An analysis of inbreeding levels and factors affecting growth and reproductive traits in the Kenya Alpine dairy goat

Introduction

The unavoidable mating of related animals in closed populations leads to accumulation of inbreeding and decreased genetic diversity. Inbreeding has deleterious effect on additive genetic variance as well as on phenotypic values (Falconer and Mackay 1996). Heterozygosity and allelic diversities can be lost from small, closed, selected populations at a rapid rate. The loss of diversity and resulting increase in homozygosity may result in decreased productions and/or fitness of inbred animals. Furthermore inbreeding depression in domestic animals can lead to a decrease in selection response and in potential genetic gains in economic traits. Measurement of the effect of inbreeding on these traits is important in order to estimate the magnitude of change associated with increases in inbreeding. Inbreeding impairs growth, production, health, reproduction traits (such as fertility) and survival. The emergence of disorders due to recessive gene action may also occur. It is apparent that different breeds and populations, as well as different traits vary in their response to inbreeding. Some populations may show a very pronounced effect of increased inbreeding for a trait, whereas others may not demonstrate much of an effect (Analla et al 1998).

The rate of inbreeding needs to be limited to maintain diversity at an acceptable level so that genetic variation will ensure that future animals can respond to changes in the environment and to selection. Without genetic variation, animals cannot adapt to these changes (van Wyk et al 2009). The Kenya Alpine dairy goat breeding has been implemented for close to twenty years, during which period breeding bucks were sourced from Germany. The foundation stock was all from German Alpine with no records of their pedigrees. There was repeated sourcing of breeding bucks from Germany but due to lack of proper recording, it was not clear if considerations were made about their relationships. Eventually, due to the outbreak of the “Bovine Spongiform Encephalopathy” (Mad Cow Disease) in Europe, importation of live animals was banned. Since then, breeding bucks have been sourced locally from within the small Alpine population but without proper records and procedures to establish their relationships, they could not be used to control inbreeding. The breed has not yet been stabilized and therefore effects of inbreeding would reverse the initial breeding objectives. Although inbreeding leads to reduced fitness, the degree to which populations suffer from inbreeding and its effects can vary widely depending on population history, the trait examined lineage effect and the environment (Pray and Goodnight 1995; Husband and Schemske 1996; Dudash et al 1997; Bijma et al 1999; Reed and Bryant 2001; Frankham et al 2002; Reed and Frankham 2002).

The objective of this study was to analyze the rate of inbreeding in Kenya Alpine dairy goat and its effects on production and reproduction. 

Materials and Methods

The study animals

The Kenya Alpine dairy goat was used in this study. The breed was developed by crossing and grading-up of the East African goat using  the German Alpine buck in an effort to providing alternative source of income to small scale farmers’ in Kenya. For over 10 years, the Kenya Alpine dairy goats were bred through natural service, a process characterized by buck rotation facilitated by the Dairy Goat Association of Kenya. The goats were usually stall-fed and every household has on average between 3-6 goats. Milking was usually done in the morning after kids have suckled. The four genetic groups include:

            i.  Foundation (50% Alpine) - F_1:  Pedigreee Alpine Buck (PAB) x Local doe.

            ii. Intermediate (75% Alpine) - Back cross 1 (R₁):  PAB x F₁ Females.

              iii. Appendix (87.5% Alpine) - Back cross 2 (R₂):  PAB x R_1.

              iv. Pedigree (≥87.5%):

                    a)      Interse mating of Back cross 2: R₂ Male x R₂ Female.  Offspring will remain 87.5% or more.

                    b)      PAB x R₂ female- Grading-up. Offspring will be 93.25% or  more. 

Kenya Alpine dairy goats usually live in the Central and Eastern highlands of Nyeri and Meru Districts respectively, but in recent years they have spread to other areas of lower potential compared to the original entry areas. These areas are characterized by a humid to sub-humid climate with long, wet and cold wet seasons. Herds are usually zero grazed and stall fed on greens and very little or no concentrate supplementation is provided. Water is also provided in the shed. The kidding season is usually not synchronized but rather depends on conditions of pasture.

The onset of the bovine spongiform encephalopathy prompted the banning of importation of live animals from Germany and therefore breeding bucks were sourced from the local population. However, recently there has been an increasing concern in the manifestations of inbreeding effects in the dairy breed and thus the need to know the inbreeding rates in order to be able to plan a better breeding program. 

Data

Initially, 1,829 dairy card records were collected from individual farm house holds within the eight study districts. These records were made for the period starting from January 1999 and ending in January 2010. Out of these, 762 dairy card records (41.7%) were deemed to be outliers and the remaining 1,067dairy card records of does were used in this study. These records included the Animal tattoo number, Breeder, birth weight (Bwt), weaning weight (Wwt), age at first service (AFS) and consequent services, age at first kidding (AFK) and consequent kiddings, as well as paternal and maternal parents and grandparents. From these 1,067 dairy card doe records, information on parentage was extracted resulting in 3,516 records which were used for pedigree analysis.  The birth and weaning weights were measured at 70±14days.

The kids were weaned at 40±3 days. Birth and weaning weights were measured for all the animals; Reproductive traits were evaluated on a total of 1282 records where three different ratios calculated as follow: fertility (% of does kidding of does bred); prolificacy (% of kids born of does kidding); fecundity (% of kids born of does bred).

Pedigree completeness was assessed by tracing back the pedigrees for five generations. Individual inbreeding coefficients (F) were calculated according to Wright’s equation (Wright 1922):

F_x = Σ (½)ⁿ (1 + F_a)

Where F is the inbreeding coefficient of each animal; n the number of generations between the sire and dam respectively and their common ancestor; F_a is the inbreeding coefficient of the ancestor, common to both the sire and dam.  

 Statistical Analysis

Separate analyses were carried out to determine the overall effects of inbreeding in the Kenya Alpine dairy goat. The first two analyses were conducted to estimate the effect of fixed factors on growth traits and the effect of fixed factors on reproductive traits. Fixed effects affecting growth included the Age at first service, effect of type of birth, effect of month of birth and effect of the area of birth. These were fitted in Model I below. The fixed effects affecting reproduction included the effect of age at first kidding, effect of age at first service, the effect of type of birth, the effect of birth weight and effect of adjusted weaning weight at 70 days. These were fitted in model II. Analysis of fixed effects on the various traits was done using Statistical Analysis Software (SAS^©) Version 9.0. Estimation of means and frequencies, generalized linear models (GLM), Analysis of variance (ANOVA), was done using the same software. Initial population estimates such as population structure and grade distribution were done using Microsoft Excel^TM package version 2007. Data was sorted and re-arranged using Microsoft Access^TM package version 2007. Inbreeding estimates were carried out using Brian Kinghorn’s Pedigree Viewer^© software version 5.5. 

Model I

Model I was used to estimate the effect of fixed factors on growth traits and the following model was fitted:

Y_ijkl =µ + G_i + S_j +Y_k +A_l +GS_ij +GA_ik +e_ijklm

 Where,

Y_ijkl – is the observed m^th parameter of a goat in the i^th genetic group (I = 1, 5), born in the jth season of birth, in the k^th year and in the l^th area (a=1,4)

µ- is the underlying constant in each observation;

G_i –is the effect of the i^th genetic group;

S_j- is the effect of the j^th season of birth;

Y_k- Is the effect of the k^th year of birth;

A_l- is the effect of the l^th area of birth;

GS_{ij -} is the effect due to interaction in the i^th genetic group and the j^th season;

GA_ik- is the interaction due to the i^th genetic group and the l^th area of birth;

e_ijklm- is the effect of random unpredictable factors, assumed to be normally distributed with a mean 0 and a variance, σ² =1. 

Model II

Model II was used to estimate the effect of fixed factors on reproduction and the following model was fitted:

Y_ijkl =µ + G_i + S_j +Y_k +A_l +GS_ij +GA_ik +e_ijkl

 Where,

Y_ijkl – is the observed i^th AFK of a goat in the i^th genetic group (I = 1, 5), born in the jth season of birth, in the k^th year and in the l^th area (l=1, 4)

µ- is the underlying constant in each observation;

G_i –is the effect of the i^th genetic group;

S_j- is the effect of the j^th season of birth

Y_k- Is the effect of the k^th year of birth

A_l- is the effect of the l^th area of birth

GS_{ij -} is the effect due to interaction in the i^th genetic group and the j^th season

GA_ik- is the interaction due to the i^th genetic group and the l^th area of birth

e_ijkl- is the effect of random unpredictable factors, assumed to be normally distributed with a mean 0 and a variance σ² =1. 

Results

3,516 goat records were available for this study and are presented in Table 1. Pedigree accounted for 32% of the records, Appendix 25%, Intermediate 16% and Foundation 27%. The range and frequency of inbreeding coefficients are presented in Table 2. Over 90% of the records had zero inbreeding. Over 7% had an inbreeding coefficient of 10% or less and 3% had an inbreeding coefficient of 13% or less. The rate of inbreeding was 0.019 F/year. For the different genetic groups, the rate of inbreeding was 0.184 Pedigree, 0.192 for Appendix, 0.201 for Intermediate and 0.253 for Foundation. Rates of inbreeding were not significantly different for all genetic groups; however, the rate of inbreeding was significantly lower for pedigree than for the other three grades.  

The analysis of pedigree (>87.5% pure) revealed that 13 animals out of 3,516 (0.40%) had a high inbreeding coefficient (F≥10%) with a mean value of 13.10% while the remaining 99.60% of doe kids were non-inbred. 

Birth and weaning weights

The means procedure of SAS showed that the Kenyan Alpine goats have a minimum birth weight of 1.5 kg and a maximum of 3.10 kg with a coefficient of variation of 17.3%. The youngest animal to be weaned in the sample population was around one and a half months and the oldest to be weaned was roughly three months old with a mean weaning age of 60.78±11.51 days. The year and month of birth both significantly affected the birth weight at P<0.5 whereas the type of birth and area of birth were significant at P<0.001.

The area which recorded highest birth weight was Murang’a District with 3.4kg (P<0.0001) with Embu District recording the lowest birth weight of 3.1 kg (P<0.001). Kirinyaga, Nyeri and Vihiga Districts recorded similar birth weights with an interval 3.21≤BWt≤ 3.35.

a.       Fecundity rate = (Total births @kidding/total females @mating)* 100%

      =864/1067*100

      = 80.97%

b.      Fertility rate = (total does @birth/Total does @mating)*100%

= 600/1067*100

=56.23%

c.       Prolificacy = (Total of births/ Total of kidding does) *100%

= 864/600*100

=144%

Or

Prolificacy = Fecundity/ Fertility

= 80.97/ 56.23

=1.44 

Kidding interval days open and gestation period

Means of the Kidding Interval, the days open and gestation period were estimated using the means procedure of SAS^©, and the results are as shown in Table 5. Kidding interval ranged from 181days to 1203days with a mean of 392±164 days. The days open also varied from between 30-1058days with a mean of 242±166 days, but since the gestation period is biologically controlled, it had a very solid mean of 152±19 days and a very small coefficient of variation of 12.55%.

An ANOVA was then carried out to discern effects on Kidding Interval by the five sources of variation as shown in Table 6. The grade, type of birth and area were not significant at P>0.05, but the month of kidding had an effect on the kidding interval (P<0.05). The year of kidding also had a significant effect at P<0.01.

Within the grades, KI revolves around 335±15days with Local (0% Alpine) having the lowest KI of 321 days and Appendix (87.5% Alpine) the highest of 349 days. Pedigree (>87.5% Alpine) and Intermediate (75% Alpine) had almost similar KI of 333 and 334 days respectively whereas Foundation (50% Alpine) registered a KI of 345 days.

The month of kidding was most significant effect (P<0.05) so was the year of kidding (P<0.01). 

Conclusions

• Out of the 3,516 animals, only 352 goats were inbred with Wrights coefficient of inbreeding (F) ranging from 0 to 0.13. This was consistent with values reported by Gipson (2002) of 0.10 on Alpine pure breeds. Over 90% of the goats had an inbreeding coefficient of 0.05 or less and only 10% had an inbreeding coefficient of 0.10 to 0.13. Half-sibs had an inbreeding coefficient of 0.0125 while full-sibs had an inbreeding coefficient of 0.025, consistent with 0.0186 reported by Bijma et al (2001). The yearly rate of inbreeding was 0.019 which was inconsistent with that predicted by Bijma et al (2001) of 0.0597/yr. Rates of inbreeding were not significantly different for the different genetic groups with 0.184 for Pedigree, 0.192 for Appendix and 0.201for Intermediate and 0.253 for Foundation, and this was almost similar to 0.247 reported by Ercanbrack and Knight (1981).

• The mean weaning weight recorded was 19.5 ± 4.47kg, heavier than that reported by Ahuya et al (2009) of 19.0±0.62 kg for Toggenburg dams between 1-2years.The Alpine goat was introduced much earlier compared to Toggenburg goat (Peackock 1996) and thus it has acclimatized to the tropical environment. Compared to other breeds reared under similar environments, the Alpine was weaned at an earlier age of 60±12days which was lower but consistent with that reported by Gaddour et al (2010) of 75days. The early age at weaning during the study period can be attributed to availability of pasture due to favorable rainfall and availability of pasture in the dry season due to surplus production in wet season (http://www.meteo.go.ke/). 

• The mean age at first service was 504 ± 210 days, as opposed to that reported by Khanal et al (2005) of 229.2 days. This was more than twice the average age at first kidding recommended for all goats of 240days (Ahuya et al 2009).  This late AFS was due to lack of timely provision of buck services. The bucks used for natural service are communally owned and one buck services in excess of 300 households over a radius of 5-15km. Given a buck to doe ratio of 1:5 (Stubbs et al 2002), AFS can increase due to late provision of bucks. A study done by Khanal et al (2005) reported that late provision of bucks in natural service could delay the AFS by between 160-240days. Vihiga district had the youngest AFS of 357±113days due to low population density of the Kenya Alpine dairy goats in the area. The low population of dairy goats in Vihiga district has made it easier for buck rotation to reach farmers at an earlier time than those in areas with high Alpine goat populations.  

Based on the scope and limitations of this study, the following conclusions were made:

1. From the analysis carried out, there is not enough evidence to show that the Kenya Alpine dairy goat population is inbred. However there is imminent inbreeding as demonstrated by the physical sign in some of the animals such as under developed udders, bisexual individuals.
   
   
2. While there was no significant difference in the growth of the different genetic groups of the Kenya Alpine dairy goat, their growth was most affected by the type of birth, the season of birth and the birth weight of the kid.
   
   
3. The study showed that though Nyeri district was the pioneer district of the Kenya Alpine dairy goat, the breed has spread out in other areas of Central, Eastern and Western provinces. This meant that the Kenya Alpine dairy goat is continually being accepted as an alternative small holder milk production breed. However, the different genetic groups need to be vetted at different levels, to avoid erroneous registration of animals in genetic groups that they do not belong.

Recommendations

1. In any population, there is always an acceptable level of inbreeding; the challenge usually is how to control this inbreeding. In the case of the Kenya Alpine dairy goats, there was no clear breeding programme and therefore, inbreeding could occur. There is therefore need to have a breeding programme and recording scheme developed.
   
   
2. Lack of adequate data on parentage of these goats and health records made it difficult to carry out more studies on genetic relationships and on more economically important traits. Dairy Goat Association of Kenya should therefore enhance proper recording procedures that aim to capture all the vital information of an individual goat.
   
   
3. A breeding programme for the Kenya Alpine dairy goat should be developed and implemented by a trained animal breeder. Furthermore, new software for buck rotation should be developed and put to use.

Reference

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Received 18 October 2011; Accepted 28 November 2011; Published 1 December 2011

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