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

Abstract

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.

Comparative Transcriptome Analysis Suggests Key Roles for 5-Hydroxytryptamlne Receptors in Control of Goose Egg Production

“…For example, transcriptome sequencing of the ovaries from hens with different egg numbers revealed an important role of the neuroactive ligand-receptor interaction pathway in the regulation of egg production performance [7]. Meanwhile, a key role for lipid metabolism in the process of follicle selection has also been recently identified by transcriptome sequencing of goose follicles at different developmental stages [8]. After hatching, the ovary of poultry differentiates into two parts, including the external cortex and internal medulla [9], with the cortex being composed of the stroma and numerous follicles [10].…”

Dynamics of the Transcriptome and Accessible Chromatin Landscapes During Early Goose Ovarian Development

“…One of the most exciting progresses in the first decade is the illustration of the pivotal roles of intra-ovarian factors (especially oocyte-derived ones) and oocyte-somatic cell interaction during primordial follicle formation and development (Guigon and Magre, 2006;Hsueh et al, 2015), and these events have recently been demonstrated to be associated with dynamic reorganization of open chromatin in both oocytes and somatic cells (Apostolou and Hochedlinger, 2013;Miyamoto et al, 2018;Gu et al, 2019). In contrast, there is almost a paucity of information about the accessible chromatin dynamic profiles during ovarian development in birds, although some epigenetic changes, such as chromatin remodeling, cytosine methylation, histone modification, and non-coding RNAs, have been evidenced to regulate avian ovarian cell functions (Krasikova et al, 2012;Guioli and Lovell-Badge, 2016;Li et al, 2019). At the transcriptomic level, a growing body of literature is emerging regarding genome-wide gene expression differences between ovaries of different breeds, or ovaries at different physiological stages, or ovarian follicles of different size class, or different types of ovarian cells, which assist in identification of a number of factors regulating avian ovarian functions (Kang et al, 2013;Xu et al, 2013;Hu et al, 2014;Li et al, 2019).…”

“…In contrast, there is almost a paucity of information about the accessible chromatin dynamic profiles during ovarian development in birds, although some epigenetic changes, such as chromatin remodeling, cytosine methylation, histone modification, and non-coding RNAs, have been evidenced to regulate avian ovarian cell functions (Krasikova et al, 2012;Guioli and Lovell-Badge, 2016;Li et al, 2019). At the transcriptomic level, a growing body of literature is emerging regarding genome-wide gene expression differences between ovaries of different breeds, or ovaries at different physiological stages, or ovarian follicles of different size class, or different types of ovarian cells, which assist in identification of a number of factors regulating avian ovarian functions (Kang et al, 2013;Xu et al, 2013;Hu et al, 2014;Li et al, 2019). Nevertheless, in addition to functional studies of a few genes (Johnson and Woods, 2009;Guioli et al, 2014;Zhao et al, 2017), very little is known about the critical events and regulation of early avian follicle development, including peri-hatching oocyte loss, oocyte nest breakdown and primordial follicle formation, and the primordial-to-secondary follicle transition.…”

Metabolomic Analysis of SCD During Goose Follicular Development: Implications for Lipid Metabolism

“…We speculate that the overexpression of SCD may facilitate the synthesis and subsequent esteri cation of cholesterol into lipid droplets (LDs) in goose GCs. Our recently published study demonstrated that vital miRNA-mRNA interactions related to lipid regulation, including LD formation, occur during goose follicular selection [19]. Furthermore, our research indicated that LD accumulation capacity depends on the stage of follicle development, with the highest lipid content found in F1 GCs (not publish).…”

“…In a previous study, we con rmed for the rst time that de novo lipogenesis (DNL) occurs in goose GCs [18]. More importantly, we identi ed miRNA-mRNA interaction pairs related to the regulation of lipid metabolism in goose follicular development [19]. As the capacity of oocytes to utilize glucose as the main energy source is limited [20], lipid metabolism in GCs is considered to be indispensable for oocyte maturation.…”