Woolliams, John - The Roslin Institute - University of Edinburgh

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Gen’ Epi’ Problems (2) • Incomplete disease models for genetic variance » ignore infectivity i.e. ‘shedders’ » impact <strong>of</strong> variation in infectivity potentially as large as variation in susceptibility » no easy way to capture this variance in genetic models
Gen’ Epi’ Problems (3) • What does h 2 ~ 0.25 on ‘underlying complementary log-log scale’ mean to an epidemiologist » epidemiologists work on ‘SIR’ models » time-dependent models with very different parameterisation • Need to reconcile models
Page 1 and 2: Prospects & Progress: Challenges fo
Page 3 and 4: One Vision of the Future • Clone-
Page 5 and 6: Issues • Cloning • Transgenics
Page 7 and 8: Precision Animal Breeding • Relev
Page 9 and 10: Translation to Poultry • Better p
Page 11 and 12: Dairy Progress • Going well! •
Page 13 and 14: Factors for Accuracy Phenotypes Gen
Page 15 and 16: Factors for Accuracy Phenotypes Gen
Page 17 and 18: Poultry Phenotypes Phenotypes • P
Page 19 and 20: Poultry Genotypes Genotypes • Gen
Page 21 and 22: Poultry Genotypes Genotypes • Gen
Page 23 and 24: Genomic Evaluation • However may
Page 25 and 26: Precision in Goals • Disease resi
Page 27: Gen’ Epi’ Problems (1) • Bias
Page 31 and 32: Role of Genomics • Genomics relea
Page 33 and 34: Genotype to Phenotype Genome Gene 1
Page 35 and 36: Genotype to Phenotype Genome Gene 1
Page 37 and 38: Genotype to Phenotype • Gene expr
Page 39 and 40: Variation in Expression • eQTL »
Page 41 and 42: Variation in Expression • mQTL ex
Page 43 and 44: Precision Breeding • Bioinformati
Page 45: Summary • Challenges to deliver P

Woolliams, John - The Roslin Institute - University of Edinburgh

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