Integrating single-cell genomics pipelines to discover mechanisms of stem cell differentiation

Integrating population genetics, stem cell biology and cellular genomics to study complex human diseases

Human pluripotent stem (hPS) cells can, in theory, be differentiated into any cell type, making them a powerful in vitro model for human biology. Recent technological advances have facilitated large-scale hPS cell studies that allow investigation of the genetic regulation of molecular phenotypes and their contribution to high-order phenotypes such as human disease. Integrating hPS cells with single-cell sequencing makes identifying context-dependent genetic effects during cell development or upon experimental manipulation possible. Here we discuss how the intersection of stem cell biology, population genetics and cellular genomics can help resolve the functional consequences of human genetic variation. We examine the critical challenges of integrating these fields and approaches to scaling them cost-effectively and practically. We highlight two areas of human biology that can particularly benefit from population-scale hPS cell studies, elucidating mechanisms underlying complex disease risk loci and evaluating relationships between common genetic variation and pharmacotherapeutic phenotypes.

Wnt dose escalation during the exit from pluripotency identifies tranilast as a regulator of cardiac mesoderm

Wnt signaling is a critical determinant of cell lineage development. This study used Wnt dose-dependent induction programs to gain insights into molecular regulation of stem cell differentiation. We performed single-cell RNA sequencing of hiPSCs responding to a dose escalation protocol with Wnt agonist CHIR-99021 during the exit from pluripotency to identify cell types and genetic activity driven by Wnt stimulation. Results of activated gene sets and cell types were used to build a multiple regression model that predicts the efficiency of cardiomyocyte differentiation. Cross-referencing Wnt-associated gene expression profiles to the Connectivity Map database, we identified the small-molecule drug, tranilast. We found that tranilast synergistically activates Wnt signaling to promote cardiac lineage differentiation, which we validate by in vitro analysis of hiPSC differentiation and in vivo analysis of developing quail embryos. Our study provides an integrated workflow that links experimental datasets, prediction models, and small-molecule databases to identify drug-like compounds that control cell differentiation.

Inferring cell diversity in single cell data using consortium-scale epigenetic data as a biological anchor for cell identity

Methods for cell clustering and gene expression from single-cell RNA sequencing (scRNA-seq) data are essential for biological interpretation of cell processes. Here, we present TRIAGE-Cluster which uses genome-wide epigenetic data from diverse bio-samples to identify genes demarcating cell diversity in scRNA-seq data. By integrating patterns of repressive chromatin deposited across diverse cell types with weighted density estimation, TRIAGE-Cluster determines cell type clusters in a 2D UMAP space. We then present TRIAGE-ParseR, a machine learning method which evaluates gene expression rank lists to define gene groups governing the identity and function of cell types. We demonstrate the utility of this two-step approach using atlases of in vivo and in vitro cell diversification and organogenesis. We also provide a web accessible dashboard for analysis and download of data and software. Collectively, genome-wide epigenetic repression provides a versatile strategy to define cell diversity and study gene regulation of scRNA-seq data.

Organoids are not organs: Sources of variation and misinformation in organoid biology

In the past decade, the term organoid has moved from obscurity to common use to describe a 3D in vitro cellular model of a tissue that recapitulates structural and functional elements of the in vivo organ it models. The term organoid is now applied to structures formed as a result of two distinct processes: the capacity for adult epithelial stem cells to re-create a tissue niche in vitro and the ability to direct the differentiation of pluripotent stem cells to a 3D self-organizing multicellular model of organogenesis. While these two organoid fields rely upon different stem cell types and recapitulate different processes, both share common challenges around robustness, accuracy, and reproducibility. Critically, organoids are not organs. This commentary serves to discuss these challenges, how they impact genuine utility, and shine a light on the need to improve the standards applied to all organoid approaches.

New Drug Targets and Preclinical Modelling Recommendations for Treating Acute Myocardial Infarction

Acute myocardial infarction (AMI) is the leading cause of morbidity and mortality worldwide and the primary underlying risk factor for heart failure. Despite decades of research and clinical trials, there are no drugs currently available to prevent organ damage from acute ischaemic injuries of the heart. In order to address the increasing global burden of heart failure, drug, gene, and cell-based regeneration technologies are advancing into clinical testing. In this review we highlight the burden of disease associated with AMI and the therapeutic landscape based on market analyses. New studies revealing the role of acid-sensitive cardiac ion channels and other proton-gated ion channels in cardiac ischaemia are providing renewed interest in pre- and post-conditioning agents with novel mechanisms of action that may also have implications for gene- and cell-based therapeutics. Furthermore, we present guidelines that couple new cell technologies and data resources with traditional animal modelling pipelines to help de-risk drug candidates aimed at treating AMI. We propose that improved preclinical pipelines and increased investment in drug target identification for AMI is critical to stem the increasing global health burden of heart failure.

Transcriptional networks of transient cell states during human prefrontal cortex development

The human brain is divided into various anatomical regions that control and coordinate unique functions. The prefrontal cortex (PFC) is a large brain region that comprises a range of neuronal and non-neuronal cell types, sharing extensive interconnections with subcortical areas, and plays a critical role in cognition and memory. A timely appearance of distinct cell types through embryonic development is crucial for an anatomically perfect and functional brain. Direct tracing of cell fate development in the human brain is not possible, but single-cell transcriptome sequencing (scRNA-seq) datasets provide the opportunity to dissect cellular heterogeneity and its molecular regulators. Here, using scRNA-seq data of human PFC from fetal stages, we elucidate distinct transient cell states during PFC development and their underlying gene regulatory circuitry. We further identified that distinct intermediate cell states consist of specific gene regulatory modules essential to reach terminal fate using discrete developmental paths. Moreover, using in silico gene knock-out and over-expression analysis, we validated crucial gene regulatory components during the lineage specification of oligodendrocyte progenitor cells. Our study illustrates unique intermediate states and specific gene interaction networks that warrant further investigation for their functional contribution to typical brain development and discusses how this knowledge can be harvested for therapeutic intervention in challenging neurodevelopmental disorders.