Whole organism lineage tracing by combinatorial and cumulative genome editing
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ABSTRACT:
PROVIDER: PRJNA322340 | ENA |
REPOSITORIES: ENA
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Project description:Multicellular systems develop from single cells through a lineage, but current lineage tracing approaches scale poorly to whole organisms. Here we use genome editing to progressively introduce and accumulate diverse mutations in a DNA barcode over multiple rounds of cell division. The barcode, an array of CRISPR/Cas9 target sites, records lineage relationships in the patterns of mutations shared between cells. In cell culture and zebrafish, we show that rates and patterns of editing are tunable, and that thousands of lineage-informative barcode alleles can be generated. By sampling hundreds of thousands of cells from individual zebrafish, we find that most cells in adult zebrafish organs derive from relatively few embryonic progenitors. Genome editing of synthetic target arrays for lineage tracing (GESTALT) will help generate large-scale maps of cell lineage in multicellular systems.
2016-05-26 | GSE81713 | GEO
Project description:Multicellular systems develop from single cells through distinct lineages. However, current lineage-tracing approaches scale poorly to whole, complex organisms. Here, we use genome editing to progressively introduce and accumulate diverse mutations in a DNA barcode over multiple rounds of cell division. The barcode, an array of clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 target sites, marks cells and enables the elucidation of lineage relationships via the patterns of mutations shared between cells. In cell culture and zebrafish, we show that rates and patterns of editing are tunable and that thousands of lineage-informative barcode alleles can be generated. By sampling hundreds of thousands of cells from individual zebrafish, we find that most cells in adult organs derive from relatively few embryonic progenitors. In future analyses, genome editing of synthetic target arrays for lineage tracing (GESTALT) can be used to generate large-scale maps of cell lineage in multicellular systems for normal development and disease.
| S-EPMC4967023 | biostudies-literature
Project description:A key goal of developmental biology is to understand how a single cell transforms into a full-grown organism consisting of many cells. Although impressive progress has been made in lineage tracing using imaging approaches, analysis of vertebrate lineage trees has mostly been limited to relatively small subsets of cells. Here we present scar-trace, a strategy for massively parallel whole-organism lineage tracing based on Cas9 induced genetic scars in the zebrafish.
2019-05-17 | GSE81533 | GEO
Project description:Endogenous CRISPR/Cas9 arrays for scalable whole-organism lineage tracing
| PRJEB37916 | ENA
Project description:Targeted epigenome editing tools allow precise manipulation and investigation of genome modifications, however they often display high context dependency and variable efficacy between target genes and cell types. While systems that simultaneously recruit multiple distinct ‘effector’ chromatin regulators can improve efficacy, they generally lack control over effector composition and spatial organisation. To overcome this we have created a modular combinatorial epigenome editing platform, called SSSavi. This system is an interchangeable and reconfigurable docking platform fused to dCas9 that enables simultaneous recruitment of up to four different effectors, allowing precise control of effector composition and spatial ordering. We demonstrate the activity and specificity of the SSSavi system and compare it to existing multi-effector targeting systems, demonstrating its efficacy. Furthermore, we demonstrate the importance of the effector recruitment spatial ordering for effective transcriptional regulation. Together, the SSSavi system enables exploration of combinatorial effector co-recruitment to enhance manipulation of chromatin contexts previously resistant to targeted editing.
2023-11-02 | GSE241460 | GEO
Project description:A modular dCas9-based recruitment platform for combinatorial epigenome editing
| PRJNA1008191 | ENA
Project description:Comprehensive single cell transcriptional profiling of a multicellular organism by combinatorial indexing
| PRJNA385514 | ENA
Project description:A key goal of developmental biology is to understand how a single cell transforms into a full-grown organism consisting of many different cell types. Single-cell RNA-sequencing (scRNA-seq) has become a widely-used method due to its ability to identify all cell types in a tissue or organ in a systematic manner. However, a major challenge is to organize the resulting taxonomy of cell types into lineage trees revealing the developmental origin of cells. Here, we present a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA-seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes, we reconstruct developmental lineage trees in zebrafish larvae and adult fish. In future analyses, LINNAEUS (LINeage tracing by Nuclease-Activated Editing of Ubiquitous Sequences) can be used as a systematic approach for identifying the lineage origin of novel cell types, or of known cell types under different conditions.
2018-04-04 | GSE106121 | GEO
Project description: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 suffers from the limitations in recording capabilities and considerable information dropout. Here, we introduce a versatile tool, DuTracer, which utilizes two orthogonal gene editing systems to record deep cell lineage history at single-cell resolution in an inducible manner. DuTracer shows the ability of enhanced lineage recording with minimized target dropouts and deepened tree depth. Application of DuTracer in mouse embryoid bodies and neuromesodermal organoids illustrates the transition pattern of the lineage relationship of different cell types and proposes potential lineage-biased molecular drivers. Moreover, we have developed an entropy-based approach to quantify the lineage recording ability of DuTracer in cell differentiation models. Together, DuTracer facilitates the precise and regulatory interrogation of cellular lineages of complex biological processes.
2024-11-20 | GSE261211 | GEO