J. Anim Sci. 2007. 85:3209-3217. doi:10.2527/jas.2007-0106
© 2007 American Society of Animal Science
Correlated responses of pre- and postweaning growth and backfat thickness to six generations of selection for ovulation rate or prenatal survival in French Large White pigs
A. Rosendo*,1,2,
L. Canario*,
T. Druet*,
J. Gogué
and
J. P. Bidanel*,3
* INRA UR337 Station de Génétique Quantitative et Appliquée, F-78350 Jouy-en-Josas, France; and
INRA UE332 Domaine de Galle, F-18520 Avord, France
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Abstract
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Correlated effects of selection for components of litter size on growth and backfat thickness were estimated using data from 3 pig lines derived from the same base population of Large White. Two lines were selected for 6 generations on either high ovulation rate at puberty (OR) or high prenatal survival corrected for ovulation rate in the first 2 parities (PS). The third line was an unselected control (C). Genetic parameters for individual piglet BW at birth (IWB); at 3 wk of age (IW3W); and at weaning (IWW); ADG from birth to weaning (ADGBW), from weaning to 10 wk of age (ADGPW), and from 25 to 90 kg of BW (ADGT); and age (AGET) and average backfat thickness (ABT) at 90 kg of BW were estimated using REML methodology applied to a multivariate animal model. In addition to fixed effects, the model included the common environment of birth litter, as well as direct and maternal additive genetic effects as random effects. Genetic trends were estimated by computing differences between OR or PS and C lines at each generation using both least squares (LS) and mixed model (MM) methodology. Average genetic trends for direct and maternal effects were computed by regressing line differences on generation number. Estimates of direct and maternal heritabilities were, respectively, 0.10, 0.12, 0.20, 0.24, and 0.41, and 0.17, 0.33, 0.32, 0.41, and 0.21 (SE = 0.03 to 0.04) for IWB, IW3W, IWW, ADGBW, and ADGPW. Genetic correlations between direct and maternal effects were moderately negative for IWB (–0.21 ± 0.18), but larger for the 4 other traits (–0.59 to –0.74). Maternal effects were nonsignificant and were removed from the final analyses of ADGT, AGET, and ABT. Direct heritability estimates were 0.34, 0.46, and 0.21 (SE = 0.03 to 0.05) for ADGT, AGET, and ABT, respectively. Direct and maternal genetic correlations of OR with performance traits were nonsignificant, with the exception of maternal correlations with IWB (–0.28 ± 0.13) and ADGPW (0.23 ± 0.11) and direct correlation with AGET (–0.23 ± 0.09). Prenatal survival also had low direct but moderate to strong maternal genetic correlations (–0.34 to –0.65) with performance traits. The only significant genetic trends were a negative maternal trend for IBW in the OR line and favorable direct trends for postweaning growth (ADGT and AGET) in both lines. Selection for components of litter size has limited effects on growth and backfat thickness, although it slightly reduces birth weight and improves postweaning growth.
Key Words: genetic parameter • growth • ovulation rate • pig • prenatal survival • selection experiment
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INTRODUCTION
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Genetic improvement has proven to be an effective means of increasing the efficiency of pork production. Even lowly heritable traits, such as litter size at birth, have been successfully selected for, either directly (Tribout et al., 2003
) or through indirect selection on its component traits (Johnson et al., 1999). However, larger litters at birth have been accompanied, in most cases, by unfavorable trends in farrowing and birth-to-weaning piglet survival (Johnson et al., 1999; Tribout et al., 2003; Canario et al., 2006b). Decreased piglet BW has been suggested as a contributor to this increased mortality (Johnson et al., 1999). Indeed, piglet birth weight has been shown to have negative genetic correlations with number of piglets born and birth to weaning survival (Kerr and Cameron, 1995; Roehe, 1999; Rosendo et al., 2007a). However, birth weight and pre-weaning growth traits are genetically complex and depend on both piglet and genetic or foster sow genotypes (Knol et al., 2002; Bouquet et al., 2006). Recent studies (Kaufmann et al., 2000; Ruiz-Flores and Johnson, 2001) suggest that genetic correlations between litter size and direct and maternal effects on piglet growth differ to some extent. Moreover, maternal effects are not necessarily limited to the suckling period and may affect pig postweaning performance (Robison, 1972; Bryner et al., 1992).
A selection experiment was carried out to estimate genetic parameters and responses to selection for components of litter size in the French Large White breed (Blasco et al., 1998; Rosendo et al., 2007b). The main objective of this study was to estimate the correlated responses to selection for either high ovulation rate or high prenatal survival on direct and maternal components of pig preweaning and postweaning growth, as well as backfat thickness.
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MATERIALS AND METHODS
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Animals and Experimental Design
The experiment took place in the INRA experimental herd of Galle (Avord, France). Animal care followed the general guidelines outlined in the European animal welfare regulations (91/630/EC directive).
Two lines of pigs were selected for either high ovulation rate at puberty (OR) or high prenatal survival (PS) over the first 2 parities corrected for ovulation rate at fertilization (ORF). Prenatal survival was computed as (total number born/ORF) + (0.018 x ORF) (Rosendo et al., 2007a). The correction term was introduced to avoid trends in PS associated with variations in OR. The term 0.018 represented an average literature value for the phenotypic regression coefficient of PS on ORF. A third line was kept as an unselected control line (C). At each generation, approximately 50 gilts and 6 to 8 boars from first litters were kept for breeding. Boars were chosen on a within-sire family basis in the 3 lines. Gilts were randomly chosen on a within-dam family basis in the C line and selected on a population basis in the 2 other lines. A mating plan was established to minimize inbreeding at each generation. Additional details on the experimental design are given in Rosendo et al. (2007a, b).
The sow herd was managed under a batch farrowing system. Females were distributed into 7 farrowing batches, which then became postweaning and performance test batches of their progeny. Litters were born in individual farrowing crates. Some cross-fostering (about 5% of the piglets) occurred on a within-line basis during the first 48 h after farrowing. Creep feed was provided to piglets beginning at about 5 d of age. Weaning occurred approximately 28 d postfarrowing. All piglets were weighed at birth (i.e., during the first 12 h after birth), and at 3 and 4 wk of age.
All available offspring from first and second parities were kept in a postweaning unit from 28 to 70 d of age. They were then allotted to a performance test building, in which they were housed in pens of 10 to 12 animals of the same line, where they stayed until the end of the test period, when they reached 90 kg of BW. Lines were randomly allocated to approximately 120 pens at each generation to avoid confounding between pen and selection line. Animals were fed ad libitum with a commercial diet formulated to contain 3,100 kcal of DE/kg and 17% CP during the entire test period. All pigs were weighed at the beginning and end of the test period. Ultrasonic backfat thickness was measured at the same time as final BW. The ultrasonic records were taken on each side of the spine, 4 cm from mid-dorsal line at the levels of the shoulder, the last rib, and the hip joint, respectively.
Statistical Analyses
The traits analyzed were individual piglet BW at birth (IWB), at 3 wk (IW3W), and at weaning (IWW); ADG from birth to weaning (ADGBW), from weaning to the beginning of performance test (ADGPW), and for the performance test period (ADGT); age (AGET); and average backfat thickness (ABT) computed as the mean of the 6 above-mentioned measurements, at the end of performance test. The performance test began at approximately 25 kg of BW and ended around 90 kg of BW. Descriptive statistics for the 8 traits are given in Table 1.
Least Squares Analyses of Line Differences.
The data were first analyzed by least squares (LS) using the GLM procedure of SAS (SAS Inst. Inc., Cary, NC). Mean performances and SE for each line-generation subclass were estimated using a linear model that included the fixed effects of selection line (OR, PS, or C), generation number (G = 0 to 6), and their interaction; parity of the dam; contemporary group (animals tested during the same period in the same building) within generation; sex (female, intact male, or castrate for all traits except ABT, which was measured only on intact males and females); and cross-fostering status (yes or no, except for IWB, AGET, and ABT). The dam and piglet inbreeding coefficients; the exact age of pigs at the different BW measurements (at 3 wk and at weaning); the number of piglets nurtured (preweaning traits and ADGPW); and BW at birth (ADGBW), at weaning (ADGPW), at the beginning (ADGT), and at the end of the test period (AGET and ABT) were included as linear covariates. The exact model used for each trait is given in Table 2. Generations 6 and 7 were grouped in final analyses, because no selection occurred in generation 7 and preliminary analyses showed that line x generation least squares means were similar.
Mixed Model Analyses.
Variance components for the traits and covariances between traits were first estimated using REML methodology (Patterson and Thompson, 1971) applied to univariate and bivariate mixed linear animal models. With the exception of generation and line effects, the fixed part of the model was similar to that used for least squares analyses. The random part of the model initially included a common litter environmental effect, direct and maternal genetic effects, and the correlation between direct and maternal effects. Maternal effects were defined as effects of either the genetic (IWB) or the foster dam (IW3W, IWW, ADGBW, ADGPW). In matrix notation
where y = the vector of observations; X, Wa, Wm, and Wc are known incidence matrices relating observations to fixed and random effects; ß = a vector of fixed effects and covariates; a = the vector of direct genetic effects; m = a vector of maternal (genetic or foster dam) genetic effects; c = the vector of common litter environmental effects; and e = the vector of random residual effects. All random effects were assumed to follow a normal distribution with zero mean and the following distribution parameters:
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where A = the additive relationship matrix; 
= the additive genetic variance for direct effects; 
= the additive genetic variance for maternal effects; 
am = the covariance between direct and maternal additive genetic effects; and 
and 
= the variances for the random common litter environmental and residual effects, respectively. Matrix I is the identity matrix of appropriate dimension in each case. The genetic parameters were estimated using VCE (Neumaier and Groeneveld, 1998) and ASREML (Gilmour et al., 2002) software. Maternal effects were nonsignificant and were consequently removed from the final analyses for AGET, ABT, and ADGT. The final model used for each trait and the significance levels of the test statistics are shown in Table 2
. The models for OR and PS were the same as those used by Rosendo et al. (2007b). Estimated breeding values were then computed as back-solutions of REML analyses at convergence. Genetic trends were estimated by averaging estimated breeding values of animals for each line x generation combination and then regressing them on generation number within each line.
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RESULTS
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Significance levels of fixed effects, random effects, and covariates are given in Table 2. Sow contemporary group and sex affected all traits (P < 0.001). Males were heavier than females at birth (83 ± 6 g) and at weaning (281 ± 40 g), grew faster during the test period (61 ± 4 g/d), and had less backfat (–2.9 ± 0.3 mm) at 90 kg of BW. Castrates had similar BW to females at weaning, had the fastest growth during the postweaning period (9 ± 3 g compared with intact males and females), and had an intermediate growth rate on test (–18 ± 5 g compared with intact males). Sow parity and fostering affected early growth, but had no effects on performance test traits. Second-litter piglets were heavier at birth (92 ± 16 g) and at weaning (895 ± 89 g) than first-parity piglets. The cross-fostering status was not included in the final model for IWB, but was considered in a preliminary analysis to check whether cross-fostered piglets were chosen at random. In fact, cross-fostered piglets were slightly heavier at birth (27 ± 12 g), but had a lower preweaning growth rate than piglets raised by their own dam (–18 ± 3 g), and were hence lighter at weaning (–562 ± 73 g). All traits except IWB were significantly affected by litter inbreeding, which amounted to 15.7, 10.9, and 7.2%, respectively, in PS, OR, and C lines at the end of the experiment (Rosendo et al., 2007a). Mean performance decreased by 159 ± 47 g, 146 ± 48 g, 5.2 ± 2.0 g/d, 15.2 ± 3.6 g/d, 20.2 ± 4.0 g/d, 2.2 ± 0.5 d, and 1.42 ± 0.35 mm, respectively, for IW3W, IWW, ADGBW, ADGPW, ADGT, AGET, and ABT per 10% increase in litter inbreeding. Maternal inbreeding significantly affected only IWB (–68 ± 12 g per 10% increase in inbreeding).
Estimates of heritability of the genetic correlation between direct and maternal effects and of common litter effects are given in Table 3. Both direct and maternal genetic effects determined growth during the suckling and postweaning periods, whereas only direct effects affected performance test traits. Maternal heritabilities were approximately twice as large as direct heritabilities up to weaning, still represented half of direct heritabilities during the postweaning period, and were nonsignificant during the test period. Direct heritability estimates were low (0.10) at birth, then progressively increased to moderate to high values (0.34 to 0.46) after weaning. The only exception concerned ABT, which had a rather low heritability estimate (0.21). Genetic correlations between direct and maternal effects were all negative. The antagonism was low at birth, but was rather strong after birth (–0.59 to –0.74). Common litter effects explained a low to moderate (9 to 19%) proportion of the phenotypic variance, except for ABT, for which a large estimate (0.47) was obtained.
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Table 3. Estimates of heritability, genetic correlation between direct and maternal effects, common litter effects, and phenotypic SD
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Phenotypic and genetic correlations of the 8 traits with OR and PS are presented in Table 4. Phenotypic correlations were all weak (absolute value 
0.12), except the direct correlation between OR and AGET (–0.20 ± 0.03). Direct genetic correlations were low (absolute value 0.20) and nonsignificant, except the correlations of AGET with OR (favorable correlation of –0.23 ± 0.09) and PS (unfavorable correlation of 0.30 ± 0.13). The maternal genetic correlations of OR with growth traits were moderately negative at birth (–0.28 ± 0.13 between OR and IWB) and became increasingly positive after birth (0.06 ± 0.10 to 0.23 ± 0.11). Maternal genetic correlations with PS were all negative, with a strong value at birth (–0.65 ± 0.11), a moderate value for pre-weaning growth rate (–0.34 ± 0.12), and a lower value during the postweaning period (–0.20 ± 0.15).
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Table 4. Estimates of phenotypic and genetic correlations of ovulation rate and prenatal survival with growth and backfat thickness traits
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Least squares and mixed models estimates of genetic trends for the 8 traits are presented in Table 5, and, for the most significant results, in Figures 1 to 3. Global estimates were obtained using least squares, whereas separate trends for direct and maternal effects were estimated using mixed model methodology. Global genetic trends in the OR line showed a significant (P < 0.05) improvement in ADGBW and a tendency toward an improvement in growth rate during the test period (i.e., ADGT and AGET). This tendency became significant (P < 0.05) when estimated using mixed model methodology. A significant decrease in maternal genetic effects was also obtained for IBW (Figure 1). In the PS line, significantly negative global trends were estimated for IW3W and IWW, whereas trends after weaning indicated (ADGPW) or tended to indicate (AGET) an increase in postweaning growth. This increase was significant when estimated with BLUP animal model. Trends for maternal effects were low and nonsignificant, except at birth, where a significantly negative trend was detected in the OR line.
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Figure 1. Difference (selected minus control line) in phenotypic least squares (LS) and average breeding value (BLUP-AM) for direct (dir) and maternal (mat) effects for individual weight at birth (IWB) plotted by generation between the line selected for ovulation rate (a) or prenatal survival (b) and the unselected control line. *P < 0.05 and ** P < 0.01.
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Figure 2. Difference (selected minus control line) in phenotypic least squares (LS) and average breeding value (BLUP-AM) for ADG between 25 and 90 kg (ADGT) plotted by generation between the line selected for ovulation rate (a) or prenatal survival (b) and the unselected control line. *P < 0.05 and **P < 0.01.
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Figure 3. Difference (selected minus control line) in phenotypic least squares (LS) and average breeding value (BLUP-AM) for age at the end of test (AGET) plotted by generation between the line selected for ovulation rate (a) or prenatal survival (b) and the unselected control line. *P < 0.05 and **P < 0.01.
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DISCUSSION
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The first aim of this study was to estimate correlated responses in growth traits and backfat thickness to selection for the 2 major components of litter size (i.e., OR and PS). This objective required estimation of genetic parameters for traits characterizing pre- and post-weaning pig growth up to harvest. Final models included 3 random effects (common birth litter effect, direct and maternal genetic effects) for traits expressed during or shortly after the suckling period and 2 random effects (common birth litter and direct genetic effects) for traits measured later in life. Preliminary analyses were performed with a 4-random-effects model, including the 3 above-mentioned effects plus a permanent sow environmental effect. This latter effect explained a very limited proportion of the genetic variance for all traits and consequently was not considered in subsequent analyses. Both 4- and 3-random-effects models showed a low and nonsignificant maternal effect for ADGT, AGET, and ABT, leading to removal of this effect in the final analyses. The 3-random-effects model is commonly used for early growth traits (Roehe, 1999; Kaufmann et al., 2000; Zhang et al., 2000; Solanes et al., 2004a). Reasonably accurate estimates of genetic parameters were obtained despite the rather limited size of the data set, because of a favorable structure (i.e., many generations, large dam families, and a large proportion of dams and grand-dams with records; Gerstmayr, 1992; Meyer, 1992; Clément et al., 2001).
Our results showed the prominent influence of maternal genetic and litter environmental effects on the genetic variability of early growth traits in pigs. Direct genetic effects were of minor importance at birth, as also shown by Young et al. (1978), Roehe (1999), Knol et al. (2002), and Solanes et al. (2004a). The effect of direct genetic effects then increased, but remained much lower than that of maternal genetic effects until weaning, as also shown by Rodriguez et al. (1994), Kaufmann et al. (2000), and Solanes et al. (2004a). This maternal influence remained important during the postweaning period, in agreement with Zhang et al. (2000), but had a very limited effect during the on-test period. This result is in line with most recent literature estimates (Crump et al., 1997; Zhang et al., 2000; Solanes et al., 2004b). Important maternal heritability estimates were reported for ADG and backfat thickness by Bryner et al. (1992), but their model did not include a random common birth litter effect. Johnson et al. (2002) confirmed the importance of maternal effects for BW at 100 d of age, but observed much lower maternal heritability estimates (0.02 to 0.11) than did Bryner et al. (1992). High estimates of maternal heritability were also obtained in older studies (e.g., Robison, 1972), even for traits that are expressed later in life, but they are likely to be related to a much greater age at weaning. Direct heritability estimates from the current study were similar for growth but lower for backfat thickness than average literature values (Ducos, 1994; Clutter and Brascamp, 1998).
The moderately negative genetic correlation between direct and maternal effects at birth is consistent with the previous results of Roehe (1999) and Knol et al. (2002), but differs slightly from the null or lowly positive correlations obtained by Kaufmann et al. (2000), Knol et al. (2002), and Solanes et al. (2004a), and from the positive estimate reported by Grandinson et al. (2002). These differences may be due to the relative inaccuracy of estimates, but may also reflect breed or environmental differences. The antagonism between direct and maternal genetic effects was much larger at 3 and 4 wk of age than at birth. Although a similar trend toward a stronger antagonism during lactation was obtained in other studies (Kaufmann et al., 2000; Bouquet et al., 2006), it generally remained less pronounced than in the current study. As suggested by Solanes et al. (2004a), the distribution of supplementary feed to piglets compensating for poor milk production may lead to a negative correlation between direct and maternal effects. Moreover, the direct-maternal genetic correlation can be overestimated (in absolute value) in the presence of genotype x environment interaction or direct-maternal environmental correlations (Robinson, 1996).
Very few estimates of genetic correlations involving ovulation rate or prenatal survival are available in the literature. Estimates of genetic relationships between litter size and production traits are more numerous. Several literature reviews have shown that litter size is, on average, weakly correlated with growth and carcass traits (Brien, 1986; Haley et al., 1988). It has been hypothesized (Rauw et al., 1999; Holm et al., 2004), however, that selection for lean growth might result in negative genetic relationships with litter size in high-producing animals. Biologically, resource allocation for growth could occur at the expense of the ability of young sows to give birth to large litters. Similarly, selection for leanness could reduce the sow’s ability to mobilize lipid during late gestation and the suckling period (Holm et al., 2004). Indeed, several recent publications have reported antagonistic relationships between sow reproduction and growth (Ducos and Bidanel, 1996; Hermesch et al., 2000; Holm et al., 2004; Arango et al., 2005) or backfat thickness (Chen et al., 2003). Nevertheless, near-zero (Noguera et al., 2002a) or even favorable (Serenius et al., 2004) genetic correlations were obtained in other studies. These differences may in some cases be related to the limited precision of estimates, but also reflect genetic differences in average performance levels and metabolic efficiency, as well as variation in management practices (including age at farrowing).
In any case, our results showed globally low genetic correlations of ovulation rate with growth rate and backfat thickness. This was particularly true for direct effects, as a single significant genetic correlation was obtained for OR with AGET. In particular, the genetic correlation between OR and ADG was close to zero, unlike the results of Young et al. (1977) and Bidanel et al. (1996), who reported significant positive genetic correlations between the 2 traits (0.41 and 0.20, respectively). Ruiz-Flores and Johnson (2001) reported a strong positive direct genetic correlation between birth weight and OR (0.44), but much lower values for subsequent BW and backfat thickness. They also obtained estimates of maternal genetic correlations with piglet BW at birth and at weaning (–0.26 and 0.11, respectively) that were very similar to those reported here. The low direct genetic correlation between most growth traits and PS is also consistent with the value obtained by Bidanel et al. (1996) and the estimates between growth traits and litter size at birth reported by Ruiz-Flores and Johnson (2001). There do not seem to be any previous estimates of the maternal genetic correlations between PS and growth traits in the literature, the only related result being the strong negative estimates between growth and litter size obtained in the Nebraska experiment (Ruiz-Flores and Johnson, 2001). The strongest negative correlation was that between PS and IBW, which may be because of uterine space acting as a limiting factor and resulting in a negative correlation between maternal effects on embryonic and fetal growth and PS.
Estimated genetic trends were globally consistent with genetic parameter estimates. Nonsignificant trends were obtained for the traits weakly correlated with OR and PS (i.e., the majority of growth traits, as well as backfat thickness). The only exceptions concerned ADGT, where significant trends were estimated in spite of near-zero genetic correlations, and maternal effects, mainly in the PS line, with nonsignificant trends in spite of strong negative genetic correlations. These latter discrepancies are likely to stem from the strong negative correlations between direct and maternal effects for these traits, which would largely reduce the efficiency of selection on both components. The significant response obtained for ADGT and AGET is consistent with the genetic correlations of OR and PS with AGET, but somewhat larger than would be expected based on the correlations with ADGT.
The lack of response for most traits is in agreement with the results of selection experiments for increased litter size (Noguera et al., 2002b; Petry et al., 2004). Similarly, no significant response in litter size was obtained in several selection experiments for lean growth rate (Fredeen and Mikami, 1986; Cleveland et al., 1988; Kerr and Cameron, 1995). Ruiz-Flores and Johnson (2001) reported correlated responses for growth and backfat that differed somewhat between lines selected for litter size and its components. The negative trends for maternal effects on birth weight are consistent with the results of Johnson et al. (1999). Decreasing piglet BW by selecting on maternal effects might thus be associated with improved PS. However, it could also have important drawbacks, as lighter piglets are associated with a greater risk of mortality at birth (Canario et al., 2006a) and during the suckling period. Wilson et al. (1999) proposed to solve this problem by selecting for placental efficiency (i.e., the ratio of birth weight to placental weight), but no increase in litter size or piglet survival could be obtained after 4 generations of selection (Mesa et al., 2005).
In conclusion, correlated responses of direct effects for growth rate and backfat thickness to selection for either OR or PS were small for most traits. Significant, albeit rather limited, favorable trends were obtained for growth rate during the test period. A negative trend was also observed for maternal effects on birth weight. This negative trend is likely to be undesirable, as lower birth weights are generally associated with a higher risk of mortality. Further research is warranted to find the best method of increasing litter size without causing deterioration in birth weight or birth to weaning survival.
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Footnotes
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1 Financial support was provided to the first author by Consejo Nacional de Ciencia y Tecnologia, Colegio de Postgraduados and Secretaria de Educacion Publica, Programa de Becas Complemantarias, Montecillo, México. 
2 Present address: Colegio de Postgraduados, Campus Veracruz km 26.5 carr. Fed. Veracruz-Xalapa, Predio Tepetates, Mpio. De Manlio Fabio Altamirano CP 91700, Apdo. Postal 421, Veracruz, Mexico.
3 Corresponding author: jean-pierre.bidanel{at}jouy.inra.fr
Received for publication February 17, 2007.
Accepted for publication June 18, 2007.
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Abstract
INTRODUCTION
