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BMC biotechnology2006; 6; 24; doi: 10.1186/1472-6750-6-24

Selection of a set of reliable reference genes for quantitative real-time PCR in normal equine skin and in equine sarcoids.

Abstract: Real-time quantitative PCR can be a very powerful and accurate technique to examine gene transcription patterns in different biological conditions. One of the critical steps in comparing transcription profiles is accurate normalisation. In most of the studies published on real-time PCR in horses, normalisation occurred against only one reference gene, usually GAPDH or ACTB, without validation of its expression stability. This might result in unreliable conclusions, because it has been demonstrated that the expression levels of so called "housekeeping genes" may vary considerably in different tissues, cell types or disease stages, particularly in clinical samples associated with malignant disease. The goal of this study was to establish a reliable set of reference genes for studies concerning normal equine skin and equine sarcoids, which are the most common skin tumour in horses. Results: In the present study the gene transcription levels of 6 commonly used reference genes (ACTB, B2M, HPRT1, UBB, TUBA1 and RPL32) were determined in normal equine skin and in equine sarcoids. After applying the geNorm applet to this set of genes, TUBA1, ACTB and UBB were found to be most stable in normal skin and B2M, ACTB and UBB in equine sarcoids. Conclusions: Based on these results, TUBA1, ACTB and UBB, respectively B2M, ACTB and UBB can be proposed as reference gene panels for accurate normalisation of quantitative data for normal equine skin, respectively equine sarcoids. When normal skin and equine sarcoids are compared, the use of the geometric mean of UBB, ACTB and B2M can be recommended as a reliable and accurate normalisation factor.
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Publication Date: 2006-04-27 PubMed ID: 16643647PubMed Central: PMC1484482DOI: 10.1186/1472-6750-6-24Google 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.

This research article focuses on identifying a reliable set of reference genes to accurately measure gene transcription levels in normal equine skin and in equine sarcoids, a common skin tumor in horses, using real-time quantitative PCR technique.

Objective and Importance of the Study

  • The primary aim of the research was to pinpoint dependable reference genes for real-time quantitative PCR studies relating to normal equine skin and equine sarcoids.
  • Equine sarcoids, which are the most prevalent skin tumors in horses, were of particular interest.
  • A crucial aspect of comparing transcript profiles is accurate normalization, often done against a single reference gene like GAPDH or ACTB, without validating its expression stability. This approach could lead to unreliable results as “housekeeping genes” expression can considerablely vary in different tissues, cell types or disease stages.

Investigation and Results Obtained

  • Six prevalent reference genes (ACTB, B2M, HPRT1, UBB, TUBA1, and RPL32) were the focus of the investigation. The researchers measured gene transcription levels in normal equine skin and in equine sarcoids using these genes.
  • The geNorm applet was employed to these genes to assess their stability. TUBA1, ACTB, and UBB were discovered to be the most stable in normal skin, while B2M, ACTB, and UBB were found the most stable in equine sarcoids.

Conclusions and Recommendations

  • Based on the study findings, TUBA1, ACTB, and UBB for normal equine skin, and B2M, ACTB, and UBB for equine sarcoids could be recommended as reference gene panels for accurate normalization of quantitative data.
  • When comparing normal skin and equine sarcoids, the geometric mean of UBB, ACTB, and B2M is recommended as a reliable and accurate normalization factor.

Cite This Article

APA
Bogaert L, Van Poucke M, De Baere C, Peelman L, Gasthuys F, Martens A. (2006). Selection of a set of reliable reference genes for quantitative real-time PCR in normal equine skin and in equine sarcoids. BMC Biotechnol, 6, 24. https://doi.org/10.1186/1472-6750-6-24

Publication

BMC biotechnology
ISSN: 1472-6750
NlmUniqueID: 101088663
Country: England
Language: English
Volume: 6
Pages: 24

Researcher Affiliations

Bogaert, Lies
  • Department of Surgery and Anaesthesiology of Domestic Animals, Faculty of Veterinary Medicine, Ghent University--UGent, Salisburylaan 133, B-9820 Merelbeke, Belgium. lies.bogaert@UGent.be
Van Poucke, Mario
    De Baere, Cindy
      Peelman, Luc
        Gasthuys, Frank
          Martens, Ann

            MeSH Terms

            • Animals
            • Gene Expression Profiling
            • Genes
            • Horse Diseases / genetics
            • Horse Diseases / pathology
            • Horses
            • Polymerase Chain Reaction / methods
            • Polymerase Chain Reaction / veterinary
            • Skin / pathology
            • Skin Neoplasms / genetics
            • Skin Neoplasms / pathology
            • Skin Neoplasms / veterinary
            • Transcription, Genetic

            References

            This article includes 28 references
            1. Radonić A, Thulke S, Bae HG, Müller MA, Siegert W, Nitsche A. Reference gene selection for quantitative real-time PCR analysis in virus infected cells: SARS corona virus, Yellow fever virus, Human Herpesvirus-6, Camelpox virus and Cytomegalovirus infections.. Virol J 2005 Feb 10;2:7.
              doi: 10.1186/1743-422X-2-7pmc: PMC549079pubmed: 15705200google scholar: lookup
            2. Zhang X, Ding L, Sandford AJ. Selection of reference genes for gene expression studies in human neutrophils by real-time PCR.. BMC Mol Biol 2005 Feb 18;6:4.
              doi: 10.1186/1471-2199-6-4pmc: PMC551605pubmed: 15720708google scholar: lookup
            3. Thellin O, Zorzi W, Lakaye B, De Borman B, Coumans B, Hennen G, Grisar T, Igout A, Heinen E. Housekeeping genes as internal standards: use and limits.. J Biotechnol 1999 Oct 8;75(2-3):291-5.
              doi: 10.1016/S0168-1656(99)00163-7pubmed: 10617337google scholar: lookup
            4. Suzuki T, Higgins PJ, Crawford DR. Control selection for RNA quantitation.. Biotechniques 2000 Aug;29(2):332-7.
              pubmed: 10948434doi: 10.2144/00292rv02google scholar: lookup
            5. Petersen BH, Rapaport R, Henry DP, Huseman C, Moore WV. Effect of treatment with biosynthetic human growth hormone (GH) on peripheral blood lymphocyte populations and function in growth hormone-deficient children.. J Clin Endocrinol Metab 1990 Jun;70(6):1756-60.
              pubmed: 2347906doi: 10.1210/jcem-70-6-1756google scholar: lookup
            6. Singh R, Green MR. Sequence-specific binding of transfer RNA by glyceraldehyde-3-phosphate dehydrogenase.. Science 1993 Jan 15;259(5093):365-8.
              pubmed: 8420004doi: 10.1126/science.8420004google scholar: lookup
            7. Ishitani R, Sunaga K, Hirano A, Saunders P, Katsube N, Chuang DM. Evidence that glyceraldehyde-3-phosphate dehydrogenase is involved in age-induced apoptosis in mature cerebellar neurons in culture.. J Neurochem 1996 Mar;66(3):928-35.
              pubmed: 8769851doi: 10.1046/j.1471-4159.1996.66030928.xgoogle scholar: lookup
            8. Neuvians TP, Gashaw I, Sauer CG, von Ostau C, Kliesch S, Bergmann M, Häcker A, Grobholz R. Standardization strategy for quantitative PCR in human seminoma and normal testis.. J Biotechnol 2005 May 4;117(2):163-71.
              doi: 10.1016/j.jbiotec.2005.01.011pubmed: 15823405google scholar: lookup
            9. Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.. Genome Biol 2002 Jun 18;3(7):RESEARCH0034.
              doi: 10.1186/gb-2002-3-7-research0034pmc: PMC126239pubmed: 12184808google scholar: lookup
            10. Giguère S, Prescott JF. Quantitation of equine cytokine mRNA expression by reverse transcription-competitive polymerase chain reaction.. Vet Immunol Immunopathol 1999 Jan 4;67(1):1-15.
              doi: 10.1016/S0165-2427(98)00212-8pubmed: 9950350google scholar: lookup
            11. Leutenegger CM, von Rechenberg B, Huder JB, Zlinsky K, Mislin C, Akens MK, Auer J, Lutz H. Quantitative real-time PCR for equine cytokine mRNA in nondecalcified bone tissue embedded in methyl methacrylate.. Calcif Tissue Int 1999 Nov;65(5):378-83.
              doi: 10.1007/s002239900717pubmed: 10541764google scholar: lookup
            12. Swiderski CE, Klei TR, Horohov DW. Quantitative measurement of equine cytokine mRNA expression by polymerase chain reaction using target-specific standard curves.. J Immunol Methods 1999 Jan 1;222(1-2):155-69.
              doi: 10.1016/S0022-1759(98)00193-8pubmed: 10022382google scholar: lookup
            13. von Rechenberg B, Leutenegger C, Zlinsky K, McIlwraith CW, Akens MK, Auer JA. Upregulation of mRNA of interleukin-1 and -6 in subchondral cystic lesions of four horses.. Equine Vet J 2001 Mar;33(2):143-9.
              pubmed: 11266063doi: 10.1111/j.2042-3306.2001.tb00592.xgoogle scholar: lookup
            14. Ainsworth DM, Appleton JA, Eicker SW, Luce R, Julia Flaminio M, Antczak DF. The effect of strenuous exercise on mRNA concentrations of interleukin-12, interferon-gamma and interleukin-4 in equine pulmonary and peripheral blood mononuclear cells.. Vet Immunol Immunopathol 2003 Jan 10;91(1):61-71.
              doi: 10.1016/S0165-2427(02)00274-Xpubmed: 12507851google scholar: lookup
            15. Lim WS, Edwards JF, Boyd NK, Payne SL, Ball JM. Simultaneous quantitation of equine cytokine mRNAs using a multi-probe ribonuclease protection assay.. Vet Immunol Immunopathol 2003 Jan 10;91(1):45-51.
              doi: 10.1016/S0165-2427(02)00263-5pubmed: 12507849google scholar: lookup
            16. Waguespack RW, Kemppainen RJ, Cochran A, Lin HC, Belknap JK. Increased expression of MAIL, a cytokine-associated nuclear protein, in the prodromal stage of black walnut-induced laminitis.. Equine Vet J 2004 Apr;36(3):285-91.
              pubmed: 15147139doi: 10.2746/0425164044877099google scholar: lookup
            17. Gerber H. Sir Frederick Hobday memorial lecture. The genetic basis of some equine diseases.. Equine Vet J 1989 Jul;21(4):244-8.
              pubmed: 2670541doi: 10.1111/j.2042-3306.1989.tb02160.xgoogle scholar: lookup
            18. Lazary S, Gerber H, Glatt PA, Straub R. Equine leucocyte antigens in sarcoid-affected horses.. Equine Vet J 1985 Jul;17(4):283-6.
              pubmed: 3865769doi: 10.1111/j.2042-3306.1985.tb02498.xgoogle scholar: lookup
            19. Meredith D, Elser AH, Wolf B, Soma LR, Donawick WJ, Lazary S. Equine leukocyte antigens: relationships with sarcoid tumors and laminitis in two pure breeds.. Immunogenetics 1986;23(4):221-5.
              doi: 10.1007/BF00373016pubmed: 3699852google scholar: lookup
            20. Gerber H, Dubath M-L, Lazary S. Association between predisposition to equine sarcoid and MHC in multiple-case families. Proceedings of the 5th International Conference on Equine Infectious Diseases 1988; pp. 272–277.
            21. Otten N, von Tscharner C, Lazary S, Antczak DF, Gerber H. DNA of bovine papillomavirus type 1 and 2 in equine sarcoids: PCR detection and direct sequencing.. Arch Virol 1993;132(1-2):121-31.
              doi: 10.1007/BF01309847pubmed: 8394687google scholar: lookup
            22. Teifke JP, Hardt M, Weiss E. Detection of bovine papillomavirus DNA in formalin-fixed and paraffin-embedded equine sarcoids by polymerase chain reaction and non-radioactive in situ hybridization. European Journal of Veterinary Pathology 1994;1:5–10.
            23. Nasir L, Reid SW. Bovine papillomaviral gene expression in equine sarcoid tumours.. Virus Res 1999 Jun;61(2):171-5.
              doi: 10.1016/S0168-1702(99)00022-2pubmed: 10475087google scholar: lookup
            24. Pascoe RR, Knottenbelt DC. Neoplastic conditions. Manual of equine dermatology 1999; pp. 244–252.
            25. Rozen S, Skaletsky H. Primer3 on the WWW for general users and for biologist programmers.. Methods Mol Biol 2000;132:365-86.
              pubmed: 10547847doi: 10.1385/1-59259-192-2:365google scholar: lookup
            26. National Center for Biotechnology Information
            27. Zuker M. Mfold web server for nucleic acid folding and hybridization prediction.. Nucleic Acids Res 2003 Jul 1;31(13):3406-15.
              doi: 10.1093/nar/gkg595pmc: PMC169194pubmed: 12824337google scholar: lookup
            28. Wain HM, Bruford EA, Lovering RC, Lush MJ, Wright MW, Povey S. Guidelines for human gene nomenclature.. Genomics 2002 Apr;79(4):464-70.
              doi: 10.1006/geno.2002.6748pubmed: 11944974google scholar: lookup

            Citations

            This article has been cited 35 times.
            1. Austin MMP, Ivey JLZ, Shepherd EA, Myer PR. Methodologies to Identify Metabolic Pathway Differences Between Emaciated and Moderately Conditioned Horses: A Review of Multiple Gene Expression Techniques. Animals (Basel) 2025 Oct 10;15(20).
              doi: 10.3390/ani15202933pubmed: 41153862google scholar: lookup
            2. Semik-Gurgul E, Gurgul A, Szmatoła T. Transcriptome and methylome sequencing reveals altered long non-coding RNA genes expression and their aberrant DNA methylation in equine sarcoids. Funct Integr Genomics 2023 Aug 8;23(3):268.
              doi: 10.1007/s10142-023-01200-2pubmed: 37552338google scholar: lookup
            3. Hisey EA, Martins BC, Donnelly CG, Cassano JM, Katzman SA, Murphy CJ, Thomasy SM, Leonard BC. Identification of putative orthologs of clinically relevant antimicrobial peptides in the equine ocular surface and amniotic membrane. Vet Ophthalmol 2023 Apr;26 Suppl 1(Suppl 1):125-133.
              doi: 10.1111/vop.13042pubmed: 36478371google scholar: lookup
            4. Podstawski P, Ropka-Molik K, Semik-Gurgul E, Samiec M, Skrzyszowska M, Podstawski Z, Szmatoła T, Witkowski M, Pawlina-Tyszko K. Tracking the Molecular Scenarios for Tumorigenic Remodeling of Extracellular Matrix Based on Gene Expression Profiling in Equine Skin Neoplasia Models. Int J Mol Sci 2022 Jun 10;23(12).
              doi: 10.3390/ijms23126506pubmed: 35742950google scholar: lookup
            5. Pawlina-Tyszko K, Semik-Gurgul E, Ząbek T, Witkowski M. Methylation Status of Gene Bodies of Selected microRNA Genes Associated with Neoplastic Transformation in Equine Sarcoids. Cells 2022 Jun 14;11(12).
              doi: 10.3390/cells11121917pubmed: 35741046google scholar: lookup
            6. Podstawski P, Ropka-Molik K, Semik-Gurgul E, Samiec M, Skrzyszowska M, Podstawski Z, Szmatoła T, Witkowski M, Pawlina-Tyszko K. Assessment of BPV-1 Mediated Matrix Metalloproteinase Genes Deregulation in the In Vivo and In Vitro Models Designed to Explore Molecular Nature of Equine Sarcoids. Cells 2022 Apr 8;11(8).
              doi: 10.3390/cells11081268pubmed: 35455948google scholar: lookup
            7. Podstawski P, Samiec M, Skrzyszowska M, Szmatoła T, Semik-Gurgul E, Ropka-Molik K. The Induced Expression of BPV E4 Gene in Equine Adult Dermal Fibroblast Cells as a Potential Model of Skin Sarcoid-like Neoplasia. Int J Mol Sci 2022 Feb 10;23(4).
              doi: 10.3390/ijms23041970pubmed: 35216085google scholar: lookup
            8. Munday JS, Orbell G, Fairley RA, Hardcastle M, Vaatstra B. Evidence from a Series of 104 Equine Sarcoids Suggests That Most Sarcoids in New Zealand Are Caused by Bovine Papillomavirus Type 2, although Both BPV1 and BPV2 DNA Are Detectable in around 10% of Sarcoids. Animals (Basel) 2021 Oct 29;11(11).
              doi: 10.3390/ani11113093pubmed: 34827825google scholar: lookup
            9. Olomski F, Fettelschoss V, Jonsdottir S, Birkmann K, Thoms F, Marti E, Bachmann MF, Kündig TM, Fettelschoss-Gabriel A. Interleukin 31 in insect bite hypersensitivity-Alleviating clinical symptoms by active vaccination against itch. Allergy 2020 Apr;75(4):862-871.
              doi: 10.1111/all.14145pubmed: 31816097google scholar: lookup
            10. Schedlbauer C, Blaue D, Gericke M, Blüher M, Starzonek J, Gittel C, Brehm W, Vervuert I. Impact of body weight gain on hepatic metabolism and hepatic inflammatory cytokines in comparison of Shetland pony geldings and Warmblood horse geldings. PeerJ 2019;7:e7069.
              doi: 10.7717/peerj.7069pubmed: 31211018google scholar: lookup
            11. Zhang Q, Zhang M, Li J, Xiao H, Wu D, Guo Q, Zhang Y, Wang H, Li S, Liao S. Selection and Validation of Reference Genes for RT-PCR Expression Analysis of Candidate Genes Involved in Morphine-Induced Conditioned Place Preference Mice. J Mol Neurosci 2018 Dec;66(4):587-594.
              doi: 10.1007/s12031-018-1198-8pubmed: 30386959google scholar: lookup
            12. Dzaki N, Azzam G. Assessment of Aedes albopictus reference genes for quantitative PCR at different stages of development. PLoS One 2018;13(3):e0194664.
              doi: 10.1371/journal.pone.0194664pubmed: 29554153google scholar: lookup
            13. Dzaki N, Ramli KN, Azlan A, Ishak IH, Azzam G. Evaluation of reference genes at different developmental stages for quantitative real-time PCR in Aedes aegypti. Sci Rep 2017 Mar 16;7:43618.
              doi: 10.1038/srep43618pubmed: 28300076google scholar: lookup
            14. Azarpeykan S, Dittmer KE. Evaluation of housekeeping genes for quantitative gene expression analysis in the equine kidney. J Equine Sci 2016;27(4):165-168.
              doi: 10.1294/jes.27.165pubmed: 27974876google scholar: lookup
            15. Hernández AH, Curi R, Salazar LA. Selection of reference genes for expression analyses in liver of rats with impaired glucose metabolism. Int J Clin Exp Pathol 2015;8(4):3946-54.
              pubmed: 26097580
            16. Finno CJ, Stevens C, Young A, Affolter V, Joshi NA, Ramsay S, Bannasch DL. SERPINB11 frameshift variant associated with novel hoof specific phenotype in Connemara ponies. PLoS Genet 2015 Apr;11(4):e1005122.
              doi: 10.1371/journal.pgen.1005122pubmed: 25875171google scholar: lookup
            17. Morrison PK, Bing C, Harris PA, Maltin CA, Grove-White D, Argo CM. Preliminary investigation into a potential role for myostatin and its receptor (ActRIIB) in lean and obese horses and ponies. PLoS One 2014;9(11):e112621.
              doi: 10.1371/journal.pone.0112621pubmed: 25390640google scholar: lookup
            18. Morrison PK, Bing C, Harris PA, Maltin CA, Grove-White D, Argo CM. Post-mortem stability of RNA in skeletal muscle and adipose tissue and the tissue-specific expression of myostatin, perilipin and associated factors in the horse. PLoS One 2014;9(6):e100810.
              doi: 10.1371/journal.pone.0100810pubmed: 24956155google scholar: lookup
            19. De Schauwer C, Goossens K, Piepers S, Hoogewijs MK, Govaere JL, Smits K, Meyer E, Van Soom A, Van de Walle GR. Characterization and profiling of immunomodulatory genes of equine mesenchymal stromal cells from non-invasive sources. Stem Cell Res Ther 2014 Jan 13;5(1):6.
              doi: 10.1186/scrt395pubmed: 24418262google scholar: lookup
            20. Najafpanah MJ, Sadeghi M, Bakhtiarizadeh MR. Reference genes selection for quantitative real-time PCR using RankAggreg method in different tissues of Capra hircus. PLoS One 2013;8(12):e83041.
              doi: 10.1371/journal.pone.0083041pubmed: 24358246google scholar: lookup
            21. Bruynsteen L, Erkens T, Peelman LJ, Ducatelle R, Janssens GP, Harris PA, Hesta M. Expression of inflammation-related genes is associated with adipose tissue location in horses. BMC Vet Res 2013 Dec 2;9:240.
              doi: 10.1186/1746-6148-9-240pubmed: 24295090google scholar: lookup
            22. Karagianni AE, Kapetanovic R, McGorum BC, Hume DA, Pirie SR. The equine alveolar macrophage: functional and phenotypic comparisons with peritoneal macrophages. Vet Immunol Immunopathol 2013 Oct 1;155(4):219-28.
              doi: 10.1016/j.vetimm.2013.07.003pubmed: 23978307google scholar: lookup
            23. Klein C, Rutllant J, Troedsson MH. Expression stability of putative reference genes in equine endometrial, testicular, and conceptus tissues. BMC Res Notes 2011 Apr 12;4:120.
              doi: 10.1186/1756-0500-4-120pubmed: 21486450google scholar: lookup
            24. Beekman L, Tohver T, Dardari R, Léguillette R. Evaluation of suitable reference genes for gene expression studies in bronchoalveolar lavage cells from horses with inflammatory airway disease. BMC Mol Biol 2011 Jan 28;12:5.
              doi: 10.1186/1471-2199-12-5pubmed: 21272375google scholar: lookup
            25. Guo Y, Chen JX, Yang S, Fu XP, Zhang Z, Chen KH, Huang Y, Li Y, Xie Y, Mao YM. Selection of reliable reference genes for gene expression study in nasopharyngeal carcinoma. Acta Pharmacol Sin 2010 Nov;31(11):1487-94.
              doi: 10.1038/aps.2010.115pubmed: 21052085google scholar: lookup
            26. Axtner J, Sommer S. Validation of internal reference genes for quantitative real-time PCR in a non-model organism, the yellow-necked mouse, Apodemus flavicollis. BMC Res Notes 2009 Dec 23;2:264.
              doi: 10.1186/1756-0500-2-264pubmed: 20030847google scholar: lookup
            27. Kessler Y, Helfer-Hungerbuehler AK, Cattori V, Meli ML, Zellweger B, Ossent P, Riond B, Reusch CE, Lutz H, Hofmann-Lehmann R. Quantitative TaqMan real-time PCR assays for gene expression normalisation in feline tissues. BMC Mol Biol 2009 Dec 11;10:106.
              doi: 10.1186/1471-2199-10-106pubmed: 20003366google scholar: lookup
            28. Smits K, Goossens K, Van Soom A, Govaere J, Hoogewijs M, Vanhaesebrouck E, Galli C, Colleoni S, Vandesompele J, Peelman L. Selection of reference genes for quantitative real-time PCR in equine in vivo and fresh and frozen-thawed in vitro blastocysts. BMC Res Notes 2009 Dec 11;2:246.
              doi: 10.1186/1756-0500-2-246pubmed: 20003356google scholar: lookup
            29. Yoo WG, Kim TI, Li S, Kwon OS, Cho PY, Kim TS, Kim K, Hong SJ. Reference genes for quantitative analysis on Clonorchis sinensis gene expression by real-time PCR. Parasitol Res 2009 Jan;104(2):321-8.
              doi: 10.1007/s00436-008-1195-xpubmed: 18815810google scholar: lookup
            30. Le Bail A, Dittami SM, de Franco PO, Rousvoal S, Cock MJ, Tonon T, Charrier B. Normalisation genes for expression analyses in the brown alga model Ectocarpus siliculosus. BMC Mol Biol 2008 Aug 18;9:75.
              doi: 10.1186/1471-2199-9-75pubmed: 18710525google scholar: lookup
            31. Cappelli K, Felicetti M, Capomaccio S, Spinsanti G, Silvestrelli M, Supplizi AV. Exercise induced stress in horses: selection of the most stable reference genes for quantitative RT-PCR normalization. BMC Mol Biol 2008 May 19;9:49.
              doi: 10.1186/1471-2199-9-49pubmed: 18489742google scholar: lookup
            32. Takle GW, Toth IK, Brurberg MB. Evaluation of reference genes for real-time RT-PCR expression studies in the plant pathogen Pectobacterium atrosepticum. BMC Plant Biol 2007 Sep 21;7:50.
              doi: 10.1186/1471-2229-7-50pubmed: 17888160google scholar: lookup
            33. Nygard AB, Jørgensen CB, Cirera S, Fredholm M. Selection of reference genes for gene expression studies in pig tissues using SYBR green qPCR. BMC Mol Biol 2007 Aug 15;8:67.
              doi: 10.1186/1471-2199-8-67pubmed: 17697375google scholar: lookup
            34. Maccoux LJ, Clements DN, Salway F, Day PJ. Identification of new reference genes for the normalisation of canine osteoarthritic joint tissue transcripts from microarray data. BMC Mol Biol 2007 Jul 25;8:62.
              doi: 10.1186/1471-2199-8-62pubmed: 17651481google scholar: lookup
            35. Toegel S, Huang W, Piana C, Unger FM, Wirth M, Goldring MB, Gabor F, Viernstein H. Selection of reliable reference genes for qPCR studies on chondroprotective action. BMC Mol Biol 2007 Feb 26;8:13.
              doi: 10.1186/1471-2199-8-13pubmed: 17324259google scholar: lookup
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