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Home / Equine Research Bank / BMC Genomics / Integrated proteomic and transcriptomic profiling identifies...
BMC genomics2021; 22(1); 438; doi: 10.1186/s12864-021-07758-0

Integrated proteomic and transcriptomic profiling identifies aberrant gene and protein expression in the sarcomere, mitochondrial complex I, and the extracellular matrix in Warmblood horses with myofibrillar myopathy.

Abstract: Myofibrillar myopathy in humans causes protein aggregation, degeneration, and weakness of skeletal muscle. In horses, myofibrillar myopathy is a late-onset disease of unknown origin characterized by poor performance, atrophy, myofibrillar disarray, and desmin aggregation in skeletal muscle. This study evaluated molecular and ultrastructural signatures of myofibrillar myopathy in Warmblood horses through gluteal muscle tandem-mass-tag quantitative proteomics (5 affected, 4 control), mRNA-sequencing (8 affected, 8 control), amalgamated gene ontology analyses, and immunofluorescent and electron microscopy. Results: We identified 93/1533 proteins and 47/27,690 genes that were significantly differentially expressed. The top significantly differentially expressed protein CSRP3 and three other differentially expressed proteins, including, PDLIM3, SYNPO2, and SYNPOL2, are integrally involved in Z-disc signaling, gene transcription and subsequently sarcomere integrity. Through immunofluorescent staining, both desmin aggregates and CSRP3 were localized to type 2A fibers. The highest differentially expressed gene CHAC1, whose protein product degrades glutathione, is associated with oxidative stress and apoptosis. Amalgamated transcriptomic and proteomic gene ontology analyses identified 3 enriched cellular locations; the sarcomere (Z-disc & I-band), mitochondrial complex I and the extracellular matrix which corresponded to ultrastructural Z-disc disruption and mitochondrial cristae alterations found with electron microscopy. Conclusions: A combined proteomic and transcriptomic analysis highlighted three enriched cellular locations that correspond with MFM ultrastructural pathology in Warmblood horses. Aberrant Z-disc mechano-signaling, impaired Z-disc stability, decreased mitochondrial complex I expression, and a pro-oxidative cellular environment are hypothesized to contribute to the development of myofibrillar myopathy in Warmblood horses. These molecular signatures may provide further insight into diagnostic biomarkers, treatments, and the underlying pathophysiology of MFM.
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Publication Date: 2021-06-11 PubMed ID: 34112090PubMed Central: PMC8194174DOI: 10.1186/s12864-021-07758-0Google Scholar: Lookup
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  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This research analyses the molecular and ultrastructural signatures of a late-onset disease known as myofibrillar myopathy in Warmblood horses. The researchers identified altered gene and protein expressions associated with this disease that may provide insights into its diagnosis, treatment, and understanding of its pathophysiology.

Introduction and Background

  • Myofibrillar myopathy, or MFM, in horses is a poorly understood disease. It is characterized by poor performance, muscle atrophy (shrinkage), muscle fiber disorder, and the accumulation of a particular muscle protein, desmin. No known cause has been established yet.
  • This disease has been parallelled to a similar condition in humans leading to skeletal muscle weakness and degeneration.

Research Methodology

  • The researchers undertook a combined approach to their study, utilizing both proteomic (studying proteins) and transcriptomic (studying gene activity) profiling.
  • Tissue samples were taken from the gluteal muscle of Warmblood horses, both healthy and those affected by MFM. Advanced techniques like tandem-mass-tag quantitative proteomics and mRNA-sequencing were used to analyze the samples.
  • Apart from this molecular profiling, researchers also studied the ultrastructural changes in the muscle fibers using electron microscopy.

Results

  • 93 proteins and 47 genes were found to be significantly differentially expressed between healthy and diseased horses.
  • Specifically, four proteins (CSRP3, PDLIM3, SYNPO2, and SYNPOL2) primarily involved in Z-disc signaling and sarcomere integrity were differently expressed. Sarcomere is the basic unit of muscle tissue, and Z-disc is an important part of it.
  • Increased expressions of desmin and CSRP3 were particularly observed in a specific type of muscle fiber (2A fibers).
  • The most significantly differentially expressed gene was CHAC1, known for its role in degrading a naturally produced antioxidant—glutathione. This suggests a state of oxidative stress and cell death (apoptosis).
  • Through electron microscopy, researchers confirmed the disruptions at Z-disc, and changes to mitochondrial cristae (interior of mitochondria)

Conclusions

  • The combined proteomic and transcriptomic approach allowed researchers to pinpoint three specific cellular locations or structures that show differences in myofibrillar myopathy affected Warmblood horses—sarcomere (Z-disc and I-band), mitochondrial complex I and the extracellular matrix.
  • These changes suggest that a complex interplay of unstable Z-disc, impaired mitochondrial function, and a pro-oxidative environment might be at play in the development of MFM.
  • This research helps in a better understanding of the pathophysiology of MFM, and might eventually aid in designing diagnostic biomarkers and therapeutic interventions.

Cite This Article

APA
Williams ZJ, Velez-Irizarry D, Gardner K, Valberg SJ. (2021). Integrated proteomic and transcriptomic profiling identifies aberrant gene and protein expression in the sarcomere, mitochondrial complex I, and the extracellular matrix in Warmblood horses with myofibrillar myopathy. BMC Genomics, 22(1), 438. https://doi.org/10.1186/s12864-021-07758-0

Publication

BMC genomics
ISSN: 1471-2164
NlmUniqueID: 100965258
Country: England
Language: English
Volume: 22
Issue: 1
Pages: 438
PII: 438

Researcher Affiliations

Williams, Zoë J
  • Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, 784 Wilson Road, East Lansing, MI, 48824, USA. will3084@msu.edu.
Velez-Irizarry, Deborah
  • Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, 784 Wilson Road, East Lansing, MI, 48824, USA.
Gardner, Keri
  • Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, 784 Wilson Road, East Lansing, MI, 48824, USA.
Valberg, Stephanie J
  • Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, 784 Wilson Road, East Lansing, MI, 48824, USA.

MeSH Terms

  • Animals
  • Extracellular Matrix / genetics
  • Horses
  • Muscle, Skeletal
  • Myopathies, Structural, Congenital
  • Proteomics
  • Sarcomeres
  • Transcriptome

Conflict of Interest Statement

The authors declare that they have no competing interests.

References

This article includes 116 references
  1. Selcen D, Ohno K, Engel AG. Myofibrillar myopathy: clinical, morphological and genetic studies in 63 patients.. Brain 2004 Feb;127(Pt 2):439-51.
    doi: 10.1093/brain/awh052pubmed: 14711882google scholar: lookup
  2. Frank D, Kuhn C, Katus HA, Frey N. Role of the sarcomeric Z-disc in the pathogenesis of cardiomyopathy.. Future Cardiol 2007 Nov;3(6):611-22.
    doi: 10.2217/14796678.3.6.611pubmed: 19804282google scholar: lookup
  3. Schröder R, Schoser B. Myofibrillar myopathies: a clinical and myopathological guide.. Brain Pathol 2009 Jul;19(3):483-92.
    doi: 10.1111/j.1750-3639.2009.00289.xpmc: PMC8094720pubmed: 19563540google scholar: lookup
  4. Goldfarb LG, Park KY, Cervenáková L, Gorokhova S, Lee HS, Vasconcelos O, Nagle JW, Semino-Mora C, Sivakumar K, Dalakas MC. Missense mutations in desmin associated with familial cardiac and skeletal myopathy.. Nat Genet 1998 Aug;19(4):402-3.
    doi: 10.1038/1300pubmed: 9697706google scholar: lookup
  5. Batonnet-Pichon S, Behin A, Cabet E, Delort F, Vicart P, Lilienbaum A. Myofibrillar Myopathies: New Perspectives from Animal Models to Potential Therapeutic Approaches.. J Neuromuscul Dis 2017;4(1):1-15.
    doi: 10.3233/JND-160203pmc: PMC5345645pubmed: 28269794google scholar: lookup
  6. Fichna JP, Maruszak A, Żekanowski C. Myofibrillar myopathy in the genomic context.. J Appl Genet 2018 Nov;59(4):431-439.
    doi: 10.1007/s13353-018-0463-4pubmed: 30203143google scholar: lookup
  7. Ferrer I, Olivé M. Molecular pathology of myofibrillar myopathies.. Expert Rev Mol Med 2008 Sep 3;10:e25.
    pubmed: 18764962doi: 10.1017/s1462399408000793google scholar: lookup
  8. Valberg SJ, McKenzie EC, Eyrich LV, Shivers J, Barnes NE, Finno CJ. Suspected myofibrillar myopathy in Arabian horses with a history of exertional rhabdomyolysis.. Equine Vet J 2016 Sep;48(5):548-56.
    doi: 10.1111/evj.12493pmc: PMC4833696pubmed: 26234161google scholar: lookup
  9. Valberg SJ, Nicholson AM, Lewis SS, Reardon RA, Finno CJ. Clinical and histopathological features of myofibrillar myopathy in Warmblood horses.. Equine Vet J 2017 Nov;49(6):739-745.
    doi: 10.1111/evj.12702pmc: PMC5640499pubmed: 28543538google scholar: lookup
  10. Williams ZJ, Bertels M, Valberg SJ. Muscle glycogen concentrations and response to diet and exercise regimes in Warmblood horses with type 2 Polysaccharide Storage Myopathy.. PLoS One 2018;13(9):e0203467.
    doi: 10.1371/journal.pone.0203467pmc: PMC6124783pubmed: 30183782google scholar: lookup
  11. Claeys KG, Fardeau M, Schröder R, Suominen T, Tolksdorf K, Behin A, Dubourg O, Eymard B, Maisonobe T, Stojkovic T, Faulkner G, Richard P, Vicart P, Udd B, Voit T, Stoltenburg G. Electron microscopy in myofibrillar myopathies reveals clues to the mutated gene.. Neuromuscul Disord 2008 Aug;18(8):656-66.
    doi: 10.1016/j.nmd.2008.06.367pubmed: 18653338google scholar: lookup
  12. Valberg SJ, Finno CJ, Henry ML, Schott M, Velez-Irizarry D, Peng S, McKenzie EC, Petersen JL. Commercial genetic testing for type 2 polysaccharide storage myopathy and myofibrillar myopathy does not correspond to a histopathological diagnosis.. Equine Vet J 2021 Jul;53(4):690-700.
    pmc: PMC7937766pubmed: 32896939doi: 10.1111/evj.13345google scholar: lookup
  13. Williams ZJ, Velez-Irizarry D, Petersen JL, Ochala J, Finno CJ, Valberg SJ. Candidate gene expression and coding sequence variants in Warmblood horses with myofibrillar myopathy.. Equine Vet J 2021 Mar;53(2):306-315.
    pmc: PMC7864122pubmed: 32453872doi: 10.1111/evj.13286google scholar: lookup
  14. Winter L, Wiche G. The many faces of plectin and plectinopathies: pathology and mechanisms.. Acta Neuropathol 2013 Jan;125(1):77-93.
    doi: 10.1007/s00401-012-1026-0pubmed: 22864774google scholar: lookup
  15. Bouhy D, Juneja M, Katona I, Holmgren A, Asselbergh B, De Winter V, Hochepied T, Goossens S, Haigh JJ, Libert C, Ceuterick-de Groote C, Irobi J, Weis J, Timmerman V. A knock-in/knock-out mouse model of HSPB8-associated distal hereditary motor neuropathy and myopathy reveals toxic gain-of-function of mutant Hspb8.. Acta Neuropathol 2018 Jan;135(1):131-148.
    doi: 10.1007/s00401-017-1756-0pmc: PMC5756276pubmed: 28780615google scholar: lookup
  16. O'Grady GL, Best HA, Sztal TE, Schartner V, Sanjuan-Vazquez M, Donkervoort S, Abath Neto O, Sutton RB, Ilkovski B, Romero NB, Stojkovic T, Dastgir J, Waddell LB, Boland A, Hu Y, Williams C, Ruparelia AA, Maisonobe T, Peduto AJ, Reddel SW, Lek M, Tukiainen T, Cummings BB, Joshi H, Nectoux J, Brammah S, Deleuze JF, Ing VO, Ramm G, Ardicli D, Nowak KJ, Talim B, Topaloglu H, Laing NG, North KN, MacArthur DG, Friant S, Clarke NF, Bryson-Richardson RJ, Bönnemann CG, Laporte J, Cooper ST. Variants in the Oxidoreductase PYROXD1 Cause Early-Onset Myopathy with Internalized Nuclei and Myofibrillar Disorganization.. Am J Hum Genet 2016 Nov 3;99(5):1086-1105.
    doi: 10.1016/j.ajhg.2016.09.005pmc: PMC5097943pubmed: 27745833google scholar: lookup
  17. Liu J, Chen Q, Huang W, Horak KM, Zheng H, Mestril R, Wang X. Impairment of the ubiquitin-proteasome system in desminopathy mouse hearts.. FASEB J 2006 Feb;20(2):362-4.
    doi: 10.1096/fj.05-4869fjepubmed: 16371426google scholar: lookup
  18. Lin X, Ruiz J, Bajraktari I, Ohman R, Banerjee S, Gribble K, Kaufman JD, Wingfield PT, Griggs RC, Fischbeck KH, Mankodi A. Z-disc-associated, alternatively spliced, PDZ motif-containing protein (ZASP) mutations in the actin-binding domain cause disruption of skeletal muscle actin filaments in myofibrillar myopathy.. J Biol Chem 2014 May 9;289(19):13615-26.
    doi: 10.1074/jbc.M114.550418pmc: PMC4036366pubmed: 24668811google scholar: lookup
  19. Ceciliani F, Restelli L, Lecchi C. Proteomics in farm animals models of human diseases.. Proteomics Clin Appl 2014 Oct;8(9-10):677-88.
    doi: 10.1002/prca.201300080pubmed: 24595991google scholar: lookup
  20. Shelton GD, Sammut V, Homma S, Takayama S, Mizisin AP. Myofibrillar myopathy with desmin accumulation in a young Australian Shepherd dog.. Neuromuscul Disord 2004 Jul;14(7):399-404.
    doi: 10.1016/j.nmd.2004.03.010pubmed: 15210162google scholar: lookup
  21. Tebani A, Afonso C, Marret S, Bekri S. Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations.. Int J Mol Sci 2016 Sep 14;17(9).
    doi: 10.3390/ijms17091555pmc: PMC5037827pubmed: 27649151google scholar: lookup
  22. Hasin Y, Seldin M, Lusis A. Multi-omics approaches to disease.. Genome Biol 2017 May 5;18(1):83.
    doi: 10.1186/s13059-017-1215-1pmc: PMC5418815pubmed: 28476144google scholar: lookup
  23. Sun YV, Hu YJ. Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases.. Adv Genet 2016;93:147-90.
    doi: 10.1016/bs.adgen.2015.11.004pmc: PMC5742494pubmed: 26915271google scholar: lookup
  24. Karczewski KJ, Snyder MP. Integrative omics for health and disease.. Nat Rev Genet 2018 May;19(5):299-310.
    doi: 10.1038/nrg.2018.4pmc: PMC5990367pubmed: 29479082google scholar: lookup
  25. Valberg SJ, Perumbakkam S, McKenzie EC, Finno CJ. Proteome and transcriptome profiling of equine myofibrillar myopathy identifies diminished peroxiredoxin 6 and altered cysteine metabolic pathways.. Physiol Genomics 2018 Dec 1;50(12):1036-1050.
    doi: 10.1152/physiolgenomics.00044.2018pmc: PMC6337024pubmed: 30289745google scholar: lookup
  26. Selcen D, Engel AG. Myofibrillar myopathies.. Handb Clin Neurol 2011;101:143-54.
    doi: 10.1016/B978-0-08-045031-5.00011-6pubmed: 21496631google scholar: lookup
  27. Clark KA, McElhinny AS, Beckerle MC, Gregorio CC. Striated muscle cytoarchitecture: an intricate web of form and function.. Annu Rev Cell Dev Biol 2002;18:637-706.
    doi: 10.1146/annurev.cellbio.18.012502.105840pubmed: 12142273google scholar: lookup
  28. Olivé M, Goldfarb L, Dagvadorj A, Sambuughin N, Paulin D, Li Z, Goudeau B, Vicart P, Ferrer I. Expression of the intermediate filament protein synemin in myofibrillar myopathies and other muscle diseases.. Acta Neuropathol 2003 Jul;106(1):1-7.
    doi: 10.1007/s00401-003-0695-0pubmed: 12669240google scholar: lookup
  29. Maerkens A, Olivé M, Schreiner A, Feldkirchner S, Schessl J, Uszkoreit J, Barkovits K, Güttsches AK, Theis V, Eisenacher M, Tegenthoff M, Goldfarb LG, Schröder R, Schoser B, van der Ven PF, Fürst DO, Vorgerd M, Marcus K, Kley RA. New insights into the protein aggregation pathology in myotilinopathy by combined proteomic and immunolocalization analyses.. Acta Neuropathol Commun 2016 Feb 3;4:8.
    doi: 10.1186/s40478-016-0280-0pmc: PMC4739336pubmed: 26842778google scholar: lookup
  30. Vafiadaki E, Arvanitis DA, Sanoudou D. Muscle LIM Protein: Master regulator of cardiac and skeletal muscle functions.. Gene 2015 Jul 15;566(1):1-7.
    doi: 10.1016/j.gene.2015.04.077pmc: PMC6660132pubmed: 25936993google scholar: lookup
  31. Vafiadaki E, Arvanitis DA, Papalouka V, Terzis G, Roumeliotis TI, Spengos K, Garbis SD, Manta P, Kranias EG, Sanoudou D. Muscle lim protein isoform negatively regulates striated muscle actin dynamics and differentiation.. FEBS J 2014 Jul;281(14):3261-79.
    doi: 10.1111/febs.12859pmc: PMC4416226pubmed: 24860983google scholar: lookup
  32. Maerkens A, Kley RA, Olivé M, Theis V, van der Ven PF, Reimann J, Milting H, Schreiner A, Uszkoreit J, Eisenacher M, Barkovits K, Güttsches AK, Tonillo J, Kuhlmann K, Meyer HE, Schröder R, Tegenthoff M, Fürst DO, Müller T, Goldfarb LG, Vorgerd M, Marcus K. Differential proteomic analysis of abnormal intramyoplasmic aggregates in desminopathy.. J Proteomics 2013 Sep 2;90:14-27.
    doi: 10.1016/j.jprot.2013.04.026pmc: PMC5120880pubmed: 23639843google scholar: lookup
  33. Kley RA, Maerkens A, Leber Y, Theis V, Schreiner A, van der Ven PF, Uszkoreit J, Stephan C, Eulitz S, Euler N, Kirschner J, Müller K, Meyer HE, Tegenthoff M, Fürst DO, Vorgerd M, Müller T, Marcus K. A combined laser microdissection and mass spectrometry approach reveals new disease relevant proteins accumulating in aggregates of filaminopathy patients.. Mol Cell Proteomics 2013 Jan;12(1):215-27.
    doi: 10.1074/mcp.M112.023176pmc: PMC3536902pubmed: 23115302google scholar: lookup
  34. Frank D, Frey N. Cardiac Z-disc signaling network.. J Biol Chem 2011 Mar 25;286(12):9897-904.
    doi: 10.1074/jbc.R110.174268pmc: PMC3060542pubmed: 21257757google scholar: lookup
  35. Buyandelger B, Mansfield C, Knöll R. Mechano-signaling in heart failure.. Pflugers Arch 2014 Jun;466(6):1093-9.
    doi: 10.1007/s00424-014-1468-4pmc: PMC4033803pubmed: 24531746google scholar: lookup
  36. Weins A, Schwarz K, Faul C, Barisoni L, Linke WA, Mundel P. Differentiation- and stress-dependent nuclear cytoplasmic redistribution of myopodin, a novel actin-bundling protein.. J Cell Biol 2001 Oct 29;155(3):393-404.
    doi: 10.1083/jcb.200012039pmc: PMC2150840pubmed: 11673475google scholar: lookup
  37. Ecarnot-Laubriet A, De Luca K, Vandroux D, Moisant M, Bernard C, Assem M, Rochette L, Teyssier JR. Downregulation and nuclear relocation of MLP during the progression of right ventricular hypertrophy induced by chronic pressure overload.. J Mol Cell Cardiol 2000 Dec;32(12):2385-95.
    doi: 10.1006/jmcc.2000.1269pubmed: 11113014google scholar: lookup
  38. Lontay B, Bodoor K, Weitzel DH, Loiselle D, Fortner C, Lengyel S, Zheng D, Devente J, Hickner R, Haystead TA. Smoothelin-like 1 protein regulates myosin phosphatase-targeting subunit 1 expression during sexual development and pregnancy.. J Biol Chem 2010 Sep 17;285(38):29357-66.
    doi: 10.1074/jbc.M110.143966pmc: PMC2937968pubmed: 20634291google scholar: lookup
  39. Ulke-Lemée A, Turner SR, Mughal SH, Borman MA, Winkfein RJ, MacDonald JA. Mapping and functional characterization of the murine smoothelin-like 1 promoter.. BMC Mol Biol 2011 Feb 27;12:10.
    doi: 10.1186/1471-2199-12-10pmc: PMC3050715pubmed: 21352594google scholar: lookup
  40. Kostek MC, Chen YW, Cuthbertson DJ, Shi R, Fedele MJ, Esser KA, Rennie MJ. Gene expression responses over 24 h to lengthening and shortening contractions in human muscle: major changes in CSRP3, MUSTN1, SIX1, and FBXO32.. Physiol Genomics 2007 Sep 19;31(1):42-52.
    doi: 10.1152/physiolgenomics.00151.2006pubmed: 17519359google scholar: lookup
  41. Vincent B, Windelinckx A, Nielens H, Ramaekers M, Van Leemputte M, Hespel P, Thomis MA. Protective role of alpha-actinin-3 in the response to an acute eccentric exercise bout.. J Appl Physiol (1985) 2010 Aug;109(2):564-73.
    doi: 10.1152/japplphysiol.01007.2009pubmed: 20507967google scholar: lookup
  42. McHugh MP. Recent advances in the understanding of the repeated bout effect: the protective effect against muscle damage from a single bout of eccentric exercise.. Scand J Med Sci Sports 2003 Apr;13(2):88-97.
    doi: 10.1034/j.1600-0838.2003.02477.xpubmed: 12641640google scholar: lookup
  43. Aoki S. BIORENDER: Biorender; 2017.
  44. Heineke J, Ruetten H, Willenbockel C, Gross SC, Naguib M, Schaefer A, Kempf T, Hilfiker-Kleiner D, Caroni P, Kraft T, Kaiser RA, Molkentin JD, Drexler H, Wollert KC. Attenuation of cardiac remodeling after myocardial infarction by muscle LIM protein-calcineurin signaling at the sarcomeric Z-disc.. Proc Natl Acad Sci U S A 2005 Feb 1;102(5):1655-60.
    doi: 10.1073/pnas.0405488102pmc: PMC547821pubmed: 15665106google scholar: lookup
  45. Louis HA, Pino JD, Schmeichel KL, Pomiès P, Beckerle MC. Comparison of three members of the cysteine-rich protein family reveals functional conservation and divergent patterns of gene expression.. J Biol Chem 1997 Oct 24;272(43):27484-91.
    doi: 10.1074/jbc.272.43.27484pubmed: 9341203google scholar: lookup
  46. Knöll R, Kostin S, Klede S, Savvatis K, Klinge L, Stehle I, Gunkel S, Kötter S, Babicz K, Sohns M, Miocic S, Didié M, Knöll G, Zimmermann WH, Thelen P, Bickeböller H, Maier LS, Schaper W, Schaper J, Kraft T, Tschöpe C, Linke WA, Chien KR. A common MLP (muscle LIM protein) variant is associated with cardiomyopathy.. Circ Res 2010 Mar 5;106(4):695-704.
    doi: 10.1161/CIRCRESAHA.109.206243pubmed: 20044516google scholar: lookup
  47. Geier C, Gehmlich K, Ehler E, Hassfeld S, Perrot A, Hayess K, Cardim N, Wenzel K, Erdmann B, Krackhardt F, Posch MG, Osterziel KJ, Bublak A, Nägele H, Scheffold T, Dietz R, Chien KR, Spuler S, Fürst DO, Nürnberg P, Ozcelik C. Beyond the sarcomere: CSRP3 mutations cause hypertrophic cardiomyopathy.. Hum Mol Genet 2008 Sep 15;17(18):2753-65.
    doi: 10.1093/hmg/ddn160pubmed: 18505755google scholar: lookup
  48. Hirst J, King MS, Pryde KR. The production of reactive oxygen species by complex I.. Biochem Soc Trans 2008 Oct;36(Pt 5):976-80.
    pubmed: 18793173doi: 10.1042/bst0360976google scholar: lookup
  49. Abramov AY, Angelova PR. Cellular mechanisms of complex I-associated pathology.. Biochem Soc Trans 2019 Dec 20;47(6):1963-1969.
    doi: 10.1042/BST20191042pubmed: 31769488google scholar: lookup
  50. Reimann J, Kunz WS, Vielhaber S, Kappes-Horn K, Schröder R. Mitochondrial dysfunction in myofibrillar myopathy.. Neuropathol Appl Neurobiol 2003 Feb;29(1):45-51.
    doi: 10.1046/j.1365-2990.2003.00428.xpubmed: 12581339google scholar: lookup
  51. Janué A, Olivé M, Ferrer I. Oxidative stress in desminopathies and myotilinopathies: a link between oxidative damage and abnormal protein aggregation.. Brain Pathol 2007 Oct;17(4):377-88.
    doi: 10.1111/j.1750-3639.2007.00087.xpmc: PMC8095628pubmed: 17784878google scholar: lookup
  52. Arbogast S, Beuvin M, Fraysse B, Zhou H, Muntoni F, Ferreiro A. Oxidative stress in SEPN1-related myopathy: from pathophysiology to treatment.. Ann Neurol 2009 Jun;65(6):677-86.
    doi: 10.1002/ana.21644pubmed: 19557870google scholar: lookup
  53. Crawford RR, Prescott ET, Sylvester CF, Higdon AN, Shan J, Kilberg MS, Mungrue IN. Human CHAC1 Protein Degrades Glutathione, and mRNA Induction Is Regulated by the Transcription Factors ATF4 and ATF3 and a Bipartite ATF/CRE Regulatory Element.. J Biol Chem 2015 Jun 19;290(25):15878-15891.
    doi: 10.1074/jbc.M114.635144pmc: PMC4505494pubmed: 25931127google scholar: lookup
  54. Mungrue IN, Pagnon J, Kohannim O, Gargalovic PS, Lusis AJ. CHAC1/MGC4504 is a novel proapoptotic component of the unfolded protein response, downstream of the ATF4-ATF3-CHOP cascade.. J Immunol 2009 Jan 1;182(1):466-76.
    doi: 10.4049/jimmunol.182.1.466pmc: PMC2846782pubmed: 19109178google scholar: lookup
  55. Fernández-Verdejo R, Vanwynsberghe AM, Essaghir A, Demoulin JB, Hai T, Deldicque L, Francaux M. Activating transcription factor 3 attenuates chemokine and cytokine expression in mouse skeletal muscle after exercise and facilitates molecular adaptation to endurance training.. FASEB J 2017 Feb;31(2):840-851.
    doi: 10.1096/fj.201600987Rpubmed: 27856557google scholar: lookup
  56. Schwartz LM. Skeletal Muscles Do Not Undergo Apoptosis During Either Atrophy or Programmed Cell Death-Revisiting the Myonuclear Domain Hypothesis.. Front Physiol 2018;9:1887.
    doi: 10.3389/fphys.2018.01887pmc: PMC6356110pubmed: 30740060google scholar: lookup
  57. Steinberg SF. Oxidative stress and sarcomeric proteins.. Circ Res 2013 Jan 18;112(2):393-405.
    doi: 10.1161/CIRCRESAHA.111.300496pmc: PMC3595003pubmed: 23329794google scholar: lookup
  58. Delort F, Segard BD, Hakibilen C, Bourgois-Rocha F, Cabet E, Vicart P, Huang ME, Clary G, Lilienbaum A, Agbulut O, Batonnet-Pichon S. Alterations of redox dynamics and desmin post-translational modifications in skeletal muscle models of desminopathies.. Exp Cell Res 2019 Oct 15;383(2):111539.
    doi: 10.1016/j.yexcr.2019.111539pubmed: 31369751google scholar: lookup
  59. Gillies AR, Lieber RL. Structure and function of the skeletal muscle extracellular matrix.. Muscle Nerve 2011 Sep;44(3):318-31.
    doi: 10.1002/mus.22094pmc: PMC3177172pubmed: 21949456google scholar: lookup
  60. Boppart MD, Mahmassani ZS. Integrin signaling: linking mechanical stimulation to skeletal muscle hypertrophy.. Am J Physiol Cell Physiol 2019 Oct 1;317(4):C629-C641.
    doi: 10.1152/ajpcell.00009.2019pmc: PMC6850995pubmed: 31314586google scholar: lookup
  61. Vidal B, Serrano AL, Tjwa M, Suelves M, Ardite E, De Mori R, Baeza-Raja B, Martínez de Lagrán M, Lafuste P, Ruiz-Bonilla V, Jardí M, Gherardi R, Christov C, Dierssen M, Carmeliet P, Degen JL, Dewerchin M, Muñoz-Cánoves P. Fibrinogen drives dystrophic muscle fibrosis via a TGFbeta/alternative macrophage activation pathway.. Genes Dev 2008 Jul 1;22(13):1747-52.
    doi: 10.1101/gad.465908pmc: PMC2492661pubmed: 18593877google scholar: lookup
  62. Sparks SE, Quijano-Roy S, Harper A, Rutkowski A, Gordon E, Hoffman EP, Pegoraro E. Congenital muscular dystrophy overview. GeneReviews®[Internet] Seattle: University of Washington; 2012.
  63. Wallace GQ, McNally EM. Mechanisms of muscle degeneration, regeneration, and repair in the muscular dystrophies.. Annu Rev Physiol 2009;71:37-57.
    doi: 10.1146/annurev.physiol.010908.163216pubmed: 18808326google scholar: lookup
  64. Perkins AD, Ellis SJ, Asghari P, Shamsian A, Moore ED, Tanentzapf G. Integrin-mediated adhesion maintains sarcomeric integrity.. Dev Biol 2010 Feb 1;338(1):15-27.
    doi: 10.1016/j.ydbio.2009.10.034pubmed: 19879257google scholar: lookup
  65. Knöll R, Buyandelger B, Lab M. The sarcomeric Z-disc and Z-discopathies.. J Biomed Biotechnol 2011;2011:569628.
    pmc: PMC3199094pubmed: 22028589doi: 10.1155/2011/569628google scholar: lookup
  66. Mizuno Y, Thompson TG, Guyon JR, Lidov HG, Brosius M, Imamura M, Ozawa E, Watkins SC, Kunkel LM. Desmuslin, an intermediate filament protein that interacts with alpha -dystrobrevin and desmin.. Proc Natl Acad Sci U S A 2001 May 22;98(11):6156-61.
    doi: 10.1073/pnas.111153298pmc: PMC33438pubmed: 11353857google scholar: lookup
  67. García-Pelagio KP, Muriel J, O'Neill A, Desmond PF, Lovering RM, Lund L, Bond M, Bloch RJ. Myopathic changes in murine skeletal muscle lacking synemin.. Am J Physiol Cell Physiol 2015 Mar 15;308(6):C448-62.
    doi: 10.1152/ajpcell.00331.2014pmc: PMC4360028pubmed: 25567810google scholar: lookup
  68. Pashmforoush M, Pomiès P, Peterson KL, Kubalak S, Ross J Jr, Hefti A, Aebi U, Beckerle MC, Chien KR. Adult mice deficient in actinin-associated LIM-domain protein reveal a developmental pathway for right ventricular cardiomyopathy.. Nat Med 2001 May;7(5):591-7.
    doi: 10.1038/87920pubmed: 11329061google scholar: lookup
  69. Sanbe A, Osinska H, Saffitz JE, Glabe CG, Kayed R, Maloyan A, Robbins J. Desmin-related cardiomyopathy in transgenic mice: a cardiac amyloidosis.. Proc Natl Acad Sci U S A 2004 Jul 6;101(27):10132-6.
    doi: 10.1073/pnas.0401900101pmc: PMC454177pubmed: 15220483google scholar: lookup
  70. Kumarapeli AR, Horak KM, Glasford JW, Li J, Chen Q, Liu J, Zheng H, Wang X. A novel transgenic mouse model reveals deregulation of the ubiquitin-proteasome system in the heart by doxorubicin.. FASEB J 2005 Dec;19(14):2051-3.
    doi: 10.1096/fj.05-3973fjepubmed: 16188962google scholar: lookup
  71. Olivé M, van Leeuwen FW, Janué A, Moreno D, Torrejón-Escribano B, Ferrer I. Expression of mutant ubiquitin (UBB+1) and p62 in myotilinopathies and desminopathies.. Neuropathol Appl Neurobiol 2008 Feb;34(1):76-87.
    doi: 10.1111/j.1365-2990.2007.00864.xpubmed: 17931355google scholar: lookup
  72. Janué A, Odena MA, Oliveira E, Olivé M, Ferrer I. Desmin is oxidized and nitrated in affected muscles in myotilinopathies and desminopathies.. J Neuropathol Exp Neurol 2007 Aug;66(8):711-23.
    doi: 10.1097/nen.0b013e3181256b4cpubmed: 17882015google scholar: lookup
  73. Chávez Zobel AT, Loranger A, Marceau N, Thériault JR, Lambert H, Landry J. Distinct chaperone mechanisms can delay the formation of aggresomes by the myopathy-causing R120G alphaB-crystallin mutant.. Hum Mol Genet 2003 Jul 1;12(13):1609-20.
    doi: 10.1093/hmg/ddg173pubmed: 12812987google scholar: lookup
  74. Bova MP, Yaron O, Huang Q, Ding L, Haley DA, Stewart PL, Horwitz J. Mutation R120G in alphaB-crystallin, which is linked to a desmin-related myopathy, results in an irregular structure and defective chaperone-like function.. Proc Natl Acad Sci U S A 1999 May 25;96(11):6137-42.
    doi: 10.1073/pnas.96.11.6137pmc: PMC26848pubmed: 10339554google scholar: lookup
  75. Ghazalpour A, Bennett B, Petyuk VA, Orozco L, Hagopian R, Mungrue IN, Farber CR, Sinsheimer J, Kang HM, Furlotte N, Park CC, Wen PZ, Brewer H, Weitz K, Camp DG 2nd, Pan C, Yordanova R, Neuhaus I, Tilford C, Siemers N, Gargalovic P, Eskin E, Kirchgessner T, Smith DJ, Smith RD, Lusis AJ. Comparative analysis of proteome and transcriptome variation in mouse.. PLoS Genet 2011 Jun;7(6):e1001393.
    doi: 10.1371/journal.pgen.1001393pmc: PMC3111477pubmed: 21695224google scholar: lookup
  76. Gygi SP, Rochon Y, Franza BR, Aebersold R. Correlation between protein and mRNA abundance in yeast.. Mol Cell Biol 1999 Mar;19(3):1720-30.
    doi: 10.1128/MCB.19.3.1720pmc: PMC83965pubmed: 10022859google scholar: lookup
  77. Chen G, Gharib TG, Huang CC, Taylor JM, Misek DE, Kardia SL, Giordano TJ, Iannettoni MD, Orringer MB, Hanash SM, Beer DG. Discordant protein and mRNA expression in lung adenocarcinomas.. Mol Cell Proteomics 2002 Apr;1(4):304-13.
    doi: 10.1074/mcp.M200008-MCP200pubmed: 12096112google scholar: lookup
  78. Bathke J, Konzer A, Remes B, McIntosh M, Klug G. Comparative analyses of the variation of the transcriptome and proteome of Rhodobacter sphaeroides throughout growth.. BMC Genomics 2019 May 9;20(1):358.
    doi: 10.1186/s12864-019-5749-3pmc: PMC6509803pubmed: 31072330google scholar: lookup
  79. Haider S, Pal R. Integrated analysis of transcriptomic and proteomic data.. Curr Genomics 2013 Apr;14(2):91-110.
    doi: 10.2174/1389202911314020003pmc: PMC3637682pubmed: 24082820google scholar: lookup
  80. Freiberg JA, Le Breton Y, Tran BQ, Scott AJ, Harro JM, Ernst RK, Goo YA, Mongodin EF, Goodlett DR, McIver KS, Shirtliff ME. Global Analysis and Comparison of the Transcriptomes and Proteomes of Group A Streptococcus Biofilms.. mSystems 2016 Nov-Dec;1(6).
    doi: 10.1128/mSystems.00149-16pmc: PMC5141267pubmed: 27933318google scholar: lookup
  81. Zak R, Martin AF, Prior G, Rabinowitz M. Comparison of turnover of several myofibrillar proteins and critical evaluation of double isotope method.. J Biol Chem 1977 May 25;252(10):3430-5.
    pubmed: 863889
  82. Wang J, Shaner N, Mittal B, Zhou Q, Chen J, Sanger JM, Sanger JW. Dynamics of Z-band based proteins in developing skeletal muscle cells.. Cell Motil Cytoskeleton 2005 May;61(1):34-48.
    doi: 10.1002/cm.20063pmc: PMC1993831pubmed: 15810059google scholar: lookup
  83. Snow DH, Guy PS. Percutaneous needle muscle biopsy in the horse.. Equine Vet J 1976 Oct;8(4):150-5.
    doi: 10.1111/j.2042-3306.1976.tb03327.xpubmed: 976229google scholar: lookup
  84. Wiśniewski JR, Zougman A, Nagaraj N, Mann M. Universal sample preparation method for proteome analysis.. Nat Methods 2009 May;6(5):359-62.
    doi: 10.1038/nmeth.1322pubmed: 19377485google scholar: lookup
  85. Rappsilber J, Mann M, Ishihama Y. Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips.. Nat Protoc 2007;2(8):1896-906.
    doi: 10.1038/nprot.2007.261pubmed: 17703201google scholar: lookup
  86. Thompson A, Schäfer J, Kuhn K, Kienle S, Schwarz J, Schmidt G, Neumann T, Johnstone R, Mohammed AK, Hamon C. Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS.. Anal Chem 2003 Apr 15;75(8):1895-904.
    doi: 10.1021/ac0262560pubmed: 12713048google scholar: lookup
  87. McAlister GC, Huttlin EL, Haas W, Ting L, Jedrychowski MP, Rogers JC, Kuhn K, Pike I, Grothe RA, Blethrow JD, Gygi SP. Increasing the multiplexing capacity of TMTs using reporter ion isotopologues with isobaric masses.. Anal Chem 2012 Sep 4;84(17):7469-78.
    doi: 10.1021/ac301572tpmc: PMC3715028pubmed: 22880955google scholar: lookup
  88. Nesvizhskii AI, Keller A, Kolker E, Aebersold R. A statistical model for identifying proteins by tandem mass spectrometry.. Anal Chem 2003 Sep 1;75(17):4646-58.
    doi: 10.1021/ac0341261pubmed: 14632076google scholar: lookup
  89. Shadforth IP, Dunkley TP, Lilley KS, Bessant C. i-Tracker: for quantitative proteomics using iTRAQ.. BMC Genomics 2005 Oct 20;6:145.
    doi: 10.1186/1471-2164-6-145pmc: PMC1276793pubmed: 16242023google scholar: lookup
  90. Oberg AL, Mahoney DW, Eckel-Passow JE, Malone CJ, Wolfinger RD, Hill EG, Cooper LT, Onuma OK, Spiro C, Therneau TM, Bergen HR 3rd. Statistical analysis of relative labeled mass spectrometry data from complex samples using ANOVA.. J Proteome Res 2008 Jan;7(1):225-33.
    doi: 10.1021/pr700734fpmc: PMC2528956pubmed: 18173221google scholar: lookup
  91. Perez-Riverol Y, Csordas A, Bai J, Bernal-Llinares M, Hewapathirana S, Kundu DJ, Inuganti A, Griss J, Mayer G, Eisenacher M, Pérez E, Uszkoreit J, Pfeuffer J, Sachsenberg T, Yilmaz S, Tiwary S, Cox J, Audain E, Walzer M, Jarnuczak AF, Ternent T, Brazma A, Vizcaíno JA. The PRIDE database and related tools and resources in 2019: improving support for quantification data.. Nucleic Acids Res 2019 Jan 8;47(D1):D442-D450.
    doi: 10.1093/nar/gky1106pmc: PMC6323896pubmed: 30395289google scholar: lookup
  92. Andrews S. FastQC: a quality control tool for high throughput sequence data. Babraham Bioinformatics 2010.
  93. Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report.. Bioinformatics 2016 Oct 1;32(19):3047-8.
    doi: 10.1093/bioinformatics/btw354pmc: PMC5039924pubmed: 27312411google scholar: lookup
  94. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data.. Bioinformatics 2014 Aug 1;30(15):2114-20.
    doi: 10.1093/bioinformatics/btu170pmc: PMC4103590pubmed: 24695404google scholar: lookup
  95. Smeds L, Künstner A. ConDeTri--a content dependent read trimmer for Illumina data.. PLoS One 2011;6(10):e26314.
    pmc: PMC3198461pubmed: 22039460doi: 10.1371/journal.pone.0026314google scholar: lookup
  96. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2.. Nat Methods 2012 Mar 4;9(4):357-9.
    doi: 10.1038/nmeth.1923pmc: PMC3322381pubmed: 22388286google scholar: lookup
  97. Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq.. Bioinformatics 2009 May 1;25(9):1105-11.
    doi: 10.1093/bioinformatics/btp120pmc: PMC2672628pubmed: 19289445google scholar: lookup
  98. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R. The Sequence Alignment/Map format and SAMtools.. Bioinformatics 2009 Aug 15;25(16):2078-9.
    doi: 10.1093/bioinformatics/btp352pmc: PMC2723002pubmed: 19505943google scholar: lookup
  99. Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation.. Nat Biotechnol 2010 May;28(5):511-5.
    doi: 10.1038/nbt.1621pmc: PMC3146043pubmed: 20436464google scholar: lookup
  100. Anders S, Pyl PT, Huber W. HTSeq--a Python framework to work with high-throughput sequencing data.. Bioinformatics 2015 Jan 15;31(2):166-9.
    doi: 10.1093/bioinformatics/btu638pmc: PMC4287950pubmed: 25260700google scholar: lookup
  101. Robinson MD, Oshlack A. A scaling normalization method for differential expression analysis of RNA-seq data.. Genome Biol 2010;11(3):R25.
    doi: 10.1186/gb-2010-11-3-r25pmc: PMC2864565pubmed: 20196867google scholar: lookup
  102. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.. Bioinformatics 2010 Jan 1;26(1):139-40.
    doi: 10.1093/bioinformatics/btp616pmc: PMC2796818pubmed: 19910308google scholar: lookup
  103. Li H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data.. Bioinformatics 2011 Nov 1;27(21):2987-93.
    doi: 10.1093/bioinformatics/btr509pmc: PMC3198575pubmed: 21903627google scholar: lookup
  104. VanRaden PM. Efficient methods to compute genomic predictions.. J Dairy Sci 2008 Nov;91(11):4414-23.
    doi: 10.3168/jds.2007-0980pubmed: 18946147google scholar: lookup
  105. Carlson M. org. Hs.eg.db: Genome wide annotation for Human. Bioconductor R package version 3.8.2 [Internet]; 2019.
  106. Farries G, Bryan K, McGivney CL, McGettigan PA, Gough KF, Browne JA, MacHugh DE, Katz LM, Hill EW. Expression Quantitative Trait Loci in Equine Skeletal Muscle Reveals Heritable Variation in Metabolism and the Training Responsive Transcriptome.. Front Genet 2019;10:1215.
    doi: 10.3389/fgene.2019.01215pmc: PMC6902038pubmed: 31850069google scholar: lookup
  107. Farries G, Bryan K, McGivney CL, McGettigan PA, Gough KF, Browne JA, MacHugh DE, Katz LM, Hill EW. Identification of expression quantitative trait loci in the skeletal muscle of Thoroughbreds reveals heritable variation in expression of genes relevant to cofactor metabolism. bioRxiv 2019;1:713669.
  108. Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters.. OMICS 2012 May;16(5):284-7.
    doi: 10.1089/omi.2011.0118pmc: PMC3339379pubmed: 22455463google scholar: lookup
  109. Yu G, He QY. ReactomePA: an R/Bioconductor package for reactome pathway analysis and visualization.. Mol Biosyst 2016 Feb;12(2):477-9.
    doi: 10.1039/C5MB00663Epubmed: 26661513google scholar: lookup
  110. Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, Simonovic M, Doncheva NT, Morris JH, Bork P, Jensen LJ, Mering CV. 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-D613.
    doi: 10.1093/nar/gky1131pmc: PMC6323986pubmed: 30476243google scholar: lookup
  111. Law CW, Chen Y, Shi W, Smyth GK. voom: Precision weights unlock linear model analysis tools for RNA-seq read counts.. Genome Biol 2014 Feb 3;15(2):R29.
    doi: 10.1186/gb-2014-15-2-r29pmc: PMC4053721pubmed: 24485249google scholar: lookup
  112. Branson OE, Freitas MA. A multi-model statistical approach for proteomic spectral count quantitation.. J Proteomics 2016 Jul 20;144:23-32.
    doi: 10.1016/j.jprot.2016.05.032pmc: PMC4967010pubmed: 27260494google scholar: lookup
  113. Min EJ, Safo SE, Long Q. Penalized co-inertia analysis with applications to -omics data.. Bioinformatics 2019 Mar 15;35(6):1018-1025.
    doi: 10.1093/bioinformatics/bty726pmc: PMC6419918pubmed: 30165424google scholar: lookup
  114. Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes.. Nucleic Acids Res 2000 Jan 1;28(1):27-30.
    doi: 10.1093/nar/28.1.27pmc: PMC102409pubmed: 10592173google scholar: lookup
  115. Kanehisa M. Toward understanding the origin and evolution of cellular organisms.. Protein Sci 2019 Nov;28(11):1947-1951.
    doi: 10.1002/pro.3715pmc: PMC6798127pubmed: 31441146google scholar: lookup
  116. Tulloch LK, Perkins JD, Piercy RJ. Multiple immunofluorescence labelling enables simultaneous identification of all mature fibre types in a single equine skeletal muscle cryosection.. Equine Vet J 2011 Jul;43(4):500-3.
    doi: 10.1111/j.2042-3306.2010.00329.xpubmed: 21496090google scholar: lookup

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  3. Wei W, Zha C, Jiang A, Chao Z, Hou L, Liu H, Huang R, Wu W. A Combined Differential Proteome and Transcriptome Profiling of Fast- and Slow-Twitch Skeletal Muscle in Pigs.. Foods 2022 Sep 14;11(18).
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    doi: 10.7717/peerj.13218pubmed: 35378934google scholar: lookup
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    doi: 10.1111/evj.13574pubmed: 35288976google scholar: lookup
  6. Henry ML, Velez-Irizarry D, Pagan JD, Sordillo L, Gandy J, Valberg SJ. The Impact of N-Acetyl Cysteine and Coenzyme Q10 Supplementation on Skeletal Muscle Antioxidants and Proteome in Fit Thoroughbred Horses.. Antioxidants (Basel) 2021 Oct 30;10(11).
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