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Trinity College Dublin

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

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Trinity College Dublin

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

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

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

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

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

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

  7. 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.

  8. 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

  9. M. Soller and J.S. Beckmann, FAO Consultation Report, March 1987 ‘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’ CCER June 2002

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

  11. 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 D1Mit403 MMU5 MMU1 120cM

  12. 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.

  13. Functional genomics technology allows us to look at what genes respond to infectionAnd especially what genes respond differently to infection

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

  15. Expression studiesCow 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)

  16. Cattle Microarray Time Course Design

  17. Cattle Microarray Time Course Design

  18. PCA Liver day 0. 1st component tissue, this is 2nd 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)

  19. And the same data for spleen. The biggest effect we see (after tissue) is breed. 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)

  20. 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

  21. Paraoxonase 3 Chr 4 Near Parasitaemia QTL??

  22. 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

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

  24. Mouse time course. Liver.

  25. Cholesterol metabolism

  26. Endogenous cholesterol production increases after infection

  27. Total Cholesterol levels

  28. 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

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

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

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

  32. 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)

  33. 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)

  34. Some conclusions

  35. 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.

  36. 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.

  37. 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.).

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

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

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