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Comparative Meta-Analysis of Transcriptomics Data during Cellular Senescence and In Vivo Tissue Ageing.

Voutetakis K, Chatziioannou A, Gonos ES, Trougakos IP - Oxid Med Cell Longev (2015)

Bottom Line: Several studies have employed DNA microarrays to identify gene expression signatures that mark human ageing; yet the features underlying this complicated phenomenon remain elusive.We thus conducted a bioinformatics meta-analysis on transcriptomics data from human cell- and biopsy-based microarrays experiments studying cellular senescence or in vivo tissue ageing, respectively.Our reported meta-analysis has revealed novel age-related genes, setting thus the basis for more detailed future functional studies.

View Article: PubMed Central - PubMed

Affiliation: National Hellenic Research Foundation, Institute of Biology, Medicinal Chemistry and Biotechnology, 48 Vassileos Constantinou Avenue, 11635 Athens, Greece.

ABSTRACT
Several studies have employed DNA microarrays to identify gene expression signatures that mark human ageing; yet the features underlying this complicated phenomenon remain elusive. We thus conducted a bioinformatics meta-analysis on transcriptomics data from human cell- and biopsy-based microarrays experiments studying cellular senescence or in vivo tissue ageing, respectively. We report that coregulated genes in the postmitotic muscle and nervous tissues are classified into pathways involved in cancer, focal adhesion, actin cytoskeleton, MAPK signalling, and metabolism regulation. Genes that are differentially regulated during cellular senescence refer to pathways involved in neurodegeneration, focal adhesion, actin cytoskeleton, proteasome, cell cycle, DNA replication, and oxidative phosphorylation. Finally, we revealed genes and pathways (referring to cancer, Huntington's disease, MAPK signalling, focal adhesion, actin cytoskeleton, oxidative phosphorylation, and metabolic signalling) that are coregulated during cellular senescence and in vivo tissue ageing. The molecular commonalities between cellular senescence and tissue ageing are also highlighted by the fact that pathways that were overrepresented exclusively in the biopsy- or cell-based datasets are modules either of the same reference pathway (e.g., metabolism) or of closely interrelated pathways (e.g., thyroid cancer and melanoma). Our reported meta-analysis has revealed novel age-related genes, setting thus the basis for more detailed future functional studies.

No MeSH data available.


Related in: MedlinePlus

Identification of (gender-independent) coregulated potential biomarkers of ageing in human postmitotic skeletal muscle and nervous tissues. Venn diagram comparing DEGs in skeletal muscle and nervous tissues of young and aged individuals (P value ≤ 0.05; FDR ≤ 0.1; FC > 1.2). In skeletal muscle (light green; 6 experiments analysed), the total number of differentially expressed genes during ageing was 1551, while 387 genes were found to be differentially expressed during ageing of the nervous tissue (light yellow; 1 experiment analysed). The intersection of the two groups contains 66 common DEGs; the identified “hub-genes” (GORevenge algorithm) are listed in descending order of their GO terms' linkage number.
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fig2: Identification of (gender-independent) coregulated potential biomarkers of ageing in human postmitotic skeletal muscle and nervous tissues. Venn diagram comparing DEGs in skeletal muscle and nervous tissues of young and aged individuals (P value ≤ 0.05; FDR ≤ 0.1; FC > 1.2). In skeletal muscle (light green; 6 experiments analysed), the total number of differentially expressed genes during ageing was 1551, while 387 genes were found to be differentially expressed during ageing of the nervous tissue (light yellow; 1 experiment analysed). The intersection of the two groups contains 66 common DEGs; the identified “hub-genes” (GORevenge algorithm) are listed in descending order of their GO terms' linkage number.

Mentions: In order to identify genes that are regulated in an age-dependent manner in postmitotic tissues, we searched for common age-related alterations in both the skeletal muscle and nervous tissues (Figure 2). The SEPP1, PIK3C2A, and NFE2L2 genes were found to be upregulated more than 1.5-fold in both tissues. On the other hand, AZIN1, ANK2, DDX3X, and PAK1 were downregulated in both tissues, while SERINC5 was found to be upregulated in nervous and downregulated in the skeletal muscle.


Comparative Meta-Analysis of Transcriptomics Data during Cellular Senescence and In Vivo Tissue Ageing.

Voutetakis K, Chatziioannou A, Gonos ES, Trougakos IP - Oxid Med Cell Longev (2015)

Identification of (gender-independent) coregulated potential biomarkers of ageing in human postmitotic skeletal muscle and nervous tissues. Venn diagram comparing DEGs in skeletal muscle and nervous tissues of young and aged individuals (P value ≤ 0.05; FDR ≤ 0.1; FC > 1.2). In skeletal muscle (light green; 6 experiments analysed), the total number of differentially expressed genes during ageing was 1551, while 387 genes were found to be differentially expressed during ageing of the nervous tissue (light yellow; 1 experiment analysed). The intersection of the two groups contains 66 common DEGs; the identified “hub-genes” (GORevenge algorithm) are listed in descending order of their GO terms' linkage number.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4419258&req=5

fig2: Identification of (gender-independent) coregulated potential biomarkers of ageing in human postmitotic skeletal muscle and nervous tissues. Venn diagram comparing DEGs in skeletal muscle and nervous tissues of young and aged individuals (P value ≤ 0.05; FDR ≤ 0.1; FC > 1.2). In skeletal muscle (light green; 6 experiments analysed), the total number of differentially expressed genes during ageing was 1551, while 387 genes were found to be differentially expressed during ageing of the nervous tissue (light yellow; 1 experiment analysed). The intersection of the two groups contains 66 common DEGs; the identified “hub-genes” (GORevenge algorithm) are listed in descending order of their GO terms' linkage number.
Mentions: In order to identify genes that are regulated in an age-dependent manner in postmitotic tissues, we searched for common age-related alterations in both the skeletal muscle and nervous tissues (Figure 2). The SEPP1, PIK3C2A, and NFE2L2 genes were found to be upregulated more than 1.5-fold in both tissues. On the other hand, AZIN1, ANK2, DDX3X, and PAK1 were downregulated in both tissues, while SERINC5 was found to be upregulated in nervous and downregulated in the skeletal muscle.

Bottom Line: Several studies have employed DNA microarrays to identify gene expression signatures that mark human ageing; yet the features underlying this complicated phenomenon remain elusive.We thus conducted a bioinformatics meta-analysis on transcriptomics data from human cell- and biopsy-based microarrays experiments studying cellular senescence or in vivo tissue ageing, respectively.Our reported meta-analysis has revealed novel age-related genes, setting thus the basis for more detailed future functional studies.

View Article: PubMed Central - PubMed

Affiliation: National Hellenic Research Foundation, Institute of Biology, Medicinal Chemistry and Biotechnology, 48 Vassileos Constantinou Avenue, 11635 Athens, Greece.

ABSTRACT
Several studies have employed DNA microarrays to identify gene expression signatures that mark human ageing; yet the features underlying this complicated phenomenon remain elusive. We thus conducted a bioinformatics meta-analysis on transcriptomics data from human cell- and biopsy-based microarrays experiments studying cellular senescence or in vivo tissue ageing, respectively. We report that coregulated genes in the postmitotic muscle and nervous tissues are classified into pathways involved in cancer, focal adhesion, actin cytoskeleton, MAPK signalling, and metabolism regulation. Genes that are differentially regulated during cellular senescence refer to pathways involved in neurodegeneration, focal adhesion, actin cytoskeleton, proteasome, cell cycle, DNA replication, and oxidative phosphorylation. Finally, we revealed genes and pathways (referring to cancer, Huntington's disease, MAPK signalling, focal adhesion, actin cytoskeleton, oxidative phosphorylation, and metabolic signalling) that are coregulated during cellular senescence and in vivo tissue ageing. The molecular commonalities between cellular senescence and tissue ageing are also highlighted by the fact that pathways that were overrepresented exclusively in the biopsy- or cell-based datasets are modules either of the same reference pathway (e.g., metabolism) or of closely interrelated pathways (e.g., thyroid cancer and melanoma). Our reported meta-analysis has revealed novel age-related genes, setting thus the basis for more detailed future functional studies.

No MeSH data available.


Related in: MedlinePlus