Linked Life Data

19152005

Source:http://linkedlifedata.com/resource/pubmed/id/19152005

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2009-3-20
pubmed:abstractText
Genetics, genomics, and biochemistry have all been of immense help in characterizing macromolecular cell entities and their interactions. Still, obtaining an overall picture of the functioning of even a simple unicellular species has remained a challenging task. One possible way to obtain a comprehensive picture has been described: by capitalizing on the observation that the overexpression on a multicopy plasmid of apparently any wild-type gene in yeast can lead to some negative effect on cell fitness (referring to the concept of "gene toxicity"), the FIG (fitness-based interferential genetics) approach was devised for selecting normal genes that are in antagonistic (and potentially also agonistic) relationship with a particular gene used as a reference. Herein, we take a complementary approach to FIG, by first selecting a "hypertoxic" allele of the reference gene--which easily provides the general possibility of obtaining gene products with the remarkable property of being inactive without altering their macromolecular interactivity--and then looking for the genes that interact functionally with this reference. Thus, FIG and the present approach (Trap-FIG), both taking advantage of the negative effects on cell fitness induced by various quantitative modulations in cellular networks, could potentially pave the way for the emergence of efficient in situ biochemistry.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
1617-4623
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
281
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
437-45
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
A fitness-based interferential genetics approach using hypertoxic/inactive gene alleles as references.
pubmed:affiliation
Centre de Génétique Moléculaire, Centre National de la Recherche Scientifique, rue de la Terrasse, 91198, Gif-sur-Yvette, France. jacques.daniel@cgm.cnrs-gif.fr
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't