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MiR-34 inhibits polycomb repressive complex 2 to modulate chaperone expression and promote healthy brain aging

Kennerdell, Jason R., Liu, Nan, Bonini, Nancy M.·2018·Nature Communications
DOI 10.1038/s41467-018-06592-5PMC PMC6180074
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Abstract

Aging is a prominent risk factor for neurodegenerative disease. Defining gene expression mechanisms affecting healthy brain aging should lead to insight into genes that modulate susceptibility to disease. To define such mechanisms, we have pursued analysis of miR-34 mutants in Drosophila . The miR-34 mutant brain displays a gene expression profile of accelerated aging, and miR-34 upregulation is a potent suppressor of polyglutamine-induced neurodegeneration. We demonstrate that Pcl and Su(z)12 , two components of polycomb repressive complex 2, (PRC2), are targets of miR-34 , with implications for age-associated processes. Because PRC2 confers the repressive H3K27me3 mark, we hypothesize that miR-34 modulates PRC2 activity to relieve silencing of genes promoting healthful aging. Gene expression profiling of the brains of hypomorphic mutants in Enhancer of zeste ( E(z) ), the enzymatic methyltransferase component of PRC2, revealed a younger brain transcriptome profile and identified the small heat shock proteins as key genes reduced in expression with age.

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Figures

Fig. 1 miR-34 targets 3′UTRs of Su(z)12 and Pcl. a, b Pcl and Su(z)12 are predicted targets of miR-34. The seed sequence of miR-34 has complementarity with the (a) Pcl 3′UTR and the (b) Su(z)12 3′UTR. The seed sequence is conserved in various homologs. Bottom, an engineered mutation in the seed sequence was also generated, red letters indicate base-pairing retained in the seed mutation, those with disrupted base-pairing are in black. c, d Luciferase assays confirm that miR-34 targets Pcl and Su(z)12. A reporter construct containing the 3′UTR of (c) Pcl or (d) Su(z)12 fused to Renilla luciferase was expressed in Drosophila SL2 cells and tested for a response to miR-34. Upon miR-34 upregulation, luciferase activity decreases in reporters containing the (c, left) Pcl 3′UTR and the (d, left) Su(z)12 3′UTR. Regulation of the Pcl 3′UTR by miR-34 was attenuated by a seed sequence mutation (c, right). Regulation of the Su(z)12 3′UTR by miR-34 was also attenuated by the seed sequence mutation (d, right). Two-way ANOVA indicated a significant interaction term for the Pcl 3′UTR (F1,8 = 8.5, p < 0.02), and Su(z)12 3′UTR (F1,8 = 17.5, p < 0.01). **p < 0.01, two-way ANOVA with Tukey post-test. Mean ± SEM, n = 3 wells. e, f The RNAi induced silencing complex (RISC) is required for regulation of the 3′UTR of Pcl and Su(z)12 by miR-34. The 3′UTR reporter constructs were expressed in DL1 cells treated with dsRNA to argonaute-1 (an essential component of RISC) or a control gene (β-gal). The cells were tested for a response to upregulation of miR-34 or a control microRNA (miR-277). In cells treated with β-gal dsRNA, upregulation of miR-34 resulted in decreased reporter expression. In cells treated with AGO1 dsRNA, the effect of miR-34 on reporter expression was eliminated (e, for Pcl 3′UTR reporter two-way ANOVA indicated a significant interaction term, F1,8 = 107, p < 0.01) or attenuated (f for Su(z)12 3′UTR reporter two-way ANOVA indicated a significant interaction term, F1,8 = 73, p < 0.01). **p < 0.01, Two-way ANOVA, Tukey post-test. Mean ± SEM, n = 3 wells
Fig. 1 miR-34 targets 3′UTRs of Su(z)12 and Pcl. a, b Pcl and Su(z)12 are predicted targets of miR-34. The seed sequence of miR-34 has complementarity with the (a) Pcl 3′UTR and the (b) Su(z)12 3′UTR. The seed sequence is conserved in various homologs. Bottom, an engineered mutation in the seed sequence was also generated, red letters indicate base-pairing retained in the seed mutation, those with disrupted base-pairing are in black. c, d Luciferase assays confirm that miR-34 targets Pcl and Su(z)12. A reporter construct containing the 3′UTR of (c) Pcl or (d) Su(z)12 fused to Renilla luciferase was expressed in Drosophila SL2 cells and tested for a response to miR-34. Upon miR-34 upregulation, luciferase activity decreases in reporters containing the (c, left) Pcl 3′UTR and the (d, left) Su(z)12 3′UTR. Regulation of the Pcl 3′UTR by miR-34 was attenuated by a seed sequence mutation (c, right). Regulation of the Su(z)12 3′UTR by miR-34 was also attenuated by the seed sequence mutation (d, right). Two-way ANOVA indicated a significant interaction term for the Pcl 3′UTR (F1,8 = 8.5, p < 0.02), and Su(z)12 3′UTR (F1,8 = 17.5, p < 0.01). **p < 0.01, two-way ANOVA with Tukey post-test. Mean ± SEM, n = 3 wells. e, f The RNAi induced silencing complex (RISC) is required for regulation of the 3′UTR of Pcl and Su(z)12 by miR-34. The 3′UTR reporter constructs were expressed in DL1 cells treated with dsRNA to argonaute-1 (an essential component of RISC) or a control gene (β-gal). The cells were tested for a response to upregulation of miR-34 or a control microRNA (miR-277). In cells treated with β-gal dsRNA, upregulation of miR-34 resulted in decreased reporter expression. In cells treated with AGO1 dsRNA, the effect of miR-34 on reporter expression was eliminated (e, for Pcl 3′UTR reporter two-way ANOVA indicated a significant interaction term, F1,8 = 107, p < 0.01) or attenuated (f for Su(z)12 3′UTR reporter two-way ANOVA indicated a significant interaction term, F1,8 = 73, p < 0.01). **p < 0.01, Two-way ANOVA, Tukey post-test. Mean ± SEM, n = 3 wellsCC BY · PubMed Central
Fig. 2 Pcl is a target of miR-34 in the brain. a, b Pcl protein levels are deregulated in miR-34 mutants. a Western immunoblots. b Quantitation of immunoblots. Pcl levels decrease with age in both wild-type and miR-34 mutants. Pcl levels were higher than wild-type control at 20d. Protein samples from dissected brains. Western immunoblot, with tubulin as the loading control. Pcl protein levels are normalized to tubulin. Mean ± SEM, n = 9 biological replicates. Significant main effects were observed (genotype: F1,32 = 12.7, p < 0.01 age: F1,32 = 232, p < 0.001). (*p < 0.05, **p < 0.01, two-way ANOVA with Tukey post-test)
Fig. 2 Pcl is a target of miR-34 in the brain. a, b Pcl protein levels are deregulated in miR-34 mutants. a Western immunoblots. b Quantitation of immunoblots. Pcl levels decrease with age in both wild-type and miR-34 mutants. Pcl levels were higher than wild-type control at 20d. Protein samples from dissected brains. Western immunoblot, with tubulin as the loading control. Pcl protein levels are normalized to tubulin. Mean ± SEM, n = 9 biological replicates. Significant main effects were observed (genotype: F1,32 = 12.7, p < 0.01 age: F1,32 = 232, p < 0.001). (*p < 0.05, **p < 0.01, two-way ANOVA with Tukey post-test)CC BY · PubMed Central
Fig. 3 Su(z)12 is a target of miR-34 in the brain. a, b Su(z)12 protein levels are deregulated in miR-34 mutants. Su(z)12 protein was detected using a transgene containing the Su(z)12 genomic region tagged with the HA epitope on the C-terminus of the predicted protein (Su(z)12-C-term HA). Su(z)12 levels decreased with age in wild-type, but remained elevated in miR-34 mutants. Protein samples from dissected brains. Su(z)12-C-term HA protein levels were normalized to tubulin loading control. Mean ± SEM, n = 3 biological replicates. Significant main effects were observed (genotype: F1,8 = 68, p < 0.001 age: F1,8 = 101, p < 0.001). (*p < 0.05, **p < 0.01, two-way ANOVA with Tukey post-test).c, d The regulation of Su(z)12 protein levels by miR-34 is dependent upon the miR-34 seed sequence in the 3′UTR of the Su(z)12 transcript. The Su(z)12-C-term HA-mutant 3′UTR transgene contains a mutation in the miR-34 seed sequence that relieves the transcript from regulation by miR-34 (see Fig. 1d). Su(z)12-C-term HA-mutant 3′UTR protein levels still decrease with age, but are no longer increased in miR-34 mutants. The difference between wild-type at 20d and miR-34 mutant at 20d is not significant. Protein samples from dissected brains. Quantification of Su(z)12-C-term HA-mutant 3′UTR protein levels using Western immunoblotting, normalized to tubulin loading control. Mean ± SEM, n = 3 biological replicates. Significant main effects were observed (genotype: F1,8 = 17, p < 0.01 age: F1,8 = 28.5, p < 0.001). (*p < 0.05, two-way ANOVA with Tukey post-test)
Fig. 3 Su(z)12 is a target of miR-34 in the brain. a, b Su(z)12 protein levels are deregulated in miR-34 mutants. Su(z)12 protein was detected using a transgene containing the Su(z)12 genomic region tagged with the HA epitope on the C-terminus of the predicted protein (Su(z)12-C-term HA). Su(z)12 levels decreased with age in wild-type, but remained elevated in miR-34 mutants. Protein samples from dissected brains. Su(z)12-C-term HA protein levels were normalized to tubulin loading control. Mean ± SEM, n = 3 biological replicates. Significant main effects were observed (genotype: F1,8 = 68, p < 0.001 age: F1,8 = 101, p < 0.001). (*p < 0.05, **p < 0.01, two-way ANOVA with Tukey post-test).c, d The regulation of Su(z)12 protein levels by miR-34 is dependent upon the miR-34 seed sequence in the 3′UTR of the Su(z)12 transcript. The Su(z)12-C-term HA-mutant 3′UTR transgene contains a mutation in the miR-34 seed sequence that relieves the transcript from regulation by miR-34 (see Fig. 1d). Su(z)12-C-term HA-mutant 3′UTR protein levels still decrease with age, but are no longer increased in miR-34 mutants. The difference between wild-type at 20d and miR-34 mutant at 20d is not significant. Protein samples from dissected brains. Quantification of Su(z)12-C-term HA-mutant 3′UTR protein levels using Western immunoblotting, normalized to tubulin loading control. Mean ± SEM, n = 3 biological replicates. Significant main effects were observed (genotype: F1,8 = 17, p < 0.01 age: F1,8 = 28.5, p < 0.001). (*p < 0.05, two-way ANOVA with Tukey post-test)CC BY · PubMed Central
Fig. 4 H3K27me3 levels with age and in miR-34 mutants. a, b H3K27me3 levels with age in heads. Total histone was purified from Drosophila heads at 3d, 20d, and 40d. H3K27me3 gradually increased with age, and increased faster in miR-34 mutants. Histone H3 is a control for total H3 levels. Quantification of relative levels of H3K27me3 was normalized to the total histone H3. Mean ± SEM, n = 5 biological replicates. Significant main effects were observed (genotype: F1,20 = 13.5, p < .01, age: F2,20 = 18, p < .001). (*p < 0.05, **p < 0.01 two-way ANOVA, with Tukey post-test).c, d H3K27me3 levels are increased in the brain of aged miR-34 mutants. Protein samples were derived from dissected brains. H3K27me3 protein levels are normalized to total Histone H3 levels. Mean ± SEM, n = 5 biological replicates. Significant interaction and main effect were observed (genotype: F1, 16 = 4.7, p < .05, age: F1, 16 = 0.28, ns, interaction: F1, 16 = 2.06, p < .001. (*p < 0.05, **p < 0.01 two-way ANOVA with Tukey post-test). e, f H3K9me3 levels are affected in miR-34 mutants. Protein samples from dissected brains. H3K9me3 levels were normalized to total histone H3. Mean ± SEM, n = 5 biological replicates. A significant interaction was observed (interaction: F1 16 = 8.76, p < 0.01, genotype: F1,16 = 1.1, p > .05, age: F1,16 = .2.7, p > .05). (*p < 0.05, two-way ANOVA, Tukey post-test)
Fig. 4 H3K27me3 levels with age and in miR-34 mutants. a, b H3K27me3 levels with age in heads. Total histone was purified from Drosophila heads at 3d, 20d, and 40d. H3K27me3 gradually increased with age, and increased faster in miR-34 mutants. Histone H3 is a control for total H3 levels. Quantification of relative levels of H3K27me3 was normalized to the total histone H3. Mean ± SEM, n = 5 biological replicates. Significant main effects were observed (genotype: F1,20 = 13.5, p < .01, age: F2,20 = 18, p < .001). (*p < 0.05, **p < 0.01 two-way ANOVA, with Tukey post-test).c, d H3K27me3 levels are increased in the brain of aged miR-34 mutants. Protein samples were derived from dissected brains. H3K27me3 protein levels are normalized to total Histone H3 levels. Mean ± SEM, n = 5 biological replicates. Significant interaction and main effect were observed (genotype: F1, 16 = 4.7, p < .05, age: F1, 16 = 0.28, ns, interaction: F1, 16 = 2.06, p < .001. (*p < 0.05, **p < 0.01 two-way ANOVA with Tukey post-test). e, f H3K9me3 levels are affected in miR-34 mutants. Protein samples from dissected brains. H3K9me3 levels were normalized to total histone H3. Mean ± SEM, n = 5 biological replicates. A significant interaction was observed (interaction: F1 16 = 8.76, p < 0.01, genotype: F1,16 = 1.1, p > .05, age: F1,16 = .2.7, p > .05). (*p < 0.05, two-way ANOVA, Tukey post-test)CC BY · PubMed Central
Fig. 5 Neural degeneration due to pathogenic ATXN3 is suppressed by PRC2 mutations. a The fly compound eye is comprised of individual optical units called ommatidia, which are arranged in a hexagonal array. Within each ommatidium are eight photoreceptors (PR), of which seven are visible by this assay. Each panel shows eleven ommatidial units; flies are 21d old. Whereas wild-type has seven PRs in each ommatidial unit, expression of SCA3trQ78 results in PR loss. Heterozygous mutation of Pcl or Su(z)12 mitigates PR cell loss. Heterozygous reduction of E(z) also mitigates PR loss. Scale bar indicates 10 μm. b Histogram showing the distribution of photoreceptors (PR) per ommatidium at 21d in wild-type (black, 7.0 PR/ommatidium), SCA3trQ78 (red, average 1.72 ± 0.06 SEM noted with red arrowhead, n = 24 flies, 240 ommatidia), and SCA3trQ78 with a heterozygous Pcl allele (green, average 4.02 ± 0.10 SEM noted with green arrowhead, n = 20 flies, 200 ommatidia). p < 0.001, Kruskal–Wallis test, Dunn post-test. Genotypes: SCA3trQ78 is rh1-GAL4, UAS-SCA3trQ78/+; Pcl5/+ is Pcl5/+; rh1-GAL4, UAS-SCA3trQ78/+. c Histogram showing the distribution of photoreceptors (PR) per ommatidium at 21d in wild-type (black, 7.0 PR), SCA3trQ78 (red, average 1.92 ± 0.06 SEM noted with red arrowhead, n = 29 flies, 291 ommatidia), and SCA3trQ78 heterozygous for a Su(z)12 allele (green, average 4.93 ± 0.11 SEM noted with arrowhead, n = 20 flies, 197 ommatidia). p < 0.001, Kruskal–Wallis test, Dunn post-test. Genotypes: SCA3trQ78 is rh1-GAL4, UAS-SCA3trQ78/+; Su(z)122/+ is rh1-GAL4, UAS-SCA3trQ78/Su(z)122. d Histogram showing the distribution of photoreceptors (PR) per ommatidium at 21d in wild-type (black, 7.0 PR), SCA3trQ78 (red, average 1.86 ± 0.06 SEM noted with red arrowhead, n = 19 flies, 379 ommatidia), and SCA3trQ78 heterozygous for an E(z) allele (green, average 3.44 ± 0.16 SEM noted with arrowhead, n = 19 flies, 349 ommatidia). p < 0.001, Kruskal–Wallis test, Dunn post-test. Genotypes: SCA3trQ78 is rh1-GAL4, UAS-SCA3trQ78/+; E(z)731/+ is rh1-GAL4, UAS-SCA3trQ78/E(z)731
Fig. 5 Neural degeneration due to pathogenic ATXN3 is suppressed by PRC2 mutations. a The fly compound eye is comprised of individual optical units called ommatidia, which are arranged in a hexagonal array. Within each ommatidium are eight photoreceptors (PR), of which seven are visible by this assay. Each panel shows eleven ommatidial units; flies are 21d old. Whereas wild-type has seven PRs in each ommatidial unit, expression of SCA3trQ78 results in PR loss. Heterozygous mutation of Pcl or Su(z)12 mitigates PR cell loss. Heterozygous reduction of E(z) also mitigates PR loss. Scale bar indicates 10 μm. b Histogram showing the distribution of photoreceptors (PR) per ommatidium at 21d in wild-type (black, 7.0 PR/ommatidium), SCA3trQ78 (red, average 1.72 ± 0.06 SEM noted with red arrowhead, n = 24 flies, 240 ommatidia), and SCA3trQ78 with a heterozygous Pcl allele (green, average 4.02 ± 0.10 SEM noted with green arrowhead, n = 20 flies, 200 ommatidia). p < 0.001, Kruskal–Wallis test, Dunn post-test. Genotypes: SCA3trQ78 is rh1-GAL4, UAS-SCA3trQ78/+; Pcl5/+ is Pcl5/+; rh1-GAL4, UAS-SCA3trQ78/+. c Histogram showing the distribution of photoreceptors (PR) per ommatidium at 21d in wild-type (black, 7.0 PR), SCA3trQ78 (red, average 1.92 ± 0.06 SEM noted with red arrowhead, n = 29 flies, 291 ommatidia), and SCA3trQ78 heterozygous for a Su(z)12 allele (green, average 4.93 ± 0.11 SEM noted with arrowhead, n = 20 flies, 197 ommatidia). p < 0.001, Kruskal–Wallis test, Dunn post-test. Genotypes: SCA3trQ78 is rh1-GAL4, UAS-SCA3trQ78/+; Su(z)122/+ is rh1-GAL4, UAS-SCA3trQ78/Su(z)122. d Histogram showing the distribution of photoreceptors (PR) per ommatidium at 21d in wild-type (black, 7.0 PR), SCA3trQ78 (red, average 1.86 ± 0.06 SEM noted with red arrowhead, n = 19 flies, 379 ommatidia), and SCA3trQ78 heterozygous for an E(z) allele (green, average 3.44 ± 0.16 SEM noted with arrowhead, n = 19 flies, 349 ommatidia). p < 0.001, Kruskal–Wallis test, Dunn post-test. Genotypes: SCA3trQ78 is rh1-GAL4, UAS-SCA3trQ78/+; E(z)731/+ is rh1-GAL4, UAS-SCA3trQ78/E(z)731CC BY · PubMed Central
Fig. 6 PRC2 mutations suppress accumulation of pathogenic polyglutamine protein. a Animals expressing SCA3trQ78 in the photoreceptor cells have prominent nuclear inclusions. 3d animals, antibody to HA tag present on the SCA3trQ78 transgene (green). Dapi (blue), nuclei. Genotype: rh1-GAL4, UAS-SCA3trQ78/+. Scale bar indicates 10 μm. b Decreasing Pcl activity decreased SCA3trQ78 inclusions of 3d animals. Genotype: Pcl5/+; rh1-GAL4, UAS-SCA3trQ78/+. c Decreasing Su(z)12 activity decreased SCA3trQ78 inclusions of 3d animals. Genotype: rh1-GAL4, UAS-SCA3trQ78/Su(z)122. d Average number of inclusions detected in the region of interest in various genotypes. Mean ± SEM, n = 3 animals, using the average of at least 4 sections per animal. F2,6 = 27.84, p < 0.001, one-way ANOVA, with Tukey post-test **p < 0.01. e Mean size of inclusions. The size of inclusions detected in at least 4 sections per animal was determined, with the control cohort adjusted to 100%. The average size of inclusions was smaller in animals heterozygous for Pcl5 or Su(z)122. Mean ± SEM, n = 3 animals, using the average of at least 4 sections per animal. F2,6 = 30.89, p < 0.001, one-way ANOVA, with Tukey post-test, **p < 0.01
Fig. 6 PRC2 mutations suppress accumulation of pathogenic polyglutamine protein. a Animals expressing SCA3trQ78 in the photoreceptor cells have prominent nuclear inclusions. 3d animals, antibody to HA tag present on the SCA3trQ78 transgene (green). Dapi (blue), nuclei. Genotype: rh1-GAL4, UAS-SCA3trQ78/+. Scale bar indicates 10 μm. b Decreasing Pcl activity decreased SCA3trQ78 inclusions of 3d animals. Genotype: Pcl5/+; rh1-GAL4, UAS-SCA3trQ78/+. c Decreasing Su(z)12 activity decreased SCA3trQ78 inclusions of 3d animals. Genotype: rh1-GAL4, UAS-SCA3trQ78/Su(z)122. d Average number of inclusions detected in the region of interest in various genotypes. Mean ± SEM, n = 3 animals, using the average of at least 4 sections per animal. F2,6 = 27.84, p < 0.001, one-way ANOVA, with Tukey post-test **p < 0.01. e Mean size of inclusions. The size of inclusions detected in at least 4 sections per animal was determined, with the control cohort adjusted to 100%. The average size of inclusions was smaller in animals heterozygous for Pcl5 or Su(z)122. Mean ± SEM, n = 3 animals, using the average of at least 4 sections per animal. F2,6 = 30.89, p < 0.001, one-way ANOVA, with Tukey post-test, **p < 0.01CC BY · PubMed Central
Fig. 7 The small HSP chaperone family is regulated with age and by E(z). RNA-seq was performed on 20d brain tissue from animals transheterozygous for the E(z)61 and E(z)731 alleles, and on wild-type. Because the E(z)61 allele is temperature-sensitive, two temperatures were used, 25 °C (permissive) and 29 °C (restrictive). Wild-type brains, 3d (young) and 20d (aged) 25 °C, were also dissected and RNA-seq performed. Genes were selected as differentially expressed using a Benjamini-Hochberg p < 0.05 and at least a 0.5 absolute log2 fold-change. a Gene overlap. Twenty genes had an expression pattern consistent with being a target of E(z) with age in the brain: upregulated in E(z) and downregulated with age. b, c Differential gene expression analysis of sHSP family genes. Gray data points are genes not differentially expressed. Black data points are genes with significant changes in expression (p<0.05, DEseq2 negative binomial generalized linear model, Benjamini-Hochberg correction). Red circles mark the sHSP family members Hsp23, Hsp26, Hsp27, Hsp67Ba, Hsp67Bc, l(2)efl, CG4461, CG7409, CG13133, and CG14207. Hsp22 was not included because no reads mapped uniquely to this gene. b Small HSP genes are upregulated in 20d E(z) mutant brains. Among these, Hsp23, Hsp26, Hsp27, and CG7409 were significantly elevated in E(z) mutants (p < 0.05, DESeq2 negative binomial generalized linear model, Bonferroni correction), compared to 20d wild-type. c Small HSPs are downregulated in the brain with age. Hsp23, Hsp26, Hsp27, Hsp67Ba, and Hsp67Bc were significantly decreased (p < 0.05, DESeq2 negative binomial generalized linear model, Bonferroni correction) with age comparing 20d to 3d wild-type. d, e Sequence coverage at specific loci indicates silencing of sHSPs with age, and release from silencing in E(z) mutants. Read coverage at the individual sHSP loci (d) Hsp26 and (e) Hsp27 demonstrates a decrease in expression of sHSPs with age. Young wild-type animals express high levels (blue) while aged wild-type animals have less sHSP expression (yellow). E(z) mutation (purple) results in increased sHSP levels compared to age and temperature matched controls (orange). Y-axis indicates sequence read coverage from one biological replicate from each cohort. Each library shown had similar depth of sequencing (24–26 × 106 reads). X-axis indicates position along the gene. Expression levels in E(z) are high, similar to young brain tissue
Fig. 7 The small HSP chaperone family is regulated with age and by E(z). RNA-seq was performed on 20d brain tissue from animals transheterozygous for the E(z)61 and E(z)731 alleles, and on wild-type. Because the E(z)61 allele is temperature-sensitive, two temperatures were used, 25 °C (permissive) and 29 °C (restrictive). Wild-type brains, 3d (young) and 20d (aged) 25 °C, were also dissected and RNA-seq performed. Genes were selected as differentially expressed using a Benjamini-Hochberg p < 0.05 and at least a 0.5 absolute log2 fold-change. a Gene overlap. Twenty genes had an expression pattern consistent with being a target of E(z) with age in the brain: upregulated in E(z) and downregulated with age. b, c Differential gene expression analysis of sHSP family genes. Gray data points are genes not differentially expressed. Black data points are genes with significant changes in expression (p<0.05, DEseq2 negative binomial generalized linear model, Benjamini-Hochberg correction). Red circles mark the sHSP family members Hsp23, Hsp26, Hsp27, Hsp67Ba, Hsp67Bc, l(2)efl, CG4461, CG7409, CG13133, and CG14207. Hsp22 was not included because no reads mapped uniquely to this gene. b Small HSP genes are upregulated in 20d E(z) mutant brains. Among these, Hsp23, Hsp26, Hsp27, and CG7409 were significantly elevated in E(z) mutants (p < 0.05, DESeq2 negative binomial generalized linear model, Bonferroni correction), compared to 20d wild-type. c Small HSPs are downregulated in the brain with age. Hsp23, Hsp26, Hsp27, Hsp67Ba, and Hsp67Bc were significantly decreased (p < 0.05, DESeq2 negative binomial generalized linear model, Bonferroni correction) with age comparing 20d to 3d wild-type. d, e Sequence coverage at specific loci indicates silencing of sHSPs with age, and release from silencing in E(z) mutants. Read coverage at the individual sHSP loci (d) Hsp26 and (e) Hsp27 demonstrates a decrease in expression of sHSPs with age. Young wild-type animals express high levels (blue) while aged wild-type animals have less sHSP expression (yellow). E(z) mutation (purple) results in increased sHSP levels compared to age and temperature matched controls (orange). Y-axis indicates sequence read coverage from one biological replicate from each cohort. Each library shown had similar depth of sequencing (24–26 × 106 reads). X-axis indicates position along the gene. Expression levels in E(z) are high, similar to young brain tissueCC BY · PubMed Central
Fig. 8 E(z) mutants have a chronologically younger aged transcriptome. a Heatmap of positively age-correlated genes. A set of genes previously shown to be positively correlated with age in the Drosophila brain6 were analyzed using hierarchical clustering to assess their pattern of expression in the E(z) mutant combination. Magenta indicates high and green indicates low expression. Colored bars on the side indicate genotype, age, and temperature. Colored bars on the top refer to genes downregulated in E(z) mutants, with color indicating the log2-fold-change threshold. Brains from young animals have the lowest expression of positively age-correlated genes, followed by brains from 20d E(z) mutants. Brains from 20d wild-type animals cultivated at 29 °C generally have the highest expression levels. For two clusters of genes (blue genes), expression is decreased in E(z) mutants relative to age-matched and temperature-matched wild-type controls. b Genes positively correlated with age are disproportionately downregulated in E(z) mutants. Gray data points are genes not differentially expressed. Black data points are differentially expressed genes (p < 0.05). Red circles are genes corresponding to probe sets previously defined as positively correlated with age6. The overlap between genes called downregulated in E(z) and the genes positively-correlated with age is statistically significant (p-value = 0.001, hypergeometric test). c Significant overlap between genes positively correlated with age and genes downregulated in E(z) mutants indicate a less advanced age transcriptome profile. Comparison of two ranked lists of genes: the list of genes ranked by degree of downregulation in E(z) mutants (Supplementary Data 1) and top 500 genes ranked by positive correlation with age Supplementary Data 2. E(z) regulated genes were ranked by the product of the -log(p-value) and the moderated log2 fold-change (low to high). All positively age-correlated genes were ranked according to decreasing significance of the correlation with age among all genes with a positive correlation, followed by genes with negative correlation which were ranked according to increasing significance (Supplementary Data 2). Yellow bars indicate 95% confidence intervals. By contrast, the correlation from the data (black line) is outside of the confidence intervals and thus is statistically significant (p < 0.01, calculated empirically using permutations, orderedList R-package)
Fig. 8 E(z) mutants have a chronologically younger aged transcriptome. a Heatmap of positively age-correlated genes. A set of genes previously shown to be positively correlated with age in the Drosophila brain6 were analyzed using hierarchical clustering to assess their pattern of expression in the E(z) mutant combination. Magenta indicates high and green indicates low expression. Colored bars on the side indicate genotype, age, and temperature. Colored bars on the top refer to genes downregulated in E(z) mutants, with color indicating the log2-fold-change threshold. Brains from young animals have the lowest expression of positively age-correlated genes, followed by brains from 20d E(z) mutants. Brains from 20d wild-type animals cultivated at 29 °C generally have the highest expression levels. For two clusters of genes (blue genes), expression is decreased in E(z) mutants relative to age-matched and temperature-matched wild-type controls. b Genes positively correlated with age are disproportionately downregulated in E(z) mutants. Gray data points are genes not differentially expressed. Black data points are differentially expressed genes (p < 0.05). Red circles are genes corresponding to probe sets previously defined as positively correlated with age6. The overlap between genes called downregulated in E(z) and the genes positively-correlated with age is statistically significant (p-value = 0.001, hypergeometric test). c Significant overlap between genes positively correlated with age and genes downregulated in E(z) mutants indicate a less advanced age transcriptome profile. Comparison of two ranked lists of genes: the list of genes ranked by degree of downregulation in E(z) mutants (Supplementary Data 1) and top 500 genes ranked by positive correlation with age Supplementary Data 2. E(z) regulated genes were ranked by the product of the -log(p-value) and the moderated log2 fold-change (low to high). All positively age-correlated genes were ranked according to decreasing significance of the correlation with age among all genes with a positive correlation, followed by genes with negative correlation which were ranked according to increasing significance (Supplementary Data 2). Yellow bars indicate 95% confidence intervals. By contrast, the correlation from the data (black line) is outside of the confidence intervals and thus is statistically significant (p < 0.01, calculated empirically using permutations, orderedList R-package)CC BY · PubMed Central
Fig. 9 Model for opposing activities of miR-34 and the PRC2 complex in aging. Our data suggest that miR-34 represses translation of Pcl and Su(z)12 transcripts, resulting in a reduction of PRC2 activity and less H3K27me3. In the miR-34 mutant and normally with age, H3K27me3 accumulates globally and at particular genes, resulting in decreased transcription. Some of these genes (the small heat shock proteins (sHSPs) are highlighted here) appear critical for healthy brain aging. Mutation of E(z) reduces the activity of PRC2, resulting in less suppression of sHSPs and a younger brain transcriptome profile. These data indicate that reduction of the activity of PRC2 with age will be associated with healthier brain aging and protection from deleterious consequences to the brain with age, including neurodegenerative disease
Fig. 9 Model for opposing activities of miR-34 and the PRC2 complex in aging. Our data suggest that miR-34 represses translation of Pcl and Su(z)12 transcripts, resulting in a reduction of PRC2 activity and less H3K27me3. In the miR-34 mutant and normally with age, H3K27me3 accumulates globally and at particular genes, resulting in decreased transcription. Some of these genes (the small heat shock proteins (sHSPs) are highlighted here) appear critical for healthy brain aging. Mutation of E(z) reduces the activity of PRC2, resulting in less suppression of sHSPs and a younger brain transcriptome profile. These data indicate that reduction of the activity of PRC2 with age will be associated with healthier brain aging and protection from deleterious consequences to the brain with age, including neurodegenerative diseaseCC BY · PubMed Central

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Metadata

Authors
Kennerdell, J. R., Liu, N., & Bonini, N. M.
ORCID
Bonini, Nancy M.
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2018-10-10
Volume
9
Issue
1
ISSN
2041-1723
DOI
10.1038/s41467-018-06592-5
PMC
PMC6180074
Cited by
56
References
10
Language
en
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