Genetics of growth in piglets and the association with homogeneity of body weight within litters

Genetics of growth in piglets and the association with homogeneity of body weight within litters L. Canario, H. Lundgren, M. Haandlykken and L. Rydhmer J Anim Sci 010.88:140-147. doi: 10.57/jas.009-056 originally published online Jan 15, 010; The online version of this article, along with updated information and services, is located on the World Wide Web at: http://jas.fass.org/cgi/content/full/88/4/140 www.asas.org

Genetics of growth in piglets and the association with homogeneity of body weight within litters L. Canario,* 1 H. Lundgren,* M. Haandlykken, and L. Rydhmer* *Swedish University of Agricultural Sciences, Department of Animal Breeding and Genetics, Box 70, S-75007 Uppsala, Sweden; and Norsvin, NO-04 Hamar, Norway ABSTRACT: The objective of this study was to examine the genetic basis of homogeneity in piglets and the genetic correlations with litter size and growth during lactation. Genetic parameters for variation in piglet BW within litters at birth and at wk of age, and in the BW of individual piglets at wk (BW) were estimated from the Norwegian Landrace nucleus population. Data on BW were collected from 146,57 piglets from 14,045 litters in 58 herds. Body weight at birth and at wk of age was recorded for 1,18 piglets from 5 nucleus herds. Litter data were evaluated using multivariate trait models. The heritability estimates for the SD of BW at birth and at wk (SDBW) were in agreement with the literature (0.10 and 0.08, respectively). The genetic correlation for the number of piglets born alive and the mean BW at wk was negative ( 0.40 ± 0.07), and the correlation of number of piglets born alive with SDBW was close to zero ( 0.0 ± 0.11). The genetic correlation between the SD of BW at birth and SDBW was moderate (0.51 ± 0.1). The mean BW at birth was genetically correlated with mean BW at wk (0.59 ± 0.16) but was independent of SDBW (0.08 ± 0.7). The estimates of direct and maternal heritability for BW were 0.0 and 0.07, respectively, and the genetic correlation between the components was negative ( 0.4 ± 0.10). The genetic correlation of SDBW with the maternal effect on BW was positive and strong (0.66 ± 0.08), whereas a negative correlation was found with the direct effect on BW ( 0.18 ± 0.14). These results suggest that it is possible to select for mean BW at birth without an increase in within-litter heterogeneity at wk of age. A more efficient strategy would be to consider both the direct and the maternal effects on BW in the genetic evaluation, together with SDBW. Thus, it is possible to avoid the increase in within-litter heterogeneity that would occur as a result of selection performed at wk on a litter trait such as mean BW. Key words: genetic correlation, growth, heterogeneity, piglet body weight, sow, within-litter standard deviation 010 American Society of Animal Science. All rights reserved. J. Anim. Sci. 010. 88:140 147 doi:10.57/jas.009-056 INTRODUCTION In the pig industry, the lack of uniformity in BW within litters is an important source of concern because it is likely to alter the ease of management of pigs in later stages of production, which may result in a loss of income for the farmer (Roberts and Deen, 1995). Heterogeneity is a problem mainly for piglets of reduced BW, which suffer from delayed growth (Foxcroft et al., 006). The full development of each individual within a litter is seldom achieved; the growth realized is the outcome of interactions between many genetic and environmental factors. Differences in BW between individuals within the same litter are accentuated when there 1 Corresponding author: laurianne.canario@jouy.inra.fr Received April 0, 009. Accepted December 1, 009. is competition for resources such as feed and space. Under these conditions, larger piglets are more efficient at gaining access to milk than their smaller littermates (Pluske and Williams, 1988; Wolter et al., 00). The degree of heterogeneity within litters increases as a response to selection for litter size (Johnson et al., 1999). In general, this selection results in larger litters, increased losses before weaning and decreased piglet growth, but the genetic relationship between litter size or mean BW at birth (MBWB) and heterogeneity is reported to be positive (Huby et al., 00; Damgaard et al., 00). Many breeding organizations wish to improve production by selecting for piglet growth. The maternal effect (the genotype of the sow) explains most of the genetic variation in birth weight (Hermesch et al., 001; Arango et al., 006). However, with the progression of lactation, the genotype of the piglet (the direct effect) accounts for an increasing proportion of the variation in piglet BW (Grandinson et al., 005). 140

Genetics of homogeneous growth in piglets 141 This study investigated the consequences of selection for piglet growth on the homogeneity in BW within litters. The objectives were to estimate genetic parameters for piglet growth and within-litter variation in piglet BW at farrowing and at wk of age, and to estimate the genetic correlations of the direct and maternal genetic effects on piglet BW with within-litter heterogeneity. MATERIALS AND METHODS The approval of an Animal Care and Use Committee was not required for this study because the data were derived from an existing database. Selection History of the Norwegian Landrace Population The selection goal of the studied population is complex, with more than 0 traits included in the genetic evaluation. Selection for litter size was begun approximately 15 yr ago, whereas piglet growth was incorporated in the breeding goal more recently. In 007, litter size accounted for 4% of the breeding goal, and litter BW (adjusted for litter size) accounted for 1%. These criteria are considered different traits over the first parities of each sow. Breeding for larger litters has been successful; the average number of piglets born alive has increased from 11.0 to 1.4 piglets during the last decade. From 004 to 006, the gain in litter weight was 0.80 kg (Norsvin, 008). The purpose of selection for piglet BW was to increase the milking ability of the sows and to maintain an increased average piglet BW (B. Zumbach, Norsvin, personal communication). Today, the genetic evaluation includes piglet BW at wk of age, both as a maternal trait and as a direct trait of the piglet. Animals and Data Recording Data from purebred Landrace piglets and their dams were collected in Norwegian nucleus herds related to the pig breeding company Norsvin (Hamar, Norway). The sows were inseminated with semen from the AI station at Norsvin. The average herd size, which was calculated as the number of sows farrowing per herd per year, was variable and rather small (mean = 46, SD = 4 in data set ). Most herds were managed during farrowing without a strict batch system. The sows entered the farrowing unit approximately 1 wk before the expected date of farrowing and were housed in individual farrowing pens. Parturition was not induced on a routine basis. Birth assistance was limited (15%). Most castrations were performed during the week after birth. Since 00, castration has been performed under anesthesia by a veterinarian, in agreement with the national directives on welfare (Skarstad and Borgen, 007). The sows were provided access to feed ad libitum during lactation. The piglets were weaned at 4 to 7 wk of age. From 001, farmers of all the nucleus herds were asked to record the individual BW of all piglets alive at wk of age. All farmers used the same type of mobile electronic scale (Antonson A/S, Gressvik, Norway), which has a precision of 100 g. The farmers were instructed to weigh the animals at 17 to 5 d of age, and to record piglet sex at the same time (male, female, or castrate). Two data sets were constructed. The first data set included individual BW obtained from piglets at birth (or within 4 h) and at approximately wk of age. These data were recorded between 001 and 005 in 5 nucleus herds located across Norway. In these herds, fewer than 4% of the piglets were cross-fostered. As a consequence, this practice was not taken into account in the models of analyses. For the purpose of the analysis, fostered piglets were considered dead. The parity of the sows ranged from 1 to 4. The data set contained data on 981 sows with 1,18 piglets born alive, of which 10,48 were weighed twice. The pedigree file included,149 animals. The second data set was much larger and comprised data collected from 00 to 007 on 58 nucleus herds located across Norway. It included data on the BW of piglets at wk of age. The frequency of cross-fostering was approximately 10% (M. Handlykken, Norsvin, personal communication), but it was not always recorded and therefore had to be ignored in the model used to analyze the data. The parity of the sows ranged from 1 to 4. The data set contained data on 9,475 sows and 47 sires, with 14,045 litters and 146,57 piglets. Among farrowing sows, 5% had data on their own piglet BW in the data set. The pedigree file included 15,550 and 155,719 animals, which were used for the analyses performed at the litter and piglet level, respectively. Statistical Analyses The MBWB and that at wk of age (MBW) were calculated from individual BW, as were the within-litter SD of BW at birth (SDBWB) and at wk of age (SDBW). Only litters in which at least 6 piglets were weighed at wk were included in the analyses. The NBA was defined as the number of piglets weighed at birth. Data set 1 allowed an analysis of the correlations in litter traits between those measured at birth and at wk of age. Data set allowed an analysis of the direct and maternal components of piglet BW at wk and their correlations with SDBWB. With data set 1, the models for the analysis of litter traits included the following effects: y birth = parity + month + sex ratio + NBA + hy + pe + a + e; [1] y wk = parity + month + sex ratio + NBA + age + hy + pe + a + e, []

14 where y i is the observation for a given sow trait, recorded at birth or wk; parity is the fixed effect of the parity of the sow, month is the fixed effect of month of farrowing, sex ratio is the fixed effect associated with the percentage of noncastrated males identified in the litter at birth or wk, age is the fixed effect of litter age at wk (17 to 5 d), and hy is a vector of random herd-year effects. The models also included a random permanent environmental effect (pe), which affects the sow, an additive genetic effect (a), and a residual effect (e). The multitrait combination analyzed was [MBWB, SDBWB, MBW, SDBW]. In data set, piglets with BW recorded outside the range of kg (.5 SD 1 kg) to 1 kg (+.5 SD) were considered to be errors of registration and were deleted from the data set. Piglet BW was blanked if the sex was not documented. A herd was required to provide data from a minimum of 15 sows to be considered for the study. The first statistical model used to analyze litter traits was the same as that described in Eq. ; it was applied on the trait combination [MBW SDBW]. Second, to estimate genetic relationships with litter size, NBA was added as a trait and was thus not considered a covariate for the other traits: Canario et al. herd-year effects associated with BW and SDBW; a BW is a vector of the direct (piglet) genetic effect associated with BW; m BW is a vector of the maternal (sow) genetic effect associated with BW; a SDBW is a vector of the direct (sow) genetic effect associated with SDBW; pe BW and pe SDBW are vectors of the permanent environment of the sow associated with BW and SDBW; l BW is a vector of the common environment of the litter associated with BW; and e BW and e SDBW are vectors of random residual effects associated with BW and SDBW. All random effects were assumed to follow the (co)variance structure a Var m a ê SD Var hy hy ê Var pe pe ê σ σ σ = û ú ê SD SD abw ambw aasdbw σ σ mbw masdbw σasdbw = σ ê = σ ê hy σ σ hyhysdbw hysd pe σ pepesdbw σ pesd ú Ä I, û ú Ä I, û Ä A, y wk = parity + month + sex ratio + age + hy + pe + a + e. [] The associated multitrait combination analyzed was [NBA MBW SDBW]. The statistical model used to analyze individual piglet BW at wk (BW) included fixed effects (see equation below), random direct (a) and maternal (m) additive genetic effects, a sow permanent environmental effect (pe), a common litter effect (l), and a residual effect (e): y BW = parity + month + sex + age + hy + pe + l + a + m + e, [4] where y BW is the observation on piglet BW. Fixed effects were defined as in the previous model (Eq. ) but included sex of the piglet (sex) instead of sex ratio. The genetic correlation between BW and SDBW was estimated by fitting the following model: y y ê SD b hy = X b + Z 1 hy ê SD ê + Z pe êpe SD SD l e BW + Z 4 + ê 0 ê e + Z SDBW a m êa, SD where y SDBW is the observation on sow SDBW; X and Z 1 to Z 4 are incidence matrices; b BW and b SDBW are vectors of fixed effects associated with BW and SDBW; hy BW and hy SDBW are vectors of random û ú Var ê l = I σ l, and Var e σ 0 e. e = ê SD ê ú Ä I σ esd û The residuals were set to be independent (i.e., the residual covariance was zero); A is the additive genetic relationship matrix, and I is an incidence matrix. The mean values and SD of all traits are shown in Table 1. The genetic variance and covariance components were estimated with the average-information REML algorithm (Jensen et al., 1997) in the DMU software package (Madsen and Jensen, 00). The maternal and direct heritability values (h m and h a, respectively) were calculated as follows: NBA, MBWB, SDBWB, MBW, SDBW: h ( ) = σ σ + σ + σ a a a pe e /, where σ a is the direct (sow) genetic variance, σ pe is the permanent environmental variance of the sow, and σ e is the residual variance. BW: h ( ) = σ / σ + σ + + σ + + a a a m am, pe l e s σ σ and ( ) h m = σ σ m a + σ m + σ am + pe + l +, σ σ σ e /, where σ m is the maternal (sow) genetic variance, σ a,m is the direct-maternal genetic covariance, and σ l is the

Genetics of homogeneous growth in piglets 14 Table 1. Descriptive data on litter and piglet traits from the Norwegian Landrace nucleus population in data set 1 (5 herds) and data set (58 herds) Trait 1 Data set n Mean SD Minimum Maximum NBA 1 1,064 1.5.8 6 NBA 14,045 1.60.70 6 MBWB, kg 1 1,064 1.55 0.7 0.89.67 SDBWB, kg 1 1,064 0.9 0.10 0.05 0.81 MBW, kg 1 1,064 6.85 1.0.90 11.97 MBW, kg 14,045 6.9 1.18.11 1.0 BW, kg 146,57 6.88 1.65.0 1.0 SDBW, kg 1 1,064 1.0 0.48 0.4.5 SDBW, kg 14,045 1.17 0.45 0.07.80 Mean age at wk, d 1 1,064 1.9 1.79 17 5 Mean age at wk, d 14,045 1.9 1.95 17 5 Sex ratio, % 1 1,064 0. 0.6 0 1 Sex ratio, % 14,045 0.1 0.1 0 1 1 NBA = number of piglets born alive; MBWB = mean BW at birth; SDBWB = SD in BW at birth; MBW = mean BW at wk; BW = individual BW at wk; SDBW = SD in BW at wk. litter variance. Standard errors of the heritability values were computed with the Taylor series expansion. RESULTS Estimates of the heritability and variance components are given in Table. The heritability values obtained for NBA and within-litter SD in BW at birth and at wk were low, and the heritability values of MBWB and MBW were moderate. The genetic correlations between the records made at birth and at wk were all positive and ranged from moderate to very high values, except for the correlation between MBWB and SDBW, which was close to zero (Table ). The SE of the estimates from data set 1 were large owing to the limited size of the data set. On the phenotypic scale, consistent correlations were found between MBWB and MBW, and between SDBWB and SDBW. The other phenotypic correlations were also positive but had small values. The model used with data set to analyze the combination [MBW SDBW] confirmed a strong genetic correlation between the traits (r g = 0.66 ± 0.07; r p = 0.09). The estimates of phenotypic and genetic correlations between litter size and within-litter SDBW are shown in Table 4. The genetic correlation was negative between MBW and NBA, but SDBW was not correlated with NBA. A moderate negative phenotypic correlation was observed between NBA and MBW. The estimates of the variance components for piglet BW and SDBW, obtained from a -trait model, are shown in Table 5. The heritability values for direct and maternal effects on BW were low (<0.10). An antagonism between the direct and the maternal components of BW was found (r g = 0.4 ± 0.10). The genetic correlation between SDBW and the maternal component was unfavorable (r g = 0.66 ± 0.08), whereas the one between SDBW and the direct component, although weak, was favorable (r g = 0.18 ± 0.14). Table. Variance component estimates for mean BW and within-litter deviation in BW at birth and at wk from the Norwegian Landrace nucleus population in data set 1 (5 herds) and (58 herds) 1 Trait Data set σ p σ pe σ a h a NBA 6.8 0.50 0.109 0.75 0.104 0.11 0.0 MBWB 1 0.044 0.007 0.00 0.014 0.00 0. 0.06 SDBWB 1 0.008 0.0005 0.0006 0.0008 0.0004 0.10 0.05 MBW 1 0.846 0.017 0.055 0.156 0.050 0.18 0.06 MBW 0.94 0.08 0.015 0.160 0.016 0.17 0.0 SDBW 1 0.17 0.005 0.011 0.014 0.007 0.08 0.04 SDBW 0.149 0.006 0.00 0.01 0.00 0.08 0.01 1 NBA = number of piglets born alive; MBWB = mean BW at birth; SDBWB = SD in BW at birth; MBW = mean BW at wk; SDBW = SD in BW at wk. σ p = phenotypic variance, σ pe = variance associated with sow permanent environment effects; σ a = variance associated with sow direct effects; h a = heritability value of direct (sow) genetic effect (SE are given as subscripts).

144 Canario et al. Table. Estimates of phenotypic (below diagonal) and genetic (above diagonal) correlations between within-litter BW characteristics measured in 5 nucleus Norwegian Landrace herds (data set 1) Trait 1 MBWB SDBWB MBW SDBW MBWB 0.6 0.5 0.60 0.16 0.09 0.7 SDBWB 0.0 0.48 0.6 0.51 0.1 MBW 0.5 0.08 0.77 0.7 SDBW 0.07 0.4 0.15 1 MBWB = mean BW at birth; SDBWB = SD in BW at birth; MBW = mean BW at wk; SDBW = SD in BW at wk (SE are given as subscripts). DISCUSSION Measurements and Models Heterogeneity within litters can be described by the SD or the CV expressed relative to the average litter BW. A litter of piglets weighing from 1.0 to 9.0 kg can have the same SD as a litter with BW from 5.0 to 1.0 kg, but the CV is smaller for the heavier litter. We used the SD because it better describes the difference between the smallest and the largest piglets in the litter. Damgaard et al. (00) underlined the relationship between variance of the heterogeneity, recorded as SD, and the number of observations. In small litters, the SD can easily be very large (e.g., with only piglets in the litter, one weighing.0 kg and the other 10.0 kg) or very small (e.g., piglets of 6.0 kg). Damgaard et al. (00) excluded all small litters when analyzing the SD of piglet BW. They compared estimates of heritability of the SD from analyses with or without an adjustment for litter size, and the difference was negligible. We excluded all litters with fewer than 6 piglets weighed at wk of age. Litter size (NBA) was included as a covariate in the model to reduce the scale effect on the estimates of SD and to avoid overestimating the litter effect on BW (Hermesch et al., 001). This correction is one way to account for some of the competition within the litter, and it should provide more precise estimates of variance components, in agreement with a previous study of birth weight conducted by Roehe (1999). Given that NBA is a very common selection trait, it is important to estimate the genetic correlation between NBA and heterogeneity. Therefore, we included NBA in the multitrait analyses of data set and, consequently, we did not include it as a covariate for the other traits in the model. Unfortunately, this model [NBA BW SDBW] did not reach convergence. With the large data set (data set ), it was possible to estimate both the maternal and the direct genetic effects. A permanent environmental effect of the sow was included because 5% of the sows produced more than 1 litter. In the analyses performed at the piglet level, when a common effect of the litter was also included, the permanent environmental effect of the sow was small. The common litter and maternal genetic effects were the main random effects that influenced piglet BW (BW). This agrees with estimates obtained by Solanes et al. (004) in a Yorkshire population in which cross-fostering was not performed. The results of the genetic analysis may have been influenced by the proportion of piglets not raised by their biological mothers, but this information was missing in our study. However, the small herd size that is common in Norway makes it difficult to manage farrowing in batches. Consequently, the amount of cross-fostering is relatively small. Relations Between Piglet Growth and Homogeneity of BW Within Litters The genetic potential of the sow for piglet growth prevails at birth (Hermesch et al., 001; Arango et al., 006). At this stage, heterogeneity of BW within a litter may be the outcome of an interaction between an increase in piglet numbers resulting from selection and insufficient uterine capacity (Johnson et al., 1999), which leads to more competition in utero. After parturition, the production of milk and nursing behavior by the sow determine the rate of piglet growth and development until weaning (Valros et al., 00; Johansen et al., 004). The moderate positive genetic correlation between MBWB and SDBWB shows that selection for MBWB leads to increased heterogeneity between those piglets that are born alive. However, the low correlation with SDBW motivates selection for MBWB as a means to promote growth without inflating withinlitter heterogeneity at wk. Selection on MBWB is comparatively easy to implement because the whole litter can be weighed at once and because the piglets are easier to handle than they are later in life. This selection favors development of piglets during the lactation period, which results in a greater growth rate (indi- Table 4. Estimates of phenotypic (below diagonal) and genetic (above diagonal) correlations between litter size at birth and litter components of -wk BW measured in 58 Norwegian Landrace nucleus herds (data set ) Trait 1 NBA MBW SDBW NBA 0.40 0.07 0.0 0.11 MBW 0.9 0.61 0.08 SDBW 0.08 0.05 1 NBA = number of piglets born alive; MBW = mean BW at wk; SDBW = SD in BW at wk (SE are given as subscripts).

Genetics of homogeneous growth in piglets 145 Table 5. Variance components for piglet BW and within-litter deviation in BW at wk from data set (58 Norwegian Landrace herds) 1 Trait σ p σ pe σ l σ a σ m σ am, h a h m BW.56 0.017 0.01 0.57 0.01 0.065 0.01 0.161 0.0019 0.044 0.014 0.0 <0.01 0.07 0.01 SDBW 0.148 0.006 0.00 0.01 0.00 0.08 0.01 1 BW = individual BW at wk; SDBW = SD in BW at wk; σ p = phenotypic variance; σ pe = variance associated with sow permanent environmental effects; σ l = variance associated with common litter environmental effects; σ a = variance associated with direct effects; σ m = variance associated with maternal effects; σ am, = covariance between direct and maternal effects; h a = heritability value associated with direct component; h m = heritability value associated with maternal component (SE are given as subscripts). cated by a positive genetic correlation between MBWB and MBW) and improved body composition of the pigs after weaning (Knol, 001). The phenotypic independence between SDBWB and MBW reported by Milligan et al. (00b) was confirmed in this study, as was a rather weak correlation between SDBWB and SDBW. In this study, stillborn piglets (which are often lighter; Canario et al., 007) were not considered. One explanation for our result is that lighter piglets, which are partially responsible for within-litter heterogeneity (Milligan et al., 00a,b), often die at birth or during the early stage of lactation (Cutler et al., 1999; Canario, 006). Conversely, we found a positive genetic correlation between SDBWB and SDBW. Damgaard et al. (00) reported an even greater correlation (r g = 0.71). The SDBWB could be used as a selection trait if piglets were weighed individually. Selection for decreased SDBWB will decrease SDBW, and Damgaard et al. (00) found a positive genetic correlation between within-litter SD at birth and piglet mortality during lactation. The current study confirms that this strategy of selection would have a favorable impact on homogeneity within litters at wk. In our study, the genetic correlation between NBA and MBW was negative, but SDBW seems to be genetically independent of NBA. Selection for litter size would not result in increased heterogeneity within litters at wk. Likewise, a low genetic correlation was described by Huby et al. (00), but Damgaard et al. (00) reported a moderate value (r g = 0.1 and 0.4, respectively). Sows with a genetic potential for increased NBA produce piglets that are smaller at wk of age because the increase in milk production with litter size is not proportional to the number of additional piglets (Auldist et al., 1998). The positive genetic correlation between MBW and SDBW shows that selection based on MBW results in litters with greater heterogeneity. Small piglets compete for growth with their littermates (English and Morrison, 1984). They never compensate for their delay in growth, and they show impaired myogenesis (Rehfeldt and Kuhn, 006) and a decreased growth rate (Klemcke et al., 199; Bauer et al., 1998). As neonates, they receive less colostrum (Devillers et al., 007), and during the whole lactation period they obtain less milk per suckle (Campbell and Dunkin, 198). As a consequence, selection for MBW alone should not be recommended. Differences in suckling ability exist between piglets. The indirect competition for resources that results from this difference lasts until weaning and is one mechanism by which within-litter heterogeneity can be accentuated. The larger piglets are more efficient at obtaining milk than their littermates (Pluske and Williams, 1988; Kim et al., 000; Wolter et al., 00). Wyeth and McBride (1964) observed that piglets that were heavier at birth monopolize the teats located in the anterior part of the udder. There is variation in the milk yield between teats (Fraser et al., 1979), with larger amounts of milk produced by the anterior mammary glands (Hoy et al., 1995). At the expense of piglets suckling other teats (Thompson and Fraser, 1986), a piglet can also enhance its milk consumption by vigorously massaging and draining the teat (King et al., 1997; Kim et al., 000). Furthermore, English and Morrison (1984) showed that small piglets are at greater risk of being excluded from the udder by heavier littermates. However, we found that the genetic correlation between the direct effect of piglet BW (BW) and SDBW tended to be negative. Our results indicate that if the direct component of piglet growth were increased by selection, it would be favorable to litter homogeneity. The stage of lactation studied here ( wk) corresponds with the peak of milk production (Toner et al., 1996). A study performed closer to weaning age could indicate a different genetic relationship between the traits because the piglets will have started to eat creep feed at this time. According to Harrell et al. (199), the milk production of a sow often becomes limiting for piglet growth from 8 to 10 d of age, and this difference between need and supply increases progressively. The genetic correlation between the maternal effect on BW and SDBW was positive and unfavorable. A sow with the genetic ability to raise piglets with increased BW at wk of age will have heterogeneous litters; as a consequence, the BW gain achieved in average piglet growth will be compromised by an increase in within-litter heterogeneity. Canario et al. (006) found a positive genetic trend in milk production, which was correlated with the selection program applied in France. However, milk yield is not proportional to the increase in the number of piglets (Auldist et al., 1998). Therefore, selection for litter size increases the investment by the sow in lactation, but this increase is limited by the needs of the

146 sow for maintenance and growth. The unfavorable correlation between the maternal effect and heterogeneity could be balanced partly by using increased weighting on the direct effect in the genetic evaluation because the correlation between the direct effect and heterogeneity seems to be favorable. Another reason to consider the direct effect when selecting for piglet growth during lactation is to correct for the antagonism between the direct and maternal effects [r am = 0.5, Zhang et al. (000); r am = 0.4, this study]. Pluske et al. (1995) suggested that differences exist between breeds in the ability of sows to nurture their piglets equally. For instance, Meishan sows achieve a more homogeneous growth among piglets than do Large White sows when the progeny are similar (i.e., F 1 Meishan-Large White piglets); the Meishan sows succeed in maintaining this advantage until weaning (Canario et al., 007). The heritability of the SDBW within litters observed here is in agreement with most previous studies (Damgaard et al., 00; Huby et al., 00). The heritability (<0.10) is not less than that of other traits associated with reproduction and health (litter size for instance), and hence should not be excluded as a target trait for selection. Selection for within-litter homogeneity in BW is efficient in rabbits. San Cristobal-Gaudy et al. (1998) developed a model for selection using a combination of the mean and the environmental variance to reach uniformity. Garreau et al. (008) applied it with success in an experiment to breed uniform rabbits. After 4 generations of selection for within-litter homogeneity in birth weight, the authors obtained no change in birth and weaning weights, but did obtain more homogeneous litters both at birth and at weaning. Owing to decreased mortality, they also obtained an increased number of weaned rabbits. A positively correlated response in the length and capacity of elongation of the uterine horns was also observed (Bolet et al., 008). Overall, selection based on an index that includes the direct and maternal components of piglet BW at wk of age and the within-litter SD of BW ought to be the best strategy. This will result in increased piglet growth without increasing the within-litter heterogeneity that develops during lactation. A simpler alternative could be to select for increased MBWB and thus obtain an increased BW at wk as a correlated response, without a large increase in heterogeneity. Selection only for increased mean piglet BW at wk is not recommended. LITERATURE CITED Arango, J., I. Misztal, S. Tsuruta, M. Culbertson, J. W. Holl, and W. Heering. 006. Genetic study of individual preweaning mortality and birth weight in Large White piglets using thresholdlinear models. Livest. Sci. 101:08 18. Auldist, D. E., L. Morrish, P. Eason, and R. H. King. 1998. 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