Office hours 3-4pm Wednesdays 304A Stanley Hall

Office hours3-4pm Wednesdays304A Stanley Hall

Simulation/theory

Expect 0.09 of a locus to reach LOD=3 by chance.

Not 1-locus dominant, or 1-locus incomplete dominance, or…

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

SWR parentC3H parent

(F2’s)

Doesn’t look like this…

Quantitative trait linkage test



(F2’s)

Not counting recombinants.Statistical test for goodness of fit.

>1 locus controlling trait



(One mouse family)

Just reporting significance of goodness of fit.QuickTime™ and a

TIFF (Uncompressed) decompressorare needed to see this picture.

What if…

C3Hparent

F2’s, C/C atmarker

F2’s, C/S atmarker

F2’s, S/S at

marker

SWRparent

Magnitude of spread within group has not changed.Locus effect is weaker.

Correct interpretation:

C3Hparent



F2’s, S/S at

marker

SWRparent

Difference between S and C at this locus has a causal role in blood pressure variation, but effect is modest.


C3Hparent



F2’s, S/S at

marker

SWRparent

Difference between S and C at this locus has a causal role in blood pressure variation, but effect is modest.

“Effect of having an S allele”


C3Hparent



F2’s, S/S at

marker

SWRparent

Most loci underlying human disease look like this.

“Effect of having an S allele”

Complex traits(one family, mouse model)


Just reporting significance of goodness of fit.QuickTime™ and a

TIFF (Uncompressed) decompressorare needed to see this picture.

Complex traitsGenetic differences at both loci affect the trait

(one family, mouse model)

Complex traitsEach locus responsible for half?


Complex traitsEach locus responsible for half? Depends on the model.




Each locus responsible for a third?

Complex traits

If 5 loci, each responsible for a fifth? 10 loci? …

The more loci, the smaller the effects and the harder to detect.

Complex traits

Genetic complexity is the rule; simple 1- or 2-locus models are the exception

One common result of a linkage study is no significant linkage anywhere.

We haven’t talked about humans lately…

With model organisms, can always study a single cross/family with lots of progeny, so better statistical power to detect weak loci.

And less chance of locus heterogeneity.

Distributions

x

N

= mean

Distributions

Genetically identical

Genetically different

Heritability in exptal organisms



Which population has the bigger variance?A. RedB. Green




Why is the green curve taller?A. There are more mice in the green populationB. More mice in the green population have high blood pressureC. Fewer differences between mice in the green populationD. Less environmental error/noise in the green population




Why is the green curve taller?A. There are more mice in the green populationB. More mice in the green population have high blood pressureC. Fewer differences between mice in the green populationD. Less environmental error/noise in the green population

(each curve adds to 100%)


Green = genetically identical, red = genetically different

Trait 1 Trait 2


(blood pressure) (blood cholesterol)


Trait 1 Trait 2

Which trait is more likely to be controlled by polymorphisms between the mice in the red population?

A. Trait 1B. Trait 2



Genetic variance = total var - “environmental var”

e

t

g = t

- e



“How much of the trait difference between genetically different individuals is due to polymorphisms?”

e

t

g = t

- e



Heritability H2 =

e

t

g = t

- e

g/t


Trait 1 Trait 2

Which trait has a higher heritability?A. Trait 1B. Trait 2


Fig. 21.13

???

What is (the square of) this quantity?A. Environmental varianceB. Total varianceC. Genetic varianceD. Population variance

Why h2?

“Are DNA differences controlling my trait?”

Otherwise, why bother with genetic mapping?

Heritability in humans: MZ twins

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Mean over all = z


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Mean each pair = zi


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Each individual = zij

Mean each pair = zi


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Mean each pair = zi

Total mean sq = (zij - z)2

T


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Mean each pair = zi


T

Within pairs mean sq = (zij - zi)2

N


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Mean each pair = zi

“Environment” alone


T


N


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Mean each pair = zi

Between pairs mean sq = (zi - z)2

N-1


T


N


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Mean each pair = zi

“Environment” and genetics


N-1


T


N


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Mean each pair = zi


N-1

= b2 = g

2 + e2


T


N


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Mean each pair = zi

NBetween pairs mean sq = (zi - z)2

N-1


T

Within pairs mean sq = (zij - zi)2 = w2

= b2


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Mean each pair = zi


N-1


T

Within pairs mean sq = (zij - zi)2 = w2

= t2

= b2

Analysis of variance (ANOVA)

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Mean each pair = zi


N-1

= w2

= t2 =b

2 + w2Total mean sq = (zij - z)2

T


= b2


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T

Mean each pair = zi


NBetween pairs mean sq = (zi - z)2

N-1

= b2

= w2

= t2 h2 =

b2w

2

t2


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h2 = b

2w2

t2

The fraction of the total variance that is attributable to differences between pairs (i.e. is genetic).

Another approach: MZ and DZ

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N

= w2


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N

= w2

h2 = w2(DZ)w

2 (MZ)]


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N

= w2

h2 = w2(DZ)w

2 (MZ)]

environment only


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N

= w2

h2 = w2(DZ)w

2 (MZ)]

Genetic + environment


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N

= w2

h2 = w2(DZ)w

2 (MZ)]

DZ twins are half as dissimilar as two unrelated people

Heritability in humans: MZ and DZ

Heritability in humans: MZ and DZ

(A more sophisticated model-fitting

method)

Adoptee studies

Biological parent # in sample% adopted sons

alcoholic

Alcoholic mother 89 39.4

Alcoholic father 42 28.6

Non-alcoholic mother 723 13.6

Non-alcoholic father 1029 15.5

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2004

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/abs

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RE

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Y=

1&S

RE

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Y=

0

Rates of alcoholism in adopted males

A qualitative argument for genetic contribution

Documents

Office hours 3-4pm Wednesdays 304A Stanley Hall