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      Histone deacetylase 4 reverses cellular senescence via DDIT4 in dermal fibroblasts

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          Abstract

          Histone deacetylases (HDACs) remove acetyl groups from lysine chains on histones and other proteins and play a crucial role in epigenetic regulation and aging. Previously, we demonstrated that HDAC4 is consistently downregulated in aged and ultraviolet (UV)-irradiated human skin in vivo. Cellular senescence is a permanent cell cycle arrest induced by various stressors. To elucidate the potential role of HDAC4 in the regulation of cellular senescence and skin aging, we established oxidative stress- and UV-induced cellular senescence models using primary human dermal fibroblasts (HDFs). RNA sequencing after overexpression or knockdown of HDAC4 in primary HDFs identified candidate molecular targets of HDAC4. Integrative analyses of our current and public mRNA expression profiles identified DNA damage-inducible transcript 4 (DDIT4) as a critical senescence-associated factor regulated by HDAC4. Indeed, DDIT4 and HDAC4 expressions were downregulated during oxidative stress- and UV-induced senescence. HDAC4 overexpression rescued the senescence-induced decrease in DDIT4 and senescence phenotype, which were prevented by DDIT4 knockdown. In addition, DDIT4 overexpression reversed changes in senescence-associated secretory phenotypes and aging-related genes, suggesting that DDIT4 mediates the reversal of cellular senescence via HDAC4. Collectively, our results identify DDIT4 as a promising target regulated by HDAC4 associated with cellular senescence and epigenetic skin aging.

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          Most cited references48

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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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            Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

            DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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              Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks.

              Recent advances in high-throughput cDNA sequencing (RNA-seq) can reveal new genes and splice variants and quantify expression genome-wide in a single assay. The volume and complexity of data from RNA-seq experiments necessitate scalable, fast and mathematically principled analysis software. TopHat and Cufflinks are free, open-source software tools for gene discovery and comprehensive expression analysis of high-throughput mRNA sequencing (RNA-seq) data. Together, they allow biologists to identify new genes and new splice variants of known ones, as well as compare gene and transcript expression under two or more conditions. This protocol describes in detail how to use TopHat and Cufflinks to perform such analyses. It also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-seq analysis results. Although the procedure assumes basic informatics skills, these tools assume little to no background with RNA-seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results. The protocol's execution time depends on the volume of transcriptome sequencing data and available computing resources but takes less than 1 d of computer time for typical experiments and ∼1 h of hands-on time.
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                Author and article information

                Journal
                Aging (Albany NY)
                Aging
                Aging (Albany NY)
                Impact Journals
                1945-4589
                15 June 2022
                09 June 2022
                : 14
                : 11
                : 4653-4672
                Affiliations
                [1 ]Department of Dermatology, Seoul National University College of Medicine, Seoul, Republic of Korea
                [2 ]Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Republic of Korea
                [3 ]Institute of Human-Environment Interface Biology, Medical Research Center, Seoul National University, Seoul, Republic of Korea
                [4 ]Department of New Biology, DGIST, Daegu, Republic of Korea
                [5 ]Department of Biological Sciences, Seoul National University, Seoul, Republic of Korea
                [6 ]Institute on Aging, Seoul National University, Seoul, Republic of Korea
                Author notes
                [*]

                Equal contribution

                Correspondence to: Daehee Hwang; email: daehee@snu.ac.kr
                Correspondence to: Dong Hun Lee; email: ivymed27@snu.ac.kr
                Correspondence to: Jin Ho Chung; email: jhchung@snu.ac.kr
                Article
                204118 204118
                10.18632/aging.204118
                9217707
                35680564
                f939b7f0-8b66-4eb0-abee-bb2bdaa24731
                Copyright: © 2022 Lee et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 09 December 2021
                : 07 May 2022
                Categories
                Research Paper

                Cell biology
                cellular senescence,dna damage-inducible transcript 4,histone deacetylase 4,oxidative stress,ultraviolet light

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