Selection for increased number of piglets at d 5 after farrowing has increased litter size and reduced piglet mortality

The Effect of Sow Maternal Behavior on the Growth of Piglets and a Genome-Wide Association Study

Sows' maternal behavior is important for improving piglet survival and growth; thus, breeding for good mothering sows is necessary for pig production. However, there is little research on the genetic mechanism of maternal behavior. In this study, a comparative analysis of piglets' growth traits between good and bad maternal behavior groups and a genome-wide association study (GWAS) was performed to elucidate the impact of sows' maternal behavior on piglet growth and identify candidate genes and markers of sow's maternal behaviors. Comparing the growth traits of piglets between good and bad sows' maternal behavior groups, the results showed that the growth traits of piglets from sows with good maternal behavior were better than those from sows with bad maternal behavior and especially for the multiparous sows group, this comparative difference was significant. For the intensive study of the genetic mechanisms of sows' maternal behavior, a total of 452 sows were genotyped using the Illumina Porcine 50K SNP Chip, and 4 traits, including biting piglets (BP), crushing piglets (CP), trampling piglets (TP) and screaming test (ST), were examined. Using a GWAS, 20 single nucleotide polymorphisms (SNPs) were found to be associated with these traits. Within 1 Mb upstream and downstream of the significant SNPs screened, 138 genes were obtained. After pathway enrichment and gene annotation, HIP1, FZD9 and HTR7 were identified as important candidate genes affecting sows' maternal behaviors. These findings preliminarily elucidate the genetic basis of sows' maternal behavior traits and provide candidate genes and markers for molecular breeding in pigs.

Introgression of pigs in Taihu Lake region possibly contributed to the improvement of fertility in Danish Large White pigs

BACKGROUND

Eurasian pigs have undergone lineage admixture throughout history. It has been confirmed that the genes of indigenous pig breeds in China have been introduced into Western commercial pigs, providing genetic materials for breeding Western pigs. Pigs in Taihu Lake region (TL), such as the Meishan pig and Erhualian pig, serve as typical representatives of indigenous pig breeds in China due to their high reproductive performances. These pigs have also been imported into European countries in 1970 and 1980 s. They have played a positive role in improving the reproductive performances in European commercial pigs such as French Large White pigs (FLW). However, it is currently unclear if the lineage of TL pigs have been introgressed into the Danish Large White pigs (DLW), which are also known for their high reproductive performances in European pigs. To systematically identify genomic regions in which TL pigs have introgressed into DLW pigs and their physiological functions, we collected the re-sequencing data from 304 Eurasian pigs, to identify shared haplotypes between DLW and TL pigs.

RESULTS

The findings revealed the presence of introgressed genomic regions from TL pigs in the genome of DLW pigs indeed. The genes annotated within these regions were found to be mainly enriched in neurodevelopmental pathways. Furthermore, we found that the 115 kb region located in SSC16 exhibited highly shared haplotypes between TL and DLW pigs. The major haplotype of TL pigs in this region could significantly improve reproductive performances in various pig populations. Around this genomic region, NDUFS4 gene was highly expressed and showed differential expression in multiple reproductive tissues between extremely high and low farrowing Erhualian pigs. This suggested that NDUFS4 gene could be an important candidate causal gene responsible for affecting the reproductive performances of DLW pigs.

CONCLUSIONS

Our study has furthered our knowledge of the pattern of introgression from TL into DLW pigs and the potential effects on the fertility of DLW pigs.

Genome-wide association study using a single-step approach for teat number in Duroc, Landrace and Yorkshire pigs in Korea

We investigated the genetic basis of teat number in sows, which is an important factor in their reproductive performance. We collected genotyping data from 20 353 pigs of three breeds (Duroc, Landrace and Yorkshire) using the Porcine SNP60K Bead Chip, and analyzed phenotypic data from 240 603 pigs. The heritability values of total teat number were 0.33 ± 0.02, 0.51 ± 0.01 and 0.50 ± 0.01 in Duroc, Landrace and Yorkshire pigs, respectively. A genome-wide association study was used to identify significant chromosomal regions associated with teat number in SSC7 and SSC9 in Duroc pig, SSC3, SSC7 and SSC18 in Landrace pig, and SSC7, SSC8 and SSC10 in Yorkshire pig. Among the markers, MARC0038565, located between the vertnin (VRTN) and synapse differentiation-inducing 1-like (SYNDIG1L) genes, showed the strongest association in the Duroc pig and was significant in all breeds. In Landrace and Yorkshire pigs, the most significant markers were located within the apoptosis resistant E3 ubiquitin protein ligase 1 (AREL1) and latent transforming growth factor beta-binding protein 2 (LTBP2) genes in SSC7, respectively. VRTN is a candidate gene regulating the teat number. Most markers were located in SSC7, indicating their significance in determining teat number and their potential as valuable genomic selection targets for improving this trait. Extensive linkage disequilibrium blocks were identified in SSC7, supporting their use in genomic selection strategies. Our study provides valuable insights into the genetic architecture of teat numbers in pigs, and helps identify candidate genes and genomic regions that may contribute to this economically important trait.

Selecting the optimal strategies when using nurse sows for supernumerous piglets

Hyper-prolific sows frequently do not have a sufficient number of functional teats for their piglets to nurse which has led to the use of nurse sows to manage these surplus piglets. This review discusses strategies for using nurse sows and factors that influence preweaning survival and weight gain of their litters, as well as those that affect their subsequent rebreeding performance. Rearing piglets using a nurse sow can be as successful as piglets reared with their biological mother and is thus a powerful management tool to decrease preweaning piglet mortality. Selecting a young sow as nurse sow is beneficial for piglet survival; however, piglets nursing first parity sows often have a lower daily weight gain than piglets nursing multiparous sows. A litter of uniform surplus piglets is preferably handled using the two-step nurse sow strategy. A consequence of nonuniform litters will most likely be an increased mortality and decreased weaning weight among the smallest piglets within a litter. The subsequent fertility of nurse sows is not compromised. There is an increased risk of lactational oestrus when using nurse sows leading to an increased weaning-to-oestrus interval; however, litter size in nurse sows is identical or even moderately higher in the subsequent parity compared with nonnurse sows.

Genetic parameters for early piglet weight, litter traits and number of functional teats in organic pigs

Knowledge remains limited on genetic variation and genetic correlations for traits in sows and piglets that are reared in an organic or outdoor setting. Here, we estimated genetic variance components for individual piglet weight, litter weight, litter size traits, and number of functional teats in a pig population raised under outdoor organic conditions. Data were collected from the largest organic multiplier farm in Denmark. Individual piglet weight was recorded at birth and on day 10. Number of live and dead piglets were recorded at birth, day 4, and day 11. Mean and total litter weight were calculated based on the individual weight of living piglets at birth and on day 10. The estimated heritability was highest for the number of functional teats (0.49), mean weight of a litter at birth (0.33) and on day 10 (0.25). In contrast, heritability was lowest for litter size traits (0.04-0.08) and piglet weight (0.06-0.07). Maternal heritability was much higher for individual piglet weight than direct heritability. The results showed that selection for higher mean weight results in smaller litters. Also, selection for individual birth weight of piglets results in heavier piglets at 10 days. In conclusion, this study confirmed that there is genetic variation in individual piglet weight, litter traits, and number of functional teats in organically and outdoor-reared pigs.

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

Simple Summary

Breeders 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.

Abstract

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.

Genetic aspects of piglet survival and related traits: a review

In livestock, mortality in general, and mortality of the young, is societal worries and is economically relevant for farm efficiency. Genetic change is cumulative; if it exists for survival of the young and genetic merit can be estimated with sufficient accuracy, it can help alleviate the pressure of mortality. Lack of survival is a moving target; livestock production is in continuous change and labor shortage is a given. There is now ample evidence of clear genetic variance and of models able to provide genomic predictions with enough accuracy for selection response. Underlying traits such as birth weight, uniformity in birth weight, gestation length, number of teats, and farrowing duration all show genetic variation and support selection for survival or, alternatively, be selected for on their own merit.

Genomic evaluation and genome-wide association studies for total number of teats in a combined American and Danish Yorkshire pig populations selected in China

Joint genomic evaluation by combining data recordings and genomic information from different pig herds and populations is of interest for pig breeding companies because the efficiency of genomic selection (GS) could be further improved. In this work, an efficient strategy of joint genomic evaluation combining data from multiple pig populations is investigated. Total Teat Number (TTN), a trait that is equally recorded on 13 060 American Yorkshire (AY) populations (~14.68 teats) and 10 060 Danish Yorkshire (DY) pigs (~14.29 teats), was used to explore the feasibility and accuracy of GS combining datasets from different populations. We first estimated the genetic correlation (rg) of TTN between AY and DY pig populations (rg=0.79, se=0.23). Then we employed the genome-wide association study (GWAS) to identify QTL regions that are significantly associated with TTN and investigate the genetic architecture of TTN in different populations. Our results suggested that the genomic regions controlling TTN are slight different in the two Yorkshire populations, where the candidate QTL regions were on SSC 7 and SSC 8 for AY population and on SSC 7 for DY population. Finally, we explored an optimal way of genomic prediction for TTN via three different Genomic Best Linear Unbiased Prediction (GBLUP) models and we concluded that when TTN across populations are regarded as different, but correlated, traits in a multi-trait model, predictive abilities for both Yorkshire populations improve. As a conclusion, joint genomic evaluation for target traits in multiple pig populations is feasible in practice and more accurate, provided a proper model is used.

Genetic variation in piglet mortality in outdoor organic production systems

Piglet mortality from farrowing to weaning is a major concern, especially in outdoor organic production systems. This issue might impair animal welfare and generate economic losses for the farmer. In particular, it is difficult to apply management tools that are commonly used for indoor pig production systems to organic or outdoor production systems. Genetics and breeding approaches might be used to improve piglet survival. However, knowledge remains limited on the genetic background underlying survival traits in organic pigs that are born and reared outdoors. Here, we investigated the mortality of piglets from farrowing to weaning in an outdoor organic pig population and suggested genetic strategies to reduce piglet mortality in this production system. The experiment included mortality records of piglets from farrowing to weaning (around 69 days of age). Pedigree-based threshold models were used to analyse the mortality traits of piglets at 0-3 days of age, 4-11 days, and 12 days to weaning. Stillborn piglets were included in the group of piglets that died at 0-3 days of age. We found that the mortality rate from farrowing to weaning was, on average, 19.2%. However, most piglet deaths (79.1%) occurred at 0-11 days of age. As the age of piglets increased, the direct heritability of piglet mortality rose from 0 to 0.04, whereas maternal heritability decreased from 0.03 to a non-significant value. Piglets with higher BW had a lower mortality rate. However, the genetic correlations between maternal effects on piglet mortality and piglet BW were not significant; thus, selection for piglets with higher BW at around 10 days of age, through improving maternal genetics, would not reduce piglet mortality. Piglet mortality increased from sows with increasing number of parities. Crossbreeding also reduced piglet mortality. In conclusion, selection focusing on sow genotype, the use of younger sows, and crossbreeding could contribute to maintain piglet mortality at lower levels in outdoor organic pig production systems.

How much energetic trade-offs limit selection? Insights from livestock and related laboratory model species

Trade-offs between life history traits are expected to occur due to the limited amount of resources that organisms can obtain and share among biological functions, but are of least concern for selection responses in nutrient-rich or benign environments. In domestic animals, selection limits have not yet been reached despite strong selection for higher meat, milk or egg yields. Yet, negative genetic correlations between productivity traits and health or fertility traits have often been reported, supporting the view that trade-offs do occur in the context of nonlimiting resources. The importance of allocation mechanisms in limiting genetic changes can thus be questioned when animals are mostly constrained by their time to acquire and process energy rather than by feed availability. Selection for high productivity traits early in life should promote a fast metabolism with less energy allocated to self-maintenance (contributing to soma preservation and repair). Consequently, the capacity to breed shortly after an intensive period of production or to remain healthy should be compromised. We assessed those predictions in mammalian and avian livestock and related laboratory model species. First, we surveyed studies that compared energy allocation to maintenance between breeds or lines of contrasting productivity but found little support for the occurrence of an energy allocation trade-off. Second, selection experiments for lower feed intake per unit of product (i.e. higher feed efficiency) generally resulted in reduced allocation to maintenance, but this did not entail fitness costs in terms of survival or future reproduction. These findings indicate that the consequences of a particular selection in domestic animals are much more difficult to predict than one could anticipate from the energy allocation framework alone. Future developments to predict the contribution of time constraints and trade-offs to selection limits will be insightful to breed livestock in increasingly challenging environments.

Effect of within-litter birth weight variation after cross-fostering on piglet preweaning growth and mortality

Cross-fostering is commonly used in commercial swine production to equalize litter sizes and/or adjust piglet birth weights within litters. However, there is limited published information on optimum cross-fostering procedures. This study evaluated the effects of within-litter birth weight variation after cross-fostering (using litters of 14 piglets) on piglet preweaning mortality (PWM) and weaning weight (WW). An RCBD was used (blocking factors were day of farrowing and sow parity, body condition score, and functional teat number) with an incomplete factorial arrangement of the following two treatments: 1) birth weight category (BWC): light (<1.0 kg), medium (1.0 to 1.5 kg), or heavy (1.5 to 2.0 kg); 2) litter composition: uniform, all piglets in the litter of the same BWC [uniform light (14 light piglets); uniform medium (14 medium piglets); uniform heavy (14 heavy piglets)]; mixed, piglets in the litter of two or more BWC [L+M (seven light and seven medium piglets); M+H (seven medium and seven heavy piglets); L+M+H (three light, six medium, and five heavy piglets)]. Piglets were weighed at 24 h after birth and randomly allotted to litter composition treatment from within BWC; all piglets were cross-fostered. There were 47 blocks of six litters (total 282 litters and 3,948 piglets). Weaning weights were collected at 18.7 ± 0.64 d of age; all PWM was recorded. Individual piglet WW and PWM data were analyzed using PROC MIXED and PROC GLIMMIX of SAS, respectively; models included fixed effects of BWC, litter composition, and the interaction, and random effects of sow within the block. There was litter composition by BWC interactions (P ≤ 0.05) for WW and PWM. Within each BWC, WW generally increased and PWM generally decreased as littermate weight decreased. For example, WW was greatest (P ≤ 0.05) for light piglets in uniform light litters, for medium piglets in L+M litters, and for heavy piglets in L+M+H litters. Preweaning mortality was lowest (P ≤ 0.05) for medium piglets in L+M litters, and for heavy piglets in L+M+H litters; however, litter composition had no effect (P > 0.05) on PWM of light piglets. In conclusion, increasing the average birth weight of littermates after cross-fostering generally decreased WW and increased PWM for piglets of all birth weight categories. This implies that the optimum approach to cross-fostering that maximizes piglet preweaning growth and survival is likely to vary depending on the birth weight distribution of the population.

Revealing New Candidate Genes for Teat Number Relevant Traits in Duroc Pigs Using Genome-Wide Association Studies

Simple Summary

Number of teats is very important for lactating sows. We conducted genome-wide association studies (GWAS) and estimated the genetic parameters for traits related to teat number. Results showed that there were nine and 22 SNPs exceeding genome-wide significance and suggestive significance levels, respectively. Eighteen genes annotated near them were concentrated on chromosomes 7 and 10. Among them, three new candidate genes were located on the genomic regions around the significant SNPs. Our findings provide new insight into investigating the complex genetic mechanism of traits related to teat number in pigs.

Abstract

The number of teats is related to the nursing ability of sows. In the present study, we conducted genome-wide association studies (GWAS) for traits related to teat number in Duroc pig population. Two mixed models, one for counted and another for binary phenotypic traits, were employed to analyze seven traits: the right (RTN), left (LTN), and total (TTN) teat numbers; maximum teat number on a side (MAX); left minus right side teat number (LR); the absolute value of LR (ALR); and the presence of symmetry between left and right teat numbers (SLR). We identified 11, 1, 4, 13, and 9 significant SNPs associated with traits RTN, LTN, MAX, TTN, and SLR, respectively. One significant SNP (MARC0038565) was found to be simultaneous associated with RTN, LTN, MAX and TTN. Two annotated genes (VRTN and SYNDIG1L) were located in genomic region around this SNP. Three significant SNPs were shown to be associated with TTN, RTN and MAX traits. Seven significant SNPs were simultaneously detected in two traits of TTN and RTN. Other two SNPs were only identified in TTN. These 13 SNPs were clustered in the genomic region between 96.10—98.09 Mb on chromosome 7. Moreover, nine significant SNPs were shown to be significantly associated with SLR. In total, four and 22 SNPs surpassed genome-wide significance and suggestive significance levels, respectively. Among candidate genes annotated, eight genes have documented association with the teat number relevant traits. Out of them, DPF3 genes on Sus scrofa chromosome (SSC) 7 and the NRP1 gene on SSC 10 were new candidate genes identified in this study. Our findings demonstrate the genetic mechanism of teat number relevant traits and provide a reference to further improve reproductive performances in practical pig breeding programs.

Sex-Specific Survival, Growth, Immunity and Organ Development in Preterm Pigs as Models for Immature Newborns

Background: After very preterm birth, male infants show higher mortality than females, with higher incidence of lung immaturity, neurological deficits, infections, and growth failure. In modern pig production, piglets dying in the perinatal period (up to 20%) often show signs of immature organs, but sex-specific effects are not clear. Using preterm pigs as model for immature infants and piglets, we hypothesized that neonatal survival and initial growth and immune development depend on sex. Methods: Using data from a series of previous intervention trials with similar delivery and rearing procedures, we established three cohorts of preterm pigs (90% gestation), reared for 5, 9, or 19 days before sample collection (total n = 1,938 piglets from 109 litters). Partly overlapping endpoints among experiments allowed for multiple comparisons between males and females for data on mortality, body and organ growth, gut, immunity, and brain function. Results: Within the first 2 days, males showed higher mortality than females (18 vs. 8%, P < 0.001), but less severe immune response to gram-positive infection. No effect of sex was observed for thermoregulation or plasma cortisol. Later, infection resistance did not differ between sexes, but growth rate was reduced for body (up to -40%) and kidneys (-6%) in males, with higher leucocyte counts (+15%) and lower CD4 T cell fraction (-5%) on day 9 and lower monocyte counts (-18%, day 19, all P < 0.05). Gut structure, function and necrotizing enterocolitis (NEC) incidence were similar between groups, but intestinal weight (-3%) and brush-border enzyme activities were reduced at day 5 (lactase, DPP IV, -8%) in males. Remaining values for blood biochemistry, hematology, bone density, regional brain weights, and visual memory (tested in a T maze) were similar. Conclusion: Following preterm birth, male pigs show higher mortality and slower growth than females, despite limited differences in organ growth, gut, immune, and brain functions. Neonatal intensive care procedures may be particularly important for compromised newborns of the male sex. Preterm pigs can serve as good models to study the interactions of sex- and maturation-specific survival and physiological adaptation in mammals.

Inferring phenotypic causal structure among farrowing and weaning traits in pigs

Direct selection for litter size or weight at weaning in pigs is often hindered by external interventions such as cross-fostering. The objective of this study was to infer the causal structure among phenotypes of reproductive traits in pigs to enable subsequent direct selection for these traits. Examined traits included: number born alive (NBA), litter size on day 21 (LS21), and litter weight on day 21 (LW21). The study included 6,240 litters from 1,673 Landrace dams and 5,393 litters from 1,484 Large White dams. The inductive causation (IC) algorithm was used to infer the causal structure, which was then fitted to a structural equation model (SEM) to estimate causal coefficients and genetic parameters. Based on the IC algorithm and temporal and biological information, the causal structure among traits was identified as: NBA → LS21 → LW21 and NBA → LW21. Owing to the causal effect of NBA on LS21 and LW21, the genetic, permanent environmental, and residual variances of LS21 and LW21were much lower in the SEM than in the multiple-trait model for both breeds. Given the strong effect of NBA on LS21 and LW21, the SEM and causal information might assist with selective breeding for LS21 and LW21 when cross-fostering occurs.

Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding

Genomic breeding programs have been paramount in improving the rates of genetic progress of productive efficiency traits in livestock. Such improvement has been accompanied by the intensification of production systems, use of a wider range of precision technologies in routine management practices, and high-throughput phenotyping. Simultaneously, a greater public awareness of animal welfare has influenced livestock producers to place more emphasis on welfare relative to production traits. Therefore, management practices and breeding technologies in livestock have been developed in recent years to enhance animal welfare. In particular, genomic selection can be used to improve livestock social behavior, resilience to disease and other stress factors, and ease habituation to production system changes. The main requirements for including novel behavioral and welfare traits in genomic breeding schemes are: (1) to identify traits that represent the biological mechanisms of the industry breeding goals; (2) the availability of individual phenotypic records measured on a large number of animals (ideally with genomic information); (3) the derived traits are heritable, biologically meaningful, repeatable, and (ideally) not highly correlated with other traits already included in the selection indexes; and (4) genomic information is available for a large number of individuals (or genetically close individuals) with phenotypic records. In this review, we (1) describe a potential route for development of novel welfare indicator traits (using ideal phenotypes) for both genetic and genomic selection schemes; (2) summarize key indicator variables of livestock behavior and welfare, including a detailed assessment of thermal stress in livestock; (3) describe the primary statistical and bioinformatic methods available for large-scale data analyses of animal welfare; and (4) identify major advancements, challenges, and opportunities to generate high-throughput and large-scale datasets to enable genetic and genomic selection for improved welfare in livestock. A wide variety of novel welfare indicator traits can be derived from information captured by modern technology such as sensors, automatic feeding systems, milking robots, activity monitors, video cameras, and indirect biomarkers at the cellular and physiological levels. The development of novel traits coupled with genomic selection schemes for improved welfare in livestock can be feasible and optimized based on recently developed (or developing) technologies. Efficient implementation of genetic and genomic selection for improved animal welfare also requires the integration of a multitude of scientific fields such as cell and molecular biology, neuroscience, immunology, stress physiology, computer science, engineering, quantitative genomics, and bioinformatics.

A probabilistic Poisson-based model to detect PRRSV recirculation using sow production records

Porcine reproductive and respiratory syndrome (PRRS) is a viral disease associated with a decrease in the number of born alive piglets (NBA) and an increase in the number of lost piglets (NLP) per farrowing. Under practical conditions, it is critical to assess whether a farm is suffering PRRSV recirculation in the sow herd as soon as possible. The aim of this research work was to develop a new method to detect potential PRRSV recirculation in sow production farms. Sow reproductive performance records from one farm (farm T) were used to set up the method and records from ten additional farms (farms V1 to V10) were used for validation. A conditional Poisson model of NLP on NBA was proposed to fit the data. A three-step procedure was implemented to detect potential PRRSV recirculation: (i) computation of the maximum-likelihood estimates of the expected values of NBA and NLP in a PRRSV non-recirculating scenario; (ii) calculation, for each farrowing, of the p-value associated with the probability of jointly observing deviations towards decreased NBA and increased NLP. The detection of a potential PRRSV recirculation was based on (iii) the combined p-value resulting from weighing the p-values of the last N farrowings by the chi-square-inverse method. In order to gain specificity, a displacement on the expected non-recirculating NBA and NLP values was used for tuning purposes. With this approach, two PRRSV circulating periods were detected in farm T, which were confirmed with standard laboratorial diagnostic techniques. The method was subsequently validated in farms V1 to V10, where ten PRRSV-recirculating time episodes had been diagnosed. The method proposed here was able to detect the ten PRRSV recirculations using a relatively small set of contiguous farrowings, with only two mismatched weeks, one as a false negative, in farm V1, and one as a false positive, in farm V4. It is concluded that a conditional Poisson-based model of NLP on NBA can be a useful tool for routinely detecting PRRSV recirculation in sow herds.

Association of Rs339939442 in the AHR Gene with Litter Size are Inconsistent among Chinese Indigenous Pigs and Western Commercial Pigs

Eastern and Southern Chinese pigs have been imported to Western countries to improve economic traits including fertility in Western pig breeds by intensive selecting Chinese advantage genes. It was reported that the selected Asian-derived non-synonymous mutations including rs339939442 (G > T) in the aryl hydrocarbon receptor (AHR) gene could increase litter size in multiple European commercial lines. The objective of this study is to identify whether rs339939442 in the AHR gene is polymorphic and has an influence on the litter size in 10 pig populations including five Chinese indigenous breeds, one cultivated breed, one lean-type breed, two North American lean-type breeds, and one European lean-type breed. We found that rs339939442 had polymorphism in all 10 populations, whereas rs339939442 was associated with litter size only in French Yorkshire (FRA-Y) and Chinese cultivated Suhuai (SH) pigs containing approximately 75% British Yorkshire pigs ancestry. Our results indicated that rs339939442 in the AHR gene was a potential marker to improve litter size in European commercial lines and the pigs containing ancestries of European commercial lines, whereas this locus maybe not a causal mutation affecting the litter size but only in linkage disequilibrium with the causal mutation for litter size.

Comparison of reproductive performances of local and improved pigs reared in south Benin

Benin's domestic production of pork is deficient because of the animals' low productivity. This study aimed to evaluate the zootechnical performances of pigs reared in south Benin. Data on zootechnical performances and reproduction management were collected from 63 farms in the departments of Ouémé and Plateau. These data were analyzed with SAS software, and the Fisher test was used for the significance of the breed, sex, and parity number effect on the zootechnical performances. It appears that estrus detection was mainly based on the observation of signs of vulvar changes and behavior of the sow. These estruses were detected at any time and without the boar. The local sows were mated as soon as estruses were detected while improved sows were mated 36 h after. The pregnancy detection was performed by control of return of estrus, 21 days after the mating by the majority (80.6%) of the respondents. The litter size, the number of piglets born alive, and the weaned piglets of improved sows were significantly higher (P < 0.001) than those of local sows. These parameters increased with the parity number until the 4th parity and decreased after. The litter size was highly correlated with the number of piglets born alive and weaned piglets. The farrowing interval was longer in local sows than in improved sows. The weights at birth, at 1 and 2 months old of improved piglets, were significantly higher than those of local piglets (P < 0.001). The knowledge of these performances will allow actions to be taken for their improvement.

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.

Duroc boars have lower progeny mortality and lower fertility than Pietrain boars

In pig production, Pietrain and Duroc lines are often used as terminal sire lines to produce crossbred slaughter pigs. The objective of this study was to identify the differences in paternal fertility and mortality during the suckling period of crossbred progeny from Pietrain and Duroc terminal sire lines. In total, 87 purebred Duroc boars and 68 purebred Pietrain boars were used as terminal sires to produce 1,823 crossbred Duroc litters (D-litters) and 1,705 crossbred Pietrain litters (P-litters) in two production herds. The sows were crosses between DanBred Landrace and Yorkshire (F1). All boars were kept at the same artificial insemination (AI) station, and all semen doses were produced in the same laboratory. The experiment was balanced according to herd, boars, and time, with approximately 13 sows from each herd mated to each boar within each breed. The results showed higher fertility expressed as litter size at birth in P-litters compared with D-litters led to 0.5 higher total number born (TNB) for P-litters (P = 0.0076). However, piglet mortality including number of stillborn piglets was lower in D-litters compared with P-litters (P < 0.0001), and 5 d after farrowing, the average litter size in P-litters ranged 0.4 below the litter size in D-litters (P < 0.027). At 21 d after birth, mean litter size in P- and D-litters were 14.5 and 14.9 piglets per litter, respectively (P < 0.015). This indicated that Pietrain progenies were weaker than Duroc progenies, and it was concluded that use of Duroc boars as the terminal sire line led to lower piglet mortality. In the two herds, the mean piglet mortality rate including still born piglets ranged from 19.5% to 23.6% and from 17.6% to 19.1% in P- and D-litters, respectively.

Invited review: Piglet survival: benefits of the immunocompetence

Piglet mortality has a negative impact on animal welfare and public acceptance. Moreover, the number of weaned piglets per sow mainly determines the profitability of piglet production. Increased litter sizes are associated with lower birth weights and piglet survival. Decreased survival rates and performance of piglets make the control of diseases and infections within pig production even more crucial. Consequently, selection for immunocompetence becomes an important key aspect within modern breeding programmes. However, the phenotypic recording of immune traits is difficult and expensive to realize within farm routines. Even though immune traits show genetic variability, only few examples exist on their respective suitability within a breeding programme and their relationships to economically important production traits. The analysis of immune traits for an evaluation of immunocompetence to gain a generally improved immune response is promising. Generally, in-depth knowledge of the genetic background of the immune system is needed to gain helpful insights about its possible incorporation into breeding programmes. Possible physiological drawbacks for enhanced immunocompetence must be considered with regards to the allocation theory and possible trade-offs between the immune system and performance. This review aims to discuss the relationships between the immunocompetence of the pig, piglet survival as well as the potential of these traits to be included into a breeding strategy for improved robustness.

Hypomethylation in the promoter region of ZPBP as a potential litter size indicator in Berkshire pigs

In pigs, litter size is typically defined as the total number of piglets born (TNB) or the number of piglets born alive (NBA). Increasing pig litter size is of great economic interest as a means to increase productivity. The capacity of the uterus is a critical component of litter size and may play a central role in prolificacy. In this study, we investigated litter-size-related epigenetic markers in uterine tissue from Berkshire pigs with smaller litter size groups (SLGs) and larger litter size groups (LLGs) using genome-wide bisulfite sequencing (GWBS). A total of 3269 differentially methylated regions (DMRs) were identified: 1566 were hypermethylated and 1703 hypomethylated in LLG compared to SLG. The zona pellucida binding protein (ZPBP) gene was significantly hypomethylated in the LLG promoter region, and its expression was significantly upregulated in uterine tissue. Thus, the methylation status of ZPBP gene was identified as a potential indicator of litter size. Furthermore, we verified its negative correlation with litter size traits (TNB and NBA) in whole blood samples from 172 Berkshire sows as a blood-based biomarker by a porcine methylation-specific restriction enzyme polymerase chain reaction (PMP) assay. The results suggest that the methylation status of the ZPBP gene can serve as a valuable epigenetic biomarker for hyperprolific sows.

Dominance and epistatic genetic variances for litter size in pigs using genomic models

Background

Epistatic genomic relationship matrices for interactions of any-order can be constructed using the Hadamard products of orthogonal additive and dominance genomic relationship matrices and standardization based on the trace of the resulting matrices. Variance components for litter size in pigs were estimated by Bayesian methods for five nested models with additive, dominance, and pairwise epistatic effects in a pig dataset, and including genomic inbreeding as a covariate.

Results

Estimates of additive and non-additive (dominance and epistatic) variance components were obtained for litter size. The variance component estimates were empirically orthogonal, i.e. they did not change when fitting increasingly complex models. Most of the genetic variance was captured by non-epistatic effects, as expected. In the full model, estimates of dominance and total epistatic variances (additive-by-additive plus additive-by-dominance plus dominance-by-dominance), expressed as a proportion of the total phenotypic variance, were equal to 0.02 and 0.04, respectively. The estimate of broad-sense heritability for litter size (0.15) was almost twice that of the narrow-sense heritability (0.09). Ignoring inbreeding depression yielded upward biased estimates of dominance variance, while estimates of epistatic variances were only slightly affected.

Conclusions

Epistatic variance components can be easily computed using genomic relationship matrices. Correct orthogonal definition of the relationship matrices resulted in orthogonal partition of genetic variance into additive, dominance, and epistatic components, but obtaining accurate variance component estimates remains an issue. Genomic models that include non-additive effects must also consider inbreeding depression in order to avoid upward bias of estimates of dominance variance. Inclusion of epistasis did not improve the accuracy of prediction of breeding values.

Correlated responses on litter size traits and survival traits after two-stage selection for ovulation rate and litter size in rabbits

Farmer profit depends on the number of slaughter rabbits. The improvement of litter size (LS) at birth by two-stage selection for ovulation rate (OR) and LS could modify survival rate from birth to slaughter. This study was aiming to estimate direct and correlated response on LS traits and peri- and postnatal survival traits in the OR_LS rabbit line selected first only for OR (first period) and then for OR and LS using independent culling levels (second period). The studied traits were OR, LS measured as number of total born, number of kits born alive (NBA) and dead (NBD), and number of kits at weaning (NW) and young rabbits at slaughter (NS). Prenatal survival (LS/OR) and survival at birth (NBA/LS), at weaning (NW/NBA) and at slaughter (NS/NW) were also studied. Data were analysed using Bayesian inference methods. Heritability for LS traits were low, 0.07 for NBA, NW and NS. Survival traits had low values of heritability 0.07, 0.03 and 0.03 for NBA/LS, NW/NBA and NS/NW, respectively. After six generations of selection by OR (first period), a small increase in NBD and a slight decrease in NBA/LS were found. However, no correlated responses on NW/NBA and NS/NW were observed. After 11 generations of two-stage selection for OR and LS (second period), correlated responses on NBA, NW and NS were 0.12, 0.12 and 0.11 kits per generation, respectively, whereas no substantial modifications on NBA/LS, NW/NBA and NS/NW were found. In conclusion, two-stage selection improves the number of young rabbits at slaughter without modifying survival from birth to slaughter.

Copy number variations of MTHFSD gene across pig breeds and its association with litter size traits in Chinese indigenous Xiang pig

Copy number variation (CNV) is a major proportion of genetic variation, which changes the gene structure and dosage and affects gene expression and function. To validate the presence and the function of CNV in pig, we used real-time quantitative polymerase chain reaction (qPCR) method to validate a 496 kb CNV region comprising MTHFSD gene on chromosome 6 of Xiang pig detected by single nucleotide polymorphism (SNP) array. Then we investigated the distribution of the MTHFSD CNV in a total of 545 pigs in four breeds. About 46.2% and 32.7% individuals in the four pig breeds were detected to be types of loss and gain of MTHFSD locus. The relative copy numbers of MTHFSD gene showed the largest variation range (0-55 copies) in the Xiang pig population. The copy numbers of MTHFSD gene presented the positive correlations with the transcript level of MTHFSD gene in adult ovaries. Statistical analysis indicated that CNVs of MTHFSD gene was significantly changed the litter size traits of Xiang pigs, and the individuals with CNV gain showed more litter size than the CNV loss pigs. We have reasons to believe that the MTHFSD as RNA-binding protein play an important role in pig reproduction as a result of regulating MTHFS mRNA metabolism.

Estimation of the effects of selection on French Large White sow and piglet performance during the suckling period

The effects of 21 yr of selection were estimated for sow and piglet performance during the suckling period in a French Large White (LW) pig population using frozen semen. Two experimental groups (EXP = L77 and L98) were produced by inseminating LW sows with either stored frozen semen from 17 LW boars born in 1977 (EXP = L77) or with fresh semen from 23 LW boars born in 1998 (EXP = L98). Seventy-four L77 and 89 L98 randomly chosen females were mated to 15 L77 and 15 L98, respectively, randomly chosen boars for 6 successive parities. They produced 2,796 L77 progeny (G77) and 3,529 L98 progeny (G98) piglets including stillbirths. To disentangle direct and maternal effects on piglet growth, a 2 × 2 factorial design was set by cross-fostering half-litters across genetic groups the day after farrowing, resulting in mixed G77/G98 litters nursed by either L77 or L98 sows. Piglet traits investigated included individual weight at birth (IWB), at 21 d of age (IW21d), and at weaning at 4 wk of age (IWW) and ADG from birth to 21 d of age (ADG21d) and from birth to weaning (ADGBW) as well as probability of stillbirth, probability of mortality on the first day after farrowing and from d 2 to weaning. Sow traits analyzed included weight before farrowing and at weaning, feed intake, milk production, colostrum, and milk composition. The variability of performance across genetic groups and litters was also investigated. The data were analyzed using generalized (piglet mortality) or linear mixed models (other traits). Results showed an increase in IWB (+240 ± 72 g in 21 yr for IWB adjusted for total number born), and a negative maternal genetic trend was observed on piglet growth during the suckling period (e.g., +33 ± 13 g/d in 21 yr for ADG21d, that is, 14% of the mean), whereas direct genetic effects remained unchanged. Piglets from L98 litters also had a 40% larger probability of being stillborn and a 28% larger probability of dying on d 1 and had a more heterogeneous IWB (358 vs. 336 g; < 0.001) and growth during the suckling period (60 vs. 56 g/d; < 0.001). Sows from L77 and L98 experimental groups did not differ in weight, feed intake, colostrum, and milk composition. These results give evidence of negative correlated effects of selection for piglet traits related to robustness. These adverse effects are at least partly of maternal origin.

A comparison of accuracy validation methods for genomic and pedigree-based predictions of swine litter size traits using Large White and simulated data

The objective of this study was to compare and determine the optimal validation method when comparing accuracy from single-step GBLUP (ssGBLUP) to traditional pedigree-based BLUP. Field data included six litter size traits. Simulated data included ten replicates designed to mimic the field data in order to determine the method that was closest to the true accuracy. Data were split into training and validation sets. The methods used were as follows: (i) theoretical accuracy derived from the prediction error variance (PEV) of the direct inverse (iLHS), (ii) approximated accuracies from the accf90(GS) program in the BLUPF90 family of programs (Approx), (iii) correlation between predictions and the single-step GEBVs from the full data set (GEBV_Full ), (iv) correlation between predictions and the corrected phenotypes of females from the full data set (Y_c ), (v) correlation from method iv divided by the square root of the heritability (Y_ch ) and (vi) correlation between sire predictions and the average of their daughters' corrected phenotypes (Y_cs ). Accuracies from iLHS increased from 0.27 to 0.37 (37%) in the Large White. Approximation accuracies were very consistent and close in absolute value (0.41 to 0.43). Both iLHS and Approx were much less variable than the corrected phenotype methods (ranging from 0.04 to 0.27). On average, simulated data showed an increase in accuracy from 0.34 to 0.44 (29%) using ssGBLUP. Both iLHS and Y_ch approximated the increase well, 0.30 to 0.46 and 0.36 to 0.45, respectively. GEBV_Full performed poorly in both data sets and is not recommended. Results suggest that for within-breed selection, theoretical accuracy using PEV was consistent and accurate. When direct inversion is infeasible to get the PEV, correlating predictions to the corrected phenotypes divided by the square root of heritability is adequate given a large enough validation data set.

Direct and maternal additive effects are not the main determinants of Iberian piglet perinatal mortality

Data of 127,800 Iberian piglets were used to study genetic parameters of mortality at birth at the piglet level. These records proceed from three data sets: 4,987 litter of 2,156 sows of a dam line, 2,768 litter of 817 sows of a complete diallel cross between four Iberian strains and 7,153 litter of 2,113 sows of the Torbiscal composite line. Perinatal mortality was considered as a binary trait, and Bayesian threshold animal models were fitted to separately analyse the three data sets. The posterior means of direct heritability were 0.010, 0.004 and 0.003, and those of maternal heritability were 0.034, 0.011 and 0.014 for dam line, diallel cross and Torbiscal line, respectively. Important effects of litter size and parity order were inferred in the three data sets, of within-breed cross-breeding parameters in the diallel cross and of sex and sow handling in the Torbiscal line Therefore, the inclusion of perinatal mortality in the objective of selection is questionable in this breed and strategies for reducing piglet mortality successful in other breeds should be considered.

Glucosamine supplementation during late gestation alters placental development and increases litter size

Background

During late gestation the placental epithelial interface becomes highly folded, which involves changes in stromal hyaluronan. Hyaluronan is composed of glucoronate and N-acetyl-glucosamine. We hypothesized that supplementing gestating dams with glucosamine during this time would support placental folded-epithelial-bilayer development and increase litter size. In Exp. 1, gilts were unilaterally hysterectomized-ovariectomized (UHO). UHO gilts were mated and then supplemented daily with 10 g glucosamine (n = 16) or glucose (control, n = 17) from d 85 of gestation until slaughter (d 105). At slaughter, the number of live fetuses was recorded and each live fetus and its placenta was weighed. Uterine wall samples adjacent to the largest and smallest fetuses within each litter were processed for histology. In Exp. 2, pregnant sows in a commercial sow farm were supplemented with either 10 g glucosamine or glucose daily from d 85 of gestation to farrowing. Total piglets born and born alive were recorded for each litter. In Exp. 3, the same commercial farm and same protocol were used except that the dose of glucosamine and glucose was doubled to 20 g/d.

Results

In Exp. 1, the number of live fetuses tended to be greater in glucosamine-treated UHO gilts (P = 0.098). Placental morphometry indicated that the width of the folded bilayer was greater (P = 0.05) in glucosamine-treated gilts. In Exp. 2, litter size did not differ between glucosamine- and glucose-treated sows. However in Exp. 3, the increased dose of glucosamine resulted in a significant treatment by parity interaction (P ≤ 0.01), in which total piglets born and born alive were greater in glucosamine treated sows of later parity (5 and 6).

Conclusions

These results indicated that glucosamine supplementation increased the width of the folds of the placental bilayer and increased litter size in later parity, intact pregnant commercial sows.

Nurse capacity, fertility, and litter size in crossbred sows and genetic correlation to purebred sow information

In pigs litter size has increased during the last decades and number of weaned piglets is an important issue. The aim of this study was to develop a new trait of nurse capacity (NC) of crossbred sows viewed as crossbred performances in the two purebred parent lines, and estimate the genetic correlation to fertility and litter size five days after birth. An experiment recording phenotypes of crossbred sows was conducted in three large production herds with 11,247 first litter Danish Landrace x Yorkshire sows. All terminal sires used were Duroc AI boars. The experiment was running from 2010 to 2013. At farrowing, the total number born (TNB) was recorded. Five days after farrowing the litter size of the biological mother (LS5) was recorded. During the first three days after farrowing the number of piglets at each nurse sow was equalized to 14 piglets and after three weeks the NC was recorded and defined as the number of piglets nursed. Additional records on TNB and LS5 from related sows in nucleus and multiplier herds were added to obtain a data set with both purebred and crossbred information. A reduced animal model including both purebred and crossbred records was used and parameters were estimated. The results show that NC recorded on crossbred first litter sows had heritabilities of 0.05 and 0.07 for crossbred performance in the purebred populations of Landrace and Yorkshire, respectively. Estimated genetic correlations between TNB in purebreds and crossbreds show that nearly 50% of genetic gain in the purebred populations was transferred to crossbreds. Unfavorable genetic correlations between TNB in purebreds and NC in crossbreds were observed. For LS5 the genetic (co)variances show that 61% of the genetic gain in the two purebred lines was transferred to the commercial pig production of crossbred first litter sows, but no statistically significant genetic correlation to NC was obtained.

Heritability of udder morphology and colostrum quality traits in swine

The heritability of udder quality traits, defined as morphology and colostrum IgG concentration at farrowing, was estimated together with the genetic and phenotypic correlations of these traits with other production and reproduction criteria. Udder morphology traits were recorded in 988 Meidam sows and colostrum samples were collected from 528 sows. Teat length, teat diameter (DIA), interteat distance within the same row (SAMER), and teat distance from the abdominal midline (AML) were recorded to the nearest millimeter. For each sow, a record was also made of udder development score (DEV), the proportion of teats oriented perpendicular to the udder, and the proportion of nonfunctional teats. Colostrum IgG concentration was estimated with a Brix refractometer. Heritability of udder morphology traits varied from high ( = 0.46 for teat length and = 0.56 for DIA) to moderate ( = 0.37 for SAMER, = 0.22 for AML, = 0.25 for DEV, = 0.3 for the proportion of nonfunctional teats, = 0.1 for the proportion of teats oriented perpendicular to the udder, and = 0.35 for colostrum IgG concentration). The SAMER was negatively genetically correlated with the number of stillborns (genetic correlation [] = -0.48) and positively genetically correlated with the number of piglets born alive ( = 0.69), with the opposite for the trait AML ( = -0.40 for number of piglets born alive and = 0.40 for stillborns). The highest genetic correlation with productive traits was estimated between AML and ADG during rearing ( = 0.42), although this had a negative phenotypic correlation (; -0.11). Teat length was also moderately correlated with ADG ( = 0.27). Backfat thickness at 100 kg was positively correlated with DIA and the total number of teats present in both rows ( = 0.28 and = 0.36, respectively) and negatively correlated only with DEV ( = -0.22). The same results were found for the phenotypic correlation between backfat thickness at end of test and the total number of teats present in both rows ( = 0.03). Udder quality traits can be included in the breeding goal and appropriately weighted with other important traits in the breeding objectives to enhance maternal performance.

Genetic analysis of teat number in pigs reveals some developmental pathways independent of vertebra number and several loci which only affect a specific side

Background

Number of functional teats is an important trait in commercial swine production. As litter size increases, the number of teats must also increase to supply nutrition to all piglets. Therefore, a genome-wide association analysis was conducted to identify genomic regions that affect this trait in a commercial swine population. Genotypic data from the Illumina Porcine SNP60v1 BeadChip were available for 2951 animals with total teat number (TTN) records. A subset of these animals (n = 1828) had number of teats on each side recorded. From this information, the following traits were derived: number of teats on the left (LTN) and right side (RTN), maximum number of teats on a side (MAX), difference between LTN and RTN (L − R) and absolute value of L − R (DIF). Bayes C option of GENSEL (version 4.61) and 1-Mb windows were implemented. Identified regions that explained more than 1.5% of the genomic variation were tested in a larger group of animals (n = 5453) to estimate additive genetic effects.

Results

Marker heritabilities were highest for TTN (0.233), intermediate for individual side counts (0.088 to 0.115) and virtually nil for difference traits (0.002 for L − R and 0.006 for DIF). Each copy of the VRTN mutant allele increased teat count by 0.35 (TTN), 0.16 (LTN and RTN) and 0.19 (MAX). 15, 18, 13 and 18 one-Mb windows were detected that explained more than 1.0% of the genomic variation for TTN, LTN, RTN, and MAX, respectively. These regions cumulatively accounted for over 50% of the genomic variation of LTN, RTN and MAX, but only 30% of that of TTN. Sus scrofa chromosome SSC10:52 Mb was associated with all four count traits, while SSC10:60 and SSC14:54 Mb were associated with three count traits. Thirty-three SNPs accounted for nearly 39% of the additive genetic variation in the validation dataset. No effect of piglet sex or percentage of males in litter was detected, but birth weight was positively correlated with TTN.

Conclusions

Teat number is a heritable trait and use of genetic markers would expedite selection progress. Exploiting genetic variation associated with teat counts on each side would enhance selection focused on total teat counts. These results confirm QTL on SSC4, seven and ten and identify a novel QTL on SSC14.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-016-0282-1) contains supplementary material, which is available to authorized users.

Variance component estimates for alternative litter size traits in swine

Litter size at d 5 (LS5) has been shown to be an effective trait to increase total number born (TNB) while simultaneously decreasing preweaning mortality. The objective of this study was to determine the optimal litter size day for selection (i.e., other than d 5). Traits included TNB, number born alive (NBA), litter size at d 2, 5, 10, 30 (LS2, LS5, LS10, LS30, respectively), litter size at weaning (LSW), number weaned (NW), piglet mortality at d 30 (MortD30), and average piglet birth weight (BirthWt). Litter size traits were assigned to biological litters and treated as a trait of the sow. In contrast, NW was the number of piglets weaned by the nurse dam. Bivariate animal models included farm, year-season, and parity as fixed effects. Number born alive was fit as a covariate for BirthWt. Random effects included additive genetics and the permanent environment of the sow. Variance components were plotted for TNB, NBA, and LS2 to LS30 using univariate animal models to determine how variances changed over time. Additive genetic variance was minimized at d 7 in Large White and at d 14 in Landrace pigs. Total phenotypic variance for litter size traits decreased over the first 10 d and then stabilized. Heritability estimates increased between TNB and LS30. Genetic correlations between TNB, NBA, and LS2 to LS29 with LS30 plateaued within the first 10 d. A genetic correlation with LS30 of 0.95 was reached at d 4 for Large White and at d 8 for Landrace pigs. Heritability estimates ranged from 0.07 to 0.13 for litter size traits and MortD30. Birth weight had an h of 0.24 and 0.26 for Large White and Landrace pigs, respectively. Genetic correlations among LS30, LSW, and NW ranged from 0.97 to 1.00. In the Large White breed, genetic correlations between MortD30 with TNB and LS30 were 0.23 and -0.64, respectively. These correlations were 0.10 and -0.61 in the Landrace breed. A high genetic correlation of 0.98 and 0.97 was observed between LS10 and NW for Large White and Landrace breeds, respectively. This would indicate that NW could possibly be used as an effective maternal trait, given a low level of cross-fostering, to avoid back calculating litter size traits from piglet records. Litter size at d 10 would be a compromise between gain in litter size at weaning and minimizing the potentially negative effects of the nurse dam and direct additive genetics of the piglets, as they are expected to increase throughout lactation.

Genome-wide association analyses using a Bayesian approach for litter size and piglet mortality in Danish Landrace and Yorkshire pigs

BACKGROUND

Litter size and piglet mortality are important traits in pig production. The study aimed to identify quantitative trait loci (QTL) for litter size and mortality traits, including total number of piglets born (TNB), litter size at day 5 (LS5) and mortality rate before day 5 (MORT) in Danish Landrace and Yorkshire pigs by genome-wide association studies (GWAS).

METHODS

The phenotypic records and genotypes were available in 5,977 Landrace pigs and 6,000 Yorkshire pigs born from 1998 to 2014. A linear mixed model (LM) with a single SNP regression and a Bayesian mixture model (BM) including effects of all SNPs simultaneously were used for GWAS to detect significant QTL association. The response variable used in the GWAS was corrected phenotypic value which was obtained by adjusting original observations for non-genetic effects. For BM, the QTL region was determined by using a novel post-Gibbs analysis based on the posterior mixture probability.

RESULTS

The detected association patterns from LM and BM models were generally similar. However, BM gave more distinct detection signals than LM. The clearer peaks from BM indicated that the BM model has an advantage in respect of identifying and distinguishing regions of putative QTL. Using BM and QTL region analysis, for the three traits and two breeds a total of 15 QTL regions were identified on SSC1, 2, 3, 6, 7, 9, 13 and 14. Among these QTL regions, 6 regions located on SSC2, 3, 6, 7 and 13 were associated with more than one trait.

CONCLUSION

This study detected QTL regions associated with litter size and piglet mortality traits in Danish pigs using a novel approach of post-Gibbs analysis based on posterior mixture probability. All of the detected QTL regions overlapped with regions previously reported for reproduction traits. The regions commonly detected in different traits and breeds could be resources for multi-trait and across-bred selection. The proposed novel QTL region analysis method would be a good alternative to detect and define QTL regions.

Within-litter variation in birth weight: impact of nutritional status in the sow

Accompanying the beneficial improvement in litter size from genetic selection for high-prolificacy sows, within-litter variation in birth weight has increased with detrimental effects on post-natal growth and survival due to an increase in the proportion of piglets with low birth-weight. Causes of within-litter variation in birth weight include breed characteristics that affect uterine space, ovulation rate, degree of maturation of oocytes, duration of time required for ovulation, interval between ovulation and fertilization, uterine capacity for implantation and placentation, size and efficiency of placental transport of nutrients, communication between conceptus/fetus and maternal systems, as well as nutritional status and environmental influences during gestation. Because these factors contribute to within-litter variation in birth weight, nutritional status of the sow to improve fetal-placental development must focus on the following three important stages in the reproductive cycle: pre-mating or weaning to estrus, early gestation and late gestation. The goal is to increase the homogeneity of development of oocytes and conceptuses, decrease variations in conceptus development during implantation and placentation, and improve birth weights of newborn piglets. Though some progress has been made in nutritional regulation of within-litter variation in the birth weight of piglets, additional studies, with a focus on and insights into molecular mechanisms of reproductive physiology from the aspects of maternal growth and offspring development, as well as their regulation by nutrients provided to the sow, are urgently needed.

Genomic BLUP including additive and dominant variation in purebreds and F1 crossbreds, with an application in pigs

BACKGROUND

Most developments in quantitative genetics theory focus on the study of intra-breed/line concepts. With the availability of massive genomic information, it becomes necessary to revisit the theory for crossbred populations. We propose methods to construct genomic covariances with additive and non-additive (dominance) inheritance in the case of pure lines and crossbred populations.

RESULTS

We describe substitution effects and dominant deviations across two pure parental populations and the crossbred population. Gene effects are assumed to be independent of the origin of alleles and allelic frequencies can differ between parental populations. Based on these assumptions, the theoretical variance components (additive and dominant) are obtained as a function of marker effects and allelic frequencies. The additive genetic variance in the crossbred population includes the biological additive and dominant effects of a gene and a covariance term. Dominance variance in the crossbred population is proportional to the product of the heterozygosity coefficients of both parental populations. A genomic BLUP (best linear unbiased prediction) equivalent model is presented. We illustrate this approach by using pig data (two pure lines and their cross, including 8265 phenotyped and genotyped sows). For the total number of piglets born, the dominance variance in the crossbred population represented about 13 % of the total genetic variance. Dominance variation is only marginally important for litter size in the crossbred population.

CONCLUSIONS

We present a coherent marker-based model that includes purebred and crossbred data and additive and dominant actions. Using this model, it is possible to estimate breeding values, dominant deviations and variance components in a dataset that comprises data on purebred and crossbred individuals. These methods can be exploited to plan assortative mating in pig, maize or other species, in order to generate superior crossbred individuals in terms of performance.

Genome-wide association study reveals novel loci for litter size and its variability in a Large White pig population

Background

In many traits, not only individual trait levels are under genetic control, but also the variation around that level. In other words, genotypes do not only differ in mean, but also in (residual) variation around the genotypic mean. New statistical methods facilitate gaining knowledge on the genetic architecture of complex traits such as phenotypic variability. Here we study litter size (total number born) and its variation in a Large White pig population using a Double Hierarchical Generalized Linear model, and perform a genome-wide association study using a Bayesian method.

Results

In total, 10 significant single nucleotide polymorphisms (SNPs) were detected for total number born (TNB) and 9 SNPs for variability of TNB (varTNB). Those SNPs explained 0.83 % of genetic variance in TNB and 1.44 % in varTNB. The most significant SNP for TNB was detected on Sus scrofa chromosome (SSC) 11. A possible candidate gene for TNB is ENOX1, which is involved in cell growth and survival. On SSC7, two possible candidate genes for varTNB are located. The first gene is coding a swine heat shock protein 90 (HSPCB = Hsp90), which is a well-studied gene stabilizing morphological traits in Drosophila and Arabidopsis. The second gene is VEGFA, which is activated in angiogenesis and vasculogenesis in the fetus. Furthermore, the genetic correlation between additive genetic effects on TNB and on its variation was 0.49. This indicates that the current selection to increase TNB will also increase the varTNB.

Conclusions

To the best of our knowledge, this is the first study reporting SNPs associated with variation of a trait in pigs. Detected genomic regions associated with varTNB can be used in genomic selection to decrease varTNB, which is highly desirable to avoid very small or very large litters in pigs. However, the percentage of variance explained by those regions was small. The SNPs detected in this study can be used as indication for regions in the Sus scrofa genome involved in maintaining low variability of litter size, but further studies are needed to identify the causative loci.

Joint analysis of binomial and continuous traits with a recursive model: a case study using mortality and litter size of pigs

This work presents a model for the joint analysis of a binomial and a Gaussian trait using a recursive parametrization that leads to a computationally efficient implementation. The model is illustrated in an analysis of mortality and litter size in two breeds of Danish pigs, Landrace and Yorkshire. Available evidence suggests that mortality of piglets increased partly as a result of successful selection for total number of piglets born. In recent years there has been a need to decrease the incidence of mortality in pig-breeding programs. We report estimates of genetic variation at the level of the logit of the probability of mortality and quantify how it is affected by the size of the litter. Several models for mortality are considered and the best fits are obtained by postulating linear and cubic relationships between the logit of the probability of mortality and litter size, for Landrace and Yorkshire, respectively. An interpretation of how the presence of genetic variation affects the probability of mortality in the population is provided and we discuss and quantify the prospects of selecting for reduced mortality, without affecting litter size.