We present CLADES (cell lineage access driven by an edition sequence), a technology for cell lineage studies based on CRISPR-Cas9 techniques. CLADES relies on a system of genetic switches to activate and inactivate reporter genes in a predetermined order. Targeting CLADES to progenitor cells allows the progeny to inherit a sequential cascade of reporters, thereby coupling birth order to reporter expression. This system, which can also be temporally induced by heat shock, enables the temporal resolution of lineage development and can therefore be used to deconstruct an extended cell lineage by tracking the reporters expressed in the progeny. When targeted to the germ line, the same cascade progresses across animal generations, predominantly marking each generation with the corresponding combination of reporters. CLADES therefore offers an innovative strategy for making programmable cascades of genes that can be used for genetic manipulation or to record serial biological events.

We present CLADES (Cell Lineage Access Driven by an Edition Sequence), a technology for cell lineage studies based on CRISPR/Cas9. CLADES relies on a system of genetic switches to activate and inactivate reporter genes in a pre-determined order. Targeting CLADES to progenitor cells allows the progeny to inherit a sequential cascade of reporters, coupling birth order with reporter expression. This gives us temporal resolution of lineage development that can be used to deconstruct an extended cell lineage by tracking the reporters expressed in the progeny. When targeted to the germ line, the same cascade progresses across animal generations, marking each generation with the corresponding combination of reporters. CLADES thus offers an innovative strategy for making programmable cascades of genes that can be used for genetic manipulation or to record serial biological events.

Acquiring both lineage and cell-type information during brain development could elucidate transcriptional programs underling neuronal diversification. This is now feasible with single-cell RNA-seq combined with CRISPR-based lineage tracing, which generates genetic barcodes with cumulative CRISPR edits. This technique has not yet been optimized to deliver high-resolution lineage reconstruction of protracted lineages. Drosophila neuronal lineages are an ideal model to consider, as multiple lineages have been morphologically mapped at single-cell resolution. Here we find the parameter ranges required to encode a representative neuronal lineage emanating from 100 stem cell divisions. We derive the optimum editing rate to be inversely proportional to lineage depth, enabling encoding to persist across lineage progression. Further, we experimentally determine the editing rates of a Cas9-deaminase in cycling neural stem cells, finding near ideal rates to map elongated Drosophila neuronal lineages. Moreover, we propose and evaluate strategies to separate recurring cell-types for lineage reconstruction. Finally, we present a simple method to combine multiple experiments, which permits dense reconstruction of protracted cell lineages despite suboptimum lineage encoding and sparse cell sampling.Competing Interest StatementThe authors have declared no competing interest.

During development, cells undergo a sequence of specification events to form functional tissues and organs. To investigate complex tissue development, it is crucial to visualize how cell lineages emerge and to be able to manipulate regulatory factors with temporal control. We recently developed TEMPO (Temporal Encoding and Manipulation in a Predefined Order), a genetic tool to label with different colors and genetically manipulate consecutive cell generations in vertebrates. TEMPO relies on CRISPR to activate a cascade of fluorescent proteins which can be imaged in vivo. Here, we explain the steps to design, generate, and express TEMPO constructs in zebrafish and mice.

Signaling pathways induce stereotyped transcriptional changes as stem cells progress into mature cell types during embryogenesis. Signaling perturbations are necessary to discover which genes are responsive or insensitive to pathway activity. However, gene regulation is additionally dependent on cell state-specific factors like chromatin modifications or transcription factor binding. Thus, transcriptional profiles need to be assayed in single cells to identify potentially multiple, distinct perturbation responses among heterogeneous cell states in an embryo. In perturbation studies, comparing heterogeneous transcriptional states among experimental conditions often requires samples to be collected over multiple independent experiments, which can introduce confounding batch effects. We present Design-Aware Integration of Single Cell ExpEriments (DAISEE), a new algorithm that models perturbation responses in single-cell datasets collected according to complex experimental designs. We demonstrate that DAISEE improves upon a previously available integrative nonnegative matrix factorization framework, more efficiently separating perturbation responses from confounding variation. We use DAISEE to integrate newly collected single-cell RNA sequencing datasets from 5-h-old zebrafish embryos expressing optimized photoswitchable MEK (psMEK), which globally activates the extracellular signal-regulated kinase (ERK), a signaling molecule involved in many cell specification events. psMEK drives some cells that are normally not exposed to ERK signals toward other wild type states and induces novel states expressing early-acting endothelial genes. Overactive signaling is therefore capable of producing unexpected gene expression states in developing embryos.

bioRxiv preprint: https://www.doi.org/10.1101/2024.09.05.610903