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

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

Genetic parameter estimation for number born alive at different parities in Landrace and Large White pigs

We estimated genetic parameters for number born alive (NBA) from the first to the seventh parities in Landrace and Large White pigs using three models. Analyzing 55,160 farrowing records for 12,677 Landrace dams and 43,839 for 10,405 Large White dams, we used a single‐trait animal model to estimate the heritability of NBA at each parity and a two‐trait animal model and a single‐trait random regression model to estimate the genetic correlations between parities. Heritability estimates of NBA at each parity ranged from 0.08 to 0.13 for Landrace and from 0.05 to 0.16 for Large White. Estimated genetic correlations between parities in all cases were positive. Genetic correlations between the first and second parities were slightly lower than those between other neighboring parities. Genetic correlations between more distant parities tended to be lower, in some cases <0.8. The results indicate the necessity to investigate the applicability of evaluating NBA at different parities as different traits (e.g., the first and later parities), although a repeatability model might still be reasonable.     

Genetic relationship of litter traits between farrowing and weaning in Landrace and Large White pigs

We estimated genetic parameters in Landrace and Large White pig populations for litter traits at farrowing (total number born, number born alive, number stillborn, total litter weight at birth (LWB), and mean litter weight at birth) and those at weaning (litter size at weaning (LSW), total litter weight at weaning (LWW), mean litter weight at weaning (MWW), and survival rate from farrowing to weaning). We analyzed 65,579 records at farrowing and 6,306 at weaning for Landrace, and 52,557 and 5,360, respectively, for Large White. Single‐trait and two‐trait repeatability animal models were exploited to estimate heritability and genetic correlation respectively. Heritability estimates of LSW were 0.09 for Landrace and 0.08 for Large White. Genetic correlations of LSW with MWW were –0.43 for Landrace and –0.24 for Large White. Genetic correlations of LSW with LWW and LWB ranged from 0.5 to 0.6. The genetic correlation of MWW with LWW was positive, but that with LWB was negligible. The results indicate that utilizing LWW or LWB could improve LSW efficiently, despite the antagonistic genetic correlation between LSW and MWW.     

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.     

Heritability and genetic correlation estimates of semen production traits with litter traits and pork production traits in purebred Duroc pigs

We estimated heritabilities of semen production traits and their genetic correlations with litter traits and pork production traits in purebred Duroc pigs. Semen production traits were semen volume, sperm concentration, proportion of morphologically normal sperms, total number of sperm, and total number of morphologically normal sperm. Litter traits at farrowing were total number born, number born alive, number stillborn, total litter weight at birth, mean litter weight at birth, and piglet survival rate at birth. Litter traits at weaning were litter size at weaning, total litter weight at weaning, mean litter weight at weaning, and piglet survival rate from birth to weaning. Pork production traits were average daily gain, backfat thickness, and loin muscle area. We analyzed 45,913 semen collection records of 896 boars, 6,950 farrowing performance records of 1,400 sows, 2,237 weaning performance records of 586 sows, and individual growth performance records of 9,550 animals measured at approximately 5 mo of age. Heritabilities were estimated using a single-trait animal model. Genetic correlations were estimated using a 2-trait animal model. Estimated heritabilities of semen production traits ranged from 0.20 for sperm concentration to 0.29 for semen volume and were equal to or higher than those of litter traits, ranging from 0.06 for number stillborn and piglet survival rate at birth to 0.25 for mean litter weight at birth, but lower than those of pork production traits, ranging from 0.50 for average daily gain to 0.63 for backfat thickness. In many cases, the absolute values of estimated genetic correlations between semen production traits and other traits were smaller than 0.3. These estimated genetic parameters provide useful information for establishing a comprehensive pig breeding scheme.     

Genetic parameters and trends for production traits and their relationship with litter traits in Landrace and Yorkshire pigs

Genetic parameters and trends in the average daily gain (ADG), backfat thickness (BF), loin muscle area (LMA), lean percentage (LP), and age at 90 kg (D90) were estimated for populations of Landrace and Yorkshire pigs. Additionally, the correlations between these production traits and litter traits were estimated. Litter traits included total born (TB) and number born alive (NBA). The data used for this study were obtained from eight farms during 1999 to 2016. Analyses were carried out with a multivariate animal model to estimate genetic parameters for production traits while bivariate analyses were performed to estimate the correlations between production and litter traits. The heritability estimates were 0.52 and 0.43 for ADG; 0.54 and 0.45 for BF; 0.25 and 0.26 for LMA; 0.54 and 0.48 for LP; and 0.56 and 0.46 for D90 in the Landrace and Yorkshire breeds, respectively. The ADG and D90 showed low genetic correlation with BF and LP. The LMA had ?0.40, ?0.32, 0.49, and 0.39 genetic correlations with ADG, BF, LP, and D90, respectively. Genetic correlations between production and litter traits were generally low, except for the correlations between LMA and TB (?0.23) in Landrace and ADG and TB (?0.16), ADG and NBA (?0.18), D90 and TB (0.19), and D90 and NBA (0.20) in Yorkshire. Genetic trends in production traits were all favorable except for LMA.     

长白和大白猪主要生长性状的遗传参数估计

旨在分析母猪的出生年份、出生季节、初生重、开测日龄等固定效应对长白、大白猪主要生长性状的影响,并对目标生长性状进行遗传参数估计(遗传力、遗传方差、表型相关和遗传相关),为猪的遗传改良提供基本依据.本试验利用GLM模型分析试验猪群(398头长白猪和1176头大白猪)的固定效应对猪生长性状的影响,并采用多性状动物模型对目标...     

Comparison of two models to estimate genetic parameters for number of born alive in pigs

The performance of the two‐trait animal model that regards the first parity and later parities as two different traits in estimating genetic parameters for number of born alive (NBA) was examined using real and simulated data. Genetic parameters for NBA were estimated in purebred Landrace and Large White pigs using a single‐trait repeatability model (Model 1) that regards all parities as the same trait and a two‐trait animal model (Model 2) that regards the first and the later parities as different traits. For Model 2, the permanent environmental effect was fitted to only the records of the later parities. Heritability for NBA estimated using Model 1 was 0.12 for Landrace and 0.11 for Large White. Estimated heritability for NBA of the first parity and the later parities was 0.21 and 0.16, respectively, for Landrace; 0.18 and 0.16, respectively, for Large White obtained using Model 2, and higher than those in both breeds obtained using Model 1. Further results based on data simulated using the Monte Carlo method suggest that estimated additive genetic variance could be more biased using Model 2 than Model 1.     

Genetic analysis for sow stayability at different parities in purebred Landrace and Large White pigs

Genetic parameters for sow stayability were estimated from farrowing records of 10,295 Landrace sows and 8192 Large White sows. The record for sow stayability from parity k to parity k + 1 (k = 1, …, 6) was 0 when a sow had a farrowing record at parity k but not at parity k + 1, and 1 when a sow had both records. Heritability was estimated by using single-trait linear and threshold animal models. Genetic correlations among parities were estimated by using two-trait linear–linear and single-trait random regression linear animal models. Genetic correlations with litter traits at birth were estimated by using a two-trait linear–linear animal model. Heritability estimates by linear model analysis were low (0.065–0.119 in Landrace & 0.061–0.157 in Large White); those by threshold model analysis were higher (0.136–0.200 & 0.110–0.283). Genetic correlations among parities differed between breeds and models. Genetic correlation between sow stayability and number born alive was positive in many cases, implying that selection for number born alive does not reduce sow stayability. The results seem to be affected by decisions on culling made by farmers.     

Estimation of litter size variability phenotypes in Large White sows

The objective of this study was to obtain new phenotypes of phenotypic variability for the total number born (TNB) in pigs using the residual variance of TNB. The analysis was based on 246,799 Large White litter observations provided by Topigs Norsvin. Three animal models were used to obtain estimates of residual variance for TNB: the basic model (BM) containing fixed effects of farm–year and season and random effects of animal and permanent environmental sow, the basic model with an additional fixed effect of parity (BMP) and a random regression model (RRM). The within-individual variance of the residuals was calculated and log-transformed to obtain three new variability traits: LnVarBM, LnVarBMP and LnVarRRM. Then, (co)variance components, heritability, the genetic coefficient of variation at the standard deviation level (GCV_SDe) and genetic correlations between the three LnVar's and between the LnVar's and mean total number born (mTNB) were estimated with uni-, bi- and trivariate models. Results indicated that genetically LnVar's are the same trait and are positively correlated with the mTNB (~0.60). Thus, both traits should be included in breeding programmes to avoid an increase in TNB variability while selecting for increased TNB. Heritability of the LnVar's was estimated at 0.021. The GCV_SDe for LnVar's showed that a change of 8% in residual standard deviation of TNB could be obtained per generation. Those results indicate that phenotypic variability of litter size is under genetic control, thus it may be improved by selection.     

Estimation of economic weights for number of teats and sperm quality traits in pigs

Accurate predictive modelling facilitates efficient and effective trait selection in animal breeding and can decrease costs while maximizing profits when raising economically important animals. The objective of this study was to extend a previously developed bioeconomic model and computer program to calculate the marginal economic values (MEVs) and economic weights (EWs) for direct and maternal pig traits affected by new reproductive traits, namely the number of sow functional teats (NFTs) and boar sperm quality traits (SQTs) that included sperm volume, sperm concentration, motility percentage and percentage of abnormal spermatozoa. The MEV of NFTs represented the cost differences between naturally and artificially reared piglets until weaning and the cost differences between naturally and artificially reared finished animals. The MEVs of SQTs expressed the saved costs for artificial insemination, assuming a decreased price per insemination dose when improving the SQTs. The absolute and relative EWs for the newly defined complex of traits in the breeding objectives for pig breeds involved in the Czech national three-way crossing system (Czech Large White [CLW], Czech Landrace [CL] and Pietrain [PN]) were calculated using gene flow methods. The NFT trait was included only for dam breeds, and the relative EW averaged 3.6% of the total economic importance based on the genetic standard deviations of all 19 simultaneously evaluated traits in CLW and CL breeds. The relative EWs of the four SQTs comprised 2.0% of the total economic importance of the 19 traits in the CLW and CL dam breeds and 8% of the total economic importance of the 18 traits in the PN sire breed. Therefore, inclusion of the NFTs for dam breeds and SQTs for sire breeds in the breeding goal is recommended to aid in obtaining ideal outcomes with optimal economic values.     

波尔山羊繁殖性状遗传参数的估计

对 2 4 8窝波尔山羊的胎产羔数、羔羊初生重和 2月龄体重的资料进行了遗传分析。结果表明 :公羊和胎次均对母羊产羔数具有显著的影响(P <0 0 5)。不同产羔季节对羔羊初生重和 2月龄体重也具有显著影响。产羔数的遗传力为 0 1 52 ,属低遗传力 ,而羔羊初生重和 2月龄体重 2个性状 (0 433 ,0 347)有中等或较高的遗传力。波尔母羊胎产羔数与羔羊初生重、 2月龄体重之间存在显著或极显著的表型相关 ,但是它们之间却存在显著或极显著的负遗传相关 (P <0 0 5或 P<0 0 1 )。羔羊的初生重和 2月龄体重间 ,无论是表型相关还是遗传相关 ,都呈极显著的正相关(P <0 0 1 )。     

Comparison of genetic improvement for litter size at birth by direct and indirect selection in swine herd

Responses to selection for number of piglets born alive (NBA) by the total number of piglets born (TNB), the NBA, and the NBA plus number of piglets born dead (NBD) were compared using the accuracy of selection and expected genetic gain calculated from the selection index with family information and the real response to selection, using data generated by Monte Carlo computer simulation. The accuracy of selection for NBA selected by TNB was higher than that by NBA only if the genetic correlation between TNB and NBA was close to 1.0, or the value of heritability for the TNB was much larger than that for the NBA. The accuracy of selection for the NBA selected by the combination of the TNB and the NBA was generally highest in the three selection methods in each family structure. Selection by the TNB resulted in the greatest expected genetic gain for the TNB among the selection methods. In the best linear unbiased prediction (BLUP) selection, the genetic gain for the NBA accumulated by the NBA tended to be similar to that accumulated by the combination of the NBA and the NBD, and both genetic gains at generation 10 were significantly larger than that by the TNB (P < 0.001). The accumulated responses selected by the two‐trait animal model BLUP estimated from genetic parameters with errors were similar to those estimated from the true parameters, and there was no significant difference between them. These results indicate that selection by the NBA or by the NBA and the NBD gives more genetic improvement in the NBA than that by the TNB.     

Genetic parameters for production traits and measures of residual feed intake in Duroc and Landrace pigs

Data on 380 Duroc boars from seven generations, and 1026 Landrace pigs (341 boars and 685 gilts) from six generations were used to estimate genetic parameters for daily gain (DG), backfat thickness (BF), metabolic weight (MWT), daily feed intake (FI), feed conversion ratio (FCR) and residual feed intake (RFI). Two measures of RFI were estimated as the difference between actual feed intake and that predicted from models that included initial test age and weight and DG (RFI1); and initial test age and weight, DG and BF (RFI2). Heritability estimates for DG, MWT and FI were moderate for both breeds. BF estimates were high for both the breeds. The measures of feed efficiency (FCR and RFI) were moderately heritable. Genetic correlations of BF with measures of RFI were stronger when BF was not included in the estimation of RFI (0.40 and 0.46 for Duroc and Landrace, respectively (for RFI1), compared with 0.05 and 0.06 for Duroc and Landrace, respectively (for RFI2)). Genetic correlations of MWT with measures of RFI were all negative and low. Genetic and phenotypic correlations between DG and measures of RFI were close to zero, which indicated that selection for reduced RFI could be made without adversely affecting DG. BF should also decrease, and MWT should increase under selection for reduced RFI. The reduction in BF would depend on the measure of RFI used.     

Effects of correcting missing daily feed intake values on the genetic parameters and estimated breeding values for feeding traits in pigs

Daily feed intake (DFI) is an important consideration for improving feed efficiency, but measurements using electronic feeder systems contain many missing and incorrect values. Therefore, we evaluated three methods for correcting missing DFI data (quadratic, orthogonal polynomial, and locally weighted (Loess) regression equations) and assessed the effects of these missing values on the genetic parameters and the estimated breeding values (EBV) for feeding traits. DFI records were obtained from 1622 Duroc pigs, comprising 902 individuals without missing DFI and 720 individuals with missing DFI. The Loess equation was the most suitable method for correcting the missing DFI values in 5–50% randomly deleted datasets among the three equations. Both variance components and heritability for the average DFI (ADFI) did not change because of the missing DFI proportion and Loess correction. In terms of rank correlation and information criteria, Loess correction improved the accuracy of EBV for ADFI compared to randomly deleted cases. These findings indicate that the Loess equation is useful for correcting missing DFI values for individual pigs and that the correction of missing DFI values could be effective for the estimation of breeding values and genetic improvement using EBV for feeding traits.     

Estimation of genetic parameters of conformation traits in Iranian Thoroughbred horses

The aim of this study was to estimate the genetic parameters of conformation traits in Iranian Thoroughbred race horses. The data set included the conformation records of 607 Thoroughbred horses. In this study, 10 conformation traits were recorded. The effect of sex was significant for length of back line (P < 0.05), withers height (P < 0.05), circumference of front cannon (P < 0.001), and circumference of hind cannon (P < 0.001). The effect of age was significant for all traits (P < 0.01). The genetic parameters were estimated by the restricted maximum likelihood (REML) method using DFREML program. The heritability estimates were for head length 0.39, length of back line 0.41, length of shoulder 0.24, heart girth 0.49, chest width 0.22, withers height 0.38, front cannon height 0.27, circumference of front cannon 0.30, hind cannon height 0.29 and circumference of hind cannon 0.34. The estimates of genetic correlation ranged from 0.18 to 0.96 and those of phenotypic correlation varied from 0.16 to 0.83.     

Quantitative trait loci for leg weakness traits in a Landrace purebred population

Leg weakness in pigs is a serious problem in the pig industry. We performed a whole genome quantitative trait locus (QTL) analysis to find QTLs affecting leg weakness traits in the Landrace population. Half-sib progeny ( n  = 522) with five sires were measured for leg weakness traits. Whole genome QTL mapping was performed using a half-sib regression-based method using 190 microsatellite markers. No experiment-wide significant QTLs affecting leg weakness traits were detected. However, at the 5% chromosome-wide level, QTLs affecting leg weakness traits were detected on chromosomes 1, 3, 10 and 11 with QTL effects ranging from 0.07 to 0.11 of the phenotypic variance. At the 1% chromosome-wide level, QTLs affecting rear feet score and total leg score were detected on chromosomes 2 and 3 with QTL effects of 0.11 and 0.13 of the phenotypic variance, respectively. On chromosome 3 and 10, some QTLs found in this study were located at nearby positions. The present study is one of the first reports of QTLs affecting fitness related traits such as leg weakness traits, that segregate within the Landrace population. The study also provides useful information for studying QTLs in purebred populations.     

Selecting for changes in average “parity curve” pattern of litter size in Large White pigs

This study aimed to analyse genetic background of variation in reproductive performance between parities of a sow and to investigate selection strategies to change the “parity curve”. Total number born (TNB) recorded in Large White sows was provided by Topigs Norsvin. Analysis with basic (BM) and random regression (RRM) models was done in ASReml 4.1. The BM included only a fixed “parity curve”, while RRM included 3rd order polynomials for additive genetic and permanent sow effects. Parameters from RRM were used in simulations in SelAction 2.1. Based on Akaike information criterion, RRM was a better model for TNB data. Genetic variance and heritability estimates of TNB from BM and RRM were increasing with parity from parity 2. Genetically, parity 1 is the most different from parities 7 to 10, whereas most similar to parities 2 and 3. This indicates presence of genetic variation to change the “parity curve”. Based on simulations, the selection to increase litter size in parity 1 only increases TNB in all parities, but does not change the observed shape of “parity curve”, whereas selection for increased TNB in parity 1 and reduced TNB in parity 5 decreases differences between parities, but also reduces overall TNB in all parities. Changing the “parity curve” will be difficult as the genetic and phenotypic relationships between the parities are hard to overcome even when selecting for one parity.     

Genetic parameters and purebred–crossbred genetic correlations for growth,meat quality,and carcass traits in pigs

Growth, meat quality, and carcass traits are of economic importance in swine breeding. Understanding their genetic basis in purebred (PB) and commercial crossbred (CB) pigs is necessary for a successful breeding program because, although the breeding goal is to improve CB performance, phenotype collection and selection are usually carried out in PB populations housed in biosecure nucleus herds. Thus, the selection is indirect, and the accuracy of selection depends on the genetic correlation between PB and CB performance (rpc). The objectives of this study were to 1) estimate genetic parameters for growth, meat quality, and carcass traits in a PB sire line and related commercial CB pigs and 2) estimate the corresponding genetic correlations between purebred and crossbred performance (rpc). Both objectives were investigated by using pedigree information only (PBLUP) and by combining pedigree and genomic information in a single-step genomic BLUP (ssGBLUP) procedure. Growth rate showed moderate estimates of heritability for both PB and CB based on PBLUP, while estimates were higher in CB based on ssGBLUP. Heritability estimates for meat quality traits were diverse and slightly different based on PB and CB data with both methods. Carcass traits had higher heritability estimates based on PB compared with CB data based on PBLUP and slightly higher estimates for CB data based on ssGBLUP. A wide range of estimates of genetic correlations were obtained among traits within the PB and CB data. In the PB population, estimates of heritabilities and genetic correlations were similar based on PBLUP and ssGBLUP for all traits, while based on the CB data, ssGBLUP resulted in different estimates of genetic parameters with lower SEs. With some exceptions, estimates of rpc were moderate to high. The SE on the rpc estimates was generally large when based on PBLUP due to limited sample size, especially for CBs. In contrast, estimates of rpc based on ssGBLUP were not only more precise but also more consistent among pairs of traits, considering their genetic correlations within the PB and CB data. The wide range of estimates of rpc (less than 0.70 for 7 out of 13 traits) indicates that the use of CB phenotypes recorded on commercial farms, along with genomic information, for selection in the PB population has potential to increase the genetic progress of CB performance.     

Estimation of genetic parameters for superovulatory response traits in Japanese Black cows

The aim of this study was to estimate genetic parameters for superovulatory response traits in order to explore the possibility of genetic improvement in Japanese Black cows. We analyzed 19 155 records of the total number of embryos and oocytes (TNE) and the number of good embryos (NGE) collected from 1532 donor cows between 2008 and 2018. A two-trait repeatability animal model analysis was performed for both. Because records of TNE and NGE did not follow a normal distribution, the records were analyzed following no, logarithmic, or Anscombe transformation. Without transformation, the heritability estimates were 0.26 for TNE and 0.17 for NGE. With logarithmic transformation, they were 0.22 for TNE and 0.18 for NGE. With Anscombe transformation, they were 0.26 for TNE and 0.18 for NGE. All analyses gave similar genetic correlations between TNE and NGE, ranging from 0.60 to 0.71. Spearman’s rank correlation coefficient between breeding values of cows with more than 10 records was ≥0.95 with both transformations. Thus, the genetic improvement of TNE and NGE of donor cows could be possible in Japanese Black cattle.