Inhibin α (INHA) is a candidate gene controlling ovulation in poultry. As the functional center of inhibin, INHA is a molecular marker associated with egg-laying performance. The objective of the current study was to analyze the expression differences of INHA in reproductive system and single nucleotide polymorphisms (SNPs) associations with reproductive traits in chickens. A total of 260 LuHua chickens (barred-feather chicken) were adopted. Twelve SNPs were detected in INHA gene. Among the exonic SNPs, three (g. 22177991A>G, g. 22178249G>C, and g. 22178414G>A) were missense mutations, resulting in the amino acid substitutions Val→Ala, Ala→Gly, and Ala→Gly, respectively. Four SNPs in the 3 untranslated region of INHA were predicted to either disturb or create microRNA-target interactions. Five SNPs (g. 22176870T>C, g. 22177100T>C, g. 22177149T>C, g. 22177991A>G, and g. 22178975G>A) were significantly associated with the number of eggs at 300 d of age (EN) (P < 0.05). Birds carrying GA genotype exhibited more EN than those with AA genotype (P < 0.01). In addition, quantitative real-time PCR revealed that INHA is mainly expressed in follicles on d 300 in chickens. Firstly, INHA expression increased and then decreased. The highest INHA mRNA abundance was found in the fifth largest preovulatory follicle (F5) (P < 0.01). In the prehierarchical follicles, INHA mRNA expression increased dramatically in small yellow follicles (SYF) (P < 0.01). Western blotting analysis showed that the INHA protein expression profile in the follicle was similar to its mRNA counterpart with greater expression in F5 and SYF follicles and lowest expression in F1 follicles (P < 0.05). These results suggest that INHA is a potential candidate gene improving reproductive traits in chickens.

1. Introduction

Inhibin, a member of the transforming growth factor-β (TGF-β) superfamily, plays an important role in modulating the reproductive axis and affects all reproductive events [1]. It is a gonadal glycoprotein hormone and is principally produced by the granulosa cells of ovarian follicles in females and by the sertoli cells of the testes in males [2]. Inhibin comprises multiple disulfide-linked dimers that shares a common α-subunit (encoded by INHA gene) and differs in β-subunit; when the α-subunit binds to βA-subunit, inhibin A (αβA) is formed, and when it binds to the βB-subunit, inhibin B (αβB) is formed. Both inhibin A and inhibin B have the ability to specifically suppress follicle-stimulating hormone (FSH) secretion in pituitary cells without affecting LH secretion [37]. In addition to its endocrine function, inhibin also shown to exert a variety of autocrine/paracrine in mammalian species. Many studies indicated a local role for these factors in modulating the growth of small follicles by regulating cell proliferation as well as expression of the inhibin subunits and gonadotropin receptors [8, 9].

Inhibin A is produced and secreted by the granulosa layer of the large pre-ovulatory follicle [10]. Immunizations against the INHA have resulted in increased ovulation in sheep, pigs, chickens, mice, and cows [1115]. Therefore, the INHA is thought to be the functional center of inhibin and a potential candidate gene increasing the ovulation rate in poultry. In a murine knockout model, the INHA was found to play a tumor suppressive role in gonadal tissue after gonadectomy for the adrenal cortex, with 99% of INHA mice developing adrenocortical steroid-secreting carcinoma after gonadectomy [16, 17]. Pathways involved in this effect include the differentiation into granulosa cell-like cells with the expression of fetal or gonadal markers such as LHR, FSHR, and Cyp17a1 [18]. Recently, Li et al. found that INHA gene polymorphisms are significantly associated with the presence of follicular cysts in Large White sows [19]. In poultry, Chen et al. reported that the downregulation of INHA expression has an antagonistic effect on granulosa cell apoptosis [20]. Although many studies have shown that inhibin was a critical regulator of gonadal function, whether its expression level in the developing follicles or polymorphisms are associated with reproductive traits in chicken is still unknown.

In characterizing candidate genes, it is important to detect single nucleotide polymorphisms (SNPs) and analyze the associations between these SNPs and reproductive traits, together with assessing the role of gene expression. Therefore, the aim of this study was to characterize the role of the chicken INHA gene in determining chicken reproductive traits through SNP association and expression analyses.

2. Materials and Methods

2.1. Chicken Populations

The LuHua chicken (LH) is a local breed in Shandong province, P. R. China. It was included in the Key Poultry Breeds Requiring Protection in 2002. A total of 260 birds after hatching were raised in cages with the same housing conditions and diets. Their performances were measured in Poultry Breeding Farm of Sichuan Agricultural University (Ya’an, China). Blood was collected, and genomic DNA was isolated using a standard phenol/chloroform method. The DNA purity and concentration were measured with a Nucleic Acid Protein Analyzer (Thermo Scientific, USA). Based on the original concentration, samples were diluted to the final concentration of 100 ng/μL with Tris-EDTA buffer. All DNA samples were stored at -20°C until use.

Six reproductive traits were measured: body weight at first egg (BWAFE), first egg weight (FEW), age at first egg (AFE), total egg number at 300 days of age (EN), body weight at 300 days of age (BWTA), and egg weight at 300 days of age (EWTA). Traits determination was conducted in accordance with the Committee on Experimental Animal Management of Sichuan Agricultural University and carried out strictly according to the Regulations for the Administration of Affairs Concerning Experimental Animals of the State Council of China.

2.2. Sequencing of the INHA Gene

Primers for amplifying and sequencing the chicken INHA gene (Table 1) were designed with Primer Premier 5.0 software based on the complete DNA sequences of Gallus gallus INHA genes (ENSGALG00000054770). A DNA pool containing 100 ng DNA from each of the 60 least closely related chickens was constructed. PCR was carried out using a Gene Amp PCR System 9700 (Bio-Rad, Hercules, CA, USA) thermal cycler in a final volume of 25 μL containing 8.6 μL distilled H2O, 15 μL 2×Taq PCR Master Mix (including Mg2+, dNTPs, and Taq DNA polymerase; Beijing Tian Wei Biology Technique Corporation, Beijing, China), 0.3 μL each primer (10 nmol/L), and 0.8 μL chicken genomic DNA template. PCR was performed with the following cycling conditions: denaturation at 94°C for 5 min; 35 cycles of 94°C for 30 s, 56-60°Cfor 35 s (Table 1), and 72°C for 40 s, followed by a final extension at 72°C for 5 min. PCR products were purified and sequenced via an ABI 377 DNA sequencer (Shanghai Sangon Biological Engineering Technology, Shanghai, China). All sequences were edited, assembled, and aligned with DNASTAR and Codon Code Aligner software (http://www.codoncode.com/aligner). SNPs were identified by the presence of multiple peaks at the same base by direct sequencing.

2.3. Genotypes Identification

Based on the DNA pools sequence results, single nucleotide polymorphisms were found in the amplification products of five primer pairs P1, P2, P3, P4, and P5. Further polymorphism genotyping was carried out one by one using DNA samples of 260 chickens. PCR and amplified products were carried out as describe as above.

2.4. Statistical Analyses

SAS 9.4 (Statistical Analysis Systems Institute Inc., Cary, NC, USA) was used to determine the relationship between genotypes and reproductive traits in chicken. The model used was: = μ + + , where is a reproductive trait measured in the chickens, μ is the population mean of the trait, is a fixed effect genotype, and is the residual error. Significance was determined using Duncan’s multiple range tests. Pearson’s chi-square test was used to assess the Hardy-Weinberg equilibrium of the four SNPs discovered in the present study. The linkage disequilibrium (LD), D and r2 values of the SNPs were estimated by Haploview [21]. The polymorphism information content (PIC) was determined following a previous method [22]. In addition, haplotypes were constructed using the PHASE program v. 2.0. Haplotypes were analyzed using the model for the single marker association test by considering birds with 0, 1, or 2 copies of the haplotype in question. The PROC REG procedure of SAS (version 9.4, SAS Institute Inc.) was used to perform the analysis. Values were significant at P < 0.05.

2.5. Expression Abundances of INHA mRNA

To determine the reproductive system tissue-specific expression patterns of INHA mRNA, total RNA was extracted from the tissues of five chickens at 25 weeks, including the fallopian tubes (infundibulum, isthmus, and uterus), hierarchical follicles (F1, F2, F3, F4, and F5), and prehierarchical follicles [small white follicles (SWF), small yellow follicles (SYF), and large white follicles (LWF)], using TRIzol reagent (TakaRa Biotech Co. Ltd., Dalian, China) and was dissolved in RNase-free H2O (Tiangen Biotech Co., Ltd, Beijing, China). The integrity of the RNA was evaluated via electrophoresis on 1 % agarose gels, and the concentration and purity were analyzed with a NanoDrop 2000 by determining the absorbance ratio of 260/280 nm (Thermo Scientific, Waltham, MA, USA). The cDNA was synthesized by reverse-transcription PCR using 1 μg total RNA, 2 μL 5 × RT buffer, 0.5 μL RT enzyme mix, 0.5 μL primer mix, and 6 μL nuclease-free water (Toyobo Life Science Department, Shanghai, China). The reverse transcription reaction was maintained at 37°C for 15 min, followed by incubation at 98°C for 5 min. The cDNA samples were stored at -20°C. Gene-specific primers (Fw: 5-ACTACTGCCACGGGAACTGT-3, Rv: 5-GGAGTAGCCACCATCAGAGG-3) for qRT-PCR were designed using Primer 5 software according to the coding sequence of the chicken INHA gene (GenBank accession no. NM_001031257). qRT-PCR was conducted via a CFX96 Real-time System (Bio-Rad, Hercules, CA, USA) with the following conditions: 98°C for 2 min; 39 cycles of 98°C for 5 s and 55.7°C for 10 s; followed by a final extension at 95°C for 10 s. Each PCR reaction contained 5 μL Ssofast Evagreen supermix (Bio- Rad, Hercules, CA, USA), 1 μL of cDNA (50 ng/μL), 0.8 μL each primer (10 μM), and 2.4 μL ddH2O to a final reaction volume of 10 μL. All samples were triplicated. The housekeeping gene β-actin (GenBank accession no. AF047874; Fw: 5-GAGAAATTGTGCGTGACATCA-3, Rv: 5-CCTGAACCTCTCATTGCCA-3) was used for normalization of target gene expression [23]. The relative gene expression levels of INHA were calculated using the comparative method [24], where ΔCt = Ct target gene - Ct housekeeping gene. Differences in INHA mRNA expression were examined by one-way analysis of variance (ANOVA). Data are presented as the mean ± standard error means (SEM), and significances were determined at P < 0.05.

2.6. Expression Abundances of INHA Protein

INHA protein expression levels in different follicles were detected by Western Blotting. Total protein was extracted from the tissues of five chickens at 25 weeks, including the hierarchical follicles (F1, F2, F3, F4, and F5) and prehierarchical follicles (SWF, SYF, and LWF) using a Protein Extraction Kit (BestBio Biotech Co. Ltd., Shanghai, China). The concentration and purity of the protein samples were determined using a BCA Protein Assay Kit (BestBio Biotech Co. Ltd., Shanghai, China); standard curves were drawn to calculate the protein concentration. Samples were triplicated. The β-actin protein was used as a reference. A total of 25 μg protein was resolved by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to polyvinylidene fluoride (PVDF) membranes. After blocking with 5 % non-fat milk in 1×Tris-buffered saline with Tween (TBST) buffer for 2 h at room temperature, membranes were incubated with rabbit anti-chicken INHA monoclonal antibody (Abcam, Cambridge, UK; 1:1000) and rabbit anti-chicken β-actin monoclonal antibody (Abcam, Cambridge, UK; 1:1000) overnight at 4°C. Blots were then washed in 1 × TBST buffer and probed with goat anti-rabbit horseradish peroxidase (HRP)-conjugated IgG secondary antibody (diluted 1:2000 in 1 × TBST; Abcam, Cambridge, UK) for 1 h at room temperature. Binding was visualized with enhanced chemiluminescence (ECL) reagent (Beyotime Institute of Biotechnology, Jiangsu, China) using a ChemiDoc XRS instrument (Bio-Rad, Hercules, CA, USA). Quantity One Software (Bio-Rad, Hercules, CA, USA) was used for densitometric analysis [25].

3. Results

3.1. Allele and Genotype Frequencies of Chicken INHA Gene SNPs

All exons and part of the untranslated region (UTR) of the chicken INHA gene were amplified and sequenced. A total of 12 SNPs were detected (Figure 1). Among them, one was located in the promoter region, three were in exon 1, three were in exon 2, and five were in the 3 UTR (Table 2). Among the exonic SNPs, g. 22177991 A>G, g. 22178249 G>C, and g. 22178414 G>A were missense mutations, which resulted in the amino acid substitutions Val→Ala, Ala→Gly, and Ala→Gly, respectively. SNPs in the 3 UTR were predicted to either disturb or create microRNA- (miRNA-) target interactions. Ten miRNA interactions weakened and four miRNA interactions strengthened (Table 3).

The genotype and allele frequencies and related genetic information for the 12 SNPs in the chicken INHA gene are summarized in Table 4. For all SNPs, their genotype and allele frequencies were above 5 %, which indicated that it was appropriate to conduct INHA gene analysis. For SNP1, the CT genotype frequency (0.6121) was higher than those of CC (0.3103) and TT (0.0776), and the allele frequency of C (0.61635) was higher than that of T (0.38365). The heterozygous genotype frequency was higher than the homozygous genotype frequencies for all 12 SNPs. The original allele frequency was higher than the mutant allele frequency for SNP1, SNP2, SNP3, SNP4, SNP7, SNP8, and SNP9, respectively, while the original allele frequency was lower than the mutant allele frequency for SNP5, SNP6, SNP10, SNP11, and SNP12. The PIC test results indicated that all SNPs could be considered intermediate polymorphisms, making them good genetic markers. All SNPs except SNP1 were in Hardy-Weinberg equilibrium (P > 0.05).

3.2. Relationships between Genotypes and Reproductive Traits

The results of the association analyses showed that g. 22176870T>C, g. 22177100T>C, g. 22177149T>C, g. 22177991A>G, and g. 22178975G>A were significantly associated with EN (P < 0.05, Table 5). No significant associations were found between other SNPs and the reproductive traits. Therefore, subsequent genotype association analyses were performed for g. 22176870T>C, g. 22177100T>C, g. 22177149T>C, g. 22177991A>G, and g. 22178975G>A (Table 6). The results showed that genotypes at the g. 22176870T>C, g. 22177100T>C, g. 22177149T>C SNPs were significantly associated with EN (P < 0.05). Birds with the TC genotype at these SNPs had significantly higher ENs than those with the CC genotype. At the INHA exon 2 SNP g. 22177991A>G was significantly associated with EN (P = 0.025), birds with the AG genotype had higher EN values. SNP g. 22178975G>A genotypes in INHA gene was significantly associated with EN (P < 0.05), with genotype GA had more EN than AA genotype (P < 0.01). Conversely, chickens with genotype AA had heavier FEW than those with GA genotype.

3.3. Construction of Haplotypes and Their Associations with Chicken Reproductive Traits

Analysis of LD between SNPs in the INHA gene was shown in Figure 2. Haplotypes were constructed based on the 12 SNPs identified in LH chickens using the Haploview program (Table 7). H1 was the most frequent haplotype at 53.7 %. Ten diplotypes were obtained based on these five haplotypes (Table 8). However, no significant associations were determined between the reproductive traits in the chicken population and the haplotypes according to regression coefficient analysis.

3.4. Expression of INHA in the Chicken Reproductive System

According to expression analysis, INHA is mainly expressed in the ovary and follicles (F1-F5, SYF, and LWF). During development of chicken follicles, the relative abundance of INHA mRNA initially increased and then decreased, with significantly higher expression in F5 than others (P < 0.05). In pre-grade follicles, the INHA mRNA expression increased abruptly in SWF follicle (P < 0.05). Expression levels in the F1, F2, and F3 follicles were low and did not significantly differ from each other (P > 0.05) (Figure 3(a)).

The protein expression levels of INHA in different chicken period follicles were detected by Western blotting, with β-actin protein used as a reference. The results showed higher expression of the INHA protein in F5 compared with other follicles (P < 0.01) (Figure 3(b)). In the prehierarchical follicles, INHA protein was highly expressed in SYF. These results suggested that INHA is a potential candidate gene for improving chicken reproductive traits.

4. Discussion

Inhibins play key roles in folliculogenesis, oocyte maturation, and embryo development [26]. The INHA gene encodes the functional center of inhibin and may exhibit potential for increasing the ovulation rate in poultry. For example, the downregulation of INHA gene expression in cultured goose granulosa cells resulted in significant increases in apoptosis and proliferation indexes, a reduced percentage of cells in the G1 phase, and a correspondingly elevated percentage of cells in the S phase [20]. Moreover, transgenic mice overexpressing the rat INHA gene exhibited a reduced litter size and longer intervals between pregnancies when compared with control mice [27]. In some studies, polymorphisms in the INHA gene have been found to be significantly associated with follicular cysts in humans [28], pigs [19, 29], and other mammals [3032]. However, INHA polymorphisms associated with reproductive traits in chicken were previously unknown. The purpose of this experiment was to improve the reproductive performance of LH chickens and provide molecular markers for the selective breeding of laying hens.

Ovulation rate is an important reproductive trait, and the important function of INHA makes it a strong candidate for improving the poultry ovulation rate. We hypothesized that INHA may be a major gene affecting chicken egg production. The AFE, as well as other egg production and egg weight parameters, are important traits used in the breeding of high-quality layers. Therefore, understanding the effects of the INHA gene on these reproductive traits is essential. However, information previously available in the literature regarding the relationships between INHA polymorphisms and reproductive traits was inconclusive.

Recently, several studies in poultry have been identified crucial genes and explored their relationship with phenotypes, such as Liu with 279 Dongxiang blue-shelled chickens [33], Yu with 188 female Muchuan black-boned chickens [34], and EI-Sabrout with 200 Lohmann Brown hens [35]. In this study, 12 SNPs were detected in INHA gene. All SNPs except for SNP1 were in Hardy-Weinberg equilibrium (P > 0.05), and their genotype and allele frequencies were above 5 %, which indicate that the population is not affected by artificial selection and its sample size is appropriate for association analysis [36].

Five SNPs (g. 22176870T>C, g. 22177100T>C, g. 22177149T>C, g. 22177991A>G, and g. 22178975G>A) that were significantly associated with chicken EN. This result is similar to that studied in Boer goats, in which the c.651G>A mutation in the INHA gene affected the lambing rate [31]. Egg production is an important economic indicator in the poultry industry, and in poultry breeding programs, EN is considered the most valuable indicator of total egg production potential. Our findings therefore confirm the influence of INHA polymorphisms on the female reproductive traits of LH chickens. We therefore deduce that INHA is an important gene for improving the EN in chickens.

The SNP g. 22177991A>G results in the amino acid substitutions Val→Ala. Zi et al. found that sequence variation in INHA was associated with the prolificacy of goat breeds, suggesting that amino acid substitutions in this gene may affect reproductive traits in chicken [37]. While SNP3 results in a synonymous mutation that causes no amino acid change, this mutation was still associated with a reproductive trait. One explanation for this is that this mutation may affect INHA function by altering the stability of the mRNA and its translation efficiency. Therefore, this SNP may be associated with the mRNA expression level and increase in INHA concentration may lead to decreases in FSH concentrations [38].

Zhu et al. analyzed miRNA-related SNPs and found that two SNPs in the 3 UTRs of target genes were predicted to either disturb or create miRNA-target interactions [39]. In the present study, SNP g. 22178618T>C in the 3 UTR of INHA was predicted to disturb miR-128-3p combination. Yu et al. confirmed the suppression of CYP2C9 by the miRNA hsa-miR-128-3p in human liver cells and its association with hepatocellular carcinoma [40], while miR-128-3p was found to suppress hepatocellular carcinoma proliferation [41]. SNP g. 22178728C>T was predicted to create bindings sites for two miRNAs miR-125b-5p and miR-34b-5p. miR-125b-5p serves as a novel biomarker for HBV-positive hepatocellular carcinoma [42], and miR-34b-5p inhibits the expression of Bcl-2 in ovarian cancer cells [43]. This suggests that miRNA-related SNPs in the 3 UTR of INHA may affect poultry reproductive performance. Further studies are needed to confirm that miRNA-related SNPs regulate mRNA and protein expression levels.

Good laying performance of poultry depends on the growth and development of follicles in the ovary. In poultry, only a few of the large number of follicles mature, with only about 5 % developing into SYF. Improving the laying rate and reproductive performance of native chicken breeds has become an urgent concern for chicken breeding and production. The expression levels and forms of inhibin are closely related to physiological activities such as follicular development, recruitment, and dominance selection. Furthermore, as INHA is the functional center of inhibin, we hypothesis that the expression level of the chicken INHA gene plays a dominant role in follicle development and is related to chicken reproductive traits. Although many studies have shown INHA to be a critical regulator of gonadal function, little is known about its expression in chicken developing follicles and the association between its expression and reproductive traits. In this study, we found that the INHA gene only expressed in the developing follicles. Intriguingly, INHA mRNA expression was the lowest in F1 and highest in F5, consistent with previous results in humans [44]. In the prehierarchical follicles, INHA mRNA expression increased sharply in the SWF. Zi et al. previously found that the mRNA expression levels of INHA affected prolificacy in goats [37]. The development of LWF into SYF is an important process in the recruitment of follicles in poultry [45]. Additionally, the INHA protein expression profile in the follicle was similar to that of its mRNA counterpart with greater expression in F5 and SYF follicles. These results indicate that the expression of INHA is related to follicle development. It can therefore hypothesize that INHA is involved in the regulation of follicle development, playing a critical role in follicle recruitment. Further study is needed to illuminate the specific action mechanism of INHA.

5. Conclusion

Generally, 12 SNPs were identified in chicken INHA gene. Five of them were significant associated with egg numbers. Among the exonic SNPs, g. 22177991A>G, g. 22178249G>C, and g. 22178414G>A were missense mutations, which resulted in the amino acid substitutions Val→Ala, Ala→Gly, and Ala→Gly. In addition, INHA highly expressed in F5 and SYF follicles. Therefore, we conclude that INHA is a candidate gene affecting egg production, and it plays a critical role in the recruitment of follicles in chickens. INHA SNPs are possible molecular markers for the genetic selection of layers.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declared no conflicts of interest.

Authors’ Contributions

Zhifu Cui and Lingbin Liu contributed equally to this work.


The authors gratefully acknowledge Lin Ye for sample collection. This work was financially supported by scientific research fund of Sichuan Provincial education department (15ZA0025), the Thirteenth Five Year Plan for Breeding Program in Sichuan (2016NYZ0050), and the China Agriculture Research System (CARS-41).