Genetic parameters of weights, ultrasonic muscle and fat depths, maternal effects and reproductive traits in Welsh Mountain sheep

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1 Animal Science 2002, 74: /02/ $ British Society of Animal Science Genetic parameters of weights, ultrasonic muscle and fat depths, maternal effects and reproductive traits in Welsh Mountain sheep I. Ap Dewi, M. Saatci and Z. Ulutas School of Agricultural and Forest Sciences, University of Wales, Bangor, LL57 2UW, UK Abstract Genetic parameters of weight traits, ultrasonic fat and muscle depths, maternal effects and reproductive traits of Welsh Mountain sheep were estimated based on analyses of data from the nucleus flock of a cooperative breeding scheme. The traits analysed were 12 week weight (TW, no. = 11201), mature weight (MW, no. = 2376), weight at scanning (SW, no. = 1022), muscle depth (SM, no. = 1024), fat depth (SF, no. = 1024), litter weaning weight (LW, no. = 3445) and litter size (LS, no. = 3445). (Co)variance components were estimated in univariate and bivariate animal models. Heritability estimates from univariate analyses were 0 16, 0 49, 0 29, 0 24, 0 22, 0 20 and 0 15 for TW, MW, SW, SF, SM, LW and LS respectively. Genetic correlations among the weight traits were high. There was no detectable correlation between SF and SM. SF and SM were strongly correlated with SW but not with the other weight traits. LW was strongly correlated with MW and SW but not with TW, although the latter analysis was inconclusive. Maternal heritability was similar (0 11) for the univariate analysis of TW and all bivariate analyses involving TW (except for TW v. LW). The permanent environmental effect of dam was generally low (0 02 to 0 04) whilst litter effects were generally high (0 20 to 0 23). The correlation between direct and maternal genetic effects for TW were generally small and non-significant. The maternal genetic effect for TW was moderately correlated with the direct additive effect for MW and SW but was not significantly correlated with the direct additive effect for LS, SM or SF. A very large positive correlation was found between the maternal genetic effect for TW and the direct additive effect for LW. The implications of the results are discussed in the context of selection indices for Welsh Mountain sheep. Keywords: body weight, carcass traits, genetic parameters, maternal effects, sheep. Introduction Selection indices utilizing estimated breeding values (EBV) for traits in the selection criteria have been adopted by sectors of the UK sheep industry, particularly for terminal sire breeds (Hall, 1997; Simm, 1998; Meat and Livestock Commission (MLC), 2000). The widespread use of ultrasonic scanning to determine fat and muscle depth has allowed the incorporation of carcass traits into selection indices (Simm and Dingwall, 1989; Gilmour et al., 1994; Fogarty, 1995; Clarke et al., 1998). Such indices require accurate estimates of genetic (co)variances for the selection criteria and of the genetic covariances between the criteria and objectives (Schneeberger et al., 1992). Whilst these techniques 399 have been used for terminal sire breeds in the UK there has been less emphasis on their application in hill breeds, particularly the Welsh Mountain. The Welsh Mountain is an important breed in the UK, both in terms of the number of purebred animals on hill farms and its contribution to the production of crossbred lambs and halfbred ewes in upland and lowland systems (MLC, 1988; Pollott, 1998). Meyer (1992) defined several models for beef cattle that incorporated combinations of direct additive, maternal genetic and maternal permanent environmental effects. Comparable models have been applied to sheep with the inclusion of litter effects in some cases (e.g. Saatci et al., 1999). Whilst

2 400 Ap Dewi, Saatci and Ulutas the correlation between direct and maternal effects have been investigated for pre-weaning weights there are only a few reports of the correlations between maternal effects on lamb weight and direct effects for other traits. Nasholm and Danell (1996) reported genetic correlations between direct ewe effect and maternal effect on lamb weight of 0 39 to Analla and Serradilla (1998) found no correlation between permanent environmental effect for litter size and maternal effect on weight. Rao and Notter (2000) examined the association between additive maternal effects on weight and direct additive effects on litter size reporting evidence of a positive correlation in some breeds. The objectives of the current analyses, based on data for Welsh Mountain sheep were to (a) estimate correlations between traits that are important selection objectives and criteria and (b) to estimate maternal effects and associated covariances in bivariate analyses. Little attention has been given to examining the consequences of including maternal effects for lamb traits in bivariate analyses that include traits of both young and mature animals. Material and methods Source of animals and data The data used in this study were collected at the CAMDA flock (near Pentrefoelas, North Wales). The CAMDA flock is the nucleus unit of a commercial group breeding scheme. CAMDA was founded in 1976 and was the first sheep group breeding scheme in the UK. The scheme, the flock and the selection index were described by Saatci et al. (1999). Data were collected for lambing years 1977 to A database containing pedigree information, lamb weights, mature weight and litter size was provided by Signet, a recording agency for UK sheep flocks (Simm, 1998). Information available included lamb, sire and dam identification, sex, birth/lambing year, birth-rearing type, dam age at lambing, true lamb age at 12-week weighing, 12-week weight, and mature weight. Ultrasonic scanning results were available from the results of an over-winter ram performance test conducted at the University of Wales, Bangor and for ewes from scanning conducted within the CAMDA nucleus flock (I. Ap Dewi, unpublished). The scanning results included weight at scanning, muscle depth, fat depth, true age at scanning, sex, year and birth-rearing type. Definition of traits analysed Twelve-week weight (TW). Lamb weight (kg) recorded at approximately 12 weeks of age. Lambs were weighed on the same day within each recording year. Mature weight (MW). Weight of females (kg) at the end of an away-wintering grazing period at a lowland site, normally March/April when animals were approximately 12 to 13 months old. Animals were weighed on the same day within each recording year. Scanning weight (SW), scanning fat (SF) and scanning muscle (SM). These traits, recorded in , were measured (in kg, mm and mm respectively) for males at the end of an over-winter performance test at a lowland site, at the end of April when animals were approximately months of age. For females, the traits were measured during the animals second grazing season (between April and October, 12 to 20 months of age) before their first mating. SF and SM were measured ultrasonically at the 3rd lumbar vertebrae by trained MLC/Signet staff by their defined procedure (MLC, 1989). Litter weaning weight (LW). Litter weaning weight (kg) was the sum of lamb TW per ewe per annum. This trait was calculated from the TW in the database. Litter size (LS). Number of lambs born per ewe per annum. LS was assigned to ewes as an animal trait by cross-referencing their identity with dam identities and corresponding birth type. Table 1 Distribution of observations by trait (in bold print on the diagonal) and between traits. The number of animals with records for both traits are shown below the diagonal and the number of animals with records for both traits in the same recording year are shown above the diagonal Trait TW MW SW SF SM LW LS 12-week weight (TW) Mature weight (MW) Scanning weight (SW) Scanning fat (SF) Scanning muscle (SM) Litter weaning weight (LW) Litter size (LS) Number of animals. These traits have repeated records. The number of recorded litters was 8219 for both LW and LS.

3 Table 2 Basic statistics for each trait and covariate Genetic parameters in Welsh Mountain sheep 401 Mean s.d. Minimum Maximum Trait 12-week weight (TW kg) Mature weight (MW kg) Scanning weight (SW kg) Scanning fat (SF mm) Scanning muscle (SM mm) Litter weaning weight (LW kg) Litter size (LS) Covariate Lamb age at TW (days) Age at scanning (days) Numbers of observations for each trait are given in Table 1. The number of observations for each trait, and trait combinations, are shown in Table 1 with summary statistics for each trait in Table 2. There were considerably more records for TW (11 201), LW (8219) and LS (8219) than the other traits with the scanning traits having 1022 to 1024 records. All trait combinations had animals with records for both traits although the number was smaller for combinations including the scanning traits. For combinations involving either LW or LS there were no animals having records in the same recording year, as expected because these were traits of females from their first lambing (approx. 2 years of age) whereas the other traits were recorded before first mating (approx. 18 months of age). There were 181, 150 and 189 sires for TW, MW and LS respectively. There were 87 sires for the scanning traits (SW, SF and SM). There were 3 25 records per dam for TW. Definition of fixed effects and covariates Year. Year of birth (in the period ) was used for TW, MW and scanning traits. Year of lambing was used for LW and LS. Sex. Records for both males and females were available for TW and scanning traits. Only female records were available for MW, LW and LS. Birth-rearing type. This was included for all traits except LW and LS. There were three classes namely single born-single reared, twin born-twin reared, twin born-single reared. Dam age. Age of dam (2 to 5 years) at the time when an animal was born was known for TW, MW and the scanning traits. Ewe age. Ewe age (2 to 5 years) at lambing was included for LW and LS. Litter code. For LW a litter code (type of rearing x sex) was created with five classes, namely, single male, single female, twins both males, twins both females, and twins with one male/one female. Animal age. The age of animals (days) at the time of recording was available for TW and scanning traits (Table 2). Age when TW was recorded was also used in the analysis of LW to correct for litter age effects. Age at MW was not available and age at TW, nested within years, was used. This is justified since, within a recording year, the interval between recording TW and MW was the same for all animals. The number of classes for each of the main effects are presented in Table 3. The number of observations per class was variable depending on the number of classes and the number of observations per trait and ranged from 18 (year for SW) to 5982 (birth-rearing type for TW). Data editing procedures The database was edited to eliminate genetic control line animals (no. = 886, from a small sub-flock based on random selection of replacements as described by Saatci et al., 1999), animals whose sire was unknown (no. = 535), animals with missing TW (no. = 911), animals with missing dam age (no. = 43) or dam age 1 (no. = 1), lambs born in one year as part of an embryo transfer experiment (no. = 123), fostered and artificially reared lambs (no. = 89), and lambs born as triplets (no. = 110) or quads (no. = 6). Animals with TW less than or greater than three standard deviations from the mean TW of the raw data were

4 402 Ap Dewi, Saatci and Ulutas Table 3 Number of classes for each of the fixed effects (minimum and maximum observations per class in parentheses) Factor TW MW SW SF and SM LW and LS Year ( ) (59-178) (18-231) (19-231) ( ) Sex ( ) ( ) ( ) Birth-rearing type ( ) ( ) (61-542) (61-544) Dam age 4 4 ( ) ( ) Ewe age 4 ( ) Litter code ( ) 5 ( ) The classes are defined in the text. Abbreviations for the traits are described in the text and in Table 1. Used in the model for LW but not LS. eliminated (no. = 46). Animals weighed at an age that was less than or greater than three standard deviations from the mean age of the raw data were also deleted (no. = 162). Genetic control line animals were also eliminated from the database of ultrasonic scanning traits as were animals whose date of birth was unavailable, and for whom age could therefore not be calculated. LW was calculated, as described above, from TW after all edits had been completed. Dam/ewe ages greater than 5 were coded to 5 before the analyses. Statistical analyses (Co)variance components and genetic parameters were estimated by ASREML (Gilmour et al., 1998). The models used for each trait are summarized in Table 4. Each trait was analysed with animal as a random factor to fit the additive direct effect, animal being the individual for which the trait was recorded, namely lambs for TW, yearlings for MW, SM and SF and ewes for LW and LS. For TW the model also included the maternal permanent environment effect, fitted as an additional random effect uncorrelated with all other effects in the model, a maternal common environment effect (i.e. litter effect), an additive maternal effect fitted as a second random effect for each animal with the same covariance structure as the additive direct effect and a covariance between direct and maternal genetic effects. The maternal permanent environmental variance and the maternal common environmental variance are referred to as σ 2 PE and σ 2 CE as defined by Saatci et al. (1999) who described models to analyse TW in Welsh Mountain sheep. For LW and LS, which were traits with repeated records, the permanent environmental variance associated with animal (σ 2 PEA) was included as an Table 4 Random factors and fixed effects included in each univariate model Trait SW, SF LW Factor TW MW and SM and LS σ 2 A σ 2 M σ 2 PE σ 2 CE σ 2 PEA σ AM σ 2 E Year Sex Birth-rearing type Dam age Ewe age Litter code Lamb age at TW Age at scanning σ 2 direct additive genetic variance; A σ2 maternal additive M genetic variance; σ AM direct-maternal genetic covariance; σ 2 maternal permanent environmental variance; σ 2 PE CE maternal common environmental variance; σ 2 permanent PEA environmental variance associated with animal; σ 2 E residual (error) variance. Interactions were also included for TW year sex; year birth-rearing type; sex birth-rearing type; year sex birth-rearing type. The use of lamb age at TW nested within year as a covariate for MW is explained in the text. For LW only.

5 Genetic parameters in Welsh Mountain sheep 403 additional random effect, uncorrelated with all other effects in the model. The fixed effects, and their interactions, included in the models were identified in preliminary analysis (Ap Dewi, unpublished) of the data that included the random terms defined above and fixed effects available in the dataset and likely to affect the traits. Non-significant (P > 0 05) fixed effects were identified and removed by backwards-elimination. Fixed effects included for each trait are defined in Table 4. Age at recording was fitted as a linear covariable for TW and scanning traits. Age at TW was also used to correct for litter age effects in the analysis of LW. As described above age at TW, nested within years, was used as a covariate in the analysis of MW. Bivariate analyses were completed for all combinations of the traits, and the numbers of observations are given in Table 1. The random factors, fixed effects and covariates for each trait were as defined in Table 4. All the bivariate analyses included the additive direct effect for both traits and the covariance between the additive direct effects. Bivariate analyses having TW as one of the traits also included the covariance between the direct additive effect for TW and the maternal genetic effect for TW. These analyses also included the covariance between the maternal genetic effect for TW and the direct additive effect for the other trait. In addition to the residual (error) variances for each trait, an error covariance was fitted for all combinations except for those involving either LW or LS with one of the other traits. The error covariance for these combinations was fixed at zero since one trait had repeated records on traits (LW and LS) recorded from 2 years of age and the other trait had single records for lambs or yearlings. For the bivariate analysis of LW and LS a covariance between permanent environmental effects was fitted. Whether (co)variance components were significantly different from zero was determined by the procedure described by Gilmour et al. (1998). Components were considered to be significant if the component divided by its standard error (C/s.e. ) was greater than or equal to 2. They were considered to be nonsignificant if C/s.e. was less than 0 5. In cases where C/s.e. was between 0 5 and 2 then the significance of a component was determined using a likelihood ratio test (P = 0 05) comparing models with and without the component. Results Summary statistics for each trait are presented in Table 2. TW, MW and SW had mean weights of 20 6, 36 1 and 42 3 kg respectively. The lower value for TW is as expected since this trait was recorded at least 8 months sooner than the other two weight traits. The lower value for MW compared to SW reflects the fact that MW was recorded only for females whilst SW was recorded for males and females, some of which would have been older at scanning than at MW. Each of the weight traits had considerable variation in recorded values. There was variation in the scanning results with large differences between minimum and Table 5 Estimates of genetic parameters (s.e.) from univariate and bivariate analyses with heritability (univariate) on diagonal, genetic correlations above and residual correlations below the diagonal TW MW SW SF SM LW LS TW (0 026) (0 060) (0 129) (0 170) (0 182) (0 109) MW (0 033) (0 044) (0 040) (0 166) (0 183) (0 051) (0 060) SW (0 048) (0 029) (0 071) (0 137) (0 176) (0 115) (0 144) SF < 0 01 (0 058) (0 079) (0 055) (0 072) (0 234) (0 139) (0 168) SM * 0 35 (0 054) (0 079) (0 056) (0 061) (0 071) (0 015) (0 162) LW (0 026) (0 100) LS < (0 018) (0 023) Abbreviations for the traits are defined in the text and in Table 1. Fixed at 0 as explained in the text. Genetic (co)variances fixed at boundary and no s.e. calculated. Associated variance component was significantly different from zero (procedure described in text).

6 404 Ap Dewi, Saatci and Ulutas maximum for both SM and SF. LW had a mean of 28 kg which is consistent with the product of the mean values for TW and LS. Average LS was 1 4. Heritabilities, genetic correlations and environmental correlations are presented in Table 5. All the h 2 estimates were significant and estimates of heritability from the bivariate analyses were generally similar to those obtained in the univariate analyses. The scanning traits, SF and SM, had similar h 2 in the range 0 2 to 0 3. Of the three weight traits, h 2 was lowest for TW and greatest for MW. LS had the lowest h 2 of the traits examined (0 15) and LW had a h 2 of 0 2. Genetic correlations amongst the weight traits, particularly MW and SW (0 93), were high. SW was strongly correlated with SF and SM but the correlations between SM and SF and the other weight traits (TW and MW) were small and nonsignificant. There was no detectable genetic correlation between SF and SM. LW was strongly correlated with MW and SW but had a low correlation with TW. There was a significant correlation between LW and SM but not between LW and SF although the magnitudes of these correlations were similar (0 28 and 0 20 respectively). LS was significantly correlated with TW and MW but not SW. There was no significant correlation between LS and SF or between LS and LW. LS and SM were positively correlated (0 35). Environmental correlations were generally significant with a strong association between the weight traits (0 4 to 0 8). There were moderate environmental correlations between the traits recorded at scanning (0 1 to 0 3), low correlations between SM v. TW and SM v. MW (0 17 and 0 16 respectively), and no significant correlation between TW v. SF. Maternal effects are shown in Table 6. Maternal heritability was similar (0 11) for all analyses except for TW v. LW, an analysis in which parameters were fixed at a boundary. Permanent environmental effects of dams were generally low (0 02 to 0 04) whilst litter effects were consistently high (0 2 to 0 23) except for TW v. LW. The correlation between the direct and maternal genetic effects for TW were generally small and non-significant, except for the TW v. MW analysis in which a correlation of 0 22 was estimated. The highest correlation between the maternal genetic effect for TW and the direct additive effect for another trait was for TW v. LW, where parameters were fixed at a boundary and a correlation of 0 98 was estimated. The correlation between the maternal genetic effect for TW and the direct additive effects was non-significant for TW v. LS, TW v. SF and TW v. SM but was moderate for TW v. MW (0 5) and TW v. SW (0 4). The permanent environmental effect of animal was non-significant for LW and small for LS. Discussion Direct additive effects and genetic correlations The animal model analyses made use of all available pedigree information. The main weakness was the smaller number of observations for some traits than others. There were considerably lower numbers of Table 6 Estimates of genetic parameters for maternal effects on TW and correlations from the univariate analysis of TW and bivariate analyses between TW and other traits TW MW SW SF SM LW LS m (0 020) (0 018) (0 020) (0 020) (0 02) (0 020) c < (0 015) (0 013) (0 014) (0 015) (0 02) (0 015) pe (0 016) (0 016) (0 016) (0 016) (0 016) (0 014) (0 016) r ATWM (0 126) (0 123) (0 128) (0 124) (0 126) (0 126) r AXM (0 076) (0 136) (0 161) (0 177) (0 103) pe 2 < TX (0 017) Components fixed at a boundary. Univariate analysis. Associated variance component was significantly different from zero (procedure described in text). m 2 is the maternal genetic effect on TW, c 2 is the maternal permanent environment effect on TW, and pe 2 is the maternal common environment (litter) effect on TW. r ATWM is the genetic correlation between direct and maternal effects for TW. r AXM is the genetic correlation between the direct effect for trait x and the maternal effect for TW. pe 2 is the permanent environmental effect for trait x. TX

7 Genetic parameters in Welsh Mountain sheep 405 records for the traits recorded at scanning than for the other traits and compared to some published work (e.g. Larsgard and Olesen, 1998). Scanning was only performed on candidate breeding animals (approximately 50% of females and 10% of males) resulting in a sub-set of data that might have biased the results. Heritabilities were moderate for weight and scanning traits suggesting that there is potential to select for these traits in the Welsh Mountain breed. The h 2 of TW was comparatively low but this is possibly due to the inclusion of a maternal genetic effect in the model. The sum of h 2 and m 2 for TW is comparable to the heritability of the other weight traits. The h 2 estimates for all traits are within the range of published values. The estimated heritability of weaning weight is in the range 0 1 to 0 3 (Burfening and Kress, 1993; Maria et al., 1993; Van Wyk et al., 1993; Vaez Torshizi et al., 1996; Clarke et al., 1998; Mousa et al., 1999). It is affected by breed, the model used and by age at weaning (Van Wyk et al., 1993; Notter, 1998). A larger range of estimates has been reported for mature weight, 0 1 to 0 6, reflecting the variety of breeds and ages at recording that have been analysed (Brash et al., 1992; Fogarty et al., 1994; Bishop et al., 1996; Nasholm and Danell, 1996; Vaez Torshizi et al., 1996). Ultrasonically measured muscle and fat depth have heritability estimates between 0 2 and 0 4 (Fogarty et al., 1994; Bishop et al., 1996; Clarke et al., 1997 and 1998) but some authors have reported estimates for muscle depth either higher (Olesen and Husabo, 1994) or lower (Gilmour et al., 1994) than this range. Estimates of heritability for weight at scanning have been in the range 0 1 to 0 4 (Fogarty et al., 1994; Gilmour et al., 1994). As found in the present analysis, published estimates of litter weaning weight heritabilities have been low, in the range 0 05 to 0 26 (Fogarty et al., 1994; Snyman et al., 1997; Bromley et al., 2001). Litter size had a low heritability (0 15) which is at the upper end of estimates in the literature (Waldron and Thomas, 1992; Fogarty et al., 1994; Analla et al., 1997; Bromley et al., 2000; Rao and Notter, 2000). Genetic correlations were strong among the weight traits. This is to be expected for MW and SW since they were very similar traits recorded in the same period of the animal s life after their first winter. Genetic correlations between lamb weights recorded at various times have been generally high and positive (Maria et al., 1993; Vaez Torshizi et al., 1996; Notter, 1998; Snyman et al., 1998; Mousa et al., 1999) and a high correlation between lamb weight and mature weight has also been recorded (Nasholm and Danell, 1996). A non-significant correlation was found between SM and SF. Some authors have reported positive genetic correlations between muscle and fat depth measured ultrasonically (Simm and Dingwall, 1989; Clarke et al., 1997) but Conington et al. (1998) reported a negative correlation between muscle and fat depths at constant age in Scottish Blackface sheep. The relationships between live weight and fat depth or muscle depth have been positive but with a large range in the estimates 0 1 to 0 8 (Fogarty et al., 1994; Brash et al., 1992; Conington et al., 1998). In the present analysis ultrasonic scanning traits (SM and SF) were strongly correlated to SW but not to TW and MW. Since SM and SF were recorded approximately 9 months later than TW, this may reflect differences in genes affecting pre-weaning growth and those affecting carcass traits as the animal approaches maturity or possibly differences in the expression of the same genes pre- and postweaning. As might have been expected since LW is a function of TW, LW was strongly correlated with MW and SW but interestingly not TW. This may be a misleading result since the analysis of LW v. TW was not conclusive. Genetic correlations between live weight and reproductive traits have been positive, 0 2 to 0 6, but not always significant (Waldron and Thomas, 1992; Fogarty et al., 1994; Al Shorepy and Notter, 1996; Analla et al., 1997; Analla and Serradilla, 1998; Rao and Notter, 2000; Bromley et al., 2001). As suggested by Analla et al. (1997) it was assumed that the environmental correlations between LS or LW and the other traits were zero because LS and LW had repeated records for mature animals whereas the other traits were recorded for lambs or yearlings. Conceptually a correlation between temporary environmental effects might exist for some of the records (e.g. between residual effects for MW and LS at first lambing). There might also be a correlation between the permanent environmental effects for both traits (e.g. between permanent environmental effects for TW, part of the error variance in the current analyses, and permanent environmental effects for LW or LS). The low estimate of permanent environmental effect on LW is consistent with the low maternal permanent environmental effect recorded for TW. Maternal effects In the univariate analysis of TW, m 2, c 2 and pe 2 accounted for proportionately 0 28, 0 07 and 0 38 of the phenotypic variation, respectively, with h 2 accounting for There was no significant directmaternal correlation. These results are consistent with those reported by Saatci et al. (1999) for a subset of the same data using a range of models for TW. Correlations between direct and maternal effects on

8 406 Ap Dewi, Saatci and Ulutas weaning weight have generally been negative with a range from 0 1 to 0 6 (Van Wyk et al., 1993; Vaez Torshizi et al., 1996; Notter, 1998) but there have been reports of zero correlations (Larsgard and Olesen, 1998; Saatci et al., 1999) and some positive (Burfening and Kress, 1993; Sousa et al., 1999). Estimates of this correlation are influenced by the model used and problems of precise estimation were noted by Larsgard and Olesen (1998). The m 2 estimate is at the lower end of the range of published values. Maternal heritabilities in the range 0 1 to 0 4 have been estimated for weaning weight with evidence that the estimate is affected by the model used and that it tends to decline from birth to slaughter (Burfening and Kress, 1993; Maria et al., 1993; Van Wyk et al., 1993; Conington et al., 1995; Al Shorepy and Notter, 1996; Nasholm and Danell, 1996; Vaez Torshizi et al., 1996; Lasgard and Olsen, 1998; Mousa et al., 1999). There are fewer estimates of litter and permanent environmental effects on weaning weight and care is needed when interpreting them since some estimates are based on models where one of these effects is included but not both. Litter effects, as a proportion of phenotypic variance have been in the range 0 1 to 0 4 (Tosh and Kemp, 1994; Al Shorepy and Notter, 1996; Clarke et al., 1998; Analla and Serradilla, 1998; Bromley et al., 2001). Permanent environmental effect has ranged from 0 05 to 0 10 (Maria et al., 1993; Al Shorepy and Notter, 1996; Mousa et al., 1999). The c 2 and pe 2 estimates are consistent with published values which show a considerably larger litter effect than permanent environmental effects. This suggests that ewe management within-year can have an important impact on the environmental influences exerted on a lamb via its dam. The estimates of maternal effects, genetic and environmental, were largely consistent between the univariate TW analysis and the bivariate analyses. Only the analysis of TW v. LW gave notably different values but these results should be treated with caution because the analysis failed to converge and parameters were fixed at a boundary. In each of the bivariate analyses the direct-maternal correlation for TW was consistently small and nonsignificant, except for the TW v. MW analysis that gave a direct-maternal correlation for TW of The direct-maternal correlation for TW in the TW v. SW analysis also tended to be higher although it was not significantly different from zero. The higher covariance between direct and maternal effects for TW in the TW v. MW analysis was due to smaller permanent environmental and litter effects in this analysis compared with the univariate TW analysis. The generally low direct-maternal correlation for TW is not typical compared with other published work but could be a feature of the Welsh Mountain breed (Saatci et al., 1999). This could be a reflection of longterm selection within a production system that has a relatively long rearing period on hill grazing areas where forage resources are limited. A strong positive correlation between direct and maternal effects under these circumstances could be potentially disadvantageous to ewe condition and ewe survival as a consequence of a high demand for milk by sucking lambs. Likewise, a strong negative correlation could disadvantage lambs of high genetic potential for growth because of their dependence on a maternal contribution to growth. There was a very high correlation between the maternal genetic effect for TW and the direct additive effect for LW. This is as expected since the maternal genetic effect on TW must be closely associated to the dams direct additive genes reflected in LW. This confirms the value of using breeding value estimates for maternal ability, obtained from analysis of TW, as a criterion in selection indices that incorporate LW as one of the objectives. There was no significant association between the TW maternal genetic effect and the direct additive effects for LS, SF or SM. However there was a significant correlation between the TW maternal genetic effect and the direct additive effects for MW and SW, presumably reflecting the association between MW and SW and one of LW s components, TW. These correlations highlight the connection between direct genes affecting weight as the animal approaches maturity and maternal genes affecting pre-weaning growth. The strength of this correlation, and the strong correlations that exist among the weight traits, suggests that using mature weight as a selection criterion may be unnecessary if TW is recorded and both direct and maternal EBVs are used as selection criteria. The low repeatability of LW contradicts the suggestion by Snyman et al. (1997) that first record of litter weaning weight could be used as a basis to improve lifetime performance due to the high genetic correlation between first and subsequent records. One limitation of the current analysis is the absence of correlations between ultrasonically measured fat and muscle depth and a measure of carcass quality that could be used as a selection objective. Generally, positive correlations have been reported between muscle depth and carcass lean content with negative correlations between fat depth and carcass lean content (Waldron et al., 1992; Conington et al., 1998; Thorsteinsson and Eythorsdottir, 1998). In the current

9 Genetic parameters in Welsh Mountain sheep 407 analyses only the direct additive effect was fitted in models for traits recorded at scanning. Other authors have included maternal and litter effects when analysing scanning traits (e.g. Clarke et al., 1998) but with considerably younger animals than in the current analysis (6 m v. 12 m). It would be important to consider maternal effects for these traits in the Welsh Mountain if animals were scanned earlier, as might be the case if lambs were scanned at about 12 weeks of age. It would also be possible to extend some of the bivariate models to include additional correlations, for example, between the permanent environmental effects and maternal genetic effects (Analla and Serradilla, 1998; Tosh et al., 2000). There are considerable variations in published estimates for the genetic parameters and correlations between objective and criteria traits, as highlighted by Tosh and Kemp (1994) and between selection lines within a breed (Bishop et al., 1996). These differences among breeds and lines justify the analysis of data for the Welsh Mountain to obtain appropriate parameters for the breed. The estimates published here can be used in the construction of selection indices for Welsh Mountain flocks, using literature estimates of the associations between the selection criteria and carcass lean content (if this is used as an objective). However, more work is required to determine the genetic correlations between the maternal effects for TW, and possibly SF and SM, and direct effects for carcass lean content. Acknowledgements The authors acknowledge with gratitude the contribution of the CAMDA group breeding scheme, Meat and Livestock Commission/Signet, Kafkas University (Turkey) and Ministry of Agriculture in Turkey, the Welsh Sheep Strategy, staff at the University of Wales, Bangor, College Farm, A. R. Gilmour, R. M. Lewis and C. J. Whitaker. References Al Shorepy, S. A. and Notter, D. R Genetic variation and covariation for ewe reproduction, lamb growth and lamb scrotal circumference in a fall-lambing sheep flock. Journal of Animal Science 74: Analla, M., Munoz Serrano, A. and Serradilla, J. M Analysis of the genetic relationship between litter size and weight traits in Segurena sheep. Canadian Journal of Animal Science 77: Analla, M. and Serradilla, J. M Estimation of correlations between ewe litter size and maternal effects on lamb weights in Merino sheep. Genetics, Selection, Evolution 30: Bishop, S. 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