The Development and Genetic Improvement of South African Goats

South Africa has a thriving goat industry, consisting of fiber, meat and dairy‐producing goat breeds. These animals play an important role in terms of food security, socioeconomic welfare and cultural well‐being. The South African goat industry is differentiated into a formal, commercial market with niche products such as mohair, chevon and goat’s cheeses versus the informal, mainly meat‐producing sector serving communal and smallholder farmers. Exotic and locally improved breeds, i.e., Angora, Saanen and Boer goats mainly serve the commercial industries, whereas the unimproved veld goat populations are well adapted in the resource‐poor environments. Genetic improvement has historically been limited to the commercial breeds, but poor participation in animal recording and improvement schemes have resulted in slow genetic progress, with the exception of the Angora goat. Molecular research has opened up new possibilities for genetic characterization, preservation and utilization of the unique genetic resources retained by these animals

Genomics for the advancement of livestock production: A South African perspective

Most of the growth of human populations worldwide will be in developing countries, including South Africa. Natural resources are under immense pressure and animal scientists are faced with the challenges for increased efficiency and long-term sustainability of livestock production. Since the completion of the Human Genome Project, animal genomes have been mapped with genomics, enabling new opportunities for application in farm animal species. The use of microsatellite markers has made significant contributions to the insight in genetic characterisation of indigenous and local developed breeds in most farm species in South Africa and Africa. The single nucleotide polymorphic (SNP) marker discovery and development of commercial SNP arrays made genomic selection possible and genomic enhanced breeding values (GEBVs) are used widely in the First World. In South Africa, genomic programmes for beef and dairy cattle were established in 2015 and 2016, with the focus on building training populations for genomic selection. The SA Bonsmara breed was the first to receive GEBV. The availability of hard-to-measure phenotypes is limited, and these are the traits that hold the most potential for genomic selection and answering to the challenges of methane (CH4) emissions and higher efficiency. Genome editing, which involves zinc-finger nucleases (ZFNs), transcription-activators such as endonucleases (TALEN) and RNA-programmable genome editor (CRISPR/CAS9), includes the most recent technology for application in precision genetics. Welfare and ethical concerns will be an important consideration in the acceptability of genome editing to consumers. Applications that benefit the animals are more acceptable to the public. The use of genome editing to produce polled cattle is one of the first applications with a direct welfare impact as it nullifies the need for painful dehorning. In this paper, genomic technology is reviewed with the focus on the most recent research trends and commercial application of genomics towards the genetic improvement of livestock with specific reference to South Africa.Keywords: Genetic diversity, genomic selection, gene editing, microsatellite markers, SN

Genetic diversity and population structure of locally adapted South African chicken lines: Implications for conservation

In this study microsatellite markers were applied to investigate the genetic diversity and population structure of the six local chicken lines kept in the “Fowls for Africa” program, for better clarification of parameters for breed differentiation and genetic conservation of this valuable resource. The lines included the Black Australorp, Potchefstroom Koekoek, New Hampshire, Ovambo, Lebova- Venda and a Naked Neck line. Unbiased estimates for heterozygosity ranged from 50% in the Potchefstroom Koekoek to as high as 65% in the Naked Neck chickens. FIS values varied from as low as 0.16 for the Black Australorp line to as high as 0.35 for the Ovambo chickens. The FST values indicated moderate to high genetic differentiation between the Naked Neck and New Hampshire (0.11); Ovambo and Naked Neck lines (0.12), and Naked Neck and Lebowa- Venda (0.14). A total of 13% of the total genetic variation observed was between the chicken lines and 87% within the lines, supporting moderate genetic differentiation. Population structure was assessed using STRUCTURE where the Black Australorp was genetically best defined. Although six clusters for the different populations could be distinguished, the other lines were not as clearly defined, with individual birds tending to share more than one cluster. Results support a broad classification of these lines and further investigation of unique alleles is recommended for conservation of the lines within the program. Keywords: Native chicken, microsatellite markers, genetic variation, population structure, South Africa South African Journal of Animal Science Vol. 38 (4) 2008: pp. 271-28

Test-day models for South African dairy cattle for participation in international evaluations

Variance components and breeding values of production traits and somatic cell score of South African Guernsey, Ayrshire, Holstein and Jersey breeds have been estimated using a multi-lactation repeatability test-day model, including tests of the first three lactations as repeated measures and fitting the permanent environmental effect across lactations. Multitrait evaluations were done for the production traits (milk, butterfat and protein) and single trait evaluations for somatic cell score. Heritability estimates were comparable with yield and somatic cell score estimates obtained by test-day models from other countries (17-24% for milk yield; 10-13% for butterfat yield; 14-19% for protein yield and 6-8% for somatic cell score). Proofs of qualifying sires were sent to the International Bull Evaluation Service (INTERBULL) for participation in the March 2005 test runs. Genetic correlations between South Africa and other participating countries, estimated by INTERBULL, compared well with those amongst the other participating countries. Trend validation tests were successful using this methodology for all traits and breeds except for somatic cell score of the Guernsey breed, due to insufficient data for this trait. South Africa can now participate in routine INTERBULL evaluations to obtain Multiple Across Country Evaluation (MACE) breeding values, using this methodology. South African Journal of Animal Science Vol. 36(1) 2006: 58-7

Genetic Improvement in South African Livestock: Can Genomics Bridge the Gap Between the Developed and Developing Sectors?

South Africa (SA) holds a unique position on the African continent with a rich diversity in terms of available livestock resources, vegetation, climatic regions and cultures. The livestock sector has been characterized by a dual system of a highly developed commercial sector using modern technology vs. a developing sector including emerging and smallholder farmers. Emerging farmers typically aim to join the commercial sector, but lag behind with regard to the use of modern genetic technologies, while smallholder farmers use traditional practices aimed at subsistence. Several factors influence potential application of genomics by the livestock industries, which include available research funding, socio-economic constraints and extension services. State funded Beef and Dairy genomic programs have been established with the aim of building reference populations for genomic selection with most of the potential beneficiaries in the well-developed commercial sector. The structure of the beef, dairy and small stock industries is fragmented and the outcomes of selection strategies are not perceived as an advantage by the processing industry or the consumer. The indigenous and local composites represent approximately 40% of the total beef and sheep populations and present valuable genetic resources. Genomic research has mostly provided insight on genetic biodiversity of these resources, with limited attention to novel phenotypes associated with adaptation or disease tolerance. Genetic improvement of livestock through genomic technology needs to address the role of adapted breeds in challenging environments, increasing reproductive and growth efficiency. National animal recording schemes contributed significantly to progress in the developed sector with regard to genetic evaluations and estimated breeding values (EBV) as a selection tool over the past three decades. The challenge remains on moving the focus to novel traits for increasing efficiency and addressing welfare and environmental issues. Genetic research programs are required that will be directed to bridge the gap between the elite breeders and the developing livestock sector. The aim of this review was to provide a perspective on the dichotomy in the South African livestock sector arguing that a realistic approach to the use of genomics in beef, dairy and small stock is required to ensure sustainable long term genetic progress

Comparison of breeding values and genetic trends for production traits estimated by a Lactation Model and a Fixed Regression Test-day Model

A comparison of breeding values and genetic trends of production traits from two models is made. One set of breeding values and trends was estimated by the September/October 2003 South African National Genetic Evaluation, using a Lactation Model (LM). The other set was obtained in the 2004 South African National Genetic Evaluation, using a Fixed Regression Test-day Model (TDM). This comparison is made for Ayrshire, Guernsey, Holstein and Jersey cows participating in the South African Dairy Animal Improvement Scheme. Specific differences between the two models were documented, with differences in statistical methodology and inclusion of test-day records of the first three parities in the TDM vs. only first lactation 305-day yields in the LM, as the main differences. Significant reranking of especially cows and unproven sires occurred between the models. Genetic trends of the TDM were not as steep as those from the LM, as the trait that was selected was first lactation yield, while the TDM trends reflect genetic progress over the first three parities. South African Journal of Animal Science Vol. 36(2) 2006: 71-7

Adjustment of heterogenous variances and a calving year effect in test-day models for national genetic evaluation of dairy cattle in South Africa

South Africa implemented test-day models for genetic evaluations of production traits, using a Fixed Regression Test-Day Model (FRTDM), which assumes equal variances of the response variable at different days in milk, the explanatory variable. Data at the beginning and at the end of lactation period, have higher variances than tests in the middle of the lactation. Furthermore, first lactations have lower mean and variances compared to second and third lactations. This is a deviation from the basic assumptions required for the application of repeatability models. A modification was therefore implemented to reduce the effect of deviating from this assumption. Test-day milk, butterfat and protein yield records of Jersey cows, participating in the South African Milk Recording Scheme, were therefore pre-adjusted such that the variances are on the same scale. Variance components estimated using the adjusted records were higher than using unadjusted records. Convergence of breeding value estimation is reached significantly faster when using adjusted data (± 4000 iterations) compared to unadjusted records (± 15 000 iterations). Although cow and bull rankings were not influenced much, significant changes in breeding values for individual animals and genetic trends of especially young animals, were found. South African Journal of Animal Science Vol. 36(3) 2006: 165-17

Genetic polymorphism of CSN1S2 in South African dairy goat populations

Alpha-s2 casein has a significant influence on protein content in goat milk, and the technological properties important for cheese processing. Specific alleles (A, B, C, E and F) of the alpha (α)s2-casein gene (CSN1S2) result in higher protein, casein and fat content, and improved coagulation properties, which are useful for improved cheese making. The aim of this study was to investigate the polymorphism and genetic variation of CSN1S2 in South African dairy goats, using DNA sequencing technology. Sixty dairy goats (20 Saanes, 20 British Alpine, and 20 Toggenburg) and 20 meat-type goats were sequenced with four primers to distinguish among the seven known alleles for αs2-casein. A total of four alleles (A, B, C and F) for CSN1S2 were observed among the dairy- and meat-type populations with ten genotypes across the populations. The A allele and the AA genotype were the most frequent across the populations, with the favourable AC genotype being the most frequent (0.300) in the Saanen population. Two unique genotypes were detected in the Toggenburg (BB and BF) and one in the meat-type goats (CF). The results indicate moderate genetic variation for αs2-casein in the South African goat populations (42.3–63.6%). Low positive FST values suggest limited inbreeding. This study confirmed the presence of favourable alleles in the South African goat populations, indicating room for genetic improvement using directional selection for favourable genotypes.Keywords: alpha-s2-casein, genetic variation, goat milk, protein content, Saane

A review of genomic selection - Implications for the South African beef and dairy cattle industries

The major advancements in molecular technology over the past decades led to the discovery of DNA-markers, sequencing and genome mapping of farm animal species. New avenues were created for identifying major genes, genetic defects, quantitative trait loci (QTL) and ultimately applying genomic selection (GS) in livestock. The identification of specific regions of interest that affect quantitative traits aimed to incorporate markers linked to QTL into breeding programs by using marker assisted selection (MAS). Most QTL explained only a small proportion of the genetic variation for a trait with limited impact on genetic improvement. Single nucleotide polymorphism (SNP) markers created the possibility to genotype cattle in a single assay with hundreds of thousands of SNPs, providing sufficient genomic information to incorporate into breeding value estimation. Genomic selection is based on the principle of associating many genetic markers with phenotypic performance. A large database of genotyped animals with relevant phenotypes pertinent to a production system is therefore required. South Africa has a long history of animal recording for dairy and beef cattle. The challenge for implementation of GS would be the establishment of breed-specific training populations. Training populations should be genotyped using a high density SNP panel, and the most appropriate genomic prediction algorithm determined. The suitability of commercially available genotyping platforms to South African populations should be established. The aim of this review is to provide an overview of the developments that occurred over the past two decades to lay the foundation for genomic selection with special reference to application in the South African beef and dairy cattle industry.Authors wish to thank the Red Meat Research and Development South Africa for their support.http://www.sasas.co.zaam201

The Tankwa Karoo National Park feral goat population:A unique genetic resource

The feral goats from Tankwa Karoo National Park in the Northern Cape, South Africa, constitute a potentially unique goat population, which dates back to the early 1900s, but is now at risk of extinction. A total of 66 feral goats from Tankwa Park and former Tankwa goats, now kept on a private farm were genotyped, using eight microsatellite markers. The data were compared with genotypic data of selected commercial breeds (Angora, Boer and Saanen dairy goats). Analysis of population structure using Bayesian and frequency-based methods suggests some uniqueness in the Tankwa populations. This uniqueness may reflect decades of random drift, but could also reflect alleles for adaptation to a harsh environment resulting from natural selection. These results are the first for the Tankwa goat and provide essential information for compiling a strategy for conservation and breeding of this genetic resource.http://www.sasas.co.za/hb201