1. Presented by,
Jeremy Logue

2. Big Question
How does DNA sequence contribute to nucleosome positioning?
And can we predict these positions by analysing DNA sequence?
Segal et al. attempt to predict the positions of all the nucleosomes in a
genome, based soley on DNA sequence.
Gene activity could then be dictated by a nucleosome code (i.e. masking
and exposing gene promoters).
Two decades ago, Satchwell et al. demonstrated significant periodicities
of dinucleotides and that DNA bending or flexibility helps in determining
nucleosome position.

3. The Nucleosome

4. Probabilistic Nucleosome-DNA Interaction Model
Sequences aligned and reverse
complements about their centers,
a dinucleotide distribution was
generated at each position.
Conditional probabilities for
dinucleotides generated according
to a hidden Markov model.
Thermodynamic model accounts
for steric hinderance between
nucleosomes (weighted conditional
probabilities).

5. Dinucleotide Frequencies

6. Periodic AA/TT/TA Dinucleotides
~10 bp periodic repeats of AA/TT/TA
that oscillate in phase.
GC repeats oscillate out of phase
with AA/TT/TA repeats.
As expected, sequence motifs that
recur periodically at helical repeat
known to facillitate DNA bending.
Confirmed by in vitro selection
experiments and by alignments of
randomly selected DNA.

7. Validation of Nucleosome-DNA Interaction Model

8. Key Dinucleotides Inferred from Alignments
Backbone inward
Backbone out
Intergenic and coding regions in yeast genome contain many more high affinity DNA sequences than expected by chance.
Scores seperated by 10 bp are strongly correlated.

9. Predicted vs Experimentally Identified Nucleosome Positions
GAL1-10 and CHA1 locus
54% of of predicted stable
nucleosomes within 35 bp
of literature reported
positions.
Predictions match stereo-
typed chromatin
organization at Pol II
promoters.
Orange ovals: lit reported, Black trace: probability of nucleosome starting at indicated base pair, Blue ovals: high probability, Light blue trace: average occupancy, Red and blue bars: protein-coding regions, Green ovals: conserved and bound DNA-binding sites

10. Experimentally Measured Nucleosome Occupancy
GAL1-10 and PHO5 promoters
~60% of predicted high occupancy
sites confirmed in vivo.
In 10 out of 11 cases, predicted
regions had higher occupancy
than sites 73 bp (one-half the
length of a nucleosome) away.
~50% of in vivo of nucleosome
organization can be explained by
sequence.
Rest are unstable.

11. In Vitro Selected Nucleosomes Nucleosomes Form Arrays
Individual nucleosomes are
organized into higher order arrays.
Significant correlations over six
adjacent nucleosomes.
Repeat length of 177 bp.
In vitro selection by salt dialysis.
Yeast genomic DNA.
Intergenic regions are enriched.

12. Occupancy Across Different Chromosomal Regions
Highest predicted occupancy
over centromeres (encodes
enhanced stability).
Unstable nucleosomes over
highly expressed genes.
Model does not account for
depleted genes, like ribosomal
proteins.

13. Functional Genes are Depleted of Nucleosomes
17 factors have significantly lower occupancy
at functional sites compared to non-functional
sites.
1 factor has significantly higher nucleosome
occupancy at non-functional sites compared
with functional sites.

14. TATA Elements are Placed Outside of Stable Nucleosomes
TATA elements lie just outside stably
occupied nucleosomes.
Positions conserved among all fungal
species.
May indicate that eukaryotic genomes
direct the transcriptional machinery to
functional sites by encoding unstable
nucleosomes over these elements.

15. Conclusions
Nucleosome organization is encoded ~50% by genome sequence.
And this is conserved across species.
Genomes encode the positioning and stability of nucleosomes in regions
that are critical for gene regulation and for other specific chromosome
functions.
Confirms work of Satchwell et al. where significant periodicities of
dinucleotides that favor DNA bending or flexibility where observed
and helps in determining nucleosome position.
May help explain how a transcription factor picks out relevant binding sites.
Approach still has many limitations, new models should account for favorable
nucleosome-nucleosome interactions and steric hinderance constraints
implied by the three-dimensional nucleosome structure.
Model does not account for competition between DNA binding proteins and
nucleosomes.