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Livestock Science

Livestock Science 146 (2012) 133–139

1871-14

http://d

n Corr

E-m

Christin

journal homepage: www.elsevier.com/locate/livsci

Genetic parameters for gestation length in French horse breeds

Bertrand Langlois n, Christine Blouin

INRA-CRJ-BIGE 78352 Jouy-en-Josas Cedex, France

a r t i c l e i n f o

Article history:

Received 10 November 2011

Received in revised form

27 February 2012

Accepted 29 February 2012

Keywords:

Heritability

Repeatability

Maternal effect

GLM

ASREML

13/$ - see front matter & 2012 Elsevier B.V.

x.doi.org/10.1016/j.livsci.2012.02.028

esponding author. Tel./fax: þ33 1 3465 2110

ail addresses: Bertrand.langlois@jouy.inra.fr (

e.blouin@jouy.inra.fr (C. Blouin).

a b s t r a c t

French administrative data of the breeding season 1994–2008 concerning gestation

lengths of 5 warm-blood breeds: 47789 Thoroughbred gestations, 14336 Arab, 7363

Anglo-Arab, 53832 French Saddle, 130769 French Trotter, and 5 cold-blood breeds:

13528 Percheron’s gestations, 7480 for Ardennes, 5181 for Cob Normand, 33335 for

Comtois and 36537 for Bretons were analyzed using the ASREML software.

After preliminary studies, the model included as fixed effects, year (15), covering

month (12), breeding area (10), mare’s status (3), sex of the foal (2); age of the mare

was accounted for as a linear covariate; direct genetic, maternal genetic, and common

maternal environment, were the random variables. The genetic correlation between

direct and maternal genetic effects was assumed to be zero.

The different sub-files did not give significantly different results: direct genetic

effect was evaluated between 8 and 12%, maternal genetic effect between 8 and 12%

also and common maternal environment between 5 and 6%.

This confirmed the dissymmetric contribution of sire and dam: 2–3% for the sire

and 13–18% for the dam. When direct and maternal effects were confounded they

accounted for 16–24%, confirming the possibility of selection for this character.

& 2012 Elsevier B.V. All rights reserved.

1. Introduction

Authors involved in zoology are interested in the geneticfactors influencing gestation length from an evolutionarypoint of view. What are the connections between litterweight, size and length of gestation? The cervids (Asher,2011) are a good example. They are a complex assemblageof taxa showing extreme diversity of reproductive strate-gies including a range from highly seasonal to completelyaseasonal birth patterns. The recent increase in knowledgeon cervid reproduction concerns the larger-bodied, gregar-ious mixed grazer-browser species that has adapted well tohuman management and commercialization. These speciesare characterized by very productive annual breedingsuccesses, singleton births and long breeding lives (around

All rights reserved.

.

B. Langlois),

10 years). Conversely little is known about the reproductivepatterns of the smaller-bodied, solitary (and often highlyterritorial), forest-dwelling browser species, which includesmany of the endangered cervid taxa that are often char-acterized by great fecundity (twinning) and shorter breed-ing lives. Zootechnicians are interested in gestation lengthfor the correlation it may have with other characters ofeconomical importance such as stillbirths and dystocia inbovines (Mc Guirk et al., 1998, 1999; Meyer et al., 2000) butalso mothering ability in the sow (Hanenberg et al., 2001)and litter size and weight in sheep (Osinovo et al., 1993;Babar, 2008) and goats (Zhang et al., 2009) as in dogs(Gavrilovic et al., 2008). The question of prediction of thedate of parturition may have some importance for maresand cows but mostly in cases of free natural matings,gestation length is used at the opposite, i.e. from the dateof parturition, to determine the date of fecundation tocorrect for the appropriate sire. Gestation length, however,as the most important part of the interval between births,gives a limit to the annual numerical productivity that

Table 1Heritability of horse gestation length, bibliographical data.

Reference Breed Heritability Repeatability

Rollins and Howell

(1951)

Arab 0.36 –

Rodero and Pozo Lora

(1960)

Arab 0.19 0.33

Spanish PB 0.12 0.52

Matassino (1962) Haflinger 0.32 –

Salerno and

Montemurro (1966)

Salernitan 0.30 0.49

Arab 0.21 0.37

Sato et al. (1973) Tokachi 0.19–0.30 –

Hintz et al. (1979) Thoroughbred 0.25 –

Shermerhorn et al.

(1980)

Standardbred 0.38 –

Vassilev et al. (2002) Pleven 0.30 0.47

Valera et al. (2006) Arab 0.21 0.37

Spanish PB 0.21 0.36

Fig. 1. Distribution of observed and true gestation length in the mating

years 2005–2008.

Fig. 2. Effect of the year on the observed and corrected gestation lengths.

B. Langlois, C. Blouin / Livestock Science 146 (2012) 133–139134

should be increased by reducing the interval betweenbirths and increasing litter size.

For horses, since Rollins and Howell (1951), manyauthors have published estimations of heritability. As acharacter of reproduction, gestation length appears reason-ably heritable (Table 1) and is submitted to importantmaternal effects. The comparison of estimations thereforeraises a problem of the analysis model. This has differentdimensions. Is gestation length a character of the fetus? Ifso the repeatability is not estimable. Is it a character ofthe mare? Then repeatability is available. In the first case,paternal halfsib resemblance would allow the estimations.In the second case maternal halfsib would allow it. Toovercome these difficulties, Vassilev et al. (2002) were thefirst to propose an animal model including a direct geneticeffect and a maternal effect, with the latter being partlygenetic and partly environmental. In their analysis, directand maternal genetic effects are supposedly uncorrelated.This kind of model was also applied for the same characterin cattle (Hwang et al. 2008; Johanson et al., 2011) and inthe pig (Rydhmer et al., 2008).

We think that this is the best approach to this ques-tion. This is indeed highly computationally demandingbut we now have the tools, hardware and software, toovercome this difficulty. The aim of this work was there-fore to analyze the French administrative data breed bybreed, for different variation factors by such a completemixed model to produce direct heritability, maternalheritability, and common maternal environmental com-ponents of the gestation length for each case.

2. Material and methods

French administrative data of the breeding season 1994–2008 concerning estimation of gestation lengths wereanalyzed. Because breeders often do not declare the dateof last mating but only that of the first mating, two variableswere analyzed: the observed gestation length Do which isthe difference of date of birth and declared date of ‘‘mating’’.We know from a preceding study on the mating years2005–2008 (Langlois et al., 2011) that Do reflects the true

gestation length with a random error of mean of 4.6 daysand 1.7 days standard deviation.

Indeed, as shown in Fig. 1 on a sample where truegestation length (mean¼342.6 days; standard deviation¼10.8 days) could be compared with the observed oneaccording to the breeder’s declarations(mean¼347.2 days;standard deviation¼12.5 days) Do is biased by an errorhaving a mean of 4.6 days and 1.7 days standard deviation.We therefore suggest a corrected gestation length Dc, toconstrain Do in the case where it is correctly evaluated. Thisgives

Dc ¼ 342:6þðDo2347:2Þ � 10:8=12:5

Three steps were then followed:In a first step, elaboration of the model of analysis was

conducted with GLM (SAS, 2002–2003) on all the avail-able data to identify the fixed effects. These concerned549,580 warm-blood observations and 348522 cold-bloodobservations (Figs. 2–4).

Then, the model for the random effects was elaboratedwith the ASREML software only on the thoroughbredpopulation (Gilmour et al., 2009).

In a third step, the elaborated model was applied onevery breed whose number of animals enables correctestimations of the genetic parameters. These numbers fordata restricted to pure breeding and for mares having atleast two gestations are given in Table 2.

The models include the following fixed effects men-tioned in the literature (Valera et al. (2006); Stattie et al.,

Fig. 3. Effect of the mare’s age on the observed and corrected gestation

lengths.

Fig. 4. Effect of the month of covering.

Table 2Structure of the data of the sub-files studied.

Breed Nb. of

gestations

Nb. Of

mares

Nb. of

sires of

fetus

Nb. of

sires of

mares

Pedigree

depth in

generations

Thoroughbred 47789 12891 5658 4935 17

Arab 14336 3583 3970 2597 23

Anglo-Arab 7363 2232 3487 2927 22

French Saddle 53832 15522 9104 7837 22

French

Trotter

130769 32688 4139 3515 14

Percheron 13528 3633 1566 1219 14

Ardennes 7480 1945 2103 1489 16

Cob Normand 5181 1248 711 535 14

Comtois 33335 8642 3959 2882 19

Breton 36537 9209 4517 3512 17

Sires of fetus: Sires involved as father in all the analyzed gestations.

Sires of mares: Sires of the mares involved as mother in the same

gestations.

B. Langlois, C. Blouin / Livestock Science 146 (2012) 133–139 135

2011). These are year, age of the mare, month of mating,breeding area, and status of the mare. We will further seethat for simplification, age of mare could be taken intoaccount as a linear covariate in the ASREML analyses.Inbreeding of the mare and fetus as the gender of thefetus were also estimated.

For the levels and each factor the reference were thefollowing:

Year of mating, 15 levels from 1994 to 2008, with 1994being the reference.

Age of mare at mating, 19 levels from 2 to 20 andmore, with 6 year-olds being the reference.

Month of mating, 12 levels from January to December,with April being the reference.

Breeding area, 10 levels soon described in the studyof fetal losses (Langlois et al., 2010), with region III(Normandy—great west) being the reference.

Status of the mare, 3 levels, maiden, barren and withfoal at feet acting as the reference.

Inbreeding, 4 levels, 40.125, [0.0625–0.125], [40–0.0625] and 0 being the reference. This was considered forthe mare and the fetus.

Breed effect: to avoid the multiplication of levels, wefirst considered the sire’s breed and secondly if the breedof the mother was identical (pure breeding acting as thereference) or if it was different (crossbreeding effect) thatis only 2 more levels. Here, only the difference betweenwarm- and cold-blood was considered with warm-bloodbeing the reference.

Gender of the conceptus, 2 levels, male, and femaleacting as the reference.

The random variables were according to the analysis:

�

Maternal genetic effect with common maternal environ-ment.

�

Direct genetic effect with common maternal environ-ment.

�

Direct genetic with maternal genetic and commonmaternal environment, correlation between directand maternal genetic effects also being estimated.

�

Direct genetic with maternal genetic and commonmaternal environment, correlation between directand maternal genetic effects supposed to be zero.

3. Results

3.1. Fixed effects, GLM results

Due to the amount of data even the small effects werefound to be significant except for inbreeding of the mareand fetus. The results obtained on Dc, which were similar,were also a little more shrinked towards the general meanthan those evaluated for Do.

3.1.1. Year effect

There was no obvious tendency but some years exhib-ited significantly longer gestation lengths (2000) and someother lower gestation lengths (2006). However the effect didnot reach a full day and could be mostly neglected.

3.1.2. Effect of the age of the mare

A linear increase of gestation length with age seemedacceptable; the rate of increase seemed to reach a max-imum for 6 year-olds. This effect is important and should betaken into consideration. Indeed, there was nearly four daysdifference between the youngest and the oldest mares.

B. Langlois, C. Blouin / Livestock Science 146 (2012) 133–139136

3.1.3. Effect of the month of covering

The seasonal effect was of great magnitude. It had twowaves: one aiming at the synchronization of births in thespring (March and April) and the second one of lessermagnitude to synchronize in the autumn (September). Aphotoperiodic signal should therefore be suspected inpreference to a thermal one for regulating the gestationlength. The high values observed for January matingleading to births in December were due to delayeddeclarations of birth because one year is added to theadministrative age of the horses each January first.

3.1.4. Effect of inbreeding

Inbreeding of the mare and/or the fetus was not foundto be significant. However, calculated from the pedigreeinformation which as shown in Table 2 is of high value,the variation of the inbreeding coefficient F was low.Indeed a great majority exhibited F¼0 and only a fewpercent F40.125.

3.1.5. Breeding areas, status of the mare

Despite the correction of the data to minimize theeffect of uncertainty on the date of fecundation, these twoeffects were found to be significant on Do but also on Dc.They express differences of uncertainty connected withmore or less experimented breeders. However the mag-nitude of this effect was mostly under one day and neverexceeded two days. It could be mostly ignored.

The effect of the mare’s status was also significant evenfor Dc. The absence of birth declarations the preceding yearled to an overestimation of the gestation length due to agreater difficulty to identify the date of fecundation. Themagnitude of this effect in days was between 1.5 (maiden)and 1.8 (barren) for Do and respectively 1.3 and 1.5 for Dc.

3.1.6. Sire’s breed and pure or crossbreeding effects

Cold-blooded horses had on average a 0.36(Do)–0.31(Dc) days longer gestation length than warm-bloodedhorses. Crossing warm with cold-blood led to 0.76(Do)–0.66(Dc) days longer gestations.

Table 3Preliminary results on the thoroughbred for testing different m

Variable and sub-file H2direct H2matern

Do-2 off./mare _ 0.107 (0.00

0.150 (0.011) _

0.090 (0.010) 0.085 (0.01

Dc-2 off./mare _ 0.108 (0.00

0.150 (0.012) _

0.090 (0.010) 0.085 (0.01

Do-2 off./mare 0.088 (0.009) 0.081 (0.00

Dc-2 off./mare 0.088 (0.009) 0.082 (0.00

Standard deviation is between brackets.

Variable and sub-file: Do and Dc refer to the observed and cor

mares with two gestations were considered.

H2direct is the heritability of the gestation length considered a

H2maternal is the heritability of the maternal effect.

Rdxm genetic correlation is the correlation between the direct

C2

m is a common environmental effect shared by the different

3.1.7. Effect of the sex of the foal

On average, males had 1.31(Do)–1.13(Dc) days longergestation lengths.

3.2. Random effects, ASREML results

Table 3 summarizes the preliminary results for theadjustment of different models on the two measure-ments of gestation length on different sub-files of theThoroughbred population in France.

From these preliminary results, one can observe thatDc, the corrected gestation length, despite a great reduc-tion in its variance has exactly the same genetic para-meters as does Do, the observed one. For simplicity,further results will therefore only be given for Do.

The simplest model also tends to overestimate the directgenetic effect and the common maternal environment byavoiding the maternal genetic effect whose effect seems tobe split between the two others. This should therefore betaken into account in further analyses. The genetic correla-tion between direct and maternal effects was never sig-nificant. The model where this correlation is zero byconstruction therefore appears as the best to conduct theanalyses breed per breed. Table 4 gives the results of thisadjustment for the main French warm- and cold-bloodedbreeds. All the effects put in the model were significant inthe analyses breed per breed except year of mating for‘‘Ardennes’’ and ‘‘Cob Normand’’ and breeding area for allthe cold-blooded breeds except ‘‘Comtois’’. However themain variation factors are the month of covering, the mare’sstatus and their age, and the sex of the foal.

4. Discussion

4.1. Fixed effects from GLM analyses

Despite the relative imprecision of these administrativedata due to too much approximation of the date offecundation, the very huge amount of data available hasmade the estimation of many levels of numerous variation

odels.

al Rdxm

genetic correlationC2

m commonmaternal envir.

9) _ 0.063 (0.007)

_ 0.109 (0.005)

1) �0.049 (0.095) 0.059 (0.007)

9) _ 0,062 (0.007)

_ 0.109 (0.005)

1) �0.047 (0.095) 0.058 (0.007)

8) 0 0.059 (0.007)

8) 0 0.058 (0.007)

rected gestation length. 2off./mare means that only the

s a character of the fetus.

genetic and the maternal genetic effects.

offspring of one mare.

Table 4Genetic parameters of gestation length in French horse breeds.

Breed H2direct H2maternal C2maternal envir.

Thoroughbreda 0.088 (0.009) 0.081 (0.008) 0.059 (0.007)

Arab 0.114 (0.018) 0.109 (0.016) 0.051 (0.013)

Anglo-Arab 0.085 (0.021) 0.156 (0.027) 0.005 (0.022)

French Saddle 0.116 (0.011) 0.087 (0.009) 0.051 (0.007)

French Trotter 0.082 (0.006) 0.083 (0.005) 0.045 (0.004)

Percheron 0.116 (0.018) 0.118 (0.016) 0.030 (0.013)

Ardennes 0.092 (0.023) 0.116 (0.023) 0.035 (0.019)

Cob Normand 0.097 (0.026) 0.093 (0.024) 0.042 (0.020)

Comtois 0.116 (0.011) 0.120 (0.011) 0.037 (0.009)

Breton 0.095 (0.010) 0.103 (0.009) 0.037 (0.008)

Standard deviation is between brackets.a Recall from Table 3.

B. Langlois, C. Blouin / Livestock Science 146 (2012) 133–139 137

factors possible with great precision. This was not possiblebefore, even on more precise data resulting from a highstandard of management of some big studs.

All the factors analyzed were significant except forinbreeding of mares and foals. The absence of an inbreedingeffect was still mentioned by Valera et al. (2006) and isconfirmed here. We also confirm the other main effects asage of the mother, season of reproduction, sex of the foaland breed. Because of the confusion between age and parity,the latter was not considered by us. This may explain thatwe did not find the curvilinear evolution signaled by Valeraet al. (2006). For us, gestation length grows linearly with theage of the mother. There may be some disturbances for ages2 and 3, but not very much because maiden mares weretaken into consideration. We also had no information on thefeeding status of the brood mares, nor on the climate.Variation in latitude was also very limited for our data.The effect of month of mating showing two waves aiming atthe synchronization of birth in the spring or autumn isshown for the first time with such precision. A photoper-iodic regulation should be involved. Males of heavy breedshave longer gestation periods than males of light breeds.This may reflect a correlation between gestation length andbirth weight as mentioned by Stattie et al. (2011).

Other significant effects of lesser importance as someyears or breeding area or status of the mare havestatistical importance but it is difficult to give them abiological interpretation. Most of the years did not haveany effect but some have longer and some shorter gesta-tions. It is impossible to say whether the reason lies in thefeeding conditions, or in the weather conditions. Theeffect of breeding area can result from the same causesbut also from differences in the evaluation of the date offecundation by more or less experimented breeders. Thesame may occur for the mares without a foal with longergestation periods than mares with a foal at feet. Indeed,for the latter, fecundation date is easier to estimate andnot as many breeders declare early mating instead of lastmating as fecundation date because it is mostly the same.The higher percentage of wrong declarations for themares that did not foal leads to the overestimation ofgestation length and produces the difference.

Finally for further genetic analysis including somerandom effects in mixed models, we decided to maintain

as fixed effects all those described here except inbreedingand to introduce age as a linear co-variable and toconduct these analyses in pure-breeding per breed.

4.2. Random effects and genetic parameters, ASREML results

It appears from these results that the genetic para-meters for gestation length did not differ significantlyfrom breed to breed. The direct genetic effect that can beassimilated to the fetus effect accounted for 8–11.5% ofthe variance. The maternal effect accounted for the sameamount, 8–12% for its additive part and for 5–6% morefor its environmental part. In total 16(8þ8) to nearly24(12þ11.5)% of the variation seemed to be controlled byadditive genetic factors. This was in agreement with thebibliographical data (Table 1) even a little lower thanthe evaluations published more recently by Valera et al.(2006). We have indeed administrative data with a greatapproximation on the date of fecundation adding an errorvariance that may not be neglected. The proposed correc-tion based on standardization did not fully succeed inreducing it. Indeed, for the estimation of the fixed effects,it was efficient by shrinking the estimations, but forestimating variance components this transformation didnot exhibit any effect. We are therefore of the opinionthat this remaining error variance could explain our lowerresults.

However, the great amount of data analyzed, allowedmore precise genetic estimations than ever. It also gavevery coherent results among 10 independent sub-filesconcerning the most representative French horse breeds.

In general the mean gestation length truly estimatedwas 342.6 days with 10.8 days standard deviation(Langlois et al., 2011). That was a little more than theeleven months believed by the breeders and is alsocharacterized by a very big variation. It was thereforedifficult to predict the date of foaling from the date offecundation or of last covering and breeders spent a lot oftime watching their mares before parturition. Improvingthe prediction of foaling date first requires a better controlof the date of fecundation and after making a predictionaccording to the breed, the month of covering, the age ofthe mother and her status as evaluated here.

To further improve the prediction, a genetic evaluationcould be conducted for the direct and maternal additiveeffects. This would allow evaluating the fetal effect andthe total maternal effect in each case. Determinationof the sex of the fetus by ultra sound examination couldalso improve the prediction. This could probably greatlyreduce the time spent watching the mare before parturi-tion, sparing money and saving sleeping time.

Selecting for long or short gestation is possible but atthis time we do not know the correlative response onother characters having more economical interest such asbirth weight, precocity, maternal behavior, etc. Indeed,short gestations facilitate the maintaining of the foalinginterval to one year. This would in this seasonal speciesfavor the numerical productivity (Langlois et al., 2011).However, the marginal gain on gestation length is lowcompared to a better management of the foaling–fecundation interval. However, the great variation of the

B. Langlois, C. Blouin / Livestock Science 146 (2012) 133–139138

gestation length is inconvenient for the breeders. There-fore canalization selection could produce more homoge-neity which could be advantageous.

5. Conclusion

The main fixed effects on gestation length, still men-tioned in the literature, were confirmed here and arespecified, thanks to the amount of data available. Becauseon these administrative data the observed gestationlength is biased by a random error of mean 4.6 days andstandard deviation 1.7 days, the use of a transformation toconstrain it by standardization in the case where it wascorrectly evaluated resulted in a corrected gestationlength. This enabled us to valorize all our data. The resultof this is changing the overall mean but only shrinks theestimation of the effects due to the overall reduction ofvariance for the corrected gestation length.

We confirmed the absence of an inbreeding effecteither of the mare or of the fetus still signed by Valeraet al. (2006).

We also confirmed the effect of breeds at least whenwarm and cold bloods are compared. The heavier the foalsare at birth, the longer their gestation lengths.

We confirmed the effect of the age of the mother,however for us, the increase was linear and the maximumwith 6 year-olds mentioned by Valera et al. (2006) wasnot confirmed despite a small change of the slope at thisage. We also confirmed that males have longer gestationlengths than females. We show for the first time the effectof crossing breeds. All these effects can be put in relationwith the birth weight and some trophic mechanisms. Weconfirmed the great effect of the season of mating stilldescribed for the synchronization of births in the springbut here also established for a second breeding season inthe autumn. We also confirmed that some year effectshave a positive or negative incidence as supposed byStattie et al. (2011). This could be related to weathercondition influencing sunlight exposition. As the seasonalinfluence, this would trigger the same photoperiodicphysiological mechanism.

However the status of the mare and breeding area hasstatistical effects that are difficult to explain by suchphysiological mechanism. Mares that did not foal thepreceding year had longer gestations. Differences betweenbreeding areas also exist, but it is difficult to attributethem to differences in latitude. Differences in the date ofdeclaration of fecundation are more likely to interfere.

The estimation of the genetic parameters confirms thedissymmetric contribution of sire and dam to the gesta-tion length of their product. Sire effect could be evaluatedto 2–3% whereas that of the mother reached 13(8þ5)–18(12þ6)%. The sire effect was 1/4 of the fetal effect(direct genetic) which was estimated between 8 and 12%.The maternal effect has two components: one is genetic(maternal genetic) also representing 8–12%; the second iscommon environment, accounting for 5–6%. When directand maternal genetic effects were confounded, theyaccounted for 16(8þ8)–24(12þ12)%. Substantial herit-ability of gestation length was therefore confirmed despitethe imprecision of the date of fecundation obtained from

administrative data, which adds an uncontrolled factor ofvariation.

Independent estimations in five warm-blooded breeds(Thoroughbred, Arab, Anglo-Arab, French Saddle, Frenchtrotter) and five cold-blooded breeds (Percheron, Ardennes,Cob Normand, Comtois, Breton) did not differ from thisgeneral figure.

Conflict of interest statement

The authors declare that they have no conflictinginterest.

Acknowledgements

We are grateful to IFCE (Institut Franc-ais du Cheval et del’equitation) for providing us with the data and to FlorencePhocas for her help in using the ASFREML software.

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