Mrode, Raphael A.

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Better lives through livestockGenetics and genomic approaches for sustainable dairy cattle improvement Prof. Raphael MrodePrincipal ScientistLivestock  Genetics  ProgramThird Research Coordination Meeting. Joint FAO/IAEA Division of Nuclear Techniques in Food and AgricultureVienna.  7 – 11th June, 20212• Characteristics of a sustainable development (FAO)• Environmentally non-degrading• Economically viable• Conserves genetic resources• Technically appropriate• Socially acceptableSustainable Dairy Improvement Program3• Components of  a sustainable dairy  genetic improvement programe therefore should  include • Improvements in productivity with no adverse effect  fitness• Improve fitness - reproductivity ability, disease resistance  robustness • Improving welfare  traits  (body condition, sound feet etc) • Little or no  negative impact on the environment Sustainable Dairy Genetic Improvement Program4Some of the genetic approaches  to achieve sustainable dairy genetic programs• Internationally efforts - broadening breeding goals • Harmonization  of trait definitions  • Establishing  data collection protocol for the difficult to measure traits • International dairy genetic evaluations –broader set of top bulls available             maintain genetic diversity• Introgression of desirable alleles5Worldwide summary of the relative weights on various major traits in national economic indexes for dairy cows from 1917 to 2017 (Miglior et al., 2017).0%10%20%30%40%50%60%70%80%90%100%1917 1927 1937 1947 1957 1967 1977 1987 1997 2007 2017ProductionConformationLongevityCalvingWorkabilityHealthFertility6Proportionate estimates of response world-wide for major traits in the national economic indexes for dairy cow from 1917 to 2017 (Miglior et al., 2017).-40%-20%0%20%40%60%80%100%1917 1927 1937 1947 1957 1967 1977 1987 1997 2007 2017ProductionConformationLongevityCalvingWorkabilityHealthFertility7Impact of  Broader indices in the UK• UK  Genetic  trends  for the for somatic cell count (SCC—indirect measure of mastitis) ,  lifespan  and fertility • Notice initial  decline  but improvements  commenced  after  putting  traits  in the index 8• Some major  sustainability  issues in dairy cattle breeding given climate change • Heat tolerance• Feed resources and  methane emission• Conserving and utilization adaptive traits in indigenous  breedsSome  approaches  for sustainability dairy cattle  breeding given climate  change9Breeding  to Adaptation to Heat stress• Trait  =   rate of decline in milk yield  with increasing THI; h2≈ 0.20• “how well does an animal cope?” ~ resilience• Dairy sires being selected in Australia  based on animal resilience to heat stress measured on the basis of productivity using THI10Evaluating the impact of heat stress on milk yield using THI for small holder dairy system (Ekine-Dzivenu et al 2020) • Effect of heat stress on milk yield assessed using THI  grouped 5 classes (61-66, 67-71, 72-78, 79-81, 82-86)• Heat stress reduced milk yield by 4.16% to 14.42% across THI groups• THI was non-linearly related with milk yield with significant negatively and positively coefficients• (-0.61, 0.004).• Next step is  to study the trait at the genetics level11• The slick hair gene located on chromosome BTA20 in Senepol cattle is responsible for• a smooth and short hair coat• confers thermotolerance• associated with an improved capacity for heat dissipation.• Introgression of the gene into some Holstein cattle has been shown• to produce animals with lower body temperatures• smaller declines in production under hot conditions (Dikmen et al., 2014; Ortiz-Colón et al., 2018) • Some breeding companies are currently marketing positive  slick bulls to farmersBreeding for  heat tolerance through introgression  of  the slick gene12Breeding for  reduction in methane emission• Important as  livestock is deemed a major contributor• Heritability  estimates vary  from 0.12 to 0.45• Difficult to measure routinely in large number of animals & lots of interest on indirect predictors• 20% reduction over 10 years feasible in Spanish Holstein with a  weight of about 33% on methane  in the toral merit index  and  a reduction in gain for  production traits by 18% (González-Recio, et al, 2020)• In Danish Holstein - accuracy of genomic selection for methane was about 0.42  but  including ECM  and BW in both  reference and  validation populations increased accuracy by  92%  (Manzanilla-Pech et al  2020)• Selection for  feed efficiency is good proxy        26% reduction in methane over a 10-year period (de Haas et al. ,2011) 13Breeding for  feed efficiency• Feeds account for about 70% of production cost• Difficult and  expensive to measure• Genomics has allowed DMI data to pooled  from 9 countries and  enabled international evaluations  ( Berry et al, 2014)14• Saved Feed = v1 x GEBVMaintenance + v2 x GEBVMetabolic• About one third of feed consumed is used for body maintenance and this is directly related to the body size. • Number of countries have implemented  index : Saved Feed cost (SFC)  for maintenance  using genomic models• Nordic  countries :  Indirect   predictors- body weight and type traits• Netherlands :  DMI or Indirect predictors :milk, fat and protein and  body weight.  • SFC accounts for 5% of the Dutch Total Merit index called NVIBreeding for  Feed efficiency 15Improving efficiency  in Tanzania Cows using milk yield and  body weightGenetic parameters , forward validation  and indexTrait Method Correlation RegressionMilk yield FRM-GBLUP 0.57 1.1FRM-ssGBLUP 0.59 1.0RRM-GBLUP 0.55 1.0RRM-ssGBLUP 0.53 0.92Body weight FRM-GBLUP 0.83 1.0FRM-ssGBLUP 0.77 1.1Milk yield, h2= 0.12 , body weight, h2 = 0.22 and rg = 0.34• Restricted index:  improves the rate of milk production but with restrictions on body weight• More efficient cows milk without increasing the amount of feed consumed. 16• Indigenous breeds represent a unique set genotypes adapted to surviving under harsh conditions and are  disease/parasite resistance. • Genomics  provide the means  for understanding the genetic  basis of this  adaptation• Kwondo et al 2020 - Several  loci in African cattle related  immunity, heat-tolerance trypanotolerance and reproduction-related genes. Sustainable cattle breeding in developing countries: Incorporating the genetic basis of adaptation17• Small  ruminants -- adaptation to arid environments and resistance to endoparasites in sheep from Tunisia (Ahbara et al, 2021)• Paths  for utilization• Incorporation of functional  regions/genes in genomic  prediction --- BayesR or BayesRC• Approach increased accuracy of prediction for heat tolerance for production traits by up  10% (Cheruiyot et al,  under review)• Gene  editing & surrogate  siresSustainable cattle breeding in developing countries: Incorporating the genetic basis of adaptation18Challenge of adequacy commercial SNP array: Examined  in three African cattle• Uniqueness  genotypes of indigenous  breeds leads to another challenge;  adequacy of commercial  SNPs panels19Assessment of the 23 commercial Bovine SNP arrays in 3 cattle breeds051015202530 Proportions of WGS in high correlation with array SNPsBoran Ndama HolsteinProportion of WGS SNPS20• Genomics gives us  the ability  to undertake • Detailed  phenotyping of difficult to measure traits in small cohort of animals• Enables  prediction of gEBVs for a wider population connected to cohort with records• Successfully used in Genomic Information Nucleus (Ginfo) project in Australia to capture fitness traits in few herds but connected to the national  population. (Pryce et al, 2017)• Increased accuracy of prediction  5 to 7 % for fertility traits in the Holstein• In developing countries, where data  capture is a challenge, genomics  may provide  an opportunity to capture difficult or expensive traitsGenomics as a platform for  collecting difficult to measure or expensive  traits21• Expanding national indices to include fitness  and welfare  traits has  been fundamental in breeding for  sustainability in dairy cattle• Genomics  have offered us the opportunity both to capture and incorporate  difficult  to measure  or expensive  traits• Genomics provide  the basis for understanding and utilizing adaptive  traits in indigenous breeds to ensure sustainabilityConclusions22Dr Okeyo  Mwai                                  Prof. John Gibson                               Dr Abdulfatai Tijjani (ILRI)Dr Julie Ojango                                   Dr Joram MwacharoDr Chinyere Ekine-Dzivenu Prof. Olivier HanotteAcknowledgementsTHANK YOUThank you for your attention 

Genetics and genomic approaches for sustainable dairy cattle improvement

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Genetics and genomic approaches for sustainable dairy cattle improvement

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