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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.

Relationships between longevity and linear type traits were estimated using data on 34,201 cows with lifetime information and linear type scores. The longevity trait considered was the number of lactations initiated and the linear type traits were rump height, body depth, angularity, rear udder height, fore udder attachment, udder depth, fore teat placement and fore teat length. Fixed effects included in the models were herd year, season of calving and herd-date of classification-classifier and days in milk. Age at first calving and age at classification were included as linear and quadratic covariates. Heritability estimates were low for longevity and moderate for most type traits except rump height and fore teat length. All the phenotypic correlations between longevity and the linear type traits were slightly positive (0.01 to 0.09) except the relationships with rump height and fore teat length which were -0.01 and -0.02, respectively. Genetic correlations between longevity and udder traits as well as angularity were moderate to high and positive (0.22 to 0.48). The only notable negative genetic correlations were longevity with body depth and fore teat length (-0.15 and -0.07, respectively). The genetic correlations suggest that selection for udder traits and angularity should improve longevity in the Holstein cattle population.

Selection accuracy for resistance to mastitis may be increased by combining somatic cell score (SCS) and udder type into an udder health index, using genetic parameter estimates among them. A multi-trait animal model was used to estimate genetic parameters among lactation average SCS and udder type traits in South African Holstein cattle, through REML procedures. Data comprised records on 22 999 Holstein cows in 722 herds, collected through the National Milk Recording Scheme from 1996 to 2002. Average SCS in the first three lactations (SCS 1 , SCS 2 , SCS 3 ) were considered as different traits and the udder type traits were fore udder attachment (FUA), rear udder height (RUH), udder cleft (UC), udder depth (UD), fore teat length (FTL) and fore teat placement (FTP). Heritability estimates for SCS were 0.19 ± 0.02, 0.17 ± 0.02 and 0.19 ± 0.02, respectively for SCS 1 , SCS 2 and SCS 3 . Udder type traits had heritability estimates ranging from 0.13 ± 0.01 for UC to 0.34 ± 0.01 for FTL. The genetic correlations between lactation SCS ranged from 0.82 ± 0.04 to 0.99 ± 0.03 for correlations of SCS 3 with SCS 1 and SCS 2 , respectively. Genetic correlations between SCS and udder type traits were in the range -0.01 ± 0.07 between FUA and SCS 3 to -0.38 ± 0.04 between UD and SCS 1 and SCS 2 . Slow genetic progress is expected when selection is applied independently on SCS and udder type traits, due to the generally low heritability estimates. Low, shallow udders with narrowly placed teats are associated with low SCS in the South African Holstein population. _______________________________________________________________________________________

Two fixed regression testday models were applied for variance component estimation and prediction of breeding values for somatic cell score, using testday records of the first three lactations of South African Holstein and Jersey cows. The first model (ML-model) considered the testdays of the different lactations as different traits in a multiple-trait animal model and the second analysis (RM-model) treated later lactation records as repeated measures of the first lactation. Heritabilities from the RM-model were more in the range of literature estimates compared to that of the ML-model, i.e. 0.19 ± 0.003 for the Holstein breed and 0.18 ± 0.003 for the Jersey breed. Rank correlations indicated that minor changes occur in the ranking of proven sires between breeding values obtained from the ML-and RM-models. Although genetic correlations between parities are not unity, the RM-model estimates more competitive variances and requires extensively less computer time to predict breeding values compared to the ML-model and are therefore recommended for breeding value estimation on a national basis. _______________________________________________________________________________________

Well-defined breeding objectives form the basis of sound genetic improvement programmes. Breeding objectives for Holstein cattle in South Africa were developed in the current study. Economic values were calculated for those economically relevant traits that had adequate bio-economic data, namely milk volume, fat yield, protein yield, liveweight, longevity, calving interval and somatic cell score (SCS). A bio-economic herd model for pasture-based and concentrate-fed systems in South Africa was used to calculate economic values by determining changes in profit arising from an independent unit increase in each trait. Alternative payment systems were used from four major milk buyers in South Africa. Relative economic values, standardized to the value of protein yield, were used to compare the relative importance of traits. Protein yield and longevity consistently had positive economic values and the converse was true for liveweight and calving interval. Economic value for volume was positive or negative, depending on whether the payment system rewarded or ignored volume. Sensitivity analysis showed that economic values were reasonably robust against fluctuations in the cost of feed and price of beef; with the exception of fat yield, whose value became negative when feed price exceeded ZAR 3.50. Generally, protein yield was the most important trait, although volume, longevity and SCS were more important in some situations. Calving interval was the least important trait, its value ranging from 4% to 22% of protein yield, although the model may have underestimated its value. Further work should focus on facilitating the wide adoption of these breeding objectives by industry. ______________________________________________________________________________________

A multi-trait animal model was used to estimate genetic parameters among lactation somatic cell score (SCS) and udder-type traits in South African Jersey cattle, through restricted maximum likelihood (REML) procedures. Data comprised records on 18 321 Jersey cows in 470 herds, collected through the National Milk Recording Scheme from 1996 to 2002. Average SCS in the first three lactations (SCS 1 , SCS 2 and SCS 3 ) were considered as different traits and the udder-type traits were fore udder attachment (FUA), rear udder height (RUH), rear udder width (RUW), udder cleft (UC), udder depth (UD), fore teat placement (FTP), rear teat placement (RTP) and fore teat length (FTL). Heritability estimates for the respective lactation SCS were 0.07 6 0.01, 0.11 6 0.01 and 0.11 6 0.02. Udder-type traits had heritability estimates ranging from 0.14 6 0.01 for UD to 0.30 6 0.02 for FTL. Genetic correlations between SCS and udder-type traits ranged from 20.003 6 0.07 between FUA and SCS 3 to 20.50 6 0.07 between UD and SCS 3 . Slow genetic progress is expected when selection is applied independently on SCS and udder-type traits, due to the generally low heritabilities. Tightly attached shallow udders with narrowly placed rear teats are associated with low SCS in the Jersey population.

An online survey on the state of existing dairy data, dairy improvement infrastructure and human capacity in sub-Saharan Africa (SSA) was undertaken with the aim of assessing whether the state of existing animal recording, dairy improvement methods and key issues facing dairy production together with means of addressing the issues differ among countries and regions of SSA. Respondents comprised experts and practitioners in livestock production and genetic resources from research institutes, animal breeding companies, universities, non-governmental organisations and government agricultural ministries. The main dairy farming system in which the respondents were involved was mixed crop-livestock system (30.2%), and this was mainly practised in the private land tenure system (46.3%). Data were analysed using linear model and paired Student t test in R software package. Respondents identified key issues affecting dairy production as poor genetic assessment of imported exotic breeds and crosses in Africa (62.3%), fluctuations in milk prices within both the formal and informal markets (50.9%), no comprehensive sire ranking systems (39.6%), housing and health management regimes which adversely affect milk yield (32.1%), poor market networks for dairy products (25.5%), poor feeding (13.3%), inadequate genetic technologies (9.4%) and poor animal performance recording systems (9.4%). Respondents emphasised the need for updated breeding policies, sire ranking systems, adequate farm management systems, capacity building, across-country collaborations and joint genetic assessments of dairy breeds found in sub-Saharan Africa. The current situation of dairy production though similar for the different countries, differed in order of emphasis and magnitude across the countries and regions in sub-Saharan Africa.