1. Trinity College Dublin KARI-TRC Shirakawa Institute of Animal Genetics Functional genomics to explore host response to trypanosome infection in particular and stress in general.

2. Trinity College Dublin KARI-TRC Shirakawa Institute of Animal Genetics

3. Trypanosomosis Is a fatal disease of livestock. The livestock equivalent of sleeping sickness in humans T. congolense, T. vivax T brucei rhodesiense T gambiense

4. Role of livestock - (should we all be vegetarians?) Ghibe valley, Ethiopia

7. Cattle Tsetse Cattle and tsetse Origins of N’Dama and Boran cattle N’Dama Boran

8. N’Dama Boran % change in PCV days after infection

9. 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.

10. Studying tolerance susceptibility any way has problems: We have no idea of the mechanisms We have no idea of effector tissue We have no in vitro model

11. ‘ Mapping trypanotolerance loci of the N’Dama would allow the rapid introgression of desired traits from other breeds into the N’Dama, while retaining the trypanotolerance traits; or the rapid introgression of the trypanotolerance trait from the N’Dama to other breeds. Mapping of trypanotolerance loci would also be the first step in their eventual cloning and manipulation through genetic engineering techniques’ M. Soller and J.S. Beckmann, FAO Consultation Report, March 1987 CCER June 2002

12. Contribution of 10 genes from Boranand N’Dama cattle to reduction in degree of trypanosomosis Boran (relatively susceptible) 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. N’Dama (tolerant)

14. MMU1 MMU17 MMU5 D17Mit16 D17Mit46 D17Mit7 D5Mit233 D5Mit24 D5Mit114 D1Mit102 D1Mit403 D1Nds2 D1Mit113 0 120cM 80 40 In mice, we mapped three genomic regions which determine survival time following T. congolense infection

15. What are these genes ? How do they affect survival ? What response pathways are common to mouse/cow/human ? What does that tell us about how to survive trypanosome challenge ? The mapping data gives us a point of attack for a functional approach.

16. Functional genomics technology allows us to look at what genes respond to infection And especially what genes respond differently to infection

17. Expression analysis of cow and mouse, resistant and susceptible.

18. Expression studies Cow N’dama vs Boran time course N’dama x Boran backcross Mouse C57 vs A/J & Balb/c time course C57*A/J congenics Various mouse mutants (C57*A/J BAC transgenics)

19. Cattle Microarray Time Course Design

21. Principle components analysis of data from genome-wide expression analysis comparing gene expression in liver of Ndama (red) vs Boran (blue) in response to infection with T. congolense. Light colour day 29 post infection, dark day 32 post infection. Components 1 and 2. (Components 3 and 4 separate by day post infection) PCA Liver day 0. 1st component tissue, this is 2nd

22. Principle components analysis of data from genome-wide expression analysis comparing gene expression in spleen of Ndama (red) vs Boran (blue) in response to infection with T. congolense. Light colour day 29 post infection, dark day 32 post infection. Components 1 and 2. (Components 3 and 4 separate by day post infection) And the same data for spleen. The biggest effect we see (after tissue) is breed.

23. Analysis 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

24. Paraoxonase 3 Chr 4 Near Parasitaemia QTL??

25. Paraoxonase 3 (PON3) PON1 knockout mice are more susceptible to T. congolense PON3 is a 40-kDa protein associated with the high density lipoprotein fraction of serum PON3 rapidly hydrolyzes lactones such as statin prodrugs (e.g. lovastatin) PON3 is more efficient than rabbit PON1 in protecting low density lipoprotein from copper-induced oxidation

26. Microarray design at each time point Resistant C57BL/6Susceptible AJ

28. Mouse time course. Liver.

29. Cholesterol metabolism

30. Endogenous cholesterol production increases after infection

31. Total Cholesterol levels

32. African cows to Salford ICU High cholesterol in African cattle identified as a protective factor against death from trypanosomiasis Is high cholesterol a protective factor in humans undergoing extreme inflammation? ICU data and physicians in Salford ‘lab’ accessible, plus heamoglobin, creatinine and glucose ‘clamping’ from normal ICU practice minimises major confounders Data cleaning, meta-data capture, analysis

34. Congenics Lines fixed for alternative ‘alleles’ of each QTL on a susceptible background.

35. Genotype males and mate carriers to female A/J Genotype males and select individuals carrying donor Tir haplotypes on Chr 1, 5 or 17. Genotype males, select individuals with the shortest donor flanks Genotype, select carriers and intercross Genotype all progeny, select homozygotes fixed for alternative haplotypes and expand Cross susceptible recipient (A/J) with Resistant (C57BL/6) donor F1 BC1 BC4 A/JC57BL/6  TirnBC6 TirnBC7 TirnAATirnCC A/J  Breeding congenic Mice carrying the Trypanotolerance QTLs

38. A/J sequence C57 number of differentially expressed genes in C57 v A/J (green) number of differentially expressed genes in Tir1AA v Tir1CC (black, *>0.99) Cxcl1 - inflammatory response. Tir 2!

39. A/J v C57: expression differences (fold change >0.5, P <0.01) sequence differences (number of informative SNPs in the 1Kb upstream of each probed gene) across the C57 and A/J genomes. (summed in 50 probe bins)

40. What to do with candidate genes All the obvious things Plus Exploit the unique populations (and high density SNP panels) of cattle –‘Recently’ admixed resistant * susceptible –Multiple resistant breeds –Multiple resistant species (sheep, goat, wildlife)

41. Some conclusions

42. Expression analysis in cow and mouse has revealed some unexpected pathways and interactions. ( Survival seems to be about the innate immune response and managing cholesterol) Overlaying QTL and expression data has been incredibly informative. 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 Salford Fundamentals of genome regulation. If you do high quality science there will be high quality - but unpredictable - outcomes.

43. Expression analysis in cow and mouse has revealed some unexpected pathways and interactions. ( Survival seems to be about the innate immune response and managing cholesterol) Overlaying QTL and expression data has been incredibly informative. 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 Salford Fundamentals of genome regulation. If you do high quality science there will be high quality - but unpredictable - outcomes. How to analyse this type of data and extract ‘important’ differences.

44. Overlaying multiple species has been extremely valuable. There is a clear synergy to be won and additional livestock species would be extremely valuable for a range of traits…… (the international sheep consortium needs to develop genetics and genomics resources - draft / skim genome sequence, dense coverage SNP panels etc.).

46. Trinity College Dublin KARI-TRC Shirakawa Institute of Animal Genetics

47. Intersection of Cholesterol and Inflammatory pathways Dunn et al Journal of Experimental Medicine Vol. 203, No. 2, February 20, 2006 401–412 Th2 bias Suppression of cholesterol synthesis