Fine mapping QTLs using Recombinant-Inbred HS and In-Vitro HS

1
Fine mapping QTLs using Recombinant-Inbred HS
and In-Vitro HS

• William Valdar
• Jonathan Flint, Richard Mott
• Wellcome Trust Centre for Human Genetics

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Heterogeneous Stocks
8 inbred lines
Pseudo-random mating for N generations
typical chromosome pair
eg, N30 3.4cM (100/30) average
distance between recombinants
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Cost of mapping with HS

• Need to genotype markers at very high density
  (sub centimorgan)
• Expensive to genotype whole genome (eg 3000
  markers for 30 generation HS)
• How can we reduce genotyping cost ?
• Use multiple phenotypes (value for money)
• Two genetic strategies
• RIHS Recombinant Inbred Heterogeneous Stock
• IVHS In vitro Heterogeneous Stock

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Recombinant Inbred HS (RIHS)
X
20 generations
HS
HS
RIHS
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Recombinant Inbred HS (RIHS)

• Genotype each RIHS line once
• Keep stock, eg, as embryos
• Distribute RIHS lines to labs for phenotyping

X
20 generations
HS
HS
RIHS
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Recombinant Inbred HS (RIHS)

• Genotype each RIHS line once
• Keep stock, eg, as embryos
• Distribute RIHS lines to labs for phenotyping

X
20 generations
HS
HS
RIHS
Advantage over standard RI resolution Advantage
over standard HS cost
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RIHS for mapping modifier QTL
X
X
20 generations
HS
HS
RIHS
inbred
F1
(may contain knockout or transgene)
modifier search
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• How many RIHS do we need for effective
  fine-mapping?
• Are there other HS strategies to reduce
  genotyping?

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In Vitro HS (IVHS)
meiosis
Fertilize inbred dam with HS sperm
IVF
recombinant
F1
HS sperm
HS donor
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IVHS-1
meiosis
IVF
recombinant
genotype donors at high resolution
F1
HS sperm
HS donor
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IVHS-1
meiosis
IVF
recombinant
pass 1
pass 2
genotype donors at high resolution
F1
HS sperm
HS donor
F1 markers
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IVHS-2
meiosis
IVF
no further genotyping
recombinant
genotype donors at high resolution
F1
HS sperm
HS donor
treat as average of donor chromosomes
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Simulations

• Compare strategies RIHS, IVHS-1, IVHS-2 by
  simulation

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Simulations

• Compare strategies RIHS, IVHS-1, IVHS-2 by
  simulation
• Simulate 25cM chromosome with single additive QTL
  placed randomly

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Simulations

• Compare strategies RIHS, IVHS-1, IVHS-2 by
  simulation
• Simulate 25cM chromosome with single additive QTL
  placed randomly
• Type 100 SNP markers

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Simulations

• Compare strategies RIHS, IVHS-1, IVHS-2 by
  simulation
• Simulate 25cM chromosome with single additive QTL
  placed randomly
• Type 100 SNP markers
• 30 generation HS

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Simulations

• Compare strategies RIHS, IVHS-1, IVHS-2 by
  simulation
• Simulate 25cM chromosome with single additive QTL
  placed randomly
• Type 100 SNP markers
• 30 generation HS
• Vary
• QTL effect size (1 to 50)
• RIHS lines used (40, 80, 120)
• Sample size (400 to 2000 total number of pups)

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Simulations

• Compare strategies RIHS, IVHS-1, IVHS-2 by
  simulation
• Simulate 25cM chromosome with single additive QTL
  placed randomly
• Type 100 SNP markers
• 30 generation HS
• Vary
• QTL effect size (1 to 50)
• RIHS lines used (40, 80, 120)
• Sample size (400 to 2000 total number of pups)
• Also investigate for IVHS-1
• Marker density
• SNPs v Microsatellites
• HS generations

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Evaluating the simulations

• Evaluation
• Perform 1000 simulations per condition
• Analysis performed with HAPPY
• Probability of detecting a QTL (must be a marker
  interval with adjusted HAPPY Pvalue lt 1)
• Mapping accuracy

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Detecting a significant locus

• Pass rate times most significant marker
  interval has (corrected) P-value less than 0.01

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Detecting a significant locus

• Pass rate times most significant marker
  interval has a corrected P-value less than 0.01

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Mapping accuracy for significant loci

• Mean mapping error average distance between
  true QTL and the predicted locus

mapping error (cM)
predicted QTL
true QTL
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Mapping accuracy for significant loci

• Mean mapping error average distance between
  true QTL and the predicted locus

mapping error (cM)
predicted QTL
true QTL
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Varying marker density and marker type

• IVHS-1 strategy with 5QTL, 1200 pups
• Vary number of markers over a 3cM region

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Varying marker density and marker type

• IVHS-1 strategy with 5QTL, 1200 pups
• Vary number of markers over a 3cM region

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Varying number of HS generations

• IVHS-1 strategy with 5QTL, 1200 pups

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Varying number of HS generations

• IVHS-1 strategy with 5QTL, 1200 pups

optimum 5,15
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Conclusions

• RIHS and IVHS strategies low genotyping cost
  without sacrificing mapping resolution
• IVHS is short term mapping strategy
• RIHS takes longer, costs more but is long term
  strategy of choice.
• 100 RIHS lines is sufficient for mapping isolated
  additive QTLs but may not be enough for
• multiple QTLs
• identifying epistatic effects
• Suitable HS need only 15 generations
• Paper submitted to Mammalian Genome (preprints
  available)