Quantitative test of the barrier nucleosome model for statistical positioning of nucleosomes up- and downstream of transcription start sites

The positions of nucleosomes in eukaryotic genomes determine which parts of the DNA sequence are readily accessible for regulatory proteins and which are not. Genome-wide maps of nucleosome positions have revealed a salient pattern around transcription start sites, involving a nucleosome-free region (NFR) flanked by a pronounced periodic pattern in the average nucleosome density. While the periodic pattern clearly reflects well-positioned nucleosomes, the positioning mechanism is less clear. A recent experimental study by Mavrich et al. argued that the pattern observed in S. cerevisiae is qualitatively consistent with a `barrier nucleosome model', in which the oscillatory pattern is created by the statistical positioning mechanism of Kornberg and Stryer. On the other hand, there is clear evidence for intrinsic sequence preferences of nucleosomes, and it is unclear to what extent these sequence preferences affect the observed pattern. To test the barrier nucleosome model, we quantitatively analyze yeast nucleosome positioning data both up- and downstream from NFRs. Our analysis is based on the Tonks model of statistical physics which quantifies the interplay between the excluded-volume interaction of nucleosomes and their positional entropy. We find that although the typical patterns on the two sides of the NFR are different, they are both quantitatively described by the same physical model, with the same parameters, but different boundary conditions. The inferred boundary conditions suggest that the first nucleosome downstream from the NFR (the +1 nucleosome) is typically directly positioned while the first nucleosome upstream is statistically positioned via a nucleosome-repelling DNA region. These boundary conditions, which can be locally encoded into the genome sequence, significantly shape the statistical distribution of nucleosomes over a range of up to ~1000 bp to each side.Comment: includes supporting materia

Robustness and Generalization

We derive generalization bounds for learning algorithms based on their robustness: the property that if a testing sample is "similar" to a training sample, then the testing error is close to the training error. This provides a novel approach, different from the complexity or stability arguments, to study generalization of learning algorithms. We further show that a weak notion of robustness is both sufficient and necessary for generalizability, which implies that robustness is a fundamental property for learning algorithms to work

Protein Kinase A Regulates Molecular Chaperone Transcription and Protein Aggregation

Heat shock factor 1 (HSF1) regulates one of the major pathways of protein quality control and is essential for deterrence of protein-folding disorders, particularly in neuronal cells. However, HSF1 activity declines with age, a change that may open the door to progression of neurodegenerative disorders such as Huntington's disease. We have investigated mechanisms of HSF1 regulation that may become compromised with age. HSF1 binds stably to the catalytic domain of protein kinase A (PKAcα) and becomes phosphorylated on at least one regulatory serine residue (S320). We show here that PKA is essential for effective transcription of HSP genes by HSF1. PKA triggers a cascade involving HSF1 binding to the histone acetylase p300 and positive translation elongation factor 1 (p-TEFb) and phosphorylation of the c-terminal domain of RNA polymerase II, a key mechanism in the downstream steps of HSF1-mediated transcription. This cascade appears to play a key role in protein quality control in neuronal cells expressing aggregation-prone proteins with long poly-glutamine (poly-Q) tracts. Such proteins formed inclusion bodies that could be resolved by HSF1 activation during heat shock. Resolution of the inclusions was inhibited by knockdown of HSF1, PKAcα, or the pTEFb component CDK9, indicating a key role for the HSF1-PKA cascade in protein quality control

The Yin and Yang of Yeast Transcription: Elements of a Global Feedback System between Metabolism and Chromatin

When grown in continuous culture, budding yeast cells tend to synchronize their respiratory activity to form a stable oscillation that percolates throughout cellular physiology and involves the majority of the protein-coding transcriptome. Oscillations in batch culture and at single cell level support the idea that these dynamics constitute a general growth principle. The precise molecular mechanisms and biological functions of the oscillation remain elusive. Fourier analysis of transcriptome time series datasets from two different oscillation periods (0.7 h and 5 h) reveals seven distinct co-expression clusters common to both systems (34% of all yeast ORF), which consolidate into two superclusters when correlated with a compilation of 1,327 unrelated transcriptome datasets. These superclusters encode for cell growth and anabolism during the phase of high, and mitochondrial growth, catabolism and stress response during the phase of low oxygen uptake. The promoters of each cluster are characterized by different nucleotide contents, promoter nucleosome configurations, and dependence on ATP-dependent nucleosome remodeling complexes. We show that the ATP:ADP ratio oscillates, compatible with alternating metabolic activity of the two superclusters and differential feedback on their transcription via activating (RSC) and repressive (Isw2) types of promoter structure remodeling. We propose a novel feedback mechanism, where the energetic state of the cell, reflected in the ATP:ADP ratio, gates the transcription of large, but functionally coherent groups of genes via differential effects of ATP-dependent nucleosome remodeling machineries. Besides providing a mechanistic hypothesis for the delayed negative feedback that results in the oscillatory phenotype, this mechanism may underpin the continuous adaptation of growth to environmental conditions

Transcriptional interaction-assisted identification of dynamic nucleosome positioning

<p>Abstract</p> <p>Background</p> <p>Nucleosomes regulate DNA accessibility and therefore play a central role in transcription control. Computational methods have been developed to predict static nucleosome positions from DNA sequences, but nucleosomes are dynamic in vivo.</p> <p>Results</p> <p>Motivated by our observation that transcriptional interaction is discriminative information for nucleosome occupancy, we developed a novel computational approach to identify dynamic nucleosome positions at promoters by combining transcriptional interaction and genomic sequence information. Our approach successfully identified experimentally determined nucleosome positioning dynamics available in three cellular conditions, and significantly improved the prediction accuracy which is based on sequence information alone. We then applied our approach to various cellular conditions and established a comprehensive landscape of dynamic nucleosome positioning in yeast.</p> <p>Conclusion</p> <p>Analysis of this landscape revealed that the majority of nucleosome positions are maintained during most conditions. However, nucleosome occupancy at most promoters fluctuates with the corresponding gene expression level and is reduced specifically at the phase of peak expression. Further investigation into properties of nucleosome occupancy identified two gene groups associated with distinct modes of nucleosome modulation. Our results suggest that both the intrinsic sequence and regulatory proteins modulate nucleosomes in an altered manner.</p

Positional variations among heterogeneous nucleosome maps give dynamical information on chromatin

Although nucleosome remodeling is essential to transcriptional regulation in eukaryotes, little is known about its genome-wide behavior. Since a number of nucleosome positioning maps in vivo have been recently determined, we examined if their comparisons might be used for obtaining a genome-wide profile of nucleosome remodeling. Using seven yeast maps, the local variability of nucleosomes, measured by the entropy, was significantly higher in a set of reported unstable nucleosomes. The binding sites of four transcription factors, known as the remodeling factors, were distinctively high both in entropy and linker ratio, whereas those of Yhp1, their potential inhibitor, showed the lowest values in both of them. Taken together, our map shows the general information of nucleosome dynamics reasonably well. The “nucleosome dynamics” map provides the new significant correlation with the degree of expression variety instead of their intensity. Furthermore, the associations with gene function and histone modification were also discussed here

Diversity of Eukaryotic DNA Replication Origins Revealed by Genome-Wide Analysis of Chromatin Structure

Eukaryotic DNA replication origins differ both in their efficiency and in the characteristic time during S phase when they become active. The biological basis for these differences remains unknown, but they could be a consequence of chromatin structure. The availability of genome-wide maps of nucleosome positions has led to an explosion of information about how nucleosomes are assembled at transcription start sites, but no similar maps exist for DNA replication origins. Here we combine high-resolution genome-wide nucleosome maps with comprehensive annotations of DNA replication origins to identify patterns of nucleosome occupancy at eukaryotic replication origins. On average, replication origins contain a nucleosome depleted region centered next to the ACS element, flanked on both sides by arrays of well-positioned nucleosomes. Our analysis identified DNA sequence properties that correlate with nucleosome occupancy at replication origins genome-wide and that are correlated with the nucleosome-depleted region. Clustering analysis of all annotated replication origins revealed a surprising diversity of nucleosome occupancy patterns. We provide evidence that the origin recognition complex, which binds to the origin, acts as a barrier element to position and phase nucleosomes on both sides of the origin. Finally, analysis of chromatin reconstituted in vitro reveals that origins are inherently nucleosome depleted. Together our data provide a comprehensive, genome-wide view of chromatin structure at replication origins and suggest a model of nucleosome positioning at replication origins in which the underlying sequence occludes nucleosomes to permit binding of the origin recognition complex, which then (likely in concert with nucleosome modifiers and remodelers) positions nucleosomes adjacent to the origin to promote replication origin function

Structural constraints revealed in consistent nucleosome positions in the genome of S. cerevisiae

<p>Abstract</p> <p>Background</p> <p>Recent advances in the field of high-throughput genomics have rendered possible the performance of genome-scale studies to define the nucleosomal landscapes of eukaryote genomes. Such analyses are aimed towards providing a better understanding of the process of nucleosome positioning, for which several models have been suggested. Nevertheless, questions regarding the sequence constraints of nucleosomal DNA and how they may have been shaped through evolution remain open. In this paper, we analyze in detail different experimental nucleosome datasets with the aim of providing a hypothesis for the emergence of nucleosome-forming sequences.</p> <p>Results</p> <p>We compared the complete sets of nucleosome positions for the budding yeast (<it>Saccharomyces cerevisiae</it>) as defined in the output of two independent experiments with the use of two different experimental techniques. We found that < 10% of the experimentally defined nucleosome positions were consistently positioned in both datasets. This subset of well-positioned nucleosomes, when compared with the bulk, was shown to have particular properties at both sequence and structural levels. Consistently positioned nucleosomes were also shown to occur preferentially in pairs of dinucleosomes, and to be surprisingly less conserved compared with their adjacent nucleosome-free linkers.</p> <p>Conclusion</p> <p>Our findings may be combined into a hypothesis for the emergence of a weak nucleosome-positioning code. According to this hypothesis, consistent nucleosomes may be partly guided by nearby nucleosome-free regions through statistical positioning. Once established, a set of well-positioned consistent nucleosomes may impose secondary constraints that further shape the structure of the underlying DNA. We were able to capture these constraints through the application of a recently introduced structural property that is related to the symmetry of DNA curvature. Furthermore, we found that both consistently positioned nucleosomes and their adjacent nucleosome-free regions show an increased tendency towards conservation of this structural feature.</p