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Physiological genomics2018; 50(12); 1036-1050; doi: 10.1152/physiolgenomics.00044.2018

Proteome and transcriptome profiling of equine myofibrillar myopathy identifies diminished peroxiredoxin 6 and altered cysteine metabolic pathways.

Abstract: Equine myofibrillar myopathy (MFM) causes exertional muscle pain and is characterized by myofibrillar disarray and ectopic desmin aggregates of unknown origin. To investigate the pathophysiology of MFM, we compared resting and 3 h postexercise transcriptomes of gluteal muscle and the resting skeletal muscle proteome of MFM and control Arabian horses with RNA sequencing and isobaric tags for relative and absolute quantitation analyses. Three hours after exercise, 191 genes were identified as differentially expressed (DE) in MFM vs. control muscle with >1 log fold change (FC) in genes involved in sulfur compound/cysteine metabolism such as cystathionine-beta-synthase ( CBS, ↓4.51), a cysteine and neutral amino acid membrane transporter ( SLC7A10, ↓1.80 MFM), and a cationic transporter (SLC24A1, ↓1.11 MFM). In MFM vs. control at rest, 284 genes were DE with >1 log FC in pathways for structure morphogenesis, fiber organization, tissue development, and cell differentiation including > 1 log FC in cardiac alpha actin ( ACTC1 ↑2.5 MFM), cytoskeletal desmoplakin ( DSP ↑2.4 MFM), and basement membrane usherin ( USH2A ↓2.9 MFM). Proteome analysis revealed significantly lower antioxidant peroxiredoxin 6 content (PRDX6, ↓4.14 log FC MFM), higher fatty acid transport enzyme carnitine palmitoyl transferase (CPT1B, ↑3.49 MFM), and lower sarcomere protein tropomyosin (TPM2, ↓3.24 MFM) in MFM vs. control muscle at rest. We propose that in MFM horses, altered cysteine metabolism and a deficiency of cysteine-containing antioxidants combined with a high capacity to oxidize fatty acids and generate ROS during aerobic exercise causes chronic oxidation and aggregation of key proteins such as desmin.
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Publication Date: 2018-10-05 PubMed ID: 30289745PubMed Central: PMC6337024DOI: 10.1152/physiolgenomics.00044.2018Google Scholar: Lookup
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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.

The research article discusses a study carried out to understand the pathophysiology of Equine Myofibrillar Myopathy (MFM), a muscle condition in horses, by profiling the proteome and transcriptome in the rest and post-exercise phases. The study revealed protein and gene alterations that suggest changes in cysteine metabolism and problematic oxidation in MFM horses.

Research Methods

  • The study was conducted on Arabic horses, both control and those afflicted with MFM. This condition is characterised by disorganised units of muscle fibres (myofibrils) and misplaced, aggregated Desmin (a protein).
  • The researchers compared both resting and post-exercise (3 hours) transcriptomes of the gluteal muscle as well as the resting proteome of skeletal muscle. Transcriptome refers to all the gene expression information while proteome refers to the entire set of proteins expressed.
  • To do this, they used RNA sequencing and a process known as isobaric tags for relative and absolute quantitation analyses.

Findings

  • Three hours after exercise, 191 genes were found to be differentially expressed (changed in a significant way) in MFM horses as compared to control ones. This included a notable change (>1 log fold) in genes involved in sulfur compound/cysteine metabolism.
  • Alongside the metabolic changes, there was a decrease in the levels of CBS (an enzyme involved in the creation of cysteine, a type of amino acid), SLC7A10 (amino acid transporter), and SLC24A1 (ionic transporter).
  • At resting stage, 284 genes showed >1 log fold change linked to the development and differentiation of cells, fibre organisation, and structural development. There were changes in the levels of ACTC1, DSP, and USH2A that play a role in the mentioned pathways.
  • The proteome analysis identified significantly lower levels of the antioxidant peroxiredoxin 6 (PRDX6), higher levels of CPT1B (a fatty acid transporter) and lower levels of TPM2 (a muscle protein) in MFM horses when compared to controls.

Conclusion

  • The study concludes that in MFM horses, an alteration in cysteine metabolism, the deficiency of cysteine-containing antioxidants coupled with a high capacity to oxidize fatty acids, leads to chronic protein oxidation and aggregation, specifically the protein desmin.
  • These observations could potentially contribute to the myofibrillar disarray and desmin aggregation observed in MFM.

Cite This Article

APA
Valberg SJ, Perumbakkam S, McKenzie EC, Finno CJ. (2018). Proteome and transcriptome profiling of equine myofibrillar myopathy identifies diminished peroxiredoxin 6 and altered cysteine metabolic pathways. Physiol Genomics, 50(12), 1036-1050. https://doi.org/10.1152/physiolgenomics.00044.2018

Publication

Physiological genomics
ISSN: 1531-2267
NlmUniqueID: 9815683
Country: United States
Language: English
Volume: 50
Issue: 12
Pages: 1036-1050

Researcher Affiliations

Valberg, Stephanie J
  • McPhail Equine Performance Center, Department of Large Animal Clinical Sciences, Michigan State University, East Lansing, Michigan.
  • Department of Population Sciences, University of Minnesota , St. Paul, Minnesota.
Perumbakkam, Sudeep
  • Department of Large Animal Clinical Sciences, Michigan State University , East Lansing, Michigan.
McKenzie, Erica C
  • Department of Clinical Sciences, Carlson College of Veterinary Medicine, Oregon State University , Corvallis, Oregon.
Finno, Carrie J
  • Department of Population Health and Reproduction, University of California Davis , Davis, California.

MeSH Terms

  • Animals
  • Antioxidants / metabolism
  • Basement Membrane / metabolism
  • Cell Differentiation / physiology
  • Cysteine / metabolism
  • Fatty Acids / metabolism
  • Female
  • Gene Expression Profiling / methods
  • Horses
  • Male
  • Metabolic Networks and Pathways / physiology
  • Muscle Proteins / metabolism
  • Muscle, Skeletal / metabolism
  • Myopathies, Structural, Congenital / metabolism
  • Peroxiredoxin VI / metabolism
  • Physical Conditioning, Animal / physiology
  • Proteome / metabolism
  • Reactive Oxygen Species / metabolism

Grant Funding

  • K01 OD015134 / NIH HHS
  • L40 TR001136 / NCATS NIH HHS

References

This article includes 72 references
  1. Andrew S.n. FastQC: a quality control tool for high throughput sequence data.. www.Citeulike.org [April 10, 2017].
  2. Apweiler R, Bairoch A, Wu CH, Barker WC, Boeckmann B, Ferro S, Gasteiger E, Huang H, Lopez R, Magrane M, Martin MJ, Natale DA, O'Donovan C, Redaschi N, Yeh LS. UniProt: the Universal Protein knowledgebase.. Nucleic Acids Res 2004 Jan 1;32(Database issue):D115-9.
    doi: 10.1093/nar/gkh131pmc: PMC308865pubmed: 14681372google scholar: lookup
  3. 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
  4. Barrey E, Jayr L, Mucher E, Gospodnetic S, Joly F, Benech P, Alibert O, Gidrol X, Mata X, Vaiman A, Guérin G. Transcriptome analysis of muscle in horses suffering from recurrent exertional rhabdomyolysis revealed energetic pathway alterations and disruption in the cytosolic calcium regulation.. Anim Genet 2012 Jun;43(3):271-81.
    doi: 10.1111/j.1365-2052.2011.02246.xpubmed: 22486498google scholar: lookup
  5. Barrey E, Mucher E, Jeansoule N, Larcher T, Guigand L, Herszberg B, Chaffaux S, Guérin G, Mata X, Benech P, Canale M, Alibert O, Maltere P, Gidrol X. Gene expression profiling in equine polysaccharide storage myopathy revealed inflammation, glycogenesis inhibition, hypoxia and mitochondrial dysfunctions.. BMC Vet Res 2009 Aug 7;5:29.
    doi: 10.1186/1746-6148-5-29pmc: PMC2741442pubmed: 19664222google scholar: lookup
  6. Bindea G, Galon J, Mlecnik B. CluePedia Cytoscape plugin: pathway insights using integrated experimental and in silico data.. Bioinformatics 2013 Mar 1;29(5):661-3.
    doi: 10.1093/bioinformatics/btt019pmc: PMC3582273pubmed: 23325622google scholar: lookup
  7. Bryan K, McGivney BA, Farries G, McGettigan PA, McGivney CL, Gough KF, MacHugh DE, Katz LM, Hill EW. Equine skeletal muscle adaptations to exercise and training: evidence of differential regulation of autophagosomal and mitochondrial components.. BMC Genomics 2017 Aug 9;18(1):595.
    doi: 10.1186/s12864-017-4007-9pmc: PMC5551008pubmed: 28793853google scholar: lookup
  8. Cabet E, Batonnet-Pichon S, Delort F, Gausserès B, Vicart P, Lilienbaum A. Antioxidant Treatment and Induction of Autophagy Cooperate to Reduce Desmin Aggregation in a Cellular Model of Desminopathy.. PLoS One 2015;10(9):e0137009.
    doi: 10.1371/journal.pone.0137009pmc: PMC4557996pubmed: 26333167google scholar: lookup
  9. Castets P, Lescure A, Guicheney P, Allamand V. Selenoprotein N in skeletal muscle: from diseases to function.. J Mol Med (Berl) 2012 Oct;90(10):1095-107.
    doi: 10.1007/s00109-012-0896-xpubmed: 22527882google scholar: lookup
  10. Cingolani P, Patel VM, Coon M, Nguyen T, Land SJ, Ruden DM, Lu X. Using Drosophila melanogaster as a Model for Genotoxic Chemical Mutational Studies with a New Program, SnpSift.. Front Genet 2012;3:35.
    doi: 10.3389/fgene.2012.00035pmc: PMC3304048pubmed: 22435069google scholar: lookup
  11. Cox J, Neuhauser N, Michalski A, Scheltema RA, Olsen JV, Mann M. Andromeda: a peptide search engine integrated into the MaxQuant environment.. J Proteome Res 2011 Apr 1;10(4):1794-805.
    doi: 10.1021/pr101065jpubmed: 21254760google scholar: lookup
  12. Craig R, Beavis RC. TANDEM: matching proteins with tandem mass spectra.. Bioinformatics 2004 Jun 12;20(9):1466-7.
    doi: 10.1093/bioinformatics/bth092pubmed: 14976030google scholar: lookup
  13. Cumming WJK, Fulthorpe J, Hudgson P, Mahon M. Color Atlas of Muscle Pathology.. London: Mosby-Wolfe, 1994.
  14. Danielson SR, Held JM, Oo M, Riley R, Gibson BW, Andersen JK. Quantitative mapping of reversible mitochondrial Complex I cysteine oxidation in a Parkinson disease mouse model.. J Biol Chem 2011 Mar 4;286(9):7601-8.
    doi: 10.1074/jbc.M110.190108pmc: PMC3045014pubmed: 21196577google scholar: lookup
  15. Diament BJ, Noble WS. Faster SEQUEST searching for peptide identification from tandem mass spectra.. J Proteome Res 2011 Sep 2;10(9):3871-9.
    doi: 10.1021/pr101196npmc: PMC3166376pubmed: 21761931google scholar: lookup
  16. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR. STAR: ultrafast universal RNA-seq aligner.. Bioinformatics 2013 Jan 1;29(1):15-21.
    doi: 10.1093/bioinformatics/bts635pmc: PMC3530905pubmed: 23104886google scholar: lookup
  17. Dorfer V, Pichler P, Stranzl T, Stadlmann J, Taus T, Winkler S, Mechtler K. MS Amanda, a universal identification algorithm optimized for high accuracy tandem mass spectra.. J Proteome Res 2014 Aug 1;13(8):3679-84.
    doi: 10.1021/pr500202epmc: PMC4119474pubmed: 24909410google scholar: lookup
  18. Edgar R, Domrachev M, Lash AE. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository.. Nucleic Acids Res 2002 Jan 1;30(1):207-10.
    pmc: PMC99122pubmed: 11752295doi: 10.1093/nar/30.1.207google scholar: lookup
  19. Elias JE, Gygi SP. Target-decoy search strategy for mass spectrometry-based proteomics.. Methods Mol Biol 2010;604:55-71.
    doi: 10.1007/978-1-60761-444-9_5pmc: PMC2922680pubmed: 20013364google scholar: lookup
  20. Eng JK, Jahan TA, Hoopmann MR. Comet: an open-source MS/MS sequence database search tool.. Proteomics 2013 Jan;13(1):22-4.
    doi: 10.1002/pmic.201200439pubmed: 23148064google scholar: lookup
  21. Feldkirchner S, Schessl J, Müller S, Schoser B, Hanisch FG. Patient-specific protein aggregates in myofibrillar myopathies: laser microdissection and differential proteomics for identification of plaque components.. Proteomics 2012 Dec;12(23-24):3598-609.
    doi: 10.1002/pmic.201100559pubmed: 23044792google scholar: lookup
  22. Ferreiro A, Ceuterick-de Groote C, Marks JJ, Goemans N, Schreiber G, Hanefeld F, Fardeau M, Martin JJ, Goebel HH, Richard P, Guicheney P, Bönnemann CG. Desmin-related myopathy with Mallory body-like inclusions is caused by mutations of the selenoprotein N gene.. Ann Neurol 2004 May;55(5):676-86.
    doi: 10.1002/ana.20077pubmed: 15122708google scholar: lookup
  23. Finno CJ, Bordbari MH, Valberg SJ, Lee D, Herron J, Hines K, Monsour T, Scott E, Bannasch DL, Mickelson J, Xu L. Transcriptome profiling of equine vitamin E deficient neuroaxonal dystrophy identifies upregulation of liver X receptor target genes.. Free Radic Biol Med 2016 Dec;101:261-271.
    doi: 10.1016/j.freeradbiomed.2016.10.009pmc: PMC5154892pubmed: 27751910google scholar: lookup
  24. Fisher AB. Peroxiredoxin 6: a bifunctional enzyme with glutathione peroxidase and phospholipase A₂ activities.. Antioxid Redox Signal 2011 Aug 1;15(3):831-44.
    doi: 10.1089/ars.2010.3412pmc: PMC3125547pubmed: 20919932google scholar: lookup
  25. Fuller HR, Graham LC, Llavero Hurtado M, Wishart TM. Understanding the molecular consequences of inherited muscular dystrophies: advancements through proteomic experimentation.. Expert Rev Proteomics 2016 Jul;13(7):659-71.
    doi: 10.1080/14789450.2016.1202768pubmed: 27329572google scholar: lookup
  26. Geer LY, Markey SP, Kowalak JA, Wagner L, Xu M, Maynard DM, Yang X, Shi W, Bryant SH. Open mass spectrometry search algorithm.. J Proteome Res 2004 Sep-Oct;3(5):958-64.
    doi: 10.1021/pr0499491pubmed: 15473683google scholar: lookup
  27. Giles NM, Watts AB, Giles GI, Fry FH, Littlechild JA, Jacob C. Metal and redox modulation of cysteine protein function.. Chem Biol 2003 Aug;10(8):677-93.
    doi: 10.1016/S1074-5521(03)00174-1pubmed: 12954327google scholar: lookup
  28. Gonorazky H, Liang M, Cummings B, Lek M, Micallef J, Hawkins C, Basran R, Cohn R, Wilson MD, MacArthur D, Marshall CR, Ray PN, Dowling JJ. RNAseq analysis for the diagnosis of muscular dystrophy.. Ann Clin Transl Neurol 2016 Jan;3(1):55-60.
    doi: 10.1002/acn3.267pmc: PMC4704476pubmed: 26783550google scholar: lookup
  29. Griffin JL, Des Rosiers C. Applications of metabolomics and proteomics to the mdx mouse model of Duchenne muscular dystrophy: lessons from downstream of the transcriptome.. Genome Med 2009 Mar 25;1(3):32.
    doi: 10.1186/gm32pmc: PMC2664943pubmed: 19341503google scholar: lookup
  30. Hakimov HA, Walters S, Wright TC, Meidinger RG, Verschoor CP, Gadish M, Chiu DK, Strömvik MV, Forsberg CW, Golovan SP. Application of iTRAQ to catalogue the skeletal muscle proteome in pigs and assessment of effects of gender and diet dephytinization.. Proteomics 2009 Aug;9(16):4000-16.
    doi: 10.1002/pmic.200900049pubmed: 19701905google scholar: lookup
  31. Heusch P, Canton M, Aker S, van de Sand A, Konietzka I, Rassaf T, Menazza S, Brodde OE, Di Lisa F, Heusch G, Schulz R. The contribution of reactive oxygen species and p38 mitogen-activated protein kinase to myofilament oxidation and progression of heart failure in rabbits.. Br J Pharmacol 2010 Jul;160(6):1408-16.
    doi: 10.1111/j.1476-5381.2010.00793.xpmc: PMC2938812pubmed: 20590631google scholar: lookup
  32. 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.xpubmed: 17784878google scholar: lookup
  33. Juo LY, Liao WC, Shih YL, Yang BY, Liu AB, Yan YT. HSPB7 interacts with dimerized FLNC and its absence results in progressive myopathy in skeletal muscles.. J Cell Sci 2016 Apr 15;129(8):1661-70.
    doi: 10.1242/jcs.179887pmc: PMC4852768pubmed: 26929074google scholar: lookup
  34. Kim S, Pevzner PA. MS-GF+ makes progress towards a universal database search tool for proteomics.. Nat Commun 2014 Oct 31;5:5277.
    doi: 10.1038/ncomms6277pmc: PMC5036525pubmed: 25358478google scholar: lookup
  35. Knöll R, Buyandelger B, Lab M. The sarcomeric Z-disc and Z-discopathies.. J Biomed Biotechnol 2011;2011:569628.
    doi: 10.1155/2011/569628pmc: PMC3199094pubmed: 22028589google scholar: lookup
  36. Kramer PA, Darley-Usmar VM. The emerging theme of redox bioenergetics in health and disease.. Biomed J 2015 Jul-Aug;38(4):294-300.
    doi: 10.4103/2319-4170.155591pubmed: 25900929google scholar: lookup
  37. Kramer PA, Duan J, Qian WJ, Marcinek DJ. The Measurement of Reversible Redox Dependent Post-translational Modifications and Their Regulation of Mitochondrial and Skeletal Muscle Function.. Front Physiol 2015;6:347.
    doi: 10.3389/fphys.2015.00347pmc: PMC4658434pubmed: 26635632google scholar: lookup
  38. Leung CL, Green KJ, Liem RK. Plakins: a family of versatile cytolinker proteins.. Trends Cell Biol 2002 Jan;12(1):37-45.
    doi: 10.1016/S0962-8924(01)02180-8pubmed: 11854008google scholar: lookup
  39. 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
  40. Lin-Moshier Y, Sebastian PJ, Higgins L, Sampson ND, Hewitt JE, Marchant JS. Re-evaluation of the role of calcium homeostasis endoplasmic reticulum protein (CHERP) in cellular calcium signaling.. J Biol Chem 2013 Jan 4;288(1):355-67.
    doi: 10.1074/jbc.M112.405761pmc: PMC3537033pubmed: 23148228google scholar: lookup
  41. 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
  42. McCarthy DJ, Chen Y, Smyth GK. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation.. Nucleic Acids Res 2012 May;40(10):4288-97.
    doi: 10.1093/nar/gks042pmc: PMC3378882pubmed: 22287627google scholar: lookup
  43. McDonagh B, Sakellariou GK, Smith NT, Brownridge P, Jackson MJ. Differential cysteine labeling and global label-free proteomics reveals an altered metabolic state in skeletal muscle aging.. J Proteome Res 2014 Nov 7;13(11):5008-21.
    doi: 10.1021/pr5006394pmc: PMC4227305pubmed: 25181601google scholar: lookup
  44. McGivney BA, Eivers SS, MacHugh DE, MacLeod JN, O'Gorman GM, Park SD, Katz LM, Hill EW. Transcriptional adaptations following exercise in thoroughbred horse skeletal muscle highlights molecular mechanisms that lead to muscle hypertrophy.. BMC Genomics 2009 Dec 30;10:638.
    doi: 10.1186/1471-2164-10-638pmc: PMC2812474pubmed: 20042072google scholar: lookup
  45. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.. Genome Res 2010 Sep;20(9):1297-303.
    doi: 10.1101/gr.107524.110pmc: PMC2928508pubmed: 20644199google scholar: lookup
  46. McKenzie EC, Eyrich LV, Payton ME, Valberg SJ. Clinical, histopathological and metabolic responses following exercise in Arabian horses with a history of exertional rhabdomyolysis.. Vet J 2016 Oct;216:196-201.
    doi: 10.1016/j.tvjl.2016.08.011pubmed: 27687952google scholar: lookup
  47. Narasimhan V, Danecek P, Scally A, Xue Y, Tyler-Smith C, Durbin R. BCFtools/RoH: a hidden Markov model approach for detecting autozygosity from next-generation sequencing data.. Bioinformatics 2016 Jun 1;32(11):1749-51.
    doi: 10.1093/bioinformatics/btw044pmc: PMC4892413pubmed: 26826718google scholar: lookup
  48. Newton BW, Russell WK, Russell DH, Ramaiah SK, Jayaraman A. Liver proteome analysis in a rodent model of alcoholic steatosis.. J Proteome Res 2009 Apr;8(4):1663-71.
    doi: 10.1021/pr800905wpmc: PMC2888666pubmed: 19714808google scholar: lookup
  49. Ouyang H, Wang Z, Chen X, Yu J, Li Z, Nie Q. Proteomic Analysis of Chicken Skeletal Muscle during Embryonic Development.. Front Physiol 2017;8:281.
    doi: 10.3389/fphys.2017.00281pmc: PMC5420592pubmed: 28533755google scholar: lookup
  50. Rivero JL, Serrano AL, Henckel P, Agüera E. Muscle fiber type composition and fiber size in successfully and unsuccessfully endurance-raced horses.. J Appl Physiol (1985) 1993 Oct;75(4):1758-66.
    doi: 10.1152/jappl.1993.75.4.1758pubmed: 8282629google scholar: lookup
  51. Roberts TC, Johansson HJ, McClorey G, Godfrey C, Blomberg KE, Coursindel T, Gait MJ, Smith CI, Lehtiö J, El Andaloussi S, Wood MJ. Multi-level omics analysis in a murine model of dystrophin loss and therapeutic restoration.. Hum Mol Genet 2015 Dec 1;24(23):6756-68.
    doi: 10.1093/hmg/ddv381pmc: PMC4634378pubmed: 26385637google scholar: lookup
  52. 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
  53. Ropka-Molik K, Stefaniuk-Szmukier M, Z Ukowski K, Piórkowska K, Bugno-Poniewierska M. Exercise-induced modification of the skeletal muscle transcriptome in Arabian horses.. Physiol Genomics 2017 Jun 1;49(6):318-326.
    doi: 10.1152/physiolgenomics.00130.2016pubmed: 28455310google scholar: lookup
  54. 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.xpubmed: 19563540google scholar: lookup
  55. Segard BD, Delort F, Bailleux V, Simon S, Leccia E, Gausseres B, Briki F, Vicart P, Batonnet-Pichon S. N-acetyl-L-cysteine prevents stress-induced desmin aggregation in cellular models of desminopathy.. PLoS One 2013;8(10):e76361.
    doi: 10.1371/journal.pone.0076361pmc: PMC3788106pubmed: 24098483google scholar: lookup
  56. Sela I, Milman Krentsis I, Shlomai Z, Sadeh M, Dabby R, Argov Z, Ben-Bassat H, Mitrani-Rosenbaum S. The proteomic profile of hereditary inclusion body myopathy.. PLoS One 2011 Jan 31;6(1):e16334.
    doi: 10.1371/journal.pone.0016334pmc: PMC3031555pubmed: 21305017google scholar: lookup
  57. Selcen D, Carpén O. The Z-disk diseases.. Adv Exp Med Biol 2008;642:116-30.
    doi: 10.1007/978-0-387-84847-1_10pubmed: 19181098google scholar: lookup
  58. Shteynberg D, Nesvizhskii AI, Moritz RL, Deutsch EW. Combining results of multiple search engines in proteomics.. Mol Cell Proteomics 2013 Sep;12(9):2383-93.
    doi: 10.1074/mcp.R113.027797pmc: PMC3769318pubmed: 23720762google scholar: lookup
  59. Tabb DL, Fernando CG, Chambers MC. MyriMatch: highly accurate tandem mass spectral peptide identification by multivariate hypergeometric analysis.. J Proteome Res 2007 Feb;6(2):654-61.
    doi: 10.1021/pr0604054pmc: PMC2525619pubmed: 17269722google scholar: lookup
  60. Thomas PD, Campbell MJ, Kejariwal A, Mi H, Karlak B, Daverman R, Diemer K, Muruganujan A, Narechania A. PANTHER: a library of protein families and subfamilies indexed by function.. Genome Res 2003 Sep;13(9):2129-41.
    doi: 10.1101/gr.772403pmc: PMC403709pubmed: 12952881google scholar: lookup
  61. Thomas PD, Kejariwal A, Campbell MJ, Mi H, Diemer K, Guo N, Ladunga I, Ulitsky-Lazareva B, Muruganujan A, Rabkin S, Vandergriff JA, Doremieux O. PANTHER: a browsable database of gene products organized by biological function, using curated protein family and subfamily classification.. Nucleic Acids Res 2003 Jan 1;31(1):334-41.
    doi: 10.1093/nar/gkg115pmc: PMC165562pubmed: 12520017google scholar: lookup
  62. Tryon RC, Penedo MC, McCue ME, Valberg SJ, Mickelson JR, Famula TR, Wagner ML, Jackson M, Hamilton MJ, Nooteboom S, Bannasch DL. Evaluation of allele frequencies of inherited disease genes in subgroups of American Quarter Horses.. J Am Vet Med Assoc 2009 Jan 1;234(1):120-5.
    doi: 10.2460/javma.234.1.120pubmed: 19119976google scholar: lookup
  63. Tyanova S, Temu T, Sinitcyn P, Carlson A, Hein MY, Geiger T, Mann M, Cox J. The Perseus computational platform for comprehensive analysis of (prote)omics data.. Nat Methods 2016 Sep;13(9):731-40.
    doi: 10.1038/nmeth.3901pubmed: 27348712google scholar: lookup
  64. 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
  65. 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
  66. Vaudel M, Barsnes H, Berven FS, Sickmann A, Martens L. SearchGUI: An open-source graphical user interface for simultaneous OMSSA and X!Tandem searches.. Proteomics 2011 Mar;11(5):996-9.
    doi: 10.1002/pmic.201000595pubmed: 21337703google scholar: lookup
  67. Vizcaíno JA, Csordas A, Del-Toro N, Dianes JA, Griss J, Lavidas I, Mayer G, Perez-Riverol Y, Reisinger F, Ternent T, Xu QW, Wang R, Hermjakob H. 2016 update of the PRIDE database and its related tools.. Nucleic Acids Res 2016 Dec 15;44(22):11033.
    doi: 10.1093/nar/gkw880pmc: PMC5159556pubmed: 27683222google scholar: lookup
  68. Waddell JN, Zhang P, Wen Y, Gupta SK, Yevtodiyenko A, Schmidt JV, Bidwell CA, Kumar A, Kuang S. Dlk1 is necessary for proper skeletal muscle development and regeneration.. PLoS One 2010 Nov 29;5(11):e15055.
    doi: 10.1371/journal.pone.0015055pmc: PMC2993959pubmed: 21124733google scholar: lookup
  69. Wilberger MS, McKenzie EC, Payton ME, Rigas JD, Valberg SJ. Prevalence of exertional rhabdomyolysis in endurance horses in the Pacific Northwestern United States.. Equine Vet J 2015 Mar;47(2):165-70.
    doi: 10.1111/evj.12255pubmed: 24579562google scholar: lookup
  70. Yang F, Shen Y, Camp DG 2nd, Smith RD. High-pH reversed-phase chromatography with fraction concatenation for 2D proteomic analysis.. Expert Rev Proteomics 2012 Apr;9(2):129-34.
    doi: 10.1586/epr.12.15pmc: PMC3337716pubmed: 22462785google scholar: lookup
  71. Zhang L, Yang Z, Liu Y. GADD45 proteins: roles in cellular senescence and tumor development.. Exp Biol Med (Maywood) 2014 Jul;239(7):773-778.
    doi: 10.1177/1535370214531879pubmed: 24872428google scholar: lookup
  72. Zhang S, Zhou R, Zhao H, Korpelainen H, Li C. iTRAQ-based quantitative proteomic analysis gives insight into sexually different metabolic processes of poplars under nitrogen and phosphorus deficiencies.. Proteomics 2016 Feb;16(4):614-28.
    doi: 10.1002/pmic.201500197pubmed: 26698923google scholar: lookup

Citations

This article has been cited 11 times.
  1. Dickson ZW, Golding GB. Low Complexity Regions in Mammalian Proteins are Associated with Low Protein Abundance and High Transcript Abundance. Mol Biol Evol 2022 May 3;39(5).
    doi: 10.1093/molbev/msac087pubmed: 35482425google scholar: lookup
  2. Valberg SJ, Henry ML, Herrick KL, Velez-Irizarry D, Finno CJ, Petersen JL. Absence of myofibrillar myopathy in Quarter Horses with a histopathological diagnosis of type 2 polysaccharide storage myopathy and lack of association with commercial genetic tests. Equine Vet J 2023 Mar;55(2):230-238.
    doi: 10.1111/evj.13574pubmed: 35288976google scholar: lookup
  3. Autry JM, Svensson B, Carlson SF, Chen Z, Cornea RL, Thomas DD, Valberg SJ. Sarcoplasmic Reticulum from Horse Gluteal Muscle Is Poised for Enhanced Calcium Transport. Vet Sci 2021 Nov 23;8(12).
    doi: 10.3390/vetsci8120289pubmed: 34941816google scholar: lookup
  4. Zhou L, Zhang C, Yang X, Liu L, Hu J, Hou Y, Tao H, Sugimura H, Chen Z, Wang L, Chen K. Melatonin inhibits lipid accumulation to repress prostate cancer progression by mediating the epigenetic modification of CES1. Clin Transl Med 2021 Jun;11(6):e449.
    doi: 10.1002/ctm2.449pubmed: 34185414google scholar: lookup
  5. Williams ZJ, Velez-Irizarry D, Gardner K, Valberg SJ. 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 2021 Jun 11;22(1):438.
    doi: 10.1186/s12864-021-07758-0pubmed: 34112090google scholar: lookup
  6. Aldrich K, Velez-Irizarry D, Fenger C, Schott M, Valberg SJ. Pathways of calcium regulation, electron transport, and mitochondrial protein translation are molecular signatures of susceptibility to recurrent exertional rhabdomyolysis in Thoroughbred racehorses. PLoS One 2021;16(2):e0244556.
    doi: 10.1371/journal.pone.0244556pubmed: 33566847google scholar: lookup
  7. Autry JM, Karim CB, Perumbakkam S, Finno CJ, McKenzie EC, Thomas DD, Valberg SJ. Sarcolipin Exhibits Abundant RNA Transcription and Minimal Protein Expression in Horse Gluteal Muscle. Vet Sci 2020 Nov 13;7(4).
    doi: 10.3390/vetsci7040178pubmed: 33202832google scholar: lookup
  8. Autry JM, Karim CB, Cocco M, Carlson SF, Thomas DD, Valberg SJ. Purification of sarcoplasmic reticulum vesicles from horse gluteal muscle. Anal Biochem 2020 Dec 1;610:113965.
    doi: 10.1016/j.ab.2020.113965pubmed: 32956693google scholar: lookup
  9. Gonzalez ML, Jacobs RD, Ely KM, Johnson SE. Dietary tributyrin supplementation and submaximal exercise promote activation of equine satellite cells. J Anim Sci 2019 Dec 17;97(12):4951-4956.
    doi: 10.1093/jas/skz330pubmed: 31630180google scholar: lookup
  10. Reemtsma FP, Giers J, Horstmann S, Stoeckle SD, Gehlen H. Concentration Changes in Plasma Amino Acids and Their Metabolites in Eventing Horses During Cross-Country Competitions. Animals (Basel) 2025 Jun 22;15(13).
    doi: 10.3390/ani15131840pubmed: 40646739google scholar: lookup
  11. Kruse CJ, Dieu M, Renaud B, François AC, Stern D, Demazy C, Burteau S, Boemer F, Art T, Renard P, Votion DM. New Pathophysiological Insights from Serum Proteome Profiling in Equine Atypical Myopathy. ACS Omega 2024 Feb 13;9(6):6505-6526.
    doi: 10.1021/acsomega.3c06647pubmed: 38371826google scholar: lookup
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