SUMMARY Genetic screens help infer gene function in mammalian cells, but it has remained difficult to assay complex phenotypes – such as transcriptional profiles – at scale. Here, we develop Perturb-seq, combining single cell RNA-seq and CRISPR based perturbations to perform many such assays in a pool. We demonstrate Perturb-seq by analyzing 200,000 cells in immune cells and cell lines, focusing on transcription factors regulating the response of dendritic cells to lipopolysaccharide (LPS). Perturb-seq accurately identifies individual gene targets, gene signatures, and cell states affected by individual perturbations and their genetic interactions. We posit new functions for regulators of differentiation, the anti-viral response, and mitochondrial function during immune activation. By decomposing many high content measurements into the effects of perturbations, their interactions, and diverse cell metadata, Perturb-seq dramatically increases the scope of pooled genomic assays.

SUMMARY Functional genomics efforts face tradeoffs between number of perturbations examined and complexity of phenotypes measured. We bridge this gap with Perturb-seq, which combines droplet-based single-cell RNA-seq with a strategy for barcoding CRISPR-mediated perturbations, allowing many perturbations to be profiled in pooled format. We applied Perturb-seq to dissect the mammalian unfolded protein response (UPR) using single and combinatorial CRISPR perturbations. Two genome-scale CRISPR interference (CRISPRi) screens identified genes whose repression perturbs ER homeostasis. Subjecting ~100 hits to Perturb-seq enabled high-precision functional clustering of genes. Single-cell analyses decoupled the three UPR branches, revealed bifurcated UPR branch activation among cells subject to the same perturbation, and uncovered differential activation of the branches across hits, including an isolated feedback loop between the translocon and IRE1α. These studies provide insight into how the three sensors of ER homeostasis monitor distinct types of stress and highlight the ability of Perturb-seq to dissect complex cellular responses.

Both intrinsic cell state changes and variations in the composition of stem cell populations have been implicated as contributors to aging. We used single-cell RNA-seq to dissect variability in hematopoietic stem cell (HSC) and hematopoietic progenitor cell populations from young and old mice from two strains. We found that cell cycle dominates the variability within each population and that there is a lower frequency of cells in the G1 phase among old compared with young long-term HSCs, suggesting that they traverse through G1 faster. Moreover, transcriptional changes in HSCs during aging are inversely related to those upon HSC differentiation, such that old short-term (ST) HSCs resemble young long-term (LT-HSCs), suggesting that they exist in a less differentiated state. Our results indicate both compositional changes and intrinsic, population-wide changes with age and are consistent with a model where a relationship between cell cycle progression and selfrenewal versus differentiation of HSCs is affected by aging and may contribute to the functional decline of old HSCs.

Finding the components of cellular circuits and determining their functions systematically remains a major challenge in mammalian cells. Here, we introduced genome-wide pooled CRISPR-Cas9 libraries into dendritic cells (DCs) to identify genes that control the induction of tumor necrosis factor (Tnf) by bacterial lipopolysaccharide (LPS), a key process in the host response to pathogens, mediated by the Tlr4 pathway. We found many of the known regulators of Tlr4 signaling, as well as dozens of previously unknown candidates that we validated. By measuring protein markers and mRNA profiles in DCs that are deficient in the known or candidate genes, we classified the genes into three functional modules with distinct effects on the canonical responses to LPS, and highlighted functions for the PAF complex and oligosaccharyltransferase (OST) complex. Our findings uncover new facets of innate immune circuits in primary cells, and provide a genetic approach for dissection of mammalian cell circuits.

Tissues contain exquisite vascular microstructures, and patterns of chemical cues for directing cell migration, homing, and differentiation for organ development and function. 3D microfabrication by multi-photon photolithography is a flexible, high-resolution tool for generating 3D bioscaffolds. However, the combined fabrication of scaffold microstructure simultaneously with patterning of cues to create both geometrically and chemically defined microenvironments remains to be demonstrated. Here, we present a high-speed method for micron-resolution fabrication of scaffold microstructure and patterning of protein cues simultaneously using native scaffold materials. By the simultaneous microfabrication of arbitrary microvasculature geometries, and patterning selected regions of the microvasculature with the homing ligand P-selectin, we demonstrate adhesion, rolling, and selective homing of cells in defined 3D regions. This novel ability to rapidly generate high-resolution geometries replete with patterned cues at high speed enables the construction of biomimetic microenvironments for complex 3D assays of cell behavior.

Abstract:As part of the process of preparing scRNA-seq libraries, a diverse template is typically amplified by PCR. During amplification, spurious chimeric molecules can be formed between molecules originating in different cells. While several computational and experimental strategies have been suggested to mitigate the impact of chimeric molecules, they have not been addressed in the context of scRNA-seq experiments. We demonstrate that chimeras become increasingly problematic as samples are sequenced deeply and propose two computational solutions. The first is unsupervised and relies only on cell barcode and UMI information. The second is a supervised approach built on labeled data and a set of molecule specific features. The classifier can accurately identify most of the contaminating molecules in a deeply sequenced species mixing dataset. Code is publicly available at https://github.com/asncd/schimera.. CC-BY-NC 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/093237 doi: bioRxiv preprint first posted online Dec. 12, 2016; 2 Context Specific Definitions:Cell barcode (CBC): A random nucleotide barcode present on the reverse transcription primer used to capture RNA that is unique for each single cell in an experiment.Unique Molecular Identifier (UMI): also known as a Random Molecular Tag (RMT).This refers specifically to a random nucleotide barcode present on the reverse transcription primer. For a given cell (as identified by a CBC), every captured mRNA molecule should be uniquely labeled by a UMI. PCR amplification is exponential and its efficiency depends on initial concentration and various sequence features. A UMI should identify all amplicons that originated from the same transcript. Thus, UMIs can be used for normalization of transcript count and allow correction of PCR bias.Chimera: also known as a recombinant molecule or hybrid molecule. A chimera is a PCR artifact generated when two template molecules anneal to each other rather than with a primer. This yields molecules that are comprised of a cell barcode and a mRNA from another cell. Cell barcode UMI tag (CBCUMI):A unique pair of cell barcode and UMI. This pair can potentially be associated with more than one mRNA molecule due to random chance in which UMIs from two distinct original molecules are the same or chimera formation. Unique Molecule (UM):A unique combination of a CBC, UMI, and an mRNA transcript.. CC-BY-NC 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/093237 doi: bioRxiv preprint first posted online Dec. 12, 2016; . CC-BY-NC 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has gra...

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Highlights d Single-cell trajectory map of the embryoid body model of early embryogenesis d A temporally precise genetic recording system for lineage tracing d PGC-like lineage commitment in EBs occurs at the preimplantation epiblast-like stage d DNA methylation determines PGC-fate choice in a narrow developmental window