Effect of inbreeding on traits of economic importance in Kenyan Sahiwal cattle

M Musingi¹, T K Muasya, E D Ilatsia² and A K Kahi

Animal Breeding and Genomics Group, Department of Animal Sciences, Egerton University, P O Box 536, 20115 Egerton, Kenya
muasyakt@yahoo.com
¹ Department of Biological Sciences, Egerton University, P O Box 536, 20115 Egerton, Kenya
² Kenya Agricultural and Livestock Research Organisation, Dairy Research Institute, P O Box 25, 20117 Naivasha, Kenya

Abstract

Pedigree and performance data for the Sahiwal cattle from the National Sahiwal Stud (NSS) in Kenya were used to evaluate the effect of inbreeding on first lactation milk yield (LMY), age at first calving (AFC), calving interval (CI), and lactation length (LL). Effects of inbreeding on the traits were determined by fitting four regression models (linear, quadratic, exponential and Michaelis-Menten) to the errors generated by the animal model. The linear, exponential and Michaelis-Menten models were significant for all the studied traits while the quadratic model was only significant for calving interval. Inbreeding had a positive effect on calving interval, age at first calving, and lactation length, shortening calving both interval and age at first calving and increasing lactation length. The relation between inbreeding and depression of traits was not linear, with greater depression after 15% inbreeding. Genetic evaluation of the Kenyan Sahiwal should account for inbreeding. The results of the current study indicate the need to consider effect of inbreeding on traits of economic importance for the Sahiwal cattle breed when carrying out genetic evaluations. The mating plan for the NSS should be designed so as to control future rates of inbreeding while achieving genetic gain.

Key words: genetic gain,inbreeding depression

Introduction

Increase in inbreeding leads to reduced genetic variability by reducing heterozygosity over many loci (Falconer and Mackay 1996), increased risk of breeding programmes due to variance of genetic gains (Meuwissen, 1991) and increased risk of emergence of lethal recessive homozygous alleles (König and Simianer 2006). An immediate concern to dairy farmers is the reduction of performance of inbred animals, referred to as inbreeding depression due to inbreeding (Falconer and Mackay 1996).

For the Kenya Sahiwal population, Muasya et al (2011) reported a gradual increase in inbred animals from 0 in 1967 to 80% in 2008 with a corresponding increase in mean individual inbreeding coefficient from 0 to about 2.5% in 2008. The proportion of inbred animals increased rapidly from 1% to about 98% in the most recent complete generation. As the proportion of inbred animals increase, reduction of inbreeding through pairing of mates that are less related than the average in the population becomes difficult (Thompson et al 2000). In the Kenyan Sahiwal cattle, inbreeding level increased from 1.2 to 2% as the proportion of inbred individuals increased (Muasya et al 2011). Other studies have reported various estimates of inbreeding for zebu the Sahiwal breed. In Nicaragua an inbreeding level of 13.0% has been reported for Creole cattle breed (Corrales et al 2010). Among the Nellore, Guzerat and Gyr zebu cattle breeds in Brazil, inbreeding levels ranging from 1.8 to 2.8% have been reported (Filho et al 2010; Faria et al2009).

Inbreeding depression decreases cow survival, reproductive performance and milk production and increases rate of disposal or loss of replacement heifers before first calving, age at puberty through reduced growth (du Toit et al 2012). Every 1% increase in inbreeding leads to a 10 kg of milk to 26kg decline in milk production per lactation (Mostert, 2011) and decrease of about 13 days in productive life (CDN, 2008; Smith et al 1998). du Toit et al (2012) reported a similar effect of inbreeding on functional herd life in Jersey cattle. Cows with high inbreeding level have also been reported to have a high risk of being culled (Rokouei et al 2010).

Inbreeding depression depends not only on actual level of inbreeding but also on the rate of inbreeding such that animals with the same level of inbreeding may have different inbreeding depression effects depending on the completeness of their respective pedigrees (González-Recio et al 2007; Gutiérrez et al 2009). The quality of pedigree can be accounted for by estimating the rate of inbreeding (Gonzalez-Recio et al 2007) which indicates the increment in inbreeding regardless of number of known generations in an individual’s pedigree (Gonzalez-Recio et al 2007). The objective of the study was therefore to evaluate the effect of inbreeding on lactation milk yield, lactation length and fertility traits in the Kenyan Sahiwal cattle population.

Materials and methods

Description of the study sites and data collection

Pedigree data for the Sahiwal cattle in Kenya were obtained from the Sahiwal National Stud at Kenya Agricultural and Livestock Research organization (KALRO), Naivasha. A database was created by systematically entering each animal, sire and dam, date of birth and sex into a database. The data were checked for consistency to ensure that all animals were ordered sequentially based on date of birth such that no progeny was born before any of its parents and that there were no cyclic pedigrees (i.e. no animal appeared as both male or female) and no animal appeared as both sire and dam using the Animal Breeder’s Tool Kit (ABTK, Golden et al 1992). Data on lactation milk yield for the first lactation (LMY), lactation length (LL), calving interval (CI) and age at first calving (AFC) were added onto the pedigree database of each animal. Age at first calving was derived as the interval in days from date of birth to first calving. Calving interval was derived as the interval between consecutive calvings for the first three lactations. Means, standard deviations (SD) and coefficients of variation (CV %) for LMY, LL, AFC CI are given in Table 1.

The large CV% for LMY reflects the great variation between individual cows in these traits. Similar results were reported for Egyptian buffalos (Khatab et al 2007).

Assessment of level of inbreeding

The inbreeding coefficient (F_i) for each individual in the pedigree was calculated as the probability that two alleles are identical by descent according to the method of VanRaden (1992). This method makes it possible to compute the inbreeding coefficients per generation, and assumes that founders are inbred or related, an assumption, which is important when pedigrees are heterogeneous. The inbreeding coefficient of an individual with unknown origin (founder) is equal to half the average genetic relationship between genetic groups of its phantom parents.

Estimation of (co)variances and estimated breeding values

Estimates of variance and estimated breeding values were obtained by performing univariate analyses on first lactation milk yield (LMY), lactation length (LL), age at first calving (AFC) and calving interval (CI) using the following animal model:

Y= Xb + Za + e

where y is a vector of observations for LMY, LL, AFC and CI in each lactation, b and a and e are vector of fixed effects, random animal effects, and random residuals, respectively and X and Z are the incidence matrices relating fixed and random animal effects to observations, respectively. The random effects will be assumed to be normally distributed with a mean=0 and variance as follows: a ~ N (0, A I σ ²_a ) and a ~ N (0, I σ ²_e ) whereσ ²_a and σ ²_e are animal and residual variances, respectively, and A and I are the numerator relationship and identity matrices, respectively. The models for LMY, CI and LL included fixed effects of year-season of calving and age at calving. A similar model was used for AFC but with year-season of birth instead of year season of calving. Variance covariance components for the traits under study were estimated using MTDFREML software package (Boldman et al 1995).

Analysis of pedigree, inbreeding coefficient (F) and equivalent complete generations were estimated using ENDOG version 4.5 computer programme (Gutiérrez and Goyache 2005). Equivalent complete generations were estimated as:

where n is the number of generations separating each individual from each known ancestor (Maignel et al 1996). Inbreeding coefficient (F) was computed after Meuwissen and Luo (1992). Rate of inbreeding (∆F) was calculated for each generation as:

where Ft and Ft-1 are the average inbreeding at t^th generation. Only animals with ECG of at least included in the analysis of F (2367 animals).

Estimation of inbreeding depression

A vector of errors for each trait were generated from univariate analysis using WOMBAT (Meyer 2007) as follows;

e_i = X_iβ + Z_ia

The effect of inbreeding on the traits studied was determined by fitting the following four regression models:

around the errors. The model of the analyses was e_i=Φ(Fi)+ɛ, where Φ(Fi) is the regression function on inbreeding efficient of an animal (Fx) and ɛ represents the deviations of the errors from the predicted errors in the regression function.

Results and discussion

Summary of number of animals, mean inbreeding levels by groups of birth year and number of animals in each inbreeding class are shown in Table 2. In the 1965-1974 birth year group 79% of the animals were not inbred, while in the last year group only 11% were non-inbred. Mean inbreeding level across the year of birth groups increased from 0.9 to 1.6%. A similar trend was reported in Jersey cattle in South Africa (du Toit et al 2012).

The mean inbreeding level and annual rate of inbreeding for the population studied were 0.7 and 0.33%, respectively. Higher average inbreeding levels of 15% in Guzerat cattle (Panetto et al 2010), 1.75 to 2.28% in Brazilian zebu cattle (Faria et al 2009) and 1.73% in the Nellore breed (Brito et al 2013) have been reported. Rates of increase in inbreeding lower than that reported in the current study ranging from 0.04 to 0.08% were reported in dairy cattle breeds in Canada (CDN 2010).

The general increase in inbreeding among the cows in the current study could be linked to intense use of a small number of superior sires and more complete pedigree information in more recent years (Muasya et al 2011).

For LMY, non-inbred animals produced more milk yield and longer CI (P<0.05) compared to inbreds. For the other traits, non-inbred animals performed better than inbred animals, though the means were not different (P>0.05). The depression in performance or inbreeding depression is attributed to inbreeding depression caused by increased homozygosity of individuals. Increased homozygosity lowers fitness through increase in the frequency of homozygous recessive detrimental mutations, and increased homozygosity for alleles at loci with heterozygote advantage (Griffiths et al 1999; Charlesworth and Willis 2009). There is emerging evidence that lowly heritable traits such as fertility (e.g. CI, AFC) exhibit more depression due to inbreeding because of their low genetic variation (Kristensen et al 2005), though results from the current study showed significant depression in LMY only (Table 3).

Effect of inbreeding on the traits studied is shown in Table 4. The linear, exponential and Michaelis-Menten models were significant (P<0.05) for all traits studied (Table 4). The quadratic model was significant (P<0.05) for CI only. Carrillo and Siewerdt (2010) and Mahlado et al (2013) reported a similar pattern, where the linear, exponential and Michaelis-Menten models were significant for all traits studied, whereas the quadratic model was not significant for any traits studied.

The residual variances for the three models were similar (Table 5) implying equivalence in goodness of fit. Similar results were reported by Carrillo and Siewerdt (2010) and Mahlado et al (2013), meaning that any of the three models would be adequate in estimating inbreeding depression. Of these models, the linear model, which is to fit and the fact that its parameters have direct interpretation, would suffice. However, its limitations are its lack of flexibility and its inability to cope with departure from linearity at higher inbreeding levels (Figure 1).

The increase in inbreeding led to a decrease in first lactation milk yield, calving interval and age at first calving (Figure 1) implying a depression in milk yield but an improvement in CI and AFC.

Figure 1. Effects of inbreeding depression on LMY, CI, LL and AFC for Kenyan Sahiwal cattle

Similar findings have been reported in previous studies. Mahlado et al (2013) found that the exponential and the Michaelis-Menten models were significant for all traits studied. However, unlike in the current study, the exponential model was not significant for any of the traits studied. In the current study, for inbreeding levels up to 0.15, inbreeding was approximately linear. Beyond that level of inbreeding, there seemed to be a higher inbreeding depression in all traits (Figure 1). Similar results have been reported by Mahlado et al (2013) and Santana Junior et al (2011). In the study by Santana Junior et al, animals with an average F=25% produced less milk by 107 kg compared to non inbreds. In the current study, inbred animals (F=15%) had a depression in milk production of 258 kg in the first lactation. In Mahlado et al (2013) study, at an average F=0.25, animals produced 50.4 kg less. Others authors that have reported a decline in milk yield due to increase in inbreeding include Panetto et al (2010) who found a reduction of 15.25 kg in milk yield in Guzerat cattle when half sibs were mated.

In populations with inbreeding levels of 12.5%, high inbreeding depression for milk yield ranging from 345 to 480 kg in Holstein cows translating to 27.6 kg to 38.4 kg per 1% increase in inbreeding have been reported (Smith et al 1998; Thompson et al 2000). Other studies have found a non-linear relationship between inbreeding and milk yield resulting in a depression of 380 kg in 305 day milk yield among highly inbred cows (F=12.5%) (Gulisija et al 2007). For cows with a similar inbreeding level, Maiwashe et al (2006) reported decline of 170kg in 305 milk yield. Panetto et al (2010) reported a positive effect of inbreeding on daily milk yield, contrary to that reported in the current study. Among Buffaloes in Brazil, Santana Junior et al (2011) reported a decrease of 4.3 kg while Malhado et al (2013) found a value of 14.8 kg for 1% increase in inbreeding; whereas Mirhabibi et al (2007) reported a decrease of 18.2 kg.

Lactation length deteriorated by 0.3 days per 1% increase in inbreeding, though the effects were not significant (P<0.05). To the contrary, inbred animals had slightly better fertility compared to non-inbreds (Table 5). Similar to the current study, Malhado et al (2013) found a favourable relationship between inbreeding and AFC among Brazilian Buffaloes. In this study, a 1% increase in inbreeding led to a shortening of AFC by 0.76 days. Thompson et al (2000) reported that low to moderate levels of inbreeding (F<0.07) reduced AFC by 3 to 5 days compared to non-inbred animals. Contrary to the positive effects of inbreeding on CI and AFC reported in the current study, Panetto et al (2010) found that these traits increased by up to 14 day and 11 days for every 1% increase in inbreeding in a Guzerat dairy herd. Other studies reported increase in CI and AFC. Hudson and Van Vleck (1984) reported an expected increase in CI by 2 day whereas AFC was expected to increase by 0.4 days for every 1% increase in inbreeding. Among Irish Holstein-Friesian cows, McParland et al (2007) reported that mating between half-sibs (F=12.5%) would result in an increase in AFC and CI of 2.5 days and 8.8 days, or 0.2 and 0.7 days per 1% increase in inbreeding, respectively. A smaller effect of inbreeding depression of 0.263 days on CI was reported for Alentejana cattle (Carolino and Gama 2008). Other studies that have reported a decline in fertility due to inbreeding include González-Recio et al (2007), Malhado et al (2013). In Iranian Holstein cattle, Rokouei et al (2010) reported a non-significant effect of inbreeding on CI in first and second lactations.

Conclusion

• Inbreeding had deleterious effect in performance on the traits studied. The relation between inbreeding and depression of traits was not linear, with greater depression after 15% inbreeding. Genetic evaluation of the Kenyan Sahiwal should account for inbreeding. Matings should be planned in order to check future increase in inbreeding while achieving acceptable rate of genetic progress in the programme’s breeding goal.

Acknowledgements

The authors are grateful to the Kenya Agriculture and Livestock research organization (KALRO) for provision of data and Egerton University, Kenya for financial support and provision of computing facilities.

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Received 14 October 2017; Accepted 8 December 2017; Published 1 January 2018

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