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Genomic approaches to trypanosomiasis resistance Trinity College - some surprises Dublin Shirakawa Institute of Animal Genetics KARI-TRC Shirakawa Institute of Animal Genetics Trinity College Dublin KARI-TRC Copyright Mike Enfield Livestock in heterogeneous environments There is extraordinary diversity in livestock (and crops) across Africa. This is TOTALLY different from the situation in the West. And reflects the ‘environment’ working on the genome. Therefore there is information in the simple occurrence of a given genotype in a given environment. Trypanosomiasis Is a fatal disease of livestock. The livestock equivalent of sleeping sickness in humans T. congolense, T. vivax T brucei rhodesiense T gambiense Studying the tolerant/susceptible phenotype has problems: • Separating cause from effect • Separating relevant from irrelevant. • Dominance of the ‘what is happening to this weeks trendy gene/protein/cytokine?’ approach. Contribution of 10 genes from Boran and N’Dama cattle to reduction in degree of trypanosomosis Boran (relatively susceptible) N’Dama (tolerant) 15 10 5 0 -5 -10 -15 15 10 5 0 -5 -10 -15 The N’Dama and Boran each contribute trypanotolerance alleles at 5 of the 10 most significant QTL, indicating that a synthetic breed could have even higher tolerance than the N’Dama. In mice, we mapped three genomic regions which determine survival time following T. congolense infection 0 D17Mit46 D17Mit16 D5Mit233 D17Mit7 40 D5Mit114 D5Mit24 D1Nds2 MMU17 D1Mit102 80 D1Mit113 MMU5 120cM D1Mit403 MMU1 PCA of Liver expression data PCA of Liver expression data Studying the tolerant/susceptible phenotype STILL has the same problems! • Separating cause from effect • Separating relevant from irrelevant. • Dominance of the ‘what is happening to this weeks trendy gene/protein/cytokine?’ approach. Analysis (Fisher et al, NAR 35 (16)p5625-5633) • What genes are differentially expressed genomewide? • What pathways are they members of? • What pathways involve genes in the QTL? • What pathways are in both lists ? • Prioritise the list by 'degree of change' • Look at the biology of each network Analysis • It is important to stress that we do NOT require (or even expect) QTG themselves to be differentially expressed. Cholesterol metabolism C57 lite vs C57 regular survival following Trypanosome challenge Patients in ICU under tight glycaemic control Total cholesterol (mmol/l) 3.4 Died Survived 3.2 3 2.8 2.6 2.4 2.2 2 0 2 4 6 ICU day 8 10 This is nothing to do with Trypanosomiasis - this is a general response. Total cholesterol (mmol/l) 3.4 Died Survived 3.2 3 2.8 2.6 2.4 2.2 2 0 2 4 6 ICU day 8 10 Some conclusions Overlaying QTL and expression data has been incredibly informative. (But don’t assume your QTG will be differentially expressed!) Expression analysis in cow and mouse has revealed some unexpected pathways and interactions. We have learned a lot about host response to trypanosomes, but also about: How to survive a tryps infection How to survive in an ICU in Northern England Fundamentals of genome regulation. It may be that much of biological variation will turn-out to result from differential use of a small number of very general networks. (Why are we surprised that QTL often (usually?) fall apart when moved onto a new genetic background?) If you do high quality science there will be high quality - but unpredictable - outcomes. Shirakawa Institute of Animal Genetics Trinity College Dublin KARI-TRC