional scaling and t-SNE, both in accuracy and in biological interpretation. Furthermore, the combination of SMs and TFs achieves better specificity than SMs or TFs alone. Applying MIMIC to a large collection of 641 RNA-seq samples covering 231 cell types identifies a panel of TFs and SMs that reveal the modularity of cell type association networks. Finally, the scalability of MIMIC is demonstrated by selecting enhancer markers from mouse ENCODE data. MIMIC is freely available at https://github.com/MengZou1/MIMIC.

The chromatin accessibility landscape reveals distinct transcriptional regulation in the induction of human primordial germ cell-like cells from pluripotent stem cells.

In vitro induction of human primordial germ cell-like cells (hPGCLCs) provides an ideal platform to recapitulate hPGC development. However, the detailed molecular mechanisms regulating the induction of hPGCLCs remain largely uncharacterized. Here, we profiled the chromatin accessibility and transcriptome dynamics throughout the process of hPGCLC induction. Genetic ablation of SOX15 indicated the crucial roles of SOX15 in the maintenance of hPGCLCs. Mechanistically, SOX15 exerted its roles via suppressing somatic gene expression and sustaining latent pluripotency. Notably, ETV5, a downstream regulator of SOX15, was also uncovered to be essential for hPGCLC maintenance. Finally, a stepwise switch of OCT4/SOX2, OCT4/SOX17, and OCT4/SOX15 binding motifs were found to be enriched in closed-to-open regions of human embryonic stem cells, and early- and late-stage hPGCLCs, respectively. Collectively, our data characterized the chromatin accessibility and transcriptome landscapes throughout hPGCLC induction and defined the SOX15-mediated regulatory networks underlying this process.

Predicting conformational ensembles and genome-wide transcription factor binding sites from DNA sequences.

DNA shape is emerging as an important determinant of transcription factor binding beyond just the DNA sequence. The only tool for large scale DNA shape estimates, DNAshape was derived from Monte-Carlo simulations and predicts four broad and static DNA shape features, Propeller twist, Helical twist, Minor groove width and Roll. The contributions of other shape features e.g. Shift, Slide and Opening cannot be evaluated using DNAshape. Here, we report a novel method DynaSeq, which predicts molecular dynamics-derived ensembles of a more exhaustive set of DNA shape features. We compared the DNAshape and DynaSeq predictions for the common features and applied both to predict the genome-wide binding sites of 1312 TFs available from protein interaction quantification (PIQ) data. The results indicate a good agreement between the two methods for the common shape features and point to advantages in using DynaSeq. Predictive models employing ensembles from individual conformational parameters revealed that base-pair opening - known to be important in strand separation - was the best predictor of transcription factor-binding sites (TFBS) followed by features employed by DNAshape. Of note, TFBS could be predicted not only from the features at the target motif sites, but also from those as far as 200 nucleotides away from the motif.

Genomic and molecular control of cell type and cell type conversions.

Organisms are made of a limited number of cell types that combine to form higher order tissues and organs. Cell types have traditionally been defined by their morphologies or biological activity, yet the underlying molecular controls of cell type remain unclear. The onset of single cell technologies, and more recently genomics (particularly single cell genomics), has substantially increased the understanding of the concept of cell type, but has also increased the complexity of this understanding. These new technologies have added a new genome wide molecular dimension to the description of cell type, with genome-wide expression and epigenetic data acting as a cell type 'fingerprint' to describe the cell state. Using these genomic fingerprints cell types are being increasingly defined based on specific genomic and molecular criteria, without necessarily a distinct biological function. In this review, we will discuss the molecular definitions of cell types and cell type control, and particularly how endogenous and exogenous transcription factors can control cell types and cell type conversions.

Generation and Analysis of GATA2w/eGFP Human ESCs Reveal ITGB3/CD61 as a Reliable Marker for Defining Hemogenic Endothelial Cells during Hematopoiesis.

The transition from hemogenic endothelial cells (HECs) to hematopoietic stem/progenitor cells (HS/PCs), or endothelial to hematopoietic transition (EHT), is a critical step during hematopoiesis. However, little is known about the molecular determinants of HECs due to the challenge in defining HECs. We report here the generation of GATA2w/eGFP reporter in human embryonic stem cells (hESCs) to mark cells expressing GATA2, a critical gene for EHT. We show that during differentiation, functional HECs are almost exclusively GATA2/eGFP+. We then constructed a regulatory network for HEC determination and also identified a panel of positive or negative surface markers for discriminating HECs from non-hemogenic ECs. Among them, ITGB3 (CD61) precisely labeled HECs both in hESC differentiation and embryonic day 10 mouse embryos. These results not only identify a reliable marker for defining HECs, but also establish a robust platform for dissecting hematopoiesis in vitro, which might lead to the generation of HSCs in vitro.

The cancer-associated CTCFL/BORIS protein targets multiple classes of genomic repeats, with a distinct binding and functional preference for humanoid-specific SVA transposable elements.

BACKGROUND: A common aberration in cancer is the activation of germline-specific proteins. The DNA-binding proteins among them could generate novel chromatin states, not found in normal cells. The germline-specific transcription factor BORIS/CTCFL, a paralog of chromatin architecture protein CTCF, is often erroneously activated in cancers and rewires the epigenome for the germline-like transcription program. Another common feature of malignancies is the changed expression and epigenetic states of genomic repeats, which could alter the transcription of neighboring genes and cause somatic mutations upon transposition. The role of BORIS in transposable elements and other repeats has never been assessed. RESULTS: The investigation of BORIS and CTCF binding to DNA repeats in the K562 cancer cells dependent on BORIS for self-renewal by ChIP-chip and ChIP-seq revealed three classes of occupancy by these proteins: elements cohabited by BORIS and CTCF, CTCF-only bound, or BORIS-only bound. The CTCF-only enrichment is characteristic for evolutionary old and inactive repeat classes, while BORIS and CTCF co-binding predominately occurs at uncharacterized tandem repeats. These repeats form staggered cluster binding sites, which are a prerequisite for CTCF and BORIS co-binding. At the same time, BORIS preferentially occupies a specific subset of the evolutionary young, transcribed, and mobile genomic repeat family, SVA. Unlike CTCF, BORIS prominently binds to the VNTR region of the SVA repeats in vivo. This suggests a role of BORIS in SVA expression regulation. RNA-seq analysis indicates that BORIS largely serves as a repressor of SVA expression, alongside DNA and histone methylation, with the exception of promoter capture by SVA. CONCLUSIONS: Thus, BORIS directly binds to, and regulates SVA repeats, which are essentially movable CpG islands, via clusters of BORIS binding sites. This finding uncovers a new function of the global germline-specific transcriptional regulator BORIS in regulating and repressing the newest class of transposable elements that are actively transposed in human genome when activated. This function of BORIS in cancer cells is likely a reflection of its roles in the germline.

Remission for Loss of Odontogenic Potential in a New Micromilieu In Vitro.

During embryonic organogenesis, the odontogenic potential resides in dental mesenchyme from the bud stage until birth. Mouse dental mesenchymal cells (mDMCs) isolated from the inductive dental mesenchyme of developing molars are frequently used in the context of tooth development and regeneration. We wondered if and how the odontogenic potential could be retained when mDMCs were cultured in vitro. In the present study, we undertook to test the odontogenic potential of cultured mDMCs and attempted to maintain the potential during culturing. We found that cultured mDMCs could retain the odontogenic potential for 24 h with a ratio of 60% for tooth formation, but mDMCs were incapable of supporting tooth formation after more than 24 h in culture. This loss of odontogenic potential was accompanied by widespread transcriptomic alteration and, specifically, the downregulation of some dental mesenchyme-specific genes, such as Pax9, Msx1, and Pdgfrα. To prolong the odontogenic potential of mDMCs in vitro, we then cultured mDMCs in a serum-free medium with Knockout Serum Replacement (KSR) and growth factors (fibroblastic growth factor 2 and epidermal growth factor). In this new micromilieu, mDMCs could maintain the odontogenic potential for 48 h with tooth formation ratio of 50%. Moreover, mDMCs cultured in KSR-supplemented medium gave rise to tooth-like structures when recombined with non-dental second-arch epithelium. Among the supplements, KSR is essential for the survival and adhesion of mDMCs, and both Egf and Fgf2 induced the expression of certain dental mesenchyme-related genes. Taken together, our results demonstrated that the transcriptomic changes responded to the alteration of odontogenic potential in cultured mDMCs and a new micromilieu partly retained this potential in vitro, providing insight into the long-term maintenance of odontogenic potential in mDMCs.

TGFß signaling regulates the choice between pluripotent and neural fates during reprogramming of human urine derived cells.

Human urine cells (HUCs) can be reprogrammed into neural progenitor cells (NPCs) or induced pluripotent stem cells (iPSCs) with defined factors and a small molecule cocktail, but the underlying fate choice remains unresolved. Here, through sequential removal of individual compound from small molecule cocktail, we showed that A8301, a TGFß signaling inhibitor, is sufficient to switch the cell fate from iPSCs into NPCs in OSKM-mediated HUCs reprogramming. However, TGFß exposure at early stage inhibits HUCs reprogramming by promoting EMT. Base on these data, we developed an optimized approach for generation of NPCs or iPSCs from HUCs with significantly improved efficiency by regulating TGFß activity at different reprogramming stages. This approach provides a simplified and improved way for HUCs reprogramming, thus would be valuable for banking human iPSCs or NPCs from people with different genetic background.

Transient Activation of Mitoflashes Modulates Nanog at the Early Phase of Somatic Cell Reprogramming.

The mechanisms of somatic cell reprogramming have been revealed at multiple levels. However, the lack of tools to monitor different reactive oxygen species (ROS) has left their distinct signals and roles in reprogramming unknown. We hypothesized that mitochondrial flashes (mitoflashes), recently identified spontaneous bursts of mitochondrial superoxide signaling, play a role in reprogramming. Here we show that the frequency of mitoflashes transiently increases, accompanied by flash amplitude reduction, during the early stages of reprogramming. This transient activation of mitoflashes at the early stage enhances reprogramming, whereas sustained activation impairs reprogramming. The reprogramming-promoting function of mitoflashes occurs via the upregulation of Nanog expression that is associated with decreases in the methylation status of the Nanog promoter through Tet2 occupancy. Together our findings provide a previously unknown role for superoxide signaling mediated epigenetic regulation in cell fate determination.

Transposable elements at the center of the crossroads between embryogenesis, embryonic stem cells, reprogramming, and long non-coding RNAs.

Transposable elements (TEs) are mobile genomic sequences of DNA capable of autonomous and non-autonomous duplication. TEs have been highly successful, and nearly half of the human genome now consists of various families of TEs. Originally thought to be non-functional, these elements have been co-opted by animal genomes to perform a variety of physiological functions ranging from TE-derived proteins acting directly in normal biological functions, to innovations in transcription factor logic and influence on epigenetic control of gene expression. During embryonic development, when the genome is epigenetically reprogrammed and DNA-demethylated, TEs are released from repression and show embryonic stage-specific expression, and in human and mouse embryos, intact TE-derived endogenous viral particles can even be detected. A similar process occurs during the reprogramming of somatic cells to pluripotent cells: When the somatic DNA is demethylated, TEs are released from repression. In embryonic stem cells (ESCs), where DNA is hypomethylated, an elaborate system of epigenetic control is employed to suppress TEs, a system that often overlaps with normal epigenetic control of ESC gene expression. Finally, many long non-coding RNAs (lncRNAs) involved in normal ESC function and those assisting or impairing reprogramming contain multiple TEs in their RNA. These TEs may act as regulatory units to recruit RNA-binding proteins and epigenetic modifiers. This review covers how TEs are interlinked with the epigenetic machinery and lncRNAs, and how these links influence each other to modulate aspects of ESCs, embryogenesis, and somatic cell reprogramming.

The oncogene c-Jun impedes somatic cell reprogramming.

Oncogenic transcription factors are known to mediate the conversion of somatic cells to tumour or induced pluripotent stem cells (iPSCs). Here we report c-Jun as a barrier for iPSC formation. c-Jun is expressed by and required for the proliferation of mouse embryonic fibroblasts (MEFs), but not mouse embryonic stem cells (mESCs). Consistently, c-Jun is induced during mESC differentiation, drives mESCs towards the endoderm lineage and completely blocks the generation of iPSCs from MEFs. Mechanistically, c-Jun activates mesenchymal-related genes, broadly suppresses the pluripotent ones, and derails the obligatory mesenchymal to epithelial transition during reprogramming. Furthermore, inhibition of c-Jun by shRNA, dominant-negative c-Jun or Jdp2 enhances reprogramming and replaces Oct4 among the Yamanaka factors. Finally, Jdp2 anchors 5 non-Yamanaka factors (Id1, Jhdm1b, Lrh1, Sall4 and Glis1) to reprogram MEFs into iPSCs. Our studies reveal c-Jun as a guardian of somatic cell fate and its suppression opens the gate to pluripotency.

Genomic analysis of LPS-stimulated myeloid cells identifies a common pro-inflammatory response but divergent IL-10 anti-inflammatory responses.

Inflammation is an essential physiological response to infection and injury that must be kept within strict bounds. The IL-10/STAT3 anti-inflammatory response (AIR) is indispensable for controlling the extent of inflammation, although the complete mechanisms downstream of STAT3 have not yet been elucidated. The AIR is widely known to extend to other myeloid cells, but it has best been characterized in macrophages. Here we set out to characterize the LPS-mediated pro-inflammatory response and the AIR across a range of myeloid cells. We found that whereas the LPS-induced pro-inflammatory response is broadly similar among macrophages, dendritic cells, neutrophils, mast cells and eosinophils, the AIR is drastically different across all myeloid cell types that respond to IL-10 (all bar eosinophils). We propose a model whereby the IL-10/STAT3 AIR works by selectively inhibiting specific pathways in distinct cell types: in macrophages the AIR most likely works through the inhibition of NF-κB target genes; in DCs and mast cells through indirect IRF disruption; and in neutrophils through IRF disruption and possibly also indirect NF-κB inhibition. In summary, no conserved IL-10/STAT3 AIR effectors were identified; instead a cell type-specific model of the AIR is proposed.

glbase: a framework for combining, analyzing and displaying heterogeneous genomic and high-throughput sequencing data.

Genomic datasets and the tools to analyze them have proliferated at an astonishing rate. However, such tools are often poorly integrated with each other: each program typically produces its own custom output in a variety of non-standard file formats. Here we present glbase, a framework that uses a flexible set of descriptors that can quickly parse non-binary data files. glbase includes many functions to intersect two lists of data, including operations on genomic interval data and support for the efficient random access to huge genomic data files. Many glbase functions can produce graphical outputs, including scatter plots, heatmaps, boxplots and other common analytical displays of high-throughput data such as RNA-seq, ChIP-seq and microarray expression data. glbase is designed to rapidly bring biological data into a Python-based analytical environment to facilitate analysis and data processing. In summary, glbase is a flexible and multifunctional toolkit that allows the combination and analysis of high-throughput data (especially next-generation sequencing and genome-wide data), and which has been instrumental in the analysis of complex data sets. glbase is freely available at http://bitbucket.org/oaxiom/glbase/.

Where cell fate conversions meet Chinese philosophy.

Accumulating evidence indicates that the mesenchymal-epithelial transition (MET) and epithelial-mesenchymal transition (EMT) are basic mechanisms for cell fate conversion and may help us understand both physiologic and pathologic processes such as development and carcinogenesis. Here, we further suggest that mammalian cells fall into two grand divisions, mesenchymal or epithelial; interconversions between these two grand divisions through EMT/MET resonate with some ancient Chinese philosophic ideas.

Systematic identification of transcriptional regulatory modules from protein-protein interaction networks.

Transcription factors (TFs) combine with co-factors to form transcriptional regulatory modules (TRMs) that regulate gene expression programs with spatiotemporal specificity. Here we present a novel and generic method (rTRM) for the reconstruction of TRMs that integrates genomic information from TF binding, cell type-specific gene expression and protein-protein interactions. rTRM was applied to reconstruct the TRMs specific for embryonic stem cells (ESC) and hematopoietic stem cells (HSC), neural progenitor cells, trophoblast stem cells and distinct types of terminally differentiated CD4(+) T cells. The ESC and HSC TRM predictions were highly precise, yielding 77 and 96 proteins, of which ∼75% have been independently shown to be involved in the regulation of these cell types. Furthermore, rTRM successfully identified a large number of bridging proteins with known roles in ESCs and HSCs, which could not have been identified using genomic approaches alone, as they lack the ability to bind specific DNA sequences. This highlights the advantage of rTRM over other methods that ignore PPI information, as proteins need to interact with other proteins to form complexes and perform specific functions. The prediction and experimental validation of the co-factors that endow master regulatory TFs with the capacity to select specific genomic sites, modulate the local epigenetic profile and integrate multiple signals will provide important mechanistic insights not only into how such TFs operate, but also into abnormal transcriptional states leading to disease.

The repertoires of ubiquitinating and deubiquitinating enzymes in eukaryotic genomes.

Reversible protein ubiquitination regulates virtually all known cellular activities. Here, we present a quantitatively evaluated and broadly applicable method to predict eukaryotic ubiquitinating enzymes (UBE) and deubiquitinating enzymes (DUB) and its application to 50 distinct genomes belonging to four of the five major phylogenetic supergroups of eukaryotes: unikonts (including metazoans, fungi, choanozoa, and amoebozoa), excavates, chromalveolates, and plants. Our method relies on a collection of profile hidden Markov models, and we demonstrate its superior performance (coverage and classification accuracy >99%) by identifying approximately 25% and approximately 35% additional UBE and DUB genes in yeast and human, which had not been reported before. In yeast, we predict 85 UBE and 24 DUB genes, for 814 UBE and 107 DUB genes in the human genome. Most UBE and DUB families are present in all eukaryotic lineages, with plants and animals harboring massively enlarged repertoires of ubiquitin ligases. Unicellular organisms, on the other hand, typically harbor less than 300 UBEs and less than 40 DUBs per genome. Ninety-one UBE/DUB genes are orthologous across all four eukaryotic supergroups, and these likely represent a primordial core of enzymes of the ubiquitination system probably dating back to the first eukaryotes approximately 2 billion years ago. Our genome-wide predictions are available through the Database of Ubiquitinating and Deubiquitinating Enzymes (www.DUDE-db.org), where users can also perform advanced sequence and phylogenetic analyses and submit their own predictions.

Distinct transcriptional regulatory modules underlie STAT3's cell type-independent and cell type-specific functions.

Transcription factors (TFs) regulate gene expression by binding to short DNA sequence motifs, yet their binding specificities alone cannot explain how certain TFs drive a diversity of biological processes. In order to investigate the factors that control the functions of the pleiotropic TF STAT3, we studied its genome-wide binding patterns in four different cell types: embryonic stem cells, CD4(+) T cells, macrophages and AtT-20 cells. We describe for the first time two distinct modes of STAT3 binding. First, a small cell type-independent mode represented by a set of 35 evolutionarily conserved STAT3-binding sites that collectively regulate STAT3's own functions and cell growth. We show that STAT3 is recruited to sites with E2F1 already pre-bound before STAT3 activation. Second, a series of different transcriptional regulatory modules (TRMs) assemble around STAT3 to drive distinct transcriptional programs in the four cell types. These modules recognize cell type-specific binding sites and are associated with factors particular to each cell type. Our study illustrates the versatility of STAT3 to regulate both universal- and cell type-specific functions by means of distinct TRMs, a mechanism that might be common to other pleiotropic TFs.