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Home / Equine Research Bank / BMC Vet Res / Investigation of gene stability in equine luteal tissue duri...
BMC veterinary research2026; 22(1); 84; doi: 10.1186/s12917-025-05241-6

Investigation of gene stability in equine luteal tissue during mid-diestrus phase and early pregnancy – Research Article.

Abstract: Real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) is a technique that allows for the semi-quantification of mRNA transcripts present within a tissue of interest. Differences in the relative abundance of mRNA between samples detected by RT-qPCR require normalization with a reference gene or genes whose transcript abundance is stable within the tissue of interest independent of experimental conditions. In the field of equine reproductive studies, ACTB, GAPDH and B2M genes are the most widely used as reference genes for the normalization of RT-qPCR results. However, recent studies have demonstrated that these genes may have drastically varied expression levels in different tissues and various physiological states. Therefore, the aim of this study was to examine different putative reference genes in equine corpus luteum samples in pregnant and non-pregnant, mid-diestrus, animals. The stability of genetic expression was evaluated via three stability software analyses (GeNorm, NormFinder and BestKeeper). We hypothesized that the commonly used reference genes (ACTB, GAPDH and B2M) would be the most stably expressed genes in equine corpus luteum samples in both pregnant and non-pregnant mares. Results: COX4I1 and SRP14 were both found to be among the top three most stable genes of all samples for all methods, though the ranking of stability changed depending on the software used. When assessing the least stably expressed genes, the commonly used reference genes were frequently identified across the three software. Conclusions: Commonly used reference genes (ACTB, GAPDH, B2M) for RT-qPCR normalization were amongst the least stably expressed genes in equine corpus luteum samples of pregnant and nonpregnant mares at days 11 and 13 of gestation. The most stably expressed putative reference genes using 3 different analysis modalities were SRP14, COX4I1, RPL13 and RPL4. Exploration of putative reference genes should be considered when investigating dynamic endocrine organs such as those used in reproductive studies.
© 2026. The Author(s).
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Publication Date: 2026-01-09 PubMed ID: 41507934PubMed Central: PMC12882240DOI: 10.1186/s12917-025-05241-6Google 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.

Overview

  • This study investigated the stability of commonly used and alternative reference genes for normalizing gene expression data in the corpus luteum tissue of pregnant and non-pregnant mares during the mid-diestrus phase using RT-qPCR.
  • The research found that widely used reference genes (ACTB, GAPDH, B2M) were not stably expressed, while other genes like SRP14 and COX4I1 showed greater stability, suggesting alternative reference genes should be used for accurate normalization in equine reproductive studies.

Background and Importance

  • Real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) is a sensitive method used for measuring mRNA levels, which reflect gene expression, in various tissues.
  • Data from RT-qPCR requires normalization against reference genes—genes whose expression levels are consistent and unaffected by experimental conditions or physiological states—to ensure accurate comparison between samples.
  • In equine reproductive research, the reference genes ACTB (beta-actin), GAPDH (glyceraldehyde 3-phosphate dehydrogenase), and B2M (beta-2-microglobulin) are commonly used for this normalization.
  • However, prior research indicates that these common reference genes often vary significantly depending on the tissue type and physiological context, which can lead to inaccurate data interpretation.

Objective

  • To evaluate and compare the expression stability of several putative reference genes, including common and novel candidates, in equine corpus luteum tissue during mid-diestrus phase for both pregnant and non-pregnant mares.
  • To identify the most appropriate reference genes for RT-qPCR normalization in studies involving dynamic endocrine tissues such as the corpus luteum.

Methodology

  • Corpus luteum samples were collected from pregnant and non-pregnant mares at mid-diestrus, specifically on days 11 and 13 of gestation.
  • A set of reference genes including common ones (ACTB, GAPDH, B2M) and putative stable candidates (COX4I1, SRP14, RPL13, RPL4, among others) were assessed for expression stability.
  • Expression stability was analyzed using three specialized algorithms/software:
    • GeNorm – evaluates gene stability based on pairwise variation between genes
    • NormFinder – identifies stable genes considering intra- and inter-group variation
    • BestKeeper – computes stability by analyzing standard deviations and correlation coefficients

Key Findings

  • COX4I1 and SRP14 consistently ranked among the top three most stable reference genes across all three software analyses.
  • There was some variation in the ranking order depending on the analysis method used, but SRP14, COX4I1, RPL13, and RPL4 emerged as the most stable overall.
  • The commonly used reference genes ACTB, GAPDH, and B2M were frequently found among the least stable genes, indicating their expression fluctuates significantly in corpus luteum tissue during this phase and physiological state.

Conclusions and Implications

  • Common reference genes traditionally used for normalization in equine luteal tissue RT-qPCR are not stably expressed during mid-diestrus and early pregnancy stages.
  • Using unstable reference genes like ACTB, GAPDH, and B2M can lead to inaccurate normalization and potentially misinterpret gene expression data in equine reproductive studies.
  • Genes such as SRP14, COX4I1, RPL13, and RPL4 should be considered as superior normalization controls in luteal tissue to improve the reliability and accuracy of RT-qPCR results.
  • The study highlights the necessity of validating reference genes for each specific tissue and physiological condition, especially in dynamic endocrine tissues such as the corpus luteum.

Significance for Future Research

  • Researchers studying equine reproductive biology and endocrine function should re-assess their choice of reference genes to avoid normalization errors.
  • The findings advocate for the routine evaluation of candidate reference genes in new experimental setups before data normalization in RT-qPCR studies.
  • This approach will enhance the quality and reproducibility of gene expression studies in horses and may be relevant to other species and tissues with fluctuating gene expression profiles.

Cite This Article

APA
Ramsaran LN, Byron M, Parry S, Lection J, Back B, Grenier J, Cheong SH, Diel de Amorim M. (2026). Investigation of gene stability in equine luteal tissue during mid-diestrus phase and early pregnancy – Research Article. BMC Vet Res, 22(1), 84. https://doi.org/10.1186/s12917-025-05241-6

Publication

BMC veterinary research
ISSN: 1746-6148
NlmUniqueID: 101249759
Country: England
Language: English
Volume: 22
Issue: 1
Pages: 84
PII: 84

Researcher Affiliations

Ramsaran, Leah N
  • Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA.
Byron, Michael
  • Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA.
Parry, Stephen
  • Cornell Statistical Consulting Unit, Cornell University, Ithaca, NY, USA.
Lection, Jennine
  • Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA.
  • Department of ClinicalSciences, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, USA.
Back, Bradley
  • Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA.
Grenier, Jen
  • Transcriptional Regulation and Expression Facility (TREx), Biotechnology Resource Center, Cornell University, Ithaca, NY, USA.
Cheong, Soon Hon
  • Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA.
Diel de Amorim, Mariana
  • Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA. md649@cornell.edu.

MeSH Terms

  • Animals
  • Female
  • Horses / genetics
  • Horses / physiology
  • Pregnancy
  • Corpus Luteum / metabolism
  • Diestrus / genetics
  • Real-Time Polymerase Chain Reaction / veterinary
  • Pregnancy, Animal / genetics
  • RNA, Messenger / genetics

Conflict of Interest Statement

Declarations. Ethics approval and consent to participate: All animals used in this study were from the teaching and research herd at Cornell University College of Veterinary Medicine. Animal users protocol was approved by the animal care and use committee of Cornell University (IACUC protocol #2019 − 0116). Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

References

This article includes 30 references
  1. Huggett J, Dheda K, Bustin S, Zumla A. Real-time RT-PCR normalisation; strategies and considerations.. Genes Immun 2005;6(4):6:279–84.
    pubmed: 15815687
  2. Giguère S, Prescott JF. Quantitation of equine cytokine mRNA expression by reverse transcription-competitive polymerase chain reaction.. Vet Immunol Immunopathol 1999;67:1–15.
    doi: 10.1016/S0165-2427(98)00212-8pubmed: 9950350google scholar: lookup
  3. Sakumoto R, Hayashi KG, Hosoe M, Iga K, Kizaki K, Okuda K. Gene expression profiles in the bovine corpus luteum (CL) during the estrous cycle and pregnancy: possible roles of chemokines in regulating CL function during pregnancy.. J Reprod Dev 2015;61:42.
    doi: 10.1262/jrd.2014-101pmc: PMC4354230pubmed: 25382605google scholar: lookup
  4. Leutenegger CM, Von Rechenberg B, Huder JB, Zlinsky K, Mislin C, Akens MK. Quantitative real-time PCR for equine cytokine mRNA in nondecalcified bone tissue embedded in Methyl methacrylate.. Calcif Tissue Int 1999;65:378–83.
    doi: 10.1007/s002239900717pubmed: 10541764google scholar: lookup
  5. 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;222:155–69.
    doi: 10.1016/S0022-1759(98)00193-8pubmed: 10022382google scholar: lookup
  6. 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;33:143–9.
    doi: 10.1111/j.2042-3306.2001.tb00592.xpubmed: 11266063google scholar: lookup
  7. Ainsworth DM, Appleton JA, Eicker SW, Luce R, Flaminio MJ, 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;91:61–71.
    doi: 10.1016/S0165-2427(02)00274-Xpubmed: 12507851google scholar: lookup
  8. Suzuki T, Higgins PJ, Crawford DR. Control selection for RNA quantitation.. Biotechniques 2000;29:332–7.
    doi: 10.2144/00292rv02pubmed: 10948434google scholar: lookup
  9. Glare EM, Divjak M, Bailey MJ, Walters EH. β-Actin and GAPDH housekeeping gene expression in asthmatic airways is variable and not suitable for normalising mRNA levels.. Thorax 2002;57:765–70.
    doi: 10.1136/thorax.57.9.765pmc: PMC1746418pubmed: 12200519google scholar: lookup
  10. Steele BK, Meyers C, Ozbun MA. Variable expression of some housekeeping genes during human keratinocyte differentiation.. Anal Biochem 2002;307:341–7.
    doi: 10.1016/S0003-2697(02)00045-3pubmed: 12202253google scholar: lookup
  11. Bas A, Forsberg G, Hammarström S, Hammarström ML. Utility of the housekeeping genes 18S rRNA, β-Actin and Glyceraldehyde-3-Phosphate-Dehydrogenase for normalization in Real-Time quantitative reverse Transcriptase-Polymerase chain reaction analysis of gene expression in human T lymphocytes.. Scand J Immunol 2004;59:566–73.
    doi: 10.1111/j.0300-9475.2004.01440.xpubmed: 15182252google scholar: lookup
  12. Mezera MA, Li W, Edwards AJ, Koch DJ, Beard AD, Wiltbank MC. Identification of stable genes in the corpus luteum of lactating Holstein cows in pregnancy and luteolysis: implications for selection of reverse-transcription quantitative PCR reference genes.. J Dairy Sci 2020;103:4846–57.
    doi: 10.3168/jds.2019-17526pubmed: 32229123google 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;4:120.
    doi: 10.1186/1756-0500-4-120pmc: PMC3083352pubmed: 21486450google scholar: lookup
  14. Galvão A, Wolodko K, Rebordão MR, Skarzynski D, Ferreira-Dias G. TGFB1 modulates in vitro secretory activity and viability of equine luteal cells.. Cytokine 2018;110:316–27.
    doi: 10.1016/j.cyto.2018.03.038pubmed: 29627157google scholar: lookup
  15. Diel de Amorim M, Bramer SA, Rajamanickam GD, Klein C, Card C. Endometrial and luteal gene expression of putative gene regulators of the equine maternal recognition of pregnancy.. Anim Reprod Sci 2022;245:107064.
    doi: 10.1016/j.anireprosci.2022.107064pubmed: 36087407google scholar: lookup
  16. Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.. Genome Biol 2002;3:1–12.
    doi: 10.1186/gb-2002-3-7-research0034pmc: PMC126239pubmed: 12184808google scholar: lookup
  17. 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;26:509–15.
    doi: 10.1023/B:BILE.0000019559.84305.47pubmed: 15127793google scholar: lookup
  18. Paris DBBP, Kuijk EW, Roelen BAJ, Stout TAE. Establishing reference genes for use in real-time quantitative PCR analysis of early equine embryos.. Reprod Fertil Dev 2011;23:353–63.
    doi: 10.1071/RD10039pubmed: 21211469google scholar: lookup
  19. Kuijk EW, Du Puy L, Van Tol HTA, Haagsman HP, Colenbrander B, Roelen BAJ. Validation of reference genes for quantitative RT-PCR studies in Porcine oocytes and preimplantation embryos.. BMC Dev Biol 2007;7:1–8.
    doi: 10.1186/1471-213X-7-58pmc: PMC1896162pubmed: 17540017google scholar: lookup
  20. SRP14 signal. Recognition particle 14 [Homo sapiens (human)] - Gene - NCBI. https://www.ncbi.nlm.nih.gov/gene/6124.
  21. Love MI, Huber W, Anders S. Moderated Estimation of fold change and dispersion for RNA-seq data with DESeq2.. Genome Biol 2014;15:1–21.
    doi: 10.1186/s13059-014-0550-8pmc: PMC4302049pubmed: 25516281google scholar: lookup
  22. COX4I1. Cytochrome c oxidase subunit 4I1 [Homo sapiens (human)] - Gene - NCBI. https://www.ncbi.nlm.nih.gov/gene?Db=gene&Cmd=DetailsSearch&Term=1327.
  23. Bioconductor - DESeq2. https://www.bioconductor.org/packages/release/bioc/html/DESeq2.html.
  24. RPL4 ribosomal. protein L4 [Homo sapiens (human)] - Gene - NCBI. https://www.ncbi.nlm.nih.gov/gene/6124.
  25. RPL13 ribosomal. Protein L13 [Homo sapiens (human)] - Gene - NCBI. https://www.ncbi.nlm.nih.gov/gene?Db=gene&Cmd=DetailsSearch&Term=6137.
  26. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S. STAR: ultrafast universal RNA-seq aligner.. Bioinformatics 2013;29:15–21.
    doi: 10.1093/bioinformatics/bts635pmc: PMC3530905pubmed: 23104886google scholar: lookup
  27. Babraham Bioinformatics - Trim. Galore! https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/.
  28. 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;64:5245–50.
    doi: 10.1158/0008-5472.CAN-04-0496pubmed: 15289330google scholar: lookup
  29. Diel de Amorim M, Nairn D, Manning S, Dedden I, Ripley E, Nielsen K. Evaluation of diagnostic utility, safety considerations, and effect on fertility of transvaginal ultrasound-guided ovarian biopsy in mares.. Theriogenology 2016;85:1030–6.
    doi: 10.1016/j.theriogenology.2015.11.013pubmed: 26719038google scholar: lookup
  30. Lection J, Wagner B, Byron M, Miller A, Rollins A, Chenier T. Inflammatory markers for differentiation of endometritis in the mare.. Equine Vet J 2024.
    doi: 10.1111/EVJ.14058pubmed: 38219734google scholar: lookup

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