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New genes drive the evolution of gene interaction networks in the human and mouse genomes.

Zhang W, Landback P, Gschwend AR, Shen B, Long M - Genome Biol. (2015)

Bottom Line: These genes experienced a gradual integration process into GGI networks, starting on the network periphery and gradually becoming highly connected hubs, and acquiring pleiotropic and essential functions.We identify a few human lineage-specific hub genes that have evolved brain development-related functions.Our data cast new conceptual insights into the evolution of genetic networks.

View Article: PubMed Central - PubMed

Affiliation: Center for Systems Biology, Soochow University, Suzhou, Jiangsu, 215006, China. wyzhang@uchicago.edu.

ABSTRACT

Background: The origin of new genes with novel functions creates genetic and phenotypic diversity in organisms. To acquire functional roles, new genes must integrate into ancestral gene-gene interaction (GGI) networks. The mechanisms by which new genes are integrated into ancestral networks, and their evolutionary significance, are yet to be characterized. Herein, we present a study investigating the rates and patterns of new gene-driven evolution of GGI networks in the human and mouse genomes.

Results: We examine the network topological and functional evolution of new genes that originated at various stages in the human and mouse lineages by constructing and analyzing three different GGI datasets. We find a large number of new genes integrated into GGI networks throughout vertebrate evolution. These genes experienced a gradual integration process into GGI networks, starting on the network periphery and gradually becoming highly connected hubs, and acquiring pleiotropic and essential functions. We identify a few human lineage-specific hub genes that have evolved brain development-related functions. Finally, we explore the possible underlying mechanisms driving the GGI network evolution and the observed patterns of new gene integration process.

Conclusions: Our results unveil a remarkable network topological integration process of new genes: over 5000 new genes were integrated into the ancestral GGI networks of human and mouse; new genes gradually acquire increasing number of gene partners; some human-specific genes evolved into hub structure with critical phenotypic effects. Our data cast new conceptual insights into the evolution of genetic networks.

No MeSH data available.


Comparison of PPI network topologies for young genes with diverse brain expression patterns. This figure shows the percentage distribution of young hub genes and young non-hub genes within different categories of brain expression patterns. The statistical significance difference was calculated using Fisher’s exact test
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Fig7: Comparison of PPI network topologies for young genes with diverse brain expression patterns. This figure shows the percentage distribution of young hub genes and young non-hub genes within different categories of brain expression patterns. The statistical significance difference was calculated using Fisher’s exact test

Mentions: Through integrative analysis of the brain expression pattern data of these young genes [2] and their network topological features based on human PPI network data, we found no significant bias on the percentages of hub genes (with minimum interaction degrees of 6) among three different brain expression categories of young genes (Fisher’s exact test, Fetus vs. Adult: P value = 0.435, Adult vs. Unbiased: P value = 0.3323, Fig. 7). In other words, young genes with diverse network connectivity contribute equally during both early and late stages of human brain development.Fig. 7


New genes drive the evolution of gene interaction networks in the human and mouse genomes.

Zhang W, Landback P, Gschwend AR, Shen B, Long M - Genome Biol. (2015)

Comparison of PPI network topologies for young genes with diverse brain expression patterns. This figure shows the percentage distribution of young hub genes and young non-hub genes within different categories of brain expression patterns. The statistical significance difference was calculated using Fisher’s exact test
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4590697&req=5

Fig7: Comparison of PPI network topologies for young genes with diverse brain expression patterns. This figure shows the percentage distribution of young hub genes and young non-hub genes within different categories of brain expression patterns. The statistical significance difference was calculated using Fisher’s exact test
Mentions: Through integrative analysis of the brain expression pattern data of these young genes [2] and their network topological features based on human PPI network data, we found no significant bias on the percentages of hub genes (with minimum interaction degrees of 6) among three different brain expression categories of young genes (Fisher’s exact test, Fetus vs. Adult: P value = 0.435, Adult vs. Unbiased: P value = 0.3323, Fig. 7). In other words, young genes with diverse network connectivity contribute equally during both early and late stages of human brain development.Fig. 7

Bottom Line: These genes experienced a gradual integration process into GGI networks, starting on the network periphery and gradually becoming highly connected hubs, and acquiring pleiotropic and essential functions.We identify a few human lineage-specific hub genes that have evolved brain development-related functions.Our data cast new conceptual insights into the evolution of genetic networks.

View Article: PubMed Central - PubMed

Affiliation: Center for Systems Biology, Soochow University, Suzhou, Jiangsu, 215006, China. wyzhang@uchicago.edu.

ABSTRACT

Background: The origin of new genes with novel functions creates genetic and phenotypic diversity in organisms. To acquire functional roles, new genes must integrate into ancestral gene-gene interaction (GGI) networks. The mechanisms by which new genes are integrated into ancestral networks, and their evolutionary significance, are yet to be characterized. Herein, we present a study investigating the rates and patterns of new gene-driven evolution of GGI networks in the human and mouse genomes.

Results: We examine the network topological and functional evolution of new genes that originated at various stages in the human and mouse lineages by constructing and analyzing three different GGI datasets. We find a large number of new genes integrated into GGI networks throughout vertebrate evolution. These genes experienced a gradual integration process into GGI networks, starting on the network periphery and gradually becoming highly connected hubs, and acquiring pleiotropic and essential functions. We identify a few human lineage-specific hub genes that have evolved brain development-related functions. Finally, we explore the possible underlying mechanisms driving the GGI network evolution and the observed patterns of new gene integration process.

Conclusions: Our results unveil a remarkable network topological integration process of new genes: over 5000 new genes were integrated into the ancestral GGI networks of human and mouse; new genes gradually acquire increasing number of gene partners; some human-specific genes evolved into hub structure with critical phenotypic effects. Our data cast new conceptual insights into the evolution of genetic networks.

No MeSH data available.