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

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...

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Autores principales: Mattiazzi Usaj, Mojca, Sahin, Nil, Friesen, Helena, Pons, Carles, Usaj, Matej, Masinas, Myra Paz D, Shuteriqi, Ermira, Shkurin, Aleksei, Aloy, Patrick, Morris, Quaid, Boone, Charles, Andrews, Brenda J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7025093/
https://www.ncbi.nlm.nih.gov/pubmed/32064787
http://dx.doi.org/10.15252/msb.20199243
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author Mattiazzi Usaj, Mojca
Sahin, Nil
Friesen, Helena
Pons, Carles
Usaj, Matej
Masinas, Myra Paz D
Shuteriqi, Ermira
Shkurin, Aleksei
Aloy, Patrick
Morris, Quaid
Boone, Charles
Andrews, Brenda J
author_facet Mattiazzi Usaj, Mojca
Sahin, Nil
Friesen, Helena
Pons, Carles
Usaj, Matej
Masinas, Myra Paz D
Shuteriqi, Ermira
Shkurin, Aleksei
Aloy, Patrick
Morris, Quaid
Boone, Charles
Andrews, Brenda J
author_sort Mattiazzi Usaj, Mojca
collection PubMed
description 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.
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spelling pubmed-70250932020-02-21 Systematic genetics and single‐cell imaging reveal widespread morphological pleiotropy and cell‐to‐cell variability Mattiazzi Usaj, Mojca Sahin, Nil Friesen, Helena Pons, Carles Usaj, Matej Masinas, Myra Paz D Shuteriqi, Ermira Shkurin, Aleksei Aloy, Patrick Morris, Quaid Boone, Charles Andrews, Brenda J Mol Syst Biol Articles 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. John Wiley and Sons Inc. 2020-02-17 /pmc/articles/PMC7025093/ /pubmed/32064787 http://dx.doi.org/10.15252/msb.20199243 Text en © 2020 The Authors. Published under the terms of the CC BY 4.0 license This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Mattiazzi Usaj, Mojca
Sahin, Nil
Friesen, Helena
Pons, Carles
Usaj, Matej
Masinas, Myra Paz D
Shuteriqi, Ermira
Shkurin, Aleksei
Aloy, Patrick
Morris, Quaid
Boone, Charles
Andrews, Brenda J
Systematic genetics and single‐cell imaging reveal widespread morphological pleiotropy and cell‐to‐cell variability
title Systematic genetics and single‐cell imaging reveal widespread morphological pleiotropy and cell‐to‐cell variability
title_full Systematic genetics and single‐cell imaging reveal widespread morphological pleiotropy and cell‐to‐cell variability
title_fullStr Systematic genetics and single‐cell imaging reveal widespread morphological pleiotropy and cell‐to‐cell variability
title_full_unstemmed Systematic genetics and single‐cell imaging reveal widespread morphological pleiotropy and cell‐to‐cell variability
title_short Systematic genetics and single‐cell imaging reveal widespread morphological pleiotropy and cell‐to‐cell variability
title_sort systematic genetics and single‐cell imaging reveal widespread morphological pleiotropy and cell‐to‐cell variability
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7025093/
https://www.ncbi.nlm.nih.gov/pubmed/32064787
http://dx.doi.org/10.15252/msb.20199243
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