The genetics of docility of the grasscutter (Thryonomys swinderianus)

S Y Annor^*,***, B K Ahunu^*, G S Aboagye^*, K Boa-Amponsem^**, K T Djang-Fordjour and J P Cassady^***

Department of Animal Science Education, College of Agriculture Education, University of Education,
Winneba, P.O. Box 40, Mampong-Ashanti, Ghana.
sayannor@yahoo.com
* Department of Animal Science, College of Agriculture and Consumer Sciences, University of Ghana,
P.O. Box LG 571, Legon, Accra, Ghana.
** Animal Research Institute, Council for Scientific and Industrial Research, P.O. Box AH 20, Achimota, Accra, Ghana.
*** Department of Animal Science, College of Agriculture and Life Sciences, North Carolina State University,
Campus Box 7621/232B Polk Hall, Raleigh NC 27695-7621, North Carolina, USA

Abstract

The objectives of this study were to estimate non-genetic effects on docility, and calculate phenotypic and genetic parameters for docility in the grasscutter. The study was carried out at the grasscutter section of the Department of Animal Science Education, University of Education, Winneba, Mampong-Ashanti campus, Ghana from 2006 to 2009. Docility was defined as ability of an animal to accept human presence. A docility test was carried out on 321 animals (162 females and 159 males) which were selected at random at weaning (2 months). Docility was scored on a scale of 1 to 4; docile (1), flighty (2), restless (3) and aggressive (4). Each animal was tested 8 times.

Average docility score of the population was 2.6. Litter size, sex, parity, year of birth, season of mating and season of birth, and their interactions did not influence (p>0.05) docility. Moderate direct and maternal genetic variations were observed for docility. The permanent environmental influence due to the dam on offspring accounted for a significant proportion (48.0%) of the phenotypic variation in docility. Direct heritability for docility was high (0.58) while the maternal heritability was medium (0.41).There were low genetic and phenotypic correlations between docility and all traits (body weight, growth rate, days of joining to conception, survival, feed intake and feed conversion ratio), except litter size. Litter size had a moderate negative genetic correlation with docility, but a low negative phenotypic correlation. Repeatability of docility was high (0.84).

It was concluded that selection for grasscutters with more favourable docility scores would be effective in producing animals with more acceptable temperaments. Selection for grasscutters belonging to large litters is likely to produce docile animals, which are easier to handle. Addition of maternal effects to the genetic evaluation of docility in the grasscutteris recommended. One or two records on the animal’s docility are enough to make selection decisions.

Keywords: Genetic diversity, heritability, non-genetic effects, phenotypic and genetic correlation, repeatability, Thryonomys swinderianus

Introduction

Docility or temperament is defined as the animal’s behavioural response to handling by humans (Fordyce et al 1988; Burrow 1997). Docility is an important trait because it is related to many production traits. For example, it has been reported that cattle with higher body weights are more docile than those with lower body weights, and grow faster during fattening than aggressive animals (Fordyce et al 1988; Burrow and Dillon 1997; Fell et al 1999). Lamb mortality was reported to be lower in docile ewes than aggressive ones (Murphy et al 1994; Neindreet al1998) and twin lambs had calmer temperament than singles (Pajor 2011).

Livestock production often requires frequent movement and handling of animals. Routine handling is carried out during castration, weighing, ear tagging and de-worming. It is difficult to handle and control aggressive animals (Fordyce et al 1988). Animals or stockmen could be injured during handling of aggressive animals (Grandin 1994). Injuries increase the cost of production. It is thus desirable to have docile animals.

In modern animal breeding, temperament or docility is added as a trait in the breeding objective (Northcutt and Bowman 2010). In the grasscutter, there is a particular need to select and breed docile animals because, even after several generations in captivity, the animals are still aggressive toward humans (NRC 1991; Mensah and Okeyo 2006). A need to improve docility in the grasscutterwould require information on the genetic characteristics of docility of current population.

There is very little information on docility of the grasscutter. The objectives of this study were to estimate non-genetic effects on docility, and calculate phenotypic and genetic parameters for docility in the grasscutter.

Materials and methods

Location and time of study

The study was carried out at the grasscutter section of the Department of Animal Science Education, University of Education, Winneba, Mampong-Ashanti campus, Ghana from 2006 to 2009. Mampong-Ashanti lies in the transitional zone between the Guinea savanna zone of the north and the tropical rain forest of the south of Ghana. The climatic, vegetation and demographic characteristics of Mampong-Ashanti have been described by Ghana Districts (2006).

Essentially, Mampong-Ashanti lies between latitude 07^o 04’ north and longitude 01^o 24’ west with an altitude of 457m above sea level. Maximum and minimum annual temperatures recorded during the study period were 30.6^oC and 21.2^oC, respectively (MSD 2010). Rainfall in the district is bimodal, occurring from April to July (major rainy season) and again August to November (minor rainy season), with about 1224mm per annum. The dry season occurs from December to March.  The vegetation is transitional savanna woodland, and this is suitable for livestock rearing because most of the feed of herbivorous animals (grass) can be obtained from the wild. The common fodder species that are routinely fed to grasscutters, Pennisetum purpureum (elephant grass) and Panicum maximum (guinea grass) are readily available.

Experimental animals and design

Docility was defined as the ability of an animal to accept human presence. Docility test was carried out on 321 animals (162 females and 159 males) which were selected at random at weaning (2 months). The animals were put into groups after weaning and separated into individual cages after 4 months. Two weeks after animals were stabilized in their individual cages at four months, a docility test was carried out every week until they were 6½ months of age. The capacity of the animal to accept human presence was scored on a scale of 1 to 4 as follows:

• Score 1: Docile - the animal is friendly and accepts being touched and caressed.
• Score 2: Flighty - the animal accepts being touched but moves away slowly.
• Score 3: Restless - the animal does not allow physical human contact. It stays away, and moves around in the cage.
• Score 4: Aggressive - the animal jumps when it sees somebody in an attempt to escape. It hits itself on the sides of the cage.

The average docility score from the 8 individual tests on each animal was used in the analysis.

Management of animals

Animals were housed singly in three-tier wooden cages. Cages were housed in a sandcrete house roofed with corrugated iron sheets. Each individual cage measured 60 cm x 50 cm x 40 cm. Cages were partitioned by wire mesh. The sides and floor of the wooden cages were also covered with wire mesh. Wire mesh had a diameter of 2 mm, and was also used to line the exposed surfaces of wood to prevent gnawing by animals. The roof of each wooden cage was slanted and lined with felt to aid cleaning and drainage of liquid from stacks above.

Animals were fed basal diet of elephant grass (Pennisetum purpureum) and a supplementary ration of concentrate that contained 14% crude protein. Composition of the concentrate supplement was maize (44.0%), wheat bran (41.0%), Soybean (9.0%), Oyster shell (5.0%), common salt (0.5%) and vitamin-mineral-premix (0.5%). Animals were fed grass two times daily in the morning (8:00 hours GMT) and evening (17:00 hours GMT). Docility tests were carried out before feeding the animals in the morning by the same observer. Supplementary concentrate was fed in the afternoon at 14:00 hours GMT. Fresh grass was fed at a rate of about 200g/head/day whilst concentrate was fed at 20g/head/day. Of the quantity of grass fed, about 30% was offered in the morning and 70% in the evening. Grass was harvested every three days and spread on the floor to wilt before being fed to animals. Water was offered ad libitum. Supplementary feed and water were provided in concrete troughs. Percentage dry matter of grass was 34.3, 89.9 and 92.5 for major rainy, minor rainy and dry seasons, respectively, whilst that of concentrate supplement was 87.2. Feed intake was measured daily at 4-6 months. Left-over feed was weighed and subtracted from amount offered to get daily feed intake.

Cleaning of cages and grasscutter house were carried out daily. Feed and water troughs were also cleaned daily. Animals were de-wormed with Albendazole, 2.5% (Mobedco-Vet, Jordan), two weeks prior to the experiment. Experimental animals were identified by metal ear tags (Hauptner, Germany). All deaths were recorded and postmortem examination was carried out on dead animals.

Data collection

Each animal record included animal (kid), sire and dam identification, docility, sex, litter size at birth and weaning, parity of dam, season of mating and birth, year of birth, days from joining (pairing) to conception of dam, age of dam at kidding, birth weight, weaning weight, 4-month weight, 6-month weight, dam weight at birth and weaning, and pre- and post-weaning survival. Survival was defined as a trait of dam.

Statistical analysis

Non-genetic effects on docility were analyzed using Generalized Linear Mixed Models (GLMM) with GLIMMIX procedure of SAS (SAS 2008). Model used was:

y = Xβ + Zu + ε

Where, y represents vector of observations (docility); X and Z are design, or regressor, matrices associated with fixed and random effects, respectively; β is a vector of fixed-effects (type of birth, sex, parity of dam, year of birth, season of mating and season of birth) parameters; u represents the random effects (animal) vector; and ε, is the vector of residuals. An account was made for repeatable observations of docility in SAS analysis.

All model equations included 2-way interactions of fixed effects. Preliminary analysis indicated that three-way and higher level interactions were not important, and were therefore not considered.

The following coding was used for fixed factors:

Type of birth (litter size): single = 1, twin = 2, triplet = 3, quadruplet = 4, quintuplet = 5 and sextuplet = 6.

Sex of kid: Females = 1 and males = 2.

Parity of dam: First birth = 1, second birth = 2 and third birth = 3.

Seasons: Major rains (April to July) = 1, minor rains (August to November) = 2 and dry season (December to March) = 3.

Year of birth: 2006, 2007, 2008 and 2009.

Data to estimate genetic parameters were analyzed by mixed model methodology using a full animal model and all known genetic relationships, in single or multiple trait analysis, using the MTDFREML programme (Boldman et al 1995). Parameters estimated were phenotypic variance, direct additive and maternal genetic variances, covariance between direct and maternal effects, direct additive and maternal genetic coefficient of variation, proportion of phenotypic variance due to permanent effects of dam, direct and maternal heritability, direct-maternal genetic correlations, and phenotypic and genetic correlations of traits.

Single trait analysis was done according to the general mixed model:

y = Xß + Z_ia + Z_jm + Z_kc + e,                        where,

y = vector of observations; X = incidence matrix that associates ß with y; ß = vector of fixed effects, including litter size at birth, sex, parity of dam, year of birth, season of mating and season of birth; a = vector of breeding values for direct genetic effects; m = vector of breeding values for maternal genetic effects; c = vector of permanent environmental effects due to dam; Z_i, Z_j and Z_k = incidence matrices that associate a, m and c with y; and e = vector of random errors or residuals. Furthermore, with A, the numerator relationship matrix between animals, I_n, an identity matrix with order n, the number of dams and I, an identity matrix with order of the number of records, the co(variance) structure of random effects can be described as : V(a) = σ²_aA, V(m) = σ²_mA, V(c) = σ²_cI_n, V(e) = σ²_eI, where σ²_a is the direct genetic variance, σ²_m is the maternal genetic variance, σ²_c is the maternal permanent environmental variance and σ²_e is the residual variance. Year and seasons were put into the model as separate independent variables because previous reports in other livestock species indicated that they show different effects on docility (Gangwar 1982; Neindre et al 1995).

The 2-trait animal model used for the estimates was:

Where, y_i and y_j are vectors of recordsof animals for trait i and trait j ; ß_i and ß_j are vectors of fixed effects for traits i and j; a_i and a_j are vectors of random additive genetic effects for animalsfor traits i and j; m_i and m_j are vectors of maternal genetic effects for traits i and j; p_i and p_j are vectors of random permanent environmental effects for dams for traits i and j; e_i and e_j are vectors of random residual effects for traits i and j; X_i, Z_i, and W_i are known design matrices for trait i; and X_j, Z_j, and W_j are known design matrices for trait j. Fixed effects included litter size at birth, sex, parity of dam, year of birth, season of mating and season of birth.

There were 321 animals in the data file and 366 animals in the pedigree file that included the base animals. Local convergence was considered to be met if the variance of the -2 log likelihoods in the simplex was less than 1 x 10^-6. After first convergence, restarts were made to find global convergence, with convergence declared when the values of -2 log likelihoods did not change to the second decimal. Heritability and repeatability were categorized as low (< 0.30), medium (≥ 0.30-< 0.50) and high (≥ 0.50) (Rice et al 1970; Falconer and Mackay 1996). Correlations were classified as low (0.10 – < 0.30), medium (≥ 0.30 – < 0.50) and high (≥ 0.50 – 1.00), regardless of sign (Cohen 1988).Genetic coefficient of variation was used as measure for ability of docility to respond to selection and to determine genetic diversity of the trait (Morris et al1978; McLennan and Lewer 2005). Coefficient of variation was computed as CV_x (%) = 100 x σ_x/μ, where σ_x is the standard deviation of the trait and μ is the estimated trait mean (Houle et al 1996). Coefficient of variation was classified as low (0-20%), medium (>20-< 40%) and high (≥ 40%).

Repeatability of docility was estimated by computing the intra-class correlation of repeated records of an individual measured at different times, using the MTDFREML programme (Boldman et al 1995).

Results

Average docility score of the population was 2.6 (Table 1). The average score was characterized by animals that were between those that accepted to be touched but moved away slowly (Flighty) and those that did not allow themselves to be touched and stayed away by moving around in the cage (Restless). However, they tended to be more restless than flighty.

Effect of fixed factors and their interactions on docility

None of the fixed factors influenced (p>0.05) docility. Docility between different litter sizes, sexes, parities, years and seasons were similar (Table 1). Interactions of all fixed factors on docility were not significant (p>0.05).

Variation and heritability

Absolute values of phenotypic, direct genetic and maternal genetic variances of docility were low (0.7, 0.4 and 0.3, respectively). Direct genetic co-efficient of variation was 24.3%, indicating moderate genetic diversity (variability). The maternal coefficient of variation was similar (21.2%) to that of the direct effects. The proportion of phenotypic variance due to permanent environmental effects of the dam on docility was moderate (0.48). The covariance between direct and maternal effects was -0.30. The direct and maternal heritability of docility were high (0.58) and medium (0.41), respectively. The correlation between direct and maternal genetic effects (r_dm) was high and negative (-0.95).

Phenotypic and genetic correlations

Genetic and phenotypic correlations between docility and 14 traits are presented in Table 2. The phenotypic correlations between size traits (body weight and growth rate) and docility were low (0.01 to 0.06) and their genetic correlations were also low (0.01 to 0.27). Genetic correlations between litter size at birth and docility, and litter size at weaning and docility were intermediate negative whilst their phenotypic correlations were all low negative. The genetic and phenotypic correlations between days of joining to conception and docility were low negative. Both the genetic and phenotypic correlations between pre-weaning survival and docility, and post-weaning survival and docility were almost zero, indicating very weak relationships. There were very weak phenotypic and genetic relationships between feed intake and docility, and feed conversion ratio and docility.

Repeatability of docility

Table 3 shows the repeatability of docility in eight (8) docility tests. Repeatability, as measured by the intra-class correlation between any two tests, was high in all cases. It ranged from 0.73 to 0.89, with an overall average of 0.84.  

Discussion

Average docility score

The average docility score of 2.6, obtained in this study, is slightly above the median score of 2.5 on a scale of 1 to 4. Animals of this score are in-between score 2 and 3 i.e. between flighty and restless animals. Grasscutters fall within two extremes, the docile and non-docile (aggressive) animals. The docile (score 1) grasscutters adapt well to life in confinement and become accustomed to man quickly, whereas the non-docile (score 4) grasscutters panic when people approach and try to escape from their cages or pens (Mensah and Okeyo 2006). Since our grasscutters were above 2.5 they can be classified as restless, tending more towards aggressive behaviour, and are therefore difficult to work with. There is therefore a particular need for breeders to include docility in the breeding objectives of grasscutter improvement programmes (NRC 1991; Mensah and Okeyo 2006).

Effects of fixed (non-genetic) factors on docility

Litter size, sex, parity, year of birth, season of mating and season of birth, and their interactions did not influence docility. There are mixed reports of the effect of non-genetic factors on docility or temperament. Pajor et al (2008) and Pajor (2011) reported no difference between temperament scores for the two sexes in sheep, but detected differences between temperament scores of different litter sizes. Twin lambs had calmer temperament than singles. Neindre et al (1995) found no differences between years and parities on docility in Limousin cattle. Gangwar (1982) observed decreased docility in summer in buffaloes, as compared to other seasons. He explained that the extent of an animal’s docility is decreased and excitability increased due to the onset of the hot dry season, probably resulting from increased thermal stress.

Variation and heritability

The moderate direct genetic variation observed in this study for docility has also been reported in other animal species (Beckman et al 2007; Reale et al 2009). Genetic variation (diversity), that is, the heritable variation within populations is usually acted upon by selection, be it natural or artificial (Mensah and Okeyo 2006). The moderate genetic variation would enable selection pressure to be exerted in a breeding programme to alter or improve docility (Morris et al 1994; Gauly et al 2001).

There have been no previous reports of maternal effects of docility in the grasscutter. The moderate proportion of permanent environmental influence due to the dam observed in docility indicates that the dam has great influence on the trait. These environmental effects (epigenetic effects) are possibly due to influence of maternal behaviour of the dam on offspring (Lovic et al 2001; Kikusui et al 2005; Champagne 2008).The negative covariance between direct and maternal effects agrees with studies by Beckman et al (2007). Based on the moderate maternal genetic variance, and moderate proportion of phenotypic variance due to permanent environmental effects of the dam on docility, it was concluded that maternal effects account for a significant proportion of total phenotypic variance, which implies that maternal effects must be accounted for to obtain accurate breeding value estimates for docility (Bryner et al 1992).

The high direct heritability obtained for docility means that genetic selection will be effective in improving the performance levels of the trait (Northcutt and Bowman 2010). The maternal heritability estimate for docility was medium, confirming the assertion made above that maternal effects have influence on the trait, and must be accounted for in breeding value estimation. The high negative genetic correlation between direct and maternal effects of docility indicates antagonistic genetic effects (Beckman et al 2007).

Phenotypic and genetic correlations

There were low positive genetic and phenotypic correlations between size traits (body weight and growth rate) and docility. Similar results were obtained by Yewadan (2000) in the grasscutter and Burrow (2001) in tropical beef cattle. Yewadan (2000) observed low but negative genetic and phenotypic correlation between body weight and docility.  Burrow (2001) observed low positive genetic and low negative phenotypic correlations between temperament (docility) and size traits. These results indicate that correlated response is not expected in docility when body weight and growth rate are genetically improved. However, evaluation of the effects of temperament on body weight in sheep showed that lambs with calmer temperament had higher weight at the end of fattening and higher average daily weight gain compared to nervous animals (Pajor et al 2008).

The moderate negative genetic relationship between litter size and docility observed in this study indicates that genetic improvement of litter size could improve docility. Similar results were reported in sheep. Twin lambs were found to have calmer temperament than singles (Pajor 2011). However, this needs to be considered carefully as selection for high litter size may bring about deterioration in body weight and growth rate because litter size is negatively correlated with size traits (Annor et al 2011).

There was little or no genetic and phenotypic relationship between days of joining to conception and docility. This means that days of joining to conception cannot be used as measure for docility, and selection for days of joining to conception cannot bring about correlated response in docility. Burrow (2001) also reported little or no genetic and phenotypic relationship between temperament and days of joining.

The phenotypic and genetic correlations between docility and pre-weaning survival, and docility and post-weaning survival were near zero, indicating no relationship between docility and survival. Low phenotypic and genetic correlations between docility and survival have been observed in sheep (Lennon et al2008) and cattle (Visscher and Goddard 1995). These results suggest that if docility is used as a selection criterion, there would be no advantage in litter survival.

Phenotypic and genetic correlations between docility and feed intake, and docility and feed conversion ratio were near zero. Similar results have been observed for phenotypic correlation, but nearly different results in genetic correlation for cattle. Nkrumah et al (2007) and Rolfe et al (2010) found no phenotypic relationship between temperament and feed intake, and feed conversion ratio, but found low to high genetic relationships between the same traits. They concluded that behaviour traits may contribute to the variation in the efficiency of growth of beef cattle, and there are potential correlated responses to selection to improve efficiency.

Repeatability of docility

High repeatability of docility obtained in this study indicates that measurement of docility for the same individual at different times was highly consistent. This means that few records on the animal are enough to make selection decision (Hohenboken 1985). Similar results were obtained by Realeet al(2000) in wild bighorn sheep. They measured temperament for the same individual at different captures, and obtained a repeatability of 0.86, which was highly consistent. Hearnshaw and Morris (1984) also obtained high repeatability of temperament of 0.67 and 0.82, respectively for calves and cows on measurements taken the same day. They concluded that the high repeatability estimates obtained indicate that the 0-5 temperament score used was effective in describing cattle behaviour in the crush and bail. It is therefore concluded in this study that the 1-4 score used in measuring docility was effective in describing the behaviour of captive grasscutter in the cage.

The repeatability describes the proportion of the phenotypic variance explained by additive genetic and permanent environmental effects (Hohenboken 1985). A high repeatability therefore also means that docility is influenced by permanent environmental effects, rather than temporal effects (Murphy et al 1994; Reale et al 2000; Reale and Festa-Bianchet 2003). This observation is confirmed by the moderate proportion of phenotypic variance due to permanent effects of dam obtained above for docility.

Conclusion

• Grasscutters belonging to large litters are more docile than those from small litters, and are easier to handle.

  
  

• Direct heritability estimates suggest that selection for grasscutters with more favourable docility scores would be effective in producing animals with more acceptable temperaments. Maternal genetic and maternal permanent environmental effects explained large proportions of the phenotypic variation.

  
  

• Considering these results, addition of maternal effects to the genetic evaluation of docility in the grasscutter is recommended.

  
  

• Repeatability of docility was high, indicating that one or two records on the animal are enough to make selection decisions.

Acknowledgement

The authors are grateful to the Teaching and Learning Innovative Fund (TALIF), Ghana for providing grasscutter facilities for this research.

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Received 16 June 2011; Accepted 17 July 2011; Published 3 August 2011

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