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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

Differential exon usage and alternative splicing changes. (A) Number of hippocampal genes affected by differential expression, splicing or RNA-editing during aging. (B) Venn-diagrams showing the overlap of genes affected by expression and/or splicing between age groups. Note that there is little to no overlap. (C) Cellular pathways affected in 3- vs. 24/29-month-old mice by splicing or expression levels. The data on differential expression is based on all up- or down-regulated genes. (D) One of the overlapping genes was Spectrin β, non-erythrocytic 1 (Sptbn1), showing higher expression of exon 10 (pink box) in aged mice, suggesting higher abundance of the transcript isoform 2 (see Figure S2 for details on isoform and domain structure).
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Figure 4: Differential exon usage and alternative splicing changes. (A) Number of hippocampal genes affected by differential expression, splicing or RNA-editing during aging. (B) Venn-diagrams showing the overlap of genes affected by expression and/or splicing between age groups. Note that there is little to no overlap. (C) Cellular pathways affected in 3- vs. 24/29-month-old mice by splicing or expression levels. The data on differential expression is based on all up- or down-regulated genes. (D) One of the overlapping genes was Spectrin β, non-erythrocytic 1 (Sptbn1), showing higher expression of exon 10 (pink box) in aged mice, suggesting higher abundance of the transcript isoform 2 (see Figure S2 for details on isoform and domain structure).

Mentions: We therefore analyzed our RNA sequencing data with respect to differential exon usage. We found 436 annotated genes with significant changes in exon usage in the 24M group and 80 genes in the 29M group (Figure 4A; Table S4). Thus, changes in RNA splicing were, at least in the 24M group, quantitatively comparable to the changes observed in gene expression (Figure 4A). However, there was little to no overlap between genes affected by altered splicing and genes that were differentially expressed (Figure 4B). In fact, less than 1% of the DEG were also differently spliced in the 24M group, while zero overlap was found in the 29M group. This data indicates that differential gene expression and alternative splicing may affect different signaling pathways. To test this hypothesis, we analyzed the differentially spliced genes for enrichment of functional pathways. Our analysis revealed that there was a significant overrepresentation of genes associated with neuronal function including synaptogenesis, regulation of synaptic transmission, axonogenesis, neuron projection morphogenesis, postsynaptic density and long-term potentiation (Figure 4C, Table S5). Of note, none of these pathways was enriched in gene-set of DEG (Figure 4C). Vice versa, pathways linked to inflammatory response–which dominated the list of DEG–could not be identified within the group of alternatively spliced genes (Figure 4C). These data suggest that inflammatory responses in the aging hippocampus are driven by changes in differential gene expression whereas de-regulation of synaptic plasticity in mainly attributed to differential splicing. One of the genes that was differentially spliced in both 24- and 29-month-old mice when compared to their young counterparts was the Spectrin β, non-erythrocytic 1 gene (Sptbn1), that showed a specific upregulation in usage of exon 10 with age (Figure 4D). Sptbn1 is best known for its role in cytoskeleton regulation during neurite outgrowth (Lee et al., 2012), which is in agreement with our previous functional enrichment analysis. The inclusion of exon 10 suggests a shift towards higher expression of Sptbn1 isoform 2, resulting in a protein that has shorter and distinct N- and C- termini compared to isoform 1 and lacks the pleckstrin homology (PH) domain that is critical for tethering F-actin filaments to the plasma membrane (Figure 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)

Differential exon usage and alternative splicing changes. (A) Number of hippocampal genes affected by differential expression, splicing or RNA-editing during aging. (B) Venn-diagrams showing the overlap of genes affected by expression and/or splicing between age groups. Note that there is little to no overlap. (C) Cellular pathways affected in 3- vs. 24/29-month-old mice by splicing or expression levels. The data on differential expression is based on all up- or down-regulated genes. (D) One of the overlapping genes was Spectrin β, non-erythrocytic 1 (Sptbn1), showing higher expression of exon 10 (pink box) in aged mice, suggesting higher abundance of the transcript isoform 2 (see Figure S2 for details on isoform and domain structure).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 4: Differential exon usage and alternative splicing changes. (A) Number of hippocampal genes affected by differential expression, splicing or RNA-editing during aging. (B) Venn-diagrams showing the overlap of genes affected by expression and/or splicing between age groups. Note that there is little to no overlap. (C) Cellular pathways affected in 3- vs. 24/29-month-old mice by splicing or expression levels. The data on differential expression is based on all up- or down-regulated genes. (D) One of the overlapping genes was Spectrin β, non-erythrocytic 1 (Sptbn1), showing higher expression of exon 10 (pink box) in aged mice, suggesting higher abundance of the transcript isoform 2 (see Figure S2 for details on isoform and domain structure).
Mentions: We therefore analyzed our RNA sequencing data with respect to differential exon usage. We found 436 annotated genes with significant changes in exon usage in the 24M group and 80 genes in the 29M group (Figure 4A; Table S4). Thus, changes in RNA splicing were, at least in the 24M group, quantitatively comparable to the changes observed in gene expression (Figure 4A). However, there was little to no overlap between genes affected by altered splicing and genes that were differentially expressed (Figure 4B). In fact, less than 1% of the DEG were also differently spliced in the 24M group, while zero overlap was found in the 29M group. This data indicates that differential gene expression and alternative splicing may affect different signaling pathways. To test this hypothesis, we analyzed the differentially spliced genes for enrichment of functional pathways. Our analysis revealed that there was a significant overrepresentation of genes associated with neuronal function including synaptogenesis, regulation of synaptic transmission, axonogenesis, neuron projection morphogenesis, postsynaptic density and long-term potentiation (Figure 4C, Table S5). Of note, none of these pathways was enriched in gene-set of DEG (Figure 4C). Vice versa, pathways linked to inflammatory response–which dominated the list of DEG–could not be identified within the group of alternatively spliced genes (Figure 4C). These data suggest that inflammatory responses in the aging hippocampus are driven by changes in differential gene expression whereas de-regulation of synaptic plasticity in mainly attributed to differential splicing. One of the genes that was differentially spliced in both 24- and 29-month-old mice when compared to their young counterparts was the Spectrin β, non-erythrocytic 1 gene (Sptbn1), that showed a specific upregulation in usage of exon 10 with age (Figure 4D). Sptbn1 is best known for its role in cytoskeleton regulation during neurite outgrowth (Lee et al., 2012), which is in agreement with our previous functional enrichment analysis. The inclusion of exon 10 suggests a shift towards higher expression of Sptbn1 isoform 2, resulting in a protein that has shorter and distinct N- and C- termini compared to isoform 1 and lacks the pleckstrin homology (PH) domain that is critical for tethering F-actin filaments to the plasma membrane (Figure 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