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Scientific reports2025; 15(1); 30714; doi: 10.1038/s41598-025-16671-5

Decoding the amniotic membrane transcriptome during equine ascending placentitis.

Abstract: Despite its critical role in protecting the fetus, the amniotic membrane remains poorly understood in the context of disease response. The equine amniotic membrane is an important physical barrier to the amniotic compartment, and there is evidence that it may contribute to surfactant synthesis. Surfactants are essential for normal fetal lung development, and disruptions in its availability may be linked to future neonatal complications. Therefore, understanding the molecular changes that occur in fetal-maternal tissues during placentitis would clarify how this condition leads to abortion, preterm delivery, and stillbirth, and identify new strategies to manage the adverse outcomes. Thus, we used RNA sequencing, bioinformatic methods, and immunohistochemistry to characterize the equine amniotic membrane gene expression during experimentally induced ascending placentitis (placentitis group, n = 6) compared to gestationally matched control groups (control group, n = 6) at 288 days of gestation. We identified 288 differentially expressed genes (DEG) in the placentitis group compared to the control group. Placentitis was associated with the upregulation of toll-like receptors (TLR4), prostaglandin synthesis (PTGS2 and PTGES), apoptosis (MMP9 and CASP3), and hypoxia-associated genes (SOD2, BNIP3, and HMOX1). Our RNA sequencing results were supported by the visual identification of two of those proteins (TLR4 and PTGS2) in the immunohistochemistry analysis. Functional annotation revealed significant enrichment between the DEGs and the toll receptor signaling pathway, which may be a key factor negatively affecting placental functions. In conclusion, our study revealed that the amniotic membrane is not only a physical barrier but also plays an active role in immune response during ascending placentitis.
© 2025. The Author(s).
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Publication Date: 2025-08-21 PubMed ID: 40841585PubMed Central: PMC12371064DOI: 10.1038/s41598-025-16671-5Google Scholar: Lookup
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  • 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 research investigates how the gene expression in the equine amniotic membrane changes during ascending placentitis, a bacterial infection that affects the placenta and can result in pregnancy complications like abortion and stillbirth.
  • The study uses RNA sequencing and immunohistochemistry to identify key molecular pathways involved in the disease response, suggesting that the amniotic membrane actively participates in immune defense rather than just serving as a physical barrier.

Background and Importance

  • The amniotic membrane is a critical fetal-maternal tissue that protects the fetus during pregnancy.
  • Despite its importance, the molecular responses of the amniotic membrane during disease states, such as placentitis, are not well understood.
  • Equine ascending placentitis is an infection that ascends from the cervix to infect the placenta, jeopardizing fetal health and possibly causing abortion, preterm birth, or stillbirth.
  • Surfactants produced partly by the amniotic membrane are essential for fetal lung development; disruptions can lead to neonatal complications.
  • Understanding the molecular changes in amniotic membrane during placentitis could help clarify disease mechanisms and inform interventions to prevent adverse pregnancy outcomes.

Study Design and Methods

  • Sample: Pregnant mares were divided into two groups—placentitis (n=6) and control (n=6), matched by gestational age (288 days).
  • Experimental induction of ascending placentitis was performed to simulate natural disease conditions.
  • RNA sequencing (RNA-seq) was used to profile gene expression in the amniotic membranes of infected versus control animals.
  • Bioinformatic analysis identified genes with significant differential expression between placentitis and control groups.
  • Immunohistochemistry validated the protein expression of key genes identified by RNA-seq, focusing on TLR4 and PTGS2.
  • Functional annotation and pathway enrichment analyses were conducted to interpret biological processes involved.

Key Findings

  • 288 genes were found to be differentially expressed in placentitis compared to controls.
  • Upregulated genes included:
    • Toll-like receptor 4 (TLR4), a key receptor involved in the immune response to bacterial infection.
    • Prostaglandin synthesis enzymes PTGS2 (COX-2) and PTGES, which play roles in inflammation and labor induction.
    • Apoptosis-related genes such as MMP9 (matrix metalloproteinase 9) and CASP3 (caspase 3), indicating tissue remodeling and cell death.
    • Hypoxia-associated genes including SOD2 (superoxide dismutase 2), BNIP3, and HMOX1 (heme oxygenase 1), suggesting oxygen deprivation stress during infection.
  • Immunohistochemistry confirmed increased presence of TLR4 and PTGS2 proteins in the amniotic membrane of infected mares, supporting transcriptomic data.
  • Functional enrichment analysis highlighted the toll-like receptor signaling pathway as significantly activated in placentitis, implicating it in placental dysfunction and immune activation.

Implications of the Study

  • The amniotic membrane is not just a passive physical barrier but actively engages in immune defense mechanisms during ascending placentitis.
  • Activation of toll-like receptor signaling suggests the amniotic membrane detects bacterial infection and triggers inflammatory pathways that could contribute to adverse pregnancy outcomes.
  • The involvement of prostaglandin synthesis and apoptotic pathways indicates possible mechanisms by which placentitis may lead to premature labor or fetal loss.
  • Hypoxia-related gene activation points to stress conditions in the placenta during infection, possibly exacerbating tissue damage.
  • These findings could help identify molecular targets for therapeutic intervention and improve management of equine placentitis to reduce fetal complications.

Conclusion

  • This study provides the first comprehensive transcriptomic profile of the equine amniotic membrane during ascending placentitis.
  • It reveals that the amniotic membrane actively participates in immune responses through toll-like receptor signaling and other pathways.
  • Understanding these molecular changes enhances knowledge of the pathophysiology of placentitis and opens avenues for developing strategies to protect fetal health during infection.

Cite This Article

APA
Marchio SP, El-Sheikh Ali H, Scott MA, Barbosa Fernandes C, Scoggin KE, Troedsson M, Boakari Y. (2025). Decoding the amniotic membrane transcriptome during equine ascending placentitis. Sci Rep, 15(1), 30714. https://doi.org/10.1038/s41598-025-16671-5

Publication

Scientific reports
ISSN: 2045-2322
NlmUniqueID: 101563288
Country: England
Language: English
Volume: 15
Issue: 1
Pages: 30714
PII: 30714

Researcher Affiliations

Marchio, Sophia P
  • College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA.
El-Sheikh Ali, Hossam
  • Department of Veterinary Science, Maxwell H. Gluck Equine Research Center, University of Kentucky, Lexington, KY, USA.
Scott, Matthew A
  • Veterinary Education, Research, and Outreach Center, Texas A&M University, Canyon, TX, USA.
Barbosa Fernandes, Claudia
  • Department of Animal Reproduction and Veterinary Radiology, School of Veterinary Medicine and Animal Science, University of São Paulo, São Paulo, SP, Brazil.
Scoggin, Kirsten E
  • Department of Veterinary Science, Maxwell H. Gluck Equine Research Center, University of Kentucky, Lexington, KY, USA.
Troedsson, Mats
  • Department of Veterinary Science, Maxwell H. Gluck Equine Research Center, University of Kentucky, Lexington, KY, USA.
Boakari, Yatta
  • College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA. yboakari@cvm.tamu.edu.

MeSH Terms

  • Animals
  • Female
  • Horses
  • Amnion / metabolism
  • Amnion / pathology
  • Pregnancy
  • Transcriptome
  • Horse Diseases / genetics
  • Horse Diseases / metabolism
  • Horse Diseases / pathology
  • Placenta Diseases / veterinary
  • Placenta Diseases / genetics
  • Placenta Diseases / metabolism
  • Placenta Diseases / pathology
  • Gene Expression Profiling

Grant Funding

  • RGS 23-02 / VLCS Faculty Grant Texas A&M University

Conflict of Interest Statement

Declarations. Competing interests: The authors declare no competing interests. Ethical approval: This study was approved by IACUC protocol number 2014-1341.

References

This article includes 85 references
  1. Giles RC. Causes of abortion, stillbirth, and perinatal death in horses: 3,527 cases (1986–1991). 1170–1175 (1993).
    doi: 10.2460/javma.1993.203.08.1170pubmed: 8244867google scholar: lookup
  2. Hong CB. Etiology and pathology of equine placentitis. 56–63 (1993).
    doi: 10.1177/104063879300500113pubmed: 8466982google scholar: lookup
  3. Fedorka CE. The feto-maternal immune response to equine placentitis. e13179 (2019).
    doi: 10.1111/aji.13179pubmed: 31373743google scholar: lookup
  4. Cantón GJ. Equine abortion and stillbirth in california: A review of 1,774 cases received at a diagnostic laboratory, 1990–2022. 153–162 (2023).
    doi: 10.1177/10406387231152788pmc: PMC9999402pubmed: 36744759google scholar: lookup
  5. Renaudin CD, Troedsson MHT, Gillis CL, King VL, Bodena A. Ultrasonographic evaluation of the equine placenta by transrectal and transabdominal approach in the normal pregnant mare. 559–573 (1997).
    doi: 10.1016/S0093-691X(97)00014-9pubmed: 16728008google scholar: lookup
  6. Canisso IF. Changes in maternal androgens and oestrogens in mares with experimentally-induced ascending placentitis. 244–249 (2017).
    doi: 10.1111/evj.12556pubmed: 26729310google scholar: lookup
  7. Abrahams VM. Bacterial modulation of human fetal membrane toll-like receptor expression. 33–40 (2013).
    doi: 10.1111/aji.12016pmc: PMC3535068pubmed: 22967004google scholar: lookup
  8. Boakari YL. Serum amyloid A, serum amyloid A1 and haptoglobin in pregnant mares and their fetuses after experimental induction of placentitis. 106766 (2021).
    doi: 10.1016/j.anireprosci.2021.106766pubmed: 34015726google scholar: lookup
  9. Canisso IF. Serum amyloid A and haptoglobin concentrations are increased in plasma of mares with ascending placentitis in the absence of changes in peripheral leukocyte counts or fibrinogen concentration. 376–385 (2014).
    doi: 10.1111/aji.12278pubmed: 24916762google scholar: lookup
  10. Loux SC, Ball BA. The proteome of fetal fluids in mares with experimentally-induced placentitis. 71–78 (2018).
    doi: 10.1016/j.placenta.2018.03.004pubmed: 29626984google scholar: lookup
  11. LeBlanc M, Macpherson M, Sheerin P. Ascending placentitis: what we know about pathophysiology, diagnosis, and treatment. 127–143 (2008).
  12. Cummins C, Carrington S, Fitzpatrick E, Duggan V. Ascending placentitis in the mare: A review. 307–313 (2008).
    doi: 10.1186/2046-0481-61-5-307pmc: PMC3113861pubmed: 21851713google scholar: lookup
  13. Lyle SK. Immunology of infective preterm delivery in the mare. 661–668 (2014).
    pubmed: 24552615
  14. Gomez-Lopez N. RNA sequencing reveals diverse functions of amniotic fluid neutrophils and monocytes/macrophages in intra-amniotic infection. 63–82 (2020).
    doi: 10.1159/000509718pmc: PMC8077468pubmed: 33152737google scholar: lookup
  15. Motomura K. RNA sequencing reveals distinct immune responses in the chorioamniotic membranes of women with preterm labor and microbial or sterile intra-amniotic inflammation. .
    pmc: PMC8091089pubmed: 33558326doi: 10.1128/iai.00819-20google scholar: lookup
  16. Pereyra S, Sosa C, Bertoni B, Sapiro R. Transcriptomic analysis of fetal membranes reveals pathways involved in preterm birth.. 53 (2019).
    doi: 10.1186/s12920-019-0498-3pmc: PMC6444860pubmed: 30935390google scholar: lookup
  17. Underhill LA, Mennella JM, Tollefson GA, Uzun A, Lechner BE. Transcriptomic analysis delineates preterm prelabor rupture of membranes from preterm labor in preterm fetal membranes.. 72 (2024).
    doi: 10.1186/s12920-024-01841-7pmc: PMC10916314pubmed: 38443884google scholar: lookup
  18. Tissarinen P. Elevated human placental heat shock protein 5 is associated with spontaneous preterm birth.. 520–529 (2023).
    doi: 10.1038/s41390-023-02501-9pmc: PMC9926443pubmed: 36788289google scholar: lookup
  19. El-Sheikh Ali H. Transcriptomic analysis of equine placenta reveals key regulators and pathways involved in ascending placentitis.. 638–656 (2020).
    doi: 10.1093/biolre/ioaa209pubmed: 33345276google scholar: lookup
  20. Pozor M. Equine placenta – a clinician’s perspective. Part 1: normal placenta – physiology and evaluation.. 327–334 (2016).
    doi: 10.1111/eve.12499google scholar: lookup
  21. Turco MY, Moffett A. Development of the human placenta.. dev163428 (2019).
    doi: 10.1242/dev.163428pubmed: 31776138google scholar: lookup
  22. El-Sheikh Ali H. Transcriptomic analysis reveals the key regulators and molecular mechanisms underlying myometrial activation during equine placentitis.. 1306–1325 (2020).
    doi: 10.1093/biolre/ioaa020pubmed: 32065222google scholar: lookup
  23. El-Sheikh Ali H. Equine cervical remodeling during placentitis and the prepartum period: A transcriptomic approach.. 603–621 (2021).
    doi: 10.1530/rep-21-0008pubmed: 33780349google scholar: lookup
  24. Fernandes CB. Uterine cervix as a fundamental part of the pathogenesis of pregnancy loss associated with ascending placentitis in mares.. 167–175 (2020).
    doi: 10.1016/j.theriogenology.2019.10.017pubmed: 31732164google scholar: lookup
  25. Fernandes CB. Upregulation of inflammatory cytokines is associated with alteration in prostaglandin pathways and sex-steroid receptors in the cervix of mares with placentitis.. 226 (2018).
    doi: 10.1016/j.jevs.2018.05.113google scholar: lookup
  26. Mi H, Muruganujan A, Casagrande JT, Thomas PD. Large-scale gene function analysis with the Panther classification system.. 1551–1566 (2013).
    doi: 10.1038/nprot.2013.092pmc: PMC6519453pubmed: 23868073google scholar: lookup
  27. Bukowski R. Onset of human preterm and term birth is related to unique inflammatory transcriptome profiles at the maternal fetal interface.. e3685 (2017).
    pmc: PMC5582610pubmed: 28879060
  28. Fedorka CE. Alterations in T cell-related transcripts at the feto-maternal interface throughout equine gestation.. 78–87 (2020).
    doi: 10.1016/j.placenta.2019.10.011pubmed: 31730925google scholar: lookup
  29. Wagner LH. Low progesterone concentration in early pregnancy is detrimental to conceptus development and pregnancy outcome in horses.. 107334 (2023).
    doi: 10.1016/j.anireprosci.2023.107334pubmed: 37725863google scholar: lookup
  30. Biggar RJ, Poulsen G, Melbye M, Ng J, Boyd HA. Spontaneous labor onset: is it immunologically mediated?. 268 (2010).
    doi: 10.1016/j.ajog.2009.10.875pubmed: 20045503google scholar: lookup
  31. Migale R. Modeling hormonal and inflammatory contributions to preterm and term labor using uterine Temporal transcriptomics. 86 (2016).
    doi: 10.1186/s12916-016-0632-4pmc: PMC4904357pubmed: 27291689google scholar: lookup
  32. Amarante-Mendes G P. Pattern recognition receptors and the host cell death molecular machinery. (2018).
    pmc: PMC6232773pubmed: 30459758doi: 10.3389/fimmu.2018.02379google scholar: lookup
  33. Šket T, Ramuta T Ž, Starčič Erjavec M, Kreft M E. The role of innate immune system in the human amniotic membrane and human amniotic fluid in protection against intra-amniotic infections and inflammation. (2021).
    pmc: PMC8566738pubmed: 34745106doi: 10.3389/fimmu.2021.735324google scholar: lookup
  34. Medzhitov R. Toll-like receptors and innate immunity. 135–145 (2001).
    doi: 10.1038/35100529pubmed: 11905821google scholar: lookup
  35. Mineev K S. Spatial structure of TLR4 transmembrane domain in bicelles provides the insight into the receptor activation mechanism. 6864 (2017).
    doi: 10.1038/s41598-017-07250-4pmc: PMC5537299pubmed: 28761155google scholar: lookup
  36. Janardhan K S. Toll like receptor-4 expression in lipopolysaccharide induced lung inflammation. 687–696 (2006).
    doi: 10.14670/hh-21.687pubmed: 16598667google scholar: lookup
  37. Moretti I F. Late p65 nuclear translocation in glioblastoma cells indicates non-canonical TLR4 signaling and activation of DNA repair genes. 1333 (2021).
    doi: 10.1038/s41598-020-79356-1pmc: PMC7809124pubmed: 33446690google scholar: lookup
  38. Kim Y M. Toll-like receptor-2 and – 4 in the chorioamniotic membranes in spontaneous labor at term and in preterm parturition that are associated with chorioamnionitis. 1346–1355 (2004).
    doi: 10.1016/j.ajog.2004.07.009pubmed: 15507964google scholar: lookup
  39. Gillaux C, Méhats C, Vaiman D, Cabrol D, Breuiller-Fouché M. Functional screening of TLRs in human amniotic epithelial cells. 2766–2774 (2011).
    pubmed: 21775685doi: 10.4049/jimmunol.1100217google scholar: lookup
  40. Takeuchi O. Differential roles of TLR2 and TLR4 in recognition of gram-negative and gram-positive bacterial cell wall components. 443–451 (1999).
    doi: 10.1016/S1074-7613(00)80119-3pubmed: 10549626google scholar: lookup
  41. Bolourani S, Brenner M, Wang P. The interplay of damps, TLR4, and Proinflammatory cytokines in pulmonary fibrosis. 1373–1384 (2021).
    doi: 10.1007/s00109-021-02113-ypmc: PMC8277227pubmed: 34258628google scholar: lookup
  42. Na K, Oh B C, Jung Y. Multifaceted role of CD14 in innate immunity and tissue homeostasis. 100–107 (2023).
    doi: 10.1016/j.cytogfr.2023.08.008pubmed: 37661484google scholar: lookup
  43. Adams Waldorf K M, Persing D, Novy M J, Sadowsky D W, Gravett M G. Pretreatment with toll-like receptor 4 antagonist inhibits lipopolysaccharide-induced preterm uterine contractility, cytokines, and prostaglandins in rhesus monkeys. 121–127 (2008).
    doi: 10.1177/1933719107310992pmc: PMC2774271pubmed: 18187405google scholar: lookup
  44. Gómez-Chávez F. NF-κb and its regulators during pregnancy. 679106 (2021).
    doi: 10.3389/fimmu.2021.679106pmc: PMC8131829pubmed: 34025678google scholar: lookup
  45. Hadfield K A, McCracken S A, Ashton A W, Nguyen T G, Morris J M. Regulated suppression of NF-κb throughout pregnancy maintains a favourable cytokine environment necessary for pregnancy success. 1–9 (2011).
    doi: 10.1016/j.jri.2010.11.008pubmed: 21411157google scholar: lookup
  46. Mendelson C R. Minireview: Fetal-maternal hormonal signaling in pregnancy and labor. 947–954 (2009).
    doi: 10.1210/me.2009-0016pmc: PMC2703595pubmed: 19282364google scholar: lookup
  47. Robertson S A, Skinner R J, Care A S. Essential role for IL-10 in resistance to lipopolysaccharide-induced preterm labor in mice. 4888–4896 (2006).
    doi: 10.4049/jimmunol.177.7.4888pubmed: 16982931google scholar: lookup
  48. Fedorka C E. Alterations of Circulating biomarkers during late term pregnancy complications in the horse part I: cytokines. 103425 (2021).
    doi: 10.1016/j.jevs.2021.103425pubmed: 33781421google scholar: lookup
  49. El-Sheikh Ali H. Equine placentitis is associated with a downregulation in myometrial progestin signaling. 162–176 (2019).
    doi: 10.1093/biolre/ioz059pubmed: 31107530google scholar: lookup
  50. Lim R, Barker G, Lappas M. A novel role for FOXO3 in human labor: Increased expression in laboring myometrium, and regulation of proinflammatory and prolabor mediators in pregnant human myometrial cells1. (2013).
    pubmed: 23636809doi: 10.1095/biolreprod.113.108126google scholar: lookup
  51. Khani H, Feizi M A, Safaralizadeh R, Mohseni J, Haghi M. Altered expression of the HLA-G and IL10RB genes in placental tissue of women with recurrent pregnancy loss. (2023).
    pubmed: 37145066doi: 10.7754/clin.lab.2022.220822google scholar: lookup
  52. Fedorka C E. Interleukin-6 pathobiology in equine placental infection. e13363 (2021).
    doi: 10.1111/aji.13363pubmed: 33098605google scholar: lookup
  53. Osmers R. Origin of cervical collagenase during parturition. 1455–1460 (1992).
    doi: 10.1016/0002-9378(92)91619-Lpubmed: 1317677google scholar: lookup
  54. Shi Y B, Li Q, Damjanovski S, Amano T, Ishizuya-Oka A. Regulation of apoptosis during development: input from the extracellular matrix (review). 273–355 (1998).
    doi: 10.3892/ijmm.2.3.273pubmed: 9855698google scholar: lookup
  55. Negara K S, Suwiyoga K, Arijana K, Tunas K. Role of caspase-3 as risk factors of premature rupture of membranes. 2091–2098 (2017).
  56. Lanci A. Morphological study of equine amniotic compartment. 165–171 (2022).
    doi: 10.1016/j.theriogenology.2021.10.019pubmed: 34710648google scholar: lookup
  57. Castagnetti C. Evaluation of lung maturity by amniotic fluid analysis in equine neonate. 1455–1462 (2007).
    pubmed: 17448529
  58. Duck-Chong C G. The isolation of lamellar bodies and their membranous content from rat lung, lamb tracheal fluid and human amniotic fluid. 2025-2030 (1978).
    pubmed: 209279doi: 10.1016/0024-3205(78)90549-0google scholar: lookup
  59. Lemke A. Human amniotic membrane as newly identified source of amniotic fluid pulmonary surfactant. 6406 (2017).
    doi: 10.1038/s41598-017-06402-wpmc: PMC5527005pubmed: 28743969google scholar: lookup
  60. Hsu T Y. The abundances of LTF and SOD2 in amniotic fluid are potential biomarkers of gestational age and preterm birth. 4903 (2023).
    doi: 10.1038/s41598-023-31486-ypmc: PMC10039869pubmed: 36966172google scholar: lookup
  61. Zhao J, Hu J, Zhang R, Deng J C. CEBPD regulates oxidative stress and inflammatory responses in hypertensive cardiac remodeling. 713–723 (2023).
    doi: 10.1097/shk.0000000000002228pubmed: 37752084google scholar: lookup
  62. Hart S N, Therneau T M, Zhang Y, Poland G A, Kocher J P. Calculating sample size estimates for RNA sequencing data. 970–978 (2013).
    doi: 10.1089/cmb.2012.0283pmc: PMC3842884pubmed: 23961961google scholar: lookup
  63. Li C I, Su P F, Shyr Y. Sample size calculation based on exact test for assessing differential expression analysis in RNA-seq data. 357 (2013).
    doi: 10.1186/1471-2105-14-357pmc: PMC3924199pubmed: 24314022google scholar: lookup
  64. Poplawski A, Binder H. Feasibility of sample size calculation for RNA-seq studies. 713–720 (2017).
    doi: 10.1093/bib/bbw144pubmed: 28100468google scholar: lookup
  65. Schurch N. How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use?. 839–851 (2016).
    doi: 10.1261/rna.053959.115pmc: PMC4878611pubmed: 27022035google scholar: lookup
  66. Seyednasrollah F, Laiho A, Elo L L. Comparison of software packages for detecting differential expression in RNA-seq studies. 59–70 (2013).
    doi: 10.1093/bib/bbt086pmc: PMC4293378pubmed: 24300110google scholar: lookup
  67. Douglas R H, Ginther O J. Development of the equine fetus and placenta. 503–505 (1975).
    pubmed: 1060832
  68. Leary, S. L. et al. (American Veterinary Medical Association, 2013).
  69. Conesa A. A survey of best practices for RNA-seq data analysis. 13 (2016).
    doi: 10.1186/s13059-016-0881-8pmc: PMC4728800pubmed: 26813401google scholar: lookup
  70. El-Sheikh Ali H. Kinetics of placenta-specific 8 (PLAC8) in equine placenta during pregnancy and placentitis. 81–89 (2021).
    doi: 10.1016/j.theriogenology.2020.10.041pubmed: 33189077google scholar: lookup
  71. Park Y S. Comparison of library construction kits for mRNA sequencing in the illumina platform. 1233–1240 (2019).
    doi: 10.1007/s13258-019-00853-3pubmed: 31350733google scholar: lookup
  72. Wang Z, Gerstein M, Snyder M. RNA-seq: A revolutionary tool for transcriptomics. 57–63 (2009).
    doi: 10.1038/nrg2484pmc: PMC2949280pubmed: 19015660google scholar: lookup
  73. Andrews S, Fastqc. A quality control tool for high throughput sequence data. (2010).
  74. Bolger A M, Lohse M, Usadel B. Trimmomatic: A flexible trimmer for illumina sequence data. 2114–2120 (2014).
    doi: 10.1093/bioinformatics/btu170pmc: PMC4103590pubmed: 24695404google scholar: lookup
  75. Kalbfleisch T S. Improved reference genome for the domestic horse increases assembly contiguity and composition. 197 (2018).
    doi: 10.1038/s42003-018-0199-zpmc: PMC6240028pubmed: 30456315google scholar: lookup
  76. Kim D, Paggi J M, Park C, Bennett C, Salzberg S L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. 907–915 (2019).
    doi: 10.1038/s41587-019-0201-4pmc: PMC7605509pubmed: 31375807google scholar: lookup
  77. Kovaka S. Transcriptome assembly from long-read RNA-seq alignments with StringTie2. 278 (2019).
    doi: 10.1186/s13059-019-1910-1pmc: PMC6912988pubmed: 31842956google scholar: lookup
  78. Pertea G. prepDE. (2019).
  79. McCarthy D J, Chen Y, Smyth G K. Differential expression analysis of multifactor RNA-seq experiments with respect to biological variation. 4288–4297 (2012).
    doi: 10.1093/nar/gks042pmc: PMC3378882pubmed: 22287627google scholar: lookup
  80. Scott M A. Hematological and gene co-expression network analyses of high-risk beef cattle defines immunological mechanisms and biological complexes involved in bovine respiratory disease and weight gain. e0277033 (2022).
    doi: 10.1371/journal.pone.0277033pmc: PMC9632787pubmed: 36327246google scholar: lookup
  81. Langfelder P, Horvath SW. WGCNA: An R package for weighted correlation network analysis. 2008;9:559.
    doi: 10.1186/1471-2105-9-559pmc: PMC2631488pubmed: 19114008google scholar: lookup
  82. Langfelder P, Horvath S. Eigengene networks for studying the relationships between co-expression modules. 2007;1:54.
    doi: 10.1186/1752-0509-1-54pmc: PMC2267703pubmed: 18031580google scholar: lookup
  83. Horvath, S. (Springer, 2011).
  84. Schuhler S. Feeding and behavioural effects of central administration of the melanocortin 3/4-R antagonist SHU9119 in obese and lean Siberian hamsters. 2004;177–185.
    doi: 10.1016/s0166-4328(03)00260-2pubmed: 15196785google scholar: lookup
  85. Ball BA, Scoggin KE, Troedsson MHT, Squires EL. Characterization of prostaglandin E2 receptors (EP2, EP4) in the horse oviduct. 2013;35–41.
    doi: 10.1016/j.anireprosci.2013.07.009pubmed: 24035156google scholar: lookup

Citations

This article has been cited 1 times.
  1. Scoggin KE, Rakha SI, Abdellatif AM, Adlan F, Helmy YA, Ruby R, Ball B, Boakari Y, Ali HE. Activation of the S100A8/A9 Alarmin Amplifies Inflammatory Pathways in Equine Ascending Placentitis. Int J Mol Sci 2026 Feb 4;27(3).
    doi: 10.3390/ijms27031550pubmed: 41683969google scholar: lookup
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