Number Of Piglets Born Alive Research Articles

Genome-Wide Association Study of Reproductive Traits in Large White Pigs.

(1) Background: Reproductive performance is crucial for the pork industry's success. The Large White pig is central to this, yet the genetic factors influencing its reproductive traits are not well understood, highlighting the need for further research. (2) Methods: This study utilized Genome-Wide Association Studies to explore the genetic basis of reproductive traits in the Large White pig. We collected data from 2237 Large White sows across four breeding herds in southern China, focusing on eight reproductive traits. Statistical analyses included principal component analysis, linkage disequilibrium analysis, and univariate linear mixed models to identify significant single-nucleotide polymorphisms and candidate genes. (3) Results: Forty-five significantly related SNPs and 17 potential candidate genes associated with litter traits were identified. Individuals with the TT genotype at SNP rs341909772 showed an increase of 1.24 in the number of piglets born alive (NBA) and 1.25 in the number of healthy births (NHBs) compared with those with the CC genotype. (4) Conclusions: The SNPs and genes identified in this study offer insights into the genetics of reproductive traits in the Large White pig, potentially guiding the development of breeding strategies to improve litter size.

Comprehensive genome-wide analysis of genetic loci and candidate genes associated with litter traits in purebred Berkshire pigs of Korea.

The objective of this study was to identify genomic regions and candidate genes associated with the total number of piglets born (TNB), number of piglets born alive (NBA), and total number of stillbirths (TNS) in Berkshire pigs. This study used a total of 11,228 records and 2,843 single-nucleotide polymorphism (SNP) data obtained from Illumina porcine 60 K and 80 K chips. The estimated genomic breeding values (GEBVs) and SNP effects were estimated using weighted single-step genomic BLUP (WssGBLUP). The heritabilities of the TNB, NBA, and TNS were determined using single-step genomic best linear unbiased prediction (ssGBLUP). The heritability estimates were 0.13, 0.12, and 0.015 for TNB, NBA, and TNS, respectively. When comparing the accuracy of breeding value estimates, the results using pedigree-based BLUP (PBLUP) were 0.58, 0.60, and 0.31 for TNB, NBA, and TNS, respectively. In contrast, the accuracy increased to 0.67, 0.66, and 0.42 for TNB, NBA, and TNS, respectively, when using WssGBLUP, specifically in the last three iterations. The results of weighted single-step genome-wide association studies (WssGWAS) showed that the highest variance explained for each trait was predominantly located in the Sus scrofa chromosome 5 (SSC5) region. Specifically, the variance exceeded 4% for TNB, 3% for NBA, and 6% for TNS. Within the SSC5 region (12.26 to 12.76 Mb), which exhibited the highest variance for TNB, 20 SNPs were identified, and five candidate genes were identified: TIMP3, SYN3, FBXO7, BPIFC, and RTCB. The identified SNP markers for TNB, NBA, and TNS were expected to provide valuable information for genetic improvement as an understanding of their expression and genetic architecture in Berkshire pigs. With the accumulation of more phenotype and SNP data in the future, it is anticipated that more effective SNP markers will be identified.

Classification of Sows for Longevity Based on Total Number of Piglets Born Alive in the First Parities

Classification of Sows for Longevity Based on Total Number of Piglets Born Alive in the First Parities

Genomic predictions and GWAS for heat tolerance in pigs based on reaction norm models with performance records and data from public weather stations considering alternative temperature thresholds.

Genetic improvement of livestock productivity has resulted in greater production of metabolic heat and potentially greater susceptibility to heat stress. Various studies have demonstrated that there is genetic variability for heat tolerance and genetic selection for more heat tolerant individuals is possible. The rate of genetic progress tends to be greater when genomic information is incorporated into the analyses as more accurate breeding values can be obtained for young individuals. Therefore, this study aimed (1) to evaluate the predictive ability of genomic breeding values for heat tolerance based on routinely recorded traits, and (2) to investigate the genetic background of heat tolerance based on single-step genome-wide association studies for economically important traits related to body composition, growth and reproduction in Large White pigs. Pedigree information was available for 265,943 animals and genotypes for 8686 animals. The studied traits included ultrasound backfat thickness (BFT), ultrasound muscle depth (MDP), piglet weaning weight (WW), off-test weight (OTW), interval between farrowing (IBF), total number of piglets born (TNB), number of piglets born alive (NBA), number of piglets born dead (NBD), number of piglets weaned (WN) and weaning-to-estrus interval (IWE). The number of phenotypic records ranged from 6059 (WN) to 172,984 (TNB). Single-step genomic reaction norm predictions were used to calculate the genomic estimated breeding values for each individual. Predictions of breeding values for the validation population individuals were compared between datasets containing phenotypic records measured in the whole range of temperatures (WR) and datasets containing only phenotypic records measured when the weather station temperature was above 10°C (10C) or 15°C (15C), to evaluate the usefulness of these datasets that may better reflect the within-barn temperature. The use of homogeneous or heterogeneous residual variance was found to be trait-dependent, where homogeneous variance presented the best fit for MDP, BFT, OTW, TNB, NBA, WN and IBF, while the other traits (WW and IWE) had better fit with heterogeneous variance. The average prediction accuracy, dispersion and bias values considering all traits for WR were 0.36 ± 0.05, -0.07 ± 0.13 and 0.76 ± 0.10, respectively; for 10C were 0.39 ± 0.02, -0.05 ± 0.07 and 0.81 ± 0.05, respectively; and for 15C were 0.32 ± 0.05, -0.05 ± 0.11 and 0.84 ± 0.10, respectively. Based on the studied traits, using phenotypic records collected when the outside temperature (from public weather stations) was above 10°C provided better predictions for most of the traits. Forty-three and 62 candidate genomic regions were associated with the intercept (overall performance level) and slope term (specific biological mechanisms related to environmental sensitivity), respectively. Our results contribute to improve genomic predictions using existing datasets and better understand the genetic background of heat tolerance in pigs. Furthermore, the genomic regions and candidate genes identified will contribute to future genomic studies and breeding applications.

123 Benchmarking of Artificial Neural Network Models for Genomic Prediction of Quantitative Traits in Pigs

Abstract Artificial neural networks (ANN) are a type of machine learning model that has been applied to various genomic problems, with the ability to learn non-linear relationships and model high-dimensional data. ANNs also have the potential in genomic prediction by capturing the intricate relationship between genetic variants and phenotypes. However, there is currently a limited effort to investigate the performance and feasibility of ANNs for pig genomic predictions. In this study, we evaluated the predictive performance of TensorFlow’s ANN models with one-layer, two-layer, and three-layer structures (with zero, one, and two hidden layers, respectively), in comparison with five linear methods, including GBLUP, LDAK, BayesR, SLEMM and scikit-learn’s ridge regression using data of six quantitative traits including off-test body weight (WT), off-test back fat thickness (BF), off-test loin muscle depth (MS), number of piglets born alive (NBA), number of piglets born dead (NBD), and number of piglets weaned (NW). Furthermore, we assessed the computational efficiency of ANNs on both CPU and GPU. The benchmarking was based on cross-validations of 26,190 genotyped pigs. We employed hyperband tuning to optimize the hyper-parameters and select the best model among one-layer, two-layer, and three-layer structures. Results showed that the one-layer structure, which is equivalent to ridge regression, yielded the best performance comparable to that of GBLUP. Using the optimal hyper-parameters for two-layer and three-layer structures, ANNs underperformed GBLUP in terms of accuracy. Of the five linear methods, BayesR and SLEMM performed similarly and the best, followed by LDAK, scikit-learn’s ridge regression, and GBLUP. Moreover, SLEMM was the fastest, which completed training with 21k individuals and 30k SNPs in 2.6 minutes. Compared with CPUs, GPUs exhibited a comparable computational speed for one-layer ANN but offered significant gains in computational efficiency for multi-layer ANNs. Based on our analysis of optimal hyper-parameters for two-layer ANN with BF, we found that using a GPU can lead to a five-fold increase in processing speed compared with using a conventional CPU, but it is still slower than GBLUP. In addition, hyper-parameter tuning (particularly for L2 regularization and the number of dense units in hidden layers) is critical for improving the genomic prediction accuracy in pigs. In conclusion, we found ANN with up to three layers could not improve genomic predictions compared with routine linear methods for pig quantitative traits.

Analysis of Reproduction Performance Traits in Sows of the CG36 Hybrid Line, Including the Effect of Selected Factors and Phenotypic Correlations

In Poland, despite a decline in the pig population, pork consumption invariably remains high. For this reason, it is important to search for a potential reduction in pig production costs. One of the feasible solutions is to use sows of hybrid lines. Currently, several sow lines are available on the Polish market, such as CG36 (Choice Genetics). The aim of this study was to determine the level of reproduction performance in this line considering the effect of parity and farrowing season. Additionally, coefficients of phenotypic correlations between analysed reproduction performance parameters were determined. The experimental material comprised 112 females inseminated with semen of a boar of the Excelium line (Choice Genetics), which produced 336 litters. The investigated population was characterised by a high level of reproduction traits and young age at first farrowing (AFF), while the number of piglets born alive (NBA), the number of piglets weaned per litter (NW), and the number of piglets weaned per sow per year (PWSY) reached high, economically advantageous levels. Primiparous sows produced and reared lower numbers of piglets than multiparous sows, which indicates the need to maintain an adequate herd structure, with a maximum share of gilts at 30%. No effect of the season on values of reproduction traits was found, which shows optimal environmental conditions in the animal housing where the pigs were kept. Dependencies between the analysed traits confirmed the results reported by other authors, where NBA was highly positively correlated with LW, although LW increased with an increase in NBA. No correlations were found between PWSY and the other traits. In turn, the observed coefficients of phenotypic correlations indicate that in order to reduce AFF in CG36 sows, it is necessary to control FI.

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

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. 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. 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. 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.

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. 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. 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). 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 Parameters of Reproductive Performances in Hungarian Large White, Landrace, and Their Crossbred F1 Pigs from 2010 to 2018

Genetic parameters, breeding values, and aggregate breeding values of number of piglets born alive (NBA), number of weaned piglets (NWE), and litter weight at weaning (LWWE) were predicted in the Hungarian Large White, Hungarian Landrace breeds, and in their cross (F1). Seven repeatability animal models were used. BLUP and REML methodology were used to estimate breeding values and variance–covariance components. PEST and VCE 6 software were used for estimating breeding values and variance components. Heritability for NBA and NWE was the same for all seven models. On the contrary, heritability estimates for LWWE were higher in comparison with NBA and NWE. The permanent environmental variance component was small for all traits. The large White breed had positive and significant genetic trends for all seven models and for all three traits. Landrace breed had significant trends for NBA, which was negative, and for NWE, the results were positive. The constructed indices result in one number (i.e., aggregate genetic merit); thus, the animals can be selected based on their overall performance considering the various aspects.

Genetic parameters for linear conformation, stayability, performance and reproduction traits in German local Swabian-Hall landrace sows.

Improvements of longevity in sows are of overriding importance from an animal welfare as well as from an economic perspective, also in the local Swabian-Hall Landrace (SHL) breed. Consequently, the aim of the present study was a detailed assessment of linear conformation traits in the context of early predictions of sow stayability and to infer genetic (co)variance components between conformation traits with reproduction and performance traits. In this regard, we implemented a linear 9-point scoring system for conformation traits reflecting the body morphology and feet and leg characteristics in gilts. Linear conformation trait scoring included body length (BLEN), body height (BHEI), hind leg angularity (HLANG), hind leg pastern (HLPAS), hind cannon bone strength (HCBS), hind leg position (HLPOS), front leg position (FLPOS), claw length (CLEN) and muscling (MUSC) from 6042 SHL gilts before first insemination at the age of 180-200 days. For the same gilts, performance traits included average daily gain (ADG) and back fat thickness (BF) measured via ultrasound, reproduction traits included the number of piglets born alive (NBA) and the number of piglets weaned (NWEAN), and stayability was a binary trait reflecting sow survival after parity 2 (STAY_12), 3 (STAY_13) and 4 (STAY_14). For the estimation of variance components and heritabilities, single-trait linear animal models were defined for conformation, performance and reproduction traits, and single-trait generalized linear mixed models with a logit link function for binary stayability traits. Genetic covariances and correlations were inferred in series of bivariate runs for all combinations of conformation and remaining traits. The distribution of the assigned conformation scores reflected a Gaussian distribution, but a large fraction of records was assigned to the intermediate score classes 4, 5 and 6. Accordingly, the restricted utilization of the 9-point scale might explain the small genetic variances and small heritabilities for feet and leg traits in the range from 0.06 to 0.17. Heritabilities were larger for the linear traits reflecting body morphology, i.e., for BLEN (0.21) and BHEI (0.20). For conformation traits, the common litter environment explained up to 17% of the phenotypic trait variation. Genetic and especially phenotypic correlations between linear conformation traits with the reproduction traits NBA and NWEAN were close to zero. Heritabilities for STAY_12, STAY_13 and STAY_14 were 0.08, 0.07 and 0.05, respectively. Moderate genetic relationships were estimated between STAY_14 with some conformation traits. Especially high scores for BHEI and BLEN (i.e., long and large gilts) implied a decline in STAY_14 genetically (rg =-0.24 and -0.53, respectively). Moderate genetic correlations were estimated between HLANG with STAY_14 (0.28), and between HCBS with STAY_12 (0.23). For most of the conformation traits with intermediate optimum, genetic correlations with STAY were close to zero, indicating improved longevity for gilts representing the population average with scores 4, 5 or 6, and suggesting the development of appropriate selection indices in this regard.

Case Study on Increasing Breeding Value Estimation Reliability of Reproductive Traits in Serbian Highly Prolific Large White and Landrace Sows.

Simple SummaryIn the Republic of Serbia, pig selection in recent decades has been based on genetic improvement of growth and carcass quality traits. Genetic improvement of reproductive traits of pigs was based on the so-called phenotypic selection. The introduction of modern information systems and the availability larger dataset have opened the possibility to perform genetic estimation of reproductive traits within the main breeding programme of the Republic of Serbia. Using the methods of gene flow and connectedness evaluation, our study investigated the possibility of improving the reliability of estimating the breeding value of reproductive traits in highly productive sows. We believe that these methods could lead to a systematic improvement of the genetic value of reproductive traits in sows. Thus far, none of the methods for estimating the degree of connectedness between herds in pigs has been used in the preparation of the National Breeding Programme of the Republic of Serbia.This study investigated the influence of the degree of connectedness on the reliability of the estimated breeding values (EBVs). The focal trait in the study was the number of piglets born alive (NBA) from sows of the highly prolific Large White and Landrace sows. An analysis included total of 58,043 farrowing’s during the 2008–2020 period. BLUP procedure was used to estimate the breeding values for NBA for the three herds separately and after merging all three herds into one herd. The model for EBV estimation included the following fixed factors: parity, genotype, seasons, litter sire, herds, sow age at farrowing, weaning-conception interval, length of previous lactation, and the following random effects: common litter environment, permanent litter environment, and direct additive genetic effect of animal. Heritability values for NBA ranged from 0.048 to 0.097, depending on the data included in the analysis. The connectedness between herds was analysed using the connectedness rating (CR) and the gene flow (GF) methods. CR among the observed herds ranged from 0.245 to 0.994%, depending on the data included. The exchange of genetic material between all three herds was determined using GF method. The high degree of connectedness determined by the CR and GF method had a strong effect on EBV reliability. The average EBV reliability ranged from 0.520 to 0.867, depending on the data included. The increase in average reliability was observed in both cases when the data were added, both in the analysis of average reliability for purebred animals and when crossbreeds were added, where an increase in this value was also observed. The increase in average EBV reliability is a consequence of the greater amount of information included in the joint evaluation. In conclusion, we believe that our research will improve EBV reliability and help in further selection work in the Republic of Serbia.

Correlations between microsatellite DNA heterozygosity and reproductive traits in Large White sows

The main aim of this paper was to determine whether heterozygosity (assessed using microsatellite genotypes) was correlated with the reproductive traits in sows. The study was conducted on two herds of sows of the Large White sows breed at the Limited Liability Company “Tavriys’ki svyni” (Kherson region, Ukraine) and the Agricultural Private Enterprise “Techmet-Yug” (Mykolayiv region, Ukraine). During the study, we used eleven microsatellite loci recommended by International Society for Animal Genetics (ISAG) – S0101, S0155, S0228, S0355, S0386, Sw24, Sw72, Sw240, Sw857, Sw936 and Sw951. The litter records included information on the total number of piglets born (TNB), number of piglets born alive (NBA), number of stillborn piglets (NSB), frequency of stillborn piglets (FSB), litter size at weaning (NW) in the first five parities. Individual heterozygosity estimates (for each microsatellite loci separately) and microsatellite multilocus heterozygosity (for all used loci) estimates (MLH) were used in our analysis. ANOVA was used to determine the relationship of the dependent effects (reproductive traits) to single locus heterozygosity using two classes: 0 (for homozygous individuals) and 1 (for heterozygous individuals). In addition, the following indicators were calculated for each genotype: the squared distances (d2) between alleles within an individual for each microsatellite loci and mean squared distances (mean d2) between alleles within an individual for 11 microsatellite loci. Spearman’s rank correlation coefficients were used to measure the association between d2 (for each microsatellite loci) and reproductive traits in sows. ANOVA on reproductive traits of sows belonging to different MLH and mean d2 classes was also undertaken. For sows from the Agricultural Private Enterprise “‘Techmet-Yug” were observed negative associations between heterozygosity and reproductive traits. We conclude that care should be taken when crossing between different breeders (English and Hungarian selection) to avoid outbreeding depression.

Definition of Environmental Variables and Critical Periods to Evaluate Heat Tolerance in Large White Pigs Based on Single-Step Genomic Reaction Norms.

Properly quantifying environmental heat stress (HS) is still a major challenge in livestock breeding programs, especially as adverse climatic events become more common. The definition of critical periods and climatic variables to be used as the environmental gradient is a key step for genetically evaluating heat tolerance (HTol). Therefore, the main objectives of this study were to define the best critical periods and environmental variables (ENV) to evaluate HT and estimate variance components for HT in Large White pigs. The traits included in this study were ultrasound backfat thickness (BFT), ultrasound muscle depth (MDP), piglet weaning weight (WW), off-test weight (OTW), interval between farrowing (IBF), total number of piglets born (TNB), number of piglets born alive (NBA), number of piglets born dead (NBD), number of piglets weaned (WN), and weaning to estrus interval (IWE). Seven climatic variables based on public weather station data were compared based on three criteria, including the following: (1) strongest G×E estimate as measured by the slope term, (2) ENV yielding the highest theoretical accuracy of the genomic estimated breeding values (GEBV), and (3) variable yielding the highest distribution of GEBV per ENV. Relative humidity (for BFT, MDP, NBD, WN, and WW) and maximum temperature (for OTW, TNB, NBA, IBF, and IWE) are the recommended ENV based on the analyzed criteria. The acute HS (average of 30 days before the measurement date) is the critical period recommended for OTW, BFT, and MDP in the studied population. For WN, WW, IBF, and IWE, a period ranging from 34 days prior to farrowing up to weaning is recommended. For TNB, NBA, and NBD, the critical period from 20 days prior to breeding up to 30 days into gestation is recommended. The genetic correlation values indicate that the traits were largely (WN, WW, IBF, and IWE), moderately (OTW, TNB, and NBA), or weakly (MDP, BFT, and NBD) affected by G×E interactions. This study provides relevant recommendations of critical periods and climatic gradients for several traits in order to evaluate HS in Large White pigs. These observations demonstrate that HT in Large White pigs is heritable, and genetic progress can be achieved through genetic and genomic selection.

Infrared Thermography of the Mammary Gland in Sows with Regard to Health and Performance

Monitoring of sows’ health is the key to preventing and controlling diseases in sows, and it guarantees optimal rearing conditions for piglets. The aim of this study was to investigate the relationship between the health status of sows shortly after parturition, and to analyze thermographic images of the mammary gland and the sows’ performance. Clinical examination of a total of 513 db.Viktoria hybrid sows was bundled individually using a modified score system. According to this, animals were divided into three health classes: healthy, clinically suspicious, and diseased. Simultaneously, the mammary glands were investigated by infrared thermography. Total born piglets (TBP), number of piglets born alive (NBA), and the daily weight gain of the piglets were significantly lower in the diseased group (p &lt; 0.05). Regarding the results of the thermographic images of the mammary gland, significantly higher mean value of the warmest pixels was found in the diseased group (38.3 °C ± 0.57), while the significantly lowest value was reported in the healthy group (37.2 °C ± 0.54; p &lt; 0.05). The results of this study show that thermography of the mammary gland at birth contains information that can help to identify diseased animals whose disease has negative effects on their piglets.

PSIV-5 Definition of environmental variables and critical periods to evaluate heat tolerance in maternal-line pigs based on single-step genomic reaction norms

Abstract Heat stress (HS) is a major welfare and economic issue in the swine industry. However, it is not a trivial task to appropriately quantify the environmental HS. Therefore, this study aimed to 1) define the critical periods and environmental descriptors (based on public weather station information) to evaluate heat tolerance (HT); and 2) estimate genetic parameters for HT in Large White pigs. The traits included in this study were: weaning weight (WW; kg), off-test weight (OTW; kg), total number of piglets born (TNB), number of piglets born alive (NBA), and number of piglets weaned (WN). The number of phenotypic records ranged from 6,059 (WN) to 172,984 (TNB), and genotypes were available for 8,686 animals. Seven climatic variables (maximum, minimum and average temperatures, average relative humidity, dew point, discomfort index and temperature-humidity index) based on public weather station records were compared based on three criteria [GxE estimate as measured by the slope term; theoretical accuracy of the genomic estimated breeding values (GEBV); deviation of GEBV per environmental value]. Relative humidity (for WN and WW) and maximum temperature (for OTW, TNB, and NBA) are the recommended environmental gradients for the studied traits. The acute HS (average of 30 days before measurement date) was the critical period recommended for OTW. For WN and WW, a period of 34 days prior to farrowing up to weaning is recommended. For TNB and NBA, the critical period of 20 days prior breeding to 30 days into gestation is recommended. In general, WN and WW were largely affected by the environment, while the remaining traits showed moderate correlations (OTW, TNB, and NBA). Heritabilities estimated for HT ranged from 0.08 (WW) to 0.25 (OTW). In summary, these results suggest that there is genotype-by-environment interaction for all traits analyzed, and genetic progress can be achieved through genetic selection.

PSXV-9 Transgenerational epigenetic variance for production and reproduction traits in maternal-line pigs

Abstract Modeling epigenetic factors impacting phenotypic expression of economically important traits has become a hot-topic in the field of animal breeding due to the variability in genetic expression caused by environmental stressors (e.g., heat stress). This variability may be due, in part, to in-utero epigenomic remodeling, which has been reported to be passed from parent to offspring. We aimed to estimate transgenerational epigenetic variance for various production and reproduction traits measured in a maternal-line pig population, using a Bayesian approach. The phenotypes for production [n = 10,862; i.e., weaning weight (WW), birth weight (BW) and ultrasound-backfat thickness (BF)] and reproduction [n = 5,235, i.e., number of piglets born alive (NBA) and total number of piglets born (TB)] traits from a purebred Landrace population were provided by Smithfield Premium Genetics (NC, USA). The pedigree information traced back to 10 generations. Single-trait genetic analyses were performed using mixed models that included additive genetic, common environmental, and epigenetic random effects. The Gibbs sampler algorithm based on Markov chain Monte Carlo was used to estimate the variance components. The epigenetic relationship matrix was constructed using a recursive parameter (λ) related to the transmissibility coefficient of epigenetic markers. A grid search approach was used to define the optimal λ value (λ values ranged from 0.1 to 0.5, with an interval of 0.1). The optimal λ value was determined based on the deviance information criterion, and it was used to estimate the additive and epigenetic variances. For instance, based on preliminary results, the optimal λ value estimated for TB was 0.3 with an additive genetic variance of 0.94 (0.19 PSD) and epigenetic variance of 0.67 (0.18 PSD). The additive genetic heritability was 0.076 (0.015 PSD) and the estimated epigenetic heritability was 0.053 (0.015 PSD). This preliminary result suggests that epigenetics contribute to the non-Mendelian variability in pigs.

Effect of dam parity on the reproductive performance of Nigeria indigenous sows and progeny survivability rates in Enugu State, South Eastern Nigeria

The effects of parity on the reproductive performance of Nigerian indigenous sow breed, progeny survivability and mortality in a commercial breeding farm in Enugu State Nigeria were investigated in this study. One hundred apparently healthy third trimester pregnant sows were randomly assigned to four treatment groups of twenty five sows per group in a completely randomized design (CRD) according to their reproductive parities as groups I, II, III and IV representing the first (P1), second (P2), third (P3) and fourth (P4) parities respectively. This study lasted for two years. The mean number of piglets born alive (NBA) of P1 (6.00±0.71 Head) and P2 (6.00±0.71 Head) were significantly decreased when compared to P4 (8.50±0.65 Head) but showed no significant difference when compared to P3 (7.50±0.50 Head). Second parity sows recorded the highest number of piglets’ deaths after birth while P1 and P3 litters recorded the lowest deaths after birth. Mean pre-weaning survival of progenies was highest in P3 (91.43±5.09 %) and lowest in P2 (84.38±11.83 %) while mean piglet mortality was highest in P2 (15.63±11.83 %) but lowest in P3 (8.57±5.09 %). It can be concluded from this research work that PIII sows provided adequate requirements necessary for their litter nourishment, growth and survival more than the other parities. Therefore progeny growth performance was best at third parity of reproduction.

Genome-wide epistatic interactions of litter size at birth in Chinese indigenous pigs.

Improving litter size at birth (TNB) and the number of piglets born alive (NBA) are the main breeding goals related to litter traits, which are economically important. A better understanding of genetic architecture underlying TNB and NBA traits could increase pig production efficiency. However, most previous studies on these traits focus on additive genetic effects, while epistatic interactions underlying TNB and NBA traits has not yet been well investigated, which are essential to understand how traits-related genes interact. Herein, we conducted genome scans of epistatic interactions underlying TNB and NBA traits in a total of 150 Chinese indigenous pigs (75 Jinhua and 75 Shengxian Spotted pigs) with high throughput genomic data. Based on SNPs with high interaction values and connectivity scores, we identified eight promising candidate genes (AKT2, TSC1, MTOR, PIK3R5, TIAM1, FGF14, RALB and ROR2) potentially associated with litter traits in pigs. Moreover, the underlying pathways, e.g., calcium ion transport, pointed out their roles in litter size-related traits. Our findings provide new insight into genetic architecture of litter traits in pigs and will benefit economic profits in pig production.

127 Antibody Response as an Indicator Trait for Improved Reproductive Performance During a PRRSV Outbreak: Genetic Correlations of S/P Ratio with Reproductive Traits in Landrace and Duroc Sows

Abstract Previous studies proposed the use of antibody response to Porcine Reproductive and Respiratory Syndrome virus (PRRSV), measured as sample-to-positive (S/P) ratio, as a potential indicator trait to improve the reproductive performance of PRRSV-infected Landrace sows. However, this indicator trait has not yet been validated in Landrace sows or evaluated in a terminal sire line, such as Duroc. The main objective of this work was to perform host-genetic analyses of S/P ratio and reproductive traits during a PRRSV outbreak in maternal and terminal breeds. The data consisted of 690 Duroc and 541 Landrace multiparous sows (1.9±1.2 and 2.3±1.5, respectively) with S/P ratio collected at approximately 54 days after the predicted beginning of the outbreak. Of these, 644 Duroc and 528 Landrace sows also had reproductive data recorded during the PRRSV outbreak comprising number of piglets born alive (NBA), stillborn piglets (NSB), mummified piglets (NBM), number born dead (NBD; sum of NSB and NBM), total number born (TNB; sum of NBA and NBD), and number weaned (NW). All animals had genotype data on ~30K SNPs common across both breeds. Heritability estimates (± standard error) of S/P ratio during the PRRSV outbreak were moderate, with 0.33±0.06 for Duroc and 0.28±0.07 for Landrace. Reproductive traits during the PRRSV outbreak had overall low heritability estimates (≤0.18). Favorable genetic correlations of S/P ratio with NBA (0.65±0.33), in accordance with previous studies, and NBD (-0.33±0.28) were observed for Landrace sows only. Estimates of genetic correlation with other traits were -0.21±0.30 (NBM), -0.12±0.29 (NSB), 0.10±0.38 (NW), and 0.54±1.29 (TNB) for Landrace. For Duroc, these estimates were weaker: -0.33±0.40 (NBA), 0.26±0.27 (NBA), and 0.28±0.30 (NW), with convergence issues for mortality traits. These results further support the use of S/P ratio as an indicator trait for improved reproductive performance during a PRRSV outbreak in Landrace sows.

128 Differences in PRRSV Resilience for Reproductive Performance Between Landrace and Duroc Sows

Abstract Studies on differences in resilience to porcine reproductive and respiratory syndrome (PRRS) virus (PRRSV) between breeds are scarce in the literature. Thus, the objective of this work was to assess PRRSV resilience in PRRSV wild-type infected sows from two breeds. Farrowing data included 2546 and 2522 litters from 894 Duroc and 813 Landrace sows, respectively, which were housed together and experienced the same PRRSV outbreak. Traits used for this study were number of piglets born alive (NBA), number born dead (NBD), total number born (TNB), and number weaned (NW). The impact of PRRSV infection was evaluated by comparing the reproductive performance of breeds between PRRS phases (pre-PRRS, PRRS, and post-PRRS). PRRS phases were defined based on the reproductive performance data. NBA, NBD, and NW were analyzed as a proportion of TNB using a Poisson mixed model. Pre-defined contrasts were used to evaluate the effect of breed on PRRSV resilience and on return to PRRSV-free performance, representing the differences between breeds for the difference between pre-PRRS and PRRS phases, and pre-PRRS and post-PRRS phases, respectively. There was a significant (P ≤ 0.003) interaction between PRRS phase and breed for all traits, as shown in Table 1. In general, reproductive performance reduced from pre-PRRS to PRRS, and then increased from PRRS to post-PRRS, as expected. The resilience contrast was significant for all traits (P ≤ 0.003). In all cases, the drop in percent reproductive performance from pre-PRRS to PRRS was lower for Duroc than for Landrace, indicating that Duroc sows have greater PRRSV resilience than Landrace sows. The return to PRRSV-free performance contrast had a trending effect for NBD (P = 0.055), and it was not significant for the other traits (P ≥ 0.515). These results indicate that Duroc sows have overall greater phenotypic PRRSV resilience for reproductive performance than Landrace sows.