Molecular Cell
Resource
A Comprehensive Genomic Binding Map of Gene
and Chromatin Regulatory Proteins in Saccharomyces
Bryan J. Venters,1 Shinichiro Wachi,1 Travis N. Mavrich,1 Barbara E. Andersen,1 Peony Jena,1 Andrew J. Sinnamon,1
Priyanka Jain,1 Noah S. Rolleri,1 Cizhong Jiang,1,2 Christine Hemeryck-Walsh,1 and B. Franklin Pugh1,*
1Center for Eukaryotic Gene Regulation, Department of Biochemistry and Molecular Biology, The Pennsylvania State University,
University Park, PA 16802, USA
2Present address: The School of Life Sciences and Technology, Tongji University, Shanghai 200065, China
*Correspondence: bfp2@psu.edu
DOI 10.1016/j.molcel.2011.01.015
SUMMARY
Hundreds of different proteins regulate and implement transcription in Saccharomyces. Yet their
interrelationships have not been investigated on
a comprehensive scale. Here we determined the
genome-wide binding locations of 200 transcription-related proteins, under normal and acute heatshock conditions. This study distinguishes binding
between distal versus proximal promoter regions
as well as the 30 ends of genes for nearly all mRNA
and tRNA genes. This study reveals (1) a greater
diversity and specialization of regulation associated
with the SAGA transcription pathway compared to
the TFIID pathway, (2) new regulators enriched at
tRNA genes, (3) a global co-occupancy network
of >20,000 unique regulator combinations that show
a high degree of regulatory interconnections among
lowly expressed genes, (4) regulators of the SAGA
pathway located largely distal to the core promoter
and regulators of the TFIID pathway located proximally, and (5) distinct mobilization of SAGA- versus
TFIID-linked regulators during acute heat shock.
INTRODUCTION
Eukaryotic transcription is regulated by sequence-specific DNAbinding proteins, chromatin regulators, the general transcription
machinery, and elongation regulators (Berger, 2000; Li et al.,
2007a; Orphanides and Reinberg, 2002; Venters and Pugh,
2009b). Their collective function is to express a subset of genes
as dictated by a complex interplay of environmental signals that
is only partly understood. Here we report the genome-wide location profiles for 202 representative regulators from diverse
stages of transcription under standard conditions and during
acute heat stress.
Earlier studies had identified TAF (TFIID)-dependent and TAFindependent genes (Cheng et al., 2002; Kuras et al., 2000; Li
et al., 2000). Subsequent genome-wide studies found that
85%–90% of the yeast genome can be generally characterized
as being TFIID dominated (Basehoar et al., 2004; Huisinga and
Pugh, 2004), in which such genes are typically TATA-less and
utilize TFIID to assemble the transcription preinitiation complex
(PIC). The remaining 10%–15% are SAGA dominated. Such
genes typically contain a TATA box and preferentially utilize
SAGA rather than TFIID to assemble the transcription machinery.
Stress-induced genes tend to reside in the SAGA-dominated
class, and are more highly regulated. TFIID-dominated genes
tend to be housekeeping genes, many of which are downregulated in response to stress. Inasmuch as a gene may be involved
to varying degrees in both stress and housekeeping responses,
differing blends of the two pathways may be used, rather than
one or the other exclusively.
Early studies on the genome-wide location of 100 sequencespecific transcription regulators and their redistribution in
response to stress have provided insight into gene regulatory
networks (Harbison et al., 2004; Lee et al., 2002). Yet, such regulators represent only part of the transcription control system. We
therefore expanded on these earlier studies to include proteins
representing nearly all known complexes that regulate chromatin, transcription initiation, and transcription elongation.
We analyzed essentially all mRNA and tRNA genes, interrogated by ChIP-chip with probes placed at distal and proximal
regions of the promoter, and near the 30 ends of genes. In
total, >800 ChIP-chip experiments were conducted, resulting
in 15 million ChIP measurements. Inasmuch as many proteins
involved in transcription elongation may reside in the body of
genes, we further examined 20 of these proteins by ChIP-seq,
which allow an unbiased evaluation of their genomic binding
locations. From this study, a more comprehensive picture of
the genome-wide regulatory organization of the genome and
its plasticity upon reprogramming was attained. This study
may be a useful resource for identifying coregulatory partners
in yeast, and orthologous interactions in other organisms.
RESULTS
Using Gene Ontology classifications, we identified nearly 400
proteins that potentially regulate transcription. From this list,
we categorized proteins according to what protein complex
and what stage of the transcription cycle they likely belong.
For this purpose, we divided the transcription cycle into four
stages (Figure 1A and see Table S1 available online): (1) ‘‘orchestration,’’ representing sequence-specific transcriptional activators and repressors; (2) ‘‘access,’’ including histones and
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Figure 1. Scope and Data Display of Genome-wide
Location Analysis
(A) Illustration of the chromatin context of a stereotype
promoter. The pie chart depicts the number of regulators
analyzed from each stage, out of the total number of
potential regulators in those stages (demarcated by
dashed lines). Those not covered largely resided within
complexes that contain regulators that were covered.
(B) Approximate positions of microarray 60-mer probes
relative to a gene (arrow). Negative control probes were
present at 300 intergenic regions between two convergently transcribed genes.
(C) Browser display of the occupancy and change in occupancy upon heat shock at the indicated probe locations
(pointed bullets), for a selected number of regulators.
The upper and lower probe tracks for each regulator
reflect occupancy levels at 25 C (grayscale) and changes
in occupancy during heat shock (red/green scale), respectively. Any region for the 200 regulators can be queried at
http://atlas.bx.psu.edu/.
chromatin regulators; (3) ‘‘initiation,’’ representing the general
transcription factors and their regulators; and (4) ‘‘elongation,’’
including RNA polymerase (Pol) II and regulators of transcription
elongation and termination.
Occupancy levels were examined at 20,000 locations
across the yeast genome, primarily at canonical locations where
upstream activating sequences (UAS), transcriptional start sites
(TSSs), and the 30 ends of open reading frames (ORFs) reside
(Figure 1B). Two probes were also located 30 and 290 bp
upstream of the annotated tRNA transcription start sites.
Several hundred negative control probes were placed between
two convergently transcribed genes for the purpose of centering
the bulk data. Controls and validation of the accuracy and
resolution of these arrays were described elsewhere (Venters
and Pugh, 2009a). Importantly, the prior study demonstrated
that the probes allow for interrogation of entire promoter regions
with mapping uncertainties of ±40 bp. Thus, binding to UAS
regions can be distinguished from core promoter regions, and
promoter regions can be distinguished from the 30 ends of
genes.
Occupancy levels reflect log2 fold over background (hybridization signal of TAP-tagged
regulator/hybridization signal for a set of
samples lacking a TAP tag) and are reported
for individual probes in Table S2 for cells grown
at 25 C, and in Table S3 for heat-shocked cells.
Each normalized log2 data set was centered
by subtracting the median value in 344 control
T-T regions, which represent intergenic regions
between convergently transcribed genes. Thus,
all values are relative to such regions. The occupancy level of each of the 200 regulators at
any gene can also be queried in a browser
format at http://atlas.bx.psu.edu/ (illustrated in
Figure 1C). Since a priori knowledge of where
a regulator binds within a promoter region (if at
all) was not known for all regulators, promoter
occupancy levels were taken to be the higher value at either
the UAS or TSS probes (reported in Table S4). Based on an error
model using an untagged control strain (Li et al., 2008), occupancy values meeting a 5% FDR cutoff were deemed to be
significant. A total of 338,704 protein-DNA interactions were
determined to be significant (231,704 at mRNA promoters,
99,216 at the 30 end of ORFs, and 7,783 at tRNA genes) for regulators (15% of all possible interactions).
More Diverse Regulation of SAGA-Dominated Genes
Than TFIID-Dominated Genes
Approximately 93% of the 5866 mRNA promoter regions had
significant occupancy of at least ten regulators (Figure 2A, which
includes histones), and 10% were significantly occupied by at
least 75 proteins. As only half of all proteins were examined, we
expect the actual number of bound proteins to be approximately
twice that. Based upon existing models on transcription initiation
it is reasonable to expect at least 75 (or 150) proteins occupying
a single promoter, since GTFs, Pol II, Mediator, and TFIID/SAGA
are commonly required for transcription, and they alone
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Figure 2. Promoter Occupancy at 25 C for Individual Genes and Groups of Genes
(A) Number of promoters or 30 ORFs significantly occupied (5% FDR) by the number of regulators indicated along the x axis.
(B) Regulators significantly bound at the indicated genes are shown as a heat map. Columns represent regulators. The color scale indicates the occupancy
percent rank for those meeting a 5% FDR cutoff. Regulators are grouped by stage. Only those regulators having potentially meaningful occupancy are shown.
(C) Regulator promoter occupancy for genes in the top tenth percentile of transcription frequency (Holstege et al., 1998) are shown, and filtered to be in one of the
three following classes: (1) RP genes, (2) TFIID-dominated and TATA-less but not RP genes, and (3) SAGA dominated and TATA containing (Basehoar et al., 2004;
Huisinga and Pugh, 2004). Potentially meaningful occupancy levels are displayed by transcription stage, with the fraction of each gene group occupied also
shown. The median values for each class of genes are shown to the right of each row.
contribute over half of the proteins. Activators, chromatin regulators, and elongation regulators, many of which are large multisubunit complexes, would make up the remaining. Indeed, a
putative gene of unknown function (YGR146C-A) had as many
as 145 proteins detected. An important caveat is that these location profiling experiments of cell populations do not distinguish
between regulators that simultaneously co-occupy a genomic
region from regulators that bind in a mutually exclusive manner
or at a different temporal order in the transcription cycle or cell
cycle.
Figure 2B displays a heat map representation that quantifies
the occupancy levels at selected genes. The number of bound
regulators varied widely from gene to gene. For example, two
highly transcribed genes from the glycolysis pathway, PGK1
and ADH1, contained 57 and 26 bound complexes (98 and 42
proteins), respectively. Two lowly transcribed genes, HO and
PHO5, had fewer regulators bound, and those regulators that
were bound had relatively low occupancy levels. Table S5 lists
a number of example genes and the complexes present at each.
To assess commonalities among similarly regulated genes,
we examined regulator occupancy at 124 highly active
(>14 mRNA/hr) ribosomal protein (RP) genes, which have highly
coordinated regulation and are TFIID dominated (Figure 2C and
Table S6). We also examined 190 of the most active TFIID-dominated/TATA-less genes excluding RP genes, and compared
them to the 41 most active SAGA-dominated/TATA-containing
genes (a transcription frequency cutoff of 14 mRNA/hr was
used for both groups). Similar trends were observed at other
data thresholds (data not shown). The percentage of those
genes meeting the 5% FDR threshold for significant occupancy
is shown in a heat map representation. In addition, the median
occupancy level of each regulator (as a percent rank of those
meeting the 5% FDR threshold) is indicated. Percent ranks,
which vary between 0 and 100, allowed occupancy to be
compared (albeit imperfectly) between regulators. Without this
scaling, occupancy levels vary widely between regulators due
to differences in ChIP efficiency.
More so than other TFIID-dominated/TATA-less genes, we
found a higher percentage of the RP genes occupied by the
sequence-specific regulators (orchestration group) Rap1, Ifh1,
and Sfp1, confirming previous reports (Marion et al., 2004; Rudra
et al., 2005; Yu et al., 2003). The RP genes were comparatively
depleted of the histone variant H2A.Z, along with the SWR1
complex, which is responsible for H2A.Z deposition.
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TFIIA, and certain Pol II regulators such as elongation factors
and Mediator, also tended toward the SAGA pathway. These
findings fit well with the notion that SAGA-dominated genes
tend to be highly regulated and are more tailored to responding
to different environmental cues than the housekeeping and less
variably regulated TFIID class (Basehoar et al., 2004; Huisinga
and Pugh, 2004; Tirosh and Barkai, 2008).
Table 1. Regulators that Are Biased toward Either the TFIID or
the SAGA Pathway
Orchestration
Access
Initiation
Elongation
DOT1
TFIID
ESS1
TFIID Pathway
RAP1
NuA4
SET2
SPT10,21
SWR1
SAGA Pathway
DIG1
Cohesin
Mediator
CCR4-NOT
FKH1
COMPASS
MOT1
PAF1
FKH2
Condensin
SAGA
SPT6
GCN4
HATB
TFIIA
THO
GCR1
Histone H1
GLN3
HOS1
LEU3
HOS2
SBF
HOS3
SKN7
ISW1b
STP1
JHDM1
UGA3
Nucleosome
URE2
RAD6/BRE1
WTM1
RPD3
WTM2
RSC
RTT109
SAS
SIG1
SNF1
TUP1
SWI/SNF
The fraction of SAGA-dominated and TFIID-dominated genes that were
significantly occupied by a regulator was determined (Huisinga and
Pugh, 2004) and a ratio between the two calculated. Regulators having
ratios >1.5 in one direction or the other were listed under the appropriate
pathway.
SAGA-dominated/TATA-containing genes were occupied by
a larger variety of regulators compared to TFIID-dominated/
TATA-less genes (Figure 2C, with values reported in Table S4).
The median value of the fraction of SAGA-dominated genes
occupied by each regulator was 24%, whereas for TFIID-dominated genes the median value was 18%. Moreover, SAGA-dominated genes tended to have higher occupancy levels of bound
regulators (12% higher, as a percent rank, than for TFIID-dominated genes).
Table 1 summarizes whether a regulator preferentially occupied active genes dominated by either the SAGA or TFIID
pathway. For example, the NuA4 histone acetyltransferase,
and TFIID-specific TAFs, preferred the TFIID pathway, whereas
other chromatin remodeling and histone modification complexes
such as RSC, SWI/SNF, RAD6/BRE1, and RTT109 preferred the
SAGA pathway. TAFs shared between SAGA and TFIID (Taf5
and Taf10), and the core transcription machinery, displayed no
preference. However, certain TBP regulators such as Mot1 and
Potential Regulatory Crosstalk in Pol II and III
Transcription
In Saccharomyces, the Pol III transcription machinery transcribes 274 tRNA genes (Dieci et al., 2007). TFIIIC binds within
each gene, immediately downstream of the TSS, and then
recruits the TBP-containing TFIIIB complex just upstream of
the TSS, which then recruits Pol III to the TSS. The core Pol III
transcription machinery is largely distinct from that involved in
Pol II regulation. Recent reports have found some unexpected
regulators at tRNA genes, such as TFIIS and Nhp6a (Braglia
et al., 2007; Ghavi-Helm et al., 2008). This led us to consider
other regulators that may bind to tRNA genes, and so we
screened the 202 data sets for regulators that occupy tRNA
genes at 25 C (Figure 3A).
In addition to the known Pol III transcription machinery (Figure 3B), a number of Pol II regulators stood out as having significant occupancy at tRNA genes (Figure 3C). The binding sites for
these regulators were enriched upstream of tRNA start sites
(Figure 3D), and include Fkh1, Reb1, and Yap6. Most of these
regulators were also enriched at the RP genes. Their presence
at genes that encode protein and RNA structural components
of the translation machinery might provide a cross-polymerase
mechanism to coordinate translation through the synthesis of
ribosomes and tRNAs. Histone deacetylase Hda1 was also
enriched at tRNA genes (Figure 3E). Inasmuch as tRNA genes
can exert a negative transcriptional effect on adjacent Pol II
genes (Hull et al., 1994), deacetylation by Hda1 might generate
hypoacetylated regions adjacent to tRNA genes, making them
refractory to Pol II transcription. Figure 3F illustrates a composite
view regarding tRNA transcription regulator assembly for the
regulators examined. An important caveat of this composite is
that the indicated Pol II regulators may only occupy a small but
statistically enriched subset of tRNA genes.
Functionally Related Regulators Tend to Work
at the Same Genes
The analysis thus far indicates a preference of some regulatory
complexes for distinct PIC assembly pathways. We next
address which regulators might be functionally linked to each
other by determining their co-occupancy at genes. If the set of
regulator-bound genes is defined by a circle, then regulator
co-occupancy is defined by the overlap of two circles in
a Venn diagram. Figure 4A tabulates the results of >40,000
Venn diagrams (see Figure S1 for a high-resolution version of
Figure 4), where the magnitude of percentage overlap is represented as a heat map color-coded pixel (numerical values are
presented in Table S7). Each Venn pair is reported as two reciprocal pixels in a 202 3 202 matrix, reflecting the percentage
overlap with respect to the two individual data sets. For example,
26% of all genes bound by Reb1 were also bound by Sua7.
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Figure 3. Regulators that Occupy tRNA Genes
(A) The median 25 C occupancy for 202 regulators was computed for 274 tRNA genes and displayed as a bar graph. The vast majority of tRNA promoters
are >200 bp from a Pol II promoter, and thus would not erroneously pick up signal from nearby genes. Such adjacent genes are also not enriched with these
regulators (data not shown).
(B and C) Bar graph showing the occupancy level of the Pol III transcription machinery and other high-occupancy regulators at tRNA genes.
(D) Frequency distribution plot for the motifs of the three sequence-specific regulator occupying tRNA genes.
(E) Hda1 frequency distribution plot for its interpolated binding location is shown along with nucleosome density (Mavrich et al., 2008) shown in gray fill.
(F) Illustration depicting a composite organization of regulators at tRNA genes. Only the TFIIIB, TFIIIC, and Pol III are like to be present at all genes, with the
remaining at a statistically enriched subset.
However, only 13% of all genes bound by Sua7 were also bound
by Reb1. This matrix was then hierarchically clustered to reveal
regulators that tend to display similar patterns of co-occupancy.
Three clusters were examined further (denoted as a, b, and c in
Figure 4A). The significance of each overlap (p value) is reported
in corresponding pixels in Figure 4B. The median transcription
frequency for the same sets of genes is reported in Figure 4C.
If two co-occupying regulators belonged to the same stage of
the transcription cycle as illustrated in Figure 1A, then the corresponding pixel was color-coded as shown in Figure 4D. The
purpose for this latter analysis was to assess whether stagerelated regulators (represented by clustered pixels) tended to
work at the same genes, or whether they were gene specific.
Cluster a was relatively small and consisted of general transcription regulators (GTFs, in the initiation class) and Pol II
subunits, and as expected, the overlapping sets of genes had
high transcription frequencies (Figure 4C). Co-occupancy of
these regulators at a common set of genes was verified more
directly via standard gene-based clustering (Figure S2A). Other
components and regulators of the core transcription machinery
occupied many cluster a genes, but also occupied genes having
other bound regulators, causing them to cluster apart from the
core transcription machinery. The lack of a variety of regulators
at cluster a genes indicates that the genes which are most highly
occupied by GTFs and most highly transcribed may have fewer
regulatory interactions in common than at other genes. If many
positive and negative regulators function to antagonize each
other, this could result in a rich assortment of co-occupancy
that produces a lower net output of transcription. As such, genes
with high levels of PICs but few other regulators may represent
an ‘‘unattenuated,’’ and thus highly active, situation.
Cluster b was enriched with regulators in the access class
(Figure 4A), including chromatin remodelers, chromatin modifying regulators, and chromatin binding proteins. Interestingly,
in contrast to cluster a, cluster b tended to be lowly transcribed
(Figure 4C) and contained generally repressive chromatin
remodelers and histone deacetylases, such as Isw1a/b, Isw2,
Cyc8/Ssn6, Hos1, and Hda1 (Figure 4D). The Xbp1 and Rfx1/
Crt1 sequence-specific repressors were also enriched in cluster
b, suggesting that they may be functionally linked to these
chromatin regulators. Thus, many chromatin regulators tend to
occupy the same set of lowly expressed genes (also verified
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Figure 4. Regulator Co-occupancy Matrices
Shown are promoter co-occupancies and other related properties between 20,301 unique combinations of 202 regulator pairs.
(A) Percent overlap for the set of genes co-occupied by each regulator pair is displayed as a heat map. Each pixel represents the overlap in a Venn diagram
between two regulators, and the heat map is color-coded in accord with the extent of overlap, as indicated. Overlaps that did not meet a significance threshold
of p < 105, or represented a self-by-self comparison, were drawn as white pixels. Rows and columns were hierarchically clustered using Cluster (Eisen et al.,
1998). See Figure S1 for high-resolution images. A blowup of a portion of cluster a (8 3 8 matrix) is shown in the upper portion of the panel.
(B) Statistical significance (p value determined by the chi-test) of overlap for the set of genes co-occupied by each regulator pair is displayed as a heat map.
For (B)–(D), pixels are in the same position as in (A) and were colored white if they were white in (A).
(C) The corresponding median transcription frequency for the set of genes co-occupied by each regulator pair is displayed as a heat map. Data for mRNA/hr are
from Holstege et al. (1998).
(D) If two compared regulators belonged to the same stage of the transcription cycle (Figure 1A), then the corresponding pixel was color coded by the stage, as
indicated. Otherwise they were colored white.
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by gene-based clustering in Figure S2B). The expression of such
genes might be rate limited by the combined repressive action of
these chromatin regulators. We observed a substantial intersection of the regulators in clusters a and b, and such genes tended
to have an intermediate level of transcription (Figures 4A and 4C).
We interpret this overlap to mean that many genes may have
both repressive and activating proteins bound, although not
temporally resolved, with the net output being an intermediate
level of transcription.
Cluster c had a large membership of regulators from all stages
of the transcription cycle (Figure 4D), and the corresponding
genes tended to be lowly expressed (Figure 4C). We interpret
the large cluster size to reflect a tendency of a large number of
positive and negative regulators at all stages of the transcription
cycle to work at many of the same genes, to produce a relatively
low transcriptional output. This contrasts to cluster a, where
apparently unbridled PICs produce high transcriptional outputs.
The co-occupancy data are displayed as a cytoscape network
in Figure S3A (Shannon et al., 2003) and those with stronger
co-occupancies in Figure S3B. Many of the sequence-specific
regulators (‘‘orchestration’’ class shown in red) were located
toward the periphery of the network, which likely reflects their
gene-selective behavior, and thus had less overlap with other
regulators. Ume6, Hho1, and Asf1 stood out as having a high
degree of co-occupancy, and this was verified by standard
gene-based clustering (Figure S3C, cluster 2). Ume6 is a key
regulator of early meiotic genes by repressing transcription
during vegetative growth (Strich et al., 1994). Asf1 is involved
in chromatin assembly/disassembly during DNA replication
and transcription (Schwabish and Struhl, 2006; Tyler et al.,
1999). The presence of Asf1 at Ume6-repressed genes is consistent with the role of Asf1 in establishing silenced chromatin
(Krawitz et al., 2002), perhaps in helping assemble the repressive
linker histone H1 (Hho1).
Further exploration of the occupancy data is presented in Figure S4 and Table S7, wherein we report on the overlapping
membership (measured as –log10 p value) between regulatoroccupied genes and genes that are in the upper or lower tenth
percentile of a measured genome-wide property available in
the public domain (e.g., expression changes in mutants, motif
enrichment, and regulator occupancy levels). Over 2300 relationships are presented for each regulator. The data set provides
a rich resource of empirical information about a regulator that
is essentially untapped here.
Spatially Distinct Promoter Organization of Regulators
Associated with the SAGA and TFIID Pathways
Understanding how the diverse repertoire of transcription regulators is organized in promoter regions can provide insight into
the interplay of the transcription machinery and chromatin.
Thus with microarray probes situated at the distal (‘‘UAS’’) and
proximal (‘‘TSS’’) ends of each promoter (230 bp center-tocenter distance), we interpolated the location of each significantly bound regulator, based upon an occupancy level weighting of each probe location (see the Experimental Procedures).
The distributions of all bound locations relative to the nearest
TSS were then plotted for each regulator as a heat map (Figure 5A and Table S8). The upper panel provides a summary list
of those complexes that bind the distal versus core promoter
region. Regulatory proteins appeared to separate out into
distal and proximal promoter binding, with the dividing line
around 120 relative to the TSS. Inasmuch as high-density
ChIP-chip microarrays produced similar genome-wide maps
as the low-density arrays described here (Figure S5), it is likely
that the distal and proximal occupancy domains were not an artifact of the microarray platform. As further support, a previous
study using site-specific DNA cleavage probes tethered to the
HIS4 promoter qualitatively agrees with the interpolated distribution profiles for Pol II and the GTFs (Miller and Hahn, 2006).
Nonetheless, there are caveats. A regulator might not have a
consensus location that resides between the two probes, or a
regulator may not have any consensus location (relative to the
TSS). In addition, patterns may be biased to reflect the most
highly occupied locations.
Complexes favoring the SAGA pathway (Table 1 and Figure 5)
tended to reside in the distal promoter region where SAGA
resides. For example, Mot1, Mediator, Histone H1, HOS1, RPD3,
SSN6-TUP1, and SWI/SNF preferentially occupied the upstream
promoter region. The SAGA pathway involves substantial
chromatin regulation. Nearly three-quarters of the chromatin
regulators (29 of 41 complexes) we examined tended to occupy
the region closer to where the 1 nucleosome resides rather
than where the +1 nucleosome resides, which implicates
substantial regulation of the 1 nucleosome. In contrast,
NuA4, SWR1, and SPT10,21, which are more enriched at
TFIID-dominated genes, tended to reside at core promoter along
with TFIID or in the adjacent downstream region near the +1
nucleosome. Taken together, the spatial arrangement of SAGA
versus TFIID suggests that these complementary PIC assembly
pathways may have distinct spatial organizations at promoters.
Since the caveats associated with location mapping in
promoter regions may be particularly problematic with elongation regulators, we mapped the locations for 20 regulators in
the elongation class by ChIP-seq (Figure 5C and Figure S6).
Pol II and the Pop2 subunit of CCR4-NOT were enriched across
the promoter. Ess1, which is a prolyl isomerase that acts on the
Pol II C-terminal heptad repeat, and Bye1, which has genetic
interactions with Ess1 (Wu et al., 2003), were enriched within
100 bp of the TSS, suggesting that they might enter the elongation complex at the promoter region. Most other complexes,
including components of the CCR-NOT, PAF, CTK1, and FACT
complexes, were enriched from 200 to 600 bp downstream of
the TSS, possibly reflecting entry into the elongation complex
as Pol II transitions from a serine 5 phosphorylated state to serine
2 phosphorylation. These results are in line with related studies
reported elsewhere (Mayer et al., 2010; Rahl et al., 2010).
Some of these regulators were also detected in the promoter
region, which could reflect lower levels of interactions or fewer
genes having those interactions.
Mobilization of the Transcription Machinery
in Response to Acute Heat Shock Differs in the SAGA
versus TFIID Pathways
In yeast, the common environmental stress response, including
the heat-shock response (abrupt change from 25 C to 37 C), involves transient downregulation of 600 genes and upregulation
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Figure 5. Composite Distribution of Regulators across Promoter Regions
(A) Complexes particularly enriched in the distal (more 50 to 120 bp) versus proximal (more 30 to 120 bp) promoter region based on (B) are listed. The consensus
locations for the TATA box, the ‘‘1’’ and ‘‘+1’’ nucleosomes are shown (Basehoar et al., 2004; Mavrich et al., 2008). The frequency distribution mode around the
TSS for individual subunits shown in (B) defined the consensus binding location for each complex. If two or more subunits were available for a complex, then the
modes for all subunits were averaged.
(B) In the heat map, the ChIP-chip binding locations for each regulator (one regulator per line) were interpolated between the UAS and TSS probe at each gene,
binned, and aligned by the TSS. Heat map color was used to indicate bin counts. Data were filtered to have at least 2-fold occupancy levels. The uppermost track
indicates the distribution of microarray probes.
(C) For elongation regulators, ChIP-seq data were used to generate a heat map display for the composite frequency distributions relative to the TSS. The ChIPseq data for each regulator were binned in 25 bp intervals and normalized to an untagged control. Log2 values were centered so that the lowest quartile value was
the same in all data sets. Genes with >2-fold normalized occupancy were plotted. See also Figures S5 and S6.
of 300 genes within 15 min of the stress (Causton et al.,
2001). While the promoter association and dissociation of a
number of regulators in response to heat shock have been determined (Harbison et al., 2004; Lee et al., 2004; Zanton and Pugh,
2004), no study has comprehensively examined the genome-
wide change in occupancy of the vast majority of regulatory
complexes.
Changes in occupancy upon heat shock were examined
at promoter regions and the 30 end of ORFs (rows in Figures
6A and 6B, respectively, and Table S9), and were K-means
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Figure 6. Assembly and Disassembly of the Transcription Machinery in Response to Heat Shock
Shown are log2 ratios of 37 C/25 C occupancy changes for promoter regions that increased (red), decreased (green), did not change (black), or did not have data
(black), the latter comprising <10% of the data. Rows representing promoter regions (A) were clustered alongside 30 ORF regions (B) by K-means (K = 8) and are
ordered identically in the two panels. The data were filtered to include promoters having >75% data present and >3-fold change in occupancy in at least seven
data sets, which resulted in 934 genes. Columns represent ChIP-chip data for a given regulator, and were clustered hierarchically by stage. For clarity, only
a subset of the 200 regulators are shown; the cluster of all regulators is shown in Figure S7. The changes in gene expression during heat shock are aligned to
the right (Zanton and Pugh, 2004). The average transcription rate at 25 C (Holstege et al., 1998) for each cluster is indicated on the right of the panel.
clustered into eight groups. Within each region, regulators
were separated by their classification into transcriptional stages
(Figure 1A). Within each stage, individual regulators (columns)
were hierarchically clustered. A list of complexes that increase/
decrease in occupancy at heat-shock-induced/-repressed
genes can be found in Table S10.
Two clusters of heat-shock-induced genes were evident.
Modestly induced genes (cluster 1 in Figure 6A) tended to preferentially accumulate TFIID, SWR1, and RSC, which may reflect
increased activity of housekeeping genes. Shifting cultures to
37 C actually increases growth rates, and this likely requires
increased activity of housekeeping genes. Accordingly, cluster
1 genes are moderately transcribed at 25 C (4 mRNA/hr, Figure 6A, far right panel). The most highly induced genes (cluster
2), which are enriched with SAGA-dominated stress-induced
genes, saw the largest increase in occupancy of regulators
such as SAGA, SWI/SNF, INO80, NuA4, Mediator, GTFs, NC2,
Cyc8/Tup1, Pol II, Iws1/Spt6, FACT, Pcf11, COMPASS, Rad6/
Bre1, and Set2. Some of these regulators act negatively, which
may reflect their involvement in quenching the transient heatshock response. In addition, heat-shock enrichment of the elongation regulatory complexes was most evident in the body of the
gene (Figure 6B), which is consistent with the role of these regulators in events that are linked to transcription elongation and
mRNA transport.
One group of genes (cluster 3) stood out because Pol II and
a variety of elongation and termination regulators (Iws1/Spt6,
FACT, Pcf11, Rtt103, Spt2, and Bye1) displayed a strong
increase in occupancy in the promoter region but not in the 30
ORF region. These genes were lowly transcribed at 25 C
(3 mRNA/hr) and remained unchanged during the heat-shock
response. Furthermore, the enrichment pattern for two negative
regulators of transcription elongation, Bye1 and Spt2 (Kruger
and Herskowitz, 1991; Roeder et al., 1985; Wu et al., 2003),
mirrored the Pol II pattern, suggesting that these regulators
may be involved in generating an elongation-refractory Pol II at
the 50 ends of these genes.
Cluster 4 stood out as having increased occupancy levels of
the GTFs and Pol II at the 30 end of the genes, but with little detectable RNA output. The basis for this needs to be further investigated, although it could reflect heat-shock-induced production
of unstable antisense transcription, as one potential example.
Occupancy changes at heat-shock-repressed genes (clusters
5–8) tended to involve many of the same regulators as seen at
induced genes, but in the opposite direction. However, the
repressed genes of cluster 5 also acquired the Xbp1 repressor,
three histone deacetylases (Rpd3, Hda1, and Hos1), the Jhd1
demethylase, and Isw1a/b in the promoter region. This cluster
was enriched with ribosome biosynthesis and rRNA maturation genes, and these genes are highly transcribed at 25 C
(85 mRNA/hr). Thus, the transient shutdown of ribosome biosynthesis that accompanies heat shock appears to be an active
shutdown by an influx of corepressor complexes, rather than
simply a loss of the transcription machinery.
488 Molecular Cell 41, 480–492, February 18, 2011 ª2011 Elsevier Inc.
Molecular Cell
Genomic Maps of the Yeast Transcription Machinery
DISCUSSION
Saccharomyces utilizes two complementary strategies to regulate its mRNA genes (Basehoar et al., 2004; Bhaumik and Green,
2002; Cheng et al., 2002; Huisinga and Pugh, 2004; Kuras et al.,
2000). Here we provide a description of the extent to which transcription proteins participate in TFIID and SAGA pathways for
PIC assembly. The namesake for these pathways is not intended
to imply a disproportionate importance of these components
compared to others. The TFIID pathway serves the vast majority
of genes by providing a relatively steady production of mRNA
that may be an inherent property of genes. The variety of regulators occupying TFIID-dominated genes is rather limited. In
contrast, the SAGA pathway provides a greater dynamic range
of mRNA output, and thus is more highly regulated. The SAGA
pathway may be best suited to respond to major cellular reprogramming events ranging from acute stress responses to cellular
differentiation. Importantly, a gene may utilize both pathways to
varying extents to achieve an appropriate level of regulation.
Here, we identify which complexes tend to be connected to
which pathway in yeast cells grown in rich media.
We surmise the following framework of regulators specific for
each pathway, based upon current and previous functional and
genome-wide occupancy studies. Since the occupancy data
presented here do not provide information on the order of
assembly, we utilize prevailing models, for example, Sikorski
and Buratowski (2009), on the order of events in the transcription
cycle to place regulators into context within each pathway. The
genome-wide location analyses presented here on hundreds of
proteins are consistent with the specificity of the assembly pathways described below.
In the TFIID-dominated pathway, aggregate available
evidence supports the idea that Rap1 (as one clear example of
a sequence-specific activator in this pathway) recruits NuA4
and TFIID to promoters (Garbett et al., 2007; Reid et al., 2000).
NuA4 acetylates histones H4 and H2A.Z, particularly at the +1
nucleosome located at the downstream edge of the promoter
(Allard et al., 1999; Keogh et al., 2006; Li et al., 2007a). These
acetylation sites dock the bromodomain-containing regulator
Bdf1, which interacts with the SWR1 complex to promote and
maintain H2A.Z deposition and acetylation (Jacobson et al.,
2000; Kobor et al., 2004; Krogan et al., 2003). Bdf1 might also
facilitate TFIID-promoter interactions, since it copurifies with
TFIID (Matangkasombut et al., 2000). A TFIID-based core PIC
then assembles, involving TBP, TFIIB, -E, -F, -H, and Pol II.
Continuing along the TFIID pathway, polymerase-associated
Ctk1 phosphorylates serine 2 of the Pol II C-terminal heptad
repeats (Sterner et al., 1995). Phosphoserine 2 helps recruit
Set2 to methylate H3K36 in the body of the gene (Li et al.,
2003), which allows the RPD3-S complex to remove activating
histone acetylation marks and help suppress internal initiation
(Li et al., 2007b).
When cells are shifted from 25 C to 37 C, the observed relocation of regulators provides additional insight into the TFIID
pathway. For example, a number of sequence-specific negative
regulators (e.g., Rfx1/Crt1, Xbp1, and others) move from heatshock-activated genes to heat-shock-repressed genes, but
they largely stay with genes regulated by the TFIID pathway.
Others such as those involved in removing active histone marks
and setting up repressive chromatin tend to accumulate at the
heat-shock-repressed genes.
In contrast to the TFIID pathway, the SAGA pathway appears
to have many more points of regulation. The utilization of a
greater variety and gene selectivity of sequence-specific regulators provides one means of integrating many different stress
and/or cell type-specific signaling events. The SAGA-dominated
genes display more heterogeneity in chromatin organization
(Albert et al., 2007), which suggests that nucleosomes have
gene-specific and position-specific roles in regulating these
genes. In support of this notion, ATP-dependent chromatin
remodeling complexes and histone deacetylases were particularly enriched at SAGA-dominated genes. Indeed, many other
types of chromatin regulators, including those that write, read,
and remove histone marks, were also enriched.
Positioning of the 1 and +1 nucleosomes could play major
roles in limiting promoter access to the GTFs at SAGA-dominated promoters. Within this context, why SAGA delivers TBP
to such promoters and utilizes a TATA box for TBP, as opposed
to TFIID that delivers TBP to TATA-less promoters (or at least
without apparent regard for TATA), is currently unclear. Perhaps
the TATA box provides added TBP-promoter stability in light
of encroaching nucleosomes, while at the same time leaving
TBP accessible to its many negative regulators such as Mot1,
which favors the SAGA pathway. In the SAGA pathway, TBP
is stabilized against these regulators by TFIIA (reviewed by
Lee and Young, 1998; Pugh, 2000). In the TFIID pathway,
TAFs may prevent negative regulators from accessing TBP.
Events surrounding the early stages of transcription, such as
COMPASS-directed H3K4 trimethylation of the nucleosomes
at the 50 ends of genes and originating through Rad6/Bre1directed H2B ubiquitylation (Sun and Allis, 2002), show a preference for the SAGA pathway.
The enrichment of elongation regulators at SAGA-dominated
genes further fits with the highly regulated status and high
dynamic range of these genes. In particular, FACT and Spt6/
Iws1 allow Pol II to move through chromatin more rapidly by
being highly efficient at dismantling nucleosomes in the path of
Pol II (Fleming et al., 2008; Kaplan et al., 2003). Finally, transcripts from SAGA-dominated genes appear to have a more
direct route to nuclear pores, in that such genes tend to be
enriched with the THO/TREX complex which is nuclear pore
associated and linked to nucleocytoplasmic trafficking of
mRNAs (Strasser et al., 2002).
While the genome-wide location analysis indicates that more
regulatory proteins at various stages of the transcription cycle
tend to be linked to the SAGA pathway rather than the TFIID
pathway, the fact that genes utilize both pathways to varying
extents suggests that components of the two pathways could
cross-regulate each other. The data presented here provide a
snapshot of how regulatory complexes that operate at various
stages of the transcription cycle may be integrated across the
yeast genome. Certainly, much more can be mined from the
data. The combined data sets may be of value in assessing direct
versus indirect effects in expression profiling studies, and in
serving as a platform to develop new questions such as the
relationship between genomic binding locations and function.
Molecular Cell 41, 480–492, February 18, 2011 ª2011 Elsevier Inc. 489
Molecular Cell
Genomic Maps of the Yeast Transcription Machinery
Importantly, the comprehensiveness of the analyses should
provide guidance in exploring coregulation in more complex
organisms. Future work will be aimed at achieving higher-resolution maps of regulator binding locations in an effort to define
the precise organizational structure at promoters. In addition,
it will be important to discern how occupancy of each regulator
depends on other regulatory components.
EXPERIMENTAL PROCEDURES
Yeast Strains and Epitope Tagging
Strains used for this study were obtained from the Yeast TAP-Fusion Library
(Open Biosystems), in which tagged proteins were immunoprecipitated with
IgG antibodies. In the ChIP-chip experiments, BY4741 was used as an
untagged Mock IP control for occupancy normalization. The identity of TAPtagged stains were confirmed by size-matching from western blot analysis
and/or by validating microarray data with published data sets (data not shown).
Chromatin Immunoprecipitation
Chromatin immunoprecipitation (ChIP) assays were performed as described
previously (Venters and Pugh, 2009a; Zanton and Pugh, 2006). Briefly, each
strain (500 ml) was grown at 25 C to mid-log phase (A600 = 0.8) in 500 ml
YPD. For heat-shock experiments, each culture was rapidly shifted to 37 C
at mid-log phase by the addition of hot media, and incubation continued at
37 C for 15 min. Cells were then fixed by the addition of formaldehyde to a final
concentration of 1% for 15 min at 25 C and quenched for 5 min with glycine.
For both normal and heat-shock conditions, cultures were diluted 2-fold with
the same volume of temperature-adjusted distilled water just prior to addition
of formaldehyde so as to achieve a media temperature of 25 C. The harvested
cells were lysed with glass beads, and the chromatin pellet washed and
sonicated. Sheared chromatin was immunoprecipitated with IgG-Sepharose.
This ChIP-enriched DNA was amplified by ligation-mediated PCR as
described elsewhere (Harbison et al., 2004), and 75–300 bp LM-PCR amplified
fragments were gel purified according to the manufacturer’s protocol
(QIAGEN). The gel-purified DNA yield was measured using the Nanodrop
ND-1000 spectrophotometer.
DNA Labeling and Microarray Hybridization
DNA labeling and hybridization to DNA microarrays were performed as
described previously (Zanton and Pugh, 2004). For the custom tiling microarrays, 100 ng of gel-purified LM-PCR ChIP-enriched DNA was amplified by 15
PCR cycles, coupled to Cy3 or Cy5 fluorescent dyes, and subsequently cohybridized to the arrays. For each ChIP sample, at least two biological replicates
were performed, employing a dye swap for each replicate.
Low-Density Tiling Microarray Design
Oligonucleotide probes (60 bp) were designed and synthesized by Operon
Biotechnologies, and were primarily against regions 320 to 260 and 90
to 30 from the start of each ORF in the S. cerevisiae genome, with positional
adjustments made to keep a uniform Tm. Additional genic oligos comprised the
Yeast Genome Oligo Set Version 1.1 (Operon Biotechnologies). An additional
1205 probes were synthesized against nonpromoter intergenic regions, and in
snRNA and tRNA promoters. Each microarray consisted of >21,000 oligonucleotide probes spotted onto aminosilane-treated glass slides.
ChIP-seq Sample Preparation and Analysis
ChIP-enriched DNA samples were prepared for the Illumina Genome Analyzer
platform according to the manufacturer’s instructions. The sequencing data
were normalized using an untagged control (BY4741) and centered to the
lowest quartile of reads in a 25 bp window.
SUPPLEMENTAL INFORMATION
Supplemental Information includes seven figures, ten tables, Supplemental
Experimental Procedures, and Supplemental References and can be found
with this article at doi:10.1016/j.molcel.2011.01.015.
ACKNOWLEDGMENTS
We thank members of the Pugh laboratory and the Center for Eukaryotic Gene
Regulation for many helpful discussions. We thank Istvan Albert for bioinformatics support and Ben Pugh for conducting strain validation tests. This
work was supported by National Institutes of Health (NIH) grant ES013768.
This project is funded, in part, under a grant with the Pennsylvania Department
of Health using Tobacco Settlement Funds. The department specifically
disclaims responsibility for any analyses, interpretations, or conclusions.
Received: July 13, 2010
Revised: September 28, 2010
Accepted: December 15, 2010
Published: February 17, 2011
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