
==== Front
Poult Sci
Poult Sci
Poultry Science
0032-5791
1525-3171
Elsevier

S0032-5791(24)00792-2
10.1016/j.psj.2024.104213
104213
GENETICS AND MOLECULAR BIOLOGY
Novel insights into the mechanisms of seasonal cyclicity of testicles by proteomics and transcriptomics analyses in goose breeder lines
Mabrouk Ichraf *1
Song Yupu *1
Liu Qiuyuan *
Ma Jingyun *
Zhou Yuxuan *
Yu Jin *
Hou Jiahui *
Hu Xiangman *
Li Xinyue *
Xue Guizhen *
Cao Heng *
Ma Xiaoming *
Xu Jing *
Wang Jingbo *
Pan Hongxiao *
Hua Guoqing *
Hu Jingtao *
Sun Yongfeng sunyongfeng@jlau.edu.cn
*†‡2
⁎ College of Animal Science and Technology, Jilin Agricultural University, Changchun, 130118, China
† Key Laboratory of Animal Production, Product Quality and Security, Jilin Agricultural University, Ministry of Education, Changchun, 130118, China
‡ Joint Laboratory of Modern Agricultural Technology International Cooperation, Ministry of Education, Jilin Agricultural University, Changchun, 130118, China
2 Corresponding author: sunyongfeng@jlau.edu.cn
1 These authors contributed equally to this work.

14 8 2024
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© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Spermatogenesis is a crucial indicator of geese reproduction performance and production. The testis is the main organ responsible for sperm production, and the egg-laying cycle in geese is a complex physiological process that demands precise orchestration of hormonal cues and cellular events within the testes, however, the seasonal changes in the transcriptomic and proteomic profiles of goose testicles remain unclear. To explore various aspects of the mechanisms of the seasonal cyclicity of testicles in different goose breeds, in this study, we used an integrative transcriptomic and proteomic approach to screen the key genes and proteins in the testes of 2 goose males, the Hungarian white goose and the Wanxi white goose, at 3 different periods of the laying cycle: beginning of laying cycle (BLC), peak of laying cycle (PLC), and end of laying cycle (ELC). The results showed that a total of 9,273 differentially expressed genes and 4,543 differentially expressed proteins were identified in the geese testicles among the comparison groups. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis suggested that the DEGs, in the comparison groups, were mainly enrichment in metabolic pathways, neuroactive ligand-receptor interaction, cyctokine-cyctokine receptor interaction, calcium signaling pathway, apelin signaling pathway, ether lipid metabolism, cysteine, and methionine metabolism. While the DEPs, in the 3 comparison groups, were mainly involved in the ribosome, metabolic pathways, carbon metabolism, proteasome, endocytosis, lysosome, regulation of actin cytoskeleton, oxidative phosphorylation, nucleocytoplasmic transport, and tight junction. The protein-protein interaction network analysis (PPI) indicated that selected DEPs, such as CHD1L, RAB18, FANCM, TAF5, TSC1/2, PHLDB2, DNAJA2, NCOA5, DEPTOR, TJP1, and RAPGEF2, were highly associated with male reproductive regulation. Further, the expression trends of 4 identified DEGs were validated by qRT-PCR. In conclusion, this work offers a new perspective on comprehending the molecular mechanisms and pathways involved in the seasonal cyclicity of testicles in the Hungarian white goose and the Wanxi white goose, as well as contributing to improving goose reproductive performance.

Key words

goose
testicule
omics
transcriptomics
proteomics
==== Body
pmcINTRODUCTION

Goose is an economically valuable waterfowl that can provide both meat and feathers (Shi et al., 2008). However, geese have the lowest reproductive performance and efficiency when compared to ducks and chickens, which severely restricts the growth of the industry and reduces farmer income. Furthermore, the egg-laying in geese is characterized to be concentrated in certain months or seasons of the year, so they exhibit seasonal or annual laying, of which this seasonality of the breeding also impedes the development of the goose industry and creates an obstacle in maintaining the whole year commercial production (Shi et al., 2008; Sun et al., 2022). To increase the reproductive performance of geese and facilitate modern goose production, animal breeders have attempted a variety of approaches and breeding techniques, including modulating environmental factors (Wang et al., 2005; Chang et al., 2016), nutrition (Zhang et al., 2019), and genetic backgrounds (Gao et al., 2021). According to previous studies, the crossbreeding strategy has emerged as the most promising method for enhancing reproductive performance (Sui et al., 2022), and more attention has been paid to the egg-laying performance of geese, which is directly influenced by male reproductive performance ( Zhang et al., 2019; Gao et al., 2021).

Generally, the continuity of the goose population and the whole goose production is mainly influenced by the reproductive ability of goose males, which directly impacts the production of fertilized eggs (Shi et al., 2008; Song et al., 2024). The testis is the only organ known to be able to create male gametes (spermatozoa) and regulate sexual maturity, which are necessary for male fertility, and the growth and physiological alterations of the testis are the main factors that influence the ability to fertilize and the quality of the semen (Akhtar et al., 2020). The seminiferous tubules within the testis are the main site of spermatogenesis, and testis spermatogenic ability is very important for the fertilization rate, with a great significance in the synchronous estrus, synchronous mating, and the acquisition of fertilized eggs (Gumułka and Rozenboim, 2015; Akhtar et al., 2020; Scanes et al., 2020). Unlike mammals, the testes of geese, as seasonal breeders, undergo dynamic changes in morphology and function in response to seasonal variations, which affect reproduction behavior (Zhuang et al., 2018). Several studies have reported the seasonal changes in goose testicles hormones and morphology (Shi et al., 2007; Leska et al., 2012; Gumułka and Rozenboim, 2015; Leska et al., 2015), but few have investigated the seasonal molecular changes in testis (Ran et al., 2021; Lin et al., 2023; Hao et al., 2024; Song et al., 2024).

In goose reproduction, the Hungarian white goose and the Wanxi white goose are 2 goose breeds generally used as male parents. Recently, Hungarian white geese (Anser anser) were frequently raised as an exceptionally imported breed, which was introduced in 2005 to China, and its popularity continues to rise in many regions around the country (Kozák, 2021; Bao et al., 2022). The Hungarian white goose is a middle-sized breed with an elegant appearance and excellent reproductive characteristics and is praised for their valuable contributions to down and meat production, as their down is renowned for their exceptional quality (Bao et al., 2022). It is widely known that Hungarian white geese typically breed during the spring and early summer months, with peak breeding activity occurring between March and May. The Wanxi white goose, a native Chinese breed, is also a medium-sized goose descended from the Greylag goose (Anser anser), known for its high meat and down production, and is one of the most prevalent terminal male parents in China's goose production industry (Li et al., 2011; Du et al., 2022). Egg production for this breed begins mainly in late autumn or early winter, ends in late spring or early summer, and generally reaches a peak when day length begins to extend (Shi et al., 2008).

With the advancement of mass spectrometry (MS) devices, numerous proteome-level studies have been conducted to identify the molecular basis of reproduction in mammals and poultry (Li et al., 2016; Shen et al., 2021; Wadood et al., 2021; Song et al., 2024). Most studies on reproduction rely on transcriptome profiling due to their sensitivity and affordability (Abdulghani et al., 2019). However, research suggests that mRNA may not be an adequate indicator of protein expression (Sun et al., 2022). Recently, the integration of transcriptome and proteomic data has become the most used technique in poultry research and has allowed the generation of large amounts of data to study complex developmental processes related to animal studies (Dehau et al., 2022). However, to our best knowledge, the expression of mRNAs and proteins in poultry male reproductive organs in different seasons is still unknown.

In this study, an integrated analysis of RNA sequencing and proteomics was used to understand the regulatory mechanisms of the identified differential gene and protein expression in the testicles of 2 different goose breeds (Hungarian white goose (HWG) and Wanxi white goose (WWG)) at the 3 important reproductive stages of the laying cycle: the beginning of laying cycle (BLC), peak of laying cycle (PLC), and end of laying cycle (ELC). Therefore, the current study aims to investigate the seasonal changes in the testicular genes and proteins expression pattern and in testicular histology to better clarify the cyclic changes in the testes during the reproductive cycle in geese, which could provide a theoretical basis for promoting male reproductive traits and breeding efficiency.

MATERIALS AND METHODS

Ethics Statement

All procedures for animal experiments were carried out in strict accordance with the Experimental Management Protocols of Jilin Agricultural University (Changchun, Jilin, China). The protocol was approved by the Animal Health Care Committee of the Animal Science and Technology College of Jilin Agricultural University (Approval No. GR (J) 18-003). All measures were taken to reduce animal suffering.

Animals and Sample Collection

Hungarian and Wanxi white geese were obtained from the Jilin Agricultural University Goose Industry R&D Center Joint Breeding Base. The ganders were healthy and reared under standardized conditions with consistent access to feed, water, and housing. We used 9 adult ganders of each breed in the current study, with 3 biological replicates that were randomly selected at each of the 3 different stages of the laying cycle (BLC [215 d of age], PLC [265 d of age], and ELC [315 d of age]). The selected ganders were fasted for 12h prior to slaughter and sacrificed by slaughter from the neck. The samples from the left and right testicles were collected, snap frozen in liquid nitrogen, and stored at -80°C for further transcriptome and proteomic sequencing and qPCR verification. For the histological observations, the testicular tissues (n = 3) were fixed in 4% paraformaldehyde.

Hematoxylin and Eosin Staining

Paraffin embedding and testicular tissue sectioning were carried out using the standard protocols. For Hematoxylin and Eosin (HE) staining, the sections were dewaxed in xylene twice for 15 min each and soaked in a series of ethanol solutions: 100, 90, 80, and 70% for 5 min each. The staining procedure followed the instructions provided in the HE staining kit. Finally, the slides were sealed with neutral resin adhesive and examined under a Nikon-300 light microscope (Nikon, Tokyo, Japan) to observe morphological alterations in the testicular tissues between the 2 goose breeds.

Collection and Analysis of Transcriptomic Data

The testicular tissues of the 2 breeds from each stage of the laying cycle were sent to Smart Genomics Technology Co., Ltd. (Tianjin, China) for RNA extraction and sequencing. Total RNA was extracted from testicular tissues using the QIAzol Lysis Reagent kit (QIAGEN, Germany), and RNA quality and integrity were determined using an Agilent 2100 bioanalyzer (Agilent Technologies, Palo Alto, CA). Eukaryotic mRNA was enriched using oligo (dT) beads, and the Ribo-Zero Magnetic Kit (Epicenter) was used to eliminate rRNA from total RNA to obtain mRNA. The enriched mRNA was then fragmented into small fragments using the NEB Fragmentation Buffer. RNA-seq library construction was performed according to the NEB normal library construction method or the strand-specific library construction method (Chen et al., 2018) by the TruSeq PE Cluster Kit v4-cBot HS (Illumina, San Diego, CA). Furthermore, the sequencing was conducted after using Qubit 2.0 for preliminary quantification and after the libraries were sequenced on an Illumina HiSeq X Ten platform (San Diego, CA) to generate 150 bp pair-end reads. Clean reads were generated by filtering the raw reads and removing reads including, adapter, poly-N and unqualified reads from the original dataset using FASTQ (Mortazavi et al., 2008) by considering quality parameters such as GC content, Q20, and Q30. Feature counts (http://subread.sourceforge.net/) were used to calculate the number of reads that mapped to each gene, and the obtained reads were compared to the goose reference genome (Anser Anser) (https://www.ncbi.nlm.nih.gov/datasets/genome/GCA_026259575.1/). Further, the HISAT 2 software (v. 2.2.1) was used to design the goose genome map.

Differential Expression of mRNAs Quantification

For RNA-seq, the gene expression levels were measured in fragments per kilobase of mappable length and million counts (FPKM). DESeq2 software (http://bioconductor.org/packages/stats/bioc/DESeq2/) was used to analyze the differential expression between the 2 comparative combinations and to obtain volcano maps, which revealed the number and distribution of the DEGs. Genes that were considered differentially expressed genes (DEGs) were found to give adjusted P-values (q values) ≤ 0.05 and |log2FC|≥1. P-values were adjusted using the Benjamini and Hochberg method (Benjamini and Hochberg 1995). The corrected P-values (q values) and |log2foldchange| were used as thresholds for significant differential expression.

Collection and Analysis of Proteomic Data

Extraction of Protein

Proteomic analyses were performed by Smart Genomics Technology Co., Ltd. (Tianjin, China). Total proteins from the testis samples were extracted using the cold acetone method with 2 mL of lysis buffer (2% SDS, 8 M urea, 1 mg/mL protease inhibitor cocktail [Roche Ltd., Basel, Switzerland]). Subsequently, sonication was performed for 30 min on ice, followed by centrifugation at 15,000 rpm for 15 min at 4°C, and incubation with ice-cold acetone at -20°C for 12 h. The pellet was rinsed with acetone 3 times and redissolved in 8M urea by sonication on ice. Protein qualification was performed by SDS-PAGE.

Digestion of Protein and Tandem Mass Tag Labeling Technique

The Pierce BCA Protein Assay Kit (catalog#23227, Thermo Fisher Scientific, MA) was utilized to identify the protein concentration. Then, 50 μg of protein was diluted in 50 μL of extraction solution. Protein samples were reduced with 1 μL of 10 mM dithiothreitol (DTT) at 55°C for 1h and alkylated in 5 μL of 20 mM iodoacetamide (IAA) in the dark at 37°C for 1h. Subsequently, the samples were precipitated with 300 μL of precooled acetone at 20°C overnight and resuspended in 50 mM ammonium bicarbonate. This was followed by overnight digestion at 37°C with trypsin (Promega Co., Ltd., Madison, WS). The mixture of peptide was marked with a Tandem Mass Tag (TMT), and the identified samples were mixed and dried under vacuum.

High pH Reverse Phase Separation and Proteomic Data Processing

The buffer A (buffer A: 20 mM ammonium formate in water, pH 10.0, adjusted with ammonium hydroxide) was used to redissolve the mixture of peptide, and then the Ultimate 3,000 system (ThermoFisher Scientific, Waltham, MA), linked to a reverse phase column (XBridge C18 column, 4.6 mm × 250 mm, 5μm, (Waters Corporation, Milford, MA), was employed to fractionate the peptide using pH separation. A linear gradient from 5% B to 45% B within 40 min (B: 80% ACN in 20 mM ammonium formate, ammonia adjusted to pH 10.0) was utilized for high pH separation. The column was equilibrated for 15 min under the initial conditions, and six fractions were collected and dried in a vacuum concentrator. The database was built using the results collected by the digital differential analyzer (DDA) method after the peptides were detached by liquid chromatography and analyzed by data-independent acquisition (DIA) mass spectrometry. The peptides were analyzed using online liquid chromatography tandem mass spectrometry (LC-MS/MS).

Detection and Quantification of Differential Expressed Proteins

Mass spectrometry data acquired from LC-MS/MS analysis were processed using the Spectronaut 17 software (Biognosys AG, Zurich, Switzerland) to quantify and identify peptides and proteins. The Scaffold Local FDR algorithm accepted protein identifications with a false discovery rate (FDR) of less than 1.0%. The proteins with unadjusted significance levels of p < 0.05 and foldchange (FC) ≥1.5 were identified as differentially expressed proteins (DEPs). Further, volcano plots of DEPs were carried out using the OmicShare online platform (https://www.omicshare.com/).

Functional Enrichment Analysis of Identified Transcripts and Proteins

Functional enrichment analyses of GO and KEGG (Huang et al., 2009 ) were conducted for DEGs and DEPs related to testicular development. Genes with q ≤ 0.05 and foldchange (FC) ≥ 2 were considered as differentially expressed genes, and proteins with p < 0.05 and foldchange (FC) ≥ 1.5 were identified as differentially expressed proteins. The Gene Ontology (GO) is an organized approach to identify genes and proteins functions, which was performed using the GeneOntology database (http://www.geneontology.org/), in which DEGs and DEPs were assigned to GO terms and annotated from 3 major categories such as, biological process, molecular function, and cellular component. The Kyoto Encyclopedia of Genes and Genomes (KEGG) (Aoki-Kinoshita and Kanehisa, 2007) is the first public-related pathway database (http://www.genome.jp/kegg/), which was used to screen the most significant pathways in which the DEGs and DEPs were mostly enriched compared with the whole genome background. GO terms and KEGG pathways with P-values < 0.05 were considered significantly enriched for DEGs and DEPs.

Quantitative Real-Time PCR (RT-qPCR) Analysis Validation

The RT-qPCR analysis was used to further test the accuracy of the transcriptome data using the genes with significant expression, with 3 biological replicates. TransStart Green qPCR SuperMix (catalog #AQ101-02, TransGene Biotech, Beijing, China) was used for RT-qPCR following the manufacturer's instructions, with the 18S rRNA gene as the internal reference gene. Relative gene expression levels were calculated using the 2−ΔΔCT method (Kenneth and Schmittgen, 2001 ). All the primers used are listed in Table 1. SPSS 22.0 software was utilized for statistical analysis of the variation between RT-qPCR and RNA-seq results, with p < 0.05 deemed as statistically significant. The results were visualized using the GraphPad Prism 10 software.Table 1 Statistics of DEGs identified in geese testicles in different groups.

Table 1Groups	Up regulated	Down regulated	Total DEGs	
BLC (HWG vs. WWG)	423	318	741	
PLC (HWG vs. WWG)	461	559	1020	
ELC (HWG vs. WWG)	3596	3916	7512	

Integrated Proteome and Transcriptome Analysis

Combined transcriptome and proteome analysis is commonly used to study organismal expression regulatory patterns and mechanisms, as well as to analyze gene and protein expression levels. Transcriptomic and proteomic data were submitted to the OmicShare online platform (https://www.omicshare.com/) to create a nine-quadrant map to investigate the relationship between the transcripts and proteins found in the testicles of ganders during the breeding season.

Network Analysis of Protein-Protein Interactions (PPI)

The STRING-db server database (https://cn.string-db.org) (Franceschini et al., 2013 ) was used to build a protein-protein interaction network map to identify key protein-protein interactions related to male reproduction regulation. PPI was created using the most differentially expressed proteins associated with male reproduction regulation. To screen the DEPs, we utilized a threshold value of fold change greater than 1.5. The resulting interaction network was displayed using Cytoscape (v.3.9.0) (Shannon et al., 2003).

RESULTS

Testicular Tissues Histology of Wanxi White Goose and Hungarian White Goose at different Periods of the Laying Cycle

The morphology of the testicular tissue at 3 stages of the laying cycle was observed using HE staining (Figure 1). The results showed that an active spermatogenesis was noticed in seminiferous tubules during the breeding season for both Wanxi and Hungarian white geese. The testes presented a normal architecture of the seminiferous tubule, in which that appeared hexagonal, or circular surrounded with basement membrane with regular contour and interstitial tissue and with a normal arrangement of cellular types. The high magnification of the testis sections confirmed that the seminiferous tubules was lined with series of spermatogenic cells, including spermatogonia, primary spermatocytes and spermatozoa. Furthermore, the results showed that both geese breeds had similar testicular development.Figure 1 Histological analysis of sections from Wanxi and Hungarian white geese gander testis at 3 different stages of the laying. BM: basement membrane, MC: myoid cells, S: spermatogonia, PS: primary spermatocytes, SZ: spermatozoa, Sp: sperm cell, Sc: Sertoli cells. Magnification: 400x. Scale bar: 20 μm.

Figure 1

Identification of Gene Expression Changes in Wanxi White Goose and Hungarian White Goose Testicles at 3 Different Periods of the Laying Cycle

Differences in the gene expression patterns of mRNAs involved in male reproduction regulation during the 3 reproductive stages of the laying cycle between the 2 goose breeds were studied. Differentially expressed genes (DEGs) were screened as those with |log2FC|≥1 and q-value ≤ 0.05. As a result, a total of 9273 genes were identified. Overall, 741 genes were identified in the BLC (HWG vs. WWG) group, with 423 upregulated and 318 downregulated genes (Figure 2A). In the PLC (HWG vs. WWG) group, 1020 genes were screened (461 upregulated and 559 downregulated) (Figure 2B), and 7,512 genes were found in the ELC (HWG vs. WWG) group (Figure 2C), of which 3596 were upregulated and 3,916 were downregulated (Table 2).Figure 2 Differentially expressed genes (DEGs) in testicles tissues of the Wanxi white goose and Hungarian white goose at the same reproductive stages of the laying cycle. (A) The volcano plot of the DEGs in the testis tissues at the beginning of the laying cycle (BLC). (B) The volcano plot of the DEGs in the testis tissues at the peak of the laying cycle (PLC). (C) The volcano plot of the DEGs in the testis tissues at the end of the laying cycle (ELC). The X-axis represents log2(Fold Change) and the Y-axis shows the -log10(q-value). Red dots represent upregulated genes, green dots represent downregulated genes and blue dots represent genes that were not differentially expressed (q ≤ 0.05, FC ≥ 2).

Figure 2

Table 2 Statistics of DEPs identified in geese testicles in different groups.

Table 2Groups	Up regulated	Down regulated	Total DEPs	
BLC (HWG vs. WWG)	514	398	912	
PLC (HWG vs. WWG)	1363	620	1983	
ELC (HWG vs. WWG)	1073	575	1648	

Identification of Protein Expression Changes in Wanxi White Goose and Hungarian White Goose Testicles at 3 Different Periods of the Laying Cycle

Differentially expressed proteins (DEPs) in Wanxi white goose and Hungarian white goose testicles at 3 reproductive stages of the laying cycle were screened using the iTRAQ labeling technology in combination with LC-MS/MS. A total of 4543 proteins were screened, of which the DEPs or the quantified proteins are those with FC ≥ 1.5 and P-value < 0.05. Generally, 912 proteins were identified in the BLC (HWG vs. WWG) group (514 upregulated and 398 downregulated), 1,983 in the PLC (HWG vs. WWG) group (1,363 upregulated and 620 downregulated), and 1648 proteins in the ELC (HWG vs. WWG) group, of which 1,073 were upregulated and 575 were downregulated (Figure 3 and Table 3).Figure 3 Differentially expressed proteins (DEPs) in testicles tissues of the Wanxi white goose and Hungarian white goose at the same reproductive stages of the laying cycle. (A) The volcano plot of the DEPs in the testis tissues at the beginning of the laying cycle (BLC). (B) The volcano plot of the DEPs in the testis tissues at the peak of the laying cycle (PLC). (C) The volcano plot of the DEPs in the testis tissues at the end of the laying cycle (ELC). The X-axis represents log2(Fold Change) and the Y-axis shows the -log10(p-value). Red dots represent upregulated genes, blue dots represent downregulated genes and gray dots represent genes that were not differentially expressed (p < 0.05, FC ≥ 1.5).

Figure 3

Table 3 The primer information of qRT-PCR.

Table 3Gene	Species	Primer sequence (5′–3′)	Tm (°C)	Product size (bp)	
EIF4G2	Anser Anser	TCCAGCCAGGTTAGCCATTG
CTCCAGGTGCACTGCTACAA	60.03
59.96	185	
HSPA4L	Anser Anser	CTCCTACAGAGCCATTCGGC
GACCATCGCCAACGAGTACA	60.25
60.11	230	
ITM2A	Anser Anser	CGAATGTCAGCTTCTTCGGC
GTGTACCGTGGCGAAATGTG	59.63
59.83	95	
SERF1A	Anser Anser	GACTTCCTCTCGTTAGCCGC
CCATGACTCGTGGGAACCAG	60.53
60.39	169	
18S rRNA	Anser Anser	GCATGGCCGTTCTTAGTTGG
GAACGCCACTTGTCCCTCTA	59.55
59.39	300	

GO Enrichment and KEGG Pathway Analysis of Differentially Expressed Genes

To investigate the function of the differentially expressed genes (DEGs), gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analyses were performed to identify their potential implications. The GO enrichment analysis focused on upregulated and downregulated DEGs. The DEGs annotated in GO terms were classified into 3 principal categories: biological process (BP), molecular function (MF), and cellular component (CC). We noticed that “cellular process”, “metabolic process”, “single organism process”, “binding”, “catalytic activity”, “membrane”, “membrane part”, and “cell” were most significantly abundant in BP, MF, and CC, respectively. Also, we discovered that some of the DEGs in the CC and MF categories were enriched in “molecular transducer activity”, “transporter activity”, “signal transducer activity”, and “extracellular region” (Figure 4).Figure 4 Gene Ontology enrichment analysis of the upregulated and downregulated DEGs in testicular tissues of the Hungarian white goose and Wanxi white goose at 3 different reproductive stages of the laying cycle. (A-C) GO analysis of BLC (HWG vs. WWG), PLC (HWG vs. WWG) and ELC (HWG vs. WWG) comparison groups, respectively. The findings are presented in 3 GO categories: biological process, molecular function and cellular component. The Y-axis displays the proportion of genes, whereas the X-axis depicts gene ontology categories.

Figure 4

The KEGG pathway enrichment analysis of the DEGs is illustrated in Figure 5. The results showed that most of the DEGs in the BLC (HWG vs. WWG) group were mainly enriched in “metabolic pathway”, “Neuroactive ligand-receptor interaction”, “cyctokine-cyctokine receptor interaction”, “apelin signaling pathway”, and “calcium signaling pathway”. For the PLC (HWG vs. WWG) group, “neuroactive ligand-receptor interaction”, “calcium signaling pathway”, “apelin signaling pathway”, “cysteine and methionine metabolism” and “ether lipid metabolism” were the most enriched pathways, while “endocytosis”, “nucleocytoplasmic transport”, “regulation of actin cytoskeleton”, “tight junction”, “carbon metabolism”, “lysosome”, “ribosome”, “spliceosome” and “oxidative phosphorylation” were the significant enriched pathways in the ELC (HWG vs. WWG) comparison group. In the PLC (HWG vs. WWG) comparison group, the most enriched DEG in the neuroactive ligand-receptor interaction was the C3 gene, in the calcium signaling pathway and the apelin signaling pathway, were EGF, AGTR1, and PIK3R5, respectively. While in the ether lipid metabolism and cysteine and methionine metabolism, the most enhanced DEGs were PLD1, PLA2G4, CDO1, and BHMT, respectively (Figure 5D).Figure 5 KEGG pathway enrichment analysis of differentially expressed genes in testicular tissues of the Hungarian white goose and Wanxi white goose at 3 different reproductive stages of the laying cycle. (A-C) KEGG analysis of BLC (HWG vs. WWG), PLC (HWG vs. WWG) and ELC (HWG vs. WWG) comparison groups, respectively. The abscissa indicates the percentage of enriched genes, whereas the ordinate shows signal pathways. (D) The Top 20 enrichment pathway and heatmap analysis of differentially expressed genes combination in the PLC (HWG vs. WWG) comparison group.

Figure 5

GO Enrichment and KEGG Pathway Analysis of Differentially Expressed Proteins

Similar to the DEGs, the function of the differentially expressed proteins (DEPs) was also studied using the GO and KEGG analyses. As shown in Figure 6, most of the DEPs were mainly enriched in “metabolic process”, “cellular process”, “single-organism process”, “binding”, “catalytic activity”, “Structural molecule activity”, “cell”, “cell part”, “macromolecular complex”, and “organelle” in biological process, molecular function, and cellular component, the 3 major categories of the Go terms.Figure 6 Gene ontology (GO) enrichment analysis of differentially expressed proteins in testicular tissues of the Hungarian white goose and Wanxi white goose at 3 different reproductive stages of the laying cycle. (A-C) Go terms of DEPs in BLC (HWG vs. WWG), PLC (HWG vs. WWG) and ELC (HWG vs. WWG) comparison groups, respectively. The findings are presented in 3 GO categories: biological process, molecular function and cellular component. The Y-axis displays the proportion of genes, whereas the X-axis depicts gene ontology categories.

Figure 6

Since numerous proteins interact and cooperate to carry out biochemical processes, a KEGG pathway analysis was conducted to determine pathways that could be influenced by changes in protein abundance in geese testicles tissues. We found that most differentially expressed proteins were involved in “ribosome”, “oxidative phosphorylation”, “carbon metabolism”, “biosynthesis of amino acids” and “endocytosis”, “nucleocytoplasmic transport”, “pyruvate metabolism”, and “citrate cycle (TCA cycle)” in the BLC (HWG vs. WWG) comparison group. In the PLC (HWG vs. WWG) group, the “metabolic pathway”, “carbon metabolism”, “endocytosis”, “biosynthesis of amino acids”, and “proteasome” were the major significant pathways, while the DEPs in the ELC (HWG vs. WWG) were participated in “endocytosis”, “regulation of actin cytoskeleton”, “lysosome”, “ribosome”, “spliceosome” and “tight junction”. Interestingly, we noticed that “nucleocytoplasmic transport”, “oxidative phosphorylation”, and “citrate cycle (TCA)” were enriched among the 3 comparison groups (Figure 7).Figure 7 The KEGG analysis identified the pathways related with testicular development of Hungarian white goose and Wanxi white goose, controlled by differentially expressed proteins at 3 different reproductive stages of the laying cycle. (A-C) KEGG analysis of BLC (HWG vs. WWG), PLC (HWG vs. WWG) and ELC (HWG vs. WWG) comparison groups, respectively. The abscissa indicates the percentage of enriched genes, whereas the ordinate shows signal pathways.

Figure 7

qRT-PCR Validation of mRNA Transcripts in Geese Testicles at 3 Different Periods of the Laying Cycle

To confirm the accuracy of the transcriptome sequencing data, we validated the 4 selected DEGs, including Heat shock protein family A member 4 like (HSPA4L), Eukaryotic translation initiation factor 4 gamma 2 (EIF4G2), Small EDRK-rich factor 1A (SERF1A), and Integral Membrane Protein 2A (ITM2A), using qRT-PCR. The results of validation were mostly consistent with the expression levels found in the RNA-sequencing results (Figure 8). This demonstrated that the transcriptome sequencing data were credible.Figure 8 qRT-PCR verification of expression patterns of 4 DEGs. The results are expressed as mean ± SD of 3 replicates and statistical significance: p < 0.05. The 18S rRNA gene expression was used as a reference expressed gene.

Figure 8

Combinative Analysis of Transcriptomic Data and Proteomic Data of the Wanxi White Goose and Hungarian White Goose Testicles at 3 Different Periods of the Laying Cycle

The integrated analysis of the transcriptomic data and the proteomic data was conducted to further explore the consistency between transcript and protein levels in goose testicles during the key reproductive stages of the laying cycle. The scatter plot analysis representing the log2 transformed ratios mRNA:protein was generated to illustrate the corresponding gene: protein ratios distribution. Genes found in the proteome and transcriptome were grouped into nine parts based on their expression patterns, producing a nine-quadrant map (Figure 9). In the scatter plots, the X axis represented the fold change threshold at the protein level, whereas the Y axis showed the fold change threshold at the RNA level. Differentially expressed proteins/genes were shown in the plot outside the threshold line, but the plot inside the threshold line showed no significant differences. Genes were considered as significantly differential genes with a ≥ 2-fold up-regulated or down-regulated in gene expression and protein with a ≥ 1.5-fold up-regulated or down-regulated in protein expression were defined as significantly differential proteins. In the present research, the combinative analysis of the transcriptomic and proteomic data of Hungarian white goose and Wanxi white goose testicles showed a weak association between gene and protein expression with a Pearson's correlation coefficient (R2) of 0.0951, 0.1733, and 0.3195 in the BLC (HWG vs. WWG), PLC (HWG vs. WWG), and ELC (HWG vs. WWG) comparison groups, respectively. We noticed that genes were highly abundant in the fifth quadrant, followed by the fourth and sixth quadrants in all the comparison groups (Figure 9A-C). In general, quadrants one, 2, and 4 reveal that protein abundance was lower than gene abundance, which could be explained by the presence of post-transcriptional or translation factors like miRNA regulation of target genes resulting in the knockdown of protein translation, which explains that genes were up-regulated but proteins were unchanged or down-regulated. Moreover, genes located in quadrants 3 and 7 were consistent in their expression patterns with the related proteins, indicating synchronous changes in transcription and translation levels. In quadrants 6, 8, and 9, the abundance of proteins was higher than that of genes, which means that proteins were up-regulated while genes were unchanged or down-regulated, implying translational level regulation or accumulation of proteins. Quadrant 5 displays that both co-expressed genes and proteins were not differentially expressed, suggesting that the majority of genes and proteins in cells were not differentially expressed.Figure 9 Correlation analysis of transcriptome-proteome associations. (A) Nine-quadrant diagram of BLC (HWG vs. WWG) comparison group. (B) Nine-quadrant diagram of PLC (HWG vs. WWG) comparison group. (C) Nine-quadrant diagram of ELC (HWG vs. WWG) comparison group. The Y-axis indicates the log2 ratio of transcripts, whereas the X-axis represents the log2 ratio of proteins. Different colors were used to symbolize different quadrants, as indicated in each diagram and the dotted line represented the threshold line for differential expression.

Figure 9

Protein-Protein Interaction Networks (PPI) of the Wanxi White Goose and Hungarian White Goose Testicles at 3 Different Periods of the Laying Cycle

We conducted PPI network analysis to study the interaction between the differentially expressed proteins using the STRING database. The results showed that the protein-protein interaction analysis network, composed of 155 nodes, illustrates the differentially expressed proteins and the edges, which show the interaction between these DEPs. We noticed that the 3 groups of DEPs were highly interacted, including Chromodomain helicase/ATPase DNA binding protein 1-like (CHD1L), Ras-related protein Rab-18 (RAB18), Fanconi anemia, complementation group M (FANCM), TATA-box binding protein associated factor 5 (TAF5), Tuberous sclerosis proteins 1 and 2 (TSC1/2), Pleckstrin homology like domain family B member 2 (PHLDB2), DnaJ homolog subfamily A member 2 (DNAJA2), Nuclear receptor coactivator 5 (NCOA5), DEP Domain Containing MTOR Interacting Protein (DEPTOR), Tight junction protein 1 (TJP1), and Rap guanine nucleotide exchange factor 2 (RAPGEF2), among others, which were higher known to be associated with cells activities and functions related to male reproduction regulation (Figure 10).Figure 10 Established protein-protein interaction (PPI) network of key proteins. The color circles symbolize the proteins, while the edges illustrate the interactions.

Figure 10

DISCUSSION

Goose is one of the most important waterfowl and a productive poultry species that, over the past 2 decades, has experienced remarkable profitability in China and worldwide as an important source of eggs, meat, fat liver, goose fat, down, and feathers (Kozák, 2021; Akhtar et al., 2022), but the goose industry faces a lot of problems that hinder the development of this sector. Geese are known to have the lowest reproductive capacity compared with other industrial poultry species such as quail, broilers, ducks, and turkeys, especially the low reproduction performances of ganders, as well as relatively poor sperm quality and fertility (Lukaszewicz et al., 2003), which remains as a significant obstacle to establish a comprehensive production approach (Tóth-Baranyi, 1957). As a result, a lot of strategies were adopted to ameliorate the reproductive performance of breeder geese stock, especially the fertility performance of the ganders, including animal husbandry practices, disease prevention measures, staff training initiatives, crossbreeding programs, nutritional adjustments, and stringent biosecurity protocols (Zhang et al., 2019; Akhtar et al., 2022).

For male reproduction, testicles are indispensable organs that play a pivotal role as the principal reproductive glands responsible for producing sperm cells and the synthesis of testosterone, the primary male sex hormone, which is important for male fertility (Ding et al., 2014; Akhtar et al., 2020). The fertility of ganders in geese is a crucial factor for the production of fertilized eggs and the continuity of goose population development (Shi et al., 2008). Studies have shown that gonadal steroid hormone secretions in geese are strongly related to egg-laying, under natural photoperiodic conditions, and the annual androgen secretion in ganders may also be influenced by the presence of female mates, with the peak of secretions being noticed before the onset of egg-laying (Shi et al., 2008; Izumi et al., 1992).

Recently, several studies have illustrated the molecular mechanism underlying the testicular development in various poultry species (Du et al., 2022; Sun et al., 2023; Zhu et al., 2023; Wang et al., 2023; Zhang et al., 2024), but a few studies have been conducted on goose male testis (Ding et al., 2014; Zhuang et al., 2018; Ran et al., 2021; Lin et al., 2023; Song et al., 2024). In this study, we used high-throughput molecular biological techniques, like transcriptomic and proteomic approaches, to investigate the complex biological mechanisms and the role of the key genes and proteins to further understand the changes in molecular processes controlling testicular function between the Wanxi white goose and the Hungarian white goose at 3 critical reproductive stages of the laying cycle. To the best of our current knowledge, this research is the first study to comparatively evaluate the transcriptional and protein pattern alterations of testicles during 3 periods of the laying cycle in 2 kinds of goose breeds, the Hungarian white goose and the Wanxi white goose.

A total of 9,273 transcripts and 4,543 proteins were found to be differentially expressed upregulated or downregulated in the testicles during the 3 critical reproductive stages of the laying cycle when comparing the 2 kinds of goose breeds. Our observations indicated that the differentially expressed genes and proteins, identified through RNA sequencing and proteomic analysis within the various comparative groups, showed substantial enrichment in several signaling pathways, including metabolic pathways, neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction, calcium signaling pathway, apelin signaling pathway, ether lipid metabolism, ribosome, carbon metabolism, proteasome, endocytosis, regulation of actin cytoskeleton, lysosome, nucleocytoplasmic transport, and tight junction.

The metabolic and calcium signaling pathways have been widely reported to be related to the regulation of major events in spermatogenesis (Rato et al., 2012; Davis et al., 2016). It is commonly recognized that the maintenance of spermatogenesis in living organisms relies heavily on the metabolic collaboration between Sertoli cells and developing germ cells, however, Sertoli cells are known to be the major source of lactate and ATP in the testes, and they can provide and supply nutrients and other essential factors to facilitate successful spermatogenesis and ensure the nutritional support of germ cells (Rato et al., 2012). Additionally, numerous studies have reported that germ cells employ diverse metabolic pathways to generate energy across their distinct developmental stages (Setchell, 2004; Rato et al., 2012), and energy metabolism is recognized as a pivotal process crucial for sustaining sperm development. The calcium signaling pathway is widely recognized for its critical involvement in multiple cellular functions, such as gene regulation, apoptosis, cell differentiation, and proliferation (Abdou et al., 2013). It is integral to steroid hormone synthesis and pivotal for male fertility (Abdou et al., 2013). We noticed that several DEGs and DEPs were enriched in these pathways, suggesting the presence of active sperm and the incidence of acrosome reactions in the testes at various reproductive stages, especially at the beginning and peak of the laying cycle. Interestingly, our data showed that the epidermal growth factor (EGF) gene was upregulated in the calcium signaling pathway during the peak of the laying cycle, which is known to participate in testes growth and spermatogenesis and is expressed in somatic testicular cells such as spermatocytes, round spermatids, and spermatogonia in several animal species (Kassab et al., 2007; Li et al., 2020).

Additionally, DEGs were found to be involved in many male reproductive related signaling pathways, including the apelin signaling pathway, especially at the beginning and peak of the laying cycle. The function of this pathway and its receptor has been extensively outlined in animal reproduction (Dupont et al., 2015; Estienne et al., 2019; Shokrollahi et al., 2021). The apelin signaling pathway contributes to the regulation of spermatogenesis, testosterone production, blood-testis barrier integrity, and Leydig cell function. Furthermore, it has been reported that apelin and its receptors are expressed in testicular tissues of multiple species and could control male reproduction through the hypothalamic-pituitary-gonadal (HPG) axis (Sandal et al., 2015; Troisi et al., 2023). Current research on canines indicates that apelin is found in spermatozoa, spermatids, seminiferous tubules and Leydig cells, highlighting its crucial role in stimulating testosterone production in Leydig cells required for normal testicular development and function (Troisi et al., 2023). A study on boars showed that the apelin signaling pathway was the most enriched in seminal plasma, which suggests that the apelin generated by the testes may be one of the elements of the seminal plasma with possible function in key reproductive processes (Fraser et al., 2021). We found that the apelin receptor (APLNR) was enriched in the apelin signaling pathway, which is discovered to be distributed in Leydig cells and plays a pivotal role in male reproduction system (Dupont et al., 2015; Estienne et al., 2019; Brzoskwinia et al., 2020). Also, in the PLC (HWG vs. WWG) group, we noticed that the angiotensin II receptor type 1 (AGTR1) and the phosphoinositide 3-kinase regulatory subunit 5 (PIK3R5) genes were upregulated in the apelin signaling pathway. The AGTR1 gene play an important role in modulating sperm function and sperm-specific processes such as, sperm motility, capacitation and fertilization, acrosome reaction and sperm/oocyte interactions (Vedantam et al., 2012; Mededovic and Fraser, 2004), while the PIK3R5 gene has been reported to be linked to multiple cellular processes, including growth, motility, differentiation, survival, proliferation, and intracellular trafficking (Klempner et al., 2013), which could be involved in the sperm development and quality and the enrichment of these genes during the peak of the laying cycle highlights their implication in geese male reproduction by regulating sperm production cells activities during the key stages of the reproduction cycle. On the other hand, it is worthy to mention that the apelin signaling pathway, including its receptor, may be involved in testosterone secretion and sperm number augmentation, crucial for egg fertilization at the beginning and peak of the laying cycle, which suggests that they may have a crucial role in ganders reproduction system.

The ether lipid metabolism is crucial for sperm function, maturation, and production, as well as male fertility (Remedios et al., 2023 ). Our results indicated that this pathway was enhanced in the PLC (HWG vs. WWG) group, and we noticed that the phospholipase D1 (PLD1) and phospholipase A2 group IVA (PLA2G4) genes were upregulated in the ether lipid metabolism. PLD1 was found to be expressed in Leydig cells, spermatogonia, primary spermatocytes, spermatids in mature tubules, and Sertoli cells in murine testis during postnatal development, suggesting its involvement in mouse testis spermatogenesis, endocrine Leydig cells, and germ cell growth and biology (Kim et al., 2007). A study by Kurusu et al. (2011) demonstrated that the PLA2G4 gene was largely produced in the testicular interstitial tissues, is required for both normal testosterone synthesis and testicular development throughout the early stages of maturation, and promotes LH-stimulated testosterone synthesis, indicating its importance in testes function and development.

Similarly, our results showed that a number of other interesting signaling pathways were enhanced in the testicle tissues of both goose breeds, involving neuroactive ligand (de Lima et al., 2021) and cytokine-cytokine (Oliveira and Alves, 2015) receptor interactions and cysteine and methionine metabolism, which were strongly found to be involved in reproduction and male testicular development, which show that geese male reproduction is controlled by a variety of signaling pathways, genes, and proteins that have been extensively researched for their reproductive roles. The translocator protein (TSPO) gene was upregulated in the neuroactive ligand- receptor interaction. This gene, known as a steroidogenesis-related gene, was reported to be expressed in Leydig and Sertoli cells in adult testis (Morohaku et al., 2013) and regulates the production of testosterone in testicular Leydig cells (Papadopoulos et al., 1990). The TSPO gene was also discovered in developing spermatogonia and pachytene spermatocytes in adult rat testes (Manku et al., 2012), and Culty et al. (2015) discovered that TSPO mRNA is prevalent in mature mice spermatogonia, round spermatids, and pachytene spermatocytes, whereas the protein is present in mice sperm. Taken all together, and despite its importance in male reproduction function, the TSPO gene could also be a key gene in goose male reproduction during the beginning of the laying cycle. Moreover, we noted that the cysteine dioxygenase type 1 (CDO1) and the Betaine Homocyteine S-Methyltransferase (BHMT) genes were upregulated in the cysteine and methionine metabolisms. The CDO1 gene is deeply related to male fertility and plays a function in the maturation of post-testicular sperm (Chen et al., 2022a ), and the absence of this gene could cause sperm head morphological abnormalities in mice (Asano et al., 2018). While the BHMT gene is known to regulate the content of betaine, which can either be kept controlling cellular osmolarity or degraded to supply a methyl group for homocysteine methylation and the testicles are one of the organs that contain the highest betaine (Sararols et al., 2021).

In addition to the reproduction-related signaling pathways mentioned above, the DEPs were significantly enriched in other pathways involved in male reproduction, including the ribosome, carbon metabolism, proteasome, endocytosis, regulation of the actin cytoskeleton, lysosome, endocytosis, nucleocytoplasmic transport, and tight junction, among others. The regulation of actin cytoskeleton pathway was reported to be important in the regulation of spermatogenesis in geese (Ran et al., 2021), also, actin is known to be present in the equator, posterior parietal region, tail, and head of sperm, which highlights its important function in sperm motility, acrosome exocytosis, and the capacitation process (Breitbart and Finkelstein, 2018). Our findings identified an oxidative phosphorylation pathway, the principal pathway of ATP production, which is recurred for sperm motility, maturation, fertilization, and function (Shibata et al., 2023), and the oxidative phosphorylation is known to occur in the sperm midpiece (du Plessis et al., 2015). This pathway was enriched in all the comparison groups, which suggested its importance in goose gander fertility and sperm production, especially at critical stages of the laying cycle, which are characterized by the incensement of sperm numbers.

Interestingly, our proteomic data results showed that DEPs were also enriched in Endocytosis, which is crucial in testis development by supporting various processes necessary for spermatogenesis and hormonal regulation, including the internalization and trafficking of hormone receptors such as FSHR and LHR (Hammes et al., 2005 ), which are essential for controlling spermatogenesis and testosterone synthesis, permits testicular cells to absorb nutrients and growth factors required for growth and function (Wu et al., 2023), which aids in the proliferation and differentiation of germ cells and Sertoli cells and contributes in the release of spermatids from Sertoli cells into the seminiferous tubules during spermatogenesis (Upadhyay et al., 2014).

Furthermore, the PPI analysis of DEPs in this research indicated that genes such as CHD1L, RAB18, FANCM, TAF5, TSC1/2, PHLDB2, DNAJA2, NCOA5, DEPTOR, TJP1, and RAPGEF2, which participate in cell activities and functions related to male reproduction regulation, may be the main factors controlling testicular function in geese. In this study, a weak correlation between transcriptome and proteome was observed among the 3 comparison groups. Similarly, Yang et al. (2023) found that there was a weak correlation between genes and proteins in normal and atretic follicles from geese (R2 = 0.107), also a study on wild-type and fads2-deletion zebrafish showed a low quantitative correlation between the transcripts and proteins (Zhao et al., 2020). In general, the modest association observed between transcriptomic and proteomic results could be attributed to intricate regulations at the post-transcriptional level. However, the testis is commonly viewed as an organ where the transcriptome and proteome may not always be directly correlated, and interestingly, this low correlation between mRNA and protein levels in the testis was clearly demonstrated in a tissue-profiling study employing multidimensional protein identification technology (MudPIT) on different human organs, in which the results showed that the correlation between genes and proteins in the testis was lowest compared with the liver (Cagney et al., 2005).

In conclusion, our integrative omics analysis provides comprehensive insights into the changes in the transcriptomic and proteomic profiles of the Wanxi and Hungarian white geese testicles across 3 distinct stages of their reproductive cycle.

CONCLUSIONS

In conclusion, an integrative transcriptomic and proteomic analysis approach was used in this study to further investigate the mechanisms of the seasonal cyclicity of testis in geese. Our findings revealed that several genes, proteins, and multiple signaling pathways related to male reproduction were identified in the testicles of 2 kinds of goose breeds at 3 stages of the laying cycle, which could be considered as potential candidates for regulating the testes and the process of spermatogenesis. The present research delineated comprehensive transcriptomic and proteomic changes in geese testicles during the breeding seasons and provided a new theoretical basis to understand reproductive biology and ameliorate reproductive performance in both Wanxi and Hungarian white geese ganders.

DISCLOSURES

Yongfeng Sun reports financial support was provided by Jilin Provincial Science and Technology Department, Jilin Animal Husbandry Administration and Jilin Provincial Department of Human Resources and Social Security.

ACKNOWLEDGMENTS

This work was supported by the 10.13039/100007847 Natural Science Foundation of Jilin Province (No. 20240101224JC ), the Jilin Provincial Innovation and Entrepreneurship Talent Funding Program (No. 2022ZY16 ), the 10.13039/501100019491 National Natural Science Foundation of China (No. 3237200703 ), the Development and Utilization Project of Livestock and Poultry Genetic Resources and Scientific and Technological Enhancement of Animal Husbandry Quality and Efficiency in Jilin Province (No. 202408 ), and the Key Research and Development Projects of the Jilin Provincial Department of Science and Technology (No. 20230202064NC ). The authors express their acknowledgment to the Jilin Agricultural University Goose Industry R&D Center Joint Breeding Base for providing the experimental Hungarian and Wanxi white geese.

Data Availability: The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive (Chen et al., 2021) in National Genomics Data Center (Sayers et al., 2022), China National Center for Bioinformation / Beijing Institute of Genomics, Chinese Academy of Sciences (GSA: CRA015710), and are publicly accessible at https://ngdc.cncb.ac.cn/gsa. For the mass spectrometry proteomics, the data were deposited to the Proteome Xchange Consortium (http://proteomecentral.proteomexchange.org) via the iProX partner repository (Ma et al., 2019; Chen et al., 2022b) with identifiers PXD051168 and PXD051163 for the Wanxi white goose and the Hungarian white goose, respectively.
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