Biology subjects

Shendure, J.

Publications and source records attributed to Shendure, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Barcoded monoclonal embryoids are a potential solution to confounding bottlenecks in mosaic organoid screens

Genetic screens in organoids hold tremendous promise for accelerating discoveries at the intersection of genomics and developmental biology. Embryoid bodies (EBs) are self-organizing multicellular structures that recapitulate aspects of early mammalian embryogenesis. We set out to perform a CRISPR screen perturbing all transcription factors (TFs) in murine EBs. Specifically, a library of TF-targeting guide RNAs (gRNAs) was used to generate mouse embryonic stem cells (mESCs) bearing single TF knockouts. Aggregates of these mESCs were induced to form mouse EBs, such that each resulting EB was mosaic with respect to the TF perturbations represented among its constituent cells. Upon performing single cell RNA-seq (scRNA-seq) on cells derived from mosaic EBs, we found many TF perturbations exhibiting large and seemingly significant effects on the likelihood that individual cells would adopt certain fates, suggesting roles for these TFs in lineage specification. However, to our surprise, these results were not reproducible across biological replicates. Upon further investigation, we discovered cellular bottlenecks during EB differentiation that dramatically reduce clonal complexity, curtailing statistical power and confounding interpretation of mosaic screens. Towards addressing this challenge, we developed a scalable protocol in which each individual EB is monoclonally derived from a single mESC and genetically barcoded. In a proof-of-concept experiment, we show how these monoclonal EBs enable us to better quantify the consequences of TF perturbations as well as inter-individual heterogeneity across EBs harboring the same genetic perturbation. Looking forward, monoclonal EBs and EB-derived organoids may be powerful tools not only for genetic screens, but also for modeling Mendelian disorders, as their underlying genetic lesions are overwhelmingly constitutional (i.e. present in all somatic cells), yet give rise to phenotypes with incomplete penetrance and variable expressivity.

developmental biology↗

bioRxiv2025

Technical and biological sources of noise confound multiplexed enhancer AAV screening

Cis-acting regulatory enhancer elements are valuable tools for gaining cell type-specific genetic access. Leveraging large chromatin accessibility atlases, putative enhancer sequences can be identified and deployed in adeno-associated virus (AAV) delivery platforms. However, a significant bottleneck in enhancer AAV discovery is charting their detailed expression patterns in vivo, a process that currently requires gold-standard one-by-one testing. Here we present a barcoded multiplex strategy for screening enhancer AAVs at cell type resolution using single cell RNA sequencing and taxonomy mapping. We executed a proof-of-concept study using a small pool of validated enhancer AAVs expressing in a variety of neuronal and non-neuronal cell types across the mouse brain. Unexpectedly, we encountered substantial technical and biological noise including chimeric packaging products, necessitating development of novel techniques to accurately deconvolve enhancer expression patterns. These results underscore the need for improved methods to mitigate noise and highlight the complexity of enhancer AAV biology in vivo.

neuroscience↗

bioRxiv2025

Extensive length and homology dependent chimerism in pool-packaged AAV libraries

Adeno-associated viruses (AAVs) have emerged as the foremost gene therapy delivery vehicles due to their versatility, durability, and safety profile. Here we demonstrate extensive chimerism, manifesting as pervasive barcode swapping, among complex AAV libraries that are packaged as a pool. The observed chimerism is length- and homology-dependent but capsid-independent, in some cases affecting the majority of packaged AAV genomes. These results have implications for the design and deployment of functional AAV libraries in both research and clinical settings.

genomics↗

bioRxiv2024

Linking candidate causal autoimmune variants to T cell networks using genetic and epigenetic screens in primary human T cells.

Genetic variants associated with autoimmune diseases are highly enriched within putative cis-regulatory regions of CD4+ T cells, suggesting that they alter disease risk via changes in gene regulation. However, very few genetic variants have been shown to affect T cell gene expression or function. We tested >18,000 autoimmune disease-associated variants for allele-specific expression using massively parallel reporter assays in primary human CD4+ T cells. The 545 expression-modulating variants (emVars) identified greatly enrich for likely causal variants. We provide evidence that many emVars are mediated by common upstream regulatory conduits, and that putative target genes of primary T cell emVars are highly enriched within a lymphocyte activation network. Using bulk and single-cell CRISPR-interference screens, we confirm that emVar-containing T cell cis-regulatory elements modulate both known and novel target genes that regulate T cell proliferation, providing plausible mechanisms by which these variants alter autoimmune disease risk.

genetics↗

bioRxiv2024

Sciphy: A Bayesian phylogenetic framework using sequential genetic lineage tracing data.

CRISPR-based lineage tracing offers a promising avenue to decipher single cell lineage trees, especially in organisms that are challenging for microscopy. A recent advancement in this domain is lineage tracing based on sequential genome editing, which not only records genetic edits but also the order in which they occur. To capitalize on this enriched data, we introduce SciPhy, a simulation and inference tool integrated within the BEAST 2 framework. SciPhy utilizes a Bayesian phylogenetic approach to estimate time-scaled phylogenies and cell population parameters. After validating SciPhy using simulations, we apply it to two lineage tracing datasets for which we estimate time-scaled trees together with cell proliferation rates. Using simulated and real lineage tracing data obtained from a monoclonal culture of HEK293T cells, we compare SciPhy to other lineage reconstruction methods, and find that SciPhy consistently constructs distinct, and more accurate lineage trees. In particular, for HEK293T cells, SciPhy trees stand out for their later estimated cell division times. In addition, SciPhy reports uncertainty as well as proliferation rates, neither of which are available within a UPGMA analysis. Our second example applies SciPhy to the study of murine gastruloids, and showcases the use of complex models of time-varying population growth to capture realistic aspects of this in-vitro model of early mammalian development. Together, these examples showcase the application of advanced phylogenetic and phylodynamic tools to explore and quantify cell lineage trees, laying the groundwork for enhanced and confident analyses to decode the complexities of biological development in multicellular organisms. SciPhys codebase is publicly available at https://github.com/azwaans/SciPhy.

developmental biology↗

bioRxiv2024

Diversified, miniaturized and ancestral parts for mammalian genome engineering and molecular recording

As the synthetic biology and genome engineering fields mature and converge, there is a clear need for a "parts list" of components that are diversified with respect to both functional activity (to facilitate design) and primary sequence (to facilitate assembly). Here we designed libraries composed of extant, ancestral, mutagenized or miniaturized variants of Pol III promoters or guide RNA (gRNA) scaffolds and quantified their ability to mediate precise edits to the mammalian genome via multiplex prime editing. We identified thousands of parts that reproducibly drive a range of editing activities in human and mouse stem cells and cancer cell lines, including hundreds exhibiting similar or greater activity than the sequences used in conventional genome engineering constructs. We further conducted saturation mutagenesis screens of canonical Pol III promoters (U6p, 7SKp, H1p) and the prime editing guide RNA (pegRNA) scaffold, which identified tolerated variants that can be superimposed on baseline parts to further enhance sequence diversity. While characterizing thousands of orthologous promoters from hundreds of extant or ancestral genomes, we incidentally mapped the functional landscape of mammalian Pol III promoter evolution. Finally, to showcase the usefulness of these parts, we designed a "ten key" molecular recording array that lacks repetitive subsequences in order to facilitate its one-step assembly in yeast. Upon delivering this 15.8 kb tandem array of promoters and guides to mammalian cells, individual pegRNAs exhibited balanced activities as predicted by the activity of component parts, despite their relocation to a single locus. Looking forward, we anticipate that the diversified parts and variant effect maps reported here can be leveraged for the design, assembly and deployment of synthetic loci encoding arrays of gRNAs exhibiting predictable, differentiated levels of activity, which will be useful for multiplex perturbation, advanced biological recorders and complex genetic circuits.

synthetic biology↗

bioRxiv2024

Leukemia-derived apelin selects endothelial niche clones to promote tumorigenesis

Hematopoietic stem cells are regulated by endothelial and mesenchymal stromal cells in the marrow niche1-3. Leukemogenesis was long believed to be solely driven by genetic perturbations in hematopoietic cells but introduction of genetic mutations in the microenvironment demonstrated the ability of niche cells to drive disease progression4-8. The mechanisms by which the stem cell niche induces leukemia remain poorly understood. Here, using cellular barcoding in zebrafish, we found that clones of niche endothelial and stromal cells are significantly expanded in leukemic marrows. The pro-angiogenic peptide apelin secreted by leukemic cells induced sinusoidal endothelial cell clonal selection and transcriptional reprogramming towards an angiogenic state to promote leukemogenesis in vivo. Overexpression of apelin in normal hematopoietic stem cells led to clonal amplification of the niche endothelial cells and promotes clonal dominance of blood cells. Knock-out of apelin in leukemic zebrafish resulted in a significant reduction in disease progression. Our results demonstrate that leukemic cells remodel the clonal and transcriptional landscape of the marrow niche to promote leukemogenesis and provide a potential therapeutic opportunity for anti-apelin treatment.

cancer biology↗

bioRxiv2024

The proteomic landscape and temporal dynamics of mammalian gastruloid development

Gastrulation is the process by which the early embryo establishes a body plan and primes itself for organogenesis. As gastrulation is challenging to study in vivo, stem cell-derived "gastruloids" have emerged as powerful surrogates. Although transcriptomics and imaging have been applied extensively to such embryo models, the dynamics of their proteomes remains largely unknown. Here, we apply quantitative proteomics to human and mouse gastruloids at four key stages. We leverage these data to map the expression dynamics of protein complexes, and to nominate cooperative proteins. With matched transcriptome and phosphosite data, we investigate global and stage/pathway-specific discordance between the transcriptome and proteome and nominate kinase-substrate relationships based on phosphosite dynamics. Finally, we apply co-regulation network analysis to identify genes linked to the Commander complex whose perturbation leads to morphological defects in gastruloids. Altogether, our work showcases the potential of applying proteomics to embryo models to advance our understanding of mammalian development in ways challenging through transcriptomics alone.

systems biology↗

bioRxiv2024

Optics-free reconstruction of 2D images via DNA barcode proximity graphs

Spatial genomics technologies include imaging- and sequencing-based methods. Sequencing-based spatial methods typically require surfaces coated with coordinate-associated DNA barcodes, but the physical registration of these barcodes to spatial coordinates is challenging, necessitating either high density printing of oligonucleotides or in situ sequencing/probing of randomly deposited, DNA-barcode-bearing beads. As a consequence, the surface areas available to sequencing-based spatial genomic methods are constrained by the time, labor, cost and instrumentation required to either print or decode a coordinate-tagged surface. To address this challenge, we developed SCOPE (Spatial reConstruction via Oligonucleotide Proximity Encoding), an optics-free, DNA microscopy-inspired method. With SCOPE, the relative positions of DNA-barcoded beads within a 2D shape, 2D image or 3D volume are inferred from the ex situ sequencing of chimeric molecules formed from diffusing "sender" and tethered "receiver" oligonucleotides. To demonstrate the potential of this approach, we applied SCOPE to reconstruct 2D shapes, 2D images or 3D volumes defined by 104-106 x 20-100 {micro}m DNA barcoded beads, including an asymmetric "swoosh" resembling the Nike logo (44 mm2), a "color" Snellen eye chart (704 mm2) and the surface topology of 3D molds of a teddy bear, star, butterfly or block letter (75-100 mm3). Each of the resulting "DNA barcode proximity graphs" was computationally reconstructed in an automated fashion, across fields of view and at resolutions that were determined by sequencing depth, bead size and diffusion kinetics, rather than by microarray or microscope instrument time. Because the ground truth shapes are known, these datasets may be particularly useful for the further development of computational algorithms by this nascent field.

genomics↗

bioRxiv2024

Multi-condition and multi-modal temporal profile inference during mouse embryonic development

The emergence of single-cell time-series datasets enables modeling of changes in various types of cellular profiles over time. However, due to the disruptive nature of single-cell measurements, it is impossible to capture the full temporal trajectory of a particular cell. Furthermore, single-cell profiles can be collected at mismatched time points across different conditions (e.g., sex, batch, disease) and data modalities (e.g., scRNA-seq, scATAC-seq), which makes modeling challenging. Here we propose a joint modeling framework, Sunbear, for integrating multi-condition and multi-modal single-cell profiles across time. Sunbear can be used to impute single-cell temporal profile changes, align multi-dataset and multi-modal profiles across time, and extrapolate single-cell profiles in a missing modality. We applied Sunbear to reveal sex-biased transcription during mouse embryonic development and predict dynamic relationships between epigenetic priming and transcription for cells in which multi-modal profiles are unavailable. Sunbear thus enables the projection of single-cell time-series snapshots to multi-modal and multi-condition views of cellular trajectories.

bioinformatics↗

bioRxiv2024

Meningioma transcriptomic landscape demonstrates novel subtypes with regional associated biology and patient outcome.

Meningiomas, the most common intracranial tumor, though mostly benign can be recurrent and fatal. WHO grading does not always identify high risk meningioma and better characterizations of their aggressive biology is needed. To approach this problem, we combined 13 bulk RNA-Seq datasets to create a dimension-reduced reference landscape of 1298 meningiomas. Clinical and genomic metadata effectively correlated with landscape regions which led to the identification of meningioma subtypes with specific biological signatures. Time to recurrence also correlated with the map location. Further, we developed an algorithm that maps new patients onto this landscape where nearest neighbors predict outcome. This study highlights the utility of combining bulk transcriptomic datasets to visualize the complexity of tumor populations. Further, we provide an interactive tool for understanding the disease and predicting patient outcome. This resource is accessible via the online tool Oncoscape, where the scientific community can explore the meningioma landscape.

cancer biology↗

bioRxiv2024

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.

developmental biology↗

bioRxiv2024

Multiplex generation and single cell analysis of structural variants in a mammalian genome

The functional consequences of structural variants (SVs) in mammalian genomes are challenging to study. This is due to several factors, including: 1) their numerical paucity relative to other forms of standing genetic variation such as single nucleotide variants (SNVs) and short insertions or deletions (indels); 2) the fact that a single SV can involve and potentially impact the function of more than one gene and/or cis regulatory element; and 3) the relative immaturity of methods to generate and map SVs, either randomly or in targeted fashion, in in vitro or in vivo model systems. Towards addressing these challenges, we developed Genome-Shuffle-seq, a straightforward method that enables the multiplex generation and mapping of several major forms of SVs (deletions, inversions, translocations) throughout a mammalian genome. Genome-Shuffle-seq is based on the integration of "shuffle cassettes to the genome, wherein each shuffle cassette contains components that facilitate its site-specific recombination (SSR) with other integrated shuffle cassettes (via Cre-loxP), its mapping to a specific genomic location (via T7-mediated in vitro transcription or IVT), and its identification in single-cell RNA-seq (scRNA-seq) data (via T7-mediated in situ transcription or IST). In this proof-of-concept, we apply Genome-Shuffle-seq to induce and map thousands of genomic SVs in mouse embryonic stem cells (mESCs) in a single experiment. Induced SVs are rapidly depleted from the cellular population over time, possibly due to Cre-mediated toxicity and/or negative selection on the rearrangements themselves. Leveraging T7 IST of barcodes whose positions are already mapped, we further demonstrate that we can efficiently genotype which SVs are present in association with each of many single cell transcriptomes in scRNA-seq data. Finally, preliminary evidence suggests our method may be a powerful means of generating extrachromosomal circular DNAs (ecDNAs). Looking forward, we anticipate that Genome-Shuffle-seq may be broadly useful for the systematic exploration of the functional consequences of SVs on gene expression, the chromatin landscape, and 3D nuclear architecture. We further anticipate potential uses for in vitro modeling of ecDNAs, as well as in paving the path to a minimal mammalian genome.

genomics↗

bioRxiv2023

Cross-species imputation and comparison of single-cell transcriptomic profiles

Cross-species comparison and prediction of gene expression profiles are important to understand regulatory changes during evolution and to transfer knowledge learned from model organisms to humans. Single-cell RNA-seq (scRNA-seq) profiles enable us to capture gene expression profiles with respect to variations among individual cells; however, cross-species comparison of scRNA-seq profiles is challenging because of data sparsity, batch effects, and the lack of one-to-one cell matching across species. Moreover, single-cell profiles are challenging to obtain in certain biological contexts, limiting the scope of hypothesis generation. Here we developed Icebear, a neural network framework that decomposes single-cell measurements into factors representing cell identity, species, and batch factors. Icebear enables accurate prediction of single-cell gene expression profiles across species, thereby providing high-resolution cell type and disease profiles in under-characterized contexts. Icebear also facilitates direct cross-species comparison of single-cell expression profiles for conserved genes that are located on the X chromosome in eutherian mammals but on autosomes in chicken. This comparison, for the first time, revealed evolutionary and diverse adaptations of X-chromosome upregulation in mammals.

bioinformatics↗

bioRxiv2023

A molecular proximity sensor based on an engineered, dual-component guide RNA

One of the goals of synthetic biology is to enable the design of arbitrary molecular circuits with programmable inputs and outputs. Such circuits bridge the properties of electronic and natural circuits, processing information in a predictable manner within living cells. Genome editing is a potentially powerful component of synthetic molecular circuits, whether for modulating the expression of a target gene or for stably recording information to genomic DNA. However, programming molecular events such as protein-protein interactions or induced proximity as triggers for genome editing remains challenging. Here we demonstrate a strategy termed "P3 editing", which links protein-protein proximity to the formation of a functional CRISPR-Cas9 dual-component guide RNA. By engineering the crRNA:tracrRNA interaction, we demonstrate that various known protein-protein interactions, as well as the chemically-induced dimerization of protein domains, can be used to activate prime editing or base editing in human cells. Additionally, we explore how P3 editing can incorporate outputs from ADAR-based RNA sensors, potentially allowing specific RNAs to induce specific genome edits within a larger circuit. Our strategy enhances the controllability of CRISPR-based genome editing, facilitating its use in synthetic molecular circuits deployed in living cells.

synthetic biology↗

bioRxiv2023

A multiplex, prime editing framework for identifying drug resistance variants at scale

CRISPR-based genome editing has revolutionized functional genomics, enabling screens in which thousands of perturbations of either gene expression or primary genome sequence can be competitively assayed in single experiments. However, for libraries of specific mutations, a challenge of CRISPR-based screening methods such as saturation genome editing is that only one region (e.g. one exon) can be studied per experiment. Here we describe prime-SGE ("prime saturation genome editing"), a new framework based on prime editing, in which libraries of specific mutations can be installed into genes throughout the genome and functionally assessed in a single, multiplex experiment. Prime-SGE is based on quantifying the abundance of prime editing guide RNAs (pegRNAs) in the context of a functional selection, rather than quantifying the mutations themselves. We apply prime-SGE to assay thousands of single nucleotide changes in eight oncogenes for their ability to confer drug resistance to three EGFR tyrosine kinase inhibitors. Although currently restricted to positive selection screens by the limited efficiency of prime editing, our strategy opens the door to the possibility of functionally assaying vast numbers of precise mutations at locations throughout the genome.

genomics↗

bioRxiv2023

Transgene directed induction of a stem cell-derived human embryo model

The human embryo undergoes morphogenetic transformations following implantation into the uterus, yet our knowledge of this crucial stage is limited by the inability to observe the embryo in vivo. Stem cell-derived models of the embryo are important tools to interrogate developmental events and tissue-tissue crosstalk during these stages1. Here, we establish a human post-implantation embryo model comprised of embryonic and extraembryonic tissues. We combine two types of extraembryonic-like cells generated by transcription factor overexpression with wildtype embryonic stem cells and promote their self-organization into structures that mimic aspects of the post-implantation human embryo. These self-organized aggregates contain a pluripotent epiblast-like domain surrounded by hypoblast-and trophoblast-like tissues. We demonstrate that these inducible human embryoids robustly generate several cell types, including amnion, extraembryonic mesenchyme, and primordial germ cell-like cells in response to BMP signaling. This model also allowed us to identify an inhibitory role for SOX17 in the specification of anterior hypoblast-like cells2. Modulation of the subpopulations in the hypoblast-like compartment demonstrated that extraembryonic-like cells impact epiblast-like domain differentiation, highlighting functional tissue-tissue crosstalk. In conclusion, we present a modular, tractable, integrated3 model of the human embryo that will allow us to probe key questions of human post-implantation development, a critical window when significant numbers of pregnancies fail.

developmental biology↗

bioRxiv2023

CTCF-mediated insulation and chromatin environment modulate Car5b escape from X inactivation

BackgroundThe number and escape levels of genes that escape X chromosome inactivation (XCI) in female somatic cells vary among tissues and cell types, potentially contributing to specific sex differences. Here we investigate the role of CTCF, a master chromatin conformation regulator, in regulating escape from XCI. CTCF binding profiles and epigenetic features were systematically examined at constitutive and facultative escape genes using mouse allelic systems to distinguish the inactive X (Xi) and active X (Xa) chromosomes. ResultsWe found that escape genes are located inside domains flanked by convergent arrays of CTCF binding sites, consistent with the formation of loops. In addition, strong and divergent CTCF binding sites often located at the boundaries between escape genes and adjacent neighbors subject to XCI would help insulate domains. Facultative escapees show clear differences in CTCF binding dependent on their XCI status in specific cell types/tissues. Concordantly, deletion but not inversion of a CTCF binding site at the boundary between the facultative escape gene Car5b and its silent neighbor Siah1b resulted in loss of Car5b escape. Reduced CTCF binding and enrichment of a repressive mark over Car5b in cells with a boundary deletion indicated loss of looping and insulation. In mutant lines in which either the Xi-specific compact structure or its H3K27me3 enrichment was disrupted, escape genes showed an increase in gene expression and associated active marks, supporting the roles of the 3D Xi structure and heterochromatic marks in constraining levels of escape. ConclusionOur findings indicate that escape from XCI is modulated both by looping and insulation of chromatin via convergent arrays of CTCF binding sites and by compaction and epigenetic features of the surrounding heterochromatin.

genomics↗