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Proteomic characterization of bovine granulosa cells in dominant and subordinate follicles

BACKGROUND: Characterization of molecular factors regulating ovarian follicular development is critical to understanding its functional mechanism of controlling the estrous cycle, determining oocyte competency, and regulating ovulation. In previous studies, we performed next-gene sequencing to inves...

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Detalles Bibliográficos
Autores principales: Hao, Qingling, Zhu, Zhiwei, Xu, Dongmei, Liu, Wenzhong, Lyu, Lihua, Li, Pengfei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6593542/
https://www.ncbi.nlm.nih.gov/pubmed/31293364
http://dx.doi.org/10.1186/s41065-019-0097-5
Descripción
Sumario:BACKGROUND: Characterization of molecular factors regulating ovarian follicular development is critical to understanding its functional mechanism of controlling the estrous cycle, determining oocyte competency, and regulating ovulation. In previous studies, we performed next-gene sequencing to investigate the differentially expressed transcripts of bovine follicular granulosa cells (GCs) at the dominant follicle (DF) and subordinate follicle (SF) stages during the first follicular wave. This study aims to investigate the proteomic characterization of GCs of DF and SF in the bovine estrous cycle. RESULTS: In total, 3409 proteins were identified from 30,321 peptides obtained from liquid chromatograph-mass spectrometer analysis. Two hundred fifty-nine of these proteins were found to be expressed differently in DF and SF. Out of 259, a total of 26 proteins were upregulated (fold change≥2) and 233 proteins were downregulated (fold change≤0.5) in DF. Gene Ontology (GO) analysis of proteome data revealed the biological process, cellular component and molecular function of expressed proteins in DF and SF, while the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed important signaling pathways associated with follicular development such as the PI3K-Akt, estrogen, and insulin signaling pathways. Immunoblotting results of OGN, ROR2, and HSPB1 confirmed the accuracy of the data. Bioinformatics analysis showed that 13 proteins may be linked to follicular development. CONCLUSIONS: Findings from this study will provide useful information for exploring follicular development and function. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s41065-019-0097-5) contains supplementary material, which is available to authorized users.