Dynamic Changes in the Follicular Transcriptome and Promoter DNA Methylation Pattern of Steroidogenic Genes in Chicken Follicles throughout the Ovulation Cycle

The influence of CCN family proteins on ovarian physiology and pathology

The CCN family of proteins is comprised of six matricellular proteins known to regulate multiple cellular processes such as adhesion, proliferation, differentiation, and apoptosis. CCN proteins are known to function through the binding of integrin receptors and through the regulation of growth factors and cytokines in the context of cardiovascular and skeletal development, injury repair, fibrosis, inflammation and cancer. The expression and roles of several CCNs, particularly CCN1 and CCN2, have been investigated in the ovary as they are effectors of the Hippo signaling pathway, and their role in the development of ovarian fibrosis has been described. Here we review the patterns of expression of CCN1-6 in the ovarian follicle, and the role of CCN2 in follicle development and steroidogenesis, and the expression and potential actions of CCN1-6 in ovarian cancers. We highlight the roles CCNs may play in inflammatory processes, and put forth a case for CCN involvement in the process of ovulation.

DNA Methylation Patterns and Transcriptomic Data Were Integrated to Investigate Candidate Genes Influencing Reproductive Traits in Ovarian Tissue from Sichuan White Geese

Ovarian tissue is critical for goose reproduction. This study aimed to investigate gene regulation by DNA methylation in relation to the reproductive traits of geese. We performed whole-genome bisulfite sequencing (WGBS) on ovarian tissues from Sichuan white geese (high-laying-rate group: HLRG, ♀ = 3; low-laying-rate group: LLRG, ♀ = 3) during the laying period. The results showed a higher level of hypermethylated differentially methylated regions (DMRs) in the HLRG, indicating a higher overall methylation level compared to the LLRG. In total, we identified 2831 DMRs and 733 differentially methylated genes (DMGs), including 363 genes with upregulated methylation. These DMGs were significantly enriched in pathways related to microtubule function (GO:0005874; GO:0000226), GnRH secretion, thyroid hormone signaling, ECM-receptor interaction, and PI3K-Akt signaling. Integration with RNA-seq data identified eight overlapping genes between DMGs and differentially expressed genes (DEGs), with five genes (CUL9, MEGF6, EML6, SYNE2, AK1BA) exhibiting a correlation between hypomethylation and high expression. EML6, in particular, emerged as a promising candidate, potentially regulating follicle growth and development in Sichuan white geese. Future studies should focus on further verifying the role of the EML6 gene. In conclusion, this study provides important insights into the regulatory mechanisms of DNA methylation influencing reproductive traits in geese, offering novel candidate markers for future goose breeding programs.

Transcriptome and chromatin accessibility landscape of ovarian development at different egg-laying stages in taihe black-bone silky fowls

Taihe Black-Bone Silky Fowl (SF) is a famous local breed in China, known for its high nutritional and medicinal value. However, its low egg-laying rate significantly limits its economic benefits. This study aims to explore the ovarian development status, as well as the changes in the transcriptome and chromatin accessibility landscape at different egg-laying stages of SF, in order to reveal the epigenetic regulatory mechanisms underlying ovarian development in laying hens. The results showed that during peak egg-laying, serum levels of follicle stimulating hormone (FSH), luteinizing hormone (LH), estradiol (E2), and progesterone (P4) in the SF were higher than in the other laying periods. Meanwhile, the serum and ovarian matrix total antioxidant capacity (T-AOC) level decreased with increasing age, whereas the ovarian matrix malondialdehyde (MDA) level showed the opposite trend. Compared to the late laying period, several genes related to ovarian development and reproductive hormone secretion, including TDRD5, CCNO, CYP17A1, BMP15, and STAR, were upregulated during the peak egg-laying period. Additionally, we identified key transcription factors (TF) associated with different egg-laying periods. Specific TF, such as Fli1, Etv2, and AT2G15740, linked to the peak egg-laying period, play significant roles in cell and tissue development. The specific transcription factor Nr5a2, associated with the late laying period, has been shown to inhibit E2 production. Furthermore, genes related to poultry reproductive performance, such as STAR and WNT4, were found to be regulated by specific distal enhancers in open chromatin regions (OCR). In conclusion, this study elucidated the dynamic changes in the transcriptome and chromatin accessibility landscape during ovarian development in SF at different egg-laying stages and highlighted key TF, including Fli1, Etv2, and Nr5a2, as well as essential genes like STAR and WNT4 that regulate ovarian development. These findings provide valuable insights into the regulatory mechanisms influencing egg-laying performance in SF and offer new strategies for improving ovarian follicle development and egg production performance in poultry.

Cross-species regulatory network analysis identifies FOXO1 as a driver of ovarian follicular recruitment

The transcriptional regulation of gene expression in the latter stages of follicular development in laying hen ovarian follicles is not well understood. Although differentially expressed genes (DEGs) have been identified in pre-recruitment and pre-ovulatory stages, the master regulators driving these DEGs remain unknown. This study addresses this knowledge gap by utilizing Master Regulator Analysis (MRA) combined with the Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) for the first time in laying hen research to identify master regulators that are controlling DEGs in pre-recruitment and pre-ovulatory phases. The constructed ARACNe network included 10,466 nodes and 292,391 edges. The ARACNe network was then used in conjunction with the Virtual Inference of Protein-activity by Enriched Regulon (VIPER) for the MRA to identify top up- and down-regulated master regulators. VIPER analysis revealed FOXO1 as a master regulator, influencing 275 DEGs and impacting pathways related to apoptosis, proliferation, and hormonal regulation. Additionally, CLOCK, known as a crucial regulator of circadian rhythm, emerged as an upregulated master regulator in the pre-ovulatory stage. These findings provide new insights into the transcriptional landscape of laying hen ovarian follicles, offering a foundation for further exploration of follicle development and enhancing reproductive efficiency in avian species.

Chicken ovarian follicular atresia: interaction network at organic, cellular, and molecular levels

Most of follicles undergo a degenerative process called follicular atresia. This process directly affects the egg production of laying hens and is regulated by external and internal factors. External factors primarily include nutrition and environmental factors. In follicular atresia, internal factors are predominantly regulated at 3 levels; organic, cellular and molecular levels. At the organic level, the hypothalamic-pituitary-ovary (HPO) axis plays an essential role in controlling follicular development. At the cellular level, gonadotropins and cytokines, as well as estrogens, bind to their receptors and activate different signaling pathways, thereby suppressing follicular atresia. By contrast, oxidative stress induces follicular atresia by increasing ROS levels. At the molecular level, granulosa cell (GC) apoptosis is not the only factor triggering follicular atresia. Autophagy is also known to give rise to atresia. Epigenetics also plays a pivotal role in regulating gene expression in processes that seem to be related to follicular atresia, such as apoptosis, autophagy, proliferation, and steroidogenesis. Among these processes, the miRNA regulation mechanism is well-studied. The current review focuses on factors that regulate follicular atresia at organic, cellular and molecular levels and evaluates the interaction network among these levels. Additionally, this review summarizes atretic follicle characteristics, in vitro modeling methods, and factors preventing follicular atresia in laying hens.

miRNA profiling of chicken follicles during follicular development

MicroRNAs (miRNAs) play a crucial role as transcription regulators in various aspects of follicular development, including steroidogenesis, ovulation, apoptosis, and gene regulation in poultry. However, there is a paucity of studies examining the specific impact of miRNAs on ovarian granulosa cells (GCs) across multiple grades in laying hens. Consequently, this study aims to investigate the roles of miRNAs in chicken GCs. By constructing miRNA expression profiles of GCs at 10 different time points, encompassing 4 pre-hierarchical, 5 preovulatory, and 1 postovulatory follicles stage, we identified highly expressed miRNAs involved in GC differentiation (miR-148a-3p, miR-143-3p), apoptosis (let7 family, miR-363-3p, miR-30c-5p, etc.), and autophagy (miR-128-3p, miR-21-5p). Furthermore, we discovered 48 developmentally dynamic miRNAs (DDMs) that target 295 dynamic differentially expressed genes (DDGs) associated with follicular development and selection (such as oocyte meiosis, progesterone-mediated oocyte maturation, Wnt signaling pathway, TGF-β signaling pathway) as well as follicular regression (including autophagy and cellular senescence). These findings contribute to a more comprehensive understanding of the intricate mechanisms underlying follicle recruitment, selection, and degeneration, aiming to enhance poultry's reproductive capacity.

Transcriptome-wide m6A methylation profiling of Wuhua yellow-feathered chicken ovary revealed regulatory pathways underlying sexual maturation and low egg-laying performance

RNA N6-melthyladenosine (m6A) can play an important role in regulation of various biological processes. Chicken ovary development is closely related to egg laying performance, which is a process primarily controlled by complex gene regulations. In this study, transcriptome-wide m6A methylation of the Wuhua yellow-feathered chicken ovaries before and after sexual maturation was profiled to identify the potential molecular mechanisms underlying chicken ovary development. The results indicated that m6A levels of mRNAs were altered dramatically during sexual maturity. A total of 1,476 differential m6A peaks were found between these two stages with 662 significantly upregulated methylation peaks and 814 downregulated methylation peaks after sexual maturation. A positive correlation was observed between the m6A peaks and gene expression levels, indicating that m6A may play an important role in regulation of chicken ovary development. Functional enrichment analysis indicated that apoptosis related pathways could be the key molecular regulatory pathway underlying the poor reproductive performance of Wuhua yellow-feathered chicken. Overall, the various pathways and corresponding candidate genes identified here could be useful to facilitate molecular design breeding for improving egg production performance in Chinese local chicken breed, and it might also contribute to the genetic resource protection of valuable avian species.

Chicken Hypothalamic and Ovarian DNA Methylome Alteration in Response to Forced Molting

Epigenetic modifications play an important role in regulating animal adaptation to external stress. To explore how DNA methylation regulates the expression levels of related genes during forced molting (FM) of laying hens, the hypothalamus and ovary tissues were analyzed at five periods using Whole-Genome Bisulfite Sequencing. The results show that methylation levels fluctuated differently in the exon, intron, 5′UTR, 3′UTR, promoter, and intergenic regions of the genome during FM. In addition, 16 differentially methylated genes (DMGs) regulating cell aging, immunity, and development were identified in the two reversible processes of starvation and redevelopment during FM. Comparing DMGs with differentially expressed genes (DEGs) obtained in the same periods, five hypermethylated DMGs (DSTYK, NKTR, SMOC1, SCAMP3, and ATOH8) that inhibited the expression of DEGs were found. Therefore, DMGs epigenetically modify the DEGs during the FM process of chickens, leading to the rapid closure and restart of their reproductive function and a re-increase in the egg-laying rate. Therefore, this study further confirmed that epigenetic modifications could regulate gene expression during FM and provides theoretical support for the subsequent optimization of FM technology.

Long-read sequencing reveals the effect of follicle-stimulating hormone on the mRNA profile of chicken granulosa cells from prehierarchical follicles

Follicle selection is an important step in the laying process of chicken, which is closely related to the laying performance and fecundity of hens. Follicle selection mainly depends on the regulation of follicle-stimulating hormone (FSH) secreted by pituitary gland and the expression of follicle stimulation hormone receptor. To uncover the role of FSH in chicken follicle selection, in this study, we analyzed the changes in the mRNA transcriptome profiles of FSH-treated chicken granulosa cells from prehierarchical follicles by long-read sequencing Oxford Nanopore Technologies (ONT) approach. Among the 10,764 genes detected, 31 differentially expressed (DE) transcripts of 28 DE genes were significantly upregulated by FSH treatment. These DE transcripts (DETs) were mainly related to the steroid biosynthetic process by GO analysis and enriched in pathways of ovarian steroidogenesis and aldosterone synthesis and secretion by KEGG analysis. Among these genes, the mRNA and protein expression of TNF receptor associated factor 7 (TRAF7) was upregulated after FSH treatment. Further study revealed that TRAF7 stimulated the mRNA expression of steroidogenic enzymes steroidogenic acute regulatory protein (StAR) and cytochrome P450 family 11 subfamily A member 1 (CYP11A1) genes and the proliferation of granulosa cells. This is the first study to investigate differences in chicken prehierarchical follicular granulosa cells before and after FSH treatment by using ONT transcriptome sequencing, which provides a reference for a more comprehensive understanding of the molecular mechanism of follicle selection in chicken.

Interacting Networks of the Hypothalamic-Pituitary-Ovarian Axis Regulate Layer Hens Performance

Egg production is a vital biological and economic trait for poultry breeding. The 'hypothalamic-pituitary-ovarian (HPO) axis' determines the egg production, which affects the layer hens industry income. At the organism level, the HPO axis is influenced by the factors related to metabolic and nutritional status, environment, and genetics, whereas at the cellular and molecular levels, the HPO axis is influenced by the factors related to endocrine and metabolic regulation, cytokines, key genes, signaling pathways, post-transcriptional processing, and epigenetic modifications. MiRNAs and lncRNAs play a critical role in follicle selection and development, atresia, and ovulation in layer hens; in particular, miRNA is known to affect the development and atresia of follicles by regulating apoptosis and autophagy of granulosa cells. The current review elaborates on the regulation of the HPO axis and its role in the laying performance of hens at the organism, cellular, and molecular levels. In addition, this review provides an overview of the interactive network regulation mechanism of the HPO axis in layer hens, as well as comprehensive knowledge for successfully utilizing their genetic resources.

Comparative Transcriptome Analysis Provides Novel Insights into the Effect of Lipid Metabolism on Laying of Geese

Simple Summary

The importance of lipid metabolism in the egg production of poultry has been widely reported. Meanwhile, geese have lower egg production and unique lipid metabolism patterns compared with chicken and duck. It is of great significance to further improve egg laying performance to explore the differences of fat metabolism and the molecular mechanisms in geese with different egg laying performance. This study compared the phenotypic differences of liver and abdominal fat, as well as the transcriptome level differences of liver, abdominal fat, and ovarian stroma among high-, low-, and no-egg production groups. The results reveal that lipid metabolism regulated by the circadian rhythm of the liver may directly or indirectly affect ovarian function through the inflammation and hormone secretion of abdominal fat.

Abstract

The lower egg production of geese (20~60 eggs per year) compared with chicken and duck limits the development of the industry, while the yolk weight and fatty liver susceptibility of geese was higher than that of other poultry. Therefore, the relationship between lipid metabolism and the laying performance of geese remains to be explored. Phenotypically, we observed that the liver fat content of the high-, low-, and no-egg production groups decreased in turn, while the abdominal fat weight increased in turn. For transcriptional regulation, the KEGG pathways related to lipid metabolism were enriched in all pairwise comparisons of abdominal fat and liver through functional analysis. However, some KEGG pathways related to inflammation and the circadian rhythm pathway were enriched by DEGs only in abdominal fat and the liver, respectively. The DEGs in ovarian stroma among different groups enriched some KEGG pathways related to ovarian steroidogenesis and cell adhesion. Our research reveals that lipid metabolism regulated by the circadian rhythm of the liver may directly or indirectly affect ovarian function through the inflammation and hormone secretion of abdominal fat. These results offer new insights into the regulation mechanisms of goose reproductive traits.

Transcriptome analyses of potential regulators of pre- and post-ovulatory follicles in the pigeon (Columba livia)

To identify the dominant genes controlling follicular maturation, ovulation and regression for pigeon, we used RNA-seq to explore the gene expression profiles of pre- and post-ovulatory follicles of pigeon. We obtained total of 4.73million (96% of the raw data) high-quality clean reads, which could be aligned with 20282 genes. Gene expression profile analysis identified 1461 differentially expressed genes (DEGs) between the pre- (P4) and post-ovulatory follicles (P5). Of these, 843 genes were upregulated, and 618 genes were down-regulated. Furthermore, many DEGs were significantly enriched in some pathways closely related to follicle maturation, ovulation and regression, such as ECM-receptor interaction, vascular smooth muscle contraction, progesterone-mediated oocyte maturation, phagosome. Importantly, the DGEs in ECM-receptor interaction pathway included COL1A1 , COL1A2 , COL4A1 , COL4A2 , ITGA11 , ITGB3 and SDC3 , in the progesterone-mediated oocyte maturation pathway involved CDK1 , CDC25A , CCNB3 , CDC20 and Plk1 , and in the vascular smooth muscle contraction covered CALD1 , KCNMA1 , KCNMB1 , CACNA1 , ACTA2 , MYH10 , MYL3 , MYL6 , MYL9 , closely related to promoting follicular maturation and ovulation in pre-ovulatory follicles. Moreover, it seems that the lysosomal cathepsin family has a decisive role in the regression of early stage of post-ovulatory follicle. Taken together, these data enrich the research of molecular mechanisms of pigeon follicular activities at the transcriptional level and provide novel insight of breeding-related physiology for birds.

Dynamic transcriptome and chromatin architecture in granulosa cells during chicken folliculogenesis

Folliculogenesis is a complex biological process involving a central oocyte and its surrounding somatic cells. Three-dimensional chromatin architecture is an important transcription regulator; however, little is known about its dynamics and role in transcriptional regulation of granulosa cells during chicken folliculogenesis. We investigate the transcriptomic dynamics of chicken granulosa cells over ten follicular stages and assess the chromatin architecture dynamics and how it influences gene expression in granulosa cells at three key stages: the prehierarchical small white follicles, the first largest preovulatory follicles, and the postovulatory follicles. Our results demonstrate the consistency between the global reprogramming of chromatin architecture and the transcriptomic divergence during folliculogenesis, providing ample evidence for compartmentalization rearrangement, variable organization of topologically associating domains, and rewiring of the long-range interaction between promoter and enhancers. These results provide key insights into avian reproductive biology and provide a foundational dataset for the future in-depth functional characterization of granulosa cells.

The domestic chicken Gallus gallus domesticus is a classic model for the study of folliculogenesis. Here the authors integrate multi-omics analyses characterizing the dynamic transcriptome and chromatin architecture in granulosa cells during chicken folliculogenesis.

Comparative analysis of hypothalamus transcriptome between laying hens with different egg-laying rates

Egg-laying performance is one of the most important economic traits in the poultry industry. Commercial layers can lay one egg almost every day during their peak-laying period. However, many Chinese indigenous chicken breeds show a relatively low egg-laying rate, even during their peak-laying period. To understand what makes the difference in egg production, we compared the hypothalamus transcriptome profiles of Lushi blue-shelled-egg chickens (LBS), a Chinese indigenous breed with low egg-laying rate and Rhode Island Red chickens (RIR), a commercial layer with relatively high egg-laying rate using RNA-seq. A total of 753 differentially expressed genes (DEGs) were obtained. Of these DEGs, 38 genes were enriched in 2 Gene Ontology (GO) terms, namely reproduction term and the reproductive process term, and 6 KEGG pathways, namely Wnt signaling pathway, Oocyte meiosis, GnRH signaling pathway, Thyroid hormone signaling pathway, Thyroid hormone synthesis and MAPK signaling pathway, which have been long known to be involved in egg production regulation. To further determine the core genes from the 38 DEGs, protein-protein interaction (PPI) network, co-expression network and transcriptional regulatory network analyses were carried out. After integrated analysis and experimental validation, 4 core genes including RAC1, MRE11A, MAP7 and SOX5 were identified as the potential core genes that are responsible for the laying-rate difference between the 2 breeds. These findings paved the way for future investigating the mechanism of egg-laying regulation and enriched the chicken reproductive regulation theory.

Ovarian transcriptomic analysis of black Muscovy duck at the early, peak and late egg-laying stages

Ovarian development is a complex process involving many genes and pathways. A well-developed ovary is essential for poultry to keep high egg production and egg fertility. In order to better understand the mechanism of egg production performance, a comparative transcriptomic analysis was performed on ovaries of black Muscovy ducks at the early (BE), peak (BP) and late laying (BL) stages. 1683 DEGs were identified from BL-vs-BE, BL-vs-BP and BP-vs-BE, and the up-regulated genes were 41, 835, 260, the down-regulated genes were 60, 255, 730, respectively. Besides, there were 32, 20 and 424 DEGs co-expressed in the two comparison groups, and 11 DEGs were co-expressed in the three comparison groups. HOXA10, HtrA3, StAR, ZP2 and TAT were found to be involved in the regulation of ovarian development were significantly differentially expressed at different laying stages, which helped to regulate ovarian maturation and egg production. Moreover, we discovered several important functional pathways, such as steroid hormone biosynthesis and ovarian steroidogenesis, that appear to be much more active in the BP ovary compared to those of the BE and BL. Furthermore, 17 coding and 244 non-coding new transcripts were detected in the three comparison groups, the gene structures were optimized and the gene annotation informations were improved. These findings will provide a solid foundation on ovarian development in black Muscovy ducks and other poultry animals at different laying stages, and help to understand the complex molecular and cellular mechanisms of ovary.

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

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.

Transcriptomic Analysis of circRNAs and mRNAs Reveals a Complex Regulatory Network That Participate in Follicular Development in Chickens

Follicular development plays a key role in poultry reproduction, affecting clutch traits and thus egg production. Follicular growth is determined by granulosa cells (GCs), theca cells (TCs), and oocyte at the transcription, translation, and secretion levels. With the development of bioinformatic and experimental techniques, non-coding RNAs have been shown to participate in many life events. In this study, we investigated the transcriptomes of GCs and TCs in three different physiological stages: small yellow follicle (SYF), smallest hierarchical follicle (F6), and largest hierarchical follicle (F1) stages. A differential expression (DE) analysis, weighted gene co-expression network analysis (WGCNA), and bioinformatic analyses were performed. A total of 18,016 novel circular RNAs (circRNAs) were detected in GCs and TCs, 8127 of which were abundantly expressed in both cell types. and more circRNAs were differentially expressed between GCs and TCs than mRNAs. Enrichment analysis showed that the DE transcripts were mainly involved in cell growth, proliferation, differentiation, and apoptosis. In the WGCNA analysis, we identified six specific modules that were related to the different cell types in different stages of development. A series of central hub genes, including MAPK1, CITED4, SOD2, STC1, MOS, GDF9, MDH1, CAPN2, and novel_circ0004730, were incorporated into a Cytoscape network. Notably, using both DE analysis and WGCNA, ESR1 was identified as a key gene during follicular development. Our results provide valuable information on the circRNAs involved in follicle development and identify potential genes for further research to determine their roles in the regulation of different biological processes during follicle growth.

Transcriptome Analysis of circRNA and mRNA in Theca Cells during Follicular Development in Chickens

Development of ovarian follicles requires interactions between granulosa cells, theca cells, and oocytes. Multiple transcription levels are involved but information about the role of noncoding RNAs, especially circular RNAs (circRNAs), is lacking. Here, we used RNA sequencing to profile circRNAs and mRNAs in theca cells from three types of follicle: small yellow follicles (SYF), the smallest hierarchical follicles (F6), and the largest hierarchical follicles (F1). Using bioinformatics analysis, we identified a total of 14,502 circRNAs in all theca cells, with 5622 widely distributed in all stages of development. Differential expression analysis suggested that some genes display differential isoforms during follicular development. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed enrichment of both differentially expressed circRNAs and mRNAs in pathways associated with reproduction, including the TGF-β signaling pathway, oocyte meiosis, and vascular smooth muscle contraction. Our study provides the first visual information about circRNAs and mRNAs in theca cells during follicle development in chickens and adds to the growing body of knowledge about theca cells.

Profiling of RNA N6-methyladenosine methylation during follicle selection in chicken ovary

Ovarian follicle selection is the critical step which determines the oocyte development and ovulation. In avian species, the somatic cells in the follicles decide the process of follicle selection but the precise molecular regulation is not well defined. N6-methyladenosine (m6A) is a ubiquitous reversible epigenetic RNA modification that plays an important role in the gene expression regulation and cell functions. In this study, we profiled transcriptome-wide m6A methylation in chicken follicles during follicular selection process in order to identify key factors involved in the follicle selection. The chicken follicle transcriptome was extensively methylated by m6A and a negative correlation was found between the m6A methylation enrichment and gene expression levels. Interestingly, both the m6A methylation peaks and the m6A modified transcripts increased during follicle selection, which lead to the dynamic expression of many folliculogenesis relevant genes. Functional enrichment analysis indicated that m6A modification of key factors in Wnt pathway could play a major role in regulating follicle selection. This study is the first to comprehensively characterize the m6A patterns in the chicken transcriptome, and provides deep insights into the m6A topology and relevant molecular mechanisms underlying follicle selection.

Dynamic expression and functional analysis of circRNA in granulosa cells during follicular development in chicken

Background

Circular RNA (circRNA) is a type of noncoding RNA involved in a variety of biological processes, especially in post-transcriptional regulation. The granulosa cells of follicles play a determining role in ovarian development. However, the function of circRNA in chicken follicles is unclear. To better understand the molecular mechanism underlying follicular development and granulosa cell function, we performed a strategy of second-generation sequencing and linear RNA depletion for granulosa cells from small yellow follicles (SYF, 5–8 mm), the smallest hierarchal follicles (F6, 9–12 mm), and the largest hierarchal follicles (F1, ~ 40 mm).

Results

We predicted a total of 11,642 circRNAs that distributed on almost all chromosomes. The majority of the splice lengths of circRNAs were 200–500 nt and mainly produced from intron and CDS regions. During follicle growth, differentially expressed (DE) circRNAs showed dynamic changes which were tissue- and stage-specific. The host genes of DE circRNAs were functionally enriched in GTPase activity and several pathways involved in reproduction. Moreover, bioinformatic prediction analysis for circRalGPS2 demonstrated that circRNAs from the same genes may share common miRNA to act as a sponge. The predicted target genes were enriched in various biological processes including cognition, cell communication, and regulation of signaling, and several pathways related to reproduction such as tight junction, oocyte meiosis, progesterone-mediated oocyte maturation, and GnRH signaling.

Conclusions

This study provides a starting point for further experimental investigations into chicken circRNAs and casts a light on the understanding of follicle development.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5462-2) contains supplementary material, which is available to authorized users.

Dynamic Changes in the Global MicroRNAome and Transcriptome Identify Key Nodes Associated With Ovarian Development in Chickens

The analysis of gene expression patterns during ovarian follicle development will advance our understanding of avian reproductive physiology and make it possible to improve laying performance. To gain insight into the molecular regulation of ovarian development, a systematic profiling of miRNAs and mRNAs at four key stages was conducted, using ovarian tissues from hens at 60 days of age (A), 100 days (B), 140 days-not yet laying (C), and 140 days-laying (D). Comparisons of consecutive stages yielded 73 differentially expressed miRNAs (DEMs) (14 for B vs. A, 8 for C vs. B, and 51 for D vs. C) and 2596 differentially expressed genes (DEGs) (51 for B vs. A, 20 for C vs. B, and 2579 for D vs. C). In addition, 174 DEMs (22 for C vs. A, 74 for D vs. A, and 78 for D vs. B) and 3205 DEGs (118 for C vs. A, 2284 for D vs. A, and 2882 for D vs. B) were identified between nonconsecutive stages. Some DEGs are involved in the Wnt and TGF-beta signaling pathways, which are known to affect ovarian development and ovulation. An integrative analysis of the miRNA and mRNA profiles identified 3166 putative miRNA-mRNA regulatory pairs containing 84 DEMs and 1047 DEGs. Functional annotation of the networks provides strong evidence that the miRNA regulatory networks may play vital roles in ovarian development and ovulation. Ten DEMs and 10 genes were validated by real-time quantitative PCR. The candidate miRNA-mRNA pairs gga-miR-200a-3p-SFRP4, gga-miR-101-3p-BMP5, gga-miR-32-5p-FZD4, and gga-miR-458b-5p-CTNNB1 potentially associated with ovarian development.

Combination of novel and public RNA-seq datasets to generate an mRNA expression atlas for the domestic chicken

Background

The domestic chicken (Gallus gallus) is widely used as a model in developmental biology and is also an important livestock species. We describe a novel approach to data integration to generate an mRNA expression atlas for the chicken spanning major tissue types and developmental stages, using a diverse range of publicly-archived RNA-seq datasets and new data derived from immune cells and tissues.

Results

Randomly down-sampling RNA-seq datasets to a common depth and quantifying expression against a reference transcriptome using the mRNA quantitation tool Kallisto ensured that disparate datasets explored comparable transcriptomic space. The network analysis tool Graphia was used to extract clusters of co-expressed genes from the resulting expression atlas, many of which were tissue or cell-type restricted, contained transcription factors that have previously been implicated in their regulation, or were otherwise associated with biological processes, such as the cell cycle. The atlas provides a resource for the functional annotation of genes that currently have only a locus ID. We cross-referenced the RNA-seq atlas to a publicly available embryonic Cap Analysis of Gene Expression (CAGE) dataset to infer the developmental time course of organ systems, and to identify a signature of the expansion of tissue macrophage populations during development.

Conclusion

Expression profiles obtained from public RNA-seq datasets – despite being generated by different laboratories using different methodologies – can be made comparable to each other. This meta-analytic approach to RNA-seq can be extended with new datasets from novel tissues, and is applicable to any species.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4972-7) contains supplementary material, which is available to authorized users.

Tamoxifen activates hypothalamic l-dopa synthesis to stimulate ovarian estrogen production in chicken

Estrogen is the primary sex hormone responsible for the development and modulation of the female reproductive system in all vertebrates including avian species. The actions of estrogen are mediated by the estrogen receptor, which could be modulated by the selective estrogen receptor modulator tamoxifen (TAM). In this study, we administered TAM into the actively laying chicken to investigate the ovarian and hypothalamic responses to the estrogen action blockage. The laying was disrupted and the development of the pre-ovulatory hierarchical follicles was arrested. However, the TAM treatment caused an increase of estrogen level in both serum and ovary. Among the main estrogen targeted tissues, the hypothalamus showed specific dopaminergic activation as indicated by gene expression analysis. In the ovary, l-dopa, the precursor of dopamine, could stimulate the estrogen synthesis in undifferentiated follicles but not in the differentiated pre-ovulatory follicles. Thus, we established a feedback loop links ovarian estrogen production with hypothalamic l-dopa synthesis and we propose that the dopamine is involved in estrogen action to regulate the ovarian follicle development and ovulation.

Transcriptome Analysis on Single Small Yellow Follicles Reveals That Wnt4 Is Involved in Chicken Follicle Selection

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.