Analyze Diet
Genes2019; 10(10); 745; doi: 10.3390/genes10100745

Differential Gene Expression in Articular Cartilage and Subchondral Bone of Neonatal and Adult Horses.

Abstract: Skeletogenesis is complex and incompletely understood. Derangement of this process likely underlies developmental skeletal pathologies. Examination of tissue-specific gene expression may help elucidate novel skeletal developmental pathways that could contribute to disease risk. Our aim was to identify and functionally annotate differentially expressed genes in equine neonatal and adult articular cartilage (AC) and subchondral bone (SCB). RNA was sequenced from healthy AC and SCB from the fetlock, hock, and stifle joints of 6 foals (≤4 weeks of age) and six adults (8-12 years of age). There was distinct clustering by age and tissue type. After differential expression analysis, functional annotation and pathway analysis were performed using PANTHER and Reactome. Approximately 1115 and 3574 genes were differentially expressed between age groups in AC and SCB, respectively, falling within dozens of overrepresented gene ontology terms and enriched pathways reflecting a state of growth, high metabolic activity, and tissue turnover in the foals. Enriched pathways were dominated by those related to extracellular matrix organization and turnover, and cell cycle and signal transduction. Additionally, we identified enriched pathways related to neural development and neurotransmission in AC and innate immunity in SCB. These represent novel potential mechanisms for disease that can be explored in future work.
Publication Date: 2019-09-25 PubMed ID: 31557843PubMed Central: PMC6826356DOI: 10.3390/genes10100745Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
  • Comparative Study
  • Journal Article
  • Research Support
  • Non-U.S. Gov't
  • Research Support
  • U.S. Gov't
  • Non-P.H.S.

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 aimed to investigate the differences in gene expression in the cartilage and bone of newborn and adult horses, and how these differences could potentially be related to developmental skeletal diseases.

Research Methodology

  • The researchers extracted RNA from healthy articular cartilage (AC) and subchondral bone (SCB) harvested from the fetlock, hock, and stifle joints of six foals (newborn horses ≤4 weeks of age) and six adult horses (8-12 years of age).
  • This extracted RNA was sequenced to identify the range of genes expressed in each sample.
  • The team used differential expression analysis to identify genes that were expressed at different amounts in the neonatal versus adult samples. This led to the discovery of approximately 1115 differentially expressed genes in the AC and 3574 in the SCB of foals compared to adults.
  • These differentially expressed genes were then categorized according to their associated biological functions, known as gene ontology terms, and assigned to specific biological pathways through functional annotation and pathway analysis using PANTHER and Reactome, two dedicated bioinformatics tools.

Major Findings

  • The study found that there was distinct clustering by age and tissue type, with the foals exhibiting a state of growth, high metabolic activity, and tissue turnover.
  • The researchers also identified several overrepresented gene ontology terms and enriched pathways, dominated by those related to extracellular matrix organization and turnover, cell cycle, and signal transduction.
  • Additionally, they discovered pathways related to neural development and neurotransmission in the AC, and innate immunity in the SCB, providing novel directions for future research into the potential mechanisms underlying disease.

Implications and Next Steps

  • The results of this study provide important insights into the differential gene expression occurring in neonatal versus adult horse cartilage and bone. This knowledge could help inform our understanding of skeletal development, and may even contribute to identifying potential new biomarkers for disease risk.
  • The researchers have identified several novel pathways which could potentially play a role in the development of disease. These findings pave the way for future investigations to further validate these pathways and to determine their precise role in disease development and progression.

Cite This Article

APA
Kemper AM, Drnevich J, McCue ME, McCoy AM. (2019). Differential Gene Expression in Articular Cartilage and Subchondral Bone of Neonatal and Adult Horses. Genes (Basel), 10(10), 745. https://doi.org/10.3390/genes10100745

Publication

ISSN: 2073-4425
NlmUniqueID: 101551097
Country: Switzerland
Language: English
Volume: 10
Issue: 10
PII: 745

Researcher Affiliations

Kemper, Ann M
  • Department of Veterinary Clinical Medicine, University of Illinois College of Veterinary Medicine, Urbana, IL 61802, USA. amkemper@illinois.edu.
Drnevich, Jenny
  • Roy J. Carver Biotechnology Center, University of Illinois, Urbana, IL 61801, USA. drnevich@illinois.edu.
McCue, Molly E
  • Veterinary Population Medicine Department, University of Minnesota College of Veterinary Medicine, St. Paul, MN 55108, USA. mccų@umn.edu.
McCoy, Annette M
  • Department of Veterinary Clinical Medicine, University of Illinois College of Veterinary Medicine, Urbana, IL 61802, USA. mccoya@illinois.edu.

MeSH Terms

  • Animals
  • Animals, Newborn / genetics
  • Bone and Bones / metabolism
  • Cartilage, Articular / metabolism
  • Female
  • Gene Expression
  • Horses / genetics
  • Male
  • Sequence Analysis, RNA
  • Transcriptome

Conflict of Interest Statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

This article includes 80 references
  1. Karsenty G. Transcriptional control of skeletogenesis.. Annu Rev Genomics Hum Genet 2008;9:183-96.
  2. Smeeton J, Askary A, Crump JG. Building and maintaining joints by exquisite local control of cell fate.. Wiley Interdiscip Rev Dev Biol 2017 Jan;6(1).
    doi: 10.1002/wdev.245pmc: PMC5877473pubmed: 27581688google scholar: lookup
  3. Mackie EJ, Tatarczuch L, Mirams M. The skeleton: a multi-functional complex organ: the growth plate chondrocyte and endochondral ossification.. J Endocrinol 2011 Nov;211(2):109-21.
    doi: 10.1530/JOE-11-0048pubmed: 21642379google scholar: lookup
  4. Fretz PB, Cymbaluk NF, Pharr JW. Quantitative analysis of long-bone growth in the horse.. Am J Vet Res 1984 Aug;45(8):1602-9.
    pubmed: 6476573
  5. Lawrence LA, Ott EA, Miller GJ, Poulos PW, Piotrowski G, Asquith RL. The mechanical properties of equine third metacarpals as affected by age.. J Anim Sci 1994 Oct;72(10):2617-23.
    doi: 10.2527/1994.72102617xpubmed: 7883619google scholar: lookup
  6. Yokoyama S, Furukawa S, Kitada S, Mori M, Saito T, Kawakami K, Belmonte JCI, Kawakami Y, Ito Y, Sato T, Asahara H. Analysis of transcription factors expressed at the anterior mouse limb bud.. PLoS One 2017;12(5):e0175673.
  7. Sensiate LA, Marques-Souza H. Bone growth as the main determinant of mouse digit tip regeneration after amputation.. Sci Rep 2019 Jul 4;9(1):9720.
    doi: 10.1038/s41598-019-45521-4pmc: PMC6609708pubmed: 31273239google scholar: lookup
  8. Hayes AJ, Mitchell RE, Bashford A, Reynolds S, Caterson B, Hammond CL. Expression of glycosaminoglycan epitopes during zebrafish skeletogenesis.. Dev Dyn 2013 Jun;242(6):778-89.
    doi: 10.1002/dvdy.23970pmc: PMC3698701pubmed: 23576310google scholar: lookup
  9. Enomoto-Iwamoto M, Kitagaki J, Koyama E, Tamamura Y, Wu C, Kanatani N, Koike T, Okada H, Komori T, Yoneda T, Church V, Francis-West PH, Kurisu K, Nohno T, Pacifici M, Iwamoto M. The Wnt antagonist Frzb-1 regulates chondrocyte maturation and long bone development during limb skeletogenesis.. Dev Biol 2002 Nov 1;251(1):142-56.
    doi: 10.1006/dbio.2002.0802pubmed: 12413904google scholar: lookup
  10. Hutchison C, Pilote M, Roy S. The axolotl limb: a model for bone development, regeneration and fracture healing.. Bone 2007 Jan;40(1):45-56.
    doi: 10.1016/j.bone.2006.07.005pubmed: 16920050google scholar: lookup
  11. Gao J, Li X, Zhang Y, Wang H. Endochondral ossification in hindlimbs during bufo gargarizans metamorphosis: A model of studying skeletal development in vertebrates.. Dev Dyn 2018 Oct;247(10):1121-1134.
    doi: 10.1002/dvdy.24669pubmed: 30198600google scholar: lookup
  12. Giffin JL, Gaitor D, Franz-Odendaal TA. The Forgotten Skeletogenic Condensations: A Comparison of Early Skeletal Development Amongst Vertebrates.. J Dev Biol 2019 Feb 1;7(1).
    doi: 10.3390/jdb7010004pmc: PMC6473759pubmed: 30717314google scholar: lookup
  13. Cosden RS, Lattermann C, Romine S, Gao J, Voss SR, MacLeod JN. Intrinsic repair of full-thickness articular cartilage defects in the axolotl salamander.. Osteoarthritis Cartilage 2011 Feb;19(2):200-5.
    doi: 10.1016/j.joca.2010.11.005pmc: PMC3555487pubmed: 21115129google scholar: lookup
  14. Lydon H, Getgood A, Henson FMD. Healing of Osteochondral Defects via Endochondral Ossification in an Ovine Model.. Cartilage 2019 Jan;10(1):94-101.
    doi: 10.1177/1947603517713818pmc: PMC6376560pubmed: 28629234google scholar: lookup
  15. Witt F, Petersen A, Seidel R, Vetter A, Weinkamer R, Duda GN. Combined in vivo/in silico study of mechanobiological mechanisms during endochondral ossification in bone healing.. Ann Biomed Eng 2011 Oct;39(10):2531-41.
    doi: 10.1007/s10439-011-0338-xpubmed: 21692004google scholar: lookup
  16. McIlwraith CW, Association AQH. Summary of panel findings. Proceedings Panel on Developmental Orthopedic Disease, AQHA Developmental Orthopedic Symposium 1986; pp. 55–61.
  17. Lepeule J, Bareille N, Robert C, Ezanno P, Valette JP, Jacquet S, Blanchard G, Denoix JM, Seegers H. Association of growth, feeding practices and exercise conditions with the prevalence of Developmental Orthopaedic Disease in limbs of French foals at weaning.. Prev Vet Med 2009 Jun 1;89(3-4):167-77.
  18. Gabel AA, Knight DA, Reed SM. Comparison of incidence and severity of developmental orthopedic disease on 17 farms before and after adjustment of ration. Am. Assoc. Equine Pract. Proc. 1987;33:163–170.
  19. Philipsson J, Andreasson E, Sandgren B, Dalin G, Carlsten J. Osteochondrosis in the tarsocrural joint and osteochondral fragments in the fetlock joints in Standardbred trotters. II. Heritability. Equine Vet. J. Suppl. 1993;16:38–41.
  20. van Grevenhof EM, Schurink A, Ducro BJ, van Weeren PR, van Tartwijk JM, Bijma P, van Arendonk JA. Genetic variables of various manifestations of osteochondrosis and their correlations between and within joints in Dutch warmblood horses.. J Anim Sci 2009 Jun;87(6):1906-12.
    doi: 10.2527/jas.2008-1199pubmed: 19213707google scholar: lookup
  21. McCoy AM, Norton EM, Kemper AM, Beeson SK, Mickelson JR, McCue ME. SNP-based heritability and genetic architecture of tarsal osteochondrosis in North American Standardbred horses.. Anim Genet 2019 Feb;50(1):78-81.
    doi: 10.1111/age.12738pubmed: 30353927google scholar: lookup
  22. Baldridge D, Shchelochkov O, Kelley B, Lee B. Signaling pathways in human skeletal dysplasias.. Annu Rev Genomics Hum Genet 2010;11:189-217.
  23. Lefebvre V, Bhattaram P. Vertebrate skeletogenesis.. Curr Top Dev Biol 2010;90:291-317.
  24. Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor.. Bioinformatics 2018 Sep 1;34(17):i884-i890.
  25. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data.. Bioinformatics 2014 Aug 1;30(15):2114-20.
  26. Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and bias-aware quantification of transcript expression.. Nat Methods 2017 Apr;14(4):417-419.
    doi: 10.1038/nmeth.4197pmc: PMC5600148pubmed: 28263959google scholar: lookup
  27. Soneson C, Love MI, Robinson MD. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences.. F1000Res 2015;4:1521.
  28. Chen Y, Lun AT, Smyth GK. From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline.. F1000Res 2016;5:1438.
  29. Leek JT, Storey JD. Capturing heterogeneity in gene expression studies by surrogate variable analysis.. PLoS Genet 2007 Sep;3(9):1724-35.
  30. Leek JT, Storey JD. A general framework for multiple testing dependence.. Proc Natl Acad Sci U S A 2008 Dec 2;105(48):18718-23.
    doi: 10.1073/pnas.0808709105pmc: PMC2586646pubmed: 19033188google scholar: lookup
  31. 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
  32. Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK. limma powers differential expression analyses for RNA-sequencing and microarray studies.. Nucleic Acids Res 2015 Apr 20;43(7):e47.
    doi: 10.1093/nar/gkv007pmc: PMC4402510pubmed: 25605792google scholar: lookup
  33. Benjamini YH, Hochberg Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B. 1995;57:289–300.
  34. McCarthy DJ, Smyth GK. Testing significance relative to a fold-change threshold is a TREAT.. Bioinformatics 2009 Mar 15;25(6):765-71.
  35. Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M. Orchestrating high-throughput genomic analysis with Bioconductor.. Nat Methods 2015 Feb;12(2):115-21.
    doi: 10.1038/nmeth.3252pmc: PMC4509590pubmed: 25633503google scholar: lookup
  36. . Annotationhub: Client to Access Annotationhub Resources, R Package Version 2.16.1. Bioconductor 3.9 2019.
  37. . KEGGREST: Client-Side REST Access to KEGG, R Package Version 1.24.0. Bioconductor 3.9 2019.
  38. Huerta-Cepas J, Szklarczyk D, Forslund K, Cook H, Heller D, Walter MC, Rattei T, Mende DR, Sunagawa S, Kuhn M, Jensen LJ, von Mering C, Bork P. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences.. Nucleic Acids Res 2016 Jan 4;44(D1):D286-93.
    doi: 10.1093/nar/gkv1248pmc: PMC4702882pubmed: 26582926google scholar: lookup
  39. 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
  40. Mi H, Dong Q, Muruganujan A, Gaudet P, Lewis S, Thomas PD. PANTHER version 7: improved phylogenetic trees, orthologs and collaboration with the Gene Ontology Consortium.. Nucleic Acids Res 2010 Jan;38(Database issue):D204-10.
    doi: 10.1093/nar/gkp1019pmc: PMC2808919pubmed: 20015972google scholar: lookup
  41. Fabregat A, Jupe S, Matthews L, Sidiropoulos K, Gillespie M, Garapati P, Haw R, Jassal B, Korninger F, May B, Milacic M, Roca CD, Rothfels K, Sevilla C, Shamovsky V, Shorser S, Varusai T, Viteri G, Weiser J, Wu G, Stein L, Hermjakob H, D'Eustachio P. The Reactome Pathway Knowledgebase.. Nucleic Acids Res 2018 Jan 4;46(D1):D649-D655.
    doi: 10.1093/nar/gkx1132pmc: PMC5753187pubmed: 29145629google scholar: lookup
  42. Staines KA, Pollard AS, McGonnell IM, Farquharson C, Pitsillides AA. Cartilage to bone transitions in health and disease.. J Endocrinol 2013 Oct;219(1):R1-R12.
    doi: 10.1530/JOE-13-0276pmc: PMC3769078pubmed: 23959079google scholar: lookup
  43. Pan Z, Zhang X, Shangguan Y, Hu H, Chen L, Wang H. Suppressed osteoclast differentiation at the chondro-osseous junction mediates endochondral ossification retardation in long bones of Wistar fetal rats with prenatal ethanol exposure.. Toxicol Appl Pharmacol 2016 Aug 15;305:234-241.
    doi: 10.1016/j.taap.2016.06.021pubmed: 27338645google scholar: lookup
  44. Adhami MD, Rashid H, Chen H, Clarke JC, Yang Y, Javed A. Loss of Runx2 in committed osteoblasts impairs postnatal skeletogenesis.. J Bone Miner Res 2015 Jan;30(1):71-82.
    doi: 10.1002/jbmr.2321pmc: PMC4280286pubmed: 25079226google scholar: lookup
  45. Glass DA 2nd, Bialek P, Ahn JD, Starbuck M, Patel MS, Clevers H, Taketo MM, Long F, McMahon AP, Lang RA, Karsenty G. Canonical Wnt signaling in differentiated osteoblasts controls osteoclast differentiation.. Dev Cell 2005 May;8(5):751-64.
    doi: 10.1016/j.devcel.2005.02.017pubmed: 15866165google scholar: lookup
  46. Green AC, Kocovski P, Jovic T, Walia MK, Chandraratna RAS, Martin TJ, Baker EK, Purton LE. Retinoic acid receptor signalling directly regulates osteoblast and adipocyte differentiation from mesenchymal progenitor cells.. Exp Cell Res 2017 Jan 1;350(1):284-297.
    doi: 10.1016/j.yexcr.2016.12.007pubmed: 27964926google scholar: lookup
  47. Day TF, Guo X, Garrett-Beal L, Yang Y. Wnt/beta-catenin signaling in mesenchymal progenitors controls osteoblast and chondrocyte differentiation during vertebrate skeletogenesis.. Dev Cell 2005 May;8(5):739-50.
    doi: 10.1016/j.devcel.2005.03.016pubmed: 15866164google scholar: lookup
  48. Iwamoto M, Tamamura Y, Koyama E, Komori T, Takeshita N, Williams JA, Nakamura T, Enomoto-Iwamoto M, Pacifici M. Transcription factor ERG and joint and articular cartilage formation during mouse limb and spine skeletogenesis.. Dev Biol 2007 May 1;305(1):40-51.
    doi: 10.1016/j.ydbio.2007.01.037pmc: PMC2104487pubmed: 17336282google scholar: lookup
  49. Teufel S, Hartmann C. Wnt-signaling in skeletal development.. Curr Top Dev Biol 2019;133:235-279.
    doi: 10.1016/bs.ctdb.2018.11.010pubmed: 30902254google scholar: lookup
  50. Marcellini S, Henriquez JP, Bertin A. Control of osteogenesis by the canonical Wnt and BMP pathways in vivo: cooperation and antagonism between the canonical Wnt and BMP pathways as cells differentiate from osteochondroprogenitors to osteoblasts and osteocytes.. Bioessays 2012 Nov;34(11):953-62.
    doi: 10.1002/bies.201200061pubmed: 22930599google scholar: lookup
  51. Chen E, Liu G, Zhou X, Zhang W, Wang C, Hu D, Xue D, Pan Z. Concentration-dependent, dual roles of IL-10 in the osteogenesis of human BMSCs via P38/MAPK and NF-κB signaling pathways.. FASEB J 2018 Sep;32(9):4917-4929.
    doi: 10.1096/fj.201701256RRRpubmed: 29630408google scholar: lookup
  52. Hosseini-Farahabadi S, Geetha-Loganathan P, Fu K, Nimmagadda S, Yang HJ, Richman JM. Dual functions for WNT5A during cartilage development and in disease.. Matrix Biol 2013 Jun 24;32(5):252-64.
    doi: 10.1016/j.matbio.2013.02.005pubmed: 23474397google scholar: lookup
  53. McCoy AM, Toth F, Dolvik NI, Ekman S, Ellermann J, Olstad K, Ytrehus B, Carlson CS. Articular osteochondrosis: a comparison of naturally-occurring human and animal disease.. Osteoarthritis Cartilage 2013 Nov;21(11):1638-47.
    doi: 10.1016/j.joca.2013.08.011pmc: PMC3815567pubmed: 23954774google scholar: lookup
  54. Kinsley MA, Semevolos SA, Duesterdieck-Zellmer KF. Wnt/β-catenin signaling of cartilage canal and osteochondral junction chondrocytes and full thickness cartilage in early equine osteochondrosis.. J Orthop Res 2015 Oct;33(10):1433-8.
    doi: 10.1002/jor.22846pubmed: 25676127google scholar: lookup
  55. Semevolos SA, Nixon AJ, Brower-Toland BD. Changes in molecular expression of aggrecan and collagen types I, II, and X, insulin-like growth factor-I, and transforming growth factor-beta1 in articular cartilage obtained from horses with naturally acquired osteochondrosis.. Am J Vet Res 2001 Jul;62(7):1088-94.
    doi: 10.2460/ajvr.2001.62.1088pubmed: 11453485google scholar: lookup
  56. Semevolos SA, Brower-Toland BD, Bent SJ, Nixon AJ. Parathyroid hormone-related peptide and indian hedgehog expression patterns in naturally acquired equine osteochondrosis.. J Orthop Res 2002 Nov;20(6):1290-7.
    doi: 10.1016/S0736-0266(02)00055-4pubmed: 12472242google scholar: lookup
  57. Henson FM, Schofield PN, Jeffcott LB. Expression of transforming growth factor-beta 1 in normal and dyschondroplastic articular growth cartilage of the young horse.. Equine Vet J 1997 Nov;29(6):434-9.
  58. Mirams M, Tatarczuch L, Ahmed YA, Pagel CN, Jeffcott LB, Davies HM, Mackie EJ. Altered gene expression in early osteochondrosis lesions.. J Orthop Res 2009 Apr;27(4):452-7.
    doi: 10.1002/jor.20761pubmed: 18932239google scholar: lookup
  59. Mirams M, Ayodele BA, Tatarczuch L, Henson FM, Pagel CN, Mackie EJ. Identification of novel osteochondrosis--Associated genes.. J Orthop Res 2016 Mar;34(3):404-11.
    doi: 10.1002/jor.23033pubmed: 26296056google scholar: lookup
  60. Austbø L, Røed KH, Dolvik NI, Skretting G. Identification of differentially expressed genes associated with osteochondrosis in standardbred horses using RNA arbitrarily primed PCR.. Anim Biotechnol 2010 Apr;21(2):135-9.
    doi: 10.1080/10495391003608316pubmed: 20379890google scholar: lookup
  61. Serteyn D, Piquemal D, Vanderheyden L, Lejeune JP, Verwilghen D, Sandersen C. Gene expression profiling from leukocytes of horses affected by osteochondrosis.. J Orthop Res 2010 Jul;28(7):965-70.
    doi: 10.1002/jor.21089pubmed: 20108324google scholar: lookup
  62. Piepoli T, Mennuni L, Zerbi S, Lanza M, Rovati LC, Caselli G. Glutamate signaling in chondrocytes and the potential involvement of NMDA receptors in cell proliferation and inflammatory gene expression.. Osteoarthritis Cartilage 2009 Aug;17(8):1076-83.
    doi: 10.1016/j.joca.2009.02.002pubmed: 19233337google scholar: lookup
  63. Wang L, Hinoi E, Takemori A, Takarada T, Yoneda Y. Abolition of chondral mineralization by group III metabotropic glutamate receptors expressed in rodent cartilage.. Br J Pharmacol 2005 Nov;146(5):732-43.
    doi: 10.1038/sj.bjp.0706358pmc: PMC1751195pubmed: 16086032google scholar: lookup
  64. Wang L, Hinoi E, Takemori A, Yoneda Y. Release of endogenous glutamate by AMPA receptors expressed in cultured rat costal chondrocytes.. Biol Pharm Bull 2005 Jun;28(6):990-3.
    doi: 10.1248/bpb.28.990pubmed: 15930732google scholar: lookup
  65. Grässel SG. The role of peripheral nerve fibers and their neurotransmitters in cartilage and bone physiology and pathophysiology.. Arthritis Res Ther 2014;16(6):485.
    doi: 10.1186/s13075-014-0485-1pmc: PMC4395972pubmed: 25789373google scholar: lookup
  66. Stüdle C, Occhetta P, Geier F, Mehrkens A, Barbero A, Martin I. Challenges Toward the Identification of Predictive Markers for Human Mesenchymal Stromal Cells Chondrogenic Potential.. Stem Cells Transl Med 2019 Feb;8(2):194-204.
    doi: 10.1002/sctm.18-0147pmc: PMC6344903pubmed: 30676001google scholar: lookup
  67. Wen ZH, Chang YC, Jean YH. Excitatory amino acid glutamate: role in peripheral nociceptive transduction and inflammation in experimental and clinical osteoarthritis.. Osteoarthritis Cartilage 2015 Nov;23(11):2009-16.
    doi: 10.1016/j.joca.2015.03.017pubmed: 26521747google scholar: lookup
  68. Xiao W, Wang Y, Pacios S, Li S, Graves DT. Cellular and Molecular Aspects of Bone Remodeling.. Front Oral Biol 2016;18:9-16.
    doi: 10.1159/000351895pubmed: 26599113google scholar: lookup
  69. Herath TDK, Larbi A, Teoh SH, Kirkpatrick CJ, Goh BT. Neutrophil-mediated enhancement of angiogenesis and osteogenesis in a novel triple cell co-culture model with endothelial cells and osteoblasts.. J Tissue Eng Regen Med 2018 Feb;12(2):e1221-e1236.
    doi: 10.1002/term.2521pubmed: 28715156google scholar: lookup
  70. Ehrnthaller C, Huber-Lang M, Nilsson P, Bindl R, Redeker S, Recknagel S, Rapp A, Mollnes T, Amling M, Gebhard F, Ignatius A. Complement C3 and C5 deficiency affects fracture healing.. PLoS One 2013;8(11):e81341.
  71. Huber-Lang M, Kovtun A, Ignatius A. The role of complement in trauma and fracture healing.. Semin Immunol 2013 Feb;25(1):73-8.
    doi: 10.1016/j.smim.2013.05.006pubmed: 23768898google scholar: lookup
  72. Yoshida Y, Yamasaki S, Oi K, Kuranobu T, Nojima T, Miyaki S, Ida H, Sugiyama E. IL-1β Enhances Wnt Signal by Inhibiting DKK1.. Inflammation 2018 Oct;41(5):1945-1954.
    doi: 10.1007/s10753-018-0838-zpubmed: 29956067google scholar: lookup
  73. Liu S, Li Y, Xia L, Shen H, Lu J. IL-35 prevent bone loss through promotion of bone formation and angiogenesis in rheumatoid arthritis.. Clin Exp Rheumatol 2019 Sep-Oct;37(5):820-825.
    pubmed: 30767867
  74. Moriwaki S, Into T, Suzuki K, Miyauchi M, Takata T, Shibayama K, Niida S. γ-Glutamyltranspeptidase is an endogenous activator of Toll-like receptor 4-mediated osteoclastogenesis.. Sci Rep 2016 Oct 24;6:35930.
    doi: 10.1038/srep35930pmc: PMC5075938pubmed: 27775020google scholar: lookup
  75. Liu YH, Huang D, Li ZJ, Li XH, Wang X, Yang HP, Tian SP, Mao Y, Liu MF, Wang YF, Wu Y, Han XF. Toll-like receptor-4-dependence of the lipopolysaccharide-mediated inhibition of osteoblast differentiation.. Genet Mol Res 2016 Apr 25;15(2).
    doi: 10.4238/gmr.15027191pubmed: 27173231google scholar: lookup
  76. Rangkasenee N, Murani E, Schellander K, Cinar MU, Ponsuksili S, Wimmers K. Gene expression profiling of articular cartilage reveals functional pathways and networks of candidate genes for osteochondrosis in pigs.. Physiol Genomics 2013 Sep 16;45(18):856-65.
  77. Rangkasenee N, Murani E, Brunner RM, Schellander K, Cinar MU, Luther H, Hofer A, Stoll M, Witten A, Ponsuksili S, Wimmers K. Genome-Wide Association Identifies TBX5 as Candidate Gene for Osteochondrosis Providing a Functional Link to Cartilage Perfusion as Initial Factor.. Front Genet 2013;4:78.
    doi: 10.3389/fgene.2013.00078pmc: PMC3650520pubmed: 23675383google scholar: lookup
  78. 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.
  79. 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
  80. 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.

Citations

This article has been cited 1 times.
  1. Premont A, Saadeh K, Edling C, Lewis R, Marr CM, Jeevaratnam K. Cardiac ion channel expression in the equine model - In-silico prediction utilising RNA sequencing data from mixed tissue samples.. Physiol Rep 2022 Jul;10(14):e15273.
    doi: 10.14814/phy2.15273pubmed: 35880716google scholar: lookup