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Dive into the research topics where Azwihangwisi Maiwashe is active.

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Featured researches published by Azwihangwisi Maiwashe.


Frontiers in Genetics | 2014

Genetic diversity and population structure among six cattle breeds in South Africa using a whole genome SNP panel.

Sithembile O. Makina; Farai C. Muchadeyi; Este Van Marle-Koster; Michael D. MacNeil; Azwihangwisi Maiwashe

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 Neis 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.


Ticks and Tick-borne Diseases | 2014

Towards a genomics approach to tick (Acari: Ixodidae) control in cattle: A review

Ntanganedzeni O. Mapholi; Munyaradzi C. Marufu; Azwihangwisi Maiwashe; Cuthbert Banga; Voster Muchenje; Michael D. MacNeil; Michael Chimonyo; K. Dzama

Ticks and tick-borne disease (TBD) are major challenges to cattle production in the tropics and subtropics. Economic losses associated with ticks amount to billions of dollars annually. Although efforts to eradicate ticks and TBD using chemical control strategies have been implemented in many developing countries for decades, these acaricides are costly, and cattle susceptibility to ticks remains unchanged. Traditional breeding methods, where the farmer selected animals using records to improve the host genetic resistance to ticks (HGRT), are less than fully effective and time consuming. The HGRT has been reported in literature. To date, solutions to fight ticks and TBD are still unclear. Development of single-nucleotide polymorphism (SNP) technologies has created an opportunity to estimate breeding values of animals from DNA samples. The use of SNP technology for genomic selection allows information retrieval from the genotype even before the gene is expressed; thus potentially giving farmers the ability to make selection decisions on HGRT at an earlier age. This review discusses factors that affect HGRT, breeding selection, immunology, and genomic approaches and their application to improve HGRT in order to enhance livestock production.


Ticks and Tick-borne Diseases | 2016

Genome-wide association study of tick resistance in South African Nguni cattle.

Ntanganedzeni O. Mapholi; Azwihangwisi Maiwashe; Oswald Matika; Valentina Riggio; Stephen Bishop; Michael D. MacNeil; Cuthbert Banga; J. F. Taylor; K. Dzama

Ticks and tick-borne diseases are among the main causes of economic loss in the South African cattle industry through high morbidity and mortality rates. Concerns of the general public regarding chemical residues may tarnish their perceptions of food safety and environmental health when the husbandry of cattle includes frequent use of acaricides to manage ticks. The primary objective of this study was to identify single nucleotide polymorphism (SNP) markers associated with host resistance to ticks in South African Nguni cattle. Tick count data were collected monthly from 586 Nguni cattle reared in four herds under natural grazing conditions over a period of two years. The counts were recorded for six species of ticks attached in eight anatomical locations on the animals and were summed by species and anatomical location. This gave rise to 63 measured phenotypes or traits, with results for 12 of these traits being reported here. Tick count (x) data were transformed using log10(x+1) and the resulting values were examined for normality. DNA was extracted from hair and blood samples and was genotyped using the Illumina BovineSNP50 assay. After quality control (call rate >90%, minor allele frequency >0.02), 40,436 SNPs were retained for analysis. Genetic parameters were estimated and association analysis for tick resistance was carried out using two approaches: a genome-wide association (GWA) analysis using the GenABEL package and a regional heritability mapping (RHM) analysis. The Bonferroni genome-wide (P<0.05) corrected significance threshold was 1.24×10(-6), with 2.47×10(-5) as the suggestive significance threshold (P<0.10) (i.e., one false positive per genome scan) in the GWA analysis. Likelihood ratio test (LRT) thresholds for genome-wide and suggestive significance were 13.5 and 9.15 for the RHM analysis. Six ixodid tick species were identified, with Amblyomma hebraeum (the vector for Heartwater disease) being the dominant species. Heritability estimates (h(2)) from the fitted animal and sire models ranged from 0.02±0.00 to 0.17±0.04 for the transformed tick count data. Several genomic regions harbouring quantitative trait loci (QTL) were identified for different tick count traits by both the GWA and RHM approaches. Three genome-wide significant regions on chromosomes 7, 10 and 19 were identified for total tick count on the head, total body A. hebraeum tick count and total A. hebraeum on the perineum region, respectively. Additional regions significant at the suggestive level were identified on chromosomes 1, 3, 6, 7, 8, 10, 11, 12, 14, 15, 17, 19 and 26 for several of the traits. The GWA approach identified more genomic regions than did the RHM approach. The chromosomal regions identified here as harbouring QTL underlying variation in tick burden form the basis for further analyses to identify specific candidate genes and polymorphisms related to cattle tick resistance and provide the potential for marker-assisted selection in Nguni cattle.


Frontiers in Genetics | 2015

Extent of Linkage Disequilibrium and Effective Population Size in Four South African Sanga Cattle Breeds

Sithembile O. Makina; Jeremy F. Taylor; Este Van Marle-Koster; Farai C. Muchadeyi; Mahlako L. Makgahlela; Michael D. MacNeil; Azwihangwisi Maiwashe

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 r2≥ 0.20 would require about 30,000–50,000 SNPs. However, r2≥ 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.


Tropical Animal Health and Production | 2017

Genetic parameters for tick counts across months for different tick species and anatomical locations in South African Nguni cattle.

Ntanganedzeni O. Mapholi; Azwihangwisi Maiwashe; Oswald Matika; Valentina Riggio; Cuthbert Banga; Michael D. MacNeil; Voster Muchenje; K. A. Nephawe; K. Dzama

The objective of the study was to characterise genetic parameters across months for different tick species and anatomical locations in South African Nguni cattle. Tick counts were conducted monthly, over a 2-year period, on 586 Nguni cattle under natural infestation, from four herds located in different provinces of South Africa. The counts were recorded for six species of ticks (Amblyomma hebraeum, Rhipicephalus evertsi evertsi, Rhipicephalus decoleratus and microplus (Boofilids), Rhipicephalus appendiculatus, Rhipicephalus simus and Hyalomma marginatum) attached on eight anatomical locations on the animals and were summed by species and anatomical location. Heritability estimates, phenotypic and genetic correlations were estimated on a monthly basis using mixed linear models, fitting univariate and bivariate sire models. Fixed effects considered were location, sex, year and age as a covariate. Tick counts were higher in the hot months, and A. hebraeum was the most dominant tick species. Heritability estimates for tick count varied by month and trait and ranged from 0 to 0.89. Genetic correlations were mostly positive, and low to high, with some negative correlations with high standard error. Phenotypic correlations were low to moderate. In general, high genetic correlations were observed between whole body count and the anatomical location counts, suggesting that it may not be necessary to conduct whole body counts. Counts from the belly and perineum appeared to be the most suitable surrogate traits for whole body count. These findings provide useful information for developing strategies for the practical implementation of genetic selection, as a supplement to the traditional tick control measures.


Genetics Selection Evolution | 2015

Genome-wide scan for selection signatures in six cattle breeds in South Africa

Sithembile O. Makina; Farai C. Muchadeyi; Este Van Marle-Koster; J. F. Taylor; Mahlako L. Makgahlela; Azwihangwisi Maiwashe


Tropical Animal Health and Production | 2012

Influence of socioeconomic factors on production constraints faced by indigenous chicken producers in South Africa

Bohani Joseph Mtileni; Farai C. Muchadeyi; Azwihangwisi Maiwashe; Michael Chimonyo; C. Mapiye; K. Dzama


Genetics Selection Evolution | 2016

Insight into the genetic composition of South African Sanga cattle using SNP data from cattle breeds worldwide

Sithembile O. Makina; Lindsey K. Whitacre; Jared E. Decker; Jeremy F. Taylor; Michael D. MacNeil; M.M. Scholtz; Este Van Marle-Koster; Farai C. Muchadeyi; Mahlako L. Makgahlela; Azwihangwisi Maiwashe


Tropical Animal Health and Production | 2016

Genetic diversity in South African Nguni cattle ecotypes based on microsatellite markers

Yandisiwe Sanarana; C. Visser; Lydia Bosman; K. A. Nephawe; Azwihangwisi Maiwashe; Este Van Marle-Koster


South African Journal of Animal Science | 2016

Genome-wide identification of breed-informative single-nucleotide polymorphisms in three South African indigenous cattle breeds

A.A. Zwane; Azwihangwisi Maiwashe; Mahlako L. Makgahlela; A. Choudhury; J. F. Taylor; E. van Marle-Köster

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K. Dzama

Stellenbosch University

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Michael Chimonyo

University of KwaZulu-Natal

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