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. 2012:19-30.

Predicting the effects of copy-number variation in double and triple mutant combinations

Gregory W Carter  1 , Michelle Hays, Song Li, Timothy Galitski
Affiliations

Predicting the effects of copy-number variation in double and triple mutant combinations

Gregory W Carter et al. Pac Symp Biocomput. 2012.

Abstract

The study of genetic interactions is a powerful tool in inferring structure and function of biological networks. To date, genetic interaction studies have been dominated by pair-wise gene deletion screens. However, classical genetic analysis and natural genetic variation involve diverse gene forms ranging from null alleles to copy number variants. Moreover, genetic variation is typically multifactorial. Addressing multiple combinatorial genetic variations ranging in gene activity is therefore of critical value. We approach this problem using genetic network modeling that quantitatively encodes how genes influence the activity of one another and phenotype outcomes. A network model was initially inferred from linear decomposition of gene expression data. We used this network to predict the effects of combining multi-copy and deletion mutations of specific gene pairs and a gene triplet. Predicted expression patterns across hundreds of genes were experimentally validated. Prediction success was critically dependent on how a multi-copy gene interacted with other genes in the network model. This strategy provides a template for the inference, prediction, and testing of genetically complex hypotheses involving diverse genetic variation.

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Figures

Figure 1
Figure 1
SVD eigenvalues and eigengenes matrix. (A) Bar chart of eigenvalues and (B) raster plot of eigengenes matrix are shown for the first five SVD modes.
Figure 2
Figure 2
Network of significant positive (green) and negative (red) gene-to-gene and gene-to-expression influences. Yellow nodes are regulator genes, white nodes are expression patterns shared by multiple genes. Each edge corresponds to a parameter inferred in the genetic model with width proportional to influence magnitude.
Figure 3
Figure 3
Fit accuracy for the six double-knockout strains (data combined). Solid lines are results for the interactive model; dashed lines are results for the additive control. Plots show (A) percentage of correct up or down-expression, (B) overall correlation of fit and data, and (C) median absolute deviation (MAD) for fit versus measured expression. All quantities are plotted as a function of fold-change, where the x-axis denotes the subset of expression ratios with the x-value or greater fold change.
Figure 4
Figure 4
Predicted expression of an example gene (FRE8) is insensitive to basal CIN5 activity beyond small values. The red line is predicted expression for CIN5* strain background, and the blue line is for yap6Δ CIN5* double mutant. Both lines begin at best-fit values for wild-type CIN5 (multiplier of 1). Red and blue points are experimental results (in triplicate) for the corresponding strains.
Figure 5
Figure 5
Prediction accuracy for CIN5 gain-of-function in wild-type, tec1Δ, cup9Δ, yap6Δ, and tec1Δcup9Δ backgrounds (data combined). Solid lines are results for the interactive model; dashed lines are results for the additive control. Plots show (A) percentage of correct up or down-expression, (B) overall correlation of predictions and data, and (C) median absolute deviation (MAD) for predicted versus measured expression. All quantities are plotted as a function of fold-change, where the x-axis denotes the subset of expression ratios with the x-value or greater fold change. Predictive power generally increases with differential expression.
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References

    1. Iles MM. PLoS Genet. 2008;4:e33. - PMC - PubMed
    1. Visscher PM, Montgomery GW. JAMA. 2009;302:2028. - PubMed
    1. Manolio TA, Collins FS, Cox NJ, et al. Nature. 2009;461:747. - PMC - PubMed
    1. Mills RE, Walter K, Stewart C, et al. Nature. 2011;470:59. - PMC - PubMed
    1. Dudley AM, Janse DM, Tanay A, Shamir R, Church GM. Mol Syst Biol. 2005;1 2005 0001. - PMC - PubMed

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