Systematic screen for human disease genes in yeast

Steinmetz, Lars M.; Scharfe, Curt; Deutschbauer, Adam M.; Mokranjac, Dejana; Herman, Zelek S.; Jones, Ted; Chu, Angela M.; Giaever, Guri; Prokisch, Holger; Oefner, Peter J.; Davis, Ronald W.

doi:10.1038/ng929

Cited by 501 publications

(484 citation statements)

References 27 publications

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“…The results of assays of a nearly complete set of single gene deletions in S. cerevisiae (Steinmetz et al 2002) were obtained, and the data were manipulated following the method of Gu et al (2003). Briefly, the fitness value f i is defined as r i /r pool , where r i is the growth rate of the strain with gene i deleted and r pool is the pooled average growth rate of different strains.…”

Section: Sequences and Data Setsmentioning

confidence: 99%

Accelerated Evolutionary Rate May Be Responsible for the Emergence of Lineage-Specific Genes in Ascomycota

et al. 2006

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Abstract. The evolutionary origin of ''orphan'' genes, genes that lack sequence similarity to any known gene, remains a mystery. One suggestion has been that most orphan genes evolve rapidly so that similarity to other genes cannot be traced after a certain evolutionary distance. This can be tested by examining the divergence rates of genes with different degrees of lineage specificity. Here the lineage specificity (LS) of a gene describes the phylogenetic distribution of that gene's orthologues in related species. Highly lineagespecific genes will be distributed in fewer species in a phylogeny. In this study, we have used the complete genomes of seven ascomycotan fungi and two animals to define several levels of LS, such as Eukaryotes-core, Ascomycota-core, Euascomycetes-specific, Hemiascomycetes-specific, Aspergillus-specific, and Saccharomyces-specific. We compare the rates of gene evolution in groups of higher LS to those in groups with lower LS. Molecular evolutionary analyses indicate an increase in nonsynonymous nucleotide substitution rates in genes with higher LS. Several analyses suggest that LS is correlated with the evolutionary rate of the gene. This correlation is stronger than those of a number of other factors that have been proposed as predictors of a gene's evolutionary rate, including the expression level of genes, gene essentiality or dispensability, and the number of protein-protein interactions. The accelerated evolutionary rates of genes with higher LS may reflect the influence of selection and adaptive divergence during the emergence of orphan genes. These analyses suggest that accelerated rates of gene evolution may be responsible for the emergence of apparently orphan genes.

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Section: Sequences and Data Setsmentioning

confidence: 99%

Accelerated Evolutionary Rate May Be Responsible for the Emergence of Lineage-Specific Genes in Ascomycota

et al. 2006

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“…These data were used to correlate protein length directly with number of interactions. Those proteins within the Meta-A protein dataset that are essential were determined from the Saccharomyces Genome Deletion Project [15]. The relationship between protein length and the probability that the encoding gene is essential was determined.…”

Section: Methods and Resultsmentioning

confidence: 99%

Length, protein–protein interactions, and complexity

Tan

Frenkel

Gupta

et al. 2005

Physica A: Statistical Mechanics and its Applications

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The evolutionary reason for the increase in gene length from archaea to prokaryotes to eukaryotes observed in large-scale genome sequencing efforts has been unclear. We propose here that the increasing complexity of protein-protein interactions has driven the selection of longer proteins, as they are more able to distinguish among a larger number of distinct interactions due to their greater average surface area. Annotated protein sequences available from the SWISS-PROT database were analyzed for 13 eukaryotes, eight bacteria, and two archaea species. The number of subcellular locations to which each protein is associated is used as a measure of the number of interactions to which a protein participates. Two databases of yeast protein-protein interactions were used as another measure of the number of interactions to which each S. cerevisiae protein participates. Protein length is shown to correlate with both number of subcellular locations to which a protein is associated and number of interactions as measured by yeast two-hybrid experiments. Protein length is also shown to correlate with the probability that the protein is encoded by an essential gene. Interestingly, average protein length and number of subcellular locations are not significantly different between all human proteins and protein targets of known, marketed drugs. Increased protein length appears to be a significant mechanism by which the increasing complexity of protein-protein interaction networks is accommodated within the natural evolution of species. Consideration of protein length may be a valuable tool in drug design, one that predicts different strategies for inhibiting interactions in aberrant and normal pathways. r ARTICLE IN PRESS

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“…Au contraire, l'étude fonctionnelle des souches délétées de S. cerevisiae, favorisée par le libre accès aux résultats obtenus pour chaque souche et aux listes des gènes de la classe III et de ses homologues humains (http://www-deletion.stanford. edu/YDPM/YDPM_index.html), constitue une source d'une richesse inestimable pour les recherches futures des fonctions de la mitochondrie chez la levure et chez l'homme, et en particulier pour la recherche des gènes responsables des maladies mitochondriales [9]. ◊ Yeast, a model to unravel mitochondrial diseases?…”

Section: Chromosomeunclassified

La levure, une aide pour décrypter les maladies mitochondriales humaines ?

Foury

2003

Med Sci (Paris)

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Systematic screen for human disease genes in yeast

Cited by 501 publications

References 27 publications

Accelerated Evolutionary Rate May Be Responsible for the Emergence of Lineage-Specific Genes in Ascomycota

Accelerated Evolutionary Rate May Be Responsible for the Emergence of Lineage-Specific Genes in Ascomycota

Length, protein–protein interactions, and complexity

La levure, une aide pour décrypter les maladies mitochondriales humaines ?

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