ArticleScientific reports2024
Granulosa cells provide transcriptomic information on ovarian follicle dynamics in southern white rhinoceros.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Beyond Routine Ultrasonography: Peri-Insemination Biomarkers in Relation to Reproductive Competence in Warmblood Mares.Animals : an open access journal from MDPI · 2026Article
- Activation of the alpha 7 nicotinic acetylcholine receptor (CHRNA7) limits hypoxia-induced inflammatory responses and regulates collagens in cultured human granulosa cells†.Biology of reproduction · 2026Article
- Integrated molecular analysis of granulosa cells and follicular fluid extracellular vesicles reveals predictive biomarkers of oocyte maturation in the southern white rhinoceros.Frontiers in cell and developmental biology · 2026Article
- Manual curation for improved genome annotation of the functionally extinct northern white rhinoceros (Ceratotherium simum cottoni).PloS one · 2026Article
- Identification and Preliminary Analysis of Granulosa Cell Biomarkers to Predict Oocyte In Vitro Maturation Outcome in the Southern White Rhinoceros (Animals : an open access journal from MDPI · 2024Article
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4 authors.
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Abstract
Much remains unknown about the reproductive physiology of southern white rhinoceros (SWR) and the effect of ovarian stimulation prior to ovum pickup (OPU) have not been fully elucidated. Granulosa cells (GC) provide valuable insight into follicle growth and oocyte maturation status. The goals of this study were to evaluate transcriptomic changes in GC from three stages of follicle development and to identify biomarkers possibly associated with follicular growth and maturation as a result of ovarian stimulation. GC collected from SWRs following OPU were assigned stages based upon follicle size. Total RNA was isolated, and cDNA libraries were prepared and sequenced on a NovaSeq 6000. All bioinformatics analyses were performed utilizing the Galaxy web platform. Reads were aligned to CerSimCot1.0, and the manual curation was performed with EquCab3.0. Overall, 39,455 transcripts (21,612 genes) were identified across follicle stages, and manual curation yielded a 61% increase in gene identification from the original annotation. Granulosa cells from preovulatory follicles expressed the highest number of unique transcripts. The following seven biomarkers were determined based upon cluster analysis and patterns of expression: COL1A1, JMY, FBXW11, NRG1, TMPO, MACIR and COL4A1. These data can be used to potentially evaluate the effects of different ovarian stimulation protocols on follicle dynamics, improve OPU results, and support conservation efforts in this species.
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