Exploring the financial implications of bovine babesiosis

The financial implications of endemic stability as a control strategy for Bovine babesiosis in veld grazing beef production systems of the KwaZulu-Natal Midlands

Industry Sector: Cattle and Small Stock

Research focus area: 

  • Animal Health & Welfare

Research Institute: University of Pretoria

Researcher: Francis Edwardes

Research Team

Title Initials Surname Highest Qualification Research Institution
Doctor W Hoffmann PhD Stellenbosch University
Title Initials Surname Highest Qualification Research Institution
Prof H Hogeveen   WUR

Completion: 2020

Aims of the project

  • Develop a model which can provide an estimate of the economic impact and financial implications of bovine babesiosis has at the herd level of a typical farm in the KwaZulu-Natal Midlands with the available data and existing research efforts.
  • Financially compare the established dipping strategies of the KwaZulu-Natal Midlands as a result of the developed model highlighted in point above.
  • Establish factors in which data relevant to the research problem is scarce or non-existent encountered through the development of the model as in the points above.
  • Establish the need for correct data collection by farmers when confronted with an infected animal in relation to point above.
  • Suggest methods of data collection in relation to Points 3 and 4 and further research opportunities in order to develop more accurate estimates of cost-effective management options.

Executive Summary

In South Africa, cattle production has increased by 46% in 2014 compared with 2005. Local consumption trends indicate that the country is a net importer of bovine meat products, due to the supply not capable of meeting demand requirements. The country’s projected population growth of 1.2% and the expected rise in beef consumption by 24% over the next ten years will require farmers to produce at greater efficiencies to meet local demand and to reverse the trade role it currently finds itself in. However, agricultural production comes with many challenges. Production diseases, such as the myriad of tick-borne diseases, are partly responsible for the challenges agriculturalists face. Amongst these, bovine babesiosis is considered as one the greatest economically important tick-borne diseases in South Africa.

Pathogenic parasites, such as Babesia bigemina and Babesia bovis, are responsible for the cause of this disease. The distribution of the parasites are directly related to the distribution of their vectors; B. bigemina has a greater distribution than that of B. bovis. Primary transmissions of B. bigemina in cattle older than nine months are less virulent when compared with B. bovis. Production losses can occur in the form of mortality, weight loss and abortions by varying degrees for either parasite. These losses coupled with treatment and prevention expenditure can result in significant costs for a farmer.  A prevention strategy that has long been discussed is to apply the concept of endemic stability. This means that the cattle are provided the opportunity to take advantage of their non-specific immunity through less aggressive tick eradication methods in order for herd resistance to develop over time.

Bovine babesiosis is considered a globally important disease and is one of South Africa most economically pertinent tick-borne diseases. However, no conclusive literature has been published regarding the economic impact caused by bovine babesiosis in South Africa and is known to be a problem since at least the early 1980’s. If bovine babesiosis is regarded with such high economic importance, why has there been little economic or financial research conducted internationally? Furthermore, why has South Africa not conducted exploratory economic or financial research studies in the last 35 years in an attempt to address this concern? The concept of developing a state of endemic stability through less aggressive acaricide applications is an intervention which has been suggested and is slowly implemented by the countries farmers, but no economic and financial insight is provided to those who implement this method of control.

The main research question for this study is; what is the value of adopting a strategic dipping option in an attempt to promote the development of endemic stability compared with an intensive acaricide treatment routine? By doing so, this study asks a question pertaining to the economic impact and financial implications of developing endemic stability by implementing a strategic dipping intervention. The study will be conducted at the herd level within the KwaZulu-
Natal Midlands and is compared with an intensive dipping approach.

Results

Preceding model development and the definition of various scenarios, simulations were run and results were analysed. For the sake of this executive summary, only the production, financial and economic analyses are presented.

The production effects of B. bigemina and B. bovis were translated into an economic impact assessment and a financial analysis of each dipping strategy per parasite prevalence.

The economic impact and financial analyses of either dipping strategy and respective scenario were compared. The economic impact assessment included the sum of all discounted costs as a result of disease prevalence and severity after a primary infection had occurred in either the breeding cows, weaners and calves in each one of the fifteen simulated years. The financial analysis included all the cash in- and outflows directly related to the production of beef weaners in the face of a bovine babesiosis challenge respective of the parasite prevalence and resulting disease severity. In light of a B. bigemina infection, the economic impact in Scenario 2 to 4 was greater for strategic dipping but less than intensive dipping in Scenario 1.

The economic consequences for intensive dipping decreased by an average of R21 115.34, with a range from R15 925.43 to R23 954.69, for each decrease in seroprevalence as per the respective scenarios. Adversely, the economic impact of strategic increased with a decrease in seroprevalence. Scenario 1 incurred the lowest impact of R82 082.86 and the greatest consequence of R95 679.96 was achieved in Scenario 4. The greatest component of the economic cost in each strategic dipping scenario was the value of weight lost consisting an average of 76% in each year. Dipping and treatment costs consisted of 10% and 9% in each year. The balance consists of recovery feed and compensatory growth costs. The value of weight lost cost component for an intensive dipping programme was greatest in Scenario 1, 2 and 3 consisting 67%, 63% and 53% of the total economic impact, respectively. This is followed by the dipping expenditure component which made up 21%, 25% and 36% of the total economic cost in each year. Dipping expenditures in Scenario 4 are greatest at 66% of the total economic cost followed by the value of weight lost at 29%. Treatment costs for Scenario 1 to three comprised 9% of the economic costs in each year and 5.0% in Scenario 4. The balance of the economic impact consists of recovery feed and compensatory feed costs. Results of the financial analyses for either dipping strategy and the respective scenarios indicate that the intensive prevention is a better financially viable option regardless of the parasite seroprevalence, and is indicated by the larger NPV and IRR values achieved.

The economic consequences of B. bovis are greater than that of the impacts realised due to B. bigemina. In all scenarios, the total economic cost of B. bovis is greater for strategic dipping when compared with the respective scenarios of intensive dipping. The largest cost component in strategic dipping is the value of weight lost as a result of a greater number of acute deaths and the longer duration of a recoverable infection. The value of weight lost held at an average of 95% of the total economic impact per year for either scenario of strategic dipping followed by treatment costs at 2.0%. The mean value of weight lost for intensive dipping in Scenario 1 to 3 made up 94% of the total economic cost while in Scenario 4 it is 8.0% less. Treatment costs outweighed dipping expenditures in Scenarios 1 and 2 whereas the latter component is greater than the former in Scenario 3 and 4. The economic impact realised in intensive dipping decreased by an average of R320 418.40, with a range from R244 736.00 to R362 558.30, with each decrease in seroprevalence as per the respective scenarios. Adversely, the economic impact increased from R1 255 592.16 to R1 492 277.39 with each respective decrease in seroprevalence. Despite the larger economic impact realised in all scenarios of strategic dipping, the financial analysis indicates that strategic dipping is more financially viable in Scenario 1 where a greater NPV is achieved. The conflict between NPV and IRR is resolved by identifying a cross-over rate of 7.89%. This indicates that strategic dipping is the more profitable prevention programme to choose while the interest rate remains below or equal to the cross-over rate and the seroprevalence of B. bovis is at 90%. In Scenario 2 to 4, intensive dipping is the more financially viable option to choose due to the greater NPV and IRR values realised.

Conclusion

The objectives of this study have been achieved. A dynamic stochastic model was developed to simulate the economic impact of bovine babesiosis a typical beef farm of the KZN Midlands would encounter where one of two dipping strategies are applied. A financial analysis of the cash in- and outflows was performed for either dipping strategy based on the data generated by the simulations. However, the model is limited in its performance due to various assumptions that were specified. Assumptions were made due to data collection difficulties.

Considering the limitations of this model, the overall results indicate that intensive dipping realises greater benefits. These benefits are increased as the seroprevalence decreases towards a 0% situation as demonstrated when NPV results are compared with those of a healthy farm. This suggests achieving a disease-free situation by means of parasite eradication. This study does not attempt to offer economic or financial insight as to the attainment of this state. Eliminating disease through eradication will contribute to an increase in animal welfare since fewer animals will have to undergo clinical infections in order for the farmer to achieve the state of endemic stability. Current results indicate that the concept of creating endemic stability as a control strategy is not a financially viable option. It is imperative to understand that these results are inconclusive due to the lack of available data as well as the limited research efforts concerned with various production effects of the disease. Emphasis is thus placed on the need for more stringent data collection routines and research efforts in order to effectively analyse the impact of various control strategies of bovine babesiosis from an economic perspective. The economic cost component of the model in this study has been developed as a foundation for future economic research in the realm of bovine babesiosis.

Objective Statement

The objective is to establish a set of principles enabling further economic and financial research to be pursued by primarily exploring the value of adopting a strategic dipping option in an attempt to promote the development of endemic stability compared with intensive acaricide prevention. This exploratory research should provide estimates identifying the economic consequences and financial implications of bovine babesiosis at the herd-level for either dipping strategy.

POPULAR ARTICLE

The economic impact of redwater and the need for data associated with the production effects of the disease

WFI Edwardes; Dr W Hoffmann

Bovine babesiosis, more commonly known as redwater in South Africa, is considered as one of the country’s most economically important tick-borne diseases. This is certainly not new information since the disease has been tagged with a label of economic importance for at least 35 years. Despite this dangling red tag of economic threat, little is known about the actual costs incurred by various stakeholders in the South African beef industry. The most recent economic impact estimate is reflected in an average annual expenditure of R5.1 million on babesicides. But how does this information help those that are affected the most by the disease; perhaps the producers? Furthermore, why has there been little to no economic research conducted to shed a little more light on this economically important disease?

A masters research study from Stellenbosch University was established to explore the economic consequences of redwater in veld grazing beef production systems of the KwaZulu Natal Midlands. For producers, research concerning the economic impact of disease is important so that a benchmark cost is known in order to compare the feasibility of other disease mitigation strategies with a current management strategy. Estimating the cost of redwater comes with difficulties due to the scarcity in data concerning the production effects of this disease in various management systems. The lack of data is a regular constraint in other economic impact assessments of disease. To cope with data scarcity, the first objective of our research was to develop a simulation model in which can provide cost estimates of African and Asiatic redwater at the herd- and cow-level based on available data and existing research efforts. The second objective was to establish factors in which data relevant to the research problem is scarce or non-existent encountered through the development of the model, in turn emphasising the need for greater data collection efforts.

A typical farm model was developed for the design of this exploratory research. An intensive dipping management strategy was chosen since it has long been the approach to manage tick populations, and therefore the transmission of the Babesia parasites, before the more recent approach of strategic dipping in order to promote the development of endemic stability. Other prevention measures such as blocking and blooding were excluded due to the lack of data. The chosen factors in which redwater affected production were the cost of mortality, weight loss, compensatory growth. The cost of recovery feed, treatment and dipping is also included. Four seroprevalence scenarios for Babesia bigemina and Babesia bovis, the respective parasites responsible for the cause of African and Asiatic redwater, were simulated. The scenarios included seroprevalence levels of i) 10% as per a situation of minimal disease; ii) 40% as per an endemically unstable situation; iii) 70% as per a situation approaching endemic stability, and iv) 90% as per an endemically stable situation. Using the seroprevalence and the average age of the herd the inoculation rate could be estimated. The inoculation rate is defined as the daily probability that an animal may receive a Babesia infection.

Simulation results, summarised in Figure 1, prove that Asiatic redwater is cause for greater concern. A comparison between the Babesia seroprevalence levels show that the economic cost of Asiatic redwater per breeding cow is on average ten fold that of African redwater. The value of weight loss either as a result of acute deaths or reduced weight gains following an infection is responsible makes up the largest cost component in all scenarios for both diseases, results are summarised in Table 1. Further investigation identified which animal cohort – cow, calf and weaner – yield the greatest economic cost given the inoculation rate for each simulated seroprevalence scenario. As illustrated in Figure 2 the economic impact is greatest in cow cohorts for lower seroprevalence levels. In higher seroprevalence scenarios the economic impact is felt greatest in weaner cohorts. This may be due to the calves being weaned where too few of them have received a primary infection before the age of nine months, resulting in too few attaining a non-specific immunity, but enough such that a risky population of Babesia parasites are harboured in the newly formed weaner cohort. Thus, more weaners receive a primary infection in which a non-specific immunity can no longer be attained. In our research, we attempted to simulate the economic impact of a strategic dipping strategy for the same herd. However, it was quickly discovered that results would not be reliable since there was not enough data to serve as input for this prevention strategy.

The objectives of this research were achieved in which a model was developed to explore the economic impact of redwater at the herd- and cow-level. Through the process of conducting this study, many constraints were encountered. These were largely in the form of scarce or non-existent data. Data concerning the production effects of redwater on Bos indicus cross Bos taurus breeds are not enough. Research efforts have investigated effects of the disease on certain variables such as weight loss, compensatory weight gain during recovery and are more concerned with Bos taurus breeds. Therefore, studies as such should be continued but more focus should be placed on the cross breeds. No studies were available concerning the effect that redwater had on milk production – and the subsequent effects it would have on calf growth, fertility, abortion and replacement. This gap in the literature should be addressed by livestock scientists and veterinarians. Greater knowledge pertaining to the effects of these production variables will lead to better cost estimates and the promotion of various cost-effective intervention strategies. Babesia bovis should continue to be the primary researched parasite due to its greater impact on production. The collection of data by farmers encountering such production effects should also be documented more strictly. Most farmers acknowledge the presence of the disease but do not document it and the resulting production effects; such data can aid research. This, however, is a challenging task as it requires the farmer to know the current seroprevalence amongst his/her heard and to continuously check its status throughout the year, to maintain strong relationships with the veterinarians in the area in order to correctly diagnose a sick animal and to communicate the data between the actors effectively. This may be costly for a farmer and lead to further economic studies researching the economic value of continuous Babesia seroprevalence monitoring in a herd.

In conclusion, this research has laid down the first stepping stone in the path of exploring the economic impact of redwater. Estimating the economic impact of redwater may only tell us something we already know, but without a cost estimate of redwater research can not compare the costs of alternative management strategies to a “norm”. Therefore, the need for more data associated with the production effects of redwater is emphasised. With the collective efforts of those in practice and research with an aim to collect data, more light will be shed on redwater for the benefit of the beef industry.

Please contact the Primary Researcher on the project if you need a copy of the comprehensive report – franco.edwardes@gmail.com

TrichLabCheck – A voluntary trichomonosis inter laboratory comparison project

TrichLabCheck – A voluntary trichomonosis inter laboratory comparison project in South Africa

Industry Sector: Cattle and Small Stock

Research focus area: 

  • Animal Health and Welfare

Research Institute: University of Pretoria

Researcher: Dietmar Holm

Research Team

Title Initials Surname Highest Qualification Research Institution
Dr T Zangure BVSc University of Pretoria

Completion: 2020

Aims of the project

  • This study aimed to validate the accuracy of voluntarily enrolled private (n = 8) and state-owned (n = 5) laboratories that perform trichomonosis diagnostic tests by estimating the sensitivity (Se) and specificity (Sp) per laboratory. It was hypothesized that diagnostic laboratories in South Africa play an insignificant role in the inaccuracy of the diagnosis of trichomonosis.

Executive Summary

Trichomonosis is currently the most important venereal disease of cattle in South Africa with adverse economic implications to the beef production industry due to cow abortions, infertility and culling of carrier bulls. Once diagnosed in a herd, eradication is difficult due to financial and biological implications. Bulls are asymptomatic carriers and susceptibility increases with age. In infected females, clinical signs include embryonal death, abortion, pyometra, foetal maceration and uterine discharge.

Diagnostic accuracy is one of the major clinical problems preventing easy eradication of trichomonosis from a herd and can be influenced by biological variance in the occurrence of the organism, sampling errors, sample degradation during sample transport and diagnostic laboratory inaccuracies.

Objective Statement

The objective of the project was to determine the role that diagnostic laboratories play in the inaccuracies of trichomonosis diagnosis in South Africa.

Results

Laboratories performed either the culture method (n = 5), polymerase chain reaction (PCR) (n = 6) or a combination of culture and PCR (n= 2). Fresh preputial scrapings from four bulls with known negative status for trichomonosis were pooled in 200ml of phosphate buffered saline (PBS) to form the sample base for 12 subsamples of 13ml each. Duplicate subsamples were then contaminated with 2ml originating from four different laboratory cultures of Tritrichomonas foetus or 2ml of culture medium for four negative samples. Aliquots of the subsamples were transferred to an anaerobic transport medium, and the final concentration reached in these samples submitted to the laboratories, were categorised as follows: weak (30 organisms/μl). A total of 312 samples were sent by courier in two separate rounds: eight (4 duplicates) positive and four negative samples per round. Multiple logistic regression was performed on sensitivity, using sampling round, laboratory sector, diagnostic test type and sample concentration as independent variables, and removing variables in a stepwise manner based on the highest P-value.

Two public laboratories only reported on one round of sampling, and one batch of 12 samples was severely delayed in reaching another public laboratory. The sample identifications of a further two batches were not recorded by the respective private laboratories. The results from these 60 unreported samples were not included in the analysis. Laboratories that performed the PCR assay (solely, or in addition to culture) were grouped for data analysis. The overall specificity (Sp) was 100% and the sensitivity was 88.7% (95% CI 83.9% – 93.5%). Laboratories using PCR recorded higher sensitivity than those using the culture method (95.5%; 95% CI 91.0% – 99.9% and 81.3%; 95% CI 72.5% – 90.0% respectively, P < 0.01), and private laboratories recorded higher Se than public laboratories (96.4%; 95% CI 92.9% – 99.9% and 73.2%; 95% CI 61.2% – 85.2%, P < 0.01). For laboratories using PCR, weak positive samples recorded a lower sensitivity than strong positive samples (86.4%; 95% CI 70.8% – 101.9% and 100%; 95% CI 100% – 100%, respectively, P < 0.01). One public and six private laboratories obtained 100% accuracy during the two sampling rounds.

In the logistic regression model, private sector (compared to public), an increasing concentration of organisms in the sample and the second round of sampling (compared to the first round) were independent predictors of laboratory sensitivity for the detection of Tritrichomonas foetus.

Conclusion

It is concluded that inaccuracies in the diagnostic laboratory contributes to the deficiencies in diagnostic sensitivity for trichomonosis in South Africa, but does not influence diagnostic specificity. It is further concluded that diagnostic sensitivity was independently influenced by the sector in which the laboratory operates (private vs public) and the concentration of Tritrichomonas foetus organisms in the sample.

POPULAR ARTICLE

Trichomonosis: what role does the laboratory play in combating the disease?

Prof Dietmar Holm

INTRODUCTION

Trichomonosis is a venereal disease of cattle that results in significant losses to the beef industry in particular, due to a severe reduction in the reproductive potential of beef herds. The disease occurs worldwide and is currently widespread in South Africa. In many cases herds are infected without the knowledge of the farmer, because there are often no external signs visible in the cattle. This means that without knowing, farmers loose thousands of rands in potential income due to the loss of unborn calves.

The diagnosis of trichomonosis is done on bulls, and must be performed by a qualified veterinarian only. Incorrect sampling results in incorrect diagnosis, which means that a farmer will remain in the dark about the status of his or her cattle herd. After collecting samples, they are submitted to a laboratory for diagnosis. This diagnosis can be done using different types of tests and must also be done under strict controlled conditions. Several laboratories in South Africa perform this service for veterinarians.

The nature of the disease is such that the diagnostic test is not 100% accurate, even when done by the correct professionals. In a recent study performed by the Faculty of Veterinary Science at the University of Pretoria, the role of diagnostic laboratories in the accuracy of the diagnostic test for trichomonosis was investigated. The TrichLabCheck research team, led by Prof Dietmar Holm, found that indeed in South Africa, amongst the 13 laboratories that voluntarily participated in the research, several false negative results were reported. There were no false positive results reported in this study to date, which is in line with similar studies done elsewhere in the world. This is important information for veterinarians and farmers in South Africa, who need to consider that in some cases a bull that tested negative may in actual fact be positive and needs to be tested again to confirm his negative status. It was found in this study that the average diagnostic sensitivity of all participating laboratories to detect trichomonosis was 88.7%. This means that potentially for every 10 positive bulls tested in South Africa, at least 1 will provide a false negative test result.

The research emphasises the need to perform repeated samples on individual bulls to confirm their individual negative status, or to test a large number of bulls in a given herd to confirm the negative status of a herd. It also highlights the fact that a negative test result of a single bull in a positive herd must be interpreted with care, because it may just be that the particular bull gave a negative test result when in fact he may be infected with the disease.

“Trichomonosis has been an increasing problem in South African beef cattle over the past decades, and we are hoping that farmers and veterinarians will use this research to be more vigilant in their diagnostic approach towards the disease”, prof Holm stated.

The research further confirmed that the number of Trichomonas organisms in the sample contributes to the accuracy of the test. This emphasises the importance of using only a qualified veterinarian to perform this important task on farms. Dr Tinashe Zangure, the masters student and veterinarian involved in this study confirmed that he gained excellent knowledge not only about the disease, but also about the importance that bull sampling and laboratory techniques play in the effort to combat the disease in cattle herds.

The University of Pretoria, in collaboration with the Ruminant Veterinary Association of South Africa, will soon be publishing a list of laboratories with acceptable levels of accuracy for trichomonosis. The research will be ongoing, and the list will be updated in an effort to ensure that the veterinary industry strive towards diagnostic excellence in South Africa.

Please contact the Primary Researcher on the project if you need a copy of the comprehensive report – dietmar.holm@up.ac.za

STEC from feedlot to abattoir

Epidemiology of Shiga toxin-producing Escherichia coli in beef cattle from feedlot through to abattoir

Industry Sector: Cattle and Small Stock

Research focus area: 

  • Red Meat Safety, Nutritional Value, Consumerism and Consumer Behaviour

Research Institute: University of Pretoria

Researcher: Peter Thompson

Research Team

Title Initials Surname Highest Qualification Research Institution
Prof. A.A. Adesiyun PhD University of Pretoria
Prof. E. Madoroba PhD ARC-OVI
Dr. K. Keddy PhD NICD

Completion: 2020

Aims of the project

  • To determine the prevalence, dynamics and factors associated with shedding of Shiga-toxin producing Escherichia coli (STEC) in feedlot cattle; To determine the relationship between faecal shedding of STEC in the feedlot and on arrival at the abattoir, and carcass contamination at various steps in the slaughter process.

Executive Summary

Shiga toxin-producing Escherichia coli (STEC) has emerged as an important foodborne pathogen globally with a significant impact on public health. Healthy colonized cattle are major reservoirs of STEC and bovine “super-shedders” are considered to play a key role in the entry of STEC into the food chain. The public health relevance is determined by the pathogen’s low infectious dose and capacity to survive and be transmitted along different stages in the beef production chain. Of the over 470 different serotypes of STEC detected in humans, the O157:H7 serotype is the most frequently associated with large food and water-borne outbreaks. However, non-O157 STEC have been increasingly isolated from sporadic cases of haemorrhagic colitis and the sometimes fatal haemorrhagic uremic syndrome. In a recent RMRD-funded project a high prevalence of STEC contamination of beef products was detected in retail outlets in Pretoria, suggesting that STEC may pose a real food-borne disease threat and that further investigation of the epidemiology of the pathogen is required. Since the majority of beef consumed passes through the feedlot system, it is essential that we understand the dynamics of shedding of the organism in the feedlot in order to identify control measures to reduce the bacterial challenge resulting in carcass contamination in the abattoir.

Objective Statement

The specific objectives of the study were (i) to determine the frequency and dynamics of shedding of STEC in cattle in a feedlot; (ii) to longitudinally follow tagged study animals to slaughter to determine the frequency of STEC contamination pre-slaughter, during slaughter and post-slaughter; (iii) to characterize STEC isolates with respect to their serotypes and presence of virulence factors; and (iv) to to establish the genetic relatedness of the isolates between feedlot and abattoir.

Results

On arrival at the feedlot, 27% (29/106; 95% CI: 19-37%) of faecal samples were STEC-positive on PCR. Regarding virulence genes, 18 (17%) tested positive for stx120 (19%) were positive for stx212 (11%) were positive for eaeA and 23 (22%) were positive for hlyA. STEC prevalence during the longitudinal study indicated non-O157 STEC shedding in 92% (72/78; 95% CI: 84-97) of samples and non-O157 STEC super shedding (≥4llog10 CFU/g faeces) in 73% (57/78; 95% CI: 62-82) of samples.

The number of cattle available for follow-up varied for the months of October, November, December and February. There were only 16 cattle that were consistently negative and none was consistently positive for STEC O157 for the whole period. There was intermittent shedding of non-O157 STEC for the entire sampling event. There was a significant difference (P < 0.0001) between the proportion of non-O157 super shedders (92%) compared with the proportion of O157 super shedders. For the longitudinal study, the median STEC shedding level for non-O157 was 4.8log10 CFU/g, while the median for O157 was 3.4log10 CFU/g. Some cattle were consistent non-O157 STEC shedders throughout the 4-month period. Four cattle were super-shedders of non-O157 STEC persistently throughout the four sampling events and five were non-O157 super shedders for 3 consecutive sampling events. Four cattle were super shedders of both O157 and non-O157 STEC.

Only 8 animals were followed up at the abattoir primarily because of missing tags and sometimes due to the inability to keep up with fast processing lines. Overall, the prevalence of STEC based on the screening of carcass swabs using PCR was 32% (6/19; 95% CI: 13-57%), while STEC prevalence along the different stages of carcass processing was as follows: 22% (2/9), 17% (2/12), 25% (3/12) and 11% (2/19) for perineum hide, pre-evisceration, post-evisceration and post-wash swabs respectively (P = 0.688). There was no association between super shedding status (just before slaughter) and STEC carcass contamination for either O157 (P = 0.061) or non-O157 (P = 0.348). Likewise, there was no association between super shedding status (just before slaughter) and perineum hide swab STEC contamination for either O157 (P = 0.714) or non-O157 (P = 0.143) STEC.

The analysis of virulence genes and serotypes included isolates from the previous study together with this one. The distribution of virulence genes was highest in feedlot faecal samples (40%) compared with abattoir (33%) and retail outlets (28%) and this was highly statistically significant. Of the 86 STEC strains tested, the frequency of detection of stx1stxand a combination of both stx1and stx2 was 24%, 17% and 19% respectively. The eaeA gene was detected in 20 (23.3%) isolates in five different combinations; stx2+eaeA (2 isolates), stx1+stx2+eaeA (1 isolate), stx1+eaeA+hlyA (13 isolates), stx2+eaeA+hlyA (3 isolates), stx1+stx2+eaeA+hlyA (1 isolate). Of the 20 isolates carrying the eaeA gene, only two isolates (2/20; 10%) were found in mince beef, 3 isolates from abattoir carcass swabs (3/20;15%), and the remaining 15 isolates (15/20;75%) were found in feedlot cattle faeces. Of the 86 isolates recovered, only 39 could be serotyped, from which a wide range of serogroups (35) were detected.

On the pulsed field gel electrophoresis (PFGE) analysis, dendrograms of 55 isolates showed a high diversity with 45 distinct PFGE patterns. This diversity of PFGE patterns was observed in some isolates of the same serogroup that did not cluster together; these included serogroup O178 (feedlot environmental sample, feedlot cattle faeces, and supermarket boerewors). Also included were two isolates belonging to serogroup O20 (boerewors) and four serogroup O168 isolates (feedlot cattle faeces samples and abattoir perineum hide swab). Some patterns were observed in the dendrogram with varying band similarity percentages. At 100% banding similarity, eight band similarity patterns were identified. At 97.5% banding similarity, four closely related patterns were identified in eight isolates (7%): i. winter butchery boerewors and summer environmental feedlot faeces, ii. autumn supermarket boerewors and winter butchery boerewors, iii. summer cattle feedlot faeces and autumn butchery mince, iv. autumn brisket and mincemeat from the same supermarket. Analysis of the PFGE patterns at the 84.5% band similarity percentage or greater, revealed that most of the clades (7-clusters) belonged to isolates from different sources.

Conclusion

This study has established the presence of persistent and intermittent super-shedding of STEC O157 and non-O157 in cattle in a feedlot and at the abattoir just before slaughter. This results in continual environmental contamination and risk of re-circulation of the pathogen in the herds, which may lead to contamination along the food chain. In addition, the high count of non-O157, and the diversity of serogroups, shows that super-shedding is not limited solely to serogroup O157. We provide evidence of horizontal transmission and STEC strain recirculation along the beef production chain in Gauteng. All serogroups detected in this study have been previously implicated in STEC infections in human, with four considered as emerging serogroups. The high heterogeneity shown by PFGE and the difference in serogroups and virulence genes demonstrate the presence of a diverse but related STEC population in the beef production chain. There is need for further scientific investigation to advance the understanding of the dynamics of super-shedding in cattle, to sample a wider geographic region representing cattle-farming areas of South Africa, to conduct studies over a longer period to assess the impact of changes in climatic conditions and to promote epidemiologic surveillance for the clinically important STEC serogroups in public health laboratories in in South Africa.

POPULAR ARTICLE

Shiga toxin-producing Escherichia coli in beef cattle from feedlot through to abattoir

Dr LO Onyeka, Prof. AA Adesiyun, Dr KH Keddy, Prof. E Madoroba, Prof. PN Thompson

INTRODUCTION

Shiga toxin-producing Escherichia coli (STEC) has emerged as an important foodborne pathogen globally. Healthy colonized cattle are major reservoirs of this pathogen and cattle that shed STEC are considered to play a key role in the entry of the pathogen into the food chain. STEC causes a broad spectrum of disease from mild to intense bloody diarrhoea and in 5-10% of cases, haemolytic uremic syndrome (HUS). Globally Foodborne STEC have caused more than 1 million illnesses and 128 deaths. Of the over 470 different serotypes of STEC detected in humans, the O157:H7 serotype is the most frequently associated with large food and water-borne outbreaks. However, non-O157 STEC have been increasingly isolated from intermittent cases of haemorrhagic colitis and the sometimes fatal HUS.

The importance of the pathogen in South Africa and other southern African countries has recently been highlighted. STEC O157 was isolated in clinical stool specimens of diarrhoeic patients and environmental water samples in Gauteng, and recent reports from the Western Cape suggest STEC may be an environmental contaminant in informal settings and it is associated with diarrhoea in children under five years of age. Furthermore, in South Africa and other southern African countries, numerous clinical cases of diarrhoea in children and adults were reported between 2006-2013, in which a diverse range of STEC serogroups (O4, O5, O21, O26, O84, O111, O113, O117 and O157) were incriminated.

However, the poor surveillance and inadequate diagnostic techniques employed, almost certainly means that the occurrence of STEC-associated disease in humans is under-reported. Since the majority of beef consumed passes through the feedlot system, it is essential that we understand the dynamics of shedding of the organism in the feedlot and the characteristics of the pathogen in the beef production chain. This will help to identify control measures to reduce the bacterial challenge resulting in carcass and beef products contamination.

The present study aimed to determine the prevalence and dynamics associated with shedding of STEC in feedlot cattle and to characterise STEC isolates recovered at every stage along the beef production chain. The specific objectives were (i) to determine the frequency of shedders of STEC in cattle and associated animal factors in a feedlot in Gauteng Province through monthly sampling of a cohort of animals over a 4-month period; (ii) to longitudinally follow tagged study animals to slaughter and to determine the frequency of STEC contamination pre-slaughter, during slaughter and post-slaughter; (iii) to characterize STEC isolates with respect to their serotypes and presence of virulence; and (iv) to use pulse-field gel electrophoresis (PFGE) and serotyping to establish the genetic relatedness of the isolates between feedlot and abattoir.

MATERIALS AND METHODS

A six-month study from Sept 2016 to Feb 2017 was conducted at a commercial cattle feedlot located near Pretoria, Gauteng. The selected feedlot also owned a mechanized abattoir that slaughtered approximately 120 units per day. One hundred and six (106) cattle were randomly selected on arrival and tagged, and a minimum of 50 g of fresh rectal faecal grab sample was collected from each. Subsequently, over a period of 4 months, 26 cattle, including 15 animals identified as shedders and at least 11 non-shedders were selected, and sampled once a month until animals were sent for slaughter at the abattoir. At the abattoir, swab samples of tagged cattle were obtained from a 100 cm2 area using a sterile square metal template from each of four selected anatomical sites (4 x100 cm2 areas): rump, flank, brisket and neck, according to a standardized method.

Broth enrichment for processing of faecal samples was carried out and DNA Template from the broth enriched samples was investigated for the presence of stx1, stx2, eaeA and hlyA genes using multiplex PCR. 10-fold serial dilutions was plated on duplicate plates of two selective media known to target E coli O157 and non-O157 serogroups, incubated for 24 h at 37oC, after which typical colonies were selected and biochemically identified. Enumeration was performed by viable plate count method and expressed as CFU/g. Serotyping was conducted at the National Institute for Communicable Diseases (NICD). Pulsed-field gel electrophoresis (PFGE) of 55 isolates (including isolates from a recent study of beef products at retail outlets in Pretoria) was carried out to determine relatedness of strains.

RESULTS AND DISCUSSION

Samples collected on arrival at the feedlot indicated a STEC prevalence of 27% (29/106), with 19% and 11% being positive for stx2 and eaeA genes respectively. The longitudinal study showed that STEC non-O157 was shed at a significantly higher level than STEC O157. These results have several implications. Firstly, it demonstrates the presence of super shedding cattle in a feedlot herd. Secondly it shows that super-shedding is not limited to STEC O157, as described in recent reports from Europe. Thirdly, the higher prevalence of STEC non-O157 compared with O157 STEC is of public health significance, since non-O157 STEC have been increasingly linked to human disease in South Africa. Numerous clinical cases of diarrhoea in children and adults, as well as HUS, have been reported, in which a diverse range of STEC serogroups (O4, O5, O21, O26, O84, O111, O113, O117 and O157) was implicated.

It was also of interest that some cattle were simultaneous shedders of both STEC O157 and non-O157. In addition, several cattle shed ≥10,000 CFU/g non-O157 persistently throughout the study or for 3 consecutive sampling events. These cattle were identified as “super shedders”. Non-O157 STEC may be gaining importance in South Africa and such super shedders may pose an increased risk of contamination along the beef production chain, possibly leading to contamination of the food chain for human consumption.

PFGE has been used to track foodborne bacterial pathogens along the food production chain. In this study, PFGE analysis revealed a high diversity of 45 distinct PFGE patterns among 55 non-O157 STEC strains, which provides useful information on the genomic diversity of non-O157 STEC strains in the beef production chain in Gauteng. We observed eight PFGE-related patterns for 16 isolates originating from the same location and source but from different stages of the beef production chain, suggesting that the specific contaminating strain multiplied and spread at that point/stage of entry into the beef chain, such that once a pathogen is established at any production stage (farm, abattoir or retail processing) it may result in within-production-stage transmission. These data suggest evidence of epidemiological lineage, hence horizontal transmission of STEC strains along the beef production chain.

In this study, of the 86 STEC isolates only 17% carried the stx2 gene and 19% carried both stx1 and stx2. Of the virulence combinations, (23.3%) harboured the eaeA combinations. Epidemiologic studies have shown that the presence of stx2+eaeA gene combinations is important in the likelihood of developing HUS and with severe clinical symptoms. Of the 86 isolates recovered, only 39 isolates were serotypeable, from which a wide range of serogroups (35) were detected, including seven serovars of clinical relevance, namely O178, O174, O117, O101, O68, O8 and O2, considered to be emerging serogroups.

CONCLUSIONS

This study confirms that multiple different STEC strains are co-circulating in cattle in South Africa and further work needs to be done to establish whether these are clinically relevant in the human population. The high count of non-O157, and the diversity of serogroups, provides further evidence that super-shedding is not limited solely to serogroup O157. Also, we provide evidence of horizontal transmission and STEC strain recirculation along the beef production chain in Gauteng. There is need for active surveillance of STEC both in their reservoir host and in humans, and further studies to investigate effective methods to prevent contamination of the food chain.

Please contact the Primary Researcher on the project if you need a copy of the comprehensive report – peter.thompson@up.ac.za

Genotype imputation for genomic selection

Genotype imputation as a cost-effective strategy to increase genotype data for genomic selection in South African beef cattle

Industry Sector: Cattle And Small Stock

Research Focus Area: Livestock production with global competitiveness: Breeding,physiology and management

Research Institute: Agricultural Research Council

Year Of Completion : 2020

Researcher: Mahlako Makgahlela

The Research Team

ProfFWCNeserPhDUniversity of the Free State
DrMDMacNeilPhDDelta Genetics
ProfMMScholtzPhDAgricultural Research Council
MsSMdyogoloMScAgricultural Research Council
DrAAZwanePhDAgricultural Research Council

Executive Summary

The discovery of DNA polymorphisms (single nucleotide polymorphisms (SNP) or simply genomic data) and their cost-effective genotyping platforms have provided breeders and scientists in animal breeding additional tools to select young animals without performance records with much higher accuracies. Breeding programmes incorporating genomic information have achieved substantial increase in genetic improvement for cattle populations around the world. As a start, genotyping strategies are determined to identify individuals that are genotyped to increase the accuracy of predictions, and estimate relationships between candidates more reliably. Meanwhile, accuracy of genome-based schemes is a function of the reference population from which prediction equations for estimating genomic breeding values (GEBV) are developed. Setting up a sizable reference population is costly and remains a challenge for the uptake of genomic selection in South Africa.

Objective Statement

The aim of this research was to assess the accuracy of genotype imputation from low-density (7 931 SNPs or 7K) or medium density (150 000 SNPs or 150K) to high density (777 962 SNPs or 777K) panels using the reference population defined as influential animals explaining substantial genetic variation in the Afrikaner (AFR), Brahman (BRA) and Brangus (BNG).

Project Aims

  1. To evaluate whether the Celtic mutation on the POLL locus is the causative mutation for polledness in Bonsmara and Drakensberger
  2. To perform a genome wide association study of the Polled and Scur genes based on phenotypic data and genotypic data from the GGP Bovine 150K SNP bead chip
  3. To apply sequence data available from the Bovine Genomics Program to finemap the suspected regions for the Polled and Scur genes

Results

In identifying influential animals for the AFR, BRA, BNG and the other beef breeds (i.e., Limousine, Santa Gertrudis, Simbra and Simmentaler), it was found that only 100 ancestors explained approximately 50% of the genetic variation, and about 90% of the genetic variation was explained by 200 ancestors for all breeds. Genetic variation explained by top 1000 important ancestors was 95, 96 and 84% for AFR, BRA and BNG, respectively. Imputation accuracies within breed reference population, measured as the concordance rate, were 96.60, 91.39 and 89.91 using Beagle and 95.3, 92.8 and 96 using FImpute for AFR, BRA and BNG, respectively. Accuracies in multi-breed were lower (±80%) than within-breed reference populations. Furthermore, results demonstrated that accuracy tends to be greater when imputing from low-density 7K to medium-density 150K than bypassing the latter and impute from low-density 7K to high-density 777K. Higher accuracies were observed using Fimpute (93-97 %) versus Beagle (89-95%) and Impute (91-94%).

Conclusion

This study investigated the accuracies of imputation within breed and across breeds by masking actual genotypes in the Afrikaner, Brahman and Brangus breeds, and through genotype imputation from low density 7K or medium density 150K to high-density 777K in the Brahman cattle breed. The reference populations for imputation for all breeds were defined as influential animals with high marginal genetic contributions to young animals who were born in the last decade of the pedigree data, which were found to be few relative to the pedigreed population. Genotyped animals used in this study were few but promising accuracies were observed in within breed reference populations for AFR and BRA. Thus, imputation workflow established in this research could be integrated within the framework for implementation of genomic evaluations of GEBV and genomic selection in the Brahman and Afrikaner cattle breeds.

Popular Article

Genotype imputation: An essential, promising and cheap tool for assembling the reference population for genomic selection in the Afrikaner and Brahman cattle breeds of South Africa

Authors: Dr M.L. Makgahlela, Ms S. Mdyogolo, Prof F.W.C. Neser, Dr M. D. MacNeil, Prof M. M. Scholtz & Prof A. Maiwashe

The world will need to produce 100% more food in the next 40 years than currently produced (UNFAO, 2002). Accordingly, the demand for beef products, being the top valuable livestock product, will continue to increase significantly. Meanwhile, competition for resources will intensify, dictating that livestock systems must increase both productivity and efficiency. More than 60% of the additional food must come through technological innovations. Genomics is among technologies that will play a pivotal role in meeting the increasing demand while safeguarding natural resources and preventing environmental degradation. Genomic selection (GS) is the selection of genetically superior breeding animals based on genomic breeding values (GEBV) calculated from thousands of DNA markers or single nucleotide polymorphisms (SNP. Breeding programmes using GEBV have achieved substantial increase in genetic improvement for cattle populations around the world. The infrastructure for implementing GS within breed is a sufficient reference population of phenotyped (measured economic traits) and genotyped (SNP genotypes) animals. Setting up a sizable reference population requires substantial capital investments, and remains a challenge for the uptake of genomic selection in South Africa. There are several SNP genotyping panels of low-, medium- and high densities in terms of the number of SNP markers. Imputation is a method used to fill missing SNP on the low-density panel using medium- or high-density panel as reference population, without paying for the extra information. It provides an opportunity to achieve a sizable reference population for timely uptake of GS.

The aim of this research was to assess the accuracy of genotype imputation from low-density (7 931 SNPs or 7K) to medium density (150 000 SNPs or 150K) or high density (777 962 SNPs or 777K) panels using the reference population defined as influential animals explaining the genetic diversity in the Afrikaner (AFR), Brahman (BRA) and Brangus (BNG). In identifying influential animals for the AFR, BRA, BNG and the Limousine, Santa Gertrudis, Simbra and Simmentaler, it was found that only 100 ancestors explained approximately 50% of the genetic diversity, and about 90% of the genetic diversity was explained by 200 ancestors for all breeds. Genetic diversity explained by top 1000 important ancestors was 95, 96 and 84% for AFR, BRA and BNG, respectively. Imputation accuracies within breed reference population, measured as correctly imputed SNP, were 96.60, 91.39 and 89.91 using Beagle and 95.3, 92.8 and 96 using FImpute for AFR, BRA and BNG, respectively. Accuracies in multi-breed were lower (±80) than within-breed reference populations. Furthermore, results demonstrated that accuracy tends to be greater when imputing from low-density 7K to medium-density 150K than bypassing the latter and impute from low-density 7K to high-density 777K. Higher accuracies were observed using Fimpute (93-97 %) versus Beagle (89-95) and Impute (91-94). Genotyped animals used in this study were few but promising accuracies were observed in within breed reference population for AFR and BRA. Thus, imputation workflow established in this research could be integrated within the framework for implementation of genomic evaluations of GEBV and genomic selection in the Brahman and Afrikaner cattle breeds.

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project on :mmakgahlela@arc.agric.za

Inheritance patterns of the Polled and Scur genes in South African beef cattle breeds

The genetic mechanisms and inheritance patterns of the polled and scur phenotypes in local South African beef cattle breeds

Industry Sector: Cattle And Small Stock

Research Focus Area: Animal Health and Welfare

Research Institute: Department of Animal & Wildlife Sciences, University of Pretoria

Year Of Completion: 2019

Researcher: E van Marle-Koster

The Research Team

TitleInitialsSurnameHighest QualificationResearch Institution
DrM.M.ScholtzPhDARC-AP
ProfEvan Marle-KosterPhDUP
MrsA. Theunissen MSc Vaalharts Research Station

Executive Summary

Introduction

It is standard practice to dehorn cattle at a young age by means of physical dehorning, but in most cases without the appropriate pain relief. The practice of dehorning has increasingly become a welfare concern and alternatives to dehorning are advocated worldwide. Breeding genetically polled cattle is a long-term, non-invasive and welfare friendly alternative to dehorning. Identification of genetically polled animals through a diagnostic test would therefore be advantageous, but a specific commercial diagnostic test for the polled phenotype is not currently available in South Africa.  The DNA tests that are available internationally are applicable to European Bos taurus breeds, which can give inconclusive results for indigenous South African and Sanga cattle breeds. Furthermore, the commercial diagnostic tests available for Taurine breeds can not identify carriers of either the scur gene or the African horn gene.

Over the past two decades commercial beef producers and feedlots in South Africa have indicated a preference for polled breeds, due to increased awareness of animal welfare and market preferences. In South Africa there are a number of polled breeds of European descent such as the Hereford, Angus, Charolais and Limousin, as well as a few local breeds, including the South African Bonsmara, Tuli and Drakensberger, that introgressed the polled gene. The Bonsmara breed requested research on the identification of homozygous polled bulls and the first research project in South Africa was performed at the Department of Animal and Wildlife Sciences, UP (Schmulian, 2006). This study was based on three Bonsmara families and the available microsatellite markers at that time were used. The study by Schmulian (2006) found linkage between the polled phenotype in the South African Bonsmara and alleles of nine microsatellite markers located on BTA1. Since the completion of this research project, the Bovine genome sequence has been completed in 2009 with high through-put molecular technology (Bovine HapMap Consortium, 2009), providing genomic information and high-density SNP chips.

The majority of previous research on the POLLED locus and polledness has been performed in European breeds, which does not provide a basis for identification of the causative mutation for polledness or scurs in indigenous South African cattle breeds. These breeds are genetically distinct from the European Bos taurus breeds (Makina et al., 2014) and besides the two main types of cattle, Bos taurus and Bos indicus, indigenous African cattle, such as the Sanga, are also found in South Africa.

Objective statement

This study focused on local South African beef cattle breeds to gain an understanding of the genetic basis and inheritance of the Polled and Scur genes by using pedigree data from phenotyped animals, as well as high density SNP data. The availability of DNA and high through-put molecular technology holds the potential to provide insight on the genetic mechanisms of polled and scurred animals with higher precision, compared to the microsatellite markers that were previously available.

Project Aims

  1. To evaluate whether the Celtic mutation on the POLL locus is the causative mutation for polledness in Bonsmara and Drakensberger
  2. To perform a genome wide association study of the Polled and Scur genes based on phenotypic data and genotypic data from the GGP Bovine 150K SNP bead chip
  3. To apply sequence data available from the Bovine Genomics Program to finemap the suspected regions for the Polled and Scur genes

Results

A total of 890 Bonsmara and 224 Drakensberger animals were screened for their status for the Celtic mutation at the POLLED locus using a PCR-based diagnostic test. It was possible to distinguish between heterozygous and homozygous polled individuals, but scurs could not be identified on a genotypic level based on the Celtic variant. The majority of animals screened, tested heterozygous polled, with homozygous polled animals occurring at a relatively low frequency. Based on the results of this Celtic screening, a total of 217 Bonsmaras (including homozygous polled, heterozygous clean polled and scurred animals) were genotyped using the GGP Bovine 150K SNP bead chip. Additional genotypes from the Bovine Genomics Program (BGP) were also included in this study.

Haplotype analysis of the POLLED locus revealed a reduced genetic diversity around the Celtic allele, with only two haploblocks (1.0-2.2 Mb) observed in the homozygous polled animals investigated. One of these haploblocks of six SNPs encompassed the Celtic mutation and presented only three distinct alleles with major differences in terms of frequencies. This result suggests that the Celtic allele was introgressed in the Bonsmara breed from a very limited number of founders. A low haplotype diversity combined with an intense selection on the polled phenotype in the Bonsmara breed can result in the selection of deleterious alleles linked with the Celtic mutation through a hitchhiking mechanism. Therefore, it is of primary importance to maintain some genetic variability around the Celtic allele.

Preliminary results of the GWAS study, based on 150k SNP chip data, indicated significant association for the scurs phenotype with three SNPs on BTA5, which contradicts previous findings that mapped the SCURS locus to BTA19. For the POLLED locus, preliminary results show significant association between the polled phenotype and BTA1, as expected. Of interest is another significant association with the polled phenotype that were observed on BTA28, which was not reported in previous studies. The significant SNPs that were identified in the GWAS analysis of the POLLED and SCURS loci will be annotated to identify candidate genes and to investigate the potential significant physiological pathways of these SNPs.

Conclusion

The POLLED Celtic variant was validated as the causative mutation of polledness in three South African beef cattle breeds and can be used as an efficient diagnostic test for polledness. This study also highlighted the current difficulties and limitations of accurate phenotypic recording of the horn status. It also confirmed that scurs cannot be identified on a genotypic level with the Celtic screening. Preliminary results of genotypic SNP data indicated significant association for the scurs phenotype on BTA5 in the Bonsmara, but these results need to be further investigated.

The following scientific output were achieved for the project:

Grobler, R., Visser, C. & van Marle-Köster, E., 2017. Accelerating selection for polledness in the South African Bonsmara using DNA technology. 50th South African Society for Animal Science (SASAS) Congress, Port Elizabeth, 18 – 21 September 2017.

Grobler, R., van-Marle-Köster, E., Visser, C.& Capitan, A., 2018. Haplotype variation at the POLLED locus in the South African Bonsmara cattle breed. World Congress on Genetics Applied to Livestock Production (WCGALP) 11-16 February, Auckland.

Grobler, R., Visser, C., Capitan, A. & van Marle-Köster, E., 2018. Validation of the POLLED Celtic variant in South African Bonsmara and Drakensberger beef cattle breeds. Livestock Science. 217, 136-139.

Popular Article

Introduction

Identifikasie van poena status in die Bonsmara met behulp van DNA tegnologie

Rulien Grobler (PhD Kandidaat)

Departement Vee- en Wildkunde, Universiteit van Pretoria

Inleiding

Die voordele van poenskop beeste vir die kommersiële vleisbeesindustrie is alombekend en wêreldwyd word die druk vir meer menslike praktyke in terme van dierebehandeling hoër, as gevolg van die impak op dierewelsyn. Alhoewel die opsie daar is om kalwers te onthoring, dui navorsing aan dat dit n pynvolle prosedure is, ten spyte van die tegniek of voorsorgmaatreëls wat gebruik word. Behalwe dat die onthoring van kalwers nie welsynsvriendelik is nie, is dit ook tydrowend en arbeidsintensief,en veroorsaak dit ook stres wat die groei van die kalf negatief kan affekteer. Hierdie faktore het dan ook ‘n verdere ekonomiese implikasie vir die boer. Dit is ook n opsie om poenskop beeste te selekteer gebaseer op fenotipiese rekords, maar hierdie proses is egter tydrowend en oneffektief, en veroorsaak stadige genetiese vordering. Deur gebruik te maak van DNA tegnologie om poenskop diere te identifiseer, kan seleksie vinniger en meer effektief plaasvind en genetiese vordering sal ook vinniger toeneem. Verder is dit ook ‘n welsynsvriendelike alternief, so wel as n langtermyn oplossing vir die onthoring van kalwers.

Poenskop oorerwing

Die Poena geen is outosomaal dominant en indien teenwoordig, sal die uitdrukking van die horing fenotipe onderduk word. Daar is twee allele teenwoordig by die Poena geen, P en p, en diere wat die dominante P alleel dra is fenotipies poenskop. Homosigotiese poenskop diere dra twee dominante P allele (PP), terwyl heterosigotiese poenskop (Pp) diere een dominante P alleel dra en een horing alleel. Dus, diere wat twee p allele dra het dan die horing fenotipe (pp). As gevolg van dominansie, kan daar nie onderskei word tussen die homosigoot en heterosigoot poena fenotipe nie. Dus is dit nodig vir n genetiese toets om draers van die poena en horing allele te identifiseer.

Afhangende van die poena status van die moer en vaar, word die poena allele in verskillende proporsies oorgedra na die nageslag (Figuur 1). Bv. Wanneer n homosigotiese poena (PP) bul, wat dan twee dominante poena allele dra, geteel word met n horing koei (pp), is daar ‘n 100% kans dat die nageslag fenotipies poenskop sal wees, omdat die nageslag een dominante P alleel kry van die vaar en een horing alleel van die moer. Maar wanneer n heterosigotiese poena (Pp) bul gebruik word, verminder die kans vir poenskop nageslag met 50% (Figuur 1).

Figuur 1 Die moontlike genotipiese proporsies vir verskillende paringsituasies van horing, hetero- en homosigotiese poenskop individue

Die oorerwing van die poena geen word verder gekompliseer deur die scurs fenotipe, as gevolg van epistatiese interaksie tussen die Poena en Scurs gene. Scurs is klein horingagtige vergroeisels wat op dieselfde plek as horings op die kop voorkom, maar hierdie abnormale vergroeisels is losweg aan die skedel geheg en is beweeglik (Figuur 2). Scurs is geslagsbeïnvloed en word gevolglik verskillend oorgeërf in manlike en vroulike diere. Dit is waargeneem dat scurs kan voorkom in diere wat heterosigoties poenskop is, en dat scurs meer in manlike diere as in vroulike diere voorkom.

Figuur 2 Die poenskop (A en B) en variasie van die scurs (C – F) fenotipes soos waargeneem in die Bonsmara

Die Poena Projek by UP

Die Poena geen is geleë op chromosoom 1 (BTA1) en minstens twee verskillende variante is verantwoordelik vir die poenskop fenotipe in beeste, naamlik die Celtic (PC) en Friesian (PF) variante (Allais-Bonnet et al., 2013).  Die Celtic (PC) variant is verantwoordelik vir die poenskop fenotipe in die meeste Bos taurus rasse van Europese herkoms, terwyl die Friesian (PF) variant hoofsaaklik voorkom in die Holstein Friesian ras.

In samewerking met ‘n navorser van Frankryk (INRA), is Bonsmara diere getoets vir beide die Celtic (PC) en Friesian variante (PF). Dit is vasgestel dat al die Bonsmara diere met n poenskop fenotipe, dra ten minste een alleel van die Celtic variant en geen diere is positief getoets vir die Friesian variant nie. Hierdie bevinding is in lyn met die geskiedenis en ontwikkeling van die Bonsmara vanuit n Europese Bos taurus ras. ‘n Groter groep Bonsmaras is getoets vir die Celtic variant (PC) en dit is bevestig dat die Celtic variant (PC) van die Poena geen verantwoordelik is vir die poenskop fenotipe in die Suid-Afrikaanse Bonsmara (Grobler et al., 2018).

Deur gebruik te maak van ‘n haarmonster, word DNA geëkstraeer uit die haarwortels. Die DNA word dan gebruik om die dier te toets vir die Celtic variant (PC) deur gebruik te maak van ‘n PCR-gebaseerde diagnostiese toets. Gevolglik kan draers van die PC variant geïdentifiseer word en sodoende kan diere ook as homo- of heterosigoties poena geïdentifiseer word op ‘n genotipiese vlak.

Bonsmara bulle en koeie, asook sekere kalwers, is uit spesifieke kuddes geselekteer om poenskop diere te identifiseer en tot dusver is n totaal van 890 Bonsmaras getoets vir die Celtic variant (PC) met die bogenoemde diagnostiese toets. ‘n Hoë frekwensie poenskop diere is waargeneem, waarvan die meerderheid diere heterosigoties poena getoets het (Figuur 3). Dit beteken dat hierdie diere slegs een PC alleel dra, asook een horing alleel, wat dan moontlik oorgedra kan word aan die dier se nageslag. Alhoewel homosigotiese poena diere wel waargeneem is, is dit waargeneem in slegs 12% van die diere wat tot dusver getoets is (Figuur 3). Die Bonsmara diere wat horing getoets het, is by n relatiewe hoë frekwensie van 42% waargeneem (Figuur 3). Dit is tog nodig om te noem dat die meerderheid van die homosigotiese poenas in een kudde waargeneem is wat vir meer as twee dekades al spesifiek selekteer vir die poenskop fenotipe. Alhoewel hierdie toets kan onderskei tussen homo- en heterosigote poenskop diere, kan die toets nie scurs op ‘n genotipiese vlak identifiseer nie en verdere navorsing is nodig vir scurs.

Figuur 3 Die genotipe frekwensie van die Celtic variant (PC) soos getoets in 890 Bonsmaras

Implikasies vir SA Bonsmara

Die diagnostiese DNA toets kan effektief gebruik word om heterosigotiese en homosigotiese poena diere te identifiseer op n genotipiese vlak. Hierdie toets kan egter nie gebruik word om scurs op n genotipe vlak te identifiseer nie, omdat beide poenskop en scurs diere genotipies heterosigoties poenskop toets (Pp). Dit is dan juis waarom dit belangrik is om die horingstatus van diere vroegtydig en akkuraat aan te teken. Die poenskop fenotipe is maklik om te observeer en verander nie tydens die dier se leeftyd nie. Die scurs fenotipe is egter moeiliker om aan te teken, omdat dit dikwels verwar word met horings of eers later uitgedruk word. Daarom word dit aanbeveel dat beeste ondersoek word by n jong ouderdom (gewoonlik tydens speen), asook tussen 18 en 24 maande.

Met behulp van hierdie DNA tegnologie kan die poena status van diere vroegtydig geïdentifiseer word, wat sodoende die genetiese seleksie van poena diere sal vergemaklik, asook versnel. Verder hou dit ‘n ekonomiese voordeel vir telers in wanneer gesertifiseerde poenskop bulle bemark kan word. Meer poenskop diere in die mark sal ook ‘n voordeel inhou deur arbeidskostes te verlaag en diere welsyn te bevorder omdat die onthoring van diere dan metteryd nie meer nodig sal wees nie. Die relatiewe hoë frekwensie van horing diere wat waargeneem is bevestig juis die belangrikheid van ‘n DNA toets, deurdat telers eers die poena status van diere op ‘n genotipiese vlak moet bevestig voordat vermeende poena diere ingesluit word in ‘n paringsprogram. Dit is veral belangrik vir bulle wat vir teeldoeleindes en veilings gebruik gaan word.

Erkennings

Dankie aan elke boer wat haarmonsters en inligting bygedrae het vir die Poena projek, en ook spesifiek vir Charl Uys vir sy hulp. Dankie aan Prof E. van Marle-Köster en Dr C. Visser; die studiepromotors op die PhD projek. Dank aan RMRD SA en die NRF vir befondsing.

Verwysings

Allais-Bonnet et al., 2013. PloS ONE. 8, 1-14.

Grobler et al., 2018. Livestock Science. 217, 136-139.

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Gene expression: Nguni and Bonsmara

A gene-expression study on the growth performance of Nguni and Bonsmara cattle grown in a feedlot fed a high and low energy diet

Industry Sector: Cattle And Small Stock

Research Focus Area: Livestock production with global competitiveness: Breeding,physiology and management

Research Institute: Agricultural Research Council

Year Of Completion : 2019

Researcher: Dina Linde

The Research Team

TitleInitialsSurnameHighest QualificationResearch Institution
DrM.M.ScholtzPhDARC-AP
ProfEvan Marle-KosterPhDUP
MrsA. Theunissen MSc Vaalharts Research Station

Executive Summary

Introduction

In South Africa, Nguni cattle are one of the breeds found predominantly in extensive production systems. The Nguni is an indigenous cattle breed and is widely used in crossbreeding systems due to their high fertility and mothering ability. Nguni cattle are also commonly used in communal production systems. The majority of beef in South Africa is produced in feedlots using commercially formulated high energy diets, where preference is given to medium and large framed later maturing cattle that include British types and composites such as the South African Bonsmara. Due to the Nguni’s small frame and low meat yield when compared to British types it is nor preferred as a feedlot animals, however studies have shown that Nguni cattle produce high quality meat.

The veldt of South Africa has a varying degree of carrying capacity, however the occasional drought conditions have necessitated the use of alternative production systems such as feedlots for finishing cattle. The use of a lower energy diet in feedlots for indigenous cattle have been suggested and warrants investigation. Nutrigenomics is the study of the effect of nutrition on the genes of the animal by quantifying the gene expression. An improved understanding of the interaction between the nutritional environment and the genetics of the animal can lead to increased efficiency and production. Diets that are different in components or ingredients can result in different phenotypes in the animals. In this study the effect of two feedlot diets with different energy levels have been investigated using a transcriptome approach.

Objective statement

The objective of this study is to determine if there are gene expression differences between Nguni and Bonsmara cattle fed a low or a high energy diet. The gene expression of the cattle can determine the underlying differences in the reaction of the two breeds to the two different diets.

Project Aims

  1. To evaluate whether the Celtic mutation on the POLL locus is the causative mutation for polledness in Bonsmara and Drakensberger
  2. To perform a genome wide association study of the Polled and Scur genes based on phenotypic data and genotypic data from the GGP Bovine 150K SNP bead chip
  3. To apply sequence data available from the Bovine Genomics Program to finemap the suspected regions for the Polled and Scur genes

Results

Conclusion

Performance results showed a higher live weight, carcass weight and marbling score for all bulls fed the high energy diet compared to bulls fed the low energy diet. Only carcass weight and marbling score had significant difference in terms of diet (p < 0.05). Live weight, average daily gain, rib fat, rump fat and eye muscle area were only significant for breed. Diet had a greater effect on the Bonsmara compared to the Nguni according to transcriptomic and phenotypic values. Transcriptomic values showed 3584 differential expressed genes (DEG) between the Bonsmara fed the two different diets, while only a difference of 288 DEG were observed between the Nguni fed the two different diets. Phenotypic values show a difference of 20 kg between the Bonsmara groups and only a 6 kg difference between the Nguni groups. Most DEG were involved with cellular processes and metabolic pathways. A total of 73 differentially expressed genes were observed between the diets across breeds. The genes that were involved in intramuscular fat deposition (CRHR2, NR4A3, MMD) were expressed on a higher level in the bulls on the low energy diet compared to bulls on the high energy diet. Genes that were involved in muscle deposition (PITX2, Leptin, AVP) was expressed higher in the bulls on the high energy diet. Comparing the breeds revealed that 2214 genes were differentially expressed between the Bonsmara and the Nguni.

At the end of the feedlot trial a higher expression of marbling genes (SIRT, ND, ADIPOQ) were observed in the Nguni, however this expression was not observed in the marbling scores recorded. Several genes (ASIP, MOGAT, SNAI3) that were involved in fat deposition were upregulated in the Bonsmara. This suggests that the Nguni was still growing at the end of the feedlot trial while the Bonsmara had reached physiological maturity. Little literature could be found on some of the gene showing the highest expression in the groups such as GSTA3, TEX28 and TUBB3. Glutathione-s transferase alpha 3 (GSTA3) is linked to steroidal genesis and could therefore have an influence on myogenesis, however no confirming literature could be found.

Conclusion

The diet had a smaller effect on the Nguni bulls compared to the Bonsmara bulls as observed in the DEG and the carcass weight of the bulls. This might indicate that the Nguni is more adaptable to a variation in feed quality. The Bonsmara bulls had a higher meat yield on the high energy diet, however it seems as if the bulls on the low energy diet had a higher expression of the marbling genes. This is in contrast to the phenotypically higher marbling score. Further research needs to be done as this study had a small sample size (n=40). An extended feedlot period for Nguni cattle should be considered in future studies. This study provides reference data for differentially expressed genes in muscle of South African feedlot cattle.

Popular Article – A low energy feedlot diet may favour our indigenous breeds

Dina Linde1,2, Michiel Scholtz1,3 & Este van Marle-Koster2

1ARC – Animal Production, Private Bag X2, Irene, 0062, South Africa; 2Department Of Animal And Wildlife Science, University Of Pretoria, Pretoria, 0002, South Africa; 3Department Of Animal, Wildlife And Grassland Sciences, University Of The Free State, Bloemfontein, 9300; South Africa;

The phenotypes of animals vary due to differences in their genetics and environment. The expression of the genes of animals can also be influenced by their diet. In South Africa, Sanga cattle (Afrikaner and Nguni) are adapted to various environments and production systems. However, these cattle are mostly found in extensive production systems that make use of natural grazing. They are not preferred in the feedlot, as their smaller frame sizes compared to Bos Taurus types and crossbreds will lead to smaller carcass sizes. The traditional diet fed in the feedlot is a high energy diet, that includes maize and maize by-products. There are however, farmers that believe that a high energy diet does not suite the genetics of Sanga cattle and that these breeds would do better on a lower energy diet.

A study was done to find alternative strategies for Sanga cattle in the feedlot. A diet low in energy (10.9 MJ ME/kg) or a high energy diet (12.5 MJ ME/kg) was fed to Nguni and Bonsmara cattle for a period of a 120 days respectively. During the feeding period the animals were weighed and real time ultrasound scanned for meat quality characteristics such as eye muscle area (EMA). At slaughter, muscle samples were taken to analyse the gene expression data.

In terms of the feedlot data, no significant difference could be found between the diets with regard to live weight, eye muscle area (EMA), rib fat and rump fat in the Nguni. Breed differences were however found. Carcass weight and marbling did however show significant difference as well as an interaction between breed and diet.

Breed had a much bigger effect compared to diet, with 2214 differentially expressed genes (DEG) and 74 DEG, respectively. Of the  genes found differentially expressed between the breeds, several genes known to be involved in marbling (SIRT, ND, COX, ADIPOQ, SERPINF2) was expressed higher in the Nguni compared to the Bonsmara. However, the phenotypic marbling score was higher in the Bonsmara compared to the Nguni.

This lead to the suggestion that the Nguni needed more time (a longer feedlot period) for the expression of the marbling genes to show phenotypically. This is in contrast to the industry that perceives that the Nguni deposits fat too early in comparison to exotic and crossbreds. Sanga cattle tend to first deposit fat intramuscularly, which might be an adaptation mechanism for the harsh conditions in which these cattle lived. It seems, however, that the Nguni only begins depositing muscle tissue after a sufficient layer of fat is deposited. This might be the reason for backgrounding, which is common practise in the Nguni breed.

Between the Nguni fed the high energy diet and the Nguni fed the low energy diet, 288 genes were differentially expressed. The different levels of energy in the diets seem to result in different components being deposited. Various genes (PITX2, PAX, Leptin, AVP, OXT) involved in muscle deposition were upregulated in the bulls that received the high energy diet, compared to the bulls fed the low energy diet. This is also seen in the phenotypic results with the carcass weight of the bulls fed the high energy diet being higher compared to the bulls fed the low energy diet.

The difference in carcass weight is very small between the Nguni fed the high energy diet and the Nguni fed the lower energy diet (6 kg). However, genes that influence intramuscular fat deposition (SPARC, CRNR2, CHRND, NR4A3, MMD) were elevated in the bulls that received the low energy diet compared to the bulls that received the high energy diet. This was also not shown in the phenotypic traits. Extending the period of feeding may result in the bulls that received the low energy diet to express the phenotype.

It seems that the low energy diet suite the Sanga cattle better, when compared to the traditional high energy diet fed in the feedlots. This should be further investigated as this study had a relatively small sample size (n=40). Furthermore, as these animals are ruminants, it would be also interesting to study the rumen microbiome in another study of this kind.

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Genetic diversity of landrace cattle breeds

Genetic diversity and relationships among seven South African landrace and exotic cattle breeds

Industry Sector: Cattle And Small Stock

Research Focus Area: Livestock production with global competitiveness: Breeding, physiology and management

Research Institute: Agricultural Research Council Animal Production (ARC-AP)

Year Of Completion : 2019

Researcher: Dr Lene van der Westhuizen

The Research Team

TitleInitialsSurnameHighest QualificationResearch Institution
DrM.M.ScholtzPhDARC-AP
ProfEvan Marle-KosterPhDUP
MrsA. Theunissen MSc Vaalharts Research Station

Executive Summary

Introduction

An existing 11 microsatellite marker database that resulted from parentage verification, was used to assess genetic diversity among nine breeds of cattle. These breeds were drawn from Bos indicus (Boran and Brahman), B. taurus (Angus and Simmental) and B. taurus africanus (Afrikaner, Bonsmara, Drakensberger, Nguni and Tuli). Due to the cost of genotyping, genetic variability and population structure studies using single nucleotide polymorphisms (SNPs) rely on relatively low numbers of animals to represent each of the breeds. However, large numbers of animals have been genotyped for parentage verification using microsatellite markers and this microsatellite information on large numbers of animals have the potential to provide more accurate estimates of genomic variability than SNPs.

The breeds in this study were characterized by unbiased heterozygosity, effective number of alleles and inbreeding. Ranges in estimates of these parameters were 0.569–0.741, 8.818–11.455 and -0.001–0.050, respectively. The analysis of population structure revealed descent from taurine, indicine, and Sanga types with K=3 and from unique progenitor populations with K=9. There are notable similarities between the results observed using a limited number of genetic markers and large numbers of animals with microsatellite markers.

The study revealed the southern African Sanga and exotic cattle breeds that are found in South Africa, are genetically distinct from each other. Therefore, using the Sanga and Sanga derived breeds in crossbreeding programs should be done with caution to ensure the conservation of genetic resources of these breeds. Furthermore, comparable genetic variability and inbreeding levels found in the present study demonstrate the genetic sturdiness of the Sanga and Sanga derived breeds. However, there is a notable similarity between the results observed in this study (using a limited number of genetic markers and large numbers of animals), with the results of studies with similar objectives which used substantial greater numbers of markers but much fewer animals.

The analyses revealed that the southern African, British and European breeds as well as the tropically adapted breed clustered separately. Therefore, exotic breeds in South Africa is expected to benefit from favourable heteroses effects due to crossing with Landrace breeds.

Objective Statement

The present study used existing microsatellite marker databases (provided by Breeders’ Societies) to estimate levels of heterozygosity and inbreeding of several southern African Sanga and exotic breeds, and quantify the genetic relationships between the breeds. To these ends, obtaining data from historical parentage databases allowed for use of substantially larger numbers of animals per breed to be studied than in previous investigations.

Project Aims

  1. To determine the level of genetic variation of each breed, therefore identifying the remaining resources of heterozygosity within the four South African landrace cattle breeds.
  2. To compare the level of genetic variation between the four landrace breeds.
  3. To determine the inbreeding for the breeds as whole.
  4. To determine the relation (genetic un-relatedness) between South Africa’s landrace breeds and Zebu, British and European breeds.

Results

From a genetic diversity perspective, all breeds had large numbers of alleles at each locus and high frequencies of heterozygous genotypes; and thus each locus had substantial polymorphic information content. The number of alleles per locus and frequency of heterozygotes found in the present study were both toward the lower ends of the corresponding ranges for the same loci that were previously observed in a substantially larger sample of Afrikaner cattle. Inbreeding is not currently at a sufficient level so as to be problematic in the South African segments of these breeds. From the present study, the number of Clusters found with the highest probability of membership, required to describe the between-breed genetic relationships, were two (K=2) and noticeably grouped the two taurine breeds separate from the Sanga and indicine (Afrikaner, Brahman, Boran, Nguni and Tuli) breeds. The second highest probability showed a total of three genetic Clusters (K=3) and grouped the taurine, indicine and Sanga breeds separately. When K=9 is used, breed individuality and admixture were clearly defined. Here, the Nguni was shown to be the most admixed with 31 % of membership belonging to the other eight Clusters. The Nguni is followed by Bonsmara and Drakensberger showing admixture from other Clusters up to 24 %. These results are in accordance with Makina et al. (2016), with the latter authors suggesting that the admixture within Nguni and Drakensberger have been involuntary, however, the admixture recognized within the Bonsmara was intentional given the breed history. Moreover, Angus showed to be the least admixed with significant membership within this Cluster with probability of 90 %. To demonstrate the genetic distances between the breeds, an NJ tree was generated. The tree illustrated the discrepancy between the three groups of cattle, with the southern African Sanga breeds grouping separately from the indicine and taurine cattle, but sharing a closer genetic background with the two indicine breeds. The NJ tree also supported the multi-locus clustering algorithm when K=2 is used with reference to Bonsmara and Drakensberger and again highlights the discrepancy between the present study and the results of Makina et al.  (2016).

Discussion

From a genetic diversity perspective, all breeds had large numbers of alleles at each locus and high frequencies of heterozygous genotypes; and thus each locus had substantial polymorphic information content. The number of alleles per locus and frequency of heterozygotes found in the present study were both toward the lower ends of the corresponding ranges for the same loci that were previously observed in a substantially larger sample of Afrikaner cattle. Inbreeding is not currently at a sufficient level so as to be problematic in the South African segments of these breeds. From the present study, the number of Clusters found with the highest probability of membership, required to describe the between-breed genetic relationships, were two (K=2) and noticeably grouped the two taurine breeds separate from the Sanga and indicine (Afrikaner, Brahman, Boran, Nguni and Tuli) breeds. The second highest probability showed a total of three genetic Clusters (K=3) and grouped the taurine, indicine and Sanga breeds separately. When K=9 is used, breed individuality and admixture were clearly defined. Here, the Nguni was shown to be the most admixed with 31 % of membership belonging to the other eight Clusters. The Nguni is followed by Bonsmara and Drakensberger showing admixture from other Clusters up to 24 %. These results are in accordance with Makina et al. (2016), with the latter authors suggesting that the admixture within Nguni and Drakensberger have been involuntary, however, the admixture recognized within the Bonsmara was intentional given the breed history. Moreover, Angus showed to be the least admixed with significant membership within this Cluster with probability of 90 %. To demonstrate the genetic distances between the breeds, an NJ tree was generated. The tree illustrated the discrepancy between the three groups of cattle, with the southern African Sanga breeds grouping separately from the indicine and taurine cattle, but sharing a closer genetic background with the two indicine breeds. The NJ tree also supported the multi-locus clustering algorithm when K=2 is used with reference to Bonsmara and Drakensberger and again highlights the discrepancy between the present study and the results of Makina et al.  (2016).

Conclusion

The study revealed the southern African Sanga and exotic cattle breeds that are found in South Africa, are genetically distinct from each other. Therefore, using the Sanga and Sanga derived breeds in crossbreeding programs should be done with caution to ensure the conservation of genetic resources of these breeds. Furthermore, comparable genetic variability and inbreeding levels found in the present study and Makina et al. (2014) demonstrate the genetic sturdiness of the Sanga and Sanga derived breeds. However, there is a notable similarity between the results observed in this study (using a limited number of genetic markers and large numbers of animals), with the results of studies with similar objectives which used substantial greater numbers of markers but much fewer animals. Thus, opportunities that arise to explore genetic diversity in both the livestock and wildlife industries in Southern Africa, may capitalize on microsatellite marker databases which remain cost-effective and accessible due to their continued use for parentage verification.

Both analyses revealed the southern African, British and European breeds as well as the tropically adapted breed clustered separately. Therefore, exotic breeds in South Africa is expected to benefit from favourable heterosis effects due to crossing with Landrace breeds. Opportunities that arise to explore genetic diversity in both the livestock- and wildlife industries may capitalize on microsatellite marker databases which remain cost-effective and accessible due to their continued use for parentage verification.

Popular Article

Genetic diversity and relationships among seven South African landrace and exotic cattle breeds

Genetic variability or genetic diversity is required for populations to be able to adapt to different environmental pressures. It can also be defined as the variation of alleles and genotypes present in a breed. This provides the basis for adaptive and evolutionary processes. The current level of diversity in livestock has been created by the combined forces of both natural- and artificial selection. These forces can be described as mutations, adaptations, segregation, selective breeding and genetic drift. Furthermore, genetic diversity in livestock species is essential for the adaptive responses needed in ever-changing farming conditions and ultimately to respond to the challenges created by climate change. Additionally, diversity also provides a reservoir for genetic variation to ensure that future market demands can be met through selection.

The indigenous cattle breeds of Southern Africa include the Sanga and Sanga derived cattle. Sanga cattle, especially those indigenous to southern Africa, are classified as Bos taurus africanus. The indigenous Sanga cattle of South Africa includes the Afrikaner, Nguni and Drakensberger, whereas the Tuli and Hugenoot are considered to be the Landrace breeds of Southern Africa. The Bonsmara is a Sanga derived composite breed. These breeds are extremely well adapted to the harsh climatic and other environmental conditions encountered under extensive ranching in South Africa. This will become even more important in the era of climate change.

Research has suggested that Sanga cattle, compared to European breeds are favourable with regard to meat tenderness. There has been speculation that the Landrace breeds may be closely related to other tropically adapted breeds (B. indicus) such as the Brahman due to their morphological similarities. However, several genetic studies have demonstrated a closer relationship between Sanga and B. taurus breeds.

In the early 1900’s there was a perception in South Africa that the indigenous breeds were inferior and this led to the promulgation of an Act in 1934 in which indigenous breeds and types were regarded as ‘scrub’ (non-descript). Inspectors were appointed to inspect the bulls in communal areas and to castrate them if regarded as inferior. Fortunately, this Act was applied effectively for only a few years, since it was very unpopular. However, the effect of this on especially the “purity” of the Nguni was never established. In addition, the Bonsmara is supposed to be 5/8 Afrikaner: 3/8 British composition. Through selection and subsequent upgrading, this composition may have shifted significantly. It is therefore important to also establish the relationship between the Landrace, Zebu, British and European breeds.

The Southern African landrace breeds are relatively poorly characterized at the genomic level in comparison to many taurine and indicine breeds. Using genotypes derived from microsatellite loci, several research projects have characterized contemporary populations of Bonsmara, Afrikaner, Nguni and the Tuli from Zimbabwe. Due to the cost of genotyping, substantially fewer animals (i.e., ≤ 50) have been characterized by single nucleotide polymorphism (SNP) arrays using approximately 50 000 DNA markers to estimate the diversity of Afrikaner, Bonsmara, Drakensberger, and Nguni cattle and to evaluate their relationship to other breeds worldwide. Bi-allelic markers such as single nucleotide polymorphisms (SNPs) are currently the subject of interest globally. However, in Southern Africa, microsatellite markers have been used routinely and are more cost-effective in the livestock, wildlife and aquaculture industries. Microsatellite markers have multiple alleles and are generally more informative than SNPs. However, the latter statement is largely dependent on sample size. Microsatellites have also been used over the years for relationship studies, inbreeding levels and breed differentiation.

The aim of this study was to use microsatellite marker databases (provided by Breeders’ Societies) to estimate levels of heterozygosity and inbreeding of nine Southern African Sanga and exotic breeds, and quantify the genetic relationships between the breeds. This allowed the use of substantially larger numbers of animals per breed to be studied than in previous investigations.

The breeds used in this study were Afrikaner, Angus, Bonsmara, Boran, Brahman, Drakensberger, Nguni, Simmental and Tuli. Animals were genotyped in response to requests from industry for parentage verification.  At least 300 animals were randomly chosen to represent each breed,

All breeds had large numbers of alleles at each locus and high frequencies of heterozygous genotypes. Inbreeding was found not to be at a level where it will be problematic in the South African segments of these breeds. While the present study used microsatellite data, another study, using SNP data, showed similar findings regarding the genetic variability and inbreeding levels of southern African Sanga cattle.

When provision was made for two ancestral populations (K=2), the two taurine (Angus and Simmental) breeds were separated from the Sanga and indicine (Afrikaner, Bonsmara, Brahman, Boran, Drakensberger, Nguni and Tuli) breeds. It was however noted that both Bonsmara and Drakensberger also showed some admixture of at least 30 % with the cluster belonging to Angus and Simmental. These results are consistent with the development of the Bonsmara breed with the B. taurus influence (5/8 Afrikaner, 3/16 Shorthorn, and 3/16 Hereford) and some uncertain or undefined breed origin of the Drakensberger.

When provision was made for three ancestral populations (K=3), it grouped the taurine (Angus and Simmental), indicine (Brahman and Boran) and Sanga (Afrikaner, Bonsmara, Drakensberger, Nguni and Tuli) breeds separately. When K=9 was used, breed individuality and admixture between the breeds could be clearly defined.

The study revealed the Southern African Sanga and exotic cattle breeds found in South Africa are genetically distinct from each other. Furthermore, comparable genetic variability and inbreeding levels found in the present- and other studies, demonstrated the genetic sturdiness of the Sanga and Sanga derived breeds.

There is a notable similarity between the results observed in this study (using a limited number of DNA markers and large numbers of animals), with the results of other studies, with similar objectives, which used substantial greater numbers of DNA markers but much fewer animals.

Both analyses revealed the southern African Sanga breeds, British and European breeds, as well as the tropically adapted Zebu breeds clustered separately. Therefore, exotic breeds in South Africa is expected to benefit from favourable heterosis effects, when crossed with Landrace breeds. Finally, the results from this study indicate that genetic diversity in both the livestock- and wildlife industries may capitalize on microsatellite marker databases which remain cost-effective and accessible due to their use for parentage verification.

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Genotype imputation for indigenous beef cattle

Genotype imputation as a genomic strategy for the South African Drakensberger beef breed

Industry Sector: Cattle And Small Stock

Research Focus Area: Livestock Production With Global Competitiveness: Breeding,Physiology And Management

Research Institute: Department Of Agriculture Forest And Fisheries (DAFF)

Year Of Completion : 2019

Researcher: Carina Visser

The Research Team

TitleInitialsSurnameHighest QualificationResearch Institution
DrM.M.ScholtzPhDARC-AP
ProfEvan Marle-KosterPhDUP
MrsA. Theunissen MSc Vaalharts Research Station

Executive Summary

The SA Drakensberger is a medium-framed breed with a sleek, black coat. Considering its history as one of the oldest indigenous breeds, its prominent role in the present beef industry and its potential for improving the beef cattle gene pool in the future; there is value in characterizing the SA Drakensberger on the genomic level. There has recently been interest in incorporating genomic information into selection strategies for this breed. Apart from the fact that the implementation of genomic technologies relies on diligent phenotyping efforts, accurate and complete pedigree recording; genomic selection also requires adequate SNP genotyping profiles (Meuwissen et al., 2001). The SA Drakensberger meets the requirements for genomic selection with 100% participation in SA Stud Book’s Logix Beef performance recording scheme as well as an extensive recorded pedigree profile (SA Stud Book, 2017). Theoretically, current EBVs can therefore be enhanced with the use of genomics if financial resources allow the generation of adequate high-density genotypic profiles. Imputation is a statistical methodology that relies on the genomic segments shared within a breed, or a group of genetically similar breeds, to predict genotypic information for SNPs that were not physically genotyped (Marchini et al., 2007). The main advantage of this methodology is the reduction in genotyping costs by allowing genotyping to be undertaken using lower density SNP panels. The utility of such low-density panels for applications such as genomic selection will depend on the accuracy with which un-genotyped SNPs can be imputed to higher density from such lower density panels. Even though imputation is integrated into routine genomic evaluations internationally, the utility of this methodology has not been evaluated for indigenous cattle resources. Considering that these breeds often have admixed genomes, applying imputation requires optimization for such breeds and this includes the SA Drakensberger.

Objective Statement

The objective of this research project was to comprehensively study the validity of genotype imputation, from lower-density single nucleotide polymorphism (SNP) panels to higher density, for the economically-important SA Drakensberger beef cattle breed towards cost-effectively implementing genomically-enhanced breed improvement strategies such as genomic selection for this indigenous breed in the future.

Project Aims

  1. To evaluate whether the Celtic mutation on the POLL locus is the causative mutation for polledness in Bonsmara and Drakensberger
  2. To perform a genome wide association study of the Polled and Scur genes based on phenotypic data and genotypic data from the GGP Bovine 150K SNP bead chip
  3. To apply sequence data available from the Bovine Genomics Program to finemap the suspected regions for the Polled and Scur genes

Results

Results generated from the first part of this study indicated that differences in genomic characteristics such as minor allele frequency (MAF), linkage disequilibrium (LD) and runs of homozygosity (ROH) exists between chromosomes. Mean genome-wide MAF was, for example, estimated to be 0.26 with chromosome-specific MAF ranging from 0.24 (Bos Taurus Autosome; BTA14) to 0.28 (BTA21). This was supported by the proportion of low-MAF (< 5%) SNPs estimated, which indicated 16.0% of SNPs to be classified as low-MAF SNPs on BTA14. The inter-SNP LD was generally weak, ranging from mean r²=0.11 (BTA28) to r²=0.17 (BTA14) for SNPs separated by≤1Mb and r²=0.20 extended only up to<30 kb. LD was weaker between SNP pairs including low-MAF SNPs. Consensus ROH segments were identified and the most prevalent of these occurred on BTA14 and was identified in ∼23% of the sampled population. The ROH length characteristics furthermore pointed towards more ancient inbreeding, reflecting known historic bottleneck events.

For the second and main object preliminary results were generated to understand the necessary dynamics, in terms of size and composition, of an appropriate sub-population to use as a reference for estimation of haplotypes to be imputed from. Initial results indicated that a larger reference population would improve imputation accuracy. For example, it was observed that a 4% increase in imputation accuracy could achieved when the ratio of reference:test population was 90:10 versus 75:25; imputation accuracy improved from 0.981 (range: 0.895-0.997) to 0.985 (range: 0.905-0.996) when the former versus the latter scenario was used. It was further observed that using a reference population consisting of animals with closer genetic relatedness to the test population would also improve imputation accuracy. A strong correlation of 0.817 (P<0.001) was observed between the mean genetic relatedness of animals in the test population, with animals in the reference population, and their resulting imputation accuracy.

This was supported by estimates showing mean imputation accuracy of 0.994 as opposed to 0.982 for animals that had both as opposed to no parents in the reference population. The influence of using different low-density SNP panels, consisting of varying density and SNP content, on more specifically animal-wise and SNP-wise imputation accuracy was then determined. Animal-wise imputation accuracy improved when the SNP density of the lower-density panel improved; correlation-based imputation accuracy ranged (minimum to maximum) from 0.625-0.990, 0.728-0.994, 0.830-0.996, 0.885-0.998 and 0.918-0.999 when 2 500, 5 000, 10 000, 20 000 and 50 000 SNPs when SNPs were randomly chosen. The variation between animals, as well as the degree of improvement in accuracy, became smaller with increasing SNP density. Improvements of 0.043 units were seen when SNPs were doubled from 2 500 to 5 000 SNPs, as opposed to an improvement 0f only 0.007 units when SNPs were (more than) doubled from 20 000 to 50 000 SNPs. Selection of SNPs based on both MAF and LD attributes proved to be the best selection strategy to maximize imputation accuracy and random selection produced the worst imputation accuracy. Mean imputation accuracy exceeding 97% (less than 3% errors) could be achieved by using only 5 000 SNPs when this method of selection was used; using other methods of selection this accuracy was only achieved when double the amount of SNPs (10 000) was used. In terms of SNP-wise imputation accuracy, accuracy estimates were lower for SNPs located on the chromosomal extremes and if the MAF of these SNPs was low. For chromosome 19, which was the chromosome with the worst mean imputation accuracy for most scenarios, SNPs located in the first (n=32), middle (n=42) and last (n=64) 1Mb of this chromosome, for example, had mean SNP-wise correlation-based accuracy measures of 0.640, 0.810 and 0.577. The difference in SNP-wise imputation accuracy moreover was 0.071 between SNPs in the highest (0.4<MAF≤0.5) and lowest MAF bins (0.01<MAF≤0.1); imputation accuracy was better for SNPs with higher MAF.

Results generated to achieve the final aim of this study are still preliminary and in the process of being analyzed. Preliminary results, however, shows strong correlations between conventionally-estimated EBVs and GEBVs, with the inclusion of genomic information being advantageous to breeding value estimation. The difference in GEBV accuracies estimated from true- versus imputed genotypes was small thus far, depending on the per animal imputation accuracy; the discrepancy is expected to be larger for animals with lower mean imputation accuracy.

Conclusion

The variation observed in genomic characteristics such as MAF and LD conformed to expectations and supported previous research suggesting that the SA Drakensberger is a composite breed with an admixed genome and heterogenous genomic architecture. This variation across the genome allowed variation in imputation accuracy between different chromosomes and genomic regions within chromosomes to be pre-empted. Genotype imputation is a valid genomic strategy for the SA Drakensberger breed and this study concluded that a genotyping panel consisting approximately 10 000 SNPs would suffice in achieving less than 3% imputation errors. Results presented further suggests that if such a panel were to be designed, that the SNPs considered for inclusion would have to be selected based on selection criteria, such as MAF and LD, specific to the SA Drakensberger breed. Considering that no Sanga-specific genotyping panel currently exists, it would be recommended that these SNPs be chosen from re-sequencing efforts, i.e. from a pool of SNPs that are identified as specific to the breed, and not necessarily from a pool of SNPs that are available on taurine- and/or indicine-derived genotyping platforms. The reason for this is that low MAF, because of ascertainment bias, was the most influential factor affecting  achievable imputation accuracy and therefore poses a concern. This study showed that it will be a valid strategy to integrate genotype imputation routinely into future genomic evaluation pipelines for the SA Drakensberger breed as imputation errors are expected to have a negligible effect on resulting GEBV accuracies. Finally, the inferences made from this study may be transferable to other Sanga breeds and may provide guidelines for consideration in future genomic endeavours for these breeds.

Popular Article

Genotype imputation as a genomic strategy for the South African Drakensberger beef breed by SF Lashmar, C Visser and FC Muchadeyi

The Drakensberger is a medium-framed breed of cattle with a sleek, black coat. It is believed to be one of South Africa’s oldest Sanga breeds and was developed from an ancestral population of cattle that was first sighted in 1659 in the Bredasdorp area of the Western Cape province. These cattle ancestors, also described as black in colour, belonged to native tribes and were crossbred with Dutch cattle of the Groningen breed, which were imported by European settlers in the 1700s. By this introduction of European Bos Taurus genetics, the development of the SA Drakensberger was initiated. The modern SA Drakensberger, as it is presently known, was however only recognized in 1947 when the SA Drakensberger Breeders’ Society was established. The breed therefore underwent a process of development that spanned centuries, whereby it withstood many harsh challenges in its history and this has led to the hardy breed it is today. Nicknamed the “profit breed”, the Drakensberger is both adapted and highly productive within SA’s beef producing environment and has a long history of diligent performance recording. In fact, it was the first breed to receive estimated breeding values (EBVs) using best linear unbiased prediction (BLUP) methodology, as performance testing was made compulsory to all breeders since 1980. Participation by Drakensberger breeders in SA Stud Book’s Logix Beef performance recording scheme is still at 100% today (SA Stud Book, 2017) and extensive pedigree records are available. Considering all of this, there has recently been interest in further enriching breed improvement strategies for the SA Drakensberger with genetic information in the form of genomic selection.

To implement genomic selection can significantly improve the efficiency of selection processes, and hence accelerate genetic progress, for the SA Drakensberger breed. This selection strategy, however, requires large numbers of animals to be “tested”, referred to as “genotyped”, for a high density of single nucleotide polymorphism markers (SNPs) in order to make reliable scientific deductions and to produce accurate genomic estimated breeding values (GEBVs) for farmers or breeders. From experience, international researchers have suggested 1 000 animals to be included in a training- or reference population to deduce the prediction equations that will be used in calculating GEBVs for selection candidates. Generating the amount of data to fulfill the number of genotyped animals necessary in the training population alone can become unfeasibly expensive, especially in developing countries, considering that the cost of genotyping an animal for about 150 000 SNPs is currently approximated at ZAR200 per animal. The cost of genotyping can, however, be alleviated by genotyping animals with SNP chips containing lower numbers of SNPs and “imputing” to higher density.

In statistical terms, imputation refers to the process of replacing missing data with substituted values. In the context of genomics, genotype imputation refers to a method of predicting SNP genotypes for SNPs that are either missing or were not physically genotyped. The genotypes are predicted based on patterns observed from a more complete data set of SNPs that are available for a group of animals that are representative of a specific breed. Consider for example that we have a young animal tested for 10 000 markers (which would be referred to as a “low-density SNP panel”) and the parents of this animal are tested for 100 000 markers (which would be referred to as a “high-density SNP panel”). Given the genetic relationship between the parents and the offspring, and the fact that these animals share large parts of the DNA, we can “impute” or infer the “missing” 90 000 markers for the young animal by making certain statistical assumptions using the principles of genetics. On a larger scale: if a “reference” population (consisting of older, high-impact animals with many offspring in the national herd) is genotyped for a high density of genetic markers (let’s say 150 000 SNPs) and a “test” population (younger, commercial animals in the national herd) is genotyped for a smaller subset of these SNPs (let’s say 50 000 SNPs), the 150 000-SNP genotype profile can be imputed for the “test” animals. The prerequisite is, however, that the animals in the reference- and test populations need to be related in some way, in other words they need to share underlying genetic patterns. These shared patterns can be used to fill in the gaps in SNP information. The imputed SNPs i.e. the 100 000 “missing” SNPs not included on the lower density panel, can however only be used in downstream application such as genomic selection if they were accurately imputed or assigned otherwise inaccurate scientific deductions will be made.

Imputation is now almost routinely included in genomic evaluation processes abroad because this methodology has been optimized, through trial-and-error and studying the factors influencing “imputability” of SNPs, for the most popular international breed. To be able to make use of this methodology within the South African beef industry, and more specifically for local breeds, requires a process of validation and this has not yet been performed for breeds such as the SA Drakensberger. The aim of the study was therefore to comprehensively evaluate genotype imputation for the SA Drakensberger breed so that it can be routinely applied in a GS pipeline.

The first step in the process of validation was to investigate the genomic characteristics of the breed. The genomic characteristics of SNPs have previously been shown to have an influence on the accuracy with which genotypes can be imputed. The genome of each animal is subdivided into different structures, called chromosomes, and on each of these chromosomes differences may furthermore exist between different DNA segments depending on the origin of these segments i.e. from which animal in the pedigree that part of DNA was inherited. As a result of the history of the SA Drakensberger, the genomes of animals belonging to this breed are expected to be composite i.e. containing genomic segments from both Bos taurus and Bos indicus. Certain parameters can provide more information on the SNPs within each of these segments and these include the minor allele frequency (MAF) and linkage disequilibrium (LD). The MAF gives an indication of the value of a specific SNP to the breed in question; if the MAF is high, it is an indication that both alleles of the SNP are present amongst the animals in the breed i.e. the SNP is informative. The LD provides an indication of the relationship between adjacent SNPs; if SNPs are in high LD, a “block” of SNPs can be inherited together and animals share larger parts of the genome with one another. This improves the ability of SNPs in these regions to be imputed. The software, Plink, was used to quantify these parameters on a per chromosome basis. Results showed that there was variation in these genomic characteristics between different chromosomes and this led us to expect differences in imputation accuracy between chromosomes.

The logical next step was to calculate the actual achievable imputation accuracy. The accuracy of imputation was calculated for imputation from several custom-derived low-density panels. To achieve this objective, different sets of SNPs were extracted from the SNP data available (150K SNP data) to mimic possible lower-density SNP panels. Panels containing 2 500, 5 000, 10 000, 20 000 and 50 000 SNPs were tested. The choice of SNPs to be included on each of these panels were based on certain SNP selection strategies i.e. different criteria were used to select the SNPs. The different strategies of selection included 1) selecting SNPs randomly, 2) selecting SNPs so that they were approximately evenly spaced, 3) selecting only SNPs with the highest MAF and 4) selecting SNPs based on a score combining its MAF and relationship to neighbouring SNPs (LD). Imputation was done using a software called FImpute and our findings suggested that a low-density SNP panel consisting of approximately 10 000 SNPs that were selected based on their MAF and LD information will be optimal. Using such a panel resulted in less than 3% imputation errors.

The final step was to determine the influence of mistakenly imputed SNPs on the accuracy of GEBVs and hence on genomic selection. The “single-step” approach to GS was tested using software called Mix99. Breeding values were calculated using 1) only pedigree information (traditional), 2) using true genotypic data (GEBV) and 3) using imputed genotypic data (imputed GEBV). These different breeding values were compared to determine whether imputation accuracy had an effect. Our preliminary findings suggest that the inclusion of genomic data is advantageous and that there is a minimal effect on GEBV accuracy estimates if imputation accuracy was good.

To conclude, results from this study indicated that imputation is a valid genomic strategy towards cost-effectively implementing GS for an indigenous breed such as the SA Drakensberger despite the uniqueness and complexity of its genome. The outcomes of this study may moreover be transferable to other Sanga breeds and may provide a set of guidelines for genomic studies requiring imputation in the future. Even though this study has shown that a more affordable lower-density panel can be developed from choosing SNPs with high MAF in indigenous breeds from currently available genotyping platforms, it would be invaluable for future genomic endeavours to develop a Sanga-specific panel using breed-specific SNPs identified from re-sequencing efforts.

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project on :mmakgahlela@arc.agric.za

Genetic markers for Haemonchus contortus in sheep


Genome wide association study to identify genetic markers associated with resistance to Haemonchus contortus in sheep

Industry Sector: Cattle And Small Stock

Research Focus Area: Livestock production with global competitiveness: Breeding,physiology and management

Research Institute: Department of Agriculture Forerst and Fisheries (DAFF)

Year Of Completion : 2019

Researcher: Margeretha Snyman

The Research Team

TitleInitialsSurnameHighest QualificationResearch Institution
DrCVisserPhDUP
DrPSomaPhDARC
DrFCMuchadeyiPhDARC-BTP
DrADFischerBVScQueenstown PVL
MrNJDlamimiMScARC

Aims Of The Project

  1. Collect blood samples and data on resistance to H. contortus on a sheep flock on a farm with major Haemonchus anthelmintic resistance problems
  2. Analyse the data, estimate genetic parameters and develop a protocol for recording of resistance to H. contortus under SA conditions
  3. Conduct various genomic studies to identify genetic markers linked to resistance

Executive Summary

The objective of this study was to compare four commonly used growth promotants in a commercial sheep feedlot. The steroidal growth promotants chosen for this trial were Ralgro (zeranol), Revalor G (Rev G; TBA/oestrogen- 17β), Revalor H (Rev H; TBA/oestrogen- 17β) and Zilmax® (zilpaterol hydrochloride). The growth promotants were compared with one another and within three sex groups, namely ewe, ram and wether (castrates), to determine which molecule or combination of molecules, if any, had the most benefit and profitability when measured against a control group.  Sheep were stratified based on initial weights and then randomly allocated to treatment groups in a completely randomised control study. All sheep originated from the same farm, and they were of  similar age, breed,  transport method,  processing method, feed (the only difference being  the groups receiving Zilmax® during the last 18 days of feeding, making provision for 3 days withdrawal), weather conditions, housing and time on feed. A time constant termination date was used in this study, in order to measure the performance of lambs in treatment groups over time.

The issue of resistance of internal parasite species to worm remedies is widespread throughout South Africa and the world and affects all small stock farmers. Especially Haemonchus contortus causes major losses among sheep in the summer rainfall regions in South Africa. For some areas, farming with animals resistant to nematodes seems to be the only solution in the long run. Genetic variation in resistance to nematode infestation in sheep, based on faecal egg count (FEC) as a criterion, has been reported for various breeds. Successful breeding programs for resistance have been reported for Australian and New Zealand sheep. There are, however, no large scale active breeding programs for resistance in South African sheep.

Because of the difficulty of routinely collecting phenotypic data associated with resistance to internal parasites, suitable data sets for the estimation of genetic parameters for resistance against H. contortus are scarce in South Africa. The history of and recent selection practices followed in the Wauldby Dohne Merino flock makes it an ideal resource for research into resistance to H. contortus in South African sheep.

In 2011, a project aimed at selection for resistance against H. contortus was started on the Wauldby Dohne Merino flock. Apart from full pedigree information, data on faecal egg counts (FEC), Famacha© score (FAM) and body condition score (BCS) were collected annually on all lambs born since 2011. FEC, FAM and BCS of all lambs were recorded from the middle of January onwards. FAM was recorded weekly and FEC and BCS every 14 days until the end of June when Haemonchus challenge had decreased. Lambs were only drenched when they had a FAM of 2.5 or more, in conjunction with a BCS of less than 1.5. Any lamb that was drenched was recorded as “Dosed” and those lambs that did not require any drenching as “Not dosed”. Replacement rams and ewes were selected from the animals that did not need dosing on the basis of a selection index incorporating FEC, FAM and BCS.

Data were analysed to compile protocols for selection against resistance to H. contortus in SA sheep.

Objective

The objective of this study is to identify of genetic markers for resistance to Haemonchus contortus in SA sheep, which could be included in the selection plan. See aims for the objectives of the three phases of the projects.

Results

The Dohne Merino lambs at Wauldby were subjected to severe H. contortus challenge. This is evident from the very high maximum FEC values recorded, even at the last two recordings during June. FEC ranged from 0 to 54100 epg among recordings over the trial period. Despite the high FEC challenge, mean FAM was still low, which is indicative of the high resilient status of the Wauldby flock. Dosing status had a significant effect on FAM, BCS and FEC. The Not dosed lambs had lower FEC, higher BCS and lower FAM compared to the lambs that were dosed. FAM increased and BCS decreased as the number of treatments received increased.

During the first year of the trial, 33% of the ram lambs and 45% of the ewe lambs were not dosed throughout the annual recording period. These percentages increased annually until 77% of the ram lambs and 82% of the ewe lambs did not need any drenching in 2016. One of the most significant results of the trial to date was the increase in percentage offspring of the sires that did not need drenching. The best performing sire used during 2011 had 53% lambs that did not need drenching, while 74% lambs of the poorest sire needed anthelmintic treatment. In 2016, the best performing sire had 97% lambs that did not need drenching, while 37% lambs of the poorest sire needed anthelmintic treatment.

FAM had a high genetic correlation and moderate phenotypic correlation with FEC. The highest heritability and repeatability of the resistance traits were recorded for BCS, but BCS had a moderate genetic and a low phenotypic correlation with FEC. In this study, BCS of the lamb, in combination with FAM, was considered in the decision whether to treat the lamb or not. However, due to the low phenotypic correlation between BCS and faecal egg count, BCS of an animal by itself is not an accurate indication of the existing level of H. contortus infection. The low phenotypic correlation estimated between BCS and FEC in this study is also indicative that other factors apart from worm load influence BCS in growing lambs.

Body weight, fleece weight and coefficient of variation of fibre diameter had favourable genetic correlations with FEC, FAM and BCS, while fibre diameter and staple length were unfavourably correlated with FEC. Inclusion of FEC in the selection protocol should therefore not adversely affect body weight and wool production.

As far as the application of FAM as criterion for the selection of resilient or resistant sires and dams is concerned, it should be used in combination with other resistance indicators such as FEC. During the high challenge summer rainfall period FAM will be recorded weekly or bi-weekly, therefore more FAM recordings will be available for inclusion in a final selection protocol. Due to its favourable genetic correlations with FEC and the production traits, and the fact that BCS of the Not dosed lambs in this study was higher than BCS of the Dosed lambs, BCS could be included in the selection protocol to be used for selection against resistance to H. contortus. BCS and FEC can be recorded at the beginning (January), at the peak (middle to end of March) and towards the end of the H. contortus season (June). Lambs that did not require any anthelmintic treatment up until selection age could be selected on the basis of a selection protocol incorporating these FEC and BCS recordings, together with all the recorded FAM.

The following selection indices, including FEC with or without incorporating FAM and BCS, were compiled / suggested:

  • SI1 = (-1 x FEC169 -1 x FAM +1 x BCS169) +10
  • SI2 = (-1 x FEC169 -1 x FAM) +10
  • SI3 = (-1 x FEC169) +10

As far as the genomic study is concerned, there were definite genetic differences among the animals in the flock and three genetic clusters were observed. Animals in the most resistant cluster had significantly lower FEC, lower FAM and higher BCS than the animals in the other two clusters. The sires of the animals in the resistant cluster also had more favourable EBVs for FEC and FAM.

The results of the genomic study further indicated the possibility of selection signatures on the same chromosomes in the Wauldby Merino animals than those on which QTL for faecal egg count and H. contortus FEC are reported in the sheep genomic databases. These will be further investigated in a comprehensive GWAS study.

Conclusion

The results indicate that progress was made when selecting for resistance to H. contortus in the Wauldby Dohne Merino flock.
There is genetic variation in host resistance against H. contortus in the Wauldby Dohne Merino flock. Sires in one genetic cluster are highly resistant and can be used in a breeding program to develop sheep that are resistant to H. contortus infections.
Moderate heritabilities and genetic correlations were estimated for and among FAM, BCS and FEC in this flock. Except for the unfavourable genetic correlation with fibre diameter, no detrimental genetic correlations between the resistance and production traits were estimated.
These results were used to develop protocols for selection for resistance to H. contortus under South African conditions. The developed protocols need to be validated on various farms before they can be implemented on a wider scale.

Popular Article

PROTOCOL FOR SELECTION FOR RESISTANCE TO HAEMONCHUS CONTORTUS IN SOUTH AFRICAN DOHNE MERINO SHEEP

Authors: M.A. Snyman, Grootfontein Agricultural Development Institute, Private Bag X529, Middelburg (EC), 5900 GrethaSn@Daff.Gov.Za. A.D. Fisher, Queenstown Provincial Veterinary Laboratory, Private Bag X7093, Queenstown, 5320 Alan.Fisher@Awe.Co.Za

INTRODUCTION

The issue of resistance of internal parasite species to worm remedies is widespread throughout South Africa and the world and affects all small stock farmers. Haemonchus contortus is the most important parasite and causes the most losses among sheep in the summer rainfall regions of South Africa. For some areas, farming with animals resistant to nematode infestation seems to be the only solution in the long run.

Because of the difficulty of routinely collecting phenotypic data associated with resistance to internal parasites, suitable data sets for the estimation of genetic parameters for resistance against H. contortus are scarce in South Africa. The history of and recent selection practices followed in the Wauldby Dohne Merino flock makes it an ideal resource for research into resistance to H. contortus in South African sheep. The farm Wauldby is located in the Stutterheim district in the Eastern Cape Province in a high summer rainfall area (800 mm annually). Wauldby has a well-documented history of heavy H. contortus challenge and H. contortus resistance and in the past the farm was used for several trials relating to resistance of H. contortus to anthelmintics.

In 2011, a project aimed at selection for resistance against H. contortus was started on the Wauldby Dohne Merino flock. Data on faecal egg counts (FEC), Famacha© score (FAM) and body condition score (BCS) were collected annually on all lambs born since 2011. FEC, FAM and BCS of all lambs were recorded from the middle of January onwards. FAM was recorded weekly and FEC and BCS every 14 days until the end of June when Haemonchus challenge had decreased. Lambs were only drenched when they had a FAM of 2.5 or more, in conjunction with a BCS of less than 1.5. Any lamb that was drenched was recorded as “Dosed” and those lambs that did not require any drenching as “Not dosed”. Data on all lambs were recorded throughout until the end of June, irrespective whether they needed drenching or not.

Selection in the flock was aimed at increasing resistance to H. contortus, while maintaining reproductive performance, body weight, wool weight and fibre diameter and improving wool quality traits. Selection for the production traits was done on the basis of selection indices and BLUP of breeding values for the mentioned traits measured at 14 months of age. Selection for resistance to H. contortus was based on a selection index incorporating FEC, FAM and BCS.

A selection line, in which the most resistant ewes were mated to the most resistant rams, has been established in 2012 as part of the project. These animals were run together with the rest of the flock animals, except during mating. Only ram and ewe lambs that had never been drenched were considered for selection into the selection line. Three rams and about 20 young ewes were selected annually for the selection line since 2012. Currently the selection line consists of 120 ewes, which are mated in three groups of 40 ewes each to the three most resistant rams in single sire mating camps. All progeny born in both the selection line and the rest of the flock were evaluated together. Rams and ewes performing the best in terms of resistance could be selected for the selection line, whether their parents came from the selection line or the other flock animals.

RESULTS TO DATE

The data collected over the years were used to estimated heritabilities and genetic correlations among the traits. Moderate heritabilities for and favourable genetic correlations among FEC, FAM and BCS were estimated. It will be impractical and expensive to record FEC every second week under commercial farming conditions. A combination of FEC recordings at the beginning, at the peak (middle to end of March) and towards the end of the season, proved to be the best alternative for selection purposes.

FAM had a high genetic correlation with FEC. In this study on-going first stage selection was done by identifying animals unsuitable for inclusion in the selection line on the basis of FAM and BCS. Identifying animals that required anthelminthic treatment according to FAM will ensure that only truly susceptible animals are identified and destined to be culled. Resilient as well as resistant animals will not be targeted and will remain untreated and available for final stage selection. As far as the application of FAM as criterion for the selection of resilient or resistant sires and dams is concerned, it should be used in combination with other resistance traits such as FEC. During the high challenge summer rainfall period, FAM will be recorded weekly or bi-weekly, therefore more FAM recordings will be available for inclusion in a final selection protocol.

The highest heritability and repeatability of the resistance traits were recorded for BCS, but BCS had a moderate genetic correlation with FEC. In this study, BCS of the lamb, in combination with FAM, were considered in the decision whether to treat the lamb or not. However, due to the low phenotypic correlation between BCS and FEC, BCS of an animal by itself is not an accurate indication of the existing level of H. contortus infection. By the time BCS is affected by H. contortus per se, the animal would have shown other clinical signs of Haemonchosis. Due to the fact that BCS of the Not dosed lambs in this study was higher than BCS of the Dosed lambs, BCS was included in one of the selection indices. BCS and FEC can be recorded at the beginning (January), at the peak (middle to end of March) and towards the end of the H. contortus season (June), as mentioned above.

SELECTION INDICES (SI)

The following selection indices, including FEC with or without incorporating FAM and BCS, were compiled / suggested:

SI1 = (-1 x FEC169 -1 x FAM +1 x BCS169) +10

SI2 = (-1 x FEC169 -1 x FAM) +10

SI3 = (-1 x FEC169) +10

For all the animals on which data were collected to date in the Wauldby flock, these three SI options were calculated. These three selection indices were evaluated on the data of the Wauldby animals born in 2015, 2016 and 2017. When the data of all the available animals were evaluated, basically the same animals will be selected with SI1 and SI2. Where selection is based only on FEC (SI3), somewhat different animals were selected in some years than when FAM and BCS were included in the selection index.

When the data of only a selected proportion of 5% rams and 25% ewes were evaluated, again basically the same animals will be selected with SI1 and SI2. However, rather different animals will be selected when only FEC was used as selection criteria. What this implies is that selection should preferably be done on SI1 or SI2. FAM should be included together with FEC, but the inclusion of BCS is optional.

PROTOCOL FOR SELECTION FOR RESISTANCE AGAINST H. CONTORTUS

The following protocols can be followed for selection for resistance against H. Contortus in stud and commercial flocks respectively.

Stud animals

Follow the normal internal parasite control program before weaning, i.e. routine pooled FEC.If the lambs needed to be drench before weaning, FEC, FAM and BCS of all the lambs could be recorded before drenching. All lambs could then be drenched after data collection.After weaning, recording of individual ram and ewe lambs should take place.FAM should be recorded every 14 days until the end of June when Haemonchus challenge has decreased.Individual FEC and BCS should be recorded at the beginning (January) and twice during the summer season (March and May).Lambs should only be drenched when they have a FAM of 2.5 or more.Any lamb that was drenched should be noted and culled.Replacement rams and ewes should be selected from the animals that did not need dosing on the basis of one of the above selection indices incorporating FEC and FAM, with or without BCS.Adult ewes should only be drenched on FAM (Targeted selective treatment). Note and cull ewes that need repeated drenching.Evaluate existing sires on the performance of their offspring.If rams are bought, buy only rams resistant to internal parasites.

Commercial animals

Follow the normal internal parasite control program before weaning, i.e. routine pooled FEC.After weaning only ewe lambs should be recorded.FAM should be recorded every 14 days until the Haemonchus challenge has decreased.FEC should be monitored through monthly pooled FEC samples.Lambs should only be drenched when they have a FAM of 2.5 or more.Any ewe lamb that was drenched should be noted and lambs that needed 2 or more drenchings should be culled.Adult ewes should only be drenched on FAM (Targeted selective treatment). Note and cull ewes that need repeated drenching.Individual FEC of all adult rams should be recorded during the peak Haemonchus season. Before faecal sampling, the rams should not receive any anthelmintic treatment for at least 3 to 4 weeks. Cull rams with too high FEC.Buy only rams resistant to internal parasites.

CONCLUSIONS

Progress was made when selecting for resistance to H. contortus in the Wauldby Dohne Merino flock. These results were used to develop protocols for selection for resistance to H. contortus under South African conditions. The developed protocols need to be validated on various farms before they can be implemented on a wider scale.

 ACKNOWLEDGEMENTS

Mr Robbie Blaine and the personnel at Wauldby for their valuable contribution in the execution of the project and RMRD-SA for funding of the project.

Conclusions

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project –

Greta Snyman on GrethaSn@daff.gov.za

Modeling veld production using MODIS LAI – Phase 3

Modeling the net primary production of arid and semi-arid rangelands in southern Africa using MODIS LAI and FPAR products – Phase 3

Industry Sector: Cattle and Small Stock

Research Focus Area: Sustainable Natural Resource utilisation

Research Institute: University of Pretoria

Year of completion : 2019

Researcher: Anthony R. Palmer

The Research Team

TitleInitialsSurnameHighest QualificationResearch Institution
DrM.M.ScholtzPhDARC-AP
ProfEvan Marle-KosterPhDUP
MrsA. Theunissen MSc Vaalharts Research Station

Aims of the Project

  1. To evaluate whether the Celtic mutation on the POLL locus is the causative mutation for polledness in Bonsmara and Drakensberger
  2. To perform a genome wide association study of the Polled and Scur genes based on phenotypic data and genotypic data from the GGP Bovine 150K SNP bead chip
  3. To apply sequence data available from the Bovine Genomics Program to finemap the suspected regions for the Polled and Scur genes

Executive Summary

The objective of this study was to compare four commonly used growth promotants in a commercial sheep feedlot. The steroidal growth promotants chosen for this trial were Ralgro (zeranol), Revalor G (Rev G; TBA/oestrogen- 17β), Revalor H (Rev H; TBA/oestrogen- 17β) and Zilmax® (zilpaterol hydrochloride). The growth promotants were compared with one another and within three sex groups, namely ewe, ram and wether (castrates), to determine which molecule or combination of molecules, if any, had the most benefit and profitability when measured against a control group.  Sheep were stratified based on initial weights and then randomly allocated to treatment groups in a completely randomised control study. All sheep originated from the same farm, and they were of  similar age, breed,  transport method,  processing method, feed (the only difference being  the groups receiving Zilmax® during the last 18 days of feeding, making provision for 3 days withdrawal), weather conditions, housing and time on feed. A time constant termination date was used in this study, in order to measure the performance of lambs in treatment groups over time.

This project has continued upon earlier, RMRD-SA funded projects that evaluate the using of earth observation (remote sensing) to model net primary production in South African grazing systems. The final results of this research are included in several research papers, students completions (PhD and BSc (Hons)), as well as a popular article. An Android application (Smartphone only) has been developed to determine the grazing capacity from the Google Earth Engine database of Landsat and MODIS imagery. This application is in the process of being tested in on-farm situations and is available to individual smartphones and tablets onto which the application can be installed. A further extension of the app development is an MSc project at Stellenbosch University that has prepared a new map of the fractional cover of grass, trees, shrubs and bare soil across South Africa. There has been one scientific paper published on the project since the last report, and two conference proceedings. A mini thesis (Geo-informatics Hons) describes how the application works. This application has also been made available in the public domain in the Google Earth Engine environment: https://liezlvermeuln.users.earthengine.app/view/spacegrazer

The objective of this phase of the project was to further validate the production estimates being made using MODIS LAI and fPAR, and to develop an Android-enabled application that can convert these estimates into grazing capacity model that could be used by farmers.

Results

Aim 1  All MODIS LAI and fPAR data are now available via the Google Earth Engine (GEE) interface. It is no longer necessary to download and archive these data from the NASA Distributed Archive. A large number of Java scripts have been written to extract data for livestock farmers throughout the Eastern Cape from the GEE user interface. Ms T Zondani has been appointed on the project and has been trained to extract data from GEE. Through GEE, data acquisition has been extended to other MODIS products, including the enhanced vegetation index (EVI), net primary production (NPP), gross primary production (GPP) and evapotranspiration (MOD16). Water use efficiency maps (WUE) have been prepared for all the years 2000-2017.

Aim 2  During this phase of the project we held workshops with the farmers in several rural villages to determine their response to the climate change predictions for that region, particularly where it is predicted to become hotter and drier. The project has established a world-class scientific installation on a livestock farm in the Smaldeel. This part of the project has seen the establishment of two eddy covariance systems on a site that had experienced bush encroachment in the past 50 years (See attachment).  Each eddy covariance system measures the direction and amount of carbon and water that moves between the earth and the atmosphere, and is a major contribution to South Africa’s understanding of the dynamics of this exchange between the earth and the atmosphere. The installation provides the opportunity to explore the consequences of climate change on grassland and bush encroachment. The RMRD-SA contribution to this site has been the transport to and from the site.

Aim 3 Using data from an eddy covariance (EC) system in the Albany Thicket, the project assessed the C sequestration options for farmers in the thicket. Carbon sequestration rates for the thicket biome are in line with those predicted by Aucamp and Cowling and Mills (2013) of 0,13-0,15 kg C m yr-1. The EC system has been moved to the farm Endwell in the Adelaide District and the C sequestration benchmarks for this area, which is being invaded by Vachellia karroo, will be available during 2018-2019. The development of the grazing capacity of South Africa based on the NPP data from 2009 has been published in both the peer-reviewed (Meissner et al 2013) and popular media (Palmer 2013). Since 2014, we have tested the map against other estimates of carrying capacity.  This beta testing of this map showed that the estimates for grazing capacity were too high (50%) and this was most likely due to the high fraction of woody plants (trees and shrubs) in the Eastern Cape. The new MSc project to prepare a tree/shrub/grass/bare soil fractional cover map was therefore initiated. The climate change predictions for the West Coast (hotter and drier conditions) have been incorporated into workshops and grazing management recommendations for two rural communities.

For the east coast, the predictions are more promising, with an increase in rainfall predicted. The effect is already being experienced in this region, with an increase in grassiness and a general improvement in the net primary production being reported. In order to deal with this understanding and its implications for commercial livestock farmers, a new experimental site has been established at Endwell farm.

Aim 4.A BSc (Hons) project was completed using the relationship between Landsat NDVI and biomass production. The application accessed Landsat and MODIS databases via the Google Earth Engine portal (GEE). The student has registered for an MSc (Stellenbosch University). She developed an Android application called Land Suitability Index (LSI) using hybrid model technology. The application determines the geographic position of the farmer from the geo-location options on an Android smartphone. It uses GEE web-interface to collect data on the NDVI history of the specific site. This provides a long-term (19 year) summary of the photosynthetic performance of the site, and evaluates the current NDVI relative to the mean for the 18 years. This history is converted into the available biomass produced in the last 12 months. The farmer can then adjust his stocking rate based on the actual production. An improvement is the addition of proportion of vegetation that is grass, as this is the major one relevant to cattle and sheep. In order to achieve this, Ms Vermeulen, in her MSc, has developed and tested a new fractional cover map. The output is now available as a Google Earth Engine application called Spacegrazer.

https://liezlvermeuln.users.earthengine.app/view/spacegrazer

This application can be used by anyone to ascertain the grazing capacity of a site in southern Africa.

Ms Vermeulen conducted field surveys where she measured the fraction of grass, shrubs, trees and bare soil in pixel of a Sentinel scene. The results from this analysis will form part of her MSc thesis.

Conclusion

The project has made excellent progress since its inception in 2010. The has been exceptional growth in the understanding of the benefits and dis-advantages of using remote sensing to estimate net primary production. In commercial farmland, where farmers tend to leave standing biomass available for the dry season, the predictions of NPP provided by the MODIS products have been very useful, and can be used to predict the grazing available to the farmer. This certainty has been converted into two applications: 1) for an Android device and 2) on-line application in the Google Earth Engine environment. Both of these applications have been tested on several commercial livestock farms and on several game farms. Several farmers have been signed up to receive monthly predictions of the biomass available for their property. One of the big challenges when using remote sensing to predict production is the presence of woody species. This is being solved through a national map of fractional woody cover which has now been produced by the project through an MSc at Stellenbosch University. However, in communal rangelands, where most biomass is consumed as it is produced (the so-called continuously grazed systems), the MODIS products are not able to detect all of the net primary production. Fially, the project has also enabled us to establish, in collaboration with Rhodes University and the National Equipment Programme, two eddy covariance systems that measure the actual C sequestration and water use of  rangelands. This collaboration has resulted in the establishment of a world-class experimental facility on a commercial livestock farm. At this site we are computing the impact of woody encroachment on grass production and water use. This will feed into policy on how the state will deal with woody encroachment and its impact on the catchment water balance.

Popular Article

Using satellite imagery for climate smart adaptive planning of grazing in near real time by Weideman, CI and Palmer, AR 2019

Click on this link to download thea article which was published in the Wool Farmer Article LINK

Conclusions

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project on :mmakgahlela@arc.agric.za