Presented by, Jeremy Logue

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.

The Nucleosome

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).

Dinucleotide Frequencies

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.

Validation of Nucleosome-DNA Interaction Model

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.

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

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.

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.

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.

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.

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.

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.