Estimation of variance components and genetic parameters for growth traits in New Zealand White rabbit (Oryctolagus cuniculus)

Abstract

Birth weights and subsequent body weights of individual kits of New Zealand White rabbits were analysed to estimate the impact of direct additive genetic, maternal additive genetic and permanent environmental litter effect on growth traits i.e. birth weight (BW), 15th day body weight (15dW), 30th day body weight (30dW), 90th day body weight (90dW) and 180th day body weight (180dW). The variance components and genetic parameters were estimated using Sire Model and two different animal models. Effect of litter size was significant on all the growth traits except 90dW. Kits born in winter season had significantly higher BW, 30dW and 90dW than the kits born in summer season. The heritability estimate for BW ranged from 0.266 (Sire Model) to 0.540 (Animal Model 2). The permanent effect of litter (c²) was highest (0.288–0.310) just before weaning at 30dW and decreased after weaning. The effect of indirectly inherited maternal genetic effect (m²) was present at early juvenile stage of growth (15dW, 30dW and 90dW) and was nil for 180dW. Selection for better growth would be more reliable at 180dW because at this age both c² and m² became lower than in previous stages of growth. Using Animal Model 1, repeatabilities of doe effects on BW, 15dW, 30dW, 90dW and 180dW were 0.35, 0.44, 0.40, 0.35 and 0.01, respectively. Animal Model 1 was better than Animal Model 2 in partitioning of variances when the maternal genetic variance () was very low or zero.

Keywords:

• animal model
• growth traits
• heritability
• maternal effect
• New Zealand White
• rabbit

Introduction

Rabbit farming is practiced for meat, fur, wool laboratory animal and biological production purposes. Litter size (Ferraz and Eler 2000), growth of individual rabbit (Lukefahr et al. 1992; Iraqi 2003; Akanno and Ibe 2005) and survival rate (Ferraz and Eler 2000) are the important economic traits in rabbits. New Zealand White rabbits are well recognised as a dam breed based on its outstanding maternal genetic merits for litter size, milking and general mothering ability (Lebas et al. 1997; McNitt 2000). In rabbits, selection of breeding stock at an early age for improving growth of individual rabbit is having utmost importance under intensive production system. The growth of individual rabbits varies and depends on many factors i.e. major genes, extra-nuclear genes, mothering ability of does, environmental effect of litter (Ferraz and Eler 2000; Iraqi 2003). Studies in different breeds of rabbit had revealed that both direct and maternal influences are important for individual growth of rabbits (Ferraz et al. 1992; Lukefahr et al. 1993; Lukefahr et al. 1996; Niranjan et al. 2010). Use of animal model procedure for estimating the direct and maternal effect on growth traits of New Zealand White rabbit is limited (Ferraz and Eler 2000). The objective of this study was, therefore, to estimate genetic (co) variance components for growth traits using Restricted Maximum Likelihood procedure with various combinations of direct and maternal effects for New Zealand White rabbits. The genetic parameters obtained using animal models were compared with genetic parameters of best linear unbiased prediction (BLUP) based Sire Model.

Materials and methods

Description of data

In present investigation the data on New Zealand White rabbits maintained at Laboratory Animal Resources Section of Indian Veterinary Research Institute, Izatnagar, were collected for a period of two years (2009–2010) and analysed for estimation of variances. In New Zealand White rabbits, litter size varies from 5 to 10 and it influences subsequent growth of individual rabbits. Growth records on 604 individual rabbits from 74 bucks and 254 primiparous does were available for study. The farm has a semi-arid climate with high temperature (4°C–47°C) during summer and winter. Summers are long, from early April to September, with the monsoon season in between followed by winter from October to March. The animals were given dry concentrate mixture with 10% fish meal and green fodder of standard composition for proper growth of the fetus as well as for its own body requirements. Five different pre-weaning and post weaning growth traits included for the analysis were body weight at birth (BW), 15th day (15dW), 30th day (30dW), 90th day (90dW) and 180th day (180dW). Weaning was practiced at 42 days post-kindling and individual kits were separated from mother.

Statistical methods

In the present investigation, BLUP based Sire Model described by Henderson (1975) was used for estimation of variance components of body weights of rabbit and further it was compared with (co) variance components and genetic parameters estimated using two different animals models based on Derivative Free Restricted Maximum Likelihood algorithm (Meyer 1998). Initially, the data were analysed for least squares analysis of variance using PROC GLM procedure (SAS 9.2) to identify the significant fixed effects to be included in the animal models. For the growth traits, the model included the fixed effects of season of birth (two levels) and litter size (uterine capacity) of does (three levels). The litter size of does at first kindling was classified into three categories based of their litter size i.e. group One for litter size < 5; group Two with litter size 5–7 and group Three for litter size > 7. Two animal models that accounted for the maternal genetic effect and permanent environmental effect of litter were fitted as follows:

where, y is the vector of records; β, a, m, c and ϵ are vectors of fixed, additive direct genetic, maternal additive genetic, permanent environmental litter effect and residual effects, respectively; X, Z_a, Z_m and Z_c are incidence matrices that relate these effects to the records_; A is the numerator relationship matrix between animals; and σ_am is the covariance between additive direct and maternal genetic effects. Assumptions for variance (V) and covariance (Cov) matrices involving random effects were:

where, I is an identity matrix and and are additive direct, additive maternal, permanent environmental litter effect and residual variances, respectively. The direct-maternal correlation (r_am) was obtained for all the traits under analyses. Maternal across year repeatability for doe performance (t_m=(1/4) h ²+m²+c²+mr_am h) was calculated. The total heritability (), was calculated using the formula _; (Willham 1972). The are the total phenotypic variances obtained in respective animal models.

Results and discussion

The least squares means for BW, 15dW, 30dW, 90dW and 180dW were 50.56±0.72, 150.09±1.71, 263.27±3.75, 994.52±15.15 and 1718.48±17.91 gram (g), respectively, (Table 1). The effect of season was significant (P<0.05) on BW, 30dW and 90dW but not significant on 15dW and 180dW. The least squares means of kits born in winter season was significantly (P<0.05) higher than the kits born during summer season which may be ascribed due to conducive weather conditions during winter season ensuring more energy and protein availability to pre-natal kits. In agreement with our findings Ghosh et al. (2008) reported that season of kindling had significant effect on individual weight at weaning and 90dW in New Zealand White rabbits. The effect of litter size was significant on all traits under investigation except 90dW. BW, 15dW, 30dW and 180dW decreased significantly with increase in litter size.

Table 1. Estimates of least squares means (g) for non-genetic factors.

	BW	15dW	30dW	90dW	180dW
Overall	50.56±0.72 (604)	150.09±1.71 (533)	263.27±3.75 (498)	994.52±15.15 (461)	1718.48±17.91 (439)
Season
Summer	48.25^a±1.09 (128)	150.00±2.37 (121)	249.43^a±5.52 (109)	947.70^a±22.74 (100)	1709.26±28.41 (95)
Winter	52.87^b±0.69 (476)	150.09±1.68 (412)	277.11^b±3.64 (389)	1041.34^b±14.63 (361)	1727.70±17.15 (344)
Litter size
< 5	52.25^a±0.85 (199)	156.39^a±1.92 (184)	276.79^a±4.33 (174)	1013.35±17.58 (164)	1774.46^a±21.73 (153)
5–7	51.31^b±0.95 (210)	148.45^b±2.14 (179)	260.61^b±4.92 (166)	986.06±20.03 (152)	1712.82^b±24.99 (144)
> 7	48.13^c±1.08 (195)	145.43^c±2.38 (170)	252.41^c±5.41 (158)	984.16±22.53 (145)	1668.15^c±27.93 (142)
Note: The least squares means with different superscript in the column indicated for significant (P<0.05) effect of the fixed effect on particular trait. Figures in parentheses are number of observations.

(Co) variance components and genetic parameters

(Co) variance components and genetic parameters estimated by different models for growth traits are presented in Tables 2 and 3.

Table 2. Estimation of variance components (g²) and genetic parameters for BW, 15dW and 30dW.

	BW			15dW			30dW
(Co) variance/genetic parameter	SM	AM I	AM II	BLUP	AM I	AM II	BLUP	AM I	AM II
	21.83	33.45	46.38	152.40	157.27	154.89	629.12	818.54	1118.54
		0.10 E-05	4.89		69.93	17.507		0.539 E-02	457.45
σam			−15.07			23.09			−645.33
		21.65	25.77		36.20	69.77		531.72	572.46
	60.02	30.64	23.88	191.77	63.31	69.77	1195.11	493.94	338.641
	81.25	85.75	85.86	344.17	326.73	329.54	1824.23	1844.22	1841.77
	0.266±0.03	0.390±0.04	0.540^a	0.442±0.05	0.481±0.03	0.470^a	0.344±0.03	0.443±0.02	0.607^a
		0.000	0.057^a		0.214±0.03	0.053^a		0.000	0.248^a
ram			−1.000			0.443			−0.902
		0.252±0.02	0.300^a		0.110±0.01	0.211^a		0.288±0.04	0.310^a
		0.39	0.32		0.59	0.60		0.44	0.20
tm		0.35	0.30		0.44	0.45		0.40	0.36
LogL			−1550.4		−1682.7	−1683.0		−2024.2	−2023.5
CV (%)	14.92	17.83	17.85	9.22	12.03	12.08	12.78	15.87	15.86
Note: , , , and are direct additive, maternal genetic, litter permanent environmental, residual and phenotypic variances, respectively; σam is covariance of direct additive and maternal genetic effect; is direct heritability; is ; is ; tm is maternal across year repeatability for doe performance; is total heritability.
^aindicates that the approximation used to define standard errors of parameter estimates failed. SM is Sire Model, AM I is Animal Model 1 and AM II is Animal Model 2.

Table 3. Estimation of variance components (g²) and genetic parameters for 90dW and 180dW.

	90dW			180dW
(Co) variance/genetic parameter	SM	AM I	AM II	BLUP	AM I	AM II
	9708.82	8314.53	14,450.83	10,624.47	6047.58	6185.75
		3253.03	14,328.84		0.491E-03	9.80
σam			−12,420.33			−246.32
		4321.49	3421.67		9070.87	9212.43
	19,319.76	12,084.50	8738.63	36,432.95	30,479.27	30,417.83
	29,028.58	27,973.56	28,519.64	47,057.42	45,597.73	45,579.50
	0.334±0.03	0.297±0.03	0.506^a	0.225±0.03	0.132±0.01	0.135^a
		0.116±0.02	0.502^a		0.000	0.000
ram			−0.863			−1.000
		0.154±0.02	0.120^a		0.198±0.03	0.202^a
		0.34	0.31		0.23	0.23
tm		0.35	0.10		0.01	0.01
LogL		−2522.5	−2521.8		−2537.9	−2537.9
CV (%)	13.64	16.41	16.57	11.07	12.38	12.38
Note: , , , and are direct additive, maternal genetic, litter permanent environmental, residual and phenotypic variances, respectively; σam is covariance of direct additive and maternal genetic effect; is direct heritability; is ; is ; tm is maternal across year repeatability for doe performance; is total heritability.
^aindicates that the approximation used to define standard errors of parameter estimates failed. SM is Sire Model, AM I is Animal Model 1 and AM II is Animal Model 2.

Birth weight (BW)

The direct additive genetic variance (21.83 g²) and direct estimate of heritability (0.266) was lowest in Sire Model as compared to both animal models (Table 2). Among two different animal models, the Animal Model 1 had maximum direct additive genetic variance (46.38 g²) and direct heritability (0.540). The maternal effect explained 5.7% of total phenotypic variation of BW in kits of New Zealand White rabbits in second Animal Model which included the correlation and covariance of direct and indirect maternal effect. But it was zero in Animal Model 1 and hence may not produce reliable estimates of genetic parameters in Animal Model 2. The permanent environmental litter heritability ranged from 25.2% to 30.0%. Inclusion of the covariance between direct and maternal effect (−15.07) produced high and negative estimate of r_am (−1.000) in Animal Model 2. The high negative genetic correlation between direct and maternal genetic effects suggests an antagonistic association between direct and maternal genetic effects for BW. Estimates of maternal repeatability estimate (t_m) were sensitive to the model fitted and ranged from 0.30 (Animal Model 1) to 0.35 (Animal Model 2). Estimate of total heritability () was medium and ranged from 0.32 (Animal Model 2) to 0.39 (Animal Model 1). Higher estimate of total heritability suggests better efficiency of Animal Model 1 than Animal Model 2 especially when LogL values in both animal models are very close and fails to discriminate the efficiency of models.

15th day body weight (15dW)

The proportion of direct estimate of additive genetic variance and heritability increased in 15dW, where direct estimate of heritability were 0.481±0.03 and 0.470, respectively, in Animal Model 1 and 2, respectively, (Table 2). The Sire Model had lowest estimate of heritability (0.442±0.05) which utilises additive genetic variances of single parent only. The permanent environmental effect of litter ranged from 0.110 (Animal Model 1) to 0.211 (Animal Model 2). The maternal effect explained 21.4 and 5.3% variation of total 15dW using Animal Model 1 and 2, respectively. Estimates of t_m were similar for both animal models (0.44 and 0.45), suggesting consistent repeatability of doe performance across different models which include maternal effects. Estimate of repeatability of doe performance were normally much more stable than the component estimates of m² and c². Also, estimate of total heritability () was high and ranged from 0.59 (Animal Model 1) to 0.60 (Animal Model 2).

30th day body weight (30dW)

The proportion of direct estimate of additive genetic variance and heritability further increased where direct estimate of heritability were 0.443±0.02 and 0.607, respectively in Animal Model 1 and 2, respectively (Table 2). The Sire Model had the lowest estimate of heritability (0.344±0.03). The maternal heritability was nil in Animal Model 1 and appeared in Animal Model 2 (0.248) when covariance between direct and indirect additive genetic variance was included in the model. The permanent environmental effect of litter was quite high for 30dW and ranged 0.288±0.04 to 0.310 in Animal Model 1 and 2, respectively. The maternal permanent environment effect indicates the importance of maternal care from birth to weaning. The moderate repeatability of doe performance and total heritability estimates for the weaning weight reflects the consistency of the maternal performance. In addition, moderate t_m estimate indicate that selection for higher monthly body weight is possible only by culling of less productive dams. Estimates were consistent in both animal models. Further, the estimates of were medium and very close to each other in both models.

90th day body weight (90dW)

Out of all three models used, the estimate of additive genetic variance and heritability was highest (0.506) in Animal Model 2 (Table 3). The estimate of heritability was 0.334 using the Sire Model of BLUP. These findings were in agreement to the estimated heritability for 52nd day body weight (0.29) and 73rd day body weight (0.20) in New Zealand White rabbits using the BLUP method (Panella et al. 1992). Similarly, Castellini and Panella (1988) reported high estimate of heritability for post weaning weights in rabbits. On contrary, Lukefahr et al. (1992) reported medium estimate of heritability for 90dBW domestic rabbit breeds using Animal Model in field data. But, estimate of permanent litter effect reduced and it ranged 12–15.4% in Animal Model 2 and 1, respectively. It was expected that as weaned kits became more independent of doe or maternal influence with the advancement of the age. These observations were consistent to the higher maternal effect and permanent environment effect for growth traits at initial stage which decreased in latter stage (Ferraz et al. 1992). However the impact of maternal genetic effect was high with respect to growth of individual rabbits and ranged from 11.6% (Animal Model 1) to 50.2% (Animal Model 2). Results indicated the importance of the maternal genetic effect, as it accounts for significant portion of the total genetic variance as carry over effect. Higher importance of maternal effect over additive genetic effect on the post weaning growth traits in rabbits had also been documented earlier (Ferraz et al. 1992; Lukefahr et al. 1993).

180th day body weight (180dW)

The direct additive genetic variance and direct estimate of heritability was highest in Sire Model (Table 3). Both the animal models were having almost equal estimate of direct additive genetic variance as well as direct estimate of heritability. The maternal effect was nil in both animal models. The magnitude of permanent litter effect was comparatively lower (19.8–20.2%) in both animal models for 180dW than in pre-weaning growth traits. Estimates of total heritability were medium and equal (0.23) in both animal models. Lowest and equal estimates repeatability of doe influence for 180dW reflects the least consistency of the maternal performance. Hence, doe selection should not practiced for improving body weight of their progeny at 180dW but individual rabbit selection would be more desirable based on their own records of 180dW. Similar to our findings Niranjan et al. (2010) reported maternal effects was more important at weaning, and declined with the advancement of age.

The log likelihood (LogL) values of both animal models for each individual trait were very close to each other, hence it was recommended that Animal Model 1 would be efficient enough in partitioning of variances especially in case the maternal additive genetic variance was very low or zero in Animal Model 1. In such cases, covariance of direct additive genetic effect and maternal effect should not be included in animal model. Also, if the LogL value is not differing significantly in both animal models the decision about choice of model must be taken on the basis of higher estimate of total heritability ().

In conclusion, it may be inferred that the additive genetic variability for growth traits in New Zealand White rabbits was moderate. The permanent environment effect of litter (c²) was more important than maternal effect (m²) in pre-weaning as well as post weaning growth of rabbits. The impact of permanent environment effect reduced with advancement of age. Significant permanent environmental litter effect on post-weaning weights was a carryover effect of maternal influences during pre-weaning age. Considerably, moderate estimate of direct heritability with zero maternal heritability and lower permanent environment effect for body weight at 180 days could make it as a suitable criterion for selection of the rabbits. Bijma (2006) reported that genetic analysis of maternally affected traits has proven difficult, and extremely negative estimates of the genetic correlation between the direct and maternal effect have been met with scepticism. Also, Bijma (2006) suggested certain simulation design for better interpretation of the genetic correlation between the direct and maternal effect. However, sizeable data-sets are required to allow reasonably accurate estimates even for designs specifically formulated for the estimation of maternal effects (Meyer 1992). Hence, it can be concluded that the common permanent litter effect and maternal effect are important for controlling growth of young growing kits.