Whi5 phosphorylation embedded in the G1/S network dynamically controls critical cell size and cell fate

Palumbo, Pasquale; Vanoni, Marco; Cusimano, Valerio; Busti, Stefano; Marano, Francesca; Manes, Costanzo; Alberghina, Lilia

doi:10.1038/ncomms11372

“…Only one of the unexpected INDELs, which CNVnator identified as a 1660 bp deletion in WHI5, differed between 1691 and 1693. Deletion of WHI5 has been previously shown to partially suppress the large cell phenotype seen in cln3 mutants [42][43][44] . It is, therefore, very likely that the unexpected wild-type-like phenotype observed for 1691 is due to suppression by a mutation in WHI5.…”

Section: Resultsmentioning

confidence: 99%

Challenges and opportunities for strain verification by whole-genome sequencing

Gallegos

¹

,

Häyrynen²,

Adames

³

et al. 2020

Sci Rep

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Laboratory strains, cell lines, and other genetic materials change hands frequently in the life sciences. Despite evidence that such materials are subject to mix-ups, contamination, and accumulation of secondary mutations, verification of strains and samples is not an established part of many experimental workflows. With the plummeting cost of next generation technologies, it is conceivable that whole genome sequencing (WGS) could be applied to routine strain and sample verification in the future. To demonstrate the need for strain validation by WGS, we sequenced haploid yeast segregants derived from a popular commercial mutant collection and identified several unexpected mutations. We determined that available bioinformatics tools may be ill-suited for verification and highlight the importance of finishing reference genomes for commonly used laboratory strains.

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“…Only one of the unexpected INDELs, which CNVnator identified as a 1660bp deletion in WHI5, differed between 1691 and 1693. WHI5, a G1 repressor, controls budding yeast cell size [42][43][44] . Deletion of WHI5 results in smaller cell-size upon entering S-phase, and has been previously shown to partially suppress the large cell phenotype seen in cln3 mutants 42 .…”

Section: Expected Indels Unexpected Indelsmentioning

confidence: 99%

Challenges and opportunities for strain verification by whole-genome sequencing

Gallegos

¹

,

Adames

²

,

Häyrynen³

et al. 2019

Preprint

View full text Add to dashboard Cite

Laboratory strains, cell lines, and other genetic materials change hands frequently in the life sciences. Despite evidence that such materials are subject to mix-ups, contamination, and accumulation of secondary mutations, verification of strains and samples is not an established part of many experimental workflows. With the plummeting cost of next generation technologies, it is conceivable that whole genome sequencing (WGS) could be applied to routine strain and sample verification in the future. To demonstrate the need for strain validation by WGS, we sequenced haploid yeast segregants derived from a popular commercial mutant collection and identified several unexpected mutations. We determined that available bioinformatics tools may be ill-suited for verification and highlight the importance of finishing reference genomes for commonly-used laboratory strains.

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“…2015; Palumbo et al. 2016). A basic challenge for models based on differential equations is the need to estimate many unknown kinetic constants that describe the reactions among the model's species.…”

Section: Introductionmentioning

confidence: 99%

Advances and challenges in logical modeling of cell cycle regulation: perspective for multi-scale, integrative yeast cell models

Barberis

¹

,

Todd

²

,

Zee

³

2016

FEMS Yeast Research

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The eukaryotic cell cycle is robustly designed, with interacting molecules organized within a definite topology that ensures temporal precision of its phase transitions. Its underlying dynamics are regulated by molecular switches, for which remarkable insights have been provided by genetic and molecular biology efforts. In a number of cases, this information has been made predictive, through computational models. These models have allowed for the identification of novel molecular mechanisms, later validated experimentally. Logical modeling represents one of the youngest approaches to address cell cycle regulation. We summarize the advances that this type of modeling has achieved to reproduce and predict cell cycle dynamics. Furthermore, we present the challenge that this type of modeling is now ready to tackle: its integration with intracellular networks, and its formalisms, to understand crosstalks underlying systems level properties, ultimate aim of multi-scale models. Specifically, we discuss and illustrate how such an integration may be realized, by integrating a minimal logical model of the cell cycle with a metabolic network.

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Whi5 phosphorylation embedded in the G1/S network dynamically controls critical cell size and cell fate

Cited by 36 publications

References 67 publications

Challenges and opportunities for strain verification by whole-genome sequencing

Challenges and opportunities for strain verification by whole-genome sequencing

Challenges and opportunities for strain verification by whole-genome sequencing

Advances and challenges in logical modeling of cell cycle regulation: perspective for multi-scale, integrative yeast cell models

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