Deciphering cell states and genealogies of human haematopoiesis.

The human blood system is maintained through the differentiation and massive amplification of a limited number of long-lived haematopoietic stem cells (HSCs)1. Perturbations to this process underlie diverse diseases, but the clonal contributions to human haematopoiesis and how this changes with age remain incompletely understood. Although recent insights have emerged from barcoding studies in model systems2-5, simultaneous detection of cell states and phylogenies from natural barcodes in humans remains challenging. Here we introduce an improved, single-cell lineage-tracing system based on deep detection of naturally occurring mitochondrial DNA mutations with simultaneous readout of transcriptional states and chromatin accessibility. We use this system to define the clonal architecture of HSCs and map the physiological state and output of clones. We uncover functional heterogeneity in HSC clones, which is stable over months and manifests as both differences in total HSC output and biases towards the production of different mature cell types. We also find that the diversity of HSC clones decreases markedly with age, leading to an oligoclonal structure with multiple distinct clonal expansions. Our study thus provides a clonally resolved and cell-state-aware atlas of human haematopoiesis at single-cell resolution, showing an unappreciated functional diversity of human HSC clones and, more broadly, paving the way for refined studies of clonal dynamics across a range of tissues in human health and disease.

Variant to function mapping at single-cell resolution through network propagation.

Genome-wide association studies in combination with single-cell genomic atlases can provide insights into the mechanisms of disease-causal genetic variation. However, identification of disease-relevant or trait-relevant cell types, states and trajectories is often hampered by sparsity and noise, particularly in the analysis of single-cell epigenomic data. To overcome these challenges, we present SCAVENGE, a computational algorithm that uses network propagation to map causal variants to their relevant cellular context at single-cell resolution. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation, applying the method to blood traits at distinct stages of human hematopoiesis, to monocyte subsets that increase the risk for severe Coronavirus Disease 2019 (COVID-19) and to intermediate lymphocyte developmental states that predispose to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data.

Patchwork Cancer Predisposition.

SUMMARY: Inherited genetic variation is increasingly identified as an important predisposing factor to a variety of cancers. In this issue of Cancer Discovery, Pareja and colleagues developed a method of reliably detecting mosaic cancer susceptibility mutations in patients who have been sequenced as part of the MSK-IMPACT tumor profiling platform. This led to the identification of a number of mosaic mutations in cancer susceptibility alleles that are generally found in the germline, suggesting that many predisposition variants may be missed through conventional testing. See related article by Pareja et al., p. 949 (6).

Variant to function mapping at single-cell resolution through network propagation.

With burgeoning human disease genetic associations and single-cell genomic atlases covering a range of tissues, there are unprecedented opportunities to systematically gain insights into the mechanisms of disease-causal variation. However, sparsity and noise, particularly in the context of single-cell epigenomic data, hamper the identification of disease- or trait-relevant cell types, states, and trajectories. To overcome these challenges, we have developed the SCAVENGE method, which maps causal variants to their relevant cellular context at single-cell resolution by employing the strategy of network propagation. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation including enrichment of blood traits at distinct stages of human hematopoiesis, defining monocyte subsets that increase the risk for severe coronavirus disease 2019 (COVID-19), and identifying intermediate lymphocyte developmental states that are critical for predisposition to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution, but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data.

Clonal hematopoiesis in sickle cell disease.

BACKGROUNDCurative gene therapies for sickle cell disease (SCD) are currently undergoing clinical evaluation. The occurrence of myeloid malignancies in these trials has prompted safety concerns. Individuals with SCD are predisposed to myeloid malignancies, but the underlying causes remain undefined. Clonal hematopoiesis (CH) is a premalignant condition that also confers significant predisposition to myeloid cancers. While it has been speculated that CH may play a role in SCD-associated cancer predisposition, limited data addressing this issue have been reported.METHODSHere, we leveraged 74,190 whole-genome sequences to robustly study CH in SCD. Somatic mutation calling methods were used to assess CH in all samples and comparisons between individuals with and without SCD were performed.RESULTSWhile we had sufficient power to detect a greater than 2-fold increased rate of CH, we found no detectable variation in rate or clone properties between individuals affected by SCD and controls. The rate of CH in individuals with SCD was unaltered by hydroxyurea use.CONCLUSIONSWe did not observe an increased risk for acquiring detectable CH in SCD, at least as measured by whole-genome sequencing. These results should help guide ongoing efforts and further studies that seek to better define the risk factors underlying myeloid malignancy predisposition in SCD and help ensure that curative therapies can be more safely applied.FUNDINGNew York Stem Cell Foundation and the NIH.

Unraveling Hematopoiesis through the Lens of Genomics.

Hematopoiesis has long served as a paradigm of stem cell biology and tissue homeostasis. In the past decade, the genomics revolution has ushered in powerful new methods for investigating the hematopoietic system that have provided transformative insights into its biology. As part of the advances in genomics, increasingly accurate deep sequencing and novel methods of cell tracking have revealed hematopoiesis to be more of a continuous and less of a discrete and punctuated process than originally envisioned. In part, this continuous nature of hematopoiesis is made possible by the emergent outcomes of vast, interconnected regulatory networks that influence cell fates and lineage commitment. It is also becoming clear how these mechanisms are modulated by genetic variation present throughout the population. This review describes how these recently uncovered complexities are reshaping our concept of tissue development and homeostasis while opening up a more comprehensive future understanding of hematopoiesis.

Sowing the Seeds of Clonal Hematopoiesis.

As humans age, hematopoietic stem cells (HSCs) occasionally acquire mutations in genes including DNMT3A that enable them to outcompete other HSCs and increase leukemia risk. In this issue of Cell Stem Cell, Tovy et al. (2020) report a previously uncharacterized mechanism by which DNMT3A loss confers increased fitness to HSCs by analyzing a rare experiment of nature.

FERMI: A Novel Method for Sensitive Detection of Rare Mutations in Somatic Tissue.

With growing interest in monitoring mutational processes in normal tissues, tumor heterogeneity, and cancer evolution under therapy, the ability to accurately and economically detect ultra-rare mutations is becoming increasingly important. However, this capability has often been compromised by significant sequencing, PCR and DNA preparation error rates. Here, we describe FERMI (Fast Extremely Rare Mutation Identification) - a novel method designed to eliminate the majority of these sequencing and library-preparation errors in order to significantly improve rare somatic mutation detection. This method leverages barcoded targeting probes to capture and sequence DNA of interest with single copy resolution. The variant calls from the barcoded sequencing data are then further filtered in a position-dependent fashion against an adaptive, context-aware null model in order to distinguish true variants. As a proof of principle, we employ FERMI to probe bone marrow biopsies from leukemia patients, and show that rare mutations and clonal evolution can be tracked throughout cancer treatment, including during historically intractable periods like minimum residual disease. Importantly, FERMI is able to accurately detect nascent clonal expansions within leukemias in a manner that may facilitate the early detection and characterization of cancer relapse.

The burden of trisomy 21 disrupts the proteostasis network in Down syndrome.

Down syndrome (DS) is a genetic disorder caused by trisomy of chromosome 21. Abnormalities in chromosome number have the potential to lead to disruption of the proteostasis network (PN) and accumulation of misfolded proteins. DS individuals suffer from several comorbidities, and we hypothesized that disruption of proteostasis could contribute to the observed pathology and decreased cell viability in DS. Our results confirm the presence of a disrupted PN in DS, as several of its elements, including the unfolded protein response, chaperone system, and proteasomal degradation exhibited significant alterations compared to euploid controls in both cell and mouse models. Additionally, when cell models were treated with compounds that promote disrupted proteostasis, we observed diminished levels of cell viability in DS compared to controls. Collectively our findings provide a cellular-level characterization of PN dysfunction in DS and an improved understanding of the potential pathogenic mechanisms contributing to disrupted cellular physiology in DS. Lastly, this study highlights the future potential of designing therapeutic strategies that mitigate protein quality control dysfunction.

Changing mutational and adaptive landscapes and the genesis of cancer.

By the time the process of oncogenesis has produced an advanced cancer, tumor cells have undergone extensive evolution. The cellular phenotypes resulting from this evolution have been well studied, and include accelerated growth rates, apoptosis resistance, immortality, invasiveness, and immune evasion. Yet with all of our current knowledge of tumor biology, the details of early oncogenesis have been difficult to observe and understand. Where different oncogenic mutations may work together to enhance the survival of a tumor cell, in isolation they are often pro-apoptotic, pro-differentiative or pro-senescent, and therefore often, somewhat paradoxically, disadvantageous to a cell. It is also becoming clear that somatic mutations, including those in known oncogenic drivers, are common in tissues starting at a young age. These observations raise the question: how do we largely avoid cancer for most of our lives? Here we propose that evolutionary forces can help explain this paradox. As humans and other organisms age or experience external insults such as radiation or smoking, the structure and function of tissues progressively degrade, resulting in altered stem cell niche microenvironments. As tissue integrity declines, it becomes less capable of supporting and maintaining resident stem cells. These stem cells then find themselves in a microenvironment to which they are poorly adapted, providing a competitive advantage to those cells that can restore their functionality and fitness through mutations or epigenetic changes. The resulting oncogenic clonal expansions then increase the odds of further cancer progression. Understanding how the causes of cancer, such as aging or smoking, affect tissue microenvironments to control the impact of mutations on somatic cell fitness can help reconcile the discrepancy between marked mutation accumulation starting early in life and the somatic evolution that leads to cancer at advanced ages or following carcinogenic insults. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.

Trisomy 21 consistently activates the interferon response.

Although it is clear that trisomy 21 causes Down syndrome, the molecular events acting downstream of the trisomy remain ill defined. Using complementary genomics analyses, we identified the interferon pathway as the major signaling cascade consistently activated by trisomy 21 in human cells. Transcriptome analysis revealed that trisomy 21 activates the interferon transcriptional response in fibroblast and lymphoblastoid cell lines, as well as circulating monocytes and T cells. Trisomy 21 cells show increased induction of interferon-stimulated genes and decreased expression of ribosomal proteins and translation factors. An shRNA screen determined that the interferon-activated kinases JAK1 and TYK2 suppress proliferation of trisomy 21 fibroblasts, and this defect is rescued by pharmacological JAK inhibition. Therefore, we propose that interferon activation, likely via increased gene dosage of the four interferon receptors encoded on chromosome 21, contributes to many of the clinical impacts of trisomy 21, and that interferon antagonists could have therapeutic benefits.