title: A gene's ability to buffer variation is predicted by its fitness contribution and genetic interactions.
abstract: BACKGROUND
  Many single-gene knockouts result in increased phenotypic (e.g., morphological) variability among the mutant's offspring. This has been interpreted as an intrinsic ability of genes to buffer genetic and environmental variation. A phenotypic capacitor is a gene that appears to mask phenotypic variation: when knocked out, the offspring shows more variability than the wild type. Theory predicts that this phenotypic potential should be correlated with a gene's knockout fitness and its number of negative genetic interactions. Based on experimentally measured phenotypic capacity, it was suggested that knockout fitness was unimportant, but that phenotypic capacitors tend to be hubs in genetic and physical interaction networks.
  
  
  RESULTS
  We re-analyse the available experimental data in a combined model, which includes knockout fitness and network parameters as well as expression level and protein length as predictors of phenotypic potential. Contrary to previous conclusions, we find that the strongest predictor is in fact haploid knockout fitness (responsible for 9% of the variation in phenotypic potential), with an additional contribution from the genetic interaction network (5%); once these two factors are taken into account, protein-protein interactions do not make any additional contribution to the variation in phenotypic potential.
  
  
  CONCLUSIONS
  We conclude that phenotypic potential is not a mysterious "emergent" property of cellular networks. Instead, it is very simply determined by the overall fitness reduction of the organism (which in its compromised state can no longer compensate for multiple factors that contribute to phenotypic variation), and by the number (and presumably nature) of genetic interactions of the knocked-out gene. In this light, Hsp90, the prototypical phenotypic capacitor, may not be representative: typical phenotypic capacitors are not direct "buffers" of variation, but are simply genes encoding central cellular functions.
authors.affiliation: Institute for Computer Science, Heinrich-Heine-University, Düsseldorf, Germany.
authors.forename: Guang-Zhong
authors.initials: GZ
authors.lastname: Wang
authors.forename: Jian
authors.initials: J
authors.lastname: Liu
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
authors.forename: Hong-Yu
authors.initials: HY
authors.lastname: Zhang
authors.forename: Martin J
authors.initials: MJ
authors.lastname: Lercher
mesh_terms: D005800:Genes, Fungal / Q000235:genetics*; D056084:Genetic Fitness; D014644:Genetic Variation; D006238:Haploidy; D016014:Linear Models; D008957:Models, Genetic; D010641:Phenotype; D012441:Saccharomyces cerevisiae / Q000235:genetics*