TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network

Ušaj, Matej; Tan, Yizhao; Wang, Wen; VanderSluis, Benjamin; Zou, A.; Myers, Chad L.; Costanzo, Michael; Andrews, Brenda; Boone, Charles

doi:10.1534/g3.117.040220

Cited by 120 publications

(134 citation statements)

References 24 publications

(59 reference statements)

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“…The spectrum of bioprocesses that are represented in genetic interaction profiles can be visualized by mapping functional enrichment within the context of the global yeast digenic interaction profile similarity network, which clusters genes into 17 distinct bioprocesses (7, 27) (Fig. 4A).…”

Section: Trigenic Interactions Expand Functional Connections Mapped Bmentioning

confidence: 99%

Systematic analysis of complex genetic interactions

Kuzmin

VanderSluis

Wang

et al. 2018

Science

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219

207

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To systematically explore complex genetic interactions, we constructed ~200,000 yeast triple mutants and scored negative trigenic interactions. We selected double mutant query genes across a broad spectrum of biological processes, spanning a range of quantitative features of the global digenic interaction network and tested for a genetic interaction with a third mutation. Trigenic interactions often occurred among functionally related genes and essential genes were hubs on the trigenic network. Despite their functional enrichment, trigenic interactions tended to link genes in distant bioprocesses and display a weaker magnitude than digenic interactions. We estimate that the global trigenic interaction network is ~100-fold larger than the global digenic network, highlighting the potential for complex genetic interactions to impact the biology of inheritance, including the genotype to phenotype relationship.

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Section: Trigenic Interactions Expand Functional Connections Mapped Bmentioning

confidence: 99%

Systematic analysis of complex genetic interactions

Kuzmin

VanderSluis

Wang

et al. 2018

Science

Self Cite

219

207

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“…We calculated Pearson's correlation for every pair of phenotype profiles as described above. Next, we grouped gene pairs by different functional criteria: (i) gene pairs that encoded members of the same protein complex or members of different protein complexes; (ii) gene pairs that encoded proteins in the same pathway or in different pathways; (iii) gene pairs that had significantly correlated genetic interaction profiles or not (PCC > 0.2, GI PCC dataset downloaded from thecellmap.org) (Costanzo et al , ; Usaj et al , ); and (iv) gene pairs that were co‐expressed or not. Functionally related gene pairs were defined as those that belong to the same protein complex or pathway, have a significant GI profile similarity, or are co‐expressed.…”

Section: Methodsmentioning

confidence: 99%

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

Ušaj

Sahin

Friesen

et al. 2020

Molecular Systems Biology

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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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“…This suggests that there are additional cellular responses that can take care of defects arising due to jjj1Δ, but are not part of the basal response to the deletion. We checked for the negative genetic interactors of jjj1Δ and found that one of the transcription factors responsible for oxidative stress response are among the top ten ( Figure 5B) (26,33). This led us to hypothesize, that a specific branch of oxidative response work in parallel with jjj1, upregulation of this pathway should lead to abrogation of the fitness defect of jjj1Δ.…”

Section: Cryptic Optimal Pathways Can Be Activated To Alleviate Pqc Dmentioning

confidence: 99%

Cellular responses to proteostasis perturbations reveal non-optimal feedback in chaperone networks

Ghosh

Gangadharan

Das

et al. 2017

Preprint

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Protein folding abnormalities are associated with the pathology of many diseases. This is surprising given the plethora of cellular machinery dedicated to aid protein folding. It is thought that cellular response to proteotoxicity is generally sufficient, but may be compromised during pathological conditions. We asked if, in a physiological condition, cells have the ability to re-program transcriptional outputs in accordance with proteostasis demands. We have used S. cerevisiae to understand the response of cells when challenged with different proteostasis impairments, by removing one protein quality control (PQC) gene from the system at a time. Using 14 PQC deletions, we investigated the transcriptional response and find the mutants were unable to upregulate pathways that could complement the function of the missing PQC gene. To our surprise, cells have inherently a limited scope of response that is not optimally tuned; with transcriptomic responses being decorrelated with respect to the sign of their epistasis. We conclude that this non-optimality in proteotoxic response may limit the cellular ability to reroute proteins through alternate and productive machineries resulting in pathological states. We posit that epistasis guided synthetic biology approaches may be helpful in realizing the true potential of the cellular chaperone machinery.

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TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network

Cited by 120 publications

References 24 publications

Systematic analysis of complex genetic interactions

Systematic analysis of complex genetic interactions

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

Cellular responses to proteostasis perturbations reveal non-optimal feedback in chaperone networks

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