Yeast as a Tool to Understand the Significance of Human Disease-Associated Gene Variants

Cervelli, Tiziana; Galli, Alvaro

doi:10.3390/genes12091303

Cited by 16 publications

(12 citation statements)

References 94 publications

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“…Our results are consistent with the common selection of model organisms for different disease groups. For example, zebrafish are widely used in models of cardiovascular disease ( Dahme et al, 2009 ; Prykhozhij and Berman, 2018 ; Narumanchi et al, 2021 ), and yeast is used as a model of metabolic disorders ( Cervelli and Galli, 2021 ). Interestingly, we did not identify model organisms besides the mouse for immune system or eye disease including that of the retina.…”

Section: Discussionmentioning

confidence: 99%

Contribution of model organism phenotypes to the computational identification of human disease genes

Alghamdi

Schofield

Hoehndorf

2022

Disease Models &Amp; Mechanisms

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Computing phenotypic similarity helps identify new disease genes and diagnose rare diseases. Genotype–phenotype data from orthologous genes in model organisms can compensate for lack of human data and increase genome coverage. In the past decade, cross-species phenotype comparisons have proven valuble, and several ontologies have been developed for this purpose. The relative contribution of different model organisms to computational identification of disease-associated genes is not fully explored. We used phenotype ontologies to semantically relate phenotypes resulting from loss-of-function mutations in model organisms to disease-associated phenotypes in humans. Semantic machine learning methods were used to measure the contribution of different model organisms to the identification of known human gene–disease associations. We found that mouse genotype–phenotype data provided the most important dataset in the identification of human disease genes by semantic similarity and machine learning over phenotype ontologies. Other model organisms' data did not improve identification over that obtained using the mouse alone, and therefore did not contribute significantly to this task. Our work impacts on the development of integrated phenotype ontologies, as well as for the use of model organism phenotypes in human genetic variant interpretation. This article has an associated First Person interview with the first author of the paper.

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Section: Discussionmentioning

confidence: 99%

Contribution of model organism phenotypes to the computational identification of human disease genes

Alghamdi

Schofield

Hoehndorf

2022

Disease Models &Amp; Mechanisms

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“…Yeast is a very reliable genetic system to evaluate the functional impact of disease-associated variants, and several assays, mostly based on protein biological functions, have been developed [ 31 , 32 ]. Here, we validated three assays, two HR assays and one GR assay, in two genetically-related yeast strains by testing 46 classified BRCA1 variants; furthermore, we tested these variants in the SCP assay that was statistically validated previously [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

Validation and Data-Integration of Yeast-Based Assays for Functional Classification of BRCA1 Missense Variants

Bellè

Mercatanti

Lodovichi

et al. 2022

IJMS

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Germline mutations in the BRCA1 gene have been reported to increase the lifetime risk of developing breast and/or ovarian cancer (BOC). By new sequencing technologies, numerous variants of uncertain significance (VUS) are identified. It is mandatory to develop new tools to evaluate their functional impact and pathogenicity. As the expression of pathogenic BRCA1 variants in Saccharomyces cerevisiae increases the frequency of intra- and inter-chromosomal homologous recombination (HR), and gene reversion (GR), we validated the two HR and the GR assays by testing 23 benign and 23 pathogenic variants and compared the results with those that were obtained in the small colony phenotype (SCP) assay, an additional yeast-based assay, that was validated previously. We demonstrated that they scored high accuracy, sensitivity, and sensibility. By using a classifier that was based on majority of voting, we have integrated data from HR, GR, and SCP assays and developed a reliable method, named yBRCA1, with high sensitivity to obtain an accurate VUS functional classification (benign or pathogenic). The classification of BRCA1 variants, important for assessing the risk of developing BOC, is often difficult to establish with genetic methods because they occur rarely in the population. This study provides a new tool to get insights on the functional impact of the BRCA1 variants.

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“…Several studies that have dissected the role of Mtr4 in aiding the RNA exosome were performed in the Saccharomyces cerevisiae system, establishing a number of mtr4 mutations that disrupt specific interactions and functions of the helicase (Kadowaki et al 1994;Kadowaki et al 1995;Liang et al 1996;Weir et al 2010;Taylor et al 2014). Thus, genetic model systems are a tractable system to investigate interactions with these nuclear cofactors that impact RNA exosome function and studies in such systems can expand our understanding of the influence the RNA exosome can exert over various cellular processes and pathways (Cervelli and Galli 2021).…”

Section: Introductionmentioning

confidence: 99%

“…2014). Thus, genetic model systems are a tractable system to investigate interactions with these nuclear cofactors that impact RNA exosome function and studies in such systems can expand our understanding of the influence the RNA exosome can exert over various cellular processes and pathways (Cervelli and Galli 2021).…”

Section: Introductionmentioning

confidence: 99%

In vivoCharacterization of the Critical Interaction between the RNA Exosome and the Essential RNA Helicase Mtr4 inSaccharomyces cerevisiae

Sterrett

Farchi

Strassler

et al. 2022

Preprint

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The RNA exosome is a conserved molecular machine that processes/degrades numerous coding and non-coding RNAs. The 10-subunit complex is composed of three S1/KH cap subunits (human EXOSC2/3/1; yeast Rrp4/40/Csl4), a lower ring of six PH-like subunits (human EXOSC4/7/8/9/5/6; (yeast Rrp41/42/43/45/46/Mtr3), and a singular 3-5 exo/endonuclease DIS3/Rrp44. Recently, several disease-linked missense mutations have been identified in genes encoding the structural cap and core subunits of the RNA exosome. In this study, we characterize a rare multiple myeloma patient missense mutation that was identified in the cap subunit geneEXOSC2. This missense mutation results in a single amino acid substitution, p.Met40Thr, in a highly conserved domain of EXOSC2. Structural studies suggest this Met40 residue makes direct contact with the essential RNA helicase, MTR4, and may help stabilize the critical interaction between the RNA exosome complex and this cofactor. To assess this interactionin vivo, we utilized theSaccharomyces cerevisiaesystem and modeled theEXOSC2patient mutation into the orthologous yeast geneRRP4, generating the variantrrp4 M68T. Therrp4 M68Tcells have accumulation of certain RNA exosome target RNAs and show sensitivity to drugs that impact RNA processing. Additionally, we identified robust negative genetic interactions therrp4 M68Tvariant and RNA exosome cofactor mutants, particularlymtr4mutant variants. This study suggests that theEXOC2mutation identified in a multiple myeloma patient may impact the function of the RNA exosome and provides anin vivoassessment of a critical interface between the RNA exosome and Mtr4.

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Yeast as a Tool to Understand the Significance of Human Disease-Associated Gene Variants

Cited by 16 publications

References 94 publications

Contribution of model organism phenotypes to the computational identification of human disease genes

Contribution of model organism phenotypes to the computational identification of human disease genes

Validation and Data-Integration of Yeast-Based Assays for Functional Classification of BRCA1 Missense Variants

In vivoCharacterization of the Critical Interaction between the RNA Exosome and the Essential RNA Helicase Mtr4 inSaccharomyces cerevisiae

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