IBD sharing patterns as intra-breed admixture indicators in small ruminants.

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.

A comprehensive analysis of the genetic diversity and environmental adaptability in worldwide Merino and Merino-derived sheep breeds.

BACKGROUND: To enhance and extend the knowledge about the global historical and phylogenetic relationships between Merino and Merino-derived breeds, 19 populations were genotyped with the OvineSNP50 BeadChip specifically for this study, while an additional 23 populations from the publicly available genotypes were retrieved. Three complementary statistical tests, Rsb (extended haplotype homozygosity between-populations), XP-EHH (cross-population extended haplotype homozygosity), and runs of homozygosity (ROH) islands were applied to identify genomic variants with potential impact on the adaptability of Merino genetic type in two contrasting climate zones. RESULTS: The results indicate that a large part of the Merino's genetic relatedness and admixture patterns are explained by their genetic background and/or geographic origin, followed by local admixture. Multi-dimensional scaling, Neighbor-Net, Admixture, and TREEMIX analyses consistently provided evidence of the role of Australian, Rambouillet and German strains in the extensive gene introgression into the other Merino and Merino-derived breeds. The close relationship between Iberian Merinos and other South-western European breeds is consistent with the Iberian origin of the Merino genetic type, with traces from previous contributions of other Mediterranean stocks. Using Rsb and XP-EHH approaches, signatures of selection were detected spanning four genomic regions located on Ovis aries chromosomes (OAR) 1, 6 and 16, whereas two genomic regions on OAR6, that partially overlapped with the previous ones, were highlighted by ROH islands. Overall, the three approaches identified 106 candidate genes putatively under selection. Among them, genes related to immune response were identified via the gene interaction network. In addition, several candidate genes were found, such as LEKR1, LCORL, GHR, RBPJ, BMPR1B, PPARGC1A, and PRKAA1, related to morphological, growth and reproductive traits, adaptive thermogenesis, and hypoxia responses. CONCLUSIONS: To the best of our knowledge, this is the first comprehensive dataset that includes most of the Merino and Merino-derived sheep breeds raised in different regions of the world. The results provide an in-depth picture of the genetic makeup of the current Merino and Merino-derived breeds, highlighting the possible selection pressures associated with the combined effect of anthropic and environmental factors. The study underlines the importance of Merino genetic types as invaluable resources of possible adaptive diversity in the context of the occurring climate changes.

Characterization of the village goat production systems in the rural communities of the Eastern Cape, KwaZulu-Natal, Limpopo and North West Provinces of South Africa.

Expansion of goat improvement programs requires exploration of the factors that influence the production system and breeding initiatives. Characterization of goat breeds or populations is crucial in providing information on prevalent goat types and their attributes and may suffice as a guideline on conservation, development, and selection for improved productivity. This study investigated the existing village goat production system and phenotypic diversity of the different village populations from four South African provinces. The study further investigated the use of phenotypic attributes to classify goats to breeds or populations. Data was collected from 142 households in 26 villages of the Eastern Cape (n = 2 villages), KwaZulu-Natal (n = 6 villages), Limpopo (n = 13 villages), and North West (n = 5 villages) provinces through a survey. Individual interviews and focus group discussions revealed that the mean goat herd size per household was least in Limpopo at 13.2 ± 12.40 and highest in Eastern Cape (34.18 ± 28.36). Flocks had more (p < 0.05) adults than kids, and the distribution of breeding animals was biased towards does and less bucks. Goats were kept mainly for meat, for selling, and for ritual ceremonies. The goat production system was mainly scavenging. Goat health was a major challenge across households and villages. Qualitative traits such coat, horn, ears, and wattle characteristics were recorded for populations of village goats (n = 319) and a feral Tankwa breed (n = 50). The dominant coat pattern was plain (74.53%) with black as the most common coat color (31.98%). Across breeds, a majority (88.08%) of the goats had horns, and 7.59% had wattles while 56.64% had beard. Adult goats (<3 years; n = 398) were further analyzed for five quantitative traits of chest girth, height, length, and pin bone and there were significant (p < 0.05) breed differences in all. A stepwise discriminatory procedure was used to rank the quantitative traits according to their discriminatory power to separate breeds or populations. Significant traits were then subjected to canonical discriminant analysis for principle component analysis. Based on the quantitative traits, the Tankwa, Xhosa, and Tswana goats formed their own cluster separated from commercial meat type breeds and the Venda and Zulu ecotypes. The discriminant function analysis correctly classified 90.41% of the Zulu goats and 82.93% of the Xhosa village populations. None of the Savanna goats were correctly classified. The study demonstrated diversity in village goat populations and production systems, which would allow for within population selection in genetic improvement programs. The heterogeneity in the phenotypic traits in the village goats is reflective of the role of village production systems in the maintenance of animal diversity in local populations.

Virulence profiles of enterotoxigenic, shiga toxin and enteroaggregative Escherichia coli in South African pigs.

Enterotoxigenic Escherichia coli (ETEC) and shiga toxin E. coli (STEC) are important causes of colibacillosis in piglets. Recently, enteroaggregative E. coli heat-stable enterotoxin 1 (EAST-1) has been implicated in pig diarrhoea. This study investigated the prevalence of enterotoxin [heat-labile toxins (LT), heat-stable toxin a (STa), heat-stable toxin b (STb)], shiga toxins (Stx1, Stx2, Stx2e), enteroaggregative heat-stable E. coli (EAST-1), associated fimbriae (F4, F5, F6, F41, F18ab, F18ac) and non-fimbrial adhesins [adhesin involved in diffuse adherence 1 (AIDA-1), attaching and effacing factor, porcine attaching- and effacing-associated factor] in South African pigs. A total of 263 E. coli strains were isolated from Landrace (n = 24), Large White (n = 126), Duroc (n = 28) and indigenous (n = 85) breeds of piglets aged between 9 and 136 days. PCR was used in the analysis. Virulent genes were detected in 40.3% of the isolates, of which 18.6, 0.4 and 17.5% were classified as ETEC, STEC and enteroaggregative E. coli (EAEC), respectively. Individual genes were found in the following proportions: STb (19.01%), LT (0.4%), STa (3.4%), St2xe (1.1%) and EAST-1 (20.2%) toxins. None of the tested fimbriae were detected in ETEC and STEC isolates. About one third of the ETEC and STEC isolates was tested negative for both fimbrial and non-fimbrial adhesins. Twenty-five pathotypes from ETEC-, EAEC- and STEC-positive strains were identified. Pathotypes EAST-1 (30.2%), STb (13.2%) and STb/AIDA-1 (10.4%) were most prevalent. The study provided insight on possible causes of colibacillosis in South African pigs.

The African Goat Improvement Network: a scientific group empowering smallholder farmers.

The African Goat Improvement Network (AGIN) is a collaborative group of scientists focused on genetic improvement of goats in small holder communities across the African continent. The group emerged from a series of workshops focused on enhancing goat productivity and sustainability. Discussions began in 2011 at the inaugural workshop held in Nairobi, Kenya. The goals of this diverse group were to: improve indigenous goat production in Africa; characterize existing goat populations and to facilitate germplasm preservation where appropriate; and to genomic approaches to better understand adaptation. The long-term goal was to develop cost-effective strategies to apply genomics to improve productivity of small holder farmers without sacrificing adaptation. Genome-wide information on genetic variation enabled genetic diversity studies, facilitated improved germplasm preservation decisions, and provided information necessary to initiate large scale genetic improvement programs. These improvements were partially implemented through a series of community-based breeding programs that engaged and empowered local small farmers, especially women, to promote sustainability of the production system. As with many international collaborative efforts, the AGIN work serves as a platform for human capacity development. This paper chronicles the evolution of the collaborative approach leading to the current AGIN organization and describes how it builds capacity for sustained research and development long after the initial program funds are gone. It is unique in its effectiveness for simultaneous, multi-level capacity building for researchers, students, farmers and communities, and local and regional government officials. The positive impact of AGIN capacity building has been felt by participants from developing, as well as developed country partners.

Carcass Quality Profiles and Associated Genomic Regions of South African Goat Populations Investigated Using Goat SNP50K Genotypes.

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.

Genetics of Base Coat Colour Variations and Coat Colour-Patterns of the South African Nguni Cattle Investigated Using High-Density SNP Genotypes.

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.

Genome Wide Assessment of Genetic Variation and Population Distinctiveness of the Pig Family in South Africa.

Genetic diversity is of great importance and a prerequisite for genetic improvement and conservation programs in pigs and other livestock populations. The present study provides a genome wide analysis of the genetic variability and population structure of pig populations from different production systems in South Africa relative to global populations. A total of 234 pigs sampled in South Africa and consisting of village (n = 91), commercial (n = 60), indigenous (n = 40), Asian (n = 5) and wild (n = 38) populations were genotyped using Porcine SNP60K BeadChip. In addition, 389 genotypes representing village and commercial pigs from America, Europe, and Asia were accessed from a previous study and used to compare population clustering and relationships of South African pigs with global populations. Moderate heterozygosity levels, ranging from 0.204 for Warthogs to 0.371 for village pigs sampled from Capricorn municipality in Eastern Cape province of South Africa were observed. Principal Component Analysis of the South African pigs resulted in four distinct clusters of (i) Duroc; (ii) Vietnamese; (iii) Bush pig and Warthog and (iv) a cluster with the rest of the commercial (SA Large White and Landrace), village, Wild Boar and indigenous breeds of Koelbroek and Windsnyer. The clustering demonstrated alignment with genetic similarities, geographic location and production systems. The PCA with the global populations also resulted in four clusters that where populated with (i) all the village populations, wild boars, SA indigenous and the large white and landraces; (ii) Durocs (iii) Chinese and Vietnamese pigs and (iv) Warthog and Bush pig. K = 10 (The number of population units) was the most probable ADMIXTURE based clustering, which grouped animals according to their populations with the exception of the village pigs that showed presence of admixture. AMOVA reported 19.92%-98.62% of the genetic variation to be within populations. Sub structuring was observed between South African commercial populations as well as between Indigenous and commercial breeds. Population pairwise F ST analysis showed genetic differentiation (P ≤ 0.05) between the village, commercial and wild populations. A per marker per population pairwise F ST analysis revealed SNPs associated with QTLs for traits such as meat quality, cytoskeletal and muscle development, glucose metabolism processes and growth factors between both domestic populations as well as between wild and domestic breeds. Overall, the study provided a baseline understanding of porcine diversity and an important foundation for porcine genomics of South African populations.