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      Transcriptome profiling of aging Drosophila photoreceptors reveals gene expression trends that correlate with visual senescence

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          Abstract

          Background

          Aging is associated with functional decline of neurons and increased incidence of both neurodegenerative and ocular disease. Photoreceptor neurons in Drosophila melanogaster provide a powerful model for studying the molecular changes involved in functional senescence of neurons since decreased visual behavior precedes retinal degeneration. Here, we sought to identify gene expression changes and the genomic features of differentially regulated genes in photoreceptors that contribute to visual senescence.

          Results

          To identify gene expression changes that could lead to visual senescence, we characterized the aging transcriptome of Drosophila sensory neurons highly enriched for photoreceptors. We profiled the nuclear transcriptome of genetically-labeled photoreceptors over a 40 day time course and identified increased expression of genes involved in stress and DNA damage response, and decreased expression of genes required for neuronal function. We further show that combinations of promoter motifs robustly identify age-regulated genes, suggesting that transcription factors are important in driving expression changes in aging photoreceptors. However, long, highly expressed and heavily spliced genes are also more likely to be downregulated with age, indicating that other mechanisms could contribute to expression changes at these genes. Lastly, we identify that circular RNAs (circRNAs) strongly increase during aging in photoreceptors.

          Conclusions

          Overall, we identified changes in gene expression in aging Drosophila photoreceptors that could account for visual senescence. Further, we show that genomic features predict these age-related changes, suggesting potential mechanisms that could be targeted to slow the rate of age-associated visual decline.

          Electronic supplementary material

          The online version of this article (10.1186/s12864-017-4304-3) contains supplementary material, which is available to authorized users.

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          Most cited references102

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          featureCounts: An efficient general-purpose program for assigning sequence reads to genomic features

          , , (2013)
          Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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            CIRI: an efficient and unbiased algorithm for de novo circular RNA identification

            Recent studies reveal that circular RNAs (circRNAs) are a novel class of abundant, stable and ubiquitous noncoding RNA molecules in animals. Comprehensive detection of circRNAs from high-throughput transcriptome data is an initial and crucial step to study their biogenesis and function. Here, we present a novel chiastic clipping signal-based algorithm, CIRI, to unbiasedly and accurately detect circRNAs from transcriptome data by employing multiple filtration strategies. By applying CIRI to ENCODE RNA-seq data, we for the first time identify and experimentally validate the prevalence of intronic/intergenic circRNAs as well as fragments specific to them in the human transcriptome. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0571-3) contains supplementary material, which is available to authorized users.
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              Gene regulation and DNA damage in the ageing human brain.

              The ageing of the human brain is a cause of cognitive decline in the elderly and the major risk factor for Alzheimer's disease. The time in life when brain ageing begins is undefined. Here we show that transcriptional profiling of the human frontal cortex from individuals ranging from 26 to 106 years of age defines a set of genes with reduced expression after age 40. These genes play central roles in synaptic plasticity, vesicular transport and mitochondrial function. This is followed by induction of stress response, antioxidant and DNA repair genes. DNA damage is markedly increased in the promoters of genes with reduced expression in the aged cortex. Moreover, these gene promoters are selectively damaged by oxidative stress in cultured human neurons, and show reduced base-excision DNA repair. Thus, DNA damage may reduce the expression of selectively vulnerable genes involved in learning, memory and neuronal survival, initiating a programme of brain ageing that starts early in adult life.
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                Author and article information

                Contributors
                hallh@purdue.edu
                patrick.medina1@gmail.com
                daphne.cooper@gmail.com
                sescobe@purdue.edu
                roundsjeremiah@gmail.com
                kbrennan@berkeley.edu
                cvincent29@gmail.com
                pmiura@unr.edu
                rwdoerge@andrew.cmu.edu
                vweake@purdue.edu
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                21 November 2017
                21 November 2017
                2017
                : 18
                : 894
                Affiliations
                [1 ]ISNI 0000 0004 1937 2197, GRID grid.169077.e, Department of Biochemistry, , Purdue University, ; West Lafayette, IN 47907 USA
                [2 ]ISNI 0000 0004 1937 2197, GRID grid.169077.e, Department of Statistics, , Purdue University, ; West Lafayette, IN 47907 USA
                [3 ]ISNI 0000 0004 1936 914X, GRID grid.266818.3, Department of Biology, , University of Nevada, ; Reno, NV 89557 USA
                [4 ]ISNI 0000 0001 2097 0344, GRID grid.147455.6, Carnegie Mellon University, ; Pittsburgh, PA 15213 USA
                [5 ]ISNI 0000 0004 1937 2197, GRID grid.169077.e, Purdue University Center for Cancer Research, , Purdue University, ; West Lafayette, 47907 USA
                Article
                4304
                10.1186/s12864-017-4304-3
                5698953
                29162050
                1426108a-85e0-4135-b948-e468f8d92f7b
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 28 August 2017
                : 14 November 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000054, National Cancer Institute;
                Award ID: CA023168
                Funded by: FundRef http://dx.doi.org/10.13039/100000053, National Eye Institute;
                Award ID: R01EY024905
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000049, National Institute on Aging;
                Award ID: R15AG052931
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Genetics
                aging,transcriptome,drosophila,neurons,photoreceptors
                Genetics
                aging, transcriptome, drosophila, neurons, photoreceptors

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