The what, why and how of Genomics for the beef cattle breeder

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1 The what, why and how of Genomics for the beef cattle breeder Este van Marle-Köster (Pr. Anim. Sci) 25 January 2019 Waguy info day 2

2 Today s talk Focus on what is genomics Brief definition & references to the markers used Why do we use/want to apply genomics Improve accuracy of parentage testing Eliminate genetic defects & manage major genes Improve accuracy of selection > accuracy of GEBV s How do we practise genomics Process 2

3 What is genomics? Genomics is the science that promotes the understanding of genetics and gene function in livestock the application of this particular to farm animal health and welfare, product quality and production efficiency

4 Understanding genetics: Chromosomes carry genes and found on the chromosome in the nucleus of the cell Gene: unit of inheritance Allele: variation of the gene at specific locus on the Chromosome

5 DNA markers DNA marker: Specific fragment of DNA Found at a specific locus Each individual has two copies (alleles) Different alleles results in variation DNA mutations = variation Polymorphic loci = useful = variation Tautz & Renz (1984) Simple sequences are ubiquitous repetitive components of eukaryotic genomes. Nucl Acids Res. Tautz et al., 1986 Cryptic simplicity in DNA is a major source of genetic variation Nature

6 Relevant markers for today s discussion: Microsatellite markers vs SNP markers Microsatellite: Short repetitive DNA sequence Repeats differ between individuals Marker for genetic diversity, parentage, forensic work SNP (Single nucleotide polymorphism) Variation in single base pair at a specific position in the genome Less diversity than microsatellite markers Found more regularly in the genome 6

7 Why SNP s for genomics? A complete sequence of the bovine genome Resulted in SNP discovery (Matukumali et al. 2009) Moved from microsatellite markers to SNP s Advantages of SNP s Higher density markers >> genomic information High throughput commercial SNP arrays 7 7

8 SNP markers 8

9 Why do we want to use genomics? Improve accuracy of parentage testing Parentage errors of 10-15% result in < 15 % in genetic progress Estimated error rates from literature: 10% estimated in UK dairy cattle (Visscher et al. 2002) 15 % error in commercial sheep flocks (Dodds et al. 2007) 25 % in S A Angora goat flocks (Friedrich, 2010) 9

10 Animal Recording: the foundation of seed stock production Step1: accurate pedigrees Grand Sire Grand Dam Sire Requires accurate identification of sire and dam. Calf/progeny Grand Sire Grand Dam Dam

11 Parentage using SNP s Evaluate potential sires alleles Know dam alleles Compare with offspring alleles Identify similar match of sire to offspring alleles 11

12 Eliminate genetic defects & manage major genes Major genes: Single traits (MAS) e.g. polled trait (Celtic test) Major genes e.g. myostatin in beef cattle 12

13 Summary of Genomic selection Process Reference population Genomic info D N A 50 K

14 Process Collect hair samples Collect from all animals store in duplicate if possible Send to the service provider/laboratory DNA extraction & genotyping Largely automated process SA ARC BTP, worldwide laboratories rendering genotyping services Genomic info provided to the service provider Checks the pedigrees Feed back on genetic defects & other genes of interest Estimates the GEBV for application by the breeder 14 14

15 Genomic Prediction: 1.Reference population: animals with genotypes & phenotypes 2. Take genotypes on related young animals 3 GRM relates animals Genomic Relationship Matrix gebvs 15

16 FERTILITY MATERNAL GROWTH NFI CARCASE BULLS WEANERS FINISHED STEERS HEIFERS BRANDED BOXED BEEF CARCASE EATING CARCASE QUALITY HUMAN HEALTH Seedstock Producers Commercia l Producers Feedlots Abattoirs/ Processors Wholesaler s Retailers Consumers Genomic Testing and Selection Registration + Performance Data PROGENY 200, 400, 600 Day WGT Feedlot Entry & Exit WGT) Wagyu Genetic Analysis (BREEDPLAN) EBVs - Predict Genetic Performance Indices combine EBVs to rank animals CARCASE Ausmeat: CWT, Marbling, Fat Digital carcass imaging: Marbling, EMA, Marbling Fineness Wagyu Genetic Analysis

17 Genomics works: Trends in Australian Holstein dairy cows (Graham Truscott, 2017) With-BLUP: 8 points per year With-Genomics: 16 points per year or 100% increase in genetic gain Pre-BLUP: 4 index points per year

18 Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle Garcia-Ruiz et al., 2016 With-Genomics In the period following implementation of genomic selection, dramatic reductions were seen in GI: Sire of Bulls - GI reduced from 7 y to < 2.5 y Dams of Bulls - GI fell from about 4 y to nearly 2.5 y 18

19 Garcia-Ruiz et al., 2016 cont Genetic gain seen for milk, fat and protein yield, Most dramatic response to GS was observed for the lowly heritable traits Daughter Pregnancy Rate, Productive Life and SCS. With-Genomics With-Genomics

20 Genomics works Genomics: long term investment Provides a competitive edge Don t miss out! 20