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Proteomic Analysis Identifies Potential Markers for Chicken Primary Follicle Development.

ABSTRACT: Follicles' development in chicken imparts a major impact on egg production. To enhance the egg-laying efficiency, comprehensive knowledge of different phases of follicular development is a prerequisite. Therefore, we used the tandem mass tag (TMT) based proteomic approach to find the genes involved in the primary follicular development of chicken. The primary follicles were divided into two groups-small primary follicles (81-150 μm) and developed primary follicles (300-500 μm). Differential expression analysis (fold change > 1.2, p-value < 0.05) revealed a total of 70 differentially expressed proteins (DEPs), of which 38 were upregulated and 32 were downregulated. Gene ontology (GO) enrichment analysis disclosed that DEPs were intricate with cellular protein localization, the establishment of protein localization, and nucleoside phosphate-binding activities. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway indicated the involvement of DEPs in different metabolic pathways such as glycolysis, pyruvate metabolism, galactose metabolism, and fructose and mannose metabolism. The current proteomic analysis suggested suitable markers such as Anxa2, Pdia3, and Capzb, which may serve as a potential role for primary follicle development. The present study provides the first insight into the proteome dynamics of primary follicle development and would play a potential role for further studies in chicken to improve egg productivity.

SUBMITTER: Wadood AA

PROVIDER: S-EPMC8069082 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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Proteomic Analysis Identifies Potential Markers for Chicken Primary Follicle Development.

Wadood Armughan Ahmed AA Wang Jingyuan J Pu Liping L Shahzad Qaisar Q Waqas Muhammad M Liu Xingting X Xie Long L Yu Lintian L Chen Dongyang D Akhtar Rana Waseem RW Lu Yangqing Y

Animals : an open access journal from MDPI 20210413 4

Follicles' development in chicken imparts a major impact on egg production. To enhance the egg-laying efficiency, comprehensive knowledge of different phases of follicular development is a prerequisite. Therefore, we used the tandem mass tag (TMT) based proteomic approach to find the genes involved in the primary follicular development of chicken. The primary follicles were divided into two groups-small primary follicles (81-150 μm) and developed primary follicles (300-500 μm). Differential expr ...[more]

PMID: 33924300

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Project description:BACKGROUND:Follicular fluid accumulates into the antrum of follicle from the early stage of follicle development. Studies on its components may contribute to a better understanding of the mechanisms underlying follicular development and oocyte quality. With this objective, we performed a proteomic analysis of mare follicular fluid. First, we hypothesized that proteins in follicular fluid may differ from those in the serum, and also may change during follicle development. Second, we used four different approaches of Immunodepletion and one enrichment method, in order to overcome the masking effect of high-abundance proteins present in the follicular fluid, and to identify those present in lower abundance. Finally, we compared our results with previous studies performed in mono-ovulant (human) and poly-ovulant (porcine and canine) species in an attempt to identify common and/or species-specific proteins. METHODS:Follicular fluid samples were collected from ovaries at three different stages of follicle development (early dominant, late dominant and preovulatory). Blood samples were also collected at each time. The proteomic analysis was carried out on crude, depleted and enriched follicular fluid by 2D-PAGE, 1D-PAGE and mass spectrometry. RESULTS:Total of 459 protein spots were visualized by 2D-PAGE of crude mare follicular fluid, with no difference among the three physiological stages. Thirty proteins were observed as differentially expressed between serum and follicular fluid. Enrichment method was found to be the most powerful method for detection and identification of low-abundance proteins from follicular fluid. Actually, we were able to identify 18 proteins in the crude follicular fluid, and as many as 113 in the enriched follicular fluid. Inhibins and a few other proteins involved in reproduction could only be identified after enrichment of follicular fluid, demonstrating the power of the method used. The comparison of proteins found in mare follicular fluid with proteins previously identified in human, porcine and canine follicular fluids, led to the identification of 12 common proteins and of several species-specific proteins. CONCLUSIONS:This study provides the first description of mare follicular fluid proteome during the late follicle development stages. We identified several proteins from crude, depleted and enriched follicular fluid. Our results demonstrate that the enrichment method, combined with 2D-PAGE and mass spectrometry, can be successfully used to visualize and further identify the low-abundance proteins in the follicular fluid.

Project description:In this study, we aimed to better understand the difference between the functions of the two types of granulosa cells and sought to discover more key genes involved in follicle development and follicle selection. Herein, we separately collected pre-hierarchical follicle granulosa cells (PHGCs) and preovulatory follicle granulosa cells (POGCs) for RNA extraction; the transcriptomes of the two groups were compared via RNA-seq. A total of 5273 differentially expressed genes (DEGs) were identified between the PHGCs and POGCs; 2797 genes were up-regulated and 2476 were down-regulated in the PHGCs compared with the POGCs. A qPCR analysis confirmed that the expression patterns of 16 randomly selected DEGs were highly consistent with the RNA-seq results. In the POGCs, many of the genes with the most significant increase in expression were related to steroid hormone synthesis. In addition, the genes with the most significant decline in expression, including AMH and WT1, were related to the inhibition of steroid hormone synthesis. These results suggest that steroid hormones play a key role in follicle development. Furthermore, a Gene Ontology (GO) analysis revealed that these DEGs were mainly involved in the primary metabolic process, the carbohydrate metabolic process, the cellular process, ribosomes, the cytoplasm, and intracellular processes. A Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the DEGs were mainly enriched in steroid biosynthesis, the cell cycle, ribosomes, the TGF-beta signaling pathway, focal adhesion, and so on. We also observed the morphology of the follicles at different developmental stages, and the results showed that the thickness of the granular layer of the small yellow follicles (SYFs) decreased significantly with further development. In addition, we also found that the thickness of the granulosa layer of hens over 300 days old was significantly lower than that of 200-day-old hens. In short, these data indicate that the tissue morphology and function of granulosa cells change throughout follicle development.

Project description:Endometriosis, a common disease that presents as polymorphism, invasiveness, and extensiveness, with clinical manifestations including dysmenorrhea, infertility, and menstrual abnormalities, seriously affects quality of life in women. To date, its underlying etiological mechanism of action and the associated regulatory genes remain unclear. This study aimed to identify molecular markers and elucidate mechanisms underlying the development and progression of endometriosis. Specifically, we downloaded five microarray expression datasets, namely, GSE11691, GSE23339, GSE25628, GSE7305, and GSE105764, from the Gene Expression Omnibus (GEO) database. These datasets, obtained from endometriosis tissues, alongside normal controls, were subjected to in-depth bioinformatics analysis for identification of differentially expressed genes (DEGs), followed by analysis of their function and pathways via gene ontology (GO) and KEGG pathway enrichment analyses. Moreover, we constructed a protein-protein interaction (PPI) network to explore the hub genes and modules, and then applied machine learning algorithms support vector machine-recursive feature elimination and least absolute shrinkage and selection operator (LASSO) analysis to identify key genes. Furthermore, we adopted the CIBERSORTx algorithm to estimate levels of immune cell infiltration while the connective map (CMAP) database was used to identify potential therapeutic drugs in endometriosis. As a result, a total of 423 DEGs, namely, 233 and 190 upregulated and downregulated, were identified. On the other hand, a total of 1,733 PPIs were obtained from the PPI network. The DEGs were mainly enriched in immune-related mechanisms. Furthermore, machine learning and LASSO algorithms identified three key genes, namely, apelin receptor (APLNR), C-C motif chemokine ligand 21 (CCL21), and Fc fragment of IgG receptor IIa (FCGR2A). Furthermore, 16 small molecular compounds associated with endometriosis treatment were identified, and their mechanism of action was also revealed. Taken together, the findings of this study provide new insights into the molecular factors regulating occurrence and progression of endometriosis and its underlying mechanism of action. The identified therapeutic drugs and molecular markers may have clinical significance in early diagnosis of endometriosis.

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Proteomic Analysis Identifies Potential Markers for Chicken Primary Follicle Development.

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Proteomic Analysis Identifies Potential Markers for Chicken Primary Follicle Development.

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