Multiplex, single-cell CRISPRa screening for cell type specific regulatory elements.

CRISPR-based gene activation (CRISPRa) is a strategy for upregulating gene expression by targeting promoters or enhancers in a tissue/cell-type specific manner. Here, we describe an experimental framework that combines highly multiplexed perturbations with single-cell RNA sequencing (sc-RNA-seq) to identify cell-type-specific, CRISPRa-responsive cis-regulatory elements and the gene(s) they regulate. Random combinations of many gRNAs are introduced to each of many cells, which are then profiled and partitioned into test and control groups to test for effect(s) of CRISPRa perturbations of both enhancers and promoters on the expression of neighboring genes. Applying this method to a library of 493 gRNAs targeting candidate cis-regulatory elements in both K562 cells and iPSC-derived excitatory neurons, we identify gRNAs capable of specifically upregulating intended target genes and no other neighboring genes within 1 Mb, including gRNAs yielding upregulation of six autism spectrum disorder (ASD) and neurodevelopmental disorder (NDD) risk genes in neurons. A consistent pattern is that the responsiveness of individual enhancers to CRISPRa is restricted by cell type, implying a dependency on either chromatin landscape and/or additional trans-acting factors for successful gene activation. The approach outlined here may facilitate large-scale screens for gRNAs that activate genes in a cell type-specific manner.

Single-cell analysis of chromatin and expression reveals age- and sex-associated alterations in the human heart.

Sex differences and age-related changes in the human heart at the tissue, cell, and molecular level have been well-documented and many may be relevant for cardiovascular disease. However, how molecular programs within individual cell types vary across individuals by age and sex remains poorly characterized. To better understand this variation, we performed single-nucleus combinatorial indexing (sci) ATAC- and RNA-Seq in human heart samples from nine donors. We identify hundreds of differentially expressed genes by age and sex and find epigenetic signatures of variation in ATAC-Seq data in this discovery cohort. We then scale up our single-cell RNA-Seq analysis by combining our data with five recently published single nucleus RNA-Seq datasets of healthy adult hearts. We find variation such as metabolic alterations by sex and immune changes by age in differential expression tests, as well as alterations in abundance of cardiomyocytes by sex and neurons with age. In addition, we compare our adult-derived ATAC-Seq profiles to analogous fetal cell types to identify putative developmental-stage-specific regulatory factors. Finally, we train predictive models of cell-type-specific RNA expression levels utilizing ATAC-Seq profiles to link distal regulatory sequences to promoters, quantifying the predictive value of a simple TF-to-expression regulatory grammar and identifying cell-type-specific TFs. Our analysis represents the largest single-cell analysis of cardiac variation by age and sex to date and provides a resource for further study of healthy cardiac variation and transcriptional regulation at single-cell resolution.

Retinoic acid induces human gastruloids with posterior embryo-like structures.

Gastruloids are a powerful in vitro model of early human development. However, although elongated and composed of all three germ layers, human gastruloids do not morphologically resemble post-implantation human embryos. Here we show that an early pulse of retinoic acid (RA), together with later Matrigel, robustly induces human gastruloids with posterior embryo-like morphological structures, including a neural tube flanked by segmented somites and diverse cell types, including neural crest, neural progenitors, renal progenitors and myocytes. Through in silico staging based on single-cell RNA sequencing, we find that human RA-gastruloids progress further than other human or mouse embryo models, aligning to E9.5 mouse and CS11 cynomolgus monkey embryos. We leverage chemical and genetic perturbations of RA-gastruloids to confirm that WNT and BMP signalling regulate somite formation and neural tube length in the human context, while transcription factors TBX6 and PAX3 underpin presomitic mesoderm and neural crest, respectively. Looking forward, RA-gastruloids are a robust, scalable model for decoding early human embryogenesis.

Symbolic recording of signalling and cis-regulatory element activity to DNA.

Measurements of gene expression or signal transduction activity are conventionally performed using methods that require either the destruction or live imaging of a biological sample within the timeframe of interest. Here we demonstrate an alternative paradigm in which such biological activities are stably recorded to the genome. Enhancer-driven genomic recording of transcriptional activity in multiplex (ENGRAM) is based on the signal-dependent production of prime editing guide RNAs that mediate the insertion of signal-specific barcodes (symbols) into a genomically encoded recording unit. We show how this strategy can be used for multiplex recording of the cell-type-specific activities of dozens to hundreds of cis-regulatory elements with high fidelity, sensitivity and reproducibility. Leveraging signal transduction pathway-responsive cis-regulatory elements, we also demonstrate time- and concentration-dependent genomic recording of WNT, NF-κB and Tet-On activities. By coupling ENGRAM to sequential genome editing via DNA Typewriter1, we stably record information about the temporal dynamics of two orthogonal signalling pathways to genomic DNA. Finally we apply ENGRAM to integratively record the transient activity of nearly 100 transcription factor consensus motifs across daily windows spanning the differentiation of mouse embryonic stem cells into gastruloids, an in vitro model of early mammalian development. Although these are proof-of-concept experiments and much work remains to fully realize the possibilities, the symbolic recording of biological signals or states within cells, to the genome and over time, has broad potential to complement contemporary paradigms for how we make measurements in biological systems.

Multiplex profiling of developmental cis-regulatory elements with quantitative single-cell expression reporters.

The inability to scalably and precisely measure the activity of developmental cis-regulatory elements (CREs) in multicellular systems is a bottleneck in genomics. Here we develop a dual RNA cassette that decouples the detection and quantification tasks inherent to multiplex single-cell reporter assays. The resulting measurement of reporter expression is accurate over multiple orders of magnitude, with a precision approaching the limit set by Poisson counting noise. Together with RNA barcode stabilization via circularization, these scalable single-cell quantitative expression reporters provide high-contrast readouts, analogous to classic in situ assays but entirely from sequencing. Screening >200 regions of accessible chromatin in a multicellular in vitro model of early mammalian development, we identify 13 (8 previously uncharacterized) autonomous and cell-type-specific developmental CREs. We further demonstrate that chimeric CRE pairs generate cognate two-cell-type activity profiles and assess gain- and loss-of-function multicellular expression phenotypes from CRE variants with perturbed transcription factor binding sites. Single-cell quantitative expression reporters can be applied in developmental and multicellular systems to quantitatively characterize native, perturbed and synthetic CREs at scale, with high sensitivity and at single-cell resolution.

Chromatin context-dependent regulation and epigenetic manipulation of prime editing.

We set out to exhaustively characterize the impact of the cis-chromatin environment on prime editing, a precise genome engineering tool. Using a highly sensitive method for mapping the genomic locations of randomly integrated reporters, we discover massive position effects, exemplified by editing efficiencies ranging from ∼0% to 94% for an identical target site and edit. Position effects on prime editing efficiency are well predicted by chromatin marks, e.g., positively by H3K79me2 and negatively by H3K9me3. Next, we developed a multiplex perturbational framework to assess the interaction of trans-acting factors with the cis-chromatin environment on editing outcomes. Applying this framework to DNA repair factors, we identify HLTF as a context-dependent repressor of prime editing. Finally, several lines of evidence suggest that active transcriptional elongation enhances prime editing. Consistent with this, we show we can robustly decrease or increase the efficiency of prime editing by preceding it with CRISPR-mediated silencing or activation, respectively.

A single-cell time-lapse of mouse prenatal development from gastrula to birth.

The house mouse (Mus musculus) is an exceptional model system, combining genetic tractability with close evolutionary affinity to humans1,2. Mouse gestation lasts only 3 weeks, during which the genome orchestrates the astonishing transformation of a single-cell zygote into a free-living pup composed of more than 500 million cells. Here, to establish a global framework for exploring mammalian development, we applied optimized single-cell combinatorial indexing3 to profile the transcriptional states of 12.4 million nuclei from 83 embryos, precisely staged at 2- to 6-hour intervals spanning late gastrulation (embryonic day 8) to birth (postnatal day 0). From these data, we annotate hundreds of cell types and explore the ontogenesis of the posterior embryo during somitogenesis and of kidney, mesenchyme, retina and early neurons. We leverage the temporal resolution and sampling depth of these whole-embryo snapshots, together with published data4-8 from earlier timepoints, to construct a rooted tree of cell-type relationships that spans the entirety of prenatal development, from zygote to birth. Throughout this tree, we systematically nominate genes encoding transcription factors and other proteins as candidate drivers of the in vivo differentiation of hundreds of cell types. Remarkably, the most marked temporal shifts in cell states are observed within one hour of birth and presumably underlie the massive physiological adaptations that must accompany the successful transition of a mammalian fetus to life outside the womb.

Induction and in silico staging of human gastruloids with neural tube, segmented somites & advanced cell types.

Embryonic organoids are emerging as powerful models for studying early mammalian development. For example, stem cell-derived 'gastruloids' form elongating structures containing all three germ layers1-4. However, although elongated, human gastruloids do not morphologically resemble post-implantation embryos. Here we show that a specific, discontinuous regimen of retinoic acid (RA) robustly induces human gastruloids with embryo-like morphological structures, including a neural tube and segmented somites. Single cell RNA-seq (sc-RNA-seq) further reveals that these human 'RA-gastruloids' contain more advanced cell types than conventional gastruloids, including neural crest cells, renal progenitor cells, skeletal muscle cells, and, rarely, neural progenitor cells. We apply a new approach to computationally stage human RA-gastruloids relative to somite-resolved mouse embryos, early human embryos and other gastruloid models, and find that the developmental stage of human RA-gastruloids is comparable to that of E9.5 mouse embryos, although some cell types show greater or lesser progression. We chemically perturb WNT and BMP signaling in human RA-gastruloids and find that these signaling pathways regulate somite patterning and neural tube length, respectively, while genetic perturbation of the transcription factors PAX3 and TBX6 markedly compromises the formation of neural crest and somites/renal cells, respectively. Human RA-gastruloids complement other embryonic organoids in serving as a simple, robust and screenable model for decoding early human embryogenesis.

Impact of an online pharmacy precepting-focused continuing professional development program.

INTRODUCTION: This study aimed to determine the preceptor-reported impact of an online continuing professional development (CPD) program on pharmacy preceptors' abilities and techniques for teaching students in clinical settings. METHODS: In 2017, an online program to educate and support pharmacy preceptors' use of CPD to create individualized clinical teaching development plans was launched. After allowing time for preceptors to implement their CPD plan, a follow-up program was launched in 2019 where preceptors completed a seven-question survey to assess their impact on clinical teaching from the initial program. Two questions described completion of the CPD plan with response options including "Yes," "No," or "Partially". Five open-ended questions allowed for descriptions of changes implemented and overall teaching impact. Impact of implemented changes were categorized as positive, negative, or no change. Changes implemented by preceptors were categorized as goal setting, feedback, communication/education skills, student-teacher connection, or educational resources development. RESULTS: Of the 119 preceptors who responded to at least one question, 52% fully implemented and 39% partially implemented their pre-identified CPD plan. A total of 75 preceptors provided responses regarding impact of implemented activities; 69 (92%) were coded as a positive impact on their clinical teaching. Preceptor skill development was most commonly in communication/educational skills (45%), student/teacher connection (33%), and educational resources development (33%). CONCLUSIONS: This online precepting CPD program had a positive preceptor-reported impact on clinical teaching delivered by preceptors to students. Further investigation is warranted to disseminate this program.

Predicting cellular responses to complex perturbations in high-throughput screens.

Recent advances in multiplexed single-cell transcriptomics experiments facilitate the high-throughput study of drug and genetic perturbations. However, an exhaustive exploration of the combinatorial perturbation space is experimentally unfeasible. Therefore, computational methods are needed to predict, interpret, and prioritize perturbations. Here, we present the compositional perturbation autoencoder (CPA), which combines the interpretability of linear models with the flexibility of deep-learning approaches for single-cell response modeling. CPA learns to in silico predict transcriptional perturbation response at the single-cell level for unseen dosages, cell types, time points, and species. Using newly generated single-cell drug combination data, we validate that CPA can predict unseen drug combinations while outperforming baseline models. Additionally, the architecture's modularity enables incorporating the chemical representation of the drugs, allowing the prediction of cellular response to completely unseen drugs. Furthermore, CPA is also applicable to genetic combinatorial screens. We demonstrate this by imputing in silico 5,329 missing combinations (97.6% of all possibilities) in a single-cell Perturb-seq experiment with diverse genetic interactions. We envision CPA will facilitate efficient experimental design and hypothesis generation by enabling in silico response prediction at the single-cell level and thus accelerate therapeutic applications using single-cell technologies.

A single-cell transcriptional timelapse of mouse embryonic development, from gastrula to pup.

The house mouse, Mus musculus, is an exceptional model system, combining genetic tractability with close homology to human biology. Gestation in mouse development lasts just under three weeks, a period during which its genome orchestrates the astonishing transformation of a single cell zygote into a free-living pup composed of >500 million cells. Towards a global framework for exploring mammalian development, we applied single cell combinatorial indexing (sci-*) to profile the transcriptional states of 12.4 million nuclei from 83 precisely staged embryos spanning late gastrulation (embryonic day 8 or E8) to birth (postnatal day 0 or P0), with 2-hr temporal resolution during somitogenesis, 6-hr resolution through to birth, and 20-min resolution during the immediate postpartum period. From these data (E8 to P0), we annotate dozens of trajectories and hundreds of cell types and perform deeper analyses of the unfolding of the posterior embryo during somitogenesis as well as the ontogenesis of the kidney, mesenchyme, retina, and early neurons. Finally, we leverage the depth and temporal resolution of these whole embryo snapshots, together with other published data, to construct and curate a rooted tree of cell type relationships that spans mouse development from zygote to pup. Throughout this tree, we systematically nominate sets of transcription factors (TFs) and other genes as candidate drivers of the in vivo differentiation of hundreds of mammalian cell types. Remarkably, the most dramatic shifts in transcriptional state are observed in a restricted set of cell types in the hours immediately following birth, and presumably underlie the massive changes in physiology that must accompany the successful transition of a placental mammal to extrauterine life.

Chromatin context-dependent regulation and epigenetic manipulation of prime editing.

Prime editing is a powerful means of introducing precise changes to specific locations in mammalian genomes. However, the widely varying efficiency of prime editing across target sites of interest has limited its adoption in the context of both basic research and clinical settings. Here, we set out to exhaustively characterize the impact of the cis- chromatin environment on prime editing efficiency. Using a newly developed and highly sensitive method for mapping the genomic locations of a randomly integrated "sensor", we identify specific epigenetic features that strongly correlate with the highly variable efficiency of prime editing across different genomic locations. Next, to assess the interaction of trans -acting factors with the cis -chromatin environment, we develop and apply a pooled genetic screening approach with which the impact of knocking down various DNA repair factors on prime editing efficiency can be stratified by cis -chromatin context. Finally, we demonstrate that we can dramatically modulate the efficiency of prime editing through epigenome editing, i.e. altering chromatin state in a locus-specific manner in order to increase or decrease the efficiency of prime editing at a target site. Looking forward, we envision that the insights and tools described here will broaden the range of both basic research and therapeutic contexts in which prime editing is useful.

Multiplex, single-cell CRISPRa screening for cell type specific regulatory elements.

CRISPR-based gene activation (CRISPRa) is a promising therapeutic approach for gene therapy, upregulating gene expression by targeting promoters or enhancers in a tissue/cell-type specific manner. Here, we describe an experimental framework that combines highly multiplexed perturbations with single-cell RNA sequencing (sc-RNA-seq) to identify cell-type-specific, CRISPRa-responsive cis- regulatory elements and the gene(s) they regulate. Random combinations of many gRNAs are introduced to each of many cells, which are then profiled and partitioned into test and control groups to test for effect(s) of CRISPRa perturbations of both enhancers and promoters on the expression of neighboring genes. Applying this method to candidate cis- regulatory elements in both K562 cells and iPSC-derived excitatory neurons, we identify gRNAs capable of specifically and potently upregulating target genes, including autism spectrum disorder (ASD) and neurodevelopmental disorder (NDD) risk genes. A consistent pattern is that the responsiveness of individual enhancers to CRISPRa is restricted by cell type, implying a dependency on either chromatin landscape and/or additional trans- acting factors for successful gene activation. The approach outlined here may facilitate large-scale screens for gRNAs that activate therapeutically relevant genes in a cell type-specific manner.

Massively parallel characterization of transcriptional regulatory elements in three diverse human cell types.

The human genome contains millions of candidate cis-regulatory elements (CREs) with cell-type-specific activities that shape both health and myriad disease states. However, we lack a functional understanding of the sequence features that control the activity and cell-type-specific features of these CREs. Here, we used lentivirus-based massively parallel reporter assays (lentiMPRAs) to test the regulatory activity of over 680,000 sequences, representing a nearly comprehensive set of all annotated CREs among three cell types (HepG2, K562, and WTC11), finding 41.7% to be functional. By testing sequences in both orientations, we find promoters to have significant strand orientation effects. We also observe that their 200 nucleotide cores function as non-cell-type-specific 'on switches' providing similar expression levels to their associated gene. In contrast, enhancers have weaker orientation effects, but increased tissue-specific characteristics. Utilizing our lentiMPRA data, we develop sequence-based models to predict CRE function with high accuracy and delineate regulatory motifs. Testing an additional lentiMPRA library encompassing 60,000 CREs in all three cell types, we further identified factors that determine cell-type specificity. Collectively, our work provides an exhaustive catalog of functional CREs in three widely used cell lines, and showcases how large-scale functional measurements can be used to dissect regulatory grammar.

All in the (Definition of) Family: Transnational Parent-Child Relationships, Rights to Family Life, and Canadian Immigration Law.

International human rights conventions, Canadian law and academic research all support the right to family life. Internationally and domestically, multiple definitions of family are recognized, acknowledging that long-term interpersonal commitments can be based on biological relationships as well as co-residential, legal, and emotional ties. Yet, the Canadian immigration system's limited and exclusionary understanding of parent-child relationships complicates migrant family reunification. Drawing on qualitative interview and survey data from separated families and key informants who support them, we analyze national status and class assumptions embedded in Canadian immigration standards. We argue that Canadian immigration policies disproportionately deny the right to family life to transnational Canadians and their children who hail from the Global South and/or who are socio-economically disadvantaged. Immigration policies neither recognize the globally accepted "best interests of the child" welfare standard nor the human right to family life. We offer suggestions for addressing these inequities in practice and policy.

Machine learning dissection of human accelerated regions in primate neurodevelopment.

Using machine learning (ML), we interrogated the function of all human-chimpanzee variants in 2,645 human accelerated regions (HARs), finding 43% of HARs have variants with large opposing effects on chromatin state and 14% on neurodevelopmental enhancer activity. This pattern, consistent with compensatory evolution, was confirmed using massively parallel reporter assays in chimpanzee and human neural progenitor cells. The species-specific enhancer activity of HARs was accurately predicted from the presence and absence of transcription factor footprints in each species. Despite these striking cis effects, activity of a given HAR sequence was nearly identical in human and chimpanzee cells. This suggests that HARs did not evolve to compensate for changes in the trans environment but instead altered their ability to bind factors present in both species. Thus, ML prioritized variants with functional effects on human neurodevelopment and revealed an unexpected reason why HARs may have evolved so rapidly.

A novel strategy to optimize critical information on over the counter labels for older adults.

Background and Aims: Labels designed to communicate critical information are paramount for the safe and effective use of over-the-counter medications; in recognition of this, the content and formatting of over the counter (OTC) labels sold in interstate commerce has been regulated for decades. Yet, available studies suggest that consumers frequently rely on limited information during decision making, failing to access the information required in the Drug Facts Label. This is particularly important for older consumers, who are at greater risk for adverse reactions to medicines. In two experiments we objectively evaluate how novel label designs that employ highlighting and a warning label placed on the package's front impact older consumers' attention to, and use of, critical information. Methods: In Experiment 1, 68 OTC patients (65+) engaged with a computer-based task answering yes/no scenario-based questions about a drug's appropriateness. In Experiment 2, 63 OTC patients (65+) conducted a forced-choice task where one of two drugs presented on a computer screen was appropriate for a provided scenario while the other was not. Both tasks required participants to access and use critical label information (i.e., warnings or active ingredients) to respond correctly. Dependent variables analyzed were the proportion of correct responses and time to correct response. Results: Highlighting or placing critical information on the front of the package significantly improved response accuracy and time to correct response in Experiment 1 as compared to responses utilizing the standard label. For Experiment 2, participants were faster and more accurate when critical information was highlighted. Conclusions: Results provide direct measures of the efficacy of novel labeling strategies. This information is relevant for regulations which dictate label design in ways that enhance ease and safety of use of medications for older adults.

Associating Student Performance in Pharmacy Practice Didactic and Skills-Based Courses With Advanced Pharmacy Practice Experiences.

Objective. To determine the association between pharmacy practice didactic course examinations and performance-based assessments with students' performance during their advanced pharmacy practice experiences (APPEs).Methods. This retrospective analysis included data from the graduating classes of 2018 to 2020. Students were coded as APPE poor performers (final course grade <83%) or acceptable performers. Assessments in pharmacy practice didactic and skills-based courses in students' second and third years were included in the analysis, with thresholds correlating to grade cutoffs. The association between poor performance mean examination scores and performance-based assessments with APPE performance was calculated.Results. Of the 403 graduates, analysis sample sizes ranged from 254 to 403. There were 49 students (12%) who met the criteria for poor performance in the APPE year. When comparing pharmacy practice didactic course performance to APPE poor performance, the proportion of mean examination scores that were <83% for six of the seven pharmacy practice didactic courses was significant; five of the seven mean examination scores were significant at the <78% threshold. Performance-based assessments that were significantly associated with APPE poor performance often required critical thinking.Conclusion. A gap in identification of students with APPE poor performance who did not fail a didactic course was demonstrated. Specifically, this finding suggests that pre-APPE curriculum should focus on assessments that include critical thinking. These methods could be used by other pharmacy programs to find components of their curricula that help identify students who need additional support prior to the APPE year.

Optimized single-nucleus transcriptional profiling by combinatorial indexing.

Single-cell combinatorial indexing RNA sequencing (sci-RNA-seq) is a powerful method for recovering gene expression data from an exponentially scalable number of individual cells or nuclei. However, sci-RNA-seq is a complex protocol that has historically exhibited variable performance on different tissues, as well as lower sensitivity than alternative methods. Here, we report a simplified, optimized version of the sci-RNA-seq protocol with three rounds of split-pool indexing that is faster, more robust and more sensitive and has a higher yield than the original protocol, with reagent costs on the order of 1 cent per cell or less. The total hands-on time from nuclei isolation to final library preparation takes 2-3 d, depending on the number of samples sharing the experiment. The improvements also allow RNA profiling from tissues rich in RNases like older mouse embryos or adult tissues that were problematic for the original method. We showcase the optimized protocol via whole-organism analysis of an E16.5 mouse embryo, profiling ~380,000 nuclei in a single experiment. Finally, we introduce a 'Tiny-Sci' protocol for experiments in which input material is very limited.