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.

中文翻译：

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系统遗传学和单细胞成像揭示了广泛的形态多效性和细胞间变异。

由于缺乏对单细胞水平表型的详细了解，我们理解基因型与表型关系的能力受到阻碍。为了系统地评估细胞间的表型变异性，我们结合了自动化酵母遗传学、高内涵筛选和基于神经网络的单细胞图像分析，重点关注影响内吞途径四个亚细胞区室结构的基因作为模型系统。我们对这些区室（内吞斑、肌动蛋白斑、晚期内体和液泡）的形态进行公正的评估，鉴定出与约 1,600 个基因（约占所有酵母基因的 30%）相关的 17 种不同的突变表型。这些突变体中大约一半表现出多种表型，突出了形态多效性的程度。定量分析还表明，不完全外显率很普遍，大多数突变体在单细胞水平上表现出显着的表型变异。我们的单细胞分析能够探索导致不完全外显率和细胞异质性的因素，包括复制年龄、细胞器遗传和对压力的反应。