Edgar Farai Dzomba

Population genetic structure, linkage disequilibrium and effective population size of conserved and extensively raised village chicken populations of Southern Africa

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 populations 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.

Seroprevalence of Ehrlichia ruminantium antibodies and its associated risk factors in indigenous goats of South Africa.

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.

Genomics Tools for the Characterization of Genetic Adaptation of Low Input Extensively Raised Chickens

Evolutionary change emanating from differential contribution of genotypes to the next generation can determine success in survival and reproduction in chickens. For extensively raised chickens reared under low-input production systems in smallholder farming areas, conditions of resources deprivation and exposure to diverse and threatening natural selection pressures are common in many countries worldwide. Numerous studies have demonstrated that village chickens and other extensively raised chicken populations represent a valuable source of biodiversity adapted to the local production conditions and selection pressures. Manipulation of their acquired adaptive genetic diversity depends on unravelling the selection footprints in the genomes of these chickens that could point towards candidate genes for traits that enable the animals to survive under the harsh production environments. This chapter summarizes the evidence for chickens’ adaptation to extreme environments and describes an inventory of modern tools that could be used in characterizing the production systems of chicken genetic resources. The role of natural selection in shaping the biodiversity of chicken genetic resources is discussed. The continued advancement of biotechnological tools to assess chicken populations has been beneficial to research in genetic adaptation. Genomics tools, as evidenced by assays of whole genome and transcriptome sequences, and single nucleotide polymorphism (SNP) genotypes of chickens, now allow analyses of functional genomic regions that are linked to adaptation. The use of these methods to characterize and investigate signatures of selection in the chicken genomes is highlighted. This chapter looks at how information on the selection hotspots in the chicken genomes can be manipulated to improve genetic adaptation in indigenous chicken populations with the desire to transfer the benefits to other chicken breeds raised under similar production systems.

Landscape genomics and pathway analysis to understand genetic adaptation of South African indigenous goat populations

In Africa, extensively raised livestock populations in most smallholder farming communities are exposed to harsh and heterogeneous climatic conditions and disease pathogens that they adapt to in order to survive. Majority of these livestock species, including goats, are of non-descript and uncharacterized breeds and their response to natural selection presented by heterogeneous environments is still unresolved. This study investigated genetic diversity and its association with environmental and geographic conditions in 194 South African indigenous goats from different geographic locations genotyped on the Illumina goat SNP50K panel. Population structure analysis revealed a homogeneous genetic cluster of the Tankwa goats, restricted to the Northern Cape province. Overall, the Boer, Kalahari Red, and Savanna showed a wide geographic spread of shared genetic components, whereas the village ecotypes revealed a longitudinal distribution. The relative importance of environmental factors on genetic variation of goat populations was assessed using redundancy analysis (RDA). Climatic and geographic variables explained 22% of the total variation while climatic variables alone accounted for 17% of the diversity. Geographic variables solitarily explained 1% of the total variation. The first axis (Model I) of the RDA analysis revealed 329 outlier SNPs. Landscape genomic approaches of spatial analysis method (SAM) identified a total of 843 (1.75%) SNPs, while latent factor mixed models (LFMM) identified 714 (1.48%) SNPs significantly associated with environmental variables. Significant markers were within genes involved in biological functions potentially important for environmental adaptation. Overall, the study suggested environmental factors to have some effect in shaping the genetic variation of South African indigenous goat populations. Loci observed to be significant and under selection may be responsible for the adaption of the goat populations to local production systems.

Genomics for the Improvement of Productivity and Robustness of South African Goat Breeds

South Africa is one of the major goat-producing countries with over 6 million goats, 63% of which are farmed under smallholder communal farming systems where poor nutrition, disease infestation, and harsh climatic conditions are common. The Boer, Kalahari Red, and Savanna breeds were developed in South Africa and have turned out to be regionally and internationally relevant. Adaptation and tolerance to local conditions are crucial for survival of these goat genetic resources in suboptimal conditions. The full genetic potential of veld goat populations is not yet fully unraveled. Complete mtDNA sequencing and diversity analysis revealed multiple maternal lineages in South African goat populations that were shared amongst the breeds and populations with absence of population sub-structuring. Median joining network analysis using different mtDNA genes suggests that South African populations have multiple maternal lineages that are shared with other global populations. Caprine SNP50K panel data analysis highlighted elevated levels of genetic diversity in South African indigenous goats compared to industrial breeds as well as the utility of the genome-wide SNP marker panels in population genetic studies. Landscape genomic analysis suggests a strong role of environmental factors in shaping the genetic diversity of South African indigenous goats. Selected loci responsible for the adaption of goat populations to local production systems may be targeted in breed improvement programs particularly under marginalized communal production systems. Successful sequencing and analysis of the Tankwa and other South African goat genomes could screen for potentially numerous genomic variants such as copy number variants. Community-based breeding programs would be the appropriate tool for breed improvement allowing sharing of production capital, pooling of resources and services and enabling joint processes of decision-making. Genomics could complement breed improvement efforts by providing pedigree estimates and can be useful in monitoring and control of inbreeding and genetic gain.