Genetic parameter estimates for daily predicted gross feed efficiency and its association with energy-corrected milk in South African Holstein cattle.

Genetic parameters for daily predicted gross feed efficiency (pGFE) and energy corrected milk (ECM) in the first three parities of South African Holstein cattle were estimated by repeatability animal models. Data comprised of 11,068 test-day milk production records of 1,575 Holstein cows that calved between 2009 and 2019. Heritability estimates for pGFE were 0.12 ± 0.06, 0.09 ± 0.04 and 0.18 ± 0.05 in early, mid and late lactation, respectively. Estimates were moderate for primiparous (0.21 ± 0.05) and low for multiparous (0.10 ± 0.04) cows. Heritability and repeatability across all lactations were 0.14 ± 0.03 and 0.37 ± 0.03, respectively. Genetic correlations between pGFE in different stages of lactation ranged from 0.87 ± 0.24 (early and mid) to 0.97 ± 0.28 (early and late), while a strong genetic correlation (0.90 ± 0.03) was found between pGFE and ECM, across all lactations. The low to moderate heritability estimates for pGFE suggest potential for genetic improvement of the trait through selection, albeit with a modest accuracy of selection. The high genetic correlation of pGFE with ECM may, however, assist to improve accuracy of selection for feed efficiency by including both traits in multi-trait analyses. These genetic parameters may be used to estimate breeding values for pGFE, which will enable the trait to be incorporated in the breeding objective for South African Holstein cattle.

Prediction of dry matter intake and gross feed efficiency using milk production and live weight in first-parity Holstein cows.

Direct measurement of dry matter intake (DMI) presents a major challenge in estimating gross feed efficiency (GFE) in dairy cattle. This challenge can, however, be resolved through the prediction of DMI and GFE from easy-to-measure traits such as milk production (i.e. milk yield, energy-corrected milk (ECM), butterfat, protein, lactose) and live weight (LW). The main objective of this study was, therefore, to investigate the feasibility of predicting dry matter intake and gross feed efficiency for first-parity Holstein cows using milk production traits and LW. Data comprised of 30 daily measurements of DMI and milk production traits, and 25 daily LW records of a group of 100 first-parity Holstein cows, fed a total mixed ration. Gross feed efficiency was calculated as kg ECM divided by kg DMI. The initial step was to estimate correlations of milk production traits and LW with DMI and GFE, to identify the best potential predictors of DMI and GFE. Subsequently, a forward stepwise regression analysis was used to develop models to predict DMI and GFE from LW and milk production traits, followed by within-herd validations. Means for DMI, butterfat yield (BFY) and LW were 21.91 ± 2.77 kg/day, 0.95 ± 0.14 kg/day and 572 ± 15.58 kg/day, respectively. Mean GFE was 1.32 ± 0.22. Dry matter intake had positive correlations with milk yield (MY) (r = 0.32, p < 0.001) and LW (r = 0.76, p < 0.0001) and an antagonistic association with butterfat percent (BFP) (r = - 0.55, p < 0.001). On the other hand, GFE was positively associated with MY (r = 0.36, p < 0.001), BFP (r = 0.53, p < 0.001) and BFY (r = 0.83, p < 0.0001), and negatively correlated with LW (r = - 0.23, p > 0.05). Dry matter intake was predicted reliably by a model comprising of only LW and MY (R2 = 0.79; root mean squared error (RMSE) = 1.05 kg/day). A model that included BFY, MY and LW had the highest ability to predict GFE (R2 = 0.98; RMSE = 0.05). Live weight and BFY were the main predictor traits for DMI and GFE, respectively. The best models for predicting DMI and GFE were as follows: DMI (kg/day) = - 54.21 - 0.192 × MY (kg/day) + 0.146 × LW (kg/day) and GFE (kg/day) = 4.120 + 0.024 × MY (kg/day) + 1.000 × BFY (kg/day) - 0.008 × LW (kg/day). Thus, daily DMI (kg/day) and GFE can be reliably predicted from LW and milk production traits using these developed models in first-parity Holstein cows. This presents a big promise to generate large quantities of data of individual cow DMI and GFE, which can be used to implement genetic improvement of feed efficiency.

Genetic diversity and population structure of three native cattle populations in Mozambique.

In the present work, the population diversity and structure of three populations of native Mozambican cattle were studied, to develop knowledge that is required for sound conservation and genetic improvement programs of these genetic resources. A total of 228 animals (Landim, Angone, and Tete) were genotyped using the International Dairy and Beef version three (IDBV3) SNP BeadChip array. Population parameters varied within a limited scope, with the average minor allele frequency (MAF) ranging from 0.228 ± 0.154 in the Angone to 0.245 ± 0.145 in the Tete population, while estimates of expected heterozygosities varied from 0.304 ± 0.166 in the Angone to 0.329 ± 0.148 in the Tete population. Low positive (0.065 ± 0.109) inbreeding rates were detected in the three cattle groups. Population structure and admixture analyses indicated low genetic differentiation and various degrees of admixture among the populations. The effective population size has decreased over time and at 12 generations ago ranged between 349 (Tete) and 929 (Landim). The average linkage disequilibrium (LD) of the studied populations ranged from 0.400 ± 0.213 (Tete) to 0.434 ± 0.232 (Landim). The findings of this study will be valuable for formulating management and conservation strategies for indigenous Mozambican cattle populations.

Genetic diversity and relationships among three Southern African Nguni cattle populations.

The Nguni cattle breed has distinct populations that are adapted to the different ecological zones of Southern Africa. This study was carried out to assess genetic diversity and establish the relationships among South African (SA), Mozambican (Landim), and Swazi Nguni cattle populations, using 25 microsatellite markers. Genotypic data were generated from deoxyribonucleic acid (DNA) samples of 90 unrelated individuals of the three cattle populations, collected from government conservations and stud herds. DNA profiles of five local beef breeds were used as the reference populations. Most of the 25 microsatellite markers were highly polymorphic across the studied populations, with an overall polymorphic information content (PIC) mean of 0.676. Genetic diversity within populations was high with expected heterozygosity varying from 0.705 ± 0.024 (Landim) to 0.748 ± 0.021 (SA Nguni) and mean number of alleles being highest in the SA Nguni (7.52 ± 0.42). Average observed heterozygosity (0.597 ± 0.046) compared to the expected heterozygosity (0.719 ± 0.022) was lowest for the Swazi Nguni, which also had a high number of Hardy-Weinberg Equilibrium (HWE) deviated loci (13), confirming the relatively high level of inbreeding (0.158 ± 0.058) in that population. Analysis of molecular variance revealed only 9.61% of the total variation between the populations and 90.39% within populations. A short genetic distance (0.299) was observed between Landim and Swazi Nguni, with the SA Nguni (> 0.500) being the most genetically distant population. The distant relationship between SA Nguni and the other two Nguni cattle populations was further confirmed by a principal coordinates analysis. The three Nguni populations clustered independently from each other, despite some evidence of admixture. Therefore, it can be concluded that SA Nguni, Landim, and Swazi Nguni populations in Southern Africa exhibit high levels of genetic diversity and are genetically distant; with the two latter populations being less genetically apart. These results present useful information for the development of strategies for regional management of animal genetic resources, through conservation and sustainable utilisation.

Use of factor scores for predicting body weight from linear body measurements in three South African indigenous chicken breeds.

Body weight and weight of body parts are of economic importance. It is difficult to directly predict body weight from highly correlated morphological traits through multiple regression. Factor analysis was carried out to examine the relationship between body weight and five linear body measurements (body length, body girth, wing length, shank thickness, and shank length) in South African Venda (VN), Naked neck (NN), and Potchefstroom koekoek (PK) indigenous chicken breeds, with a view to identify those factors that define body conformation. Multiple regression was subsequently performed to predict body weight, using orthogonal traits derived from the factor analysis. Measurements were obtained from 210 chickens, 22 weeks of age, 70 chickens per breed. High correlations were obtained between body weight and all body measurements except for wing length in PK. Two factors extracted after varimax rotation explained 91, 95, and 83% of total variation in VN, NN, and PK, respectively. Factor 1 explained 73, 90, and 64% in VN, NN, and PK, respectively, and was loaded on all body measurements except for wing length in VN and PK. In a multiple regression, these two factors accounted for 72% variation in body weight in VN, while only factor 1 accounted for 83 and 74% variation in body weight in NN and PK, respectively. The two factors could be used to define body size and conformation of these breeds. Factor 1 could predict body weight in all three breeds. Body measurements can be better selected jointly to improve body weight in these breeds.

Livestock phenomics and genetic evaluation approaches in Africa: current state and future perspectives.

The African livestock sector plays a key role in improving the livelihoods of people through the supply of food, improved nutrition and consequently health. However, its impact on the economy of the people and contribution to national GDP is highly variable and generally below its potential. This study was conducted to assess the current state of livestock phenomics and genetic evaluation methods being used across the continent, the main challenges, and to demonstrate the effects of various genetic models on the accuracy and rate of genetic gain that could be achieved. An online survey of livestock experts, academics, scientists, national focal points for animal genetic resources, policymakers, extension agents and animal breeding industry was conducted in 38 African countries. The results revealed 1) limited national livestock identification and data recording systems, 2) limited data on livestock production and health traits and genomic information, 3) mass selection was the common method used for genetic improvement with very limited application of genetic and genomic-based selection and evaluation, 4) limited human capacity, infrastructure, and funding for livestock genetic improvement programmes, as well as enabling animal breeding policies. A joint genetic evaluation of Holstein-Friesian using pooled data from Kenya and South Africa was piloted. The pilot analysis yielded higher accuracy of prediction of breeding values, pointing to possibility of higher genetic gains that could be achieved and demonstrating the potential power of multi-country evaluations: Kenya benefited on the 305-days milk yield and the age at first calving and South Africa on the age at first calving and the first calving interval. The findings from this study will help in developing harmonized protocols for animal identification, livestock data recording, and genetic evaluations (both national and across-countries) as well as in designing subsequent capacity building and training programmes for animal breeders and livestock farmers in Africa. National governments need to put in place enabling policies, the necessary infrastructure and funding for national and across country collaborations for a joint genetic evaluation which will revolutionize the livestock genetic improvement in Africa.

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

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.