FREE SHIPPING over $40
OVER 10000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Journal of equine science2016; 27(4); 165-168; doi: 10.1294/jes.27.165

Evaluation of housekeeping genes for quantitative gene expression analysis in the equine kidney.

Abstract: Housekeeping genes (HKGs) are used as internal controls for normalising and calculating the relative expression of target genes in RT-qPCR experiments. There is no unique universal HKG and HKGs vary among organisms and tissues, so this study aimed to determine the most stably expressed HKGs in the equine kidney. The evaluated HKGs included 18S ribosomal RNA (18S), 28S ribosomal RNA (28S), ribosomal protein L32 (RPL32), β-2-microglobulin (B2M), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), succinate dehydrogenase complex (SDHA), zeta polypeptide (YWHAZ), and hypoxanthine phosphoribosyltransferase 1 (HPRT1). The HKGs expression stability data were analysed with two software packages, geNorm and NormFinder. The lowest stability values for geNorm suggests that YWHAZ and HPRT1 would be most optimal (M=0.31 and 0.32, respectively). Further, these two genes had the best pairwise stability value using NormFinder (geNorm V=0.085). Therefore, these two genes were considered the most useful for RT-qPCR studies in equine kidney.
Get Full Text
Publication Date: 2016-12-15 PubMed ID: 27974876PubMed Central: PMC5155135DOI: 10.1294/jes.27.165Google 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.
LinkedInCopy
  • 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 investigated various housekeeping genes to identify the ones with the most stable expression in the equine kidney, with the aim of normalising gene expression data in RT-qPCR experiments. The study found that the YWHAZ and HPRT1 genes showed the greatest stability, suggesting they are the most suitable for use in such experiments on equine kidney.

Objective and Methodology of Study

  • The main objective of this study was to discover the most stably expressed housekeeping genes (HKGs) in the equine kidney. These HKGs are vital in quantitative gene expression studies for standardising and evaluating the relative expression of target genes.
  • To achieve this, the researchers examined numerous HKGs including 18S rRNA, 28S rRNA, RPL32, B2M, GAPDH, SDHA, YWHAZ, and HPRT1. This selection of genes is not unique and will differ between organisms and tissues.
  • Regulating and stabilising data for these HKGs were carried out through two software packages: geNorm and NormFinder.

Findings of the Study

  • After performing the evaluations through the mentioned software, the study found that the YWHAZ and HPRT1 genes indicated the lowest stability values according to geNorm (with M values of 0.31 and 0.32 respectively).
  • The same genes also provided the best pairwise stability value when analysed using NormFinder (with a geNorm V value of 0.085).
  • Given these results, the study suggests that YWHAZ and HPRT1 are the most effective HKGs to be used in RT-qPCR experiments involving the equine kidney due to their high stability.

Implication of the Findings

  • These findings are significant because choosing the optimal HKGs is crucial in conducting accurate and reliable RT-qPCR studies. Appropriate selection helps to control variables which can create variations and inaccuracies in experimental results.
  • With the identification of YWHAZ and HPRT1 as the most stable HKGs, researchers can now more reliably normalise and interpret their gene expression data from equine kidney RT-qPCR experiments.
  • This study contributes to a better understanding of equine genetics, and it could have wider implications delivering more accurate results in related gene expression and genetic studies.

Cite This Article

APA
Azarpeykan S, Dittmer KE. (2016). Evaluation of housekeeping genes for quantitative gene expression analysis in the equine kidney. J Equine Sci, 27(4), 165-168. https://doi.org/10.1294/jes.27.165

Publication

Journal of equine science
ISSN: 1340-3516
NlmUniqueID: 9503751
Country: Japan
Language: English
Volume: 27
Issue: 4
Pages: 165-168

Researcher Affiliations

Azarpeykan, Sara
  • Institute of Veterinary, Animal and Biomedical Science, Massey University, Palmerston North 4442, New Zealand.
Dittmer, Keren E
  • Institute of Veterinary, Animal and Biomedical Science, Massey University, Palmerston North 4442, New Zealand.

References

This article includes 21 references
  1. Ahn K, Bae JH, Nam KH, Lee CE, Park KD, Lee HK, Cho BW, Kim HS. Identification of reference genes for normalization of gene expression in thoroughbred and Jeju native horse (Jeju pony) tissues. Genes Genomics 2011;33:245–250.
  2. Andersen CL, Jensen JL, Ørntoft TF. Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets.. Cancer Res 2004 Aug 1;64(15):5245-50.
    pubmed: 15289330doi: 10.1158/0008-5472.can-04-0496google scholar: lookup
  3. 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.
    pmc: PMC3039571pubmed: 21272375doi: 10.1186/1471-2199-12-5google scholar: lookup
  4. Bogaert L, Van Poucke M, De Baere C, Peelman L, Gasthuys F, Martens A. Selection of a set of reliable reference genes for quantitative real-time PCR in normal equine skin and in equine sarcoids.. BMC Biotechnol 2006 Apr 27;6:24.
    pmc: PMC1484482pubmed: 16643647doi: 10.1186/1472-6750-6-24google scholar: lookup
  5. Brinkhof B, Spee B, Rothuizen J, Penning LC. Development and evaluation of canine reference genes for accurate quantification of gene expression.. Anal Biochem 2006 Sep 1;356(1):36-43.
    pubmed: 16844072doi: 10.1016/j.ab.2006.06.001google scholar: lookup
  6. Brito AB, Lima JS, Brito DC, Santana LN, Costa NN, Miranda MS, Ohashi OM, Santos RR, Domingues SF. Validation of reference genes for ovarian tissue from capuchin monkeys (Cebus apella).. Zygote 2013 May;21(2):167-71.
    pubmed: 22475447doi: 10.1017/s0967199411000748google scholar: lookup
  7. 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.
    pmc: PMC2412902pubmed: 18489742doi: 10.1186/1471-2199-9-49google scholar: lookup
  8. Feng H, Huang X, Zhang Q, Wei G, Wang X, Kang Z. Selection of suitable inner reference genes for relative quantification expression of microRNA in wheat.. Plant Physiol Biochem 2012 Feb;51:116-22.
    pubmed: 22153247doi: 10.1016/j.plaphy.2011.10.010google scholar: lookup
  9. Figueiredo MD, Salter CE, Andrietti AL, Vandenplas ML, Hurley DJ, Moore JN. Validation of a reliable set of primer pairs for measuring gene expression by real-time quantitative RT-PCR in equine leukocytes.. Vet Immunol Immunopathol 2009 Sep 15;131(1-2):65-72.
    pubmed: 19376596doi: 10.1016/j.vetimm.2009.03.013google scholar: lookup
  10. Hellemans J, Mortier G, De Paepe A, Speleman F, Vandesompele J. qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data.. Genome Biol 2007;8(2):R19.
    pmc: PMC1852402pubmed: 17291332doi: 10.1186/gb-2007-8-2-r19google scholar: lookup
  11. Huggett J, Dheda K, Bustin S, Zumla A. Real-time RT-PCR normalisation; strategies and considerations.. Genes Immun 2005 Jun;6(4):279-84.
    pubmed: 15815687doi: 10.1038/sj.gene.6364190google scholar: lookup
  12. Kayis SA, Atli MO, Kurar E, Bozkaya F, Semacan A, Aslan S, Guzeloglu A. Rating of putative housekeeping genes for quantitative gene expression analysis in cyclic and early pregnant equine endometrium.. Anim Reprod Sci 2011 May;125(1-4):124-32.
    pubmed: 21411251doi: 10.1016/j.anireprosci.2011.02.019google scholar: lookup
  13. 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.
    pmc: PMC3083352pubmed: 21486450doi: 10.1186/1756-0500-4-120google scholar: lookup
  14. Lisowski P, Pierzchała M, Gościk J, Pareek CS, Zwierzchowski L. Evaluation of reference genes for studies of gene expression in the bovine liver, kidney, pituitary, and thyroid.. J Appl Genet 2008;49(4):367-72.
    pubmed: 19029684doi: 10.1007/bf03195635google scholar: lookup
  15. Paris DB, Kuijk EW, Roelen BA, Stout TA. Establishing reference genes for use in real-time quantitative PCR analysis of early equine embryos.. Reprod Fertil Dev 2011;23(2):353-63.
    pubmed: 21211469doi: 10.1071/rd10039google scholar: lookup
  16. Penning LC, Vrieling HE, Brinkhof B, Riemers FM, Rothuizen J, Rutteman GR, Hazewinkel HA. A validation of 10 feline reference genes for gene expression measurements in snap-frozen tissues.. Vet Immunol Immunopathol 2007 Dec 15;120(3-4):212-22.
    pubmed: 17904230doi: 10.1016/j.vetimm.2007.08.006google scholar: lookup
  17. Peters IR, Peeters D, Helps CR, Day MJ. Development and application of multiple internal reference (housekeeper) gene assays for accurate normalisation of canine gene expression studies.. Vet Immunol Immunopathol 2007 May 15;117(1-2):55-66.
    pubmed: 17346803doi: 10.1016/j.vetimm.2007.01.011google scholar: lookup
  18. Pfaffl MW, Tichopad A, Prgomet C, Neuvians TP. Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper--Excel-based tool using pair-wise correlations.. Biotechnol Lett 2004 Mar;26(6):509-15.
    pubmed: 15127793doi: 10.1023/b:bile.0000019559.84305.47google scholar: lookup
  19. Silver N, Best S, Jiang J, Thein SL. Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR.. BMC Mol Biol 2006 Oct 6;7:33.
    pmc: PMC1609175pubmed: 17026756doi: 10.1186/1471-2199-7-33google scholar: lookup
  20. 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.
    pmc: PMC126239pubmed: 12184808doi: 10.1186/gb-2002-3-7-research0034google scholar: lookup
  21. Zhang YW, Davis EG, Bai J. Determination of internal control for gene expression studies in equine tissues and cell culture using quantitative RT-PCR.. Vet Immunol Immunopathol 2009 Jul 15;130(1-2):114-9.
    pubmed: 19269038doi: 10.1016/j.vetimm.2009.01.012google scholar: lookup

Citations

This article has been cited 8 times.
  1. 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
  2. Storch C, Fuhrmann H, Schoeniger A. HOX Gene Expressions in Cultured Articular and Nasal Equine Chondrocytes. Animals (Basel) 2021 Aug 30;11(9).
    doi: 10.3390/ani11092542pubmed: 34573508google scholar: lookup
  3. Dittmer KE, Heathcott RW, Marshall JC, Azarpeykan S. Expression of Phosphatonin-Related Genes in Sheep, Dog and Horse Kidneys Using Quantitative Reverse Transcriptase PCR. Animals (Basel) 2020 Oct 5;10(10).
    doi: 10.3390/ani10101806pubmed: 33027890google scholar: lookup
  4. Lee GKC, Tessier L, Bienzle D. Salivary Scavenger and Agglutinin (SALSA) Is Expressed in Mucosal Epithelial Cells and Decreased in Bronchial Epithelium of Asthmatic Horses. Front Vet Sci 2019;6:418.
    doi: 10.3389/fvets.2019.00418pubmed: 31850379google scholar: lookup
  5. Beutelstetter M, Livolsi A, Greney H, Helms P, Schmidt-Mutter C, De Melo C, Roul G, Zores F, Bolle A, Dali-Youcef N, Beaugey M, Simon A, Niederhoffer N, Regnard J, Bouhaddi M, Adamopoulos C, Schaeffer M, Sauleau E, Bousquet P. Increased expression of blood muscarinic receptors in patients with reflex syncope. PLoS One 2019;14(7):e0219598.
    doi: 10.1371/journal.pone.0219598pubmed: 31318899google scholar: lookup
  6. Niu P, Tao W, Huang F, Li X, Wang X, Wang J, Gao Q, Fang D. Amplification of Ultra-Trace DNA from Early Sheep Embryos Based on qPCR: Establishing a Gender Identification System. Biology (Basel) 2025 Aug 29;14(9).
    doi: 10.3390/biology14091144pubmed: 41007289google scholar: lookup
  7. Sharma NK, Singh P, Saha B, Bhardwaj A, Iquebal MA, Pal Y, Nayan V, Jaiswal S, Giri SK, Legha RA, Bhattacharya TK, Kumar D, Rai A. Genome wide landscaping of copy number variations for horse inter-breed variability. Anim Biotechnol 2025 Dec;36(1):2446251.
    doi: 10.1080/10495398.2024.2446251pubmed: 39791493google scholar: lookup
  8. Ivanova Z, Petrova V, Grigorova N, Vachkova E. Identification of the Reference Genes for Relative qRT-PCR Assay in Two Experimental Models of Rabbit and Horse Subcutaneous ASCs. Int J Mol Sci 2024 Feb 14;25(4).
    doi: 10.3390/ijms25042292pubmed: 38396967google scholar: lookup
Subscribe to our newsletter
Join 100,113 horse owners like you who receive our email updates on horse health and nutrition.