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      High-throughput gene screen reveals modulators of nuclear shape

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          Abstract

          Using a high-throughput RNAi screen of epigenetic regulators combined with an automated elliptical Fourier analysis, we identify genes required for the maintenance of nuclear shape in breast epithelial cells.

          Abstract

          Irregular nuclear shapes characterized by blebs, lobules, micronuclei, or invaginations are hallmarks of many cancers and human pathologies. Despite the correlation between abnormal nuclear shape and human pathologies, the mechanism by which the cancer nucleus becomes misshapen is not fully understood. Motivated by recent evidence that modifying chromatin condensation can change nuclear morphology, we conducted a high-throughput RNAi screen to identify epigenetic regulators that are required to maintain normal nuclear shape in human breast epithelial MCF-10A cells. We silenced 608 genes in parallel using an epigenetics siRNA library and used an unbiased Fourier analysis approach to quantify nuclear contour irregularity from fluorescent images captured on a high-content microscope. Using this quantitative approach, which we validated with confocal microscopy, we significantly expand the list of epigenetic regulators that impact nuclear morphology.

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          Most cited references43

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          Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

          The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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            Scoring diverse cellular morphologies in image-based screens with iterative feedback and machine learning.

            Many biological pathways were first uncovered by identifying mutants with visible phenotypes and by scoring every sample in a screen via tedious and subjective visual inspection. Now, automated image analysis can effectively score many phenotypes. In practical application, customizing an image-analysis algorithm or finding a sufficient number of example cells to train a machine learning algorithm can be infeasible, particularly when positive control samples are not available and the phenotype of interest is rare. Here we present a supervised machine learning approach that uses iterative feedback to readily score multiple subtle and complex morphological phenotypes in high-throughput, image-based screens. First, automated cytological profiling extracts hundreds of numerical descriptors for every cell in every image. Next, the researcher generates a rule (i.e., classifier) to recognize cells with a phenotype of interest during a short, interactive training session using iterative feedback. Finally, all of the cells in the experiment are automatically classified and each sample is scored based on the presence of cells displaying the phenotype. By using this approach, we successfully scored images in RNA interference screens in 2 organisms for the prevalence of 15 diverse cellular morphologies, some of which were previously intractable.
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              • Record: found
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              Is Open Access

              Chromatin histone modifications and rigidity affect nuclear morphology independent of lamins

              Chromatin decompaction via increasing euchromatin or decreasing heterochromatin results in a softer nucleus and abnormal nuclear blebbing, independent of lamin perturbations. Conversely, increasing heterochromatin stiffens the nucleus and rescues nuclear morphology in lamin-perturbed cells that present abnormal nuclear morphology.
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                Author and article information

                Journal
                Molecular Biology of the Cell
                MBoC
                American Society for Cell Biology (ASCB)
                1059-1524
                1939-4586
                June 15 2020
                June 15 2020
                : 31
                : 13
                : 1392-1402
                Affiliations
                [1 ]Department of Chemical Engineering and
                [2 ]Department of Medicinal Chemistry and Center for Natural Products, Drug Discovery and Development (CNPD3), University of Florida, Gainesville, FL 32610
                [3 ]Biology Department, University of Massachusetts Amherst, Amherst, MA 01003
                [4 ]Division of Hematology/Oncology, University of Florida Health Cancer Center, Gainesville, FL 32610
                Article
                10.1091/mbc.E19-09-0520
                314188f3-acaf-44cd-aecd-acf9931e1c42
                © 2020
                History

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