Selection potential of different prolificacy traits in the finnish landrace and large white populations

Variance and covariance components for piglet survival in different periods were estimated from individual records of 133 004 Danish Landrace piglets and 89 928 Danish Yorkshire piglets, using a liability threshold model including both direct and maternal additive genetic effects. At the individual piglet level, the estimates of direct heritability in Landrace were 0.035, 0.057 and 0.027, and in Yorkshire the estimates were 0.012, 0.030 and 0.025 for liability of survival at farrowing (SVB), from birth to day 5 (SV5) and from day 6 to weaning (SVW), respectively. The estimates of maternal heritability for SVB, SV5 and SVW were, respectively, 0.057, 0.040 and 0.030 in Landrace, and 0.050, 0.038 and 0.019 in Yorkshire. Both direct and maternal genetic correlations between the three survival traits were low and not significantly different from zero, except for a moderate direct genetic correlation between SVB and SV5 and between SV5 and SVW in Landrace. Direct and maternal genetic correlations between piglet birth weight (BW) and SV5 were moderately high, but the correlations between BW and SVB and between BW and SVW were low and most of them were not significantly different from zero. These results suggest that effective genetic improvement in piglet survival before weaning by selection should be based on both direct and maternal additive genetic effects and treat survival in different periods as different traits.

Section: Discussionsupporting

confidence: 91%

Variance and covariance components for liability of piglet survival during different periods

Sörensen

Lund

2008

“…In this study, survival as SB was analysed at sow level, since individual piglet information was not available. These estimated heritabilities were in the same range as what other studies that analysed survival at the sow level, but using numbers of stillborn piglets as the trait, found (0.02 to 0.12) (Hanenberg et al, 2001;Serenius et al, 2004a and2004b).…”

Section: Reproduction Traitssupporting

confidence: 74%

“…Studies analysing and comparing different breeds showed that there are clear differences in genetic parameters between breeds (See et al, 1993;Roehe and Kennedy, 1995;Su et al, 2008). Only a few studies (Ferraz and Johnson, 1993;Hermesch et al, 2000c;Serenius et al, 2004b) have used data from Large White pigs in their studies to compare different breeds, and none of these studies differentiated between sire and dam line within the breed. The restriction of the dataset of the dam line showed the effect of the change of parameters, given a more recent base population.…”

Section: Discussionmentioning

confidence: 99%

“…These heritabilities are generally low, but the genetic variation is large enough to provide improvement through breeding. Correlations between survival traits and reproduction traits show contradictory results in the literature (Serenius et al, 2004b;Rosendo et al, 2007b;Su et al, 2007), if considered at all, and there are few reports of correlations between piglet survival traits and production traits (Hermesch et al, 2000c;Serenius et al, 2004a).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Estimation of genetic associations between reproduction and production traits based on a sire and dam line with common ancestry

Kapell

Ashworth

Walling

et al. 2009

Genetic parameters for survival, reproduction and production traits were estimated for a sire and dam line, originating from one Large White breed separated more than 25 years ago. The change in parameters due to different selection pressure on reproduction and production traits in both lines was also examined. Data collected between 1990 and 2007 were available for the analysis of reproduction traits in 4713 litters (sire line) and 14 836 litters (dam line) and for the production traits in 58 329 pigs (sire line) and 108 912 pigs (dam line). Genetic parameters were estimated using a Bayesian approach. Average phenotypic differences between lines were substantial with 1.5 more piglets born in the dam line and 1.7 mm less backfat thickness (BF) in the sire line. Based on a multiple trait analysis which included both reproduction and production traits, heritabilities for survival and litter size traits in the sire (or dam) line were estimated at 0.03 6 0.01 (0.06 6 0.01) for percentage of stillborn piglets (SB), 0.10 6 0.03 (0.11 6 0.01) for total number of piglets born (NBT) and 0.09 6 0.03 (0.09 6 0.01) for number of piglets born alive. Heritabilities for production traits were estimated at 0.29 6 0.01 (0.29 6 0.01) for average daily gain, 0.50 6 0.01 (0.42 6 0.01) for BF and 0.41 6 0.01 for muscle depth. Selection pressure on litter size in the dam line resulted in a slightly unfavourable correlation for SB-NBT (0.21 6 0.11), which was only marginally unfavourable in the sire line (0.06 6 0.24). Selection pressure on BF in the sire line may have resulted in the moderately undesirable correlation with SB (20.46 6 0.15), which was not significant in the dam line (20.08 6 0.06). Changing the base population in the dam line to animals born since the year 2000 indicated that selection pressure on different traits has altered the heritabilities and correlations of the traits within the line. The undesirable correlations between survival at birth and reproduction traits or production traits were low so that simultaneous improvement of all traits can be achieved. Heritabilities for survival at birth and reproduction traits were low, but genetic variation was substantial and extensive pedigree information can be used to improve the accuracy of breeding values, so that genetic improvement is expected to be efficient.

“…The moderate to high values of heritability estimated for gestation length during last decade (Hanenberg et al, 2001;Serenius et al, 2004;Nguyen et al, 2006) have increased its importance as a potential breeding goal to improve the efficiency of the sow per time unit. On the other hand, an increase in gestation length has been related with an improved piglet vitality at birth and the reduced stillbirths (Zaleski and Hacker, 1993;Leenhouwers et al, 1999;Knol et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

Empirical Bayes factor analyses of quantitative trait loci for gestation length in Iberian × Meishan F2 sows

Casellas

Varona²,

Muñoz³

et al. 2008

The aim of this study was to investigate chromosomal regions affecting gestation length in sows. An experimental F 2 cross between Iberian and Meishan pig breeds was used for this purpose and we genotyped 119 markers covering the 18 porcine autosomal chromosomes. Within this context, we have developed a new empirical Bayes factor (BF) approach to compare between nested models, with and without the quantitative trait loci (QTL) effect, and after including the location of the QTL as an unknown parameter in the model. This empirical BF can be easily calculated from the output of a Markov chain Monte Carlo sampling by averaging conditional densities at the null QTL effects. Linkage analyses were performed in each chromosome using an animal model to account for infinitesimal genetic effects. Initially, three QTL were detected at chromosomes 6, 8 and 11 although, after correcting for multiple testing, only the additive QTL located in cM 110 of chromosome 8 remained. For this QTL, the allelic effect of substitution of the Iberian allele increased gestation length in 0.521 days, with a highest posterior density region at 95% ranged between 0.121 and 0.972 days. Although future studies are necessary to confirm if detected QTL is relevant and segregating in commercial pig populations, a hot-spot on the genetic regulation of gestation length in pigs seems to be located in chromosome 8.