Cellular barcoding: lineage tracing, screening and beyond

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.

Immunotyping of thyroid cancer for clinical outcomes and implications

BACKGROUND

Tumor immune microenvironment (TIME) plays a crucial role in cancer development. However, the prognostic significance of immune-related genes (IRGs) in thyroid cancer (THCA) is unclear.

METHODS

The Cancer Genome Atlas (TCGA)-THCA dataset was downloaded. The CIBERSORT algorithm was used to determine immune cell infiltration and a Weighted Gene Co-expression Network Analysis (WGCNA) was executed to obtain immune cell-related genes. Univariate Cox analysis was performed to screen prognostic genes and THCA samples were categorized into different immune cell-related clusters. The correlations between clusters and THCA prognosis and clinical characteristics were explored. Differentially expressed genes (DEGs) between THCA and controls from TCGA-THCA were identified. Macrophage and lymphocyte abundances, IFN-γ, wound healing, and TGF-beta levels were determined using the single set gene set enrichment analysis (GSEA), and THCA samples were categorized into different immune-related clusters, and corresponding genes were obtained from WGCNA. DEGs, IRGs, and immune-related clusters genes were subjected to overlap analysis to obtain differentially expressed IRGs (DE-IRGs), and these were subjected to least absolute shrinkage and selection operator (LASSO) and multivariate Cox analyses to identify prognosis-related genes. THCA samples were divided into high/low-risk groups based on the median risk score. Furthermore, the prognostic model's utility in predicting immunotherapy response was analyzed. The potential therapeutic drugs were obtained. The expression of the corresponding genes in 10 pairs of clinical specimens was evaluated and those of proteins were analyzed by immunofluorescence assay.

RESULTS

TCGA-THCA samples were categorized into two immune cell-related clusters based on 141 prognostic immune cell-related genes. Significant differences in survival and clinical characteristics such as T Stage between clusters. In total, 16,648 DEGs between THCA and control samples were extracted. THCA samples were categorized into two immune-related clusters and were found to affect the prognosis and TIME of THCA. By using LASSO and multivariate Cox analyses for 88 DE-IRGs, three prognostic IRGs, namely FLNC, IL18, and MMP17 were identified. The TIDE score of the low-risk group was significantly lower than that of the other one, indicating that these samples were more responsive to immunotherapy. The 50% inhibitory concentration (IC50) of camptothecin, methotrexate, rapamycin, and others were notably different between the risk groups.

CONCLUSION

Based on bioinformatics analysis, we constructed an immune-related prognosis model for THCA, which is expected to provide new ideas for studies related to the prognosis and treatment of THCA.

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.

Temporal and spatial omics technologies for 4D profiling

Cells have distinct molecular repertoires on their surfaces and unique intracellular biomolecular profiles that play pivotal roles in orchestrating a myriad of biological responses in the context of growth, development and disease. A persistent challenge in the deep exploration of these cues has been in our inability to effectively and precisely capture the temporal and spatial characteristics of living cells. In this Perspective, we delve into techniques for temporal and two- and three-dimensional spatial omics analyses and underscore how their harmonious fusion promises to unlock insights into the dynamics and diversity of individual cells within biological systems such as tissues and organoids. We then explore four-dimensional profiling, a nascent but promising frontier that adds a temporal (fourth-dimension) component to three-dimensional omics; highlight the advancements, challenges and gaps in the field; and discuss potential strategies for further technological development.

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.

Cutting-edge methodologies for tagging and tracing active neuronal coding in the brain

Decoding the neural substrates that underlie learning and behavior is a fundamental goal in neuroscience. Identifying "key players" at the molecular, cellular, and circuit levels has become possible with recent advancements in molecular technologies offering high spatiotemporal resolution. Immediate-early genes are effective markers of neural activity and plasticity, allowing for the identification of active cells involved in memory-based behavior. A calcium-dependent labeling system coupled with light or biochemical proximity labeling allows characterization of active cell ensembles and circuitry across broader brain regions within short time windows, particularly during transient behaviors. The integration of these systems expands the ability to address diverse research questions across behavioral paradigms. This review examines current molecular systems for activity-dependent labeling, highlighting their applications in identifying specific cell ensembles and circuits relevant to various scientific questions and further discuss their significance, along with future directions for the development of innovative methodologies.

Transcriptomic neuron types vary topographically in function and morphology

Neuronal phenotypic traits such as morphology, connectivity and function are dictated, to a large extent, by a specific combination of differentially expressed genes. Clusters of neurons in transcriptomic space correspond to distinct cell types and in some cases-for example, Caenorhabditis elegans neurons1 and retinal ganglion cells2-4-have been shown to share morphology and function. The zebrafish optic tectum is composed of a spatial array of neurons that transforms visual inputs into motor outputs. Although the visuotopic map is continuous, subregions of the tectum are functionally specialized5,6. Here, to uncover the cell-type architecture of the tectum, we transcriptionally profiled its neurons, revealing more than 60 cell types that are organized in distinct anatomical layers. We measured the visual responses of thousands of tectal neurons by two-photon calcium imaging and matched them with their transcriptional profiles. Furthermore, we characterized the morphologies of transcriptionally identified neurons using specific transgenic lines. Notably, we found that neurons that are transcriptionally similar can diverge in shape, connectivity and visual responses. Incorporating the spatial coordinates of neurons within the tectal volume revealed functionally and morphologically defined anatomical subclusters within individual transcriptomic clusters. Our findings demonstrate that extrinsic, position-dependent factors expand the phenotypic repertoire of genetically similar neurons.

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.

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.

Overcoming Resistance Mechanisms to Melanoma Immunotherapy

The advent of immune checkpoint inhibition has revolutionized treatment of advanced melanoma. While most patients derive survival benefit from established immunotherapies, notably monoclonal antibodies blocking cytotoxic T-lymphocyte antigen 4 and programmed cell death protein 1, a subset does not optimally respond due to the manifestation of innate or acquired resistance to these therapies. Combination regimens have proven efficacious relative to single-agent blockade, but also yield high-grade treatment toxicities that are often dose-limiting for patients. In this review, we discuss the significant strides made in the past half-decade toward expanding the melanoma immunotherapy treatment paradigm. These include newly approved therapies, adoption of neoadjuvant immunotherapy, and studies in the clinical trials pipeline targeting alternative immune checkpoints and key immunoregulatory molecules. We then review how developments in molecular and functional diagnostics have furthered our understanding of the tumor-intrinsic and -extrinsic mechanisms driving immunotherapy resistance, as well as highlight novel biomarkers for predicting treatment response. Throughout, we discuss potential approaches for targeting these resistance mechanisms in rational combination with established immunotherapies to improve outcomes for patients with melanoma.

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.

High-Complexity Barcoded Rabies Virus for Scalable Circuit Mapping Using Single-Cell and Single-Nucleus Sequencing

Single cell genomics has revolutionized our understanding of neuronal cell types. However, scalable technologies for probing single-cell connectivity are lacking, and we are just beginning to understand how molecularly defined cell types are organized into functional circuits. Here, we describe a protocol to generate high-complexity barcoded rabies virus (RV) for scalable circuit mapping from tens of thousands of individual starter cells in parallel. In addition, we introduce a strategy for targeting RV-encoded barcode transcripts to the nucleus so that they can be read out using single-nucleus RNA sequencing (snRNA-seq). We apply this tool in organotypic slice cultures of the developing human cerebral cortex, which reveals the emergence of cell type-specific circuit motifs in midgestation. By leveraging the power and throughput of single cell genomics for mapping synaptic connectivity, we chart a path forward for scalable circuit mapping of molecularly-defined cell types in healthy and disease states.

Droplet-based single-cell sequencing: Strategies and applications

Notable advancements in single-cell omics technologies have not only addressed longstanding challenges but also enabled unprecedented studies of cellular heterogeneity with unprecedented resolution and scale. These strides have led to groundbreaking insights into complex biological systems, paving the way for a more profound comprehension of human biology and diseases. The droplet microfluidic technology has become a crucial component in many single-cell sequencing workflows in terms of throughput, cost-effectiveness, and automation. Utilizing a microfluidic chip to encapsulate and profile individual cells within droplets has significantly improved single-cell research. Therefore, this review aims to comprehensively elaborate the droplet microfluidics-assisted omics methods from a single-cell perspective. The strategies for using droplet microfluidics in the realms of genomics, epigenomics, transcriptomics, and proteomics analyses are first introduced. On this basis, the focus then turns to the latest applications of this technology in different sequencing patterns, including mono- and multi-omics. Finally, the challenges and further perspectives of droplet-based single-cell sequencing in both foundational research and commercial applications are discussed.

Decoding senescence of aging single cells at the nexus of biomaterials, microfluidics, and spatial omics

Aging has profound effects on the body, most notably an increase in the prevalence of several diseases. An important aging hallmark is the presence of senescent cells that no longer multiply nor die off properly. Another characteristic is an altered immune system that fails to properly self-surveil. In this multi-player aging process, cellular senescence induces a change in the secretory phenotype, known as senescence-associated secretory phenotype (SASP), of many cells with the intention of recruiting immune cells to accelerate the clearance of these damaged senescent cells. However, the SASP phenotype results in inducing secondary senescence of nearby cells, resulting in those cells becoming senescent, and improper immune activation resulting in a state of chronic inflammation, called inflammaging, in many diseases. Senescence in immune cells, termed immunosenescence, results in further dysregulation of the immune system. An interdisciplinary approach is needed to physiologically assess aging changes of the immune system at the cellular and tissue level. Thus, the intersection of biomaterials, microfluidics, and spatial omics has great potential to collectively model aging and immunosenescence. Each of these approaches mimics unique aspects of the body undergoes as a part of aging. This perspective highlights the key aspects of how biomaterials provide non-cellular cues to cell aging, microfluidics recapitulate flow-induced and multi-cellular dynamics, and spatial omics analyses dissect the coordination of several biomarkers of senescence as a function of cell interactions in distinct tissue environments. An overview of how senescence and immune dysregulation play a role in organ aging, cancer, wound healing, Alzheimer's, and osteoporosis is included. To illuminate the societal impact of aging, an increasing trend in anti-senescence and anti-aging interventions, including pharmacological interventions, medical procedures, and lifestyle changes is discussed, including further context of senescence.

A spatial-temporal map of glutamatergic neurogenesis in the murine embryonic cerebellar nuclei uncovers a high degree of cellular heterogeneity

The nuclei are the main output structures of the cerebellum. Each and every cerebellar cortical computation reaches several areas of the brain by means of cerebellar nuclei processing and integration. Nevertheless, our knowledge of these structures is still limited compared to the cerebellar cortex. Here, we present a mouse genetic inducible fate-mapping study characterizing rhombic lip-derived glutamatergic neurons of the nuclei, the most conspicuous family of long-range cerebellar efferent neurons. Glutamatergic neurons mainly occupy dorsal and lateral territories of the lateral and interposed nuclei, as well as the entire medial nucleus. In mice, they are born starting from about embryonic day 9.5, with a peak between 10.5 and 12.5, and invade the nuclei with a lateral-to-medial progression. While some markers label a heterogeneous population of neurons sharing a common location (BRN2), others appear to be lineage specific (TBR1, LMX1a, and MEIS2). A comparative analysis of TBR1 and LMX1a distributions reveals an incomplete overlap in their expression domains, in keeping with the existence of separate efferent subpopulations. Finally, some tagged glutamatergic progenitors are not labeled by any of the markers used in this study, disclosing further complexity. Taken together, our results obtained in late embryonic nuclei shed light on the heterogeneity of the excitatory neuron pool, underlying the diversity in connectivity and functions of this largely unexplored cerebellar territory. Our findings contribute to laying the groundwork for a comprehensive functional analysis of nuclear neuron subpopulations.

Clonal analysis of fetal hematopoietic stem/progenitor cells reveals how post-transplantation capabilities are distributed

It has been proposed that adult hematopoiesis is sustained by multipotent progenitors (MPPs) specified during embryogenesis. Adult-like hematopoietic stem cell (HSC) and MPP immunophenotypes are present in the fetus, but knowledge of their functional capacity is incomplete. We found that fetal MPP populations were functionally similar to adult cells, albeit with some differences in lymphoid output. Clonal assessment revealed that lineage biases arose from differences in patterns of single-/bi-lineage differentiation. Long-term (LT)- and short-term (ST)-HSC populations were distinguished from MPPs according to capacity for clonal multilineage differentiation. We discovered that a large cohort of long-term repopulating units (LT-RUs) resides within the ST-HSC population; a significant portion of these were labeled using Flt3-cre. This finding has two implications: (1) use of the CD150+ LT-HSC immunophenotype alone will significantly underestimate the size and diversity of the LT-RU pool and (2) LT-RUs in the ST-HSC population have the attributes required to persist into adulthood.

Flexible parsing, interpretation, and editing of technical sequences with splitcode

MOTIVATION

Next-generation sequencing libraries are constructed with numerous synthetic constructs such as sequencing adapters, barcodes, and unique molecular identifiers. Such sequences can be essential for interpreting results of sequencing assays, and when they contain information pertinent to an experiment, they must be processed and analyzed.

RESULTS

We present a tool called splitcode, that enables flexible and efficient parsing, interpreting, and editing of sequencing reads. This versatile tool facilitates simple, reproducible preprocessing of reads from libraries constructed for a large array of single-cell and bulk sequencing assays.

AVAILABILITY AND IMPLEMENTATION

The splitcode program is available at http://github.com/pachterlab/splitcode.

Clonal tracking in cancer and metastasis

The eradication of many cancers has proven challenging due to the presence of functionally and genetically heterogeneous clones maintained by rare cancer stem cells (CSCs), which contribute to disease progression, treatment refractoriness, and late relapse. The characterization of functional CSC activity has necessitated the development of modern clonal tracking strategies. This review describes viral-based and CRISPR-Cas9-based cellular barcoding, lineage tracing, and imaging-based approaches. DNA-based cellular barcoding technology is emerging as a powerful and robust strategy that has been widely applied to in vitro and in vivo model systems, including patient-derived xenograft models. This review also highlights the potential of these methods for use in the clinical and drug discovery contexts and discusses the important insights gained from such approaches.

Single-cell lineage tracing approaches to track kidney cell development and maintenance

The kidney is a complex organ consisting of various cell types. Previous studies have aimed to elucidate the cellular relationships among these cell types in developing and mature kidneys using Cre-loxP-based lineage tracing. However, this methodology falls short of fully capturing the heterogeneous nature of the kidney, making it less than ideal for comprehensively tracing cellular progression during kidney development and maintenance. Recent technological advancements in single-cell genomics have revolutionized lineage tracing methods. Single-cell lineage tracing enables the simultaneous tracing of multiple cell types within complex tissues and their transcriptomic profiles, thereby allowing the reconstruction of their lineage tree with cell state information. Although single-cell lineage tracing has been successfully applied to investigate cellular hierarchies in various organs and tissues, its application in kidney research is currently lacking. This review comprehensively consolidates the single-cell lineage tracing methods, divided into 4 categories (clustered regularly interspaced short palindromic repeat [CRISPR]/CRISPR-associated protein 9 [Cas9]-based, transposon-based, Polylox-based, and native barcoding methods), and outlines their technical advantages and disadvantages. Furthermore, we propose potential future research topics in kidney research that could benefit from single-cell lineage tracing and suggest suitable technical strategies to apply to these topics.

Analysis of synthetic cellular barcodes in the genome and transcriptome with BARtab and bartools

Cellular barcoding is a lineage-tracing methodology that couples heritable synthetic barcodes to high-throughput sequencing, enabling the accurate tracing of cell lineages across a range of biological contexts. Recent studies have extended these methods by incorporating lineage information into single-cell or spatial transcriptomics readouts. Leveraging the rich biological information within these datasets requires dedicated computational tools for dataset pre-processing and analysis. Here, we present BARtab, a portable and scalable Nextflow pipeline, and bartools, an open-source R package, designed to provide an integrated end-to-end cellular barcoding analysis toolkit. BARtab and bartools contain methods to simplify the extraction, quality control, analysis, and visualization of lineage barcodes from population-level, single-cell, and spatial transcriptomics experiments. We showcase the utility of our integrated BARtab and bartools workflow via the analysis of exemplar bulk, single-cell, and spatial transcriptomics experiments containing cellular barcoding information.

Hallmarks of cancer stemness

Cancer stemness is recognized as a key component of tumor development. Previously coined "cancer stem cells" (CSCs) and believed to be a rare population with rigid hierarchical organization, there is good evidence to suggest that these cells exhibit a plastic cellular state influenced by dynamic CSC-niche interplay. This revelation underscores the need to reevaluate the hallmarks of cancer stemness. Herein, we summarize the techniques used to identify and characterize the state of these cells and discuss their defining and emerging hallmarks, along with their enabling and associated features. We also highlight potential future directions in this field of research.

From Hematopoietic Stem Cells to Platelets: Unifying Differentiation Pathways Identified by Lineage Tracing Mouse Models

Platelets are the terminal progeny of megakaryocytes, primarily produced in the bone marrow, and play critical roles in blood homeostasis, clotting, and wound healing. Traditionally, megakaryocytes and platelets are thought to arise from multipotent hematopoietic stem cells (HSCs) via multiple discrete progenitor populations with successive, lineage-restricting differentiation steps. However, this view has recently been challenged by studies suggesting that (1) some HSC clones are biased and/or restricted to the platelet lineage, (2) not all platelet generation follows the "canonical" megakaryocytic differentiation path of hematopoiesis, and (3) platelet output is the default program of steady-state hematopoiesis. Here, we specifically investigate the evidence that in vivo lineage tracing studies provide for the route(s) of platelet generation and investigate the involvement of various intermediate progenitor cell populations. We further identify the challenges that need to be overcome that are required to determine the presence, role, and kinetics of these possible alternate pathways.

Barcoding of episodic memories in the hippocampus of a food-caching bird

The hippocampus is critical for episodic memory. Although hippocampal activity represents place and other behaviorally relevant variables, it is unclear how it encodes numerous memories of specific events in life. To study episodic coding, we leveraged the specialized behavior of chickadees-food-caching birds that form memories at well-defined moments in time whenever they cache food for subsequent retrieval. Our recordings during caching revealed very sparse, transient barcode-like patterns of firing across hippocampal neurons. Each "barcode" uniquely represented a caching event and transiently reactivated during the retrieval of that specific cache. Barcodes co-occurred with the conventional activity of place cells but were uncorrelated even for nearby cache locations that had similar place codes. We propose that animals recall episodic memories by reactivating hippocampal barcodes. Similarly to computer hash codes, these patterns assign unique identifiers to different events and could be a mechanism for rapid formation and storage of many non-interfering memories.

Chromosomal barcodes for simultaneous tracking of near-isogenic bacterial strains in plant microbiota

DNA-amplicon-based microbiota profiling can estimate species diversity and abundance but cannot resolve genetic differences within individuals of the same species. Here we report the development of modular bacterial tags (MoBacTags) encoding DNA barcodes that enable tracking of near-isogenic bacterial commensals in an array of complex microbiome communities. Chromosomally integrated DNA barcodes are then co-amplified with endogenous marker genes of the community by integrating corresponding primer binding sites into the barcode. We use this approach to assess the contributions of individual bacterial genes to Arabidopsis thaliana root microbiota establishment with synthetic communities that include MoBacTag-labelled strains of Pseudomonas capeferrum. Results show reduced root colonization for certain mutant strains with defects in gluconic-acid-mediated host immunosuppression, which would not be detected with traditional amplicon sequencing. Our work illustrates how MoBacTags can be applied to assess scaling of individual bacterial genetic determinants in the plant microbiota.

Timing of treatment shapes the path to androgen receptor signaling inhibitor resistance in prostate cancer

There is optimism that cancer drug resistance can be addressed through appropriate combination therapy, but success requires understanding the growing complexity of resistance mechanisms, including the evolution and population dynamics of drug-sensitive and drug-resistant clones over time. Using DNA barcoding to trace individual prostate tumor cells in vivo , we find that the evolutionary path to acquired resistance to androgen receptor signaling inhibition (ARSI) is dependent on the timing of treatment. In established tumors, resistance occurs through polyclonal adaptation of drug-sensitive clones, despite the presence of rare subclones with known, pre-existing ARSI resistance. Conversely, in an experimental setting designed to mimic minimal residual disease, resistance occurs through outgrowth of pre-existing resistant clones and not by adaptation. Despite these different evolutionary paths, the underlying mechanisms responsible for resistance are shared across the two evolutionary paths. Furthermore, mixing experiments reveal that the evolutionary path to adaptive resistance requires cooperativity between subclones. Thus, despite the presence of pre-existing ARSI-resistant subclones, acquired resistance in established tumors occurs primarily through cooperative, polyclonal adaptation of drug-sensitive cells. This tumor ecosystem model of resistance has new implications for developing effective combination therapy.

ECM-derived biomaterials for regulating tissue multicellularity and maturation

Recent breakthroughs in developing human-relevant organotypic models led to the building of highly resemblant tissue constructs that hold immense potential for transplantation, drug screening, and disease modeling. Despite the progress in fine-tuning stem cell multilineage differentiation in highly controlled spatiotemporal conditions and hosting microenvironments, 3D models still experience naive and incomplete morphogenesis. In particular, existing systems and induction protocols fail to maintain stem cell long-term potency, induce high tissue-level multicellularity, or drive the maturity of stem cell-derived 3D models to levels seen in their in vivo counterparts. In this review, we highlight the use of extracellular matrix (ECM)-derived biomaterials in providing stem cell niche-mimicking microenvironment capable of preserving stem cell long-term potency and inducing spatial and region-specific differentiation. We also examine the maturation of different 3D models, including organoids, encapsulated in ECM biomaterials and provide looking-forward perspectives on employing ECM biomaterials in building more innovative, transplantable, and functional organs.

Digital Barcodes for High-Throughput Screening

High-throughput screening is an indispensable technology in drug discovery, cancer therapy, and disease diagnosis, and it could greatly reduce time cost, reagent consumption, and labor expense. Here, four high-throughput screening methods with high sensitivity and accessibility are discussed in detail. Fluorescence, DNA, heavy metal, and nonmetal isotope barcodes, which generally label antibodies, proteins, and saccharides to identify cells, are detected by flow cytometry, second-generation DNA sequencing, mass cytometry, and second-ion mass spectrometry, respectively. Encoding binary information in barcodes, labeling individual cells by barcodes, performing the characterization of cells together, and identifying the result belonging to individual cells via barcodes are the main steps for high-throughput screening. Applications of the four digital barcodes in high-throughput screening for both in vitro and in vivo tests are described in detail, and their advantages and disadvantages are also summarized. High-throughput screening has provided a powerful platform widely accessible for multidisciplinary studies and has greatly sped up the progress of drug discovery, disease diagnosis, and cancer therapy.

Unsupervised classification of brain-wide axons reveals the presubiculum neuronal projection blueprint

We present a quantitative strategy to identify all projection neuron types from a given region with statistically different patterns of anatomical targeting. We first validate the technique with mouse primary motor cortex layer 6 data, yielding two clusters consistent with cortico-thalamic and intra-telencephalic neurons. We next analyze the presubiculum, a less-explored region, identifying five classes of projecting neurons with unique patterns of divergence, convergence, and specificity. We report several findings: individual classes target multiple subregions along defined functions; all hypothalamic regions are exclusively targeted by the same class also invading midbrain and agranular retrosplenial cortex; Cornu Ammonis receives input from a single class of presubicular axons also projecting to granular retrosplenial cortex; path distances from the presubiculum to the same targets differ significantly between classes, as do the path distances to distinct targets within most classes; the identified classes have highly non-uniform abundances; and presubicular somata are topographically segregated among classes. This study thus demonstrates that statistically distinct projections shed light on the functional organization of their circuit.

Single-cell lineage tracing with endogenous markers

Resolving lineage relationships between cells in an organism provides key insights into the fate of individual cells and drives a fundamental understanding of the process of development and disease. A recent rapid increase in experimental and computational advances for detecting naturally occurring somatic nuclear and mitochondrial mutation at single-cell resolution has expanded lineage tracing from model organisms to humans. This review discusses the advantages and challenges of experimental and computational techniques for cell lineage tracing using somatic mutation as endogenous DNA barcodes to decipher the relationships between cells during development and tumour evolution. We outlook the advantages of spatial clonal evolution analysis and single-cell lineage tracing using endogenous genetic markers.

Chronic active Epstein-Barr virus disease originates from infected hematopoietic stem cells

ABSTRACT

Chronic active Epstein-Barr virus (EBV) disease (CAEBV) is a lethal syndrome because of persistent EBV infection. When diagnosed as CAEBV, EBV infection was observed in multiple hematopoietic lineages, but the etiology of CAEBV is still elusive. Bone marrow and peripheral cells derived from 5 patients with CAEBV, 1 patient with EBV-associated hemophagocytic lymphohistiocytosis, and 2 healthy controls were analyzed. Multiple assays were applied to identify and characterize EBV-infected cells, including quantitative polymerase chain reaction, PrimeFlow, and single-cell RNA-sequencing (scRNA-seq). Based on scRNA-seq data, alterations in gene expression of particular cell types were analyzed between patients with CAEBV and controls, and between infected and uninfected cells. One patient with CAEBV was treated with allogeneic hematopoietic stem cell transplantation (HSCT), and the samples derived from this patient were analyzed again 6 months after HSCT. EBV infected the full spectrum of the hematopoietic system including both lymphoid and myeloid lineages, as well as the hematopoietic stem cells (HSCs) of the patients with CAEBV. EBV-infected HSCs exhibited a higher differentiation rate toward downstream lineages, and the EBV infection had an impact on both the innate and adaptive immunity, resulting in inflammatory symptoms. EBV-infected cells were thoroughly removed from the hematopoietic system after HSCT. Taken together, multiple lines of evidence presented in this study suggest that CAEBV disease originates from the infected HSCs, which might potentially lead to innovative therapy strategies for CAEBV.

DNA Barcoding Technology for Lineage Recording and Tracing to Resolve Cell Fate Determination

In various biological contexts, cells receive signals and stimuli that prompt them to change their current state, leading to transitions into a future state. This change underlies the processes of development, tissue maintenance, immune response, and the pathogenesis of various diseases. Following the path of cells from their initial identity to their current state reveals how cells adapt to their surroundings and undergo transformations to attain adjusted cellular states. DNA-based molecular barcoding technology enables the documentation of a phylogenetic tree and the deterministic events of cell lineages, providing the mechanisms and timing of cell lineage commitment that can either promote homeostasis or lead to cellular dysregulation. This review comprehensively presents recently emerging molecular recording technologies that utilize CRISPR/Cas systems, base editing, recombination, and innate variable sequences in the genome. Detailing their underlying principles, applications, and constraints paves the way for the lineage tracing of every cell within complex biological systems, encompassing the hidden steps and intermediate states of organism development and disease progression.

Flexible parsing, interpretation, and editing of technical sequences with splitcode

Next-generation sequencing libraries are constructed with numerous synthetic constructs such as sequencing adapters, barcodes, and unique molecular identifiers. Such sequences can be essential for interpreting results of sequencing assays, and when they contain information pertinent to an experiment, they must be processed and analyzed. We present a tool called splitcode, that enables flexible and efficient parsing, interpreting, and editing of sequencing reads. This versatile tool facilitates simple, reproducible preprocessing of reads from libraries constructed for a large array of single-cell and bulk sequencing assays.

How colonization bottlenecks, tissue niches, and transmission strategies shape protozoan infections

Protozoan pathogens such as Plasmodium spp., Leishmania spp., Toxoplasma gondii, and Trypanosoma spp. are often associated with high-mortality, acute and chronic diseases of global health concern. For transmission and immune evasion, protozoans have evolved diverse strategies to interact with a range of host tissue environments. These interactions are linked to disease pathology, yet our understanding of the association between parasite colonization and host homeostatic disruption is limited. Recently developed techniques for cellular barcoding have the potential to uncover the biology regulating parasite transmission, dissemination, and the stability of infection. Understanding bottlenecks to infection and the in vivo tissue niches that facilitate chronic infection and spread has the potential to reveal new aspects of parasite biology.

Stem cell heterogeneity, plasticity, and regulation

As a population of homogeneous cells with both self-renewal and differentiation potential, stem cell pools are highly compartmentalized and contain distinct subsets that exhibit stable but limited heterogeneity during homeostasis. However, their striking plasticity is showcased under natural or artificial stress, such as injury, transplantation, cancer, and aging, leading to changes in their phenotype, constitution, metabolism, and function. The complex and diverse network of cell-extrinsic niches and signaling pathways, together with cell-intrinsic genetic and epigenetic regulators, tightly regulate both the heterogeneity during homeostasis and the plasticity under perturbation. Manipulating these factors offers better control of stem cell behavior and a potential revolution in the current state of regenerative medicine. However, disruptions of normal regulation by genetic mutation or excessive plasticity acquisition may contribute to the formation of tumors. By harnessing innovative techniques that enhance our understanding of stem cell heterogeneity and employing novel approaches to maximize the utilization of stem cell plasticity, stem cell therapy holds immense promise for revolutionizing the future of medicine.

Live birth of chimeric monkey with high contribution from embryonic stem cells

A formal demonstration that mammalian pluripotent stem cells possess preimplantation embryonic cell-like (naive) pluripotency is the generation of chimeric animals through early embryo complementation with homologous cells. Whereas such naive pluripotency has been well demonstrated in rodents, poor chimerism has been achieved in other species including non-human primates due to the inability of the donor cells to match the developmental state of the host embryos. Here, we have systematically tested various culture conditions for establishing monkey naive embryonic stem cells and optimized the procedures for chimeric embryo culture. This approach generated an aborted fetus and a live chimeric monkey with high donor cell contribution. A stringent characterization pipeline demonstrated that donor cells efficiently (up to 90%) incorporated into various tissues (including the gonads and placenta) of the chimeric monkeys. Our results have major implications for the study of primate naive pluripotency and genetic engineering of non-human primates.

Single basolateral amygdala neurons in macaques exhibit distinct connectional motifs with frontal cortex

Basolateral amygdala (BLA) projects widely across the macaque frontal cortex, and amygdalo-frontal projections are critical for appropriate emotional responding and decision making. While it is appreciated that single BLA neurons branch and project to multiple areas in frontal cortex, the organization and frequency of this branching has yet to be fully characterized. Here, we determined the projection patterns of more than 3,000 macaque BLA neurons. We found that one-third of BLA neurons had two or more distinct projection targets in frontal cortex and subcortical structures. The patterns of single BLA neuron projections to multiple areas were organized into repeating motifs that targeted distinct sets of areas in medial and ventral frontal cortex, indicative of separable BLA networks. Our findings begin to reveal the rich structure of single-neuron connections in the non-human primate brain, providing a neuroanatomical basis for the role of BLA in coordinating brain-wide responses to valent stimuli.

Genetic models for lineage tracing in musculoskeletal development, injury, and healing

Musculoskeletal development and later post-natal homeostasis are highly dynamic processes, marked by rapid structural and functional changes across very short periods of time. Adult anatomy and physiology are derived from pre-existing cellular and biochemical states. Consequently, these early developmental states guide and predict the future of the system as a whole. Tools have been developed to mark, trace, and follow specific cells and their progeny either from one developmental state to the next or between circumstances of health and disease. There are now many such technologies alongside a library of molecular markers which may be utilized in conjunction to allow for precise development of unique cell 'lineages'. In this review, we first describe the development of the musculoskeletal system beginning as an embryonic germ layer and at each of the key developmental stages that follow. We then discuss these structures in the context of adult tissues during homeostasis, injury, and repair. Special focus is given in each of these sections to the key genes involved which may serve as markers of lineage or later in post-natal tissues. We then finish with a technical assessment of lineage tracing and the techniques and technologies currently used to mark cells, tissues, and structures within the musculoskeletal system.

Cellular barcoding: From developmental tracing to anti-tumor drug discovery

Clonal evolution has gained immense attention in explaining cancer cell status, history, and fate during cancer progression. Current single-cell or spatial transcriptome technologies have broadened our understanding of various mechanisms underlying cancer initiation, relapse, and drug resistance. However, technical challenges still hinder a better understanding of the dynamics of distinctive phenotypic states and abnormal trajectories from normal physiological transition to malignant stages. Cellular barcoding enabled lineage tracing on parallelly massive cells at single-cell resolution through different mechanisms lately, enabling new insights into exploring developmental trajectories, cancer progression, and targeted therapies. This review summarizes the latest noteworthy and robust strategies for different types of cellular barcodes. To introduce the major characteristics, advantages and limitations of these different strategies, this review will further guide in choosing or improving cellular barcoding technologies and their applications in cancer research.

High-throughput library transgenesis in Caenorhabditis elegans via Transgenic Arrays Resulting in Diversity of Integrated Sequences (TARDIS)

High-throughput transgenesis using synthetic DNA libraries is a powerful method for systematically exploring genetic function. Diverse synthesized libraries have been used for protein engineering, identification of protein-protein interactions, characterization of promoter libraries, developmental and evolutionary lineage tracking, and various other exploratory assays. However, the need for library transgenesis has effectively restricted these approaches to single-cell models. Here, we present Transgenic Arrays Resulting in Diversity of Integrated Sequences (TARDIS), a simple yet powerful approach to large-scale transgenesis that overcomes typical limitations encountered in multicellular systems. TARDIS splits the transgenesis process into a two-step process: creation of individuals carrying experimentally introduced sequence libraries, followed by inducible extraction and integration of individual sequences/library components from the larger library cassette into engineered genomic sites. Thus, transformation of a single individual, followed by lineage expansion and functional transgenesis, gives rise to thousands of genetically unique transgenic individuals. We demonstrate the power of this system using engineered, split selectable TARDIS sites in Caenorhabditis elegans to generate (1) a large set of individually barcoded lineages and (2) transcriptional reporter lines from predefined promoter libraries. We find that this approach increases transformation yields up to approximately 1000-fold over current single-step methods. While we demonstrate the utility of TARDIS using C. elegans, in principle the process is adaptable to any system where experimentally generated genomic loci landing pads and diverse, heritable DNA elements can be generated.

Best Practices in Designing, Sequencing, and Identifying Random DNA Barcodes

Random DNA barcodes are a versatile tool for tracking cell lineages, with applications ranging from development to cancer to evolution. Here, we review and critically evaluate barcode designs as well as methods of barcode sequencing and initial processing of barcode data. We first demonstrate how various barcode design decisions affect data quality and propose a new design that balances all considerations that we are currently aware of. We then discuss various options for the preparation of barcode sequencing libraries, including inline indices and Unique Molecular Identifiers (UMIs). Finally, we test the performance of several established and new bioinformatic pipelines for the extraction of barcodes from raw sequencing reads and for error correction. We find that both alignment and regular expression-based approaches work well for barcode extraction, and that error-correction pipelines designed specifically for barcode data are superior to generic ones. Overall, this review will help researchers to approach their barcoding experiments in a deliberate and systematic way.

Base editors: development and applications in biomedicine

Base editor (BE) is a gene-editing tool developed by combining the CRISPR/Cas system with an individual deaminase, enabling precise single-base substitution in DNA or RNA without generating a DNA double-strand break (DSB) or requiring donor DNA templates in living cells. Base editors offer more precise and secure genome-editing effects than other conventional artificial nuclease systems, such as CRISPR/Cas9, as the DSB induced by Cas9 will cause severe damage to the genome. Thus, base editors have important applications in the field of biomedicine, including gene function investigation, directed protein evolution, genetic lineage tracing, disease modeling, and gene therapy. Since the development of the two main base editors, cytosine base editors (CBEs) and adenine base editors (ABEs), scientists have developed more than 100 optimized base editors with improved editing efficiency, precision, specificity, targeting scope, and capacity to be delivered in vivo, greatly enhancing their application potential in biomedicine. Here, we review the recent development of base editors, summarize their applications in the biomedical field, and discuss future perspectives and challenges for therapeutic applications.

Stem cell-based modeling and single-cell multiomics reveal gene-regulatory mechanisms underlying human skeletal development

Although the skeleton is essential for locomotion, endocrine functions, and hematopoiesis, the molecular mechanisms of human skeletal development remain to be elucidated. Here, we introduce an integrative method to model human skeletal development by combining in vitro sclerotome induction from human pluripotent stem cells and in vivo endochondral bone formation by implanting the sclerotome beneath the renal capsules of immunodeficient mice. Histological and scRNA-seq analyses reveal that the induced bones recapitulate endochondral ossification and are composed of human skeletal cells and mouse circulatory cells. The skeletal cell types and their trajectories are similar to those of human embryos. Single-cell multiome analysis reveals dynamic changes in chromatin accessibility associated with multiple transcription factors constituting cell-type-specific gene-regulatory networks (GRNs). We further identify ZEB2, which may regulate the GRNs in human osteogenesis. Collectively, these results identify components of GRNs in human skeletal development and provide a valuable model for its investigation.

The fractal brain: scale-invariance in structure and dynamics

The past 40 years have witnessed extensive research on fractal structure and scale-free dynamics in the brain. Although considerable progress has been made, a comprehensive picture has yet to emerge, and needs further linking to a mechanistic account of brain function. Here, we review these concepts, connecting observations across different levels of organization, from both a structural and functional perspective. We argue that, paradoxically, the level of cortical circuits is the least understood from a structural point of view and perhaps the best studied from a dynamical one. We further link observations about scale-freeness and fractality with evidence that the environment provides constraints that may explain the usefulness of fractal structure and scale-free dynamics in the brain. Moreover, we discuss evidence that behavior exhibits scale-free properties, likely emerging from similarly organized brain dynamics, enabling an organism to thrive in an environment that shares the same organizational principles. Finally, we review the sparse evidence for and try to speculate on the functional consequences of fractality and scale-freeness for brain computation. These properties may endow the brain with computational capabilities that transcend current models of neural computation and could hold the key to unraveling how the brain constructs percepts and generates behavior.

Targeting the metastatic niche: Single-cell lineage tracing in prime time

Identification of actionable drug targets remains a rate-limiting step of, and one of the most prominent barriers to successful drug development for metastatic cancers. CRISPR-Cas9, a tool for making targeted genomic edits, has given rise to various novel applications that have greatly accelerated discovery in developmental biology. Recent work has coupled a CRISPR-Cas9-based lineage tracing platform with single-cell transcriptomics in the unexplored context of cancer metastasis. In this perspective, we briefly reflect on the development of these distinct technological advances and the process by which they have become integrated. We also highlight the importance of single-cell lineage tracing in oncology drug development and suggest the profound capacity of a high-resolution, computational approach to reshape cancer drug discovery by enabling identification of novel metastasis-specific drug targets and mechanisms of resistance.

Optimization of CRISPR-Cas system for clinical cancer therapy

Cancer is a genetic disease caused by alterations in genome and epigenome and is one of the leading causes for death worldwide. The exploration of disease development and therapeutic strategies at the genetic level have become the key to the treatment of cancer and other genetic diseases. The functional analysis of genes and mutations has been slow and laborious. Therefore, there is an urgent need for alternative approaches to improve the current status of cancer research. Gene editing technologies provide technical support for efficient gene disruption and modification in vivo and in vitro, in particular the use of clustered regularly interspaced short palindromic repeats (CRISPR)-Cas systems. Currently, the applications of CRISPR-Cas systems in cancer rely on different Cas effector proteins and the design of guide RNAs. Furthermore, effective vector delivery must be met for the CRISPR-Cas systems to enter human clinical trials. In this review article, we describe the mechanism of the CRISPR-Cas systems and highlight the applications of class II Cas effector proteins. We also propose a synthetic biology approach to modify the CRISPR-Cas systems, and summarize various delivery approaches facilitating the clinical application of the CRISPR-Cas systems. By modifying the CRISPR-Cas system and optimizing its in vivo delivery, promising and effective treatments for cancers using the CRISPR-Cas system are emerging.

Application of CRISPR Cas systems in DNA recorders and writers

The necessity to record and store biological data is increasing in due course of time. However, it is quite difficult to understand biological mechanisms and keep a track of these events in some storage mediums. DNA (deoxyribonucleic acid) is the best candidate for the storage of cellular events in the biological system. It is energy efficient as well as stable at the same time. DNA-based writers and memory devices are continually evolving and finding new avenues in terms of their wide range of applications. Among all the DNA-based storage devices that employ enzymes like recombinases, nucleases, integrases, and polymerases, one of the most popular tools used for these devices is the emerging and versatile CRISPR Cas technology. CRISPR Cas is a prokaryotic immune system that keeps a memory of viral attacks and protects prokaryotes from potential future infections. The main aim of this short review is to study such molecular recorders and writers that employ CRISPR Cas technologies and obtain an in-depth overview of the mechanisms involved and the applications of these molecular devices.

High-throughput sequencing of macaque basolateral amygdala projections reveals dissociable connectional motifs with frontal cortex

The basolateral amygdala (BLA) projects widely across the macaque frontal cortex1-4, and amygdalo-frontal projections are critical for optimal emotional responding5 and decision-making6. Yet, little is known about the single-neuron architecture of these projections: namely, whether single BLA neurons project to multiple parts of the frontal cortex. Here, we use MAPseq7 to determine the projection patterns of over 3000 macaque BLA neurons. We found that one-third of BLA neurons have two or more distinct targets in parts of frontal cortex and of subcortical structures. Further, we reveal non-random structure within these branching patterns such that neurons with four targets are more frequently observed than those with two or three, indicative of widespread networks. Consequently, these multi-target single neurons form distinct networks within medial and ventral frontal cortex consistent with their known functions in regulating mood and decision-making. Additionally, we show that branching patterns of single neurons shape functional networks in the brain as assessed by fMRI-based functional connectivity. These results provide a neuroanatomical basis for the role of the BLA in coordinating brain-wide responses to valent stimuli8 and highlight the importance of high-resolution neuroanatomical data for understanding functional networks in the brain.

Mechanisms of Acquired Resistance and Tolerance to EGFR Targeted Therapy in Non-Small Cell Lung Cancer

Non-small cell lung cancers (NSCLC) harboring activating mutations of the epidermal growth factor receptor (EGFR) are treated with specific tyrosine kinase inhibitors (EGFR-TKIs) of this receptor, resulting in clinically responses that can generally last several months. Unfortunately, EGFR-targeted therapy also favors the emergence of drug tolerant or resistant cells, ultimately resulting in tumor relapse. Recently, cellular barcoding strategies have arisen as a powerful tool to investigate the clonal evolution of these subpopulations in response to anti-cancer drugs. In this review, we provide an overview of the currently available treatment options for NSCLC, focusing on EGFR targeted therapy, and discuss the common mechanisms of resistance to EGFR-TKIs. We also review the characteristics of drug-tolerant persister (DTP) cells and the mechanistic basis of drug tolerance in EGFR-mutant NSCLC. Lastly, we address how cellular barcoding can be applied to investigate the response and the behavior of DTP cells upon EGFR-TKI treatment.

Accurate estimation of molecular counts from amplicon sequence data with unique molecular identifiers

MOTIVATION

Amplicon sequencing is widely applied to explore heterogeneity and rare variants in genetic populations. Resolving true biological variants and quantifying their abundance is crucial for downstream analyses, but measured abundances are distorted by stochasticity and bias in amplification, plus errors during polymerase chain reaction (PCR) and sequencing. One solution attaches unique molecular identifiers (UMIs) to sample sequences before amplification. Counting UMIs instead of sequences provides unbiased estimates of abundance. While modern methods improve over naïve counting by UMI identity, most do not account for UMI reuse or collision, and they do not adequately model PCR and sequencing errors in the UMIs and sample sequences.

RESULTS

We introduce Deduplication and Abundance estimation with UMIs (DAUMI), a probabilistic framework to detect true biological amplicon sequences and accurately estimate their deduplicated abundance. DAUMI recognizes UMI collision, even on highly similar sequences, and detects and corrects most PCR and sequencing errors in the UMI and sampled sequences. DAUMI performs better on simulated and real data compared to other UMI-aware clustering methods.

AVAILABILITY AND IMPLEMENTATION

Source code is available at https://github.com/DormanLab/AmpliCI.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.