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Human pluripotent stem cells (hPSCs) offer an unprecedented opportunity to model diverse cell types and tissues. To enable systematic exploration of the programming landscape mediated by transcription factors (TFs), we present the Human TFome, a comprehensive library containing 1,564 TF genes and 1,732 TF splice isoforms. By screening the library in three hPSC lines, we discovered 290 TFs, including 241 that were previously unreported, that induce differentiation in 4 days without alteration of external soluble or biomechanical cues. We used four of the hits to program hPSCs into neurons, fibroblasts, oligodendrocytes and vascular endothelial-like cells that have molecular and functional similarity to primary cells. Our cell-autonomous approach enabled parallel programming of hPSCs into multiple cell types simultaneously. We also demonstrated orthogonal programming by including oligodendrocyte-inducible hPSCs with unmodified hPSCs to generate cerebral organoids, which expedited in situ myelination. Large-scale combinatorial screening of the Human TFome will complement other strategies for cell engineering based on developmental biology and computational systems biology.

Natural and induced somatic mutations that accumulate in the genome during development record the phylogenetic relationships of cells; however, whether these lineage barcodes can capture the dynamics of complex progenitor fields remains unclear. Here, we introduce quantitative fate mapping, an approach to simultaneously map the fate and quantify the commitment time, commitment bias, and population size of multiple progenitor groups during development based on a time-scaled phylogeny of their descendants. To reconstruct time-scaled phylogenies from lineage barcodes, we introduce Phylotime, a scalable maximum likelihood clustering approach based on a generalizable barcoding mutagenesis model. We validate these approaches using realistically-simulated barcoding results as well as experimental results from a barcoding stem cell line. We further establish criteria for the minimum number of cells that must be analyzed for robust quantitative fate mapping. Overall, this work demonstrates how lineage barcodes, natural or synthetic, can be used to obtain quantitative fate maps, thus enabling analysis of progenitor dynamics long after embryonic development in any organism.

Natural and induced somatic mutations that accumulate in the genome during development record the phylogenetic relationships of cells; whether these lineage barcodes capture the complex dynamics of progenitor states remains unclear. We introduce quantitative fate mapping, an approach to reconstruct the hierarchy, commitment times, population sizes, and commitment biases of intermediate progenitor states during development based on a time-scaled phylogeny of their descendants. To reconstruct time-scaled phylogenies from lineage barcodes, we introduce Phylotime, a scalable maximum likelihood clustering approach based on a general barcoding mutagenesis model. We validate these approaches using realistic in silico and in vitro barcoding experiments. We further establish criteria for the number of cells that must be analyzed for robust quantitative fate mapping and a progenitor state coverage statistic to assess the robustness. This work demonstrates how lineage barcodes, natural or synthetic, enable analyzing progenitor fate and dynamics long after embryonic development in any organism.

INTRODUCTION The remarkable development of a single cell, the zygote, into the full organism occurs through a complex series of division and differentiation events that resemble a tree, with the zygote at the base branching through lineages that end in the terminal cell types at the top. Characterizing this tree of development has long been a subject of interest, and the combination of modern genome engineering and sequencing technologies promises a powerful strategy in its service: in vivo barcoding. For in vivo barcoding, heritable random mutations are induced to accumulate during development and sequenced post hoc to reconstruct the lineage tree. Demonstrations thus far have largely focused on lower vertebrates and have used a barcoding element with a constrained window of activity for clonal tracing of individual cells or cell types. Implementation in mammalian model systems, such as the mouse, incurs unique challenges that require major enhancements. RATIONALE To address the complexity of mammalian development, we reasoned that multiple independent in vivo barcoding elements could be deployed in parallel to exponentially expand their recording power. Independence requires both an absence of cross-talk between the elements and an absence of interference between their mutation outcomes. A system with the potential to deliver on these requirements is homing CRISPR, a modified version of canonical CRISPR wherein the homing guide RNA (hgRNA) combines with CRISPR-Cas9 nuclease for repeated targeting of its own locus, leading to diverse mutational outcomes. Therefore, in mouse embryonic stem cells, we scattered multiple hgRNA loci with distinct spacers in the genome to serve as barcoding elements. With this arrangement, each hgRNA acts independently as a result of its unique spacer sequence, and undesirable deletion events between multiple adjacent cut sites are less likely. Using these cells, we generated a chimeric mouse with 60 hgRNAs as the founder of the MARC1 (Mouse for Actively Recording Cells 1) line that enables barcoding and recording of cell lineages. RESULTS In the absence of Cas9, hgRNAs are stable and dormant; to initiate barcoding, we crossed MARC1 mice with Cas9 knock-in mice. In the resulting offspring, hgRNAs were activated, creating diverse mutations such that an estimated 10 23 distinct barcode combinations can be generated with only 10 hgRNAs. Furthermore, hgRNAs showed a range of activity profiles, with some mutating soon after conception while others exhibited lower activity through most of the gestation period. This range resulted in sustained barcoding throughout gestation and recording of developmental lineages: Each cell inherits a set of unique mutations that are passed on to its daughter cells, where further unique mutations can be added. Consequently, at any stage in such developmentally barcoded mice, closely related cells have a more similar mutation profile, or barcode, than the more distant ones. These recordings remain embedded in the genomes of the cells and can be extracted by sequencing. We used these recordings to carry out bottom-up reconstruction of the mouse lineage tree, starting with the first branches that emerged after the zygote, and observed robust reconstruction of the correct tree. We also investigated axis development in the brain by sequencing barcodes from the left and right side of the forebrain, midbrain, and hindbrain regions. We found that barcodes from the left and right sides of the same region were more closely related than those from different regions; this result suggests that in the precursor of the brain, commitment to the anterior-posterior axis is established prior to the lateral axis. CONCLUSION This system provides an enabling and versatile platform for in vivo barcoding and lineage tracing in a mammalian model system. It can straightforwardly create developmentally barcoded mice in which lineage information is prerecorded in cell genomes. Combining multiple independently acting molecular recording devices greatly enhances their capacity and allows for reliable information recovery and reconstruction of deep lineage trees.

Cellular barcoding using nuclease-induced genetic mutations is an effective approach that is emerging for recording biological information, including developmental lineages. We have previously introduced the homing CRISPR system as a promising methodology for generating such barcodes with scalable diversity and without crosstalk. Here, we present a mouse line (MARC1) with multiple genomically-integrated and heritable homing guide RNAs (hgRNAs). We determine the genomic locations of these hgRNAs, their activity profiles during gestation, and the diversity of their mutants. We apply the line for unique barcoding of mouse embryos and differential barcoding of embryonic tissues. We conclude that this mouse line can address the unique challenges associated with in vivo barcoding in mammalian model organisms and is thus an enabling platform for recording and lineage tracing applications in a mammalian model system.