ArticleMolecular systems biology2020
Systematic genetics and single-cell imaging reveal widespread morphological pleiotropy and cell-to-cell variability.
Article in Molecular systems biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
35 citing papers in PubMed, 62 citations in OpenAlex.
- Time-resolved functional genomics using deep learning reveals global hierarchical control of autophagy.Nature cell biology · 2026Article
- Morphological map of under- and overexpression of genes in human cells.Nature methods · 2025Article
- From whole bodies to single cells: A guide to transcriptomic approaches for ecology and evolutionary biology.Molecular ecology · 2025Review
- Fusion of microscopic and diffraction images with VGG net for budding yeast recognition in imaging flow cytometry.Scientific reports · 2025Article
- A single-cell resolved genotype-phenotype map using genome-wide genetic and environmental perturbations.Nature communications · 2025Article
- Systematic data analysis pipeline for quantitative morphological cell phenotyping.Computational and structural biotechnology journal · 2024Review
- Rapid mechanical phenotyping of breast cancer cells based on stochastic intracellular fluctuations.iScience · 2024Article
- Expanding TheCellVision.org: a central repository for visualizing and mining high-content cell imaging projects.Genetics · 2024Article
- PIFiA: self-supervised approach for protein functional annotation from single-cell imaging data.Molecular systems biology · 2024Article
- Application of unimodal probability distribution models for morphological phenotyping of budding yeast.FEMS yeast research · 2024Article
- QATS: an ImageJ plugin for the quantification of toroidal nuclei in biological images.Bioinformatics (Oxford, England) · 2024Article
- Using Dimensionality Reduction to Visualize Phenotypic Changes in High-Throughput Microscopy.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Surveying the global landscape of post-transcriptional regulators.Nature structural & molecular biology · 2023Article
- Global analysis of the yeast knockout phenome.Science advances · 2023Article
- A global genetic interaction network by single-cell imaging and machine learning.Cell systems · 2023Article
- Data-driven microscopy allows for automated context-specific acquisition of high-fidelity image data.Cell reports methods · 2023Article
- Article
- Fisheye transformation enhances deep-learning-based single-cell phenotyping by including cellular microenvironment.Cell reports methods · 2022Article
- BIONIC: biological network integration using convolutions.Nature methods · 2022Article
- Cryo-EM structures of Gid12-bound GID E3 reveal steric blockade as a mechanism inhibiting substrate ubiquitylation.Nature communications · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 4 institutions in 4 countries.
Funding
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.