12
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A cell-type-specific atlas of the inner ear transcriptional response to acoustic trauma

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          SUMMARY

          Noise-induced hearing loss (NIHL) results from a complex interplay of damage to the sensory cells of the inner ear, dysfunction of its lateral wall, axonal retraction of type 1C spiral ganglion neurons, and activation of the immune response. We use RiboTag and single-cell RNA sequencing to survey the cell-type-specific molecular landscape of the mouse inner ear before and after noise trauma. We identify induction of the transcription factors STAT3 and IRF7 and immune-related genes across all cell-types. Yet, cell-type-specific transcriptomic changes dominate the response. The ATF3/ATF4 stress-response pathway is robustly induced in the type 1A noise-resilient neurons, potassium transport genes are downregulated in the lateral wall, mRNA metabolism genes are downregulated in outer hair cells, and deafness-associated genes are downregulated in most cell types. This transcriptomic resource is available via the Gene Expression Analysis Resource (gEAR; https://umgear.org/NIHL) and provides a blueprint for the rational development of drugs to prevent and treat NIHL.

          In brief

          Milon et al. show that cell-type-specific transcriptomic changes following noise exposure dominate the response compared to common changes. The noise-resilient type 1A neurons induce the ATF3/ATF4 stress-response pathway, and the outer hair cells and lateral wall downregulate mRNA metabolism genes and potassium transport genes, respectively.

          Graphical Abstract

          Related collections

          Most cited references111

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Fiji: an open-source platform for biological-image analysis.

            Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              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/.
                Bookmark

                Author and article information

                Journal
                101573691
                39703
                Cell Rep
                Cell Rep
                Cell reports
                2211-1247
                22 October 2021
                28 September 2021
                24 December 2021
                : 36
                : 13
                : 109758
                Affiliations
                [1 ]Department of Otorhinolaryngology Head and Neck Surgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA
                [2 ]Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
                [3 ]Decibel Therapeutics, Boston, MA 02215, USA
                [4 ]Laboratory of Experimental Audiology, Department of Physiology and Pharmacology, Karolinska Institute, 171 77 Stockholm, Sweden
                [5 ]Hearing Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham NG7 2UH, UK
                [6 ]Applied Immunology & Immunotherapy, Neuroimmunology Unit, Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska University Hospital, 171 77 Stockholm, Sweden
                [7 ]Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA
                [8 ]Otolith Labs, Washington, DC 20009, USA
                [9 ]Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
                [10 ]These authors contributed equally
                [11 ]Lead contact
                Author notes

                AUTHOR CONTRIBUTIONS

                Conceptualization, K.S.S., G.P., C.R.C., J.B.S., A.T.P., J.B., B.C., and R.H.; methodology, E.D.S., K.S.S., G.P., J.B.S., A.T.P., D.A.D., J.B., B.C., R.E., and R.H.; software, J.O. and R.H.; validation, B.M, E.L.L., B.S., and R.H.; formal analysis, B.M., E.D.S., G.P., M.S., Y.S., B.C., R.E., and R.H.; investigation, B.M., E.D.S., K.S.S., E.L.L., G.P., H.S., B.S., S.M., Z.M., Y.O., C.S., J.B.S., A.T.P., J.B., B.C., and R.H.; resources, J.O., A.T.P., J.B., B.C., and R.H.; data curation, B.M., E.D.S., Y.S., G.P., R.E., and R.H.; writing – original draft, B.M., E.D.S., C.R.C., B.C., R.E., and R.H.; writing – review & editing, B.M., E.D.S., K.S.S., E.L.L., G.P., C.R.C., J.B.S., D.A.D., J.B., B.C., R.E., and R.H.; visualization, B.M., E.D.S., E.L.L., Y.S., J.O., and R.H.; supervision, C.R.C., D.A.D., A.T.P., J.B., B.C., R.E., and R.H.; project administration, B.C. and R.H.; funding acquisition, B.C., R.E., and R.H.

                Article
                NIHMS1744539
                10.1016/j.celrep.2021.109758
                8709734
                34592158
                f3478f97-09a6-42f4-b213-d5839a188076

                This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                Categories
                Article

                Cell biology
                Cell biology

                Comments

                Comment on this article