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The genomic code for nucleosome positioning

DNA double helix

Nucleosomes

ChromosomeFelsenfeld & Groudine, Nature (2003)

Luger et al., Nature (1997)

Side view(Space filling representation)

Top view(Ribbon representation)

DNA in nucleosomes is extremely sharply bent

~80 bp per superhelical turn

Nucleosomes dislike forming on this DNA sequence;

Nucleosomes like forming on this DNA sequence;CCAGCACCACCTGTAACCAATACAATTTTAGAAGTACTTTCACTTTGTAACTGAGCTGTCATTTATATTGAATTTTCAAAAATTCTTACTTTTTTTTTGGATGGACGCAA

The nucleosome positioning code

ACTCTCCTCCGTGCGTCCTCGTCTTCACCGGTCGCGTTCCTGAAACGCAGATGTGCCTCCAATCGCACTGCTCCGAACAATAAAGATTCTACAATACTAGCTTTTATGGT

Nucleosomes dislike forming on this DNA sequence;

Nucleosomes like forming on this DNA sequence;CCAGCACCACCTGTAACCAATACAATTTTAGAAGTACTTTCACTTTGTAACTGAGCTGTCATTTATATTGAATTTTCAAAAATTCTTACTTTTTTTTTGGATGGACGCAA

The nucleosome positioning code

CC

AA

TAccess of proteins to target site is hindered

ACTCTCCTCCGTGCGTCCTCGTCTTCACCGGTCGCGTTCCTGAAACGCAGATGTGCCTCCAATCGCACTGCTCCGAACAATAAAGATTCTACAATACTAGCTTTTATGGT

Nucleosomes dislike forming on this DNA sequence;ACTCTCCTCCGTGCGTCCTCGTCTTCACCGGTCGCGTTCCTGAAACGCAGATGTGCCTCCAATCGCACTGCTCCGAACAATAAAGATTCTACAATACTAGCTTTTATGGT

Nucleosomes like forming on this DNA sequence;CCAGCACCACCTGTAACCAATACAATTTTAGAAGTACTTTCACTTTGTAACTGAGCTGTCATTTATATTGAATTTTCAAAAATTCTTACTTTTTTTTTGGATGGACGCAA

The nucleosome positioning code

CC

AA

TAccess of proteins to target site is hindered

CCAAT

Easy access of proteins to target site in this region

GC

Deciphering the nucleosome positioning code

•In vitro selection of nucleosome-favoring DNAs

•Isolation of natural nucleosome DNAs

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

Physical selection for DNAsthat attract nucleosomes

Lowary & Widom, 1998

•Differing DNA sequences exhibit a > 5,000-fold range of affinities for nucleosome formation

Lowary & Widom, 1998Thåström et al., 1999Widom, 2001Thåström et al., 2004

Summary

AATTTA

AATTTA

AA

TTTA

AATTTA

AATT

TA

AA TT TA

AA

TT

TA

GC

GC

GC

GC

GC

GC

GC

DNA sequence motifs that stabilize nucleosomes and facilitate spontaneous sharp looping

Thåström et al., 2004Cloutier & Widom 2004Segal et al., 2006

Digest unwrapped DNA

Extract protected DNA

Isolation of natural nucleosome DNAs

Clone, sequence, analyze individuals

The nucleosome signature in living yeast cells

0.22

0.25

0.28

0.31

0.34

0 20 40 60 80 100 120 140

Position on nucleosome (bp)

AA/TT/TA (fraction)

Position on nucleosome (bp)

Fra

ctio

n(A

A/T

T/T

A)

• ~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

0.15

0.2

0.25

0.3

0.35

0.4

0 50 100 150

Position in nucleosome (bp)

Wang & Widom, 2005

Two alignments of nucleosome DNAs

Center alignment

Location mixture model alignment

The nucleosome signatureis common to yeast and chickens

Chicken (in vivo)

Yeast (in vivo)

0.16

0.2

0.24

0.28

0.32

0.36

0 20 40 60 80 100 120 140

Position on nucleosome (bp)

AA/TT/TA (fraction)

0.16

0.2

0.24

0.28

0.32

0 20 40 60 80 100 120 140

Position on nucleosome (bp)

AA/TT/TA (fraction)

0.22

0.25

0.28

0.31

0.34

0 20 40 60 80 100 120 140

Position on nucleosome (bp)

AA/TT/TA (fraction)

Chicken + Yeast merge

Segal et al., 2006

The nucleosome signature in vitro and in vivo

0.2

0.25

0.3

0.35

-70 -50 -30 -10 10 30 50 70

AA/TT/TA (fraction)

0.22

0.25

0.28

0.31

0.34

-70 -50 -30 -10 10 30 50 70

Position on nucleosome (bp)

AA/TT/TA (fraction)

0.16

0.2

0.24

0.28

0.32

-70 -50 -30 -10 10 30 50 70

AA/TT/TA (fraction)

0.14

0.19

0.24

0.29

-70 -50 -30 -10 10 30 50 70

AA/TT/TA (fraction)

0

0.1

0.2

0.3

0.4

0.5

-70 -50 -30 -10 10 30 50 70

AA/TT/TA (fraction)

Chicken (in vivo)

Yeast (in vivo)

Yeast (in vitro)

Mouse (in vitro)

Random DNA (in vitro)

Segal et al., 2006

dyad

c

In vitro experimental validationof histone-DNA interaction model

• Adding key motifs increases nucleosome affinity• Deleting motifs or disrupting their spacing decreases affinity

dyad

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

Log

likel

ihoo

d

Genomic Location (bp)

Placing nucleosomes on the genome

A free energy landscape, not just scores and a threshold !!

•Nucleosomes occupy 147 bp and exclude 157 bp

Segal et al., 2006

• One of very many possible configurations

P(S)

PB(S) P(S)

P(S)

P(S)

PB(S) PB(S) PB(S)

Chemical potential – apparent concentration

Equilibrium configurations of nucleosomeson the genome

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 andpredicting the in vivo locations of nucleosomes

GAL10 GAL1Binding sites

for Gal4activator protein

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

Distinctive nucleosome occupancy adjacent to TATA elements at yeast promoters

0.83

0.84

0.85

0.86

0.87

0.88

-500 -250 0 250 500 750 1000

Distance from Coding Start (bp)

Average Nucleosome Occupancy

Stable nucleosome

Semi-stable nucleosomes

Semi-stable nucleosomes

Permuted Model

0

0.05

0.1

-500 -250 0

Fraction

TATA Box

Segal et al., 2006

Segal et al., 2006Fondufe-Mittendorf, Segal, & JW

Predicted nucleosome organization near5’ ends of genes – comparison to experiment

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

AATT

TA

AATTTA

AA

TTTA

AATT

TA

AATT

TA

AA TT TA

AA

TT

TA

GC

GC

GC

GC

GC

GC

GC

Morozov, Fortney, Widom, & Siggia

Luger et al., Nature (1997)

Side view(Space filling representation)

Top view(Ribbon representation)

DNA in nucleosomes is extremely sharply bent

~80 bp per superhelical turn

An elastic energy model for the sequence-dependent cost of DNA wrapping

AATT

TA

AATTTA

AA

TTTA

AATT

TA

AATT

TA

AA TT TA

AA

TT

TA

GC

GC

GC

GC

GC

GC

GC

Morozov, Fortney, Widom, & Siggia

E = E0 +1

2fij Δθ ˆ

i j =1

6

∑i =1

6

∑ Δθ ˆ j

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 of dinucleotide step

•Knowledge-based harmonic potential

E = Eelastic + Edeviation from superhelix

Elastic energy model for nucleosomal DNA

Ideal superhelixCrystal structure

Morozov, Fortney, Widom, & Siggia

Felsenfeld & Groudine, 2003

A genomic code for higher order chromatin structure?

30 nm fiber

Widom, 1992

Regular 3-d superstructures favor~10 bp quantized linker DNA lengths

Stable nucleosomes come in correlated groups

Segal et al., 2006

Pairwise distances histogram

(stable nucleosomes)

Auto-correlations(average

occupancy)Stable nucleosomes (model)

Stable nucleosomes (permuted)

1

10

100

1000

157 357 557 757 957 1157

Distance between centers of proximal nucleosomes (bp)

Frequency

220000

225000

230000

235000

240000

245000

-1000 -500 0 500 1000

Correlation offset (bp)

Correlation

Correlation offset (bp)C

orr

ela

tion

Fre

que

ncy

Center-center distance (bp)

Wang, Fondufe-Mittendorf, & Widom

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

Yao et al., 1990;Fondufe-Mittendorf, Wang, & Widom

Clone & sequence

Digestlinker DNA

Isolatedinucleosomes

Biochemical isolation of dinucleosomes

Linker lengths in purified dinucleosomes

Predict locations of the two nucleosomes

•Duration hidden Markov model: L’, N, L, N, L’’

LNL’ L’’N

N: Nucleosome

L: Linker

L’, L’’: Partial linkers

Wang, Fondufe-Mittendorf, & Widom

Felsenfeld & Groudine, 2003

The genomic code for nucleosome positioning

DNA

Nucleosomes

30 nm fiber

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

Sandman & Reeve,Curr. Op. Microbiol. 2006

+ Nucleosomes– nucleosomes

Acknowledgements

The genomic code for nucleosome positioning

Northwestern University

Yvonne Fondufe-MittendorfIrene MooreLingyi Chen

Karissa FortneyAnnchristine Thåström

Timothy CloutierPeggy Lowary

Jiping Wang (NU Statistics Dept.)

Weizmann Institute

Eran SegalYair Field

Rockefeller University

Eric SiggiaAlexandre Morozov

UCLA

Robijn BruinsmaJoe Rudnick

David Schwab

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