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ANIMAL GENETICS |
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* University of Debrecen, Faculty of Agriculture, Department of Animal Breeding and Nutrition, Debrecen, Hungary 4032;
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University of Zagreb, Faculty of Agriculture, Department of Animal Science, Zagreb, Croatia 10000; and
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BOKU-University of Natural Resources and Applied Life Sciences, Department of Sustainable Agricultural Systems, Vienna, Austria 1180
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Abstract |
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 Top Abstract INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONIMPLICATIONSLITERATURE CITED |
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Key Words: coat color • heritability • horse • melanin • repeatability
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INTRODUCTION |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONIMPLICATIONSLITERATURE CITED |
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; Wolf and Swafford, 1988; Rieder et al., 2001) and was among the first traits demonstrating the validity of Mendel’s laws in mammals (Hurst, 1906; Wright, 1917). The variation of coat color primarily depends on melanin. Melanin occurs in the form of pigment granules in melanocytes, which are cells found in hair follicles, skin, iris, and some internal tissues. The inheritance of coat color in horses has been mainly studied from a qualitative perspective (Sponenberg, 1996; Bowling, 2000) where phenotypes are defined by distinctive categories (bay, black, brown, gray, etc.) and are controlled by few genes showing an epistatic mode of inheritance (Rieder et al., 2001; Henner et al., 2002).
However, coat color variation is also affected by a large number of other genes. For example, up to 127 genes affecting coat color have been identified in mice, and at least 59 genes related to these coat color mutations have now been molecularly cloned (Bennett and Lamoreux, 2003). Klungland and Vage (2000) observed that the underlying genetics of pigmentation is complex, exhibiting quantitative as well as qualitative features. In studies of inheritance of the graying process (Curik et al., 2002) and analyzing nongenetic factors affecting color variation in Polish Konik and Bilgoraj horses (Stachurska et al., 2004), coat color was measured as spectrometric reflectance according to standardized tristimulus color determination of Commission Internationale de l’Eclairage.
The objective of this study was to estimate genetic parameters for coat color in horses defined quantitatively according to spectrometric reflectance. In addition, to validate the biological meaning of variables quantifying color, the relationship between lightness (L*) and total melanin content of the horse coat hair was also analyzed.
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MATERIALS AND METHODS |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONIMPLICATIONSLITERATURE CITED |
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). Horses
The data were collected on 5 horse breeds raised in Hungary (a total of 294 horses): Lipizzan from Szilvasvarad Stud Farm; Nonius from Hortobagy Stud Farm; Arabian Pure Bred, Shagya Arabian from Babolna and Toponar Stud Farms; and Gidran from Marocpuszta Stud Farm. The Lipizzan, Nonius, Arabian Pure Bred, Shagya Arabian, and Gidran horses in the samples represent 13, 14, 10, 24, and 19% of the corresponding breeds in Hungary, respectively (following Bodo, 2003). The pedigree of all recorded animals was traced at least back to their grandparents. The numbers of horses with records in the pedigree are shown in Table 1. Horses were measured repeatedly, up to 3 times, during the period of 2002–2004.
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During the formation of some breeds, particular colors were strongly selected for, resulting in the following color distribution of the breeds: Gidran (chestnut), Nonius (bay, black), Lipizzan (gray, black), Shagya Arabian, and Arabian Pure Bred (gray, black, or chestnut).
According to Sponenberg (1996), each of these coat colors classes represents a unique genotype combination of major genes (for example, Agouti, Extension, etc.). These genotypes can be viewed as outcomes of the random variable of coat color. The sample of Lipizzan, Shagya Arabian, and Arabian Pure Bred horses used in this study contained only gray horses. Thus, there were 6 breed and color combinations: Gidran (chestnut), Nonius (bay, black), Lipizzan (gray), Shagya Arabian (gray), and Arabian Pure Bred (gray).
Definition of the Color as a Continuous Variable
For objective measurement of coat color, the Commission Internationale de l’Eclairage L*a*b* system was applied using a Minolta ChromaMeter (Model CR-310, Minolta Inc., Osaka, Japan). The values of L* indicate light intensity and are related to the luminous reflectance (quantity of reflected light weighted with the spectral response of the human eye) and have values from 0 (black) to 100 (white). The values of a* measure the color saturation from red to green on a scale from +60 to –60, where positive values indicate varying intensities of red; b* measures the color saturation from yellow to blue on a scale from +60 to –60, where positive values indicate varying intensities of yellow. The a* and b* coordinates were converted into polar coordinates defined as Chroma and referred to as saturation of color, where Chroma = [(a*)2 + (b*)2]1/2. Chroma describes the intensity of color, with greater Chroma indicating greater intensity. In this study, color was measured on the right side of the body at 3 places (neck, shoulder, and belly).
Estimation of Parameters
Gray and nongray (chestnut, bay, and black) horses were analyzed separately due to obvious differences caused by the rate of graying. Variance components, heritabilities, and repeatabilities for color traits were estimated using REML from univariate animal models of the following general form:
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where y is the vector of observations for the L*, a*, b*, and Chroma traits; ß denotes the vectors of fixed effects for sex, month of year when measurements were taken, age defined as a covariate (age of horses ranged from 1 to 30 yr), and age x mo and age x sex interactions; s defines nonlinear effects of age (if any) explained by smoothing cubic splines as outlined by Verbyla et al. (1999); b is the random vector of breed effects (defined only for gray horses); c is the random vector of color class effects (defined only for nongray horses); a is the random vector of additive genetic effects within breed and color class; p is the random vector of permanent environmental effects due to repeated measurements on the same animal; e is the vector of temporary environmental effects; and X, Z1, Z2, Z3, Z4, and Z5, are known incidence matrices relating ß, s, b, c, a, and p to y. The variances of breeds, color classes, additive genetic effects within breeds and color classes, and permanent and temporary environment were I*
2b, I*2c, A*2a, I*2p, and I*2e, respectively, in which A is the relationship matrix and I is the identity matrix.
Mean values of L*, a*, b*, and Chroma for color classes within breeds were predicted from the defined animal models as µage + c, where µage is the value for a particular age averaged over fixed effects and c describes the BLUP of breed and color class combination.
The significance of the fixed effects was tested using the MIXED procedure of SAS software (SAS Inst. Inc., Cary, NC). All of the defined fixed effects proved to be important in the model. The calculations of variance components were carried out using the ASREML program (Gilmour et al., 2002) and VCE 5 (Kovac and Groeneveld, 2003). The following heritabilities and repeatability were calculated.
Between-breeds heritability (hb2) describes the proportion of the total phenotypic variability attributable to breeds (calculated only for gray horses), as follows:
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Color class heritability (hc2) describes the proportion of the total phenotypic variability attributable to genetic variability between color classes (calculated only for nongray horses). It defines the variability due to major gene effects, as follows:
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Within-breed and color class heritability (ha2) describes the part of the variability attributable to the polygenic color effects within breeds and color classes. It is defined as the ratio of the additive genetic variance within breeds and color classes to the phenotypic variance within breeds and color classes, as follows:
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Within-breed and color class repeatability (r) describes the part of variability attributable to repeated measurements on the same horse and body part within breeds and color classes, as follows:
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Combined heritability (ht2) describes the proportion of total phenotypic variability attributable to the breeds, major genes and polygenic variability, as follows:
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Analysis of Hair Melanin Content
For quantitative estimation of the total amount of melanin in horse hair, 54 samples (6 randomly chosen samples from each color class, out of the total number of horses) were dissolved in 1 mL of a mixture of Soluene-350:water (9:1, vol/vol) by heating in a boiling water bath for 45 min. According to Ozeki et al. (1996), the absorbance at 500 nm per 1 mg of hair (A500) is considered to reflect the total amount of eu- plus pheomelanin. The relationship between total melanin content of horse coat hair and L* was estimated using polynomial regression functions of L* on melanin content.
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RESULTS AND DISCUSSION |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONIMPLICATIONSLITERATURE CITED |
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The current study confirmed that the total melanin content of horse coat hair was strongly related to L*. Because there is an obvious difference between gray and nongray horses in L* and melanin, these 2 groups of horses were analyzed separately (Figure 1). For both gray and nongray horses, a strong negative linear relationship was detected (P < 0.01). The scatter plot for nongray horses indicated a slight curvilinear relationship, but the quadratic component was not significant for this sample (P = 0.07). Also, the linear component gives an R2 of 0.66, and adding a quadratic component into the model increased the R2 only by 0.04. Note that there was larger unexplained variability for gray horses than for nongray horses (R2 = 0.48 compared with R2 = 0.66). Decrease of L* corresponds to increased total melanin content, and low L* values depict less lightness and less reflectance. Similar relationships between pigmentation and L* were also reported by Cecchi et al. (2004) for llamas and by Shiver and Parra (2000) in humans.
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Mean values and standard errors calculated from neck, shoulder, and belly measurements for L*, a*, b*, and Chroma color traits within breeds and for ages of 4, 8, 12, and 16 yr are shown in Table 2. Changes of L* values were related to visual appearance of the coat color intensities. As expected, darker horses had lower L* values than lighter ones. Gray horses showed higher increases in L* values with age compared with nongray horses due to progressive rate of graying. The predicted means of L* at particular ages for different breeds of gray horses were the same because there was no variability between breeds.
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Genetic Parameters for Coat Color Traits
For gray horses, most or all of the estimated genetic variability was due to the within-breeds effect, showing that considerable variation is inherited through a polygenic component (Table 3). Similarly, a moderate heritability estimate (h2 = 0.46) for L* in gray Lipizzan horses was reported by Curik et al. (2002). For nongray horses, the greater part of the genetic variability of L* values was attributable to color class definition, which describes the effects of major genes. The estimated between-color class heritability ranged from 0.70 to 0.80 (Table 4). However, moderate within-color class heritability for the average of neck, shoulder, and belly L* values was estimated (0.21), showing that considerable variation is inherited through a polygenic component. Moderate heritabilities for L* were also obtained in studies related to the inheritance of the pigmentation color of the meat in different species. Le Bihan-Duval et al. (2001) reported heritability for L* values of the broiler meat color ranging from 0.50 to 0.57. For the color of the pork carcass, Sellier (1998) reported an average heritability of 0.28 for L* from 29 published estimates, with a range of 0.15 to 0.57.
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The large phenotypic variability of coat color in horses is well known. The estimates of genetic parameters obtained for L* in this study were high between color class and moderate within color class, indicating that major gene and polygenic effects are important. A strong relationship between coat pigmentation and L* was observed, indicating that the mechanism of the polygenic component is the inherited variability in melanin content. How presence, shape, and number or arrangement of pigment granules affect inherited variation captured by L* was not studied here. Research related to human pigmentation suggests that there is a quantifiable individual variation in the number, size, and packing of melanosomes (Sturm et al., 2001). It would not be a surprise if those factors are inherited and explain high heritability of L*.
In nongray horses polygenic effects seem to be less important for chromatic parameters (a*, b*, and Chroma). The genetic variability was explained mostly by color class definition. On the contrary, in gray horses polygenic components were considerable. There is quite a difference in appearance of gray horses with different patterns, such as flea-bitten or dappled. In this study those patterns were defined as unique gray color class because their inheritance is still not completely characterized.
The results obtained in this study do not only have an aesthetic value because melanin has a variety of functions including photo-protection, routing of the optic nerve tracts, and possibly the scavenging of free radicals (Sturm et al., 1988). For horse breeding, the association between coat color and physiological, morphological, and behavioral traits (Keeler, 1968; Wright, 1978; Klungland and Vage, 2000) might be of particular interest. Recent developments in molecular genetics and statistical analyses combined with the approach presented here offer new perspectives for better understanding of coat color inheritance as a trait with multiple contributing factors.
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IMPLICATIONS |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONIMPLICATIONSLITERATURE CITED |
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Footnotes |
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2 Corresponding author: mkaps{at}agr.hr
Received for publication December 8, 2005. Accepted for publication May 21, 2006.
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LITERATURE CITED |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONIMPLICATIONSLITERATURE CITED |
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  L. J. Royo, I. Fernandez, P. J. Azor, I. Alvarez, L. Perez-Pardal, and F. Goyache Technical note: A novel method for routine genotyping of horse coat color gene polymorphisms J Anim Sci, June 1, 2008; 86(6): 1291 - 1295. [Abstract] [Full Text] [PDF]
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