Edgar Farai Dzomba

Domesticated sheep have adapted to contrasting and extreme environments and continue to play important roles in local community‐based economies throughout Africa. Here we review the Neolithic migrations of thin‐tailed sheep and the later introductions of fat‐tailed sheep into eastern Africa. According to contemporary pictorial evidence, the latter occurred in Egypt not before the Ptolemaic period (305–25 BCE). We further describe the more recent history of sheep in Egypt, the Maghreb, west and central Africa, central‐east Africa, and southern Africa. We also present a comprehensive molecular survey based on the analysis of 50 K SNP genotypes for 59 African breeds contributed by several laboratories. We propose that gene flow and import of fat‐tailed sheep have partially overwritten the diversity profile created by the initial migration. We found a genetic contrast between sheep north and south of the Sahara and a west–east contrast of thin‐ and fat‐tailed sheep. There is no close relationship between African and central and east Asian fat‐tailed breeds, whereas we observe within Africa only a modest effect of tail types on breed relationships.

South Africa boasts a diverse range of pig populations, encompassing intensively raised commercial breeds, as well as indigenous and village pigs reared under low-input production systems. The aim of this study was to investigate how natural and artificial selection have shaped the genomic landscape of South African pig populations sampled from different genetic backgrounds and production systems. For this purpose, the integrated haplotype score (iHS), as well as cross population extended haplotype homozygosity (XP-EHH) and Lewontin and Krakauer’s extension of the Fst statistic based on haplotype information (HapFLK) were utilised. Our results revealed several population-specific signatures of selection associated with the different production systems. The importance of natural selection in village populations was highlighted, as the majority of genomic regions under selection were identified in these populations. Regions under natural and artificial selection causing the distinct genetic footprints of these populations also allow for the identification of genes and pathways that may influence production and adaptation. In the context of intensively raised commercial pig breeds (Large White, Kolbroek, and Windsnyer), the identified regions included quantitative loci (QTLs) associated with economically important traits. For example, meat and carcass QTLs were prevalent in all the populations, showing the potential of village and indigenous populations’ ability to be managed and improved for such traits. Results of this study therefore increase our understanding of the intricate interplay between selection pressures, genomic adaptations, and desirable traits within South African pig populations.

In this study, we investigated how IBD patterns shared between individuals of the same breed could be informative of its admixture level, with the underlying assumption that the most admixed breeds, i.e. the least genetically isolated, should have a much more fragmented genome. We considered 111 goat breeds (i.e. 2501 individuals) and 156 sheep breeds (i.e. 3304 individuals) from Europe, Africa and Asia, for which beadchip SNP genotypes had been performed. We inferred the breed’s level of admixture from: (i) the proportion of the genome shared by breed’s members (i.e. “genetic integrity level” assessed from ADMIXTURE software analyses), and (ii) the “AV index” (calculated from Reynolds’ genetic distances), used as a proxy for the “genetic distinctiveness”. In both goat and sheep datasets, the statistical analyses (comparison of means, Spearman correlations, LM and GAM models) revealed that the most genetically isolated breeds, also showed IBD profiles made up of more shared IBD segments, which were also longer. These results pave the way for further research that could lead to the development of admixture indicators, based on the characterization of intra-breed shared IBD segments, particularly effective as they would be independent of the knowledge of the whole genetic landscape in which the breeds evolve. Finally, by highlighting the fragmentation experienced by the genomes subjected to crossbreeding carried out over the last few generations, the study reminds us of the need to preserve local breeds and the integrity of their adaptive architectures that have been shaped over the centuries.

Merino sheep are a breed of choice across the world, popularly kept for their wool and mutton value. They are often reared as a pure breed or used in crossbreeding and are a common component in synthetic breed development. This study evaluated genetic diversity, population structure, and breed divergence in 279 animals of Merino and Merino-based sheep breeds in South Africa using the Illumina Ovine SNP 50K BeadChip. The sheep breeds analysed included the three Merino-derived breeds of Dohne Merino (n = 50); Meatmaster (n = 47); and Afrino (n = 52) and five presumed ancestral populations of Merinos (Merino (n = 46); South African Merino (n = 10); and South African Mutton Merino (n = 8)); and the non-Merino founding breeds of Damara (n = 20); Ronderib Afrikaner (n = 17); and Nguni (n = 29). Highest genetic diversity values were observed in the Dohne Merino (DM), with H_o = 0.39 ± 0.01, followed by the Meatmaster and South African Merino (SAM), with H_o = 0.37 ± 0.03. The level of inbreeding ranged from 0.0 ± 0.02 (DM) to 0.27 ± 0.05 (Nguni). Analysis of molecular variance (AMOVA) showed high within-population variance (>80%) across all population categories. The first principal component (PC1) separated the Merino, South African Mutton Merino (SAMM), DM, and Afrino (AFR) from the Meatmaster, Damara, Nguni, and Ronderib Afrikaner (RDA). PC2 aligned each Merino-derived breed with its presumed ancestors and separated the SAMM from the Merino and SAM. The iHS analysis yielded selection sweeps across the AFR (12 sweeps), Meatmaster (four sweeps), and DM (29 sweeps). Hair/wool trait genes such as FGF12; metabolic genes of ICA1, NXPH1, and GPR171; and immune response genes of IL22, IL26, IFNAR1, and IL10RB were reported. Other genes include HMGA, which was observed as selection signatures in other populations; WNT5A, important in the development of the skeleton and mammary glands; ANTXR2, associated with adaptation to variation in climatic conditions; and BMP2, which has been reported as strongly selected in both fat-tailed and thin-tailed sheep. The DM vs. SAMM shared all six sweep regions on chromosomes 1, 10, and 11 with AFR vs. SAMM. Genes such as FGF12 on OAR 1:191.3–194.7 Mb and MAP2K4 on OAR 11:28.6–31.3 Mb were observed. The selection sweep on chromosome 10 region 28.6–30.3 Mb harbouring the RXFP2 for polledness was shared between the DM vs. Merino, the Meatmaster vs. Merino, and the Meatmaster vs. Nguni. The DM vs. Merino and the Meatmaster vs. Merino also shared an Rsb-based selection sweep on chromosome 1 region 268.5–269.9 Mb associated with the Calpain gene, CAPN7. The study demonstrated some genetic similarities between the Merino and Merino-derived breeds emanating from common founding populations and some divergence driven by breed-specific selection goals. Overall, information regarding the evolution of these composite breeds from their founding population will guide future breed improvement programs and management and conservation efforts.

The Nguni cattle of South Africa are a Sanga breed, characterized by many eco-types and research populations that have been established in an effort to conserve the diversity within the breed. The aim of this study was to investigate the overall genetic diversity as well as similarities and differences within and between two conservation herds of the South African Nguni Cattle. Mean LD (r²) estimates were 0.413 ± 0.219 for Bartlow Combine and 0.402 ± 0.209 for Kokstad. Genome-wide average LD (r²) decreased with increasing genetic marker distance for both populations from an average of 0.76 ± 0.28 and 0.77 ± 0.27 at 0–1 kb bin to 0.31 ± 0.13 and 0.32 ± 0.13 at 900–1000 kb bin in Bartlow Combine and Kokstad populations, respectively. Variation in LD levels across autosomes was observed in both populations. The results showed higher levels of LD than previously reported in Nguni field populations and other South African breeds, especially at shorter marker distances of less than 20 kb. A total number of 77,305 and 66,237 haplotype blocks covering a total of 1570.09 Mb (61.99% genome coverage) and 1367.42 Mb (53.96% genome coverage) were detected in Bartlow Combine and Kokstad populations, respectively. A total of 18,449 haploblocks were shared between the two populations while 58,856 and 47,788 haploblocks were unique to Bartlow Combine and Kokstad populations, respectively. Effective population size (N_e) results demonstrated a rapid decrease in N_e across generations for both Bartlow Combine and Kokstad conservation herds. Two complementary methods, integrated haplotype score (iHS) and Extend Haplotype Homozygosity Test (XP-EHH), were implemented in this study to detect the selection signatures in the two herds. A total of 553 and 166 selected regions were identified in Bartlow Combine and Kokstad populations, respectively. DAVID and GO terms analysis of the regions under selection reported genes/QTLs associated with fertility, carcass weight, coat colour, immune response, and eye area pigmentation. Some genes, such as HCAR1, GNAI1, PIK3R3, WNT3, RAB5A, BOLA-N (Class IB MHC Antigen QA-2-Related), BOLA (Class IB MHC Antigen QA-2-Related), and Rab-8B, etc., were found in regions under selection in this study. Overall, the study implied reduced genetic diversity in the two herds calling for corrective measures to maintain the diversity of the South African Nguni cattle. This study presented a comprehensive analysis of the genomic architecture of South African Nguni cattle populations, providing essential genetic information of utility in the management of conservation flocks.

Nguni cattle are a Sanga type breed with mixed B. taurus and B. indicus ancestry and proven resistance to ticks, diseases and other harsh conditions of the African geographical landscape. The multi-coloured Nguni coats have found a niche market in the leather industry leading to breeding objectives towards the promotion of such diversity. However, there is limited studies on the genomic architecture underlying the coat colour and patterns hampering any potential breeding and improvement of such trait. This study investigated the genetics of base coat colour, colour-sidedness and the white forehead stripe in Nguni cattle using coat colour phenotyped Nguni cattle and Illumina Bovine HD (770K) genotypes. Base coat colour phenotypes were categorised into eumelanin (n = 45) and pheomelanin (n = 19). Animals were categorised into either colour-sided (n = 46) or non-colour-sided (n = 94) and similarly into presence (n = 15) or absence (n = 67) of white forehead stripe. Genome-wide association tests were conducted using 622,103 quality controlled SNPs and the Efficient Mixed Model Association eXpedited method (EMMAX) implemented in Golden Helix SNP Variation Suite. The genome-wide association studies for base coat colour (eumelanin vs. pheomelanin) resulted into four indicative SNPs on BTA18 and a well-known gene, MC1R, was observed within 1 MB from the indicative SNPs (p < 0.00001) and found to play a role in the melanogenesis (core pathway for melanin production) and the MAPK signalling pathway. GWAS for colour-sidedness resulted in four indicative SNPs, none of which were in close proximity to the KIT candidate gene known for colour-sidedness. GWAS for the white forehead stripe resulted in 17 indicative SNPs on BTA6. Four genes MAPK10, EFNA5, PPP2R3C and PAK1 were found to be associated with the white forehead stripe and were part of the MAPK, adrenergic and Wnt signalling pathways that are synergistically associated with the synthesis of melanin. Overall, our results prove prior knowledge of the role of MC1R in base coat colours in cattle and suggested a different genetic mechanism for forehead stripe phenotypes in Nguni cattle.

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.

Background: Population history, production system and within-breed selection pressure impacts the genome architecture resulting in reduced genetic diversity and increased frequency of runs of homozygosity islands. This study tested the hypothesis that production systems geared towards specific traits of importance or natural or artificial selection pressures influenced the occurrence and distribution of runs of homozygosity (ROH) in the South African sheep population. The Illumina OvineSNP50 BeadChip was used to genotype 400 sheep belonging to 13 breeds from South Africa representing mutton, pelt and mutton and wool dual-purpose breeds, including indigenous non-descript breeds that are reared by smallholder farmers. To get more insight into the autozygosity and distribution of ROH islands of South African breeds relative to global populations, 623 genotypes of sheep from worldwide populations were included in the analysis. Runs of homozygosity were computed at cut-offs of 1–6 Mb, 6–12 Mb, 12–24 Mb, 24–48 Mb and > 48 Mb, using the R package detectRUNS. The Golden Helix SVS program was used to investigate the ROH islands.Results: A total of 121,399 ROH with mean number of ROH per animal per breed ranging from 800 (African White Dorper) to 15,097 (Australian Poll Dorset) were obtained. Analysis of the distribution of ROH according to their size showed that, for all breeds, the majority of the detected ROH were in the short (1–6 Mb) category (88.2%). Most animals had no ROH > 48 Mb. Of the South African breeds, the Nguni and the Blackhead Persian displayed high ROH based inbreeding (F_ROH) of 0.31 ± 0.05 and 0.31 ± 0.04, respectively. Highest incidence of common runs per SNP across breeds was observed on chromosome 10 with over 250 incidences of common ROHs. Mean proportion of SNPs per breed per ROH island ranged from 0.02 ± 0.15 (island ROH224 on chromosome 23) to 0.13 ± 0.29 (island ROH175 on chromosome 15). Seventeen (17) of the islands had SNPs observed in single populations (unique ROH islands). The MacArthur Merino (MCM) population had five unique ROH islands followed by Blackhead Persian and Nguni with three each whilst the South African Mutton Merino, SA Merino, White Vital Swakara, Karakul, Dorset Horn and Chinese Merino each had one unique ROH island. Genes within ROH islands were associated with predominantly metabolic and immune response traits and predomestic selection for traits such as presence or absence of horns.Conclusions: Overall, the frequency and patterns of distribution of ROH observed in this study corresponds to the breed history and implied selection pressures exposed to the sheep populations under study.

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 H_o revealed that the genetic diversity of a population ranged between 0.39 ± 0.11 H_o in LP to 0.42 ± 0.09 H_o 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 F_ST (Limpopo versus commercial goat populations) revealed 442 outlier single nucleotide polymorphisms (SNPs) across all chromosomes, and the SNP with the highest F_ST value (F_ST = 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 F_ST 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.

Summary: South Africa has a diverse array of phenotypically distinct and locally adapted sheep breeds that have been developed for different production systems ranging from mutton to wool and pelt, and some dual‐purpose and nondescript breeds kept by smallholder farmers. This study investigated genetic diversity, population genetic structure and divergence between South African sheep breeds in order to gain an insight into breed history and genomic architecture aligned to breeding goals and production systems. The Illumina OvineSNP50 BeadChip was used to genotype 400 sheep belonging to 14 breeds representing mutton, pelt and mutton and wool dual‐purpose breeds. Nguni sheep were included as a representative of indigenous nondescript breeds that are reared by smallholder farmers. Seeking a clearer understanding of the genetic diversity of South African breeds relative to global populations, 623 genotypes of sheep from worldwide populations were included in the analysis. These sheep breeds included six African, two Asian and eight European breeds. Across breeds, genetic diversity ranged from observed heterozygosity (H₀) = 0.26 ± 0.02 in Namaqua Afrikaner to H₀ = 0.38 ± 0.01 in Dohne Merino. The overall mean H₀ was 0.35 ± 0.04. The African and Asian populations were the most inbred populations with F_IS ranging from 0.17 ± 0.05 in Grey Swakara and Ronderib Afrikaner sheep to 0.34 ± 0.07 in the Namaqua Afrikaner. The South African Dohne Merino (F_IS = 0.03 ± 0.01), SA Merino (F_IS = 0.05 ± 0.04) and Afrino (F_IS = 0.09 ± 0.02) and other global Merino‐derived breeds were the least inbred. The first principal component explained 27.7% of the variation and separated the fat‐ and rump‐tailed sheep (i.e. Swakara, Nguni, Blackhead Persian, Ethiopian Menzi, Meatmaster) from the Merino and Merino‐derived breeds and the Dorset Horn. The second principal component separated the Merino and Merino‐derived breeds from the English breed of Dorset Horn. Overall, South African indigenous breeds clustered together with indigenous breeds from other African and Asian countries. The optimal admixture cluster (K = 20) revealed various sources of within‐ and amongst‐breed genomic variation associated with production purpose, adaptation and history of the breeds. The Blackhead Persian, Nguni and Namaqua Afrikaner breeds differed significantly from other breeds, particularly with the South African Mutton Merino and Dorset Horn. Breed‐differentiating SNPs were observed within genomic regions associated with growth, adaptation and reproduction. Genes such as RAB44, associated with growth and meat/carcass traits, differentiated the Blackhead Persian from the Dorset Horn and South African Mutton Merino. The MAP2 and HRAS genes, which are associated with immune traits involving Toll‐like receptors and Chemokine signalling pathways, differentiated the Nguni from the Dorset Horn. The current results give insight into the current status of the sheep genetic resources of South Africa relative to the global sheep population, highlighting both genetic similarities as well as divergence associated with production systems, geographical distribution and local adaptation.