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Modification of Gene Duplicability during the Evolution of Protein Interaction Network

Overview of attention for article published in PLoS Computational Biology, April 2011
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Title
Modification of Gene Duplicability during the Evolution of Protein Interaction Network
Published in
PLoS Computational Biology, April 2011
DOI 10.1371/journal.pcbi.1002029
Pubmed ID
Authors

Matteo D'Antonio, Francesca D. Ciccarelli

Abstract

Duplications of genes encoding highly connected and essential proteins are selected against in several species but not in human, where duplicated genes encode highly connected proteins. To understand when and how gene duplicability changed in evolution, we compare gene and network properties in four species (Escherichia coli, yeast, fly, and human) that are representative of the increase in evolutionary complexity, defined as progressive growth in the number of genes, cells, and cell types. We find that the origin and conservation of a gene significantly correlates with the properties of the encoded protein in the protein-protein interaction network. All four species preserve a core of singleton and central hubs that originated early in evolution, are highly conserved, and accomplish basic biological functions. Another group of hubs appeared in metazoans and duplicated in vertebrates, mostly through vertebrate-specific whole genome duplication. Such recent and duplicated hubs are frequently targets of microRNAs and show tissue-selective expression, suggesting that these are alternative mechanisms to control their dosage. Our study shows how networks modified during evolution and contributes to explaining the occurrence of somatic genetic diseases, such as cancer, in terms of network perturbations.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 139 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 5%
United Kingdom 4 3%
Belgium 3 2%
France 2 1%
Brazil 2 1%
Spain 2 1%
Argentina 2 1%
Netherlands 1 <1%
Italy 1 <1%
Other 7 5%
Unknown 108 78%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 43 31%
Researcher 41 29%
Professor > Associate Professor 15 11%
Student > Postgraduate 10 7%
Professor 8 6%
Other 19 14%
Unknown 3 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 82 59%
Biochemistry, Genetics and Molecular Biology 20 14%
Computer Science 10 7%
Mathematics 4 3%
Environmental Science 4 3%
Other 9 6%
Unknown 10 7%