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The largest beef breed in South Africa is the Bonsmara, a locally developed composite breed, consisting of approximately 81,000 registered cows. The Bonsmara was developed specifically for adaptability to sub-tropical conditions, using objective measurements between 1937 and 1963, and as a breed is subjected to mandatory performance recording. Biological samples have also been stored for the last 10 yr. The Bonsmara is therefore well placed to engage in genomic selection and is in the process of compiling a genomic reference population. To date, 583 Bonsmara cattle (388 bulls and 195 cows) were genotyped with the GeneSeek Genomic Profiler Bovine HD Chip (GGP-HD) 80K chip (Neogen, Lincoln, NE, USA) and the results of another approximately 990 Bonsmara cattle are pending, using the GeneSeek GGP-HD 150K chip. In this preliminary study, the genotypes of the initial 583 Bonsmara cattle were characterized for genome-wide linkage disequilibrium, as this may affect the accuracy of genomic estimated breeding values (GEBV). We used 56,248 autosomal SNPs to determine extent of LD in the current reference population. The software package PLINK was used in the analysis and the squared correlation of the alleles at 2 loci (r2) was used as a measure of LD. A 50 SNP sliding window was used with a 5 SNP increment between windows. Analysis of the marker pairs found that the level of LD in the current reference population decreased with physical distance between SNPs. Overall, the mean r2was 0.405. Genomic regions smaller than 420 kb and 815 kb displayed strong LD (r2> 0.8) and useful LD (r2> 0.2), respectively. These preliminary results indicate that some population stratification may be present in the reference population and should be taken into consideration during the estimation of GEBVs.

Indigenous breeds generally perform poorly as compared to other commercial breeds. This is because there have not been in-depth studies that focus on determining the important production traits at a genome-wide level that will help to improve them. This is due to lack of genomic data that allows these breeds to be thoroughly investigated. SNP arrays have revolutionized the ability of genome-wide studies to detect regions harboring sequence variants that affect complex traits. Extensive numbers of validated SNPs with known allele frequencies have rather mainly focused on breeds other than South African breeds, and were essential to construct genotyping assays with broad utility. This biasness makes the use of existing assays in local breeds less efficient in studies such as genome-wide association studies due to lower minor allele frequencies exhibited by these breeds as described in previous studies. The aim of this project was to discover SNPs in Afrikaner, Drakensberger and Nguni indigenous breeds and estimate their allele frequencies. 90 cattle representing these three populations were used to identify more than 30 000 putative SNPs and predicted their allele frequencies. The data from 90 individuals validated about 90% of 10 000 SNPs selected genome-wide with a genotypic and allele frequency correlation of r= 0.42. Analysis included mapping of the sequence to the available Bos taurusreference genome. Identification of high frequency markers in indigenous breeds suggests the utility of whole genome SNPs as a potential resource for identifying naturally selected trait-regulating genomic targets and functional allelic variants adaptive to diverse climatic regions, for genetic enhancement of the gene-pools.