Gene expression: Nguni and Bonsmara cattle

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

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

Introduction

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.

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;

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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: 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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Please contact the Primary Researcher if you need a copy of the comprehensive report of this project. Lene van der Westhuizen lenevdwest@gmail.com

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 :LindeD@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 :LindeD@arc.agric.za

Innovative management for beef productivity

Innovative management to increase beef productivity in South Africa : Phase II

Industry Sector: Cattle and Small Stock

Research focus area: Livestock production with global competitiveness

Research Institute: ARC – Animal Production Institute

Researcher: Ms SM Grobler MSc (agric) Animal Science

Research Team:

TitleInitialsSurnameHighest Qualification
DrM.M..ScholtzDSc (Agric) Animal Science
DrA.MaiwashePhD (Agric) Animal Science
MrP.J.J.BreytenbachMSc (Agric) Animal Science
DrJ.P.C.GreylingPhD (Agric) Animal Science
DrF.W.C.Neser
PhD (Agric) Animal Science

Final report approved: 2016

Aims of the project

  • To establish if synchronization can lead to an increase in the total mass of calves weaned from a limited calving season, most likely by decreasing the days to calving, but also by increasing number of calves born
  • To establish if breeding replacement heifers at 14 months have an economic advantage over breeding heifers at 26 months in term of reproductive performance
  • To establish the impact of the two different grazing strategies on veld condition, grass species composition and basal vegetation cover over time

Executive Summary

This report presents the final results of the combined first and second phase of the project: Innovative management for improved productivity: Beef.  The motivation for this project was that the South African beef market has changed with a need for livestock research and development to think in terms of a livestock systems approach.  This entails the combination of sound natural resource utilization, forage management and reproduction management to ensure a sustainable production enterprise over time through the allocation of limited resources.

When the project was planned it was clear that a period of 3 years was not enough to evaluate extremely valuable long term effects on herd life and veld condition; however, the RMRD-SA only fund projects for a maximum of 3 years and therefore a second application was approved to cover the remaining two-year project period.

South Africa is still a net importer of beef. Therefore, by increasing off take in the beef sector, South Africa can move towards self-sufficiency. With fertility being regarded as one of the main components influencing total beef herd efficiency, it is essential that the quoted calving percentage of 62% in the commercial beef sector of South Africa must be improved.  If the long calving seasons can be shortened and the calving percentage increased, more and heavier calves with a more uniform age can be weaned.  Cows that calve early also have a better chance of conceiving in the next breeding season and are generally seen as the more fertile animals

Development, production and quality of replacement heifers is a crucial component in the extensive beef production system.  In general, beef heifers are managed to calve for the first time at three years of age, but in some cases mating of heifers at one year of age have been advocated. 

All extensive beef production systems in South Africa are dependent on natural veld and it is well documented that veld condition have a huge influence on a number of beef production parameters. Studies conducted on natural veld have concentrated mainly on aspects that affect herd efficiency, including calving percentage, pre-weaning growth and supplementation of cows and calves.  However, none of the studies focused on the reproduction performance of beef cattle mated naturally after synchronization, heifer age at breeding and effect of grazing system on veld condition.

The aim of the study was to evaluate: the effect of estrous synchronization followed by natural mating on the calving percentage and calving distribution of multiparous beef cows and heifers; effect of breeding heifers at either 14 months or 26 months of age and the evaluation of a high utilized grazing system and controlled selective grazing on veld condition and animal performance.  The effects of climate on cow-calf production characteristics over time was also evaluated.

The study was conducted from 2009 to 2015 at the Roodeplaat experimental farm (REF) of the ARC-Animal Production Institute (25°34’11.27’’S; 28°22’05.36’’E) on 900 ha of natural rangeland described as Sourish Mixed Bushveld.  The experimental herd (n=92) was divided in four sub-herds consisting of 23 cows each at the beginning of the project in 2009.  It was ensured that the four sub-herds were as uniform as possible at the beginning of the project e.g. age, weight, previous number of calves. Within each sub-herd, 50% of the cows and heifers were synchronized prior to the commencement of the breeding season. Two sub-herds were subjected to high utilized grazing and two sub-herds were subjected to controlled selective grazing. The two grazing systems were related to the use of 30% or 60% of the available grass dry matter.  Half the heifers were mated at 14 months and the other half at 26 months.

Results from this study indicated that calving percentage and body condition score did not differ significantly (P=0.54) between cows that was either synchronized or not synchronized followed by natural mating.  However, estrous synchronization prior to natural mating did influence the average days to conception with synchronized cows calving earlier, except for 2012 in the calving season.  Over the six-year project period 15% more cows from the synchronized group conceived within 293 days after the onset of the breeding season. Calves from the synchronized cows weaned on average 5kg heavier than the cows that were not synchronized although this difference was not significant.

Conception rates of heifers mated at 26 months were significantly (P<0.05) higher than heifers mated at 14 months of age.  It would seem that it may be more viable to breed Bonsmara heifers in an extensive production system in the Sourish Mixed Bushveld region at 26 months of age for the first time.  Synchronization of 14 month old heifers did not improve conception rate over 14 month old heifers bred naturally.  However, the calving percentage of synchronized heifers bred at 26 months was 6% higher than the non-synchronized heifers.

Almost no veld condition change was recorded except for veld condition scores for both controlled selective grazing and high utilization grazing.  In addition, the results indicate a tendency that high utilization grazing improved veld condition score and grass species composition over that of controlled selective grazing, but the duration of the study is too short to make a definite conclusion on the effect of grazing strategy on veld condition.

It was also shown that grazing strategy did not have a significant influence on cow weight and calf growth over the six-year period, indicating that both grazing strategies are sustainable in the Sourish Mixed Bushveld if carrying capacity is adhered to. 

With the significant differences between years (P ≤ 0.05) for calving percentage, cow weight at calving, cow weight at weaning, calf birth weight, calf weaning weight and body condition score over the six-year observation period, the effect of seasonal temperature, relative humidity and rainfall is elucidated.  Forward stepwise regression procedures were performed to determine what climatic data were involved in cow and calf weight at birth and weaning as well as calving percentage.  In spite of the high standard errors (which were probably due to the small sample size), maximum relative humidity one month prior to the start of the breeding season, made a major contribution to explain calving percentage and minimum temperature within the last month of the 3 month breeding season, had a low negative correlation with calving percentage.   It can be speculated that high humidity in the study region (Sourish Mixed Bushveld) is an indication of warm and wet conditions, negatively impacting cow and bull comfort, leading to lower conception rates.  The negative correlation between minimum temperature within the last month of the breeding season and calving percentage may indicate that the cows were unable to cool down at night during the warmer summer months of the year, leading to lower conception rates and resorptions. The researcher acknowledge that the available herd size may be a limitation and that a bigger herd or sub-herds’ size combined with bigger land size could benefit the project outcome, possibly resulting in more significant differences and/or enhanced interpretation of results

Conferences

  1. Grobler, S.M., Scholtz, M.M. & J.P.C. Greyling, 2013.  Reproduction performance of beef cattle mated naturally after synchronization in the Central Bushveld Bioregion.  South African Society of Animal Science 47th Congress – University of the Free State, Bloemfontein, Free State Province 23-26 June 2013. Poster
  2. Grobler, S.M., Breytenbach, P.J.J. & M.M. Scholtz, 2013.  Effects of 2 grazing systems on veld in the Marikana Thornveld.  Grassland Society of Southern Africa.  48th annual Congress – Modimolle, Limpopo Province 15-19 July 2013.  Presentation
  3. Grobler, S.M., Scholtz, M.M., Neser, F.W.C., Greyling, J.P.C, Morey, L. & F. Calitz, 2016.  Reproductibve performance of extensively managed beef heifers mated at 14 months or 24 months in the Marikana Thornveld.  51th annual Congress – Stellenbosch, Western Cape Province 3 – 5 July 2016.  Poster

scientific articles

  1. Grobler, S.M., Scholtz, M.M., Greyling, J.P.C. & F.W.C. Neser, 2014.  Reproduction performance of beef cattle mated naturally following synchronization in the Central Bushveld bioregion of South Africa. S. Afr. J. Anim. Sci. 44: S70-S74
  2. Grobler, S.M., Scholtz, M.M., & Schwalbach, L.M.J. & J.P.C. Greyling, 2013.  Effect of synchronization on calving date following natural mating in beef cattle.  Appl. Anim. Husb. Rural Develop. 6:15-17

Popular Article

  • Grobler, S.M., Scholtz, M.M. & Breytenbach, P.J.J., 2014. Innovation = improved productivity. Red Meat/Rooi vleis. Agri Connect Pty (Ltd), Pretoria. Vol 5(1): 74-77

PhD Thesis submitted

  • Grobler, S.M., 2016. Alternative management systems to increase beef production under extensive conditions. PhD thesis. University of the Free State, Bloemfontein.

Popular Article

Will follow later

Supplementation of ruminants on winter pastures

Supplementation of ruminants on winter pastures

Industry Sector: Cattle and Small Stock

Research focus area: Livestock production with global competitiveness

Research Institute: University of Pretoria

Researcher: Prof Willem.A. van Niekerk PhD (Agric) Animal Science

Research Team:

TitleInitialsSurnameHighest Qualification
ProfLourens. J.ErasmusPhD (Agric) Animal Science
DrA.Hassan
PhD (Agric) Animal Science
MrR.J.Coetzer
MSc (Agric) Animal Science
MrHMynhardtMSc (Agric) Animal Science

Final report approved: 2016

Aims of the project

  • To develop a cost-effective supplementation strategy for ruminants under low quality winter forage conditions
  • To maintain body weight during the wineter season by assessing different sources and levels of nutrients that enhances poor quality roughage utilisation
  • To investigate intake, fiber degradation and microbial protein production when various types and levels of nutrients are supplemented to ruminants kept at maintenance under extensive conditions

Executive Summary

A series of studies was conducted to evaluate differential energy and nitrogen (N) sources as supplemental feed to sheep grazing low quality winter grazing in the High veldt. Knowledge on supplementation under local conditions are limiting as the majority of supplementation studies are funded and performed in the more temperate areas. Results indicated that higher N and energy inclusion levels are necessary to optimize ruminant production under local conditions compared to temperate areas. In addition, the ratio of fermentable energy to available protein is an important parameter in optimizing supplementation programs. It is concluded that the supplementary recommendations from the current feeding tables does not describe the requirements and nutrient quality of the tropical grasses satisfactorily and as such, cannot be used to predict supplementation responses by the tropical forage fed ruminant.  del can be used for further sensitivity analyses and “what if” scenarios as well as a database to answer specific questions.

Popular

SUPPLEMENTATION OF SHEEP GRAZING LOW QUALITY GRASSES WITH UREA AND STARCH

BY:  *H. MYNHARDT, W. A. VAN NIEKERK AND L. J. ERASMUS, UNIVERSITY OF PRETORIA

Every year sheep might lose up to 30% of their summer body weight gain during the dry winter periods in the high veldt.  While these weight losses have an economic impact on its own, it also is associated with an increased susceptibility for diseases and parasitic infestations and decreased reproductive performances. It generally is considered that protein or non-protein nitrogen (NPN) supplementation is necessary to limit these weight losses during these periods. However, due to the type of grass found in the High veldt area of Southern Africa, data is limiting on the effects of supplementation of ruminants grazing these types of grasses (See box: Differences between C4 and C3 grasses). As such, supplementations recommendations derived from current feeding tables seldom satisfy the needs of the grazing ruminant in Southern Africa. Therefore, a series of studies was conducted at the University of Pretoria to determine and quantify the requirements of the ruminant grazing low quality Eragrostis curvula hay commonly found in the Southern Africa High veldt.

* References and correspondence can be obtained from the author: hermanmynhardt@yahoo.com


Box 1: Differences between C4 and C3 Grasses

The acronyms C3 and C4 refer to the first product of the photosynthetic processes in the respective grasses with the first product of photosynthesis in the C3 grass being phosphoglycerate (a 3 carbon structure) while for the C4 plant, the corresponding molecule is a 4 carbon molecule (oxaloacetate). C3 grasses are temperate grasses and are adapted to the temperate regions of the world where rainfall is more constant with maximum temperatures seldom topping 22 OC. In contrast, C4 grasses are more adapted to the subtropical and tropical climates with temperatures frequently topping 25oC during the growth period. These areas also are associated with seasonal droughts and the occasional frost. Due to these extremes in temperatures and seasonal droughts, C4 grasses contain more bundle sheath cells and less available nutrients compared to C3 grasses during all maturity stages. Ruminant production therefore in general is significantly lower in ruminants grazing C4 grasses compared to temperate C3 grasses, especially during the dormant stage of the grass where lignification of the C4 grasses reduces the availability of the nutrients even further. As such, supplementation requirements and responses differ between ruminants grazing these grasses. However, the majority of supplementation studies in the past have been conducted on C3 grasses as it is found more in the European countries where research funding is more available. As such, as more studies conducted on low quality C3 grasses are incorporated in the current feeding tables, supplementation requirements derived from these tables to the low quality tropical forage fed ruminant are not always accurate. As such, the need was established to conduct research through the financial support of the **RMRD-SA on the nutritional requirements of the low quality tropical forage fed ruminant in order to improve ruminant production in Southern Africa.


*RMRD -SA – Red Meat and Research Development, South Africa



Results and Discussion

Forage intake and digestibility was not influenced by either the level of urea or starch supplementation to the wethers. However, CP-balance, measured as CP intake – CP excretion in the faeces and urine, increased from 12.5 g CP/day in the LU wethers up to 70 g CP/day in the EHU wethers. Based on these observations, only the EHU treatment supplied sufficient protein to potentially satisfy the needs of the 50 kg wethers as they require 65 – 70 g CP for maintenance. These recommendations are significantly higher than the recommendations set in the current feeding standards, however, it is in alignment with the observations and recommendations set out by **Leng (1995) studying ruminants grazing tropical grasses in Australia.

Forage intake and digestibility was not influenced by either the level of urea or starch supplementation to the wethers. However, CP-balance, measured as CP intake – CP excretion in the faeces and urine, increased from 12.5 g CP/day in the LU wethers up to 70 g CP/day in the EHU wethers. Based on these observations, only the EHU treatment supplied sufficient protein to potentially satisfy the needs of the 50 kg wethers as they require 65 – 70 g CP for maintenance. These recommendations are significantly higher than the recommendations set in the current feeding standards, however, it is in alignment with the observations and recommendations set out by **Leng (1995) studying ruminants grazing tropical grasses in Australia.

HIGHER LEVELS OF PROTEIN AND ENERGY SUPPLEMENTATION IS NECCESARY TO OPTIMISE THE GRAZING RUMINANT IN THE S.A. HIGH VELDT DURING THE DRY WINTER MONTHS

An important parameter in ruminant nutrition is microbial protein synthesis (MPS) as it gives an indication of the efficiency of the rumen microbes. During the dry winter months, MPS generally decreases due to the lack of available nutrients in the roughages (Leng, 1990, 1995) which decreases the productivity of the animal which is experienced as weight loss by the farmer.  In this study, MPS increased almost 50% from 78 g MPS to 106 g MPS as the level of starch supplemented was increased from 200 (LS) to 280 (HS) g starch/day. This observation is in agreement with suggestions made by Leng, (1990; 1995) that energy is an important nutrient driving MPS in the tropical forage fed ruminant, provided that the protein requirements of the ruminant have been met. Interestingly, energy supplementation for the temperate forage fed ruminant is not always advocated as these grasses contain higher concentrations of water soluble carbohydrates compared to the tropical grass.

Based on the above results, higher levels of both protein and energy supplementation is necessary to optimise ruminant production during the dry winter months in the High Veldt. The question now was asked whether there was an “ideal” quantity of protein and energy to be supplemented to ruminants grazing low quality “tropical” forages.

Graph 1 is a schematic representation of MPS per unit CP intake (MNS: N intake) while Graph 2 represents the mean rumen ammonia nitrogen (RAN) concentration as influenced by the ratio of starch supplemented to available protein intake.

Graph 1

Urea supplementation across all three starch treatments affected the MPS: CP ratio similarly with the ratio decreasing from almost 3 to below 1 where the wethers were supplemented with the higher urea treatments (HU and EHU). It is important to note that alleviated MPS: CP levels (above 1) could be indicative of CP deficiency as more microbial protein was synthesized in the rumen compared to dietary CP intake. The additional CP required to produce the microbial protein under these circumstances is derived from body protein catabolism which in itself, is an inefficient process, resulting in an excessive body weight loss. As such, in this trial, it is suggested that the protein intake of the wethers supplemented with at least 26.4 g urea/day (HU) was sufficient to meet the requirements of the wethers.

Graph 2

An inverse relationship was observed between RAN and the ratio of starch: digestible protein intake (Graph 2) with RAN decreasing and plateau between 5 and 10 mg RAN/ dL rumen fluid as the ratio increased. An inflexion point was observed where RAN increased exponentially to levels as high as 25 and even 30 mg RAN/dL rumen fluid as the ratio decreased below 2: 1. This graph highlights the importance of supplementation of both rumen available energy sources (starch in this instance) as the supplementation of only RDP sources to the ruminant could lead to an increased risk of ammonia toxicity under these circumstances.

Conclusion

The results from this study suggest that the supplementation requirements of 50 kg wethers grazing low quality tropical forages (2.7% CP) differs to the current feeding standards as:

  • Higher levels of protein (urea supplementation up to 26.4 g urea per day per wether or 3% urea of the total DM intake) is necessary to optimise CP balance in the tropical forage ruminant.
  • Starch supplementation (up to 280 g/wether/day or almost 20% of the total DM intake) in addition to urea supplementation is necessary as tropical grasses not only are deficient in protein, but also in easy available energy.
  • For wethers grazing low quality tropical grasses, the ideal ratio of starch supplemented to digestible protein intake lies between 2 and 3: 1.
  • Additional research is necessary to study the effects of other energy sources and protein sources on rumen environment and the production parameters of the tropical forage fed ruminant as these sources might have different availabilities compared to urea and pure starch within the rumen.

The authors wish to thank the Red Meat Industry and Research Development (RMRD) for their financial support of this study.

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project –
Willem van Niekerk on willem.vanniekerk@up.ac.za

Jackal ecology on reserves and farms

Ecology and population dynamics of black-backed jackal (Canis mesomelas) on reserves and farms

Industry Sector: Cattle and Small Stock

Research focus area: Predation management

Research Institute: Centre for African Conservation Ecology, Nelson Mandela University

Researcher: Prof Graham Kerley

The Research Team

TitleInitialsSurnameHighest Qualification
DrLMinniePhD

Year of completion : 2017

Aims of the project

  • To determine dispersal direction between subpopulations
  • To compare demographic structures between subpopulatins
  • To resource use between subpopulations

Executive Summary

xxx.

Lethal carnivore management, aimed at reducing carnivore impacts, threatens the persistence of carnivores globally. The effects of killing carnivores will depend on their life histories and social structures. Smaller canids, like black-backed jackals (Canis mesomelas), are highly adaptable and display variable population-level responses to mortality sources, which may contribute to their success in fragmented landscapes. Jackals, the dominant predator of livestock in South Africa, are widely hunted to reduce this predation. This hunting is heterogeneous across the landscape, focussed on livestock and game farms, with nature reserves acting as refuges.

The aim of this research was to investigate the ecology and population dynamics of jackals in response to heterogeneous anthropogenic mortality. I hypothesized that the spatial variation in hunting results in the formation of a source-sink population structure, which contributes to the persistence of jackals. I addressed this hypothesis by evaluating two criteria, essential for the formation of a source-sink system in larger mammals.

Firstly, I confirm that hunting pressures result in the formation of distinct subpopulations with asymmetrical dispersal (i.e. compensatory immigration) from unhunted reserves to neighbouring hunted farms. Secondly, I show that jackal subpopulation display asynchronous demographics, with farm populations displaying a relatively younger age structure and an associated increase in reproductive output (i.e. compensatory reproduction). This confirms the formation of a hunting-induced source-sink system. Additionally, I show that jackals have a catholic diet, which confers a level of adaptability to direct (anthropogenic mortality, prey provisioning) and indirect (alteration in prey base) habitat modifications. This dietary flexibility allows jackals to obtain the appropriate resources to achieve reproductive condition. The relatively better body condition of younger jackals in sink habitats allows for compensatory reproduction which contributes to the success of jackals on hunted farms.

Based on my findings, I hypothesize that the compensatory life history responses of jackals to anthropogenic mortality may be ascribed to two interconnected mechanism. Dispersal is presumably driven by density-dependent interference competition, as dominant territorial pairs outcompete subordinates in high-density reserve areas, forcing them to disperse onto low-density farms (i.e. ideal despotic model). Additionally, farms likely represent attractive habitats, owing to a reduction in conspecifics and a concomitant increase in resource availability (including anthropogenic resource provisioning). Therefore, dispersing subordinates presumably select for farms which are perceived as good quality habitats, as the high risks of anthropogenic mortality cannot be perceived by dispersing individuals. This results in the formation of an attractive sink or ecological trap. These compensatory processes will continue to counter population management actions as long as recruitment from unmanaged areas persists. This hypothesis provides a conceptual framework for future research directions in understanding jackal persistence and management (i.e. specifically focussing on controlling dispersal) of jackal populations.

POPULAR ARTICLE

To follow soon

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project – Graham Kerly on graham.kerley@mandela.ac.za

Jackal ecology on reserves and farms