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How to find genetic determinants of naturally
varying traits?
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Mapping a disease locus
Fig. 11.A
(Autosomal dom)phenotype (variation in locus 1)
marker genotype (variation in locus 2)
A1
A2
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Mapping a disease locus
Fig. 11.A
A1 D
A2 d
A1 d
A1 d
A2 d
A1
A2
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Mapping a disease locus
Fig. 11.A
A1 D
A2 d
A1 d
A1 d
A1 D
A1
A2
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Mapping a disease locus
Fig. 11.A
A1 d
A1 d
A2 D
A1 D
A2 d(sperm)
A1
A2
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LOD scores
Odds = P(pedigree | r)
P(pedigree | r = 0.5)
Odds = (1-r)n • rk
0.5(total # meioses)
r odds
0.1 12.244
0.2 10.737
0.3 6.325
0.4 2.867
0.5 1
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A computational search through many r values
observed RF is single best estimate, 1/8 = 0.125.
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A computational search through many r values
observed RF is single best estimate, 1/8 = 0.125.
But we already knew that. What’s the point?
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More realistic situation: in dad, phase of alleles unknown
A1 d
A1 d
A1 D
A2 d
A1
A2
or
A1 d
A2 D
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Dad phase unknown
Odds = 1/2[(1-r)n • rk]P(pedigree|r)
A1
A2
A1 D
A2 d
+ 1/2[(1-r)n • rk]
assume one phase for dad
7 non-recomb, 1 recomb
(k = # recomb, n = # non-recomb)
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Dad phase unknown
A1
A2
A1 d
A2 D
assume the other phase for dad
1 non-recomb, 7 recomb
Odds = 1/2[(1-r)n • rk] + 1/2[(1-r)n • rk]P(pedigree|r)
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Dad phase unknown
A1
A2
Odds = 1/2[(1-r)n • rk] + 1/2[(1-r)n • rk]
Odds = 1/2[(1-r)7 • r1] + 1/2[(1-r)1 • r7]
P(pedigree|r)
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Dad phase unknown
A1
A2
= 1/2•P(pedigree|r, phase 1) + 1/2•P(pedigree|r, phase 2)
0.5(total # meioses)
Odds = 1/2[(1-r)n • rk] + 1/2[(1-r)n • rk]odds ratio
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Dad phase unknown
A1
A2
0.5(total # meioses)
Odds = 1/2[(1-r)n • rk] + 1/2[(1-r)n • rk]odds ratio
Now there are two k’s, one for each phase.We could ask for observed r; would be 1/8 or 7/8.
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Dad phase unknown
A1
A2
0.5(total # meioses)
Odds = 1/2[(1-r)n • rk] + 1/2[(1-r)n • rk]odds ratio
Now there are two k’s, one for each phase.We could ask for observed r; would be 1/8 or 7/8.
What single r value best explains the data?
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Now you really need the computational search.
maximum likelihood r = 0.13
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maximum likelihood r = 0.13
between the observed r’s, 1/8 and 7/8.
Now you really need the computational search.
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Maximization method was invented to map mammalian
diseases in complex pedigrees.
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Cystic fibrosis mapping, 1985
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Cystic fibrosis mapping, 1985
What does this mean?
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Cystic fibrosis mapping, 1985
Paraoxonase activity
Ary
lest
eras
e ac
tivity
homozyg high
homozyg low
(Metabolizes insecticide)
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Cystic fibrosis mapping, 1985
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Cystic fibrosis mapping, 1985
(via somatic cell hybrid mapping)
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Cystic fibrosis mapping, 1985
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Cystic fibrosis mapping, 1985
Best model is r = 0: what does this mean?
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Cystic fibrosis mapping, 1985
Fig. 5A
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How did they get 27 kids?
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1,2 2,3
2,3 1,2 1,3
2,3 1,3
1,2 2,3
1,2 1,2 1,3
2,3 1,3
1,3 2,3
1,3 1,2 2,3
2,3 2,2 2,2
Combining families
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Given r
Odds1
Given r
Odds2
Given r
Odds3
1,2 2,3
2,3 1,2 1,3
2,3 1,3
1,2 2,3
1,2 1,2 1,3
2,3 1,3
1,3 2,3
1,3 1,2 2,3
2,3 2,2 2,2
Combining families
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How to get an overall estimate of probability of linkage?
A. Multiply odds togetherB. Add odds togetherC. Take the largest oddsD. Take the average odds
Given r
Odds1
Given r
Odds2
Given r
Odds3
1,2 2,3
2,3 1,2 1,3
2,3 1,3
1,2 2,3
1,2 1,2 1,3
2,3 1,3
1,3 2,3
1,3 1,2 2,3
2,3 2,2 2,2
Combining families
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How do you know which marker to test?
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Modern genetic scans
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Modern genetic scans
Fig. 11.17
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Modern genetic scans
Fig. 11.17
Genotype 1000’s of markers for each individual; test each marker at various r’s across all individuals
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Modern genetic scans
Fig. 11.17
Genotype 1000’s of markers for each individual; test each marker at various r’s across all individuals
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Modern genetic scans
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
(single family)
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Modern genetic scans
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
(single family)
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
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Modern genetic scans
What does the “max” in “max LOD score” refer to?A. The strongest-linking markerB. The most probable recombination fractionC. The most severe phenotype
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
(single family)
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Remember?
maximum likelihood r = 0.13
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Modern genetic scans
Max LOD score is the one from the best r value
r odds
0.1 12.244
0.2 10.737
0.3 6.325
0.4 2.867
0.5 1
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Modern genetic scans
What is the simplest explanation for so many tall black lines around Chr 13?
A. Multiple markers in the region, which makes LOD higherB. Multiple markers are all linked to a single disease
mutationC. Multiple mutations on Chr 13 cause the diseaseD. Higher LOD is counted by the number of linking markers
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
(single family)
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Modern genetic scans
What is the simplest explanation for so many tall black lines around Chr 13?
A. Multiple markers in the region, which makes LOD higherB. Multiple markers are all linked to a single disease
mutationC. Multiple mutations on Chr 13 cause the diseaseD. Higher LOD is counted by the number of linking markers
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
(single family)
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Modern genetic scans(22 families)
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Modern genetic scans
(Smooth curve = inferred genotype at positions between markers)
(22 families)
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Modern genetic scans Fit model twice
(22 families)
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But…(779 small families or sib pairs)
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Why would an experiment fail to observe linkage?
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Marker density matters
? Try to minimize genotyping cost.
But if the only marker you test is >50 cM away, will get no linkage.
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Number of families matters
If low number of patients, no statistical significance.
Tune in next lecture for more about this.
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Improper statistics
Can make noise look like a fabulously significant linkage peak.
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Locus heterogeneity
Fig. 3.16
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Locus heterogeneity
Fig. 3.16
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Age of onset in breast cancer
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Age of onset in breast cancerage of onset
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Age of onset in breast cancerage of onset
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Age of onset in breast cancerage of onset
Only early-onset families show linkage.Familial breast cancer is heterogeneous.
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A landmark: BRCA1
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Bring a coin and a calculator to next class.
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