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

Basiese oorsig van vee-genomika

Stoettelers, produsente en veekundiges word deesdae links en regs met die term ‘genomika’ gekonfronteer. Terme soos dié word egter nie aldag goed verstaan nie en dikwels in die verkeerde konteks gebruik. In hierdie artikel verduidelik ek graag hierdie vakwoord en gee ’n bietjie agtergrond oor die algemene beginsels van vee-genomika.http://www.veeplaas.co.zaam2022Animal and Wildlife Science

Ouerskapbepaling deur DNS-toetsing

In Suid-Afrika is vleisbeesboerdery dikwels ekstensief van aard. Diere word oor groot oppervlakareas aangetref en dit bemoeilik akkurate waarneming en rekordhouding van parings. In kommersiële kuddes waar groep- en/of kuddeparings gedoen word en minder intense bestuursbeginsels somtyds toegepas word, is onbekende of verkeerde vaderskaptoekenning 'n groot probleem. Selfs in stoetboerdery, waar enkelparings en kunsmatige inseminasie (KI) algemeen toegepas word, word daar dikwels foute gemaak met die aantekening van veral vaderskap van nuwe kalfieshttp://reference.sabinet.co.za/sa_epublication/vp_stud?am201

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

Strategies for the genetic improvement of South African Angora goats

Selection of Angora goats over the past decades has focused on traits related to fitness, body weight and fiber production. Research for genetic improvement of the Angora has been based on quantitative selection and more recently molecular technology has been applied. Although considerable progress has been made at increasing fine mohair production, the inability of Angora goats to survive sub-optimum conditions has become a concern. Selection emphasis on fibre production resulted in unthrifty animals and the South African (SA) Angora industry is still hampered by the loss of young goats. DNA marker information assists conventional selection by increasing selection accuracy, improving the rate of genetic improvement and leading to a better understanding of the physiological background of traits. The genetic diversity of the SA Angora goat breed was estimated and an improved linkage map was recently developed. The extensive production systems in South Africa pose a challenge for pedigree integrity, and a microsatellite panel was constructed for parentage verification. Selection for quantitative trait loci (QTL) will lead to increased genetic progress and offers the opportunity to improve understanding of and exploit phenotypic variation. Putative QTL associated with fleece and growth traits have been identified in the South African Angora goat population. The current goat SNP chip does not include any fibre-producing goat breed, and this chip is currently being verified in the SA Angora goat population, in conjunction with the sequencing of certain keratin genes.http://www.elsevier.com/locate/smallrumreshb201

Smallholder Goat Production in Southern Africa: A Review

Goats play a crucial role in improved livelihoods and food security in Africa. Indigenous and locally developed types exhibit a wide range of phenotypic diversity, but are commonly well adapted to the harsh environment in which they need to survive and produce. They have various functions in communities in developing countries, from providing food security to being a liquid form of cash and playing a role in ceremonial occasions. The Southern African goat population exceeds 35 million animals, most of which are kept in small-scale traditional production systems in communal areas. These traditional production systems are characterised by informal, lowly-skilled labour, small numbers of animals and limited resources. Most goats are part of mixed crop-livestock systems, where different livestock species and crop farming compliment one another. The productivity and offtake from these animals are relatively low. Some goats form part of agropastoral production systems, with marginally higher management and resource inputs. Both of these systems are dependent on a high degree of variability where the keepers/farmers can exploit various resources as and when necessary. Goats possess a range of adaptive mechanisms that enable them to deal with harsh and challenging environments, making them the ideal species for use in these production systems. This chapter aims to provide background information on the current smallholder management practices of goat keepers in Southern Africa

Parentage verification of South African Angora goats, using microsatellite markers

South African Angora goats are farmed under extensive production systems in relatively large herds. As a result, breeders make use of group and flock-mating systems that limit accurate parentage recording and selection efficiency. In this study the aim was to refine a panel of microsatellite markers suitable for parentage verification in South African Angora goats. The markers were first evaluated based on the number of alleles, allele frequency, PIC, HE, HO and individual exclusion probability, and secondly as part of a panel. Eighteen markers were tested in 192 South African Angora goats representing different family structures with known and unknown parent information. The final set of microsatellite markers, with the strongest exclusion and the least number of microsatellite markers, consisted of 14 microsatellite markers namely BM1258, BM1329, BM1818, BM7160, CSRD247, HSC, INRA63, INRABERN192, MCM527, OarFCB48, SRCRSP5, SRCRSP8, SRCRSP9 and SRCRSP24. This panel had a combined first-parent exclusion probability of 99.7% and it was possible to perform parental identification in a test family.http://www.sasas.co.zanf201

Comparative performance of dairy cows in low-input smallholder and high-input production systems in South Africa

The aim of this study was to benchmark the performance of dairy cows in the low-input smallholder system against their counterparts in the high-input system, in South Africa. Data comprised of cow performance records from the national dairy recording scheme. Performance measures included production (305-day yields of milk, fat, and protein), lactation length, somatic cell count (SCC), and reproductive traits, represented by age at first calving (AFC) and calving interval (CI). Least squares means of each trait were compared between the two systems, and lactation curves for production traits and SCC were plotted for each production system. Mean yields of milk, fat, and protein were significantly (P < 0.05) lower in the smallholder (4097 ± 165, 174 ± 5.1, and 141 ± 4.5 respectively) compared to the high-input system (6921 ± 141, 298 ± 4.7, and 245 ± 4.1 respectively). Mean lactation length was significantly (P < 0.05) shorter for the smallholder (308 ± 15.1) than the high-input system (346 ± 12.8). Log-transformed somatic cell count (SCS) was, however, significantly (P < 0.05) higher in the smallholder (2.41 ± 0.01) relative to the high-input system (2.27 ± 0.01). Cows in high-input herds showed typical lactation curves, in contrast to the flat and low peaking curves obtained for the smallholder system. Cows on smallholder herds had their first calving significantly (P < 0.05) older (30 ± 0.5) than those in the high-input system (27 ± 0.5). There was, however, no significant difference (P < 0.05) in CI between the two systems. These results highlight large room for improvement of dairy cow performance in the smallholder system and could assist in decision-making aimed at improving the productivity of the South African dairy industry.The University of Pretoria and the South African, Agricultural Research Council-Animal Production Institute.http://link.springer.com/journal/112502019-10-01hj2018Animal and Wildlife Science

Genetic diversity and population structure of three native cattle populations in Mozambique

In the present work, the population diversity and structure of three populations of native Mozambican cattle were studied, to develop knowledge that is required for sound conservation and genetic improvement programs of these genetic resources. A total of 228 animals (Landim, Angone, and Tete) were genotyped using the International Dairy and Beef version three (IDBV3) SNP BeadChip array. Population parameters varied within a limited scope, with the average minor allele frequency (MAF) ranging from 0.228 ± 0.154 in the Angone to 0.245 ± 0.145 in the Tete population, while estimates of expected heterozygosities varied from 0.304 ± 0.166 in the Angone to 0.329 ± 0.148 in the Tete population. Low positive (0.065 ± 0.109) inbreeding rates were detected in the three cattle groups. Population structure and admixture analyses indicated low genetic differentiation and various degrees of admixture among the populations. The effective population size has decreased over time and at 12 generations ago ranged between 349 (Tete) and 929 (Landim). The average linkage disequilibrium (LD) of the studied populations ranged from 0.400 ± 0.213 (Tete) to 0.434 ± 0.232 (Landim). The findings of this study will be valuable for formulating management and conservation strategies for indigenous Mozambican cattle populations.The Ministry of Science, Technology, and Higher Education of Mozambique.http://link.springer.com/journal/11250hj2022Animal and Wildlife Science

Genetic diversity of South African dairy goats for genetic management and improvement

The dairy goatindustry is a small, butimportant role player in the South African agricultural sector. The limited number of animals representing the three main breeds (Saanen, British Alpine and Toggenburg) has raised concerns over the genetic diversity of these animals and the impact on their genetic management. In this study, 240 dairy goats representing three breeds were genotyped with 25 microsatellite markers. Sufficientlevels of genetic diversity were observed in all the breeds, with observed heterozygosity values exceeding 60%. A slight population differentiation was indicated by the low FST values across and within the populations. This was confirmed by the AMOVA analyses with most of the variation shown within populations (91.7%). Negative FIS values in the three breeds indicated limited inbreeding. Population structure analyses revealed six distinct groups, with the Saanen population clustering into three sub-groups. The Toggenburg and British Alpine breeds formed their own separate cluster, with a last cluster formed by animals from all three pure-bred populations, indicating high levels of admixture. These results caution farmers against uncontrolled crossbreeding practices and recommend routine evaluation of genetic diversity.This work is based on the research supported in part by a number of grants from the National Research Foundation of South Africa (UID: 78566 (NRF RISP grant for the ABI3500)).http://www.elsevier.com/locate/smallrumreshb2017Animal and Wildlife Science