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. 2023 Mar 6;102(6):102624. doi: 10.1016/j.psj.2023.102624

Transcriptome identification of genes associated with uterus–vagina junction epithelial folds formation in chicken hens

Liubin Yang *,†, Jinping Cai †, Li Rong †, Sendong Yang †, Shijun Li †,1
PMCID: PMC10240375  PMID: 37011465

Abstract

The development regulation of the uterine–vaginal junction (UVJ) epithelial folds during the sexual maturation of female birds played crucial roles in the adults’ sperm storage duration and fertilization capability. However, there is a lack of studies on it in the breeding field of laying hens. In this study, White Leghorn was used for the morphological and developmental studies. According to the morphological characteristics, the development of the UVJ epithelial folds was classified into 4 stages (morphological stage T1–T4). Significant individual differences were observed simultaneously, which is one of the factors leading to the adults’ UVJ morphological differences. Bulk RNA-seq suggested the different regulations of UVJ epithelial folds were classified into 3 stages (developmental stage S1–S3). Genes enriched in cell proliferation, differentiation, polarity, migration, adhesion and junction were supposed to regulate UVJ epithelial fold formation. Single-cell RNA-sequencing (scRNA-seq) showed significant differences between different types of cells within UVJ at the developmental stage S2. Immunohistochemical studies confirmed that the different proliferation rates between the epithelium and nonepithelium were one of the key factors leading to the formation of UVJ epithelial folds. Genes in the TGF-beta and WNT pathways may play roles in regulating the proliferation and differentiation of epithelium. Some factors, such as CHD2, CDC42, and carbonic anhydrases, were important participants in forming UVJ epithelial folds. This study will provide new thoughts on the differential regulation of fertilization traits from the developmental biology perspective.

Key words: epithelial fold, epithelial tubule, oviduct, sperm storage tubule, uterus–vagina junction

INTRODUCTION

In chicken hens, the uterine–vaginal junction (UVJ) was the main site for sperm storage and fertilization regulation. At UVJ, the pseudostratified columnar ciliated cells bulge from the submucosa to form the main components of epithelial folds. Sperm storage tubules (SSTs) were blind-ended by epithelial tubules consisting of single-layer nonciliated columnar cells and invaginating from the surface of UVJ epithelium (Bakst, 1998). Besides the epithelial cells, there are many other types of cells, including fibroblasts, immune cells, blood capillaries, and nerve fibers within the UVJ epithelial folds (Bakst et al., 1994; Freedman et al., 2001).

After mating or artificial insemination (AI), a few screened sperms will enter the SSTs for short-term storage (days to weeks in hens). They are then released and transferred to the infundibulum for fertilization (Bakst et al., 1994). UVJ epithelial folds and SSTs provide a suitable microenvironment, including immune response, sperm metabolic inhibition, and metabolic compensation, for the temporary storage and release of sperms (Holm et al., 2000; Das et al., 2008; Bakst and Bauchan, 2015; Matsuzaki et al., 2015; Huang et al., 2017). Although females are capable of storing sperm and fertilizing the ovum, there is still a significant fertility difference between or within species. For example, in the breeding of laying hens, the storage duration of sperm is more than 15 d, whereas the short one is less than 3 d after artificial insemination (Bakst et al., 2010; Yang et al., 2022). Several studies have suggested that the morphological differences in adult UVJ folds (containing SSTs) were the key factor responsible for the differences in sperm storage duration (Pierson et al., 1988; Adetula et al., 2018; Wen et al., 2020; Yang et al., 2021a). However, it is worth mentioning that the morphological differences of adult individuals possibly originated from the differential regulation during sex maturation. There is still a lack of studies on the developmental regulation of UVJ epithelial folds or SSTs in hens.

Studies in other animals showed that multiple types of cells (such as epithelial cells and fibroblast) and regulating factors (such as planar cell polarity, cell proliferation, and cell adhesion) are involved in epithelial folds formation (Koyama et al., 2016; Koyama and Fujimori, 2018; Koyama et al., 2019). However, for a long time, due to the close relationships between different types of cells, the UVJ was usually regarded as a whole to be studied (Atikuzzaman et al., 2015; Huang et al., 2016; Yang et al., 2020b). The interactions between different types of cells within the UVJ epithelial folds were also unclear. The oviduct in avian species showed the most significant morphological and functional changes during sex maturation (Holm and Ridderstrale, 2002; Yin et al., 2019).

In this study, we hypothesized that regulations at different stages and cell interactions within UVJ are the potential factors promoting UVJ epithelial fold formation. Both morphological and transcriptome studies identify the transcriptome changes at different developmental stages, revealing crucial genes and pathways that regulate UVJ epithelial fold formation. This study will help understand the regulation of UVJ epithelial folds and provide theoretical bases for improving individual sperm storage duration in laying breeders.

MATERIALS AND METHODS

Ethical Statement

All animal experiments were carried out according to protocols (No. 5 proclaim of the Standing Committee of Hubei People's Congress) approved by the Standing Committee of Hubei People's Congress, and the ethics committee of Huazhong Agricultural University, China.

Animal Resources and Sampling

White Leghorn hens were raised in an experimental chicken farm at Huazhong Agricultural University, with the same feeding and management as our previous study (Yang et al., 2020a). Hens from 15 to 21 wk of age (a stage in the reproductive system from slowly developing to the onset of laying) were selected to obtain samples before and during sex maturation. Hens at 30 wk of age (hens were completely sexual maturity, possessing the best laying and fertilization performance) were selected to obtain samples after sex maturation.

After the chickens were killed by euthanasia, the oviduct was taken out. The oviduct length, weight and largest follicle diameter were measured and recorded. Then, cut off the approximate range of UVJ and then cut open along the long axis of the oviduct tube. Accurate UVJ sites were distinguished under the stereomicroscope. Half of the UVJ tissue was sampled and fix them with polyformaldehyde. The other half was placed in a petri dish, and epithelial folds were cut off from the mucosa layer with a scalpel at high magnification. The UVJ folds were cleaned with PBS and then stored in liquid nitrogen. The whole operation process is carried out on ice within 15 min. Detailed methods to distinguish UVJ epithelial folds were shown in Supplementary file 1.

Morphological Studies

A total of 81 samples were used for the morphological study. The fixed UVJ tissues were embedded into paraffin wax perpendicular to the long axis of the oviduct. Paraffin section preparation and hematoxylin-eosin staining followed the same steps as previously reported (Yang et al., 2021b). The classification of morphological stages is mainly based on morphological characteristics, including the development of primary UVJ epithelial folds, secondary epithelial folds, and SSTs. Individuals with similar morphological features will be divided into the same morphological stages.

Individual Differences Statistics Analysis

Vertical distance (UVJ height) from the mucosa to the top of primary UVJ was measured using the Image J software (Wayne Rasband, Bethesda, MD) to reflect the developmental status. Weeks of age is used to reflect the time scale. Oviduct length, weight, and largest follicle diameter reflect the development of other parts of the reproductive system. Eighty-one individuals were selected to generate the box plot between weeks of age and oviduct weight, length, and largest follicle diameter. Thirty-six individuals were selected to generate the box plot between weeks of age and UVJ epithelial fold height during sex maturation (from 16.5 to 18.5 wk of age). Forty-one individuals were randomly selected to calculate the Pearson's coefficient between the UVJ epithelial folds (measured by UVJ primary epithelial fold height) and other parts of the reproductive system (measured by oviduct weight, oviduct length, and largest follicle diameter) by Excel 2016 (Microsoft,Redmond, WA).

Bulk RNA-Seq and Data Analysis

A total of 19 samples from 4 morphological stages (5 samples from morphological stage T1, 5 from morphological stage T2, 5 from morphological stage T3, and 4 from morphological stage T4) were used for RNA-seq in this study. RNA isolation, bulk RNA-seq strategy selection, and data analysis followed the same steps as previously reported (Yang et al., 2021b). PCA and heatmap analysis were based on the Fragments Per Kilobase of exon model per Million mapped fragments (FPKM) values and generated by Omicshare online tools (https://www.omicshare.com/). Morphological stages with similar expression trends were combined into the same developmental stages for further analysis. The data from different developmental stages were compared to investigate the transcriptome changes. Genes with the adjusted P value <0.05 and |log2(Foldchange)|>1 were considered as differentially expressed genes (DEGs). The online Venn tools compare the DEGs derived from different development stages (https://bioinformatics.psb.ugent.be/webtools/Venn/). Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of DEGs were carried out by the KOBAS 3.0 website (http://kobas.cbi.pku.edu.cn/kobas3/), and the terms with a P value <0.05 were regarded as significantly enriched. Protein–protein interactions were analyzed using the string website online tools (https://cn.string-db.org). The highest confidence scores (0.9) and interaction types, including gene neighborhood, gene fusions, gene co-occurrence, coexpression, and protein homology, were selected to reveal the relationships among different proteins.

Analysis of Differentially Expressed Genes by Quantitative Real-Time PCR

DEGs, including BMP4, CA4, FGF10, SMAD9, and WIF1, were selected to verify the reliability of bulk RNA-seq by quantitative real-time PCR (qRT-PCR). cDNA was synthesized using the 1-step gDNA removal and cDNA synthesis supermix (TransScript, Beijing, China). A total of 20 samples from 3 developmental stages (5 from developmental stage S1, 10 from S2, and 5 from S3) were used for qRT-PCR. The primers were designed by Oligo 7.6 (Molecular Biology Insights, Springs, CO). Primer information is listed in Supplementary file 2. The qRT-PCR reaction conditions were as follows: 95°C for 5 min; 39 cycles of 95°C for 15 s and 57.5°C for 20 s; 72°C for 15 s; and 72°C for 5 min. The fold change was calculated by the 2−ΔΔCt method followed by the t-test for significance analysis.

scRNA-Seq of Developmental Stage 2 and Data Analysis

The UVJ epithelial folds of 1 White Leghorn hen at 19 wk of age were used to prepare the single-cell suspension for scRNA-seq. Briefly, the UVJ epithelial folds were cut into small fragments and digested in the collagenase I solution (10 mg/mL, Sigma) at 37°C for 10 min. Then, a 40 μm cell filter was used to remove the undigested tissues. The cell suspension was washed 3 times with PBS, then the cell concentration and viability were checked using a trypan blue and Countstar cell count system (ALIT Life Science, Shanghai, China). The qualified cell suspension was then subjected to library construction and sequencing by Novogene Biotechnology Company. The raw data were processed for quality control using FASTQ (version 0.20.0) software, and the gene expression matrix was generated by CellRanger software (version 3.1.0). Double cells were screened out by DoubletFinder software. Seurat (version 3.1.0) software was used to eliminate low-quality cells, dimensionality reduction, and cell cluster analysis. In this study, the uniform manifold approximation and projection (UMAP) algorithm and a graph-based algorithm were used for dimensionality reduction and cluster analysis, respectively. The DEGs of each cluster were generated by CellRanger software.

The cell cluster analysis was carried out by Loupe Browser 5.0 software (10 × genomics,Pleasanton, CA), and the cell types of each cluster were identified according to the CellMarker website (http://biocc.hrbmu.edu.cn/CellMarker/) and NCBI PubMed database (https://pubmed.ncbi.nlm.nih.gov/). The top 4 DEGs were regarded as the marker genes for each cluster. The heatmap of overall gene expression was generated by Seurat software, and some gene expression patterns in different clusters were generated by Loupe Browser 5.0 software.

Immunohistochemistry Studies

Primary antibodies against BMP4 (1:750 dilution, Abcam, Cambridge, UK), CDH2 (1:500 dilution, Abcam), PCNA (1:1,000 dilution, Bioss, Shanghai, China), and WIF1 (1:1,000 dilution, Sangon, Shanghai China) were used for the immunohistochemical studies at developmental stages. Briefly, UVJ sections from different development stages were prepared with 6-μm thickness. According to the standard procedures, they were stained with the primary antibodies at 4°C for 6 to 12 h, followed by secondary antibody incubation for 1 h at room temperature using an immunological kit (Proteintech, Wuhan, China). Visualization was performed by DAB (1:50) staining followed by hematoxylin staining for seconds. The Olympus microscope and imaging system took photographs.

RESULTS

Morphological Studies

The developmental process of UVJ epithelial folds was classified into 4 basic stages according to morphological changes. The detailed characteristics of developing UVJ folds were shown in Figure 1A to D. At morphological stage T1 (15–16 wk of age), only the primary UVJ epithelial folds were observed, and neither secondary UVJ folds nor SSTs could be observed in the paraffin sections. At morphological stage T2 (16–19 wk of age), both the secondary UVJ epithelial folds and SSTs were at the initial morphogenesis stage. At morphological stage T3 (17–21 wk of age), the secondary UVJ epithelial fold and SSTs rapidly developed. At morphological stage T4 (30 wk of age), hens were at the peak of the laying period, and both the secondary UVJ epithelial folds and SSTs performed normal functions.

Figure 1.

Figure 1

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Morphological changes in the UVJ epithelial fold from morphological stage T1 to T4 during sex maturation. The bold arrow indicates primary epithelial folds; the triangle indicates secondary epithelial folds; the thin arrow indicates SST. UVJ epithelium belongs to pseudostratified columnar ciliated cells, SSTs belongs to single columnar cell, and other types of cells are located between UVJ epithelium and SSTs. The scale bar represents 100 μm at normal size and 20 μm in an enlarged view.

Individual Differences Statistics Analysis

The oviduct weight, length, largest follicle diameter, and UVJ epithelial fold height showed obvious differences simultaneously (Figure 2A–D). The Pearson's coefficients between the height of primary UVJ epithelial fold and oviduct weight, length, and largest follicle diameter were 0.45 (P < 0.01), 0.6 (P < 0.01), and 0.45 (P < 0.01), respectively.

Figure 2.

Figure 2

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Statistical analysis of relationships between weeks of age and oviduct weight, length, and largest follicle diameter (A–C) using box plot (n = 81). The X-axis represents weeks of age, OL represents the onset of laying, and PL represents the peak of the laying period. (D) Statistical analysis of UVJ epithelial fold height and weeks of age during sex maturation (from 16.5 to 18.5 wk of age) using box plot (n = 36). The X-axis represents weeks of age.

Bulk RNA-Seq Data Analysis and Differentially Expressed Gene Enrichment

The correlation coefficients between samples were larger than 0.9. Morphological stages 2 and 3 showed similar gene expression patterns and were combined as the new developmental stage 2 according to the PCA and heatmap (Figure 3A and B) analysis. Morphological stages 1 and 4 were redefined again as developmental stages 1 and 3, respectively.

Figure 3.

Figure 3

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(A) PCA of individuals from different morphological stages. Individuals at T2 and T3 showed similar expression patterns (they were merged to be the development stage S2). (B) Heatmap of gene expression patterns from morphological stages T1 to T4. (C) Venn diagram of DEGs derived from development stage S2 compared to S1, S3 to S2, and S2 to S1. (D) qPCR verification of bulk RNA-seq results. All 5 genes (BMP4, CA4, FGF10, SMAD9, and WIF1) followed a similar expression pattern of RNA-seq. The X-axis represents different developmental stages, and the Y-axis represents the relative expression levels. Different uppercase or lowercase letters refer to significant differences with P values <0.05 or <0.01, respectively. Error bars indicate standard errors.

Then, developmental stage 2 was compared with stage 1 to investigate the genes and pathways that regulate the early stage of UVJ epithelial fold development. A total of 2,705 DEGs were identified, of which 1,066 were upregulated and 1,699 were downregulated (the detailed gene list was shown in Supplementary file 3). A total of 704 GO terms and 16 pathways were significantly enriched. Especially the pathways, such as the TGF-beta signaling pathway (20 genes were enriched, including BMP4, BMPR2, TGFB2, TGFBR2, and TGIF2) and WNT signaling pathway (24 genes were enriched, including LEF1, SFRP1, SFRP2, TCF7, and WNT7A) were significantly enriched. The GO terms, such as the positive regulation of cell population proliferation (35 genes were enriched, including CNTF, CNTFR, EDN2, FGF10, and FGF18) and morphogenesis of an epithelium (5 genes were enriched, including CA2, CITED2, FREM2, SERPINB5, and SOX10).

Developmental stage 3 was compared with stage 2 to explore the genes and pathways related to regulating later-stage UVJ epithelial development. A total of 2,271 DEGs were identified, of which 1,187 were upregulated and 1,084 were downregulated. The detailed genes were listed in Supplementary file 4. A total of 238 GO terms and 14 pathways were significantly enriched. Especially the GO terms, such as the cell division (18 genes were enriched, and the CCNA2, CCNB1, CCNB3, CDK1, and MASTL genes were enriched) and cell cycle arrest (9 genes were enriched, including CDKN2C, CDKN3, ERN1, IL12B, and SKIL) were significantly enriched. The cell cycle pathway was the most significant (29 genes were enriched, and the BUB1B, CCNA1, E2F1, ESPL1, and PTTG2 genes were included). GO terms and pathways that potentially regulate UVJ epithelial fold development were listed in Tables 1 and 2.

Table 1.

Candidate GO terms that are related to UVJ epithelial fold formation.

Stages GO term Count Gene list
S2 vs. S1 Positive regulation of cell population proliferation 35 CHRNA7, CNTF, CNTFR, EDN2, FGF10, FGF18, FGF2, FGF9, FGFR4, GDNF, GREM1, GRK5, HDAC4, HLX, HPSE2, ID4, IL11RA, IL6R, ISL1, KIF14, KLB, MYC, MYOCD, NRG1, NTRK2, NTRK3, PDGFB, PDGFC, PTGFR, PTH2R, S100B, SFRP2, TGFB2, THPO, TWIST1
S2 vs. S1 Morphogenesis of an epithelium 5 CA2, CITED2, FREM2, SERPINB5, SOX10
S2 vs. S1 Epithelial cell proliferation 3 COL8A1, COL8A2, EHF, HGF
S2 vs. S1 Establishment or maintenance of cell polarity 8 CAP2, ENSGALG00000040291, PARD6A, PARVA, PARVB, RHOBTB1, RHOC, RND3
S2 vs. S1 Cell–cell adhesion 13 BCL2, CDH11, CDH2, DSP, ENSGALG00000005257, FAT3, FAT4, FBLIM1, KIRREL1, LRRC7, PKD1, THY1, TMEM47
S2 vs. S1 Cell differentiation 50 C2H8ORF22, DLX1, EHF, ELF5, ENSGALG00000001136, ENSGALG00000027983, ETV1, EYA1, EYA4, FGF10, FGF18, FGF2, FGF9, FOXI1, FOXL2, FRZB, FSTL1, FSTL3, GLI1, HCK, HES5, HNF4beta, ID4, ILDR2, ITGA8, LYN, MDK, MGP, NHS, NOV, NRG1, PPARG, RBM24, RBM38, ROS1, RXFP1, RXRG, SDC3, SFRP1, SFRP2, SMAD2Z, SMAD9, SOX2, SOX21, SRC, SSPO, SYT1, TESC, THRB, ZFPM2
S2 vs. S1 Cell migration 32 ATRNL1, CCDC88A, CDH2, CDH7, DOCK5, ENPEP, EPHA3, FGFR4, FUT8, GPC4, IL12B, ITGB6, ITGB8, LAMA4, LAMB2, MERTK, NEDD9, NOV, NTN4, NTNG1, NTNG2, PRAG1, RHOC, RHOV, RND3, SDC3, STRIP2, TGFB2, TGFBR2, TGFBR3, TNFAIP3, WNT11
S3 vs. S2 Cell division 18 CCNA2, CCNB1, CCNB3, CDK1, CENPJ, CENPW, CKS2, ITGB3BP, KIF14, KIF18B, MASTL, NCAPH, NDC80, NUF2, RB1, SMC2, SPECC1L, TOP2A
S3 vs. S2 Cell cycle arrest 9 CDKN2C, CDKN3, ERN1, IL12B, INHBA, NOTCH2, PKD1, RB1, SKIL
S3 vs. S2 Cell population proliferation 15 ACE, BRCA2, CDK1, CKS2, DACH1, E2F8, ENPEP, EXFABP, GLUL, IGF-I, IL12B, LARP1, MCM10, OCA2, USP13,
S3 vs. S2 Gap junction 4 PANX2, SPECC1L, DBN1, CCN3
S3 vs. S2 Cell adhesion 29 ADGRG1, ANOS1, BCAN, CCN3, CDHR1, CHL1, CLDN19, CNTNAP5, COL5A1, COL6A1, COL6A2, COL6A3, COL8A1, ENSGALG00000009355, ENSGALG00000013624, HAPLN1, HES5, NOV, PCDH10, PCDH8, PODXL, PRKX, SPON1, SPP1, SUSD5, TNC, TNR, VCAN, WISP1
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Table 2.

Candidate pathways that are related to UVJ epithelial fold formation.

Stage KEGG Count Gene list
S2 vs. S1 ECM–receptor interaction 19 CD36, COL2A1, COL9A2, ENSGALG00000003283, ENSGALG00000010316, ENSGALG00000019761, ENSGALG00000042388, FREM1, FREM2, HSPG2, ITGA11, ITGA8, ITGB6, ITGB8, LAMA1, LAMA4, LAMB2, NPNT, VTN
S2 vs. S1 TGF-beta signaling pathway 20 ACVR2B, BMP2, BMP4, BMPR2, CDKN2B, CHRD, ENSGALG00000012055, GREM1, ID1, ID4, INHBA, INHBB, LTBP1, MYC, RGMA, SMAD2Z, SMAD9, TGFB2, TGFBR2, TGIF2
S2 vs. S1 Cytokine–cytokine receptor interaction 34 ACVR2B, BMP2, BMP4, BMPR2, CCL17, CNTF, CNTFR, CSF3R, CXCL12, CXCL14, CXCR4, EDA2R, ENSGALG00000012055, GDF10, GDF8, GHR, IL11RA, IL12A, IL12B, IL13RA2, IL19, IL20RA, IL6R, INHBA, INHBB, NGFR, TGFB2, TGFBR2, THPO, TNFRSF10B, TNFRSF13B, TNFRSF1B, TNFSF13B, TNFSF15
S2 vs. S1 Cell adhesion molecules (CAMs) 21 BLB1, CD99, CDH2, CLDN16, CLDN19, CLDN8, CNTNAP1, ENSGALG00000005257, ENSGALG00000009355, ENSGALG00000029002, ITGA8, ITGB8, JAM2, NCAM1, NFASC, NLGN4Y, NRXN1, NTNG1, NTNG2, SDC3, VCAN
S2 vs. S1 Focal adhesion 31 BCL2, CAPN2, COL2A1, COL9A2, ENSGALG00000003283, ENSGALG00000010335, ENSGALG00000019761, ENSGALG00000034605, ENSGALG00000042388, HGF, ITGA11, ITGA8, ITGB6, ITGB8, JUN, LAMA1, LAMA4, LAMB2, MYL10, MYL9, MYLK, PARVA, PARVB, PDGFA, PDGFB, PDGFC, PDGFRA, PRKCA, RASGRF1, SRC, VTN
S2 vs. S1 Wnt signaling pathway 24 AXIN2, ENSGALG00000028041, GPC4, JUN, LEF1, LGR5, MYC, NKD1, PRICKLE1, PRKCA, ROR1, ROR2, RSPO3, SFRP1, SFRP2, TCF7, WIF1, WISP1, WNT11, WNT16, WNT2B, WNT6, WNT7A, WNT9A
S3 vs. S2 Cell cycle 29 BUB1, BUB1B, CCNA1, CCNA2, CCNB1, CCNB3, CCNE2, CDC20, CDC7, CDK1, CDK2, CDKN2C, CHEK1, E2F1, ESPL1, GADD45G, MAD2L1, MCM2, MCM3, MCM4, MCM5, MCM6, ORC1, PLK1, PTTG2, RB1, TFDP1, TTK, WEE1
S3 vs. S2 ECM–receptor interaction 18 CD36, COL1A2, COL4A1, COL6A1, COL6A2, COL6A3, ENSGALG00000002389, ENSGALG00000008141, ENSGALG00000042388, HMMR, ITGA2, ITGB6, LAMA4, SPP1, TNC, TNR, VTN, VWF
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The overlapped DEGs derived from the comparison of developmental stages S2 to S1, stages S3 to S2, and stages S3 to S1 were shown in Figure 3 C. Strong DEG interactions were also derived by comparing developmental stages S2 to S1 and stages S3 to S2 (Supplementary file 5).

Analysis of DEGs by qRT-PCR

The qRT-PCR verification showed that all 5 genes (BMP4, CA4, FGF10, SMAD9, and WIF1) followed a similar expression tendency with the RNA-seq data (Figure 3D).

scRNA-Seq and Data Analysis at Developmental Stage 2

A total of 13,500 cells were estimated. The mean reads per cell were 41,082, and the number of medium genes per cell was 935. After quality control and DoubletFinder filtering, 12,168 cells were used for subsequent analysis. As shown in Figure 4A, a total of 17 cell clusters were generated after dimension reduction analysis. Cell clusters were identified as ciliated epithelium, nonciliated epithelium, SST epithelium, fibroblasts, red blood cells, immune-related cells, and unknown clusters. The results of cell cluster identification and the top 4 DEGs of each cluster were given in Table 3. Gene expression patterns of DCN, MKI67, SLC14A2, JCHAIN, HEY1, and CA8 were shown in Figure 4B. The heatmap of the top 200 DEGs was shown in Figure 4C.

Figure 4.

Figure 4

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(A) Results of UMAP dimensionality reduction analysis. The X-axis and Y-axis represent 2 dimensions after dimensionality reduction by the UMAP method. Each dot represents a cell, and cells with similar expression patterns will gather into a cell cluster. Different colors refer to a different cell cluster. Clusters 0, 3, 4, 6, and 9 were identified as ciliated epithelium. Clusters 1, 10, and 13 were identified as nonciliated epithelium. Clusters 2 and 5 were identified as red blood cells. Cluster 7 was identified as fibroblasts. Clusters 8, 15, and 16 were identified as immune-related cells. Cluster 11 was identified as SST epithelium. Clusters 12 and 14 were unknown cell types. (B) Expression patterns of DCN, MKI67, SLC14A2, JCHAIN, HEY1, and CA8 in different cell clusters. The X-axis and Y-axis represent 2 dimensions after dimensionality reduction by the UMAP method. Each dot refers to a cell, and the depth of color represents the expression of corresponding genes. (C) Gene expression heatmap of top 200 DEGs derived from different clusters. Each row represents the cell cluster, and the names of cell clusters have been marked on the left. Different colors represent the gene expression level.

Table 3.

Results of cell cluster identification and the top 4 highly expressed genes.

Cluster Cell type Top 4 highly expressed gene
Cluster 0 Ciliated epithelium RP1, SYNE1, DNAH5, TTC6
Cluster 1 Goblet cells or secretory cells FUT9, CA4, SLC14A2, TSPAN1
Cluster 2 Red blood cell MOG, B2M, TAL1, ZFAD2A
Cluster 3 Ciliated epithelium SPINK5, RP11-400G3.5, GPIHBP1, RARRES1
Cluster 4 Ciliated epithelium SNTN, CKB, DYNLT1, SPINK2
Cluster 5 Red blood cell HBAD, HBA1, HBBA, CA2
Cluster 6 Ciliated epithelium SPINK5, RARRES1, LOC771972, SPINK7
Cluster 7 Fibroblast COL1A1, COL1A2, COL3A1, DCN
Cluster 8 Immune cell GNLY, LOC42365, LOC419545, CD3D
Cluster 9 Ciliated epithelium LOC107052288, SPINK5, RARRES1, LOC771972
Cluster 10 Nonciliated epithelium RASL10A, RPL12, HEY1, PP1A
Cluster 11 Presumptive SST cell EDIL3, NAT8L, CA8, AMER2
Cluster 12 Unknown SPHKAP, SLC4A1, CRABP1, NEDD4L
Cluster 13 Progenitor cells of some kind of epithelium MKI67, CENPF, LOC100859737, COL4A1
Cluster 14 Unknown VWF, PLVAP, COL4A1, PRKCDBP
Cluster 15 Immune cell JCHAIN, LOC 422643, IGLL1, LOC107051274
Cluster 16 Immune cell BLB1, BLB2, CD74, SELENOP1
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Immunohistochemistry Studies

Immunohistochemistry of BMP4, CDH2, PCNA, and WIF1 exhibited different expression patterns in different developmental stages. Of which, BMP4 and WIF1 were mostly located in the epithelium at all 3 stages, CDH2 was mainly located in SST cells from developmental stage S2, and PCNA showed more distribution on the epithelium than on the nonepithelium. All results showed different regulatory effects of different cell clusters. The detailed results were shown in Figure 5.

Figure 5.

Figure 5

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Immunohistochemical staining of PCNA, BMP4, CDH2, and WIF1 at developmental stages S1, S2, and S3. An arrow indicates UVJ epithelium, and SST is indicated by a triangle (no visible SSTs at developmental stage S1). Other types of cells are located between UVJ epithelium and SSTs. Scale bar: normal size 100 μm, enlarged size 20 μm.

DISCUSSION

Several studies suggest that the morphological differences in adults’ UVJ closely correlate with sperm storage duration and fertility fertilization capability (Adetula et al., 2018; Wen et al., 2020; Yang et al., 2021a). In order to understand the formation of UVJ morphological differences, it is necessary first to investigate factors related to the formation of UVJ epithelial folds. After birth, the reproductive system of birds enters a slow development stage, which shows little morphological differences during this stage. During sex maturation, the hen oviducts rapidly develop from incomplete differentiation to a state with normal function for several weeks (Holm and Ridderstrale, 2002; Yin et al., 2019). Morphological studies revealed the obvious individual differences during the UVJ epithelial folds development process, consistent with SST developmental results in quail (Holm and Ridderstrale, 2002). Our statistics analysis showed that the development of UVJ epithelial folds was not completely consistent with the oviduct and follicle. Although epithelial folds belong to parts of the oviduct, it also has a specific regulatory effect on the development compared with other parts of the reproductive system. Moreover, morphological differences of UVJ existed in each stage during sex maturation, suggesting that developmental regulation partly contributes to the morphological differences of adults’ UVJ epithelial folds.

Although significant morphological differences between morphological stages T2 and T3 were observed, heatmap and PCA analysis showed individuals at these 2 stages followed similar gene expression patterns. Two reasons may be responsible for it. One is that the individual differences have been strictly controlled when sampling, and the other is that the duration of morphological stage T2 to T3 was too short (1–3 wk) to generate great differences. Thus, the following analysis combined the morphological stage T2 and T3 as the developmental stage S2. The cell numbers showed the most remarkable increase within UVJ epithelial folds during the development process. Regulation of cell proliferation and differentiation are considered to be key regulators in UVJ epithelial fold formation. Enrichment analysis of DEGs from bulk RNA-seq showed dynamic changes in gene expression patterns at different stages. A series of genes and pathways involved in the regulation of cell proliferation and differentiation were identified, among which genes in the TGF-beta signaling pathway (20 genes were enriched) and the WNT signaling pathway (24 genes were enriched) showed the most significant enrichment. scRNA-seq revealed that different types of cells showed different gene expression and proliferation patterns within the UVJ. Further immunohistochemical staining of cell proliferation marker PCNA suggested that epithelial cells have a higher proliferation signal than nonepithelial cells, which was one of the key factors responsible for the formation of epithelial folds.

WNT and TGF-beta signaling pathways have been reported to play curial roles in cell proliferation and differentiation (Moustakas et al., 2002; Teo and Kahn, 2010; Kahata et al., 2018; Zhao et al., 2021). BMP4, an important ligand of the TGF-beta pathway, was first increased at development stage S2 and then decreased at stage S3. In mice, BMP4 was expressed in the most distal regions of epithelium and functioned as an important molecule to promote lung morphogenesis (Hyatt et al., 2004). In chickens, BMP4 played an important role in promoting primordial germ cell formation in vitro (Zuo et al., 2019), and the expression of BMP4 was increased during the proliferation and differentiation. In addition, the downstream genes such as SMAD9, ID1, MYC, and CDKN2B also showed different expression levels. WIF1 is an important inhibitor that can directly interact with a variety of WNT ligands (such as Wnt3a, Wnt4, Wnt5a, Wnt7a, wnt9a, and Wnt11) and inhibit their binding to the membrane-bound receptors (Poggi et al., 2018). During the development of the reproductive system in mammals, WIF1 is expressed in the mesenchyme surrounding the Müllerian duct epithelium during Müllerian duct regression, which is speculated to be related to the decline of the Müllerian duct in the male reproductive system (Park et al., 2014). In humans, WIF1 is expressed in interfollicular epithelial stem cells and plays a role in suppressing keratinocyte proliferation (Schluter et al., 2013). As an important WNT ligand inhibitor, it found that in developmental stage S2, a number of WNT ligands such as Wnt9a, Wnt11, and Wnt7a showed an opposite expression pattern with WIF1. Additionally, immunohistochemical verifications revealed that BMP4 and WIF1 were mainly expressed in the epithelium, suggesting that these 2 pathways may mainly function in the epithelium and play roles in cell proliferation and differentiation.

Genes and pathways related to cell migration, cell polarity, and adhesion were also regarded as important participants in regulating the UVJ epithelial fold formation (Koyama et al., 2016; Koyama and Fujimori, 2018; Koyama et al., 2019). Bulk RNA-seq identified a series of important genes related to cell polarity, adhesion and migration. For example, cadherin families (CDH2, CDH7, CDH10, CDH17, and CDH19 were all included.) played important roles in organogenesis, tissue homeostasis, renal epithelial integrity, and polarity (Prozialeck et al., 2004; Terada et al., 2017). The immunohistochemistry of CDH2 (N-cadherin) showed that it was mostly expressed in SST cells at developmental stages S2 and S3, suggesting that it may function as a specific adhesion molecule in SST development. CDC42 gene, a member of the Rho subfamily small GTPase, has multiple functions, including maintenance of cell polarity, migration, differentiation, and morphogenesis (Aizawa et al., 2012). Studies in Drosophila showed that CDC42 could define apical identity and promote the pupal photoreceptor and follicular epithelium morphogenesis (Nunes de Almeida et al., 2019). Additionally, CDC42 was one of the key regulators in the development of the Drosophila salivary gland (Pirraglia et al., 2010) and also had close relationships with epithelial cell junctions (Citi et al., 2014). Bulk RNA-seq showed CDC42 was highly expressed in the developmental stage S2, which means it may play multiple roles in the development of UVJ epithelial folds (including SSTs).

Another important finding of scRNA-seq was that cell types within UVJ epithelial folds were much more complex than in previous reports (Bakst et al., 1994; Bakst, 1998). Some of these cell clusters were easy to identify. For example, the carbonic anhydrase was located in goblet cells, whereas the ESR was in SST cells (Holm et al., 1996; Yoshimura et al., 2000). Moreover, the same type of cells may be divided into different clusters due to the differences in gene expressions. For example, clusters 0, 3, 4, 6, and 9 were identified as ciliated cells. The enrichment analysis of DEGs derived from each cluster revealed that different cell clusters process different regulatory mechanisms. Interactions between cells are also more complex than previously reported. For example, carbonic anhydrases have been reported to play important roles in sperm storage and pH regulation in UVJ epithelium (Holm et al., 1996; Holm and Ridderstrale, 1998). Our study showed that CA4 was mainly located on the UVJ epithelium, CA2 was primarily expressed in red blood cells, and CA8 was mainly expressed in SST cells. This result suggested that different carbonic anhydrases played various roles during UVJ epithelial fold formation. Bulk RNA-seq provided a general overview of transcriptome differences among different developmental stages, whereas scRNA-seq provided a more refined regulatory mechanism during the formation of UVJ epithelial folds.

In summary, our results suggested that the differences in developmental regulation partly contribute to the morphological differences in adults’ UVJ epithelial folds. The difference in proliferation rates between epithelial and nonepithelial was a key factor in the formation of epithelial folds. Genes in the TGF-beta and WNT pathways were mainly expressed in the epithelium and may play roles in regulating epithelium proliferation and differentiation. Cell adhesion, junctions, migration, and polarity were important participants during the development process. Genes such as BMP4, WIF1, CDH2, CDC42, and carbonic anhydrases played different roles during UVJ fold formation.

ACKNOWLEDGMENTS

This work was supported by the Natural Science Foundation of China (No.32072707), the National Key R&D Program of China (No. 2021YFD1300100), and grants from the Science and Technology Major Project of Hubei Province (2021ABA016).

DISCLOSURES

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled.

Footnotes

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.psj.2023.102624.

Appendix. Supplementary materials

mmc1.docx (1.5MB, docx)
mmc2.docx (21.1KB, docx)
mmc3.xlsx (557.6KB, xlsx)
mmc4.xlsx (483.1KB, xlsx)
mmc5.docx (1.8MB, docx)

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Supplementary Materials

mmc1.docx (1.5MB, docx)
mmc2.docx (21.1KB, docx)
mmc3.xlsx (557.6KB, xlsx)
mmc4.xlsx (483.1KB, xlsx)
mmc5.docx (1.8MB, docx)

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