Analyze Diet
International journal of molecular sciences2024; 25(4); 2292; doi: 10.3390/ijms25042292

Identification of the Reference Genes for Relative qRT-PCR Assay in Two Experimental Models of Rabbit and Horse Subcutaneous ASCs.

Abstract: Obtaining accurate and reliable gene expression results in real-time RT-PCR (qRT-PCR) data analysis requires appropriate normalization by carefully selected reference genes, either a single or a combination of multiple housekeeping genes (HKGs). The optimal reference gene/s for normalization should demonstrate stable expression across varying conditions to diminish potential influences on the results. Despite the extensive database available, research data are lacking regarding the most appropriate HKGs for qRT-PCR data analysis in rabbit and horse adipose-derived stem cells (ASCs). Therefore, in our study, we comprehensively assessed and compared the suitability of some widely used HKGs, employing RefFinder and NormFinder, two extensively acknowledged algorithms for robust data interpretation. The rabbit and horse ASCs were obtained from subcutaneous stromal vascular fraction. ASCs were induced into tri-lineage differentiation, followed by the eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) treatment of the adipose-differentiated rabbit ASCs, while horse experimental groups were formed based on adipogenic, osteogenic, and chondrogenic differentiation. At the end of the experiment, the total mRNA was obtained and used for the gene expression evaluation of the observed factors. According to our findings, glyceraldehyde 3-phosphate dehydrogenase was identified as the most appropriate endogenous control gene for rabbit ASCs, while hypoxanthine phosphoribosyltransferase was deemed most suitable for horse ASCs. The obtained results underscore that these housekeeping genes exhibit robust stability across diverse experimental conditions, remaining unaltered by the treatments. In conclusion, the current research can serve as a valuable baseline reference for experiments evaluating gene expression in rabbit and horse ASCs. It highlights the critical consideration of housekeeping gene abundance and stability in qPCR experiments, emphasizing the need for an individualized approach tailored to the specific requirements of the study.
Publication Date: 2024-02-14 PubMed ID: 38396967PubMed Central: PMC10889259DOI: 10.3390/ijms25042292Google 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.
  • 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.

Overview

  • This study identifies the most stable reference genes for normalizing qRT-PCR data in adipose-derived stem cells (ASCs) from rabbits and horses under various experimental conditions.
  • The researchers evaluated common housekeeping genes to ensure accurate gene expression analysis in these specific stem cell models.

Introduction and Importance of Reference Genes

  • qRT-PCR is a widely-used technique for measuring gene expression levels, but data accuracy depends heavily on normalization.
  • Normalization is done using reference genes, typically housekeeping genes (HKGs), which should have consistent expression across different samples and conditions.
  • Choosing inappropriate reference genes can lead to misleading or incorrect results.
  • There is limited information about the best reference genes for adipose-derived stem cells from rabbits and horses, which are increasingly used in regenerative medicine research.

Experimental Setup

  • Adipose-derived stem cells (ASCs) were isolated from the subcutaneous tissue of rabbits and horses.
  • Rabbit ASCs were induced to differentiate into three lineages (tri-lineage differentiation) and then treated with eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), fatty acids relevant to cell function and inflammation.
  • Horse ASCs underwent adipogenic, osteogenic, and chondrogenic differentiation, forming multiple experimental groups based on these lineages.
  • Total mRNA was extracted after treatments/differentiation for gene expression analysis.

Selection and Evaluation of Housekeeping Genes

  • The study tested several widely-used housekeeping genes for their stability in both rabbit and horse ASCs under these experimental conditions.
  • Two computational algorithms, RefFinder and NormFinder, were used to analyze and rank the stability of these candidate reference genes.
  • These algorithms assess gene stability by integrating multiple statistical methods, providing a robust evaluation of gene expression consistency.

Key Findings

  • For rabbit ASCs, glyceraldehyde 3-phosphate dehydrogenase (GAPDH) showed the most stable expression and is recommended as the best endogenous control gene for normalization.
  • For horse ASCs, hypoxanthine phosphoribosyltransferase (HPRT) was found to be the most suitable reference gene due to its consistent expression.
  • Both identified genes remained stable despite different treatments or differentiation protocols, implying their reliability for future experiments.

Implications and Conclusions

  • The research provides a validated baseline for selecting appropriate reference genes in qRT-PCR experiments involving rabbit and horse ASCs.
  • It underscores the necessity of validating reference genes for each specific experimental model rather than assuming universal stability.
  • This individualized approach improves the accuracy and reliability of gene expression studies in stem cell research and potentially other veterinary or biomedical applications involving these species.
  • Researchers working with adipose-derived stem cells from rabbits or horses can use these findings to better design their gene expression analyses, reducing variability and improving reproducibility.

Cite This Article

APA
Ivanova Z, Petrova V, Grigorova N, Vachkova E. (2024). Identification of the Reference Genes for Relative qRT-PCR Assay in Two Experimental Models of Rabbit and Horse Subcutaneous ASCs. Int J Mol Sci, 25(4), 2292. https://doi.org/10.3390/ijms25042292

Publication

ISSN: 1422-0067
NlmUniqueID: 101092791
Country: Switzerland
Language: English
Volume: 25
Issue: 4
PII: 2292

Researcher Affiliations

Ivanova, Zhenya
  • Department of Pharmacology, Animal Physiology, Biochemistry and Chemistry, Faculty of Veterinary Medicine, Trakia University, 6000 Stara Zagora, Bulgaria.
Petrova, Valeria
  • Department of Pharmacology, Animal Physiology, Biochemistry and Chemistry, Faculty of Veterinary Medicine, Trakia University, 6000 Stara Zagora, Bulgaria.
Grigorova, Natalia
  • Department of Pharmacology, Animal Physiology, Biochemistry and Chemistry, Faculty of Veterinary Medicine, Trakia University, 6000 Stara Zagora, Bulgaria.
Vachkova, Ekaterina
  • Department of Pharmacology, Animal Physiology, Biochemistry and Chemistry, Faculty of Veterinary Medicine, Trakia University, 6000 Stara Zagora, Bulgaria.

MeSH Terms

  • Horses
  • Rabbits
  • Animals
  • Real-Time Polymerase Chain Reaction
  • Genes, Essential
  • Cell Differentiation
  • Glyceraldehyde-3-Phosphate Dehydrogenases
  • Adipogenesis
  • Reference Standards
  • Gene Expression Profiling / methods

Grant Funding

  • Project No 09/23, and the Ph.D. Fellowship of Dr. Valeria Petrova / Trakia University

Conflict of Interest Statement

The authors declare no conflicts of interest.

References

This article includes 63 references
  1. Ginzinger DG. Gene quantification using real-time quantitative PCR: An emerging technology hits the mainstream.. Exp. Hematol. 2002;30:503–512.
    doi: 10.1016/S0301-472X(02)00806-8pubmed: 12063017google scholar: lookup
  2. Dheda K, Huggett JF, Bustin SA, Johnson MA, Rook G, Zumla A. Validation of housekeeping genes for normalizing RNA expression in real-time PCR.. Biotechniques 2004;37:112–119.
    doi: 10.2144/04371RR03pubmed: 15283208google scholar: lookup
  3. Nestorov J, Matić G, Elaković I, Tanić N. Gene expression studies: How to obtain accurate and reliable data by quantitative real-time RT PCR.. J. Med. Biochem. 2013;32:325–338.
    doi: 10.2478/jomb-2014-0001google scholar: lookup
  4. Eisenberg E, Levanon EY. Human housekeeping genes, revisited.. Trends Genet. 2013;29:569–574.
    doi: 10.1016/j.tig.2013.05.010pubmed: 23810203google scholar: lookup
  5. Suzuki T, Higgins PJ, Crawford DR. Control selection for RNA quantitation.. Biotechniques 2000;29:332–337.
    doi: 10.2144/00292rv02pubmed: 10948434google scholar: lookup
  6. You S, Cao K, Chen C, Li Y, Wu J, Zhu G, Fang W, Wang X, Wang L. Selection and validation reference genes for qRT-PCR normalization in different cultivars during fruit ripening and softening of peach (Prunus persica). Sci. Rep. 2021;11:7302.
    doi: 10.1038/s41598-021-86755-5pmc: PMC8012606pubmed: 33790378google scholar: lookup
  7. 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;64:5245–5250.
    doi: 10.1158/0008-5472.CAN-04-0496pubmed: 15289330google scholar: lookup
  8. 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;26:509–515.
  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;3:research0034.1.
  10. Xie F, Xiao P, Chen D, Xu L, Zhang B. miRDeepFinder: A miRNA analysis tool for deep sequencing of plant small RNAs.. Plant Mol. Biol. 2012;80:75–84.
    doi: 10.1007/s11103-012-9885-2pubmed: 22290409google scholar: lookup
  11. Song J, Cho J, Park J, Hwang JH. Identification and validation of stable reference genes for quantitative real time PCR in different minipig tissues at developmental stages.. BMC Genom. 2022;23:585.
    doi: 10.1186/s12864-022-08830-zpmc: PMC9374586pubmed: 35962323google scholar: lookup
  12. Tsotetsi TN, Collins NE, Oosthuizen MC, Sibeko-Matjila KP. Selection and evaluation of housekeeping genes as endogenous controls for quantification of mRNA transcripts in Theileria parva using quantitative real-time polymerase chain reaction (qPCR). PLoS ONE 2018;13:0196715.
  13. De Jonge HJM, Fehrmann RSN, de Bont ESJM, Hofstra RMW, Gerbens F, Kamps WA, de Vries EGE, van der Zee AGJ, te Merrman GJ, ter Elst A. Evidence based selection of housekeeping genes.. PLoS ONE 2007;2:e898.
  14. Guaita-Cespedes M, Grillo-Risco R, Hidalgo MR, Fernández-Veledo S, Burks DJ, de la Iglesia-Vayá M, Galan A, Garcia-Garcia F. Deciphering the sex bias in housekeeping gene expression in adipose tissue: A comprehensive meta-analysis of transcriptomic studies.. Biol. Sex Differ. 2023;14:20.
    doi: 10.1186/s13293-023-00506-xpmc: PMC10114345pubmed: 37072826google scholar: lookup
  15. Meyer-Siegler K, Mauro DJ, Seal G, Wurzer J, Deriel JK, Sirover MA. A human nuclear uracil DNA glycosylase is the 37-kDa subunit of glyceraldehyde-3-phosphate dehydrogenase.. Proc. Natl. Acad. Sci. USA 1991;88:8460–8464.
    doi: 10.1073/pnas.88.19.8460pmc: PMC52528pubmed: 1924305google scholar: lookup
  16. Singh R., Green M.R. Sequence-specific binding of transfer RNA by glyceraldehyde-3-phosphate dehydrogenase. Science. 1993;259:365–368. doi: 10.1126/science.8420004.
    doi: 10.1126/science.8420004pubmed: 8420004google scholar: lookup
  17. Tisdale E.J. Glyceraldehyde-3-phosphate dehydrogenase is required for vesicular transport in the early secretory pathway. J. Biol. Chem. 2001;276:2480–2486. doi: 10.1074/jbc.M007567200.
    doi: 10.1074/jbc.M007567200pubmed: 11035021google scholar: lookup
  18. Tarze A., Deniaud A., Le Bras M., Maillier E., Mollé D., Larochette N., Zamzami N., Jan G., Kroemer G., Brenner C. GAPDH, a novel regulator of the pro-apoptotic mitochondrial membrane permeabilization. Oncogene. 2007;26:2606–2620. doi: 10.1038/sj.onc.1210074.
    doi: 10.1038/sj.onc.1210074pubmed: 17072346google scholar: lookup
  19. Hara M.R., Agrawal N., Kim S.F., Cascio M.B., Fujimuro M., Ozeki Y., Takahashi M., Cheah J.H., Tankou S.K., Hester L.D., et al. S-nitrosylated GAPDH initiates apoptotic cell death by nuclear translocation following Siah1 binding. Nat. Cell Biol. 2005;7:665–674. doi: 10.1038/ncb1268.
    doi: 10.1038/ncb1268pubmed: 15951807google scholar: lookup
  20. Wilson J.M., Tarr G.E., Kelley W.N. Human hypoxanthine (guanine) phosphoribosyltransferase: An amino acid substitution in a mutant form of the enzyme isolated from a patient with gout. Proc. Nat. Acad. Sci. USA. 1983;80:870–873. doi: 10.1073/pnas.80.3.870.
    doi: 10.1073/pnas.80.3.870pmc: PMC393482pubmed: 6572373google scholar: lookup
  21. Stout J.T., Caskey C.T. HPRT: Gene structure, expression, and mutation. Annu. Rev. Genet. 1985;19:127–148. doi: 10.1146/annurev.ge.19.120185.001015.
  22. Becerra A., Lazcano A. The role of gene duplication in the evolution of purine nucleotide salvage pathways. Orig. Life Evol. Biosphere. 1998;28:539–553. doi: 10.1023/A:1006500327962.
    doi: 10.1023/A:1006500327962pubmed: 9742728google scholar: lookup
  23. Yamada H., Chen D., Monstein H.J., Hakanson R. Effects of fasting on the expression of gastrin, cholecystokinin, and somatostatin genes and of various housekeeping genes in the pancreas and upper digestive tract of rats. Biochem. Biophys. Res. Commun. 1997;231:835–838. doi: 10.1006/bbrc.1997.6198.
    doi: 10.1006/bbrc.1997.6198pubmed: 9070905google scholar: lookup
  24. Ferreira-Cerca S., Pöll G., Gleizes P.E., Tschochner H., Milkereit P. Roles of eukaryotic ribosomal proteins in maturation and transport of pre-18S rRNA and ribosome function. Mol. Cell. 2005;20:263–275. doi: 10.1016/j.molcel.2005.09.005.
    doi: 10.1016/j.molcel.2005.09.005pubmed: 16246728google scholar: lookup
  25. Ferguson B.S., Nam H., Hopkins R.G., Morrison R.F. Impact of reference gene selection for target gene normalization on experimental outcome using real-time qRT-PCR in adipocytes. PLoS ONE. 2010;5:e15208. doi: 10.1371/journal.pone.0015208.
  26. Gong H., Sun L., Chen B., Han Y., Pang J., Wu W., Qi R., Zhang T.M. Evaluation of candidate reference genes for RT-qPCR studies in three metabolism related tissues of mice after caloric restriction. Sci. Rep. 2016;6:38513. doi: 10.1038/srep38513.
    doi: 10.1038/srep38513pmc: PMC5138604pubmed: 27922100google scholar: lookup
  27. Almeida-Oliveira F., Leandro J.G., Ausina P., Sola-Penna M., Majerowicz D. Reference genes for quantitative PCR in the adipose tissue of mice with metabolic disease. Biomed. Pharmacother. 2017;88:948–955. doi: 10.1016/j.biopha.2017.01.091.
    doi: 10.1016/j.biopha.2017.01.091pubmed: 28178626google scholar: lookup
  28. Baer P.C., Geiger H. Adipose-derived mesenchymal stromal/stem cells: Tissue localization, characterization, and heterogeneity. Stem Cells Int. 2012;2012:812693. doi: 10.1155/2012/812693.
    doi: 10.1155/2012/812693pmc: PMC3345279pubmed: 22577397google scholar: lookup
  29. Vidal M.A., Kilroy G.E., Lopez M.J., Johnson J.R., Moore R.M., Gimble J.M. Characterization of equine adipose tissue-derived stromal cells: Adipogenic and osteogenic capacity and comparison with bone marrow-derived mesenchymal stromal cells. Vet. Surg. 2007;36:613–622. doi: 10.1111/j.1532-950X.2007.00313.x.
  30. Corsini N.S., Knoblich J.A. Human organoids: New strategies and methods for analyzing human development and disease. Cell. 2022;185:2756–2769. doi: 10.1016/j.cell.2022.06.051.
    doi: 10.1016/j.cell.2022.06.051pubmed: 35868278google scholar: lookup
  31. Tirpáková M., Vašíček J., Svoradová A., Baláži A., Tomka M., Bauer M., Makarevich A., Chrenek P. Phenotypical characterization and neurogenic differentiation of rabbit adipose tissue-derived mesenchymal stem cells. Genes. 2021;12:431. doi: 10.3390/genes12030431.
    doi: 10.3390/genes12030431pmc: PMC8002684pubmed: 33802902google scholar: lookup
  32. Bukowska J., Szóstek-Mioduchowska A.Z., Kopcewicz M., Walendzik K., Machcińska S., Gawrońska-Kozak B. Adipose-derived stromal/stem cells from large animal models: From basic to applied science. Stem Cell Rev. Rep. 2021;17:719–738. doi: 10.1007/s12015-020-10049-y.
    doi: 10.1007/s12015-020-10049-ypmc: PMC8166671pubmed: 33025392google scholar: lookup
  33. Al Naem M., Bourebaba L., Kucharczyk K., Röcken M., Marycz K. Therapeutic mesenchymal stromal stem cells: Isolation, characterization and role in equine regenerative medicine and metabolic disorders. Stem Cell Rev. Rep. 2020;16:301–322. doi: 10.1007/s12015-019-09932-0.
    doi: 10.1007/s12015-019-09932-0pubmed: 31797146google scholar: lookup
  34. Ribitsch I., Baptista P.M., Lange-Consiglio A., Melotti L., Patruno M., Jenner F., Schnabl-Feichter E., Dutton L., Connolly D.J., van Steenbeek F., et al. Large animal models in regenerative medicine and tissue engineering: To do or not to do. Front. Bioeng. Biotechnol. 2020;8:972. doi: 10.3389/fbioe.2020.00972.
    doi: 10.3389/fbioe.2020.00972pmc: PMC7438731pubmed: 32903631google scholar: lookup
  35. Gugjoo M.B., Sharma G.T. Equine mesenchymal stem cells: Properties, sources, characterization, and potential therapeutic applications. J. Equine Vet. Sci. 2019;72:16–27. doi: 10.1016/j.jevs.2018.10.007.
    doi: 10.1016/j.jevs.2018.10.007pubmed: 30929778google scholar: lookup
  36. Matsuhisa F., Kitajima S., Nishijima K., Akiyoshi T., Morimoto M., Fan J. Transgenic rabbit models: Now and the future. Appl. Sci. 2020;10:7416. doi: 10.3390/app10217416.
    doi: 10.3390/app10217416google scholar: lookup
  37. Bacakova L., Zarubova J., Travnickova M., Musilkova J., Pajorova J., Slepicka P., Kasalkova N.S., Svorcik V., Kolska Z., Motarjemi H., et al. Stem cells: Their source, potency and use in regenerative therapies with focus on adipose-derived stem cells—A review. Biotechnol. Adv. 2018;36:1111–1126. doi: 10.1016/j.biotechadv.2018.03.011.
  38. Fraser J.K., Wulur I., Alfonso Z., Hedrick M.H. Fat tissue: An underappreciated source of stem cells for biotechnology. Trends Biotechnol. 2006;24:150–154. doi: 10.1016/j.tibtech.2006.01.010.
    doi: 10.1016/j.tibtech.2006.01.010pubmed: 16488036google scholar: lookup
  39. Farré-Guasch E., Bravenboer N., Helder M.N., Schulten E.A., Ten Bruggenkate C.M., Klein-Nulend J. Blood vessel formation and bone regeneration potential of the stromal vascular fraction seeded on a calcium phosphate scaffold in the human maxillary sinus floor elevation model. Materials. 2018;11:161. doi: 10.3390/ma11010161.
    doi: 10.3390/ma11010161pmc: PMC5793659pubmed: 29361686google scholar: lookup
  40. Scioli M.G., Storti G., D’Amico F., Gentile P., Kim B.S., Cervelli V., Orlandi A. Adipose-derived stem cells in cancer progression: New perspectives and opportunities. Int. J. Mol. Sci. 2019;20:3296. doi: 10.3390/ijms20133296.
    doi: 10.3390/ijms20133296pmc: PMC6651808pubmed: 31277510google scholar: lookup
  41. Zuk P.A., Zhu M., Mizuno H., Huang J.J., Futrell W., Katz A.J., Benhaim P., Lorenz H.P., Hedrick M.H. Multilineage cells from human adipose tissue: Implications for cell-based therapies. Tissue Eng. 2001;7:211–228. doi: 10.1089/107632701300062859.
    doi: 10.1089/107632701300062859pubmed: 11304456google scholar: lookup
  42. Quiroz F.G., Posada O.M., Gallego-Perez D., Higuita-Castro N., Sarassa C., Hansford D.J., Agudelo-Florez P., López L.E. Housekeeping gene stability influences the quantification of osteogenic markers during stem cell differentiation to the osteogenic lineage. Cytotechnology. 2010;62:109–120. doi: 10.1007/s10616-010-9265-1.
    doi: 10.1007/s10616-010-9265-1pmc: PMC2873986pubmed: 20396946google scholar: lookup
  43. Wiraja C., Yeo D.C., Chong M.S., Xu C. Nanosensors for continuous and noninvasive monitoring of mesenchymal stem cell osteogenic differentiation. Small. 2016;12:1342–1350. doi: 10.1002/smll.201502047.
    doi: 10.1002/smll.201502047pubmed: 26756453google scholar: lookup
  44. Zainuddin A., Chua K.H., Abdul Rahim N., Makpol S. Effect of experimental treatment on GAPDH mRNA expression as a housekeeping gene in human diploid fibroblasts. BMC Mol. Biol. 2008;9:59. doi: 10.1186/1471-2199-11-59.
    doi: 10.1186/1471-2199-11-59pmc: PMC2930638pubmed: 20707929google scholar: lookup
  45. Zhang J., Tang H., Zhang Y., Deng R., Shao L., Liu Y., Li F., Wang X., Zhou L. Identification of suitable reference genes for quantitative RT-PCR during 3T3-L1 adipocyte differentiation. Int. J. Mol. Med. 2014;33:1209–1218. doi: 10.3892/ijmm.2014.1695.
    doi: 10.3892/ijmm.2014.1695pubmed: 24626784google scholar: lookup
  46. Salmerón C., Riera-Heredia N., Gutiérrez J., Navarro I., Capilla E. Adipogenic gene expression in gilthead sea bream mesenchymal stem cells from different origin. Front. Endocrinol. 2016;7:113. doi: 10.3389/fendo.2016.00113.
    doi: 10.3389/fendo.2016.00113pmc: PMC4992700pubmed: 27597840google scholar: lookup
  47. Krautgasser C., Mandl M., Hatzmann F.M., Waldegger P., Mattesich M., Zwerschke W. Reliable reference genes for expression analysis of proliferating and adipogenically differentiating human adipose stromal cells. Cell. Mol. Biol. Lett. 2019;24:14. doi: 10.1186/s11658-019-0140-6.
    doi: 10.1186/s11658-019-0140-6pmc: PMC6377720pubmed: 30815013google scholar: lookup
  48. Gorzelniak K., Janke J., Engeli S., Sharma A.M. Validation of endogenous controls for gene expression studies in human adipocytes and preadipocytes. Horm. Metab. Res. 2001;33:625–627. doi: 10.1055/s-2001-17911.
    doi: 10.1055/s-2001-17911pubmed: 11607884google scholar: lookup
  49. Fink T., Lund P., Pilgaard L., Rasmussen J.G., Duroux M., Zachar V. Instability of standard PCR reference genes in adipose-derived stem cells during propagation, differentiation and hypoxic exposure. BMC Mol. Biol. 2008;9:98. doi: 10.1186/1471-2199-9-98.
    doi: 10.1186/1471-2199-9-98pmc: PMC2585587pubmed: 18976469google scholar: lookup
  50. Ebrahimi R., Toolabi K., Jannat Ali Pour N., Mohassel Azadi S., Bahiraee A., Zamani-Garmsiri F., Emamgholipour S. Adipose tissue gene expression of long non-coding RNAs; MALAT1, TUG1 in obesity: Is it associated with metabolic profile and lipid homeostasis-related genes expression? Diabetol. Metab. Syndr. 2020;12:36. doi: 10.1186/s13098-020-00544-0.
    doi: 10.1186/s13098-020-00544-0pmc: PMC7191796pubmed: 32368256google scholar: lookup
  51. Bourebaba L., Kornicka-Garbowska K., Al Naem M., Röcken M., Łyczko J., Marycz K. MSI-1436 improves EMS adipose derived progenitor stem cells in the course of adipogenic differentiation through modulation of ER stress, apoptosis, and oxidative stress. Stem Cell Res. Ther. 2021;12:97. doi: 10.1186/s13287-020-02102-x.
    doi: 10.1186/s13287-020-02102-xpmc: PMC7860037pubmed: 33536069google scholar: lookup
  52. El-Gindy Y.M., Hafsa S.H.A., El-Deeb N.M. The expression of liver TNF-α gene, liver and small intestine histology of thermal stressed growing rabbits affected by allicin and lycopene. J. Therm. Biol. 2023;113:103521. doi: 10.1016/j.jtherbio.2023.103521.
  53. Radtke C.L., Nino-Fong R., Gonzalez B.P.E., Stryhn H., McDuffee L.A. Characterization and osteogenic potential of equine muscle tissue–and periosteal tissue–derived mesenchymal stem cells in comparison with bone marrow–and adipose tissue–derived mesenchymal stem cells. Am. J. Vet. Res. 2013;74:790–800. doi: 10.2460/ajvr.74.5.790.
    doi: 10.2460/ajvr.74.5.790pubmed: 23627394google scholar: lookup
  54. Azarpeykan S., Dittmer K.E. Evaluation of housekeeping genes for quantitative gene expression analysis in the equine kidney. J. Equine Sci. 2016;27:165–168. doi: 10.1294/jes.27.165.
    doi: 10.1294/jes.27.165pmc: PMC5155135pubmed: 27974876google scholar: lookup
  55. Hotham W.E., Thompson C., Szu-Ting L., Henson F.M.D. The anti-inflammatory effects of equine bone marrow stem cell-derived extracellular vesicles on autologous chondrocytes. Vet. Rec. Open. 2021;8:22. doi: 10.1002/vro2.22.
    doi: 10.1002/vro2.22pmc: PMC8580791pubmed: 34795904google scholar: lookup
  56. Jarazo J.M. Master’s Thesis. Louisiana State University and Agricultural & Mechanical College; Baton Rouge, LA, USA: 2014. Effect of Tissue Source on Adult Equine Multipotent Stromal Cell Pluripotency Induction Treatment with Synthetic mRNA.
  57. Bruynsteen L., Erkens T., Peelman L.J., Ducatelle R., Janssens G.P.J., Harris P.A., Hesta M. Expression of inflammation-related genes is associated with adipose tissue location in horses. BMC Vet. Res. 2013;9:240. doi: 10.1186/1746-6148-9-240.
    doi: 10.1186/1746-6148-9-240pmc: PMC4220830pubmed: 24295090google scholar: lookup
  58. Dheda K., Huggett J.F., Chang J.S., Kim L.U., Bustin S.A., Johnson M.A., Rook G.A.W., Zumla A. The implications of using an inappropriate reference gene for real-time reverse transcription PCR data normalization. Anal. Biochem. 2005;344:141–143. doi: 10.1016/j.ab.2005.05.022.
    doi: 10.1016/j.ab.2005.05.022pubmed: 16054107google scholar: lookup
  59. Nazari F., Parham A., Maleki A.F. GAPDH, β-actin and β2-microglobulin, as three common reference genes, are not reliable for gene expression studies in equine adipose-and marrow-derived mesenchymal stem cells. J. Anim. Sci. Technol. 2015;57:18. doi: 10.1186/s40781-015-0050-8.
    doi: 10.1186/s40781-015-0050-8pmc: PMC4540241pubmed: 26290738google scholar: lookup
  60. De Spiegelaere W., Dern-Wieloch J., Weigel R., Schumacher V., Schorle H., Nettersheim D., Bergmann M., Brehm R., Kliesch S., Vandekerckhove L., et al. Reference gene validation for RT-qPCR, a note on different available software packages. PLoS ONE. 2015;10:e0122515. doi: 10.1371/journal.pone.0122515.
  61. Raabe O., Shell K., Würtz A., Reich C.M., Wenisch S., Arnhold S. Further insights into the characterization of equine adipose tissue-derived mesenchymal stem cells. Vet. Res. Commun. 2011;35:355–365. doi: 10.1007/s11259-011-9480-z.
    doi: 10.1007/s11259-011-9480-zpubmed: 21614641google scholar: lookup
  62. Vachkova E., Bosnakovski D., Yonkova P., Grigorova N., Ivanova Z., Todorov P., Penchev G., Milanova A., Simeonova G., Stanilova S., et al. Adipogenic potential of stem cells derived from rabbit subcutaneous and visceral adipose tissue in vitro. Vitr. Cell. Dev. Biol.-Anim. 2016;52:829–837. doi: 10.1007/s11626-016-0048-7.
    doi: 10.1007/s11626-016-0048-7pubmed: 27173612google scholar: lookup
  63. Arnhold S., Elashry M.I., Klymiuk M.C., Geburek F. Investigation of Stemness and Multipotency of Equine Adipose-Derived Mesenchymal Stem Cells (ASCs) from Different Fat Sources in Comparison with Lipoma. Stem Cell Res. Ther. 2019;10:309. doi: 10.1186/s13287-019-1429-0.
    doi: 10.1186/s13287-019-1429-0pmc: PMC6805636pubmed: 31640774google scholar: lookup

Citations

This article has been cited 2 times.
  1. Vachkova E, Arnhold S, Petrova V, Heimann M, Koynarski T, Simeonova G, Piperkov P. Transcriptional Factors Related to Cellular Kinetics, Apoptosis, and Tumorigenicity in Equine Adipose-Derived Mesenchymal Stem Cells (ASCs) Are Influenced by the Age of the Donors.. Animals (Basel) 2025 Jun 28;15(13).
    doi: 10.3390/ani15131910pubmed: 40646808google scholar: lookup
  2. Chen YP, Hu CC, Tsai S, Wen ZH, Lin C. Identification of housekeeping gene for future studies exploring effects of cryopreservation on gene expression in shrimp.. Sci Rep 2025 Apr 1;15(1):11046.
    doi: 10.1038/s41598-025-95258-6pubmed: 40169849google scholar: lookup