Goats were amongst the first livestock to be domesticated more than 10,000 years ago for their meat, milk, skin, and fiber. They were introduced to Southern Africa by migrating nations from Central Africa to the south. Due to local adaptation to the different agro-ecological zones and selection, indigenous goats are identified as ecotypes within the indigenous veld goat breed. Their ability to thrive in a resource-limited production system and in challenging environmental conditions makes them valuable animal resources for small-scale and emerging farmers. They play important roles in household agriculture and cultural activities as well as in poverty alleviation. Studies have described the phenotypic and genetic variations in indigenous goats, targeting the major goat-producing regions and the breeds of South Africa. In turn, information is restricted to certain breeds and regions, and the experimental design is often not adequate to inform the conservation status and priorities in changing environments. Advances in genomics technologies have availed more opportunities for the assessment of the biodiversity, demographic histories, and detection regions associated with local adaptation. These technologies are essential for breeding and conservation strategies for sustainable production for food security. This review focuses on the status of indigenous goats in South Africa and the application of genomics technologies for characterization, with emphasis on prioritization for conservation and sustainable utilization.
Selection pressures found in the prevailing production environments have shaped the genetic structure of indigenous chickens we see today. Indigenous chickens, raised in villages, provide essential genetic resources and income for poverty alleviation by providing affordable protein. However, they are threatened by predators, emerging diseases, and market demand for ideal breeds and fast production which causes loss of their valuable traits. The lack of knowledge about genetic diversity and genetic mechanisms underlying adaptive variants may compromise the goal of conserving indigenous chicken breeds. The main insights of the study are that indigenous chickens are highly diversified, and environmental factors play a key role in enabling chicken adaptation and distribution. Genomic and spatial technologies have made it possible to explore the genetic structure and fully comprehend the mechanism underlying the local adaptation of indigenous chickens. These technologies can aid in creating programs that enhance productivity and promote climate-resilient breeds. This review explores the impact of natural selection on indigenous chicken, genetic diversity, population size, and the advancement of technologies in understanding local adaptation drivers. In conclusion, this review highlights the importance of studying the habitats and how this will guide in conserving local breeds in their intended production environment.
Genome-wide assessments of the genetic landscape of Farm Animal Genetic Resources (FAnGR) are key to developing sustainable breed improvements. Understanding the FAnGR adaptation to different environments and supporting their conservation programs from community initiative to national policymakers is very important. The objective of the study was to investigate the genetic diversity and population structure of communal indigenous goat populations from four provinces of South Africa. Communal indigenous goat populations from the Free State (FS) (n = 24), Gauteng (GP) (n = 28), Limpopo (LP) (n = 30), and North West (NW) (n = 35) provinces were genotyped using the Illumina Goats SNP50 BeadChip. An Illumina Goats SNP50 BeadChip data from commercial meat-type breeds: Boer (n = 33), Kalahari Red (n = 40), and Savanna (n = 31) was used in this study as reference populations. The Ho revealed that the genetic diversity of a population ranged between 0.39 ± 0.11 Ho in LP to 0.42 ± 0.09 Ho in NW. Analysis of molecular variance revealed variations of 3.39% (p < 0.0001) and 90.64% among and within populations, respectively. The first two Principal Component Analyses (PCAs) revealed a unique Limpopo population separated from GP, FS, and NW communal indigenous goat populations with high levels of admixture with commercial goat populations. There were unique populations of Kalahari and Savanna that were observed and admixed individuals. Marker FST (Limpopo versus commercial goat populations) revealed 442 outlier single nucleotide polymorphisms (SNPs) across all chromosomes, and the SNP with the highest FST value (FST = 0.72; chromosome 8) was located on the UHRF2 gene. Population differentiation tests (PCAdapt) revealed PC2 as optimal and five outlier SNPs were detected on chromosomes 10, 15, 20, and 21. The study revealed that the SNPs identified by the first two principal components show high FST values in LP communal goat populations and allowed us to identify candidate genes which can be used in the development of breed selection programs to improve this unique LP population and other communal goat population of FS, GP, and NW, and find genetic factors contributing to the adaptation to harsh environments. Effective management and utilization of South African communal indigenous goat populations is important, and effort should be made to maintain unique genetic resources for conservation.
Carcass quality includes a battery of essential economic meat traits that play a significant role in influencing farmer breed preferences. A preliminary study was undertaken to investigate the carcass quality and the associated genomic regions in a small nucleus of animals that are representative of South African goat genetic resources. Samples of the South African Boer (n = 14), Northern Cape Speckled (n = 14), Eastern Cape Xhosa Lob ear (n = 12), Nguni/Mbuzi (n = 13), and Village (n = 20) were genotyped using the Illumina goat SNP50K and were phenotyped for carcass quality traits. SA Boer goats had heavier warm and cold carcass weights (17.2 ± 2.3 kg and 16.3 ± 2.3 kg). Pella village goats raised under an intensive system had significantly (p < 0.05) heavier warm and cold carcass weights (9.9 ± 1.1 kg and 9.2 ± 1.2 kg) compared to the village goats that are raised extensively (9.1 ± 2.0 kg and 8.4 ± 1.9). A total of 40 SNPs located on chromosomes 6, 10, 12, 13, 19, and 21 were significantly associated with carcass traits at (−log10 [p < 0.05]). Candidate genes that were associated with carcass characteristics (GADD45G, IGF2R, GAS1, VAV3, CAPN8, CAPN7, CAPN2, GHSR, COLQ, MRAS, and POU1F1) were also observed. Results from this study will inform larger future studies that will ultimately find use in breed improvement programs.
Semen quality plays a crucial role in the successful implementation of breeding programs, especially where artificial insemination (AI) is practiced. Bulls with good semen traits have good fertility and can produce a volume of high semen per ejaculation. The aim of this review is to use an information approach to highlight candidate genes and their relation to bull semen production traits. The use of genome-wide association studies (GWAS) has been demonstrated to be successful in identifying genomic regions and individual variations associated with production traits. Studies have reported over 40 genes associated with semen traits using Illumina BeadChip single-nucleotide polymorphism (SNPs).