Genetic parameters for piglet survival, litter size and birth weight or its variation within litter in sire and dam lines using Bayesian analysis

Kapell, D. N. R. G.; Ashworth, Cheryl; Knap, P. W.; Roehe, R.

doi:10.1016/j.livsci.2010.07.005

Cited by 65 publications

(65 citation statements)

References 23 publications

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“…In fact, there is a linear relationship between piglet survival and coefficient of variation for within-litter birth weight, and a curvilinear relationship between average birth weight and mortality of piglets (Fahmy and Bernard, 1971). Although there is also a favorable correlation between pre-weaning survival and within-litter variation in birth weight from the genetic perspective (Knol et al, 2002;Kapell et al, 2011), it is worth emphasizing that the adverse effects of high variation in birth weight on piglet survival are mainly due to an increase in the proportion of small piglets (Milligan et al, 2002a) since normal variation in birth weight has little effect on piglet survival in healthy litters (Milligan et al, 2001).…”

Section: Pre-weaning Mortalitymentioning

confidence: 99%

“…At the same time, a maternal line selected on litter size at weaning in rabbits for 21 generations improved the number of progeny born alive and litter size at weaning, compared with selection on litter size at birth (García and Baselga, 2002), suggesting that it is effective in both promoting litter size at birth and survival rate during lactation (Savietto et al, 2014). Additionally, it is feasible to select for within-litter uniformity in birth weight (Damgaard et al, 2003;Kapell et al, 2011) to improve piglet survival (Canario et al, 2010). A selection experiment on within-litter birth-weight variation in rabbits yielded a favorable response and decreased pre-weaning morbidity (Garreau et al, 2004).…”

Section: Genetic Selectionmentioning

confidence: 99%

“…Over the last few decades, selection for highly prolific sows has resulted in an increase in litter size (Quiniou et al, 2002); however, this is positively related to a substantial increase in pre-and post-natal mortality before weaning (Johnson et al, 1999) due to greater within-litter variation in birth weights characterized by a higher proportion of low-birth-weight piglets in the litter (Milligan et al, 2002a;Quesnel et al, 2008;Kapell et al, 2011). There is a tendency for the proportion of runt piglets to be higher in litters in which birth weights of piglets are highly variable (van der Lende and Dejager, 1991).…”

Section: Introductionmentioning

confidence: 99%

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

Yuan

Zhu

Shi

et al. 2015

J. Zhejiang Univ. Sci. B

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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.

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Section: Pre-weaning Mortalitymentioning

confidence: 99%

Section: Genetic Selectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Yuan

Zhu

Shi

et al. 2015

J. Zhejiang Univ. Sci. B

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“…Whether plastic genotypes with high V E or stable genotypes with small V E are better capable of handling unpredictable environments is under debate. In livestock little is known about trade-offs between V E and means of other traits, except that uniformity of birth weight in litter-bearing animals does increase the survival of the offspring, e.g., in pigs (Kapell et al 2011) and rabbits (Garreau et al 2008).…”

mentioning

confidence: 99%

Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

2015

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There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of other traits, however. A genetic covariance between these is expected to lead to nonlinearity between them, for example between birth weight and survival of piglets, where animals of extreme weights have lower survival. The objectives were to derive this nonlinear relationship analytically using multiple regression and apply it to data on piglet birth weight and survival. This study provides a framework to study such nonlinear relationships caused by genetic covariance of environmental variance of one trait and the mean of the other. It is shown that positions of phenotypic and genetic optima may differ and that genetic relationships are likely to be more curvilinear than phenotypic relationships, dependent mainly on the environmental correlation between these traits. Genetic correlations may change if the population means change relative to the optimal phenotypes. Data of piglet birth weight and survival show that the presence of nonlinearity can be partly explained by the genetic covariance between environmental variance of birth weight and survival. The framework developed can be used to assess effects of artificial and natural selection on means and variances of traits and the statistical method presented can be used to estimate trade-offs between environmental variance of one trait and mean levels of others.KEYWORDS genetics of environmental variance; optimum trait; fitness; complex traits; mass selection I N the classic model of quantitative genetics, the phenotype is assumed to be the sum of an effectively infinite number of genes and environmental effects; i.e., P ¼ G þ E (Falconer and Mackay 1996; Lynch and Walsh 1998). The phenotypic variance is the sum of the genetic (V G ) and environmental (V E ) variance. It is assumed that the environmental variance is homogeneous across genotypes, but recently there is evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its V E ; is under genetic control (Hill and Mulder 2010). This might be expressed as genetic heterogeneity in the withinindividual variance of a trait with repeat measurements, such as weight of individual piglets in a litter or total litter weight across parities, or as a difference in within-family variance for traits such as juvenile body weight expressed once.The median genetic coefficient of variation for V E (GCV VE ¼ s Av =V E ; where s Av is additive genetic variance in V E ) is 0.3 based on a review of 14 studies with estimates of genetic variance in V E primarily on livestock populations (Hill and Mulder 2010). This indicates that V E could be increased or decreased by 30% if changed by one genetic standard deviation. These analyses were mainly based on genetic analysis...

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“…Estimated heritabilities were in the range from 0.03 to 0.26. Kapell et al (2011) used a Bayesian analysis for reproductive traits. Wittenbourg et al (2011) studied within litter variability of piglet birth weight and its relationship to piglet survival.…”

Section: Pigsmentioning

confidence: 99%

Recent developments in cattle, pig, sheep and horse breeding - a review

et al. 2014

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The aim of this review was to summarize new genetic approaches and techniques in the breeding of cattle, pigs, sheep and horses. Often production and reproductive traits are treated separately in genetic evaluations, but advantages may accrue to their joint evaluation. A good example is the system in pig breeding. Simplified breeding objectives are generally no longer appropriate and consequently becoming increasingly complex. The goal of selection for improved animal performance is to increase the profit of the production system; therefore, economic selection indices are now used in most livestock breeding programmes. Recent developments in dairy cattle breeding have focused on the incorporation of molecular information into genetic evaluations and on increasing the importance of longevity and health in breeding objectives to maximize the change in profit. For a genetic evaluation of meat yield (beef, pig, sheep), several types of information can be used, including data from performance test stations, records from progeny tests and measurements taken at slaughter. The standard genetic evaluation method of evaluation of growth or milk production has been the multi-trait animal model, but a test-day model with random regression is becoming the new standard, in sheep as well. Reviews of molecular genetics and pedigree analyses for performance traits in horses are described. Genome -wide selection is becoming a world standard for dairy cattle, and for other farm animals it is under development.

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Genetic parameters for piglet survival, litter size and birth weight or its variation within litter in sire and dam lines using Bayesian analysis

Cited by 65 publications

References 23 publications

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

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

Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

Recent developments in cattle, pig, sheep and horse breeding - a review

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