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Distinct modes of regulation by chromatin encoded through nucleosome positioning signals.

Field Y, Kaplan N, Fondufe-Mittendorf Y, Moore IK, Sharon E, Lubling Y, Widom J, Segal E - PLoS Comput. Biol. (2008)

Bottom Line: The detailed positions of nucleosomes profoundly impact gene regulation and are partly encoded by the genomic DNA sequence.We find that Poly(dA:dT) tracts are an important component of these nucleosome positioning signals and that their nucleosome-disfavoring action results in large nucleosome depletion over them and over their flanking regions and enhances the accessibility of transcription factors to their cognate sites.Our results suggest that the yeast genome may utilize these nucleosome positioning signals to regulate gene expression with different transcriptional noise and activation kinetics and DNA replication with different origin efficiency.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.

ABSTRACT
The detailed positions of nucleosomes profoundly impact gene regulation and are partly encoded by the genomic DNA sequence. However, less is known about the functional consequences of this encoding. Here, we address this question using a genome-wide map of approximately 380,000 yeast nucleosomes that we sequenced in their entirety. Utilizing the high resolution of our map, we refine our understanding of how nucleosome organizations are encoded by the DNA sequence and demonstrate that the genomic sequence is highly predictive of the in vivo nucleosome organization, even across new nucleosome-bound sequences that we isolated from fly and human. We find that Poly(dA:dT) tracts are an important component of these nucleosome positioning signals and that their nucleosome-disfavoring action results in large nucleosome depletion over them and over their flanking regions and enhances the accessibility of transcription factors to their cognate sites. Our results suggest that the yeast genome may utilize these nucleosome positioning signals to regulate gene expression with different transcriptional noise and activation kinetics and DNA replication with different origin efficiency. These distinct functions may be achieved by encoding both relatively closed (nucleosome-covered) chromatin organizations over some factor binding sites, where factors must compete with nucleosomes for DNA access, and relatively open (nucleosome-depleted) organizations over other factor sites, where factors bind without competition.

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Two different types of regulation by chromatin in yeast promoters.(A) Promoters with TATA elements and whose binding sites are located in regions covered by nucleosomes exhibit large transcriptional noise. Genes were divided into four groups based on the presence or absence of TATA elements [53], and by whether their binding sites are covered by nucleosomes or are nucleosome-depleted as measured in our map (see Methods). For each group of genes, shown is the fraction of its genes (y-axis) whose noise level is within the k most noisy genes (x-axis; expressed as fraction), for all possible values of k. Measurements of transcriptional noise are available for 2197 genes [49] and are presented in their ranked value. (B) Yeast promoters are enriched with architectures that are associated with high- and low-noise. For each of the four gene sets from (A), shown is the actual number of genes in each set (red bar) compared to the expected number of genes in each set (blue bar). The number of genes in the two extreme promoter types (type I: leftmost columns, genes with TATA elements and nucleosome-covered factor sites; type II: rightmost columns, genes without TATA elements and with nucleosome-depleted factor sites) is significantly more than would be expected just from the counts of the number of genes with/without TATA elements and with nucleosome-depleted/nucleosome-covered sites (P<10−16, hypergeometric test). (C) Promoters with TATA elements and whose binding sites are located in regions covered by nucleosomes as measured in our map exhibit large degrees of histone turnover. For each of the four gene sets from (A), shown is the fraction of its genes (y-axis) whose histone turnover level [55] is within the k promoters with the largest degree of histone turnover (x-axis; expressed as fraction), for all possible values of k. Measurements of histone turnover are presented in their ranked value. (D) Promoters with distinct transcriptional noise characteristics can be predicted from sequence alone. Same as (A), but when dividing genes using only sequence information, based on the presence of Poly(dA:dT)-boundaries and TATA elements. Genes were divided into four groups based on the presence of TATA elements [53], and by whether or not they have a boundary of strength >5 within the 200 bp region upstream of their transcription start site (where the boundary strength is defined based on DNA sequence alone).
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pcbi-1000216-g011: Two different types of regulation by chromatin in yeast promoters.(A) Promoters with TATA elements and whose binding sites are located in regions covered by nucleosomes exhibit large transcriptional noise. Genes were divided into four groups based on the presence or absence of TATA elements [53], and by whether their binding sites are covered by nucleosomes or are nucleosome-depleted as measured in our map (see Methods). For each group of genes, shown is the fraction of its genes (y-axis) whose noise level is within the k most noisy genes (x-axis; expressed as fraction), for all possible values of k. Measurements of transcriptional noise are available for 2197 genes [49] and are presented in their ranked value. (B) Yeast promoters are enriched with architectures that are associated with high- and low-noise. For each of the four gene sets from (A), shown is the actual number of genes in each set (red bar) compared to the expected number of genes in each set (blue bar). The number of genes in the two extreme promoter types (type I: leftmost columns, genes with TATA elements and nucleosome-covered factor sites; type II: rightmost columns, genes without TATA elements and with nucleosome-depleted factor sites) is significantly more than would be expected just from the counts of the number of genes with/without TATA elements and with nucleosome-depleted/nucleosome-covered sites (P<10−16, hypergeometric test). (C) Promoters with TATA elements and whose binding sites are located in regions covered by nucleosomes as measured in our map exhibit large degrees of histone turnover. For each of the four gene sets from (A), shown is the fraction of its genes (y-axis) whose histone turnover level [55] is within the k promoters with the largest degree of histone turnover (x-axis; expressed as fraction), for all possible values of k. Measurements of histone turnover are presented in their ranked value. (D) Promoters with distinct transcriptional noise characteristics can be predicted from sequence alone. Same as (A), but when dividing genes using only sequence information, based on the presence of Poly(dA:dT)-boundaries and TATA elements. Genes were divided into four groups based on the presence of TATA elements [53], and by whether or not they have a boundary of strength >5 within the 200 bp region upstream of their transcription start site (where the boundary strength is defined based on DNA sequence alone).

Mentions: We hypothesized that since factor binding sites near boundaries are depleted of nucleosomes, factors could bind such sites in promoters with little or no competition with nucleosomes, leading to a homogeneous cell population with relatively low cell-to-cell expression variability, or transcriptional noise. In contrast, since steric hindrance may not permit simultaneous binding by factors and nucleosomes, factors that bind sites that are far from boundaries may need to compete with nucleosomes for access to the DNA. Such a competition may result in a mixed population comprising both cells in which a nucleosome covers the factor's site and the promoter is inactive, and cells in which that nucleosome is displaced and the promoter is active. To test this hypothesis, we utilized a dataset [49], which for the majority of the genes in yeast, used a GFP-tagged strain to measure their protein expression variability in single-cells. Since they are easier to obtain, such measurements of variability at the protein level are typically used as a proxy for variability measurements at the RNA level [49]–[51]. This approach is justified by the experimental observation that variability in protein expression is dominated by variability in RNA levels [49]. Using these data, we compared the noise of promoters in which the sites [47] are covered by nucleosomes, to the noise of promoters in which the sites are not covered. Indeed, the former promoter set exhibits significantly more noise (P<10−5, Kolmogorov-Smirnov test). A similar model, in which high noise promoters are those where nucleosomes compete successfully with transcription factors, was suggested and validated for the Pho5 gene [51]. That model further suggested that the presence of TATA sequences should confer even more noise, presumably through facilitation of transcription re-initiation [51],[52]. Thus, under this noise model, we expect, and indeed find, that within each of our two promoter sets above, the presence of TATA [53] elements further increases transcriptional noise (Figure 11A).


Distinct modes of regulation by chromatin encoded through nucleosome positioning signals.

Field Y, Kaplan N, Fondufe-Mittendorf Y, Moore IK, Sharon E, Lubling Y, Widom J, Segal E - PLoS Comput. Biol. (2008)

Two different types of regulation by chromatin in yeast promoters.(A) Promoters with TATA elements and whose binding sites are located in regions covered by nucleosomes exhibit large transcriptional noise. Genes were divided into four groups based on the presence or absence of TATA elements [53], and by whether their binding sites are covered by nucleosomes or are nucleosome-depleted as measured in our map (see Methods). For each group of genes, shown is the fraction of its genes (y-axis) whose noise level is within the k most noisy genes (x-axis; expressed as fraction), for all possible values of k. Measurements of transcriptional noise are available for 2197 genes [49] and are presented in their ranked value. (B) Yeast promoters are enriched with architectures that are associated with high- and low-noise. For each of the four gene sets from (A), shown is the actual number of genes in each set (red bar) compared to the expected number of genes in each set (blue bar). The number of genes in the two extreme promoter types (type I: leftmost columns, genes with TATA elements and nucleosome-covered factor sites; type II: rightmost columns, genes without TATA elements and with nucleosome-depleted factor sites) is significantly more than would be expected just from the counts of the number of genes with/without TATA elements and with nucleosome-depleted/nucleosome-covered sites (P<10−16, hypergeometric test). (C) Promoters with TATA elements and whose binding sites are located in regions covered by nucleosomes as measured in our map exhibit large degrees of histone turnover. For each of the four gene sets from (A), shown is the fraction of its genes (y-axis) whose histone turnover level [55] is within the k promoters with the largest degree of histone turnover (x-axis; expressed as fraction), for all possible values of k. Measurements of histone turnover are presented in their ranked value. (D) Promoters with distinct transcriptional noise characteristics can be predicted from sequence alone. Same as (A), but when dividing genes using only sequence information, based on the presence of Poly(dA:dT)-boundaries and TATA elements. Genes were divided into four groups based on the presence of TATA elements [53], and by whether or not they have a boundary of strength >5 within the 200 bp region upstream of their transcription start site (where the boundary strength is defined based on DNA sequence alone).
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Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC2570626&req=5

pcbi-1000216-g011: Two different types of regulation by chromatin in yeast promoters.(A) Promoters with TATA elements and whose binding sites are located in regions covered by nucleosomes exhibit large transcriptional noise. Genes were divided into four groups based on the presence or absence of TATA elements [53], and by whether their binding sites are covered by nucleosomes or are nucleosome-depleted as measured in our map (see Methods). For each group of genes, shown is the fraction of its genes (y-axis) whose noise level is within the k most noisy genes (x-axis; expressed as fraction), for all possible values of k. Measurements of transcriptional noise are available for 2197 genes [49] and are presented in their ranked value. (B) Yeast promoters are enriched with architectures that are associated with high- and low-noise. For each of the four gene sets from (A), shown is the actual number of genes in each set (red bar) compared to the expected number of genes in each set (blue bar). The number of genes in the two extreme promoter types (type I: leftmost columns, genes with TATA elements and nucleosome-covered factor sites; type II: rightmost columns, genes without TATA elements and with nucleosome-depleted factor sites) is significantly more than would be expected just from the counts of the number of genes with/without TATA elements and with nucleosome-depleted/nucleosome-covered sites (P<10−16, hypergeometric test). (C) Promoters with TATA elements and whose binding sites are located in regions covered by nucleosomes as measured in our map exhibit large degrees of histone turnover. For each of the four gene sets from (A), shown is the fraction of its genes (y-axis) whose histone turnover level [55] is within the k promoters with the largest degree of histone turnover (x-axis; expressed as fraction), for all possible values of k. Measurements of histone turnover are presented in their ranked value. (D) Promoters with distinct transcriptional noise characteristics can be predicted from sequence alone. Same as (A), but when dividing genes using only sequence information, based on the presence of Poly(dA:dT)-boundaries and TATA elements. Genes were divided into four groups based on the presence of TATA elements [53], and by whether or not they have a boundary of strength >5 within the 200 bp region upstream of their transcription start site (where the boundary strength is defined based on DNA sequence alone).
Mentions: We hypothesized that since factor binding sites near boundaries are depleted of nucleosomes, factors could bind such sites in promoters with little or no competition with nucleosomes, leading to a homogeneous cell population with relatively low cell-to-cell expression variability, or transcriptional noise. In contrast, since steric hindrance may not permit simultaneous binding by factors and nucleosomes, factors that bind sites that are far from boundaries may need to compete with nucleosomes for access to the DNA. Such a competition may result in a mixed population comprising both cells in which a nucleosome covers the factor's site and the promoter is inactive, and cells in which that nucleosome is displaced and the promoter is active. To test this hypothesis, we utilized a dataset [49], which for the majority of the genes in yeast, used a GFP-tagged strain to measure their protein expression variability in single-cells. Since they are easier to obtain, such measurements of variability at the protein level are typically used as a proxy for variability measurements at the RNA level [49]–[51]. This approach is justified by the experimental observation that variability in protein expression is dominated by variability in RNA levels [49]. Using these data, we compared the noise of promoters in which the sites [47] are covered by nucleosomes, to the noise of promoters in which the sites are not covered. Indeed, the former promoter set exhibits significantly more noise (P<10−5, Kolmogorov-Smirnov test). A similar model, in which high noise promoters are those where nucleosomes compete successfully with transcription factors, was suggested and validated for the Pho5 gene [51]. That model further suggested that the presence of TATA sequences should confer even more noise, presumably through facilitation of transcription re-initiation [51],[52]. Thus, under this noise model, we expect, and indeed find, that within each of our two promoter sets above, the presence of TATA [53] elements further increases transcriptional noise (Figure 11A).

Bottom Line: The detailed positions of nucleosomes profoundly impact gene regulation and are partly encoded by the genomic DNA sequence.We find that Poly(dA:dT) tracts are an important component of these nucleosome positioning signals and that their nucleosome-disfavoring action results in large nucleosome depletion over them and over their flanking regions and enhances the accessibility of transcription factors to their cognate sites.Our results suggest that the yeast genome may utilize these nucleosome positioning signals to regulate gene expression with different transcriptional noise and activation kinetics and DNA replication with different origin efficiency.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.

ABSTRACT
The detailed positions of nucleosomes profoundly impact gene regulation and are partly encoded by the genomic DNA sequence. However, less is known about the functional consequences of this encoding. Here, we address this question using a genome-wide map of approximately 380,000 yeast nucleosomes that we sequenced in their entirety. Utilizing the high resolution of our map, we refine our understanding of how nucleosome organizations are encoded by the DNA sequence and demonstrate that the genomic sequence is highly predictive of the in vivo nucleosome organization, even across new nucleosome-bound sequences that we isolated from fly and human. We find that Poly(dA:dT) tracts are an important component of these nucleosome positioning signals and that their nucleosome-disfavoring action results in large nucleosome depletion over them and over their flanking regions and enhances the accessibility of transcription factors to their cognate sites. Our results suggest that the yeast genome may utilize these nucleosome positioning signals to regulate gene expression with different transcriptional noise and activation kinetics and DNA replication with different origin efficiency. These distinct functions may be achieved by encoding both relatively closed (nucleosome-covered) chromatin organizations over some factor binding sites, where factors must compete with nucleosomes for DNA access, and relatively open (nucleosome-depleted) organizations over other factor sites, where factors bind without competition.

Show MeSH
Related in: MedlinePlus