Genetic parameters for reproductive traits at different parities in Large White pigs

Genetic polymorphisms in ESR and FSHβ genes and their association with litter traits in Large White pigs

The estrogen receptor (ESR) gene and follicle-stimulating hormone β (FSHβ) gene are responsible for litter traits. The present study aimed to verify the polymorphisms of ESR and FSHβ and assess their effects on the litter traits in 201 Large White pigs. Four SNPs (g.C669T, g.A1296G, g.C1665T and g.A1755G) were found in ESR. The TT genotype at g.C1665T locus and AA genotype at g.A1755G locus could significantly increase the total litter size of the first litter of American Large White pigs (p < 0.05). Eight SNPs were found in exon 3 of FSHβ. The AA genotype at g.A511G locus, AA and AG genotypes at g.A617G locus, CC and CT genotypes at g.C630T locus, CT and TT genotypes at g.C652T locus, CT and TT genotypes at g.C735T locus, AA and AG genotypes at g.A746G, AA and AG genotypes at g.A921G and CT genotype at g.C678T could significantly increase the litter size of different strains of Large White pigs (p < 0.05). Our study revealed that the genetic variations of ESR and FSHβ were closely related to the litter trait of Large White pigs. Therefore, ESR and FSHβ genes could be used as molecular markers for the genetic selection of Large White pigs.

Estimation of heritabilities and additive genetic correlations for reproduction traits in swine: insights for tropical commercial production systems using multiple trait animal models

OBJECTIVE

This study was to estimate heritabilities, additive genetic correlations, and phenotypic correlations between number of piglets born alive (NBA), litter birth weight (LTBW), number of piglets weaned (NPW) and litter weaning weight (LTWW) in different parities of Landrace (L), Yorkshire (Y), Landrace×Yorkshire (LY), and Yorkshire×Landrace (YL) sows in a commercial swine operation in Northern Thailand.

METHODS

Two models were utilized, a single trait repeatability model (RM) and a multiple trait animal model (MTM). The RM assumed reproductive records from different parities to be repeated values of the same trait, whereas the MTM assumed these records to be different traits. The two models accounted for the fixed effects of farrowing year-season, genetic group of the sow, heterosis, and age at first farrowing, and the random effects of sow, boar, and residual.

RESULTS

Heritability estimates from RM were 0.02±0.01 for NBA, 0.10±0.01 for LTBW, 0.04±0.01 for NPW, and 0.11±0.01 for LTWW. Heritability estimates from MTM fluctuated across parities, ranging from 0.04±0.01 in parity 2 to 0.09±0.02 in parity 4 for NBA, 0.07±0.02 in parity 2 to 0.16±0.02 in parity 3 for LTBW, 0.04±0.02 in parity 4 to 0.08±0.01 in parity 1 for NPW, and 0.16±0.02 in parity 1 to 0.20±0.02 in parity 2 for LTWW. Additive genetic correlation estimates from MTM were also variable, ranging from 0.29±0.24 between NBA in parity 1 and NBA in parity 2 to 0.99±0.05 between LTWW in parity 3 and LTWW in parity 4.

CONCLUSION

The findings of this study highlight the advantage of using MTM for the genetic improvement of reproductive traits in swine and contribute to the development of sustainable swine breeding programs in Thailand.

Estimation of genetic parameters of pig reproductive traits

Introduction

In this study, we aimed to estimate the genetic parameters of the reproductive traits in three popular commercial pig breeds: Duroc, Landrace, and Yorkshire. Additionally, we evaluated the factors that influence these traits.

Method

We collected data from a large number of litters, including 1,887 Duroc, 21,787 Landrace, and 74,796 Yorkshire litters. Using the ASReml-R software to analyze 11 traits, which included: total number of pigs born (TNB); number of piglets born alive (NBA); number of piglets born healthy (NBH); number of piglets born weak (NBW); number of new stillborn piglets (NS); number of old stillborn piglets (OS); number of piglets born with malformation (NBM); number of mummified piglets (NM); total litter birthweight (LBW); litter average weight (LAW); duration of gestational period (GP). We investigated the effects of 4 fixed factors on the genetic parameters of these traits.

Results

Among the 11 reproductive-related traits, the gestational period belonged to the medium heritability traits (0.251-0.430), while remaining traits showed low heritability, ranging from 0.005 to 0.159. TNB, NBA, NBH, LBW had positive genetic correlation (0.737 ~ 0.981) and phenotype correlation (0.711 ~ 0.951). There was a negative genetic correlation between NBW and LAW (-0.452 ~ -0.978) and phenotypic correlation (-0.380 ~ -0.873). LBW was considered one of the most reasonable reproductive traits that could be used for breeding improvement. Repeatability of the three varieties was within the range of 0.000-0.097. In addition, the fixed effect selected in this study had a significant effect on Landrace and Yorkshire (p < 0.05).

Discussion

We found a positive correlation between LBW and TNB, NBA, and NBH, suggesting the potential for multi-trait association breeding. Factors such as farm, farrowing year, breeding season, and parity should be taken into consideration in practical production, as they may impact the reproductive performance of breeding pigs.

Genetic parameter analysis of reproductive traits in Large White pigs

OBJECTIVE

The primary objective of this study was to determine the genetic parameters for reproductive traits among Large White pigs, including the following traits: total number born (TNB), number born alive (NBA), litter birth weight (LBW), average birth weight (ABW), gestation length (GL), age at first service (AFS) and age at first farrowing (AFF).

METHODS

The dataset consisted of 19,036 reproductive records from 4,986 sows, and a multi-trait animal model was used to estimate genetic variance components of seven reproductive traits.

RESULTS

The heritability estimates for these reproductive traits ranged from 0.09 to 0.26, with the highest heritability for GL and AFF, and the lowest heritability for NBA. The repeatabilities for TNB, NBA, LWB, ABW, and GL were ranged from 0.16 to 0.34. Genetic and phenotypic correlations ranged from -0.41 to 0.99, and -0.34 to 0.98, respectively. In particular, the correlations between TNB, NBA and LBW, between AFS and AFF, exhibited a strong positive correlation. Furthermore, for TNB, NBA, LBW, ABW, and GL, genetic correlations of the same trait between different parities were moderately to strongly correlated (0.32 to 0.97), and the correlations of adjacent parities were higher than those of nonadjacent parities.

CONCLUSION

All the results in the present study can be used as a basis for the genetic assessment of the target population. In the formulation of dam line selection index, AFS or AFF can be considered to combine with TNB in a multiple trait swine breeding value estimation system. Moreover, breeders are encouraged to increase the proportion of sows at parity 3-5 and reinforce the management of sows at parity 1 and parity ≥8.

GWAS of Reproductive Traits in Large White Pigs on Chip and Imputed Whole-Genome Sequencing Data

Total number born (TNB), number of stillborn (NSB), and gestation length (GL) are economically important traits in pig production, and disentangling the molecular mechanisms associated with traits can provide valuable insights into their genetic structure. Genotype imputation can be used as a practical tool to improve the marker density of single-nucleotide polymorphism (SNP) chips based on sequence data, thereby dramatically improving the power of genome-wide association studies (GWAS). In this study, we applied Beagle software to impute the 50 K chip data to the whole-genome sequencing (WGS) data with average imputation accuracy (R2) of 0.876. The target pigs, 2655 Large White pigs introduced from Canadian and French lines, were genotyped by a GeneSeek Porcine 50K chip. The 30 Large White reference pigs were the key ancestral individuals sequenced by whole-genome resequencing. To avoid population stratification, we identified genetic variants associated with reproductive traits by performing within-population GWAS and cross-population meta-analyses with data before and after imputation. Finally, several genes were detected and regarded as potential candidate genes for each of the traits: for the TNB trait: NOTCH2, KLF3, PLXDC2, NDUFV1, TLR10, CDC14A, EPC2, ORC4, ACVR2A, and GSC; for the NSB trait: NUB1, TGFBR3, ZDHHC14, FGF14, BAIAP2L1, EVI5, TAF1B, and BCAR3; for the GL trait: PPP2R2B, AMBP, MALRD1, HOXA11, and BICC1. In conclusion, expanding the size of the reference population and finding an optimal imputation strategy to ensure that more loci are obtained for GWAS under high imputation accuracy will contribute to the identification of causal mutations in pig breeding.

Heterozygosity and homozygosity regions affect reproductive success and the loss of reproduction: a case study with litter traits in pigs

Runs of heterozygosity (ROHet) and homozygosity (ROH) harbor useful information related to traits of interest. There is a lack of investigating the effect of ROHet and ROH on reproductive success and the loss of reproduction in mammals. Here, we detected and characterized the ROHet and ROH patterns in the genomes of Chinese indigenous pigs (i.e., Jinhua, Chun’an, Longyou Black, and Shengxian Spotted pigs), revealing the similar genetic characteristics of indigenous pigs. Later, we highlighted the underlying litter traits-related ROHet and ROH using association analysis with linear model in these four indigenous pig breeds. To pinpoint the promising candidate genes associated with litter traits, we further in-depth explore the selection patterns of other five pig breeds (i.e., Erhualian, Meishan, Minzhu, Rongchang, and Diqing pigs) with different levels of reproduction performance at the underlying litter traits-related ROHet and ROH using F_ST and genetic diversity ratio. Then, we identified a set of known and novel candidate genes associated with reproductive performance in pigs. For the novel candidate genes (i.e., CCDC91, SASH1, SAMD5, MACF1, MFSD2A, EPC2, and MBD5), we obtained public available datasets and performed multi-omics analyses integrating transcriptome-wide association studies and comparative single-cell RNA-seq analyses to uncover the roles of them in mammalian reproductive performance. The genes have not been widely reported to be fertility-related genes and can be complementally considered as prior biological information to modify genomic selections models that benefits pig genetic improvement of litter traits. Besides, our findings provide new insights into the function of ROHet and ROH in mammals.

A genome-wide association study of important reproduction traits in large white pigs

Augmenting the reproductive efficiency of sows remains the predominant challenge in the swine industry. This work was aimed at scrutinizing vital genetic markers for reproductive traits in this animal. This entailed probing of the records of vital attributes of Large White pigs (n = 695) inclusive of the total number of born (TNB), number of born alive (NBA), number of weaned pigs (NWP), number of healthy births (NHS), total litter weight of piglets born alive (BALWT), weaning litter weight (WNWT), and corrected litter weight at 21 days (W21). A genome-wide association study (GWAS) for the four litter traits and three traits of litter weight in the Denmark Large White population then ensued. We discovered seven significantly related SNPs and eleven potential candidate genes (e.g., TUSC3, THRB for TNB; STT3B for NBA). The subsequent functional enrichment analysis of these genes showed that the significant gene were associated with steroid hormone receptor activity. Our findings indicated that the genes TUSC3, THRB and STT3B probably contribute to litter traits in this population. This work reveals genetic mechanisms of reproduction traits and also supports ensuing genetic improvement employing marker-assisted selection in Large White pigs.

Identification of Genomic Regions and Candidate Genes for Litter Traits in French Large White Pigs Using Genome-Wide Association Studies

The reproductive traits of sows are one of the important economic traits in pig production, and their performance directly affects the economic benefits of the entire pig industry. In this study, a total of 895 French Large White pigs were genotyped by GeneSeek Porcine 50K SNP Beadchip and four phenotypic traits of 1407 pigs were recorded, including total number born (TNB), number born alive (NBA), number healthy piglets (NHP) and litter weight born alive (LWB). To identify genomic regions and genes for these traits, we used two approaches: a single-locus genome-wide association study (GWAS) and a single-step GWAS (ssGWAS). Overall, a total of five SNPs and 36 genomic regions were identified by single-locus GWAS and ssGWAS, respectively. Notably, fourof all five significant SNPs were located in 10.72–11.06 Mb on chromosome 7, were also identified by ssGWAS. These regions explained the highest or second highest genetic variance in the TNB, NBA and NHP traits and harbor the protein coding gene ENSSSCG00000042180. In addition, several candidate genes associated with litter traits were identified, including JARID2, PDIA6, FLRT2 and DICER1. Overall, these novel results reflect the polygenic genetic architecture of the litter traits and provide a theoretical reference for the following implementation of molecular breeding.

Genome-wide association studies reveals polygenic genetic architecture of litter traits in Duroc pigs

With continuous improvement of sow litter size, breeders are gradually paying more attention to the quality of litter traits that directly impact the production efficiency of pig companies, such as the rate of piglets born alive (RBA) and the rate of healthy births (RHB). The objectives of this study are to dissect the genetic basis of litter traits in pig and to identify valuable genes and genetic markers, especially pleiotropic, for pig breeding. Herein, 1140 Duroc pigs and 2046 reproduction records, 5 litter traits, including the number of healthy births (NHB), number of deformed fetuses (NDF), number of stillborn (NSB), RBA, and RHB, were used in this study. Subsequently, a genome-wide association study (GWAS) was performed for the five litter traits in the first two parities from two Duroc populations. A total of 76 significantly related SNPs and 10 potential candidate genes (CAV1, DAB2, FGF12, FHOD3, DYNC2H1, GRHL1, TCTN3, PYROXD2, MMP8, MMP13, and PGR) were detected, including 13 pleiotropic SNPs that affected more than one litter trait. Finally, the functional enrichment analysis of functional genes that were closest to these significant SNPs indicated that most of the significant pathways were associated with hormone secretion and embryo and organ development. This study advances our understanding of the genetic mechanisms of litter traits, especially the survival rate of piglets born, and provides an opportunity to increase the quality of litter using marker-assisted selection or genomic selection in pigs.

Evaluation of reproductive traits and ovarian and uterine morphology of sows with different genotypes for the estrogen receptor, prolactin receptor, and follicle-stimulating hormone subunit beta genes

The purpose of this study was to analyze the morpho-functional features of the ovaries and uterus of sows with different genotypes for the estrogen receptor (ESR), prolactin receptor (PRLR), and follicle-stimulating hormone subunit beta (FSHβ) genes associated with reproductive traits. Healthy Large White sows were studied. The genotypic status of the ESR, PRLR, and FSHβ genes was detected by polymerase chain reaction-restriction fragment length polymorphism. The structure of the ovaries and uterus was studied using quantitative assessment of organs and histological research. Sows with the ESR ^BB genotype significantly exceeded animals with the ESR ^AA genotype in milk yield (by 0.3 kg) and in the number of piglets at birth (by 0.9 animals) and at weaning (by 0.7 animals). Sows with the ESR ^AB genotype were midway between those with ESR ^BB and ESR ^AA genotypes in terms of these reproductive traits. Animals with the PRLR ^AA genotype significantly exceeded those with the PRLR ^BB genotype in the number of piglets born (P < 0.05); the differences in litter weight at birth were not significant. Compared to other genotypes, sows with genotypes ESR ^BB (P < 0.05) and PRLR ^{AA (AB)} (P < 0.05) had larger uteruses and more yellow bodies, tertiary follicles, and primordial follicles in their ovaries. Animals with the FSHβ ^BB genotype significantly exceeded animals with the FSHβ ^AB genotype in the length of uterus by 21 cm (P < 0.05).

Genetic Analysis of Major Production and Reproduction Traits of Korean Duroc, Landrace and Yorkshire Pigs

The study aimed to investigate the genetic parameters of the production and reproduction traits of Korean Duroc, Landrace, and Yorkshire pigs. Three production traits, namely average daily gain (ADG), age at 105 kg body weight (DAYS105) and backfat thickness (BFT), and three reproduction traits, namely age at first farrowing (AFF), total number of piglets born (TNB) and number of piglets born alive (NBA), were analyzed. The reproduction dataset was based on first-parity gilts only. However, the production dataset comprised pigs of both sexes. Genetic parameters were estimated from individual datasets using a multiple-trait animal model in AIREMLF90 software. The heritability values of ADG, DAYS105 and BFT were 0.34-0.36, 0.41-0.44 and 0.38-0.48, respectively, across breeds. Heritability values for AFF, TNB and NBA were 0.07-0.14, 0.09-0.11 and 0.09-0.10, respectively. Strong genetic correlations existed between ADG and DAYS105 (-0.97) and between TNB and NBA (0.90 to 0.96). In line with breeding goals, all productive traits in Duroc pigs, and all reproduction traits except AFF in Landrace and Yorkshire pigs, also showed noticeable improvements in recent years. In conclusion, we believe that our findings on economic traits would greatly assist future pig breeding decisions in Korea.

Assessing the Effect of SNPs on Litter Traits in Pigs

The reproductive ability of sows is the principle of continuous and efficient production, based on such traits as the number of piglets, the total number of parities, and the period of economic use. Currently, SNPs associated with the TNB and NBA are presented in the PigQTLdb. The aim of this work was the assessment of the SNP effects on the litter traits in Large White (LW, n = 502) and Landrace (LN, n = 432) sow breeds in a farm in Russia. 9 SNPs (SNP_1: rs80956812; SNP_2: rs81471381; SNP_3: rs80891106; SNP_4: rs81399474; SNP_5: rs81421148; SNP_6: rs81242222; SNP_7: rs81319839; SNP_8: rs81312912; SNP_9: rs80962240) were selected for the study. Associative analysis was performed using the GLM procedure in R version 3.5.1. The analysis of reproductive traits was carried out according to the results of the first parity, the second and subsequent parities, and totals for lifetime of sows. The significant effect on litter traits in LW was determined for SNP rs80956812, SNP rs81471381, SNP rs81421148, and SNP rs81399474. The significant effect on litter traits in LN was determined for SNP rs81421148 and SNP rs81319839. AKT3 gene was identified as perspective candidate gene, whose biological functions, as well as the results obtained in our work and in other studies, indicate its potential role in the reproductive process regulation in pigs. In general, the data obtained help to explain the genetic mechanisms of reproductive traits.

Genetic parameters for litter traits at different parities in purebred Landrace and Yorkshire pigs

Comparison of the multi-trait animal model and the traditional repeatability model was carried out using data obtained from 6,424 Landrace and 20,835 Yorkshire sows farrowed from January 2000 to April 2018 in order to estimate genetic parameters for litter traits at different parities. Specifically, records of the total number born (TNB), number born alive (NBA), total number of mortality (MORT), number of stillborn (NSB) and number of mummified pigs (MUM) were used. Although results showed the heterogeneity of heritability for litter traits at different parities, the mean heritability estimates from the multi-trait model were found to be higher than those of the repeatability model for all traits in both pig breeds. In terms of genetic correlation between parities, a slight difference in genetic control in the first parity was noted for TNB and NBA in Landrace and Yorkshire pigs. The correlation between the first parity and later parities ranged from 0.48 to 0.74 for TNB and NBA in both breeds. Moreover, genetic correlation between parities for MORT and NSB was observed to be high for parities higher than 2 in Yorkshire pigs. For MUM, genetic correlation between the first and other parities was generally low in both breeds, indicating that culling pigs on the basis of MUM at the first parity could probably be unreasonable. Overall, the results of this study suggest that the multi-trait approach for litter size traits is useful for the accurate estimation of genetic parameters.

Estimation of genetic parameters for reproductive traits in connectedness groups of Duroc, Landrace and Yorkshire pigs in China

The objective of this study was to estimate group- and breed-specific genetic parameters for reproductive traits in Chinese Duroc, Landrace, and Yorkshire populations. Records for reproductive traits between April 1998 and December 2017 from 92 nucleus pig breeding farms, which were involved in the China Swine Genetic Improvement Program, were analysed. Due to weak genetic connectedness across all farms, connectedness groups consisting of related farms were used. Three, two and four connectedness groups for Duroc, Landrace and Yorkshire were firstly established according to the genetic connectedness rating among farms. For each connectedness group a five-trait animal model was implemented, and via restricted maximum likelihood procedure the genetic parameters were estimated for five reproductive traits i.e., total number born (TNB), number born alive (NBA), litter weight at farrowing (LWF), farrowing interval (FI) and age at first farrowing (AFF). The average of heritabilities among connectedness groups ranged from .01 (for FI in Yorkshire) to .30 (for AFF in Duroc). Estimates of repeatability for litter traits ranged from .14 to .20 and were consistent for each breed, and for FI, the estimates varied from .01 to .11 across breeds and groups. The estimated genetic correlations among litter traits (i.e., TNB, NBA and LWF) were all significantly high (>.56) and similar across breeds. Averaged genetic correlations over three breeds were -.25, -.27, -.18, -.04, -.10, -.02, and .28 for FI-TNB, FI-NBA, FI-LWF, AFF-TNB, AFF-NBA, AFF-LWF and FI-AFF, respectively. The standard errors of the estimates were all very low (<0.01) in most situations. Results from this study suggest that selection based on TNB which is currently used in dam line selection index can improve NBA and LWF simultaneously. However, care should be taken on FI and AFF as they are both greatly influenced by non-genetic factors such as management and measurement.

Genome-wide association studies for the number of animals born alive and dead in duroc pigs

Litter size is one of the most important economic traits for pig production as it is directly related to the production efficiency. As an important litter size trait in pigs, the number of piglets born alive at birth (NBA) receives widespread interests in the pig industry. However, traits of piglets born dead, including the number of stillborn piglets (NS) and the piglets mummified at birth (NM) should be noted to explain the loss of reproduction. Herein, in the present study, a total of 803 producing sows were sampled and 2807 farrowing records for NBA, NM, and NS traits were collected in a Duroc swine population. Subsequently, a genome-wide association study (GWAS) was performed for NBA, NS and NM in parity groups 1 to 5. In total, 10 putative regions were found associated with these traits. After stepwise conditional analyses around the putative regions, eight independent signals were ultimately identified for NBA, NS, and NM, and there were seven promising candidate genes related to these traits, including ARID1A, RXRG, NFATC4, ABTB2, GRAMD1B, NDRG1, and APC. Our findings contribute to the understanding of the significant genetic causes of piglets born alive and dead, and could have a positive effect on pig production efficiency and economic profits.