Transcriptional control of embryonic and induced pluripotent stem cells

Causal Inference Engine: a platform for directional gene set enrichment analysis and inference of active transcriptional regulators

Inference of active regulatory mechanisms underlying specific molecular and environmental perturbations is essential for understanding cellular response. The success of inference algorithms relies on the quality and coverage of the underlying network of regulator–gene interactions. Several commercial platforms provide large and manually curated regulatory networks and functionality to perform inference on these networks. Adaptation of such platforms for open-source academic applications has been hindered by the lack of availability of accurate, high-coverage networks of regulatory interactions and integration of efficient causal inference algorithms. In this work, we present CIE, an integrated platform for causal inference of active regulatory mechanisms form differential gene expression data. Using a regularized Gaussian Graphical Model, we construct a transcriptional regulatory network by integrating publicly available ChIP-seq experiments with gene-expression data from tissue-specific RNA-seq experiments. Our GGM approach identifies high confidence transcription factor (TF)–gene interactions and annotates the interactions with information on mode of regulation (activation vs. repression). Benchmarks against manually curated databases of TF–gene interactions show that our method can accurately detect mode of regulation. We demonstrate the ability of our platform to identify active transcriptional regulators by using controlled in vitro overexpression and stem-cell differentiation studies and utilize our method to investigate transcriptional mechanisms of fibroblast phenotypic plasticity.

Neural In Vitro Models for Studying Substances Acting on the Central Nervous System

Animal models have been greatly contributing to our understanding of physiology, mechanisms of diseases, and toxicity. Yet, their limitations due to, e.g., interspecies variation are reflected in the high number of drug attrition rates, especially in central nervous system (CNS) diseases. Therefore, human-based neural in vitro models for studying safety and efficacy of substances acting on the CNS are needed. Human iPSC-derived cells offer such a platform with the unique advantage of reproducing the "human context" in vitro by preserving the genetic and molecular phenotype of their donors. Guiding the differentiation of hiPSC into cells of the nervous system and combining them in a 2D or 3D format allows to obtain complex models suitable for investigating neurotoxicity or brain-related diseases with patient-derived cells. This chapter will give an overview over stem cell-based human 2D neuronal and mixed neuronal/astrocyte models, in vitro cultures of microglia, as well as CNS disease models and considers new developments in the field, more specifically the use of brain organoids and 3D bioprinted in vitro models for safety and efficacy evaluation.

m6A methylation controls pluripotency of porcine induced pluripotent stem cells by targeting SOCS3/JAK2/STAT3 pathway in a YTHDF1/YTHDF2-orchestrated manner

Embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) hold great promise for regenerative medicine, disease treatment, and organ transplantation. As the ethical issue of human ESCs and similarity of pig in human genome and physiological characteristics, the porcine iPSCs (piPSCs) have become an ideal alternative study model. N⁶-methyladenosine (m⁶A) methylation is the most prevalent modification in eukaryotic mRNAs, regulating the self-renewal and differentiation of pluripotency stem cells. However, the explicit m⁶A-regulating machinery remains controversial. Here, we demonstrate that m⁶A modification and its modulators play a crucial role in mediating piPSCs pluripotency. In brief, loss of METTL3 significantly impairs self-renewal and triggers differentiation of piPSCs by interfering JAK2 and SOCS3 expression, further inactivating JAK2-STAT3 pathway, which then blocks the transcription of KLF4 and SOX2. We identify that both of JAK2 and SOSC3 have m⁶A modification at 3'UTR by m⁶A-seq analysis. Dual-luciferase assay shows that METTL3 regulates JAK2 and SOCS3 expression in an m⁶A-dependent way. RIP-qPCR validates JAK2 and SOCS3 are the targets of YTHDF1 and YTHDF2, respectively. SiMETTL3 induced lower m⁶A levels of JAK2 and SOCS3 lead to the inhibition of YTHDF1-mediated JAK2 translation and the block of YTHDF2-dependent SOCS3 mRNA decay. Subsequently, the altered protein expressions of JAK2 and SOCS3 inhibit JAK2-STAT3 pathway and then the pluripotency of piPSCs. Collectively, our work uncovers the critical role of m⁶A modification and its modulators in regulating piPSCs pluripotency and provides insight into an orchestrated network linking the m⁶A methylation and SOCS3/JAK2/STAT3 pathway in pluripotency regulation.

Single-cell RNA-seq of human induced pluripotent stem cells reveals cellular heterogeneity and cell state transitions between subpopulations

Heterogeneity of cell states represented in pluripotent cultures has not been described at the transcriptional level. Since gene expression is highly heterogeneous between cells, single-cell RNA sequencing can be used to identify how individual pluripotent cells function. Here, we present results from the analysis of single-cell RNA sequencing data from 18,787 individual WTC-CRISPRi human induced pluripotent stem cells. We developed an unsupervised clustering method and, through this, identified four subpopulations distinguishable on the basis of their pluripotent state, including a core pluripotent population (48.3%), proliferative (47.8%), early primed for differentiation (2.8%), and late primed for differentiation (1.1%). For each subpopulation, we were able to identify the genes and pathways that define differences in pluripotent cell states. Our method identified four transcriptionally distinct predictor gene sets composed of 165 unique genes that denote the specific pluripotency states; using these sets, we developed a multigenic machine learning prediction method to accurately classify single cells into each of the subpopulations. Compared against a set of established pluripotency markers, our method increases prediction accuracy by 10%, specificity by 20%, and explains a substantially larger proportion of deviance (up to threefold) from the prediction model. Finally, we developed an innovative method to predict cells transitioning between subpopulations and support our conclusions with results from two orthogonal pseudotime trajectory methods.

Fam60al as a novel factor involved in reprogramming of somatic cell nuclear transfer in zebrafish (Danio rerio)

The main reason for abnormal development of cloned animals or embryos, and inefficient animal cloning, is a poor understanding of the reprogramming mechanism. To better comprehend reprogramming and subsequent generation of pluripotent stem cells, we must investigate factors related to reprogramming of somatic cells as nuclear donors. As we know, fam60al (family with sequence similarity 60, member A, like) is a coding gene only found in zebrafish and frog (Xenopus laevis) among vertebrates. However, until now, its functions have remained unknown. Here, we generated a zebrafish fam60al^-/- mutant line using transcription activator-like effector nucleases (TALENs), and found that both nanog and klf4b expression significantly decreased while myca expression significantly increased in fam60al^-/- mutant embryos. Concurrently, we also uncovered that in developmentally arrested embryos of somatic cell nuclear transfer, nanog, klf4b and myca expression was down-regulated, accompanying a decrease of fam60al expression. Interestingly, we identified a long noncoding RNA (lncRNA) of fam60al, named fam60al-AS, which negatively regulated fam60al by forming double-stranded RNA (dsRNA). RNase protection assay and real-time PCR confirmed these findings. Taken together, these results suggest that fam60al is a novel factor related to the reprogramming of somatic cell nuclear transfer in zebrafish, which is regulated by its reverse lncRNA.

Transcriptional and epigenetic regulation of T-helper lineage specification

Combined with TCR stimuli, extracellular cytokine signals initiate the differentiation of naive CD4(+) T cells into specialized effector T-helper (Th) and regulatory T (Treg) cell subsets. The lineage specification and commitment process occurs through the combinatorial action of multiple transcription factors (TFs) and epigenetic mechanisms that drive lineage-specific gene expression programs. In this article, we review recent studies on the transcriptional and epigenetic regulation of distinct Th cell lineages. Moreover, we review current study linking immune disease-associated single-nucleotide polymorphisms with distal regulatory elements and their potential role in the disease etiology.

CHIR99021 promotes self-renewal of mouse embryonic stem cells by modulation of protein-encoding gene and long intergenic non-coding RNA expression

Embryonic stem cells (ESCs) can proliferate indefinitely in vitro and differentiate into cells of all three germ layers. These unique properties make them exceptionally valuable for drug discovery and regenerative medicine. However, the practical application of ESCs is limited because it is difficult to derive and culture ESCs. It has been demonstrated that CHIR99021 (CHIR) promotes self-renewal and enhances the derivation efficiency of mouse (m)ESCs. However, the downstream targets of CHIR are not fully understood. In this study, we identified CHIR-regulated genes in mESCs using microarray analysis. Our microarray data demonstrated that CHIR not only influenced the Wnt/β-catenin pathway by stabilizing β-catenin, but also modulated several other pluripotency-related signaling pathways such as TGF-β, Notch and MAPK signaling pathways. More detailed analysis demonstrated that CHIR inhibited Nodal signaling, while activating bone morphogenetic protein signaling in mESCs. In addition, we found that pluripotency-maintaining transcription factors were up-regulated by CHIR, while several developmental-related genes were down-regulated. Furthermore, we found that CHIR altered the expression of epigenetic regulatory genes and long intergenic non-coding RNAs. Quantitative real-time PCR results were consistent with microarray data, suggesting that CHIR alters the expression pattern of protein-encoding genes (especially transcription factors), epigenetic regulatory genes and non-coding RNAs to establish a relatively stable pluripotency-maintaining network.

Dynamics and stability: epigenetic conversions in position effect variegation

Position effect variegation (PEV) refers to quasi-stable patterns of gene expression that are observed at specific loci throughout the genomes of eukaryotes. The genes subjected to PEV can be completely silenced or fully active. Stochastic conversions between these 2 states are responsible for the variegated phenotypes. Positional variegation is used by human pathogens (Trypanosoma, Plasmodium, and Candida) to evade the immune system or adapt to the host environment. In the yeasts Saccharomyces cerevisiae and S accharomyces pombe, telomeric PEV aids the adaptation to a changing environment. In metazoans, similar epigenetic conversions are likely to accompany cell differentiation and the setting of tissue-specific gene expression programs. Surprisingly, we know very little about the mechanisms of epigenetic conversions. In this article, earlier models on the nature of PEV are revisited and recent advances on the dynamic nature of chromatin are reviewed. The normal dynamic histone turnover during transcription and DNA replication and its perturbation at transcription and replication pause sites are discussed. It is proposed that such perturbations play key roles in epigenetic conversions and in PEV.