Lineage tracing on transcriptional landscapes links state to fate during differentiation

Barcodes based on nucleic acid sequences: Applications and challenges (Review)

Cells are the fundamental structural and functional units of living organisms and the study of these entities has remained a central focus throughout the history of biological sciences. Traditional cell research techniques, including fluorescent protein tagging and microscopy, have provided preliminary insights into the lineage history and clonal relationships between progenitor and descendant cells. However, these techniques exhibit inherent limitations in tracking the full developmental trajectory of cells and elucidating their heterogeneity, including sensitivity, stability and barcode drift. In developmental biology, nucleic acid barcode technology has introduced an innovative approach to cell lineage tracing. By assigning unique barcodes to individual cells, researchers can accurately identify and trace the origin and differentiation pathways of cells at various developmental stages, thereby illuminating the dynamic processes underlying tissue development and organogenesis. In cancer research, nucleic acid barcoding has played a pivotal role in analyzing the clonal architecture of tumor cells, exploring their heterogeneity and resistance mechanisms and enhancing our understanding of cancer evolution and inter‑clonal interactions. Furthermore, nucleic acid barcodes play a crucial role in stem cell research, enabling the tracking of stem cells from diverse origins and their derived progeny. This has offered novel perspectives on the mechanisms of stem cell self‑renewal and differentiation. The present review presented a comprehensive examination of the principles, applications and challenges associated with nucleic acid barcode technology.

Clonal tracing with somatic epimutations reveals dynamics of blood ageing

Current approaches used to track stem cell clones through differentiation require genetic engineering1,2 or rely on sparse somatic DNA variants3,4, which limits their wide application. Here we discover that DNA methylation of a subset of CpG sites reflects cellular differentiation, whereas another subset undergoes stochastic epimutations and can serve as digital barcodes of clonal identity. We demonstrate that targeted single-cell profiling of DNA methylation5 at single-CpG resolution can accurately extract both layers of information. To that end, we develop EPI-Clone, a method for transgene-free lineage tracing at scale. Applied to mouse and human haematopoiesis, we capture hundreds of clonal differentiation trajectories across tens of individuals and 230,358 single cells. In mouse ageing, we demonstrate that myeloid bias and low output of old haematopoietic stem cells6 are restricted to a small number of expanded clones, whereas many functionally young-like clones persist in old age. In human ageing, clones with and without known driver mutations of clonal haematopoieis7 are part of a spectrum of age-related clonal expansions that display similar lineage biases. EPI-Clone enables accurate and transgene-free single-cell lineage tracing on hematopoietic cell state landscapes at scale.

A multi-kingdom genetic barcoding system for precise clone isolation

Cell-tagging strategies with DNA barcodes have enabled the analysis of clone size dynamics and clone-restricted transcriptomic landscapes in heterogeneous populations. However, isolating a target clone that displays a specific phenotype from a complex population remains challenging. Here we present a multi-kingdom genetic barcoding system, CloneSelect, which enables a target cell clone to be triggered to express a reporter gene for isolation through barcode-specific CRISPR base editing. In CloneSelect, cells are first stably tagged with DNA barcodes and propagated so that their subpopulation can be subjected to a given experiment. A clone that shows a phenotype or genotype of interest at a given time can then be isolated from the initial or subsequent cell pools stored during the experiment using CRISPR base editing. CloneSelect is scalable and compatible with single-cell RNA sequencing. We demonstrate the versatility of CloneSelect in human embryonic kidney 293T cells, mouse embryonic stem cells, human pluripotent stem cells, yeast cells and bacterial cells.

Genetically Encoded Fluorescence Barcodes Allow for Single-Cell Analysis via Spectral Flow Cytometry

Genetically encoded, single-cell barcodes are broadly useful for experimental tasks such as lineage tracing or genetic screens. For such applications, a barcode library would ideally have high diversity (many unique barcodes), nondestructive identification (repeated measurements in the same cells or population), and fast, inexpensive readout (many cells and conditions). Current nucleic acid barcoding methods generate high diversity but require destructive and slow/expensive readout, and current fluorescence barcoding methods are nondestructive, fast, and inexpensive to readout but lack high diversity. We recently proposed a theory for how fluorescent protein combinations may generate a high-diversity barcode library with nondestructive, fast, and inexpensive identification. Here, we present an initial experimental proof-of-concept by generating a library of ∼150 barcodes from two-way combinations of 18 fluorescent proteins, 61 of which are tested experimentally. We use a pooled cloning strategy to generate a barcode library that is validated to contain every possible combination of the 18 fluorescent proteins. Experimental results using single mammalian cells and spectral flow cytometry demonstrate excellent classification performance of individual fluorescent proteins, with the exception of mTFP1, and of most evaluated barcodes, with many true positive rates >99%. The library is compatible with genetic screening for hundreds of genes (or gene pairs) and lineage tracing hundreds of clones. This work lays a foundation for greater diversity libraries (potentially ∼105 and more) generated from hundreds of spectrally resolvable tandem fluorescent protein probes.

LoxCode in vivo barcoding reveals epiblast clonal fate bias to fetal organs

Much remains to be learned about the clonal fate of mammalian epiblast cells. Here, we develop high-diversity Cre recombinase-driven LoxCode barcoding for in vivo clonal lineage tracing for bulk tissue and single-cell readout. Embryonic day (E) 5.5 pre-gastrulation embryos were barcoded in utero, and epiblast clones were assessed for their contribution to a wide range of tissues in E12.5 embryos. Some epiblast clones contributed broadly across germ layers, while many were biased toward either blood, ectoderm, mesenchyme, or limbs, across tissue compartments and body axes. Using a stochastic agent-based model of embryogenesis and LoxCode barcoding, we inferred and experimentally validated cell fate biases across tissues in line with shared and segregating differentiation trajectories. Single-cell readout revealed numerous instances of asymmetry in epiblast contribution, including left-versus-right and kidney-versus-gonad fate. LoxCode barcoding enables clonal fate analysis for the study of development and broader questions of clonality in murine biology.

DNMT3A regulates murine megakaryocyte-biased hematopoietic stem cell fate decisions

ABSTRACT

Hematopoietic stem cells (HSCs) are defined by their capacity to regenerate all main components of peripheral blood, but individual HSCs exhibit a range of preferences for generating downstream cell types. Their propensities are thought to be epigenetically encoded, but few differential regulatory mechanisms have been identified. In this work, we explored the role of DNA methyltransferase 3A (DNMT3A) in the megakaryocyte-biased HSC population, which is thought to reside at the top of the hematopoietic hierarchy. We demonstrate that heterozygous loss of DNMT3A (Dnmt3a+/-) in these megakaryocyte-biased HSCs has distinct consequences compared with the rest of the HSC pool. These megakaryocyte-biased HSCs become delayed in their lymphoid-repopulating ability but can ultimately regenerate all lineages. We further demonstrate that Dnmt3a+/- mice have increased numbers of megakaryocytes in the bone marrow. Analysis of DNA methylation differences between wild-type (WT) and Dnmt3a+/- HSC subsets, megakaryocyte-erythroid progenitors, and megakaryocytes revealed that DNA methylation is eroded in the mutants in a cell type-specific fashion. Although transcriptional differences between WT and Dnmt3a+/- megakaryocyte-biased HSCs are subtle, the pattern of DNA methylation loss in this HSC subset is almost completely different from that in non-megakaryocyte-biased HSCs. Together, our findings establish the role of epigenetic regulation in the fate of megakaryocyte-biased HSCs and their downstream progeny and suggest that the outcomes of DNMT3A loss might vary depending on the identity of the HSC that acquires the mutation.

Monocytes can efficiently replace all brain macrophages and fetal liver monocytes can generate bona fide SALL1+ microglia

Microglia and border-associated macrophages (BAMs) are critical for brain health, and their dysfunction is associated to disease. Replacing brain macrophages holds substantial therapeutic promise but remains challenging. Here, we demonstrate that monocytes can efficiently replace all brain macrophages. Monocytes readily replaced embryonal BAMs upon their depletion and engrafted as monocyte-derived microglia (Mo-Microglia) upon more sustained niche availability. Mo-Microglia expanded comparably to their embryonic counterparts and showed similar longevity. However, monocytes were unable to replicate the distinct identity of embryonically derived BAMs and microglia. Using xenotransplantation, we found that human monocytes exhibited similar behavior, enabling identification of putative Mo-Microglia in Alzheimer's disease individuals. In mice and humans, monocyte ontogeny shaped their identity as brain macrophages. Importantly, mouse fetal liver monocytes exhibited a distinct epigenetic landscape and could develop a bona fide microglial identity. Our results illuminate brain macrophage development and highlight monocytes as an abundant progenitor source for brain macrophage replacement therapies.

Fitness and transcriptional plasticity of human breast cancer single-cell-derived clones

Clonal fitness and plasticity drive cancer heterogeneity. We used expressed lentiviral-based cellular barcodes combined with single-cell RNA sequencing to associate single-cell profiles with in vivo clonal growth. This generated a significant resource of growth measurements from over 20,000 single-cell-derived clones in 110 xenografts from 26 patient-derived breast cancer xenograft models. 167,375 single-cell RNA profiles were obtained from 5 models and revealed that rare propagating clones display a highly conserved model-specific differentiation program with reproducible regeneration of the entire transcriptomic landscape of the original xenograft. In 2 models of basal breast cancer, propagating clones demonstrated remarkable transcriptional plasticity at single-cell resolution. Dichotomous cell populations with different clonal growth properties, signaling pathways, and metabolic programs were characterized. By directly linking clonal growth with single-cell transcriptomes, these findings provide a profound understanding of clonal fitness and plasticity with implications for cancer biology and therapy.

Understanding rheumatic disease through continuous cell state analysis

Autoimmune rheumatic diseases are a heterogeneous group of conditions, including rheumatoid arthritis (RA) and systemic lupus erythematosus. With the increasing availability of large single-cell datasets, novel disease-associated cell types continue to be identified and characterized at multiple omics layers, for example, 'T peripheral helper' (TPH) (CXCR5- PD-1hi) cells in RA and systemic lupus erythematosus and MerTK+ myeloid cells in RA. Despite efforts to define disease-relevant cell atlases, the very definition of a 'cell type' or 'lineage' has proven controversial as higher resolution assays emerge. This Review explores the cell types and states involved in disease pathogenesis, with a focus on the shifting perspectives on immune and stromal cell taxonomy. These understandings of cell identity are closely related to the computational methods adopted for analysis, with implications for the interpretation of single-cell data. Understanding the underlying cellular architecture of disease is also crucial for therapeutic research as ambiguity hinders translation to the clinical setting. We discuss the implications of different frameworks for cell identity for disease treatment and the discovery of predictive biomarkers for stratified medicine - an unmet clinical need for autoimmune rheumatic diseases.

Anti-tumor necrosis factor therapy in the treatment of systemic autoinflammatory diseases: the responses of innate immune cells

Systemic autoinflammatory diseases are rare conditions resulting from dysregulation of the innate immune system, culminating in repetitive bouts of systemic inflammation without the presence of external or self-antigens. Most systemic autoinflammatory diseases are associated with mutations in genes affecting the innate immune response. Tumor necrosis factor is a central player in the pathogenesis of numerous chronic inflammatory disorders, and anti-tumor necrosis factor therapy is widely used in the clinical management of systemic autoinflammatory diseases. Tumor necrosis factor inhibitors block the interaction of tumor necrosis factor with its 2 receptors, tumor necrosis factor receptor 1 and tumor necrosis factor receptor 2. These inhibitors primarily target soluble tumor necrosis factor, which mainly binds to tumor necrosis factor receptor 1, exerting anti-inflammatory effects. Interestingly, tumor necrosis factor inhibitors also affect transmembrane tumor necrosis factor, which engages tumor necrosis factor receptor 2 to initiate reverse signaling. This reverse signaling can activate innate immune cells, prevent apoptosis, or paradoxically inhibit the production of pro-inflammatory cytokines. Tumor necrosis factor inhibitors also promote the release of soluble tumor necrosis factor receptor 2, which neutralizes circulating tumor necrosis factor. Some agents targeting tumor necrosis factor receptor 2 can even act as agonists, triggering reverse signaling by binding to transmembrane tumor necrosis factor. While effective, prolonged use of tumor necrosis factor inhibitors may cause significant side effects due to the widespread expression and pleiotropic functions of tumor necrosis factor receptors. A more thorough understanding of the mechanisms underlying the action of tumor necrosis factor inhibitors is required to develop a more effective and safer treatment for systemic autoinflammatory diseases. This article reviews current studies on the role of the innate immune system in systemic autoinflammatory disease pathogenesis, the impact of anti-tumor necrosis factor therapy on innate immune cells, and perspectives on developing improved agents targeting tumor necrosis factor or its receptors.

Design principles of cell-state-specific enhancers in hematopoiesis

During cellular differentiation, enhancers transform overlapping gradients of transcription factors (TFs) to highly specific gene expression patterns. However, the vast complexity of regulatory DNA impedes the identification of the underlying cis-regulatory rules. Here, we characterized 64,400 fully synthetic DNA sequences to bottom-up dissect design principles of cell-state-specific enhancers in the context of the differentiation of blood stem cells to seven myeloid lineages. Focusing on binding sites for 38 TFs and their pairwise interactions, we found that identical sites displayed both repressive and activating function as a consequence of cell state, site combinatorics, or simply predicted occupancy of a TF on an enhancer. Surprisingly, combinations of activating sites frequently neutralized one another or gained repressive function. These negative synergies convert quantitative imbalances in TF expression into binary activity patterns. We exploit this principle to automatically create enhancers with specificity to user-defined combinations of hematopoietic progenitor cell states from scratch.

Integrating Dynamical Systems Modeling with Spatiotemporal scRNA-Seq Data Analysis

Understanding the dynamic nature of biological systems is fundamental to deciphering cellular behavior, developmental processes, and disease progression. Single-cell RNA sequencing (scRNA-seq) has provided static snapshots of gene expression, offering valuable insights into cellular states at a single time point. Recent advancements in temporally resolved scRNA-seq, spatial transcriptomics (ST), and time-series spatial transcriptomics (temporal-ST) have further revolutionized our ability to study the spatiotemporal dynamics of individual cells. These technologies, when combined with computational frameworks such as Markov chains, stochastic differential equations (SDEs), and generative models like optimal transport and Schrödinger bridges, enable the reconstruction of dynamic cellular trajectories and cell fate decisions. This review discusses how these dynamical system approaches offer new opportunities to model and infer cellular dynamics from a systematic perspective.

Pre-existing stem cell heterogeneity dictates clonal responses to the acquisition of leukemic driver mutations

Cancer cells display wide phenotypic variation even across patients with the same mutations. Differences in the cell of origin provide a potential explanation, but traditional assays lack the resolution to distinguish clonally heterogeneous subsets of stem and progenitor cells. To address this challenge, we developed simultaneous tracking of recombinase activation and clonal kinetics (STRACK), a method to trace clonal dynamics and gene expression before and after the acquisition of cancer mutations. Using mouse models, we studied two leukemic mutations, Dnmt3a-R878H and Npm1c, and found that their effect was highly variable across different stem cell states. Specifically, a subset of differentiation-primed stem cells, which normally becomes outcompeted with time, expands with both mutations. Intriguingly, Npm1c mutations reversed the intrinsic bias of the clone of origin, with differentiation-primed stem cells giving rise to more primitive malignant states. Thus, we highlight the relevance of single-cell lineage tracing to unravel early events in cancer evolution and posit that different cellular histories carry distinct cancer phenotypic potential.

Cell Lineage Affiliation During Hematopoiesis

By the mid-1960s, hematopoietic stem cells (HSCs) were well described. They generate perhaps the most complex array of functionally mature cells in an adult organism. HSCs and their descendants have been studied extensively, and findings have provided principles that have been applied to the development of many cell systems. However, there are uncertainties about the process of HSC development. They center around when and how HSCs become affiliated with a single-cell lineage. A longstanding view is that this occurs late in development and stepwise via a series of committed oligopotent progenitor cells, which eventually give rise to unipotent progenitors. A very different view is that lineage affiliation can occur as early as within HSCs, and the development of these cells to a mature end cell is then a continuous process. A key consideration is the extent to which lineage-affiliated HSCs self-renew to make a major contribution to hematopoiesis. This review examines the above aspects in relation to our understanding of hematopoiesis.

Central Nervous System Macrophages in Health and Disease

The central nervous system (CNS) has a unique set of macrophages that seed the tissue early during embryonic development. Microglia reside in the parenchyma, and border-associated macrophages are present in border regions, including the meninges, perivascular spaces, and choroid plexus. CNS-resident macrophages support brain homeostasis during development and steady state. In the diseased brain, however, the immune landscape is altered, with phenotypic and transcriptional changes in resident macrophages and the invasion of blood-borne monocytes, which differentiate into monocyte-derived macrophages upon entering the CNS. In this review, we focus on the fate and function of the macrophage compartment in health, neurodegenerative conditions such as amyloidosis, and neuroinflammation as observed in multiple sclerosis and infection. We discuss our current understanding that monocyte-derived macrophages contribute to neuropathology whereas native macrophages play a neuroprotective role in disease.

Limitations and optimizations of cellular lineages tracking

Tracking cellular lineages using genetic barcodes provides insights across biology and has become an important tool. However, barcoding strategies remain ad hoc. We show that elevating barcode insertion probability and thus increasing the average number of barcodes within the cells, adds to the number of traceable lineages but may decrease the accuracy of lineages inference due to reading errors. We establish the trade-off between accuracy in tracing lineages and the total number of traceable lineages, and find optimal experimental parameters under limited resources concerning the populations size of tracked cells and barcode pool complexity.

Genetically-Encoded Fluorescence Barcodes Allow for Single-Cell Analysis via Spectral Flow Cytometry

Genetically-encoded, single-cell barcodes are broadly useful for experimental tasks such as lineage tracing or genetic screens. For such applications, a barcode library would ideally have high diversity (many unique barcodes), non-destructive identification (repeated measurements in the same cells or population), and fast, inexpensive readout (many cells and conditions). Current nucleic acid barcoding methods generate high diversity but require destructive and slow/expensive readout, and current fluorescence barcoding methods are non-destructive, fast, and inexpensive to readout but lack high diversity. We recently proposed theory for how fluorescent protein combinations may generate a high-diversity barcode library with non-destructive, fast and inexpensive identification. Here, we present an initial experimental proof-of-concept by generating a library of ~150 barcodes from two-way combinations of 18 fluorescent proteins, 61 of which are tested experimentally. We use a pooled cloning strategy to generate a barcode library that is validated to contain every possible combination of the 18 fluorescent proteins. Experimental results using single mammalian cells and spectral flow cytometry demonstrate excellent classification performance of individual fluorescent proteins, with the exception of mTFP1, and of most evaluated barcodes, with many true positive rates >99%. The library is compatible with genetic screening for hundreds of genes (or gene pairs) and lineage tracing hundreds of clones. This work lays a foundation for greater diversity libraries (potentially ~105 and more) generated from hundreds of spectrally-resolvable tandem fluorescent protein probes.

Cell Function Graphics: TOGGLE delineates fate and function within individual cell types via single-cell transcriptomics

Functional RNA plays a crucial role in regulating cellular processes throughout the life cycle of a cell. Identifying functional changes at each stage, from inception to development to maturation, functional execution, and eventual death or pathological transformation, often requires systematic comparisons of functional expression across cell populations. However, because cells of the same type often exhibit similar gene expression patterns regardless of function or fate, it is challenging to distinguish the stages of cellular fate or functional states within the same cell type, which also limits our understanding of cellular memory. Cells of the same type that share structural and gene expression similarities but originate from different regions and perform slightly distinct functions often retain unique epigenetic memory signatures. Although RNA serves as a key executor of fundamental cellular functions, its high expression similarity among cells of the same type limits its ability to distinguish functional heterogeneity. To overcome this challenge, we developed TOGGLE, utilizing higher-resolution analytical methods to uncover functional diversity at the cellular level. Then we based on TOGGLE developed an innovative Graph Diffusion Functional Map, which can significantly reduce noise, thereby more clearly displaying the functional grouping of RNA and enabling the capture of more subtle functional differences in high-dimensional data. Ultimately, this method effectively removes the influence of baseline functions from classification criteria and identifies key trajectories of cell fate determination.

Clonal memory of colitis accumulates and promotes tumor growth

Chronic inflammation is a well-established risk factor for cancer, but the underlying molecular mechanisms remain unclear. Using a mouse model of colitis, we demonstrate that colonic stem cells retain an epigenetic memory of inflammation following disease resolution, characterized by a cumulative gain of activator protein 1 (AP-1) transcription factor activity. Further, we develop SHARE-TRACE, a method that enables simultaneous profiling of gene expression, chromatin accessibility and clonal history in single cells, enabling high resolution tracking of epigenomic memory. This reveals that inflammatory memory is propagated cell-intrinsically and inherited through stem cell lineages, with certain clones demonstrating dramatically stronger memory than others. Finally, we show that colitis primes stem cells for amplified expression of regenerative gene programs following oncogenic mutation that accelerate tumor growth. This includes a subpopulation of tumors that have exceptionally high AP-1 activity and the additional upregulation of pro-oncogenic programs. Together, our findings provide a mechanistic link between chronic inflammation and malignancy, revealing how long-lived epigenetic alterations in regenerative tissues may contribute to disease susceptibility and suggesting potential therapeutic strategies to mitigate cancer risk in patients with chronic inflammatory conditions.

Decoding the ontogeny of myeloid lineage diversity by cross-species and developmental analyses of hematopoietic progenitor atlases

Myeloid cells play vital roles in homeostasis and immune responses in vertebrates, but the developmental pathway underlying their lineage diversity remains elusive. Here, we construct a single-cell transcriptional map of myeloid progenitors from mouse bone marrow and conduct cross-species and developmental analyses across human, monkey, mouse, and zebrafish. We uncover a conserved specification program separating the eosinophil-basophil-mast cell (EBM) lineage and neutrophil-monocyte (NM) lineage, reclassifying myeloid cells beyond the conventional granulocytic and monocytic framework. By generating Ikzf2-EGFP reporter mice, we identify IKZF2 as a priming marker for EBM lineage specification. Ikzf2-EGFP+ and Ikzf2-EGFP- granulocyte-monocyte progenitors (GMPs) exhibit distinct potential to generate EBM and NM lineages, and Ikzf2-EGFP expression robustly distinguishes their progenies. Additionally, we demonstrate that lineage specification emerges early during myelopoiesis. These findings provide a redefined perspective on myeloid lineage ontogeny, highlighting the conservation of lineage specification and offering insights into the understanding and therapeutic development of myelopoiesis.

DARLIN mouse for in vivo lineage tracing at high efficiency and clonal diversity

Lineage tracing is a powerful tool to study cell history and cell dynamics during tissue development and homeostasis. An increasingly popular approach for lineage tracing is to generate high-frequent mutations at given genomic loci, which can serve as genetic barcodes to label different cell lineages. However, current lineage tracing mouse models suffer from low barcode diversity and limited single-cell lineage coverage. We recently developed the DARLIN mouse model by incorporating three barcoding arrays within defined genomic loci and combining Cas9 and terminal deoxynucleotidyl transferase (TdT) to improve editing diversity in each barcode array. We estimated that DARLIN generates 1018 distinct lineage barcodes in theory, and enables the recovery of lineage barcodes in over 70% of cells in single-cell assays. In addition, DARLIN can be induced with doxycycline to generate stable lineage barcodes across different tissues at a defined stage. Here we provide a step-by-step protocol on applying the DARLIN system for in vivo lineage tracing, including barcode induction, estimation of induction efficiency, barcode analysis with bulk and single-cell sequencing, and computational analysis. The execution time of this protocol is ~1 week for experimental data collection and ~1 d for running the computational analysis pipeline. To execute this protocol, one should be familiar with sequencing library generation and Linux operation. DARLIN opens the door to study the lineage relationships and the underlying molecular regulations across various tissues at physiological context.

Natural Killer Cell-Mediated Cytotoxicity Shapes the Clonal Evolution of B-cell Leukemia

The term cancer immunoediting describes the dual role by which the immune system can suppress and promote tumor growth and is divided into three phases: elimination, equilibrium, and escape. The role of NK cells has mainly been attributed to the elimination phase. Here, we show that NK cells play a role in all three phases of cancer immunoediting. Extended co-culturing of DNA-barcoded mouse BCR/ABLp185+ B-cell acute lymphoblastic leukemia (B-ALL) cells with NK cells allowed for a quantitative measure of NK cell-mediated immunoediting. Although most tumor cell clones were efficiently eliminated by NK cells, a certain fraction of tumor cells harbored an intrinsic primary resistance. Furthermore, DNA barcoding revealed tumor cell clones with secondary resistance, which stochastically acquired resistance to NK cells. NK cell-mediated cytotoxicity put a selective pressure on B-ALL cells, which led to an outgrowth of primary and secondary resistant tumor cell clones, which were characterized by an IFNγ signature. Besides well-known regulators of immune evasion, our analysis of NK cell-resistant tumor cells revealed the upregulation of genes, including lymphocyte antigen 6 complex, locus A (Ly6a), which we found to promote leukemic cell resistance to NK cells. Translation of our findings to the human system showed that high expression of LY6E on tumor cells impaired their physical interaction with NK cells and led to worse prognosis in patients with leukemia. Our results demonstrate that tumor cells are actively edited by NK cells during the equilibrium phase and use different avenues to escape NK cell-mediated eradication.

Single-cell lineage tracing techniques in hematology: unraveling the cellular narrative

Lineage tracing is a valuable technique that has greatly facilitated the exploration of cell origins and behavior. With the continuous development of single-cell sequencing technology, lineage tracing technology based on the single-cell level has become an important method to study biological development. Single-cell Lineage tracing technology plays an important role in the hematological system. It can help to answer many important questions, such as the heterogeneity of hematopoietic stem cell function and structure, and the heterogeneity of malignant tumor cells in the hematological system. Many studies have been conducted to explore the field of hematology by applying this technology. This review focuses on the superiority of the emerging single-cell lineage tracing technologies of Integration barcodes, CRISPR barcoding, and base editors, and summarizes their applications in the hematology system. These studies have suggested the vast potential in unraveling complex cellular behaviors and lineage dynamics in both normal and pathological contexts.

High-resolution, noninvasive single-cell lineage tracing in mice and humans based on DNA methylation epimutations

In vivo lineage tracing holds great potential to reveal fundamental principles of tissue development and homeostasis. However, current lineage tracing in humans relies on extremely rare somatic mutations, which has limited temporal resolution and lineage accuracy. Here, we developed a generic lineage-tracing tool based on frequent epimutations on DNA methylation, enabled by our computational method MethylTree. Using single-cell genome-wide DNA methylation datasets with known lineage and phenotypic labels, MethylTree reconstructed lineage histories at nearly 100% accuracy across different cell types, developmental stages, and species. We demonstrated the epimutation-based single-cell multi-omic lineage tracing in mouse and human blood, where MethylTree recapitulated the differentiation hierarchy in hematopoiesis. Applying MethylTree to human embryos, we revealed early fate commitment at the four-cell stage. In native mouse blood, we identified ~250 clones of hematopoietic stem cells. MethylTree opens the door for high-resolution, noninvasive and multi-omic lineage tracing in humans and beyond.

Decoding the blueprints of embryo development with single-cell and spatial omics

Embryonic development is a complex and intricately regulated process that encompasses precise control over cell differentiation, morphogenesis, and the underlying gene expression changes. Recent years have witnessed a remarkable acceleration in the development of single-cell and spatial omic technologies, enabling high-throughput profiling of transcriptomic and other multi-omic information at the individual cell level. These innovations offer fresh and multifaceted perspectives for investigating the intricate cellular and molecular mechanisms that govern embryonic development. In this review, we provide an in-depth exploration of the latest technical advancements in single-cell and spatial multi-omic methodologies and compile a systematic catalog of their applications in the field of embryonic development. We deconstruct the research strategies employed by recent studies that leverage single-cell sequencing techniques and underscore the unique advantages of spatial transcriptomics. Furthermore, we delve into both the current applications, data analysis algorithms and the untapped potential of these technologies in advancing our understanding of embryonic development. With the continuous evolution of multi-omic technologies, we anticipate their widespread adoption and profound contributions to unraveling the intricate molecular foundations underpinning embryo development in the foreseeable future.

Decoding heterogeneous single-cell perturbation responses

Understanding how cells respond differently to perturbation is crucial in cell biology, but existing methods often fail to accurately quantify and interpret heterogeneous single-cell responses. Here we introduce the perturbation-response score (PS), a method to quantify diverse perturbation responses at a single-cell level. Applied to single-cell perturbation datasets such as Perturb-seq, PS outperforms existing methods in quantifying partial gene perturbations. PS further enables single-cell dosage analysis without needing to titrate perturbations, and identifies 'buffered' and 'sensitive' response patterns of essential genes, depending on whether their moderate perturbations lead to strong downstream effects. PS reveals differential cellular responses on perturbing key genes in contexts such as T cell stimulation, latent HIV-1 expression and pancreatic differentiation. Notably, we identified a previously unknown role for the coiled-coil domain containing 6 (CCDC6) in regulating liver and pancreatic cell fate decisions. PS provides a powerful method for dose-to-function analysis, offering deeper insights from single-cell perturbation data.

The lives of cells, recorded

A paradigm for biology is emerging in which cells can be genetically programmed to write their histories into their own genomes. These records can subsequently be read, and the cellular histories reconstructed, which for each cell could include a record of its lineage relationships, extrinsic influences, internal states and physical locations, over time. DNA recording has the potential to transform the way that we study developmental and disease processes. Recent advances in genome engineering are driving the development of systems for DNA recording, and meanwhile single-cell and spatial omics technologies increasingly enable the recovery of the recorded information. Combined with advances in computational and phylogenetic inference algorithms, the DNA recording paradigm is beginning to bear fruit. In this Perspective, we explore the rationale and technical basis of DNA recording, what aspects of cellular biology might be recorded and how, and the types of discovery that we anticipate this paradigm will enable.

Uncovering two neutrophil-committed progenitors that immediately precede promyelocytes during human neutropoiesis

Technological advances have greatly improved our knowledge of myelopoiesis, for example, with the discovery of granulocyte‒monocyte‒dendritic cell (DC) progenitors (GMDPs), monocyte‒DC progenitors (MDPs), common DC progenitors (CDPs) and common monocyte progenitors (cMoPs) on the basis of flow cytometry approaches. Concomitantly, some progress has been made in characterizing the very early phases of human neutropoiesis with the description of novel CD66b+ progenitors, including eNePs, PMs w/o eNePs, ProNeus, and PreNeus. More recently, we identified four SSCloLin-CD66b-CD45dimCD34+/CD34dim/-CD64dimCD115- cells as the earliest precursors specifically committed to the neutrophil lineage present in human bone marrow (BM), which we called neutrophil-committed progenitors (NCPs, from NCP1s to NCP4s). In this study, we report the isolation and characterization of two new SSChiCD66b-CD64dimCD115-NCPs that, by phenotypic, transcriptomic, maturation and immunohistochemistry properties, as well as by flow cytometric side-scattered light (SSC), stand after NCP4s but precede promyelocytes during the neutropoiesis cascade. Similar to SSCloCD45RA+NCP2s/NCP3s and SSCloCD45RA-NCP1s/NCP4s, these cells exhibit phenotypic differences in CD45RA expression levels and, therefore, were named SSChiCD45RA+NCP5s and SSChiCD45RA-NCP6s. Moreover, NCP5s were more immature than NCP6s, as determined by cell differentiation and proliferative potential, as well as by transcriptomic and phenotypical features. Finally, by examining whether NCPs and all other CD66b+ neutrophil precursors are altered in representative hematological malignancies, we found that, in patients with chronic-phase chronic myeloid leukemia (CP-CML), but not with systemic mastocytosis (SM), there is an increased frequency of BM NCP4s, NCP6s, and all downstream CD45RA-negative neutrophil progenitors, suggesting their expansion in CML pathogenesis. Taken together, our data advance our knowledge of human neutropoiesis.

The landscape of cell lineage tracing

Cell fate changes play a crucial role in the processes of natural development, disease progression, and the efficacy of therapeutic interventions. The definition of the various types of cell fate changes, including cell expansion, differentiation, transdifferentiation, dedifferentiation, reprogramming, and state transitions, represents a complex and evolving field of research known as cell lineage tracing. This review will systematically introduce the research history and progress in this field, which can be broadly divided into two parts: prospective tracing and retrospective tracing. The initial section encompasses an array of methodologies pertaining to isotope labeling, transient fluorescent tracers, non-fluorescent transient tracers, non-fluorescent genetic markers, fluorescent protein, genetic marker delivery, genetic recombination, exogenous DNA barcodes, CRISPR-Cas9 mediated DNA barcodes, and base editor-mediated DNA barcodes. The second part of the review covers genetic mosaicism, genomic DNA alteration, TCR/BCR, DNA methylation, and mitochondrial DNA mutation. In the final section, we will address the principal challenges and prospective avenues of enquiry in the field of cell lineage tracing, with a particular focus on the sequencing techniques and mathematical models pertinent to single-cell genetic lineage tracing, and the value of pursuing a more comprehensive investigation at both the spatial and temporal levels in the study of cell lineage tracing.

Esr1-Dependent Signaling and Transcriptional Maturation in the Medial Preoptic Area of the Hypothalamus Shapes the Development of Mating Behavior during Adolescence

Mating and other behaviors emerge during adolescence through the coordinated actions of steroid hormone signaling throughout the nervous system and periphery. In this study, we investigated the transcriptional dynamics of the medial preoptic area (MPOA), a critical region for reproductive behavior, using single-cell RNA sequencing (scRNAseq) and in situ hybridization techniques in male and female mice throughout adolescence development. Our findings reveal that estrogen receptor 1 (Esr1) plays a pivotal role in the transcriptional maturation of GABAergic neurons within the MPOA during adolescence. Deletion of the estrogen receptor gene, Esr1, in GABAergic neurons (Vgat+) disrupted the developmental progression of mating behaviors in both sexes, while its deletion in glutamatergic neurons (Vglut2+) had no observable effect. In males and females, these neurons displayed distinct transcriptional trajectories, with hormone-dependent gene expression patterns emerging throughout adolescence and regulated by Esr1. Esr1 deletion in MPOA GABAergic neurons, prior to adolescence, arrested adolescent transcriptional progression of these cells and uncovered sex-specific gene-regulatory networks associated with Esr1 signaling. Our results underscore the critical role of Esr1 in orchestrating sex-specific transcriptional dynamics during adolescence, revealing gene regulatory networks implicated in the development of hypothalamic controlled reproductive behaviors.

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.

Clonal memory of colitis accumulates and promotes tumor growth

Chronic inflammation is a well-established risk factor for cancer, but the underlying molecular mechanisms remain unclear. Using a mouse model of colitis, we demonstrate that colonic stem cells retain an epigenetic memory of inflammation following disease resolution, characterized by a cumulative gain of activator protein 1 (AP-1) transcription factor activity. Further, we develop SHARE-TRACE, a method that enables simultaneous profiling of gene expression, chromatin accessibility and clonal history in single cells, enabling high resolution tracking of epigenomic memory. This reveals that inflammatory memory is propagated cell-intrinsically and inherited through stem cell lineages, with certain clones demonstrating dramatically stronger memory than others. Finally, we show that colitis primes stem cells for amplified expression of regenerative gene programs following oncogenic mutation that accelerate tumor growth. This includes a subpopulation of tumors that have exceptionally high AP-1 activity and the additional upregulation of pro-oncogenic programs. Together, our findings provide a mechanistic link between chronic inflammation and malignancy, revealing how long-lived epigenetic alterations in regenerative tissues may contribute to disease susceptibility and suggesting potential therapeutic strategies to mitigate cancer risk in patients with chronic inflammatory conditions.

Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution

During early mammalian development, the endoderm germ layer forms the foundation of the respiratory and digestive systems through complex patterning. This intricate process, guided by a series of cell fate decisions, remains only partially understood. Our study introduces innovative genetic tracing codes for 14 distinct endodermal regions using novel mouse strains. By integrating high-throughput and high-precision single-cell RNA sequencing with sophisticated imaging, we detailed the spatiotemporal and genetic lineage differentiation of the endoderm at single-cell resolution. We discovered an unexpected multipotentiality within early endodermal regions, allowing differentiation into various organ primordia. This research illuminates the complex and underestimated phenomenon where endodermal organs develop from multiple origins, prompting a reevaluation of traditional differentiation models. Our findings advance understanding in developmental biology and have significant implications for regenerative medicine and the development of advanced organoid models, providing insights into the intricate mechanisms that guide organogenesis.

Combining transcriptomic and metabolomic insights to guide the clinical application of adipose- and bone marrow-derived mesenchymal stem cells

Adipose-derived mesenchymal stem cells (ADSCs) and bone marrow-derived mesenchymal stem cells (BMSCs) have shown great potential in clinical applications. However, the similarities and differences between these two cell types have not been fully elucidated. Recent advances in transcriptomic and metabolomic research have provided valuable insight into the characteristics and functions of ADSCs and BMSCs. In this perspective article, we review the key findings from these studies, including cellular heterogeneity as well as differences in metabolic and secretory properties. We discuss how these insights can help guide the selection of the most suitable cell source for the clinic, and the optimization of preconditioning strategies prior to clinical deployment. Furthermore, we analyze the current landscape of products and clinical trials involving ADSCs and BMSCs, highlighting their therapeutic potential. We propose that the integration of multi-omics datasets will be crucial for establishing a comprehensive understanding of ADSC and BMSC identity and potency, and the provision of quality-assured stem cell-derived products for the clinic.

Computing hematopoiesis plasticity in response to genetic mutations and environmental stimulations

Cell plasticity (CP), describing a dynamic cell state, plays a crucial role in maintaining homeostasis during organ morphogenesis, regeneration, and trauma-to-repair biological process. Single-cell-omics datasets provide an unprecedented resource to empower CP analysis. Hematopoiesis offers fertile opportunities to develop quantitative methods for understanding CP. In this study, we generated high-quality lineage-negative single-cell RNA-sequencing datasets under various conditions and introduced a working pipeline named scPlasticity to interrogate naïve and disturbed plasticity of hematopoietic stem and progenitor cells with mutational or environmental challenges. Using embedding methods UMAP or FA, a continuum of hematopoietic development is visually observed in wild type where the pipeline confirms a low proportion of hybrid cells ( P hc , with bias range: 0.4∼0.6) on a transition trajectory. Upon Tet2 mutation, a driver of leukemia, or treatment of DSS, an inducer of colitis, P hc is increased and plasticity of hematopoietic stem and progenitor cells was enhanced. We prioritized several transcription factors and signaling pathways, which are responsible for P hc alterations. In silico perturbation suggests knocking out EGR regulons or pathways of IL-1R1 and β-adrenoreceptor partially reverses P hc promoted by Tet2 mutation and inflammation.

Hematopoietic stem cell metabolism within the bone marrow niche - insights and opportunities

Hematopoiesis unfolds within the bone marrow niche where hematopoietic stem cells (HSCs) play a central role in continually replenishing blood cells. The hypoxic bone marrow environment imparts peculiar metabolic characteristics to hematopoietic processes. Here, we discuss the internal metabolism of HSCs and describe external influences exerted on HSC metabolism by the bone marrow niche environment. Importantly, we suggest that the metabolic environment and metabolic cues are intertwined with HSC cell fate, and are crucial for hematopoietic processes. Metabolic dysregulation within the bone marrow niche during acute stress, inflammation, and chronic inflammatory conditions can lead to reduced HSC vitality. Additionally, we raise questions regarding metabolic stresses imposed on HSCs during implementation of stem cell protocols such as allo-SCT and gene therapy, and the potential ramifications. Enhancing our comprehension of metabolic influences on HSCs will expand our understanding of pathophysiology in the bone marrow and improve the application of stem cell therapies.

Dual-nuclease single-cell lineage tracing by Cas9 and Cas12a

Single-cell lineage tracing based on CRISPR-Cas9 gene editing enables the simultaneous linkage of cell states and lineage history at a high resolution. Despite its immense potential in resolving the cell fate determination and genealogy within an organism, existing implementations of this technology suffer from limitations in recording capabilities and considerable barcode dropout. Here, we introduce DuTracer, a versatile tool that utilizes two orthogonal gene editing systems to record cell lineage history at single-cell resolution in an inducible manner. DuTracer shows the ability to enhance lineage recording with minimized target dropouts and potentially deeper tree depths. Applying DuTracer in mouse embryoid bodies and neuromesodermal organoids illustrates the lineage relationship of different cell types and proposes potential lineage-biased molecular drivers, showcased by identifying transcription factor Foxb1 as a modulator in the cell fate determination of neuromesodermal progenitors. Collectively, DuTracer facilitates the precise and regulatory interrogation of cellular lineages of complex biological processes.

Integrating representation learning, permutation, and optimization to detect lineage-related gene expression patterns

Recent barcoding technologies allow reconstructing lineage trees while capturing paired single-cell RNA-sequencing (scRNA-seq) data. Such datasets provide opportunities to compare gene expression memory maintenance through lineage branching and pinpoint critical genes in these processes. Here we develop Permutation, Optimization, and Representation learning based single Cell gene Expression and Lineage ANalysis (PORCELAN) to identify lineage-informative genes or subtrees where lineage and expression are tightly coupled. We validate our method using synthetic data and apply it to recent paired lineage and scRNA-seq data of lung cancer in a mouse model and embryogenesis of mouse and C. elegans. Our method pinpoints subtrees giving rise to metastases or new cell states, and genes identified as most informative about lineage overlap with known pathways involved in lung cancer progression. Furthermore, our method highlights differences in how gene expression memory is maintained through divisions in cancer and embryogenesis, thereby providing a tool for studying cell state memory through divisions across biological systems.

Transformer-based modeling of Clonal Selection and Expression Dynamics reveals resistance mechanisms in breast cancer

Understanding transcriptional heterogeneity in cancer cells and its implication for treatment response is critical to identify how resistance occurs and may be targeted. Such heterogeneity can be captured by in vitro studies through clonal barcoding methods. We present TraCSED (Transformer-based modeling of Clonal Selection and Expression Dynamics), a dynamic deep learning approach for modeling clonal selection. Using single-cell gene expression and the fitness of barcoded clones, TraCSED identifies interpretable gene programs and the time points at which they are associated with clonal selection. When applied to cells treated with either giredestrant, a selective estrogen receptor (ER) antagonist and degrader, or palbociclib, a CDK4/6 inhibitor, pathways dynamically associated with resistance are revealed. For example, ER activity is associated with positive selection around day four under palbociclib treatment and this adaptive response can be suppressed by combining the drugs. Yet, in the combination treatment, one clone still emerged. Clustering based on partial least squares regression found that high baseline expression of both SNHG25 and SNCG genes was the primary marker of positive selection to co-treatment and thus potentially associated with innate resistance - an aspect that traditional differential analysis methods missed. In conclusion, TraCSED enables associating features with phenotypes in a time-dependent manner from scRNA-seq data.

scLTdb: a comprehensive single-cell lineage tracing database

Single-cell lineage tracing (scLT) is a powerful technique that integrates cellular barcoding with single-cell sequencing technologies. This new approach enables the simultaneous measurement of cell fate and molecular profiles at single-cell resolution, uncovering the gene regulatory program of cell fate determination. However, a comprehensive scLT database is not yet available. Here, we present the single-cell lineage tracing database (scLTdb, https://scltdb.com) containing 109 datasets that are manually curated and analyzed through a standard pipeline. The scLTdb provides interactive analysis modules for visualizing and re-analyzing scLT datasets, especially the comprehensive cell fate analysis and lineage relationship analysis. Importantly, scLTdb also allows users to identify fate-related gene signatures. In conclusion, scLTdb provides an interactive interface of scLT data exploration and analysis, and will facilitate the understanding of cell fate decision and lineage commitment in development and diseases.

Deciphering the effect of UM171 on human hematopoietic progenitor cell fate through clonal analysis

Ex vivo expansion of hematopoietic stem cells (HSC) requires the maintenance of a stemness state while cells are proliferating. This can be achieved via exposure to UM171 which leads to the degradation of chromatin modifiers and prevents the loss of key epigenetic marks. However, the chromatin landscape varies across populations within the hematopoietic system and the effect of UM171 on self-renewal and differentiation potential of different hematopoietic progenitor cells is less characterized. To address this, we use the CellTag barcoding approach to track the fate of individual stem and progenitor cells during in vitro expansion. We show that, in addition to its HSC self-renewing property, UM171 specifically modulates cell fate of a precursor common to erythroid, megakaryocytic, and mast cells in favor of self-renewal and a mast-bias differentiation trajectory. This differentiation bias can be driven by pro-inflammatory signaling pathways that are activated downstream of UM171 and results in an abundant mast cell population that can be transplanted as part of the graft to populate mice tissues in xenotransplantation studies.

Hematopoietic Stem Cell Fates and the Cellular Hierarchy of Mammalian Hematopoiesis: from Transplantation Models to New Insights from in Situ Analyses

Hematopoiesis is the process that generates the cells of the blood and immune system from hematopoietic stem and progenitor cells (HSPCs) and represents the system with the most rapid cell turnover in a mammalian organism. HSPC differentiation trajectories, their underlying molecular mechanisms, and their dysfunctions in hematologic disorders are the focal research questions of experimental hematology. While HSPC transplantations in murine models are the traditional tool in this research field, recent advances in genome editing and next generation sequencing resulted in the development of many fundamentally new approaches for the analyses of mammalian hematopoiesis in situ and at single cell resolution. The current review will cover many recent developments in this field in murine models, from the bulk lineage tracing studies of HSPC differentiation to the barcoding of individual HSPCs with Cre-recombinase, Sleeping Beauty transposase, or CRISPR/Cas9 tools, to map hematopoietic cell fates, together with their transcriptional and epigenetic states. We also address studies of the clonal dynamics of human hematopoiesis, from the tracing of HSPC clonal behaviours based on viral integration sites in gene therapy patients to the recent analyses of unperturbed human hematopoiesis based on naturally accrued mutations in either nuclear or mitochondrial genomes. Such studies are revolutionizing our understanding of HSPC biology and hematopoiesis both under homeostatic conditions and in the response to various forms of physiological stress, reveal the mechanisms responsible for the decline of hematopoietic function with age, and in the future may advance the understanding and management of the diverse disorders of hematopoiesis.

Recording Lineage History with Cellular Barcodes in the Mammary Epithelium and in Breast Cancer

Lineage tracing methods have extensively advanced our understanding of physiological cell behaviour in vivo and in situ and have vastly contributed to decipher the phylogeny and cellular hierarchies during normal and tumour development. In recent years, increasingly complex systems have been developed to track thousands of cells within a given tissue or even entire organisms. Cellular barcoding comprises all techniques designed to genetically label single cells with unique DNA sequences or with a combination of fluorescent proteins, in order to trace their history and lineage production in space and time. We distinguish these two types of cellular barcoding as genetic or optical barcodes. Furthermore, transcribed cellular barcodes can integrate the lineage information with single-cell profiling of each barcoded cell. This enables the potential identification of specific markers or signalling pathways defining distinct stem cell states during development, but also signals promoting tumour growth and metastasis or conferring therapy resistance.In this chapter, we describe recent advances in cellular barcoding technologies and outline experimental and computational challenges. We discuss the biological questions that can be addressed using single-cell dynamic lineage tracing, with a focus on the study of cellular hierarchies in the mammary epithelium and in breast cancer.

Predicting Alzheimer's disease subtypes and understanding their molecular characteristics in living patients with transcriptomic trajectory profiling

INTRODUCTION

Deciphering the diverse molecular mechanisms in living Alzheimer's disease (AD) patients is a big challenge but is pivotal for disease prognosis and precision medicine development.

METHODS

Utilizing an optimal transport approach, we conducted graph-based mapping of transcriptomic profiles to transfer AD subtype labels from ROSMAP monocyte samples to ADNI and ANMerge peripheral blood mononuclear cells. Subsequently, differential expression followed by comparative pathway and diffusion pseudotime analysis were applied to each cohort to infer the progression trajectories. Survival analysis with real follow-up time was used to obtain potential biomarkers for AD prognosis.

RESULTS

AD subtype labels were accurately transferred onto the blood samples of ADNI and ANMerge living patients. Pathways and associated genes in neutrophil degranulation-like immune process, immune acute phase response, and IL-6 signaling were significantly associated with AD progression.

DISCUSSION

The work enhanced our understanding of AD progression in different subtypes, offering insights into potential biomarkers and personalized interventions for improved patient care.

HIGHLIGHTS

We applied an innovative optimal transport-based approach to map transcriptomic data from different Alzheimer's disease (AD) cohort studies and transfer known AD subtype labels from ROSMAP monocyte samples to peripheral blood mononuclear cell (PBMC) samples within ADNI and ANMerge cohorts. Through comprehensive trajectory and comparative analysis, we investigated the molecular mechanisms underlying different disease progression trajectories in AD. We validated the accuracy of our AD subtype label transfer and identified prognostic genetic markers associated with disease progression, facilitating personalized treatment strategies. By identifying and predicting distinctive AD subtypes and their associated pathways, our study contributes to a deeper understanding of AD heterogeneity.

Reconstructing Progenitor State Hierarchy and Dynamics Using Lineage Barcoding Data

Measurements of cell phylogeny based on natural or induced mutations, known as lineage barcodes, in conjunction with molecular phenotype have become increasingly feasible for a large number of single cells. In this chapter, we delve into Quantitative Fate Mapping (QFM) and its computational pipeline, which enables the interrogation of the dynamics of progenitor cells and their fate restriction during development. The methods described here include inferring cell phylogeny with the Phylotime model, and reconstructing progenitor state hierarchy, commitment time, population size, and commitment bias with the ICE-FASE algorithm. Evaluation of adequate sampling based on progenitor state coverage statistics is emphasized for interpreting the QFM results. Overall, this chapter describes a general framework for characterizing the dynamics of cell fate changes using lineage barcoding data.

Spatial Transcriptomics: Integrating Morphology and Molecular Mechanisms of Kidney Diseases

The recent arrival of high-resolution spatial transcriptomics (ST) technologies is generating a veritable revolution in life sciences, enabling biomolecules to be measured in their native spatial context. By integrating morphology and molecular biology, ST technologies offer the potential of improving the understanding of tissue biology and disease and may also provide meaningful clinical insights. This review describes the main ST technologies currently available and the computational analysis for data interpretation and visualization, and illustrate their scientific and potential medical interest in the context of kidney disease. Finally, we discuss the perspectives and challenges of these booming new technologies.

Advancements in prospective single-cell lineage barcoding and their applications in research

Single-cell lineage tracing (scLT) has emerged as a powerful tool, providing unparalleled resolution to investigate cellular dynamics, fate determination, and the underlying molecular mechanisms. This review thoroughly examines the latest prospective lineage DNA barcode tracing technologies. It further highlights pivotal studies that leverage single-cell lentiviral integration barcoding technology to unravel the dynamic nature of cell lineages in both developmental biology and cancer research. Additionally, the review navigates through critical considerations for successful experimental design in lineage tracing and addresses challenges inherent in this field, including technical limitations, complexities in data analysis, and the imperative for standardization. It also outlines current gaps in knowledge and suggests future research directions, contributing to the ongoing advancement of scLT studies.

Tracking the gene expression programs and clonal relationships that underlie mast, myeloid, and T lineage specification from stem cells

T cells develop from hematopoietic progenitors in the thymus and protect against pathogens and cancer. However, the emergence of human T cell-competent blood progenitors and their subsequent specification to the T lineage have been challenging to capture in real time. Here, we leveraged a pluripotent stem cell differentiation system to understand the transcriptional dynamics and cell fate restriction events that underlie this critical developmental process. Time-resolved single-cell RNA sequencing revealed that downregulation of the multipotent hematopoietic program, upregulation of >90 lineage-associated transcription factors, and cell-cycle exit all occur within a highly coordinated developmental window. Gene-regulatory network inference uncovered a role for YBX1 in T lineage specification. We mapped the differentiation cell fate hierarchy using transcribed lineage barcoding and discovered that mast and myeloid potential bifurcate from each other early in hematopoiesis, upstream of T lineage restriction. Our systems-level analyses provide a quantitative, time-resolved model of human T cell fate specification. A record of this paper's transparent peer review process is included in the supplemental information.

Smarcd1 subunit of SWI/SNF chromatin-remodeling complexes collaborates with E2a to promote murine lymphoid specification

Lymphocyte development from murine hematopoietic stem cells (HSCs) entails a loss of self-renewal capacity and a progressive restriction of developmental potential. Previous research from our laboratory suggests that specialized assemblies of ATP-dependent SWI/SNF chromatin-remodeling complexes play lineage-specific roles during murine hematopoiesis. Here, we demonstrate that the Smarcd1 subunit is essential for specification of lymphoid cell fate from multipotent progenitors. Acute deletion of Smarcd1 in murine adult hematopoiesis leads to lymphopenia, characterized by a near-complete absence of early lymphoid progenitors and mature B and T cells, while the myeloid and erythroid lineages remain unaffected. Mechanistically, we demonstrate that Smarcd1 is essential for the coordinated activation of a lymphoid gene signature in murine multipotent progenitors. This is achieved by interacting with the E2a transcription factor at proximal promoters and by regulating the activity of distal enhancers. Globally, these findings identify Smarcd1 as an essential chromatin remodeler that governs lymphoid cell fate.