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      Lysine-36 of Drosophila histone H3.3 supports adult longevity

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          Abstract

          Aging is a multifactorial process that disturbs homeostasis, increases disease susceptibility, and ultimately results in death. Although the definitive set of molecular mechanisms responsible for aging remain to be discovered, epigenetic change over time is proving to be a promising piece of the puzzle. Several post-translational histone modifications have been linked to the maintenance of longevity. Here, we focus on lysine-36 of the replication-independent histone protein, H3.3 (H3.3K36). To interrogate the role of this residue in Drosophila developmental gene regulation, we generated a lysine-to-arginine mutant that blocks the activity of its cognate-modifying enzymes. We found that an H3.3B K36R mutation causes a significant reduction in adult lifespan, accompanied by dysregulation of the genomic and transcriptomic architecture. Transgenic co-expression of wild-type H3.3B completely rescues the longevity defect. Because H3.3 is known to accumulate in nondividing tissues, we carried out transcriptome profiling of young vs aged adult fly heads. The data show that loss of H3.3K36 results in age-dependent misexpression of NF-κB and other innate immune target genes, as well as defects in silencing of heterochromatin. We propose H3.3K36 maintains the postmitotic epigenomic landscape, supporting longevity by regulating both pericentric and telomeric retrotransposons and by suppressing aberrant immune signaling.

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          Most cited references101

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Gene Ontology: tool for the unification of biology

            Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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              STAR: ultrafast universal RNA-seq aligner.

              Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                G3 (Bethesda)
                Genetics
                g3journal
                G3: Genes|Genomes|Genetics
                Oxford University Press (US )
                2160-1836
                April 2024
                16 February 2024
                16 February 2024
                : 14
                : 4
                : jkae030
                Affiliations
                Integrative Program for Biological and Genome Sciences, University of North Carolina , Chapel Hill, NC 27599, USA
                Integrative Program for Biological and Genome Sciences, University of North Carolina , Chapel Hill, NC 27599, USA
                Department of Biology, University of North Carolina , Chapel Hill, NC 27599, USA
                Integrative Program for Biological and Genome Sciences, University of North Carolina , Chapel Hill, NC 27599, USA
                Department of Biology, University of North Carolina , Chapel Hill, NC 27599, USA
                Integrative Program for Biological and Genome Sciences, University of North Carolina , Chapel Hill, NC 27599, USA
                Integrative Program for Biological and Genome Sciences, University of North Carolina , Chapel Hill, NC 27599, USA
                Department of Biology, University of North Carolina , Chapel Hill, NC 27599, USA
                Department of Genetics, University of North Carolina , Chapel Hill, NC 27599, USA
                RNA Discovery Center, Lineberger Comprehensive Cancer Center, University of North Carolina , Chapel Hill, NC 27599, USA
                Author notes
                Corresponding author: IBGS Program, University of North Carolina, 3352 Genome Sciences Bldg, Chapel Hill, NC 27599, USA. Email: hsalzler@ 123456email.unc.edu
                Corresponding author: IBGS Program, University of North Carolina, 3352 Genome Sciences Bldg, Chapel Hill, NC 27599. USA. Email: matera@ 123456unc.edu (A.G.M.)

                John C Brown, Benjamin D McMichael and Vasudha Vandadi contributed equally to this work.

                Conflicts of interest. The author(s) declare no conflict of interest.

                Author information
                https://orcid.org/0000-0002-6987-0173
                https://orcid.org/0000-0002-6406-0630
                Article
                jkae030
                10.1093/g3journal/jkae030
                10989886
                38366796
                15ff96bd-a45e-4398-9dbf-20aba01ed32c
                © The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 16 January 2024
                : 04 February 2024
                : 02 March 2024
                Page count
                Pages: 15
                Funding
                Funded by: NIH, DOI 10.13039/100000002;
                Award ID: R35-GM136435
                Categories
                Investigation
                AcademicSubjects/SCI01180
                AcademicSubjects/SCI01140

                Genetics
                histone variant,post-transcriptional modification,ptms,aging,senescence,telomeres,retrotransposition,gene expression,innate immunity,heterochromatin

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