High serum reproductive hormone levels at mid-pregnancy support Meishan pig prolificacy

ZHOU Rong, YANG Ya-lan, LlU Ying, CHEN Jie, YANG Bing, TANG Zhong-lin

1 MOE Laboratory of Biosystem Homeostasis and Protection, Life Sciences Institute, Zhejiang University, Hangzhou 310058,P.R.China

2 State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, P.R.China

3 Kunpeng Institute of Modern Agriculture at Foshan, Institute of Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences Foshan 528226, P.R.China

4 Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Shenzhen 518000, P.R.China

5 Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, P.R.China

Abstract Increasing prolificacy is an important aim in the pig industry.Regions associated with litter size have been revealed, but detailed molecular mechanisms are unclear.The Meishan pig is one of the most prolific breeds, with higher prolificacy than the Yorkshire pig, which exhibits high feeding efficiency and lean meat yield.The ovary is the key organ determining reproductive traits during pregnancy by synthesizing and secreting reproductive hormones essential for conceptus maintenance.In this comparative multi-omics study of the ovary transcriptome, proteome, and metabolome on day 49 of pregnancy, we aimed to identify genomic, proteomic, and metabolomic differences between the ovaries of Meishan and Yorkshire pigs to reveal potential molecular mechanisms conferring high prolifciacy.Meishan pigs demonstrated general downregulation of steroid biosynthesis and butanoate metabolism in the ovary during mid-pregnancy at both transcriptome and proteome levels but exhibited higher serum cholesterol, estradiol, and progesterone levels than Yorkshire pigs.We also identified several single-nucleotide polymorphisms in the genes of the steroid hormone pathway associated with litter number, average birth weight, and total litter weight.Lower biosynthesis rates but elevated serum levels of reproductive hormones during mid- and late pregnancy are essential for the greater prolificacy of Meishan pigs.

Keywords: ovary, progesterone, Meishan, steroid biosynthesis, multi-omics

1.lntroduction

Prolificacy is a key trait in the pig industry as it is directly related to production efficiency.Pig litter size is determined by multiple factors including ovulation rate, embryonic survival, uterine capacity, and fetal survival (Spotter and Distl 2006).These processes are regulated by genetic and environmental factors and vary substantially between pig breeds and even individuals within a breed.An important strategy to detect genes influencing litter size is linkage analysis of genomic regions associated with reproduction traits (Nogueraet al.2009; Hernandezet al.2014).Such studies have identified significant prolificacy qualitative trail loci (QTLs)in pig chromosomes 13 and 17, but there is still little understanding of the underlying molecular mechanisms influencing reproductive capacity among individuals and breeds.Pig prolificacy is regulated by multiple epistatic interactions, so an integrative (“multi-omics”) approach is required for understanding regulation of litter size in pigs.

Fetal survival rate is a key factor determining litter size,especially after day 30 of gestation.During pregnancy,ovaries synthesize and secrete reproductive hormones are essential for conceptus maintenance.Comparison of the ovarian transcriptome between high and low prolificacy individuals (Fernandez-Rodriguezet al.2011; Zhanget al.2015) has revealed lipid metabolism as a key pathway regulating litter size.Such studies have also demonstrated that steroid hormones differentially regulate litter size across stages of pregnancy, although it is still unknown how these variations control the rate of fetal loss.

In addition to individual variation, there is also marked variation in litter size among domestic breeds.The Chinese Meishan pig is one of the most prolific breeds in the world.We previously identified structural variants (SVs) clustered in a 30 Mb hotspot on chromosome X that is unique to Asian domestic breeds, which is not present in European domestic pigs, indicating the genomic basis of distinct phenotypic differences between Asian and European breeds(Zhouet al.2021; Liuet al.2022).Genetic linkage analysis comparing Meishan and Yorkshire pigs has revealed several candidate markers and important contributions of maternal traits to the larger litter size in Meishan pigs (Haleyet al.1995; Hernandezet al.2014), suggesting that the high prolificacy of this breed is conferred by specific attributes of the female reproductive organs.

To investigate the molecular mechanisms for high prolificacy in Meishan pigs, we compared the ovarian transcriptome, proteome, and metabolome between Meishan and Yorkshire pigs at mid-pregnancy (day 49).We also analyzed the associations between singlenucleotide polymorphisms (SNPs) in reproductive genes and reproductive traits (litter size, birth weight, and total litter weight) of Meishan pigs.

2.Materials and methods

2.1.Animals and tissue collection

Ovary tissue and serum samples for transcriptomic,proteomic, and metabolomic analysis of Meishan and Yorkshire pigs at mid-pregnancy were obtained from our previous study (Wanget al.2019).We collected entire ovary as samples from six pigs (three each of Yorkshire and Meishan pigs) at 49 days.

2.2.Radioimmunossay (RlA)

The serum of Meishan and Yorkshire pig in day 49 of gestation were collected for steroid hormones determinations.Experiments were performed three times.Steroid hormones were analyzed using RIA reagents by the Beijing North Institute Biological Technology (Beijing,China).For each RIA, the intra- and interassay coefficients of variation were less than 15 and 10%, respectively.

2.3.Real-time quantitative PCR (RT-qPCR)

The tissues were homogenized in 500 μL of RNAiso Plus (TaKaRa, Japan) according to the manufacturer’s instructions, purified by DNaseI, and quantified by spectrophotometry.cDNA for qPCR analysis was synthesized using the PrimeScript RT Reagent Kit with gDNA Eraser (Perfect Real Time) (TaKaRa, Japan).Prior to qPCR amplification, cDNA was diluted to 300 ng μL–1.The reaction mixture for the qPCR step was TB Green Premix Ex Taq II (Tli RNaseH Plus) (TaKaRa, Japan).RTqPCR was performed using TB Green Premix Ex Taq in an QuantStudio 3 (Thermo Fisher Scientific, USA).

2.4.RNA sequencing (RNA-seq)

The transcriptome data, which were generated from the ovary tissues of Meishan and Yorkshire pigs at midpregnancy (day 49), were obtained from our previous study (Wanget al.2019).RNA-seq reads were aligned to the pig reference genome Sscrofa11.1 using HISAT2(v2.0.5) (Kimet al.2015) with default parameters.Genelevel read counts were calculated using HTSeq (v0.6.1p1)(Anderset al.2015).

2.5.Quantitative proteomics analysis

For trypsin digestion and Isobaric tags for relative and absolute quantitation (iTRAQ) labeling, 200 μg protein from each sample was reduced with 50 mmol L–1DTT(Thermo Scientific, USA) at 56°C for 1 h, alkylated by 5 mmol L–1iodoacetamide (Sigma-Aldrich, Germany) for 45 min at room temperature in the dark, and then digested with 4 μg trypsin (Promega, USA) at 37°C overnight.The digested samples were labeled with iTRAQ reagent (6-plex; AB SCIEX, USA) according to the manufacturer’s instructions.Proteomic data were acquired using Thermo Obitrap QE Mass Spectrometry (Thermo, USA).

Protein identification and quantitation were performed using MaxQuant (Cox and Mann 2008).Differentially expressed proteins were identified using a cuff-off adjustedP-value<0.05 and fold change>1.5.

2.6.Differential expression analysis and pathway enrichment

Differential expression analysis was performed using the DESeq2 Package (v1.18.1) (Loveet al.2014) for R version 3.The resultingP-values were adjusted using the Benjamini and Hochberg’s approach for controlling the false discovery rate.Genes with an adjustedP-value<0.05 by DESeq2 were defined as differentially expressed.Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis of differentially expressed genes was implemented by the clusterProfiler R package (v3.6.0) (Yuet al.2012).KEGG terms with correctedP-value<0.1 were considered significantly enriched in differentially expressed genes.

2.7.Metabolomics data analysis

Metabolomics instrumental analysis was performed on an Agilent 7890A gas chromatography (GC) system coupled to an Agilent 5975C Inert MSD System (Agilent, Canada).The peak selection, alignment, deconvolution, and further processing of raw GC-MS data were referred to the previous published protocols (Gaoet al.2010).The data was normalized against total peak intensities before performing univariate and multivariate statistics.The differentially expressed metabolites were determined by a variable importance in the projection value >1 of OPLSDA model andP<0.05 from two-tailed Student’st-test on normalized peak intensities.Fold change was calculated as the binary logarithm of the average normalized peak intensity ratio between breeds.

2.8.Selection pressure, genotyping, and association analysis

The Fst and π values were calculated for each 50-kb region in 25-kb steps across the whole genome using SNP data of 14 Yorkshire and 10 Meishan pigs (Groenenet al.2012; Frantzet al.2015).Association analyses were conducted using 375 Lansi white pigs (n=375).The total number born, total litter weight, and average birth weight were recorded during consecutive years from 2005 to 2010.Genomic DNA was extracted from ear tissue samples using a Tissue & Cell Genomic DNA Purification Kit (Tiangen, China) according to the manufacturer’s instructions.Genotyping was performed using Matrix-assisted laser desorption/ionization time of flight mass spectrometry by MALDI-TOF MS, Sequenom MassARRAY (Beijing Compass Biotechnology Co.,Ltd., China).Association analysis between SNPs and reproductive traits was conducted using the general linear model procedure in SAS Software version 9.2 according to previously published methods (Liuet al.2009).

3.Results

3.1.Comparative transcriptome profiling of ovaries in Meishan and Yorkshire pigs

We collected ovary samples from Meishan and Yorkshire pigs on day 49 of gestation, which is within the third period of fetal loss in pigs, and compared transcriptome profiles by RNA-seq (with three biological repeats for each breed).Five of the six transcriptomes obtained fell into two distinct clusters, with all three Yorkshire samples in one cluster and two Meishan samples in the other (Fig.1-A and B), while the third Meishan sample did not fall into either cluster and was not used in further analysis.Among the whole ovary transcriptome, 1 708 genes were differentially expressed between breeds, with 857 significantly more abundant and 851 significantly less abundant in Meishan pig ovary (adjustedP-value<0.05)(Fig.1-C).A subset of the differentially expressed genes was validated by qRT-PCR, and results were consistent with transcriptome profiling results, highlighting the accuracy of our transcriptome data (Fig.1-F).

GO terms and KEGG pathway enrichment analysis were then performed for genes upregulated and downregulated in the ovaries of Meishan pig’s downregulation of steroid metabolism, steroid transport, and cholesterol transport.In addition, KEGG signaling pathways related to “protein translation”, “steroid”, “butanoate”, and “ketone bodies”were also significantly downregulated in Meishan pig ovaries, while no KEGG pathway was enriched for genes upregulated in Meishan pig ovaries (Fig.1-D).Further,multiple metabolic processes related to “l(fā)ipid”, “thioester”,and “acyl-CoA” was downregulated in Meishan pig ovaries(Fig.1-E).These functional enrichment results suggest reduced metabolic rate in Meishan pig ovaries compared to Yorkshire pigs at gestation day 49.

3.2.Quantitative proteomic analysis confirmed downregulation of steroid and butanoate metabolism pathways in Meishan pig ovaries

Fig.1 Comparison of ovarian transcriptome between Meishan and Yorkshire pig breeds on day 49 of pregnancy.A, Heatmap of Spearman correlation coefficients between transcriptomes from the six samples (three biological repeats for each breed).B,PCA of ovary transcriptome data.C, MA plot of DEGs between Meishan and Yorkshire pig ovaries.Red dots indicate DEGs with adjusted P-values<0.05.D, KEGG enrichment analysis of DEGs.Plot label “up” indicates greater gene abundance in Meishan pig ovary, “down” indicates greater gene abundance in Yorkshire pig ovary, and “up_down” indicates the whole DEGs gene list.E, GO enrichment analysis of DEGs.F, RT-qPCR validation of DEGs.Data were shown as mean±SD (n=3).

The iTRAQ-based quantitative proteomic analysis was performed on the same samples used for transcriptome analysis.The high quality of the proteomic data was supported by principal component analysis (PCA) and hierarchical clustering (Fig.2-A and B).Among the 3 857 quantified proteins, 185 were significantly upregulated and 199 significantly downregulated in Meishan pig ovary as defined by a cutoffadjustedP<0.05 and fold change>1.5(Fig.2-C).

Fig.2 Comparison of the ovarian proteome between Meishan and Yorkshire pigs on day 49 of pregnancy.A, Heatmap of Spearman correlation coefficients between samples.B, PCA of ovary proteome data.C, Volcano plot showing differentially expressed proteins(DEPs) between Meishan and Yorkshire pig ovaries.Red dots indicate DEPs with adjusted P-value<0.05 and fold change>1.5.D, KEGG enrichment analysis of DEPs.E, GO enrichment analysis of DEPs.

Among genes with significantly abundance differences at the mRNA level, most protein products showed parallel abundance changes (Spearman correlation coefficientr=0.58) (Fig.3-A).Although fewer proteins were included in the proteomic profiling than mRNAs in the transcriptome profiling, functional enrichment of differentially expressed proteins was generally consistent with transcriptome analysis.Among the four pathways significantly enriched in downregulated transcripts, two (“steroid biosynthesis”and “butanoate metabolism”) were also enriched in downregulated proteins (Figs.1-E, 2-D, and 3-B;Appendix A).Steroid biosynthesis is the primary step in the synthesis of several reproductive hormones.Most steroid biosynthesis pathway genes showing significant differences in mRNA or protein abundance between breeds (Fig.3-C and D) were downregulated at either the mRNA or protein level in Meishan ovary (left half,mRNA; right half, protein) (Fig.3-B).Only two pathways were enriched in proteins overexpressed by Meishan pigs, “spliceosome” and “complement” and “coagulation cascades”.The complement and coagulation cascades were also overexpressed in other high prolificacy pigs(Fernandez-Rodriguezet al.2011), suggesting this as a common pathway influencing prolificacy both within and between breeds.Although enriched KEGG pathways were mostly downregulated in Meishan pig ovary,enrichment analysis of “cellular components” revealed upregulation of several intermediate filament and extracellular proteins, suggesting stronger secretion of ovarian factors in Meishan pigs at gestation day 49.

3.3.Reduced metabolites in Meishan pig ovaries and serum

The biased enrichment of pathways with downregulated transcripts and proteins in Meishan pigs suggests metabolic downregulation.To identify specific metabolic pathways suppressed in Meishan pig ovaries at pregnancy day 49, we conducted untargeted metabolomics analysis comparing metabolite levels between Meishan and Yorkshire ovaries.Among 152 metabolites included in the analysis, 33 differed in amount between Meishan and Yorkshire pig ovaries.Similar to the analysis of pathway enrichment at the gene expression level, most of these metabolites were downregulated in Meishan pig ovaries,including 10 amino acids (Fig.4-A), suggesting reduced metabolic rate in Meishan pig ovaries at pregnancy day 49.Serum metabolic profiling also showed that the majority of metabolites were less abundant in Meishan pigs, consistent with general downregulation of genes in metabolic pathways (Fig.4-B).

3.4.Higher reproductive hormone levels in serum of Meishan pigs

Fig.4 Metabolites and hormone levels in the ovary and serum of day 49 pregnant Meishan and Yorkshire pigs.A and B, metabolites levels in ovaries (A) and in serum (B).C–E, ovarian levels of cholesterol (C), estradiol (D), and progesterone (E).Data are mean±SE(n=3).F–H, serum levels of cholesterol (F), estradiol (G), and progesterone (H).Data are mean±SE (n=6).＊, P<0.05; ＊＊, P<0.01;ns, not significant.

As reproductive hormones are essential for conceptus maintenance, we measured reproductive hormone levels in both the ovaries and serum of Meishan and Yorkshire pigs.Unexpectedly, ovarian cholesterol, estradiol and progesterone levels did not differ significantly between breeds (Fig.4-A–C).In contrast, serum levels of cholesterol and progesterone were significantly higher in Meishan pigs than Yorkshire pigs (Fig.4-F and H).These higher cholesterol, and progesterone levels in Meishan pigs may support greater fetal survival during this third period of fetal loss, thereby conferring high prolificacy.The ovaries no longer synthesize estrogen on day 49 of pregnancy.In addition, overexpression of theCYP19A1gene, which converts androgen to estrogen in the follicles, is associated with lower prolificacy in pigs (Corbinet al.2003).These results suggest that when follicles turn into corpora lutea after about day 30 of pregnancy, serum estradiol, and progesterone levels are more essential than ovarian levels for supporting high prolificacy.

3.5.Genetic basis for differences in reproductive traits between Meishan and Yorkshire pigs

Fig.5 Positively selected genes in the genomes of Meishan and Yorkshire pigs.A and B, Pi and Fst values of each 50-kb genome region.C, Venn diagram showing protein coding genes with top 5% Fst values and –log10π values.

To identify genetic factors contributing to breed divergence of Meishan and Yorkshire pigs, selection pressure screening was performed using the publically available genomic resequencing data (Groenenet al.2012; Frantzet al.2015) of 10 Meishan and 14 Yorkshire pigs.Calculation of Fst and π values for each 50-kb region in 25-kb steps across the whole genome (Fig.5-A and B) yielded 195 protein coding genes with both top 5%Fst values and –log10π values (Fig.5-C), which may be positively selected genes during domestication (Fig.5-A).Among these 195 genes, 21 were differentially expressed at the mRNA level and eight at the protein level between breeds (Appendix B).The NAD(P) dependent steroid dehydrogenase-like protein (NSDHL), which promotes biosynthesis of cholesterol by catalyzing the conversion of 4-methylzymosterol-carboxylate to 3-keto-4-methylzymosterol, was downregulated in Meishan pig ovaries at both mRNA and protein levels (Fig.3-B).

This differential expression of steroid hormone biosynthesis factors between Meishan and Yorkshire pig ovaries may stem from genetic variation.To address this possibility, we examined the relationships between 24 SNPs in three steroid hormone biosynthesis pathway genes differentially expressed between Meishan and Yorkshire pig ovaries and the reproductive traits average litter size, birth weight, and total litter weight per sow among 375 Lansi white (LSW) pigs, a crossbred population derived from Yorkshire and Chinese Yimeng black pigs (Appendix C).The C to T mutation in intron one of CYP19A1 was significantly associated with total litter weight (P<0.01) and piglet average birth weight(P<0.01) (Ronget al.2017).Also, SNP rs323407415 of HSD17B1 was significantly associated with total number of live births (P<0.01) and piglet average birth weight(P<0.01), with AA genotype sows delivering significantly fewer offspring compared to AG and GG genotypes(5.00±1.40vs.8.76±0.35 and 8.40±0.63; bothP<0.01vs.AA).Collectively, these integrative multi-omics analyses suggest that genomic divergence of cholesterol biosynthesis pathways during the domestication of Meishan and Yorkshire pigs is responsible for the difference in reproductive capacity between breeds.

4.Discussion

4.1.Feedback control of steroid biosynthesis in porcine ovary

The Chinese Meishan is one of the oldest domesticated swine breeds, and is best known for its large litter size.To understand the mechanisms for this strong prolificacy,transcriptome analyses have been performed in several organs of pregnant Meishan pigs using the Yorkshire breed as a control (Guet al.2014; Huanget al.2015).Here we used transcriptomic, quantitative proteomic, and metabolomic technologies to analyze gene expression and metabolic differences between Meishan and Yorkshire ovary.Functional enrichment analysis of differentially expressed mRNAs and proteins revealed downregulation of steroid synthesis and butanoate metabolism pathways in Meishan ovary, an unexpected finding given that cholesterol, the final product of the steroid biosynthesis pathway, is essential for the generation of the reproductive hormones estrogen, progesterone, and testosterone.To support high prolificacy, Meishan pig ovaries should secrete more cholesterol or reproductive hormones.Indeed, serum cholesterol and reproductive hormone levels were higher in Meishan pigs than Yorkshire pigs on gestation day 49 (Fig.4).As day 49 is within the period of high fetal loss, these results suggest that high serum and low ovary reproductive hormone levels contribute to the high prolificacy of Meishan pig.

Cellular cholesterol level is tightly controlled by multiple feedback loops to prevent potential cytotoxicity.3-Hydroxy-3-methylglutaryl coenzyme A (HMG CoA) reductase is the rate-limiting enzyme in cholesterol synthesis, and this enzyme is subject to multiple feedback control mechanisms mediated by sterol and nonsterol end-products of mevalonate metabolism(DeBose-Boyd 2008).Sterols can inhibit the activity of sterol regulatory element-binding proteins, which normally enhance cholesterol synthesis and uptake by modulating genes encoding cholesterol biosynthetic enzymes, especially the HMG CoA reductase.Our mRNA-seq data revealed a nearly twofold decrease in ovarian HMG CoA reductase expression in Meishan pigs, suggesting stronger feedback control of ovarian cholesterol biosynthesis in this breed.

Feedback control of steroid hormone biosynthesis from cholesterol occurs not only at the transcriptional level, but also at the translational level.Several genes of the steroid hormone biosynthetic pathway showed inconsistent changes at the mRNA and protein levels in Meishan and Yorkshire pig ovaries.For instance, HSD17B8 was highly expressed at the transcriptional level in the Meishan pig ovary, but protein expression was higher in Yorkshire pig ovary.Also, HSD17B2 mRNA expression was higher in Meishan pig ovary (although the difference did not reach statistical significance); while protein expression was significantly lower in Meishan pig ovary.These observations further support a multilayer feedback control system involving steroids, steroid hormones, and associated biosynthetic genes.

4.2.Coordinated alterations of the butanoate metabolism pathway and steroid biosynthesis in porcine ovary

The butanoate metabolism pathway and steroid biosynthesis were downregulated in the ovaries of Meishan pigs compared to Yorkshire pigs at both transcriptomic and proteomic levels.The secretion of steroid hormones is linked to butyric acid levels in porcine granulosa cells through cAMP signaling (Luet al.2017).Treatment of porcine granulosa cells with butyric acid can regulate steroid hormone production and the expression of downstream genes.STARD6, which acts as the ratelimiting gene in hormone-dependent steroidogenesis by controlling the transport of cholesterol into mitochondria,was significantly downregulated in Meishan pig ovaries.The transcriptional level ofSTARD6was also lower in high prolificacy F2Iberian×Meishan pigs (Fernandez-Rodriguezet al.2011).Ovaries at the corpora lutea stage synthesize and secret progesterone to maintain pregnancy.STARD6 restricts the synthesis of cholesterol,steroids, and other lipids, suggesting higherSTARD6expression or activity as a common limiting factor for litter size in low prolificacy individuals and pig breeds.Moreover,STARD6can also be downregulated by butyric acid treatment in porcine granulosa cells (Luet al.2017).Thus, the downregulation of steroid transport in Meishan pigs may be caused by lower butyric acid levels.

4.3.Timing requirements of ovarian and serum reproductive hormones for high prolificacy

Factors influencing porcine litter size differ among the stages of pregnancy.During the first 12–18 days of pregnancy, conceptus mortality is the major factor affecting litter size (Spotter and Distl 2006).At 30 days of gestation, the embryo is already attached to the endometrium, and its viability critically depends on several external and internal factors (Rosset al.2009).From the 31st day of gestation, fetal survival rate determines litter size.High prolificacy is primary associated with higher levels of reproductive hormones, which in turn is usually associated with greater expression levels of genes involved in steroid hormone and cholesterol biosynthesis.In the current study, however, these genes were actually downregulated in the ovaries of high prolificacy Meishan pigs on day 49.It has been suggested that when follicles turn into corpora lutea during this period, there is a shift from estrogen to progesterone synthesis.Overexpression ofCYP19A1, which converts androgen to estrogen, is associated with low prolificacy (Corbinet al.2003).High levels of estrogen in the ovary could be associated with either high prolificacy or low prolificacy depending on the stage of pregnancy (Fernandez-Rodriguezet al.2011; Zhanget al.2015).On day 49, ovarian cholesterol and reproductive hormone levels were actually similar between Meishan and Yorkshire.However, serum reproductive hormone levels were higher in Meishan pigs,suggesting unique temporal and spatial requirements of reproductive hormones for fetal maintenance.

4.4.Genomic basis of reproductive trait divergence in Meishan and Yorkshire pigs

Through an integrative analysis of genome sequencing data from Meishan and Yorkshire pigs, we identified 195 genes that may have been positively selected during domestication according to π and Fst values, including a subset differentially expressed in Meishan and Yorkshire pig ovaries.Among them, NSDHL directly participates in cholesterol biosynthesis, and integrative analysis of multi-omics data revealed divergence at genome,transcriptome, and proteome levels between the two breeds, highlighting its potential as a candidate gene for precision breeding to improve prolificacy.Most positively selected genes were not differentially expressed between these two breeds, however, possible because sequence alterations do not affect RNA or protein level.However,such alterations may still influence activity or expression regulation in different tissues.Thus, many of these genes may confer distinct reproductive traits to Meishan or Yorkshire pigs, possibly manifested in other tissues.

5.Conclusion

Steroid and steroid hormone pathways are essential for the high prolificacy of Meishan pigs.Indeed, several SNPs within these pathways were associated with reproductive traits in an independent Yorkshire hybrid population.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (31972541 and 31830090),the Central Public-interest Scientific Institution Basal Research Fund, China (Y2021XK20), the Special Construction Project Fund for Shandong Province Taishan Scholars, China and the Agricultural Science and Technology Innovation Program, China (ASTIP-IAS05).

Declaration of competing interest

The authors declare that they have no conflict of interest.

Ethical approval

All animals were treated humanely according to criteria outlined in the “Guide for the Care and Use of Laboratory Animals” published by the Institute of Animal Sciences,Chinese Academy of Agricultural Sciences (Beijing,China).Procedures were approved by the Animal Care and Use Committee (IAS20160616).Pigs were slaughtered following the Animal Care Guidelines of the Ethics Committee of Chinese Academy of Agricultural Sciences.

Appendicesassociated with this paper are available on https://doi.org/10.1016/j.jia.2023.05.014