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Functional genomics to identify genes and networks influencing survival following Trypanosome challenge.

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Title: Functional genomics to identify genes and networks influencing survival following Trypanosome challenge.


1
Functional genomics to identify genes and
networks influencing survival following
Trypanosome challenge.
2
Shirakawa Institute of Animal Genetics
KARI-TRC
3
Origins of NDama and Boran cattle
Boran
NDama
4
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5
Mouse model
6
  • 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.

7
  • 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

8
Mapping trypanotolerance loci of the NDama
would allow the rapid introgression of desired
traits from other breeds into the NDama, while
retaining the trypanotolerance traits or the
rapid introgression of the trypanotolerance trait
from the NDama 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
9
Contribution of 10 genes from Boran and NDama
cattle to reduction in degree of trypanosomosis
Boran (susceptible)
NDama (tolerant)
The NDama 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
NDama.
10
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




11
  • 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.

12
Functional genomics technology allows us to look
at what genes respond to infectionAnd
especially what genes respond differently to
infection
13
Expression analysis of cow and mouse, resistant
and susceptible.
14
Expression studiesCow Ndama vs Boran time
course Ndama x Boran backcross Mouse C57
vs A/J Balb/c time course C57A/J
congenics Various mouse mutants (C57A/J BAC
transgenics)
15
Microarray design at each time point
Resistant C57BL/6
Susceptible AJ
16
Mouse time course. Liver.
17
Cholesterol metabolism
18
Endogenous cholesterol production increases after
infection
19
Total Cholesterol levels
20
Congenics
  • Lines fixed for alternative alleles of each QTL
    on a susceptible background.

21
Breeding congenic Mice carrying the
Trypanotolerance QTLs
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Cxcl1 - inflammatory response
29
Cattle Microarray Time Course Design
30
Cattle Microarray Time Course Design
31
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)

32
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)

33
Cattle Microarrays
Paraoxonase 3 Chr 4 Near Parasitaemia QTL??
34
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

35
Expression profiling of NDama-Boran backcross
cattle
36
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 clampingfrom normal ICU practice
minimises major confounders
Data cleaning, meta-data capture, analysis
37
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38
What to do with candidate genes
  • All the obvious things
  • Plus
  • Exploit the unique populations of cattle
  • Recently admixed resistant susceptible
  • Multiple resistant breeds
  • Multiple resistant species (sheep, goat, wildlife)

39
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40
Shirakawa Institute of Animal Genetics
KARI-TRC
41
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 401412
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