Towards genomic breeding values for sheep in South Africa

1. Towards genomic breeding values for sheep in South Africa Geoff Kingwill

2. Outline • Background • Why Genomic breeding values? • Need for a reference population • Resources • Implementation • Progress thus far • Budget

3. Background • Large parts of SA arid and not suitable for cropping - only fit for the extensive production of meat and fibre • Stock farming dominant enterprise among small-scale and emerging farmers • Small stock is predominant in the central and western regions

4. Background • Small stock relatively small at ~8% of animal GDP • Mostly sheep (~21 M) and goats (~3 M) • Of major regional importance despite modest monetary output • Shown to be sustainable under adverse conditions • Concentrate on the sheep industry

5. Background: Sheep numbers and products

6. Background: A wool example • Wool competes with other fibres (cotton, synthetics) • Synthetics produced in factory environment – great potential for productivity improvements • Cotton yields increased by 66% over the past 15 years • Similar progress is needed for wool to remain competitive • Harnessing genomic information is essential

7. Why Genomic breeding values? • Genomic revolution • To harness this technology certain things need to be put in place • Genomic Estimated Breeding value • Reproduction hugely important. Currently we are limited because it is sex specific and due to short herd life. • Increased accuracy of selection • Selection at earlier age • Opportunity for sheep industry in RSA • Increases in economic output & lower greenhouse gasses / kg of product • Increase reproduction among small scale farmers in what is often a harsh environment

8. TOTAL Weight weaned135 ewes with 4 lambing chances

9. Potential Gains • This variation is in all flocks • Best 15 ewes - 48 kg of lambs per year (weaned 1.75 lambs) • Worst 15 ewes - 11 kg of lambs per year (weaned 0.5 lambs) • Difference = 37 kg of lamb per ewe per year – 148 kg per ewe over 4 years

10. Selection candidates Reference population Genotype Phenotype Genotype Prediction equation Genomic Breeding Value Selected animals

11. Need for a reference population • Quantify the relationship between variation trait and SNP alleles in the South African sheep • Genotyping –R1500/animal • Phenotyping (trait recording) • >5000 animals representative of selection group • Capture all genetic and phenotypic variation • Least related • Heritability of traits • Constant maintenance

12. Resources: Institutional resource flocks • Resource flocks (Schoeman et al., 2010) • Include different breeds • Mostly under institutional control • Could fulfill a similar role to the Information Nucleus Flock in Australia • Traits no recorded by commercial flocks are recorded in these resource flocks

13. Resources: Commercial flocks • Flocks with data and pedigrees recorded • Roughly 92.6 thousand weaning weights recorded in 2012 • Phenotyped for standard production traits • Influential sires and dams can be identified for genotyping

14. Resources: commercial records

15. Resources: commercial records

16. Resources: commercial records

17. Resources: commercial records

18. Resources • All breeds at once? • Across breed GEBV’s not very accurate • Cost prevents reference population for all breeds • Which breed to consider? • Presently Merino • Well-phenotyped resource flocks • Relatively stable commercial flock

19. Implementation • Genotyping of a representative sample from resource flocks • Genetic composition of the available resource • Calculate population parameters • Determine necessary composition of reference population • Identification of samples representative of the national flock • Create genetic links between resource flocks, industry flocks and the larger national flock • Influential sires • Genotyping at GeneSeek Inc (USA) and/or ARC Biotech Platform • BLUP EBV + genomic information →GBLUP→GEBV • Assess accuracy of GEBV in validation flock • National GEBV for producers to use in selection

20. Implementation • Sample processing: • Labs at Elsenburg and GADI • Sample storage in -80 °C freezers at Elsenburg and GADI • Genotyping at GeneSeek Inc (USA) and/or ARC Biotech Platform • Data: • Storage on allocated harddrives and analyses on CAF HPC

21. Implementation - people • WCDA - Prof SWP Cloete and Dr JJ Olivier • GADI - Dr Gretha Snyman, Dr Willem Olivier • UP - Prof Este Van Marle-Köster • US - Prof Kennedy Dzama and Ms LiseSandenbergh • UFS - Prof Japie van Wyk • Industry Partners - Cape Wools SA, WCART, GADI, THRIP and RMRDT ? as co-funders • Commercial farmers - access to phenotypic records and commercial flocks • International groups already involved in ovine GBLUP

22. Progress thus far • Illumina SNP50K beadchip evaluated in several resource flocks • Namaqua Afrikaner – 34448 informative SNP’s • Dorper – 41352 informative SNP’s • SAMM – 41948 informative SNP’s • Grootfontein Merino – 44595 informative SNP’s • Cradock Merino – 44936 informative SNP’s • Consistent with results during international evaluation of chip • Appropriate genotyping tool in all breeds

23. Progress thus far • Blood sampling for 2014 completed in 3 identified commercial Merino flocks • A fourth flock scheduled to be sampled in May-June 2014 • Samples stored in duplicate at -80C at Elsenburg and GADI • Genotyped when needed

24. Progress thus far • Phenotype of two divergently selected Elsenburg lines differ significantly • Factorial component analysis confirmed presence of two genetically distinct lines • Several loci under selection on all 27 chromosomes • 48 SNP markers identified under directional selection by both Bayesian and Frequentist methods • Therefore several loci affecting reproduction

25. Current Funding: 2014

26. 7 year Budget for 4 sheep breeds