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Comparative Study
. 2003 Dec;13(12):2568-76.
doi: 10.1101/gr.1111403.

From gene networks to gene function

Thomas Schlitt  1 , Kimmo Palin, Johan Rung, Sabine Dietmann, Michael Lappe, Esko Ukkonen, Alvis Brazma
Affiliations
Comparative Study

From gene networks to gene function

Thomas Schlitt et al. Genome Res. 2003 Dec.

Abstract

We propose a novel method to identify functionally related genes based on comparisons of neighborhoods in gene networks. This method does not rely on gene sequence or protein structure homologies, and it can be applied to any organism and a wide variety of experimental data sets. The character of the predicted gene relationships depends on the underlying networks;they concern biological processes rather than the molecular function. We used the method to analyze gene networks derived from genome-wide chromatin immunoprecipitation experiments, a large-scale gene deletion study, and from the genomic positions of consensus binding sites for transcription factors of the yeast Saccharomyces cerevisiae. We identified 816 functional relationships between 159 genes and show that these relationships correspond to protein-protein interactions, co-occurrence in the same protein complexes, and/or co-occurrence in abstracts of scientific articles. Our results suggest functions for seven previously uncharacterized yeast genes: KIN3 and YMR269W may be involved in biological processes related to cell growth and/or maintenance, whereas IES6, YEL008W, YEL033W, YHL029C, YMR010W, and YMR031W-A are likely to have metabolic functions.

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Figures

Figure 1
Figure 1
Illustration of the correspondence between functionally related genes and similarity of the _target sets. Pairs of functionally unrelated genes have smaller _target-set overlaps. Large overlaps can be used to predict a functional relationship between the respective genes (top).
Figure 2
Figure 2
Transcription factors with known binding sites and mutated genes form two sets of source genes (lefthand side). (A) The set T1 on the right represents all the genes in the genome that have binding sites for selected transcription factor s1 in their putative promoter regions (i.e., the _target set of s1). The set T2 represents all the genes whose expression levels are changed in the deletion mutant of gene s2 (i.e., the _target set of s1). If the _target sets T1 and T2 overlap more than expected by chance, we can hypothesize that the two genes s1 and s2 are related. (B) The case when we compare two _target sets from different networks, but for one gene s1.
Figure 3
Figure 3
ROC plots of true-positive rate (sensitivity) vs. false-positive rate (1 - specificity) for the prediction of protein–protein interaction (ppi1, ppi2), protein complexes (mips), and“co-citation” (mi2, mi3). The source genes s1, s2 are chosen from same (A) or different networks (B). (C) An ROC plot using the union of ppi2, mips, and mi3 as verification network, with source genes s1, s2 chosen from the same network (all-same) or different networks (all-diff).
Figure 4
Figure 4
Visualization of the source gene pairs with highly similar _target sets as a graph. Genes involved in the same biological processes are often connected and are thus close in the resulting graph; e.g., pheromone response genes or cell-cycle genes (encircled). Genes sharing highly similar _target sets (P ≤ 10-12) are connected by gray edges or, if there is also a corresponding edge in one of the reference networks ppi2, mi3, and mips, by black edges. The thicker edges indicate that the respective source gene pair had significantly similar _target sets in several network comparisons. White nodes: genes which are not present in any of the reference networks; these genes therefore are not adjacent to any confirmed edges. Gray nodes: genes present in at least one of the reference networks. Rectangular nodes: genes with unknown molecular function (BUD14, ERG28, RMD7, BUD22, and AEP2). Arrow-shaped nodes: genes of unknown biological process (KIN3, YEL008W, YEL033W, YHL029C).
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References

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WEB SITE REFERENCES

    1. http://db.yeastgenome.org/cgi-bin/SGD/GO/goTermMapper; goTermMapper from SGD.
    1. http://mips.gsf.de/ and http://mips.gsf.de/proj/yeast/; MIPS.
    1. http://www.yeastgenome.org/; SGD.
    1. http://srs.ebi.ac.uk; SRS server.
    1. http://www.ebi.ac.uk/proteome/; EBI Proteome Analysis Database.

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