Fuzziness and noise in nucleosomal architecture

Abstract

Nucleosome organization plays a key role in the regulation of gene expression. However, despite the striking advances in the accuracy of nucleosome maps, there are still severe discrepancies on individual nucleosome positioning and how this influences gene regulation. The variability among nucleosome maps, which precludes the fine analysis of nucleosome positioning, might emerge from diverse sources. We have carefully inspected the extrinsic factors that may induce diversity by the comparison of microccocal nuclease (MNase)-Seq derived nucleosome maps generated under distinct conditions. Furthermore, we have also explored the variation originated from intrinsic nucleosome dynamics by generating additional maps derived from cell cycle synchronized and asynchronous yeast cultures. Taken together, our study has enabled us to measure the effect of noise in nucleosome occupancy and positioning and provides insights into the underlying determinants. Furthermore, we present a systematic approach that may guide the standardization of MNase-Seq experiments in order to generate reproducible genome-wide nucleosome patterns.

Figure 1.

Nucleosome coverage and gene clustering in single- and paired-end sequencing. Heat maps showing nucleosome occupancy around TSS in replicas 1 (top) and 2 (bottom) for single-end sequencing (1x, left) and paired-end sequencing (2x, right). Genes are clustered based on their nucleosome profile and their coverage is plotted taking +1 nucleosome dyad as ′0′.

Figure 2.

Nucleosome coverage and clustering under different experimental conditions. Similar to Figure 2, but for asynchronous (top), over-digested (middle) and under-digested (bottom) samples.

Figure 3.

Effect of variable read length on map coverage. (A) Coverage distribution of short, mid and long reads in under-digested (left) and over-digested (right) samples. (B) Normalized coverage profiles of trimmed reads around TSSs derived from different sequencing lengths.

Figure 4.

Statistical positioning and intrinsic DNA energetic barriers. (A) Average experimental nucleosome coverage from WoW (top) and WcW (bottom) patterns in replica 1 are compared against a nucleosome positioning statistical model. (B) The experimental coverage of WoW (top) and WcW (bottom) classes (red) are overlapped with deformation energy (cyan) and predictive TFBS (blue) around TSSs.

Figure 5.

Possible sources of intrinsic nucleosome noise. (A) In single-end sequencing, reads mapped in opposite strands (light red, light blue) are shifted 74-bp downstream to align the nucleosome dyad (dark red, dark blue). Despite this approach is suitable for mono-nucleosome fragment alignment (left), shorter (middle) or longer fragments (right) are misaligned, causing a fuzzy peak coverage. (B) In paired-end sequencing, the detection of mono-nucleosome dyads can be obtained by trimming the reads (left). However, in the case of long di-nucleosome fragments, the trimmed reads are aligned to the linker space between mono-nucleosomes, which in turn increase the fuzziness. (C) Energetic barriers due to intrinsic DNA deformability potential or presence of competing proteins (represented as purple line) act as a phasing element in adjacent nucleosomes (top) leading to well-localized nucleosome signals. In the absence of such barriers, the periodicity of this potential cannot act in nucleosome phasing (bottom) leading to diffuse signals originated by spontaneous nucleosome sliding. (D) Individual nucleosome arrays of asynchronous cells in different stages of the cell-cycle capture intrinsic chromatin dynamics (left) which is visualized as fuzzy signals. This effect is minimized in synchronized cell populations (right).