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Systematic Analysis of the Molecular Mechanism Underlying Decidualization Using a Text Mining Approach.

Liu JL, Wang TS - PLoS ONE (2015)

Bottom Line: Decidualization is a crucial process for successful embryo implantation and pregnancy in humans.We prioritized genes in this network and identified 12 genes that may be key regulators of decidualization.These findings would provide some clues for further research on the mechanism underlying decidualization.

View Article: PubMed Central - PubMed

Affiliation: College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China.

ABSTRACT
Decidualization is a crucial process for successful embryo implantation and pregnancy in humans. Defects in decidualization during early pregnancy are associated with several pregnancy complications, such as pre-eclampsia, intrauterine growth restriction and recurrent pregnancy loss. However, the mechanism underlying decidualization remains poorly understood. In the present study, we performed a systematic analysis of decidualization-related genes using text mining. We identified 286 genes for humans and 287 genes for mice respectively, with an overlap of 111 genes shared by both species. Through enrichment test, we demonstrated that although divergence was observed, the majority of enriched gene ontology terms and pathways were shared by both species, suggesting that functional categories were more conserved than individual genes. We further constructed a decidualization-related protein-protein interaction network consisted of 344 nodes connected via 1,541 edges. We prioritized genes in this network and identified 12 genes that may be key regulators of decidualization. These findings would provide some clues for further research on the mechanism underlying decidualization.

No MeSH data available.


Related in: MedlinePlus

Gene prioritization by protein-protein interaction (PPI) network analysis.(A) The structure of the PPI network of decidualization-related genes. Nodes are color-coded (red, human-specific; green, mouse-specific; blue, shared by both) and the diameter of each node is proportional to its decidualization impact factor (DIF) value. (B) Degree distribution of the PPI network. The degree distribution follows a power law distribution. (C) Bar plot showing the DIF values for all selected genes with DIF values exceeding the mean plus two standard deviations.
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pone.0134585.g004: Gene prioritization by protein-protein interaction (PPI) network analysis.(A) The structure of the PPI network of decidualization-related genes. Nodes are color-coded (red, human-specific; green, mouse-specific; blue, shared by both) and the diameter of each node is proportional to its decidualization impact factor (DIF) value. (B) Degree distribution of the PPI network. The degree distribution follows a power law distribution. (C) Bar plot showing the DIF values for all selected genes with DIF values exceeding the mean plus two standard deviations.

Mentions: A genome-wide protein-protein interaction (PPI) network was constructed by merging up-to-date protein-protein interactions available in IntAct [25], BioGRID [26], MINT [27], DIP [28], HPRD [35] and MIPS [29]. The network related to decidualization was generated by mapping decidualization-related genes to the genome-wide PPI network. The decidualization network consisted of 344 nodes connected via 1,541 edges (Fig 4A). Topological analysis showed that the network follows a power-law distribution (Fig 4B) and therefore is a scale-free small world network [36]. Networks of this type have the particular feature that some nodes are highly connected compared with others. The highly connected nodes, also known as hub genes, represent functionally important genes in the network. Taking the number of publications into consideration, we prioritized genes by the decidualization impact factor (DIF), which is defined as degree times the number of publications for each gene. Using a defined threshold value of 193, we identified 12 genes (Fig 4C). Interestingly, all these genes (PGR, EGFR, AKT1, STAT3, SRC, PRL, TP53, VIM, IL1B, CTNNB1 and FN1), except FOXO1 which was specific to human, were shared by both humans and mice, suggesting that the core gene network underlying decidualization is conserved between species.


Systematic Analysis of the Molecular Mechanism Underlying Decidualization Using a Text Mining Approach.

Liu JL, Wang TS - PLoS ONE (2015)

Gene prioritization by protein-protein interaction (PPI) network analysis.(A) The structure of the PPI network of decidualization-related genes. Nodes are color-coded (red, human-specific; green, mouse-specific; blue, shared by both) and the diameter of each node is proportional to its decidualization impact factor (DIF) value. (B) Degree distribution of the PPI network. The degree distribution follows a power law distribution. (C) Bar plot showing the DIF values for all selected genes with DIF values exceeding the mean plus two standard deviations.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4519252&req=5

pone.0134585.g004: Gene prioritization by protein-protein interaction (PPI) network analysis.(A) The structure of the PPI network of decidualization-related genes. Nodes are color-coded (red, human-specific; green, mouse-specific; blue, shared by both) and the diameter of each node is proportional to its decidualization impact factor (DIF) value. (B) Degree distribution of the PPI network. The degree distribution follows a power law distribution. (C) Bar plot showing the DIF values for all selected genes with DIF values exceeding the mean plus two standard deviations.
Mentions: A genome-wide protein-protein interaction (PPI) network was constructed by merging up-to-date protein-protein interactions available in IntAct [25], BioGRID [26], MINT [27], DIP [28], HPRD [35] and MIPS [29]. The network related to decidualization was generated by mapping decidualization-related genes to the genome-wide PPI network. The decidualization network consisted of 344 nodes connected via 1,541 edges (Fig 4A). Topological analysis showed that the network follows a power-law distribution (Fig 4B) and therefore is a scale-free small world network [36]. Networks of this type have the particular feature that some nodes are highly connected compared with others. The highly connected nodes, also known as hub genes, represent functionally important genes in the network. Taking the number of publications into consideration, we prioritized genes by the decidualization impact factor (DIF), which is defined as degree times the number of publications for each gene. Using a defined threshold value of 193, we identified 12 genes (Fig 4C). Interestingly, all these genes (PGR, EGFR, AKT1, STAT3, SRC, PRL, TP53, VIM, IL1B, CTNNB1 and FN1), except FOXO1 which was specific to human, were shared by both humans and mice, suggesting that the core gene network underlying decidualization is conserved between species.

Bottom Line: Decidualization is a crucial process for successful embryo implantation and pregnancy in humans.We prioritized genes in this network and identified 12 genes that may be key regulators of decidualization.These findings would provide some clues for further research on the mechanism underlying decidualization.

View Article: PubMed Central - PubMed

Affiliation: College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China.

ABSTRACT
Decidualization is a crucial process for successful embryo implantation and pregnancy in humans. Defects in decidualization during early pregnancy are associated with several pregnancy complications, such as pre-eclampsia, intrauterine growth restriction and recurrent pregnancy loss. However, the mechanism underlying decidualization remains poorly understood. In the present study, we performed a systematic analysis of decidualization-related genes using text mining. We identified 286 genes for humans and 287 genes for mice respectively, with an overlap of 111 genes shared by both species. Through enrichment test, we demonstrated that although divergence was observed, the majority of enriched gene ontology terms and pathways were shared by both species, suggesting that functional categories were more conserved than individual genes. We further constructed a decidualization-related protein-protein interaction network consisted of 344 nodes connected via 1,541 edges. We prioritized genes in this network and identified 12 genes that may be key regulators of decidualization. These findings would provide some clues for further research on the mechanism underlying decidualization.

No MeSH data available.


Related in: MedlinePlus