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We present CLADES (Cell Lineage Access Driven by an Edition Sequence), a 7 technology for cell lineage studies based on CRISPR/Cas9. CLADES relies on a system of genetic 8 switches to activate and inactivate reporter genes in a pre-determined order. Targeting CLADES 9 to progenitor cells allows the progeny to inherit a sequential cascade of reporters, coupling birth 10 order with reporter expression. This gives us temporal resolution of lineage development that can 11 be used to deconstruct an extended cell lineage by tracking the reporters expressed in the progeny. 12 When targeted to the germ line, the same cascade progresses across animal generations, marking 13 each generation with the corresponding combination of reporters. CLADES thus offers an 14 innovative strategy for making programmable cascades of genes that can be used for genetic 15 manipulation or to record serial biological events. 16 One Sentence Summary: A sequence of reporters for lineage analysis 17 Main Text: Cell lineage is an essential determinant in the acquisition of cell identity (1-2). 18 Establishing the association between cell lineage and fate is one of the fundamental challenges in 19 biology. Solving this puzzle will provide a unique framework to interrogate the molecular 20 mechanisms involved in cell type specification: it is not possible to fully understand how a 21 molecular factor affects cell fate decisions if we do not even know where/when these cell fate 22 decisions occur. 23While single-cell transcriptomics has made it possible to identify cell types with great detail, 24 tracing lineages in complex organisms remains challenging. Two main strategies have been 25 deployed: i) imaging-based methods that label cell lineages in intact tissues (3-4), and ii) DNA 26 sequencing-based methods which unravel cell lineages via phylogenetic analysis of DNA 27 mutations accumulated during development (5-7). Unless the specimen is accessible for real-time 28 visualization, imaging-based strategies are only able to label cell clones rather than tracing lineage 29 progression in a single individual. For organisms with stereotyped development, full lineages can 30 be assembled by resolving smaller segments in multiple individuals (8). Besides overlooking inter-31 individual differences, this approach is tedious and makes it impractical to analyze mutant lineages 32 in detail. On the other hand, methods based on DNA sequencing allow high-throughput analysis 33 of lineage progression, although the resolution is currently limited to major lineage branches (7). 34 Moreover, sequencing methods fail to recover spatial and morphological information, critical 35 features for identification of cell types and mutant phenotypes. 36 To circumvent these limitations, we developed CLADES, a technology based on CRISPR/Cas9 to 37 trace and manipulate lineages in Drosophila. Inspired by principles of synthetic biology, we 38 engineered a programmable system of genetic switches to control the activation and inactivation 39 of re...
We present CLADES (Cell Lineage Access Driven by an Edition Sequence), a 7 technology for cell lineage studies based on CRISPR/Cas9. CLADES relies on a system of genetic 8 switches to activate and inactivate reporter genes in a pre-determined order. Targeting CLADES 9 to progenitor cells allows the progeny to inherit a sequential cascade of reporters, coupling birth 10 order with reporter expression. This gives us temporal resolution of lineage development that can 11 be used to deconstruct an extended cell lineage by tracking the reporters expressed in the progeny. 12 When targeted to the germ line, the same cascade progresses across animal generations, marking 13 each generation with the corresponding combination of reporters. CLADES thus offers an 14 innovative strategy for making programmable cascades of genes that can be used for genetic 15 manipulation or to record serial biological events. 16 One Sentence Summary: A sequence of reporters for lineage analysis 17 Main Text: Cell lineage is an essential determinant in the acquisition of cell identity (1-2). 18 Establishing the association between cell lineage and fate is one of the fundamental challenges in 19 biology. Solving this puzzle will provide a unique framework to interrogate the molecular 20 mechanisms involved in cell type specification: it is not possible to fully understand how a 21 molecular factor affects cell fate decisions if we do not even know where/when these cell fate 22 decisions occur. 23While single-cell transcriptomics has made it possible to identify cell types with great detail, 24 tracing lineages in complex organisms remains challenging. Two main strategies have been 25 deployed: i) imaging-based methods that label cell lineages in intact tissues (3-4), and ii) DNA 26 sequencing-based methods which unravel cell lineages via phylogenetic analysis of DNA 27 mutations accumulated during development (5-7). Unless the specimen is accessible for real-time 28 visualization, imaging-based strategies are only able to label cell clones rather than tracing lineage 29 progression in a single individual. For organisms with stereotyped development, full lineages can 30 be assembled by resolving smaller segments in multiple individuals (8). Besides overlooking inter-31 individual differences, this approach is tedious and makes it impractical to analyze mutant lineages 32 in detail. On the other hand, methods based on DNA sequencing allow high-throughput analysis 33 of lineage progression, although the resolution is currently limited to major lineage branches (7). 34 Moreover, sequencing methods fail to recover spatial and morphological information, critical 35 features for identification of cell types and mutant phenotypes. 36 To circumvent these limitations, we developed CLADES, a technology based on CRISPR/Cas9 to 37 trace and manipulate lineages in Drosophila. Inspired by principles of synthetic biology, we 38 engineered a programmable system of genetic switches to control the activation and inactivation 39 of re...
Cell differentiation is often associated with specific divisions and generations in a lineage tree. The presence of phenotypic noise, however, can make it difficult to observe such patterns. Using the group symmetry representation of a binary tree, it is shown how variation in a lineage can be compactly described by a set of natural variables each of which is labelled by the division at which a type of variation arises and the generation at which it is expressed. This harmonic analysis for a rooted tree provides a disciplined way to aggregate tree-structured data, improving the ability to identify differentiation patterns in noisy lineages. It also allows the proportion of variation of a phenotypic fate associated with each division to be estimated and compared to the proportion of variation expressed at each generation. The method has been applied to T-lymphocyte lineages tracked using time-lapse microscopy over several generations. For comparison, the analysis has been applied to C. elegans, a lineage with clear differentiation stages, and to a stationary branching process, which has none.
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