Whole-genome evaluation of complex traits using SNP, haplotype, or QTL information
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Transcript of Whole-genome evaluation of complex traits using SNP, haplotype, or QTL information
Whole-genome evaluation of complex traits using SNP, haplotype, or QTL
information
Gorjanc G. & Hickey J. M.
Genetika 2012, Maribor, Slovenia
Introduction
• Whole-genome technologies rich data
• In complex traits (e.g., body height, weight, …) gene discovery still very limited
• Rich genome-wide data can be used for prediction (classicaly based on phenotype and pedigree data)
• AIM: Show the value of different types of information for prediction in complex traits
Different sources of information (simplistic scheme)
k-1 k k+1 k+2 k+3 k+4 k+5 k+6
… C C T A G A … … G G A T C T … … C C T A G A … … G G A T C T …
… C C T A G A … … G G A T C T … … C T C A G A … … G A G T C T …
… C T C A T A … … G A G T A T … … C T C A T A … … G A G T A T …
+0 cm
+1 cm
+2 cm
QTL SNP SNP
Haplotypes
Methods - Idea
Methods - Simulation
AGV
Methods – Simulated data
1
Genotype
Pedigree
Phenotype
Genotype
2
3
4
5
6
7
8
9
10
Genotype
Genotype
Validation Calibration Gen.
Methods – Statistical analysis
GWAS vs. relationship modelling
• GWAS
• Relationships use the same underlying information (phenotype and genotype data) to infer the sum of all GWAS estimates
Haplotype similarity
• Long haplotypes „explosion“ in #haplotypes
• But parts of haplotypes are similar efective number of haplotypes is smaller
• Similarities (several variations tested)
k-1 k k+1 k+2 k+3 k+4 k+5 k+6
… C C T A G A … … G G A T C T … … C T C A G A … … G A G T C T … … C T C A T A … … G A G T A T …
Haplotype 1 Haplotype 2 Haplotype 3
Haplotype 1 6/6 4/6 3/6
Haplotype 2 6/6 5/6
Haplotype 3 6/6
Results – Gaussian QTL
QTL Pedigree SNP V SNP Y
Haplotypes – no similarity
Haplotypes – similarity 1 Haplotypes – similarity 2
QTL
Results – Gamma QTL
QTL Pedigree SNP V SNP Y
Haplotypes – no similarity
Haplotypes – similarity 1 Haplotypes – similarity 2
QTL
Conclusions
• Genome-wide information increases accuracy in comparison to classic methods using pedigrees and phenotypes only
• Long haplotypes large #haplotypes – low accuracies
– similarities help
– no advantage over SNP data (perhaps due to large #haplotypes)
• Accuracies drop in further generations (not so much with Gamma QTL data)
can not predict distant relatives or unrelated individuals accurately!!!
• Even with QTL data accuracies are not perfect!!!
Whole-genome evaluation of complex traits using SNP, haplotype, or QTL
information
Gorjanc G. & Hickey J. M.
Genetika 2012, Maribor, Slovenia