Copy number variation discovery in South African Nguni-sired and Bonsmara-sired crossbred cattle

SUPPLEMENTARY MATERIALS : TABLE S1: Information on the crossbred animals used in this study, TABLE S2: Sequencing depth and mapped reads of Nguni-sired and Bonsmara-sired crossbreds, FIGURE S1: CNV summary statistics of Copy number (CN) and number of CNVs for each CN class, FIGURE S2: Bar plot displaying the contribution of each copy number class to the total number of CNV calls per chromosome for all crossbred individuals, TABLE S3: All the CNVs detected in the crossbreds.DATA AVAILABILITY STATEMENT : The raw data supporting the conclusions of this article will be made available by the authors upon reasonable request in line with ARC intellectual property regulations.Crossbreeding forms part of Climate-Smart beef production and is one of the strategies to mitigate the effects of climate change. Two Nguni-sired and three Bonsmara-sired crossbred animals underwent whole genome sequencing. Following quality control and file preparation, the sequence data were investigated for genome-wide copy number variation (CNV) using the panelcn.MOPS tool. A total of 355 CNVs were identified in the crossbreds, of which 274 were unique in Bonsmara-sired crossbreds and 81 unique in the Nguni-sired crossbreds. Genes that differed in copy number in both crossbreds included genes related to growth (SCRN2, LOC109572916) and fertility-related factors (RPS28, LOC1098562432, LOC109570037). Genes that were present only in the Bonsmara-sired crossbreds included genes relating to lipid metabolism (MAF1), olfaction (LOC109569114), body size (HES7), immunity (LOC10957335, LOC109877039) and disease (DMBT1). Genes that were present only in the Nguni-sired crossbreds included genes relating to ketosis (HMBOX1) and amino acid transport (LOC109572916). Results of this study indicate that Nguni and Bonsmara cattle can be utilized in crossbreeding programs as they may enhance the presence of economically important traits associated with both breeds. This will produce crossbred animals that are good meat producers, grow faster, have high fertility, strong immunity and a better chance of producing in South Africa’s harsh climate conditions. Ultimately, this study provides new genetic insights into the adaptability of Nguni and Bonsmara crossbred cattle.Climate change plays a major role in livestock production. Hence the utilization of crossbreeding strategies allows for the improvement of animal production during harsh environmental conditions. The aim of this study was to identify the genetic differences in the F1 Nguni × Bonsmara and its reciprocal cross (Bonsmara × Nguni). This was achieved by studying the changes in structural variation, such as copy number variants in these two crosses. The major findings from this study have revealed several genes relating to adaption in these crossbred cattle.The National Research Foundation of South Africa.https://www.mdpi.com/journal/animalsBiochemistryGenetic

A balanced perspective on the importance of extensive ruminant production for human nutrition and livelihoods and its contribution to greenhouse gas emissions

There is a general perception that ruminants produce large quantities of greenhouse gases which contribute to global warming. Sometimes percentages are quoted out of context. For example, the percentage quoted for developed countries indicates the greenhouse gas contribution from livestock is less than 6%, while that for developing countries is 40–50%. However, the reason for this relatively low contribution from developed countries is because of very high contributions from other sectors. Ruminant production also is in the spotlight as it is the world’s largest user of land and South Africa is no exception. Only ruminants can utilise areas of non-arable land where the vegetation is rich in fibre and convert this fibre into high-quality nutrients for human consumption. Foods from animal sources (including ruminants) are essential for the human diet, as they support early childhood and cognitive development. Many rural households depend on ruminants and these animals are central to the livelihoods and well-being of these communities. The negative effects of red meat on human health and the negative environmental impact of livestock production are overemphasised, while the higher bioavailability of nutrients from livestock source foods, which stimulates mental and cognitive development compared to vegetarian or grain based foods, is ignored. Here we estimate that livestock are responsible for only 4% of the world’s greenhouse gases through methane production. We also highlight that if the high fibre vegetation is not utilised by livestock, it will still produce greenhouse gases through burning or rotting, without any benefit to humans. Livestock source foods are important if global nutritional, educational and economic needs are to be met; and this message should be conveyed to the public. Significance: We propose that a balanced message should be conveyed to the broader scientific community and the public on the role of livestock in meeting global nutritional needs and contributing to global warming. Livestock source foods are important if the global nutritional, educational and economic needs are to be met and can be used to feed developing countries out of poverty

Evaluation of partial body weight for predicting body weight and average daily gain in growing beef cattle

peer-reviewedInformation on body weight and average daily gain (ADG) of growing animals is key not only to monitoring performance, but also for use in genetic evaluations in the pursuit of achieving sustainable genetic gain. Accurate calculation of ADG, however, requires serial measures of body weight over at least 70 days. This can be resource intensive and thus alternative approaches to predicting individual animal ADG warrant investigation. One such approach is the use of continuously collected individual animal partial body weights. The objective of the present study was to determine the utility of partial body weights in predicting both body weight and ADG; a secondary objective was to deduce the appropriate length of test to determine ADG from partial body weight records. The dataset used consisted of partial body weights, predicted body weights and recorded body weights recorded for 8,972 growing cattle from a range of different breed types in 35 contemporary groups. The relationships among partial body weight, predicted body weight and recorded body weight at the beginning and end of the performance test were determined and calculated ADG per animal from each body weight measure were also compared. On average, partial body weight explained 90.7 ± 2.0% of the variation in recorded body weight at the beginning of the postweaning gain test and 87.9 ± 2.9% of the variation in recorded body weight at its end. The GrowSafe proprietary algorithm to predict body weight from the partial body weight strengthened these coefficients of determination to 95.1 ± 0.9% and 94.9 ± 0.8%, respectively. The ADG calculated from the partial body weight or from the predicted body weight were very strongly correlated (r = 0.95); correlations between these ADG values with those calculated from the recorded body weights were weaker at 0.81 and 0.78, respectively. For some applications, ADG may be measured with sufficient accuracy with a test period of 50 days using partial body weights. The intended inference space is to individual trials which have been represented in this study by contemporary groups of growing cattle from different genotypes.Vytelle LL

Evaluation of partial body weight for predicting body weight and average daily gain in growing beef cattle

Information on body weight and average daily gain (ADG) of growing animals is key not only to monitoring performance, but also for use in genetic evaluations in the pursuit of achieving sustainable genetic gain. Accurate calculation of ADG, however, requires serial measures of body weight over at least 70 days. This can be resource intensive and thus alternative approaches to predicting individual animal ADG warrant investigation. One such approach is the use of continuously collected individual animal partial body weights. The objective of the present study was to determine the utility of partial body weights in predicting both body weight and ADG; a secondary objective was to deduce the appropriate length of test to determine ADG from partial body weight records. The dataset used consisted of partial body weights, predicted body weights and recorded body weights recorded for 8,972 growing cattle from a range of different breed types in 35 contemporary groups. The relationships among partial body weight, predicted body weight and recorded body weight at the beginning and end of the performance test were determined and calculated ADG per animal from each body weight measure were also compared. On average, partial body weight explained 90.7 ± 2.0% of the variation in recorded body weight at the beginning of the post-weaning gain test and 87.9 ± 2.9% of the variation in recorded body weight at its end. The GrowSafe proprietary algorithm to predict body weight from the partial body weight strengthened these coefficients of determination to 95.1 ± 0.9% and 94.9 ± 0.8%, respectively. The ADG calculated from the partial body weight or from the predicted body weight were very strongly correlated (r = 0.95); correlations between these ADG values with those calculated from the recorded body weights were weaker at 0.81 and 0.78, respectively. For some applications, ADG may be measured with sufficient accuracy with a test period of 50 days using partial body weights. The intended inference space is to individual trials which have been represented in this study by contemporary groups of growing cattle from different genotypes

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

International audienceAbstractBackgroundUnderstanding the history of cattle breeds is important because it provides the basis for developing appropriate selection and breed improvement programs. In this study, patterns of ancestry and admixture in Afrikaner, Nguni, Drakensberger and Bonsmara cattle of South Africa were investigated. We used 50 K single nucleotide polymorphism genotypes that were previously generated for the Afrikaner (n = 36), Nguni (n = 50), Drakensberger (n = 47) and Bonsmara (n = 44) breeds, and for 394 reference animals representing European taurine, African taurine, African zebu and Bos indicus.Results and discussionOur findings support previous conclusions that Sanga cattle breeds are composites between African taurine and Bos indicus. Among these breeds, the Afrikaner breed has significantly diverged from its ancestral forebears, probably due to genetic drift and selection to meet breeding objectives of the breed society that enable registration. The Nguni, Drakensberger and Bonsmara breeds are admixed, perhaps unintentionally in the case of Nguni and Drakensberger, but certainly by design in the case of Bonsmara, which was developed through crossbreeding between the Afrikaner, Hereford and Shorthorn breeds.ConclusionsWe established patterns of admixture and ancestry for South African Sanga cattle breeds, which provide a basis for developing appropriate strategies for their genetic improvement