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EXOSC3 S1-domain variants implicated in PCH1b alter RNA exosome cap subunit abundance and thermal stability disrupting rRNA processing and targeting of AU-rich mRNA

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Runnebohm, Avery M., Wijeratne, H.R. Sagara, Barron, Monica P., Smith-Kinnaman, Whitney R., Rooney, James D., Peck Justice, Sarah A., Cureton, Lauryn A., Holland, Annalise +5 more·2025·bioRxiv (Cold Spring Harbor Laboratory)

Abstract

Missense variants in EXOSC3, an RNA exosome subunit, have been identified in patients with PCH1b. We investigated three missense variants in the S1 domain of EXOSC3, including one variant of uncertain significance (VUS) and two pathogenic variants (hence S1 variants). EXOSC3 S1 variant cell lines were generated using CRISPR-Cas9 resulting in widespread proteome changes including decreases in some RNA exosome subunits paired with increases in the catalytic subunit DIS3. Thermal stability, analyzed by PISA, revealed extensive destabilization of RNA exosome cap subunits and the cap-associated exonuclease EXOSC10. Functionally, S1 variants altered rRNA processing with corresponding protein compensation observed in rRNA processing proteins outside the RNA exosome. Exogenous overexpression of EXOSC3 rescues many molecular defects caused by S1 variants suggesting that protein destabilization and turnover strongly contribute to molecular defects. Overall, our findings define the mechanisms through which cells respond to EXOSC3 S1 variant disruption of RNA processing homeostasis.

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  • The RNA exosome has specialized functions in RNA splicing and regulation of AU-rich element (ARE)-containing transcripts.

    “In addition to RNA turnover, the RNA exosome has specialized functions in RNA splicing and the regulation of AU-rich element (ARE)-containing transcripts44–47.”

    From EXOSC3 G191 Variants Trigger System-Wide Recalibration of RNA Processing Machinery (2026) · cites this paper as [47]

    The Introduction (page unavailable) describes AU-rich binding proteins targeting RNAs to the exosome, and the Results section on AU-rich mRNA targeting reports altered targeting of ARE-containing transcripts in EXOSC3 variant cells. The copy describes snRNA processing but does not establish a specialized function for the exosome in RNA splicing; a search for splicing found no supporting passage. (LLM, conf=0.87)

    Experimental — accuracy not yet measured
  • Total RNA-Seq analysis of homozygous EXOSC3 D132A/D132A HEK293T cells relative to controls revealed more modest changes to the transcriptome than observed for EXOSC3 G191 cell lines.

    “We have also performed total RNA-Seq analysis of homozygous EXOSC3 D132A/D132A HEK293T cells relative to controls, which revealed more modest changes to the transcriptome than observed for the EXOSC3 G191 cell lines47.”

    From EXOSC3 G191 Variants Trigger System-Wide Recalibration of RNA Processing Machinery (2026) · cites this paper as [47]

    The Results section, “Differential transcript abundance indicates RNA exosome function is altered by S1 variants” (page unavailable), reports total RNA sequencing of D132A/D132A cells relative to controls and substantial transcript changes. It does not compare those changes with EXOSC3 G191 cell lines, so the claim that they were more modest is not supported by this source. (LLM, conf=0.88)

    Experimental — accuracy not yet measured
  • In our recent studies, we observed rRNA processing defects in human cell lines expressing EXOSC3 variants although in an allele-specific manner.

    “In our recent studies, we have also observed rRNA processing defects in human cells lines expressing EXOSC3 variants although in an allele-specific manner47.”

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Research works printed but not linked: 74

  1. [1]Chin L, Hahn WC, Getz G, Meyerson M. Making sense of cancer genomic data. Genes Dev. 2011 Mar 15; 25(6): 534– 55. 21406553 PMC3059829
  2. [2]Hutter C, Zenklusen JC. The Cancer Genome Atlas: Creating Lasting Value beyond Its Data. Cell. 2018 Apr 5; 173(2): 283– 5. 29625045
  3. [3]Amberger J, Bocchini C, Hamosh A. A new face and new challenges for Online Mendelian Inheritance in Man (OMIM®). Hum Mutat. 2011 May; 32(5): 564– 7. 21472891
  4. [5]Morton DJ, Kuiper EG, Jones SK, Leung SW, Corbett AH, Fasken MB. The RNA exosome and RNA exosome-linked disease. RNA. 2018 Feb; 24(2): 127– 42. 29093021 PMC5769741
  5. [6]Barth PG. Pontocerebellar hypoplasias. An overview of a group of inherited neurodegenerative disorders with fetal onset. Brain Dev. 1993 Dec; 15(6): 411– 22. 8147499
  6. [7]Eggens VR, Barth PG, Niermeijer JMF, Berg JN, Darin N, Dixit A, EXOSC3 mutations in pontocerebellar hypoplasia type 1: novel mutations and genotypephenotype correlations. Orphanet J Rare Dis. 2014 Dec; 9(1): 1– 10. 24524299 PMC3928094
  7. [8]Rudnik-Schöneborn S, Senderek J, Jen JC, Houge G, Seeman P, Puchmajerová A, Pontocerebellar hypoplasia type 1. Neurology. 2013 Jan 29; 80(5): 438– 46. 23284067 PMC3590055
  8. [9]Wan J, Yourshaw M, Mamsa H, Rudnik-Schöneborn S, Menezes MP, Hong JE, Mutations in the RNA exosome component gene EXOSC3 cause pontocerebellar hypoplasia and spinal motor neuron degeneration. Nat Genet. 2012 Jun; 44(6): 704– 8. 22544365 PMC3366034
  9. [10]Schwabova J, Brozkova DS, Petrak B, Mojzisova M, Pavlickova K, Haberlova J, Homozygous EXOSC3 mutation c.92G→C, p.G31A is a founder mutation causing severe pontocerebellar hypoplasia type 1 among the Czech Roma. J Neurogenet. 2013 Dec; 27(4): 163– 9. 23883322
  10. [11]Schottmann G, Picker-Minh S, Schwarz JM, Gill E, Rodenburg RJT, Stenzel W, Recessive mutation in EXOSC3 associates with mitochondrial dysfunction and pontocerebellar hypoplasia. Mitochondrion. 2017 Nov; 37: 46– 54. 28687512
  11. [12]Biancheri R, Cassandrini D, Pinto F, Trovato R, Di Rocco M, Mirabelli-Badenier M, EXOSC3 mutations in isolated cerebellar hypoplasia and spinal anterior horn involvement. J Neurol. 2013 Jul; 260(7): 1866– 70. 23564332
  12. [13]Szeto CH, Rubin S, Sidlow R. Homozygous EXOSC3 c.395A>C Variants in Pontocerebellar Hypoplasia Type 1B: A Sibling Pair With Childhood Lethal Presentation and Literature Review. Cureus. 2023 May; 15(5): e39226. 37337484 PMC10277028
  13. [15]Fox MJ, Mosley AL. Rrp6: Integrated roles in nuclear RNA metabolism and transcription termination. WIREs RNA. 2016 Jan; 7(1): 91– 104. 26612606 PMC4715707
  14. [16]Mitchell P, Petfalski E, Shevchenko A, Mann M, Tollervey D. The Exosome: A Conserved Eukaryotic RNA Processing Complex Containing Multiple 3′→5′ Exoribonucleases. Cell. 1997 Nov 14; 91(4): 457– 66. 9390555
  15. [17]Allmang C, Kufel J, Chanfreau G, Mitchell P, Petfalski E, Tollervey D. Functions of the exosome in rRNA, snoRNA and snRNA synthesis. EMBO J. 1999 Oct 1; 18(19): 5399– 410. 10508172 PMC1171609
  16. [18]Allmang C, Mitchell P, Petfalski E, Tollervey D. Degradation of ribosomal RNA precursors by the exosome. Nucleic Acids Res. 2000 Apr 15; 28(8): 1684– 91. 10734186 PMC102825
  17. [19]Malet H, Topf M, Clare DK, Ebert J, Bonneau F, Basquin J, RNA channelling by the eukaryotic exosome. EMBO Rep. 2010 Dec; 11(12): 936– 42. 21072061 PMC2999861
  18. [20]Schilders G, Raijmakers R, Raats JMH, Pruijn GJM. MPP6 is an exosome-associated RNA-binding protein involved in 5.8S rRNA maturation. Nucleic Acids Res. 2005; 33(21): 6795– 804. 16396833 PMC1310903
  19. [21]Mitchell P, Petfalski E, Houalla R, Podtelejnikov A, Mann M, Tollervey D. Rrp47p Is an Exosome-Associated Protein Required for the 3′ Processing of Stable RNAs. Mol Cell Biol. 2003 Oct; 23(19): 6982– 92. 12972615 PMC193929
  20. [22]Schuch B, Feigenbutz M, Makino DL, Falk S, Basquin C, Mitchell P, The exosome-binding factors Rrp6 and Rrp47 form a composite surface for recruiting the Mtr4 helicase. EMBO J. 2014 Dec; 33(23): 2829– 46. 25319414 PMC4282559
  21. [23]Wasmuth EV, Zinder JC, Zattas D, Das M, Lima CD. Structure and reconstitution of yeast Mpp6-nuclear exosome complexes reveals that mpp6 stimulates RNA decay and recruits the Mtr4 helicase. eLife. 2017; 6. PMC5553935 28742025
  22. [24]LaCava J, Houseley J, Saveanu C, Petfalski E, Thompson E, Jacquier A, RNA degradation by the exosome is promoted by a nuclear polyadenylation complex. Cell. 2005 Jun 3; 121(5): 713– 24. 15935758
  23. [25]Puno MR, Lima CD. Structural basis for RNA surveillance by the human nuclear exosome targeting (NEXT) complex. Cell. 2022 Jun 9; 185(12): 2132– 2147.e26. 35688134 PMC9210550
  24. [26]Silla T, Schmid M, Dou Y, Garland W, Milek M, Imami K, The human ZC3H3 and RBM26/27 proteins are critical for PAXT-mediated nuclear RNA decay. Nucleic Acids Res. 2020 Mar 18; 48(5): 2518– 30. 31950173 PMC7049725
  25. [27]Meola N, Domanski M, Karadoulama E, Chen Y, Gentil C, Pultz D, Identification of a Nuclear Exosome Decay Pathway for Processed Transcripts. Mol Cell. 2016 Nov 3; 64(3): 520– 33. 27871484
  26. [28]Chen CY, Gherzi R, Ong SE, Chan EL, Raijmakers R, Pruijn GJM, AU Binding Proteins Recruit the Exosome to Degrade ARE-Containing mRNAs. Cell. 2001 Nov 16; 107(4): 451– 64. 11719186
  27. [29]Otsuka H, Fukao A, Funakami Y, Duncan KE, Fujiwara T. Emerging Evidence of Translational Control by AU-Rich Element-Binding Proteins. Front Genet [Internet]. 2019 May 2 [cited 2024 Sep 30]; 10. Available from: https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2019.00332/full PMC6507484 31118942 · DOI
  28. [30]Puno MR, Weick EM, Das M, Lima CD. SnapShot: The RNA Exosome. Cell. 2019 Sep 19; 179(1): 282– 282.e1. 31539497
  29. [31]de Amorim J, Slavotinek A, Fasken MB, Corbett AH, Morton DJ. Modeling Pathogenic Variants in the RNA Exosome. RNA Dis Houst Tex. 2020; 7: e1166. PMC8528344 34676290
  30. [32]Lubas M, Christensen MS, Kristiansen MS, Domanski M, Falkenby LG, Lykke-Andersen S, Interaction Profiling Identifies the Human Nuclear Exosome Targeting Complex. Mol Cell. 2011 Aug; 43(4): 624– 37. 21855801
  31. [33]Wu G, Schmid M, Rib L, Polak P, Meola N, Sandelin A, A Two-Layered Targeting Mechanism Underlies Nuclear RNA Sorting by the Human Exosome. Cell Rep. 2020 Feb 18; 30(7): 2387– 2401.e5. 32075771
  32. [34]Lubas M, Andersen PR, Schein A, Dziembowski A, Kudla G, Jensen TH. The human nuclear exosome targeting complex is loaded onto newly synthesized RNA to direct early ribonucleolysis. Cell Rep. 2015 Jan 13; 10(2): 178– 92. 25578728
  33. [35]Gockert M, Schmid M, Jakobsen L, Jens M, Andersen JS, Jensen TH. Rapid factor depletion highlights intricacies of nucleoplasmic RNA degradation. Nucleic Acids Res. 2022 Feb 22; 50(3): 1583– 600. 35048984 PMC8860595
  34. [37]Fasken MB, Losh JS, Leung SW, Brutus S, Avin B, Vaught JC, Insight into the RNA Exosome Complex Through Modeling Pontocerebellar Hypoplasia Type 1b Disease Mutations in Yeast. Genetics. 2017 Jan 1; 205(1): 221– 37. 27777260 PMC5223504
  35. [39]Sterrett MC, Cureton LA, Cohen LN, van Hoof A, Khoshnevis S, Fasken MB, Comparative analyses of disease-linked missense mutations in the RNA exosome modeled in budding yeast reveal distinct functional consequences in translation. bioRxiv. 2023 Oct 19;2023.10.18.562946. PMC12170193 40246537
  36. [40]Gillespie A, Gabunilas J, Jen JC, Chanfreau GF. Mutations of EXOSC3/Rrp40p associated with neurological diseases impact ribosomal RNA processing functions of the exosome in S. cerevisiae. RNA. 2017 Apr; 23(4): 466– 72. 28053271 PMC5340910
  37. [42]Müller JS, Burns DT, Griffin H, Wells GR, Zendah RA, Munro B, RNA exosome mutations in pontocerebellar hypoplasia alter ribosome biogenesis and p53 levels. Life Sci Alliance. 2020 Aug; 3(8):e202000678. PMC7295610 32527837
  38. [44]Latini C, Eichlinger J, Fuchs AL, Zhai SN, Ho-Xuan H, Lehmann G, Cytoplasmic DIS3 is an exosome-independent endoribonuclease with catalytic activity toward circular RNAs. Cell Rep. 2025 Jun; 44(6): 115769. 40440169
  39. [45]McCracken NA, Justice SAP, Smith-Kinnaman WR, Wijeratne HS, Runnebohm AM, Pelletier S, Application of Whole Proteome Thermal Shift Assays to Define PERK-dependent Changes in Protein Homeostasis during the Unfolded Protein Response [Internet]. bioRxiv; 2025 [cited 2025 May 7]. p. 2025.04.08.647882. Available from: https://www.biorxiv.org/content/10.1101/2025.04.08.647882v1 · DOI
  40. [47]Gaetani M, Zubarev RA. Proteome Integral Solubility Alteration (PISA) for High-Throughput Ligand Target Deconvolution with Increased Statistical Significance and Reduced Sample Amount. Methods Mol Biol Clifton NJ. 2023; 2554: 91– 106. 36178622
  41. [48]Berlivet S, Moussette S, Ouimet M, Verlaan DJ, Koka V, Al Tuwaijri A, Interaction between genetic and epigenetic variation defines gene expression patterns at the asthma-associated locus 17q12-q21 in lymphoblastoid cell lines. Hum Genet. 2012 Jul; 131(7): 1161– 71. 22271045 PMC3374122
  42. [49]Gicquel C, Rossignol S, Cabrol S, Houang M, Steunou V, Barbu V, Epimutation of the telomeric imprinting center region on chromosome 11p15 in Silver-Russell syndrome. Nat Genet. 2005 Sep; 37(9): 1003– 7. 16086014
  43. [50]Jentarra GM, Rice SG, Olfers S, Rajan C, Saffen DM, Narayanan V. Skewed allele-specific expression of the NF1 gene in normal subjects: a possible mechanism for phenotypic variability in neurofibromatosis type 1. J Child Neurol. 2012 Jun; 27(6): 695– 702. 22068829
  44. [51]St. Pierre CL, Macias-Velasco JF, Wayhart JP, Yin L, Semenkovich CF, Lawson HA. Genetic, epigenetic, and environmental mechanisms govern allele-specific gene expression. Genome Res. 2022 Jun; 32(6): 1042– 57. 35501130 PMC9248887
  45. [52]Pastinen T. Genome-wide allele-specific analysis: insights into regulatory variation. Nat Rev Genet. 2010 Aug; 11(8): 533– 8. 20567245
  46. [53]Hinnebusch AG, Ivanov IP, Sonenberg N. Translational control by 5’-untranslated regions of eukaryotic mRNAs. Science. 2016 Jun 17; 352(6292): 1413– 6. 27313038 PMC7422601
  47. [54]Leppek K, Das R, Barna M. Functional 5′ UTR mRNA structures in eukaryotic translation regulation and how to find them. Nat Rev Mol Cell Biol. 2018 Mar; 19(3): 158– 74. 29165424 PMC5820134
  48. [55]Mayr C. Regulation by 3’-Untranslated Regions. Annu Rev Genet. 2017 Nov 27; 51: 171– 94. 28853924
  49. [56]Dassi E, Re A, Leo S, Tebaldi T, Pasini L, Peroni D, AURA 2: Empowering discovery of post-transcriptional networks. Transl Austin Tex. 2014; 2(1): e27738. PMC4705823 26779400
  50. [57]Dassi E, Malossini A, Re A, Mazza T, Tebaldi T, Caputi L, AURA: Atlas of UTR Regulatory Activity. Bioinformatics. 2012 Jan 1; 28(1): 142– 4. 22057158
  51. [60]Mateus A, Kurzawa N, Becher I, Sridharan S, Helm D, Stein F, Thermal proteome profiling for interrogating protein interactions. Mol Syst Biol [Internet]. 2020 Mar [cited 2022 Feb 18]; 16(3). Available from: https://onlinelibrary.wiley.com/doi/10.15252/msb.20199232 PMC7057112 32133759 · DOI · Paper page
  52. [61]Singh S, Vanden Broeck A, Miller L, Chaker-Margot M, Klinge S. Nucleolar maturation of the human small subunit processome. Science. 2021 Sep 10; 373(6560): eabj5338. 34516797 PMC8744464
  53. [62]Phipps KR, Charette JM, Baserga SJ. The SSU Processome in Ribosome Biogenesis – Progress and Prospects. Wiley Interdiscip Rev RNA. 2011 Jan; 2(1): 1– 21. 21318072 PMC3035417
  54. [63]Costello JL, Stead JA, Feigenbutz M, Jones RM, Mitchell P. The C-terminal region of the exosome-associated protein Rrp47 is specifically required for box C/D small nucleolar RNA 3’-maturation. J Biol Chem. 2011 Feb 11; 286(6): 4535– 43. 21135092 PMC3039359
  55. [64]Milligan L, Decourty L, Saveanu C, Rappsilber J, Ceulemans H, Jacquier A, A Yeast Exosome Cofactor, Mpp6, Functions in RNA Surveillance and in the Degradation of Noncoding RNA Transcripts. Mol Cell Biol. 2008 Sep; 28(17): 5446– 57. 18591258 PMC2519741
  56. [65]Halevy A, Lerer I, Cohen R, Kornreich L, Shuper A, Gamliel M, Novel EXOSC3 mutation causes complicated hereditary spastic paraplegia. J Neurol. 2014 Nov; 261(11): 2165– 9. 25149867
  57. [66]Ryan MM, Cooke-Yarborough CM, Procopis PG, Ouvrier RA. Anterior horn cell disease and olivopontocerebellar hypoplasia. Pediatr Neurol. 2000 Aug; 23(2): 180– 4. 11020648
  58. [67]Mu W, Heller T, Barañano KW. Two siblings with a novel variant of EXOSC3 extended phenotypic spectrum of pontocerebellar hypoplasia 1B to an exceptionally mild form. BMJ Case Rep CP. 2021 Jan 1; 14(1): e236732. PMC7813329 33462000
  59. [68]Kuliyev E, Gingras S, Guy CS, Howell S, Vogel P, Pelletier S. Overlapping Role of SCYL1 and SCYL3 in Maintaining Motor Neuron Viability. J Neurosci Off J Soc Neurosci. 2018 Mar 7; 38(10): 2615– 30. PMC6705897 29437892
  60. [69]Pelletier S, Gingras S, Green DR. Mouse genome engineering via CRISPR-Cas9 for study of immune function. Immunity. 2015 Jan 20; 42(1): 18– 27. 25607456 PMC4720985
  61. [72]Yates AD, Achuthan P, Akanni W, Allen J, Allen J, Alvarez-Jarreta J, Ensembl 2020. Nucleic Acids Res. 2020 Jan 8; 48(D1): D682– 8. 31691826 PMC7145704
  62. [73]Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, STAR: ultrafast universal RNA-seq aligner. Bioinforma Oxf Engl. 2013 Jan 1; 29(1): 15– 21. PMC3530905 23104886
  63. [74]Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinforma Oxf Engl. 2014 Apr 1; 30(7): 923– 30. 24227677
  64. [75]Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinforma Oxf Engl. 2010 Jan 1; 26(1): 139– 40. PMC2796818 19910308
  65. [76]Stephens M. False discovery rates: a new deal. Biostat Oxf Engl. 2017 Apr 1; 18(2): 275– 94. PMC5379932 27756721
  66. [77]Ge SX, Jung D, Yao R. ShinyGO: a graphical gene-set enrichment tool for animals and plants. Bioinformatics. 2020 Apr 15; 36(8): 2628– 9. 31882993 PMC7178415
  67. [78]Snel B, Lehmann G, Bork P, Huynen MA. STRING: a web-server to retrieve and display the repeatedly occurring neighbourhood of a gene. Nucleic Acids Res. 2000 Sep 15; 28(18): 3442– 4. 10982861 PMC110752
  68. [79]von Mering C, Huynen M, Jaeggi D, Schmidt S, Bork P, Snel B. STRING: a database of predicted functional associations between proteins. Nucleic Acids Res. 2003 Jan 1; 31(1): 258– 61. 12519996 PMC165481
  69. [80]von Mering C, Jensen LJ, Snel B, Hooper SD, Krupp M, Foglierini M, STRING: known and predicted protein-protein associations, integrated and transferred across organisms. Nucleic Acids Res. 2005 Jan 1; 33(Database issue): D433– 437. 15608232 PMC539959
  70. [81]Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019 Jan 8; 47(D1): D607– 13. 30476243 PMC6323986
  71. [82]Szklarczyk D, Kirsch R, Koutrouli M, Nastou K, Mehryary F, Hachilif R, The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 2023 Jan 6; 51(D1): D638– 46. 36370105 PMC9825434
  72. [83]Wickham H. ggplot2: Elegant Graphics for Data Analysis [Internet]. New York, NY: Springer; 2009 [cited 2023 Jun 6]. Available from: https://link.springer.com/10.1007/978-0-387-98141-3 · DOI · Paper page
  73. [84]Zinder JC, Lima CD. Targeting RNA for processing or destruction by the eukaryotic RNA exosome and its cofactors. Genes Dev. 2017 Jan 15; 31(2): 88– 100. 28202538 PMC5322736
  74. [86]Metsalu T, Vilo J. ClustVis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap. Nucleic Acids Res. 2015 Jul 1; 43(W1): W566– 70. 25969447 PMC4489295

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Authors
Runnebohm, A. M., Wijeratne, H. R. S., Barron, M. P., Smith-Kinnaman, W. R., Rooney, J. D., Peck Justice, S. A., Cureton, L. A., Holland, A., Ghalei, H., Pelletier, S., Doud, E. H., Vilseck, J. Z., & Mosley, A. L.
Affiliations
  • Indiana University Health (US)
  • Indiana University Indianapolis (US)
  • Indiana University School of Medicine (US)
  • Department of Biology, Marian University, Indianapolis, IN
  • Emory University (US)
Corresponding author
Mosley, Amber L.
Venue
bioRxiv (Cold Spring Harbor Laboratory)
Publisher
openRxiv
Published
2025-06-01
OpenAlex
W4410940018
Cited by
4
References
8
Citations by year
2026: 3 · 2025: 1
Type
posted content
Language
en
Open access
Locations
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion, cc-by-nc-nd)
  • IUScholarWorks (Indiana University) (submittedVersion, cc-by-nc-nd)
Funders
National Institute of Neurological Disorders and Stroke (R01NS121550)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA regulation and disease
Keywords
EXOSC3, RNA exosome, missense mutations, DIS3, rRNA processing, protein thermal stability, protein destabilization, variants of uncertain significance

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