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

Mol Syst Biol. 2020 Feb;16(2):e9243. doi: 10.15252/msb.20199243.


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.

Keywords: cell-to-cell variability; endocytosis; high-content screening; phenotype classification; single-cell analysis.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Genetic Pleiotropy
  • Genetic Variation
  • Microscopy, Fluorescence
  • Mutation*
  • Neural Networks, Computer
  • Penetrance
  • Phenotype
  • Saccharomyces cerevisiae / genetics
  • Saccharomyces cerevisiae / growth & development*
  • Saccharomyces cerevisiae Proteins / genetics*
  • Single-Cell Analysis / methods*
  • Systems Biology
  • Time-Lapse Imaging


  • Saccharomyces cerevisiae Proteins