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Low Level of Expression of C-Terminally Truncated Human FUS Causes Extensive Changes in the Spinal Cord Transcriptome of Asymptomatic Transgenic Mice

Neurochemical Research volume 45, pages 1168–1179 (2020)Cite this article

Abstract

A number of mutations in a gene encoding RNA-binding protein FUS have been linked to the development of a familial form of amyotrophic lateral sclerosis known as FUS-ALS. C-terminal truncations of FUS by either nonsense or frameshift mutations lead to the development of FUS-ALS with a particularly early onset and fast progression. However, even in patients bearing these highly pathogenic mutations the function of motor neurons is not noticeably compromised for at least a couple of decades, suggesting that until cytoplasmic levels of FUS lacking its C-terminal nuclear localisation signal reaches a critical threshold, motor neurons are able to tolerate its permanent production. In order to identify how the nervous system responds to low levels of pathogenic variants of FUS we produced and characterised a mouse line, L-FUS[1–359], with a low neuronal expression level of a highly aggregation-prone and pathogenic form of C-terminally truncated FUS. In contrast to mice that express substantially higher level of the same FUS variant and develop severe early onset motor neuron pathology, L-FUS[1–359] mice do not develop any clinical or histopathological signs of motor neuron deficiency even at old age. Nevertheless, we detected substantial changes in the spinal cord transcriptome of these mice compared to their wild type littermates. We suggest that at least some of these changes reflect activation of cellular mechanisms compensating for the potentially damaging effect of pathogenic FUS production. Further studies of these mechanism might reveal effective targets for therapy of FUS-ALS and possibly, other forms of ALS.

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Data Availability

Data generated during this study are included in this published article and its Supplementary Information files and the RNA sequencing data were deposited in Gene Expression Omnibus (GEO) under the number GSE130604.

References

  1. Deng HX, Zhai H, Bigio EH et al (2010) FUS-immunoreactive inclusions are a common feature in sporadic and non-SOD1 familial amyotrophic lateral sclerosis. Ann Neurol 67(6):739–748. https://doi.org/10.1002/ana.22051

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Al-Chalabi A, Jones A, Troakes C, King A, Al-Sarraj S, van den Berg LH (2012) The genetics and neuropathology of amyotrophic lateral sclerosis. Acta Neuropathol 124(3):339–352. https://doi.org/10.1007/s00401-012-1022-4

    Article  CAS  PubMed  Google Scholar 

  3. Polymenidou M, Lagier-Tourenne C, Hutt KR, Bennett CF, Cleveland DW, Yeo GW (2012) Misregulated RNA processing in amyotrophic lateral sclerosis. Brain Res 1462:3–15. https://doi.org/10.1016/j.brainres.2012.02.059

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Deng H, Gao K, Jankovic J (2014) The role of FUS gene variants in neurodegenerative diseases. Nat Rev Neurol 10(6):337–348. https://doi.org/10.1038/nrneurol.2014.78

    Article  CAS  PubMed  Google Scholar 

  5. Mackenzie IR, Munoz DG, Kusaka H, Yokota O, Ishihara K, Roeber S, Kretzschmar HA, Cairns NJ, Neumann M (2011) Distinct pathological subtypes of FTLD-FUS. Acta Neuropathol 121(2):207–218. https://doi.org/10.1007/s00401-010-0764-0

    Article  PubMed  Google Scholar 

  6. Mackenzie IR, Rademakers R, Neumann M (2010) TDP-43 and FUS in amyotrophic lateral sclerosis and frontotemporal dementia. Lancet Neurol 9(10):995–1007. https://doi.org/10.1016/S1474-4422(10)70195-2

    Article  CAS  PubMed  Google Scholar 

  7. Neumann M, Rademakers R, Roeber S, Baker M, Kretzschmar HA, Mackenzie IR (2009) A new subtype of frontotemporal lobar degeneration with FUS pathology. Brain 132(Pt 11):2922–2931. https://doi.org/10.1093/brain/awp214

    Article  PubMed  PubMed Central  Google Scholar 

  8. Neumann M, Roeber S, Kretzschmar HA, Rademakers R, Baker M, Mackenzie IR (2009) Abundant FUS-immunoreactive pathology in neuronal intermediate filament inclusion disease. Acta Neuropathol 118(5):605–616. https://doi.org/10.1007/s00401-009-0581-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Snowden JS, Hu Q, Rollinson S (2011) The most common type of FTLD-FUS (aFTLD-U) is associated with a distinct clinical form of frontotemporal dementia but is not related to mutations in the FUS gene. Acta Neuropathol 122(1):99–110. https://doi.org/10.1007/s00401-011-0816-0

    Article  CAS  PubMed  Google Scholar 

  10. Nolan M, Talbot K, Ansorge O (2016) Pathogenesis of FUS-associated ALS and FTD: insights from rodent models. Acta Neuropathol Commun 4(1):99. https://doi.org/10.1186/s40478-016-0358-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Van Damme P, Robberecht W, Van Den Bosch L (2017) Modelling amyotrophic lateral sclerosis: progress and possibilities. Dis Models Mech 10(5):537–549. https://doi.org/10.1242/dmm.029058

    Article  CAS  Google Scholar 

  12. Shang Y, Huang EJ (2016) Mechanisms of FUS mutations in familial amyotrophic lateral sclerosis. Brain Res 1647:65–78. https://doi.org/10.1016/j.brainres.2016.03.036

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Shelkovnikova TA, Peters OM, Deykin AV et al (2013) Fused in Sarcoma (FUS) protein lacking nuclear localization signal (NLS) and major RNA binding motifs triggers proteinopathy and severe motor phenotype in transgenic mice. J Biol Chem 288(35):25266–25274. https://doi.org/10.1074/jbc.M113.492017

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. DeJesus-Hernandez M, Kocerha J, Finch N (2010) De novo truncating FUS gene mutation as a cause of sporadic amyotrophic lateral sclerosis. Hum Mutat 31(5):E1377–1389. https://doi.org/10.1002/humu.21241

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Bosco DA, Lemay N, Ko HK, Zhou H, Burke C, Kwiatkowski TJ Jr, Sapp P, McKenna-Yasek D, Brown RH Jr, Hayward LJ (2010) Mutant FUS proteins that cause amyotrophic lateral sclerosis incorporate into stress granules. Hum Mol Genet 19(21):4160–4175. https://doi.org/10.1093/hmg/ddq335

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Belzil VV, Langlais JS, Daoud H, Dion PA, Brais B, Rouleau GA (2012) Novel FUS deletion in a patient with juvenile amyotrophic lateral sclerosis. Arch Neurol 69(5):653–656. https://doi.org/10.1001/archneurol.2011.2499

    Article  PubMed  Google Scholar 

  17. Waibel S, Neumann M, Rosenbohm A, Birve A, Volk AE, Weishaupt JH, Meyer T, Müller U, Andersen PM, Ludolph AC (2013) Truncating mutations in FUS/TLS give rise to a more aggressive ALS-phenotype than missense mutations: a clinico-genetic study in Germany. Eur J Neurol 20(3):540–546. https://doi.org/10.1111/ene.12031

    Article  CAS  PubMed  Google Scholar 

  18. Lattante S, Rouleau GA, Kabashi E (2013) TARDBP and FUS mutations associated with amyotrophic lateral sclerosis: Summary and update. Hum Mutat 34(6):812–826. https://doi.org/10.1002/humu.22319

    Article  CAS  PubMed  Google Scholar 

  19. Robinson HK, Deykin AV, Bronovitsky EV et al (2015) Early lethality and neuronal proteinopathy in mice expressing cytoplasm-targeted FUS that lacks the RNA recognition motif. Amyotroph Lateral Scler Frontotemporal Degener 16(5–6):402–409. https://doi.org/10.3109/21678421.2015.1040994

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Ninkina N, Peters O, Millership S, Salem H, van der Putten H, Buchman VL (2009) Gamma-synucleinopathy: neurodegeneration associated with overexpression of the mouse protein. Hum Mol Genet 18(10):1779–1794. https://doi.org/10.1093/hmg/ddp090

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Connor-Robson N, Peters OM, Millership S, Ninkina N, Buchman VL (2016) Combinational losses of synucleins reveal their differential requirements for compensating age-dependent alterations in motor behavior and dopamine metabolism. Neurobiol Aging 46:107–112. https://doi.org/10.1016/j.neurobiolaging.2016.06.020

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Peters OM, Millership S, Shelkovnikova TA, Soto I, Keeling L, Hann A, Marsh-Armstrong N, Buchman VL, Ninkina N (2012) Selective pattern of motor system damage in gamma-synuclein transgenic mice mirrors the respective pathology in amyotrophic lateral sclerosis. Neurobiol Dis 48(1):124–131. https://doi.org/10.1016/j.nbd.2012.06.016

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Millership S, Ninkina N, Guschina IA, Norton J, Brambilla R, Oort PJ, Adams SH, Dennis RJ, Voshol PJ, Rochford JJ, Buchman VL (2012) Increased lipolysis and altered lipid homeostasis protect gamma-synuclein-null mutant mice from diet-induced obesity. Proc Natl Acad Sci USA 109(51):20943–20948. https://doi.org/10.1073/pnas.1210022110

    Article  PubMed  PubMed Central  Google Scholar 

  24. Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30(15):2114–2120. https://doi.org/10.1093/bioinformatics/btu170

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29(1):15–21. https://doi.org/10.1093/bioinformatics/bts635

    Article  CAS  PubMed  Google Scholar 

  26. Krasnov GS, Dmitriev AA, Kudryavtseva AV et al (2015) PPLine: An automated pipeline for SNP, SAP, and splice variant detection in the context of proteogenomics. J Proteome Res 14(9):3729–3737. https://doi.org/10.1021/acs.jproteome.5b00490

    Article  CAS  PubMed  Google Scholar 

  27. Liao Y, Smyth GK, Shi W (2014) featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30(7):923–930. https://doi.org/10.1093/bioinformatics/btt656

    Article  CAS  PubMed  Google Scholar 

  28. Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26(1):139–140. https://doi.org/10.1093/bioinformatics/btp616

    Article  CAS  PubMed  Google Scholar 

  29. Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK (2015) limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43(7):e47. https://doi.org/10.1093/nar/gkv007

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Bandyopadhyay U, Cotney J, Nagy M, Oh S, Leng J, Mahajan M, Mane S, Fenton WA, Noonan JP, Horwich AL (2013) RNA-Seq profiling of spinal cord motor neurons from a presymptomatic SOD1 ALS mouse. PLoS ONE 8(1):e53575. https://doi.org/10.1371/journal.pone.0053575

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Chiu IM, Morimoto ET, Goodarzi H, Liao JT, O'Keeffe S, Phatnani HP, Muratet M, Carroll MC, Levy S, Tavazoie S, Myers RM, Maniatis T (2013) A neurodegeneration-specific gene-expression signature of acutely isolated microglia from an amyotrophic lateral sclerosis mouse model. Cell Rep 4(2):385–401. https://doi.org/10.1016/j.celrep.2013.06.018

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Funikov SY, Rezvykh AP, Mazin PV, Morozov AV, Maltsev AV, Chicheva MM, Vikhareva EA, Evgen'ev MB, Ustyugov AA (2018) FUS(1–359) transgenic mice as a model of ALS: pathophysiological and molecular aspects of the proteinopathy. Neurogenetics 19(3):189–204. https://doi.org/10.1007/s10048-018-0553-9

    Article  CAS  PubMed  Google Scholar 

  33. Fresno C, Fernandez EA (2013) RDAVIDWebService: a versatile R interface to DAVID. Bioinformatics 29(21):2810–2811. https://doi.org/10.1093/bioinformatics/btt487

    Article  CAS  PubMed  Google Scholar 

  34. Supek F, Bosnjak M, Skunca N, Smuc T (2011) REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS ONE 6(7):e21800. https://doi.org/10.1371/journal.pone.0021800

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. R Core Team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna

    Google Scholar 

  36. Wickham H (2016) ggplot2: elegant graphics for data analysis. Springer, New York

    Book  Google Scholar 

  37. Walter W, Sanchez-Cabo F, Ricote M (2015) GOplot: an R package for visually combining expression data with functional analysis. Bioinformatics 31(17):2912–2914. https://doi.org/10.1093/bioinformatics/btv300

    Article  CAS  PubMed  Google Scholar 

  38. Lopez-Erauskin J, Tadokoro T, Baughn MW et al (2018) ALS/FTD-linked mutation in FUS suppresses intra-axonal protein synthesis and drives disease without nuclear loss-of-function of FUS. Neuron 100(4):816–830. https://doi.org/10.1016/j.neuron.2018.09.044

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Sharma A, Lyashchenko AK, Lu L, Nasrabady SE, Elmaleh M, Mendelsohn M, Nemes A, Tapia JC, Mentis GZ, Shneider NA (2016) ALS-associated mutant FUS induces selective motor neuron degeneration through toxic gain of function. Nat Commun 7:10465. https://doi.org/10.1038/ncomms10465

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Devoy A, Kalmar B, Stewart M et al (2017) Humanized mutant FUS drives progressive motor neuron degeneration without aggregation in 'FUSDelta14' knockin mice. Brain 140(11):2797–2805. https://doi.org/10.1093/brain/awx248

    Article  PubMed  PubMed Central  Google Scholar 

  41. Scekic-Zahirovic J, Sendscheid O, El Oussini H et al (2016) Toxic gain of function from mutant FUS protein is crucial to trigger cell autonomous motor neuron loss. EMBO J 35(10):1077–1097. https://doi.org/10.15252/embj.201592559

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Shiihashi G, Ito D, Yagi T, Nihei Y, Ebine T, Suzuki N (2016) Mislocated FUS is sufficient for gain-of-toxic-function amyotrophic lateral sclerosis phenotypes in mice. Brain 139(Pt 9):2380–2394. https://doi.org/10.1093/brain/aww161

    Article  PubMed  Google Scholar 

  43. Humphrey J, Birsa N, Milioto C et al (2019) FUS ALS-causative mutations impact FUS autoregulation and the processing of RNA-binding proteins through intron retention. bioRxiv. https://doi.org/10.1101/567735

    Article  Google Scholar 

  44. Scekic-Zahirovic J, Oussini HE, Mersmann S et al (2017) Motor neuron intrinsic and extrinsic mechanisms contribute to the pathogenesis of FUS-associated amyotrophic lateral sclerosis. Acta Neuropathol 133(6):887–906. https://doi.org/10.1007/s00401-017-1687-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Lerga A, Hallier M, Delva L, Orvain C, Gallais I, Marie J, Moreau-Gachelin F (2001) Identification of an RNA binding specificity for the potential splicing factor TLS. J Biol Chem 276(9):6807–6816. https://doi.org/10.1074/jbc.M008304200

    Article  CAS  PubMed  Google Scholar 

  46. Bentmann E, Neumann M, Tahirovic S, Rodde R, Dormann D, Haass C (2012) Requirements for stress granule recruitment of fused in sarcoma (FUS) and TAR DNA-binding protein of 43 kDa (TDP-43). J Biol Chem 287(27):23079–23094. https://doi.org/10.1074/jbc.M111.328757

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Liu X, Niu C, Ren J, Zhang J, Xie X, Zhu H, Feng W (1832) Gong W (2013) The RRM domain of human fused in sarcoma protein reveals a non-canonical nucleic acid binding site. Biochim Biophys Acta 2:375–385. https://doi.org/10.1016/j.bbadis.2012.11.012

    Article  CAS  Google Scholar 

  48. Shelkovnikova TA, Robinson HK, Connor-Robson N, Buchman VL (2013) Recruitment into stress granules prevents irreversible aggregation of FUS protein mislocalized to the cytoplasm. Cell Cycle 12(19):3194–3202. https://doi.org/10.4161/cc.26241

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Shelkovnikova TA, Robinson HK, Southcombe JA, Ninkina N, Buchman VL (2014) Multistep process of FUS aggregation in the cell cytoplasm involves RNA-dependent and RNA-independent mechanisms. Hum Mol Genet 23(19):5211–5226. https://doi.org/10.1093/hmg/ddu243

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Belly A, Moreau-Gachelin F, Sadoul R, Goldberg Y (2005) Delocalization of the multifunctional RNA splicing factor TLS/FUS in hippocampal neurones: exclusion from the nucleus and accumulation in dendritic granules and spine heads. Neurosci Lett 379(3):152–157. https://doi.org/10.1016/j.neulet.2004.12.071

    Article  CAS  PubMed  Google Scholar 

  51. Fujii R, Okabe S, Urushido T, Inoue K, Yoshimura A, Tachibana T, Nishikawa T, Hicks GG, Takumi T (2005) The RNA binding protein TLS is translocated to dendritic spines by mGluR5 activation and regulates spine morphology. Curr Biol 15(6):587–593. https://doi.org/10.1016/j.cub.2005.01.058

    Article  CAS  PubMed  Google Scholar 

  52. Schoen M, Reichel JM, Demestre M, Putz S, Deshpande D, Proepper C, Liebau S, Schmeisser MJ, Ludolph AC, Michaelis J, Boeckers TM (2015) Super-resolution microscopy reveals presynaptic localization of the ALS/FTD related protein FUS in Hippocampal neurons. Front Cell Neurosci 9:496. https://doi.org/10.3389/fncel.2015.00496

    Article  CAS  PubMed  Google Scholar 

  53. So E, Mitchell JC, Memmi C, Chennell G, Vizcay-Barrena G, Allison L, Shaw CE, Vance C (2018) Mitochondrial abnormalities and disruption of the neuromuscular junction precede the clinical phenotype and motor neuron loss in hFUSWT transgenic mice. Hum Mol Genet 27(3):463–474. https://doi.org/10.1093/hmg/ddx415

    Article  CAS  PubMed  Google Scholar 

  54. Udagawa T, Fujioka Y, Tanaka M et al (2015) FUS regulates AMPA receptor function and FTLD/ALS-associated behaviour via GluA1 mRNA stabilization. Nat Commun 6:7098. https://doi.org/10.1038/ncomms8098

    Article  CAS  PubMed  Google Scholar 

  55. Yasuda K, Zhang H, Loiselle D, Haystead T, Macara IG, Mili S (2013) The RNA-binding protein Fus directs translation of localized mRNAs in APC-RNP granules. J Cell Biol 203(5):737–746. https://doi.org/10.1083/jcb.201306058

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We are thankful to Angela Marchbank and Georgina Smethurst from the Cardiff School of Biosciences Genomics Research Hub for help with RNA sequencing, Don Cleveland for sharing with us human FUS specific antibody, and Harri Harrison for critical reading of the manuscript. This study was supported by Russian Science Foundation Projects RScF#18–15-00357 (phenotyping of L-FUS mice), RScF#17-75-20-249, (producing the L-FUS mice) and the Motor Neuron Disease Association research grant (Buchman/Apr13/6096). Bioresource Collection of IPAC RAS (No. 0090-2017-0016) and Core Facility IGB RAS were used to maintain transgenic mice and test their behaviour using equipment of the Centre for Collective Use IPAC RAS. RNA sequencing analysis was supported by Russian President Foundation grant MК-3316.2019.4. Differential expression analysis was performed using the equipment of the Engelhardt Institute of Molecular Biology RAS “Genome” center (https://www.eimb.ru/rus/ckp/ccu_genome_c.php).

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Authors and Affiliations

  1. Institute of Physiologically Active Compounds, Russian Academy of Sciences, 1 Severnyj Proezd, Chernogolovka, Russian Federation

    Ekaterina A. Lysikova, Kirill D. Chaprov, Michail S. Kukharsky, Aleksey Ustyugov, Sergey O. Bachurin, Natalia Ninkina & Vladimir L. Buchman

  2. School of Biosciences, Cardiff University, Sir Martin Evans Building, Museum Avenue, Cardiff, CF10 3AX, UK

    Ekaterina A. Lysikova, Natalia Ninkina & Vladimir L. Buchman

  3. Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Vavilova str., 32, Moscow, Russian Federation, 119991

    Sergei Funikov & Alexander P. Rezvykh

  4. Moscow Institute of Physics and Technology, 9 Institutskiy Per., Dolgoprudny, Moscow Region, Russian Federation, 141701

    Alexander P. Rezvykh

  5. Pirogov Russian National Research Medical University, Ostrovitianova str 1, Moscow, Russian Federation

    Michail S. Kukharsky

  6. Institute of Gene Biology, Russian Academy of Sciences, Vavilova str., 34/5, Moscow, Russian Federation, 19334

    Alexey V. Deykin

  7. MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK

    Ilya M. Flyamer & Shelagh Boyle

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  1. Ekaterina A. Lysikova
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Contributions

NN and VLB conceived the project, designed the study, carried out certain experiments, interpreted experimental data and wrote the manuscript. EAL acquired and analysed molecular biology and behaviour data, prepared figures and wrote drafts of manuscript sections. SF and APR performed bioinformatic analysis of RNAseq data, drafted results and prepared corresponding table and figures. KDC and MSK performed immunohistochemical and Western blot analyses. AU and AVD produced transgenic mice and generated survival data. IMF and SB defined chromosomal localisation of transgenic cassettes in both hFUS[1–359] lines. SOB interpreted experimental data. All authors reviewed the manuscript.

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Correspondence to Ekaterina A. Lysikova.

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The authors declare no competing interests.

Ethical Approval

All procedures performed in studies involving animals were in accordance with the ethical standards of the institution or practice at which the studies were conducted (The Bioethics committee of Institute of Physiologically Active Compounds, Russian Academy of Sciences approval No. 20 dated 23.06.2017). All animal work was carried out in accordance with this approval and the Rules of Good Laboratory Practice in Russian Federation (2016).

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Lysikova, E.A., Funikov, S., Rezvykh, A.P. et al. Low Level of Expression of C-Terminally Truncated Human FUS Causes Extensive Changes in the Spinal Cord Transcriptome of Asymptomatic Transgenic Mice. Neurochem Res 45, 1168–1179 (2020). https://doi.org/10.1007/s11064-020-02999-z

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Keywords

  • ALS
  • FUS
  • Proteinopathy
  • Gene expression
  • Transgenic mice