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Gene network landscape of the ciliate Tetrahymena thermophila.

Xiong J, Yuan D, Fillingham JS, Garg J, Lu X, Chang Y, Liu Y, Fu C, Pearlman RE, Miao W - PLoS ONE (2011)

Bottom Line: The TGN was partitioned, and 55 modules were found.We also investigated human disease orthologs in Tetrahymena that are missing in yeast and provide evidence indicating that some of these are involved in the same process in Tetrahymena as in human.This study constructed a Tetrahymena gene network, provided new insights to the properties of this biological network, and presents an important resource to study Tetrahymena genes at the pathway level.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China.

ABSTRACT

Background: Genome-wide expression data of gene microarrays can be used to infer gene networks. At a cellular level, a gene network provides a picture of the modules in which genes are densely connected, and of the hub genes, which are highly connected with other genes. A gene network is useful to identify the genes involved in the same pathway, in a protein complex or that are co-regulated. In this study, we used different methods to find gene networks in the ciliate Tetrahymena thermophila, and describe some important properties of this network, such as modules and hubs.

Methodology/principal findings: Using 67 single channel microarrays, we constructed the Tetrahymena gene network (TGN) using three methods: the Pearson correlation coefficient (PCC), the Spearman correlation coefficient (SCC) and the context likelihood of relatedness (CLR) algorithm. The accuracy and coverage of the three networks were evaluated using four conserved protein complexes in yeast. The CLR network with a Z-score threshold 3.49 was determined to be the most robust. The TGN was partitioned, and 55 modules were found. In addition, analysis of the arbitrarily determined 1200 hubs showed that these hubs could be sorted into six groups according to their expression profiles. We also investigated human disease orthologs in Tetrahymena that are missing in yeast and provide evidence indicating that some of these are involved in the same process in Tetrahymena as in human.

Conclusions/significance: This study constructed a Tetrahymena gene network, provided new insights to the properties of this biological network, and presents an important resource to study Tetrahymena genes at the pathway level.

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Possible components of the Tetrahymena proteasome complex.A, KEGG annotated Tetrahymena proteasome complex (http://www.kegg.jp/kegg-bin/show_pathway?tet03050); B, Silver stained gel of a pull down experiment using Dss1 (Rpn15) as bait that identifies proteins of the Tetrahymena proteasome; C, The network of the possible Tetrahymena proteasome complex.
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pone-0020124-g003: Possible components of the Tetrahymena proteasome complex.A, KEGG annotated Tetrahymena proteasome complex (http://www.kegg.jp/kegg-bin/show_pathway?tet03050); B, Silver stained gel of a pull down experiment using Dss1 (Rpn15) as bait that identifies proteins of the Tetrahymena proteasome; C, The network of the possible Tetrahymena proteasome complex.

Mentions: Module-19 contains 117 genes with the highest GO annotated percent (65.8 %) and the highest percent of orthologs (also 65.8 %) with other eukaryotes (Table 1). GO enrichment analysis shows that proteins encoded by genes in this module are significantly involved in proteolysis with GO terms including proteolysis involved in cellular protein catabolic process (GO: 0051603) and regulation of protein metabolic process (GO: 0051246), (Table S1). Comparison to the KEGG pathway also shows that this module contains a majority of genes in the proteasome complex (KEGG pathway: tet03050). The main function of the proteasome is to degrade unneeded or damaged proteins by proteolysis, and the complex is part of a major mechanism by which cells regulate the concentration of particular proteins and degrade misfolded proteins [45]. The most common form is the 26S proteasome containing the 20S core particle and the 19S regulatory particle (Figure 3-A). Using immunopurification and mass spectrometry, we have identified 17 proteins in the 19S regulatory particle (Figure 3-B). Sixteen of these 17 genes are densely connected, and the other gene (TTHERM_01014660, a homolog of Rpt2) was mispredicted by the gene model as shown by our RNA-Seq data (unpublished data) (Figure S4), which caused an incorrect normalization for the expression value in the microarray data. Using the 16 genes as the bait (Figure 3-C, red nodes), we find that each of the 13 genes (Figure 3-C, green nodes) in the 20S core particle (annotated by the KEGG pathway) is connected to at least 13 genes in the bait. Again, setting the 29 genes (16 genes of the 19S regulatory particle and 13 genes of the 20S core particle) as bait, we find that the other two KEGG annotated genes, TTHERM_00471830 (a homolog of Rpn10) and TTHERM_00476810 (another homolog of Rpn11 different from the pull down experiment), are also densely connected to the 29 bait genes (Figure 3-C, blue nodes), suggesting these two genes as possible components of the Tetrahymena 26S proteasome. In addition, two ubiquitin-associated genes (TTHERM_00471920 and TTHERM_00355130) in Module-19 are also densely connected to the proteasome complex, indicating that these two genes may function in proteolysis processes.


Gene network landscape of the ciliate Tetrahymena thermophila.

Xiong J, Yuan D, Fillingham JS, Garg J, Lu X, Chang Y, Liu Y, Fu C, Pearlman RE, Miao W - PLoS ONE (2011)

Possible components of the Tetrahymena proteasome complex.A, KEGG annotated Tetrahymena proteasome complex (http://www.kegg.jp/kegg-bin/show_pathway?tet03050); B, Silver stained gel of a pull down experiment using Dss1 (Rpn15) as bait that identifies proteins of the Tetrahymena proteasome; C, The network of the possible Tetrahymena proteasome complex.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3102692&req=5

pone-0020124-g003: Possible components of the Tetrahymena proteasome complex.A, KEGG annotated Tetrahymena proteasome complex (http://www.kegg.jp/kegg-bin/show_pathway?tet03050); B, Silver stained gel of a pull down experiment using Dss1 (Rpn15) as bait that identifies proteins of the Tetrahymena proteasome; C, The network of the possible Tetrahymena proteasome complex.
Mentions: Module-19 contains 117 genes with the highest GO annotated percent (65.8 %) and the highest percent of orthologs (also 65.8 %) with other eukaryotes (Table 1). GO enrichment analysis shows that proteins encoded by genes in this module are significantly involved in proteolysis with GO terms including proteolysis involved in cellular protein catabolic process (GO: 0051603) and regulation of protein metabolic process (GO: 0051246), (Table S1). Comparison to the KEGG pathway also shows that this module contains a majority of genes in the proteasome complex (KEGG pathway: tet03050). The main function of the proteasome is to degrade unneeded or damaged proteins by proteolysis, and the complex is part of a major mechanism by which cells regulate the concentration of particular proteins and degrade misfolded proteins [45]. The most common form is the 26S proteasome containing the 20S core particle and the 19S regulatory particle (Figure 3-A). Using immunopurification and mass spectrometry, we have identified 17 proteins in the 19S regulatory particle (Figure 3-B). Sixteen of these 17 genes are densely connected, and the other gene (TTHERM_01014660, a homolog of Rpt2) was mispredicted by the gene model as shown by our RNA-Seq data (unpublished data) (Figure S4), which caused an incorrect normalization for the expression value in the microarray data. Using the 16 genes as the bait (Figure 3-C, red nodes), we find that each of the 13 genes (Figure 3-C, green nodes) in the 20S core particle (annotated by the KEGG pathway) is connected to at least 13 genes in the bait. Again, setting the 29 genes (16 genes of the 19S regulatory particle and 13 genes of the 20S core particle) as bait, we find that the other two KEGG annotated genes, TTHERM_00471830 (a homolog of Rpn10) and TTHERM_00476810 (another homolog of Rpn11 different from the pull down experiment), are also densely connected to the 29 bait genes (Figure 3-C, blue nodes), suggesting these two genes as possible components of the Tetrahymena 26S proteasome. In addition, two ubiquitin-associated genes (TTHERM_00471920 and TTHERM_00355130) in Module-19 are also densely connected to the proteasome complex, indicating that these two genes may function in proteolysis processes.

Bottom Line: The TGN was partitioned, and 55 modules were found.We also investigated human disease orthologs in Tetrahymena that are missing in yeast and provide evidence indicating that some of these are involved in the same process in Tetrahymena as in human.This study constructed a Tetrahymena gene network, provided new insights to the properties of this biological network, and presents an important resource to study Tetrahymena genes at the pathway level.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China.

ABSTRACT

Background: Genome-wide expression data of gene microarrays can be used to infer gene networks. At a cellular level, a gene network provides a picture of the modules in which genes are densely connected, and of the hub genes, which are highly connected with other genes. A gene network is useful to identify the genes involved in the same pathway, in a protein complex or that are co-regulated. In this study, we used different methods to find gene networks in the ciliate Tetrahymena thermophila, and describe some important properties of this network, such as modules and hubs.

Methodology/principal findings: Using 67 single channel microarrays, we constructed the Tetrahymena gene network (TGN) using three methods: the Pearson correlation coefficient (PCC), the Spearman correlation coefficient (SCC) and the context likelihood of relatedness (CLR) algorithm. The accuracy and coverage of the three networks were evaluated using four conserved protein complexes in yeast. The CLR network with a Z-score threshold 3.49 was determined to be the most robust. The TGN was partitioned, and 55 modules were found. In addition, analysis of the arbitrarily determined 1200 hubs showed that these hubs could be sorted into six groups according to their expression profiles. We also investigated human disease orthologs in Tetrahymena that are missing in yeast and provide evidence indicating that some of these are involved in the same process in Tetrahymena as in human.

Conclusions/significance: This study constructed a Tetrahymena gene network, provided new insights to the properties of this biological network, and presents an important resource to study Tetrahymena genes at the pathway level.

Show MeSH