Background: Selective gene duplicability, the extensive expansion of a small number of gene families, is universal. Quantitatively, the number of genes (P(K)) with K duplicates in a genome decreases precipitously as K increases, and often follows a power law (P(k)∝k-α). Functional diversification, either neo- or sub-functionalization, is a major evolution route for duplicate genes.

Results: Using three lines of genomic datasets, we studied the relationship between gene duplicability and diversifiability in the topology of biochemical networks. First, we explored scenario where two pathways in the biochemical networks antagonize each other. Synthetic knockout of respective genes for the two pathways rescues the phenotypic defects of each individual knockout. We identified duplicate gene pairs with sufficient divergences that represent this antagonism relationship in the yeast S. cerevisiae. Such pairs overwhelmingly belong to large gene families, thus tend to have high duplicability. Second, we used distances between proteins of duplicate genes in the protein interaction network as a metric of their diversification. The higher a gene's duplicate count, the further the proteins of this gene and its duplicates drift away from one another in the networks, which is especially true for genetically antagonizing duplicate genes. Third, we computed a sequence-homology-based clustering coefficient to quantify sequence diversifiability among duplicate genes - the lower the coefficient, the more the sequences have diverged. Duplicate count (K) of a gene is negatively correlated to the clustering coefficient of its duplicates, suggesting that gene duplicability is related to the extent of sequence divergence within the duplicate gene family.

Conclusion: Thus, a positive correlation exists between gene diversifiability and duplicability in the context of biochemical networks - an improvement of our understanding of gene duplicability.

• PMID: 25005725
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Reference Type

Journal Article | Research Support, N.I.H., Extramural | Research Support, Non-U.S. Gov't

Authors

Guo Z, Jiang W, Lages N, Borcherds W, Wang D

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