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


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.

SUBMITTER: Mattiazzi Usaj M 

PROVIDER: S-EPMC7025093 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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

Mattiazzi Usaj Mojca M   Sahin Nil N   Friesen Helena H   Pons Carles C   Usaj Matej M   Masinas Myra Paz D MPD   Shuteriqi Ermira E   Shkurin Aleksei A   Aloy Patrick P   Morris Quaid Q   Boone Charles C   Andrews Brenda J BJ  

Molecular systems biology 20200201 2


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 morpholo  ...[more]

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