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Genetic variation of farrowing kinetics traits and their relationships with litter size and perinatal mortality in French Large White sows

L. Canario^*,1,2, N. Roy, J. Gruand and J. P. Bidanel^*

^* Station de Genetique Quantitative et Appliquée, Institut National de la Recherche Agronomique, 78352 Jouy-en-Josas, France; and La Basse Trappe, 79700 Rorthais, France; and and Unité experimentale de Génétique et Expérimentation en Productions Animales, Institut National de la Recherche Agronomique, 86480 Rouillé, France

	Abstract

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Genetic parameters of litter traits and their relationships with farrowing kinetics traits were estimated in a Large White population to examine the impact of selection for litter size on perinatal mortality and one of its main determinants, farrowing kinetics. Data were collected on 2,947 farrowings from 1,267 sows between 1996 and 2004. Litter traits included the number born in total (NBT), number born alive (NBA), and the number (NSB) and proportion (PSB) of stillborn piglets. Four farrowing kinetics traits were considered: farrowing duration (FD), birth interval (BI = FD/NBT), heterogeneity of birth intervals (SDNB = SD of the number of piglets born each one-half hour), and birth assistance (BA) during the farrowing process. Genetic parameters were estimated using restricted maximum likelihood methodology. All traits were analyzed using a mixed linear animal model including year x month and parity as fixed effects; the additive genetic value of each animal and the sow permanent environment were treated as random effects. To normalize their distribution, kinetics traits were Box-Cox-transformed. Low heritability estimates were obtained for litter size and mortality traits, which was in agreement with literature results (i.e., 0.10 ± 0.02, 0.08 ± 0.02, 0.19 ± 0.02, and 0.14 ± 0.02 for NBT, NBA, NSB, and PSB, respectively). Heritability values were also low for kinetics traits: 0.10 ± 0.02, 0.08 ± 0.02, 0.01 ± 0.01, and 0.05 ± 0.03 for FD, BI, SDNB, and BA, respectively. The genetic correlation between NBT and NBA was strongly positive (r_a = 0.90). On both phenotypic and genetic scales, NBT was positively associated with stillbirth (r_a = 0.45 ± 0.11, r_p = 0.38 for NSB; r_a = 0.46 ± 0.13, r_p = 0.17 for PSB). Conversely, NBA had low correlations with SB and PSB. Number born in total was moderately correlated to FD (r_a = 0.34 ± 0.15) and BI (r_a = –0.37 ± 0.15). A stronger relationship was found between NBA and BI (r_a = –0.49 ± 0.13), whereas the relationship with FD was lower (r_a = 0.16 ± 0.17). Moreover, FD was strongly correlated with stillbirth (r_a = 0.42 ± 0.12 with NSB), whereas BI was nearly independent of stillbirth. Contrary to selection on NBT, selection on NBA appears to be a good way to limit the negative side effects on stillbirth. Moreover, selection on NBA would lead to a small increase in FD and a faster and more regular birth process than would be obtained by selecting on NBT.

Key Words: birth interval • farrowing duration • genetic parameter • litter size • pig • stillbirth

	INTRODUCTION

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Litter size has been efficiently selected in several pig populations over the last decade (Bidanel et al., 1994; Estany and Sorensen 1995; Johnson et al., 1999; Tribout et al., 2003). However, it has often been accompanied by an unfavorable correlative response in the proportions of stillbirths (PSB) and, to a lesser extent, birth to weaning mortality (Rydhmer, 2000; Knol, 2001; Tribout et al., 2003). The causes of these unfavorable trends are complex and remain poorly known. However, the probability of intrapartum stillbirth has been shown to be phenotypically increased in prolonged farrowings (Zaleski and Hacker, 1993; Fraser et al., 1997; Borges et al., 2005). Indeed, piglets born after a long delay are more likely to be asphyxiated or suffer some degree of hypoxia (Randall, 1972a,b; Zaleski and Hacker, 1993). Longer preceding birth intervals (BI) have been shown to be positively associated with stillbirth rate on the phenotypic scale (Zaleski and Hacker, 1993). Prolonged or difficult farrowings are also associated with a greater need for birth assistance (BA; Holm et al., 2004).

Genetic parameters of farrowing kinetics and their genetic relationships with litter traits are necessary to predict correlative responses to selection for litter size. Very few estimates of such parameters are currently available in the literature. Genetic variation of the need for BA has been reported by Berg et al. (2001) and Holm et al. (2004). The latter researchers recently reported that, in Danish Landrace sows, there exists a large positive genetic correlation of farrowing duration (FD) with the number of stillbirths (NSB) and a moderate negative correlation with the number of piglets born alive (NBA). The main objective of this study was to estimate the genetic relationships between farrowing kinetics traits and litter traits to predict the consequences of selection for litter size [with number born in total (NBT) or NBA as a selection criterion] in a Large White population.

	MATERIALS AND METHODS

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Animal Management and Data Recording
Litter and farrowing kinetics data were collected in a privately owned, purebred Large White herd located in Poitou-Charentes, France, between 1996 and 2004. Thus, the data that were collected and analyzed were field data, and animal care followed the general guidelines outlined in the European animal welfare regulations. Sows were managed under a batch farrowing system with a 1-wk interval between contiguous batches. Sows entered the farrowing unit approximately 1 wk before the expected date of farrowing and were housed in individual farrowing crates with fully slatted flooring until weaning. To stimulate parturition and to facilitate supervision, a prostaglandin treatment was administered to the sows the day before the expected date of farrowing. Around the anticipated time of farrowing, the sows were watched very closely by 2 persons in charge of the farrowing unit. Treatments with oxytocin and/or vaginal palpations, performed during parturition, were used for approximately 80% of the litters produced. All piglets born were counted and classified every 15 min as born alive or stillborn, until 5.25 h from the onset of farrowing had elapsed. The 2 persons who counted piglets had been trained together in the same fashion. A piglet was considered stillborn if it was an apparently full-term fetus that made no visible movement after birth.

Litter records were available on NBA and NSB each one-quarter hour and for the whole duration of parturition. The following were calculated from these traits: 1) NBT (NBA + NSB); 2) PSB (NSB/NBT); 3) FD, which was defined as the time elapsed between the births of the first and the last piglet of the litter; 4) average BI, estimated as FD/NBT; and 5) SD of the number of piglets born each one-half hour (SDNB), a measure of heterogeneity of BI. Birth assistance corresponded to providing at least one treatment (oxytocin, vaginal palpation, or both) during parturition.

Parturitions were observed from 0600 to 2300 during the farrowing week. The onset of farrowing was not missed if the first piglet(s) born was (were) not dry when observed for the first time. If the beginning or the end of farrowing was missed (too many pigs born in the first or the last interval, respectively), FD was not considered. The SDNB was calculated for parturitions <5.25 h with no doubtful gap in the kinetics (i.e., a long interval without birth(s) often followed by several births within only one-quarter hour, corresponding to lunch time or the period between midnight and the morning).

Statistical Analysis
The number of stillborn piglets ranged between 0 and 12, showing a strongly skewed distribution (42.7% of the litters did not have any stillborn piglets, 29.3% had 1, 14.3% had 2, and the remainder had 3 stillborn piglets). The PSB was also analyzed after logit transformation. Birth assistance was recorded as a binary trait (yes or no) relative to the frequency of assistance given to a parturient sow.

Genetic parameters were estimated using restricted maximum likelihood methodology (Patterson and Thompson, 1971) applied to a multivariate model, using the VCE software (version 4.5; Neumaier and Groeneveld, 1998). Stillbirth traits and BA were also analyzed as categorical traits with a binomial distribution and a logit link function with the ASReml software (version release 1.0; Gilmour et al., 2002). These additional analyses were carried out using an animal model for stillbirth traits, but a sire model was used for BA because of convergence problems with the animal model. Because FD and BI had a skewed distribution, they were Box-Cox-transformed (Box and Cox, 1964; Figure 1).

View larger version (18K): [in this window] [in a new window]   Figure 1. Distribution of farrowing duration in a Large White nucleus herd without (a) and with (b) Box-Cox transformation.

	RESULTS

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The high prolificacy (14.2 NBT) and the relatively low number of stillborn piglets (1.1 NSB, i.e., 7.4%) in this population should be emphasized (Table 1).

Litter size traits had negative phenotypic and genetic correlations with BI and had positive correlations with the 3 other kinetics traits. In other words, an increased litter size tended to be associated with a longer farrowing, shorter BI, and a greater need for BA. However, correlations differed again between NBT and NBA. Number born in total had moderate genetic correlations with both FD and BI (0.34 and –0.37, respectively), whereas NBA had a much stronger relationship with BI (–0.49) than with FD (0.16).

The number and proportion of stillbirths had positive phenotypic and genetic correlations with all kinetics traits. Stillbirth was more strongly associated with FD (0.42 and 0.49, respectively) than with BI (0.06 and 0.20, respectively). The SDNB showed moderate to high positive correlations with all traits, in particular with litter size (0.72 and 0.59 with NBT and NBA, respectively). The need for BA was genetically almost independent of NBA (0.09). It had a moderate positive correlation with NBT (0.37), but was strongly correlated with NSB and PSB.

	DISCUSSION

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Very few and only recent studies have estimated the genetic variation of farrowing kinetics traits and their relationships with litter characteristics, partly because they are time-consuming to measure. The current study was possible because the manager of the farm considered it necessary to very closely supervise the farrowings to save a maximum number of piglets and decided to collect farrowing kinetics data. In preliminary trials in an experimental herd, we found that collecting new birth data every 15 min gave a rather good accuracy of farrowing kinetics while allowing sow and piglet care (L. Canario, unpublished data). Nevertheless, a noticeable number of farrowings (about 20%) had incomplete kinetics records because of very long durations of parturition, births during unsupervised hours, etc., and were discarded from the final analyses. This resulted in some underestimation of the phenotypic variance of FD, because long FD were more likely to be eliminated than shorter ones. The impact of data removal on heritability and correlation estimates was likely to be limited for the following reasons: 1) there was no difference in average litter performance when FD was considered as missing or not (13.1 vs. 13.0 NBA) and 2) the genetic variance was reduced almost proportionally to the reduction in phenotypic variance. This was shown by analyzing the data set after removing the 10% longest farrowings. Heritability estimates before and after data removal were similar.

Some bias may also result from the use of standard mixed linear models (MLM) to analyze categorical traits such as NSB or BA. Indeed, threshold models have been shown to be superior to MLM when the number of categories is small and with unbalanced frequencies (Meijering and Gianola, 1985; Hoeschele and Tier, 1995). However, their use is still difficult, particularly to estimate genetic correlations between categorical and normally distributed traits. Software based on approximate methods often gives unexpected results, and exact methods based on stochastic inference such as Gibbs sampling (e.g., Holm et al., 2004) are still computationally demanding. The use of standard MLM, which are known to be robust to strong departures from normality assumptions, was hence considered as a simple and satisfactory method to obtain first estimates of farrowing kinetics genetic parameters. The similar heritability values obtained for NSB and PSB analyzed as continuous or binary traits confirmed the acceptability of this approximation.

The close supervision and high level of human intervention when farrowing difficulties occurred might have hidden some of the variation that would have existed under less intensive surveillance. This possibility (i.e., the existence of genotype x environment interactions for reproductive traits) could be tested by placing related animals into different management conditions and using video cameras to measure FD while limiting human intervention.

Although strongly correlated, NBT and NBA had rather different relationships with perinatal mortality. A strong genetic antagonism was obtained between NBT and both NSB and PSB, whereas NBA was independent from PSB and was lowly correlated with NSB. This result was in agreement with those from several other studies (Johnson et al., 1999; Lund et al., 2002; Holm et al., 2004; Serenius et al., 2004) and indicates that selection for NBT is likely to result in a noticeable increase in PSB, as recently observed in several pig populations (Tribout et al., 2003 in the French Large White population). Conversely, selection for NBA should not result in deterioration of PSB and should consequently be preferred to NBT as a selection criterion for prolificacy, as advocated by Johnson et al. (1999). An alternative strategy could be to select for high NBT and low NSB (Serenius et al., 2004).

All traits but NSB had low heritability values. Estimates for NBT and NBA were similar to the average literature values (Rothschild and Bidanel, 1998), whereas heritability values for NSB and PSB were much greater than the literature means (0.05; Rothschild and Bidanel, 1998; Knol et al., 2002; Holm et al., 2004; Rydhmer and Lundeheim, 2005). However, greater values obtained in several recent studies (0.13 to 0.27; Johnson et al., 1999; Grandinson et al., 2000; Damgaard et al., 2003) agree with our findings.

The FD and BI appeared as low, but significant, heritable traits. Estimates of heritability were substantially greater than those obtained by Canario et al. (2003) in a previous analysis of a limited subset of these data and by Holm et al. (2003, 2004), who made a more approximate measurement of FD (2- and 4-h intervals) and included data from several herds obtained from records registered by farmers. Conversely, the heritability value for BA was very similar to that reported by Berg et al. (2001) and Holm et al. (2004), even though the definition of the trait differed slightly between the studies. With the exception of NSB and PSB, permanent environmental effects were larger than the usual literature values (Bolet et al., 2001; Hanenberg et al., 2001; Damgaard et al., 2003).

Somewhat different correlative responses to selection for NBT vs. NBA can be expected for farrowing kinetics traits. Selection for NBT would result in an increase in both FD and rhythm (BI), whereas selection for NBA would primarily affect rhythm with a more limited impact on FD. This may partly explain the different correlative responses in perinatal mortality, because a clear genetic antagonism seems to exist between NSB or PSB and FD, in accordance with Holm et al. (2004), whereas genetic correlations with BI are rather weak.

The strong positive genetic correlations between BA and stillbirths, as well as FD and rhythm (BI), were in agreement with the results of Holm et al. (2004). The much lower phenotypic correlations are presumably due to the high level of human intervention, which limits NSB, BI, and FD. The underlying causes of these relationships, such as the role of variations in hormonal changes during parturition or sow and piglet effects on uterine contractions, remain largely unknown. Again, it should be emphasized that selection for NBT would result in a greater need for BA, whereas selection for NBA would only have a limited impact on BA.

The heritability of SDNB was very low. Its strong relationships with NBT and NBA might have been partly due to a scale phenomenon associated with the acceleration of the birth process, which is likely to result from some intervals with numerous piglets. However, it might also indicate a greater irregularity in the birth process, likely in association with increased birthing difficulties. The unfavorable phenotypic and genetic correlations with perinatal mortality were in agreement with the positive phenotypic correlation between the SD of BI and stillbirth obtained by Pedersen et al. (2006). These results tend to show that regular births throughout farrowing are associated with a lower NSB and PSB. This may be due to the fact that dead piglets have a larger probability of retention than live piglets (Christianson, 1992; Zaleski and Hacker, 1993), thus resulting in long BI followed by short intervals for the remaining piglets that have been blocked from being born.

	IMPLICATIONS

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Genetic antagonism between farrowing duration and the number or proportion of stillbirths, as well as birth assistance, was shown. Total number of piglets born and number born alive have different relationships with farrowing kinetics traits. Selection for total number born results in an increase in farrowing duration, in the number and proportion of stillbirths, and in birth assistance. Conversely, selection for number born alive accelerates the farrowing process and has a limited impact on farrowing duration and birth assistance and, hence, should not increase the proportion of stillbirths. Therefore, number born alive should be preferred as a selection criterion for prolificacy to avoid unfavorable correlative trends in the proportion of stillbirths. Farrowing kinetics traits are too laborious to measure to be considered as selection criteria but are important to take into account to better understand the biological consequences of selection for litter size.

	Footnotes

 
² L. Canario was funded by a joint fellowship of the French Pig Technical Institute and the Institut National de la Recherche Agronomique Département de Génétique Animale.

¹ Corresponding author: laurianne.canario{at}jouy.inra.fr

Received for publication September 15, 2005. Accepted for publication December 27, 2005.

	LITERATURE CITED

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