Rapidly evolving homing CRISPR barcodes

A method for characterizing Cas9 variants via a one-million target sequence library of self-targeting sgRNAs

Detailed target-selectivity information and experiment-based efficacy prediction tools are primarily available for Streptococcus pyogenes Cas9 (SpCas9). One obstacle to develop such tools is the rarity of accurate data. Here, we report a method termed ‘Self-targeting sgRNA Library Screen’ (SLS) for assaying the activity of Cas9 nucleases in bacteria using random target/sgRNA libraries of self-targeting sgRNAs. Exploiting more than a million different sequences, we demonstrate the use of the method with the SpCas9-HF1 variant to analyse its activity and reveal motifs that influence its target-selectivity. We have also developed an algorithm for predicting the activity of SpCas9-HF1 with an accuracy matching those of existing tools. SLS is a facile alternative to the much more expensive and laborious approaches used currently and has the capability of delivering sufficient amount of data for most of the orthologs and variants of SpCas9.

New insights on CRISPR/Cas9-based therapy for breast Cancer

CRISPR/Cas9 has revolutionized genome-editing techniques in various biological fields including human cancer research. Cancer is a multi-step process that encompasses the accumulation of mutations that result in the hallmark of the malignant state. The goal of cancer research is to identify these mutations and correlate them with the underlying tumorigenic process. Using CRISPR/Cas9 tool, specific mutations responsible for cancer initiation and/or progression could be corrected at least in animal models as a first step towards translational applications. In the present article, we review various novel strategies that employed CRISPR/Cas9 to treat breast cancer in both in vitro and in vivo systems.

The bone microenvironment invigorates metastatic seeds for further dissemination

Metastasis has been considered as the terminal step of tumor progression. However, recent genomic studies suggest that many metastases are initiated by further spread of other metastases. Nevertheless, the corresponding pre-clinical models are lacking, and underlying mechanisms are elusive. Using several approaches, including parabiosis and an evolving barcode system, we demonstrated that the bone microenvironment facilitates breast and prostate cancer cells to further metastasize and establish multi-organ secondary metastases. We uncovered that this metastasis-promoting effect is driven by epigenetic reprogramming that confers stem cell-like properties on cancer cells disseminated from bone lesions. Furthermore, we discovered that enhanced EZH2 activity mediates the increased stemness and metastasis capacity. The same findings also apply to single cell-derived populations, indicating mechanisms distinct from clonal selection. Taken together, our work revealed an unappreciated role of the bone microenvironment in metastasis evolution and elucidated an epigenomic reprogramming process driving terminal-stage, multi-organ metastases.

The bone microenvironment increases phenotypic plasticity of ER+ breast cancer cells

Estrogen receptor-positive (ER+) breast cancer exhibits a strong bone tropism in metastasis. How the bone microenvironment (BME) impacts ER signaling and endocrine therapy remains poorly understood. Here, we discover that the osteogenic niche transiently and reversibly reduces ER expression and activities specifically in bone micrometastases (BMMs), leading to endocrine resistance. As BMMs progress, the ER reduction and endocrine resistance may partially recover in cancer cells away from the osteogenic niche, creating phenotypic heterogeneity in macrometastases. Using multiple approaches, including an evolving barcoding strategy, we demonstrated that this process is independent of clonal selection, and represents an EZH2-mediated epigenomic reprogramming. EZH2 drives ER+ BMMs toward a basal and stem-like state. EZH2 inhibition reverses endocrine resistance. These data exemplify how epigenomic adaptation to BME promotes phenotypic plasticity of metastatic seeds, fosters intra-metastatic heterogeneity, and alters therapeutic responses. Our study provides insights into the clinical enigma of ER+ metastatic recurrences despite endocrine therapies.

Evolving barcodes shed light into evolving metastases

Selective pressure and signals from the tissue microenvironment drive metastasis and determine the survival of metastatic tumor cells at distant organs. Zhang et al. and Bado et al. apply CRISPR-mediated evolving barcode technology to elucidate the role of the bone microenvironment in the evolution of breast cancer metastasis.

Lineage barcoding in mice with homing CRISPR

Classic approaches to mapping the developmental history of cells in vivo have relied on techniques that require complex interventions and often capture only a single trajectory or moment in time. We have previously described a developmental barcoding system to address these issues using synthetically induced mutations to record information about each cell's lineage in its genome. This system uses MARC1 mouse lines, which have multiple homing guide RNAs that each generate hundreds of mutant alleles and combine to produce an exponential diversity of barcodes. Here, we detail two MARC1 lines that are available from a public repository. We describe strategies for using MARC1 mice and experimental design considerations. We provide a protocol for barcode retrieval and sequencing as well as the analysis of the sequencing data. This protocol generates barcodes based on synthetically induced mutations in mice to enable lineage analysis.

ESTIMATION OF CELL LINEAGE TREES BY MAXIMUM-LIKELIHOOD PHYLOGENETICS

CRISPR technology has enabled cell lineage tracing for complex multicellular organisms through insertion-deletion mutations of synthetic genomic barcodes during organismal development. To reconstruct the cell lineage tree from the mutated barcodes, current approaches apply general-purpose computational tools that are agnostic to the mutation process and are unable to take full advantage of the data's structure. We propose a statistical model for the CRISPR mutation process and develop a procedure to estimate the resulting tree topology, branch lengths, and mutation parameters by iteratively applying penalized maximum likelihood estimation. By assuming the barcode evolves according to a molecular clock, our method infers relative ordering across parallel lineages, whereas existing techniques only infer ordering for nodes along the same lineage. When analyzing transgenic zebrafish data from McKenna, Findlay and Gagnon et al. (2016), we find that our method recapitulates known aspects of zebrafish development and the results are consistent across samples.

Recording of elapsed time and temporal information about biological events using Cas9

DNA has not been utilized to record temporal information, although DNA has been used to record biological information and to compute mathematical problems. Here, we found that indel generation by Cas9 and guide RNA can occur at steady rates, in contrast to typical dynamic biological reactions, and the accumulated indel frequency can be a function of time. By measuring indel frequencies, we developed a method for recording and measuring absolute time periods over hours to weeks in mammalian cells. These time-recordings were conducted in several cell types, with different promoters and delivery vectors for Cas9, and in both cultured cells and cells of living mice. As applications, we recorded the duration of chemical exposure and the lengths of elapsed time since the onset of biological events (e.g., heat exposure and inflammation). We propose that our systems could serve as synthetic "DNA clocks."

Sequential Activation of Guide RNAs to Enable Successive CRISPR-Cas9 Activities

Currently, either highly multiplexed genetic manipulations can be delivered to mammalian cells all at once or extensive engineering of gene regulatory sequences can be used to conditionally activate a few manipulations. Here, we provide proof of principle for a new system enabling multiple genetic manipulations to be executed as a preprogrammed cascade of events. The system leverages the programmability of the S. pyogenes Cas9 and is based on flexible arrangements of individual modules of activity. The basic module consists of an inactive single-guide RNA (sgRNA)-like component that is converted to an active state through the effects of another sgRNA. Modules can be arranged to bring about an algorithmic program of sequential genetic manipulations without the need for engineering cell-type-specific promoters or gene regulatory sequences. With the expanding diversity of available tools that use spCas9, this sgRNA-based system provides multiple levels of interfacing with mammalian cell biology.

Next-Generation Lineage Tracing and Fate Mapping to Interrogate Development

Lineage tracing and fate mapping, overlapping yet distinct disciplines to follow cells and their progeny, have evolved rapidly over the last century. Lineage tracing aims to identify all progeny arising from an individual cell, placing them within a lineage hierarchy. The recent emergence of genomic technologies, such as single-cell and spatial transcriptomics, has fostered sophisticated new methods to reconstruct lineage relationships at high resolution. In contrast, fate maps, schematics showing which parts of the embryo will develop into which tissue, have remained relatively static since the 1970s. However, fate maps provide spatial information, often lost in lineage reconstruction, that can offer fundamental mechanistic insight into development. Here, we broadly review the origins of fate mapping and lineage tracing approaches. We focus on the most recent developments in lineage tracing, permitted by advances in single-cell genomics. Finally, we explore the current potential to leverage these new technologies to synthesize high-resolution fate maps and discuss their potential for interrogating development at new depths.

CRISPR-Cas deployment in non-small cell lung cancer for target screening, validations, and discoveries

Continued advancements in CRISPR-Cas systems have accelerated genome research. Use of CRISPR-Cas in cancer research has been of great interest that is resulting in development of orthogonal methods for drug target validations and discovery of new therapeutic targets through genome-wide screens of cancer cells. CRISPR-based screens have also revealed several new cancer drivers through alterations in tumor suppressor genes (TSGs) and oncogenes inducing resistance to targeted therapies via activation of alternate signaling pathways. Given such dynamic status of cancer, we review the application of CRISPR-Cas in non-small cell lung cancer (NSCLC) for development of mutant models, drug screening, target validation, novel target discoveries, and other emerging potential applications. In addition, CRISPR-based approach for development of novel anticancer combination therapies is also discussed in this review.

Light-sheet fluorescence imaging charts the gastrula origin of vascular endothelial cells in early zebrafish embryos

It remains challenging to construct a complete cell lineage map of the origin of vascular endothelial cells in any vertebrate embryo. Here, we report the application of in toto light-sheet fluorescence imaging of embryos to trace the origin of vascular endothelial cells (ECs) at single-cell resolution in zebrafish. We first adapted a previously reported method to embryo mounting and light-sheet imaging, created an alignment, fusion, and extraction all-in-one software (AFEIO) for processing big data, and performed quantitative analysis of cell lineage relationships using commercially available Imaris software. Our data revealed that vascular ECs originated from broad regions of the gastrula along the dorsal–ventral and anterior–posterior axes, of which the dorsal–anterior cells contributed to cerebral ECs, the dorsal–lateral cells to anterior trunk ECs, and the ventral–lateral cells to posterior trunk and tail ECs. Therefore, this work, to our knowledge, charts the first comprehensive map of the gastrula origin of vascular ECs in zebrafish, and has potential applications for studying the origin of any embryonic organs in zebrafish and other model organisms.

RNA timestamps identify the age of single molecules in RNA sequencing

Current approaches to single-cell RNA sequencing (RNA-seq) provide only limited information about the dynamics of gene expression. Here we present RNA timestamps, a method for inferring the age of individual RNAs in RNA-seq data by exploiting RNA editing. To introduce timestamps, we tag RNA with a reporter motif consisting of multiple MS2 binding sites that recruit the adenosine deaminase ADAR2 fused to an MS2 capsid protein. ADAR2 binding to tagged RNA causes A-to-I edits to accumulate over time, allowing the age of the RNA to be inferred with hour-scale accuracy. By combining observations of multiple timestamped RNAs driven by the same promoter, we can determine when the promoter was active. We demonstrate that the system can infer the presence and timing of multiple past transcriptional events. Finally, we apply the method to cluster single cells according to the timing of past transcriptional activity. RNA timestamps will allow the incorporation of temporal information into RNA-seq workflows.

Discovering New Progenitor Cell Populations through Lineage Tracing and In Vivo Imaging

Identification of progenitor cells that generate differentiated cell types during development, regeneration, and disease states is central to understanding the mechanisms governing such transitions. For more than a century, different lineage-tracing strategies have been developed, which helped disentangle the complex relationship between progenitor cells and their progenies. In this review, we discuss how lineage-tracing analyses have evolved alongside technological advances, and how this approach has contributed to the identification of progenitor cells in different contexts of cell differentiation. We also highlight a few examples in which lineage-tracing experiments have been instrumental for resolving long-standing debates and for identifying unexpected cellular origins. This discussion emphasizes how this century-old quest to delineate cellular lineage relationships is still active, and new discoveries are being made with the development of newer methodologies.

Parallel Single-Cell RNA-Seq and Genetic Recording Reveals Lineage Decisions in Developing Embryoid Bodies

Early developmental specification can be modeled by differentiating embryonic stem cells (ESCs) to embryoid bodies (EBs), a heterogeneous mixture of three germ layers. Here, we combine single-cell transcriptomics and genetic recording to characterize EB differentiation. We map transcriptional states along a time course and model cell fate trajectories and branchpoints as cells progress to distinct germ layers. To validate this inferential model, we propose an innovative inducible genetic recording technique that leverages recombination to generate cell-specific, timestamp barcodes in a narrow temporal window. We validate trajectory architecture and key branchpoints, including early specification of a primordial germ cell (PGC)-like lineage from preimplantation epiblast-like cells. We further identify a temporally defined role of DNA methylation in this PGC-epiblast decision. Our study provides a high-resolution lineage map for an organoid model of embryogenesis, insights into epigenetic determinants of fate specification, and a strategy for lineage mapping of rapid differentiation processes.

Kim et al. present a temporally precise genetic recording system for lineage tracing and transcriptomics analysis of single cells. They generate a trajectory map and single-cell transcriptional atlas of developing embryoid bodies, an organoid model of pre-gastrulation embryogenesis. These data reveal transcriptional and epigenetic regulators of early cell fate decisions.

Genetic Tools to Study Cardiovascular Biology

Progress in biomedical science is tightly associated with the improvement of methods and genetic tools to manipulate and analyze gene function in mice, the most widely used model organism in biomedical research. The joint effort of numerous individual laboratories and consortiums has contributed to the creation of a large genetic resource that enables scientists to image cells, probe signaling pathways activities, or modify a gene function in any desired cell type or time point, à la carte. However, as these tools significantly increase in number and become more sophisticated, it is more difficult to keep track of each tool's possibilities and understand their advantages and disadvantages. Knowing the best currently available genetic technology to answer a particular biological question is key to reach a higher standard in biomedical research. In this review, we list and discuss the main advantages and disadvantages of available mammalian genetic technology to analyze cardiovascular cell biology at higher cellular and molecular resolution. We start with the most simple and classical genetic approaches and end with the most advanced technology available to fluorescently label cells, conditionally target their genes, image their clonal expansion, and decode their lineages.

Reading the heart at single-cell resolution

The burgeoning field of single-cell transcriptomics augments our ability to scrutinize organ systems at unprecedented resolutions. Single-cell RNA sequencing (scRNA-seq) and analytical techniques have shed light on the cellular heterogeneity, developmental trajectories, intercellular communications of the cardiac system, and thus contributed much to the understanding of cardiac development, homeostasis and disorders. Although generalized protocols are well established for scRNA-seq pipelines, customized sample preparation, quality control, and data interpretation are still needed in cardiac research. In this article, we highlight major steps that impact data quality in scRNA-seq experiments, with particular focus on sample and data processing of cardiomyocytes. We also summarize popular applications of scRNA-seq, outlining general tools, caveats and examples in cardiac research.

Lineage tracing meets single-cell omics: opportunities and challenges

A fundamental goal of developmental and stem cell biology is to map the developmental history (ontogeny) of differentiated cell types. Recent advances in high-throughput single-cell sequencing technologies have enabled the construction of comprehensive transcriptional atlases of adult tissues and of developing embryos from measurements of up to millions of individual cells. Parallel advances in sequencing-based lineage-tracing methods now facilitate the mapping of clonal relationships onto these landscapes and enable detailed comparisons between molecular and mitotic histories. Here we review recent progress and challenges, as well as the opportunities that emerge when these two complementary representations of cellular history are synthesized into integrated models of cell differentiation.

Alignment of Cell Lineage Trees Elucidates Genetic Programs for the Development and Evolution of Cell Types

A full understanding of the developmental process requires fine-scale characterization of cell divisions and cell types, which are naturally organized as the developmental cell lineage tree (CLT). Technological breakthroughs facilitated determination of more CLTs, but complete comprehension of the data remains difficult without quantitative comparison among CLTs. We hereby quantified phenotypic similarity between CLTs using a novel computational method that exhaustively searches for optimal correspondence between individual cells meanwhile retaining their topological relationships. The revealed CLT similarities allowed us to infer functional similarity at the transcriptome level, identify cell fate transformations, predict functional relationships between mutants, and find evolutionary correspondence between cell types of different species. By allowing quantitative comparison between CLTs, our work is expected to greatly enhance the interpretability of relevant data and help answer the myriad of questions surrounding the developmental process.

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Align cell lineage trees (CLTs) to search/quantify their phenotypic similarities

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Aligning worm CLTs captured known genetic/developmental programs

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Similarities between knockdown CLTs revealed functional relationships between genes

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CLT alignments between species gave insight on the evolution of cell types

CRISPRpic: fast and precise analysis for CRISPR-induced mutations via prefixed index counting

Analysis of CRISPR-induced mutations at targeted locus can be achieved by polymerase chain reaction amplification followed by parallel massive sequencing. We developed a novel algorithm, named as CRISPRpic, to analyze the sequencing reads for the CRISPR experiments via counting exact-matching and pattern-searching. Compare to the other methods based on sequence alignment, CRISPRpic provides precise mutation calling and ultrafast analysis of the sequencing results. Python script of CRISPRpic is available at https://github.com/compbio/CRISPRpic.

Endogenous CRISPR/Cas9 arrays for scalable whole-organism lineage tracing

The past decade has seen a renewed appreciation of the central importance of cellular lineages to many questions in biology (especially organogenesis, stem cells and tumor biology). This has been driven in part by a renaissance in genetic clonal-labeling techniques. Recent approaches are based on accelerated mutation of DNA sequences, which can then be sequenced from individual cells to re-create a ‘phylogenetic’ tree of cell lineage. However, current approaches depend on making transgenic alterations to the genome in question, which limit their application. Here, we introduce a new method that completely avoids the need for prior genetic engineering, by identifying endogenous CRISPR/Cas9 target arrays suitable for lineage analysis. In both mouse and zebrafish, we identify the highest quality compact arrays as judged by equal base composition, 5′ G sequence, minimal likelihood of residing in the functional genome, minimal off targets and ease of amplification. We validate multiple high-quality endogenous CRISPR/Cas9 arrays, demonstrating their utility for lineage tracing. Our pragmatically scalable technique thus can produce deep and broad lineages in vivo, while removing the dependence on genetic engineering.

Inference of single-cell phylogenies from lineage tracing data using Cassiopeia

The pairing of CRISPR/Cas9-based gene editing with massively parallel single-cell readouts now enables large-scale lineage tracing. However, the rapid growth in complexity of data from these assays has outpaced our ability to accurately infer phylogenetic relationships. First, we introduce Cassiopeia-a suite of scalable maximum parsimony approaches for tree reconstruction. Second, we provide a simulation framework for evaluating algorithms and exploring lineage tracer design principles. Finally, we generate the most complex experimental lineage tracing dataset to date, 34,557 human cells continuously traced over 15 generations, and use it for benchmarking phylogenetic inference approaches. We show that Cassiopeia outperforms traditional methods by several metrics and under a wide variety of parameter regimes, and provide insight into the principles for the design of improved Cas9-enabled recorders. Together, these should broadly enable large-scale mammalian lineage tracing efforts. Cassiopeia and its benchmarking resources are publicly available at www.github.com/YosefLab/Cassiopeia.

Deciphering Cell Fate Decision by Integrated Single-Cell Sequencing Analysis

Cellular differentiation is a common underlying feature of all multicellular organisms through which naïve cells progressively become fate restricted and develop into mature cells with specialized functions. A comprehensive understanding of the regulatory mechanisms of cell fate choices during de- velopment, regeneration, homeostasis, and disease is a central goal of mod- ern biology. Ongoing rapid advances in single-cell biology are enabling the exploration of cell fate specification at unprecedented resolution. Here, we review single-cell RNA sequencing and sequencing of other modalities as methods to elucidate the molecular underpinnings of lineage specification. We specifically discuss how the computational tools available to reconstruct lineage trajectories, quantify cell fate bias, and perform dimensionality re- duction for data visualization are providing new mechanistic insights into the process of cell fate decision. Studying cellular differentiation using single- cell genomic tools is paving the way for a detailed understanding of cellular behavior in health and disease.

CellTagging: combinatorial indexing to simultaneously map lineage and identity at single-cell resolution

Single-cell technologies are offering unparalleled insight into complex biology, revealing the behavior of rare cell populations that are masked in bulk population analyses. One current limitation of single-cell approaches is that lineage relationships are typically lost as a result of cell processing. We recently established a method, CellTagging, permitting the parallel capture of lineage information and cell identity via a combinatorial cell indexing approach. CellTagging integrates with high-throughput single-cell RNA sequencing, where sequential rounds of cell labeling enable the construction of multi-level lineage trees. Here, we provide a detailed protocol to (i) generate complex plasmid and lentivirus CellTag libraries for labeling of cells; (ii) sequentially CellTag cells over the course of a biological process; (iii) profile single-cell transcriptomes via high-throughput droplet-based platforms; and (iv) generate a CellTag expression matrix, followed by clone calling and lineage reconstruction. This lentiviral-labeling approach can be deployed in any organism or in vitro culture system that is amenable to viral transduction to simultaneously profile lineage and identity at single-cell resolution.

Viral approaches to study the mammalian brain: Lineage tracing, circuit dissection and therapeutic applications

Viral vectors are widely used to study the development, function and pathology of neural circuits in the mammalian brain. Their flexible payloads with customizable choices of tool genes allow versatile applications ranging from lineage tracing, circuit mapping and functional interrogation, to translational and therapeutic applications. Different applications have distinct technological requirements, therefore, often utilize different types of virus. This review introduces the most commonly used viruses for these applications and some recent advances in improving the resolution and throughput of lineage tracing, the efficacy and selectivity of circuit tracing and the specificity of cell type targeting.

CRISPR-mediated modeling and functional validation of candidate tumor suppressor genes in small cell lung cancer

Small cell lung cancer (SCLC) is a highly aggressive subtype of lung cancer that remains among the most lethal of solid tumor malignancies. Recent genomic sequencing studies have identified many recurrently mutated genes in human SCLC tumors. However, the functional roles of most of these genes remain to be validated. Here, we have adapted the CRISPR-Cas9 system to a well-established murine model of SCLC to rapidly model loss-of-function mutations in candidate genes identified from SCLC sequencing studies. We show that loss of the gene p107 significantly accelerates tumor progression. Notably, compared with loss of the closely related gene p130, loss of p107 results in fewer but larger tumors as well as earlier metastatic spread. In addition, we observe differences in proliferation and apoptosis as well as altered distribution of initiated tumors in the lung, resulting from loss of p107 or p130 Collectively, these data demonstrate the feasibility of using the CRISPR-Cas9 system to model loss of candidate tumor suppressor genes in SCLC, and we anticipate that this approach will facilitate efforts to investigate mechanisms driving tumor progression in this deadly disease.

In vivo single-cell lineage tracing in zebrafish using high-resolution infrared laser-mediated gene induction microscopy

Heterogeneity broadly exists in various cell types both during development and at homeostasis. Investigating heterogeneity is crucial for comprehensively understanding the complexity of ontogeny, dynamics, and function of specific cell types. Traditional bulk-labeling techniques are incompetent to dissect heterogeneity within cell population, while the new single-cell lineage tracing methodologies invented in the last decade can hardly achieve high-fidelity single-cell labeling and long-term in-vivo observation simultaneously. In this work, we developed a high-precision infrared laser-evoked gene operator heat-shock system, which uses laser-induced CreERT2 combined with loxP-DsRedx-loxP-GFP reporter to achieve precise single-cell labeling and tracing. In vivo study indicated that this system can precisely label single cell in brain, muscle and hematopoietic system in zebrafish embryo. Using this system, we traced the hematopoietic potential of hemogenic endothelium (HE) in the posterior blood island (PBI) of zebrafish embryo and found that HEs in the PBI are heterogeneous, which contains at least myeloid unipotent and myeloid-lymphoid bipotent subtypes.

In situ readout of DNA barcodes and single base edits facilitated by in vitro transcription

Molecular barcoding technologies that uniquely identify single cells are hampered by limitations in barcode measurement. Readout by sequencing does not preserve the spatial organization of cells in tissues, whereas imaging methods preserve spatial structure but are less sensitive to barcode sequence. Here we introduce a system for image-based readout of short (20-base-pair) DNA barcodes. In this system, called Zombie, phage RNA polymerases transcribe engineered barcodes in fixed cells. The resulting RNA is subsequently detected by fluorescent in situ hybridization. Using competing match and mismatch probes, Zombie can accurately discriminate single-nucleotide differences in the barcodes. This method allows in situ readout of dense combinatorial barcode libraries and single-base mutations produced by CRISPR base editors without requiring barcode expression in live cells. Zombie functions across diverse contexts, including cell culture, chick embryos and adult mouse brain tissue. The ability to sensitively read out compact and diverse DNA barcodes by imaging will facilitate a broad range of barcoding and genomic recording strategies.

Advancing CRISPR-Based Programmable Platforms beyond Genome Editing in Mammalian Cells

Human diseases are caused by dysregulation of cellular biological programs that are encoded in DNA. Unveiling the endogenous programs and encoding new programs into the genome are key to creating novel diagnostic and therapeutic strategies. CRISPR/Cas9, originally identified in bacteria, has revolutionized genome editing in mammalian cells. Recent advances in CRISPR technologies have provided new programmable platforms for modifying cell function and behavior. CRISPR-based transcriptional regulators and modified gRNAs have enabled multiplexed regulation and visualization of genome dynamics with spatiotemporal precision. Using these toolkits, genome-scale screening platforms can identify key genetic elements or combinations thereof that modulate phenotypes in mammalian cells. In addition, imaging platforms for multiplexed genomic labeling have been created to study the conformation and dynamics of chromatin in living cells, which are essential for genome function. Furthermore, CRISPR-based computation and memory platforms have been built in living mammalian cells by using DNA as a data processing and storage medium to regulate and monitor cellular behaviors. The conditional regulation of CRISPR-based parts has enabled the design of complex multilayered biological programs. CRISPR-based memory platforms can continuously record biological events as mutations in defined DNA loci. By making use of base editors, CRISPR-based computation and memory platforms have been interconnected to perform logic operations based on past events. These technologies open up new avenues for understanding biological phenomena and designing mammalian cells as living machines for biomedical applications.

Molecular digital data storage using DNA

Molecular data storage is an attractive alternative for dense and durable information storage, which is sorely needed to deal with the growing gap between information production and the ability to store data. DNA is a clear example of effective archival data storage in molecular form. In this Review, we provide an overview of the process, the state of the art in this area and challenges for mainstream adoption. We also survey the field of in vivo molecular memory systems that record and store information within the DNA of living cells, which, together with in vitro DNA data storage, lie at the growing intersection of computer systems and biotechnology.

Next Generation Precision Medicine: CRISPR-mediated Genome Editing for the Treatment of Neurodegenerative Disorders

Despite significant advancements in the field of molecular neurobiology especially neuroinflammation and neurodegeneration, the highly complex molecular mechanisms underlying neurodegenerative diseases remain elusive. As a result, the development of the next generation neurotherapeutics has experienced a considerable lag phase. Recent advancements in the field of genome editing offer a new template for dissecting the precise molecular pathways underlying the complex neurodegenerative disorders. We believe that the innovative genome and transcriptome editing strategies offer an excellent opportunity to decipher novel therapeutic targets, develop novel neurodegenerative disease models, develop neuroimaging modalities, develop next-generation diagnostics as well as develop patient-specific precision-targeted personalized therapies to effectively treat neurodegenerative disorders including Alzheimer's disease, Parkinson's disease, Huntington's disease, Amyotrophic lateral sclerosis, Frontotemporal dementia etc. Here, we review the latest developments in the field of CRISPR-mediated genome editing and provide unbiased futuristic insights regarding its translational potential to improve the treatment outcomes and minimize financial burden. However, despite significant advancements, we would caution the scientific community that since the CRISPR field is still evolving, currently we do not know the full spectrum of CRISPR-mediated side effects. In the wake of the recent news regarding CRISPR-edited human babies being born in China, we urge the scientific community to maintain high scientific and ethical standards and utilize CRISPR for developing in vitro disease in a dish model, in vivo testing in nonhuman primates and lower vertebrates and for the development of neurotherapeutics for the currently incurable neurodegenerative disorders. Graphical Abstract.

Difference in Acquired Radioresistance Induction Between Repeated Photon and Particle Irradiation

In recent years, advanced radiation therapy techniques, including stereotactic body radiotherapy and carbon–ion radiotherapy, have progressed to such an extent that certain types of cancer can be treated with radiotherapy alone. The therapeutic outcomes are particularly promising for early stage lung cancer, with results matching those of surgical resection. Nevertheless, patients may still experience local tumor recurrence, which might be exacerbated by the acquisition of radioresistance after primary radiotherapy. Notwithstanding the risk of tumors acquiring radioresistance, secondary radiotherapy is increasingly used to treat recurrent tumors. In this context, it appears essential to comprehend the radiobiological effects of repeated photon and particle irradiation and their underlying cellular and molecular mechanisms in order to achieve the most favorable therapeutic outcome. However, to date, the mechanisms of acquisition of radioresistance in cancer cells have mainly been studied after repeated in vitro X-ray irradiation. By contrast, other critical aspects of radioresistance remain mostly unexplored, including the response to carbon-ion irradiation of X-ray radioresistant cancer cells, the mechanisms of acquisition of carbon-ion resistance, and the consequences of repeated in vivo X-ray or carbon-ion irradiation. In this review, we discuss the underlying mechanisms of acquisition of X-ray and carbon-ion resistance in cancer cells, as well as the phenotypic differences between X-ray and carbon-ion-resistant cancer cells, the biological implications of repeated in vivo X-ray or carbon-ion irradiation, and the main open questions in the field.

Unravelling cellular relationships during development and regeneration using genetic lineage tracing

Tracking the progeny of single cells is necessary for building lineage trees that recapitulate processes such as embryonic development and stem cell differentiation. In classical lineage tracing experiments, cells are fluorescently labelled to allow identification by microscopy of a limited number of cell clones. To track a larger number of clones in complex tissues, fluorescent proteins are now replaced by heritable DNA barcodes that are read using next-generation sequencing. In prospective lineage tracing, unique DNA barcodes are introduced into single cells through genetic manipulation (using, for example, Cre-mediated recombination or CRISPR-Cas9-mediated editing) and tracked over time. Alternatively, in retrospective lineage tracing, naturally occurring somatic mutations can be used as endogenous DNA barcodes. Finally, single-cell mRNA-sequencing datasets that capture different cell states within a developmental or differentiation trajectory can be used to recapitulate lineages. In this Review, we discuss methods for prospective or retrospective lineage tracing and demonstrate how trajectory reconstruction algorithms can be applied to single-cell mRNA-sequencing datasets to infer developmental or differentiation tracks. We discuss how these approaches are used to understand cell fate during embryogenesis, cell differentiation and tissue regeneration.

Designing cell function: assembly of synthetic gene circuits for cell biology applications

Synthetic biology is the discipline of engineering application-driven biological functionalities that were not evolved by nature. Early breakthroughs of cell engineering, which were based on ectopic (over)expression of single sets of transgenes, have already had a revolutionary impact on the biotechnology industry, regenerative medicine and blood transfusion therapies. Now, we require larger-scale, rationally assembled genetic circuits engineered to programme and control various human cell functions with high spatiotemporal precision in order to solve more complex problems in applied life sciences, biomedicine and environmental sciences. This will open new possibilities for employing synthetic biology to advance personalized medicine by converting cells into living therapeutics to combat hitherto intractable diseases.

The new technologies of high-throughput single-cell RNA sequencing

A wealth of genome and transcriptome data obtained using new generation sequencing (NGS) technologies for whole organisms could not answer many questions in oncology, immunology, physiology, neurobiology, zoology and other fields of science and medicine. Since the cell is the basis for the living of all unicellular and multicellular organisms, it is necessary to study the biological processes at its level. This understanding gave impetus to the development of a new direction – the creation of technologies that allow working with individual cells (single-cell technology). The rapid development of not only instruments, but also various advanced protocols for working with single cells is due to the relevance of these studies in many fields of science and medicine. Studying the features of various stages of ontogenesis, identifying patterns of cell differentiation and subsequent tissue development, conducting genomic and transcriptome analyses in various areas of medicine (especially in demand in immunology and oncology), identifying cell types and states, patterns of biochemical and physiological processes using single cell technologies, allows the comprehensive research to be conducted at a new level. The first RNA-sequencing technologies of individual cell transcriptomes (scRNA-seq) captured no more than one hundred cells at a time, which was insufficient due to the detection of high cell heterogeneity, existence of the minor cell types (which were not detected by morphology) and complex regulatory pathways. The unique techniques for isolating, capturing and sequencing transcripts of tens of thousands of cells at a time are evolving now. However, new technologies have certain differences both at the sample preparation stage and during the bioinformatics analysis. In the paper we consider the most effective methods of multiple parallel scRNA-seq using the example of 10XGenomics, as well as the specifics of such an experiment, further bioinformatics analysis of the data, future outlook and applications of new high-performance technologies.

The next generation of CRISPR-Cas technologies and applications

The prokaryote-derived CRISPR-Cas genome editing systems have transformed our ability to manipulate, detect, image and annotate specific DNA and RNA sequences in living cells of diverse species. The ease of use and robustness of this technology have revolutionized genome editing for research ranging from fundamental science to translational medicine. Initial successes have inspired efforts to discover new systems for targeting and manipulating nucleic acids, including those from Cas9, Cas12, Cascade and Cas13 orthologues. Genome editing by CRISPR-Cas can utilize non-homologous end joining and homology-directed repair for DNA repair, as well as single-base editing enzymes. In addition to targeting DNA, CRISPR-Cas-based RNA-targeting tools are being developed for research, medicine and diagnostics. Nuclease-inactive and RNA-targeting Cas proteins have been fused to a plethora of effector proteins to regulate gene expression, epigenetic modifications and chromatin interactions. Collectively, the new advances are considerably improving our understanding of biological processes and are propelling CRISPR-Cas-based tools towards clinical use in gene and cell therapies.

Towards quantitative and multiplexed in vivo functional cancer genomics

Large-scale sequencing of human tumours has uncovered a vast array of genomic alterations. Genetically engineered mouse models recapitulate many features of human cancer and have been instrumental in assigning biological meaning to specific cancer-associated alterations. However, their time, cost and labour-intensive nature limits their broad utility; thus, the functional importance of the majority of genomic aberrations in cancer remains unknown. Recent advances have accelerated the functional interrogation of cancer-associated alterations within in vivo models. Specifically, the past few years have seen the emergence of CRISPR-Cas9-based strategies to rapidly generate increasingly complex somatic alterations and the development of multiplexed and quantitative approaches to ascertain gene function in vivo.

Nucleic Acid Databases and Molecular-Scale Computing

DNA outperforms most conventional storage media in terms of information retention time, physical density, and volumetric coding capacity. Advances in synthesis and sequencing technologies have enabled implementations of large synthetic DNA databases with impressive storage capacity and reliable data recovery. Several robust DNA storage architectures featuring random access, error correction, and content rewritability have been constructed with the potential for scalability and cost reduction. We survey these recent achievements and discuss alternative routes for overcoming the hurdles of engineering practical DNA storage systems. We also review recent exciting work on in vivo DNA memory including intracellular recorders constructed by programmable genome editing tools. Besides information storage, DNA could serve as a versatile molecular computing substrate. We highlight several state-of-the-art DNA computing techniques such as strand displacement, localized hybridization chain reactions, and enzymatic reaction networks. We summarize how these simple primitives have facilitated rational designs and implementations of in vitro DNA reaction networks that emulate digital/analog circuits, artificial neural networks, or nonlinear dynamic systems. We envision these modular primitives could be strategically adapted for sophisticated database operations and massively parallel computations on DNA databases. We also highlight in vivo DNA computing modules such as CRISPR logic gates for building scalable genetic circuits in living cells. To conclude, we discuss various implications and challenges of DNA-based storage and computing, and we particularly encourage innovative work on bridging these two areas of research to further explore molecular parallelism and near-data processing. Such integrated molecular systems could lead to far-reaching applications in biocomputing, security, and medicine.

DiSNE Movie Visualization and Assessment of Clonal Kinetics Reveal Multiple Trajectories of Dendritic Cell Development

A thorough understanding of cellular development is incumbent on assessing the complexities of fate and kinetics of individual clones within a population. Here, we develop a system for robust periodical assessment of lineage outputs of thousands of transient clones and establishment of bona fide cellular trajectories. We appraise the development of dendritic cells (DCs) in fms-like tyrosine kinase 3 ligand culture from barcode-labeled hematopoietic stem and progenitor cells (HSPCs) by serially measuring barcode signatures and visualize these multidimensional data using developmental interpolated t-distributed stochastic neighborhood embedding (DiSNE) time-lapse movies. We identify multiple cellular trajectories of DC development that are characterized by distinct fate bias and expansion kinetics and determine that these are intrinsically programmed. We demonstrate that conventional DC and plasmacytoid DC trajectories are largely separated already at the HSPC stage. This framework allows systematic evaluation of clonal dynamics and can be applied to other steady-state or perturbed developmental systems.

Synthetic evolution

The combination of modern biotechnologies such as DNA synthesis, λ red recombineering, CRISPR-based editing and next-generation high-throughput sequencing increasingly enables precise manipulation of genes and genomes. Beyond rational design, these technologies also enable the targeted, and potentially continuous, introduction of multiple mutations. While this might seem to be merely a return to natural selection, the ability to target evolution greatly reduces fitness burdens and focuses mutation and selection on those genes and traits that best contribute to a desired phenotype, ultimately throwing evolution into fast forward.

Development of CRISPR-Cas systems for genome editing and beyond

The development of clustered regularly interspaced short-palindromic repeat (CRISPR)-Cas systems for genome editing has transformed the way life science research is conducted and holds enormous potential for the treatment of disease as well as for many aspects of biotechnology. Here, I provide a personal perspective on the development of CRISPR-Cas9 for genome editing within the broader context of the field and discuss our work to discover novel Cas effectors and develop them into additional molecular tools. The initial demonstration of Cas9-mediated genome editing launched the development of many other technologies, enabled new lines of biological inquiry, and motivated a deeper examination of natural CRISPR-Cas systems, including the discovery of new types of CRISPR-Cas systems. These new discoveries in turn spurred further technological developments. I review these exciting discoveries and technologies as well as provide an overview of the broad array of applications of these technologies in basic research and in the improvement of human health. It is clear that we are only just beginning to unravel the potential within microbial diversity, and it is quite likely that we will continue to discover other exciting phenomena, some of which it may be possible to repurpose as molecular technologies. The transformation of mysterious natural phenomena to powerful tools, however, takes a collective effort to discover, characterize, and engineer them, and it has been a privilege to join the numerous researchers who have contributed to this transformation of CRISPR-Cas systems.

DNA sequencing in high-throughput neuroanatomy

Mapping brain connectivity at single cell resolution is critical for understanding brain structure. For decades, such mapping has been principally approached with microscopy techniques, aiming to visualize neurons and their connections. However, these techniques are often very labor intensive and do not scale well to the complexity of mammalian brains. We recently leveraged the speed and parallelization of DNA sequencing to map the projections of thousands of single neurons in single experiments, and to map cortical mesoscale connectivity in single mice. Here, I review the state of sequencing-based neuroanatomy, and discuss future directions in synaptic connectivity mapping and comparative connectomics.

Developmental origins and oncogenic pathways in malignant brain tumors

Brain tumors such as adult glioblastomas and pediatric high-grade gliomas or medulloblastomas are among the leading causes of cancer-related deaths, exhibiting poor prognoses with little improvement in outcomes in the past several decades. These tumors are heterogeneous and can be initiated from various neural cell types, contributing to therapy resistance. How such heterogeneity arises is linked to the tumor cell of origin and their genetic alterations. Brain tumorigenesis and progression recapitulate key features associated with normal neurogenesis; however, the underlying mechanisms are quite dysregulated as tumor cells grow and divide in an uncontrolled manner. Recent comprehensive genomic, transcriptomic, and epigenomic studies at single-cell resolution have shed new light onto diverse tumor-driving events, cellular heterogeneity, and cells of origin in different brain tumors. Primary and secondary glioblastomas develop through different genetic alterations and pathways, such as EGFR amplification and IDH1/2 or TP53 mutation, respectively. Mutations such as histone H3K27M impacting epigenetic modifications define a distinct group of pediatric high-grade gliomas such as diffuse intrinsic pontine glioma. The identification of distinct genetic, epigenomic profiles and cellular heterogeneity has led to new classifications of adult and pediatric brain tumor subtypes, affording insights into molecular and lineage-specific vulnerabilities for treatment stratification. This review discusses our current understanding of tumor cells of origin, heterogeneity, recurring genetic and epigenetic alterations, oncogenic drivers and signaling pathways for adult glioblastomas, pediatric high-grade gliomas, and medulloblastomas, the genetically heterogeneous groups of malignant brain tumors. This article is categorized under: Gene Expression and Transcriptional Hierarchies > Gene Networks and Genomics Adult Stem Cells, Tissue Renewal, and Regeneration > Stem Cell Differentiation and Reversion Signaling Pathways > Cell Fate Signaling.

Lineage tracing using a Cas9-deaminase barcoding system targeting endogenous L1 elements

Determining cell lineage and function is critical to understanding human physiology and pathology. Although advances in lineage tracing methods provide new insight into cell fate, defining cellular diversity at the mammalian level remains a challenge. Here, we develop a genome editing strategy using a cytidine deaminase fused with nickase Cas9 (nCas9) to specifically target endogenous interspersed repeat regions in mammalian cells. The resulting mutation patterns serve as a genetic barcode, which is induced by targeted mutagenesis with single-guide RNA (sgRNA), leveraging substitution events, and subsequent read out by a single primer pair. By analyzing interspersed mutation signatures, we show the accurate reconstruction of cell lineage using both bulk cell and single-cell data. We envision that our genetic barcode system will enable fine-resolution mapping of organismal development in healthy and diseased mammalian states.

Lineage Tracing: Computational Reconstruction Goes Beyond the Limit of Imaging

Tracking the fate of individual cells and their progeny through lineage tracing has been widely used to investigate various biological processes including embryonic development, homeostatic tissue turnover, and stem cell function in regeneration and disease. Conventional lineage tracing involves the marking of cells either with dyes or nucleoside analogues or genetic marking with fluorescent and/or colorimetric protein reporters. Both are imaging-based approaches that have played a crucial role in the field of developmental biology as well as adult stem cell biology. However, imaging-based lineage tracing approaches are limited by their scalability and the lack of molecular information underlying fate transitions. Recently, computational biology approaches have been combined with diverse tracing methods to overcome these limitations and so provide high-order scalability and a wealth of molecular information. In this review, we will introduce such novel computational methods, starting from single-cell RNA sequencing-based lineage analysis to DNA barcoding or genetic scar analysis. These novel approaches are complementary to conventional imaging-based approaches and enable us to study the lineage relationships of numerous cell types during vertebrate, and in particular human, development and disease.