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Transcriptomic and proteomic analyses of ovarian follicles reveal the role of VLDLR in chicken follicle selection.

ABSTRACT: BACKGROUND:Follicle selection in chickens refers to the process of selecting one follicle from a group of small yellow follicles (SY, 6-8?mm in diameter) for development into 12-15?mm hierarchical follicles (usually F6 follicles), which is an important process affecting laying performance in the poultry industry. Although transcriptomic analysis of chicken ovarian follicles has been reported, integrated analysis of chicken follicles for selection by using both transcriptomic and proteomic approaches is still rarely performed. In this study, we compared the proteomes and transcriptomes of SY and F6 follicles in laying hens and identified several genes involved in chicken follicle selection. RESULTS:Transcriptomic analysis revealed 855 differentially expressed genes (DEGs) between SY follicles and F6 follicles in laying hens, among which 202 were upregulated and 653 were downregulated. Proteomic analysis revealed 259 differentially expressed proteins (DEPs), including 175 upregulated and 84 downregulated proteins. Among the identified DEGs and DEPs, changes in the expression of seven genes, including VLDLR1, WIF1, NGFR, AMH, BMP15, GDF6 and MMP13, and nine proteins, including VLDLR, VTG1, VTG3, PSCA, APOB, APOV1, F10, ZP2 and ZP3L2, were validated. Further analysis indicated that the mRNA level of chicken VLDLR was higher in F6 follicles than in SY follicles and was also higher in granulosa cells (GCs) than in thecal cells (TCs), and it was stimulated by FSH in GCs. CONCLUSIONS:By comparing the proteomes and transcriptomes of SY and F6 follicles in laying hens, we identified several differentially expressed proteins/genes that might play certain roles in chicken follicle selection. These data may contribute to the identification of functional genes and proteins involved in chicken follicle selection.

SUBMITTER: Chen Q

PROVIDER: S-EPMC7367319 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Transcriptomic and proteomic analyses of ovarian follicles reveal the role of VLDLR in chicken follicle selection.

Chen Qiuyue Q Wang Yiya Y Liu Zemin Z Guo Xiaoli X Sun Yi Y Kang Li L Jiang Yunliang Y

BMC genomics 20200716 1

<h4>Background</h4>Follicle selection in chickens refers to the process of selecting one follicle from a group of small yellow follicles (SY, 6-8 mm in diameter) for development into 12-15 mm hierarchical follicles (usually F6 follicles), which is an important process affecting laying performance in the poultry industry. Although transcriptomic analysis of chicken ovarian follicles has been reported, integrated analysis of chicken follicles for selection by using both transcriptomic and proteomi ...[more]

PMID: 32677893

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Project description:BackgroundFollicle selection in chickens refers to the process of selecting one follicle from a group of small yellow follicles (SY, 6-8 mm in diameter) for development into 12-15 mm hierarchal follicles (usually F6 follicles), which is controlled by sex hormones including follicle-stimulating factor (FSH), estrogen and progesterone. Follicle selection is a critical process impacting egg production in chicken, therefore, is the focus of many studies. Phosphorylation is important for the proper function of proteins, thus, needs to be analyzed by proteomic level.ResultIn this study, we compared the phosphoproteomes of SY and F6 follicles in laying hens and identified 2,386 phosphoproteins and 5,940 phosphosites, of which 4,235 sites of 1,963 phosphoproteins were quantified. From SY to F6 follicles, 190 phosphorylation sites of 149 proteins changed significantly, among which the phosphorylation level of lysine demethylase 1 A (LSD1) at the conserved 54th serine (LSD1Ser54p) was significantly upregulated in F6 follicles compared to SY follicles (p < 0.05); however, the expression of chicken LSD1 were not significantly different on both mRNA and protein levels. LSD1Ser54p is mainly located in the nucleus of both SY and F6 follicles, and was higher in F6 follicles than that of SY follicles revealed by both immunofluorescence and Western blotting. LSD1Ser54p level increased after treatment with 5 ng/mL and 10 ng/mL of FSH in the theca cells and the granulosa cells of pre-hierarchal follicles, and with 50 ng/mL in granulosa cells of hierarchal follicles. In the theca cells of hierarchal follicles, estrogen stimulated the level of LSD1Ser54p in a dosage-dependent manner, and in granulosa cells of pre-hierarchal follicles, 10 ng/mL of estrogen increased LSD1Ser54p expression. Treatment with 50 ng/mL of progesterone increased LSD1Ser54p expression in theca cells of pre-hierarchal follicles, and with 10 to 100 ng/ml enhanced LSD1Ser54p expression in the granulosa cells of hierarchal follicles.ConclusionThe expression dynamics of LSD1Ser54p in follicles from SY to F6 and its regulation by sex hormones suggest that it is involved in chicken follicle selection.

Project description:ObjectiveFollicle selection is an important process in chicken egg laying. Among several small yellow (SY) follicles, the one exhibiting the highest expression of follicle stimulation hormone receptor (FSHR) will be selected to become a hierarchal follicle. The role of lncRNA, miRNA and other non-coding RNA in chicken follicle selection is unclear.MethodsIn this study, the whole transcriptome sequencing of SY follicles with different expression levels of FSHR in Jining Bairi hens was performed, and the expression of 30 randomly selected mRNAs, lncRNAs and miRNAs was validated by quantitative real-time polymerase chain reaction. Preliminary studies and bioinformatics analysis were performed on the selected mRNA, lncRNA, miRNA and their target genes. The effect of identified gene was examined in the granulosa cells of chicken follicles.ResultsIntegrated transcriptomic analysis on chicken SY follicles differing in FSHR expression revealed 467 differentially expressed mRNA genes, 134 differentially expressed lncRNA genes and 34 differentially expressed miRNA genes, and sosondowah ankyrin repeat domain family member A (SOWAHA) was the common target gene of three miRNAs and one lncRNA. SOWAHA was mainly expressed in small white (SW) and SY follicles and was affected by follicle stimulation hormone (FSH) treatment in the granulosa cells. Knockdown of SOWAHA inhibited the expression of Wnt family member 4 (Wnt4) and steroidogenic acute regulatory protein (StAR) in the granulosa cells of prehierarchal follicles, while stimulated Wnt4 in hierarchal follicles. Overexpression of SOWAHA increased the expression of Wnt4 in the granulosa cells of prehierarchal follicles, decreased that of StAR and cytochrome P450 family 11 subfamily A member 1 in the granulosa cells of hierarchal follicles and inhibited the proliferation of granulosa cells.ConclusionIntegrated analysis of chicken SY follicle transcriptomes identified SOWAHA as a network gene that is affected by FSH in granulosa cells of ovarian follicles. SOWAHA affected the expression of genes involved in chicken follicle selection and inhibited the proliferation of granulosa cells, suggesting an inhibitory role in chicken follicle selection.

Project description:Ovarian follicle selection is an important process impacting the laying performance and fecundity of hens, and is regulated by follicle-stimulating hormone (FSH) through binding to its receptor [follicle-stimulating hormone receptor (FSHR)]. In laying hens, the small yellow follicle (6-8 mm in diameter) with the highest expression of FSHR will be recruited into the preovulatory hierarchy during ovarian follicle development. The study of molecular mechanism of chicken follicle selection is helpful for the identification of genes underlying egg-laying traits in chicken and other poultry species. Herein, the transcriptomes of chicken small yellow follicles differing in the mRNA expression of FSHR were compared, and a total of 17,993 genes were identified in 3 pairs of small yellow follicles. The Wnt signaling pathway was significantly enriched in the follicles with the greatest fold change in FSHR expression. In this pathway, the expression level of Wnt4 mRNA was significantly upregulated with a log2(fold change) of 2.12. We further investigated the expression, function, and regulation of Wnt4 during chicken follicle selection and found that Wnt4 mRNA reached its peak in small yellow follicles; Wnt4 stimulated the proliferation of follicular granulosa cells (GCs), increased the expression of StAR and CYP11A1 mRNA in prehierarchical and hierarchical follicles, increased the expression of FSHR mRNA, and decreased the expression of anti-Müllerian hormone and OCLN mRNA. Treatment with FSH significantly increased Wnt4 expression in GCs. Moreover, Wnt4 facilitated the effects of FSH on the production of progesterone (P4) and the mRNA expression of steroidogenic enzyme genes in the GCs of hierarchical follicles, but inhibited the effects of FSH in the GCs of prehierarchical follicles. Collectively, these data suggest that Wnt4 plays an important role in chicken follicle selection by stimulating GC proliferation and steroidogenesis. This study provides a theoretical basis for improving the egg-laying performance of chicken and a reference for the elucidation of the molecular mechanism of follicular selection in mammals.

Project description:BackgroundThere has been a significant surge in the global prevalence of diabetes mellitus (DM), which increases the susceptibility of individuals to ovarian cancer (OC). However, the relationship between DM and OC remains largely unexplored. The objective of this study is to provide preliminary insights into the shared molecular regulatory mechanisms and potential biomarkers between DM and OC.MethodsMultiple datasets from the GEO database were utilized for bioinformatics analysis. Single cell datasets from the GEO database were analysed. Subsequently, immune cell infiltration analysis was performed on mRNA expression data. The intersection of these datasets yielded a set of common genes associated with both OC and DM. Using these overlapping genes and Cytoscape, a protein‒protein interaction (PPI) network was constructed, and 10 core targets were selected. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then conducted on these core targets. Additionally, advanced bioinformatics analyses were conducted to construct a TF-mRNA-miRNA coregulatory network based on identified core targets. Furthermore, immunohistochemistry staining (IHC) and real-time quantitative PCR (RT-qPCR) were employed for the validation of the expression and biological functions of core proteins, including HSPAA1, HSPA8, SOD1, and transcription factors SREBF2 and GTAT2, in ovarian tumors.ResultsThe immune cell infiltration analysis based on mRNA expression data for both DM and OC, as well as analysis using single-cell datasets, reveals significant differences in mononuclear cell levels. By intersecting the single-cell datasets, a total of 119 targets related to mononuclear cells in both OC and DM were identified. PPI network analysis further identified 10 hub genesincludingHSP90AA1, HSPA8, SNRPD2, UBA52, SOD1, RPL13A, RPSA, ITGAM, PPP1CC, and PSMA5, as potential targets of OC and DM. Enrichment analysis indicated that these genes are primarily associated with neutrophil degranulation, GDP-dissociation inhibitor activity, and the IL-17 signaling pathway, suggesting their involvement in the regulation of the tumor microenvironment. Furthermore, the TF-gene and miRNA-gene regulatory networks were validated using NetworkAnalyst. The identified TFs included SREBF2, GATA2, and SRF, while the miRNAs included miR-320a, miR-378a-3p, and miR-26a-5p. Simultaneously, IHC and RT-qPCR reveal differential expression of core targets in ovarian tumors after the onset of diabetes. RT-qPCR further revealed that SREBF2 and GATA2 may influence the expression of core proteins, including HSP90AA1, HSPA8, and SOD1.ConclusionThis study revealed the shared gene interaction network between OC and DM and predicted the TFs and miRNAs associated with core genes in monocytes. Our research findings contribute to identifying potential biological mechanisms underlying the relationship between OC and DM.

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Transcriptomic and proteomic analyses of ovarian follicles reveal the role of VLDLR in chicken follicle selection.

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Transcriptomic and proteomic analyses of ovarian follicles reveal the role of VLDLR in chicken follicle selection.

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