Development of an animal model for across-herd genetic evaluation of number born alive in swine

Genetic and nongenetic factors influencing ewe prolificacy and lamb body weight in a closed Romanov flock

The U.S. Meat Animal Research Center was the first entity in the United States to import the Romanov breed and it has been maintained as a closed flock for over 30 yr. Incorporating this super-prolific breed into crossbred and composite populations has resulted in large improvements in ewe productivity. However, few have quantified factors contributing to genetic and nongenetic variation in ewe reproduction and lamb growth within purebred Romanov populations, which were the objectives of this study. The pedigree contained a total of 8,683 lambs born to 218 and 1,600 unique sires and dams, respectively. Number of lambs born on a per ewe exposed (NLBE) and lambing (NLBL) basis were analyzed in univariate repeatability animal models. As expected, the proportion of phenotypic variance (σP2) in litter size attributable to additive genetic (0.06 to 0.08) and permanent environmental (0.05 to 0.07) effects of the ewe was low. The service sire permanent environmental effect contributed to a small but significant amount of σP2 in NLBE (0.03) but not NLBL. However, the service sire additive genetic effect did not influence σP2 in NLBE or NLBL. Lamb body weight was recorded at birth (BWB) and upon weaning from either milk replacer (~30 d; BWW-N) or their dam (~60 d; BWW-D) and were analyzed in a three-trait model with random additive direct and maternal effects. Estimated direct heritabilities were low for all body weight (BW) traits (0.07 to 0.10). Maternal heritability was moderate for BWB (0.34) but low for weaning BW (0.11 to 0.18). This was the first to report direct and maternal genetic correlations between BW of nursery- and dam-reared lambs, and both were estimated to be moderate (0.43 to 0.47). Additionally, the direct and maternal effects of BWB were more strongly correlated with BWW-N (0.74 to 0.82) than BWW-D (0.17 to 0.33). Despite inbreeding coefficients having increased at a rate of 0.33% per birth year (1986 to 2019) in this flock, they were not consistently associated with reductions in ewe or lamb performance. Parameter estimates generally agreed with those from less-prolific breeds, and results indicate that selection can be an effective means of improving subcomponents of ewe productivity.

Genetic Parameters of Reproductive and Meat Quality Traits in Korean Berkshire Pigs

Genetic parameters of Berkshire pigs for reproduction, carcass and meat quality traits were estimated using the records from a breeding farm in Korea. For reproduction traits, 2,457 records of the total number of piglets born (TNB) and the number of piglets born alive (NBA) from 781 sows and 53 sires were used. For two carcass traits which are carcass weight (CW) and backfat thickness (BF) and for 10 meat quality traits which are pH value after 45 minutes (pH45m), pH value after 24 hours (pH24h), lightness in meat color (LMC), redness in meat color (RMC), yellowness in meat color (YMC), moisture holding capacity (MHC), drip loss (DL), cooking loss (CL), fat content (FC), and shear force value (SH), 1,942 pig records were used to estimate genetic parameters. The genetic parameters for each trait were estimated using VCE program with animal model. Heritability estimates for reproduction traits TNB and NBA were 0.07 and 0.06, respectively, for carcass traits CW and BF were 0.37 and 0.57, respectively and for meat traits pH45m, pH24h, LMC, RMC, YMC, MHC, DL, CL, FC, and SH were 0.48, 0.15, 0.19, 0.36, 0.28, 0.21, 0.33, 0.45, 0.43, and 0.39, respectively. The estimate for genetic correlation coefficient between CW and BF was 0.27. The Genetic correlation between pH24h and meat color traits were in the range of −0.51 to −0.33 and between pH24h and DL and SH were −0.41 and −0.32, respectively. The estimates for genetic correlation coefficients between reproductive and meat quality traits were very low or zero. However, the estimates for genetic correlation coefficients between reproductive traits and drip and cooking loss were in the range of 0.12 to 0.17 and −0.14 to −0.12, respectively. As the estimated heritability of meat quality traits showed medium to high heritability, these traits may be applicable for the genetic improvement by continuous measurement. However, since some of the meat quality traits showed negative genetic correlations with carcass traits, an appropriate breeding scheme is required that carefully considers the complexity of genetic parameters and applicability of data.

Genetic parameters for performance traits in commercial sows estimated before and after an outbreak of porcine reproductive and respiratory syndrome

Porcine reproductive and respiratory syndrome (PRRS), caused by the PRRS virus (PRRSV), is globally the most economically important disease in commercial pigs, and novel control strategies are sought. This paper explores the potential to use host genetics to decrease the impact of PRRS on reproductive sows. Commercial pig data (7,542 phenotypic records) from a farm undergoing an outbreak of PRRSV were analyzed to assess the impact of PRRS on reproductive traits and the inheritance of such traits. First, differing methodologies were used to partition the data into time periods when the farm was disease free and when the farm was experiencing PRRSV outbreaks. The methods were a date/threshold method based on veterinary diagnosis and a threshold/threshold method based on trends in underlying performance data, creating the DTD and TTD data sets, respectively. The threshold/threshold method was more stringent in defining periods when PRRS was likely to be having an impact on reproductive performance, resulting in a data set (TTD) that was slightly smaller (1,977 litters from 1,526 sows) than that from the date/threshold method (3,164 litters and 1,662 sows), and it showed more pronounced impacts of PRRS on performance. Impacts on performance included significant increases in mean values of mummified and stillborn piglets (0.04 to 1.13 and 0.63 to 1.02, respectively) with a significant decrease in total born alive (10.3 to 9.08). Estimated heritabilities during the healthy phase were generally less (mummified piglets = 0.03 +/- 0.01, matings per conception = 0.04 +/- 0.01) than during the PRRSV outbreak (TTD data set; mummified piglets = 0.10 +/- 0.03, matings per conception = 0.46 +/- 0.04). These results imply genetic variation for host resistance to, or tolerance of, PRRSV, particularly with the TTD data set. Genetic correlations between reproductive traits measured in the healthy phase and TTD data set varied from effectively zero for traits describing numbers of mummified or dead piglets to strongly positive for litter size traits. This indicates genetic variation in piglet losses during PRRSV outbreaks is independent of genetic variation in the same traits in healthy herds. In summary, our findings show that there is within-breed genetic variation for commercially relevant traits that could be exploited in future breeding programs against PRRSV infection. Selection for increased PRRS resistance would be desirable to the industry because effective control measures remain elusive.

Selection for litter size at day five to improve litter size at weaning and piglet survival rate

Selection for total number of piglets born (TNB) since 1992 has led to a significant increase in this trait in Danish Landrace and Danish Yorkshire but has also been accompanied by an increase in piglet mortality. The objective of this study was to estimate the genetic and phenotypic parameters for litter size and survival to find alternative selection criteria to improve litter size at weaning. Data from Landrace (9,300 litters) and Yorkshire (6,861 litters) were analyzed using REML based on a linear model including genetic effects of sow and service-sire. The estimates of heritability (based on the sow component) for TNB, number born alive (NBA), and number alive at d 5 after birth (N5D) and at weaning (about 3 wk, N3W) ranged from 0.066 to 0.090 in Landrace and 0.050 to 0.070 in Yorkshire. Genetic correlations between TNB and N3W were 0.289 in Landrace and 0.561 in Yorkshire, but between N5D and N3W the estimated genetic correlation was 0.995 in both populations. The approximate estimates of heritability for survival rate per litter at birth (SVB = NBA/TNB), from birth to d 5 (SV5 = N5D/NBA), and from d 5 to weaning (SVW = N3W/N5D) were 0.130, 0.131, and 0.023, respectively, in Landrace, and 0.095, 0.043, and 0.009, respectively, in Yorkshire. Genetic correlations between TNB and survival rates at different stages were negative. On the other hand, genetic correlations between N5D and survival rates and between N3W and survival rates were strongly or moderately positive, except for the correlations with SVW in Yorkshire. The results suggest that selection for N5D could be an interesting alternative to improve litter size at weaning and piglet survival for Danish Landrace and Danish Yorkshire.