31 research outputs found

    Systematic genetics and single‐cell imaging reveal widespread morphological pleiotropy and cell‐to‐cell variability

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    Abstract Our ability to understand the genotype‐to‐phenotype relationship is hindered by the lack of detailed understanding of phenotypes at a single‐cell level. To systematically assess cell‐to‐cell phenotypic variability, we combined automated yeast genetics, high‐content screening and neural network‐based image analysis of single cells, focussing on genes that influence the architecture of four subcellular compartments of the endocytic pathway as a model system. Our unbiased assessment of the morphology of these compartments—endocytic patch, actin patch, late endosome and vacuole—identified 17 distinct mutant phenotypes associated with ~1,600 genes (~30% of all yeast genes). Approximately half of these mutants exhibited multiple phenotypes, highlighting the extent of morphological pleiotropy. Quantitative analysis also revealed that incomplete penetrance was prevalent, with the majority of mutants exhibiting substantial variability in phenotype at the single‐cell level. Our single‐cell analysis enabled exploration of factors that contribute to incomplete penetrance and cellular heterogeneity, including replicative age, organelle inheritance and response to stress

    TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network

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    Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae. In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner

    A cohesin traffic pattern genetically linked to gene regulation [preprint]

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    Cohesin-mediated loop extrusion folds interphase chromosomes at the ten to hundreds kilobases scale. This process produces structural features such as loops and topologically associating domains. We identify three types of cis-elements that define the chromatin folding landscape generated by loop extrusion. First, CTCF sites form boundaries by stalling extruding cohesin, as shown before. Second, transcription termination sites form boundaries by acting as cohesin unloading sites. RNA polymerase II contributes to boundary formation at transcription termination sites. Third, transcription start sites form boundaries that are mostly independent of cohesin, but are sites where cohesin can pause. Together with cohesin loading at enhancers, and possibly other cis-elements, these loci create a dynamic pattern of cohesin traffic along the genome that guides enhancer-promoter interactions. Disturbing this traffic pattern, by removing CTCF barriers, renders cells sensitive to knock-out of genes involved in transcription initiation, such as the SAGA and TFIID complexes, and RNA processing such DEAD-Box RNA helicases. In the absence of CTCF, several of these factors fail to be efficiently recruited to active promoters. We propose that the complex pattern of cohesin movement along chromatin contributes to appropriate promoter-enhancer interactions and localization of transcription and RNA processing factors to active genes

    Essential Gene Profiles for Human Pluripotent Stem Cells Identify Uncharacterized Genes and Substrate Dependencies

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    Summary: Human pluripotent stem cells (hPSCs) provide an invaluable tool for modeling diseases and hold promise for regenerative medicine. For understanding pluripotency and lineage differentiation mechanisms, a critical first step involves systematically cataloging essential genes (EGs) that are indispensable for hPSC fitness, defined as cell reproduction in this study. To map essential genetic determinants of hPSC fitness, we performed genome-scale loss-of-function screens in an inducible Cas9 H1 hPSC line cultured on feeder cells and laminin to identify EGs. Among these, we found FOXH1 and VENTX, genes that encode transcription factors previously implicated in stem cell biology, as well as an uncharacterized gene, C22orf43/DRICH1. hPSC EGs are substantially different from other human model cell lines, and EGs in hPSCs are highly context dependent with respect to different growth substrates. Our CRISPR screens establish parameters for genome-wide screens in hPSCs, which will facilitate the characterization of unappreciated genetic regulators of hPSC biology. : Mair et al. establish a robust, inducible CRISPR screening platform for forward genetics in human pluripotent stem cells (hPSCs). Genome-wide proliferation screens identified core essential genes for hPSCs and revealed context-dependent genetic requirements on different substrates. This underlines hPSC plasticity and helps us to understand the genetic wiring of hPSCs. Keywords: human pluripotent stem cells, genome-wide CRISPR screen, functional genomics, essential genes, DRICH

    Data from: Systematic analysis of complex genetic interactions

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    To systematically explore complex genetic interactions, we constructed ~200,000 yeast triple mutants and scored negative trigenic interactions. We selected double-mutant query genes across a broad spectrum of biological processes, spanning a range of quantitative features of the global digenic interaction network and tested for a genetic interaction with a third mutation. Trigenic interactions often occurred among functionally related genes, and essential genes were hubs on the trigenic network. Despite their functional enrichment, trigenic interactions tended to link genes in distant bioprocesses and displayed a weaker magnitude than digenic interactions. We estimate that the global trigenic interaction network is ~100 times as large as the global digenic network, highlighting the potential for complex genetic interactions to affect the biology of inheritance, including the genotype-to-phenotype relationship
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