Total Number Born Research Articles

Effects of Interactions between Feeding Patterns and the Gut Microbiota on Pig Reproductive Performance.

The feeding mode is an important factor affecting the reproductive performance of pigs. The composition and expression of the intestinal microbiota are closely related to the physiological and biochemical indicators of animals. Therefore, to explore the impact of different feeding patterns on the reproductive performance of pigs, this study collected reproductive performance data from 1607 Yorkshire pigs raised under different feeding patterns and conducted a fixed-effect variance analysis. Among them, 731 were in the artificial feeding (AM) group and 876 were in the feeding station feeding (SM) group. Additionally, 40 Yorkshire sows in the late gestation period were randomly selected from each feeding mode for intestinal microbiota analysis. The results of the analysis showed that, in the AM group, both the number of birth deformities (NBD) and the number of stillbirths (NSB) were significantly greater than they were in the SM group (p < 0.05). Additionally, the total number born (TNB) in the AM group was significantly lower than that in the SM group (p < 0.05). The results of the intestinal microbiota analysis revealed that at the phylum level, there were significant differences in nine bacterial taxa between the AM and SM groups (p < 0.05). At the genus level, the abundance of a variety of beneficial bacteria related to reproductive performance in the SM group was significantly greater than that in the AM group. Finally, fecal metabolomic analysis revealed that the contents of butyric acid, isovaleric acid, valeric acid, and isobutyric acid, which are associated with reproductive performance, in the feces of sows in the SM group were significantly higher than those in the AM group (p < 0.05). These results indicate that different feeding methods can affect the gut microbiota composition of Yorkshire pigs and further influence the reproductive performance of pigs through the gut microbiota-metabolic product pathway. The results of this study provide valuable insights for further exploring the relationships between feeding modes, intestinal microbial composition, and host phenotypes.

Genomic Regions Associated with Growth and Reproduction Traits in Pink-Eyed White Mink.

In mink breeding, balanced selection for growth and reproductive features is essential because these traits are contradictory. The variables of total number born (TNB), number born alive (NBA), and body weight (BW) are highly valuable in terms of their importance in mink production. A comprehensive understanding of the molecular mechanisms that drive these features could offer vital insights into their genetic compositions. In the present study, the single-nucleotide polymorphism (SNP) genotypes of 219 minks were obtained via double digest restriction-site associated DNA sequencing (ddRAD-seq). Following several rounds of screening, about 2,415,121 high-quality SNPs were selected for a genome-wide association study (GWAS). The GWAS was used to determine BW and reproductive traits in pink-eyed white mink. It was suggested that SLC26A36, STXBP5L, and RPS 29 serve as potential genes for the total number of kits born (TNB), while FSCB, PDPN, NKX 2-1, NFKB 1, NFKBIA, and GABBR1 are key genes for the number born alive (NBA). Moreover, RTTN, PRPF31, MACROD1, and KYAT1 are possible BW genes based on association results and available functional data from gene and mammalian phenotype databases. These results offer essential information about the variety of mink and theoretical principles for applying mink breeds.

Integration of ssGWAS and ROH analyses for uncovering genetic variants associated with reproduction traits in Large White pigs.

The low heritability of reproduction traits such as total number born (TNB), number born alive (NBA) and adjusted litter weight until 21 days at weaning (ALW) poses a challenge for genetic improvement. In this study, we aimed to identify genetic variants that influence these traits and evaluate the accuracy of genomic selection (GS) using these variants as genomic features. We performed single-step genome-wide association studies (ssGWAS) on 17 823 Large White (LW) pigs, of which 2770 were genotyped by 50K single nucleotide polymorphism (SNP) chips. Additionally, we analyzed runs of homozygosity (ROH) in the population and tested their effects on the traits. The genomic feature best linear unbiased prediction (GFBLUP) was then carried out in an independent population of 350 LW pigs using identified trait-related SNP subsets as genomic features. As a result, our findings identified five, one and four SNP windows that explaining more than 1% of genetic variance for ALW, TNB, and NBA, respectively and discovered 358 hotspots and nine ROH islands. The ROH SSC1:21814570-27186456 and SSC11:7220366-14276394 were found to be significantly associated with ALW and NBA, respectively. We assessed the genomic estimated breeding value accuracy through 20 replicates of five-fold cross-validation. Our findings demonstrate that GFBLUP, incorporating SNPs located in effective ROH (p-value < 0.05) as genomic features, might enhance GS accuracy for ALW compared with GBLUP. Additionally, using SNPs explaining more than 0.1% of the genetic variance in ssGWAS for NBA as genomic features might improve the GS accuracy, too. However, it is important to note that the incorporation of inappropriate genomic features can significantly reduce GS accuracy. In conclusion, our findings provide valuable insights into the genetic mechanisms of reproductive traits in pigs and suggest that the ssGWAS and ROH have the potential to enhance the accuracy of GS for reproductive traits in LW pigs.

ZALEŻNOŚCI POMIĘDZY POLIMORFIZMAMI GENÓW RBP4, FSHB I EGF A CECHAMI ROZRODCZYMI U ŚWIŃ

Genes encoding retinol binding protein 4 (RBP4), follicle stimulating hormone subunit beta (FSHB) and epidermal growth factor (EGF) have been proposed as candidate genes for reproduction traits in pigs. The study presented in this work aimed to find associations between variants of these genes and reproduction traits in pigs reared in Poland. Investigation included Polish Large White x Polish Landrace (n = 288) crossbreed and Yorkshire (n = 195) breed sows. Insertion-deletion polymorphism (indel) in EGF gene was determined by means of PCR (polymerase chain reaction) method, however single nucleotide polymorphism (SNP) in RBP4 and FSHB genes by means of PCR-RFLP (restriction fragment length polymorphism) method. Obtained results showed that total number born (TNB) and number born alive (NBA) in 1st, 2nd and 5th parities were associated with RBP4 gene variants, TNB and NBA in first two parities with FSHB variants, however both traits in all parities with EGF variants (p ≤ 0.05 or p ≤ 0.01). In case of RBP4 gene, heterozygous genotype (AB) was favorable for analyzed traits, however in relation to FSHB and EGF genes homozygous genotypes, AA and BB respectively. Obtained results indicate that polymorphism in three analyzed genes is associated with important reproductive traits of pigs kept in Poland.

228 The effect of temperature-humidity index in different pregnancy stages on litter traits in Taiwan Landrace sows

Abstract Because of climate change, annual average temperatures are gradually rising. Hence, increasing heat stress can impair the litter traits of Taiwanese sows located in tropical and subtropical zones. However, some pregnancy stages may be impacted more by heat stress than other periods. Thus, the purpose of this study was to demonstrate the effect of temperature-humidity index (THI) in different pregnancy stages on total number born (TNB), number born alive (NBA), and stillborn rate (STB). Data were collected in two Taiwanese farms from 2008 to 2021 for TNB, NBA, and STB, while weather data were collected from the closest respective weather station. There were 4,247 and 6,812 pure line Landrace record from farm 1 and farm 2, respectively. Pregnancy stages included 28 d before mating (BEFORE), mating to 30 d of pregnancy (EARLY), 31 to 70 d of pregnancy (MIDDLE), and 71 d of pregnancy to farrowing (LATE). Average THI was calculated in each pregnancy stage and regression coefficients were estimated by linear mixed models within ASReml. A two-trait analysis was used to estimate regression coefficients and genetic correlations among TNB, NBA, and STB. Results showed THI impacted (P &amp;lt; 0.05) TNB and NBA BEFORE and EARLY, while THI influenced (P &amp;lt; 0.05) STB EARLY and MIDDLE. Regression coefficients for TNB were -0.0069 and -0.0228 for BEFORE and EARLY, respectively. For NBA, regression coefficients were 0.0106 and -0.0391 for BEFORE and EARLY, respectively. Regression coefficients for STB were -0.0651 and 0.1332 for EARLY and MIDDLE, respectively. Heritability estimates for TNB, NBA, and STB were 0.168, 0.113, and 0.069, respectively. Genetic correlations between TNB with NBA and STB were 0.913 and 0.539, respectively. While the genetic correlation between NBA and STB was 0.158. In conclusion, THI impacted BEFORE and EARLY stages for TNB and NBA, while the stages of EARLY and MIDDLE were impacted by THI for STB. Hence, control of the environments in these specific stages for sows could improve the performance of litter traits.

Estimation of genotype by environmental interaction for litter traits by reaction norm model in Taiwan Landrace sows.

The negative effects of heat stress on swine reproduction have been well documented and the recent global warming trend caused by climate change is leading to more days with high temperatures every year. This has caused a reduction in litter trait performance of Landrace sows in Taiwan, a country extending across tropical and subtropical oceanic zones. Therefore, this study developed a modified model to determine which stages of pregnancy, before, early, middle, and late, had the largest impacts of heat stress on litter traits. A reaction norm model (RNM) was used to identify sows with high resilience to heat stress for litter traits followed by analysis of the modified model. Data from Landrace sows were collected from 2 farms in Taiwan between 2008 and 2021. A total of 11,059 records were collected for total number born (TNB), number born alive (NBA), and stillborn rate (STBR). The results showed that the heritabilities of TNB, NBA, and STBR were 0.170, 0.115, and 0.077, respectively. These results were similar between the conventional model and the modified model. In the modified model, the before and early stages of sow pregnancy were the significant periods for TNB and NBA (P < 0.05), while the early and middle stages were significant for STBR (P < 0.05). According to the RNM results, the heritability estimates for TNB, NBA, and STBR were 0.23 to 0.11, 0.18 to 0.08, and 0.10 to 0.04, respectively, showing a decrease from low temperature-humidity index (THI) to high THI. The minimum genetic correlations between the highest and the lowest THI for TNB, NBA, and STBR were 0.85, 0.64, and 0.80, respectively. The results of the RNM for breeding value showed re-ranking across THI values. In conclusion, similar results were obtained for heritability when the model was modified for heat stress estimation. Yet re-ranking of breeding values across THI could help farmers to select not only for improved litter trait performance but also for heat stress resilience of Landrace sows in Taiwan.

Changes in Gut Microbiota Associated with Parity in Large White Sows.

As one of the most critical economic traits, the litter performance of sows is influenced by their parity. Some studies have indicated a connection between the gut microbiota and the litter performance of animals. In this study, we examined litter performance in 1363 records of different parities of Large White sows. We observed a marked decline in TNB (Total Number Born) and NBH (Number of Healthy Born) We observed a marked decline in TNB (Total Number Born) and NBH (Number of Healthy Born) among sows with parity 7 or higher. To gain a deeper understanding of the potential role of gut microbiota in this phenomenon, we conducted 16S rRNA amplicon sequencing of fecal DNA from 263 Large White sows at different parities and compared the changes in their gut microbiota with increasing parity. The results revealed that in comparison to sows with a parity from one to six, sows with a parity of seven or higher exhibited decreased alpha diversity in their gut microbiota. There was an increased proportion of pathogenic bacteria (such as Enterobacteriaceae, Streptococcus, and Escherichia-Shigella) and a reduced proportion of SCFA-producing families (such as Ruminococcaceae), indicating signs of inflammatory aging. The decline in sow function may be one of the primary reasons for the reduction in their litter performance.

Genome-wide single nucleotide polymorphism (SNP) data reveal potential candidate genes for litter traits in a Yorkshire pig population.

The litter trait is one of the most important economic traits, and increasing litter size is of great economic value in the pig industry. However, the molecular mechanisms underlying pig litter traits remain elusive. To identify molecular markers and candidate genes for pig litter traits, a genome-wide association study (GWAS) and selection signature analysis were conducted in a Yorkshire pig population. A total of 518 producing sows were genotyped with Illumina Porcine SNP 50 BeadChip, and 1969 farrowing records for the total number born (TNB), the number born alive (NBA), piglets born dead (PBD), and litter weight born alive (LWB) were collected. Then, a GWAS was performed for the four litter traits using a repeatability model. Based on the estimated breeding values (EBVs) of TNB, 15 high- and 15 low-prolificacy individuals were selected from the 518 sows to implement selection signature analysis. Subsequently, the selection signatures affecting the litter traits of sows were detected by using two methods including the fixation index (FST) and . Combining the results of the GWAS and selection signature analysis, 20 promising candidate genes (NKAIN2, IGF1R, KISS1R, TYRO3, SPINT1, ADGRF5, APC2, PTBP1, CLCN3, CBR4, HPF1, FAM174A, SCP2, CLIC1, ZFYVE9, SPATA33, KIF5C, EPC2, GABRA2, and GABRA4) were identified. These findings provide novel insights into the genetic basis of pig litter traits and will be helpful for improving the reproductive performances of sows in pig breeding.

PSV-6 The Impacts of Heat Stress on Litter Traits of Landrace Population in Taiwan

Abstract Global warming becomes a serious issue in the swine industries of most countries. Sow reproduction suffers the brunt of heat stress problems in tropical and subtropical zones, such as in Taiwan. Litter traits, total number born (TNB) and number born alive (NBA), are essential for sow stability and farm economics. However, these traits are influenced by management, facilities, and environmental conditions. Adjustments to management practices and facilities must be considered environmental conditions, including temperature and relative humidity, particularly in Taiwan under oceanic climates. Such specific climate with high temperature and relative humidity caused heat stress for sows around Taiwan over six months in a year. Therefore, the impact of heat stress at different stages of pregnancy in sows had been analyzed using the best linear unbiased prediction model with heterogeneous residuals. A total of 11,074 records for TNB and NBA from 3,080 Landrace sows were collected from two farms between 2008 and 2021. Simultaneously, weather data were obtained from those weather stations closest to the farms. Sows from mating to farrowing, about four months, had been classified into cool (C) or hot (H) climate condition in each month based on temperature-humidity index equals 70. Hence, there were eight combinations (CCCC, CCCH, CCHH, CHHH, HHHH, HHHC, HHCC, HCCC) of the climate effect in this study. The results of climate effect showed that there was not significant difference among the groups of CCCC, CCCH, CCHH, and CHHH in TNB and NBA, while no significant difference (P &amp;gt; 0.05) was found among the groups of HHHH, HHHC, HHCC, and HCCC in both traits. However, the climate effects of CCCH, CCHH, and CHHH were greater (P &amp;lt; 0.05) than those of HHHC, HHCC, and HCCC in TNB. The climate effects of CCCH and CCHH were greater than those of HHHH, HHHC, HHCC, and HCCC in NBA (P &amp;lt; 0.05). These fluctuations generally indicated when sows experience heat stress on mating and early stage of pregnancy (HHHH, HHHC, HHCC, HCCC), could decrease litter sizes. In the heterogeneous residual variances, the groups of CCCC, CCCH, CCHH, and CHHH were less than the groups of HHHH, HHHC, and HHCC in TNB, significantly, while the groups of CCCC, CCCH, and CHHH were less than the groups of HHHH, HHHC, and HHCC in NBA (P &amp;lt; 0.05). The greatest estimated residual variances were shown in HHCC in both TNB and NBA. These changing of trends indicated high heterogeneous residual variance was discovered when heat stress happened during mating and early pregnancy of sows (HHHH, HHHC, HHCC). In conclusion, heat stress at mating and early stage of sow pregnancy decreased the average and increased the residual variances of TNB and NBA.

Genomic Scanning of Inbreeding Depression for Litter Size in Two Varieties of Iberian Pigs.

Inbreeding depression is expected to be more pronounced in fitness-related traits, such as pig litter size. Recent studies have suggested that the genetic determinism of inbreeding depression may be heterogeneous across the genome. Therefore, the objective of this study was to conduct a genomic scan of the whole pig autosomal genome to detect the genomic regions that control inbreeding depression for litter size in two varieties of Iberian pigs (Entrepelado and Retinto). The datasets consisted of 2069 (338 sows) and 2028 (327 sows) records of litter size (Total Number Born and Number Born Alive) for the Entrepelado and Retinto varieties. All sows were genotyped using the Geneseek GGP PorcineHD 70 K chip. We employed the Unfavorable Haplotype Finder software to extract runs of homozygosity (ROHs) and conducted a mixed-model analysis to identify highly significant differences between homozygous and heterozygous sows for each specific ROH. A total of eight genomic regions located on SSC2, SSC5, SSC7, SSC8, and SSC13 were significantly associated with inbreeding depression, housing some relevant genes such as FSHR, LHCGR, CORIN, AQP6, and CEP120.

Does the climate influence the variance of residual in litter traits of Taiwan Landrace sows?

Heat stress adversely affects the litter traits of Landrace, the primary dam breed in Taiwan. This study aimed to evaluate the effects of heat stress during sow pregnancy with homogeneous and heterogeneous residuals to estimate the genetic parameters of the Taiwan Landrace. Performance records for 11 657 litters and weather data from 2008 to 2021 were collected. The climate effect was defined proportionally from cool to hot for climates 1 to 5. The homogeneous residual analysis showed that the heritabilities of the total number born (TNB) and number born alive (NBA) were 0.164 ± 0.014 and 0.111 ± 0.014 with residual variances of 10.338 and 9.164, respectively. The heterogeneous residual analysis showed that the residual variances for TNB and NBA were 8.934–11.113 and 8.196–9.810, respectively. For TNB, the residual variance in the herd–year–climate effect differed significantly in climate 1 from climates 3 to 5 ( p &lt; 0.01). In NBA, the residual variance was significantly lower in climates 1 and 2 than in climates 3 and 5 ( p &lt; 0.01). In conclusion, heritability was estimated for TNB and NBA. In addition, residual variances could interact with the climate effect in heterogeneous residual analysis.

Genome-Wide Association Study on Reproductive Traits Using Imputation-Based Whole-Genome Sequence Data in Yorkshire Pigs.

Reproductive traits have a key impact on production efficiency in the pig industry. It is necessary to identify the genetic structure of potential genes that influence reproductive traits. In this study, a genome-wide association study (GWAS) based on chip and imputed data of five reproductive traits, namely, total number born (TNB), number born alive (NBA), litter birth weight (LBW), gestation length (GL), and number of weaned (NW), was performed in Yorkshire pigs. In total, 272 of 2844 pigs with reproductive records were genotyped using KPS Porcine Breeding SNP Chips, and then chip data were imputed to sequencing data using two online software programs: the Pig Haplotype Reference Panel (PHARP v2) and Swine Imputation Server (SWIM 1.0). After quality control, we performed GWAS based on chip data and the two different imputation databases by using fixed and random model circulating probability unification (FarmCPU) models. We discovered 71 genome-wide significant SNPs and 25 potential candidate genes (e.g., SMAD4, RPS6KA2, CAMK2A, NDST1, and ADCY5). Functional enrichment analysis revealed that these genes are mainly enriched in the calcium signaling pathway, ovarian steroidogenesis, and GnRH signaling pathways. In conclusion, our results help to clarify the genetic basis of porcine reproductive traits and provide molecular markers for genomic selection in pig breeding.

The impact of Box-Cox transformation on phenotypic and genomic characteristics of litter size variability in Landrace pigs

The genetic background of variability remains of interest especially in traits of high economic importance, e.g. litter size in pigs. It has been indicated that the data transformation can affect the variability phenotype. This study aims to evaluate the phenotypic and genomic background of variability of litter size obtained from data before and after the Box-Cox transformation. In total, 67 500 records on the total number born (TNB) in Landrace pig population were used. Since the data presented skewness, the decision was made to perform Box-Cox transformation on TNB and obtain bcTNB. Next, the phenotypic variability was estimated as log-transformed variance of residuals (LnVar) for both TNB (LnVar_TNB) and bcTNB (LnVar_bcTNB). The variability traits were further used in the genome-wide association study (GWAS) performed on 10 688 sows genotyped with Axiom porcine 660 K or imputed to 660 K SNP-chip. The substantial difference in skewness was observed after data transformation, represented as a change from −0.46 to −0.02. Heritability for TNB was 0.118 vs 0.125 for bcTNB. The heritability for LnVar_TNB was 0.0025 vs 0.0037 for LnVar_bcTNB. The change in the genetic variance was confirmed when genetic coefficients on SD level were compared: 2% for LnVar_TNB vs 4% for LnVar_bcTNB. In bivariate analysis, the genetic correlation between the additive genetic effects of the mean TNB and its variability changed from 0.38 to 0.63. The observed positive genetic correlations indicated that selection focused on increasing the litter size will simultaneously cause an increase in litter size variability. Based on GWAS, 14 SNPs were detected for LnVar_TNB and eight for LnVar_bcTNB, with two of them indicating the most promising candidate genes. First candidate gene located on Sus scrofa chromosome (SSC) 3 is STAG3, which plays an essential role in gametogenesis. Second gene located on SSC 10 is ESRRG, which affects placenta development. The additional post-GWAS analysis indicated even more candidate genes for LnVar_TNB and LnVar_bcTNB. The most promising candidate gene was located on SSC 13 – MFN1, which is involved in embryonic development. The results of this study indicated a substantial change in variance components for variability when the Box-Cox transformation was applied to data presenting skewness. Moreover, the data transformation changed the phenotype substantially enough that only part of SNP overlapped between two variability traits. Our investigation shows that it is essential to perform Box-Cox transformation for skewed data in order to properly describe phenotypic and genomic properties of litter size variability in Landrace pigs.

Genetic parameter analysis of reproductive traits in Large White pigs.

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). 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. 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. 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.

Genome-wide association studies uncover genes associated with litter traits in the pig

Litter traits are critical economic variables in the pig industry as they represent a production indicator that can serve to determine sow fertility. In this study, a genome-wide association study on litter traits, including total number born (TNB), number born alive (NBA), litter birth weight (LBW), average birth weight (ABW), and piglet uniformity (PU), was carried out on two pig breeds (Yorkshire and Landrace). A total of 3 637 pigs of both breeds were genotyped using the GeneSeek GGP Porcine 50K SNP BeadChip. A mixed linear model (MLM) and fixed and random model circulating probability unification (FarmCPU) were employed in the genome-wide association studies for litter traits using combined data from the two pig breeds and data from each breed separately. Additionally, the heritability of traits was estimated using three methods—pedigree-based best linear unbiased prediction (PBLUP), genomic best linear unbiased prediction (GBLUP), and single-step best linear unbiased prediction (ssGBLUP)—and was found to lie between 0.065 and 0.1289, 0.0478 and 0.0938, 0.0793 and 0.0935, 0.1862 and 0.2163, and 0.0327 and 0.0419 for TNB, NBA, LBW, ABW, and PU, respectively. We also compared the genomic prediction accuracies and unbiasedness for litter traits of the three BLUP models. Our results indicated that the ssGBLUP method provided higher predictive accuracies and more rational unbiasedness compared with the PBLUP and GBLUP methodologies. Furthermore, based on their possible roles, eight candidate genes (INHBA, LEPR, HDHD2, CTNND2, RNF216, HMX1, PAPPA2, and NTN1) were identified as being linked with litter traits. In the middle of the test, these genes were found to be connected with pig metabolism and ovulation rate. Our results provide the insights into the genetic architecture of litter traits in pigs, and the potential single nucleotide polymorphisms (SNPs) and candidate genes identified may benefit economic profits in pig-breeding industry and contribute to improve litter traits.

Meta-Analysis of SNPs Determining Litter Traits in Pigs.

Nearly 2000 SNPs associated with pig litter size traits have been reported based on genome-wide association studies (GWASs). The aims of this study were to gather and integrate previously reported associations between SNPs and five litter traits: total number born (TNB), number born alive (NBA), number of stillborn (SB), litter birth weight (LWT), and corpus luteum number (CLN), in order to evaluate their common genetic background and to perform a meta-analysis (MA) of GWASs for total number born (TNB) recorded for animals from five pig populations. In this study, the genes with the largest number of associations with evaluated litter traits were GABRG3, RBP7, PRKD1, and STXBP6. Only 21 genes out of 233 associated with the evaluated litter traits were reported in more than one population or for more than one trait. Based on this evaluation, the most interesting candidate gene is PRKD1, which has an association with SB and TNB traits. Based on GO term analysis, PRKD1 was shown to be involved in angiogenesis as well. As a result of the MA, two new genomic regions, which have not been previously reported, were found to be associated with the TNB trait. One SNP was located on Sus scrofa chromosome (SSC) 14 in the intron of the FAM13C gene. The second SNP was located on SSC9 within the intron of the AGMO gene. Functional analysis revealed a strong candidate causal gene underlying the QTL on SSC9. The third best hit and the most promising candidate gene for litter size was found within the SOSTDC1 gene, associated with lower male fertility in rats. We showed that litter traits studied across pig populations have only a few genomic regions in common based on candidate gene comparison. PRKD1 could be an interesting candidate gene with a wider association with fertility. The MA identified new genomic regions on SSC9 and SSC14 associated with TNB. Further functional analysis indicated the most promising gene was SOSTDC1, which was confirmed to affect male fertility in other mammals. This is an important finding, as litter traits are by default linked with females rather than males.

Effective Selection for Lower Mortality in Organic Pigs through Selection for Total Number Born and Number of Dead Piglets.

Simple SummaryBreeders use breeding goals to guide genetic gain in a population in a desired direction. Breeding goals consist of economically interesting traits, in which each trait receives an economic value. For example, to increase the size of a piglet litter, breeders use a breeding goal that includes the trait “number of live piglets in a litter” for a specific day after birth. While the litter size is selected using the trait “number of live piglets,” it is composed of two traits: “total number born” and “number of dead piglets.” The current study used simulations to illustrate that selection for litter size could be improved by selecting for the latter two traits rather than the former. This approach corrects for the fact that these two traits are genetically related to each other, but they also have genetic differences. Further, splitting one trait into two traits allows breeders to focus on the specific elements of a trait. For example, organic pig breeders could select for better piglet welfare by splitting “number of live piglets” into two traits, giving a negative economic value to the number of dead piglets.Selection for the number of living pigs on day 11 (L11) aims to reduce piglet mortality and increase litter size simultaneously. This approach could be sub-optimal, especially for organic pig breeding. This study evaluated the effect of selecting for a trait by separating it into two traits. Genetic parameters for L11, the total number born (TNB), and the number of dead piglets at day 11 (D11) were estimated using data obtained from an organic pig population in Denmark. Based on these estimates, two alternative breeding schemes were simulated. Specifically, selection was made using: (1) a breeding goal with L11 only versus (2) a breeding goal with TNB and D11. Different weightings for TNB and D11 were tested. The simulations showed that selection using the first breeding scheme (L11) produced lower annual genetic gain (0.201) compared to the second (TNB and D11; 0.207). A sensitivity analysis showed that the second scheme performed better because it exploited differences in heritability, and accounted for genetic correlations between the two traits. When the second breeding scheme placed more emphasis on D11, D11 declined, whereas genetic gain for L11 remained high (0.190). In conclusion, selection for L11 could be optimized by separating it into two correlated traits with different heritability, reducing piglet mortality and enhancing L11.

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.

Simple SummarySow reproductive performance is crucial in the entire pig industry. However, the heritability of reproductive traits is slowthat it is difficult to make great genetic progress by traditional breeding methods. Therefore, in this study, we performed genome-wide association analyses of litter traits in French White sows to explore genes related to sow reproductive traits and we finally detected a notable region (10.72–11.06 Mb on chromosome 7) and four promising genes (JARID2, PDIA6, FLRT2 and DICER1). The results of this study provide a theoretical basis for subsequent molecular breeding.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.