**4. Molecular research and genetic improvement**

Since the advent of molecular genetics, research on goats has entered a new era, also influencing the South African goat populations. The first research on South African goats was performed using microsatellite markers in the early 2000s and mainly involved genetic diversity and char‐ acterization studies. Genetic characterization assists in the conservation of unique character‐ istics of indigenous populations, whereas genetic diversity has a direct influence on genetic progress, selection strategies and the control of inbreeding levels. The identification of quan‐ titative trait loci (QTL) explaining significant fractions of the genetic variance in economically important traits could lead to increased accuracy of estimated breeding values (EBVs) with a corresponding faster rate of genetic improvement. A few QTL identification studies were performed on Angora goats, but the limited amount of variation explained by these fragments restricted the application of the results in terms of marker‐assisted selection (MAS). Some effort has gone into sequencing genes of economic importance and estimating their population fre‐ quencies as well as identifying novel variants in the local populations. The first caprine single nucleotide polymorphism (SNP) chip became commercially available in 2012, and since then (as with almost all other livestock species) SNP markers have become the marker of choice.

#### **4.1. Angora goats**

**3.3. Dairy goats**

28 Goat Science

tively [29].

improvement.

The South African dairy population is small in comparison with the other goat breeds and small stock. There are currently 45 registered herds representing 16,561 animals [24], and the remaining animals are used in commercial milk operations. Of the 45 herds, 16 herds (approximately 1217 goats) participate in official recording. Although participation in offi‐ cial animal recording is limited, the opportunity is available to record milk yield, milk composition and linear traits for selection and improvement. Heritability estimates have been reported for the SA Saanen for milk yield (0.23), butter fat yield (0.22) and protein yield (0.20). Protein and butterfat percentages had a heritability of 0.44 and 0.21, respec‐

**Figure 6.** Participation of meat goat breeders in the National Small Stock Improvement Scheme [24].

ADG 0.170 Schoeman et al. [26]

**Table 3.** Heritability estimates for preweaning weights of Boer goats.

Weaning weight direct 0.18–0.15 Van Niekerk et al. [26]; Schoeman

Weaning weight maternal 0.05–0.45 Van Niekerk et al. [26]; Schoeman

et al. [27]

et al. [27]

**Trait** *h***<sup>2</sup> References** Birth weight 0.05–0.14 Schoeman et al.[26]

Despite this relatively small population size, a niche market is served with the produc‐ tion of fresh milk and specialty cheeses. Marketing of these products occurs mostly in an informal way, such as by selling directly to consumers via on‐farm sales, or at various mar‐ kets. The renewed interest in organic products and dairy goats in general may result in breeders adopting modern technologies to overcome limitations in parentage recording and thus improved recording in order to perform accurate selection for long‐term genetic Without a doubt, the Angora goat breed is the South African goat breed on which most molec‐ ular research has been performed. The SA Angora goat served as the model breed for improv‐ ing the goat linkage map in 2010, using 94 microsatellite markers [30]. Both the accuracy and the coverage of the map were improved by adding markers, correcting previously reported order alignments and decreasing map distances. This linkage map formed the basis for a number of studies performed on the SA Angora goat.

Angora goats in South Africa are primarily farmed extensively and are subjected to group mating and over‐mating. This limits accurate parentage recording and has a negative effect on the accuracy of estimated breeding value estimation and selection progress. A DNA par‐ entage verification panel was created, using 14 microsatellite markers with a combined prob‐ ability of exclusion of 99.7% [31]. The impact of DNA‐based parentage verification on EBV accuracies and ranking of sires were evaluated a few years later [32]. It was shown that correct allocation of parentage had a significant effect on EBV estimation and ranking of sires, espe‐ cially for growth traits. DNA‐based parentage verification enhanced selection accuracy and would result in faster genetic progress.

Phenotypic recording and EBV selection on mohair and growth traits were relatively success‐ ful during the 1980–1990s. However, intense selection pressure for increased mohair quality and yield resulted in small, unthrifty goats with high mortality rates. QTL identification stud‐ ies were performed to identify chromosomal segments associated with product and qual‐ ity traits of mohair [33] as well as preweaning growth [34]. Eighteen QTL for mohair traits (including fleece weight, fiber diameter, coefficient of variation of fiber diameter, comfort factor, spinning fineness and variation along the length of the fiber) were identified on 13 chromosomes [15]. In the study focusing on preweaning growth traits, four chromosomal regions of interest with an influence on birth weight were identified on CHI 4, 8, 18 and 27 and two candidate regions for weaning weight on CHI 16 and 19, respectively [34]. Although putative QTL were identified in both studies, the QTL explained limited phenotypic variation of the traits, which is one of the main restrictions of marker‐assisted selection. No MAS has yet been implemented in the SA Angora goat breed.

The first molecular study on SA meat goats was performed in 2004 when the genetic varia‐ tion of the three commercial breeds as well as three indigenous goat populations were inves‐ tigated using microsatellite markers [40]. A clear differentiation between the Kalahari Red and Boer goat breeds was observed, whereas the Savanna breed showed significant genetic similarity to the Boer goat. Limited differentiation was observed between the veld goat popu‐ lations, as was expected. Of all the breeds and populations, the Kalahari Red breed was the most clearly differentiated on a genetic level. The distinctiveness of the Kalahari Red breed was further investigated [41], also using microsatellite markers. Although it appeared that the breed was largely uniform, limited differences suggested local selection and adaptation. The clear genetic differentiation of the Kalahari Red breed was confirmed by a later study focusing on only commercial goat breeds [11]. A factorial correspondence analysis was performed with microsatellite data and the Kalahari Red goats clustered on their own, while the Boer goat and

The Development and Genetic Improvement of South African Goats

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31

The commercial Boer goat and Kalahari Red breeds, as well the Tankwa and two indigenous populations, were included in a study to characterize African goat populations using the Illumina Goat SNP50K genotyping array [42]. These South African breeds showed a higher level of variation when compared to other African populations. Preliminary results were reported by [43, 44] on the population structure and landscape genomics of indigenous goats using genome‐wide SNP data. The goat populations showed sufficient genetic diversity, and the Tankwa population was revealed as a distinct breed. Associations between the genomic variation of the goats and climatic conditions were limited to associations with longitude,

The genetic architecture of the three commercial meat breeds, the Tankwa and five distinct ecotypes (Nguni, Venda, Xhosa, Zulu and Tswana) were investigated by Ref. [45]. Ecotypes were found to have the highest levels of genetic diversity and low levels of inbreeding, proba‐ bly due to the lack of directional selection in communal systems. Most of the ecotypes showed some level of genetic relatedness with one another. The Tankwa breed was again identified as a unique genetic resource with low genetic diversity and high inbreeding levels, which can be

The Saanen, British Alpine and Toggenburg are the three breeds contributing to South Africa's small dairy goat industry. Most goat milk is processed and sold as goat's cheese; thus, the quality of the milk produced and specifically the casein content is of importance. Limited

To date, two studies have been performed to characterize casein in the SA goat breeds, one on κ‐casein [46] and another on αS2‐casein [47]. The first study investigated indig‐ enous, Boer and Saanen goats using restriction fragment length polymorphism (RFLP) and DNA sequencing. Two less favorable alleles (B' and H) were found exclusively in the meat goat populations, while the favorable B allele was fixated in the Saanen goats. In the latter study, αS2‐casein was genotyped in the three SA dairy breeds, as well as in some meat‐ type goats using DNA sequencing. Four alleles and 10 genotypes were observed across the

attributed to the small population size and geographical isolation of these animals.

Savanna populations tended to overlap.

**4.3. Dairy goats**

temperature and altitude using the spatial analyses method.

molecular research has been performed on these breeds.

The QTL identification study did however indicate that QTL associated with mohair pro‐ duction and quality were located on chromosomes where the KRT and KAP genes have previously been assigned to mainly CHI 1 and 5 [33]. Polymerase chain reaction (PCR) and sequencing technology were used to identify and characterize KAP 1.1, KAP 8.1 and KAP 13.3 in South African Angora, Boer and Angora x Boer goat populations. A total of 19 novel variants were identified in total, and in these, three genes were responsible for structure and quality of hair fibers. The predominant alleles differed between the various populations and together with high levels of observed heterozygosity hold promise for selection based on favorable allelic associations [35].

The development of a moderate‐density genotyping tool, the 50K SNP chip (Illumina Inc., San Diego, CA) [36], was a key milestone for molecular research in goats. Due to the fact that no fiber‐producing breeds were included in the development of this commercial chip, it was first validated in the SA Angora goat population [37]. Fortunately, the high level of polymorphism observed (88.1% of loci) and the sufficient observed heterozygosity levels in the population (0.365) made the bead chip suitable for application in this breed.

The 50K SNP chip was subsequently used to estimate genetic diversity in the SA Angora goat. Results indicated that sufficient genetic diversity still exists within this breed to allow suc‐ cessful selection strategies and genetic improvement [38]. A high proportion of SNP with low minor allele frequency (MAF) values suggested a high proportion of fixed alleles, which was in line with the high selection pressure on specific traits within this population. An linkage disequilibrium (LD) estimate (using the *r*<sup>2</sup> measure) of 0.15 was calculated, which implied that a denser SNP genotyping array would be necessary before genomic selection (GS) could be considered for the SA Angora.

The SA Angora goat was included in a study to analyze the genetic variability of Angora goats from three distinct geographical locations (South Africa, France and Argentina) in order to assess the influence of genetic and geographical isolation [39]. The fixation index (FST) indi‐ cated three distinct subpopulations, with intrapopulation values (0.12) corresponding to those normally observed between breeds. An effective population size (Ne) of 93 was estimated for the SA Angora goat, 100 generations ago, and is currently probably even lower. The distinctive‐ ness of the South African population indicated strict directional selection which has resulted in a well‐defined cluster. The high diversity between populations could be useful when exchang‐ ing genetic material to improve certain unfavorable characteristics of specific populations.

#### **4.2. Commercial and indigenous meat goats**

Both commercial and indigenous goats have been included in studies where DNA mark‐ ers have been applied to gain insight into their genetic diversity and population structure. However, significantly, less research in terms of molecular studies has been performed on meat goats than on the Angora goat breed.

The first molecular study on SA meat goats was performed in 2004 when the genetic varia‐ tion of the three commercial breeds as well as three indigenous goat populations were inves‐ tigated using microsatellite markers [40]. A clear differentiation between the Kalahari Red and Boer goat breeds was observed, whereas the Savanna breed showed significant genetic similarity to the Boer goat. Limited differentiation was observed between the veld goat popu‐ lations, as was expected. Of all the breeds and populations, the Kalahari Red breed was the most clearly differentiated on a genetic level. The distinctiveness of the Kalahari Red breed was further investigated [41], also using microsatellite markers. Although it appeared that the breed was largely uniform, limited differences suggested local selection and adaptation. The clear genetic differentiation of the Kalahari Red breed was confirmed by a later study focusing on only commercial goat breeds [11]. A factorial correspondence analysis was performed with microsatellite data and the Kalahari Red goats clustered on their own, while the Boer goat and Savanna populations tended to overlap.

The commercial Boer goat and Kalahari Red breeds, as well the Tankwa and two indigenous populations, were included in a study to characterize African goat populations using the Illumina Goat SNP50K genotyping array [42]. These South African breeds showed a higher level of variation when compared to other African populations. Preliminary results were reported by [43, 44] on the population structure and landscape genomics of indigenous goats using genome‐wide SNP data. The goat populations showed sufficient genetic diversity, and the Tankwa population was revealed as a distinct breed. Associations between the genomic variation of the goats and climatic conditions were limited to associations with longitude, temperature and altitude using the spatial analyses method.

The genetic architecture of the three commercial meat breeds, the Tankwa and five distinct ecotypes (Nguni, Venda, Xhosa, Zulu and Tswana) were investigated by Ref. [45]. Ecotypes were found to have the highest levels of genetic diversity and low levels of inbreeding, proba‐ bly due to the lack of directional selection in communal systems. Most of the ecotypes showed some level of genetic relatedness with one another. The Tankwa breed was again identified as a unique genetic resource with low genetic diversity and high inbreeding levels, which can be attributed to the small population size and geographical isolation of these animals.

#### **4.3. Dairy goats**

and two candidate regions for weaning weight on CHI 16 and 19, respectively [34]. Although putative QTL were identified in both studies, the QTL explained limited phenotypic variation of the traits, which is one of the main restrictions of marker‐assisted selection. No MAS has

The QTL identification study did however indicate that QTL associated with mohair pro‐ duction and quality were located on chromosomes where the KRT and KAP genes have previously been assigned to mainly CHI 1 and 5 [33]. Polymerase chain reaction (PCR) and sequencing technology were used to identify and characterize KAP 1.1, KAP 8.1 and KAP 13.3 in South African Angora, Boer and Angora x Boer goat populations. A total of 19 novel variants were identified in total, and in these, three genes were responsible for structure and quality of hair fibers. The predominant alleles differed between the various populations and together with high levels of observed heterozygosity hold promise for selection based on

The development of a moderate‐density genotyping tool, the 50K SNP chip (Illumina Inc., San Diego, CA) [36], was a key milestone for molecular research in goats. Due to the fact that no fiber‐producing breeds were included in the development of this commercial chip, it was first validated in the SA Angora goat population [37]. Fortunately, the high level of polymorphism observed (88.1% of loci) and the sufficient observed heterozygosity levels in the population

The 50K SNP chip was subsequently used to estimate genetic diversity in the SA Angora goat. Results indicated that sufficient genetic diversity still exists within this breed to allow suc‐ cessful selection strategies and genetic improvement [38]. A high proportion of SNP with low minor allele frequency (MAF) values suggested a high proportion of fixed alleles, which was in line with the high selection pressure on specific traits within this population. An linkage

a denser SNP genotyping array would be necessary before genomic selection (GS) could be

The SA Angora goat was included in a study to analyze the genetic variability of Angora goats from three distinct geographical locations (South Africa, France and Argentina) in order to assess the influence of genetic and geographical isolation [39]. The fixation index (FST) indi‐ cated three distinct subpopulations, with intrapopulation values (0.12) corresponding to those normally observed between breeds. An effective population size (Ne) of 93 was estimated for the SA Angora goat, 100 generations ago, and is currently probably even lower. The distinctive‐ ness of the South African population indicated strict directional selection which has resulted in a well‐defined cluster. The high diversity between populations could be useful when exchang‐ ing genetic material to improve certain unfavorable characteristics of specific populations.

Both commercial and indigenous goats have been included in studies where DNA mark‐ ers have been applied to gain insight into their genetic diversity and population structure. However, significantly, less research in terms of molecular studies has been performed on

measure) of 0.15 was calculated, which implied that

yet been implemented in the SA Angora goat breed.

(0.365) made the bead chip suitable for application in this breed.

favorable allelic associations [35].

30 Goat Science

disequilibrium (LD) estimate (using the *r*<sup>2</sup>

**4.2. Commercial and indigenous meat goats**

meat goats than on the Angora goat breed.

considered for the SA Angora.

The Saanen, British Alpine and Toggenburg are the three breeds contributing to South Africa's small dairy goat industry. Most goat milk is processed and sold as goat's cheese; thus, the quality of the milk produced and specifically the casein content is of importance. Limited molecular research has been performed on these breeds.

To date, two studies have been performed to characterize casein in the SA goat breeds, one on κ‐casein [46] and another on αS2‐casein [47]. The first study investigated indig‐ enous, Boer and Saanen goats using restriction fragment length polymorphism (RFLP) and DNA sequencing. Two less favorable alleles (B' and H) were found exclusively in the meat goat populations, while the favorable B allele was fixated in the Saanen goats. In the latter study, αS2‐casein was genotyped in the three SA dairy breeds, as well as in some meat‐ type goats using DNA sequencing. Four alleles and 10 genotypes were observed across the populations, with the A allele being the most frequent in all the breeds. Limited gene‐spe‐ cific selection opportunities are possible based on these results.

[2] DAFF. National Livestock Statistics. Newsletter. Directorate: Statistics and Economic

The Development and Genetic Improvement of South African Goats

http://dx.doi.org/10.5772/intechopen.70065

33

[3] Maree C, Plug I. Origin of Southern African livestock and their potential role in the industry. In: Casey M, editor. Livestock Production Systems. Pretoria, South Africa:

[4] Campbell QP. The origin and description of Southern Africa's indigenous goats. South

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The genetic diversity of SA dairy goats was investigated using a panel of 25 microsatellite mark‐ ers [48]. High levels of diversity were estimated in all three breeds, with heterozygosity values exceeding 60%. Limited inbreeding was observed within the populations. The genetic differ‐ entiation between the dairy breeds was very low, as could be expected within one production type. An admixture group of animals was identified, suggesting that inadvertent crossbreed‐ ing between purebred animals was taking place. The SA Milch Goat Breeders' Society allows the registration of goats with unknown pedigree, based on a physical inspection (mainly color pattern and functional efficiency). It has however been clearly demonstrated that coat color is not a definitive way of assigning breed status. Some dairy goats were included in the SNP‐ based genetic diversity study by Ref. [38]. The results corresponded with that of the previous study, with relatively high gene diversity estimates within the breeds. A 30% co‐ancestry was calculated between the breeds, supporting the previous findings [48] regarding admixture.

### **5. Conclusion**

The various goat breeds and populations in South Africa serve a number of purposes rang‐ ing from important economic contributions to the commercial livestock production sector, to the improvement of livelihoods and food security in rural communities. Genetic progress can primarily be attributed selection following a quantitative approach, with a focus on fer‐ tility, growth and some breed‐specific production traits such as fiber yield. Future research and selection for genetic improvement will most likely be targeted toward molecular‐based approaches. Molecular research has shown that most SA goat breeds have sufficient genetic diversity to be exploited in selection programs. Specific projects are targeted toward the iden‐ tification of genes associated with traits of economic importance, managing inbreeding levels and sustainable conservation and utilization of scarce genotypes.

## **Author details**

Carina Visser\* and Este van Marle‐Köster

\*Address all correspondence to: carina.visser@up.ac.za

Department of Animal and Wildlife Sciences, University of Pretoria, South Africa

## **References**

[1] Mohlatlole RP, Dzomba EF, Muchadeyi FC. Addressing production challenges in goat production systems of South Africa: The genomics approach. Small Ruminant Research. 2015;**131**:43‐49

[2] DAFF. National Livestock Statistics. Newsletter. Directorate: Statistics and Economic Analysis, Pretoria, South Africa; 2016

populations, with the A allele being the most frequent in all the breeds. Limited gene‐spe‐

The genetic diversity of SA dairy goats was investigated using a panel of 25 microsatellite mark‐ ers [48]. High levels of diversity were estimated in all three breeds, with heterozygosity values exceeding 60%. Limited inbreeding was observed within the populations. The genetic differ‐ entiation between the dairy breeds was very low, as could be expected within one production type. An admixture group of animals was identified, suggesting that inadvertent crossbreed‐ ing between purebred animals was taking place. The SA Milch Goat Breeders' Society allows the registration of goats with unknown pedigree, based on a physical inspection (mainly color pattern and functional efficiency). It has however been clearly demonstrated that coat color is not a definitive way of assigning breed status. Some dairy goats were included in the SNP‐ based genetic diversity study by Ref. [38]. The results corresponded with that of the previous study, with relatively high gene diversity estimates within the breeds. A 30% co‐ancestry was calculated between the breeds, supporting the previous findings [48] regarding admixture.

The various goat breeds and populations in South Africa serve a number of purposes rang‐ ing from important economic contributions to the commercial livestock production sector, to the improvement of livelihoods and food security in rural communities. Genetic progress can primarily be attributed selection following a quantitative approach, with a focus on fer‐ tility, growth and some breed‐specific production traits such as fiber yield. Future research and selection for genetic improvement will most likely be targeted toward molecular‐based approaches. Molecular research has shown that most SA goat breeds have sufficient genetic diversity to be exploited in selection programs. Specific projects are targeted toward the iden‐ tification of genes associated with traits of economic importance, managing inbreeding levels

cific selection opportunities are possible based on these results.

and sustainable conservation and utilization of scarce genotypes.

Department of Animal and Wildlife Sciences, University of Pretoria, South Africa

[1] Mohlatlole RP, Dzomba EF, Muchadeyi FC. Addressing production challenges in goat production systems of South Africa: The genomics approach. Small Ruminant Research.

**5. Conclusion**

32 Goat Science

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**Section 2**

**Nutrition**


**Section 2**
