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Genetic variation of plasma insulin-like growth factor-1 in young crossbred ewes and its relationship with their maintenance feed intake at maturity and production traits¹

The Australian Sheep Industry Cooperative Research Centre, NSW Department of Primary Industries, Orange Agricultural Institute, Orange, NSW 2800, Australia

	Abstract

Top Abstract INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
The genetic variation of plasma IGF-I in crossbred ewe lambs postweaning was evaluated together with its potential use as a physiological marker for selection in meat sheep. Genetic variation for IGF-I was analyzed among 1,246 young crossbred ewes that were the progeny of 30 sires from various maternal breeds and Merino dams. The estimate of heritability of IGF-I was 0.28 ± 0.10, with sire breed not being significant. Genetic correlations were estimated between IGF-I and performance traits of the ewes, including feed intake, growth, body composition, wool, and reproduction over 3 matings. Although the genetic correlations had high standard errors because of the limited size of the data set, the correlation between IGF-I and grazing feed intake of the mature ewes at maintenance was positive (0.32 ± 0.31). The genetic correlations of IGF-I with other traits ranged from positive and low to moderate for growth (0.05 to 0.36), positive for ultrasound eye muscle depth (0.15), and negative for ultrasound fat depth (–0.12) in the mature ewes, and close to zero for the wool traits. The genetic correlation between IGF-I and the average number of lambs born per ewe mated was negative (–0.18), whereas that for the average number of lambs weaned per ewe mated was positive (0.10). The parameters indicated that genetic variation exists for IGF-I in sheep, and selection for low IGF-I in young ewes may result in some reduction in feed intake and improvement in maintenance efficiency of mature ewes under grazing, with little impact on other production traits. However, the genetic correlations had high standard errors, and more precise estimates of these parameters are required for genetic evaluation and to predict with confidence the outcome of breeding programs.

Key Words: ewe • feed intake • genetic parameter • heritability • insulin-like growth factor-I

	INTRODUCTION

Top Abstract INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
Insulin-like growth factor-I could be a useful physiological indicator to assist in the screening and selection of livestock at an early age. Insulin-like growth factor-I is a naturally occurring hormone that influences growth and development as part of a complex system. It can be measured relatively easily in young animals and could be used to predict future performance, especially for production traits that are difficult or expensive to measure, such as feed efficiency (Bunter et al., 2005b).

Several studies have shown a link between circulating IGF-I concentration and growth traits in laboratory animals (Blair et al., 1988), cattle (Davis and Simmen, 1997), sheep (Olsen et al., 1981; Roberts et al., 1990; Hegarty et al., 2006), swine (Buonomo et al., 1987; Scanes et al., 1987), and chickens (Goddard et al., 1988). Carcass quality characteristics have also been correlated with IGF-I in cattle (Davis and Simmen, 2000) and pigs (Suzuki et al., 2004). There is moderate heritability for IGF-I levels in beef cattle (Herd et al., 1995; Davis et al., 2003) and dairy cattle (Hayhurst et al., 2006). Bunter et al. (2005b) reported a range of 0.21 to 0.58 for heritability of IGF-I in juvenile pigs and that IGF-I was genetically correlated with backfat depth, feed intake, and feed conversion ratio. Divergent selection for plasma IGF-I in sheep over 5 generations indicated moderate heritability and some association between juvenile IGF-I and feed efficiency and lean growth (Blair et al., 2002).

This study reports on the genetic variation in postweaning plasma IGF-I of crossbred ewe lambs and the genetic correlations of their IGF-I level with the maintenance grazing feed intake of the ewes at maturity and several other growth and body composition, wool production, and reproduction traits of the ewes. The implications for use of IGF-I in sheep breeding programs are discussed.

	MATERIALS AND METHODS

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The project was conducted under approval of the NSW Department of Primary Industries Orange Animal Ethics Committee (ORA 97/001).

Animals and Traits

The 1,246 crossbred ewes in this study were a subset of ewes at the Cowra site of the Maternal Sire Central Progeny Test (MCPT; Fogarty et al., 2005). The ewes were progeny of medium wool Merino dams and 30 individual sires from several maternal crossing breeds. There were 3 cohorts of the crossbred ewes, born in August 1997 and in July of 1998 and 1999 following synchronized matings by laparoscopic AI using thawed-frozen semen. Nine different sires were used each year and 3 additional sires were used every year to provide genetic links across years for evaluation. The sires were from several breeds, including Border Leicester (n = 7), East Friesian (3), Finnsheep (3), Coopworth (3), White Suffolk (3), Corriedale (2), Booroola Leicester (3), and other (1 sire from each of English Leicester, Gromark, Merino, Wiltshire Horn, and 2 composite breeds). Further details of the MCPT, including generation of the crossbred ewes, management at the sites, and genetic merit of the sires used, have been provided by Fogarty et al. (2005)

Live weights were measured on the ewes at birth (BWT), weaning (WWT) at 9 to 12 wk of age, postweaning (PWWT) at approximately 6 mo of age, and as mature adults (AWT) at approximately 4 yr of age. Wool production of the ewes was measured in their first year after a lamb shearing, and the traits included greasy and clean fleece weight, clean yield, and average fiber diameter. The ewes were mated naturally to groups of Poll Dorset rams for 5 to 6 wk in either autumn or spring over 3 yr to assess ewe reproductive performance. After being weaned, each cohort of crossbred ewe lambs was randomly assigned within sire group to either autumn or spring mating groups. The autumn cohort groups were first mated at 7 mo of age (February to March) to lamb at 12 mo of age (July to August). The spring cohort groups were first mated at 14 mo of age (October to November) to lamb at 19 mo of age (March to April). The reproduction traits were the number of lambs born and weaned (of ewes mated), which was averaged over their first 3 matings. Where ewes did not survive for 3 matings, the average of available matings was used.

The feed intake (DDMI, digestible DMI) of the mature ewes (nonpregnant and nonlactating at approximately 4 yr of age) while grazing on pasture at maintenance was also obtained. This was estimated by using the fecal marker dilution technique with chromium sesquioxide controlled-release devices, which has been shown to allow relatively precise estimation of grazing intake for large numbers of sheep (Parker et al., 1989; Lee et al., 1995). The ewes grazed mixed grass-alfalfa pasture with greater than 1.5 t of DM/ha. The paddock for each group was selected to be as uniform as possible and to have sufficient growth to maintain the ewes for 4 wk. Pastures were sampled to estimate available DM, green and dead material, the proportion of legume, and DM digestibility. Fecal samples were collected on 3 occasions over a 7- to 10-d period after an initial 7- to 10-d period following administration of the controlled release devices, with the detailed procedures and results reported separately (Fogarty et al., 2006). There was a decline in the release rate of the devices over the 3 yr of sampling, resulting in heterogeneity of variance of DDMI across cohort groups. This was removed by expressing the DDMI of individual ewes as a ratio of the mean for each cohort group, that is, relative DDMI (rDDMI; Fogarty et al., 2006). The body composition traits (fat depth and eye muscle depth) were measured on the mature ewes by an accredited ultrasound scanner at the time of feed intake estimation, and AWT was recorded as well. Fat depth and eye muscle depth were measured at the C site, which is 45 mm from the mid-line over the 12th rib. Feed intake data were available for 1,088 ewes.

Blood Collection and IGF-I Assay Procedures

A blood sample was collected from the crossbred ewe lambs after weaning at approximately 18, 22, and 31 wk of age for the 1997, 1998, and 1999 cohort ewes, respectively. Both age at collection and the interval from weaning to collection differed between cohorts. Blood was collected by jugular venipuncture into 10-mL heparin Vacutainer (Becton Dickinson, Franklin Lakes, NJ) tubes, held on ice and spun in a refrigerated centrifuge, and the plasma was pipetted into a container and held frozen at –20°C. Samples were assayed at the Primegro Limited laboratory (Adelaide, Australia) by using a commercially available ELISA assay (Diagnostic Systems Laboratories Inc., Webster, TX). This kit is a nonextraction IGF-I ELISA, using an enzymatically amplified "2-step" sandwich-type immunoassay. It is validated to quantify IGF-I concentration in human plasma with an intra-assay CV of <10% and sensitivity for minimum detection of 0.01 ng/mL.

Statistical Analysis

A linear mixed model was used to analyze the plasma IGF-I level in the young crossbred ewes. The model included fixed effects for assay (batch and plate), cohort (1997, 1998, 1999, year of birth), and sire breed (1 to 8). The effect of mating group was not significant because the groups were split close to or after blood sampling, and the effect was not included in the final model. Age of the ewe lambs was not included because they were produced from synchronized matings with a small age range of approximately 7 d within each cohort. There were age differences at sampling across the years that are part of the cohort effect. All 2-way interactions were not significant (P > 0.05) and were excluded from the final model (model 1). A second model (model 2) was also fitted, which included linear covariates to examine the effects of WWT and postweaning ADG (PADG) on IGF-I. A univariate animal model was used to estimate variance components for IGF-I by restricted maximum likelihood procedures using ASReml (Gilmour et al., 2006). Under this model, the sire breed fixed effect was tested relative to the genetic (between-sire) variance. The sire progeny means for IGF-I were predicted from the sire solution deviations in the univariate analysis (using the fixed-effects model 1), which are estimates of the breeding values. The overall mean was added to the sire solutions so that they were expressed in actual IGF-I values rather than deviations. Genetic and phenotypic correlations between plasma IGF-I and the various production traits for the crossbred ewes were estimated by using bivariate animal models. The fixed effects in the bivariate models included those above for the univariate model for IGF-I, with cohort having 6 levels to account for year of birth and autumn and spring mating groups for all the other traits except BWT and WWT. The bivariate models for live weight, wool, and reproduction traits also included the type of birth and rearing (11, 21, and 22) of the ewe and the source of dam (detailed in Fogarty et al., 2005). The feed intake traits included AWT, ewe weight gain over the sampling period, previous lambing record, and the ultrasound fat and eye muscle depth measurements to account for these environmental effects (Fogarty et al., 2006). Fat and eye muscle depth included AWT as a covariate. The random effect of dam was significant for BWT, WWT, and PWWT, and it was included in the bivariate analyses for these traits.

	RESULTS

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The number of sires and crossbred ewes sampled for plasma IGF-I analyses in the various cohorts and their growth performance traits are shown in Table 1. There was considerable variation among the cohorts for plasma IGF-I, with the coefficient of variation ranging from 15 to 21% for the various cohorts. The 1999 cohort ewes had greater plasma IGF-I levels and were 2 to 3 mo older than the other cohorts at sampling, with little difference in IGF-I between the 1997 and 1998 cohorts. There was little difference among the cohorts for BWT, whereas at later ages the 1998 cohort ewes were lower than the 1997 and 1999 cohort ewes for WWT, PWWT, and PADG. The growth difference was not obvious at mature weight because of compensatory growth in advanced ages.

There was considerable genetic variance for plasma IGF-I of the crossbreed ewe lambs, with an estimated heritability of 0.28 ± 0.10 and phenotypic standard deviation of 62.1 ng/mL. Inclusion of WWT and PADG as covariates in the model had little effect on the estimate of heritability (0.27 ± 0.09) and slightly reduced the phenotypic standard deviation to 59.7 ng/mL. Removal of breed of sire of the crossbred ewe from the model also did not significantly change the genetic variance or the estimate of heritability. The predicted sire means showed a considerable range for plasma IGF-I within the various sire breeds, as well as across all 30 sires (Table 4). There was a range of >15% in plasma IGF-I level across sire progeny groups within most sire breeds of the crossbred ewes, with the range for the Finnsheep and East Friesian being 28%, White Suffolk 19%, and Border Leicester 15%. The numbers of ewe progeny sampled per sire for the 3 link sires (Border Leicester 12, Finnsheep 7, and Coopworth 5) were 84, 77, and 81, respectively. The other 27 sires had an average of 25.7 crossbred ewe progeny per sire, ranging from 17 to 34. Heritabilities estimated from the bivariate analyses of IGF-I with all the production traits were similar to those estimated from the univariate analysis.

	DISCUSSION

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The moderate estimate of heritability (0.28 ± 0.10) indicates there is scope for genetic change in IGF-I with selection in young sheep. Our results are consistent with the divergent response in IGF-I achieved in Romney sheep selected after weaning at 4 mo of age (Blair et al., 2002). The heritability is also similar to the estimates in terminal (0.21) and maternal (0.24) sire lines of juvenile pigs (Bunter et al., 2005b) and in beef cattle (0.31 to 0.52; Herd et al., 1995; Johnston et al., 2001; Moore et al., 2005; Davis and Simmen, 2006).

Because IGF-I can be measured relatively easily at low cost early in life, Bunter et al. (2005b) suggested it could be used as a physiological indicator for performance traits related to growth and feed efficiency. From a simulation study in beef cattle, Wood et al. (2002) concluded that IGF-I could be used effectively as a screening test in a 2-stage selection strategy for identifying animals for expensive residual feed intake testing. High genetic correlations have also been reported between various measures of feed efficiency in growing cattle and efficiency in mature cows (Archer et al., 2002). The utility of using IGF-I as an indirect selection criterion depends largely on its genetic correlations with the direct traits of interest and other important production traits. The genetic correlation between postweaning plasma IGF-I and relative feed intake of the mature crossbred ewes at maintenance was positive (rDDMI, 0.32 ± 0.31), although with a high standard error because of the limited size of the data set. The positive correlation indicates that low IGF-I levels may be associated with reduced feed intake for ewe maintenance and improved efficiency, because feed intake was adjusted for weight and other environmental effects (Fogarty et al., 2006). For young growing animals of other species, the genetic correlations reported between IGF-I and feed efficiency traits have usually been in the same direction, although generally higher in magnitude than in our study. In reviewing 5 pig trials, Bunter et al. (2005b) reported means for the genetic correlations of IGF-I with feed intake of 0.41 (the range of estimates was –0.20 to 0.78, generally with SE of approximately 0.3) and with a feed conversion ratio of 0.65 (range 0.50 to 0.84). In 2 beef cattle trials reported by Johnston et al. (2002), the genetic correlations for IGF-I were 0.01 ± 0.30 and 0.27 ± 0.14 for feed intake, 0.56 ± 0.35 and 0.39 ± 0.13 for residual feed intake, and 0.37 ± 0.42 and 0.55 ± 0.16 for feed conversion ratio, and Moore et al. (2005) reported an estimate of 0.41 ± 0.21 for residual feed intake in another study. As expected, our estimate of the phenotypic correlation between IGF-I and relative feed intake (0.05 ± 0.04) was much lower than the corresponding genetic correlation, which was similar to the pig trials (Bunter et al., 2005b).

We found positive genetic correlations between plasma IGF-I and birth and subsequent live weights of the ewes, although the magnitude of the correlation was close to zero at birth. On the contrary, negative genetic correlations between IGF-I and growth traits have been reported in pigs for birth weight (–0.33, Hermesch et al., 2001) and daily gain (–0.09, Bunter et al., 2005b) and in beef cattle for daily gain (–0.2, Johnston et al., 2002, and –0.52, Moore et al., 2005) and 200-d weight (–0.40, Moore et al., 2005). The age at IGF-I sampling may be important because Bunter et al. (2005b) noted, in reviewing several pig trials, there was a suggestion that the genetic correlation was positive for early growth and changed to negative for later growth. However, the genetic correlations among measures of IGF-I at different ages in cattle are very high (>0.86, Moore et al., 2005; Davis and Simmen, 2006). The phenotypic correlations between IGF-I and growth were also much lower than the corresponding genetic correlations in our results and for these other reports.

Although the genetic correlation between IGF-I and ultrasound subcutaneous fat depth of the mature ewes was not significantly different from zero (–0.12 ± 0.24) in this study, a similar correlation was reported in Angus beef carcasses (Davis and Simmen, 2000), although there were contrary positive correlations for ultrasound measures of fat in Angus beef cattle in the United States (Davis et al., 2003) and Australia (Moore et al., 2005), as well as in pigs (0.46 ± 0.08, Hermesch et al., 2001; 0.57, Bunter et al., 2005b). The genetic correlation between plasma IGF-I level and eye muscle depth (0.15 ± 0.24) was small and positive, which is similar in direction and magnitude to those reported for eye muscle area in beef carcasses (Davis and Simmen, 2000), although they were negative early postweaning and positive at older ages for ultrasound measures in live animals (Davis et al., 2003; Moore et al., 2005). The positive direction of the genetic correlation between IGF-I and eye muscle depth in this study is supported by that between IGF-I and the weight traits. The genetic correlations between IGF-I and the reproduction traits were smaller than their standard errors. Although the negative genetic correlation with average number of lambs born (–0.18 ± 0.25) indicates that selection for low IGF-I may result in improved lambing potential, the change in sign to a positive genetic correlation between IGF-I and average number of lambs weaned (0.10 ± 0.26) may indicate an adverse response associated with maternal environment. However, both correlations have high standard errors, as is the case with the few reports of correlations with reproduction traits in pigs (Bunter et al., 2005a) and cattle (Yilmaz et al., 2004; Hayhurst et al., 2006). The genetic correlations for the important wool traits are close to zero and little change would be expected from selection for IGF-I. The heritability estimates for the various correlated traits from the bivariate analyses are generally higher than those from the larger MCPT data set (Ingham et al., 2007)

Sheep breeding programs could be enhanced by inclusion of a physiological trait that is an indicator of performance if genetic variation can be measured cost effectively at an early age. The range in sire progeny means and estimated heritability of plasma IGF-I in young sheep shows there is genetic variation that could respond to selection. In some species, plasma IGF-I level has been suggested as an indicator of growth and feed efficiency, and this is the first report for these genetic correlations in sheep. The genetic correlations are only moderate to low in magnitude and have high standard errors because of the limited size of the data set. They are in a direction that indicates selection for low plasma IGF-I may reduce feed intake and improve the maintenance efficiency of mature ewes under grazing, with little impact on lamb growth, wool production, and reproduction. However, more precise estimates of these parameters are required for accurate prediction of the likely outcomes of breeding programs and inclusion of IGF-I in the genetic evaluation of sheep.

	Footnotes

 
¹ Financial support was provided by Meat and Livestock Australia (Sydney), the Australian Government through The Australian Sheep Industry Cooperative Research Centre (Armidale, Australia), and NSW Department of Primary Industries (Orange, Australia). The authors wish to thank K. Lees, J. Morgan, K. Thornberry, D. Stanley, and Ashley Radburn for technical support; K. Bunter and R. Banks for discussions and facilitation of the study; and Arthur Gilmour for statistical advice. Primegro Limited (Adelaide, Australia) carried out the IGF-I assays.

² Corresponding author: neal.fogarty{at}dpi.nsw.gov.au

Received for publication August 16, 2007. Accepted for publication May 7, 2008.

	LITERATURE CITED

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