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The genomic code for nucleosome positioning
DNA double helix
Nucleosomes
Chromosome
Felsenfeld & Groudine, Nature (2003)
DNA in nucleosomes is extremely sharply bent
Side view
Top view
(Space filling representation)
(Ribbon representation)
~80 bp per superhelical turn
Luger et al., Nature (1997)
The nucleosome positioning code
Nucleosomes like forming on this DNA sequence;
CCAGCACCACCTGTAACCAATACAATTTTAGAAGTACTTTCACTTTGTAACTGAGCTGTCATTTATATTGAATTTTCAAAAATTCTTACTTTTTTTTTGGATGGACGCA
A
Nucleosomes dislike forming on this DNA sequence;
ACTCTCCTCCGTGCGTCCTCGTCTTCACCGGTCGCGTTCCTGAAACGCAGATGTGCCTCCAATCGCACTGCTCCGAACAATAAAGATTCTACAATACTAGCTTTTATGGT
The nucleosome positioning code
Nucleosomes like forming on this DNA sequence;
CCAGCACCACCTGTAACCAATACAATTTTAGAAGTACTTTCACTTTGTAACTGAGCTGTCATTTATATTGAATTTTCAAAAATTCTTACTTTTTTTTTGGATGGACGCA
A
Access of proteins to target site is hindered
Nucleosomes dislike forming on this DNA sequence;
ACTCTCCTCCGTGCGTCCTCGTCTTCACCGGTCGCGTTCCTGAAACGCAGATGTGCCTCCAATCGCACTGCTCCGAACAATAAAGATTCTACAATACTAGCTTTTATGGT
The nucleosome positioning code
Nucleosomes like forming on this DNA sequence;
CCAGCACCACCTGTAACCAATACAATTTTAGAAGTACTTTCACTTTGTAACTGAGCTGTCATTTATATTGAATTTTCAAAAATTCTTACTTTTTTTTTGGATGGACGCA
A
Access of proteins to target site is hindered
Nucleosomes dislike forming on this DNA sequence;
ACTCTCCTCCGTGCGTCCTCGTCTTCACCGGTCGCGTTCCTGAAACGCAGATGTGCCTCCAATCGCACTGCTCCGAACAATAAAGATTCTACAATACTAGCTTTTATGGT
Easy access of proteins to target site in this region
Deciphering the nucleosome positioning code
•In vitro selection of nucleosome-favoring DNAs
•Isolation of natural nucleosome DNAs
GC
AA
TT
TA
AA
TT
TA
GC
GC
AA
TT
TA
AA
TT
TA
GC
C
G
AA
TT
TA
GC
AA
TT
TA
GC
AA
TT
TA
Physical selection for DNAs
that attract nucleosomes
Random sequence DNA synthesis
(1 each of 5 x 1012 different DNA sequences)
Make many copies by PCR
Equilibrium selection of highest affinity 10%
Extract DNA
Clone, sequence, analyze individuals
Lowary & Widom, 1998
Summary
•Differing DNA sequences exhibit a > 5,000-fold range of
affinities for nucleosome formation
Lowary & Widom, 1998
Thåström et al., 1999
Widom, 2001
Thåström et al., 2004
DNA sequence motifs that stabilize nucleosomes
and facilitate spontaneous sharp looping
GC
Thåström et al., 2004
Cloutier & Widom 2004
Segal et al., 2006
Isolation of natural nucleosome DNAs
Digest unwrapped DNA
Extract protected DNA
Clone, sequence, analyze individuals
AA/TT/TA (fraction)
Fraction
(AA/TT/TA)
The nucleosome signature in living yeast cells
0.34
0.31
0.28
0.25
0.22
0
20
40
60
80
100
120
140
Position on nucleosome (bp)
Position on nucleosome (bp)
• ~10 bp periodicity of AA/TT/TA
• Same period for GC, out of phase with AA/TT/TA
• Same signals from the in vitro nucleosome selection
• NO signal from randomly chosen genomic regions
Segal et al., 2006
Two alignments of nucleosome DNAs
0.4
Fraction AA/TT/TA
0.35
0.3
0.25
0.2
0.15
0
50
100
150
Position in nucleosome (bp)
Center alignment
Location mixture model alignment
Wang & Widom, 2005
The nucleosome signature
is common to yeast and chickens
AA/TT/TA (fraction)
0.36
0.32
0.28
Chicken + Yeast merge
0.24
0.2
0.16
0
20
40
AA/TT/TA (fraction)
0.32
60
80
100
120
140
Position on nucleosome (bp)
0.28
Chicken (in vivo)
0.24
0.2
0.16
0
20
40
AA/TT/TA (fraction)
0.34
60
80
100
120
140
Position on nucleosome (bp)
0.31
Yeast (in vivo)
0.28
0.25
0.22
0
20
40
60
80
100
Position on nucleosome (bp)
120
140
Segal et al., 2006
The nucleosome signature in vitro and in vivo
AA/TT/TA (fraction)
0.29
Mouse (in vitro)
0.24
0.19
0.14
-70
-50
-30
AA/TT/TA (fraction)
0.5
-10
10
30
50
70
Position on nucleosome (bp)
0.4
Random DNA (in vitro)
0.3
0.2
0.1
0
AA/TT/TA (fraction)
-70
-50
-30
-10
10
30
50
70
Position on nucleosome (bp)
0.35
Yeast (in vitro)
0.3
0.25
0.2
-70
-50
-30
AA/TT/TA (fraction)
-10
10
30
50
70
Position on nucleosome (bp)
0.32
0.28
Chicken (in vivo)
0.24
0.2
0.16
AA/TT/TA (fraction)
-70
-50
-30
-10
10
30
50
70
Position on nucleosome (bp)
0.34
0.31
Yeast (in vivo)
0.28
0.25
0.22
-70
-50
-30
-10
10
Position on nucleosome (bp)
30
50
70
Segal et al., 2006
In vitro experimental validation
of histone-DNA interaction model
• Adding key motifs increases nucleosome affinity
• Deleting motifs or disrupting their spacing decreases affinity
tc
g
c
c
t
gc
aa
C
g
a cc c t ta a a
c
g
cg
ta
c
t
a
AA
TT
TA
G
g
t
GC
GC
t
gcc a a g
acc
g
g
ta
g
tt
a
AA
TT
TA
AA
TT
TA
g
t
dyad
c
ct gtcc
cc
gc g
c
c
a
g
a
GC
AA
TT
TA
AA
TT
TA
c
GC
dyad
Segal et al., 2006
GC
AA
TT
TA
GC
AA
TT
TA
Summary
Differing DNA sequences exhibit a > 5,000-fold range of
affinities for nucleosome formation
We have a predictive understanding of the DNA sequence
motifs that are responsible
Sequences matching these motifs are abundant in eukaryotic
genomes, and are occupied by nucleosomes in vivo
Placing nucleosomes on the genome
Log likelihood
A free energy landscape, not just scores and a threshold !!
Genomic Location (bp)
•Nucleosomes occupy 147 bp and exclude 157 bp
Segal et al., 2006
Equilibrium configurations of nucleosomes
on the genome
• One of very many possible configurations
P(S PB(S)
)
P(S
)
PB(S)
P(S
)
PB(S)
P(S PB(S)
)
Chemical potential – apparent concentration
Probability of placing a nucleosome starting at each allowed basepair i of S
Probability of any nucleosome covering position i ( average occupancy)
Locations i with high probability for starting a nucleosome ( stable nucleosomes)
Segal et al., 2006
Reading the nucleosome code and
predicting the in vivo locations of nucleosomes
GAL10
Binding sites
for Gal4
activator protein
GAL1
147 bp
Segal et al., 2006
Summary
Differing DNA sequences exhibit a > 5,000-fold range of
affinities for nucleosome formation
We have a predictive understanding of the DNA sequence
motifs that are responsible
Sequences matching these motifs are abundant in eukaryotic
genomes, and are occupied by nucleosomes in vivo
A model based only on these DNA sequence motifs and
nucleosome-nucleosome exclusion explains ~50% of in
vivo nucleosome positions
0.88
Model
Permuted
0.87
0.86
0.85
0.84
0.83
-500
-250
0
250
500
750
1000
Distance from Coding Start (bp)
Semi-stable
nucleosomes
Fraction
Average Nucleosome Occupancy
Distinctive nucleosome occupancy adjacent
to TATA elements at yeast promoters
Stable
nucleosome
Semi-stable
nucleosomes
TATA Box
0.1
0.05
0
-500
-250
0
Segal et al., 2006
Predicted nucleosome organization near
5’ ends of genes – comparison to experiment
Segal et al., 2006
Fondufe-Mittendorf, Segal, & JW
Summary
Differing DNA sequences exhibit a > 5,000-fold range of
affinities for nucleosome formation
We have a predictive understanding of the DNA sequence
motifs that are responsible
Sequences matching these motifs are abundant in eukaryotic
genomes, and are occupied by nucleosomes in vivo
A model based only on these DNA sequence motifs and
nucleosome-nucleosome exclusion explains ~50% of in
vivo nucleosome positions
These intrinsically encoded nucleosome positions are
correlated with, and may facilitate, essential aspects of
chromosome structure and function
An elastic energy model for the sequence-dependent
cost of DNA wrapping
GC
Morozov, Fortney, Widom, & Siggia
DNA in nucleosomes is extremely sharply bent
Side view
Top view
(Space filling representation)
(Ribbon representation)
~80 bp per superhelical turn
Luger et al., Nature (1997)
An elastic energy model for the sequence-dependent
cost of DNA wrapping
GC
Morozov, Fortney, Widom, & Siggia
Elastic energy of dinucleotide step
1 6 6
E  E0   fij  iˆ  jˆ
2 i 1 j 1
•Knowledge-based harmonic potential
E0
= Energy at equilibrium conformation for step
fij = elastic constants impeding deformation; calculated
from dispersion of parameters in X-ray crystal
structures, assuming harmonic potential
i = i – i0,
= fluctuation of step parameter from equilibrium
Olson et al., (1998)
Elastic energy model for nucleosomal DNA
E = Eelastic + Edeviation from superhelix
Crystal structure
Ideal superhelix
Morozov, Fortney, Widom, & Siggia
A genomic code for higher order chromatin structure?
30 nm fiber
Felsenfeld & Groudine, 2003
Regular 3-d superstructures favor
~10 bp quantized linker DNA lengths
Widom, 1992
Stable nucleosomes come in correlated groups
Auto-correlations
(average occupancy)
1000
Stable nucleosomes (model)
245000
Correlation
Correlation
Frequency
Frequency
Pairwise distances histogram
(stable nucleosomes)
Stable nucleosomes (permuted)
100
10
1
240000
235000
230000
225000
220000
157
357
557
757
957
1157
Distance between centers of proximal nucleosomes (bp)
Center-center distance (bp)
-1000
-500
0
500
1000
Correlation offset (bp)
Correlation
offset (bp)
Segal et al., 2006
Fourier transforms in extended regions
Averaged for extended regions starting i = 11,…20
bp beyond end of mapped nuclesome:
Period with max amplitude = 10.2 bp
Phase offset at max period = 5 bp
Wang, Fondufe-Mittendorf, & Widom
Biochemical isolation of dinucleosomes
Digest
linker DNA
Isolate
dinucleosomes
Clone & sequence
Yao et al., 1990;
Fondufe-Mittendorf, Wang, & Widom
Linker lengths in purified dinucleosomes
Predict locations of the two nucleosomes
•Duration hidden Markov model: L’, N, L, N, L’’
L: Linker
N: Nucleosome
L’
N
L
N
L’’
L’, L’’: Partial linkers
Wang, Fondufe-Mittendorf, & Widom
The genomic code for nucleosome positioning
DNA
Nucleosomes
30 nm fiber
Felsenfeld & Groudine, 2003
Multiplexing
Layering two or more signals on top of each
other without cross-interference
•Multiple phone conversations in a single wire
or optical fiber
•Stereo broadcast on an FM channel
•Text message hidden in a picture, in a spy novel
How is multiplexing accomplished?
•Nucleosomes not evolved for highest affinity; many
ways to have suboptimal affinity over 147 bp length
•Protein coding sequences and gene regulatory
sequences are degenerate
•A remarkable feature of DNA mechanics
Evolution of the nucleosome positioning code
+ Nucleosomes
– nucleosomes
Sandman & Reeve,
Curr. Op. Microbiol. 2006
Acknowledgements
The genomic code for nucleosome positioning
Northwestern University
Yvonne Fondufe-Mittendorf
Irene Moore
Lingyi Chen
Karissa Fortney
Annchristine Thåström
Timothy Cloutier
Peggy Lowary
Jiping Wang (NU Statistics Dept.)
Weizmann Institute
Eran Segal
Yair Field
Rockefeller University
Eric Siggia
Alexandre Morozov
UCLA
Robijn Bruinsma
Joe Rudnick
David Schwab