Genetic parameters of piglet survival and birth weight from a two-generation crossbreeding experiment under outdoor conditions designed to disentangle direct and maternal effects.
ABSTRACT Multivariate Bayesian linear-threshold models were used to estimate genetic parameters of peri- and postnatal piglet survival and individual birth weight of piglets reared under outdoor conditions. Data of 21,835 individual piglet observations were available from a 2-generation crossbreeding experiment selected for direct and maternal genetic effects of postnatal piglet survival on piglet and dam levels, respectively. In the first generation, approximately one-half of the Landrace sires used were selected for large or average breeding values of maternal genetic effects on postnatal piglet survival, whereas in the second generation the Large White sires used were selected for direct genetic effects of the same trait. Estimates of direct and maternal heritability were 0.21 and 0.15, 0.24 and 0.14, and 0.36 and 0.28 for piglet survival at birth and during the nursing period, and individual birth weight, respectively. In particular, direct heritabilities are substantially larger than those from the literature estimated for indoor-reared piglets, suggesting that genetic effects of these traits are substantially greater under outdoor conditions. Direct or maternal genetic correlations between survival traits or with birth weight were small (ranging from 0.06 to 0.17), indicating that peri- and postnatal survival are genetically under rather different control, and survival was only slightly positively influenced by birth weight. There were significant (P < 0.05) negative genetic correlations between direct and maternal genetic effects within each of the analyzed traits ranging from -0.36 to -0.45, which have to be considered when selecting for piglet survival. Adjustment of traits for litter size or inclusion of genetic groups showed insignificant effects on the magnitude of the estimated genetic parameters. The magnitude of genetic parameters suggested that there is substantial potential for genetic improvement of survival traits and birth weight in direct and maternal genetic effects, especially when piglets are kept under outdoor conditions.
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ABSTRACT: Birth weight is an economically important trait in pig production because it directly impacts piglet growth and survival rate. In the present study, we performed a genome wide survey of candidate genes and pathways associated with individual birth weight (IBW) using the Illumina PorcineSNP60 BeadChip on 24 high (HEBV) and 24 low estimated breeding value (LEBV) animals. These animals were selected from a reference population of 522 individuals produced by three sires and six dam lines, which were crossbreds with multiple breeds. After quality-control, 43,257 SNPs (single nucleotide polymorphisms), including 42,243 autosomal SNPs and 1,014 SNPs on chromosome X, were used in the data analysis. A total of 27 differentially selected regions (DSRs), including 1 on Sus scrofa chromosome 1 (SSC1), 1 on SSC4, 2 on SSC5, 4 on SSC6, 2 on SSC7, 5 on SSC8, 3 on SSC9, 1 on SSC14, 3 on SSC18, and 5 on SSCX, were identified to show the genome wide separations between the HEBV and LEBV groups for IBW in piglets. A DSR with the most number of significant SNPs (including 7 top 0.1% and 31 top 5% SNPs) was located on SSC6, while another DSR with the largest genetic differences in F ST was found on SSC18. These regions harbor known functionally important genes involved in growth and development, such as TNFRSF9 (tumor necrosis factor receptor superfamily member 9), CA6 (carbonic anhydrase VI) and MDFIC (MyoD family inhibitor domain containing). A DSR rich in imprinting genes appeared on SSC9, which included PEG10 (paternally expressed 10), SGCE (sarcoglycan, epsilon), PPP1R9A (protein phosphatase 1, regulatory subunit 9A) and ASB4 (ankyrin repeat and SOCS box containing 4). More importantly, our present study provided evidence to support six quantitative trait loci (QTL) regions for pig birth weight, six QTL regions for average birth weight (ABW) and three QTL regions for litter birth weight (LBW) reported previously by other groups. Furthermore, gene ontology analysis with 183 genes harbored in these 27 DSRs suggested that protein, metal, ion and ATP binding, viral process and innate immune response present important pathways for deciphering their roles in fetal growth or development. Overall, our study provides useful information on candidate genes and pathways for regulating birth weight in piglets, thus improving our understanding of the genetic mechanisms involved in porcine embryonic or fetal development.International journal of biological sciences 01/2014; 10(3):236-244. · 3.17 Impact Factor
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ABSTRACT: Explanations for positive and negative genetic correlations between growth and fitness traits are essential for life-history theory and selective breeding. Here, we test whether growth and survival display genetic trade-off. Furthermore, we assess the potential of third-party traits to explain observed genetic associations. First, we estimated genetic correlations of growth and survival of rainbow trout. We then explored whether these associations are explained by genetic correlations with health, body composition and maturity traits. Analysis included 14 traits across life stages and environments. Data were recorded from 249 166 individuals belonging to 10 year classes of a pedigreed population. The results revealed that rapid growth during grow-out was genetically associated with enhanced survival (mean r(G) = 0.17). This resulted because genotypes with less nematode caused cataract grew faster and were more likely to survive. Fingerling survival was not genetically related to weight or to grow-out survival. Instead, rapid fingerling growth made fish prone to deformations (r(G) = 0.18). Evolutionary genetics provides a theoretical framework to study variation in genetic correlations. This study demonstrates that genetic correlation patterns of growth and survival can be explained by a set of key explanatory traits recorded at different life stages and that these traits can be simultaneously improved by selective breeding.Evolutionary Applications 11/2012; 5(7):732-45. · 4.15 Impact Factor