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Heritability in exptal organisms
Genetically identical
Genetically different
Heritability in exptal organisms
 e
t
Genetic variance = total var - “environmental var”
 g  =  t -  e 
Heritability H2 = g/t
http://www.sciam.com/media/inline/15DD5B0E-AB4123B8-2B1E53E8573428C5_1.jpg
http://www.twinsrealm.com/othrpics/twins16.jpg
http://www.twinsrealm.com/ot
hrpics/sarahandsandra.jpg
http://www.twinsinsurance.net/images/twins.jpg
Heritability in humans: MZ twins
Mean each pair = zi
Each individual = zij

2
(z
z)
ij

=  t2
Within pairs mean sq = 
T
2
(z
z
)
 ij i
= w2
Total mean sq =
N
Between pairs mean sq =  (zi - z)2
N-1
=  b2
h2 =
b2 w2
 t2
mRNA expression
Significance of heritability?
all
progeny
P1
P2
progeny,
marker
genotype
P1
progeny,
marker
genotype
P2
How to find genetic
determinants of naturally
varying traits?
Thus far, we have only found
linkage to a marker. The
causal variant is still unknown.
Mapping imprecision
wide
mapped
interval
Mapping imprecision
wide
mapped
interval
You should now know
from the first problem
set why the LOD score is
highest for markers
close to the causal
variant locus…
Mapping imprecision
wide
mapped
interval
But why not just look at
the single marker with
the best LOD score?
Single best locus isn’t the
answer
True distance 30 cM
Diseasecausing
mutation
Restriction
fragment
length
polymorphism
observed recombination
fraction = 1/8 = 12.5 cM
this is our observation
The observed number of
recombinants is just a
point estimate, with some
error associated.
True variant is “under” peak
Fig. 11.17
Submergence tolerance in rice
Variation in submergence
tolerance
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
http://www.a2mediagroup.com/data/images/news/categories/riceplant.jpg
Linkage mapping
me™ and a
ed) decompressor
see this picture.
intolerant
tolerant
Finding the causative variant
Finding the causative variant
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Finding the causative variant
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Transgenic test
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
http://www.plantsci.cam.ac.uk/Haseloff/SITEGRAPHICS/Agrotrans.GIF
Transgenic test
From Prof. Garriga
problem set
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
http://www.plantsci.cam.ac.uk/Haseloff/SITEGRAPHICS/Agrotrans.GIF
Transgenic test
QuickTime™ and a
Uncompressed) decompressor
needed to see this picture.
Time™ and a
ssed) decompressor
see this picture.
Transgenic test
Time™ and a
ssed) decompressor
see this picture.
Transgenic test
Only
expressed
upon
submergence
Time™ and a
ssed) decompressor
see this picture.
Transgenic test
Expressed
all the
time…
Now in a real crop strain
Swarna INTOL x IR49830 TOL
F1 x Swarna INTOL
Check for Sub1A+
Now in a real crop strain
Swarna INTOL x IR49830 TOL
F1 x Swarna INTOL
B1 x Swarna INTOL
Check for Sub1A+
Now in a real crop strain
Swarna INTOL x IR49830 TOL
F1 x Swarna INTOL
B1 x Swarna INTOL
B2 x Swarna INTOL
…
Now in a real crop strain
Swarna INTOL x IR49830 TOL
F1 x Swarna INTOL
B1 x Swarna INTOL
B2 x Swarna INTOL
…
Result: Sub1A in Swarna genome
Common in plant breeding
Wild:
resistant to
fungus
Cultivated:
bred for
yield, etc.
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
http://www.anbg.gov.au/cpbr/program/sc/barl_mole.htm
“Naturally genetically modified”
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Every linkage study faces this
problem
What is the causative
variant linked to the
marker?
How to formulate a guess?
How to formulate a guess?
Here a very obvious hypothesis.
Often not such a large gain or loss.
QuickTime™ and a
TIFF (Uncompressed) decompressor
Fine-mapping
Fig. 11.17
Fine-mapping: new markers
Fig. 11.17
Fine-mapping: new markers
Between two
humans, 1
polymorphism
every 1000 bp;
linkage study
probably started
with a tiny fraction
of total.
Fine-mapping: new markers
Position of true causal variant
A simulation of a
qualitative trait in a
large mouse cross;
sparse marker set
Best marker
Fine-mapping: new markers
Position of true causal variant
Peak looks pretty
close—why bother
improving resolution?
Best marker
Fine-mapping: new markers
Position of true causal variant
Because you have to
hunt through by hand to
find the causal gene, and
test experimentally. The
smaller the region, the
better.
Best marker
Fine-mapping: new markers
Position of true causal variant
Increased
marker
density
Fine-mapping: new markers
Position of true causal variant
Why did the LOD
score go up?
A.
B.
C.
D.
More markers increases
multiple testing, which
boosts LODs in the region.
Closer markers have more
significant linkage,
increasing their LODs.
Peak is narrower, so LODs
increase in the region.
The LOD score scales with
the number of markers, so
actually it isn’t different if
you normalize correctly.
What do functional (e.g.
disease-causing) variants look
like?
Rearrangements/large gain
and loss
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Rearrangements/large gain
and loss
Coding variants
Fig. 7.25
http://homepages.strath.ac.uk/~dfs99109/BB310/CFTRgene.jpg
Coding variants
Fig. 2B
http://homepages.strath.ac.uk/~dfs99109/BB310/CFTRgene.jpg
Coding variants
New amino acid
Fig. 2B
http://homepages.strath.ac.uk/~dfs99109/BB310/CFTRgene.jpg
Coding variants
Premature STOP
Fig. 2B
http://homepages.strath.ac.uk/~dfs99109/BB310/CFTRgene.jpg
Coding variants
Regulatory change, not coding!
Fig. 2B
http://graphics.jsonline.com/graphi
cs/badger/img/may02/5martin506.j
pg
Nucleotide repeat diseases
Fig. 11.13
http://geneticsmodules.duhs.duke.edu/Design/Print.asp
Nucleotide repeat diseases
Fig. 7A,B
Think about it: most identified
variants are rare alleles with
strong effect.
Most likely to be coding
changes.
Old school
Promoter variants
Fig. 9.22
Promoter variants
Fig. 9.22
Promoter mutations can cause misregulation and
disease/phenotype.
Promoter variants
DOC
Promoter variants
Subtle single-nucleotide
promoter variants probably
very common, but hard to find.
Stay tuned.
DOC