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Lessons from the past: How performance data availability and quality has led to genetic and economic gains in different breeds

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Presented by Raphael Mrode, ILRI, at the 7 All Africa Conference on Animal Agriculture (AACAA), Accra, Ghana, 29 July–2 August 2019

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Lessons from the past: How performance data availability and quality has led to genetic and economic gains in different breeds

  1. 1. Lessons from the past: How performance data availability and quality has led to genetic and economic gains in different breeds Raphael Mrode, ILRI 7 All Africa Conference on Animal Agriculture (AACAA), Accra, Ghana, 29 July–2 August 2019
  2. 2. Outline • Foundational role of data in genetic gain and economic returns • Importance of data for sustainable selective breeding – Dairy cattle, Poultry , beef cattle • Obvious trends from the past lessons • Conclusion 2
  3. 3. Foundational role of data in genetic gains and economic returns • Genetic improvement programs have delivered huge economic returns • In the UK dairy industry benefits of genetic improvement estimated to be between £2.2 billion and £2.4 billion from 1980 to 2011. • Rate of genetical change -typically 1 - 3 % of mean per annum • Cumulative from one generation to the other • Foundational to these improvements are – Efficient performance data collection and storage systems – Analytical system for the computation of genetic merit 3
  4. 4. 4 Foundational role of Data • Examine the breeder equations ΔG = ih2σp / L • Fundamental parameters that drive ΔG are directly related to the availability and quality of data. • For example, estimates of h2 are function of depth and quality of data. Estimates of heritability for milk yield in dairy cattle over time < 1980’s 1991 2000’s 0.25 0.30-0.33 0.35 – 0.50 ANOVA Animal Model Test day models • Indirect predictions of phenotypes is a major research area in order to reduce L (Mid-infra red spectrum, pedometers etc)
  5. 5. 5 Importance of data in addressing the consequences of selective breeding for only productivity • Dairy Cattle • Dominant breed worldwide for milk production is the Holstein breed. • Until to 1990’s, the breeding program focused on selection for milk productivity. Consequences: – a decline in fitness such fertility over time resulting in poor concept rate – increased lameness and reduced longevity. – On average, cows milked for about 3 lactations (alive for about 5.5 years).
  6. 6. 6 Importance of data in addressing the challenges in the dairy industry • In 1999, Lifespan predicted from type information plus direct measure based on number of parities completed was introduced in PLI • In 2003, somatic cell count (SCC—indirect measure of mastitis) and lameness( via locomotion was introduced in PLI • In 2006, fertility was introduced into PLI • Notice initial decline but improvements after incorporating data on traits in the index
  7. 7. 7 Importance of data of addressing challenges of selective breeding for growth rate in the poultry • Broilers • Growth rates increased over 300% over 50 years till the 2000’s • 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 Heritabilityovertime BWT@35days Aviagen - Genetic Trend BWT (g) - 35d
  8. 8. 8 1957 Broiler 1977 Broiler 2005 Broiler Source: Renema et al, 2006
  9. 9. 9 Importance of data in addressing the consequences of selective breeding for only productivity • Major problems of rapid improvement in body weight in the poultry were associated with leg issues • Sample of 51,000 birds in 176 flocks – At a mean age of 40 days, over 27.6% of birds in showed poor locomotion – 3.3% were almost unable to walk – The above was after culling birds with severe lameness – Toby et al, 2001. Leg Disorders in Broiler Chickens: Prevalence, Risk Factors and Prevention PLoS One. 2008; 3(2): e1545.
  10. 10. 10 Broader selection (based on data) in Poultry- overcoming leg problems • Broilers: – Broader Selection index include growth traits and leg health traits (deformities of the long bones, crooked toes, tibial dyschondroplasia and hock burn) • Turkeys – Growth traits plus gait score as an overall measure of leg health, footpad dermatitis, and 2 skeletal leg health traits, namely, valgus and varus deformities and tibial dyschondroplasia. – Kapell et al 2012. Poultry Science, 91:3032–3043 – Kapell et al 2017. Poultry Science, 96:1553–1562
  11. 11. 11 Independent report Canadian Food inspection agency on the incidence of some leg problems
  12. 12. 12 FCR Testing in Groups • Commercial like environment – Birds housed in groups – In open pens – Capture individual intake data • Allow testing of more birds • Evaluate feeding behaviour – Individual & Group 0 20 40 60 80 100 120 140 160 180 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 TotalEaten(g) 0 5 10 15 20 25 30 35 40 No.Meals,Eaten/Meal(g) eaten/bird eaten/meal meals/bird
  13. 13. 13 Long-term improvements in Biological Efficiency -38grs Feed/year -0.14% Mortality/year From http://www.nationalchickencouncil.org/about-the-industry/statistics/u-s-broiler-performance/
  14. 14. 14 14 Impact of relevant data enabling BLUP on Beef value in the UK
  15. 15. 15 British Cattle Movement Service • COMMERCIAL animals • Information – Dam – Breed – Date of birth – Date of death – Movement – Sire (not compulsory)
  16. 16. 16 Benefits of industry data • ‘Super-pedigree’ – Most complete pedigree in the UK including all bovine – BCMS – Pedigree (beef and dairy) – Milk recording records • Super-pedigree to create linkage between commercial phenotypes, which are often crossbred and registered pedigree animals
  17. 17. 17 Super-Pedigree –Evaluate Carcass cuts • Evaluation of carcass cuts for both purebreds, non-pedigree and crosses using Video Image analysis (VIA) – VIA technology allows us to better assess carcass yields for the valuable primal cuts • Some registered pedigree are genotyped and therefore genomic prediction (Single-step)
  18. 18. 18 Genomic prediction - huge gain in accuracy --- Striploin accuracy 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 gebv EBV 0-2yr EBV 6yr EBV own carcass record EBV 5+ progeny breedingvalueestiamte Striploin accuracy +55% +51% +6% -4% From Birth Average age = 9yrs (5-15)
  19. 19. 19 Obvious trends from the past lessons • Data is critical for make informed decision – Identification of the consequences of selective breeding were identified only by data analysis – Steps to implement sustainable improvement were based on acquiring relevant data • Application of appropriate models to drive genetic progress is dependent on good quality data • Design of relevant breeding programs and feedback to farmers are dependent on data
  20. 20. 20 Obvious trends from the past lessons • This is the trend in developed countries, private companies and Africa is no exception • So how are we doing? – Good in collecting DNA samples – Focus on breed characterization • Lots of international collaborations focused – Breed characterization, signatures of selection, domestication history and gene editing • These are goods steps but we have often ignored the step of collecting fundamental data - the basis for sustainable breed development for our farmers and countries.
  21. 21. 21 Obvious trends from the past lessons • We can not continue in this same trend ; we need a fundamental change in thinking • The design any project must include – how can we collect production data – first priority • Feasibility of collecting phenotypes demonstrated by – ADGG/ACCG – uses of digital tool – CBBP –uses of mobile app • There are many other less complicated Apps to collect data out there in the digital world • Implement a simple animal identification system • Include a budget for data collection at onset of any project design and any international collaboration • Issues? –sustainability? Let us begin first – just walk and we might be able to learn to run with time!
  22. 22. 22 Repository of available Data collecting tools • Proposition -- is to set a website with information on the following – Available, cheap and digital tools for data collection – Information of rules that govern animal identification and available tools – Information on free data base – Analytical tools and algorithm for data interrogation and analysis – Genetic software • Want it up and running by March 2020 and fully functional by December 2020 • Send information to africadatatools2019@gmail.com
  23. 23. 23 Conclusion • Obvious trends on the crucial role of data for genetic gains and economic returns have been outlined • This leads to one conclusion • Even in the era of genomics • #PHENOTYPE IS KING!
  24. 24. 24 Acknowledgements

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