Transcriptional response to stress in the dynamic
chromatin environment of cycling and mitotic cells
Anniina Vihervaaraa,b, Christian Sergeliusa, Jenni Vasaraa,b, Malin A. H. Bloma,b, Alexandra N. Elsinga,b,
Pia Roos-Mattjusa, and Lea Sistonena,b,1
a
Department of Biosciences, Åbo Akademi University, 20520 Turku, Finland; and bTurku Centre for Biotechnology, University of Turku and Åbo Akademi
University, 20520 Turku, Finland
Edited by Susan Lindquist, Whitehead Institute for Biomedical Research, Cambridge, MA, and approved July 18, 2013 (received for review March 23, 2013)
Heat shock factors (HSFs) are the master regulators of transcription under protein-damaging conditions, acting in an environment
where the overall transcription is silenced. We determined the
genomewide transcriptional program that is rapidly provoked by
HSF1 and HSF2 under acute stress in human cells. Our results
revealed the molecular mechanisms that maintain cellular homeostasis, including HSF1-driven induction of polyubiquitin genes, as
well as HSF1- and HSF2-mediated expression patterns of cochaperones, transcriptional regulators, and signaling molecules. We
characterized the genomewide transcriptional response to stress
also in mitotic cells where the chromatin is tightly compacted. We
found a radically limited binding and transactivating capacity of
HSF1, leaving mitotic cells highly susceptible to proteotoxicity. In
contrast, HSF2 occupied hundreds of loci in the mitotic cells and
localized to the condensed chromatin also in meiosis. These results
highlight the importance of the cell cycle phase in transcriptional
responses and identify the specific mechanisms for HSF1 and HSF2
in transcriptional orchestration. Moreover, we propose that HSF2
is an epigenetic regulator directing transcription throughout cell
cycle progression.
ChIP-seq
| ENCODE | human genome | proteostasis
C
ells exposed to proteotoxic conditions provoke a rapid and
transient response to maintain homeostasis. The stress response induces profound cellular adaptation as cytoskeleton and
membranes are reorganized, cell cycle progression is stalled, and
the global transcription and translation are silenced (1, 2). Despite the silenced chromatin environment, the stressed cell
mounts a transcriptional program that involves induction of
genes coding for heat shock proteins (HSPs). HSPs are molecular chaperones and proteases that assist in protein folding and
maintain cellular structures and molecular functions (3).
Heat shock factor 1 (HSF1) is an evolutionarily well-conserved
transcription factor that is rapidly activated by stress and absolutely required for the stress-induced HSP expression (4). Aberrant HSF1 levels are associated with stress sensitivity, aging,
neurodegenerative diseases, and cancer (5–9). Instead of a single
HSF in yeasts and invertebrates, vertebrates contain a family of
four members, HSF1–4. HSF2 and HSF4 are involved in corticogenesis, spermatogenesis, and formation of sensory epithelium, and they have primarily been considered as developmental
factors (10–14). HSF1 and HSF2 share high sequence homology
of the DNA-binding and oligomerization domains and are able
to form heterotrimers at the chromatin (15, 16). Moreover,
HSF2 participates in the regulation of stress-responsive genes
and is required for proper protein clearance also at febrile
temperatures (17, 18). Although HSF1 and HSF2 have been
shown to interplay on the heat shock elements (HSEs) of the
target loci, their impacts on transcription of chaperone genes are
remarkably different; HSF1 is a potent inducer of transcription,
whereas HSF2 is a poor transactivator of HSPs on heat stress
(19–21). HSF1 and HSF2 are also subjected to distinct regulatory
mechanisms, because HSF1 is a stable protein that undergoes
E3388–E3397 | PNAS | Published online August 19, 2013
rapid posttranslational modifications (PTMs), and HSF2 is predominantly regulated at the level of expression (22, 23).
The rapid and robust chaperone expression has served as a
model for inducible transcriptional responses (24). However, the
previous studies have almost exclusively concentrated on the
expression of a handful of HSP genes in unsynchronized cell
populations (17, 25–28). Currently, comprehensive knowledge
on the target genes for HSF1 and HSF2 and their cooperation
during stress responses is missing. Moreover, the cell cycle progression creates profoundly different environments for transcription depending on whether the chromatin undergoes
replication or division or whether the cell resides in the gap
phases. For transcription factors, the synthesis phase provides an
opportunity to access the transiently unwound DNA, whereas in
mitosis, most factors are excluded from the condensed chromatin
(29–32). Importantly, throughout the cell cycle progression,
epigenetic cues are required to maintain the cellular identity and
fate (33).
In this study, we investigated the genomewide transcriptional
response that is provoked in the acute phase of heat stress in
freely cycling cells and in cells arrested in mitosis. We characterized the transactivator capacities and the genomewide target
loci for HSF1 and HSF2 and analyzed chromatin landmarks at
the HSF target sites. By comparing transcriptional responses in
cycling versus mitotic cells, we determined the ability of mitotic
cells to respond to proteotoxic insults and the capacity of transcription factors to interact with chromatin that is condensed for
Significance
We determined the transcriptional program that is rapidly
provoked to counteract heat-induced stress and uncovered the
broad range of molecular mechanisms that maintain cellular
homeostasis under hostile conditions. Because transcriptional
responses are directed in the complex chromatin environment
that undergoes dramatic changes during the cell cycle progression, we identified the genomewide transcriptional response to stress also in cells where the chromatin is condensed
for mitotic division. Our results highlight the importance of the
cell cycle phase in provoking cellular responses and identify
molecular mechanisms that direct transcription during the
progression of the cell cycle.
Author contributions: A.V. and L.S. designed research; A.V., J.V., M.A.H.B., and A.N.E.
performed research; A.V. and C.S. performed computational data analysis; A.V., C.S., P.R.-M.,
and L.S. analyzed data; and A.V. and L.S. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
Freely available online through the PNAS open access option.
Data deposition: The high-throughput sequencing data reported in this paper have been
deposited in the Gene Expression Omnibus (GEO) database, www.ncbi.nlm.nih.gov/geo
(accession no. GSE43579).
1
To whom correspondence should be addressed. E-mail: lea.sistonen@abo.fi.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
1073/pnas.1305275110/-/DCSupplemental.
www.pnas.org/cgi/doi/10.1073/pnas.1305275110
Results
Genomewide Identification of Target Sites for HSF1 and HSF2 in
Cycling and Mitotic Cells. ChIP coupled to massively parallel se-
quencing (ChIP-seq) is a powerful method that enables genomewide mapping of protein binding sites in a high-resolution and
unbiased manner (34–36). We used ChIP-seq to characterize the
binding sites for HSF1 and HSF2 in cycling and mitotic cells that
were either untreated or heat treated for 30 min at 42 °C. As the
model system, we chose human K562 erythroleukemia cells, where
HSF1 and HSF2 levels and regulatory mechanisms are well
characterized (17, 20, 37), and chromatin landmarks have been
identified by the Encyclopedia of DNA Elements (ENCODE)
consortium (38). The efficiency of cell cycle arrest was improved
by collecting the cells in S-phase before nocodazole treatment
(39). Histograms of cells based on the DNA content are shown in
Fig. 1A, confirming the mitotic arrest (5% of cells in G1 and 85%
in G2/M) compared with freely cycling cells (45% in G1 and 15%
in G2/M). For sequencing, 10 PCR-verified ChIP-replicates were
collected per sample, and two controls, IgG and input, were included (Fig. S1).
The ChIP-seq provided high-resolution maps of HSF1 and
HSF2 target loci in the human genome (Dataset S1; Gene Expression Omnibus accession no. GSE43579). Under optimal
growth conditions in cycling cells, 45 target sites were identified
for HSF1 and 148 for HSF2. On acute stress, both the number of
the target sites (1242 for HSF1 and 899 for HSF2) and the fold
enrichments of the targets were considerably higher, indicating
a rapid recruitment of HSF1 and HSF2 to their target loci in
heat-stressed cycling cells (Fig. 1B; Dataset S1). In mitosis, the
ability of HSFs to bind chromatin was clearly different; HSF2
occupied 50 loci under optimal conditions and 545 loci on acute
stress. In contrast, HSF1 interacted only with the promoter of
HSPA1B/HSP70.2 in the absence of stress, and with 35 loci on
heat stress (Fig. 1B; Dataset S1). Although effectively excluded
from the dividing chromatin, HSF1 displayed prominent heatinduced occupancy on certain loci, including promoters of
HSPA1A/HSP70.1, HSPA1B/HSP70.2, HSPH1/HSP110, MRPS6
HSF1 and HSF2 Recognize Similar Consensus DNA Sequences but
Display Distinct Binding Profiles in the Human Genome. Binding of
HSF2 to target genes on stress has been considered to occur in
an HSF1-dependent manner (16, 17). However, we identified
target genes that are specific for either HSF1 or HSF2 (Fig. 1 E
and F; Fig. S2A; Dataset S1). In heat-treated cycling cells, HSF1
and HSF2 shared a majority of their target sites, but under optimal growth conditions and in mitosis, they displayed strikingly
different localization to the human genome (Fig. S2A). Despite
their distinct binding sites, HSF1 and HSF2 recognized similar
HSEs both in cycling and mitotic cells (Fig. S2B), demonstrating
that the DNA sequence alone is not sufficient to determine the
binding site for HSF1 vs. HSF2.
Given that promoters and exons account for <2% of the human genome (Human Genome Project), HSF1 and HSF2 were
enriched on gene promoters and protein coding sequences (Fig.
S3A). For example, 19% of HSF1 and 22% of HSF2 target loci
were found within promoters in heat-treated cycling cells (Fig.
Fig. 1. Binding sites for HSF1 and HSF2 in cycling and mitotic
K562 cells. (A) Histograms of cycling and mitotic cells based on
the DNA content. (B) (Upper) Number of HSF1 (red) and HSF2
(green) target loci in cycling and mitotic cells. (Lower) Fold
enrichment over input of each identified HSF1 (red) and HSF2
(green) target locus. The dashed gray line indicates fold enrichment five, which was set as cutoff criterion for HSF target
sites. (C–F) Enrichments of HSF1 (red) and HSF2 (green) on indicated target genes in cycling and mitotic cells. (C) HSPA1A
and HSPA1B promoters are bound by HSF1 and HSF2 in cycling
and mitotic cells. (D) DUSP1 promoter harbors prominent HSF1
and HSF2 enrichments in stressed cycling cells only. (E) GBA is
an HSF1-specific and (F) MLL is an HSF2-specific target promoter. Distribution of RNPII in nontreated cycling cells (blue) is
recovered from the ENCODE project (wgEncodeEH000616;
Snyder Laboratory, Yale University). The scale for each HSF or
input sample is set to 0–100, except at the HSPA1 locus, where,
due to high enrichments, the scale is set to 0–250 in cycling and
0–125 in mitotic cells. C, control; HS, heat shock.
Vihervaara et al.
PNAS PLUS
(mitochondrial ribosome protein 6), and DNAJB6 (Fig. 1C;
Dataset S1). Enrichments of HSF1 and HSF2 on selected target
genes are illustrated in Fig. 1 C–F.
The HSPA1/HSP70 locus was strongly bound by HSF1 and
HSF2 in heat-treated cycling and mitotic cells (Fig. 1C), whereas
DUSP1 (dual specific phosphatase 1) was occupied by HSF1 and
HSF2 in cycling cells only, demonstrating the importance of the
cell cycle phase in transcriptional responses (Fig. 1D). In Fig. 1 E
and F, the capacity of HSF1 and HSF2 to bind their individual
target loci is indicated with promoters of GBA (glucosidase β
acid) and MLL (myeloid/lymphoid or mixed-lineage leukemia).
Intriguingly, HSF2 occupied the promoter of MLL in unstressed
mitotic cells, although in cycling cells the binding was strictly
induced by heat shock (Fig. 1F). Promoter-proximally paused
RNA polymerase II (RNPII) was originally identified at the
HSP70 promoter (40, 41), and it is estimated to poise ∼30% of
human genes for rapid or synchronous activation (42). We investigated the status of RNPII at selected HSF target promoters
using an existing ChIP-seq data on RNPII (wgEncodeEH000616;
Snyder Laboratory, Yale University). ChIP cannot determine
transcriptional engagement, but recent global-run-on sequencing
(GRO-seq) experiments revealed that the majority of promoterassociated polymerases are transcriptionally engaged and competent for elongation (43). Accordingly, we refer to RNPII
whose enrichment on a promoter site exceeds at least five times
the overall signal on the gene as paused RNPII (see below). In
Fig. 1 C–F, the distribution of RNPII is visualized.
PNAS | Published online August 19, 2013 | E3389
CELL BIOLOGY
cell division. We discovered the broad range of molecular
mechanisms that maintain cellular homeostasis in stressed cells
and provide unique mechanistic insights into the regulation of
gene expression during the cell cycle progression. Our results
revealed the cooperation of HSF1 and HSF2 in orchestrating
gene expression in stressed cycling cells and identified their
profoundly distinct capacities to coordinate transcription in cells
where the chromatin is compacted for cell division.
S3A). On average, the enrichments of HSF1 and HSF2 were
higher on promoter regions than on coding sequences (Fig. S3B),
but prominent HSF1 and HSF2 targets were found also within
introns, exons, and intergenic regions as illustrated with PRKCA
and PRKCB (protein kinase C α and β, respectively), KCNN1
(calcium-activated channel N1), and an intergenic region upstream of HSPB1/HSP27 (Fig. S3C).
HSF1 and HSF2 Bind Selected Chaperone Gene Promoters. HSF1 and
HSF2 are best known for their stress-related regulatory functions
on certain chaperone genes, such as HSPA1A/HSP70.1, HSPC/
HSP90, HSPB1/HSP27, and DNAJB1/HSP40 (4, 17, 26, 27). The
ChIP-seq enabled unbiased analyses of HSF1 and HSF2 on every
chaperone gene encoded in the human genome and revealed
HSF occupancy on 70% of HSP, 90% of chaperonin, and 13% of
DNAJ genes (Table 1; Table S1). A majority of the HSF-targeted
chaperone genes were bound by both HSF1 and HSF2 on promoters that contained paused RNPII (Table 1; Table S1).
Exceptions were the small HSPs HSPB2/HSP27-2, HSPB5/
CRYAB, and HSPB9, whose promoters lacked paused RNPII
(Table 1). To address the impact of HSF1 and HSF2 on transcription, we depleted either HSF1 or HSF2, or both factors
together, by shRNA-mediated degradation and analyzed a set
of HSF-targeted chaperone genes for their mRNA expression
Table 1. HSF1 and HSF2 occupancy on HSPA, HSPB, HSPC, HSPH, and chaperonin genes
HSF1
HSF2
Cycling
Mitosis
Cycling
Mitosis
Family
Gene
Alias
C
HS
C
HS
C
HS
C
HS
Binding
site
Paused
RNPII*
HSPA
HSPA1A
HSPA1B
HSPA1L
HSPA2
HSPA5
HSPA6
HSPA7
HSPA8
HSPA9
HSPA12A
HSPA12B
HSPA13
HSPA14
HSPB1
HSPB2
HSPB3
HSPB4
HSPB5
HSPB6
HSPB7
HSPB8
HSPB9
HSPB10
HSPB11
HSPC1
HSPC2
HSPC3
HSPC4
HSPC5
HSPD1
HSPE1
HSPH1
HSPH2
HSPH3
HSPH4
CCT1
CCT2
CCT3
CCT4
CCT5
CCT6A
CCT6B
CCT7
CCT8
HSP70-1
HSP70-2
HSP70-1L
HSPA3
BIP, GRP78
HSP70B’
HSP70
HSC70
GRP75
FLJ13874
RP23-32L15.1
Stch
HSP70-4
HSP27-1
HSP27-2
HSPL27
CRYAA
CRYAB
HSP20
cvHSP
HSP22
FLJ27437
ODF1
HSP16.2
HSP90AA1
HSP90AA2
HSP90AB1
HSP90B1
TRAP1, HSP90L
HSP60, GROEL
HSP10, GROES
HSP105/110
HSPA4
HSPA4L
HYOU1
TCP1, CCTA
CCTB
CCTG
CCTD
CCTE
CCTZ
CCTZ2
CCTH
CCTQ
2.8
4.3
2.8
—
—
—
—
4.3
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
5.8
5.8
—
—
—
—
3.5
—
—
—
—
—
—
—
—
40.4
45.1
40.4
—
—
15.2
3.0
29.5
6.6
—
—
—
—
23.8
14.1
—
—
14.1
—
—
—
12.3
—
—
13.2
—
23.8
—
—
43.0
43.0
32.6
22.5
9.1
—
31.8
8.7
8.5
12.4
14.0
—
—
12.5
5.0
2.5
5.3
2.5
—
—
—
—
2.8
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
3.5
3.5
—
—
—
—
—
—
—
—
—
—
—
—
—
16.3
20.5
16.3
—
—
—
—
5.3
—
—
—
—
—
6.3
—
—
—
—
—
—
—
3.5
—
—
6.0
—
8.2
—
—
15.1
15.1
8.8
4.2
4.2
—
4.6
—
—
3.9
2.7
—
—
3.5
—
5.2
5.4
5.2
—
—
—
—
20.2
—
—
—
—
—
—
—
—
—
—
—
—
—
7.0
—
—
—
—
6.8
—
—
17.8
17.8
—
—
—
—
8.5
—
—
4.7
—
—
—
—
—
25.6
26.8
25.6
—
—
7.3
—
26.8
5.9
—
—
—
—
16.5
10.4
—
—
10.4
—
—
—
19.0
—
—
10.5
—
14.1
—
—
33.4
33.4
19.0
20.9
5.5
—
21.5
6.3
8.5
8.5
15.3
5.7
—
11.4
7.1
3.3
5.4
3.3
—
—
—
—
8.3
—
—
—
—
—
3.5
—
—
—
—
—
—
—
—
—
3.1
3.2
—
—
—
—
6.0
6.0
—
—
—
—
—
—
3.9
—
—
—
—
—
—
10.8
15.5
10.8
—
—
—
—
12.3
—
—
—
—
—
5.6
—
—
—
—
—
—
—
6.0
—
—
5.3
—
9.9
—
—
9.5
9.5
6.3
4.2
3.5
—
5.2
—
—
—
4.9
—
—
3.9
—
Promoter
Promoter
Promoter
—
—
Promoter
Promoter
Promoter
Promoter
—
—
—
—
Promoter
Promoter
—
—
Promoter
—
—
—
Promoter
—
Promoter
Promoter
—
Promoter
—
—
Promoter
Promoter
Promoter
Promoter
Promoter
—
Promoter
Prom/Int
Prom/Int
Promoter
Promoter
Promoter
—
Promoter
Promoter
Yes
Yes
Yes
No
Yes
Yes
No
Yes
Yes
No
No
Yes
Yes
Yes
No
No
No
No
No
No
No
No
NA
Yes
Yes
NA
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
HSPB
HSPC
HSPD
HSPE
HSPH
TRiC
Fold enrichments ≥2 are shown. The nomenclature of HSPs is according to ref. 85. C, control; HS, heat shock; NA, not analyzed; Prom/Int, promoter or
intron depending on the transcript variant.
*The RNPII density signal is recovered from ENCODE (wgEncodeEH000616; Snyder Laboratory, Yale University).
E3390 | www.pnas.org/cgi/doi/10.1073/pnas.1305275110
Vihervaara et al.
HSP90 protein complex (49), showed a threefold heat-induced
expression that required the presence of HSF1 (Fig. 2D). CDC37
and p23 are involved in client protein recruitment and maturation, and they inhibit the HSP90 ATPase cycle (48, 50, 51). We
did not detect any significant change in CDC37 mRNA levels
during the 2-h heat shock but found a twofold HSF1-dependent
increase in p23 mRNA (Fig. 2D). Curiously, HSF1 and HSF2
bound the promoters of AHSA1 and PTGES3, but the first intron
of the noninducible CDC37 (Fig. 2C). We conclude that in addition to controlling the set of chaperones induced by acute heat
stress, HSFs also determine the expression patterns of cochaperones, which are critical for the recognition and fate of the
clients, as well as for the chaperoning efficacy.
HSF1 Is Required for Heat-Induced Cochaperone Expression. As
shown in Fig. 2C and Dataset S1, HSF1 and HSF2 occupied
many cochaperone genes, which have not previously been demonstrated to be under control of HSFs. Most cochaperones
possess intrinsic chaperone activity but are termed cochaperones
because they determine the activities of the HSP70 and/or
HSP90 protein complexes (47, 48). As summarized in Fig. 2C,
HSF1 and HSF2 showed a strong tendency to bind cochaperone
gene promoters that contain the paused RNPII. We determined
the mRNA levels of the HSP90 cochaperones AHSA1 (encoding
AHA1), CDC37, and PTGES3 (encoding p23) in the presence
and absence of HSF1 or HSF2 (Fig. 2D). AHA1, which stimulates the ATPase cycle and is the most potent activator of the
aggregated proteins accumulate and generate an increased demand for protein clearance. The vast majority of proteins destined for degradation are marked by ubiquitin, which is encoded
by four genes in humans (52). As revealed by ChIP-seq, HSF1
and HSF2 selectively bound to the promoters of polyubiquitin
genes UBB and UBC but were absent on the monoubiquitin
genes RPS27A and UBA52 (Fig. 3A). Transcription of UBB or
UBC enables a prompt increase in the ubiquitin levels because
their corresponding mRNAs encode a precursor for three and
nine ubiquitin proteins, respectively (Fig. 3B). In comparison,
transcription of RPS27A or UBA52 would generate one ribosomal protein per each ubiquitin produced (Fig. 3B). In heattreated cycling cells, the mRNA levels of UBB and UBC rapidly
PNAS PLUS
during heat shock (Fig. 2 A and B; Fig. S4A). In freely cycling
cells, HSPH1/HSP110, HSPH2, and DNAJB6 were identified as
unique HSF-regulated genes whose heat-induced expression was
strictly dependent on HSF1 (Fig. 2B; Fig. S4A). CCT1 (chaperonin 1) has previously been shown to be regulated by HSFs (44),
which we corroborated in K562 cells (Fig. 2B). The HSPH1/
HSP110 mRNA expression rapidly increased to sevenfold,
whereas the levels of DNAJB6 and CCT1 mRNA doubled
during the acute heat stress (Fig. 2B). DNAJB6 is the most potent chaperone in inhibiting protein aggregation, and HSPH1/
HSP110 remodels the HSP70-HSP40 machinery to solubilize
and refold aggregated proteins in metazoan cells (45, 46). These
results indicate a considerably wider repertoire of HSF-induced
chaperones than earlier anticipated and highlight the importance
of managing aggregated proteins under proteotoxic conditions.
CELL BIOLOGY
Stress-Generated Demand for Protein Clearance Is Mitigated by HSF1Dependent Ubiquitin Expression. On heat stress, damaged and
Fig. 2. HSFs define the set of chaperones and cochaperones
induced in response to acute heat stress. (A) HSF1 and HSF2
protein levels during the 2-h heat stress in scrambled-transfected (Scr), HSF1-depleted (shHSF1), and HSF2-depleted
(shHSF2) cycling cells. HSF2 levels decline on heat stress as
previously reported (25). (B) mRNA levels of chaperones HSPH1,
HSPH2, DNAJB6, and chaperonin CCT1 during heat stress in the
presence or absence of HSF1 or HSF2. (C) Cochaperone genes
bound by HSF1 and HSF2 in cycling cells. Fold enrichments over
input as detected with ChIP-seq are indicated. (D) mRNA levels
of HSP90 cochaperones AHA1, CDC37, and p23 in nontreated
and heat-treated cycling cells with or without HSF1 or HSF2. In
B and D, SDs of a minimum of three biological replicates are
shown. The statistical analyses were conducted with two-tailed
independent Student t test and asterisks denote statistical
significance between indicated scrambled-transfected and HSFdepleted cells. *P < 0.1; **P < 0.05; ***P < 0.01.
Vihervaara et al.
PNAS | Published online August 19, 2013 | E3391
Fig. 3. HSF1 induces polyubiquitin gene expression in cycling
cells. (A) HSF1 and HSF2 bind to polyubiquitin (UBB and UBC)
but not to monoubiquitin (RPS27A, UBA52) genes as shown by
ChIP-seq. (B) Schematic illustration of the four ubiquitin coding
genes in the human genome. (C and D) Heat stress leads to
increased expression of polyubiquitin but not monoubiquitin
genes in cycling cells, and the heat-induced ubiquitin expression is abolished in HSF1-depleted cells. The mRNA levels and
statistical significances were analyzed as in Fig. 2.
increased to two- and fourfold, respectively, whereas the levels of
RPS27A and UBA52 mRNA remained unchanged (Fig. 3 C and
D). Depletion of HSF1 severely compromized the heat-induced
ubiquitin expression in cycling cells (Fig. 3D), revealing that
HSF1 localization to the promoters of polyubiquitin genes is
required for the cell to generate adequate levels of ubiquitin
mRNA under proteotoxic stress.
HSF1- and HSF2-Driven Transcriptional Programming Extends to
Genes Encoding Transcriptional and Translational Regulators, Cell
Cycle Determinants, and Core Signaling Components. To investigate
the biological processes associated with HSF1 and HSF2 target
genes in acute stress, we performed gene ontology analysis using
Database for Annotation, Visualization and Integrated Discovery
(DAVID) (53). Because heat shock leads to a rapid transcriptional
response, we sought to understand whether HSFs are recruited to
genomic loci that harbor RNPII before stress (wgEncodeEH000529; Iyer Laboratory, University of Texas) and whether the
presence or absence of RNPII characterizes HSF target genes
associated with a specific function. Interestingly, 90% of HSF1- or
HSF2-targeted loci on promoters were occupied by RNPII, and at
the gene bodies, approximately half of the HSF1 or HSF2 target
sites harbored RNPII (Fig. 4A).
In heat-shocked cycling cells, HSF1 and HSF2 co-occupied
promoters of chaperones and cochaperones, transcriptional and
translational regulators, and mediators of cell cycle progression
(Fig. 4A; Dataset S2). On the gene bodies, HSF1 occupied
RNPII-containing loci of genes that mediate transcriptional repression, methylation, and inhibition of mRNA metabolism. As a
comparison, HSF2 localized to the coding sequences of genes
involved in activation of diverse cellular processes, specifically on
the sites that lacked RNPII (Fig. 4A; Dataset S2). Among the
promoter-targeted genes, we verified the mRNA levels of transcriptional regulators TAF7 (TATA-box associated factor 7) and
MLL, translational components EEF1G (eukaryote elongation
factor 1γ) and MRPS6, as well as mitotic factors NUDC (nuclear
distribution C homolog) and BANF1 (barrier to autointegration
factor 1). Among the genes that harbored HSF on the coding
sequence, mRNA levels of CTCF (CCCTC-binding factor) and
PRKCA were investigated. In response to heat stress, an HSF1dependent increase to 3-fold was detected for TAF7, 2-fold for
EEF1G, and 1.5-fold for NUDC (Fig. 4B). Depletion of HSF2
did not hamper the heat-inducible expression of any of the
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studied genes, but it disrupted the expression kinetics of MLL
(Fig. 4B). Moreover, absence of HSF2 caused more than a twofold increase in mRNA levels of BANF1 and PRKCA under
optimal growth conditions (Fig. 4B).
Mitosis Inhibits Transcriptional Activation and Renders Chromatin
Inaccessible for HSF1. HSF1 bound to 35 target loci in heat-trea-
ted mitotic cells, mainly on the promoters of chaperones and
translational components (Fig. 5 A and B; Datasets S1 and S2). It
is noteworthy that HSF1 was unable to bind to 1,207 loci, which
it occupied in heat-stressed cycling cells (Fig. 5B). Among the
genes that lacked HSF1 in stressed mitotic cells were UBB and
UBC (Fig. S4B), and subsequently, the ubiquitin gene expression
remained unchanged during heat treatment of mitotic cells (Fig.
S4C). In contrast to the radically limited capacity of HSF1 to
interact with the mitotic chromatin, HSF2 occupied hundreds of
target loci both in cycling and mitotic cells (Figs. 1B and 5B;
Dataset S1). However, depending on the phase of the cell cycle,
HSF2 localized to a distinct set of targets (Fig. 5 A and B;
Datasets S1 and S2). We confirmed that depletion of HSF1 or
HSF2 did not interfere with synchronization of cells to mitosis
(Fig. 5 C and D) and investigated whether binding of HSF1 or
HSF2 leads to induced transcription of their target genes in
mitotic cells (Fig. 5E; Fig. S4D). Although HSF1 was a potent
transactivator in cycling cells (Figs. 2–4), no significant induction
of any of the studied HSF1 and HSF2 target genes, HSPH1/
HSP110, HSPH2, NUDC, DNAJB6, or MRPS6, was detected in
mitosis (Fig. 5E; Fig. S4D). These results indicate that besides
displaying an impaired ability to bind to the mitotic chromatin,
the occupancy of HSF1 at promoters does not induce transcription in the mitotic environment, where the promoters likely
lack RNPII and the condensed chromatin generates barriers for
transcriptional initiation and elongation (30). Moreover, mitotic
cells have been shown to be highly susceptible to heat-induced
stress (54, 55), which is in agreement with increased cell death
that we observed in heat-treated mitotic cells (Fig. S4E).
The mRNA levels of the HSF2-specific target gene, MLL,
remained relatively constant in the mitotic cells exposed to acute
heat stress. However, depletion of HSF2 led to increased MLL
expression under nonstress conditions (Fig. 5E), suggesting that
HSF2 either inhibits transcription or modifies the chromatin environment of MLL. To elucidate the role of HSF2 in mitosis, when
the overall transcription is silenced (30), we monitored the expresVihervaara et al.
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CELL BIOLOGY
Fig. 4. HSFs control a broad range of cellular processes during stress. (A) Gene ontology analyses of HSF1 and HSF2 target genes in heat-treated cycling cells
in respect to genomic region and to presence or absence of RNPII. Promoter is defined as −1,200 to +300 bp from the TSS, and gene body is coding sequence
from +301 bp to the end of the gene. HSF1-specific target gene groups are indicated in red, HSF2-specific target gene groups are in green, and their shared
target gene groups are in blue. (Lower) Fractions of HSF1 or HSF2 target sites that localize to RNPII-occupied sites. RNPII-containing sites in nontreated cycling
cells are recovered from the ENCODE project (wgEncodeEH000529; Iyer Laboratory, University of Texas). (B) mRNA levels of HSF target genes during heat
shock. mRNA levels and statistical significances were analyzed as in Fig. 2.
sion kinetics of MLL after the non–heat-shocked cells had been
released from the mitotic arrest (Fig. 6A). In scrambled-transfected
cells, the mRNA levels of MLL gradually doubled as the cells
progressed from mitosis to G1 phase (Fig. 6A). These results are
in agreement with a previous study where the MLL protein levels
were shown to increase after mitosis (56). However, the postmitotic induction of MLL expression in HSF2-depleted cells was
only minute and showed delayed kinetics (Fig. 6A). As a control,
we used DUSP1, which was not bound by HSFs in the mitotic
cells (Fig. 1D). DUSP1 is a heat-inducible gene (57), and no
elevation in DUSP1 mRNA expression was detected after the
mitotic release, nor did the absence of HSF2 affect the DUSP1
expression during cell cycle progression (Fig. 6A). In conclusion,
the ability of HSF2 to bind to the MLL promoter in mitosis (Fig.
1D) and to direct its postmitotic expression (Fig. 6A) indicates
the involvement of HSF2 in restoring the transcription of MLL
after the mitotic silencing.
The binding of HSF2 to mitotic chromatin (Figs. 1B and 5B;
Fig. S2A) argued that a great number of HSEs are accessible for
transcription factors during cell division. We compared the HSF
Vihervaara et al.
target sites in heat-treated mitotic cells to DNaseI hypersensitive
regions in mitosis (wgEncodeEH003472; Crawford Laboratory,
Duke University) and found that open chromatin is a prerequisite for HSF1 binding, as 97% of its target sites occurred
within DNaseI sensitive regions (Fig. 6B). Instead, 42% of HSF2
targets in mitosis were found within open chromatin (Fig. 6B).
Although HSF2 was able to bind both to DNaseI hypersensitive
and insensitive regions, this did not explain why HSF1 was absent
from 195 DNaseI hypersensitive loci that contained HSF2. Next,
we addressed whether the exclusion of HSF1 from the mitotic
chromatin is mediated by inhibiting the intrinsic DNA-binding
capacity of HSF1 or by rendering the chromatin inaccessible for
HSF1. As analyzed with oligonucleotide-mediated pull-down,
both HSF1 and HSF2 bound to the exogenous HSE-containing
oligonucleotides in cycling and mitotic heat-treated cells (Fig.
6C). Curiously, HSF2 bound to DNA also in untreated cycling
cells, and its levels declined in mitosis (Fig. 6C). Besides binding
to the exogenous HSE, hyperphosphorylation of HSF1 was
detected in mitosis (Fig. 6C), indicating HSF1 transactivating
capacity (22). These results demonstrate that HSF1 was indeed
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maintain homeostasis, highlighting the myriad of different cellular
processes that are orchestrated under protein-damaging conditions. In stressed freely cycling cells, HSFs induced the expression of polyubiquitin genes, which is a rapid means to
produce a large amount of ubiquitin (Fig. 3). Ubiquitin is a small
signaling molecule with versatile functions in the cell, and it is
required for the proteasomal degradation of damaged proteins
(52). Polyubiquitin genes have been shown to be induced on
exposure to heat (52, 62), and here we provide evidence for the
direct involvement of HSF1 and HSF2 in the regulation of polyubiquitin gene expression. HSFs also defined the expression of
chaperones (Table 1; Table S1; Fig. 2B) and cochaperones (Fig.
2 C and D) that facilitate protein folding. Previously, a subset of
chaperone genes has been used as a model for induced transcriptional responses, but here we characterized the complete set
of human chaperones that are transcriptionally regulated by HSF1
and HSF2 (Table 1; Table S1). Importantly, we discovered that
HSF1 and HSF2 also determine the cochaperones that are induced during heat stress, demonstrating that HSFs orchestrate the
Fig. 5. HSF2 interacts with mitotic chromatin. (A) Gene ontology analyses of
HSF1 and HSF2 target loci in mitosis. The genomic regions were defined as in
Fig. 4. (B) The number of HSF1 (red) and HSF2 (green) target loci in cycling
and mitotic heat-treated cells. (C) HSF1 and HSF2 protein levels in scrambledtransfected (Scr), HSF1-depleted (shHSF1), and HSF2-depleted (shHSF2) mitotic cells during heat stress. (D) Histograms of scrambled-transfected (Scr),
HSF1-depleted (shHSF1), and HSF2-depleted (shHSF2) mitotic cells after a 1-h
heat treatment, indicating that neither transfection nor lack of HSF1 or HSF2
compromises the synchronization of cells to G2/M. (E) mRNA levels of HSPH1,
HSPH2, NUDC, and MLL in mitotic cells with or without HSF1 or HSF2. mRNA
levels and statistical significances were analyzed as in Fig. 2.
capable of binding to DNA in mitosis, but its access to chromatin
was dramatically reduced from 1,242 sites in heat-treated cycling
cells to only 35 sites in cells arrested to mitosis.
An intriguing congruency has been reported during meiotic
division in mouse spermatocytes, where HSF1 was shown to bind
to the exogenous HSE on heat stress but no binding to the
HSP70 promoter could be detected (11, 58–60). Because HSF2deficient mice display meiotic defects (61), we investigated by
confocal microscopy the subcellular localization of HSF1 and
HSF2 in metaphase spermatocytes. HSF2 was abundant at the
chromatin in meiotic divisions, whereas HSF1, albeit highly expressed, was detected only outside the dividing chromatin (Fig.
6D). These results suggest a common mechanism in cell division
that selectively allows HSF2 to bind mitotic and meiotic chromatin from which HSF1 is efficiently excluded.
Discussion
Characterization of the genomewide binding sites and transactivating capacities for HSF1 and HSF2 discovered the extent
of HSF-mediated transcriptional reprogramming under acute
heat stress. The results uncovered molecular mechanisms that
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Fig. 6. Chromatin compaction during mitosis and meiosis renders DNA inaccessible for HSF1. (A) mRNA levels of MLL and DUSP1 in the presence (Scr)
or absence (shHSF2) of HSF2. The analyses were conducted in non–heat
shock conditions at indicated times points after releasing the cells from
mitotic arrest. mRNA levels and statistical significances were analyzed as in
Fig. 2. (Right) Progression of cells from mitotic arrest is illustrated with FACS
profiles. (B) Fraction of HSF1 or HSF2 target sites in mitosis that occur within
DNaseI hypersensitive regions. The DNaseI sensitive regions in G2/M are recovered from the ENCODE project (wgEncodeEH003472; Crawford Laboratory, Duke University). (C) Oligonucleotide-mediated pull-down in cycling
and mitotic cells. Bound fraction indicates binding of HSF1 or HSF2 to the
HSE-containing oligonucleotide (+). The scrambled oligonucleotide sequence
(−) lacks an HSE. WB indicates the total HSF1 and HSF2 protein levels in the
respective samples. (D) Single sections of confocal microscope images
showing localization of HSF1 (red) and HSF2 (green) in mouse male germ
cells during meiotic division I. DNA (stained with Hoechst) is shown in blue.
(Scale bar, 100 μm.)
Vihervaara et al.
Functions of HSF1 and HSF2 Are Tightly Interlinked, but Their Effects
on Promoters Are Profoundly Distinct. Previous genomewide stud-
ies in yeast (69), fly (70, 71), and humans (8, 72) identified the
HSE for HSF1, showing a striking conservation of the HSF1recognized DNA sequence over evolution. Our analyses corroborated the importance of inverted nGAAn pentamers for
HSF1 binding both in cycling and mitotic cells (Fig. S2B). By
revealing the HSF2-targeted HSEs in a genomewide scale, we
expected to find a major difference between the DNA sequences
preferred by HSF1 vs. HSF2. Despite their unique target sites in
the human genome (Figs. 1 B, E, and F and 5B; Fig. S2A), HSF1
and HSF2 recognized a staggeringly similar HSE (Fig. S2B).
Earlier footprinting studies have revealed that HSF2 is able to
bind shorter HSEs than HSF1 (19, 37). The ability of HSF2 to
bind less extensive HSEs could provide an advantage when
accessing HSEs in the compacted chromatin regions. The overlapping genomic coordinates and highly similar binding profiles
of HSF1 and HSF2 at the shared target sites (Figs. 1 C and D and
3A; Fig. S3C; Dataset S1) suggest their intimate interplay in transcriptional regulation. The resolution of our ChIP-seq analyses,
however, cannot distinguish HSF1-HSF2 heterotrimers from
homotrimers on adjacent pentamers of the same or nearby HSE.
Cancer cells display a nononcogene addiction to HSF1 as a result of ameliorated proteotoxic stress (5, 73). Moreover, the
binding profile of HSF1 in nontransformed cells radically differs
from that in cancer cells with high malignant potential (8). Because K562 cells are an erythroleukemia cell line and express high
basal levels of HSPs, HSF1 could have cancer-specific target genes
also in these cells. However, the low fold enrichments and the
limited number of HSF1 target sites in nonstressed K562 cells
(Fig. 1B) are in accordance with the HSF1 binding profiles in
nontransformed cells and in cells with low malignant potential (8).
The detailed analyses of target gene expression revealed HSF1
as a potent transactivator that responds instantly to stress (Figs.
1B and 2–4). Also HSF2 rapidly localized to the target sites (Fig.
1B), but it did not enhance transcription during 2 h of heat stress
(Figs. 2–4). HSF1 and HSF2 show similar recruitment kinetics to
the HSP70 promoter, but HSF2 is gradually degraded from the
HSE after 30 min of heat stress (25), indicating the need for
delicate regulation of the HSF1-HSF2 composition at the promoter. Our preliminary results show an HSF2-mediated effect
on transcription during prolonged stress when HSF2 levels have
already declined (Fig. S4F) (25) and suggest that HSF2 modifies
the chromatin landscape for transcriptional responses. HSF2 is
also involved in many developmental processes when the epigenetic features of the cells are determined (10, 12, 61), and it
has been shown to affect the chromatin compaction and integrity
(10). These results argue for an HSF2-mediated establishment of
the transcriptional environment and indicate profoundly distinct
mechanisms for HSF1 and HSF2 during their dynamic interplay
Vihervaara et al.
PNAS PLUS
in driving gene expression. The versatility of cellular processes
directed by HSF1 and HSF2 underscore the importance of
establishing their specific activators and inhibitors, PTM signatures, and chromatin-associated factors that direct HSFs to
their individual target loci.
Is HSF2 an Epigenetic Regulator of Cell Fate? An unexpected finding
of our studies was the ability of HSF2 to interact with the dividing chromatin where HSF1 was hardly detected (Figs. 1B and
6D). HSF2 has been reported to bind HSP promoters in mitosis
and suggested to mediate bookmarking of stress-responsive
genes (74, 75). We identified both HSF1 and HSF2 on chaperone genes in mitosis, including promoters of HSPA1A/HSP70.1,
HSPA1B/HSP70.2, HSPH1/HSP110, and HSPE1/HSP10 (Fig.
1C; Dataset S1). However, we did not detect HSF1-induced
transcription in mitosis (Fig. 5E; Fig. S4D), indicating an impaired ability of dividing cells to provoke transcriptional responses. HSF1 has been shown to recruit chromatin modifiers
and facilitate RNPII loading (76), which could explain why HSF1
localized to 25 target gene promoters in heat-treated mitotic
cells without inducing transcription (Fig. 5; Fig. S4D; Dataset
S1). The unbiased analyses by ChIP-seq identified a broad range
of mitotic target genes for HSF2 both under optimal growth and
stress conditions (Fig. 5A; Datasets S1 and S2). One prominent
unique HSF2 target gene in mitosis is MLL, a trithorax homolog
and a transcriptional coactivator that has been found to interact
with promoters in mitotic human cells, marking the genes for
early activation in G1 (77, 78). We discovered that HSF2 controls the cell cycle phase–dependent expression of MLL, which is
prerequisite for an efficient induction of MLL after mitotic silencing (Fig. 6A). Moreover, recent computational analyses
found MLL target promoters to be enriched with HSEs (77),
arguing for either cooperation or competition of MLL and HSFs
on the genome. Several studies have addressed how the memory
of cell fate is maintained during mitosis when most of the transcriptional regulators are erased from the chromatin (33). To this
end, the capacity of HSF2 to bind mitosis-specific target genes
both under optimal growth conditions and on stress (Figs. 1B and
5B; Dataset S1) indicates that HSF2 directs gene expression
throughout cell cycle progression.
Genomewide analyses in high resolution enable broad views
on the interplay of transcriptional regulators and chromatin state
in different cell types, cell cycle phases, and in response to various
stimuli. In this study, we characterized the HSF1- and HSF2driven transcriptional response to acute stress in cycling and mitotic cells. Our results revealed the molecular mechanisms that
maintain cellular homeostasis in cycling cells and identified
a dramatically impaired capacity of mitotic cells to provoke transcriptional responses, even when challenged with proteotoxicity.
We characterized the complete set of chaperones, cochaperones,
and ubiquitin genes that is directed by HSFs under acute stress
and highlighted the various processes that are transcriptionally
reprogrammed in proteotoxic conditions. We uncovered the
strikingly distinct mechanisms for HSF1 and HSF2 in orchestrating transcription and discovered HSF2 as an epigenetic regulator
that controls transcription throughout cell cycle progression. Future studies, expanding beyond acute heat shock, will establish
whether cells are able to epigenetically remember past environmental exposures, such as stress.
Materials and Methods
Cell Culture, Synchronization of Cells to Mitosis, and Heat Treatments. Human
K562 erythroleukemia cells were maintained at 37 °C in a humidified 5% CO2
atmosphere and cultured in RPMI medium (Sigma) containing 10% (vol/vol)
FCS, 2 mM L-glutamate, and streptomycin/penicillin. Cells were arrested to
mitosis using thymidine and nocodazole (39). Briefly, after 16 h in 2 mM
thymidine (Sigma), the cells were washed with PBS to allow cell cycle progression for 8 h. The cells were collected in S-phase by a second thymidine
PNAS | Published online August 19, 2013 | E3395
CELL BIOLOGY
whole machinery that maintains proteostasis. Beyond the protein
quality control, HSFs directed genes encoding transcriptional and
translational regulators, mitotic determinants, and core components of various signaling pathways (Fig. 4; Dataset S2). For example, TAF7 has been suggested to function as a transcriptional
checkpoint regulator by inhibiting RNPII phosphorylation at the
promoter (63, 64), whereas BANF1 and NUDC are key regulators
in mitosis required for correct spindle assembly, cytokinesis, and
nuclear envelope assembly (65–68). The stress response has dramatic effects on cellular physiology, but the basic mechanisms of
the adaptation processes such as the transcriptional and translational silencing or the stalling of the cell cycle progression are
not understood. The characterized HSF1- and HSF2-driven
transcriptional reprogramming will aid in elucidating the detailed
mechanisms that rapidly adjust cellular processes during stress, as
well as clarify how the processes are reestablished once favorable
conditions for proliferation are again restored.
treatment for 24 h. After cell cycle progression for 5 h, the cells were
arrested in mitosis with nocodazole (100 ng/mL; Fluka) for 12 h. The nocodazole was removed, and the cells were harvested, allowed to proceed the
cell cycle at 37 °C, or heat treated. The heat shock treatments were conducted in a water bath at 42 °C. The DNA content of the cells was determined by propidium iodide (PI) staining (40 μg/mL; Sigma) and
fluorescence-mediated counting by FACSCalibur (BD Biosciences). The FACS
histograms were generated using Cell Quest Pro-6.0 (BD Biosciences) and
Flowing Software 2.5 (Turku Centre for Biotechnology). The error bars in
statistical analyses indicate SDs.
scribed earlier (17) using ABI Prism 7900 (Applied Biosystems). The primers
were purchased from Oligomer (Helsinki) and the probes were purchased
from Roche Applied Science. Primer and probe sequences are listed in Table
S3. Relative quantities of the target gene mRNAs were normalized to
GAPDH, and the fold inductions were calculated against the respective
mRNA level in nontreated cells. All reactions were made in triplicate for
samples derived from at least three biological replicates. SDs were calculated
and are shown in the graphs. An independent two-tailed Student t test was
used to determine the P value when comparing mRNA levels between
scrambled-transfected and shHSF1- or shHSF2-transfected cells.
ChIP. HSF1- and HSF2-bound DNA fragments were isolated by ChIP using
a previously described protocol (11, 17) and the following ChIP-verified
antibodies: HSF1 (Spa-901; Enzo) and HSF2 (17). IgG (sc-2027; Santa Cruz)
was used as a negative antibody and AcH4 (06-866; Upstate) was used as
a positive antibody. PCR primers are listed in Table S2.
Western Blotting. Cells were lysed with buffer C [25% (vol/vol) glycerol, 20 mM
Hepes, pH 7.4, 1.5 mM MgCl2, 0.42 M NaCl, 0.2 mM EDTA, 0.5 mM PMSF, and
0.5 mM DTT], and the protein concentration in the soluble fraction was
measured using Bradford analysis. Twenty micrograms of total protein was
boiled in Laemmli sample buffer and subjected to SDS/PAGE followed by transfer to nitrocellulose membrane (Protran nitrocellulose; Schleicher & Schuell).
Proteins were analyzed with primary antibodies against HSF1 (Spa-901; Enzo),
HSF2 (3E2; Upstate), and β-TUBULIN (ab6046; Abcam). The secondary antibodies were HRP conjugated (GE Healthcare), and the blots were developed
using an enhanced chemiluminescence method (ECL kit; GE Healthcare).
High-Throughput Sequencing and Data Analysis. For sequencing, 10 ChIP
replicates per sample were collected. Sequencing libraries were generated
using New England BioLabs NEBNext kits, and adapters and primers were
from a Bioo Scientific AIR DNA Barcodes kit. Template amplification and
cluster generation were performed using the cBot and Truseq SR Cluster kit
for cBot v, and 36 nucleotides were sequenced with Illumina Genome Analyzer IIx using v5 TruSeq SBS sequencing kits. After quality trim and removal of
duplicates, the reads were mapped to the human genome (hg19) with Bowtie
(79). The peaks were called with MACS 1.4 (80), and a minimum fold enrichment of five times over input was set as a cutoff criterion for target sites.
Any site that exceeded the cutoff in the negative IgG sample was discarded.
Identification of HSF1- and HSF2-Targeted DNA Sequences and Genomic
Regions and Functional Annotation of Target Genes. The consensus DNA
sequences for HSF1 and HSF2 were identified by motif analysis of large DNA
datasets (MEME-ChIP) (81) using a 120-bp region centered on the summit
point. HSF1 and HSF2 target sites were annotated to genomic regions using
exon and intron coordinates provided by RefSeq and by defining a core
promoter to span from −1,200 to +300 bp from the transcriptional start site
(TSS). Fifty percent of peak length was centered on the summit point, and
peaks that fell on exon-intron boundaries are indicated as exons. Biological
processes associated with HSF1 or HSF2 target genes in cycling and mitotic
cells were analyzed with DAVID (53), which uses Fisher’s exact test for calculation of the P value for enriched gene ontology terms. The density signals
of HSF1, HSF2, and RNPII on the human genome were visualized with the
Integrative Genomics Viewer (82).
Depletion of HSF1 and HSF2 with RNAi by shRNA. HSF1 and HSF2 were depleted from the cells using shRNA constructs ligated into pSUPER vectors
(Oligoengine) as previously described (17). The vector-encoded oligonucleotides were specific for HSF1 (GCT CAT TCA GTT CCT GAT C) or HSF2 (CAG
GCG AGT ACA ACA GCA T). A scrambled sequence (GCG CGC TTT GTA GGA
TTC G) was used as a control. The shRNA constructs were transfected into
cells by electroporation (970 μF, 220 mV), and the cells were incubated for
72 h prior to harvesting. Synchronization of cells to mitosis was initiated
after a 7-h recovery from the transfection, allowing for simultaneous sample
preparation of the cycling and mitotic cells.
Oligonucleotide-Mediated Pull-Down Assay. The oligonucleotide-mediated
pull-down assay was performed as described previously (83) using biotinylated oligonucleotides (Oligomer). The double-stranded HSE contained
the sequence 5′-biotin-TCG ACT AGA AGC TTC TAG AAG CTT CTA G-3′ and
the scrambled control 5′-biotin-AAC GAC GGT CGC TCC GCC TGG CT-3′.
Buffer C extracts of 100–400 μg total protein were annealed to oligonucleotide (0.5 μM) in binding buffer [20 mM Tris·HCl, pH 7.5, 100 mM NaCl, 2 mM
EDTA, and 10% (vol/vol) glycerol] containing salmon sperm DNA (0.5 μg/μL).
The samples were precleared, and the oligonucleotides were precipitated
with a 50% (vol/vol) slurry of UltraLink streptavidin beads (Pierce). Bound
fractions were washed three times with binding buffer containing 0.1%
Triton X-100. DNA-bound proteins were eluted with Laemmli buffer and
detected by SDS/PAGE and Western blotting.
Immunofluorescence of HSF1 and HSF2 in Dividing Male Spermatocytes. Testes
of 60- to 80-d-old C57BL/6N mice were isolated, fixed in 4% (wt/vol) paraformaldehyde, and sectioned to 4 μm. All mice were handled according to
the institutional animal care policies of the Åbo Akademi University (Turku,
Finland). Confocal immunofluorescence analyses were performed as previously described (11) using primary antibodies against HSF1 and HSF2 (20)
and secondary antibodies conjugated to Alexa 488 or Alexa 568 (Invitrogen).
The DNA was stained with Hoechst 33342 (H-1399; Molecular Probes).
Images for all channels were sequentially captured from a single confocal
section using a Zeiss Meta510 confocal microscope. For analyzing the meiotic
divisions, stage XII of the mouse seminiferous cycle was selected, and dividing spermatocytes in meiotic division I were imaged. The channels were
merged using ImageJ (84).
Quantitative Real-Time RT-PCR. RNA was isolated using the RNeasy kit (Qiagen), and 1 μg of total RNA was DNaseI treated (Promega) and reverse
transcribed with Moloney murine leukemia virus reverse transcriptase RNase
H(–) (Promega). Real-time RT-PCR reactions were prepared and run as de-
ACKNOWLEDGMENTS. We thank Michael J. Guertin for insightful discussions and for sharing his expertise in bioinformatics. The Functional
Genomics Unit (University of Helsinki) is acknowledged for performing the
high-throughput sequencing, Jukka Lehtonen for expert assistance in
computational analyses, and Diana M. Toivola, Johanna K. Björk, and Eva
Henriksson for constructive advice during manuscript preparation. This work
was financially supported by the Academy of Finland, the Sigrid Jusélius
Foundation, the Finnish Cancer Organizations, Åbo Akademi University
Foundation, the Tor, Joe, and Pentti Borg Foundation, BioCenter Finland,
and the Turku Doctoral Program of Biomedical Sciences (A.V. and A.N.E.).
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Supporting Information
Vihervaara et al. 10.1073/pnas.1305275110
Fig. S1. Identification of heat shock factor 1 (HSF1) and HSF2 binding sites in cycling and mitotic K562 cells with ChIP-seq. (A) Schematic presentation of the
sample preparations, sequencing, and data analysis. (B) HSF1-bound respective HSF2-bound DNA fragments were isolated by ChIP as previously described (1, 2).
IgG was used as a negative and AcH4 as a positive control antibody. The quality of each sample was determined using PCR for a known HSF target locus, the
HSPA1A/HSP70.1 promoter, and a non-HSF target, the β-ACTIN promoter. Ten individual ChIP replicates for each sample were combined for sequencing. PCR of
HSPA1A/HSP70.1 and β-ACTIN promoters are shown for the pooled samples. (C) Sequencing libraries were generated using Illumina’s standard protocol. The
distribution of DNA fragment sizes for each sample library are shown. (D) Table showing the number of reads, unmapped reads, and duplication percent of the
sequenced samples.
1. Åkerfelt M, et al. (2010) Heat shock transcription factor 1 localizes to sex chromatin during meiotic repression. J Biol Chem 285(45):34469–34476.
2. Östling P, Björk JK, Roos-Mattjus P, Mezger V, Sistonen L (2007) Heat shock factor 2 (HSF2) contributes to inducible expression of hsp genes through interplay with HSF1. J Biol Chem
282(10):7077–7086.
Vihervaara et al. www.pnas.org/cgi/content/short/1305275110
1 of 7
Fig. S2. HSF1 and HSF2 recognize a similar consensus DNA sequence but display distinct binding profiles in the human genome. (A) The number of HSF1-specific
(red), HSF2-specific (green), and HSF1-HSF2 shared (blue) target sites in untreated (C) and heat-treated (HS) cycling and mitotic cells. The areas are not proportional
to the number of their constituents. (B) Consensus DNA-binding sequences for HSF1 and HSF2 in heat-treated cycling (Left) and mitotic (Right) cells.
Vihervaara et al. www.pnas.org/cgi/content/short/1305275110
2 of 7
Fig. S3. Binding sites of HSF1 and HSF2 within functional regions of the human genome. (A) HSF1- and HSF2-targeted genomic regions in nontreated (C) and
heat-treated (HS) cycling and mitotic cells. Exons and introns are from RefSeq; promoter is defined to span from −1,200 to + 300 bp from the transcriptional
start site. (B) Fold enrichment over input of each HSF1 (red) and HSF2 (green) target site on promoter (Prom.) or on gene body (Coding) in heat-treated cycling
and mitotic cells. Gene body is the coding sequence from +301 to the end of the gene. Average fold enrichment is shown with a line, and the dashed gray line
indicates fold enrichment five, which was set as a cutoff criterion for HSF target sites. In cycling cells, the HSF target sites were categorized according to the
presence (+) or absence (−) of RNPII. RNPII localization in nontreated cycling K562 is recovered from the Encyclopedia of DNA Elements (ENCODE) project
(wgEncodeEH000529; Iyer Laboratory, University of Texas). (C) HSF1 (red) and HSF2 (green) enrichments on introns (Upper), exon (Lower Left), and intergenic
region (Lower Right). The density signal of RNPII in nontreated cycling K562 cells (blue) is recovered from the ENCODE project (wgEncodeEH000616; Snyder
laboratory, Yale University). The scale for HSF and input samples is 0–100.
Vihervaara et al. www.pnas.org/cgi/content/short/1305275110
3 of 7
Fig. S4. Analyses of stress responses in cycling and mitotic cells. (A) mRNA expression of HSPH1 and DNAJB6 in cells deficient of both HSF1 and HSF2 (shHSF1shHSF2). Scrambled-transfected cells (Scr) express HSF1 and HSF2 and were used as a control. (B) Mitotic cells are unable to induce ubiquitin expression on heat
stress. No clear HSF1 or HSF2 binding to ubiquitin genes was detected in mitosis. (C) The mRNA levels of UBB, UBC, RPS27A, and UBA52 in heat-treated mitotic
cells. The mRNA levels were analyzed as in Fig. 2, except that the relative expressions were calculated against the respective untreated sample in cycling cells
(shown in Fig. 3C), enabling the comparison of ubiquitin levels between cycling and mitotic cells. (D) The mRNA levels of DNAJB6 and MRPS6 in mitotic cells in
the presence (Src) or absence of HSF1 (shHSF1) or HSF2 (shHSF2). (E) Flow cytometric analysis of heat-treated cycling and mitotic cells showing the percent cells
with fragmented DNA (sub G1/G0), indicative of cell death. Error bars denote SDs. (F) mRNA levels of HSPA1A/HSP70 in cycling cells showing HSF2-dependent
mRNA expression after 2 h of heat stress. mRNA levels and statistical significances were analyzed as in Fig. 2, and the SDs are indicated.
Vihervaara et al. www.pnas.org/cgi/content/short/1305275110
4 of 7
Table S1. HSF1 and HSF2 occupancy on DNAJ/Hsp40 genes
HSF1
HSF2
Cycling
Mitosis
Cycling
Mitosis
Family
Gene
C
HS
C
HS
C
HS
C
HS
DNAJA
DNAJA1
DNAJA2
DNAJA3
DNAJA4
DNAJB1
DNAJB2
DNAJB3
DNAJB4
DNAJB5
DNAJB6
DNAJB7
DNAJB8
DNAJB9
DNAJB11
DNAJB12
DNAJB13
DNAJB14
DNAJC1
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
11.2
—
—
—
9.6
6.6
—
9.0
3.9
20.1
—
—
—
—
2
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
2.1
3.9
—
—
—
5.3
—
—
—
—
11.2
—
—
—
—
—
—
—
—
5.0
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
14.7
—
—
—
5.6
5.8
—
8.6
—
12.0
—
—
—
—
—
—
—
—
3.9
2.8
2.5
—
3.1
—
—
—
—
—
—
—
—
—
2.2
—
—
—
3.9
—
—
—
4.6
—
—
—
—
7.9
—
—
2.9
—
—
—
—
4.6
DNAJC2
DNAJC3
DNAJC4
DNAJC5
DNAJC5B
DNAJC5G
DNAJC6
DNAJC7
DNAJC8
DNAJC9
DNAJC10
DNAJC11
DNAJC12
DNAJC13
DNAJC14
DNAJC15
DNAJC16
DNAJC17
DNAJC18
DNAJC19
DNAJC21
DNAJC22
DNAJC24
DNAJC25
DNAJC27
DNAJC28
DNAJC30
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
12.9
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
2.1
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
2.0
—
—
—
2.4
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
4.2
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
3.1
—
11.9
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
2.8
—
3.5
—
—
—
2.8
—
—
3.7
—
—
—
—
—
3.9
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
3.5
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
3.8
DNAJB
DNAJC
Binding
site
Paused
RNPII*
Promoter
Intron
Exon
—
Promoter
Promoter
—
Promoter
—
Promoter
—
—
Promoter
—
Intron
—
—
Intron,
exon
—
—
Intron
—
Intron
Both
Promoter
Promoter
Exon
—
Intron
Intron
Promoter
—
Exon
—
Promoter
Intron
—
—
—
—
—
—
—
—
Promoter
Yes
Yes
Yes
No
Yes
Yes
No
Yes
Yes
Yes
No
No
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
NA
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
No
Yes
Yes
No
Yes
NA
No
NA
Yes
NA
NA
Yes
Fold enrichments ≥2 are shown. C, control; HS, heat treated; NA, not analyzed; RNPII, RNA polymerase II.
*The RNPII density signal is recovered from ENCODE (wgEncodeEH000616; Snyder Laboratory, Yale University).
Vihervaara et al. www.pnas.org/cgi/content/short/1305275110
5 of 7
Table S2. ChIP-PCR primers
Amplicon
Gene
β-ACTIN
HSPA1A
Primer (5′ to 3′)
Forward
Reverse
Forward
Reverse
AACTCTCCCTCCTCCTCTTCCTC
GAGCCATAAAAGGCAACTTTCGG
CCATGGAGACCAACACCCT
CCCTGGGCTTTTATAAGTCG
Start*
End*
Length
−213
−73
141nt
−243
+14
258nt
*From transcriptional start site.
Table S3. Primers and probes used in quantitative RT-PCR
Amplicon
Transcript
NM_012111.2
mRNA
AHA1
Forward
Reverse
Probe
NM_003860.3
BANF1
Forward
Reverse
Probe
NM_001008897.1 CCT1
Forward
Reverse
Probe
NM_006565.2
CTCF
Forward
Reverse
Probe
NM_007065.3
CDC37
Forward
Reverse
Probe
NM_005494.2
DNAJB6 Forward
Reverse
Probe
NM_004417.2
DUSP1
Forward
Reverse
Probe
NM_001404.4
EEF1G
Forward
Reverse
Probe
NM_002046
GAPDH Forward
Reverse
Probe
NM_006644.2
HSPH1
Forward
Reverse
Probe
NM_002154.3
HSPH2
Forward
Reverse
Probe
NM_005933.2
MLL
Forward
Reverse
Probe
NM_032476.3
MRPS6
Forward
Reverse
Probe
NM_006600.2
NUDC
Forward
Reverse
Probe
NM_002737.2
PRKCA
Forward
Reverse
Probe
NM_006601.5
p23
Forward
Reverse
Primers and probes (5′ to 3′)
CATCAGCACCCTCAAAACAG
CCCACTGGGTCTACTGACTCTC
# 37
GAACCGTTACGGGAACTGAA
GCTCCCCACTGGCTTCTC
# 53
CCCATGGGAGAAGTCAAATG
CAAGCAATTTTTGCATTTACGA
# 37
GGCTTGAGAGCTGGGTTCTA
CGACTGCATCACCTTCCAT
#34
TTCCGGCAGTTCTTCACTAAG
CTTCATGGCCTTCTCGATG
# 11
GGAAGGGACCCATTTTCATT
CTGAACGCAGAGAAAAACGA
# 38
CGAGGCCATTGACTTCATAGA
CCAGCTTGACTCGATTAGTCCT
#83
AACCCCACCCCCTTTCTT
TACTGAGCAGCGATGAGAGC
# 28
GTTCGACAGTCAGCCGCATC
GGAATTTGCCATGGGTGGA
FAM-ACCAGGCGCCCAATACGACCAA-TAMRA
AGCCATGTTGTTGACTAAGCTG
TCTGTAAAGAAGGAGGGGACTG
# 90
CAGCAGACACCAGCAGAAAA
CCTTGGATCCAGCTTGAGAG
# 13
TGAATACAACCCCAATGATGAA
GGCAGATCCATGCTAGTTGC
# 63
CGAGCTGGCTTTAATCCTGA
AGGTTTTCCAAGTCCCTCACT
# 82
GATGGGGAGCTCTACAATGAA
GGCTCCACCACTCCATCTTA
# 39
TCGACTGGGAAAAACTGGAG
CTCTGCTCCTTTGCCACAC
# 83
AGAGAAGTCGACTCCCTAGCAG
CGTACCACTTTGCAGAAGCA
Vihervaara et al. www.pnas.org/cgi/content/short/1305275110
Start*
End* Length
Intron-spanning assay
+613
+690
73nt
Yes Fourth intron spanned
+466
+574
109nt
Yes First intron spanned
+748
+856
109nt
Yes Fifth intron spanned
+225
+309
85nt
Yes First intron spanned
+816
+944
129nt
Yes Fifth intron spanned
+471
+589
119nt
Yes Fifth intron spanned
+962
+1092
131nt
Yes Second intron spanned
+117
+217
101nt
Yes First intron spanned
+752
+847
96nt
Yes Third intron spanned
+1887
+1953
67nt
Yes 13th intron spanned
+11390 +11467 78nt
Yes 30th intron spanned
+190
+303
114nt
Yes First intron spanned
+771
+882
112nt
Yes Sixth intron spanned
+1843
+1916
74nt
Yes Fourth intron spanned
+217
+323
107nt
Yes First intron spanned
6 of 7
Table S3. Cont.
Transcript
mRNA
NM_001177413.1 RPS27A
NM_005642.2
TAF7
NM_003333.3
UBA52
NM_018955.2
UBB
NM_021009.4
UBC
Primers and probes (5′ to 3′)
Probe
Forward
Reverse
Probe
Forward
Reverse
Probe
Forward
Reverse
Probe
Forward
Reverse
Probe
Forward
Reverse
Probe
# 70
TGTCTCTTCCTTTTCCTCAACC
CTATCGTATCCGAGGGTTCAA
# 39
AAAGGAGGCAGAAAATCAAGG
CCCTGCCTGTGACCAGAC
# 80
GGTGGCATTATTGAGCCTTCT
GTGAAGGCGAGCATAGCACT
# 61
TGGTATCCGCTAACAGGTCA
GCCTTCACATTTTCGATGGT
# 39
AGGCAAAGATCCAAGATAAGGA
GGACCAAGTGCAGAGTGGAC
# 11
Start*
Amplicon
End* Length
Intron-spanning assay
+105
+217
113nt
Yes First intron spanned
+1307
+1369
63nt
No
315
+404
90nt
Yes First intron spanned
+117
+221
105nt
No
Nonintron spanning assay
+2352
+2483
132nt
No
Nonintron spanning assay
An intron-less gene
Probes and GAPDH primers are from Roche Universal Probe Library.
*From transcriptional start site.
Dataset S1.
Genomic target loci for HSF1 and/or HSF2 as identified by ChIP-seq
Dataset S1
Dataset S2.
Complete Gene Ontology analyses of HSF1 and HSF2 target genes
Dataset S2
Vihervaara et al. www.pnas.org/cgi/content/short/1305275110
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