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Identification of Biomarkers for Predicting Ovarian Reserve of Primordial Follicle via Transcriptomic Analysis
Ovarian reserve (OR) is mainly determined by the number of primordial follicles in the ovary and continuously depleted until ovarian senescence. With the development of assisted reproductive technology such as ovarian tissue cryopreservation and autotransplantation, growing demand has arisen for obj...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9174591/ https://www.ncbi.nlm.nih.gov/pubmed/35692832 http://dx.doi.org/10.3389/fgene.2022.879974 |
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author | Liu, Li Liu, Biting Li, Ke Wang, Chunyan Xie, Yan Luo, Ning Wang, Lian Sun, Yaoqi Huang, Wei Cheng, Zhongping Liu, Shupeng |
author_facet | Liu, Li Liu, Biting Li, Ke Wang, Chunyan Xie, Yan Luo, Ning Wang, Lian Sun, Yaoqi Huang, Wei Cheng, Zhongping Liu, Shupeng |
author_sort | Liu, Li |
collection | PubMed |
description | Ovarian reserve (OR) is mainly determined by the number of primordial follicles in the ovary and continuously depleted until ovarian senescence. With the development of assisted reproductive technology such as ovarian tissue cryopreservation and autotransplantation, growing demand has arisen for objective assessment of OR at the histological level. However, no specific biomarkers of OR can be used effectively in clinic nowadays. Herein, bulk RNA-seq datasets of the murine ovary with the biological ovarian age (BOA) dynamic changes and single-cell RNA-seq datasets of follicles at different stages of folliculogenesis were obtained from the GEO database to identify gene signature correlated to the primordial follicle pool. The correlations between gene signature expression and OR were also validated in several comparative OR models. The results showed that genes including Lhx8, Nobox, Sohlh1, Tbpl2, Stk31, and Padi6 were highly correlated to the OR of the primordial follicle pool, suggesting that these genes might be used as biomarkers for predicting OR at the histological level. |
format | Online Article Text |
id | pubmed-9174591 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91745912022-06-09 Identification of Biomarkers for Predicting Ovarian Reserve of Primordial Follicle via Transcriptomic Analysis Liu, Li Liu, Biting Li, Ke Wang, Chunyan Xie, Yan Luo, Ning Wang, Lian Sun, Yaoqi Huang, Wei Cheng, Zhongping Liu, Shupeng Front Genet Genetics Ovarian reserve (OR) is mainly determined by the number of primordial follicles in the ovary and continuously depleted until ovarian senescence. With the development of assisted reproductive technology such as ovarian tissue cryopreservation and autotransplantation, growing demand has arisen for objective assessment of OR at the histological level. However, no specific biomarkers of OR can be used effectively in clinic nowadays. Herein, bulk RNA-seq datasets of the murine ovary with the biological ovarian age (BOA) dynamic changes and single-cell RNA-seq datasets of follicles at different stages of folliculogenesis were obtained from the GEO database to identify gene signature correlated to the primordial follicle pool. The correlations between gene signature expression and OR were also validated in several comparative OR models. The results showed that genes including Lhx8, Nobox, Sohlh1, Tbpl2, Stk31, and Padi6 were highly correlated to the OR of the primordial follicle pool, suggesting that these genes might be used as biomarkers for predicting OR at the histological level. Frontiers Media S.A. 2022-05-25 /pmc/articles/PMC9174591/ /pubmed/35692832 http://dx.doi.org/10.3389/fgene.2022.879974 Text en Copyright © 2022 Liu, Liu, Li, Wang, Xie, Luo, Wang, Sun, Huang, Cheng and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Liu, Li Liu, Biting Li, Ke Wang, Chunyan Xie, Yan Luo, Ning Wang, Lian Sun, Yaoqi Huang, Wei Cheng, Zhongping Liu, Shupeng Identification of Biomarkers for Predicting Ovarian Reserve of Primordial Follicle via Transcriptomic Analysis |
title | Identification of Biomarkers for Predicting Ovarian Reserve of Primordial Follicle via Transcriptomic Analysis |
title_full | Identification of Biomarkers for Predicting Ovarian Reserve of Primordial Follicle via Transcriptomic Analysis |
title_fullStr | Identification of Biomarkers for Predicting Ovarian Reserve of Primordial Follicle via Transcriptomic Analysis |
title_full_unstemmed | Identification of Biomarkers for Predicting Ovarian Reserve of Primordial Follicle via Transcriptomic Analysis |
title_short | Identification of Biomarkers for Predicting Ovarian Reserve of Primordial Follicle via Transcriptomic Analysis |
title_sort | identification of biomarkers for predicting ovarian reserve of primordial follicle via transcriptomic analysis |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9174591/ https://www.ncbi.nlm.nih.gov/pubmed/35692832 http://dx.doi.org/10.3389/fgene.2022.879974 |
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