Canine SNP Analysis
Matthew Kusner
Background
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
Samples
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Studying
Progressive Retinal
Atrophy (PRA)
–
8 affected & 2
unaffected Italian
Greyhounds
SNP Genotyping and
Errors
–
Allele-specific PCR
–
No call vs. allele
miscall
Background
•
SNP data
–
File conversion
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Ordered by
genomic position
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Genotype “codes”
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•
•
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0 = AA
1 = AB
2 = BB
-1 = unknown
Background
•
Disease Characteristics
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Autosomal Recessive
•
Increased likelihood of some loss of genomic
functionality
•
Disease loci near homozygous SNPs
•
Duplicate gene copies
•
Larger region = possibly more genes involved
•
Program
Nomenclature
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For a given SNP:
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•
•
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Consistent – All affected dogs homozygous for
one allele (A or B).
Inconsistent – All affected dogs consist of a
combination of both alleles (A and B).
Informative – All affected and unaffected dogs
consist of a combination of both alleles.
Uninformative – All affected and unaffected
dogs homozygous for one allele.
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•
Program
Seed Formation
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Run through data
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Form blocks of >= 5 consecutive consistent SNPs.
These are the seeds.
Expansion
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Forward (based on genomic position) seed expansion
if one of the cases apply:
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•
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Next SNP is consistent
Next SNP is inconsistent, yet an underrepresentation of inconsistent SNPs in block
Next SNP is inconsistent based on one allele
and an under-representation of such SNPs.
We'll call these “changed” SNPs.
Program
•
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Backward (based on genomic position) seed
expansion is the same.
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If block collision occurs, blocks combined.
Merge
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Blocks merged (equivalent to “combining”
blocks as above) if both cases apply:
•
•
An under-representation of inconsistent SNPs in
merged block.
An under-representation of changed SNPs in
merged block.
Program
•
Sort
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Blocks sorted first by size (based on earlier
reasoning) then by Consistent/Informative
product (for blocks of the same size). Blocks
are then outputted.