RNA sequencing reveals pronounced changes in the noncoding transcriptome of aging synaptosomes

Neurobiology of Aging 56 (2017) 67e77

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Neurobiology of Aging journal homepage: www.elsevier.com/locate/neuaging

RNA sequencing reveals pronounced changes in the noncoding transcriptome of aging synaptosomes Bei Jun Chen a,1, Uwe Ueberham b,1, James D. Mills c, Ludmil Kirazov b, d, Evgeni Kirazov b, d, Mara Knobloch b, Jana Bochmann b, Renate Jendrek b, Konii Takenaka a, Nicola Bliim a, Thomas Arendt b, Michael Janitz a, * a

School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia Paul-Flechsig-Institute for Brain Research, University of Leipzig, School of Medicine, Leipzig, Germany Department of (Neuro)Pathology, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands d Institute of Experimental Morphology, Pathology and Anthropology with Museum, Bulgarian Academy of Sciences, Sofia, Bulgaria b c

a r t i c l e i n f o

a b s t r a c t

Article history: Received 15 January 2017 Received in revised form 31 March 2017 Accepted 8 April 2017 Available online 18 April 2017

Normal aging is associated with impairments in cognitive functions. These alterations are caused by diminutive changes in the biology of synapses, and ineffective neurotransmission, rather than loss of neurons. Hitherto, only a few studies, exploring molecular mechanisms of healthy brain aging in higher vertebrates, utilized synaptosomal fractions to survey local changes in aging-related transcriptome dynamics. Here we present, for the first time, a comparative analysis of the synaptosomes transcriptome in the aging mouse brain using RNA sequencing. Our results show changes in the expression of genes contributing to biological pathways related to neurite guidance, synaptosomal physiology, and RNA splicing. More intriguingly, we also discovered alterations in the expression of thousands of novel, unannotated lincRNAs during aging. Further, detailed characterization of the cleavage and polyadenylation factor I subunit 1 (Clp1) mRNA and protein expression indicates its increased expression in neuronal processes of hippocampal stratum radiatum in aging mice. Together, our study uncovers a new layer of transcriptional regulation which is targeted by aging within the local environment of interconnecting neuronal cells. Ó 2017 Elsevier Inc. All rights reserved.

Keywords: Synaptosome Brain aging Transcriptome RNA-Seq lincRNAs Clp1

1. Introduction Human brain aging is characterized by decreasing cognitive function of various severities affecting 60% of aged population. Decline in cognitive capabilities might be the only symptom of aging in otherwise healthy humans. Even more important is agingrelated development of neurodegenerative diseases, which together with nonpathologic cognitive decline present a significant burden to society and the health care system. Despite advances in understanding both age-related neurodegenerative diseases and nonpathologic age-related changes in the brain, little is known about the etiology of age-related cognitive decline. As a result, development of targeted therapeutics designed to prevent or reverse loss of cognitive function in aging individuals has proven

* Corresponding author at: School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia. Tel.: þ61 2 938 58608; fax: þ61 2 938 51483. E-mail address: [email protected] (M. Janitz). 1 These authors contributed equally to the paper as first co-authors. 0197-4580/$ e see front matter Ó 2017 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.neurobiolaging.2017.04.005

difficult, and currently, few effective treatments for age-related cognitive impairment exist (Orgeta et al., 2015). Plasticity, memory encoding, and consolidation are dependent on local protein synthesis, initiated and regulated at a site within the synapse (Bliim et al., 2016; Pfeiffer and Huber, 2006). Alongside rodent brain slices and primary neuronal cultures, synaptosomes (isolated nerve terminals) have been an important model system for studying the molecular mechanisms of synaptic function in the brain. Synaptosome experiments were instrumental in first identifying neurotransmitters, including the proof that amino acids, such as glutamate, were indeed neurotransmitters (Levy et al., 1973). Genome-wide approaches to assess synaptosomal transcriptome in the postnatal rat hippocampus and perturbations of synaptic gene expression as an effect of alcohol consumption and in incipient Alzheimer’s disease (AD) provided the first insights into local specificity of gene expression in these fundamental neuronal structures (Cajigas et al., 2012; Most et al., 2015; Williams et al., 2009). These initial studies have, however, been performed using microarrays or early next-generation sequencing technologies and hence they inherently lack the comprehensiveness available when

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using current RNA sequencing approaches. This limitation in particular relates to surveying of a noncoding part of the transcriptome. Hitherto, there is a lack of comparative studies of the changes in local synaptic transcriptome as a result of healthy aging. A rapidly growing number of studies clearly show that intergenic regions of the human genome have tissue-specific transcription. This so-called pervasive transcription results in generation of a variety of noncoding RNA species, including long noncoding RNA (lncRNA) transcripts (i.e., longer than 200 bp), which are involved in a wide range of structural, regulatory, and catalytic processes (Ward et al., 2015). LncRNAs are transcribed in complex intergenic, overlapping, and antisense patterns relative to adjacent protein-coding genes, suggesting that many lncRNAs regulate the expression of these genes (Clark and Mattick, 2011; Mills et al., 2016a). LncRNAs also participate in a wide array of subcellular processes, including the formation and function of cellular organelles (Chen and Carmichael, 2009; Tripathi et al., 2010). Interestingly, half of all lncRNA is expressed in the central nervous system, including the brain (Mehler and Mattick, 2007). The most recently identified subclass of lncRNAs are long intervening noncoding RNAs (lincRNAs), located between protein-coding loci (Ulitsky and Bartel, 2013). LincRNAs have been shown to regulate epigenetic markers and gene expression (Zhou et al., 2015). LincRNA expression is strikingly tissue-specific compared with coding genes, and lincRNAs are typically coexpressed with their neighboring genes, albeit to a similar extent to that of pairs of neighboring protein-coding genes (Cabili et al., 2011). LincRNA expression is also perturbed in neurodegenerative diseases such as multiple system atrophy (Mills et al., 2015, 2016b) and Alzheimer’s disease (Magistri et al., 2015). Here we present, for the first time, a comparative analysis of the synaptosome transcriptome in aging mouse brain. Our results show that, along with changes in expression of genes contributing to biological pathways related to neurite guidance and synaptosomal physiology, a vast number of novel, unannotated lincRNAs is also affected within local synaptic environment as a result of aging. Moreover, a detailed analysis of increased mRNA and protein expression levels of the tRNA metabolism regulator, cleavage, and polyadenylation factor I subunit 1 (Clp1), in old synapses suggests that brain aging is accompanied with augmented clearance of tRNA splicing by-products. 2. Materials and methods 2.1. Mice strains and brain tissue isolation Wild-type C57BL/6 were housed in standard cages and fed standard lab chow and water ad libitum. Animal experiments were carried out in accordance with the European Council Directive of 24 November 1986 (86/609/EEC) and were approved by the local authorities. For the synaptosome studies, cerebral cortices of young (w2.5 months) and old (w23 months) mice were dissected and immediately used for further preparation. For Western blot analysis or total RNA preparation, the brain tissue was frozen at 80  C and stored for subsequent processing. For immunohistochemical analysis, mice were anaesthetized and transcardially perfused with 0.1-M phosphate buffered saline (PBS) and then with 4% paraformaldehyde in PBS (pH 7.4). After cryoprotection in 30% sucrose solution, the brain was sectioned at 30-mm intervals on a freezing microtome.

in homogenizing buffer by 10 strokes using a Teflon-glass tissue grinder. The homogenate was centrifuged at 1000  g for 10 minutes at 4  C. The supernatant S1 was directly applied onto a discontinuous Percoll gradient ranging from 0% up to 23% Percoll and centrifuged at 31,000  g for 5 minutes allowing the isolation of synaptosome fraction (Dunkley et al., 2008). 2.3. RNA isolation Total RNA preparation of frozen cerebral cortices was performed as previously described (Ueberham et al., 2009). Isolation of synaptosome RNA also mainly followed this protocol with slight modifications. In detail, for improved results during isopropanol precipitation, glycogen (GlycoBlue; Life Technologies) was added to the samples. In addition, after washing and drying the pellet was resolved in 100-mL nuclease-free water and a subsequent phenol/ chloroform/isoamylalcohol purification step was performed. After this step about 100 mL of an aqueous phase containing RNA was obtained and a sodium acetate precipitation was performed in the presence of GlycoBlue. For this, 100-mL aqueous RNA solution, 0.1 volumes of 3M Na Acetate (pH 5.2), 2.5 volumes ethanol, and 1e3 mL GlycoBlue were carefully mixed and stored at 70  C overnight, then a centrifugation at 25,000  g for 25 minutes at 4  C was performed. The pellet was washed with 70% ethanol, dried, and resolved in ultrapure water. 2.4. RNA sequencing For ribosomal RNA depletion, total RNA was processed for sequencing using Ribo-Zero rRNA Removal Kit (Epicentre, San Diego, CA, USA). The samples were then prepared for strandspecific sequencing according to the manufacturer’s guidelines using the TruSeq Stranded Total RNA Library Preparation Kit (Illumina, San Diego, CA, USA). Each sample was sequenced using 100-bp paired-end sequencing on an Illumina HiSeq2000. 2.5. Sequence reads mapping, transcript assembly, and differential quantification Bioinformatic analysis of 731 million reads generated from 12 mouse synaptic preparations, including 6 young and 6 aged samples, was performed using the Tuxedo protocol (Trapnell et al., 2012). Using TopHat, the reads were processed and aligned to the Mus musculus reference genome (build mm10) (Trapnell et al., 2009). The aligned reads were processed with Cufflinks and Cuffdiff (Trapnell et al., 2010). Abundance was measured as fragments per kilobase of exon per million fragments mapped (FPKM) and normalized at both interlibrary and intercondition levels. For this analysis, a GTF annotation file (M5) was used to guide the assembly. The output GTF files from each of the Cufflinks analysis and the GTF annotation file were sent to Cuffmerge (Trapnell et al., 2010). The merged GTF file was then fed to Cuffdiff along with the original alignment files produced from TopHat. Genes were considered to be expressed if they had an FPKM value greater than 1 in at least one condition. Cuffdiff applies the t-test statistics: T ¼ E[log(y)]/Var [log(y)], where y is the ratio of the FPKM between 2 conditions. Q values are calculated after false discovery correction based on p values generated by t-test. Changes in expression with a q value <0.05 were considered statistical significant. 2.6. Classification as putative lincRNAs and antisense transcripts

2.2. Synaptosomes preparation Preparation of synaptosomes was carried out according to Dunkley et al. (2008). In brief, cerebral cortices were homogenized

The differentially expressed unannotated genes were classified as putative lincRNAs if they fulfilled the following criteria: (1) longer than 200 nucleotides; (2) had no overlap with any other

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Fig. 2. Distribution of 6637 unannotated, nonprotein coding, differentially expressed genes in terms of their strand specificity and genomic location.

the gene ontology (GO) terms for over-representation in each of the gene lists. The GO terms list produced by DAVID, were processed using the “Enrichment Map” plug in for Cytoscape (http://www. cytoscape.org/) (Cline et al., 2007). This produces a visual output of the text based GO term lists. 2.8. RT-PCR and RT-qPCR validation of Clp1 gene expression

Fig. 1. Detection of synaptic marker proteins (syntaxin-1 and PSD-95) in synaptosome fractions derived from young and aging mice brains. The blots show cortical homogenates, and the corresponding cytosol and synaptosome fractions of 2 young and 2 old mice, respectively. As expected in the synaptosome fraction, syntaxin-1 and PSD-95 are enriched compared with homogenate extracts while the cytosol fractions only show a very faint protein band.

transcribed loci; and (3) lack of open reading frames (ORFs) longer than 100 amino acids (Hangauer et al., 2013). The presence of ORFs was checked using NCBI’s ORF finder (http://www.ncbi.nlm.nih. gov/gorf/gorf.html). Using the Interactive Genomics Viewer (http://www.broadinstitute.org/igv/), transcripts were manually viewed and classified as antisense transcripts if they completely or partially overlapped any transcribed region from the opposite strand, this included both exonic and intronic regions (VanheeBrossollet and Vaquero, 1998). For identification of human orthologs to unannotated putative mouse lincRNAs UCSC LiftOver tool (https://genome.ucsc.edu/cgibin/hgLiftOver) was utilized. As an input, the chromosomal coordinates of the mouse lincRNAs were used with the “minimum ratio of bases that must remap” set to 0.9 and other parameters as default settings. 2.7. Pathway analysis The gene list of differentially expressed genes was split into 2 groups; those upregulated in young and those upregulated in aging synaptosomes. Only annotated genes can be utilized by enrichment tools, hence all novel genes and indecisively annotated genes were removed. Each of these lists was fed into the Database for Annotation, Visualization and Integrated Discovery (DAVID) (http://david.abcc.ncifcrf.gov/) (Huang da et al., 2009). DAVID tested

RT-PCR for real-time quantification of Clp1 mRNA was performed using the One Step RT-PCR kit (Qiagen GmbH, Hilden, Germany) and SYBR-Green (Molecular Probes, Leiden, The Netherlands) according to the instructions of the manufacturer’s as previously described (Ueberham et al., 2005). Rotor-Gene 6000 real-time thermal cycling system (Corbett Research, Mortlake, Australia) and Rotor-Gene software, V4.6 (Corbett Research, Mortlake, Australia) were used for amplification and quantification. The specific primer sets (biomers.net GmbH, Ulm, Germany) applied to mRNA quantification are listed in Table S1. Normalization of the amplified gene products was performed as previously described (Ueberham et al., 2006). Briefly, each RT-PCR was performed with the same content of total RNA. To obtain a primer-specific standard curve, control RNA was diluted over a broad range. The obtained curve following a linear function was used to determine the relation of the amount of PCR products of each other individual sample RNA (Ueberham et al., 2005). 2.9. Western blotting For Western blotting, 6 mg of protein was loaded onto a 10% sodium dodecyl sulfate (SDS) polyacrylamide gel and separated by electrophoresis (TV200 chamber; biostep GmbH, Jahnsdorf, Germany). Proteins were blotted onto polyvinylidene difluoride membrane (PVDF; NEN, Koeln, Germany), blocked for 1 hour with 4% BSA in 0.1-M Tris-buffered saline (TBS) containing 0.05% Tween 20 (TBST, pH 7.4) and incubated with primary antibodies (Table S2) overnight at 4  C. The polyvinylidene difluoride membrane membrane was washed 3 times with TBST and incubated with HRPconjugated antirabbit antibody in TBST (1:2000; Dianova, Hamburg, Germany). Membranes were washed with TBS and incubated with SuperSignal West Pico Substrate (Pierce, Rockford, IL, USA). Blots were densitometrically quantified using image analysis on a KODAK Image Station 2000R (Raytest GmbH, Straubenhard, Germany) with TINA software (version 2.09, Raytest GmbH). For normalization of protein levels on Western blots,

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Table 1 Top 10 upregulated and downregulated annotated genes in aging synapses Gene

Chromosomal location

Young FPKM

Old FPKM

Log2FC

q-value

Rprl3 Gm16355 3110082J24Rik Gm13322 Gm5899 CH36-12I15.2 Gm27253 Rprl2 Gm13988 Gm13443 Gm5093 Gm37746 5830432E09Rik Gm10269 Gm12516 Ftx Dhx58 Lyrm1 Gm5507 Cfap43

chr8:3803068e3803358 chr2:175153997e175154228 chr5:30103583e30155191 chr2:17181742e17185487 chr7:94197209e94197461 chr5:128444415e128447731 chr9:72268613e72274856 chr3:22251373e22251663 chr2:123273923e123274211 chr2:35340408e35340963 chr17:46439577e46440099 chr3:43955720e43955918 chr7:135537823e135686443 chr18:20682591e20682963 chr4:55392316e55392701 chrX:103560906e103623755 chr11:100574903e100704271 chr7:119853162e120095177 chr18:53984320e53985328 chr19:47737560e47919299

0 0 0 0 0 0 0 0 0 0 12.76 5.91 4.59 2.75 1.54 407.74 4.60 249.17 6.80 2.91

157.98 18.25 4.67 3.50 3.22 2.86 2.54 2.47 2.40 2.15 0 0 0 0 0 1.50 0.02 2.39 0.15 0.09

Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite Infinite -Infinite -Infinite -Infinite -Infinite -Infinite 8.08 8.05 6.70 5.47 5.08

0.005 0.008 0.035 0.005 0.005 0.005 0.005 0.006 0.005 0.008 0.005 0.005 0.006 0.005 0.005 0.005 0.005 0.005 0.020 0.007

beta-actin levels were determined and used as reference for each individual sample. To this end, blots were incubated for 45 minutes at room temperature (RT) with stripping solution consisting of 32mL 5-N NaCl, 10-mL glacial acetic acid, and 278-mL distilled water, then washed, blocked again for 1 hour and incubated with antiebeta-actin antibody (clone AC-74, Sigma, Taufkirchen, Germany; 1:3000) for 1 hour at RT. After washing, the membrane was incubated with HRP-conjugated antimouse antibody in TBST (1:5000; Dianova, Hamburg, Germany), washed with TBST, incubated with SuperSignal West Pico Substrate, and analyzed by densitometry. 2.10. Immunohistochemistry Free-floating mouse brain sections were incubated with 0.5% H2O2 for 30 minutes to quench endogenous peroxidase activity. After blocking of unspecific binding sites with 0.5% dry milk and

0.1% gelatin in 0.1-M TBS, pH 7.4, sections were incubated with rabbit anti-Clp1 antibodies for 16 hours at RT which were detected with biotinylated goat antirabbit IgG (Dianova, Hamburg, Germany; 1:1000). Sections were further processed with extravidinperoxidase conjugate (Sigma, Taufkirchen, Germany; 1:2000) and 0.04% 3,30 -diaminobenzidine (Sigma)/NiCl2/0.015% H2O2 as chromogen. Primary antibodies were omitted in control sections. For simultaneous detection of Clp1 with vGlut1, sections were incubated with anti-Clp1 antibody, washed several times, and incubated with the Cy2-labeled donkey antirabbit antibody (Dianova; 1:1000). After a second round of blocking and washing, sections were incubated with the second primary antibody (anti-vGlut1 antibody) and after washing incubated with the Cy3-labeled donkey antieguinea pig antibody (Dianova; 1:1000). After mounting, sections were covered with Entellan (Merck, Darmstadt, Germany), examined, and digitized using a Keyence fluorescence microscope BZ9000

Fig. 3. Enrichment map visualizing GO terms enriched in protein-coding genes which are differentially expressed in aging synaptosome. Each node represents a different GO term and the size of the node relates to the level of enrichment of each term. The connections between the GO terms represent genes shared by particular nodes and the thickness of the link resembles a number of shared genes. The more closely related GO terms are, the closer they appear on the enrichment map. A large number of closely related GO terms form a cluster. Each cluster has been labeled with a general term that captures all GO terms. Abbreviation: GO, gene ontology.

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Table 2 Enriched GO clusters for genes upregulated in young and aging synaptosomes GO term

p-value

Gene

Cell migration Immune response Transmission of nerve impulse Succinate metabolic process Post-translational regulation of gene expression Regulation of cellular protein metabolic process Regulation of gene expression, epigenetic Translation rRNA transcription

0.0002 0.011 0.012 0.02 0.021 0.025 0.032 0.038 0.043

Pouf3f3, Cx3cl1, Hif1a, Itga3, Met, Nrp1, Nup85, Scg2, Satb2 Cd180, Traf3ip2, C1qb, Fth1, Gbp3, Prkcd, C4b Aldh5a1, Gad2, Mbp, Qk, Scd2 Gad2, Aldh5a1 Clp1, Cdkn2a, Eif5a2, Qk Cdkn2a, Gab1, Prkcd, Eif5a2, Qk Clp1, Airn, Sirt7 Eif5a2, Rpl10, Rpl30, Gm4462, Rps4x Cdkn2a, Sirt7

(Keyence, Neu-Isenburg, Germany), an Axiophot microscope (Zeiss, Oberkochen, Germany) equipped with an AxioCam HRC camera (Zeiss) or using Laser scanning microscope (LSM 510, Zeiss). 3. Results 3.1. Validation of synaptosomes preparations We prepared synaptosomes from brains of young (2 month old) and old (23 month old) mice. Identities of synaptosomal fractions were proved by Western blotting analysis using antibody-detecting synaptic proteins. Fig. 1 depicts the representative immunoblot with positive detection of syntaxin and PSD-95 in synaptosome fractions. 3.2. Transcriptome profiles in young and aging synaptosomes We performed transcriptome sequencing of synaptic fractions derived from the cortical tissue of young (2 month old) and aging (23 month old) mice. RNA-Seq analysis revealed expression of

16,360 and 22,288 transcripts in young and aging synaptosomes, respectively. Comparative transcriptome analysis revealed 6902 differentially expressed genes (DEGs) out of which only 260 (3.8%) have been previously annotated to the mouse reference genome. Out of the 260 annotated genes, 5 (1.9%) genes were expressed only in young fraction whereas 23 (8.8%) only in aging synaptic samples (Table S3). Further, 212 (81.5%) genes where annotated as protein-coding genes whereas 48 (18.5%) as nonprotein-coding genes. Eight (16.7%) DEGs from the latter group are classified as long intergenic noncoding RNAs (lincRNAs) and 7 (14.6%) as antisense transcripts. The remaining 6642 DEGs, out of 6902, were detected based on TopHat/Cufflinks identification of expressing loci within unannotated parts of the genome. We observed remarkable disproportion of gene expression distribution with 4670 genes (70.3%) expressed only in aging synaptosomes and 1955 (29.4%) only in young fraction. Merely, 17 (0.3%) unannotated DEGs were expressed in both conditions. Predictive analysis for putative open reading frames, of over 100 aa in length, revealed 5 transcripts fulfilling this condition. Accordingly, genes expressing these transcripts were classified as genes with protein-coding potential. They composed less than 0.1% of unannotated DEGs as depicted in Fig. 2. The remaining 6637 unannotated genes were consequently defined as noncoding RNAs (ncRNAs). Among them, 24 were antisense ncRNAs, 167 had their loci entirely within introns, and 962 genes composed novel long intervening noncoding RNAs (lincRNAs) (Fig. 2). 3.3. Comparative analysis of annotated genes Differential expression analysis performed by CuffDiff software revealed that only 260 DEGs, out of 6,902, could be annotated to the mouse reference genome. Further, despite available annotation, 27 (10.4%) DEGs were lacking any functional information on encoded protein or represented uncharacterized lncRNAs. Thus, only 233 DEGs could be further processed for analysis of enriched gene ontology (GO) terms. Table 1 presents top 10 annotated up- and downregulated genes in aging synaptosome. 3.4. Pathway analysis of differentially expressed protein-coding genes

Fig. 4. Distribution of expression magnitude of differentially expressed putative lincRNAs (A) and their exonic composition (B). For estimates of expression levels, the higher FPKM value in either young or aging synaptosome has been used for generation of the expression distribution. Abbreviations: FPKM, fragments per kilobase of exon per million fragments mapped; lincRNA, long intervening noncoding RNAs.

In the next step of the study, we performed pathway analysis for 233 protein-coding DEGs. Specifically, we separately analyzed 81 up- and 152 downregulated genes in aging synaptosome. As depicted in Fig. 3, significantly enriched GO terms in the former group of DEGs comprised succinate metabolic process, transmission of nerve impulse, immune response, post-transcriptional regulation of gene expression, regulation of cellular protein metabolic process, rRNA transcription, and epigenetic regulation of gene expression. In case of DEGs, downregulated in aging synaptosome enrichment in genes related to cell migration could be observed.

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Fig. 5. Circos plot connecting human orthologs of the putative mouse lincRNAs differentially expressed between young and old synaptosome fractions. Gene symbols under the yellow bands in the left half of the circle indicate annotated human orthologs. Note that most of the mouse putative lincRNAs are orthologous to unannotated part of the human genome as indicated by strings with blank endings. Yellow bands: human hg38 reference genome; blue bands: mouse mm10 reference genome. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

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tool was used to search for human orthologs of the 962 mouse lincRNAs. Out of 962 mouse genes, 389 revealed a positive hit within the reference human genome. Among the 389 genes, 91 could be linked to 72 annotated human genes, since some of the mouse genes showed similar degree of sequence homology to the same human counterpart (Fig. 5 and Table S5). Interestingly, 4 mouse lincRNAs could be assigned to human annotated lincRNAs, namely LINC01465, LINC01250, LINC01057, and LINC00290. The latter shows unique expression in the brain among 53 human tissues as determined using GTEx Portal RNA-Seq data repository (gtexportal.org; data not shown). 3.6. Clp1 overexpression in aging synaptosome

Fig. 6. RT-qPCR validation of increased Clp1 expression in aging synaptosome using RNA samples derived from independent synaptosome preparations (right) and compared to Clp1 mRNA expression in total cortical RNA (left) (n ¼ 6; t-test; *p < 0.05). Abbreviation: Clp1; cleavage and polyadenylation factor I subunit 1.

Overall, GO term clusters composed of DEGs upregulated in aging synaptosome formed 3 separate superclusters related to neurotransmission, immune response, and regulation of gene expression. To acquire more global view in the context of entire genome, the genes contributing to individual GO terms clusters (listed in Table 2) were plotted in the context of their chromosomal localization using circos algorithm (Fig. S1). Notably, cell migrationrelated genes represented the strongest network followed by immune response genes. In total, 100 out of 233 genes subjected to the pathway analysis contributed to enriched GO terms clusters, which have been listed in Table S4.

3.5. Analysis of novel, differentially expressed lincRNAs The lincRNAs remained in our particular focus due their tissuetype specificity and previously described involvement in brain functions (Ulitsky and Bartel, 2013). We used the following criteria to define novel lincRNAs out of the 6642 gene pool of unannotated transcripts: (1) lack of ORFs longer than 300 bp; (2) lack of overlap with any expressing loci in terms of genomic localization; and (3) transcripts longer than 200 bp. Following these criteria, 961 DEGs were identified (Table S3). Interestingly, only 11 lincRNAs were expressed, at significantly different levels, in both conditions, that is, young and aging synaptosome samples. The remaining 950 putative lincRNAs were either only expressed in young (259 transcripts) or aging condition (691 transcripts). To better understand transcript features and their pattern of expression, we analyzed the 962 novel lincRNAs for a distribution of FPKM values across all transcripts and number of exons contributing to processed transcripts. The results of this analysis are shown in Fig. 4. Clearly, most of the lincRNAs remained in lower range of expression of up to 5 FPKM. Nevertheless, 131 transcripts showed expression of over 10 FPKM in either young or aging synaptosome, thus remaining at comparable level with abundant protein-coding genes (Fig. 4A). In terms of the exonic composition, most of the lincRNAs (96.9%) consisted of single exon which have been also observed in previous transcriptome surveys of human tissues (Millset al., 2016b, Popadin et al., 2013). Nonetheless, 1 transcript consisted of more than 3 exons, thus potentially being alternatively spliced to multiple isoforms (Fig. 4B). Of all 6892 exons that made up the 6642 genes, 5922 are less or equal to 200 bp. Finally, we asked a question to what extent the mouse differentially expressed lincRNAs have human orthologs. UCSC’s LiftOver

One of the annotated DEGs, namely Clp1 gene, caught our particular attention due to its 115-fold upregulation in aging synaptosome and its presence in several GO enrichment clusters related to RNA processing and expression. Using RT-qPCR, we successfully confirmed elevated Clp1 expression in an independent synaptosome RNA fractions (Fig. 6). Clp1 encodes a protein which is a multifunctional kinase involved in tRNA, mRNA, and siRNA maturation (Weitzer et al., 2015) and has been recently reported as an important coregulator of central nervous system functions (Karaca et al., 2014; Schaffer et al., 2014). We, therefore, have been interested in changes in Clp1 expression pattern as a result of aging. As depicted in Fig. 7A and B, the protein Clp1 is scatterly located in neuronal soma as well as in neuronal processes. Double labeling experiments show a colocalization with vGlut1 (Fig. 7C) corroborating a partially synaptic localization of Clp1. Though the overall Clp1 content in mouse brain cortical homogenates decreases, an increase of synaptosomal Clp1 amount characterizes brain aging as shown in Fig. 8. Interestingly, semi-quantitative analysis of immunohistochemical staining revealed a shift of Clp1 to neuronal processes in hippocampal neurons of aged mice probably at the expense of cytoplasmic Clp1 supporting our Western blot data (Fig. 9). 4. Discussion In this study, we surveyed local transcriptome changes in synaptosome fractions derived from young and aging mice using RNASeq technique. This report, for the first time, provides insights into age-related changes of gene expression profiles encoding proteinand noncoding transcripts with unprecedented resolution. Our comparative analysis revealed that majority of the genes affected by the aging process within the synapses are novel and their RNA products lack protein-coding capacity. Moreover, a significant fraction of those unannotated DEGs were identified as putative lincRNAs, an RNA species which has been previously reported to be important regulatory molecules in preserving neuronal functionality (Kour and Rath, 2016, 2017). Further, we performed detailed analysis of age-related changes in expression pattern of the Clp1 protein which is a crucial element of tRNA metabolism (Weitzer et al., 2015). Our observations suggest that Clp1 might be involved in control of cognitive functions governed by hippocampus and related structures of the cerebrum. Previous studies, utilizing RNA-Seq for the characterization of rodent synaptic neuropil transcriptome, have detected expression of limited number of lncRNAs as compared with the present report (Cajigas et al., 2012). There are 2 reasons contributing to this discrepancy. First, Cajigas et al. used polyadenylated RNA for sequencing which have led to limited discovery rate due to the omission of RNAs lacking poly(A) tails. Second, the authors utilized 454 sequencing with 1.5 million reads generated per sample, which

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Fig. 7. Immunohistochemical detection of Clp1 protein in mouse cortical neurons. Labeling (DAB/Ni, black) both in cell bodies (A) as well as in cell processes (B) is shown. Co-detection (C) of Clp1 protein (Cy2, green) and vGlut1 (Cy3, red) indicates Clp1 localization in neuronal synapse (merged, white arrows) corroborating biochemical data. Scale bar, 10 mm. Abbreviation: Clp1; cleavage and polyadenylation factor I subunit 1. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

in comparison to our rate of 80 million reads per sample, led to a limited sensitivity of their transcriptome survey. Altogether, it is surprising that mouse neurons do express such a high number of lincRNAs in synapses spatially distant from the neuronal body, and in particular nucleus. The latter has been regarded as a main location of lincRNAs exerting their function through control of structural and epigenetic mechanism controlling chromatin structures and promoter region activities (Nakagawa and Kageyama, 2014). Previous comparative studies have shown, that the primate genomes, and especially human genome, evolved an immense number of noncoding loci to the point to which the number of noncoding genes by far exceed the number of protein-coding genes (Necsulea and Kaessmann, 2014). Here, we provide indications that the mouse genome is also a vigorous source of pervasive transcription with many lncRNAs reshaping their expression patterns during aging. One of the

reasons that previous studies have been rather scarce in their observations of noncoding transcriptome might be recent advances in sequencing technology, in particular dramatic increase in sequencing coverage (Sims et al., 2014). This improved efficiency of sequencing led to elevated sensitivity of the RNA-Seq toward detection of transcripts expressed at lower levels as argued recently (Briggs et al., 2015). The large distance of synapses from the soma creates a fundamental challenge for the neuron. They must prevent synthesis of synaptic proteins during mRNA transport, yet quickly allow synthesis on demand in response to synaptic activity. The solution to the geometry of neurons demands local mechanisms for control of RNA translation to allow synthesis of new proteins in a manner that is spatially and temporally restricted. Several previous studies have shown that local protein translation plays an important role in synaptic development and plasticity

B.J. Chen et al. / Neurobiology of Aging 56 (2017) 67e77

Fig. 8. Distribution of Clp1 protein expression in the young and aging mouse brain shows a reduction of Clp1 protein in total homogenates (A) but an increase of Clp1 in synaptosomes (B) corroborating observed overexpression of the Clp1 mRNA in the aging synaptosome (n ¼ 6; t-test; *p < 0.05). In (C), a representative Western blot detecting Clp1 protein of homogenate (homo) and synaptosome fraction (synapt) of young (y) and old (o) mice is shown. Abbreviation: Clp1; cleavage and polyadenylation factor I subunit 1.

(Liu-Yesucevitz et al., 2011; Martin and Ephrussi, 2009; Richter and Klann, 2009). The observation that neuronal dendrites and dendritic spines contain mRNA and polyribosomes suggested that synaptic efficacy might depend, in part, on local, synapto-dendritic protein synthesis. Our study adds another layer of complexity to this emerging understanding where lincRNAs comprise much more abundant fraction of the local synaptic transcriptome than previously anticipated. Indeed, substantial fraction of differentially expressed novel lincRNAs, reported in this study, remain at expression levels above 10 FPKM; a level which is typical for abundant protein-coding genes. Mammalian lincRNAs have been shown to regulate gene transcription and to contribute to a variety of other cellular functions. For example, the imprinted lincRNA Airn downregulates the expression of the Igf2r gene cluster using a cis-regulatory mechanism whereas Malat-1 regulates the expression of genes involved in synaptic function and influences alternative splicing through its interaction with splicing factor proteins in the nucleus (reviewed in Bliim et al. (2016)). Here, we observe hundreds of differentially expressed lincRNAs when young and aging transcriptomes are compared. This number exceeds 4 times the number of differentially expressed protein-coding genes. This clearly indicates that lincRNAs play a functional role in local synaptic environment and are not merely passive products of pervasive transcription. Thus,

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our study provides a repository of new transcriptional targets for future functional analysis of individual lincRNAs to elucidate their role in synaptic physiology. Another noticeable feature of differential gene expression pattern in aging synaptosomes is its significant polarization, in particular in case of unannotated transcripts. Only 0.3% of DEGs are expressed in both conditions and the remaining genes express their RNAs exclusively only in one age. Hence, the genes solely expressed in the aging brain might be considered as potential molecular markers of aging. This would be of particular interest for those novel mouse genes that have human orthologs as we determined for 389 of the differentially expressed putative lincRNAs. The noncoding RNAs might then serve as additional molecular signature of brain aging along with protein-coding genes identified in the present and previous studies with utilization of microarray approaches (Lee et al., 2000). Earlier reports, investigating nonfractionated cortical tissue, revealed enrichment of similar, to our study, biological pathways in relation to aging including immune response genes, neurotransmission, energy metabolism, and RNA splicing (Park et al., 2009). The enrichment of genes involved in immune response in aging synapses reflects general inflammation within the brain tissue induced by cellular damage and cell loss in healthy aging (Kumar et al., 2013; Mortera and Herculano-Houzel, 2012). Coordinated perturbation of genes involved in RNA processing, including splicing, and maturation corroborate earlier observations that modification of RNA seems to be a central process targeted by aging (Harries et al., 2011). Interestingly, Harries et al. saw enrichment of genes involved in mRNA splicing in aging peripheral blood cells. This similarity of age-related changes in peripheral tissues and the brain might support earlier notions that transcriptomic alterations with age might be, at least to some extent, conserved between different tissues. Another study, involving the analysis of 16 different mouse tissues, including cerebrum and cerebellum, again showed enrichment of RNA processing as pathways affected by age (Southworth et al., 2009). Marked upregulation of the Clp1 indicates that tRNA splicing might be an important part of protein translation machinery affected in aging neurons. Indeed, previously observed overexpression of Clp1 protein, in particular in the aging hippocampus, might indicate aging-related accumulation of unspliced tRNAs and thus an increased demand for tRNA-specific splicing of which Clp1 protein is a part of (Szafranski et al., 2015). To this end, it has been observed that tRNA splicing machinery is perturbed in neurodegeneration, an aging-related pathology (Anderson and Ivanov, 2014). Clp1 protein, being an RNA kinase, is essential for re-ligation of tRNAs halves by catalyzing phosphorylation of their 5’ends (Weitzer et al., 2015). Thus, elevated expression of Clp1 in aging synaptosomes might be related to increased demand for clearance of accumulating tRNA splicing by-products. From this perspective, a recent report on changes in levels of 50 tRNA halves in mouse serum and blood cells, and prevention of these alterations by calorie restriction, would further support an emerging role of tRNA metabolism in aging (Dhahbi et al., 2013). In conclusion, this is the first report presenting unique transcriptome profiles reshaped by the brain aging in functionally critical parts of the neuronal network namely synapses. Our study also provides a critically important resource for future functional and structural analysis of individual genes, in particular those that lack annotation. This includes detailed functional exploration of nonprotein-coding transcripts and, from the perspective of present study, their role in distinct and functionally critical structures of neuronal cells.

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Fig. 9. Increased detection of Clp1 protein in neuronal processes of hippocampal stratum radiatum using 2 different anti-Clp1 antibodies (a - GTX115518 [Biozol], black, DAB/Ni; b - ab133669 [Abcam], black, DAB/Ni) supporting our data on increased levels of Clp1 RNA and protein in synaptosomes. Immunoreactivity of anti-Clp1 antibodies was examined using ImageJ software (Rasband W.S. 1997e2016) in young (A) and old (B) mice showing more intensive staining in stratum radiatum of hippocampal CA1 in old mice (B-B00 , C, C0 ). The black dashed rectangle in A and B, respectively, indicate the region from oriens layer to hippocampal fissure (about 0.6 mm in length) which was densitometrically analyzed using ImageJ. The obtained intensities were normalized (using corpus callosum as internal reference) and depicted in C. The black line in C represents young and the green line the old mice. In C0 differences of intensities between old and young mice for each distance point are shown. Increased Clp1 signals in old mice are depicted in green while reduced Clp1 signals in old mice are black. The range between 0.2 mm and 0.4 mm, covering hippocampal stratum radiatum, demonstrates higher Clp1 protein amount in aged animals. Abbreviations: hif, hippocampal fissure; LMol, lacunosum moleculare layer; Or, oriens layer; Py, pyramidal cell layer; Rad, stratum radiatum. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Disclosure statement The authors have no conflicts of interest to disclose. Acknowledgements The authors thank Hildegard Gruschka and Marie Freier for their technical assistance. This work was supported by Deutsche Forschungsgemeinschaft DFG (SPP1738; UE123/1-1) and EraNet-RUS (DLR/01DJ16018). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.neurobiolaging. 2017.04.005.

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