GENETIC PARAMETERS AND FACTORS AFFECTING BODY SIZE AND FUR TRAITS IN ARCTIC FOXES (VULPES LAGOPUS)

Magdalena Zatoń-Dobrowolska¹, Anna Mucha², Heliodor Wierzbicki², Piotr Przysiecki^3
1 Department of Genetics and Animal Breeding, Agricultural University in Wrocław, Poland
² Department of Genetics, Wrocław University of Environmental and Life Sciences, Poland
³ Institute of Agriculture, State School Higher Education in Leszno

ABSTRACT

The aim of this study was to determine factors, which significantly affect pelt size and fur quality in arctic foxes, and to estimate genetic parameters and breeding values for these traits. Data set consisted of 444 arctic foxes of different colour types was analyzed. All animals were kept at one private farm. The data were collected in 2004 – 2007. The studied traits were body length, body circumference, body size and conformation, colour type, purity of coat colour, coat quality and total score. GLM procedure and Duncan test were used to test significance of differences between means. For all studied traits heritabilities, genetic and phenotypic correlations and breeding values were estimated. For this analysis, traits (graded on the discrete scale) were logistic transformed using L_n function. Four different mixed models with different effects were applied

Key words: genetic parameters, pelt traits, body size, arctic fox.

INTRODUCTION

In fur animal farming the most important traits are pelt size and fur quality. These traits determine pelt price in the trading system. Although there are many species of fur-bearing animals, similar factors are important in their breeding.  Pelt size depends on animal body size and factors such as technical skin preparation. Important information about body size and pelt length gives trunk length, which shows high genetic correlation with the both traits interesting for breeders [4, 7, 8]. Another important factors affecting traits of interest are animal sex and year of birth [4, 11].

The most important tool in genetic improvement of pelt size and fur quality is selection. Results of selection are closely related to genetic variation of a trait in a population. High heritability of trait under selection enables to obtain better genetic progress. Many studies have reported high heritabilities of pelt traits [1, 3, 5, 8, 9, 12, 13]. Currently, a key role in breeding programs of livestock plays estimation of breeding value for each animal, which are selected to be sires and dams. Also in fur animal farming it is a crucial point of breeding program [15, 16].

The aim of this study was to determine factors, which significantly affect pelt size and fur quality in arctic foxes, and to estimate genetic parameters and breeding values for these traits. This information will be used in the next stage of the study to search for important genetic markers of coat traits in arctic fox.

MATERIAL AND METHODS

Data set consisted of 444 arctic foxes of different colour types was analyzed. All animals were kept at one private farm. The data were collected in 2004 – 2007. For each individual the following information was collected: pedigree, pavilion number, cage number, year of birth, sex, colour type, body length, body circumference and results of grading  (graded traits were: body size and conformation, colour type, purity of coat colour, coat quality and total score). In statistical analysis means and standard deviation for each trait were estimated. GLM procedure and Duncan test were used to test significance of differences between means. The following linear models with fixed effects were fitted:

1) model without interaction:

y_ijk = µ + p_i + t_j + e_ijk,

where: y_ijk is the trait, µ is the population mean, p_i is the i-th pavilion effect (i = 1,2,…,15), t_j is the j-th colour type effect (j = 1, 2, …,6), e_ijk is random residual effect.

2) model with interaction:

y_ijk = µ + p_i + t_j + (pt)_ij + e_ijk,

where: y_ijk is the trait, µ is the population mean, p_i is the i-th pavilion effect (i = 1,2,…,15), t_j is the j-th colour type effect (j = 1, 2, …,6), (pt)_ij is the interaction of the i-th pavilion and the j-th type effect, e_ijk is random residual effect.

For all studied traits heritabilities and breeding values were estimated. For this analysis traits (graded on a discrete scale) were logistic transformed using Ln function. Three different mixed models with different fixed effects were applied: (1) model I – with two effects (year and sex); (2) model II – with four effects (pavilion, year, sex, colour type); and (3) model III – only with mean effect. The equation of the mixed linear model was as follows:

y = Xb + Za + e,

where: y is n×1 vector of observations, n in number of records, b is p×1 vector of fixed effects, p is number of levels for fixed effects, a is q×1 vector of random animal effects, q is number of levels for random effects, e is n×1 vector of random residual effects, X is incidence matrix of order n×p, which relates records to fixed effects, Z is incidence matrix of order n×q, which relates records to random animal effects, E(y) = Xb, E(a) = E(e) = 0.

Furthermore, it is assumed that residual effects include random environmental and non-additive genetic effects and eN(0, σ_e²). Then var(e) = Iσ_e² = R, var(a) = Aσ_a²= G, where A is the relationship matrix.

The following mixed model equations estimate solutions b and predict a simultaneously:

Matrices R and G are assumed to be non-singular.

Phenotypic and genetic correlations were estimated as well.

RESULTS

The statistical description of analyzed traits is given in Table 1. Results of GLM procedure and Duncan test are shown in Tables 2 – 4. It was found that all traits were significantly affected by two factors – cage and pavilion. Also an interaction between these two factors had influence on several traits. Colour types significantly differed for only two graded traits. In contrast, for almost all traits significant differences were found between pavilions the animals were kept in (expect body circumference and body size and conformation). Significant differences were found between sexes for body length, body circumference and two graded traits: body size and conformation and total score. Males were characterized by higher means of the traits.

Table 1. Statistical description of studied traits

Trait		N	Mean	SD	Min.	Max.
Pelt length [cm]		444	67.98	3.61	57.0	79.0
Body circumference [cm]		444	55.74	5.54	42.0	80.0
Graded traits	Body size and conformation [1 – 6]	440	5.69	0.77	2.0	6.0
	Colour type [1 – 3]	440	2.77	0.44	1.0	3.0
	Purity of coat colour [1 – 3]	440	2.56	0.50	2.0	3.0
	Fur quality [1 – 8]	440	6.27	0.64	5.0	8.0
	Total score [0 – 20]	440	17.31	1.23	12.0	20.0

 

Table 2. Factors significantly affecting studied traits

Trait		Factors					Interactions
		Year of birth	Sex	Colour type	Pavilion	Cage	Sex * year	Sex * pavilion	Sex * cage	Pavilion * cage
Pelt length		♦**	♦***			♦***	♦*			♦*
Body circumference			♦*		♦**	♦*
Graded traits	Body size and conformation				♦***	♦***
	Colour type			♦***		♦**
	Purity of coat colour					♦**			♦*	♦**
	Fur quality	♦**			♦***	♦**				♦*
	Total score			♦*	♦***	♦***				♦**

* P ≤ 0.05; **P ≤ 0.01; *** P ≤ 0.001

 

Table 3. Differences between means in relation to colour type

Trait		Coat colour
		White	Very light blue	Light blue	Medium blue	Dark blue	Very dark blue
		N=32	N=7	N=118	N=184	N=93 / N=91 *	N=5 / N=4 *
Pelt length		68.35	65.29	67.58	68.08	68.33	69.40
Body circumference		55.16	53.71	55.75	65.87	55.42	57.60
Graded traits	Body size and build	5.10a	6.00	5.73b	5.72b	5.80b	5.50
	Colour type	3.00a	2.00	2.99a	3.00a	2.08b	1.00
	Purity of coat colour	2.77	2.28	2.54	2.52	2.66	2.50
	Coat quality	6.16	6.43	6.20	6.30	6.31	6.50
	Total score	17.03	16.71	17.47	17.55	16.85	15.50

a,b – statistically different at P ≤ 0.05 * Sample size: first value for length and circumference, and the second value for other traits

 

Table 4. Differences between means in relation to pavilions and sexes

Trait		Pavilion						Sex
		A	B	D	E	K	I	Male	Female
		N=55 / N=52 *	N=94	N=86	 N=136	N=11	N=10	N=239	N=196
Pelt length		69.71a	68.14ab	67.79b	68.46ab	54.14c	54.00c	69.79a	65.73b
Body circumference		56.13	54.14	55.73	56.62	65.00	64.20	56.60a	54.57b
Graded traits	Body size and conformation	5.65	5.70	5.77	5.59	5.81	6.00	5.77a	5.61b
	Colour type	2.79a	2.74ab	2.76ab	2.82a	2.45c	2.70b	2.77	2.77
	Purity of coat colour	2.69a	2.57a	2.27b	2.79a	2.27b	2.60a	2.57	2.57
	Coat quality	6.25bc	6.15bc	6.03c	6.36b	6.91a	6.30bc	6.32	6.21
	Total score	17.38ab	17.17ab	16.85b	17.56a	17.45ab	17.60a	17.43a	17.16b

a,b – statistically different at P ≤ 0.05 * Sample size: first value for length and circumference, and the second value for other traits

For all models used to estimate genetic parameters and breeding values, the correlation between real data and prognostic data was ~ 0.9, and the results obtained were comparable. So we present results only for model III. Mean breeding values for analyzed traits within studied years, expressed as deviation from the farm mean can be found in Table 5. For all graded traits mean breeding values did not markedly differ from the population mean. Mean breeding values for traits describing body size (pelt length and body circumference) were more diversified (ranged from -0.102 to 1.048) as compared to mean breeding values of traits graded alive.

Table 5. Mean breeding values within years (ranges presented are in brackets) for all studied traits

Trait		Year
		2004 (N=189)	2005 (N=58)	2006 (N=159)	2007 (N=38)
Pelt length		-0.102 (-3.525 – 2.879)	-1.048 (-4.024 – 3.098)	-0.949 (-3.998 – 3.848)	-0.779 (-4.280 – 3.866)
Body circumference		-0.444 (-7.707 – 7.628)	-0.862 (-8.521 – 8.299)	-0.494 (-4.891 – 9.447)	0.364 (-4.164 – 3.380)
Graded traits	Body size and conformation	0.008 (-0.865 – 0.243)	0.015 (-0.839 – 0.322)	-0.094 (-0.856 – 0.261)	-0.030 (-0.933 – 0.274)
	Colour type	-0.029 (-1.088 – 0.320)	-0.081 (-1.109 – 0.355)	-0.008 (-0.747 – 0.302)	0.013 (-0.613 – 0.313)
	Purity of coat colour	0.013 (-0.155 – 0.100)	-0.007 (-0.206 – 0.149)	-0.007 (-0.129 – 0.143)	-0.013 (-0.136 – 0.154)
	Fur quality	0.054 (-0.558 – 0.331)	0.041 (-0.480 – 0.374)	-0.007 (-0.549 – 0.201)	-0.061 (-0.668 – 0.210)
	Total score	0.026 (-0.834 – 0.253)	0.021 (-0.297 – 0.380)	-0.025 (-0.919 – 0.197)	-0.007 (-0.567 – 0.253)

Heritabilities and genetic and phenotypic correlations are given in Table 6. Values of heritability were rather high for body length and body circumference, reaching 0.410 and 0.417 respectively. For graded traits heritability was rather small, except the total score (0.180) and purity of coat colour (0.188).

Table 6. Estimates of heritability (on diagonal), phenotypic (over diagonal) and genetic (below diagonal) correlation

		Pelt length	Body circumference	Graded traits
				Body size and conformation	Type of coat colour	Purity of coat colour	Coat quality	Total score
Pelt length		0.410	0.537***	0.307***	0.009	0.127**	0.318***	0.715***
Body circumference		0.608***	0.417	0.344**	0.024	0.039	0.302***	0.401***
Graded traits	Body size and conformation	0.286***	0.420***	0.146	-0.084	-0.110*	0.272***	0.695***
	Colour type	0.014	-0.0002	-0.088*	0.143	-0.048	-0.054	0.261***
	Purity of coat colour	0.174***	0.081	-0.457***	0.003	0.188	-0.026	0.301***
	Coat quality	-0.075	-0.296***	-0.217***	0.053	0.011	0.105	0.660***
	Total score	0.162***	0.053	0.365***	0.203***	-0.107*	0.492***	0.180

Genetic correlations between graded traits were found to be low and almost all were negative. Higher negative correlation was found between body size and conformation and purity of coat colour (-0.457). Positive high correlations were estimated between three traits describing animal size: body length, body circumference and body size and conformation (from 0.286 to 0.608). The total score was highly correlated with all traits expect: body circumference (0.053) and purity of coat colour (-0.107).

Phenotypic correlations between the total score and all other traits were very high (from 0.401 to 0.715), except for type and purity of coat colour, which were moderate (0.261 and 0.301 respectively). All correlations were statistically significant. Also correlation between body length and body circumference was high (0,537) and statistically significant. Body parameters (body length and circumference) were highly correlated with coat quality and body size and conformation (correlation about 0.3). In contrast, body parameters had very weak correlations with colour type (0.009 and 0.024, respectively). Phenotypic correlations between graded traits were found to be rather small (from -0,084 to 0,272) and mostly negative.

Higher values of genetic correlation then phenotypic correlations were found for body size traits. In contrast, the traits connected with coat and skin quality and the total score expressed higher phenotypic correlations.

DISCUSSION

Gugołek et al. [4] who studied body length in arctic foxes reported statistically significant differences between sexes. Males were characterized by higher value of that trait. Also other traits studied: body weight and pelt size had higher values in a group of males. The same relations were found in the present study. Similar results were reported by Socha et al. [11] for mink population. They also confirmed that year of grading influenced colour purity and body size. Animals of different colour type differed significantly as far as two traits were concerned: body size and conformation and colour type.

Comparable results for breeding values were reported by Wierzbicki et al. [14] who estimated genetic trends for traits graded alive in arctic foxes. Analyzing period of 14 years they found not satisfactory genetic progress and breeding values oscillated rather around the population mean.

Similar heritabilities were found by Peura et al. [8] for traits measured after slaughter (on dry skin) and graded alive, such as pelt/animal length, colour clarity, pelt/coat quality, coat density. Only for colour darkness heritability was estimated at higher level. In other study Peura [9] estimated heritability for pelt size at 0.29. Comparable values of heritability for pelt size were reported also by other authors [13, 15, 16]. Reported heritabilities for graded traits ranged from 0.1 for general appearance, 0,2 for colour purity, coat density or total score to 0,3-0,4 for body size, hair length and colour type (2, 3, 15, 16).

Wierzbicki and Filistowicz [13] estimated heritability for hair length at 0.76. Heritabilities for other fur animal species were: from 0.082 for colour type to 0.478 for body size in mink; from 0.31 for coat quality to 0.52 for purity of coat colour in raccoon dog; from 0.135 for body weight to 0.623 for hair length in nutria [1, 5, 12]. Lagerkvist et al. [6] carried out the study in a mink population and estimated genetic parameters for fur traits (colour shade, guard hair quality, underfur density and general appearance), which were graded alive or after pelting animals. The estimated heritabilities had the same values, regardless of the grading method only for color shade. For underfur density and general appearance higher values of heritability were estimated when traits were graded after pelting, except for guard hair quality where heritability was higher for alive graded animals.

Almost all genetic correlations between graded traits were negative, but between three traits describing animal size these correlations were positive and high. Results reported by other researchers showed, that genetic correlations in arctic fox populations were high between traits connected with body and pelt size, small between traits of coat and colour quality and negative between pelt and body traits and reproductive traits [8, 9, 13, 15]. In mink population positive genetic correlation was estimated only between body size and colour type, whereas genetic correlations between other graded traits were negative, reaching the lowest value between body size and coat quality (-0.543) [12]. Results of another study on mink [6] reported high and significant genetic correlation between skin weight and its length. The authors also reported high genetic correlation between fur traits (0.68 – 0.93), except correlation values between colour shade and two other traits: underfur density and guard hair quality (-0.05 and 0.18, respectively). In raccoon dog population genetic correlations were positive and ranged from 0.04 to 0.43 [5]. The opposite results were obtained in the present study.

The studies on body length and pelt length reported positive and high correlation between these two traits [4, 7]. Values of correlations between three traits: body length, body weight and pelt length were smaller for males (0.509 – 0.587) than for females (0.583 – 0.754) [4]. It must be kept in mind that pelt size can also be influenced by another factors, such as technical preparation of pelt for selling. The correlation between body size and pelt length suggests that we can use information about body length to predict pelt length. In other studies carried out in populations of arctic fox phenotypic correlations ranged from 0.326 (between total score and colour type) to 0.686 (between body size and conformation and total score) [10]. The authors also found high phenotypic correlation between pelt length and total score (0.530), which is comparable to the results obtained in the present study. The phenotypic correlations estimated for silver foxes ranged from 0.308 (between total score and body weight) to 0.753 (between total score and coat quality) [10]. In other studies phenotypic correlations ranged from -0.2 between purity of coat colour and body size, followed by 0.01 between hair length and pelt length, to 0.68 between total score and coat density [13]. In nutria population the phenotypic correlations were higher between guard hairs length and underhair length (0.744 – 0.805) and very small between body weight and underhair length (-0.095) [1]. In raccoon dog populations positive phenotypic correlations ranging from 0.03 to 0.18 were estimated, and these values were smaller than genetic correlations [5]. For mink Socha and Kołodziejczyk [12] estimated phenotypic correlations between graded traits and they were very small and almost all were negative (from -0.130 to -0.006). Only correlation between colour type and purity of coat colour was positive and reached 0.027. Lagerkvist et al. [6] estimated different values of phenotypic correlation between fur traits. Correlations of colour shade with hair traits were very small (ranging from -0.10 to 0.06), with slightly higher values with general impression. Moderate values of phenotypic correlation were found between underfur and guard hair quality and general impression (0.35 and 0.33, respectively). Very high phenotypic correlation was estimated only between general impression and guard hair quality (0.77).

CONCLUSIONS

The results obtained indicate a significant effect of place an animal is kept on traits important in fur breeding. This effect should be included in linear models used when estimating (co)variance components and breeding values. Coat colour purity, which is an important fur feature from the buyer point of view, was found to be negatively genetically correlated with animal size This information should be taken into account when preparing breeding program which concentrates on genetic improvement of those traits.

Acknowledgements

This study was supported by the State Committee for Scientific Research (grant No. 2 P06D 006 27)

REFERENCES

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Accepted for print: 21.12.2011

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Magdalena Zatoń-Dobrowolska
Department of Genetics and Animal Breeding,
Agricultural University in Wrocław, Poland
Kożuchowska 7, 51-631 Wrocław, Poland
email: magda@gen.ar.wroc.pl

Anna Mucha
Department of Genetics, Wrocław University of Environmental and Life Sciences, Poland
Kożuchowska 7
51-631 Wrocław
Poland
email: anna.mucha@up.wroc.pl

Heliodor Wierzbicki
Department of Genetics, Wrocław University of Environmental and Life Sciences, Poland
Kożuchowska 7
51-631 Wrocław
Poland
email: heliodor.wierzbicki@up.wroc.pl

Piotr Przysiecki
Institute of Agriculture, State School Higher Education in Leszno
Mickiewicza 5, 64-100 Leszno, Poland,
tel. +48 65 528 78 67
email: piotr.przysiecki@gmail.com

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