Nozaki et al. BMC Genomics 2011, 12:416
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RESEARCH ARTICLE

Open Access

Tight associations between transcription
promoter type and epigenetic variation inhistone positioning and modification
Tadasu Nozaki1,2, Nozomu Yachie1,3,6, Ryu Ogawa1,4, Anton Kratz1,4,8, Rintaro Saito1,2,5,7* and Masaru Tomita1,2,4Abstract
Background: Transcription promoters are fundamental genomic cis-elements controlling gene expression. They
can be classified into two types by the degree of imprecision of their transcription start sites: peak promoters,
which initiate transcription from a narrow genomic region; and broad promoters, which initiate transcription froma wide-ranging region. Eukaryotic transcription initiation is suggested to be associated with the genomic positions
and modifications of nucleosomes. For instance, it has been recently shown that histone with H3K9 acetylation(H3K9ac) is more likely to be distributed around broad promoters rather than peak promoters; it can thus beinferred that there is an association between histone H3K9 and promoter architecture.
Results: Here, we performed a systematic analysis of transcription promoters and gene expression, as well as of
epigenetic histone behaviors, including genomic position, stability within the chromatin, and several modifications.
We found that, in humans, broad promoters, but not peak promoters, generally had significant associations with
nucleosome positioning and modification. Specifically, around broad promoters histones were highly distributed
and aligned in an orderly fashion. This feature was more evident with histones that were methylated or acetylated;moreover, the nucleosome positions around the broad promoters were more stable than those around the peak
ones. More strikingly, the overall expression levels of genes associated with broad promoters (but not peakpromoters) with modified histones were significantly higher than the levels of genes associated with broad
promoters with unmodified histones.
Conclusion: These results shed light on how epigenetic regulatory networks of histone modifications areassociated with promoter architecture.

Background
Recent progress in high-throughput technologies has
made it possible to collect a variety of “omics” data on
transcripts and on the epigenetic behaviors of the histones
that are often associated with these transcripts [1-5].
Cap analysis of gene expression (CAGE) is a highthroughput method that enables large-scale identification of transcription start sites (TSSs) of eukaryotic species. This method measures gene expression levels
simultaneously with TSS identification by counting thesequenced 5’ ends of full-length cDNAs, termed CAGE
tags [2,6]. With the development of deep sequencing* Correspondence: rsaito@sfc.keio.ac.jp1
Institute for Advanced Biosciences, Keio University, Tsuruoka, 997-0017,
Japan
Full list of author information is available at the end of the article

methods, more high-throughput, and high resolution“tag depth” measurements have become available(DeepCAGE, nanoCAGE and CAGEscan) [1,7]. Such
recent whole-cell-level pictures of quantitative transcriptomes have revealed the complex transcriptional network of mammalian species [1,2,6]. According to recent
CAGE-based analyses of human TSSs, the human “promotome” can be classified into two types of promotersby the degree of imprecision of their transcription initiation sites [8]. One is the peak promoter, which initiates
transcription strictly from a narrow genomic region(within a distance of 1-4 bp), and the other is the broad
promoter, which initiates transcription from wide-ranging positions (> 4 bp) [8,9]. The peak promoters aresuggested to be closely associated with the presence of
the TATA box (which enables proper control of gene© 2011 Nozaki et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction inany medium, provided the original work is properly cited.

Nozaki et al. BMC Genomics 2011, 12:416
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expression by binding with transcription factors) andwith tissue-specific gene expression. The broad promoters have been observed in the presence of CpG islands
and drive relatively ubiquitous expression of the genes
they control [8,10-12]. The CpG-rich broad promoters
are considered evolutionarily new and more likely to becontrolled by epigenetic mechanisms, including DNA
methylation and sense-antisense regulation, than thepeak promoters [8,11,13]. These differences between
broad and peak promoters raise questions of how thesepromoter types are associated with chromosomal structures and modifications and of how their difference confers cellular function.
In eukaryotic species, chromosomal DNAs is packed
into nucleosomes, each of which comprises approximately 147 base pairs wrapped around a histone protein
octamer consisting of two copies of each of the four
core histones, H2A, H2B, H3, and H4 [14,15]. Two biologically important aspects of these histones are theirpositions and modifications, and it has been shown thatthese factors regulate transcription initiation [16-18].
Several methodologies have rapidly been developed forhigh-throughput identification of histone positions andmodifications. ChIP-chip identifies the histone-binding
positions of genomic DNA by using a combination ofchromatin immunoprecipitation and tiling array [19].
Although ChIP-chip used to be a widely-used method,
today, with the growing demand to develop highthroughput sequencing, the ChIP-Seq method has beendeveloped as a promising alternative to the tiling arraybased approach in analyzing genome-wide nucleosome
positioning [20,21]. These methodologies have revealed
several insights into the intertwining of gene expression
with nucleosome position and histone modification. For
example, the degree of eviction of nucleosomes fromthe upstream regions of TSSs is correlated with gene
expression patterns in yeasts [19,22] and humans[4,23,24]. Moreover, the methylated histone H3 at lysine
4 (H3K4me1, 2, and 3) and acetylated histone H3 atlysine 9 (H3K9ac), located around TSSs, are linked togene activation [3,25-28], whereas H3K27me3 andH3K9me3 are linked to gene repression [3,27,29,30].
These modifications and related gene regulatory behaviors support the “histone code” hypothesis [28], i.e. thatmultiple histone modifications specify unique downstream functions. However, the detailed mechanisms
underlying transcriptional regulation by these histone
behaviors are still obscure.
H3K9ac has recently been frequently observed aroundbroad promoters [9]. This implies that histone behavior
is associated with promoter architecture, although thisassociation has so far been found only in the case of
H3K9ac, and the extent of such associations is unclear.
In this study, we systematically analyzed the relationships

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between histone behaviors and promoter architecture
types by using information about (1) modified/unmodified histones; (2) their genomic positions relative to TSSs;(3) their positional stabilities on the genome under two
cellular conditions; and (4) gene expression. The results
showed that promoter architecture type and gene expression are tightly associated with the modification pattern
and genomic positional stability of the histones forming
nucleosomes. They provide new insights into the epigenetic mechanisms of transcriptional regulation in termsof histone behavior.

Results
Promoter architecture and nucleosome positioning

We first focused on differences in nucleosome distribution around the two different types of transcription promoters (i.e. peak and broad promoters). We usedhuman promoter positions for which information about
the degree of transcription start imprecision had beenobtained in a previous study [9], as well as nucleosome
positions defined as the genomic positions of histone
H3 proteins in the resting condition in human CD4+ Tcells [4]. We mapped them on human genomic
sequences. (See Methods for details of data manipulations.) We then calculated the ratio of nucleosomes
located at each genomic position relative to each peak
and broad promoter. We found that the nucleosome
positions associated with broad promoters had markedlyaligned and periodic patterns compared with those ofpeak promoters (Figure 1A). More strikingly, only inbroad promoters, the first nucleosomes immediately
downstream of the promoter were likely to be located insimilar positions and those immediately upstream of thepromoter were depleted (see the magnified view in Figure 1A). This was contrary to our expectation; previous
studies have reported that, in general, nucleosomes are
distributed evenly around the promoter region [31,32].
We had therefore expected that the nucleosome positions would be spread around the broad promoter andwell aligned around the peak promoter, because TSSs
are widely spread in the broad promoter region but narrowly spread in the peak promoter region. However, ourresults show that the broad promoter was specificallyassociated with a more aligned pattern of nucleosomes
than the peak promoter.
H2A.Z is a histone variant of H2A that is highly conserved among lower and higher eukaryotes. Enrichmentof H2A.Z around the promoter region has been also
reported in yeast [33] and humans [34]. In terms of promoter architecture, we performed a similar analysis tothe one of H3 shown in Figure 1A of the positions ofhuman nucleosomes harboring the histone variant H2A.
Z in human resting CD4+ T-cells [3]. H2A.Z was highly
enriched around broad promoters but not peakNozaki et al. BMC Genomics 2011, 12:416
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Figure 1 Distributions of nucleosome positions aroundtranscription start sites (TSSs). (A) Distributions of the central
positions of histone H3 around broad and peak promoters. The xaxis shows genomic positions with respect to TSSs (from -5 kb to 5
kb, upper panel; and from -500 bp to 500 bp, lower panel). The
central positions of nucleosomes are defined as the positions from-15 bp to 15 bp with respect to the center of the nucleosome. (B)Distributions of nucleosomes containing the histone variant H2A.Z
around TSSs (from -5 kb to 5 kb). H2A.Z around TSSs associatedwith broad promoters are highly enriched, unlike those associatedwith peak promoters. (C) Distributions of minimum distances fromeach of the nucleosomes in human resting T cells compared withthose in activated T cells. The x-axis shows the minimum distances
and the y-axis shows the proportions of nucleosomes with thespecified minimum distances. Proportions within every 15 bp wereaveraged. Minimum distances were calculated for all nucleosomeson the genome (dashed line), for those associated with broad
promoters (red line), and for those associated with peak promoters(blue line).

promoters (Figure 1B). For example, the statistical significance of the enrichment was P < 1.0 × 10-25 (chisquared test) for positions +100 to +130 with respect to
the TSS. Moreover, the distribution patterns of H2A.Z
were similar to those of H3; the positions of H2A.Z
were markedly aligned around broad promoters but notaround peak promoters.
Accessibility of transcription factor Sp1

The two promoter architectures are associated withcharacteristic sequence contexts: the peak promoter islocated close to a TATA box and the broad promoter
close to CpG islands [8]. Using the genomic positions ofputative TATA-box sites predicted by a position-specificweight matrix and the positions of CpG islands obtained
from the UCSC Genome Browser database [35,36], we
confirmed that TATA boxes were overrepresented inpeak promoters and that broad promoters were highly
associated with the presence of CpG islands (Additional
file 1, Figure S1).
It is possible that the aligned patterns of nucleosome
positions around broad promoters are due to the accessibility of transcription factors to DNA. For instance, in
the absence of the TATA box, the ubiquitousPage 3 of 10

transcription factor Sp1 can recruit TATA-binding proteins to initiate transcription [37]. It has already beenreported that consensus Sp1 sites with high overall GC
contents are overrepresented among broad promoters,
and the positions of these sites for individual transcription units are less precise than those of TATA boxes[8]. Consequently, we investigated the possibility thatthe nucleosomes around a broad promoter align in amore orderly fashion than those around the peak promoter because of the need to create a nucleosome-free
region upstream of the TSS to confer DNA accessibilityof transcription factor proteins. We superimposed the
distribution of putative Sp1 sites [1] around broad promoters onto that of the nucleosome positions (seeMethods), and we observed increased proportions ofSp1 sites about -50 bp upstream of the broad promoter,
where the nucleosome distribution was markedly
depleted (Additional file 2, Figure S2). We conducted
the same analysis for peak promoters. The inverse relationship between Sp1 site and nucleosome abundancearound the broad promoter was much higher than thataround the peak promoter, suggesting the plausibility of
the DNA accessibility model. Furthermore, we conducted a similar analysis for the binding sites of twoother transcription factors, PU.1 and MAZ, as a previous study (FANTOM4) had analyzed the binding sitesof these two factors in detail [1]. The binding sites ofboth PU.1 and MAZ were distributed on nucleosomefree regions around broad promoters, whereas no such
trends were observed around peak promoters (Additional file 3, Figure S3). These results support the strong
connection between the nucleosome-free region and theaccessibility of transcription factors, which was specificto broad promoters.
Positional stability of nucleosomes around broad
promoters

If nucleosome positioning around broad promoters confers DNA accessibility for the binding of transcription
factors, then the nucleosome positions around broad
promoters should be more stable throughout different
cellular conditions than those around peak promoters,
because broad promoters are usually associated withubiquitously expressed gene (in contrast, peak promoters are associated with tissue- and condition-specificexpressed gene) [8,10-12] and the genomic positions oftranscription factor binding sites are fixed. We analyzed
the positional stability of nucleosomes located within
positions +1 to +200 with respect to each promoter
under “resting” and “activated” conditions of humanCD4+ T-cells [4] (see Methods). For each nucleosome
position in the resting condition, we calculated the distance to the nearest nucleosome position in the activated condition in order to assess the positional

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stabilities of single nucleosomes under the two different
cellular conditions. The overall minimum distance wasmarkedly shorter for broad promoter-associated nucleosomes than for peak promoter-associated ones (Figure1C). In fact, the average absolute minimum distance inthe case of the broad promoter (20.70 bp) was significantly shorter than that for the peak promoter (25.08bp) (P = 4.83 × 10-7; t-test. Note that we did not take
into account nucleosomes for which a minimum distance longer than 100 bp was found between the two
conditions, because these were more likely to be different or neighboring nucleosomes rather than those thatmoved along the DNA with the change in conditions.).
These results demonstrated that the positions of nucleosomes around the broad promoters were more stable
than those of nucleosomes around the peak promoters.
Distribution of nucleosomes containing modified histones

It has been suggested that not only nucleosome position,
but also nucleosomal histone modification, can regulatetranscription [3,25-27]. For instance, histone methylation is associated with either gene activation or repression, depending on the methylation site and state on thehistone protein; in particular, methylation of histone H3(H3K4me1, -2, and -3) in nucleosomes around the transcription promoter are well known to regulate gene
expression [3,25-28]. To investigate the differences inpositional distribution of nucleosomes containing
methylated histones around the two different types ofpromoter, we obtained nucleosome positions corresponding to each of three methylation types (H3K4me1,
2, and 3) in human CD4+ T cells from a previous study[3], and we mapped these onto genomic sequences withthe broad and peak promoter positions. Similar to theresult for histone H3, nucleosomes having H3K4me1,-2, and -3 were all highly enriched and well aligned
around broad promoters, whereas they were depleted
around peak promoter regions (Figure 2A-C). However,
the alignment pattern of nucleosome positions differeddepending on the type of methylation. Within the region
downstream of the broad promoter, the first frequency
peak of nucleosomes having H3K4me1 and 2 occurredin the +700 to +730 region (Figure 2A and 2B), whereas
those having H3K4me3 occurred in the +100 to +130
region (Figure 2C; this was similar to the result for histone H3, perhaps because the majority of H3K4 weretrimethylated). For each methylation type, the differencein frequency of occurrence of nucleosomes with eachtype of modified histone in these regions between thepeak and broad promoters was significant (P < 1.0 × 1010 for H3K4me1 and 2, and P < 1.0 × 10-50 for
H3K4me3; chi-squared test). Note that the values on they-axes in Figure 2 are not influenced by the absolute
numbers of nucleosomes in each type of promoter, as

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Figure 2 Distribution of modified histones around transcription
start sites (TSSs). Distributions of nucleosomes containing
methylated and acetylated histones. (A) H3K4me1, (B) H3K4me2,and (C) H3K4me3 and (D) H3K9ac around TSSs are shown. All of themodified histones were highly enriched around the TSSs associatedwith broad promoters, unlike those associated with peak promoters.
The x-axis shows the genomic positions with respect to the TSSs
(from -5 kb to 5 kb).

they indicate the proportion of nucleosome-harboring
TSSs for each type of TSS. In addition to methylation,acetylation may control gene expression [3,25-28]. We
further analyzed nucleosome positioning corresponding
to histone acetylation (H3K9ac) in human CD4+ T cells
and observed results similar to those for H3K4me3 (P <1.0 × 10-50 for +100 to +130 region; chi-squared test;
Figure 2D). For each of H3, H2A.Z, H3K4me3, andH3K9ac, we estimated the abundance of nucleosomes
associated with peak promoters relative to that ofnucleosomes associated with broad promoters (Figure 3;
see Methods). Compared with nucleosomes carrying histone H3, the relative abundances of nucleosomes carrying the modified histones or the histone variant werelarge, suggesting that the presence of histone

Figure 3 Relative abundance in histone distributions.
Normalized differences in histone distributions (H3, H3K4me3,
H3K9ac, and H2A.Z) between broad and peak promoters (from -2 kb
to 2 kb) at each position are shown. The y-axis shows thenormalized differences in histone distributions between broad andpeak promoters. H3K4me3, H3K9ac, and H2A.Z had larger
differences than H3.

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modifications or a histone variant was highly associatedwith the broad promoter but not the peak promoter.
Analysis of another genomic element that potentiallyinfluences histone behavior

Methylation of CpG islands is tightly associated with theexpression of downstream genes; a number of studies
have therefore been conducted to analyze CpG islands
at a genome-wide level [38,39]. As described above,
broad promoters are strongly associated with CpG
islands (Additional file 1, Figure S1). Therefore, it ispossible that the enrichment of histone modifications
and histone variants in the broad promoter region isderived merely from the effect of CpG islands and isindependent of promoter architecture. In fact, it has
been shown that promoters with many CpG islands are
more likely to harbor modified histones than promoterswith fewer CpG islands [40]. To address this issue, we
analyzed the positions of nucleosomes having histone
H3 and those having H3K4me3 around broad and peakpromoters with and without CpG islands (Figure 4). We
found that, in the case where promoters were associatedwith CpG islands, nucleosomes with histone H3K4me3
were likely to be well aligned even around peak promoters. However, broad promoter-associated nucleosomes
were significantly more enriched than peak promoterassociated nucleosomes, especially in the region downstream of the promoter (Figure 4A; P < 1.0 × 10-16 for+100 to +130 region; chi-squared test). (Note, however,

Figure 4 Distributions of nucleosomes around transcription
start sites (TSSs) with and without CpG islands. Distributions of
nucleosomes containing H3K4me3 (A, B) and H3 (C, D) aroundbroad and peak promoters are shown. The analyses wereconducted separately for TSSs that were associated with CpG
islands (A, C) and those that were not (B, D). Broad promoters hadaligned patterns of nucleosomes containing H3 and H3K4me3,
regardless of the existence of CpG islands, and were enriched in
H3K4me3. In contrast, peak promoters had little alignment of theH3 pattern, regardless of the presence of CpG islands. The
proportion of nucleosomes containing H3K4me3 associated withpeak promoters was lower than that associated with broad
promoters, particularly in the absence of CpG islands.

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that the set of “peak promoters” used in this study may
have included “broad promoters,” and that this may
have affected the highly aligned nature of H3K4me3
around “peak promoters.” This was because the definition of promoter architecture thus far was whether
there was a cluster of TSSs located within a narrowgenomic region or whether the TSSs were dispersed,
and low TSS coverage increased the possibility of promoters being classified as “peak promoters”.)
In contrast, when we focused only on promoters without CpG islands, nucleosomes having H3K4me3 were
well aligned and enriched only around broad promoters(Figure 4B); the difference in the frequencies of downstream nucleosomes (from +100 to 130) potentiallyresulting from the difference in the alignment were significant (P < 1.0 × 10-56, chi-squared test). Broad promoters with CpG islands had an aligned pattern of
nucleosomes carrying H3, whereas no clear alignment
was observed for peak promoters (Figure 4C). Broad
promoters without CpG islands still showed an aligned
pattern of nucleosomes having H3 (although the pattern
was less clear than in those with CpG islands), whereas
peak promoters had little alignment in the pattern (Figure 4D). These results show that the enrichment of
nucleosomes having certain histones around a broad
promoter is independent of the existence of CpG
islands.
Effect of histone modification on gene expression

To explore whether histone modification around thepromoter affects gene expression, we analyzed the difference in expression levels of RNAs transcribed frompeak and broad promoters in terms of the existence ofmodified/unmodified histones in their surrounding
regions. We compared data sets of methylated/unmethylated histones and acetylated/unacetylated histones measured under resting conditions in human CD4+ T cells[3,5]. Gene expression data for resting CD4+ T cells
were obtained from a previous study [4]; we used only
those genes for which the expression levels had beenmeasured. We classified promoters having at least one
methylated/acetylated histone within the region from-500 to +500 as “promoters with methylated/acetylated
histones” and all others as ones with unmethylated/
unacetylated histones (see Methods). Expression levelsof genes ‘associated with broad promoters that had
methylated histones were significantly higher than thoseof genes associated with broad promoters withunmethylated histones (P < 9.1 × 10-11, U-test; Figure5). Conversely, the expression levels of genes associatedwith peak promoters having only unmethylated histones
were as high as those of genes associated with peak promoters with methylated histones, and thus no significant
difference was observed (P = 0.97, U-test; Figure 5).

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Figure 5 Box plots of gene expression in human resting CD4+
T cells. The box plots represent the distributions of gene expression
levels. Distributions of the four groups of genes are drawn
separately, i.e. those with broad or peak promoters, each of which
was further associated with modified histones in activated cells orwith unmodified histones. The y-axis shows the microarray
intensities of the gene sets in each category.

Likewise, in the comparison between acetylated andunacetylated histones, the expression levels of genes
associated with broad promoters that had acetylated histones were significantly higher than those of genes associated with broad promoters with no acetylated histones(P < 2.2 × 10-16, U-test; Figure 5), but the expression
levels of genes associated with peak promoters that had
acetylated histones did not differ markedly from thoseof genes associated with peak promoters with only unacetylated histones (P = 0.69, U-test; Figure 5). These
results suggest that the regulation of gene expression
levels by histone modification is specific to broad promoter-associated genes.

Discussion
We analyzed the global landscape of epigenetic relationships between histone modifications and transcription
initiation by investigating genome-wide ChIP-Seq data
and DeepCAGE data. The results presented here show
differences in the architecture of the broad and peakpromoters that regulate gene expression. Especially, we
revealed that the broad promoters were strongly associated with histones immediately downstream of the
TSS and they were frequently modified, presumably toregulate gene expression levels.
In previous studies, aligned patterns of nucleosome
positions around TSSs have been identified in yeasts
and humans [22,31,32,41]. However, we confirmed thisalignment only for regions around TSSs derived frombroad promoters, not for those around TSSs derived
from peak promoters. Broad promoters have an aligned
pattern of nucleosome positions around TSSs and havelarge nucleosome-free regions immediately upstream of
TSSs. Studies in yeasts have validated the model ofPage 6 of 10“open promoters,” which have large, nucleosome-free
regions immediately upstream of the TSS and are often
associated with TATA-less promoters and poly (dA:dT)rich tracts, the sequences of which are unbendable andunstable for histone binding [42]. The broad promoter
characteristics that we found in humans are consistent
with this model, because in humans the sequence patterns in CpG islands located upstream of TSSs, in contrast to the yeast poly (dA:dT)-rich tracts, have beenshown to be unstable [31].
Our data indicate that the nucleosomes that are
immediately downstream of TSSs and associated withbroad promoters are positioned in specific regions. We
suggest that broad promoters have these aligned patterns of nucleosome positions around TSSs because thenucleosome position has a stronger impact on broad
promotors than on peak promoters on the determination of TSSs by transcription factors in the cell.
As an example of transcription factors that target
broad promoters, we investigated the Sp1 binding sitesaround TSSs. Sp1 recognizes binding region of DNA via
its zinc finger domain whereas TBP recognizes TATAbox via its DNA binding domain. Sp1 binding sites wereenriched in the regions upstream of TSSs corresponding
to the nucleosome-free regions. We observed similartendencies for the binding sites of two transcription factors, PU.1 and MAZ. Although biological experiments
are necessary to investigate molecular mechanism
behind this observation, we speculate that the nucleosome-free regions serve as “landing sites” for transcription factors, including Sp1, which have less precise
binding motifs (which are overrepresented among broad
promoters) than the TATA box [43-45].
In addition to histone H3, we also analyzed the positions of the histone H2A variant H2A.Z, which isenriched around TSSs [46], and we obtained similar
results. In contrast, peak promoters did not have aligned
patterns of nucleosome positions. One might suspectthat the observation is due to high expression of genes
associated with broad promoters, and low expression of
those associated with peak promoters. However evenafter we limited the analysis to broad and peak promoters both of which are associated with highly expressed
genes, we still observed the preferences of H3 for broad
promoters (region 100-130 bp with respect to TSSs)
compared to peak promoters (P < 1.0 × 10 -9 , chisquared test, data not shown). Although TSSs for TATA
promoters are often fixed to single positions, our results
suggest that such strictly controlled positions of TSSs
are not regulated by nucleosome position. However,there is some evidence that the nucleosomes around
TATA promoters have regulatory roles in gene expression. In yeasts, the TATA promoter is one type of “covered promoter,” and expression of the genes associatedNozaki et al. BMC Genomics 2011, 12:416
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with such promoters is more likely to be inhibited by
the presence of nucleosomes than expression of thegenes associated with “open promoters,” which arelocated in nucleosome-free regions [42]; in covered promoters, nucleosomes often cover transcription factor
binding sites to repress the expression of downstream
genes. It is also possible that, in humans, peak promoters associated with the TATA box belong to one typeof “covered promoter” where the expression of downstream genes is repressed by the presence of nucleosomes. Therefore, we speculate that transcription factor
binding is controlled by nucleosome position in the caseof peak promoters.
In our analysis of epigenetic control by histone modification, we uncovered an difference between broad andpeak promoters. H3K4me1, -2, and -3 and H3K9ac,
which are associated with gene activation, were more
highly enriched around TSSs associated with broad promoters than around those associated with peak promoters. Thus broad promoters appeared to be understronger epigenetic control than peak promoters. We
found a trend that further supported this hypothesis: theexpression levels of genes associated with broad promoters that had modified histones had higher expression
levels than genes associated with broad promoters without modified histones. In contrast, peak promotersappeared to be under weaker epigenetic control, because
far fewer of them harbored modified histones. Furthermore, there were no significant differences in theexpression levels of genes associated with peak promoters that harbored or did not harbor modified histones.
It has been shown that promoters with many CpG
islands are more likely to harbor modified histones thanpromoters with fewer CpG islands [40]. However, evenafter we limited our analysis to promoters having CpG
islands, number of broad promoters harboring
H3K4me3 was still statistically higher than that of peakpromoters. Even more remarkable differences wereobserved after we limited our analysis to promoters
without CpG islands. Although these results may
depend on the dataset of CpG islands we used, enrichment of H3K4me3 in downstream region (+100 to+130-bp) of broad promoters were still observed in theanalysis using different dataset of CpG islands [47] (Pvalue of < 1.0 × 10-20 for CpG-related genes, P value of< 1.0 × 10-30 for CpG-unrelated genes).
Genes associated with broad promoters tend to be
expressed ubiquitously, whereas those associated withpeak promoters are likely to be expressed in specific tissues and may show low expression levels in most tissue
types [8]. Therefore, if high levels of gene expression are
directly associated with histone modifications around
TSSs, then we may observe spurious correlations
between promoter type and histone modification. In

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fact, H3K4me3 is known to upregulate the expression ofdownstream genes. We therefore compared the distribution patterns of nucleosomes containing H3K4me3
around broad and peak promoters in cases where thedownstream genes showed similar expression levels(Additional file 4, Figure S4). We found that the broad
promoters also harbored more nucleosomes containing
H3K4me3 in cases where the downstream genes showedsimilar expression levels (data not shown); the differencein the distributions of H3K4me3 around the broad andpeak promoters was statistically significant (all positions
from +100 to +130 showed significant differences; P <1.0 × 10-3, chi-squared test), suggesting that promoter
type was indeed associated with differences in epigenetic
regulation by histone modifications.
Peak promoters containing the TATA box are regulated at their transcription initiation step, generally by
the assembly of a pre-initiation complex with three
additional components: the TATA-associated factors,
the so-called mediator complexes, and positive andnegative cofactors. We presume that peak promoters
containing no TATA box are regulated in a similar way.
This transcription system is widely used in various species, and our results suggest that it is unlikely to use
epigenetic controls. Thus, broad and peak promoters
have distinct systems to regulate gene expression.
Throughout this work, we employed widely-accepted
definition of peak promoters, i.e. those which initiate
transcription within the range of 4 bps. Changing thisthreshold to 10 bp did not have much effect on the distribution patterns of nucleosomes around broad andpeak promoters as shown by Pearson’s correlation coefficients between histone distribution pattern aroundbroad promoters (-5000 to 5000 bps with respect toTSS) defined by > 4 bps threshold and that defined by >10 bps threshold. For H3 distribution patterns, correlation coefficients were 0.99 and 0.94 for broad and peakpromoters, respectively. For H3K4me3 distribution patterns, the correlation coefficients were 0.99 for both
broad and peak promoters. These results suggest therobustness of the relationships between the imprecisionof TSS and patterns of histone distributions.
TATA boxes are used in a wide range of organisms,
including prokaryotes, and are thought to be part of anancient transcriptional system. In contrast, broad promoters are thought to be newly evolved [8] and haveincorporated histone modification systems. Our results
showed that peak promoters, which are frequently associated with such ancient TATA boxes, have not incorporated histone modification systems.

Conclusions
By using a computational approach, we discovered thegeneral relationships between the two types of promoter

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architecture and histone behavior, including positioning
and modification. We first showed that the positions ofhistones around broad promoters were highly aligned
and stable compared with those around peak promoters.
Furthermore, we suggest that marked numbers of transcription initiations related to broad promoters areunder the control of histone methylation and acetylation
and are associated with gene expression level, whereas
this is not the case with peak promoters. These results
indicate that the expression of genes associated withbroad promoters, but not peak promoters, is highly
associated with histone position and modification. We
believe that our study is a step in uncovering the generalmechanisms underlying transcriptional systems andinferring how these systems have evolved. This should
eventually help us to understand the complexity of
mammalian transcription.

Page 8 of 10

respect to TSSs were calculated by dividing the numberof nucleosomes at each position by the number of TSSs.
Genomic positions from -15 bp to 15 bp with respect tothe central positions of the nucleosomes were assumed
as the genomic positions where nucleosomes existed.
The distributions of nucleosomes near broad and peakpromoters were calculated separately.
Distribution of Sp1 binding sites and other transcription
factor binding sites

Sp1, MAZ, and PU.1 binding sites were obtained fromFANTOM 4 (http://fantom.gsc.riken.jp/4/download/
GenomeBrowser/hg18/TFBS_CAGE/allsites_cage_tfbs_feb09_latest.gff.gz) [1]. The distributions of these transcription factor binding sites around TSSs (from -500
bp to 500 bp) were calculated by dividing the number ofthese sites for each position by the number of TSSs used
for the analysis.

Methods
Nucleosome position detection and dataset

Nucleosome-resolution (MNase digestion) ChIP-Seq
Solexa tags for histone H3 were obtained by [4]. The
genomic positions of the methylated histones and thehistone variant H2A.Z were obtained from [3], andthose of acetylated histones were from the study by [5].
All of these data were obtained in human resting CD4+
T cells. To determine the genomic positions of nucleosomes according to the ChIP-Seq data, we used the software published in [48]. Human genome hg18 was used.
Transcription start site detection and dataset

TSSs were detected by DeepCAGE data obtained by the
FANTOM 4 project [1]; 10,971 TSSs of broad promoters and 3621 TSSs of peak promoters were detected byapplying the methods used in FANTOM 3 [8,9] to the
FANTOM 4 dataset [9]. We used only those promotersfor which the corresponding probes were clustered on
the genome (level 3 promoters; [1,9]), and for each promoter the neighboring position that had the highest
density of overlapping CAGE tags was determined as
the position of the TSS. Promoters containing TATA
boxes within 50 bp upstream of TSSs were determinedby using position-specific weight matrices from JASPAR4 [49] (with a confidence score of more than 75%),
and promoters containing CpG islands within 200 bp
upstream of TSSs were obtained from the UCSC Genome Browser database (http://genome.ucsc.edu/). Alternative dataset of CpG islands were obtained from [47].
Distribution of nucleosome positions around TSSs

As described above, the genomic positions of nucleosomes as well as TSSs for both broad and peak promoters were determined. The distributions of nucleosomes
within the genomic regions from -5 kb to 5 kb with

Stability of nucleosome positions under different cellularconditions

We compared the nucleosome positions obtained inhuman resting CD4+ T cells with those obtained inhuman activated CD4+ T cells. We calculated the minimum distance between each nucleosome in resting T
cells and the closest nucleosome in activated cells. Thisdistance was considered to denote how far each nucleosome moved along the genome in response to thechange in cellular condition (from resting to activated).
The distributions of these distances were calculated by
dividing the number of nucleosomes that moved specified distances (from × bp to × + 15 bp) by the total
number of nucleosomes. The average absolute minimum
distance between each nucleosome in resting T cells andthe closest nucleosome in activated cells was also
calculated.
Relative abundances of peak promoters and broad
promoters

The abundance of peak promoters relative to that ofbroad promoters at position j was calculated by (Bj P j )/Σ i B i , where B j and P j denote the proportions of
nucleosomes at position j for broad and peak promoters,and ΣiBi denotes the sum of proportions of nucleosomesaround the TSS (from -2000 bp to 2000 bp),
respectively.
Gene expression in human resting CD4+ T cells

The gene expression profile in human resting CD4+ T
cells was obtained from the Gene Expression Omnibus(GSE10437) [4]. We used genes (total number 8007,
with 7591 associated with broad promoters and 416
associated with peak promoters) annotated with Entrez
gene IDs in FANTOM 4 and with expression present inNozaki et al. BMC Genomics 2011, 12:416
http://www.biomedcentral.com/1471-2164/12/416

Present/Absent calls generated by the Affymetrix microarray platform. Nineteen types of methylated histones
and 18 types of acetylated histones obtained in CD4+ T
cells were used [3,5]. Acetylated histones located around
TSSs are linked only to gene activation. To investigate
the upregulation of genes associated with histone acetylation and their dependence on promoter type, we madetwo groups of histones: one having modified histones(18 types of acetylated histone) around TSSs (from -500
bp to 500 bp) and the other having no modified histones. In contrast to acetylated histones, methylated histones located around TSSs are linked to both geneactivation and repression (see Background). Furthermore, the functions of many methylated histones arestill unknown. Therefore, for histone methylation, we
made the following two groups, one having H3K4me1,-2 or -3, which are known to upregulate downstream
genes, and the other having no modified histones. Distributions of gene expression levels were represented asbox plots. P values for evaluating the significance ofgene expression changes were calculated by the Wilcoxon rank sum test.
To compare the distributions of nucleosomes that had
H3K4me3, were located upstream of TSSs (positions
from -150 to -100 bp), and were associated with either
broad promoters or peak promoters in cases where thedownstream genes showed similar expression levels, weselected 1788 genes associated with broad promotersand 138 associated with peak promoters that had
expression levels in the range of 250 to 750 (Additional
File 4: Figure S4). The chi-squared test was applied toassess the difference in nucleosome distribution between
these two types of promoter.

Additional material
Additional file 1: Supplemental figure 1. Figure S1. Frequencies ofoccurrence of TATA boxes and CpG islands around transcription startsites (TSSs). Frequencies of the characteristic sequence patterns
associated with promoters are shown by bar charts. The y-axis shows the
proportions of broad and peak promoters that have TATA boxes (A) and
CpG islands (B).
Additional file 2: Supplemental figure 2. Figure S2. Distributions ofSp1 sites around transcription start sites (TSSs). Distributions of
nucleosome regions and Sp1 sites around TSSs associated with broad (A)and peak (B) promoters are shown. Nucleosome position is defined as
the center position of the nucleosome. The x-axis shows genomic
positions with respect to TSSs (from -500 bp to 500 bp). Sp-1 sites wereobtained by the FANTOM 4 project.
Additional file 3: Supplemental figure 3. Figure S3. Distributions of thebinding sites of two transcription factors (MAZ and PU.1) aroundtranscription start sites (TSSs). Distributions of nucleosome regions andtranscription factor binding sites around TSSs associated with broad (A:MAZ, C: PU.1) and peak (B: MAZ, D: PU.1) promoters are shown.
Nucleosome position is defined as the center position of thenucleosome. The x-axis shows genomic positions with respect to TSSs
(from -500 bp to 500 bp). Both MAZ and PU.1 sites were obtained by
the FANTOM 4 project.

Page 9 of 10

Additional file 4: Supplemental figure 4. Figure S4. Distributions ofexpression levels of genes selected for comparison of broad and peakpromoters associated with similar downstream gene expression. The box
plots represent the distributions of the microarray intensities of the genesets that were selected from among those associated with broad andpeak promoters and that had similar expression levels (from 250 to 750).

Acknowledgements
This research was supported by research funds from the Yamagata
Prefectural Government and Tsuruoka City, Japan, and by a Grant-in-Aid
from the Japan Society for the Promotion of Science (JSPS) to NY (grant no.
1924).
Author details
Institute for Advanced Biosciences, Keio University, Tsuruoka, 997-0017,
Japan. 2Systems Biology Program, Department of Environment andInformation Studies, Keio University, Fujisawa, 252-8520, Japan. 3Departmentof Biological Chemistry and Molecular Pharmacology, Harvard Medical
School, Boston, MA 02445, USA. 4Systems Biology Program, Graduate Schoolof Media and Governance, Keio University, Fujisawa, 252-8520, Japan.
5
Systems Biology Program, Department of Environment and Information
Studies, Keio University, Fujisawa, Kanagawa 252-8520, Japan. 6Donnelly
Centre of Cellular and Biomolecular Research, University of Toronto, Toronto,
ON M5S-3E1, Canada. 7Department of Medicine, University of California, San
Diego, La Jolla, CA 92093, USA. 8Omics Science Center, RIKEN Yokohama
Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045
Japan.
1

Authors’ contributions
TN performed all computational analyses. TN, NY, and RO designed thestudy and helped with the computational analyses. AK provided some data.
RS supervised the research and helped to interpret the data. MT supervised
the study. TN, NY, and RS wrote the paper. All authors read and approved
the final manuscript.
Received: 21 December 2010 Accepted: 17 August 2011
Published: 17 August 2011
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doi:10.1186/1471-2164-12-416
Cite this article as: Nozaki et al.: Tight associations between
transcription promoter type and epigenetic variation in histone
positioning and modification. BMC Genomics 2011 12:416.