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. 2025 Apr 4;104(6):105127. doi: 10.1016/j.psj.2025.105127

Genome-wide association study and candidate gene analysis of reproductive traits in Yili geese

Xiaoyu Zhao 1, Zhiyong Mei 1, Haiying Li 1,⁎, Yingping Wu 1, Lu Pan 1, Yan Cao 1
PMCID: PMC12005294  PMID: 40203614

Abstract

Reproductive traits are important economic traits in goose production, and geese's reproductive ability directly affects goose farms' economic benefits. In this study, we selected 240 Yili females goose in the egg-laying stage to construct a test population and measured the individual egg-laying performance and hatching performance of Yili females goose. Based on the above phenotypic data, we conducted genome-wide linkage analysis for five indicators of reproductive traits of Yili geese (egg-laying capacity, fertilization rate, hatching rate, egg weight, and egg shape) to screen candidate genes. Genome-wide association analysis of reproductive traits in Yili geese was performed by resequencing, and a total of 1 single nucleotide polymorphism (SNP) were screened for significant association with hatchability, 34 SNPs were screened for potential association with egg production, egg weight, egg shape, and fertilisation rate, and 35 candidate genes were screened for association with egg production, egg weight, egg shape and fertilization rate in the vicinity of these loci across the whole genome. 35 candidate genes were screened near these loci. Through bioinformatics analysis, genes such as carbonic anhydrase 2 (CA2), very low density lipoprotein receptor (VLDLR), HMG-box transcription factor 1 (HBP1), and transient receptor potential cation channel subfamily M member 5 (TRPM5) were obtained to be closely related to calcium deposition, follicular development, embryonic development, and estrogen secretion level. These genes can be used as candidate genes affecting the reproductive performance of Yili geese. This study provides a reference basis for further analysis of the molecular regulation mechanism of goose reproductive performance and enriches the theory of genetic regulation of goose reproductive performance.

Keywords: Yili geese, Egg production, Hatchability, GWAS

Introduction

China is recognized as the leading nation globally in both the farming and consumption of geese (Wang et al., 2020). The meat and eggs derived from waterfowl are esteemed for their high nutritional quality and distinctive flavor, which is widely regarded as palatable. Additionally, waterfowl serve as a significant source of down and feathers. The Yili geese is a high-quality local characteristic species poultry in Xinjiang, China, are mainly characterized by strong adaptability, heat resistance, cold resistance, rough feeding resistance, and a certain flying ability. However, the low reproductive performance of Yili geese has greatly constrained its industrial development. Consequently, investigating the reproductive traits that directly influence the economic efficiency of the goose industry holds substantial practical importance. Studies have shown that reproductive traits such as egg production and hatchability in poultry are closely related to several genetic factors (Emamgholi et al., 2019; Xu et al., 2022; Zhou et al., 2024). Genetic studies of reproductive traits in poultry can improve the reproductive efficiency of poultry and thus enhance economic efficiency. Genetic progress using traditional breeding methods has been slow due to the low heritability of reproductive traits and the complexity of the inheritance mechanisms(Wang et al., 2022). With the development of molecular biotechnology, molecular breeding provides a new research strategy for animal breeding. The application of identified important functional genes related to reproductive traits, such as estrogen receptor genes (Sell-Kubiak et al., 2022) and follicle stimulating hormone genes (Yang et al., 2023), to breeding can effectively improve the genetic progress of reproductive traits. However, reproductive traits are under microefficient polygenic control, and the few identified candidate genes reveal only a fraction of the genetic variation (Ma et al., 2022). Therefore, further identification of genetic variants and candidate genes affecting reproductive traits in geese will help to unravel the genetic mechanism of reproductive performance in geese.

In recent years, the Genome-wide Association Study (GWAS) has become an important method to identify candidate genes for economically important traits in livestock and poultry. In the study of reproductive traits in poultry, genomic association studies are a powerful tool to help identify genetic variants and genes associated with reproductive traits. Gao et al. (2021) screened four genes, including transmembrane protein 161A (TMEM161A), a candidate gene for egg number in geese at 48 weeks of age and 60 weeks of age, as well as calcitonin receptor (CALCR) and tissue factor pathway inhibitor 2 (TFPI2), which were significantly associated with goose egg yolk color, by GWAS analysis. Liu et al. (2018) investigated a gene-wide association analysis of egg quality in late-laying hens at 72 and 80 weeks of age using a 600 K high-density SNP array and found that a genomic region of ∼0.36 Mb on GGA13 was strongly associated with albumin height and albumin units, and screened three candidate genes, ras homolog family member A (RHOA), associated with eggshell color, stromal cell derived factor 4 (SDF4) and TNF receptor superfamily member 4 (TNFRSF4). However, there are few GWAS studies on reproductive traits in Yili geese. Therefore, to further explore the genetic potential of reproductive traits in Yili geese, 240 Yili females goose in the egg-laying stage were selected to build a test population, and the individual egg-laying and hatching performances of the Yili females goose were measured, and the genome-wide linkage analysis (GWAS) was carried out on the five indexes (egg-laying capacity, fertilization rate, hatchability, egg weight, and egg shape) based on the above phenotypic data to identify SNPs and functional genes related to reproductive traits in geese. Based on the above phenotypic data, genome-wide association analyses were conducted for five indicators of reproductive traits (egg production, fertilization rate, hatching rate, egg weight, and egg shape) in Yili geese, to identify SNPs and functional genes related to reproductive traits.

Materials and methods

Ethics statement

All experimental procedures involving animals were approved (animal protocol number: 2019004) by the Animal Welfare and Ethics Committee of Xinjiang Agricultural University, Urumqi, Xinjiang, China.

Experimental animals

In this experiment, 240 3-year-old Yili geese in good health, with consistent feeding level and in the egg-laying period were selected as research subjects, and the male to female ratio was 1:5; the experiment lasted for 80 days. The experimental animals were kept in captivity on flat land, and the goose house was equipped with troughs, laying nests with soft wheatgrass as bedding, and exercise yards and pools in the goose house. During the experimental period, geese were fed a full-price ration during the egg-laying period, fed and watered ad libitum, and underwent normal immunisation procedures.

Egg production traits

An automatic video collection system was installed in the goose house, and the egg-laying situation of the geese in the goose house could be observed through the monitoring probes. To facilitate observation and recording, different colors of paint were sprayed on the necks and heads of the geese, and different colors of neck and foot numbers were worn to mark them, and the eggs were picked up twice a day (10:00 am and 4:00 pm). The video was extracted and played back every day from the second day of the experiment to record the egg production of the geese throughout the year.

Incubation traits

Seed eggs were collected daily and incubated uniformly every week. A total of 8 incubations were carried out during the experimental period. Light fluoroscopy was carried out on days 7 and 14 after hatching to pick out non-fertilized and dead embryos. The fertilization rate and hatching rate of fertilized eggs were calculated from the incubation records. The formulae for calculating fertilization and hatchability rates are as follows:

Fertilizationrate(%)=(no.offertilizedeggs/totalno.ofeggs)×100
Hatchabilityrate(%)=(no.ofeggshatched/totalno.offertilizedeggs)×100

Genomic DNA extraction

Whole blood samples were collected from 200 female geese on the day of the end of the laying period, and blood DNA was extracted by the kit method. The degree of DNA degradation was analyzed by 0.8 % agarose gel electrophoresis, and the DNA concentration was accurately quantified by using Qubit 3.0, and the total amount of DNA samples with a total amount of more than 1.5 μg was selected for the construction of libraries.

Quality control and comparison of genomic data

Raw data were obtained by IlluminaHiSeqTM sequencing (Illumina Inc., San Diego, CA, USA), and the Plink 1.07 software package was applied for quality control: individuals with >10 % SNP genotypic deletions were excluded; loci with SNP detection rate (Call rate) <90 %; SNP loci with minor allele frequency (MAF) <3 %; and SNP loci with extreme failure to meet the Hardy-Weinberg equilibrium (HWE) test (P < 10-6). The QC-qualified sequencing data were compared with the goose reference genome ASM1303099v1 (Li et al., 2020), and the comparison results were subjected to SAMTOOLS (version 1.9, https://github.com/samtools/samtools) to remove duplicates.

Genome-wide association analysis

In this study, GEMMA software (version 0.96, https://github.com/genetics-statistics/GEMMA/releases) was used to construct a mixed linear model (MLM) for GWAS analysis with the following model:

y=Xα+Zβ+Wμ+ε,

where y is the phenotypic trait, X is the indicator matrix for the fixed effect, α is the estimated parameter for the fixed effect, Z is the indicator matrix for the SNP, β is the effect of the SNP, W is the indicator matrix for the random effect, μ is the predicted random individual, and ε is the random residual.

Multiple hypothesis testing

The results of the correlation analyses were corrected using the multiple hypothesis testing LD correction method, with 650397 loci remaining after LD filtering. The corrected thresholds were 7.11 (0.05/650397) for significant correlation, 5.81 (1/650397) for potential correlation, and the Manhattan plot threshold line was set to 6, indicating potentially correlated loci.

Results

Trait phenotype statistics

Descriptive statistical analyses of reproductive traits of Yili females goose were carried out in this experiment (Table 1). Among 196 individual Yili females goose, the highest number of eggs laid by individual Yili females goose was 27, and the lowest was one. The average number of eggs laid was 11.48, the average egg weight was 128.57 g, the average egg shape index was 1.33, and the average hatching rate of fertilized eggs was 70.73 %.

Table 1.

Descriptive statistical analysis of reproductive traits of Yili geese.

Indicators Max Min Mean SD
Egg production (pieces) 27.00 1.00 11.48 5.42
Egg weight (g) 177.80 98.00 128.57 19.34
Egg-shaped index 1.76 1.13 1.33 0.12
Fertilization rate (%) 100.00 25.00 60.18 16.42
Fertilized egg hatchability (%) 100.00 25.00 70.73 13.85
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Sequencing data quality control and SNP detection

The average GC content of the samples was 44.03 %, the average Q20 was 96.77 %, and the average Q30 was 92.30 %. The average comparison efficiency between the sample genomic DNA and the reference genomic DNA was 97.00 % (Table S1-1), indicating that the similarity between the sample and the reference genome meets the requirements for resequencing analysis. 16411466 SNPs were detected in this study, of which the conversion (Ti), subversion (Tv) ratio was 2.3 and the heterozygosity rate was 21.4 % (Table S1-2).

Principal component analysis (PCA)

In order to avoid false positives due to individual relatedness as well as population stratification, which can affect the accuracy of the test results. In this study, principal component analysis (PCA) was used and group stratification analysis was performed. As shown in Fig. 1, there were no subgroups in the test population, indicating that the test could be subjected to subsequent correlation analyses.

Fig. 1.

Fig. 1

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Principal component analysis.

Linkage disequilibrium (LD) analysis

The level of LD can determine the precision of association analysis and the number of selected markers; the slower the decay of LD, the fewer the number of markers required for GWAS analysis and the lower the localization precision; on the contrary, the faster the decay of LD, the higher the density of markers required for GWAS analysis, and the closer the distance of the significance loci associated with phenotypic variations of the target traits to the functional loci, i.e., the higher the precision of localization. As can be seen in Fig. 2, r2 gradually decreased with the increase of genetic distance between markers, indicating the existence of a strong linkage disequilibrium relationship in the marker check.

Fig. 2.

Fig. 2

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Linkage disequilibrium analysis. The abscissa represents the size of genetic distance and the ordinate represents the correlation coefficient.

Genome-wide association analysis

From Fig. 3 and Table S2, one SNP (rs11731958) was significantly associated with hatching rate; 34 SNPs were potentially associated with egg production, egg weight, egg shape and fertilisation rate. Genes were annotated within 200 kb upstream and downstream of the significantly associated SNPs for each trait, and a total of 17,569 genes were annotated, of which a total of 35 genes were associated with reproductive traits in Yili geese (Table S3). Genes were annotated within 200 kb upstream and downstream of the significantly associated SNPs for each trait, and a total of 17,569 genes were annotated, of which a total of 35 genes were associated with breeding traits in Yili geese (Table S3). The genes protein phosphatase 2C family protein (POL), RNA polymerase III subunit H (RPC22), CA2, leucine rich repeat neuronal 1 (LRRN1), and RNA-binding protein Musashi homolog 2 (MSI2H) have been identified as being associated with the egg production of Yili geese. Additionally, eight genes, including Glutamyl-tRNA amidotransferase, subunit A (GATA), VLDLR, aryl hydrocarbon receptor (AHR), are linked to the egg weight of Yili geese. Furthermore, thirteen genes, such as HMG-box transcription factor 1 (HBP1), Kinesin associated protein 3 (KAP3) and calcyphosine 2 (CAPS2), are correlated with the egg shape index of Yili geese. Six genes, including TRPM5, cordon-bleu WH2 repeat protein (COBL), and myeloid leukemia factor 1 (MLF1), are related to the fertilization rate of Yili geese. Lastly, the genes P2R3B, RNA binding motif protein 41 (RBM41), and KAISO are associated with the hatching rate of Yili geese.

Fig. 3.

Fig. 3

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The Manhattan and Q-Q plots for five traits. In the Manhattan plot, the horizontal coordinates are the chromosomes corresponding to the loci of SNPs, and the vertical coordinates are the thresholds corrected for multiple hypothesis testing. In Quantile-quantileplot, the blue line indicates the actual p-value and the red line indicates the threshold under the null expectation null hypothesis condition.

Discussion

The initial sample size of this experiment was 240 Yili geese, and to ensure the truthfulness and accuracy of the data, we eliminated the individuals who did not lay eggs during the laying period. To reduce human error, egg weight and egg shape, index were measured by the same person, and egg production was monitored from the start of the laying period using a monitoring system to accurately correlate the number of eggs laid with the geese, thus guaranteeing the authenticity and reliability of the data. After extracting genomic DNA, integrity, purity, and concentration tests, the final number of test samples was 196. The genome-wide association analyses of egg production, egg weight, egg shape, fertilization rate, and hatching rate of Yili geese were selected, which are not only closely related to the breed characteristics of Yili geese but also help to obtain genome-wide candidate genes related to the reproductive performance of Yili geese. In this study, genome-wide association analysis of egg weight, egg shape, egg production, fertilization rate, and hatching rate in Yili geese was performed by resequencing technology, and 35 SNPs associated with the above five reproductive traits were identified, among which one SNP was significantly associated with hatching rate, and 34 SNPs were potentially associated with egg production, egg weight, egg shape, and fertilization rate. A total of 35 genes related to reproductive traits were identified in the 200 kb region upstream and downstream of these relevant loci. Finally, through bioinformatics analysis and literature search, it was hypothesized that KAISO, CA2, TRPM5, and VLDLR might be candidate genes affecting the reproductive traits of the Yili geese.

Carbonic Anhydrase 2 (CA2), the protein encoded by this gene is one of several isoenzymes of carbonic anhydrase. Nishita et al. (2011) collected blood from White Laiwai chickens of different ages and found that there was no significant change in CA-II content in hens from 1 to 16 weeks of age and that the content of CA-II in hens continued to increase from 17 weeks of age to 63 weeks of age, and then decreased from 63 weeks to 92 weeks of age, and then increased again after 93 weeks of age. From 17 weeks of age to 63 weeks of age, the content of CA-II in hens showed a continuous increase and then decreased significantly from 63 weeks of age to 92 weeks of age, and then increased significantly after 93 weeks of age. In addition, the experiment also studied the change of the content in roosters, and it was found that there was no significant change of CA-II in roosters, and the study finally found that there was a significant correlation between the content of CA-II in hens and the rate of laying eggs. Nishita et al. (2011) found that the trend of CA-II and CA-II content in laying ducks was similar to that of hens, which suggests that there is a close relationship between CA-II and CA-II and the egg-laying performance of poultry. Gao et al. (2021) found that the carbonic anhydrase II (CA2) gene was one of the transcription products differentially expressed in the isthmus epithelium of duck eggs during the egg formation stage by cDNA microarray study. In addition, a single nucleotide polymorphism in the CA2 gene of the Shiba duck was found, and the relationship between SNP genotypes and egg-laying traits in ducks was explored, and significant correlations were found between different genotypes of the CA2 gene and egg weight and egg production (Chang et al., 2013). In this study, we found a potential correlation between the SNP (rs20194456) corresponding to the CA2 gene and egg production. Calcium is an indispensable element in the formation of avian eggs, and calcium deficiency may lead to the formation of soft-shelled and malformed eggs, and the results of a related study showed that osteoblasts are able to regulate calcium deposition by altering the expression of carbonic anhydrase (Gao et al., 2011), so we speculate that the CA2 gene may be related to eggshell formation during embryonic development of Yili geese.

VLDLR plays an important role in the oogenesis and development of poultry eggs. During reproduction in poultry, VLDLR is closely associated with the synthesis and transport of yolk precursor material, which is essential for proper egg development (Du et al., 2022). VLDLR shows different expression patterns in different physiological stages and cell types, which may be related to follicle development and egg maturation (Shen et al., 2020). In this study, the corresponding SNP (rs2968526) of the VLDLR gene was potentially correlated with egg weight. The results of previous studies have shown that the VLDLR gene is associated with follicle development and yolk formation (Chen et al., 2020; Cui et al., 2020), which led to the speculation that the VLDLR gene may affect the egg weight of the Yili geese in the present study by regulating the development of the oocyte as well as yolk formation. It was hypothesized that the VLDLR gene in this study might affect the egg weight of Yili geese by regulating the development of the oocyte and the formation of the yolk.

Members of the GATA transcription factor family play important roles in animal reproductive development and function. GATA transcription factors play an important role in proliferation, differentiation and apoptosis of ovarian cells (Laitinen et al., 2000; Gillio-Meina et al., 2003). For example, studies on the molecular characterisation and expression patterns of GATA-4 and GATA-6 in goose follicle development have shown that these transcription factors have important functions during follicle development (Yuan et al., 2014). Furthermore, in the buffalo ovary, GATA-4 is involved in the regulation of the CYP19 gene, which plays a role in folliculogenesis and luteinisation (Monga et al., 2012). The results of this study showed that the GATA gene was detected on chromosome 1, and the SNP corresponding to this gene (rs39448208) was significantly correlated with egg weight, suggesting that the GATA gene may affect the reproductive performance of Yili geese by regulating the proliferation, differentiation and apoptosis of ovarian cells.

HMG box protein 1 (HBP1) is a ubiquitous transcription factor that belongs to the high mobility (HMG) family of DNA-binding proteins (Stros et al., 2007).The HBP1 gene plays an important role in cell proliferation, differentiation, and senescence (He et al., 2018). Arraztoa et al. (2005) reported the expression of the HBP1 gene in primate primordial oocytes. Reduction of HBP1 may induce the release of primordial follicles from cell cycle arrest and entry into the growth phase to become primary follicles (Yang and Fortune, 2015). In addition, HBP1 inhibits WNT/FZD1 signaling and prevents cell proliferation (Sampson et al., 2001). WNT ligands and frizzled G protein-coupled receptors regulate cell fate, including embryonic development of the mouse ovary (Hsieh et al., 2002).WNT signalling promotes skeletal growth and development by regulating the balance between bone formation and bone resorption (Amjadi-Moheb and Akhavan-Niaki, 2019). In poultry, body size egg shape, and egg weight generally have a positive correlation. In this study, we found that chr3:13386334 SNPs significantly correlated with egg shape index were localized in HBP1, which is hypothesized to influence egg shape formation by acting on the WNT signaling pathway.

The transient receptor potential 5 (TRPM5) channel is an important Ca2+ permeable non-selective cation channel in the human body, which is normally expressed on normal cell cytosolic and lysosomal membranes and plays an important ionic regulatory role in oxidative stress.The channel is thought to be involved in the control of membrane potential.TRPM5 can promote cell proliferation, invasion and metastasis by activating the signalling pathways of a wide variety of different molecules capacity (Wu et al., 2020). TRPM5 is also involved in regulating the physiological functions of the female reproductive system. It has been found that TRPM5 also plays an important role in regulating thermal sensitivity and physiological functions of the female reproductive system. Fluctuations in estrogen and progesterone during the menstrual cycle affect the function of TRPM5 channels, which in turn affects physiological functions in women (Uchida and Izumizaki, 2021). In the results of this study, the SNP corresponding to the TRPM5 gene (rs25871979) was potentially correlated with the fertilisation rate, and it was hypothesised that the TRPM5 gene may regulate the hatching rate of Yili geese by regulating membrane potential channels associated with oestrogen secretion.

KAISO binds to the signalling molecule p120-catenin and binds to the methylated sequence MCGMCG or the unmethylated sequence CTGCNA to regulate transcription (Daniel et al., 2002). In studies on the African Xenopus laevis, KAISO deficiency leads to embryonic death and is accompanied by premature activation of genes in the blastocyst and upregulation of the Wnt11 gene (Daniel et al., 2002). In Xenopus laevis, loss of KAISO protein function results in the premature expression of syncytial genes prior to the mid-cycle transition, and Xenopus laevis embryos that are deficient in KAISO function exhibit apoptosis in some cells (Ruzov et al., 2004). Studies in related zebrafish have also shown that KAISO is a methylation-dependent transcriptional repressor and is essential for zebrafish embryonic development, and that loss of KAISO protein function in zebrafish embryos is manifested by high mortality rates up to 48 hr of embryonic development, with the vast majority of surviving embryos exhibiting developmental delays, and axial and head deletions after introduction of KAISO (Ruzov et al., 2009). KAISO plays an important role in mammalian synapse-specific transcription, and studies have evaluated its role in mammalian development and reproduction by knocking out the KAISO gene in mice, showing that deletion of the KAISO gene results in the inability of mice to reproduce (Prokhortchouk et al., 2006). The results of this study showed that the KAISO gene was detected on chromosome 22, and the SNP corresponding to this gene (rs11731958) had a significant correlation with hatching rate, and it was hypothesised that the KAISO gene might affect the reproductive performance of Yili geese by regulating the transcription and synthesis of the relevant proteins during the embryonic development period.

Conclusions

In this study, genome-wide association analysis was performed for reproductive traits in Yili geese, and a total of 1 SNPs were screened genome-wide for significant association with hatchability, and 34 SNPs were screened for potential association with egg production, egg weight, egg shape and fertilisation rate. A total of 35 candidate genes were screened near these loci, among which CA2, VLDLR, HBP1 and TRPM5 are closely related to calcium deposition, follicular development, embryonic development and estrogen secretion level, which can be used as candidate genes affecting the reproductive performance of Yili geese. The present study may provide important genetic references for the subsequent investigation of the genetic mechanism of reproduction traits in Yili geese and the search for reproduction-related molecular markers and candidate genes in Yili geese.

Declaration of competing interest

All authors declare that they have no competing interests.

Acknowledgments

This research was funded by the Xinjiang Uygur Autonomous Region Modern Livestock and Poultry Breeding Industry Promotion Project (2025xjjq-z-04), and the Xinjiang Uygur Autonomous Region Modern Agricultural Industrial Technology System (XJARS-12-01, XJARS-12-10).

Footnotes

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.psj.2025.105127.

Appendix. Supplementary materials

mmc1.xlsx (10.9KB, xlsx)
mmc2.xlsx (11.7KB, xlsx)
mmc3.xlsx (12.4KB, xlsx)

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Supplementary Materials

mmc1.xlsx (10.9KB, xlsx)
mmc2.xlsx (11.7KB, xlsx)
mmc3.xlsx (12.4KB, xlsx)

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