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De-regulation of gene expression and alternative splicing affects distinct cellular pathways in the aging hippocampus.

Stilling RM, Benito E, Gertig M, Barth J, Capece V, Burkhardt S, Bonn S, Fischer A - Front Cell Neurosci (2014)

Bottom Line: This approach enabled us to test differential expression of coding and non-coding transcripts, as well as differential splicing and RNA editing.We report a specific age-associated gene expression signature that is associated with major genetic risk factors for late-onset AD (LOAD).This signature is dominated by neuroinflammatory processes, specifically activation of the complement system at the level of increased gene expression, while de-regulation of neuronal plasticity appears to be mediated by compromised RNA splicing.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychiatry and Psychotherapy, University Medical Center Göttingen Göttingen, Germany ; Research Group for Epigenetics in Neurodegenerative Diseases, German Center for Neurodegenerative Diseases (DZNE) Göttingen Göttingen, Germany.

ABSTRACT
Aging is accompanied by gradually increasing impairment of cognitive abilities and constitutes the main risk factor of neurodegenerative conditions like Alzheimer's disease (AD). The underlying mechanisms are however not well understood. Here we analyze the hippocampal transcriptome of young adult mice and two groups of mice at advanced age using RNA sequencing. This approach enabled us to test differential expression of coding and non-coding transcripts, as well as differential splicing and RNA editing. We report a specific age-associated gene expression signature that is associated with major genetic risk factors for late-onset AD (LOAD). This signature is dominated by neuroinflammatory processes, specifically activation of the complement system at the level of increased gene expression, while de-regulation of neuronal plasticity appears to be mediated by compromised RNA splicing.

No MeSH data available.


Related in: MedlinePlus

Promoter analysis of aging-regulated genes for overrepresented transcription factor binding sites (TFBS). (A) Z-score (enrichments score) for different position weight matrices of known transcription factors in the set of gene up-regulated in 3 vs. 24-month-old mice. Higher Z-score means higher enrichment. Shown are only the top 20 most significantly enriched matrices. (B) The same analysis as described in (A) was performed for up-regulated genes in 3 vs. 29-month-old mice. (C) Pie charts showing the percentage of differentially expressed genes that can be explained by the selected core set of transcription factors.
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Figure 3: Promoter analysis of aging-regulated genes for overrepresented transcription factor binding sites (TFBS). (A) Z-score (enrichments score) for different position weight matrices of known transcription factors in the set of gene up-regulated in 3 vs. 24-month-old mice. Higher Z-score means higher enrichment. Shown are only the top 20 most significantly enriched matrices. (B) The same analysis as described in (A) was performed for up-regulated genes in 3 vs. 29-month-old mice. (C) Pie charts showing the percentage of differentially expressed genes that can be explained by the selected core set of transcription factors.

Mentions: To further elucidate potential upstream mechanisms of the identified transcriptional program, we searched the promoters of regulated genes for common TFBS. We found a large number of potential TFBS significantly enriched at promoters of genes that were up-regulated with aging (Table S3). Of these, the TOP20 most strongly enriched TFBS were largely similar in the 24M and 29M group (Figures 3A,B). We could identify a number of common transcription factor families that together made up the bulk of the significantly enriched TFBS [Signal transducer and activator of transcription (STATs), Interferon regulatory factor (IRF), Spleen focus forming virus proviral integration oncogene (SPI), Activator protein 1, (AP1, composed of Fos, Jun and ATF family members), Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κ B), the GATA and the E26 transformation-specific (ETS) family of transcription factors (Table S3)], which are strongly associated with their roles in immune-related signaling (Peng, 2008). Of note, this set of TFs explained 44% of all up-regulated genes in 24- and 53% in 29-month-old mice. In fact, up to 87% of all up-regulated genes could be assigned to the action of enriched TFs (Figure 3C, Table S3).


De-regulation of gene expression and alternative splicing affects distinct cellular pathways in the aging hippocampus.

Stilling RM, Benito E, Gertig M, Barth J, Capece V, Burkhardt S, Bonn S, Fischer A - Front Cell Neurosci (2014)

Promoter analysis of aging-regulated genes for overrepresented transcription factor binding sites (TFBS). (A) Z-score (enrichments score) for different position weight matrices of known transcription factors in the set of gene up-regulated in 3 vs. 24-month-old mice. Higher Z-score means higher enrichment. Shown are only the top 20 most significantly enriched matrices. (B) The same analysis as described in (A) was performed for up-regulated genes in 3 vs. 29-month-old mice. (C) Pie charts showing the percentage of differentially expressed genes that can be explained by the selected core set of transcription factors.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4230043&req=5

Figure 3: Promoter analysis of aging-regulated genes for overrepresented transcription factor binding sites (TFBS). (A) Z-score (enrichments score) for different position weight matrices of known transcription factors in the set of gene up-regulated in 3 vs. 24-month-old mice. Higher Z-score means higher enrichment. Shown are only the top 20 most significantly enriched matrices. (B) The same analysis as described in (A) was performed for up-regulated genes in 3 vs. 29-month-old mice. (C) Pie charts showing the percentage of differentially expressed genes that can be explained by the selected core set of transcription factors.
Mentions: To further elucidate potential upstream mechanisms of the identified transcriptional program, we searched the promoters of regulated genes for common TFBS. We found a large number of potential TFBS significantly enriched at promoters of genes that were up-regulated with aging (Table S3). Of these, the TOP20 most strongly enriched TFBS were largely similar in the 24M and 29M group (Figures 3A,B). We could identify a number of common transcription factor families that together made up the bulk of the significantly enriched TFBS [Signal transducer and activator of transcription (STATs), Interferon regulatory factor (IRF), Spleen focus forming virus proviral integration oncogene (SPI), Activator protein 1, (AP1, composed of Fos, Jun and ATF family members), Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κ B), the GATA and the E26 transformation-specific (ETS) family of transcription factors (Table S3)], which are strongly associated with their roles in immune-related signaling (Peng, 2008). Of note, this set of TFs explained 44% of all up-regulated genes in 24- and 53% in 29-month-old mice. In fact, up to 87% of all up-regulated genes could be assigned to the action of enriched TFs (Figure 3C, Table S3).

Bottom Line: This approach enabled us to test differential expression of coding and non-coding transcripts, as well as differential splicing and RNA editing.We report a specific age-associated gene expression signature that is associated with major genetic risk factors for late-onset AD (LOAD).This signature is dominated by neuroinflammatory processes, specifically activation of the complement system at the level of increased gene expression, while de-regulation of neuronal plasticity appears to be mediated by compromised RNA splicing.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychiatry and Psychotherapy, University Medical Center Göttingen Göttingen, Germany ; Research Group for Epigenetics in Neurodegenerative Diseases, German Center for Neurodegenerative Diseases (DZNE) Göttingen Göttingen, Germany.

ABSTRACT
Aging is accompanied by gradually increasing impairment of cognitive abilities and constitutes the main risk factor of neurodegenerative conditions like Alzheimer's disease (AD). The underlying mechanisms are however not well understood. Here we analyze the hippocampal transcriptome of young adult mice and two groups of mice at advanced age using RNA sequencing. This approach enabled us to test differential expression of coding and non-coding transcripts, as well as differential splicing and RNA editing. We report a specific age-associated gene expression signature that is associated with major genetic risk factors for late-onset AD (LOAD). This signature is dominated by neuroinflammatory processes, specifically activation of the complement system at the level of increased gene expression, while de-regulation of neuronal plasticity appears to be mediated by compromised RNA splicing.

No MeSH data available.


Related in: MedlinePlus