High-dimensional phenotyping to define the genetic basis of cellular morphology.

Autor: Tegtmeyer M; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA.; Centre for Gene Therapy and Regenerative Medicine, King's College, London, UK., Arora J; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.; Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Asgari S; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.; Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.; Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Cimini BA; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Nadig A; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA., Peirent E; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Liyanage D; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Way GP; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Weisbart E; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Nathan A; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.; Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA., Amariuta T; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.; Halıcıoğlu Data Science Institute, University of California, La Jolla, CA, USA.; Department of Medicine, University of California, La Jolla, CA, USA., Eggan K; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA., Haghighi M; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., McCarroll SA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.; Department of Genetics, Harvard Medical School, Boston, MA, USA., O'Connor L; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA., Carpenter AE; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Singh S; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA. shsingh@broadinstitute.org., Nehme R; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA. rnehme@broadinstitute.org.; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA. rnehme@broadinstitute.org., Raychaudhuri S; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. soumya@broadinstitute.org.; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. soumya@broadinstitute.org.; Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. soumya@broadinstitute.org.; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. soumya@broadinstitute.org.; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. soumya@broadinstitute.org.; Centre for Genetics and Genomics Versus Arthritis, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK. soumya@broadinstitute.org.
Jazyk: angličtina
Zdroj: Nature communications [Nat Commun] 2024 Jan 06; Vol. 15 (1), pp. 347. Date of Electronic Publication: 2024 Jan 06.
DOI: 10.1038/s41467-023-44045-w
Abstrakt: The morphology of cells is dynamic and mediated by genetic and environmental factors. Characterizing how genetic variation impacts cell morphology can provide an important link between disease association and cellular function. Here, we combine genomic sequencing and high-content imaging approaches on iPSCs from 297 unique donors to investigate the relationship between genetic variants and cellular morphology to map what we term cell morphological quantitative trait loci (cmQTLs). We identify novel associations between rare protein altering variants in WASF2, TSPAN15, and PRLR with several morphological traits related to cell shape, nucleic granularity, and mitochondrial distribution. Knockdown of these genes by CRISPRi confirms their role in cell morphology. Analysis of common variants yields one significant association and nominate over 300 variants with suggestive evidence (P < 10 -6 ) of association with one or more morphology traits. We then use these data to make predictions about sample size requirements for increasing discovery in cellular genetic studies. We conclude that, similar to molecular phenotypes, morphological profiling can yield insight about the function of genes and variants.
(© 2024. The Author(s).)
Databáze: MEDLINE
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