IsoVis - a webserver for visualization and annotation of alternative RNA isoforms.

Genes commonly express multiple RNA products (RNA isoforms), which differ in exonic content and can have different functions. Making sense of the plethora of known and novel RNA isoforms being identified by transcriptomic approaches requires a user-friendly way to visualize gene isoforms and how they differ in exonic content, expression levels and potential functions. Here we introduce IsoVis, a freely available webserver that accepts user-supplied transcriptomic data and visualizes the expressed isoforms in a clear, intuitive manner. IsoVis contains numerous features, including the ability to visualize all RNA isoforms of a gene and their expression levels; the annotation of known isoforms from external databases; mapping of protein domains and features to exons, allowing changes to protein sequence and function between isoforms to be established; and extensive species compatibility. Datasets visualised on IsoVis remain private to the user, allowing analysis of sensitive data. IsoVis visualisations can be downloaded to create publication-ready figures. The IsoVis webserver enables researchers to perform isoform analyses without requiring programming skills, is free to use, and available at https://isomix.org/isovis/.

Stemformatics data portal enables transcriptional benchmarking of lab-derived myeloid cells.

Stemformatics.org has been serving the stem cell research community for over a decade, by making it easy for users to find and view transcriptional profiles of pluripotent and adult stem cells and their progeny, comparing data derived from multiple tissues and derivation methods. In recent years, Stemformatics has shifted its focus from curation to collation and integration of public data with shared phenotypes. It now hosts several integrated expression atlases based on human myeloid cells, which allow for easy cross-dataset comparisons and discovery of emerging cell subsets and activation properties. The atlases are designed for external users to benchmark their own data against a common reference. Here, we use case studies to illustrate how to find and explore previously published datasets of relevance and how in-vitro-derived cells can be transcriptionally matched to cells in the integrated atlas to highlight phenotypes of interest.

The status of the human gene catalogue.

Scientists have been trying to identify every gene in the human genome since the initial draft was published in 2001. In the years since, much progress has been made in identifying protein-coding genes, currently estimated to number fewer than 20,000, with an ever-expanding number of distinct protein-coding isoforms. Here we review the status of the human gene catalogue and the efforts to complete it in recent years. Beside the ongoing annotation of protein-coding genes, their isoforms and pseudogenes, the invention of high-throughput RNA sequencing and other technological breakthroughs have led to a rapid growth in the number of reported non-coding RNA genes. For most of these non-coding RNAs, the functional relevance is currently unclear; we look at recent advances that offer paths forward to identifying their functions and towards eventually completing the human gene catalogue. Finally, we examine the need for a universal annotation standard that includes all medically significant genes and maintains their relationships with different reference genomes for the use of the human gene catalogue in clinical settings.

ISSCR standards for the use of human stem cells in basic research.

The laboratory culture of human stem cells seeks to capture a cellular state as an in vitro surrogate of a biological system. For the results and outputs from this research to be accurate, meaningful, and durable, standards that ensure reproducibility and reliability of the data should be applied. Although such standards have been previously proposed for repositories and distribution centers, no widely accepted best practices exist for laboratory research with human pluripotent and tissue stem cells. To fill that void, the International Society for Stem Cell Research has developed a set of recommendations, including reporting criteria, for scientists in basic research laboratories. These criteria are designed to be technically and financially feasible and, when implemented, enhance the reproducibility and rigor of stem cell research.

The status of the human gene catalogue.

Scientists have been trying to identify all of the genes in the human genome since the initial draft of the genome was published in 2001. Over the intervening years, much progress has been made in identifying protein-coding genes, and the estimated number has shrunk to fewer than 20,000, although the number of distinct protein-coding isoforms has expanded dramatically. The invention of high-throughput RNA sequencing and other technological breakthroughs have led to an explosion in the number of reported non-coding RNA genes, although most of them do not yet have any known function. A combination of recent advances offers a path forward to identifying these functions and towards eventually completing the human gene catalogue. However, much work remains to be done before we have a universal annotation standard that includes all medically significant genes, maintains their relationships with different reference genomes, and describes clinically relevant genetic variants.

The Human Dendritic Cell Atlas: An Integrated Transcriptional Tool to Study Human Dendritic Cell Biology.

Dendritic cells (DCs) are functionally diverse and are present in most adult tissues, but deep understanding of human DC biology is hampered by relatively small numbers of these in circulation and their short lifespan in human tissues. We built a transcriptional atlas of human DCs by combining samples from 14 expression profiling studies derived from 10 laboratories. We identified significant gene expression variation of DC subset-defining markers across tissue type and upon viral or bacterial stimulation. We further highlight critical gaps between in vitro-derived DC subsets and their in vivo counterparts and provide evidence that monocytes or cord blood progenitor in vitro-differentiated DCs fail to capture the repertoire of primary DC subsets or behaviors. In constructing a reference DC atlas, we provide an important resource for the community wishing to identify and annotate tissue-specific DC subsets from single-cell datasets, or benchmark new in vitro models of DC biology.

Defining the Role of Nuclear Factor (NF)-κB p105 Subunit in Human Macrophage by Transcriptomic Analysis of NFKB1 Knockout THP1 Cells.

Since its discovery over 30 years ago the NF-ĸB family of transcription factors has gained the status of master regulator of the immune response. Much of what we understand of the role of NF-ĸB in immune development, homeostasis and inflammation comes from studies of mice null for specific NF-ĸB subunit encoding genes. The role of inflammation in diseases that affect a majority of individuals with health problems globally further establishes NF-ĸB as an important pathogenic factor. More recently, genomic sequencing has revealed loss of function mutations in the NFKB1 gene as the most common monogenic cause of common variable immunodeficiencies in Europeans. NFKB1 encodes the p105 subunit of NF-ĸB which is processed to generate the NF-ĸB p50 subunit. NFKB1 is the most highly expressed transcription factor in macrophages, key cellular drivers of inflammation and immunity. Although a key role for NFKB1 in the control of the immune system is apparent from Nfkb1-/- mouse studies, we know relatively little of the role of NFKB1 in regulating human macrophage responses. In this study we use the THP1 monocyte cell line and CRISPR/Cas9 gene editing to generate a model of NFKB1-/- human macrophages. Transcriptomic analysis reveals that activated NFKB1-/- macrophages are more pro-inflammatory than wild type controls and express elevated levels of TNF, IL6, and IL1B, but also have reduced expression of co-stimulatory factors important for the activation of T cells and adaptive immune responses such as CD70, CD83 and CD209. NFKB1-/- THP1 macrophages recapitulate key observations in individuals with NFKB1 haploinsufficiency including decreased IL10 expression. These data supporting their utility as an in vitro model for understanding the role of NFKB1 in human monocytes and macrophages and indicate that of loss of function NFKB1 mutations in these cells is an important component in the associated pathology.

An integrated analysis of human myeloid cells identifies gaps in in vitro models of in vivo biology.

The Stemformatics myeloid atlas is an integrated transcriptome atlas of human macrophages and dendritic cells that systematically compares freshly isolated tissue-resident, cultured, and pluripotent stem cell-derived myeloid cells. Three classes of tissue-resident macrophage were identified: Kupffer cells and microglia; monocyte-associated; and tumor-associated macrophages. Culture had a major impact on all primary cell phenotypes. Pluripotent stem cell-derived macrophages were characterized by atypical expression of collagen and a highly efferocytotic phenotype. Myeloid subsets, and phenotypes associated with derivation, were reproducible across experimental series including data projected from single-cell studies, demonstrating that the atlas provides a robust reference for myeloid phenotypes. Implementation in Stemformatics.org allows users to visualize patterns of sample grouping or gene expression for user-selected conditions and supports temporary upload of your own microarray or RNA sequencing samples, including single-cell data, to benchmark against the atlas.

Computational Stem Cell Biology: Open Questions and Guiding Principles.

Computational biology is enabling an explosive growth in our understanding of stem cells and our ability to use them for disease modeling, regenerative medicine, and drug discovery. We discuss four topics that exemplify applications of computation to stem cell biology: cell typing, lineage tracing, trajectory inference, and regulatory networks. We use these examples to articulate principles that have guided computational biology broadly and call for renewed attention to these principles as computation becomes increasingly important in stem cell biology. We also discuss important challenges for this field with the hope that it will inspire more to join this exciting area.

Challenges for Computational Stem Cell Biology: A Discussion for the Field.

The first meetup for Computational Stem Cell Biologists was held at the 2020 annual meeting of the International Society for Stem Cell Research. The discussions highlighted opportunities and barriers to computational stem cell research that require coordinated action across the stem cell sector.

Pharmacological validation of targets regulating CD14 during macrophage differentiation.

The signalling receptor for LPS, CD14, is a key marker of, and facilitator for, pro-inflammatory macrophage function. Pro-inflammatory macrophage differentiation remains a process facilitating a broad array of disease pathologies, and has recently emerged as a potential target against cytokine storm in COVID19. Here, we perform a whole-genome CRISPR screen to identify essential nodes regulating CD14 expression in myeloid cells, using the differentiation of THP-1 cells as a starting point. This strategy uncovers many known pathways required for CD14 expression and regulating macrophage differentiation while additionally providing a list of novel targets either promoting or limiting this process. To speed translation of these results, we have then taken the approach of independently validating hits from the screen using well-curated small molecules. In this manner, we identify pharmacologically tractable hits that can either increase CD14 expression on non-differentiated monocytes or prevent CD14 upregulation during macrophage differentiation. An inhibitor for one of these targets, MAP2K3, translates through to studies on primary human monocytes, where it prevents upregulation of CD14 following M-CSF induced differentiation, and pro-inflammatory cytokine production in response to LPS. Therefore, this screening cascade has rapidly identified pharmacologically tractable nodes regulating a critical disease-relevant process.

A simple, scalable approach to building a cross-platform transcriptome atlas.

Gene expression atlases have transformed our understanding of the development, composition and function of human tissues. New technologies promise improved cellular or molecular resolution, and have led to the identification of new cell types, or better defined cell states. But as new technologies emerge, information derived on old platforms becomes obsolete. We demonstrate that it is possible to combine a large number of different profiling experiments summarised from dozens of laboratories and representing hundreds of donors, to create an integrated molecular map of human tissue. As an example, we combine 850 samples from 38 platforms to build an integrated atlas of human blood cells. We achieve robust and unbiased cell type clustering using a variance partitioning method, selecting genes with low platform bias relative to biological variation. Other than an initial rescaling, no other transformation to the primary data is applied through batch correction or renormalisation. Additional data, including single-cell datasets, can be projected for comparison, classification and annotation. The resulting atlas provides a multi-scaled approach to visualise and analyse the relationships between sets of genes and blood cell lineages, including the maturation and activation of leukocytes in vivo and in vitro. In allowing for data integration across hundreds of studies, we address a key reproduciblity challenge which is faced by any new technology. This allows us to draw on the deep phenotypes and functional annotations that accompany traditional profiling methods, and provide important context to the high cellular resolution of single cell profiling. Here, we have implemented the blood atlas in the open access Stemformatics.org platform, drawing on its extensive collection of curated transcriptome data. The method is simple, scalable and amenable for rapid deployment in other biological systems or computational workflows.

Unique properties of a subset of human pluripotent stem cells with high capacity for self-renewal.

Archetypal human pluripotent stem cells (hPSC) are widely considered to be equivalent in developmental status to mouse epiblast stem cells, which correspond to pluripotent cells at a late post-implantation stage of embryogenesis. Heterogeneity within hPSC cultures complicates this interspecies comparison. Here we show that a subpopulation of archetypal hPSC enriched for high self-renewal capacity (ESR) has distinct properties relative to the bulk of the population, including a cell cycle with a very low G1 fraction and a metabolomic profile that reflects a combination of oxidative phosphorylation and glycolysis. ESR cells are pluripotent and capable of differentiation into primordial germ cell-like cells. Global DNA methylation levels in the ESR subpopulation are lower than those in mouse epiblast stem cells. Chromatin accessibility analysis revealed a unique set of open chromatin sites in ESR cells. RNA-seq at the subpopulation and single cell levels shows that, unlike mouse epiblast stem cells, the ESR subset of hPSC displays no lineage priming, and that it can be clearly distinguished from gastrulating and extraembryonic cell populations in the primate embryo. ESR hPSC correspond to an earlier stage of post-implantation development than mouse epiblast stem cells.

Multipotent RAG1+ progenitors emerge directly from haemogenic endothelium in human pluripotent stem cell-derived haematopoietic organoids.

Defining the ontogeny of the human adaptive immune system during embryogenesis has implications for understanding childhood diseases including leukaemias and autoimmune conditions. Using RAG1:GFP human pluripotent stem cell reporter lines, we examined human T-cell genesis from pluripotent-stem-cell-derived haematopoietic organoids. Under conditions favouring T-cell development, RAG1+ cells progressively upregulated a cohort of recognized T-cell-associated genes, arresting development at the CD4+CD8+ stage. Sort and re-culture experiments showed that early RAG1+ cells also possessed B-cell, myeloid and erythroid potential. Flow cytometry and single-cell-RNA-sequencing data showed that early RAG1+ cells co-expressed the endothelial/haematopoietic progenitor markers CD34, VECAD and CD90, whereas imaging studies identified RAG1+ cells within CD31+ endothelial structures that co-expressed SOX17+ or the endothelial marker CAV1. Collectively, these observations provide evidence for a wave of human T-cell development that originates directly from haemogenic endothelium via a RAG1+ intermediate with multilineage potential.

Transcriptional Profiling of Stem Cells: Moving from Descriptive to Predictive Paradigms.

Transcriptional profiling is a powerful tool commonly used to benchmark stem cells and their differentiated progeny. As the wealth of stem cell data builds in public repositories, we highlight common data traps, and review approaches to combine and mine this data for new cell classification and cell prediction tools. We touch on future trends for stem cell profiling, such as single-cell profiling, long-read sequencing, and improved methods for measuring molecular modifications on chromatin and RNA that bring new challenges and opportunities for stem cell analysis.

Stemformatics: visualize and download curated stem cell data.

Stemformatics is an established gene expression data portal containing over 420 public gene expression datasets derived from microarray, RNA sequencing and single cell profiling technologies. Developed for the stem cell community, it has a major focus on pluripotency, tissue stem cells, and staged differentiation. Stemformatics includes curated 'collections' of data relevant to cell reprogramming, as well as hematopoiesis and leukaemia. Rather than simply rehosting datasets as they appear in public repositories, Stemformatics uses a stringent set of quality control metrics and its own pipelines to process handpicked datasets from raw files. This means that about 30% of datasets processed by Stemformatics fail the quality control metrics and never make it to the portal, ensuring that Stemformatics data are of high quality and have been processed in a consistent manner. Stemformatics provides easy-to-use and intuitive tools for biologists to visually explore the data, including interactive gene expression profiles, principal component analysis plots and hierarchical clusters, among others. The addition of tools that facilitate cross-dataset comparisons provides users with snapshots of gene expression in multiple cell and tissues, assisting the identification of cell-type restricted genes, or potential housekeeping genes. Stemformatics is freely available at stemformatics.org.

Age-specific biological and molecular profiling distinguishes paediatric from adult acute myeloid leukaemias.

Acute myeloid leukaemia (AML) affects children and adults of all ages. AML remains one of the major causes of death in children with cancer and for children with AML relapse is the most common cause of death. Here, by modelling AML in vivo we demonstrate that AML is discriminated by the age of the cell of origin. Young cells give rise to myeloid, lymphoid or mixed phenotype acute leukaemia, whereas adult cells give rise exclusively to AML, with a shorter latency. Unlike adult, young AML cells do not remodel the bone marrow stroma. Transcriptional analysis distinguishes young AML by the upregulation of immune pathways. Analysis of human paediatric AML samples recapitulates a paediatric immune cell interaction gene signature, highlighting two genes, RGS10 and FAM26F as prognostically significant. This work advances our understanding of paediatric AML biology, and provides murine models that offer the potential for developing paediatric specific therapeutic strategies.

Designer macrophages: Pitfalls and opportunities for modelling macrophage phenotypes from pluripotent stem cells.

Macrophages are phagocytic immune cells resident in every tissue that are not only important for host defence, but are also involved in tissue homeostasis, injury, and disease. Despite increasingly sophisticated methods for in vitro macrophage isolation, expansion and activation over the past three decades, these have largely been restricted to modelling bone-marrow or blood-derived cells. The in vitro derivation of macrophages from human pluripotent stem cells provides new opportunities to study macrophage biology, including the factors that impact human myeloid development and those that induce macrophage activation. While sharing many of the functional characteristics of monocyte-derived macrophages, stem cell-derived macrophages may offer new opportunities to understand the role of development or tissue context in innate immune cell function. Immune responsiveness to pathogenic challenge is known to be impacted by a macrophage's history of prior exposure, as well as ontogeny and tissue context. Therefore, we explore the factors of in vitro derivation likely to influence macrophage phenotype and function.

Lipoteichoic acid anchor triggers Mincle to drive protective immunity against invasive group A Streptococcus infection.

Group A Streptococcus (GAS) is a Gram-positive bacterial pathogen that causes a range of diseases, including fatal invasive infections. However, the mechanisms by which the innate immune system recognizes GAS are not well understood. We herein report that the C-type lectin receptor macrophage inducible C-type lectin (Mincle) recognizes GAS and initiates antibacterial immunity. Gene expression analysis of myeloid cells upon GAS stimulation revealed the contribution of the caspase recruitment domain-containing protein 9 (CARD9) pathway to the antibacterial responses. Among receptors signaling through CARD9, Mincle induced the production of inflammatory cytokines, inducible nitric oxide synthase, and reactive oxygen species upon recognition of the anchor of lipoteichoic acid, monoglucosyldiacylglycerol (MGDG), produced by GAS. Upon GAS infection, Mincle-deficient mice exhibited impaired production of proinflammatory cytokines, severe bacteremia, and rapid lethality. GAS also possesses another Mincle ligand, diglucosyldiacylglycerol; however, this glycolipid interfered with MGDG-induced activation. These results indicate that Mincle plays a central role in protective immunity against acute GAS infection.