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mRNA and miRNA Transcriptome Profiling of Granulosa and Theca Layers From Geese Ovarian Follicles Reveals the Crucial Pathways and Interaction Networks for Regulation of Follicle Selection
Follicle development is characterized by the recruitment, growth, selection, and dominance of follicles, and follicle selection determines the lifetime reproductive performance. However, in birds, the molecular mechanisms underlying follicle selection still remain elusive. This study analyzed genome...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6820619/ https://www.ncbi.nlm.nih.gov/pubmed/31708963 http://dx.doi.org/10.3389/fgene.2019.00988 |
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author | Li, Qin Hu, Shenqiang Wang, Yushi Deng, Yan Yang, Shuang Hu, Jiwei Li, Liang Wang, Jiwen |
author_facet | Li, Qin Hu, Shenqiang Wang, Yushi Deng, Yan Yang, Shuang Hu, Jiwei Li, Liang Wang, Jiwen |
author_sort | Li, Qin |
collection | PubMed |
description | Follicle development is characterized by the recruitment, growth, selection, and dominance of follicles, and follicle selection determines the lifetime reproductive performance. However, in birds, the molecular mechanisms underlying follicle selection still remain elusive. This study analyzed genome-wide changes in the mRNA and miRNA expression profiles in both the granulosa and theca layers of geese ovarian follicles before selection (4–6- and 8–10-mm follicles) and after selection (F5). The sequencing results showed that a higher number of both differentially expressed (DE) mRNAs and DE miRNAs were identified between 8–10-mm and F5 follicles compared with those between the 4–6- and 8–10-mm follicles, especially in the granulosa layer. Moreover, a Short Time-series Expression Miner analysis identified a large number of DE mRNAs and DE miRNAs that are associated with follicle selection. The functional enrichment analysis showed that DE genes in the granulosa layer during follicle selection were mainly enriched in five pathways related to junctional adhesion and two pathways associated with lipid metabolism. Additionally, an interaction network was constructed to visualize interactions among protein-coding genes, which identified 53 junctional adhesion- and 15 lipid regulation-related protein-coding genes. Then, a co-expression network between mRNAs and miRNAs in relation to junctional adhesion was also visualized and mainly included acy-miR-2954, acy-miR-218, acy-miR-2970, acy-miR-100, acy-miR-1329, acy-miR-199, acy-miR-425, acy-miR-181, and acy-miR-147. Furthermore, miRNA–mRNA interaction pairs related to lipid regulation were constructed including acy-miR-107, acy-miR-138, acy-miR-130, acy-miR-128, and acy-miR-101 during follicular selection. In summary, these data highlight the key roles of junctional adhesion and lipid metabolism during follicular selection and contribute to a better understanding of the mechanisms underlying follicle selection in birds. |
format | Online Article Text |
id | pubmed-6820619 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68206192019-11-08 mRNA and miRNA Transcriptome Profiling of Granulosa and Theca Layers From Geese Ovarian Follicles Reveals the Crucial Pathways and Interaction Networks for Regulation of Follicle Selection Li, Qin Hu, Shenqiang Wang, Yushi Deng, Yan Yang, Shuang Hu, Jiwei Li, Liang Wang, Jiwen Front Genet Genetics Follicle development is characterized by the recruitment, growth, selection, and dominance of follicles, and follicle selection determines the lifetime reproductive performance. However, in birds, the molecular mechanisms underlying follicle selection still remain elusive. This study analyzed genome-wide changes in the mRNA and miRNA expression profiles in both the granulosa and theca layers of geese ovarian follicles before selection (4–6- and 8–10-mm follicles) and after selection (F5). The sequencing results showed that a higher number of both differentially expressed (DE) mRNAs and DE miRNAs were identified between 8–10-mm and F5 follicles compared with those between the 4–6- and 8–10-mm follicles, especially in the granulosa layer. Moreover, a Short Time-series Expression Miner analysis identified a large number of DE mRNAs and DE miRNAs that are associated with follicle selection. The functional enrichment analysis showed that DE genes in the granulosa layer during follicle selection were mainly enriched in five pathways related to junctional adhesion and two pathways associated with lipid metabolism. Additionally, an interaction network was constructed to visualize interactions among protein-coding genes, which identified 53 junctional adhesion- and 15 lipid regulation-related protein-coding genes. Then, a co-expression network between mRNAs and miRNAs in relation to junctional adhesion was also visualized and mainly included acy-miR-2954, acy-miR-218, acy-miR-2970, acy-miR-100, acy-miR-1329, acy-miR-199, acy-miR-425, acy-miR-181, and acy-miR-147. Furthermore, miRNA–mRNA interaction pairs related to lipid regulation were constructed including acy-miR-107, acy-miR-138, acy-miR-130, acy-miR-128, and acy-miR-101 during follicular selection. In summary, these data highlight the key roles of junctional adhesion and lipid metabolism during follicular selection and contribute to a better understanding of the mechanisms underlying follicle selection in birds. Frontiers Media S.A. 2019-10-23 /pmc/articles/PMC6820619/ /pubmed/31708963 http://dx.doi.org/10.3389/fgene.2019.00988 Text en Copyright © 2019 Li, Hu, Wang, Deng, Yang, Hu, Li and Wang http://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 Li, Qin Hu, Shenqiang Wang, Yushi Deng, Yan Yang, Shuang Hu, Jiwei Li, Liang Wang, Jiwen mRNA and miRNA Transcriptome Profiling of Granulosa and Theca Layers From Geese Ovarian Follicles Reveals the Crucial Pathways and Interaction Networks for Regulation of Follicle Selection |
title | mRNA and miRNA Transcriptome Profiling of Granulosa and Theca Layers From Geese Ovarian Follicles Reveals the Crucial Pathways and Interaction Networks for Regulation of Follicle Selection |
title_full | mRNA and miRNA Transcriptome Profiling of Granulosa and Theca Layers From Geese Ovarian Follicles Reveals the Crucial Pathways and Interaction Networks for Regulation of Follicle Selection |
title_fullStr | mRNA and miRNA Transcriptome Profiling of Granulosa and Theca Layers From Geese Ovarian Follicles Reveals the Crucial Pathways and Interaction Networks for Regulation of Follicle Selection |
title_full_unstemmed | mRNA and miRNA Transcriptome Profiling of Granulosa and Theca Layers From Geese Ovarian Follicles Reveals the Crucial Pathways and Interaction Networks for Regulation of Follicle Selection |
title_short | mRNA and miRNA Transcriptome Profiling of Granulosa and Theca Layers From Geese Ovarian Follicles Reveals the Crucial Pathways and Interaction Networks for Regulation of Follicle Selection |
title_sort | mrna and mirna transcriptome profiling of granulosa and theca layers from geese ovarian follicles reveals the crucial pathways and interaction networks for regulation of follicle selection |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6820619/ https://www.ncbi.nlm.nih.gov/pubmed/31708963 http://dx.doi.org/10.3389/fgene.2019.00988 |
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