MOLECULAR AND CELLULAR BIOLOGY, Jan. 2010, p. 344–353
Copyright © 2010, American Society for Microbiology. All Rights Reserved.
Vol. 30, No. 1
Regulation of the Histone Demethylase JMJD1A by Hypoxia-Inducible
Factor 1? Enhances Hypoxic Gene Expression and Tumor Growth?†
Adam J. Krieg,1* Erinn B. Rankin,1Denise Chan,1Olga Razorenova,1
Sully Fernandez,2and Amato J. Giaccia1
Division of Radiation and Cancer Biology, Department of Radiation Oncology, Center for Clinical Sciences Research,
Department of Radiation Oncology, Stanford University, Stanford, California 94303-5152,1and University of
Pennsylvania School of Medicine, Philadelphia, Pennsylvania 191042
Received 6 April 2009/Returned for modification 8 July 2009/Accepted 15 October 2009
The hypoxia-inducible transcription factors (HIFs) directly and indirectly mediate cellular adaptation to
reduced oxygen tensions. Recent studies have shown that the histone demethylase genes JMJD1A, JMJD2B, and
JARID1B are HIF targets, suggesting that HIFs indirectly influence gene expression at the level of histone
methylation under hypoxia. In this study, we identify a subset of hypoxia-inducible genes that are dependent
on JMJD1A in both renal cell and colon carcinoma cell lines. JMJD1A regulates the expression of ad-
renomedullin (ADM) and growth and differentiation factor 15 (GDF15) under hypoxia by decreasing promoter
histone methylation. In addition, we demonstrate that loss of JMJD1A is sufficient to reduce tumor growth in
vivo, demonstrating that histone demethylation plays a significant role in modulating growth within the tumor
microenvironment. Thus, hypoxic regulation of JMJD1A acts as a signal amplifier to facilitate hypoxic gene
expression, ultimately enhancing tumor growth.
Cellular hypoxia occurs when the demands of growth and
metabolism of a tissue surpass the vascular oxygen supply. In
response to hypoxia, cells undergo specific alterations in gene
expression patterns geared to promote cell survival and main-
tain homeostasis. This response not only is important in nor-
mal development but also is a critical part in the progression of
cancers (7). Hypoxia has been implicated in activating the
metabolic shift to anaerobic glycolysis, promoting the epithe-
lial-to-mesenchymal transition (EMT), inducing the secretion
of proangiogenic factors, and remodeling the extracellular ma-
trix. Although several transcription programs are activated in
response to hypoxia, the hypoxia-inducible factors (HIFs) reg-
ulate a critical repertoire of genes, making them central regu-
lators of the cellular response to hypoxia (10, 34).
The HIFs are heterodimeric transcription factors consisting
of an oxygen-sensitive alpha subunit (HIF-1?, HIF-2?, or HIF-
3?) and a constitutively expressed HIF-1? subunit (also known
as the arylhydrocarbon nuclear translocator [ARNT]). Under
conditions where oxygen concentration is not limiting, HIF-?
subunits are hydroxylated by prolyl-hydroxylases, targeting them
for ubiquitin-mediated degradation by the von Hippel-Lindau
tumor suppressor (VHL) (18, 19). Under hypoxic conditions,
HIF-? protein is stabilized, translocates to the nucleus, dimer-
izes with ARNT, and binds hypoxia-responsive elements
(HREs) in the regulatory regions of target genes (51). HIF-1?
and HIF-2? will bind the same sequences in cells but do not
have completely overlapping abilities to regulate genes (5, 17,
44). Under certain conditions, HIF-3? functions as a dominant
negative, antagonizing the activity of HIF-1 and HIF-2 (32).
Several hundred genes are induced in response to hypoxia, and
a great deal of research has been focused on identifying direct
HIF target genes (34). The massive transcriptional reorganization
mediated by hypoxia and HIFs suggests that changes in histone
modification would create epigenetic reinforcement of this phe-
notype (20). HIF-1? function has been shown to influence and be
influenced by histone deacetylases (22, 33), yet comparatively
little is known regarding HIF-dependent dynamics of histone
methylation (8, 21). In a screen for HIF-regulated changes in
gene expression, we and others have identified several Jumonji
C-domain-containing histone demethylase (JHDM) promoters as
direct binding targets of HIF-1? and HIF-2? (3, 43, 53, 55).
Histone demethylases constitute a large and diverse family of
enzymes, each with a specific ability to influence transcriptional
activation or repression that is dependent on the specific histone
residue targeted for demethylation (46); however, the specific
roles of Jumonjis in modulating transcriptional responses to hyp-
oxia remain unknown.
Using microarray analysis and chromatin immunoprecipita-
tion, we identified HIF targets including the adrenomedullin
gene (ADM) and the growth and differentiation factor 15 gene
(GDF15) and show that JMJD1A reduces histone H3K9 meth-
ylation at these promoters during hypoxia. Furthermore, we
demonstrate that loss of JMJD1A is sufficient to reduce tumor
growth in vivo, consistent with its role in regulating histone
methylation during hypoxia. These studies identify a transcrip-
tional regulatory circuit where induction of JMJD1A by HIF-1?
acts as an epigenetic signal amplifier to enhance cellular re-
sponses to hypoxia.
MATERIALS AND METHODS
Cell lines and culture conditions. All cell lines were maintained in Dulbecco
modified Eagle medium (DMEM) supplemented with 10% fetal bovine serum
* Corresponding author. Mailing address: Division of Radiation and
Cancer Biology, Department of Radiation Oncology, Center for Clin-
ical Sciences Research, Department of Radiation Oncology, Stanford
University, Stanford, CA 94303-5152. Phone: (650) 723-7366. Fax:
(650) 723-7382. E-mail: email@example.com.
† Supplemental material for this article may be found at http://mcb
?Published ahead of print on 26 October 2009.
(FBS). Small interfering RNA (siRNA) transfections were carried out using
Dharmacon Smart Pools with Dharmafect 1 transfection reagent according to
manufacturer’s protocol (Dharmacon, Laffayette, CO). Short hairpin RNA
(shRNA) retroviral constructs against JMJD1A were purchased from Open Bio-
systems (Huntsville, AL). Retroviral constructs were packaged and introduced
into cells as described previously (57). For hypoxia treatments, cells were plated
at the desired density 12 h prior to placement in a hypoxia chamber (Invivo2-400;
Ruskin Technologies, Leeds, United Kingdom) maintained at 0.5 to 2% oxygen
for 0 to 20 h, depending on the experiment. For in vitro growth assays, cells (105)
were plated in triplicate in 6-cm plates and counted every 3 days as described
ChIP. Chromatin immunoprecipitation (ChIP) assays were performed as de-
scribed previously (26) with the following modifications. Hypoxia-treated cells
were fixed within the chamber to avoid reoxygenation. For HIF-1? and HIF-2?
immunoprecipitations, 120 ?g of sonicated chromatin (measured as protein) was
incubated with 10 ?g of anti-HIF-1? or HIF-2? antibodies, respectively. For
histone ChIPs, sonicated chromatin was immunoprecipitated according to guide-
lines provided by the manufacturer (Abcam). Data were analyzed in a fashion
similar to that described by Johnson et al. (21). Relative enrichment was mea-
sured by quantitative real-time PCR using a titration of pooled input samples as
a standard curve. Histone H3 methylation signals were normalized to input and
bulk histone H3 signal, the corresponding IgG/H3 ratio was subtracted, and the
fold change in methylation relative to the normoxic control cells was calculated.
For calculation of fold difference of methylation (see Fig. 5D), the H3 normal-
ized methylation signal with JMJD1A knockdown was divided by the correspond-
ing signal from the nonsilencing control cells for each time point.
For high-throughput ChIP (ChIP-chip) analysis, immunoprecipitated DNA
was amplified as described previously (37) and hybridized to NimbleGen tiled
promoter arrays (Roche NimbleGen, Madison, WI) spanning approximately
23,000 promoter regions in the human genome. Promoter summary reports
provided by NimbleGen were linked to expression information in Microsoft
Access to correlate HIF binding to RCC4 expression (see Table S1 in the
supplemental material). Signal Map was used to confirm binding and to extract
the coordinates of putative binding peaks for validation experiments. Antibodies
used for ChIPs were anti-HIF-1 (BD Biosciences), anti-HIF-2 (Novus), histone
H3 (Abcam), histone H3K9me1 (Abcam), histone H3K9me2 (Abcam), histone
H3K9me3 (Abcam), and JMJD1A (Abcam). Rabbit IgG (Sigma) was used for a
nonspecific IgG control. Primer sequences are available upon request.
Expression microarray analysis. All microarray sample preparations and hy-
bridizations were carried out with Stanford Human Exonic Evidence Based
Oligo (HEEBO) arrays according to protocols available from Pat Brown’s lab
(http://cmgm.stanford.edu/pbrown/protocols/index.html). HEEBO arrays con-
tain probes for 31,000 unique genes and 8,500 alternate transcripts. Data from
scanned microarrays were entered into the Stanford Microarray Database
(SMD) for normalization and analysis.
For comparing expression in RCC4 cells to that in RCC4 cells with recon-
stituted VHL expression (RCC4?VHL cells), amino-allyl-labeled cDNA was
reverse transcribed from 25 ?g of total RNA and coupled to Cy dyes as de-
scribed at http://cmgm.stanford.edu/pbrown/protocols/RTaminoAllylCoupling
.html. cDNA from RCC4 or RCC4?VHL cells was labeled with Cy5 and hy-
bridized to common reference cDNA from RCC4?VHL cells labeled with Cy3.
Labeled cDNA was hybridized and washed as described at http://cmgm.stanford
.edu/pbrown/protocols/Direct_Label_Protocol1.html. Expression changes were
calculated by averaging data from duplicate RCC4 samples and calculating fold
change in expression compared to RCC4?VHL controls.
For profiling the effect of JMJD1A siRNA knockdown in RCC4?VHL cells,
RNA was amplified from 1 ?g total RNA using the Amino Allyl MessageAmp II
aRNA kit (Ambion) and labeled with Cy dyes as described at http://cmgm
.stanford.edu/pbrown/protocols/Amplified_Protocol1.html. Samples were from
independent triplicate experiments and were labeled with Cy5 and hybridized to
common reference cDNA from untreated RCC4?VHL cells. Data were ana-
lyzed using multicomponent Significance analysis of microarrays (SAM) (50) to
identify genes significantly changed among the siRNA transfections. Genes with
a false-discovery rate lower than 0.5% were extracted to calculate fold changes
relative to the normoxic siControl samples. Fold change was calculated to iden-
tify genes induced greater than 1.5-fold by hypoxia (SiCon-Hypox) and genes
where hypoxic expression with siJMJD1A is at least 1.5 times lower than that with
the equivalent hypoxic siControl (SiD1A-Hypox). These two groups were im-
ported into GeneVenn (42) to identify regions of overlap (see Table S2 in the
QRT-PCR. Gene expression was measured using quantitative real-time PCR
(QRT-PCR) exactly as described previously (26) using the 18S rRNA or TATA-
binding protein (TBP) gene as an internal control. Primer sequences are avail-
able upon request.
In vivo experiments. All animal experiments were performed in accordance
with institutional and national guidelines and approved by Stanford University’s
Administrative Panel on Laboratory Animal Care (APLAC). Male SCID mice,
4 to 6 weeks old, were obtained from Charles River Laboratories. HCT116 cells
stably expressing shRNA to JMJD1A or a nonsilencing control sequence were
counted and resuspended in sterile phosphate-buffered saline (PBS). Three
million cells were injected into the flank of the animal and measured with
calipers at regular intervals.
Jumonji domain histone demethylase genes are direct HIF
target genes. To identify direct and functionally relevant HIF
target genes involved in chromatin regulation, we performed a
directed screen by combining high-throughput chromatin im-
munoprecipitation (ChIP-chip) with gene expression analysis.
The RCC4 clear-cell renal cell carcinoma line was used as a
model system because of abundant normoxic expression of
HIF-1? and HIF-2? due to genetic inactivation of von Hippel-
Lindau (VHL) (35). We probed tiled arrays representing
23,000 human promoter regions for HIF-1? and HIF-2? bind-
ing. Using a global average of promoter enrichment (provided
as NimbleGen promoter summaries), we biased our search to
identify promoter regions with the highest HIF enrichment.
Using gene expression profiling, we identified genes induced
greater than 1.5-fold in RCC4 cells compared to RCC4
cells with reconstituted VHL expression (RCC4?VHL cells).
These genes were then sorted for HIF-1? or HIF-2? binding
(Fig. 1A shows a schematic representation; see Table S1 in the
supplemental material for complete tabulated results). A com-
mon phenomenon with genome-wide ChIP experiments is
nonfunctional binding, where a transcription factor is shown to
bind but fails to regulate nearby genes (29). Even though our
initial filter comparing VHL-repressed expression to HIF bind-
ing would be expected to select functional HIF targets, VHL
has also been shown to regulate several cellular processes
independently of HIF (4, 49). Therefore, we followed up po-
tential HIF targets only if they were also induced by hypoxia in
RCC4 cells expressing functional VHL (RCC4?VHL cells).
The screen identified several known HIF target genes, includ-
ing those for vascular endothelial growth factor (VEGF), 6-phos-
phofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3), and
stanniocalcin 2 (STC2), providing validity for our ChIP-chip
analysis (12, 28, 36). HIF binding at these promoters was con-
firmed by ChIP-PCR (Fig. 1B). The Jumonji C-terminal-do-
main-containing histone demethylase (JHDM) gene JMJD1A
was also identified as a putative HIF target. JHDMs have
received a great deal of attention for their ability to demethyl-
ate histones and either activate or repress transcription (46).
JMJD1A (also known as JHDM2A and KDM3A) has recently
been shown to be a coactivator for nuclear hormone receptors
and myogenic factors by demethylating dimethyl lysine 9 on
histone H3 (H3K9me2) of target promoters (30, 31, 38, 56).
We then searched through our binding data and identified
JMJD2B as another strong target of HIF binding. JMJD2B
recognizes tri- and dimethylated lysine 9 (H3K9me3/2) on
histone H3, reducing both modifications to the monomethyl-
ated state (11, 24, 54). Both HIF-1? and HIF-2? bind near the
JMJD1A and JMJD2B promoters (Fig. 1B), confirming recent
reports (3, 43, 53, 55).
VOL. 30, 2010JMJD1A REGULATES HYPOXIC GENE EXPRESSION 345
Specificity of our screen was validated by ChIP-PCR to the
promoter of PCNA, a region with no visible HIF enrichment
and no hypoxic regulation. We then retrospectively searched
our expression data to identify additional Jumonji domain pro-
teins that might be regulated by hypoxia. Expression of the
histone H3 lysine 4 (H3K4me3) demethylase JARID1B was
increased in RCC4?VHL cells during hypoxia (1.7-fold) (see
Table S2 in the supplemental material). Consistent with our
finding, recent studies have also identified JARID1B as a hy-
poxia-inducible gene (16, 55).
Hypoxic transcriptional induction of the JHDMs was con-
firmed in RCC4?VHL cells. Expression of JMJD1A, JMJD2B,
and JARID1B was induced and sustained for at least 24 h upon
cellular exposure to hypoxia (Fig. 1D), similar to the case for
VEGFA, PFKFB3, and STC2 (Fig. 1C). Our approach combin-
ing high-throughput ChIP and gene expression analysis has
FIG. 1. Jumonji domain histone demethylases are hypoxia inducible in a HIF-dependent manner. (A) Experimental scheme of the HIF binding
to expression screen. RCC4 renal cell carcinoma cells were processed for ChIP-chip as described in Materials and Methods. Promoters
corresponding to genes induced greater than 1.5-fold with loss of VHL were sorted by mean HIF binding. An illustrative set of data is shown (the
full data set is in Table S1 in the supplemental material). (B) Validation of HIF-1? and HIF-2? binding to selected promoters. VEGF serves as
experimental validation control for both HIF-1? and HIF-2?. Multiple amplicons were used to screen promoters containing widely spaced HREs
and are denoted A, B, or C as necessary. (C) QRT-PCR analysis or VEGF, PFKFB3, and STC2 expression in RCC4?VHL cells exposed to either
21% or 0.5% O2for 0, 4, 8, 12, or 24 h. (D) QRT-PCR analysis for JMJD1A, JMJD2B, and JARID1B expression. Data for panel C and D are plotted
as fold change normalized to TBP gene expression. Error bars represent standard deviations.
346 KRIEG ET AL.MOL. CELL. BIOL.
identified at least three different JHDMs as potential HIF
targets, suggesting that HIF plays an important role in regu-
lating widespread epigenetic phenomena through alterations
in histone methylation.
Jumonji domain histone demethylases are hypoxia induc-
ible in a HIF-dependent manner. To determine if hypoxic
induction of histone demethylases is dependent on HIF-1?, we
next utilized wild-type and HIF-1?-deficient mouse embryonic
fibroblasts (MEFs). Previous studies have indicated that
MEFs have nonfunctional HIF-2? protein (40). Real-time
PCR analysis demonstrated that the hypoxic induction of
JMJD1A, JMJD2B, and JARID1B was significantly reduced
in HIF-1?-deficient MEFs compared to wild-type MEFs,
demonstrating dependence on HIF-1? for hypoxic induction
(Fig. 2A). JMJD1A expression was also robustly induced in
MCF-7 breast cancer and HCT116 colon cancer cells, as was
that of JMJD2B and VEGF (Fig. 2B).
Transfection of siRNAs to HIF-1?, HIF-2?, and ARNT
reduced the hypoxic induction of JMJD1A in RCC4?VHL
cells in a statistically significant manner, indicating that in
certain cell types, JMJD1A may be regulated by either HIF-1?
or HIF-2? (Fig. 2C). In contrast siRNAs to HIF-1? and
ARNT, but not HIF-2?, resulted in a statistically significant
reduction of JMJD1A expression under hypoxia in MCF-7 cells.
VEGF expression was disrupted by knockdown of HIF-2? and
ARNT, confirming functional knockdown of HIF-2 and previous
reports that VEGF is primarily a target of HIF-2? in renal cell
carcinoma (17, 44). In MCF-7 cells, hypoxic expression of VEGF
was reduced in a statistically significant manner by knockdown of
HIF-1, HIF-2, and ARNT, demonstrating functional knockdown
of HIF-1? and HIF-2?. These experiments demonstrate that the
regulation of JMJD1A by HIF-1? is a conserved phenomenon in
both mice and humans, while HIF-2? may regulate JMJD1A in
certain cellular contexts. Identification of JMJD1A as a HIF-1?
target reveals an important mechanistic link between the cellular
microenvironment, HIF activation, and epigenetic regulation of
JMJD1A regulates hypoxic gene expression. Of the three
JHDM genes identified in our experiments, JMJD1A seemed
the most likely to have a direct effect on hypoxic gene induc-
tion. JMJD1A was one of the strongest HIF-1? peaks identified
by the ChIP-chip experiment (Fig. 1A), and its ability to func-
tion as a coactivator has been well characterized (56). Since
many coactivators identified within specific transcription path-
ways were later found to enhance HIF-1? activity (6), we
hypothesized that JMJD1A might also mediate hypoxic gene
In order to identify potential JMJD1A targets during hyp-
oxia, RCC4?VHL cells were transfected with siRNA to
JMJD1A or control siRNA and exposed to hypoxia (0.5% O2)
or normoxia (21% O2), and gene expression was analyzed
using Stanford HEEBO microarrays (see Materials and Meth-
ods). Knockdown of JMJD1A mRNA was approximately 3-fold
under normoxia and hypoxia (Fig. 3A). We identified 821
genes induced ?1.5-fold by hypoxia in cells transfected with
control siRNA (Fig. 3B, left circle), a result similar to those in
earlier reports (34). Of these genes, 53 were dependent on
JMJD1A for full hypoxic induction (region of overlap in Fig.
3B). Included in this data set were a number of known HIF
targets such as ADM, EDN1, SERPINE1, PLAUR, and
FIG. 2. Jumonji domain histone demethylases are hypoxia inducible
in a HIF-dependent manner. (A) QRT-PCR measurement of murine
Jmjd1a, Jmjd2b, and Jarid1b in wild-type and HIF-1? knockout MEFs
(HKO) exposed to 21%, 2%, and 0.5% O2for 20 h. Pgk1 serves as a
control for a HIF-1?-specific gene. Statistical significance was calculated
using Student’s t test:*, P ? 0.05;**, P ? 0.01;***, P ? 0.001. Asterisks
refer to comparisons within the respective oxygen concentrations.
exposed to 21% or 0.5% oxygen for 20 h. (C) QRT-PCR measurement of
hypoxic expression of JMJD1A and VEGF in RCC4?VHL cells after
transfection with siRNAs to HIF-1?, HIF-2?, and ARNT. Data represent
the averages from six independent experiments. Statistical significance
was calculated using Student’s t test:*, P ? 0.05;**, P ? 0.01;***, P ?
VEGF in MCF-7 cells transfected as for panel C. Data represent the
averages from three independent experiments, measured in triplicate and
normalized to 18S rRNA. Error bars indicate standard errors of the
means. Statistical significance was calculated using Student’s t test:*, P ?
0.05;**, P ? 0.01.
VOL. 30, 2010JMJD1A REGULATES HYPOXIC GENE EXPRESSION 347
HMOX1 (complete lists are in Table S2 in the supplemental
material). We also identified 208 genes with decreased hypoxic
expression with loss of JMJD1A but were not induced in the
control cell line, implying that hypoxic induction of JMJD1A
plays a broader role in maintaining gene expression during
hypoxia (Fig. 3B, right circle; see Table S2 in the supplemental
Validation of JMJD1A-dependent expression was con-
firmed using QRT-PCR (Fig. 3C). ADM, SERPINE1 (PAI1),
EDN1, and HMOX1 had statistically significant dependence
on JMJD1A for hypoxic induction. These genes were chosen
for further analysis because they were known HIF targets and
had known functions, making them more fruitful targets for
later functional analysis. Though not statistically significant,
JMJD1A increased hypoxic expression of SERPINB8, EDN2,
and GDF15 (data not shown), confirming a trend of regulation
by JMJD1A. The majority of hypoxia-induced genes, including
STC2 and PFKFB3, showed little or no dependence on
JMJD1A (Fig. 3C; see Table S2 in the supplemental material).
The specific regulation of some but not all hypoxia-induced
genes by JMJD1A suggests that multiple mechanisms regulate
hypoxic gene expression, highlighting the importance of pro-
moter-specific recruitment of transcription regulators.
Because of the clear link between VHL loss, HIF activation,
and progression of renal cell carcinoma, cell lines like RCC4
are ideal systems for the study of HIF activity and hypoxic
transcription phenomena. A significant disadvantage of using
RCC-derived cells is the generally poor rate of tumor initiation
in xenograft experiments, making it difficult to evaluate the
functional aspects of gene expression. We found that JMJD1A
is also robustly induced in HCT116 colon carcinoma cells (Fig.
2B), which grow well in tumor xenograft experiments, making
them a better system for studying in vivo function of JMJD1A.
In HCT116 cells transfected with siRNA to JMJD1A, there
was a robust knockdown of JMJD1A RNA and protein (Fig.
4A and B). Accordingly, the hypoxic induction of ADM and
GDF15 was robustly and significantly dependent on hypoxic
JMJD1A expression (Fig. 4C and D). For use in longer-term
studies, we also established two HCT116-derived cell lines
expressing shRNA to JMJD1A. Compared to a line expressing
a nonsilencing control construct, JMJD1A mRNA was reduced
approximately 2- to 3-fold in both cell lines in normoxia (Fig.
4E). While both shJMJD1A-1 and shJMJD1A-2 significantly
suppressed hypoxic induction of ADM by approximately 25 to
30% compared to the nonsilencing control (Fig. 4E), cells
expressing shJMJD1A-2 maintained effective knockdown
more consistently over time, making it a more useful line for
further experiments (data not shown). These results demon-
strate that hypoxic induction of JMJD1A is crucial for optimal
hypoxic expression of targets and not solely a result of reduced
expression under normoxia.
Transcriptional regulation by JMJD1A during hypoxia is
due to changes in histone methylation of target promoters.
Since JMJD1A induces gene expression by specifically reducing
the methylation of histone H3K9me2 and H3K9me1 to the
unmethylated state in vitro and in vivo (56), reduction of
JMJD1A expression would be expected to increase H3K9 di-
methylation on target promoters such as ADM and GDF15.
HCT116 cells expressing shJMJD1A-2 shRNA or a nonsilenc-
ing control construct were exposed to hypoxia for 4 or 16 h and
fixed with formaldehyde for chromatin immunoprecipitation.
Cells grown in normoxia were fixed at time zero as a control for
hypoxic changes. Using chromatin immunoprecipitation fol-
lowed by QPCR analysis, we measured the ratio of H3K9me1,
H3K9me2, and H3K9me3 to bulk histone H3 on regions ap-
proximately 200 bp downstream of the transcription start sites
of ADM and GDF15. A representative ChIP on the ADM
promoter is depicted in Fig. 5A, demonstrating robust enrich-
ment over the IgG control for all histone antibodies tested.
After 16 h of hypoxia, H3K9me2 was approximately two times
higher in the shJMJD1A-2 cells than in the nonsilencing con-
trol, proportional to the reduction of JMJD1A (Fig. 4C). This
result was confirmed by calculating the fold change in histone
methylation compared to the normoxic, nonsilencing control
cells for four independent experiments and averaging the data
at each time point (Fig. 5C). While there was no statistically
significant difference in HeK9me1 or H3K9me3 for either
FIG. 3. JMJD1A regulates hypoxic induction of a subset of hypoxia-
regulated genes in RCC4?VHL cells. (A) Quantitative RT-PCR of
JMJD1A expression in RCC4?VHL cells transfected with siRNA to
JMJD1A (siD1A) and exposed to 21% or 0.5% oxygen for 16 h.
(B) Venn diagram graphically showing the intersection between genes
induced greater than 1.5-fold by hypoxia in the siControl-transfected
cells (left circle) and genes reduced at least 1.5-fold under hypoxia with
siJMJD1A compared to the hypoxic siControl (right circle). Genes
dependent on JMJD1A for hypoxic induction are depicted in the over-
lap. (C) RCC4?VHL cells were transfected as for panel A, and the
expression of genes identified in panel B (ADM, SERPINE1, EDN1,
and HMOX) was measured by QRT-PCR. STC2 and PFKFB3 serve as
examples of two JMJD1A-independent hypoxia inducible genes. Data
are from six experiments measured in triplicate (? standard errors of
the means) and normalized to the normoxic control siRNA (SiCon).
Statistical significance was calculated using Student’s t test:*, P ? 0.05;
**, P ? 0.01.
348KRIEG ET AL.MOL. CELL. BIOL.