Somatic mutations and cell identity linked by Genotyping of Transcriptomes

Protocol for high-quality RNA sequencing, cell surface protein analysis, and genotyping in single cells using TARGET-seq

Studying the consequences of somatic mutations in pre-malignant and cancerous tissues is challenging due to noise in single-cell transcriptome data and difficulty in identifying the clonal identity of single cells. We optimized TARGET-seq to develop TARGET-seq+, which combines RNA sequencing (RNA-seq), the analysis of cell surface protein expression, and genotyping in single cells with improved sensitivity. We describe the steps for cell isolation, the preparation of single-cell RNA-seq (scRNA-seq) and genotyping libraries, and sequencing. We also provide guidance on the analysis of single-cell genotyping, transcriptome pre-processing, and data integration. For complete details on the use and execution of this protocol, please refer to Jakobsen et al.1.

Deconvoluting clonal and cellular architecture in IDH-mutant acute myeloid leukemia

Isocitrate dehydrogenase 1/2 (IDH) mutations are early initiating events in acute myeloid leukemia (AML). The complex clonal architecture and cellular heterogeneity in IDH-mutant AML underlies the heterogeneous clinical presentation and outcomes. Integrating single-cell genotyping and transcriptomics, we demonstrate a stem-like and inflammatory phenotype of IDH-mutant AML and identify clone-specific programs associated with NPM1, NRAS, and SRSF2 co-mutations. Furthermore, these clones had distinct responses to treatment with combination IDH inhibitors and chemotherapy, including elimination, reconstitution of myeloid differentiation, or retention within progenitor populations. At relapse after IDH inhibitor monotherapy, we identify upregulated stemness, inflammation, mitochondrial metabolism, and anti-apoptotic factors, as well as downregulated major histocompatibility complex (MHC) class II antigen presentation. At the pre-leukemic stage, we observe upregulation of IDH2-associated pathways, including inflammation. We deliver a detailed phenotyping of IDH-mutant AML and a framework for dissecting contributions of recurrently mutated genes in AML at diagnosis and following therapy, with implications for precision medicine.

In depth transcriptomic profiling defines a landscape of dysfunctional immune responses in patients with VEXAS syndrome

VEXAS (Vacuoles, E1 enzyme, X-linked, Autoinflammatory, Somatic) syndrome is caused by inactivating somatic mutations in the UBA1 gene. Here, we characterize the immunological landscape of VEXAS syndrome by performing multi-omics single-cell RNA analysis, cytokine multiplex assays, and in vitro functional assays on patients' peripheral blood. Our data reveals a broad immune system activation with upregulation of multiple inflammatory response pathways and proinflammatory cytokines. Unexpectedly, we find that monocytes have dysfunctional features irrespective of UBA1 mutation status, exhibiting impaired efferocytosis and blunted cytokine production in vitro. In contrast, UBA1-mutated NK cells show an upregulation of the inflammation pathways and enhanced cytotoxicity. Within the lymphocyte subsets, predominantly UBA1 wild-type, we identify clonal expansion of effector memory CD8+ T cells and skewed B cell differentiation with loss of transitional B cells and expansion of plasmablasts. Thus, our analysis indicates that VEXAS syndrome is characterized by profound alterations in both adaptive and innate immune systems, accounting for the complex pathophysiology of the disease, and provides a basis to understand the marked clinical heterogeneity and variable disease course.

Differential regulation of mTORC2 signalling by type I and type II calreticulin (CALR) driver mutations of myeloproliferative neoplasm

Calreticulin (CALR) is an endoplasmic reticulum chaperone. Frameshift mutations in CALR were discovered in patients with myeloproliferative neoplasm showing increased platelet counts. The frameshift was observed in the last exon of CALR, leading to a novel C-terminal tail. Calreticulin mutations were categorised into Type I and Type II depending upon the extent of retention of CALR WT sequences. Clinically, Type I mutations induced myelofibrosis, while Type II mutations were associated with early onset of the disease. Both mutations induced ligand-independent activation of the thrombopoietin receptor (TpoR) and consequently enhanced platelet production. However, no specific difference in signalling mechanism could be demonstrated between them. Using over-expression of CALR WT, CALR ∆52 (Type I) and CALR ins5 (Type II) in HEK cells, we showed that Type I CALR mutations downregulated the basal mTORC2 signalling without affecting mTORC1. The decrease in basal mTORC2 signalling was attributed to CALR ∆52-induced increased expression of c-JUN through occupation of the enhancer sequences of jun. Furthermore, increased c-JUN expression decreased the expression of RICTOR, a component of mTORC2. Strikingly, overexpression of RICTOR or knockdown of c-JUN reversed the inhibitory effect of CALR ∆52 on mTORC2 activity. Finally, we demonstrated that CALR ∆52 decreased the glucose uptake and cellular ATP levels in a c-JUN-mTORC2-dependent manner. These findings not only contribute to our understanding of the molecular mechanisms underlying mutant CALR driven myeloproliferative neoplasm but also provide potential therapeutic targets against the disease.

Deciphering the complex clonal heterogeneity of polycythemia vera and the response to interferon alfa

ABSTRACT

Interferon alfa (IFN-α) is approved for the therapy of patients with polycythemia vera (PV), a subtype of myeloproliferative neoplasm (MPN). Some patients achieve molecular responses (MRs), but clonal factors sensitizing for MRs remain elusive. We integrated colony formation assays with single-cell RNA sequencing (scRNA-seq) and genotyping in PV-derived cells and healthy controls (HCs) to dissect how IFN-α targets diseased clones during erythroid differentiation. IFN-α significantly decreased colony growth in MPNs and HCs with variable transcriptional responses observed in individual colonies. scRNA-seq of colonies demonstrated more mature erythroid colonies in PV than HCs. JAK2V617F-mutant cells exhibited upregulated STAT5A, heme, and G2M checkpoint pathways compared with JAK2WT cells from the same patients. Subgroup analysis revealed that IFN-α significantly decreased immature erythrocytic cells in PV (basophilic erythroblasts P < .05; polychromatic erythroblasts P < .05) but not in HCs. CD71-/CD235a+ cells from HCs (P < .05) but not PV were inhibited by IFN-α, and the number of reticulocytes was less affected in PV. Robust IFN-α responses persisted throughout differentiation, leading to significant apoptosis in PV. Apoptotic cells displayed downregulation of ribosomal genes. This link between apoptosis and ribosomal genes was corroborated through the analysis of mitochondrial variants, demonstrating IFN-α-induced eradication of specific clones, characterized by elevated expression of ribosomal genes. Our findings indicate that PV-derived clones either undergo apoptosis or pass through differentiation, overall reducing the cycling mutant cells over long-term treatment. Furthermore, the significance of ribosomal genes and clonal prerequisites in IFN-α's therapeutic mechanism is underscored, shedding light on the intricate dynamics of IFN-α treatment in PV.

Extreme Thrombocytosis in Patients with Overt Myelofibrosis and Its Clinical Associations

Background/Objectives: Overt primary myelofibrosis (PMF), secondary post-polycythemia vera (post-PV), and post-essential thrombocythemia (post-ET) myelofibrosis (SMF) are chronic myeloproliferative neoplasms (MPN) that sometimes present with extreme thrombocytosis (ExTh, platelet count > 1000 × 109/L), a phenomenon of uncertain clinical significance since there are no published data available. Methods: We retrospectively investigated the clinical correlations and associated outcomes of ExTh in a cohort of 172 patients with overt myelofibrosis diagnosed in six Croatian hematology centers. Results: ExTh was present in 5.8% of patients and was associated with post-ET etiology of myelofibrosis, older age, smaller spleen size, and the presence of arterial hypertension (p < 0.05 for all analyses). No significant associations were observed with sex, degree of bone marrow fibrosis, or driver mutation status. Over the follow-up period, patients with ExTh experienced a favorable course regarding survival (p < 0.001) and bleeding risk (p = 0.034), whereas no significant association with thrombotic risk was observed (p = 0.682). Conclusions: In contrast to its context in ET, ExTh in overt fibrotic MPN does not appear to confer higher bleeding or thrombotic risk. Instead, it is associated with more favorable survival outcomes and reduced bleeding risk.

Single-cell Rapid Capture Hybridization sequencing reliably detects isoform usage and coding mutations in targeted genes

Single-cell long-read sequencing has transformed our understanding of isoform usage and the mutation heterogeneity between cells. Despite unbiased in-depth analysis, the low sequencing throughput often results in insufficient read coverage, thereby limiting our ability to perform mutation calling for specific genes. Here, we developed a single-cell Rapid Capture Hybridization sequencing (scRaCH-seq) method that demonstrates high specificity and efficiency in capturing targeted transcripts using long-read sequencing, allowing an in-depth analysis of mutation status and transcript usage for genes of interest. The method includes creating a probe panel for transcript capture, using barcoded primers for pooling and efficient sequencing via Oxford Nanopore Technologies platforms. scRaCH-seq is applicable to stored and indexed single-cell cDNA, which allows analysis to be combined with existing short-read RNA-seq data sets. In our investigation of BTK and SF3B1 genes in samples from patients with chronic lymphocytic leukemia (CLL), we detect SF3B1 isoforms and mutations with high sensitivity. Integration with short-read single-cell RNA sequencing (scRNA-seq) data reveals significant gene expression differences in SF3B1-mutated CLL cells, although it does not impact the sensitivity of the anticancer drug venetoclax. scRaCH-seq's capability to study long-read transcripts of multiple genes makes it a powerful tool for single-cell genomics.

New approaches to standard of care in early-phase myeloproliferative neoplasms: can interferon-α alter the natural history of the disease?

The classical BCR::ABL-negative myeloproliferative neoplasms (MPN) include polycythemia vera, essential thrombocythemia, and primary myelofibrosis. They are acquired clonal disorders of hematopoietic stem cells leading to hyperplasia of one or several myeloid lineages. MPN are caused by three main recurrent mutations, JAK2V617F and mutations in the calreticulin (CALR) and thrombopoietin receptor (MPL) genes. Here, we review the general diagnosis, the complications, and the management of MPN. Second, we explain the physiopathology of the natural disease development and its regulation, which contributes to MPN heterogeneity. Thirdly, we describe the new paradigm of MPN development highlighting the early origin of driver mutations, decades before the onset of symptoms, and the consequence of early detection of MPN cases in the general population for prompt diagnosis and better medical management. Finally, we present interferon-α therapy as a potential, early disease-modifying drug after reporting its good hematologic and molecular efficacies in polycythemia vera, essential thrombocythemia, and early myelofibrosis in clinical trials as well as its mechanism of action in pre-clinical studies. As a result, we may expect that, in the future, MPN patients will be diagnosed very early during the course of disease and that new selective therapies under development, such as interferon-α, JAK2V617F inhibitors and CALRmut monoclonal antibodies, will be able to intercept the mutated clones.

Protocol for mitochondrial variant enrichment from single-cell RNA sequencing using MAESTER

Single-cell RNA sequencing (scRNA-seq) enables detailed characterization of cell states but often lacks insights into tissue clonal structures. Here, we present a protocol to probe cell states and clonal information simultaneously by enriching mitochondrial DNA (mtDNA) variants from 3'-barcoded full-length cDNA. We describe steps for input library preparation, mtDNA enrichment, PCR product cleanup, and paired-end sequencing. We then detail computational steps for running maegatk, variant calling, and data integration to illuminate cell states and clonal dynamics in primary human tissues. For complete details on the use and execution of this protocol, please refer to Miller et al.1.

The Crossroads of Clonal Evolution, Differentiation Hierarchy, and Ontogeny in Leukemia Development

SIGNIFICANCE

In recent years, remarkable technological advances have illuminated aspects of the pathogenesis of myeloid malignancies-yet outcomes for patients with these devastating diseases have not significantly improved. We posit that a synthesized view of the three dimensions through which hematopoietic cells transit during their healthy and diseased life-clonal evolution, stem cell hierarchy, and ontogeny-promises high yields in new insights into disease pathogenesis and new therapeutic avenues.

The end of the genetic paradigm of cancer

Genome sequencing of cancer and normal tissues, alongside single-cell transcriptomics, continues to produce findings that challenge the idea that cancer is a 'genetic disease', as posited by the somatic mutation theory (SMT). In this prevailing paradigm, tumorigenesis is caused by cancer-driving somatic mutations and clonal expansion. However, results from tumor sequencing, motivated by the genetic paradigm itself, create apparent 'paradoxes' that are not conducive to a pure SMT. But beyond genetic causation, the new results lend credence to old ideas from organismal biology. To resolve inconsistencies between the genetic paradigm of cancer and biological reality, we must complement deep sequencing with deep thinking: embrace formal theory and historicity of biological entities, and (re)consider non-genetic plasticity of cells and tissues. In this Essay, we discuss the concepts of cell state dynamics and tissue fields that emerge from the collective action of genes and of cells in their morphogenetic context, respectively, and how they help explain inconsistencies in the data in the context of SMT.

Scalable co-sequencing of RNA and DNA from individual nuclei

The ideal technology for directly investigating the relationship between genotype and phenotype would analyze both RNA and DNA genome-wide and with single-cell resolution; however, existing tools lack the throughput required for comprehensive analysis of complex tumors and tissues. We introduce a highly scalable method for jointly profiling DNA and expression following nucleosome depletion (DEFND-seq). In DEFND-seq, nuclei are nucleosome-depleted, tagmented and separated into individual droplets for messenger RNA and genomic DNA barcoding. Once nuclei have been depleted of nucleosomes, subsequent steps can be performed using the widely available 10x Genomics droplet microfluidic technology and commercial kits. We demonstrate the production of high-complexity mRNA and gDNA sequencing libraries from thousands of individual nuclei from cell lines, fresh and archived surgical specimens for associating gene expression with both copy number and single-nucleotide variants.

Consequences of training data composition for deep learning models in single-cell biology

Foundation models for single-cell transcriptomics have the potential to augment (or replace) purpose-built tools for a variety of common analyses, especially when data are sparse. Recent work with large language models has shown that training data composition greatly shapes performance; however, to date, single-cell foundation models have ignored this aspect, opting instead to train on the largest possible corpus. We systematically investigate the consequences of training dataset composition on the behavior of deep learning models of single-cell transcriptomics, focusing on human hematopoiesis as a tractable model system and including cells from adult and developing tissues, disease states, and perturbation atlases. We find that (1) these models generalize poorly to unseen cell types, (2) adding malignant cells to a healthy cell training corpus does not necessarily improve modeling of unseen malignant cells, and (3) including an embryonic stem cell differentiation atlas during training improves performance on out-of-distribution tasks. Our results emphasize the importance of diverse training data and suggest strategies to optimize future single-cell foundation models.

Exploring genome-transcriptome correlations in cancer

We examine the complex relationship between genomic copy number variation (CNV) and gene expression, highlighting the relevance to cancer biology and other biological contexts. By tracing the history of genometranscriptome correlations, we emphasize the complexity and challenges in understanding these interactions, particularly within the heterogeneous landscape of human cancers. Recent advances in computational algorithms and high-throughput single-cell multi-omic sequencing technologies are discussed, demonstrating their potential to refine our understanding of cancer biology and their limitations. The integration of genomic and transcriptomic analyses, which offers novel insights into tumor evolution and heterogeneity as well as therapeutic strategies, is presented as a crucial approach for advancing cancer research.

Single-cell sequencing applications in acute myeloid leukemia

Acute myeloid leukemia (AML) is a heterogeneous group of malignancies with poor prognosis. AML result from the proliferation of immature myeloid cells blocked at a variable stage of differentiation. Beyond inter-patient heterogeneity, AMLs are characterized by genetic and phenotypic intra-patient heterogeneity. Despite major advances in deciphering AML biology with bulk sequencing studies, pivotal questions remain unanswered. Analyses at the single-cell level could thus transform our understanding of these neoplasms. We review recent progresses in single-cell sequencing technologies from cell processing to bioinformatic pipelines. We next discuss how single-cell applications have helped understand the genetic and functional intra-leukemic heterogeneity, emphasizing aspects related to leukemic stem cells, clonal evolution and measurable residual disease (MRD) monitoring. We finally delineate how single-cell technologies could be implemented in routine clinical practice to improve patient management.

Next-generation sequencing protocol of hematopoietic stem cells (HSCs). Step-by-step overview and troubleshooting guide

Populations of very small embryonic-like stem cells (VSELs) (CD34+lin-CD45- and CD133+lin-CD45-), circulating in the peripheral blood of adults in small numbers, have been identified in several human tissues and together with the populations of hematopoietic stem cells (HSCs) (CD34+lin-CD45+) and CD133+lin-CD45+constitute a pool of cells with self-renewal and pluripotent stem cell characteristics. Using advanced cell staining and sorting strategies, we isolated populations of VSELs and HSCs for bulk RNA-Seq analysis to compare the transcriptomic profiles of both cell populations. Libraries were prepared from an extremely small number of cells; however, their good quality was preserved, and they met the criteria for sequencing. We present here a step-by-step NGS protocol for sequencing VSELs and HSC with a description of troubleshooting during library preparation and sequencing.

Mutant Calreticulin in MPN: Mechanistic Insights and Therapeutic Implications

PURPOSE OF REVIEW

More than a decade following the discovery of Calreticulin (CALR) mutations as drivers of myeloproliferative neoplasms (MPN), advances in the understanding of CALR-mutant MPN continue to emerge. Here, we summarize recent advances in mehanistic understanding and in targeted therapies for CALR-mutant MPN.

RECENT FINDINGS

Structural insights revealed that the mutant CALR-MPL complex is a tetramer and the mutant CALR C-terminus is exposed on the cell surface. Targeting mutant CALR utilizing antibodies is the leading therapeutic approach, while mutant CALR-directed vaccines are also in early clinical trials. Additionally, chimeric antigen receptor (CAR) T-cells directed against mutant CALR are under evaluation in preclinical models. Approaches addressing the cellular effects of mutant CALR beyond MPL-JAK-STAT activation, such as targeting the unfolded protein response, proteasome, and N-glycosylation pathways, have been tested in preclinical models. In CALR-mutant MPN, the path from discovery to mechanistic understanding to direct therapeutic targeting has advanced rapidly. The longer-term goal remains clonally-selective therapies that modify the disease course in patients.

Single-cell mapping of regulatory DNA:Protein interactions

Gene expression is coordinated by a multitude of transcription factors (TFs), whose binding to the genome is directed through multiple interconnected epigenetic signals, including chromatin accessibility and histone modifications. These complex networks have been shown to be disrupted during aging, disease, and cancer. However, profiling these networks across diverse cell types and states has been limited due to the technical constraints of existing methods for mapping DNA:Protein interactions in single cells. As a result, a critical gap remains in understanding where TFs or other chromatin remodelers bind to DNA and how these interactions are perturbed in pathological contexts. To address this challenge, we developed a transformative single-cell immuno-tethering DNA:Protein mapping technology. By coupling a species-specific antibody-binding nanobody to a cytosine base editing enzyme, this approach enables profiling of even weak or transient factor binding to DNA, a task that was previously unachievable in single cells. Thus, our Docking & Deamination followed by sequencing (D&D-seq) technique induces cytosine-to-uracil edits in genomic regions bound by the target protein, offering a novel means to capture DNA:Protein interactions with unprecedented resolution. Importantly, this technique can be seamlessly incorporated into common single-cell multiomics workflows, enabling multimodal analysis of gene regulation in single cells. We tested the ability of D&D-seq to record TF binding both in bulk and at the single-cell level by profiling CTCF and GATA family members, obtaining high specificity and efficiency, with clear identification of TF footprint and signal retention in the targeted cell subpopulations. Furthermore, the deamination reaction showed minimal off-target activity, with high concordance to bulk ChIP-seq reference data. Applied to primary human peripheral blood mononuclear cells (PBMCs), D&D-seq successfully identified CTCF binding sites and enabled integration with advanced machine-learning algorithms for predicting 3D chromatin structure. Furthermore, we integrated D&D-seq with single-cell genotyping to assess the impact of IDH2 mutations on CTCF binding in a human clonal hematopoiesis sample, uncovering altered binding and chromatin co-accessibility patterns in mutant cells. Altogether, D&D-seq represents an important technological advance enabling the direct mapping of TF or chromatin remodeler binding to the DNA in primary human samples, opening new avenues for understanding chromatin and transcriptional regulation in health and disease.

Data acquisition approaches for single cell proteomics

Single-cell proteomics (SCP) aims to characterize the proteome of individual cells, providing insights into complex biological systems. It reveals subtle differences in distinct cellular populations that bulk proteome analysis may overlook, which is essential for understanding disease mechanisms and developing targeted therapies. Mass spectrometry (MS) methods in SCP allow the identification and quantification of thousands of proteins from individual cells. Two major challenges in SCP are the limited material in single-cell samples necessitating highly sensitive analytical techniques and the efficient processing of samples, as each biological sample requires thousands of single cell measurements. This review discusses MS advancements to mitigate these challenges using data-dependent acquisition (DDA) and data-independent acquisition (DIA). Additionally, we examine the use of short liquid chromatography gradients and sample multiplexing methods that increase the sample throughput and scalability of SCP experiments. We believe these methods will pave the way for improving our understanding of cellular heterogeneity and its implications for systems biology.

RAS-mutant leukaemia stem cells drive clinical resistance to venetoclax

Cancer driver mutations often show distinct temporal acquisition patterns, but the biological basis for this, if any, remains unknown. RAS mutations occur invariably late in the course of acute myeloid leukaemia, upon progression or relapsed/refractory disease1-6. Here, by using human leukaemogenesis models, we first show that RAS mutations are obligatory late events that need to succeed earlier cooperating mutations. We provide the mechanistic explanation for this in a requirement for mutant RAS to specifically transform committed progenitors of the myelomonocytic lineage (granulocyte-monocyte progenitors) harbouring previously acquired driver mutations, showing that advanced leukaemic clones can originate from a different cell type in the haematopoietic hierarchy than ancestral clones. Furthermore, we demonstrate that RAS-mutant leukaemia stem cells (LSCs) give rise to monocytic disease, as observed frequently in patients with poor responses to treatment with the BCL2 inhibitor venetoclax. We show that this is because RAS-mutant LSCs, in contrast to RAS-wild-type LSCs, have altered BCL2 family gene expression and are resistant to venetoclax, driving clinical resistance and relapse with monocytic features. Our findings demonstrate that a specific genetic driver shapes the non-genetic cellular hierarchy of acute myeloid leukaemia by imposing a specific LSC target cell restriction and critically affects therapeutic outcomes in patients.

RNA splicing as a therapeutic target in myelodysplastic syndromes

Myelodysplastic syndromes (MDS) represent a heterogeneous group of hematological disorders and are more commonly found in people over the age of 60. MDS patients exhibit peripheral blood cytopenias and carry an increased risk of disease progression to acute myeloid leukemia (AML). Splicing factor mutations (including genes SF3B1, SRSF2, U2AF1, and ZRSR2) are early events identified in more than 50% of MDS cases. These mutations cause aberrant pre-mRNA splicing and impact MDS pathophysiology. Emerging evidence shows that splicing factor-mutant cells are more sensitive to perturbations targeting the spliceosome, aberrantly spliced genes and/or their regulated molecular pathways. This review summarizes current therapeutic strategies and ongoing efforts targeting splicing factor mutations for the treatment of MDS.

Splicing the Difference: Harnessing the Complexity of the Transcriptome in Hematopoiesis

Alternative splicing has long been recognized as a powerful tool to expand the diversity of the transcriptome and the proteome. The study of hematopoiesis, from hematopoietic stem cell maintenance and differentiation into committed progenitors to maturation into functional blood cells, has led the field of stem cell research and cellular differentiation for decades. The importance of aberrant splicing due to mutations in cis has been exemplified in thalassemias, resulting from aberrant expression of β-globin. The simultaneous development of increasingly sophisticated technologies, in particular the combination of multicolor flow cytometric cell sorting with bulk and single-cell sequencing, has provided sophisticated insights into the complex regulation of the blood system. The recognition that mutations in key splicing factors drive myeloid malignancies, in particular myelodysplastic syndromes, has galvanized research into alternative splicing in hematopoiesis and its diseases. In this review, we will update the audience on the exciting novel technologies, highlight alternative splicing events and their regulators with essential functions in hematopoiesis, and provide a high-level overview how splicing factor mutations contribute to hematologic malignancies.

ER stress as a sentinel mechanism for ER Ca2+ homeostasis

Endoplasmic reticulum (ER) stress is triggered upon the interference with oxidative protein folding that aims to produce fully folded, disulfide-bonded and glycosylated proteins, which are then competent to exit the ER. Many of the enzymes catalyzing this process require the binding of Ca2+ ions, including the chaperones BiP/GRP78, calnexin and calreticulin. The induction of ER stress with a variety of drugs interferes with chaperone Ca2+ binding, increases cytosolic Ca2+through the opening of ER Ca2+ channels, and activates store-operated Ca2+ entry (SOCE). Posttranslational modifications (PTMs) of the ER Ca2+ handling proteins through ER stress-dependent phosphorylation or oxidation control these mechanisms, as demonstrated in the case of the sarco/endoplasmic reticulum ATPase (SERCA), inositol 1,4,5 trisphosphate receptors (IP3Rs) or stromal interaction molecule 1 (STIM1). Their aim is to restore ER Ca2+ homeostasis but also to increase Ca2+ transfer from the ER to mitochondria during ER stress. This latter function boosts ER bioenergetics, but also triggers apoptosis if ER Ca2+ signaling persists. ER Ca2+ toolkit oxidative modifications upon ER stress can occur within the ER lumen or in the adjacent cytosol. Enzymes involved in this redox control include ER oxidoreductin 1 (ERO1) or the thioredoxin-family protein disulfide isomerases (PDI) and ERp57. A tight, but adaptive connection between ER Ca2+ content, ER stress and mitochondrial readouts allows for the proper functioning of many tissues, including skeletal muscle, the liver, and the pancreas, where ER stress either maintains or compromises their function, depending on its extent and context. Upon mutation of key regulators of ER Ca2+ signaling, diseases such as muscular defects (e.g., from mutated selenoprotein N, SEPN1/SELENON), or diabetes (e.g., from mutated PERK) are the result.

CaClust: linking genotype to transcriptional heterogeneity of follicular lymphoma using BCR and exomic variants

Tumours exhibit high genotypic and transcriptional heterogeneity. Both affect cancer progression and treatment, but have been predominantly studied separately in follicular lymphoma. To comprehensively investigate the evolution and genotype-to-phenotype maps in follicular lymphoma, we introduce CaClust, a probabilistic graphical model integrating deep whole exome, single-cell RNA and B-cell receptor sequencing data to infer clone genotypes, cell-to-clone mapping, and single-cell genotyping. CaClust outperforms a state-of-the-art model on simulated and patient data. In-depth analyses of single cells from four samples showcase effects of driver mutations, follicular lymphoma evolution, possible therapeutic targets, and single-cell genotyping that agrees with an independent targeted resequencing experiment.

Unlocking the Complexity: Exploration of Acute Lymphoblastic Leukemia at the Single Cell Level

Acute lymphoblastic leukemia (ALL) is the most common cancer in children. ALL originates from precursor lymphocytes that acquire multiple genomic changes over time, including chromosomal rearrangements and point mutations. While a large variety of genomic defects was identified and characterized in ALL over the past 30 years, it was only in recent years that the clonal heterogeneity was recognized. Thanks to the latest advancements in single-cell sequencing techniques, which have evolved from the analysis of a few hundred cells to the analysis of thousands of cells simultaneously, the study of tumor heterogeneity now becomes possible. Different modalities can be explored at the single-cell level: DNA, RNA, epigenetic modifications, and intracellular and cell surface proteins. In this review, we describe these techniques and highlight their advantages and limitations in the study of ALL biology. Moreover, multiomics technologies and the incorporation of the spatial dimension can provide insight into intercellular communication. We describe how the different single-cell sequencing technologies help to unravel the molecular complexity of ALL, shedding light on its development, its heterogeneity, its interaction with the leukemia microenvironment and possible relapse mechanisms.

Defining the transcriptome of PIK3CA-altered cells in a human capillary malformation using single cell long-read sequencing

PIK3CA-related overgrowth spectrum (PROS) disorders are caused by somatic mosaic variants that result in constitutive activation of the phosphatidylinositol-3-kinase/AKT/mTOR pathway. Promising responses to molecularly targeted therapy have been reported, although identification of an appropriate agent can be hampered by the mosaic nature and corresponding low variant allele frequency of the causal variant. Moreover, our understanding of the molecular consequences of these variants-for example how they affect gene expression profiles-remains limited. Here we describe in vitro expansion of a human capillary malformation followed by molecular characterization using exome sequencing, single cell gene expression, and targeted long-read single cell RNA-sequencing in a patient with clinical features consistent with Megalencephaly-Capillary Malformation Syndrome (MCAP, a PROS condition). These approaches identified a targetable PIK3CA variant with expression restricted to PAX3+ fibroblast and undifferentiated keratinocyte populations. This study highlights the innovative combination of next-generation single cell sequencing methods to better understand unique transcriptomic profiles and cell types associated with MCAP, revealing molecular intricacies of this genetic syndrome.

Human embryonic genetic mosaicism and its effects on development and disease

Nearly every mammalian cell division is accompanied by a mutational event that becomes fixed in a daughter cell. When carried forward to additional cell progeny, a clone of variant cells can emerge. As a result, mammals are complex mosaics of clones that are genetically distinct from one another. Recent high-throughput sequencing studies have revealed that mosaicism is common, clone sizes often increase with age and specific variants can affect tissue function and disease development. Variants that are acquired during early embryogenesis are shared by multiple cell types and can affect numerous tissues. Within tissues, variant clones compete, which can result in their expansion or elimination. Embryonic mosaicism has clinical implications for genetic disease severity and transmission but is likely an under-recognized phenomenon. To better understand its implications for mosaic individuals, it is essential to leverage research tools that can elucidate the mechanisms by which expanded embryonic variants influence development and disease.

Temporal recording of mammalian development and precancer

Temporal ordering of cellular events offers fundamental insights into biological phenomena. Although this is traditionally achieved through continuous direct observations1,2, an alternative solution leverages irreversible genetic changes, such as naturally occurring mutations, to create indelible marks that enables retrospective temporal ordering3-5. Using a multipurpose, single-cell CRISPR platform, we developed a molecular clock approach to record the timing of cellular events and clonality in vivo, with incorporation of cell state and lineage information. Using this approach, we uncovered precise timing of tissue-specific cell expansion during mouse embryonic development, unconventional developmental relationships between cell types and new epithelial progenitor states by their unique genetic histories. Analysis of mouse adenomas, coupled to multiomic and single-cell profiling of human precancers, with clonal analysis of 418 human polyps, demonstrated the occurrence of polyclonal initiation in 15-30% of colonic precancers, showing their origins from multiple normal founders. Our study presents a multimodal framework that lays the foundation for in vivo recording, integrating synthetic or natural indelible genetic changes with single-cell analyses, to explore the origins and timing of development and tumorigenesis in mammalian systems.

The stress response regulator HSF1 modulates natural killer cell anti-tumour immunity

Diverse cellular insults converge on activation of the heat shock factor 1 (HSF1), which regulates the proteotoxic stress response to maintain protein homoeostasis. HSF1 regulates numerous gene programmes beyond the proteotoxic stress response in a cell-type- and context-specific manner to promote malignancy. However, the role(s) of HSF1 in immune populations of the tumour microenvironment remain elusive. Here, we leverage an in vivo model of HSF1 activation and single-cell transcriptomic tumour profiling to show that augmented HSF1 activity in natural killer (NK) cells impairs cytotoxicity, cytokine production and subsequent anti-tumour immunity. Mechanistically, HSF1 directly binds and regulates the expression of key mediators of NK cell effector function. This work demonstrates that HSF1 regulates the immune response under the stress conditions of the tumour microenvironment. These findings have important implications for enhancing the efficacy of adoptive NK cell therapies and for designing combinatorial strategies including modulators of NK cell-mediated tumour killing.

Megakaryocyte maturation involves activation of the adaptive unfolded protein response

Endoplasmic reticulum stress triggers the unfolded protein response (UPR) to promote cell survival or apoptosis. Transient endoplasmic reticulum stress activation has been reported to trigger megakaryocyte production, and UPR activation has been reported as a feature of megakaryocytic cancers. However, the role of UPR signaling in megakaryocyte biology is not fully understood. We studied the involvement of UPR in human megakaryocytic differentiation using PMA (phorbol 12-myristate 13-acetate)-induced maturation of megakaryoblastic cell lines and thrombopoietin-induced differentiation of human peripheral blood-derived progenitors. Our results demonstrate that an adaptive UPR is a feature of megakaryocytic differentiation and that this response is not associated with ER stress-induced apoptosis. Differentiation did not alter the response to the canonical endoplasmic reticulum stressors DTT or thapsigargin. However, thapsigargin, but not DTT, inhibited differentiation, consistent with the involvement of Ca2+ signaling in megakaryocyte differentiation.

The evolutionary theory of cancer: challenges and potential solutions

The clonal evolution model of cancer was developed in the 1950s-1970s and became central to cancer biology in the twenty-first century, largely through studies of cancer genetics. Although it has proven its worth, its structure has been challenged by observations of phenotypic plasticity, non-genetic forms of inheritance, non-genetic determinants of clone fitness and non-tree-like transmission of genes. There is even confusion about the definition of a clone, which we aim to resolve. The performance and value of the clonal evolution model depends on the empirical extent to which evolutionary processes are involved in cancer, and on its theoretical ability to account for those evolutionary processes. Here, we identify limits in the theoretical performance of the clonal evolution model and provide solutions to overcome those limits. Although we do not claim that clonal evolution can explain everything about cancer, we show how many of the complexities that have been identified in the dynamics of cancer can be integrated into the model to improve our current understanding of cancer.

Unveiling aging dynamics in the hematopoietic system insights from single-cell technologies

As the demographic structure shifts towards an aging society, strategies aimed at slowing down or reversing the aging process become increasingly essential. Aging is a major predisposing factor for many chronic diseases in humans. The hematopoietic system, comprising blood cells and their associated bone marrow microenvironment, intricately participates in hematopoiesis, coagulation, immune regulation and other physiological phenomena. The aging process triggers various alterations within the hematopoietic system, serving as a spectrum of risk factors for hematopoietic disorders, including clonal hematopoiesis, immune senescence, myeloproliferative neoplasms and leukemia. The emerging single-cell technologies provide novel insights into age-related changes in the hematopoietic system. In this review, we summarize recent studies dissecting hematopoietic system aging using single-cell technologies. We discuss cellular changes occurring during aging in the hematopoietic system at the levels of the genomics, transcriptomics, epigenomics, proteomics, metabolomics and spatial multi-omics. Finally, we contemplate the future prospects of single-cell technologies, emphasizing the impact they may bring to the field of hematopoietic system aging research.

SIngle cell level Genotyping Using scRna Data (SIGURD)

MOTIVATION

By accounting for variants within measured transcripts, it is possible to evaluate the status of somatic variants using single-cell RNA-sequencing (scRNA-seq) and to characterize their clonality. However, the sparsity (very few reads per transcript) or bias in protocols (favoring 3' ends of the transcripts) makes the chance of capturing somatic variants very unlikely. This can be overcome by targeted sequencing or the use of mitochondrial variants as natural barcodes for clone identification. Currently, available computational tools focus on genotyping, but do not provide functionality for combined analysis of somatic and mitochondrial variants and functional analysis such as characterization of gene expression changes in detected clones.

RESULTS

Here, we propose SIGURD (SIngle cell level Genotyping Using scRna Data) (SIGURD), which is an R-based pipeline for the clonal analysis of scRNA-seq data. This allows the quantification of clones by leveraging both somatic and mitochondrial variants. SIGURD also allows for functional analysis after clonal detection: association of clones with cell populations, detection of differentially expressed genes across clones, and association of somatic and mitochondrial variants. Here, we demonstrate the power of SIGURD by analyzing single-cell data of colony-forming cells derived from patients with myeloproliferative neoplasms.

Differential modulation of mutant CALR and JAK2 V617F-driven oncogenesis by HLA genotype in myeloproliferative neoplasms

It has been demonstrated previously that human leukocyte antigen class I (HLA-I) and class II (HLA-II) alleles may modulate JAK2 V617F and CALR mutation (CALRmut)-associated oncogenesis in myeloproliferative neoplasms (MPNs). However, the role of immunogenetic factors in MPNs remains underexplored. We aimed to investigate the potential involvement of HLA genes in CALRmut+ MPNs. High-resolution genotyping of HLA-I and -II loci was conducted in 42 CALRmut+ and 158 JAK2 V617F+ MPN patients and 1,083 healthy controls. A global analysis of the diversity of HLA-I genotypes revealed no significant differences between CALRmut+ patients and controls. However, one HLA-I allele (C*06:02) showed an inverse correlation with presence of CALR mutation. A meta-analysis across independent cohorts and healthy individuals from the 1000 Genomes Project confirmed an inverse correlation between the presentation capabilities of the HLA-I loci for JAK2 V617F and CALRmut-derived peptides in both patients and healthy individuals. scRNA-Seq analysis revealed low expression of TAP1 and CIITA genes in CALRmut+ hematopoietic stem and progenitor cells. In conclusion, the HLA-I genotype differentially restricts JAK2 V617F and CALRmut-driven oncogenesis potentially explaining the mutual exclusivity of the two mutations and differences in their presentation latency. These findings have practical implications for the development of neoantigen-based vaccines in MPNs.

Transcripts of repetitive DNA elements signal to block phagocytosis of hematopoietic stem cells

Macrophages maintain hematopoietic stem cell (HSC) quality by assessing cell surface Calreticulin (Calr), an "eat-me" signal induced by reactive oxygen species (ROS). Using zebrafish genetics, we identified Beta-2-microglobulin (B2m) as a crucial "don't eat-me" signal on blood stem cells. A chemical screen revealed inducers of surface Calr that promoted HSC proliferation without triggering ROS or macrophage clearance. Whole-genome CRISPR-Cas9 screening showed that Toll-like receptor 3 (Tlr3) signaling regulated b2m expression. Targeting b2m or tlr3 reduced the HSC clonality. Elevated B2m levels correlated with high expression of repetitive element (RE) transcripts. Overall, our data suggest that RE-associated double-stranded RNA could interact with TLR3 to stimulate surface expression of B2m on hematopoietic stem and progenitor cells. These findings suggest that the balance of Calr and B2m regulates macrophage-HSC interactions and defines hematopoietic clonality.

Cancer cell states: Lessons from ten years of single-cell RNA-sequencing of human tumors

Human tumors are intricate ecosystems composed of diverse genetic clones and malignant cell states that evolve in a complex tumor micro-environment. Single-cell RNA-sequencing (scRNA-seq) provides a compelling strategy to dissect this intricate biology and has enabled a revolution in our ability to understand tumor biology over the last ten years. Here we reflect on this first decade of scRNA-seq in human tumors and highlight some of the powerful insights gleaned from these studies. We first focus on computational approaches for robustly defining cancer cell states and their diversity and highlight some of the most common patterns of gene expression intra-tumor heterogeneity (eITH) observed across cancer types. We then discuss ambiguities in the field in defining and naming such eITH programs. Finally, we highlight critical developments that will facilitate future research and the broader implementation of these technologies in clinical settings.

New frameworks for hematopoiesis derived from single-cell genomics

ABSTRACT

Recent advancements in single-cell genomics have enriched our understanding of hematopoiesis, providing intricate details about hematopoietic stem cell biology, differentiation, and lineage commitment. Technological advancements have highlighted extensive heterogeneity of cell populations and continuity of differentiation routes. Nevertheless, intermediate "attractor" states signify structure in stem and progenitor populations that link state transition dynamics to fate potential. We discuss how innovative model systems quantify lineage bias and how stress accelerates differentiation, thereby reducing fate plasticity compared with native hematopoiesis. We conclude by offering our perspective on the current model of hematopoiesis and discuss how a more precise understanding can translate to strategies that extend healthy hematopoiesis and prevent disease.

Identifying cancer cells from calling single-nucleotide variants in scRNA-seq data

MOTIVATION

Single-cell RNA sequencing (scRNA-seq) data are widely used to study cancer cell states and their heterogeneity. However, the tumour microenvironment is usually a mixture of healthy and cancerous cells and it can be difficult to fully separate these two populations based on transcriptomics alone. If available, somatic single-nucleotide variants (SNVs) observed in the scRNA-seq data could be used to identify the cancer population and match that information with the single cells' expression profile. However, calling somatic SNVs in scRNA-seq data is a challenging task, as most variants seen in the short-read data are not somatic, but can instead be germline variants, RNA edits or transcription, sequencing, or processing errors. In addition, only variants present in actively transcribed regions for each individual cell will be seen in the data.

RESULTS

To address these challenges, we develop CCLONE (Cancer Cell Labelling On Noisy Expression), an interpretable tool adapted to handle the uncertainty and sparsity of SNVs called from scRNA-seq data. CCLONE jointly identifies cancer clonal populations, and their associated variants. We apply CCLONE on two acute myeloid leukaemia datasets and one lung adenocarcinoma dataset and show that CCLONE captures both genetic clones and somatic events for multiple patients. These results show how CCLONE can be used to gather insight into the course of the disease and the origin of cancer cells in scRNA-seq data.

AVAILABILITY AND IMPLEMENTATION

Source code is available at github.com/HaghverdiLab/CCLONE.

Transient Differentiation-State Plasticity Occurs during Acute Lymphoblastic Leukemia Initiation

Leukemia is characterized by oncogenic lesions that result in a block of differentiation, whereas phenotypic plasticity is retained. A better understanding of how these two phenomena arise during leukemogenesis in humans could help inform diagnosis and treatment strategies. Here, we leveraged the well-defined differentiation states during T-cell development to pinpoint the initiation of T-cell acute lymphoblastic leukemia (T-ALL), an aggressive form of childhood leukemia, and study the emergence of phenotypic plasticity. Single-cell whole genome sequencing of leukemic blasts was combined with multiparameter flow cytometry to couple cell identity and clonal lineages. Irrespective of genetic events, leukemia-initiating cells altered their phenotypes by differentiation and dedifferentiation. The construction of the phylogenies of individual leukemias using somatic mutations revealed that phenotypic diversity is reflected by the clonal structure of cancer. The analysis also indicated that the acquired phenotypes are heritable and stable. Together, these results demonstrate a transient period of plasticity during leukemia initiation, where phenotypic switches seem unidirectional. Significance: A method merging multicolor flow cytometry with single-cell whole genome sequencing to couple cell identity with clonal lineages uncovers differentiation-state plasticity in leukemia, reconciling blocked differentiation with phenotypic plasticity in cancer.

Multiomic profiling of human clonal hematopoiesis reveals genotype and cell-specific inflammatory pathway activation

ABSTRACT

Clonal hematopoiesis (CH) is an age-associated phenomenon that increases the risk of hematologic malignancy and cardiovascular disease. CH is thought to enhance disease risk through inflammation in the peripheral blood.1 Here, we profile peripheral blood gene expression in 66 968 single cells from a cohort of 17 patients with CH and 7 controls. Using a novel mitochondrial DNA barcoding approach, we were able to identify and separately compare mutant Tet methylcytosine dioxygenase 2 (TET2) and DNA methyltransferase 3A (DNMT3A) cells with nonmutant counterparts. We discovered the vast majority of mutated cells were in the myeloid compartment. Additionally, patients harboring DNMT3A and TET2 CH mutations possessed a proinflammatory profile in CD14+ monocytes through previously unrecognized pathways such as galectin and macrophage inhibitory factor. We also found that T cells from patients with CH, although mostly unmutated, had decreased expression of GTPase of the immunity associated protein genes, which are critical to T-cell development, suggesting that CH impairs T-cell function.

Discovering mechanisms of human genetic variation and controlling cell states at scale

Population-scale sequencing efforts have catalogued substantial genetic variation in humans such that variant discovery dramatically outpaces interpretation. We discuss how single-cell sequencing is poised to reveal genetic mechanisms at a rate that may soon approach that of variant discovery. The functional genomics toolkit is sufficiently modular to systematically profile almost any type of variation within increasingly diverse contexts and with molecularly comprehensive and unbiased readouts. As a result, we can construct deep phenotypic atlases of variant effects that span the entire regulatory cascade. The same conceptual approach to interpreting genetic variation should be applied to engineering therapeutic cell states. In this way, variant mechanism discovery and cell state engineering will become reciprocating and iterative processes towards genomic medicine.

Cell Type- and Age-Specific Expression of lncRNAs across Kidney Cell Types

Key Points

Background

Accumulated evidence demonstrates that long noncoding RNAs (lncRNAs) regulate cell differentiation and homeostasis, influencing kidney aging and disease. Despite their versatility, the function of lncRNA remains poorly understood because of the lack of a reference map of lncRNA transcriptome in various cell types.

Methods

In this study, we used a targeted single-cell RNA sequencing method to enrich and characterize lncRNAs in individual cells. We applied this method to various mouse tissues, including normal and aged kidneys.

Results

Through tissue-specific clustering analysis, we identified cell type–specific lncRNAs that showed a high correlation with known cell-type marker genes. Furthermore, we constructed gene regulatory networks to explore the functional roles of differentially expressed lncRNAs in each cell type. In the kidney, we observed dynamic expression changes of lncRNAs during aging, with specific changes in glomerular cells. These cell type– and age-specific expression patterns of lncRNAs suggest that lncRNAs may have a potential role in regulating cellular processes, such as immune response and energy metabolism, during kidney aging.

Conclusions

Our study sheds light on the comprehensive landscape of lncRNA expression and function and provides a valuable resource for future analysis of lncRNAs (https://gist-fgl.github.io/sc-lncrna-atlas/).

GoT-Splice protocol for multi-omics profiling of gene expression, cell-surface proteins, mutational status, and RNA splicing in human cells

Studying RNA splicing factor mutations is challenging due to difficulties in distinguishing wild-type and mutant cells within complex human tissues and inaccuracies associated with reconstructing splicing signals from short-read sequencing data. Here, we present Genotyping of Transcriptomes (GoT)-Splice, a protocol that overcomes these limitations by combining GoT with enhanced long-read single-cell transcriptome and cell-surface proteomics profiling. We describe steps for long-read library preparation and analysis, followed by cDNA re-amplification, enrichment of mutation of interest, sample indexing, and GoT library preparation. For complete details on the use and execution of this protocol, please refer to Cortés-López et al.1.

Massively parallel in vivo Perturb-seq reveals cell-type-specific transcriptional networks in cortical development

Leveraging AAVs' versatile tropism and labeling capacity, we expanded the scale of in vivo CRISPR screening with single-cell transcriptomic phenotyping across embryonic to adult brains and peripheral nervous systems. Through extensive tests of 86 vectors across AAV serotypes combined with a transposon system, we substantially amplified labeling efficacy and accelerated in vivo gene delivery from weeks to days. Our proof-of-principle in utero screen identified the pleiotropic effects of Foxg1, highlighting its tight regulation of distinct networks essential for cell fate specification of Layer 6 corticothalamic neurons. Notably, our platform can label >6% of cerebral cells, surpassing the current state-of-the-art efficacy at <0.1% by lentivirus, to achieve analysis of over 30,000 cells in one experiment and enable massively parallel in vivo Perturb-seq. Compatible with various phenotypic measurements (single-cell or spatial multi-omics), it presents a flexible approach to interrogate gene function across cell types in vivo, translating gene variants to their causal function.

Single-cell genomics-based immune and disease monitoring in blood malignancies

Achieving long-term disease control using therapeutic immunomodulation is a long-standing concept with a strong tradition in blood malignancies. Besides allogeneic hematopoietic stem cell transplantation that continues to provide potentially curative treatment for otherwise challenging diagnoses, recent years have seen impressive progress in immunotherapies for leukemias and lymphomas with immune checkpoint blockade, bispecific monoclonal antibodies, and CAR T cell therapies. Despite their success, non-response, relapse, and immune toxicities remain frequent, thus prioritizing the elucidation of the underlying mechanisms and identifying predictive biomarkers. The increasing availability of single-cell genomic tools now provides a system's immunology view to resolve the molecular and cellular mechanisms of immunotherapies at unprecedented resolution. Here, we review recent studies that leverage these technological advancements for tracking immune responses, the emergence of immune resistance, and toxicities. As single-cell immune monitoring tools evolve and become more accessible, we expect their wide adoption for routine clinical applications to catalyze more precise therapeutic steering of personal immune responses.

Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease

Efforts to cure BCR::ABL1 B cell acute lymphoblastic leukemia (Ph+ ALL) solely through inhibition of ABL1 kinase activity have thus far been insufficient despite the availability of tyrosine kinase inhibitors (TKIs) with broad activity against resistance mutants. The mechanisms that drive persistence within minimal residual disease (MRD) remain poorly understood and therefore untargeted. Utilizing 13 patient-derived xenograft (PDX) models and clinical trial specimens of Ph+ ALL, we examined how genetic and transcriptional features co-evolve to drive progression during prolonged TKI response. Our work reveals a landscape of cooperative mutational and transcriptional escape mechanisms that differ from those causing resistance to first generation TKIs. By analyzing MRD during remission, we show that the same resistance mutation can either increase or decrease cellular fitness depending on transcriptional state. We further demonstrate that directly targeting transcriptional state-associated vulnerabilities at MRD can overcome BCR::ABL1 independence, suggesting a new paradigm for rationally eradicating MRD prior to relapse. Finally, we illustrate how cell mass measurements of leukemia cells can be used to rapidly monitor dominant transcriptional features of Ph+ ALL to help rationally guide therapeutic selection from low-input samples.

Application of omics in the diagnosis, prognosis, and treatment of acute myeloid leukemia

Acute myeloid leukemia (AML) is the most frequent leukemia in adults with a high mortality rate. Current diagnostic criteria and selections of therapeutic strategies are generally based on gene mutations and cytogenetic abnormalities. Chemotherapy, targeted therapies, and hematopoietic stem cell transplantation (HSCT) are the major therapeutic strategies for AML. Two dilemmas in the clinical management of AML are related to its poor prognosis. One is the inaccurate risk stratification at diagnosis, leading to incorrect treatment selections. The other is the frequent resistance to chemotherapy and/or targeted therapies. Genomic features have been the focus of AML studies. However, the DNA-level aberrations do not always predict the expression levels of genes and proteins and the latter is more closely linked to disease phenotypes. With the development of high-throughput sequencing and mass spectrometry technologies, studying downstream effectors including RNA, proteins, and metabolites becomes possible. Transcriptomics can reveal gene expression and regulatory networks, proteomics can discover protein expression and signaling pathways intimately associated with the disease, and metabolomics can reflect precise changes in metabolites during disease progression. Moreover, omics profiling at the single-cell level enables studying cellular components and hierarchies of the AML microenvironment. The abundance of data from different omics layers enables the better risk stratification of AML by identifying prognosis-related biomarkers, and has the prospective application in identifying drug targets, therefore potentially discovering solutions to the two dilemmas. In this review, we summarize the existing AML studies using omics methods, both separately and combined, covering research fields of disease diagnosis, risk stratification, prognosis prediction, chemotherapy, as well as targeted therapy. Finally, we discuss the directions and challenges in the application of multi-omics in precision medicine of AML. Our review may inspire both omics researchers and clinical physicians to study AML from a different angle.

Genotype-to-phenotype mapping of somatic clonal mosaicism via single-cell co-capture of DNA mutations and mRNA transcripts

Somatic mosaicism is a hallmark of malignancy that is also pervasively observed in human physiological aging, with clonal expansions of cells harboring mutations in recurrently mutated driver genes. Bulk sequencing of tissue microdissection captures mutation frequencies, but cannot distinguish which mutations co-occur in the same clones to reconstruct clonal architectures, nor phenotypically profile clonal populations to delineate how driver mutations impact cellular behavior. To address these challenges, we developed single-cell Genotype-to-Phenotype sequencing (scG2P) for high-throughput, highly-multiplexed, single-cell joint capture of recurrently mutated genomic regions and mRNA phenotypic markers in cells or nuclei isolated from solid tissues. We applied scG2P to aged esophagus samples from five individuals with high alcohol and tobacco exposure and observed a clonal landscape dominated by a large number of clones with a single driver event, but only rare clones with two driver mutations. NOTCH1 mutants dominate the clonal landscape and are linked to stunted epithelial differentiation, while TP53 mutants and double-driver mutants promote clonal expansion through both differentiation biases and increased cell cycling. Thus, joint single-cell highly multiplexed capture of somatic mutations and mRNA transcripts enables high resolution reconstruction of clonal architecture and associated phenotypes in solid tissue somatic mosaicism.

Cell of origin epigenetic priming determines susceptibility to Tet2 mutation

Hematopoietic stem cell (HSC) mutations can result in clonal hematopoiesis (CH) with heterogeneous clinical outcomes. Here, we investigate how the cell state preceding Tet2 mutation impacts the pre-malignant phenotype. Using an inducible system for clonal analysis of myeloid progenitors, we find that the epigenetic features of clones at similar differentiation status are highly heterogeneous and functionally respond differently to Tet2 mutation. Cell differentiation stage also influences Tet2 mutation response indicating that the cell of origin's epigenome modulates clone-specific behaviors in CH. Molecular features associated with higher risk outcomes include Sox4 that sensitizes cells to Tet2 inactivation, inducing dedifferentiation, altered metabolism and increasing the in vivo clonal output of mutant cells, as confirmed in primary GMP and HSC models. Our findings validate the hypothesis that epigenetic features can predispose specific clones for dominance, explaining why identical genetic mutations can result in different phenotypes.

Analyzing the functional effects of DNA variants with gene editing

Continual advancements in genomics have led to an ever-widening disparity between the rate of discovery of genetic variants and our current understanding of their functions and potential roles in disease. Systematic methods for phenotyping DNA variants are required to effectively translate genomics data into improved outcomes for patients with genetic diseases. To make the biggest impact, these approaches must be scalable and accurate, faithfully reflect disease biology, and define complex disease mechanisms. We compare current methods to analyze the function of variants in their endogenous DNA context using genome editing strategies, such as saturation genome editing, base editing and prime editing. We discuss how these technologies can be linked to high-content readouts to gain deep mechanistic insights into variant effects. Finally, we highlight key challenges that need to be addressed to bridge the genotype to phenotype gap, and ultimately improve the diagnosis and treatment of genetic diseases.