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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.
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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.
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Growth and carcass quality are economically important traits in goat production. This study investigated differentially expressed genes from the caprine pituitary gland transcriptome of South African indigenous goat breeds of varying growth performances and carcass quality parameters. Tissues were harvested from the pituitary gland of three South African Boer goats and three village ecotype goats all raised under similar conditions simulating intensive commercial production systems. Three additional tissues were harvested from village ecotype goats that were raised extensively on village farms. Between breed differences were investigated by comparing differential gene expression among three South African Boer and three village goats that were both raised under intensive commercial production system at a research farm. Within-breed differences were investigated by comparing differential gene expression among three village goats raised under extensive conditions (on-farm in Pella, S.A. village farming community) and three village goats raised under intensive commercial production system (at ARC research farm in Pretoria, South Africa. Total RNA was isolated from the pituitary gland of 36-week-old animals (n = 9) and sequenced individually in triplicates. An average of 28,298,512 trimmed, and quality-controlled reads/animal were mapped to the goat genome (Capra_hircus.ARS1.94) using HiSat2 software. Transcript assembly and quantification yielded 104 differentially expressed genes for village goats raised under extensive system and 62 for village goats raised under the intensive production system at the false discovery rate (FRD) of ≤0.05 and a fold change of ≥2. Growth-related genes such as POU3F4 and TSHZ1 were highly expressed within breeds raised under both production systems. Conversely, growth-related genes such as FGFR2 and SMPX genes were highly expressed between breeds raised under similar production systems. Ballgown analysis revealed a high expression of GH1 and IGF1 in the intensively raised compared to extensively raised goats. Both genes were also highly expressed in the village goats when compared to the Boer. The differential gene expression data provided insights into genes and molecular mechanisms associated with growth and growth development in goats.
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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 (Ne) results demonstrated a rapid decrease in Ne 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.
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Ungulates are a group of hoofed animals that have long interacted with humans as essential sources of food, labor, clothing, and transportation. These consist of domesticated, feral, and wild species raised in a wide range of habitats and biomes. Given the diverse and extreme environments inhabited by ungulates, unique adaptive traits are fundamental for fitness. The documentation of genes that underlie their genomic signatures of selection is crucial in this regard. The increasing availability of advanced sequencing technologies has seen the rapid growth of ungulate genomic resources, which offers an exceptional opportunity to understand their adaptive evolution. Here, we summarize the current knowledge on evolutionary genetic signatures underlying the adaptations of ungulates to different habitats.
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A major obstacle in applying genomic selection (GS) to uniquely adapted local breeds in less-developed countries has been the cost of genotyping at high densities of single-nucleotide polymorphisms (SNP). Cost reduction can be achieved by imputing genotypes from lower to higher densities. Locally adapted breeds tend to be admixed and exhibit a high degree of genomic heterogeneity thus necessitating the optimization of SNP selection for downstream imputation. The aim of this study was to quantify the achievable imputation accuracy for a sample of 1,135 South African (SA) Drakensberger cattle using several custom-derived lower-density panels varying in both SNP density and how the SNP were selected. From a pool of 120,608 genotyped SNP, subsets of SNP were chosen (1) at random, (2) with even genomic dispersion, (3) by maximizing the mean minor allele frequency (MAF), (4) using a combined score of MAF and linkage disequilibrium (LD), (5) using a partitioning-around-medoids (PAM) algorithm, and finally (6) using a hierarchical LD-based clustering algorithm. Imputation accuracy to higher density improved as SNP density increased; animal-wise imputation accuracy defined as the within-animal correlation between the imputed and actual alleles ranged from 0.625 to 0.990 when 2,500 randomly selected SNP were chosen vs. a range of 0.918 to 0.999 when 50,000 randomly selected SNP were used. At a panel density of 10,000 SNP, the mean (standard deviation) animal-wise allele concordance rate was 0.976 (0.018) vs. 0.982 (0.014) when the worst (i.e., random) as opposed to the best (i.e., combination of MAF and LD) SNP selection strategy was employed. A difference of 0.071 units was observed between the mean correlation-based accuracy of imputed SNP categorized as low (0.01 < MAF ≤ 0.1) vs. high MAF (0.4 < MAF ≤ 0.5). Greater mean imputation accuracy was achieved for SNP located on autosomal extremes when these regions were populated with more SNP. The presented results suggested that genotype imputation can be a practical cost-saving strategy for indigenous breeds such as the SA Drakensberger. Based on the results, a genotyping panel consisting of ~10,000 SNP selected based on a combination of MAF and LD would suffice in achieving a <3% imputation error rate for a breed characterized by genomic admixture on the condition that these SNP are selected based on breed-specific selection criteria.
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Polimorfismo de Nucleótido Simple , Animales , Bovinos/genética , Frecuencia de los Genes , Genotipo , Desequilibrio de LigamientoRESUMEN
In this study, we evaluated an admixed South African Simbra crossbred population, as well as the Brahman (Indicine) and Simmental (Taurine) ancestor populations to understand their genetic architecture and detect genomic regions showing signatures of selection. Animals were genotyped using the Illumina BovineLD v2 BeadChip (7K). Genomic structure analysis confirmed that the South African Simbra cattle have an admixed genome, composed of 5/8 Taurine and 3/8 Indicine, ensuring that the Simbra genome maintains favorable traits from both breeds. Genomic regions that have been targeted by selection were detected using the linkage disequilibrium-based methods iHS and Rsb. These analyses identified 10 candidate regions that are potentially under strong positive selection, containing genes implicated in cattle health and production (e.g., TRIM63, KCNA10, NCAM1, SMIM5, MIER3, and SLC24A4). These adaptive alleles likely contribute to the biological and cellular functions determining phenotype in the Simbra hybrid cattle breed. Our data suggested that these alleles were introgressed from the breed's original indicine and taurine ancestors. The Simbra breed thus possesses derived parental alleles that combine the superior traits of the founder Brahman and Simmental breeds. These regions and genes might represent good targets for ad-hoc physiological studies, selection of breeding material and eventually even gene editing, for improved traits in modern cattle breeds. This study represents an important step toward developing and improving strategies for selection and population breeding to ultimately contribute meaningfully to the beef production industry.
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[This corrects the article DOI: 10.3389/fgene.2018.00163.].
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Copy number variations (CNVs) comprise deletions, duplications, and insertions found within the genome larger than 50 bp in size. CNVs are thought to be primary role-players in breed formation and adaptation. South Africa boasts a diverse ecology with harsh environmental conditions and a broad spectrum of parasites and diseases that pose challenges to livestock production. This has led to the development of composite cattle breeds which combine the hardiness of Sanga breeds and the production potential of the Taurine breeds. The prevalence of CNVs within these respective breeds of cattle and the prevalence of CNV regions (CNVRs) in their diversity, adaptation and production is however not understood. This study therefore aimed to ascertain the prevalence, diversity, and correlations of CNVRs within cattle breeds used in South Africa. Illumina Bovine SNP50 data and PennCNV were utilized to identify CNVRs within the genome of 287 animals from seven cattle breeds representing Sanga, Taurine, Composite, and cross breeds. Three hundred and fifty six CNVRs of between 36 kb to 4.1 Mb in size were identified. The null hypothesis that one CNVR loci is independent of another was tested using the GENEPOP software. One hunded and two and seven of the CNVRs in the Taurine and Sanga/Composite cattle breeds demonstrated a significant (p ≤ 0.05) association. PANTHER overrepresentation analyses of correlated CNVRs demonstrated significant enrichment of a number of biological processes, molecular functions, cellular components, and protein classes. CNVR genetic variation between and within breed group was measured using phiPT which allows intra-individual variation to be suppressed and hence proved suitable for measuring binary CNVR presence/absence data. Estimate PhiPT within and between breed variance was 2.722 and 0.518 respectively. Pairwise population PhiPT values corresponded with breed type, with Taurine Holstein and Angus breeds demonstrating no between breed CNVR variation. Phylogenetic trees were drawn. CNVRs primarily clustered animals of the same breed type together. This study successfully identified, characterized, and analyzed 356 CNVRs within seven cattle breeds. CNVR correlations were evident, with many more correlations being present among the exotic Taurine breeds. CNVR genetic diversity of Sanga, Taurine and Composite breeds was ascertained with breed types exposed to similar selection pressures demonstrating analogous incidences of CNVRs.
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BACKGROUND: Understanding the history of cattle breeds is important because it provides the basis for developing appropriate selection and breed improvement programs. In this study, patterns of ancestry and admixture in Afrikaner, Nguni, Drakensberger and Bonsmara cattle of South Africa were investigated. We used 50 K single nucleotide polymorphism genotypes that were previously generated for the Afrikaner (n = 36), Nguni (n = 50), Drakensberger (n = 47) and Bonsmara (n = 44) breeds, and for 394 reference animals representing European taurine, African taurine, African zebu and Bos indicus. RESULTS AND DISCUSSION: Our findings support previous conclusions that Sanga cattle breeds are composites between African taurine and Bos indicus. Among these breeds, the Afrikaner breed has significantly diverged from its ancestral forebears, probably due to genetic drift and selection to meet breeding objectives of the breed society that enable registration. The Nguni, Drakensberger and Bonsmara breeds are admixed, perhaps unintentionally in the case of Nguni and Drakensberger, but certainly by design in the case of Bonsmara, which was developed through crossbreeding between the Afrikaner, Hereford and Shorthorn breeds. CONCLUSIONS: We established patterns of admixture and ancestry for South African Sanga cattle breeds, which provide a basis for developing appropriate strategies for their genetic improvement.
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Cruzamiento , Genética de Población , Genoma , Patrón de Herencia , Polimorfismo de Nucleótido Simple , Alelos , Animales , Bovinos , Cruzamientos Genéticos , Femenino , Frecuencia de los Genes , Genotipo , Masculino , Fenotipo , Análisis de Componente Principal , SudáfricaRESUMEN
The majority of rural households in developing countries own village chickens that are reared under traditional scavenging systems with few inputs and exposure to various parasitic infestations. Understanding of the village chicken farming system and its influence on helminth infestation is a prerequisite for optimal prevention and control strategies. This study investigated the village chicken production system and associated gastrointestinal parasites in 87 households from Limpopo (n = 39) and KwaZulu-Natal (n = 48) provinces of South Africa. A total of 191 village chicken faecal samples and 145 intestines were collected to determine the prevalence of gastrointestinal parasites in villages of Limpopo and KwaZulu-Natal provinces, respectively. The faecal floatation analysis of samples from Limpopo and KwaZulu-Natal provinces indicated infestations by Ascaridia galli (18.77%), Heterakis gallinarum (15.56%) and Capillaria spp. (4.00%); tapeworms Choanotaenia infundibulum (2.10%) and Raillietina cesticillus (6.00%) and Eimeria spp. (29.46%). Mixed infestations were observed in five (4.90%) samples from Limpopo province and in only four (4.49%) from KwaZulu-Natal province, of which 1.12% were a mixture of C. infundibulum and Eimeria spp. and 3.37% a combination of H. gallinarum and Eimeria spp. In Limpopo, 2.94% of the chickens were positive for H. gallinarum and Eimeria spp., whilst 0.98% had A. galli and Capillaria spp. infestations. Further investigation is needed to understand the impact of gastrointestinal parasites on village chicken health and production and develop appropriate intervention and control strategies feasible for smallholder farmers.
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Crianza de Animales Domésticos/métodos , Pollos , Parasitosis Intestinales/veterinaria , Enfermedades Parasitarias en Animales/epidemiología , Enfermedades de las Aves de Corral/epidemiología , Animales , Parasitosis Intestinales/epidemiología , Parasitosis Intestinales/parasitología , Enfermedades Parasitarias en Animales/parasitología , Enfermedades de las Aves de Corral/parasitología , Prevalencia , Sudáfrica/epidemiologíaRESUMEN
The present study investigated the seroprevalence of antibodies to Ehrlichia ruminantium and the associated risk factors in goats from five different farming provinces of South Africa. Sera collected from 686 goats of the commercial meat type (n=179), mohair type (n=9), non-descript indigenous goats from Eastern Cape (n=56), KwaZulu-Natal (n=209), Limpopo (n=111), North West (n=61) and Northern Cape (n=11) provinces and a feral Tankwa goat (n=50) were tested for the presence of immunoglobulin G (IgG) antibodies to antigens of E. ruminantium using the indirect fluorescent-antibody test (IFAT). Fifty two percent of these goats had ticks. The overall seroprevalence of antibodies to E. ruminantium was 64.87% (445/686) with the highest seroprevalence reported for Limpopo (95.50%) and lowest for Northern Cape (20.29%). Highest seroprevalence for antibodies to E. ruminantium was observed in goats from endemic regions (76.09%), and from smallholder production systems (89.54%). High seroprevalence was also observed in non-descript indigenous goats (85.04%), adult goat (69.62%), in does (67.46%) and goats infested with ticks (85.79%). The logistic model showed a gradient of increasing risk for commercial meat type Savanna (OR=3.681; CI=1.335-10.149) and non-descript indigenous (OR=3.466; CI=1.57-7.645) compared to Boer goats and for goats from the smallholder production system (OR=2.582; CI=1.182-5.639) and those with ticks (OR=3.587; CI=2.105-6.112). Results from this study showed that E. ruminantium infections were prevalent but were widely and unevenly distributed throughout South Africa. Findings from the study facilitate identification and mapping of risk areas for heartwater and its endeminicity in South Africa and should be taken into consideration for future disease control strategies and local goat improvement programs.
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Crianza de Animales Domésticos/métodos , Ehrlichia ruminantium/aislamiento & purificación , Enfermedades de las Cabras/epidemiología , Hidropericardio/epidemiología , Animales , Anticuerpos Antibacterianos/sangre , Femenino , Geografía , Enfermedades de las Cabras/microbiología , Cabras , Hidropericardio/microbiología , Masculino , Factores de Riesgo , Estudios Seroepidemiológicos , Sudáfrica/epidemiologíaRESUMEN
Knowledge on the extent of linkage disequilibrium (LD) in livestock populations is essential to determine the minimum distance between markers required for effective coverage when conducting genome-wide association studies (GWAS). This study evaluated the extent of LD, persistence of allelic phase and effective population size (Ne) for four Sanga cattle breeds in South Africa including the Afrikaner (n = 44), Nguni (n = 54), Drakensberger (n = 47), and Bonsmara breeds (n = 46), using Angus (n = 31) and Holstein (n = 29) as reference populations. We found that moderate LD extends up to inter-marker distances of 40-60 kb in Angus (0.21) and Holstein (0.21) and up to 100 kb in Afrikaner (0.20). This suggests that genomic selection and association studies performed within these breeds using an average inter-marker r (2)≥ 0.20 would require about 30,000-50,000 SNPs. However, r (2)≥ 0.20 extended only up to 10-20 kb in the Nguni and Drakensberger and 20-40 kb in the Bonsmara indicating that 75,000 to 150,000 SNPs would be necessary for GWAS in these breeds. Correlation between alleles at contiguous loci indicated that phase was not strongly preserved between breeds. This suggests the need for breed-specific reference populations in which a much greater density of markers should be scored to identify breed specific haplotypes which may then be imputed into multi-breed commercial populations. Analysis of effective population size based on the extent of LD, revealed Ne = 95 (Nguni), Ne = 87 (Drakensberger), Ne = 77 (Bonsmara), and Ne = 41 (Afrikaner). Results of this study form the basis for implementation of genomic selection programs in the Sanga breeds of South Africa.
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BACKGROUND: Copy number variations (CNVs) are modifications in DNA structure comprising of deletions, duplications, insertions and complex multi-site variants. Although CNVs are proven to be involved in a variety of phenotypic discrepancies, the full extent and consequence of CNVs is yet to be understood. To date, no such genomic characterization has been performed in indigenous South African Nguni cattle. Nguni cattle are recognized for their ability to sustain harsh environmental conditions while exhibiting enhanced resistance to disease and parasites and are thought to comprise of up to nine different ecotypes. METHODS: Illumina BovineSNP50 Beadchip data was utilized to investigate genomic population structure and the prevalence of CNVs in 492 South African Nguni cattle. PLINK, ADMIXTURE, R, gPLINK and Haploview software was utilized for quality control, population structure and haplotype block determination. PennCNV hidden Markov model identified CNVs and genes contained within and 10 Mb downstream from reported CNVs. PANTHER and Ensembl databases were subsequently utilized for gene annotation analyses. RESULTS: Population structure analyses on Nguni cattle revealed 5 sub-populations with a possible sub-structure evident at K equal to 8. Four hundred and thirty three CNVs that formed 334 CNVRs ranging from 30 kb to 1 Mb in size are reported. Only 231 of the 492 animals demonstrated CNVRs. Two hundred and eighty nine genes were observed within CNVRs identified. Of these 149, 28, 44, 2 and 14 genes were unique to sub-populations A, B, C, D and E respectively. Gene ontology analyses demonstrated a number of pathways to be represented by respective genes, including immune response, response to abiotic stress and biological regulation processess. CONCLUSIONS: CNVs may explain part of the phenotypic diversity and the enhanced adaptation evident in Nguni cattle. Genes involved in a number of cellular components, biological processes and molecular functions are reported within CNVRs identified. The significance of such CNVRs and the possible effect thereof needs to be ascertained and may hold interesting insight into the functional and adaptive consequence of CNVs in cattle.
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Variaciones en el Número de Copia de ADN/genética , Genética de Población , Genoma , Animales , Bovinos , Ontología de Genes , GenómicaRESUMEN
BACKGROUND: The detection of selection signatures in breeds of livestock species can contribute to the identification of regions of the genome that are, or have been, functionally important and, as a consequence, have been targeted by selection. METHODS: This study used two approaches to detect signatures of selection within and between six cattle breeds in South Africa, including Afrikaner (n = 44), Nguni (n = 54), Drakensberger (n = 47), Bonsmara (n = 44), Angus (n = 31) and Holstein (n = 29). The first approach was based on the detection of genomic regions in which haplotypes have been driven towards complete fixation within breeds. The second approach identified regions of the genome that had very different allele frequencies between populations (F ST). RESULTS AND DISCUSSION: Forty-seven candidate genomic regions were identified as harbouring putative signatures of selection using both methods. Twelve of these candidate selected regions were shared among the breeds and ten were validated by previous studies. Thirty-three of these regions were successfully annotated and candidate genes were identified. Among these genes the keratin genes (KRT222, KRT24, KRT25, KRT26, and KRT27) and one heat shock protein gene (HSPB9) on chromosome 19 between 42,896,570 and 42,897,840 bp were detected for the Nguni breed. These genes were previously associated with adaptation to tropical environments in Zebu cattle. In addition, a number of candidate genes associated with the nervous system (WNT5B, FMOD, PRELP, and ATP2B), immune response (CYM, CDC6, and CDK10), production (MTPN, IGFBP4, TGFB1, and AJAP1) and reproductive performance (ADIPOR2, OVOS2, and RBBP8) were also detected as being under selection. CONCLUSIONS: The results presented here provide a foundation for detecting mutations that underlie genetic variation of traits that have economic importance for cattle breeds in South Africa.
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Cruzamiento , Estudio de Asociación del Genoma Completo , Genoma , Genómica , Selección Genética , Alelos , Animales , Bovinos , Cromosomas de los Mamíferos , Biología Computacional/métodos , Frecuencia de los Genes , Estudios de Asociación Genética , Marcadores Genéticos , Estudio de Asociación del Genoma Completo/métodos , Genómica/métodos , Haplotipos , Polimorfismo de Nucleótido Simple , Sitios de Carácter Cuantitativo , SudáfricaRESUMEN
Bacillus anthracis is a Gram-positive bacterium that causes anthrax, mainly in herbivores through exotoxins and capsule produced on plasmids, pXO1 and pXO2. This paper compares the whole-genome sequences of two B. anthracis strains from an endemic region and a sporadic outbreak in South Africa. Sequencing was done using next-generation sequencing technologies.
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Extensively raised village chickens are considered a valuable source of biodiversity, with genetic variability developed over thousands of years that ought to be characterized and utilized. Surveys that can reveal a population's genetic structure and provide an insight into its demographic history will give valuable information that can be used to manage and conserve important indigenous animal genetic resources. This study reports population diversity and structure, linkage disequilibrium and effective population sizes of Southern African village chickens and conservation flocks from South Africa. DNA samples from 312 chickens from South African village and conservation flocks (n = 146), Malawi (n = 30) and Zimbabwe (n = 136) were genotyped using the Illumina iSelect chicken SNP60K BeadChip. Population genetic structure analysis distinguished the four conservation flocks from the village chicken populations. Of the four flocks, the Ovambo clustered closer to the village chickens particularly those sampled from South Africa. Clustering of the village chickens followed a geographic gradient whereby South African chickens were closer to those from Zimbabwe than to chickens from Malawi. Different conservation flocks seemed to have maintained different components of the ancestral genomes with a higher proportion of village chicken diversity found in the Ovambo population. Overall population LD averaged over chromosomes ranged from 0.03 ± 0.07 to 0.58 ± 0.41 and averaged 0.15 ± 0.16. Higher LD, ranging from 0.29 to 0.36, was observed between SNP markers that were less than 10 kb apart in the conservation flocks. LD in the conservation flocks steadily decreased to 0.15 (PK) and 0.24 (VD) at SNP marker interval of 500 kb. Genomewide LD decay in the village chickens from Malawi, Zimbabwe and South Africa followed a similar trend as the conservation flocks although the mean LD values for the investigated SNP intervals were lower. The results suggest low effective population sizes particularly in the conservation flocks. The utility and limitations of the iselect chicken SNP60K in village chicken populations is discussed.
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Information about genetic diversity and population structure among cattle breeds is essential for genetic improvement, understanding of environmental adaptation as well as utilization and conservation of cattle breeds. This study investigated genetic diversity and the population structure among six cattle breeds in South African (SA) including Afrikaner (n = 44), Nguni (n = 54), Drakensberger (n = 47), Bonsmara (n = 44), Angus (n = 31), and Holstein (n = 29). Genetic diversity within cattle breeds was analyzed using three measures of genetic diversity namely allelic richness (AR), expected heterozygosity (He) and inbreeding coefficient (f). Genetic distances between breed pairs were evaluated using Nei's genetic distance. Population structure was assessed using model-based clustering (ADMIXTURE). Results of this study revealed that the allelic richness ranged from 1.88 (Afrikaner) to 1.73 (Nguni). Afrikaner cattle had the lowest level of genetic diversity (He = 0.24) and the Drakensberger cattle (He = 0.30) had the highest level of genetic variation among indigenous and locally-developed cattle breeds. The level of inbreeding was lower across the studied cattle breeds. As expected the average genetic distance was the greatest between indigenous cattle breeds and Bos taurus cattle breeds but the lowest among indigenous and locally-developed breeds. Model-based clustering revealed some level of admixture among indigenous and locally-developed breeds and supported the clustering of the breeds according to their history of origin. The results of this study provided useful insight regarding genetic structure of SA cattle breeds.
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PURPOSE AND METHODS: In situ conservation of pig genetic resources requires understanding of the farming systems under which the pigs are kept. The objective of the study was to characterise smallholder pig production systems where indigenous pigs are kept in order to assess opportunities for in situ conservation of these pigs. Factors influencing pig herd sizes, ranking of pigs in smallholder production systems, breeds and breed preferences, pig ownership patterns, traits preferred by farmers and constraints to production were investigated in a survey involving 199 farmers from Chirimhanzu District of Zimbabwe, Vhembe, Alfred Nzo and O. R. Tambo Districts of South Africa. RESULTS: Income was the major factor influencing most pig production related parameters. Most pigs (69.67 %) were owned by women, with most of the women falling into the very low income group. Farmers kept pigs for several reasons that were common across geographical zones and income groups. The odds of a farmer ranking pigs first in the production system depended on the absence of other livestock (P < 0.05). Farmers in the higher income group tended to mention poor feed resources and access to information as constraints (P < 0.05) compared to the very low income group. There was preference heterogeneity in the breeds kept and the reasons for breed choice across the income groups and geographical zones. Fewer farmers in the very low income group (42.62 %) recognised the need to conserve local pigs compared to the low income group (80.49 %), the medium income group (50.00 %) and the high income group (100.00 %; χ (2) = 19.14; P < 0.001). CONCLUSIONS: It was concluded that farmers see value in local pigs and are willing to conserve them. In situ conservation programmes are possible and these should recognise the role of poor women in conserving and enhancing indigenous pig genetic resources.