BackgroundThe 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.MethodsThis 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 (FST).Results and discussionForty-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.ConclusionsThe 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-015-0173-x) contains supplementary material, which is available to authorized users.

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.

ABSTRACT. Genetic variation provides a basis upon which populations can be genetically improved. Management of animal genetic resources in order to minimize loss of genetic diversity both within and across breeds has recently received attention at different levels, e.g., breed, national and international levels. A major need for sustainable improvement and conservation programs is accurate estimates of population parameters, such as rate of inbreeding and effective population size. A software system (POPREP) is presented that automatically generates a typeset report. Key parameters for population management, such as age structure, generation interval, variance in family size, rate of inbreeding, and effective population size form the core part of this report. The report includes a default text that describes definition, computation and meaning of the various parameters. The report is summarized in two pdf files, named Population Structure and Pedigree Analysis Reports. In addition, results (e.g., individual inbreeding coefficients, rate of inbreeding and effective population size) are stored in comma-separate-values files that are available for 1159 ©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 8 (3): 1158-1178 POPREP: a generic report for population management further processing. Pedigree data from eight livestock breeds from different species and countries were used to describe the potential of POPREP and to highlight areas for further research.

In this study, we compare the level and distribution of genetic variation between South African conserved and village chicken populations using microsatellite markers. In addition, diversity in South African chickens was compared to that of a reference data set consisting of other African and purebred commercial lines. Three chicken populations Venda, Ovambo and Eastern Cape and four conserved flocks of the Venda, Ovambo, Naked Neck and Potchefstroom Koekoek from the Poultry Breeding Resource Unit of the Agricultural Research Council were genotyped at 29 autosomal microsatellite loci. All markers were polymorphic. Village chicken populations were more diverse than conservation flocks. structure software was used to cluster individuals to a predefined number of 2 ≤ K ≤ 6 clusters. The most probable clustering was found at K = 5 (95% identical runs). At this level of differentiation, the four conservation flocks separated as four independent clusters, while the three village chicken populations together formed another cluster. Thus, cluster analysis indicated a clear subdivision of each of the conservation flocks that were different from the three village chicken populations. The contribution of each South African chicken populations to the total diversity of the chickens studied was determined by calculating the optimal core set contributions based on Marker estimated kinship. Safe set analysis was carried out using bootstrapped kinship values calculated to relate the added genetic diversity of seven South African chicken populations to a set of reference populations consisting of other African and purebred commercial broiler and layer chickens. In both core set and the safe set analyses, village chicken populations scored slightly higher to the reference set compared to conservation flocks. Overall, the present study demonstrated that the conservation flocks of South African chickens displayed considerable genetic variability that is different from that of the assumed founder populations (village chickens).

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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.

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.

The Nguni cattle breed is a landrace breed adapted to different ecological regions of South Africa. A number of ecotypes are recognised based on phenotype within the breed, but it is not known if they are genetically distinct. In this study molecular characterization was performed on Makhathini (MAK), Pedi (PED), Shangaan (SHA) and Venda (VEN) Nguni cattle ecotypes. Two Nguni cattle populations, not kept as separate ecotypes, from University of Fort Hare (UFH) and Agricultural Research Council Loskop South farm (LOS) were also included. Genotypic data was generated for 189 unrelated Nguni cattle selected based on pedigree records using 22 microsatellite markers. The expected heterozygosity values varied from 69% (UFH) to 72% PED with a mean number of alleles ranging from 6.0 to 6.9. The F ST estimate demonstrated that 4.8% of the total genetic variation was due to the genetic differentiation between the populations and 92.2% accounted for differences within the populations. The genetic distances and structure analysis revealed the closest relationship between MAK, PEDI and SHA ecotypes, followed by SHA and VEN. The UFH population clustered with the MAK ecotype, indicating that they are more genetically similar, while the LOS cattle grouped as a distinct cluster. Results suggest that the genetic differentiation between the PED and SHA ecotypes is low and can be regarded as one ecotype based on 2 limited genetic differences. The results of this study can be applied as a point of reference for further genetic studies towards conservation of Nguni cattle ecotypes.