Predicting the mutations generated by repair of Cas9-induced double-strand breaks.

The DNA mutation produced by cellular repair of a CRISPR-Cas9-generated double-strand break determines its phenotypic effect. It is known that the mutational outcomes are not random, but depend on DNA sequence at the targeted location. Here we systematically study the influence of flanking DNA sequence on repair outcome by measuring the edits generated by >40,000 guide RNAs (gRNAs) in synthetic constructs. We performed the experiments in a range of genetic backgrounds and using alternative CRISPR-Cas9 reagents. In total, we gathered data for >109 mutational outcomes. The majority of reproducible mutations are insertions of a single base, short deletions or longer microhomology-mediated deletions. Each gRNA has an individual cell-line-dependent bias toward particular outcomes. We uncover sequence determinants of the mutations produced and use these to derive a predictor of Cas9 editing outcomes. Improved understanding of sequence repair will allow better design of gene editing experiments

A spatially resolved atlas of the human lung characterizes a gland-associated immune niche

Single-cell transcriptomics has allowed unprecedented resolution of cell types/states in the human lung, but their spatial context is less well defined. To (re)define tissue architecture of lung and airways, we profiled five proximal-to-distal locations of healthy human lungs in depth using multi-omic single cell/nuclei and spatial transcriptomics (queryable at lungcellatlas.org ). Using computational data integration and analysis, we extend beyond the suspension cell paradigm and discover macro and micro-anatomical tissue compartments including previously unannotated cell types in the epithelial, vascular, stromal and nerve bundle micro-environments. We identify and implicate peribronchial fibroblasts in lung disease. Importantly, we discover and validate a survival niche for IgA plasma cells in the airway submucosal glands (SMG). We show that gland epithelial cells recruit B cells and IgA plasma cells, and promote longevity and antibody secretion locally through expression of CCL28, APRIL and IL-6. This new 'gland-associated immune niche' has implications for respiratory health

Cells of the human intestinal tract mapped across space and time

Acknowledgements We acknowledge support from the Wellcome Sanger Cytometry Core Facility, Cellular Genetics Informatics team, Cellular Generation and Phenotyping (CGaP) and Core DNA Pipelines. This work was financially supported by the Wellcome Trust (W1T20694, S.A.T.; 203151/Z/16/Z, R. A. Barker.); the European Research Council (646794, ThDefine, S.A.T.); an MRC New Investigator Research Grant (MR/T001917/1, M.Z.); and a project grant from the Great Ormond Street Hospital Children’s Charity, Sparks (V4519, M.Z.). The human embryonic and fetal material was provided by the Joint MRC/Wellcome (MR/R006237/1) Human Developmental Biology Resource (https://www.hdbr.org/). K.R.J. holds a Non-Stipendiary Junior Research Fellowship from Christ’s College, University of Cambridge. M.R.C. is supported by a Medical Research Council Human Cell Atlas Research Grant (MR/S035842/1) and a Wellcome Trust Investigator Award (220268/Z/20/Z). H.W.K. is funded by a Sir Henry Wellcome Fellowship (213555/Z/18/Z). A.F. is funded by a Wellcome PhD Studentship (102163/B/13/Z). K.T.M. is funded by an award from the Chan Zuckerberg Initiative. H.H.U. is supported by the Oxford Biomedical Research Centre (BRC) and the The Leona M. and Harry B. Helmsley Charitable Trust. We thank A. Chakravarti and S. Chatterjee for their contribution to the analysis of the enteric nervous system. We also thank R. Lindeboom and C. Talavera-Lopez for support with epithelium and Visium analysis, respectively; C. Tudor, T. Li and O. Tarkowska for image processing and infrastructure support; A. Wilbrey-Clark and T. Porter for support with Visium library preparation; A. Ross and J. Park for access to and handling of fetal tissue; A. Hunter for assistance in protocol development; D. Fitzpatrick for discussion on developmental intestinal disorders; and J. Eliasova for the graphical images. We thank the tissue donors and their families, and the Cambridge Biorepository for Translational Medicine and Human Developmental Biology Resource, for access to human tissue. This publication is part of the Human Cell Atlas: https://www.humancellatlas.org/publications.Peer reviewedPublisher PD

Cells of the human intestinal tract mapped across space and time.

Funder: Medical Research CouncilThe cellular landscape of the human intestinal tract is dynamic throughout life, developing in utero and changing in response to functional requirements and environmental exposures. Here, to comprehensively map cell lineages, we use single-cell RNA sequencing and antigen receptor analysis of almost half a million cells from up to 5 anatomical regions in the developing and up to 11 distinct anatomical regions in the healthy paediatric and adult human gut. This reveals the existence of transcriptionally distinct BEST4 epithelial cells throughout the human intestinal tract. Furthermore, we implicate IgG sensing as a function of intestinal tuft cells. We describe neural cell populations in the developing enteric nervous system, and predict cell-type-specific expression of genes associated with Hirschsprung's disease. Finally, using a systems approach, we identify key cell players that drive the formation of secondary lymphoid tissue in early human development. We show that these programs are adopted in inflammatory bowel disease to recruit and retain immune cells at the site of inflammation. This catalogue of intestinal cells will provide new insights into cellular programs in development, homeostasis and disease

Astrocyte layers in the mammalian cerebral cortex revealed by a single-cell in situ transcriptomic map.

Although the cerebral cortex is organized into six excitatory neuronal layers, it is unclear whether glial cells show distinct layering. In the present study, we developed a high-content pipeline, the large-area spatial transcriptomic (LaST) map, which can quantify single-cell gene expression in situ. Screening 46 candidate genes for astrocyte diversity across the mouse cortex, we identified superficial, mid and deep astrocyte identities in gradient layer patterns that were distinct from those of neurons. Astrocyte layer features, established in the early postnatal cortex, mostly persisted in adult mouse and human cortex. Single-cell RNA sequencing and spatial reconstruction analysis further confirmed the presence of astrocyte layers in the adult cortex. Satb2 and Reeler mutations that shifted neuronal post-mitotic development were sufficient to alter glial layering, indicating an instructive role for neuronal cues. Finally, astrocyte layer patterns diverged between mouse cortical regions. These findings indicate that excitatory neurons and astrocytes are organized into distinct lineage-associated laminae.The study was supported by the Paul G. Allen Foundation Distinguished Investigator Program (E.M.U. and D.H.R.), the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation (D.H.R., D.G. and G. C.), BRAIN initiative (1U01 MH105991 to D.G.) and National Institute of Health (1R01 MH109912 to D.G.; P01NS08351 to D.H.R.), National Institute of Health Research and the European Union Seventh Framework (to P.H.), NINDS Informatics Center for Neurogenetics and Neurogenomics (P30 NS062691 to G.C.), Wellcome Trust core support (M.H., O.A.B.), European Research Council (281961 to M.G.H.), Fonds Wetenschappelijk Onderzoek (G066715N and 1523014N to M.G.H.), Stichting Alzheimer Onderzoek (S#16025 to M.G.H.) and VIB Institutional Support and Tech Watch funding (to M.G.H.), Howard Hughes Medical Institute and the Wellcome Trust (to D.H.R.)

Probabilistic models to resolve cell identity and tissue architecture

Cell identity drives cell-cell communication and tissue architecture and is in return regulated by cell-extrinsic cues. Cell identity is determined by the combination of intrinsic developmentally established transcription factor use (TF) and constitutive as well as cell communication-dependent TF activities. In my thesis, I developed two probabilistic models that advance the understanding of these processes using single-cell and spatial genomic data. Spatial transcriptomic technologies promise to resolve cellular wiring diagrams of tissues in health and disease, but comprehensive mapping of cell types in situ remains a challenge. I present cell2location, a Bayesian model that can resolve fine-grained cell types in spatial transcriptomic data and create comprehensive cellular maps of diverse tissues. Cell2location accounts for technical sources of variation and borrows statistical strength across locations, thereby enabling the integration of single-cell and spatial transcriptomics with higher sensitivity and resolution than existing tools.We assess cell2location in three different tissues and demonstrate improved mapping of fine-grained cell types. In the mouse brain, we discover fine regional astrocyte subtypes across the thalamus and hypothalamus. In the human lymph node, we spatially map a rare pre-germinal centre B cell population. In the human gut, we resolve fine immune cell populations in lymphoid follicles. Collectively our results present cell2location as a versatile analysis tool for mapping tissue architectures in a comprehensive manner. Cell identity and plasticity is regulated by a combinatorial code mediated by transcription factors and the cell communication environment. Systematically dissecting how the regulatory code robustly defines the vast complexity of cell populations across tissues is a long-standing challenge. Measured using the assay for transposase-accessible chromatin with sequencing (ATAC-seq), DNA accessibility provides a readout of intermediate gene regulation steps at single-cell resolution, with technologies measuring both RNA and ATAC providing the necessary evidence to build mechanistic models of regulation. Existing methods address one or several subproblems of modelling DNA accessibility. For example, the DNA sequence-based deep learning models represent combinatorial interactions and in-vivo TF-DNA recognition preferences. In contrast, GRN models use TF abundance profiles across cells and in-vitro-derived TF-DNA recognition preferences, optionally incorporating ATAC-seq data as a filter. All models learn cell-type specific weights/properties and don't generalise to new TF abundance states such as new cell types. Therefore, we are missing an end-to-end mechanistic model that represents all steps of the biological process, that generalises to both new DNA sequences and TF abundance combinations and can simultaneously characterise hundreds to thousands of cell states observed in single-cell genomics atlases. Here, I formulated cell2state, a mechanistic end-to-end probabilistic model of TF recruitment to a chromatin locus and downstream TF effect on DNA accessibility. Cell2state is designed to achieve the generalisation of regulatory predictions to unseen cell types. Cell2state A) estimates TF nuclear protein abundance and models B) how TFs recognise DNA, C) how TF sites in DNA lead to TF recruitment to a chromatin locus, D) how the activity of DNA-associated TFs affects chromatin accessibility. To evaluate generalisation, I defined the computational problem and developed a workflow for predicting the scATAC-seq readout for previously unseen chromosomes and cell types. I show that cell2state outperforms the state-of-the-art deep learning models (ChromDragoNN) at explaining DNA accessibility differences across cells. Finally, to look at cell state plasticity, I developed ways to use cell2state to simulate the possible chromatin states given TF abundance of source cell types.Wellcome Sanger Institute 4-Year PhD scholarship

Use of viral motif mimicry improves the proteome-wide discovery of human linear motifs

Linear motifs have an integral role in dynamic cell functions, including cell signaling. However, due to their small size, low complexity, and frequent mutations, identifying novel functional motifs poses a challenge. Viruses rely extensively on the molecular mimicry of cellular linear motifs. In this study, we apply systematic motif prediction combined with functional filters to identify human linear motifs convergently evolved also in viral proteins. We observe an increase in the sensitivity of motif prediction and improved enrichment in known instances. We identify >7,300 non-redundant motif instances at various confidence levels, 99 of which are supported by all functional and structural filters. Overall, we provide a pipeline to improve the identification of functional linear motifs from interactomics datasets and a comprehensive catalog of putative human motifs that can contribute to our understanding of the human domain-linear motif code and the associated mechanisms of viral interference

Spatial genomics maps the structure, nature and evolution of cancer clones

Genome sequencing of cancers often reveals mosaics of different subclones present in the same tumour1,2,3. Although these are believed to arise according to the principles of somatic evolution, the exact spatial growth patterns and underlying mechanisms remain elusive4,5. Here, to address this need, we developed a workflow that generates detailed quantitative maps of genetic subclone composition across whole-tumour sections. These provide the basis for studying clonal growth patterns, and the histological characteristics, microanatomy and microenvironmental composition of each clone. The approach rests on whole-genome sequencing, followed by highly multiplexed base-specific in situ sequencing, single-cell resolved transcriptomics and dedicated algorithms to link these layers. Applying the base-specific in situ sequencing workflow to eight tissue sections from two multifocal primary breast cancers revealed intricate subclonal growth patterns that were validated by microdissection. In a case of ductal carcinoma in situ, polyclonal neoplastic expansions occurred at the macroscopic scale but segregated within microanatomical structures. Across the stages of ductal carcinoma in situ, invasive cancer and lymph node metastasis, subclone territories are shown to exhibit distinct transcriptional and histological features and cellular microenvironments. These results provide examples of the benefits afforded by spatial genomics for deciphering the mechanisms underlying cancer evolution and microenvironmental ecology

scverse/scvi-tools: scvi-tools 1.1.0-rc.1

<p>See the <a href="https://docs.scvi-tools.org/en/stable/release_notes/index.html">release notes</a> for all changes.</p> <p>This release is available via PyPi:</p> <pre><code>pip install scvi-tools </code></pre> <p>Conda availability will follow (< 2 days typically)</p> <p>Please report any issues on <a href="https://github.com/scverse/scvi-tools">GitHub</a>.</p&gt