Genome-wide binding of the orphan nuclear receptor TR4 suggests its general role in fundamental biological processes.

Abstract

The orphan nuclear receptor TR4 (human testicular receptor 4 or NR2C2) plays a pivotal role in a variety of biological and metabolic processes. With no known ligand and few known target genes, the mode of TR4 function was unclear.
We report the first genome-wide identification and characterization of TR4 in vivo binding. Using chromatin immunoprecipitation followed by high throughput sequencing (ChIP-seq), we identified TR4 binding sites in 4 different human cell types and found that the majority of target genes were shared among different cells. TR4 target genes are involved in fundamental biological processes such as RNA metabolism and protein translation. In addition, we found that a subset of TR4 target genes exerts cell-type specific functions. Analysis of the TR4 binding sites revealed that less than 30% of the peaks from any of the cell types contained the DR1 motif previously derived from in vitro studies, suggesting that TR4 may be recruited to the genome via interaction with other proteins. A bioinformatics analysis of the TR4 binding sites predicted a cis regulatory module involving TR4 and ETS transcription factors. To test this prediction, we performed ChIP-seq for the ETS factor ELK4 and found that 30% of TR4 binding sites were also bound by ELK4. Motif analysis of the sites bound by both factors revealed a lack of the DR1 element, suggesting that TR4 binding at a subset of sites is facilitated through the ETS transcription factor ELK4. Further studies will be required to investigate the functional interdependence of these two factors.
Our data suggest that TR4 plays a pivotal role in fundamental biological processes across different cell types. In addition, the identification of cell type specific TR4 binding sites enables future studies of the pathways underlying TR4 action and its possible role in metabolic diseases.

Full text

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RESEARCH ARTICLEOpen Access
Genome-wide binding of the orphan nuclear
receptor TR4 suggests its general role in
fundamental biological processes
Henriette O’Geen1†, Yu-Hsuan Lin2,3†, Xiaoqin Xu1, Lorigail Echipare1, Vitalina M Komashko1, Daniel He1,
Seth Frietze1, Osamu Tanabe2, Lihong Shi2, Maureen A Sartor3, James D Engel2, Peggy J Farnham1*
Abstract
Background: The orphan nuclear receptor TR4 (human testicular receptor 4 or NR2C2) plays a pivotal role in a
variety of biological and metabolic processes. With no known ligand and few known target genes, the mode of
TR4 function was unclear.
Results: We report the first genome-wide identification and characterization of TR4 in vivo binding. Using
chromatin immunoprecipitation followed by high throughput sequencing (ChIP-seq), we identified TR4 binding
sites in 4 different human cell types and found that the majority of target genes were shared among different
cells. TR4 target genes are involved in fundamental biological processes such as RNA metabolism and protein
translation. In addition, we found that a subset of TR4 target genes exerts cell-type specific functions. Analysis of
the TR4 binding sites revealed that less than 30% of the peaks from any of the cell types contained the DR1 motif
previously derived from in vitro studies, suggesting that TR4 may be recruited to the genome via interaction with
other proteins. A bioinformatics analysis of the TR4 binding sites predicted a cis regulatory module involving TR4
and ETS transcription factors. To test this prediction, we performed ChIP-seq for the ETS factor ELK4 and found that
30% of TR4 binding sites were also bound by ELK4. Motif analysis of the sites bound by both factors revealed a
lack of the DR1 element, suggesting that TR4 binding at a subset of sites is facilitated through the ETS transcription
factor ELK4. Further studies will be required to investigate the functional interdependence of these two factors.
Conclusions: Our data suggest that TR4 plays a pivotal role in fundamental biological processes across different
cell types. In addition, the identification of cell type specific TR4 binding sites enables future studies of the
pathways underlying TR4 action and its possible role in metabolic diseases.
Background
There are an estimated 1400 site-specific DNA binding
factors encoded in the human genome [1]. Although these
factors can influence transcription when their binding
sites are cloned in front of core promoters, they usually do
not function alone. Most often, individual transcription
factors collaborate to orchestrate gene expression through
combinatorial binding to regulatory regions in chromatin
[2]. These regions, termed cis modules, thereby activate,
repress or otherwise epigenetically modify the transcrip-
tional responses of individual genes. Elucidating the
position and activities of individual cis modules using
reporter genes is time consuming and expensive. With
recent advances in DNA sequencing technology, it is now
feasible to generate global protein-DNA interaction pro-
files by chromatin immunoprecipitation (ChIP) followed
by ultra-high-throughput sequencing [3]. Cis modules can
then often be identified by applying bioinformatics
searches for one or more cis motifs recognized by unre-
lated alternative factors near the binding sites of the factor
analyzed by ChIP-seq or by the co-localization of bound
sites for two or more unrelated different site-specific
factors.
Nuclear receptors (NRs) represent a special class of tran-
scription factors that direct target gene transcription in a
ligand-dependent fashion. NRs contain a DNA-binding
* Correspondence: pjfarnham@ucdavis.edu
† Contributed equally
1Genome Center, University of California at Davis, Davis, CA 95616, USA
Full list of author information is available at the end of the article
O’Geen et al. BMC Genomics 2010, 11:689
http://www.biomedcentral.com/1471-2164/11/689
© 2010 O’Geen et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in
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domain that recognizes a specific DNA sequence, as well
as a ligand binding domain that renders these factors
environmentally-dependent regulators via interaction with
distinct cognate ligands [4]. The great majority of NRs
homodimerize or heterodimerize with another NR, and
then bind to two copies of a repeated hexanucleotide
sequence (called a half-site) separated by variable spacing
[5]. The half-site consensus, AGGTCA, can occur in either
orientation and variation from the consensus allows
numerous alternative binding sites of (probably) variable
affinity [5]. Based on the number of spacer nucleotides
separating the two half-sites and the orientation of the two
half-sites relative to each other, NR binding sites have
been categorized as direct repeats (DR0 - DR8), everted
repeats (ER0 - ER8) or inverted repeats (IR0-IR8) [5].
NR2C2 (human testicular receptor 4, TR4, in the older
nomenclature) belongs to the nuclear receptor super-
family and is termed an orphan receptor due to the fact
that no ligand has been discovered [6-8]. TR4 was initi-
ally identified in hypothalamus, prostate, and testis
cDNA libraries, but has since been demonstrated to be
broadly expressed in many physiological systems [9,10].
For example, TR4 has been shown to activate target
gene expression in liver carcinoma HepG2 cells [11]. In
contrast, in erythroid cells, TR4 can heterodimerize with
another closely related family member (TR2, or NR2C1)
and binds to a DR1 (direct repeats with one nucleotide
spacer) element to repress target gene transcription
[12-15]. The binding affinity of the TR4 homodimer for
the DR1 element in vitro is equivalent to that of the
TR2:TR4 heterodimer [15], and TR4 mRNA is more
abundant than TR2 in human erythroid cells (Tanabe,
unpublished observations). However, the broader phy-
siological functions for, and the in vivo genome-wide
binding patterns of, this broadly expressed nuclear
receptor are obscure. We therefore chose to initially
investigate genome wide TR4 binding anticipating that
these studies might reveal some common, but also per-
haps some tissue-specific, metabolic processes to which
this factor contributes.
In this study we investigated the first genome-wide
identification of cellular targets of TR4 and preliminary
characterization of TR4 in vivo binding in multiple cell
types, including those in which TR4 has been suggested
to be an activator (liver) and cells in which TR4 has
been suggested to be a repressor (blood). Using ChIP-
seq, we determined TR4 in vivo binding in four human
ENCODE cell lines: K562 erythroleukemia cells, HepG2
liver carcinoma, HeLa cervical carcinoma, and
GM12878 immortalized lymphoblast cells. TR4 binding
patterns identified in the four diverse cell lines suggest
that this factor controls cell metabolism by binding to
the proximal promoter regions that are common to sev-
eral hundred genes. Motif analysis shows that TR4
strongly prefers a DR1 sequence to all other categories
of repeat elements in vivo. By integration of TR4 bind-
ing data with histone modification patterns and other
genomic structures, we predict, and then experimentally
test, putative cis modules.
Results and Discussion
Identification of genome-wide TR4 binding sites
With no known ligand and few proposed binding sites
in mouse and human cell lines [16-19], the function of
the TR4 orphan nuclear receptor was largely unknown
when we began these studies. Previous studies examined
its function in different blood cells and found that TR4
bound to the CD36 promoter in macrophages [20] and
to the GATA1 enhancer G1HE [12] in CD34+cells, but
only after in vitro differentiation for 11 days. To further
elucidate biological roles for TR4, we set out to identify
in vivo TR4 binding sites throughout the entire human
genome using chromatin immunoprecipitation followed
by high throughput sequencing (ChIP-seq). We wanted
to compare its binding profiles in cells derived from dif-
ferent tissue types. We chose to identify TR4 targets in
cell types selected by the ENCODE Consortium (http://
www.genome.gov/10005107), including human chronic
myelogenous leukemia cells (K562), human cervical car-
cinoma cells (HeLa), lymphoblastoid cells (GM12878),
and hepatocellular carcinoma cells (HepG2). By charac-
terizing its binding in these cell lines, we could compare
TR4 binding sites with other transcription factor binding
sites and histone marks determined by other ENCODE
groups examining these same cell types. We first vali-
dated the presence of TR4 protein in these cell lines by
Western Blot analysis (see Additional file 1). We began
our ChIP experiments using the hematopoietic cell line
K562 and the liver cell line HepG2, but were unable to
confirm TR4 enrichment at targets previously published
in the specialized and differentiated hematopoietic cells.
Therefore, we initially proceeded without having positive
controls for the ChIP assays. We prepared sequencing
libraries from ChIP experiments from two independently
grown batches of HepG2 cells. Samples were sequenced
using the Illumina GA2 platform and ChIP-seq data
were analyzed using the Sole-search software (http://
chipseq.genomecenter.ucdavis.edu/cgi-bin/chipseq.cgi;
[21]). Only sequences that uniquely matched those in
the human genome were retained for analysis. 9.7 mil-
lion sequence reads were obtained from replicate 1 and
8.2 million from replicate 2. Using the Sole-search peak
calling program with default settings (FDR 0.0001, alpha
value 0.001), 1,547 and 2,246 TR4 binding sites were
identified in HepG2 cells for replicate 1 and replicate 2,
respectively. 1,243 (80%) of the 1,547 peaks called from
replicate 1 were also present in the 2,246 peaks called
from replicate 2. This overlap demonstrates good
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reproducibility between biological replicates. To obtain
the final list of 2,672 TR4 binding sites in HepG2 cells,
all reads (17.8 million) from both biological replicates
were merged. We then performed TR4 ChIP experi-
ments for the other cell types and used standard PCR to
confirm enrichment at three sites (TNFIAP1, SCAP,
ECSIT) previously identified in HepG2 cells (see Addi-
tional file 2 for primer information; see Additional file 3
for representative PCR validation). ChIP-seq libraries
were then prepared from two biological replicates using
the TR4 antibody resulting in 23 million sequence reads
for HeLa cells, 30 million for GM12878 cells and 16
million for K562 cells (see Additional file 4 for a sum-
mary of the data analysis). 1,767 TR4 binding sites were
identified in HeLa cells, 1,180 TR4 binding sites in
GM12878 cells and 732 TR4 binding sites in K562 cells;
see Figure 1 for the binding patterns of TR4 across the
entire chromosome 12 in all four cell types.
The position to which a transcription factor binds rela-
tive to the start site of transcription can provide insight
into how the factor regulates transcription. For example,
E2F family members bind to core promoter regions and
are thought to stimulate transcription by interaction
with the basal transcription machinery [22,23]. In con-
trast, other transcription factors, such as GATA1 or
TCF4 (TCF7L2), show significant binding to sites often
located more than 10 kb away from the gene that they
regulate [21,24], suggesting that these factors may regu-
late transcription by looping mechanisms. Although the
number of TR4 binding sites varied among the different
cell types, location analysis revealed that TR4 preferen-
tially binds close to the transcription start sites of
its target genes. The majority of TR4 binding sites
(65-82%) is located either in the proximal promoter (up
to 2 kb upstream of TSS) or is found within the first
exon or first intron of a RefSeq gene. In HeLa cells, 36%
100
50
0
200
100
0
200
100
0
200
100
0
NR2C1FGD6
93,980,00093,990,000 94,000,000
K562
GM12878
HeLaS3
HepG2
200
100
0
200
100
0
200
100
0
200
100
0
KRAS
25,280,000 25,290,00025,300,000
K562
GM12878
HeLaS3
HepG2
200
100
0
200
100
0
200
100
0
150
75
0
K562
GM12878
HeLaS3
HepG2
A
B
(+)
(-)
Figure 1 Comparison of TR4 targets in 4 different cell types. ChIP-seq binding patterns of TR4 (NR2C2) from K562, GM12878, HeLa, and
HepG2 cells are shown (A) for entire chromosome 12 and (B) for target genes KRAS and TR2 (NR2C1). The number of tags reflecting the ChIP
enrichments is plotted on the y axis and chromosomal coordinates (hg18) are shown on the x axis. RefSeq genes are indicated in (+) and (-)
orientation. Target genes KRAS and TR2 are in (-) orientation as indicated by the arrows.
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of TR4 binding occurred in the proximal promoter and
41% in the gene region, mainly in the first exon or first
intron (Figure 2A and 2B). To further characterize TR4
binding sites, TR4 ChIP-seq reads were organized into
100 bp bins relative to the start site of transcription.
The distribution of TR4 peaks relative to the transcrip-
tion start site demonstrated that the majority of TR4
binding occurs between 1 kb upstream and 1 kb down-
stream of a TSS (Figure 2C). For example, 1,135 (63%)
of the 1,767 HeLa binding sites were located within ± 1
kb from a TSS (see Additional file 4 for results from all
cell types). This preference was also reflected in an ele-
vated median height of peaks near a TSS; the median
peak value was 114 for peaks within ± 1 kb of a TSS,
but only 50 for peaks outside this range. For the rest of
our studies, we therefore focused on the targets found
within 1 kb of a TSS. This encompassed 1,154 TR4
binding sites for HeLa, 1,732 for HepG2, 537 for K562
and 535 for GM12878 cells.
A significant fraction of TR4 binding sites was shared
among cell types (Figure 1B). For example, out of the
537 TR4 binding sites in K562 cells, 504 (94%) are also
occupied in HeLa cells, 471 (88%) are also bound in
HepG2 cells and 406 (76%) are also bound in GM12878
cells. When comparing 1,157 TR4 binding sites from
HeLa with 1,732 from HepG2 cells, we found 922 (80%)
were shared TR4 target sites. We next matched the TR4
peaks to the nearest gene. In some cases more than one
peak matched to a given gene. As a consequence, the
number of TR4 binding sites is slightly higher than the
number of target genes. We compared 1,135 TR4 target
genes from HeLa, 535 from K562, 530 from GM12878
and 1,688 from HepG2 cells (Figure 3). 532 target genes
were shared in at least 3 cell types and 332 target genes
were shared among all four cell types. While blood cells
shared most of their TR4 targets, liver cells contained
the largest number of unique target genes. TR4 may
regulate genes important for basic biological processes
A
B
1 2 3 4 9
Intron
1 2 3 4 5 6 7 8 9 10 11 12 13
Exon
400
300
200
100
0
Number of peaks
C
300
200
100
0
Number of peaks
Distance to TSS
-3000 -2000 -1000
0
100020003000
gene
(41%)
proximal
promoter
(36%)
3’ proximal (1%)
3’ distal (2%)
gene desert (3%)
5d (9%)
distal promoter (2%)
3d (3%)
Figure 2 Location analysis of TR4 binding sites in HeLa cells.
(A) Shown is a pie chart indicating the distribution of called TR4
peaks. Categories are based on the distance of the peak to the
nearest RefSeq gene: 5 d (10 - 100 kb upstream of TSS), distal
promoter (2 - 10 kb upstream of TSS), proximal promoter (<2 kb
upstream of TSS), gene (exon or intron), 3’ proximal (<2 kb
downstream of the last exon), 3’ distal (2 - 10 kb downstream of the
last exon), 3 d (10 - 100 kb downstream of the last exon), and gene
desert (>100 kb from a RefSeq gene). (B) Distribution of peaks
found within genes. (C) Histogram showing the distribution of peak
distances relative to the transcription start site (TSS) of the nearest
gene. Peaks were combined in 100 bp bins
TR4/K562
(535)
TR4/HepG2
(1,688)
TR4/HeLa
(1,135)
TR4/GM
(530)
11
11
9
17
11
42
332
400
56
9
183
51
20
756
102
Figure 3 Overlap of TR4 target genes in 4 cell types. A target
gene is defined as the nearest gene to a ChIP-seq peak. In some
cases a target gene was contained more than one peak. Genome-
wide TR4 ChIP-seq has identified 535 target genes in K562, 1,688 in
HepG2, 1,135 in HeLa, and 530 in GM12878 cells within ± 1 kb of a
transcription start site. 332 genes are identified as common targets
in the 4 cell types.
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shared in multiple cell types, while it may play an addi-
tional role in regulating cell type specific genes.
TR4 target genes are involved in fundamental biological
processes
As shown above, the majority of TR4 targets are shared
between different cell types. To shed light on the common
function of genes targeted by TR4, gene ontology analysis
was performed using ConceptGen (http://conceptgen.
ncibi.org/core/conceptGen/index.jsp; [25]) to identify
the functional categories enriched in the overlapping
targets in 4 cell types (p-value < 0.05, modified Fisher’s
exact test). All Entrez Genes were used as background to
determine the significance of over-representation. Cate-
gories of TR4 target genes are highly enriched in funda-
mental biological processes, such as RNA metabolism and
protein translation (ribosome) (Figure 4A). In addition,
TR4 may also regulate cell type-specific genes. To test this
hypothesis, we performed gene ontology analysis on genes
found in only one cell type. The number of unique target
genes in K562, HeLa, and GM12878 cells was not suffi-
cient to perform meaningful gene ontology analysis. How-
ever when 756 TR4 target genes specific to HepG2 cells
were analyzed, we found some unique functional cate-
gories (Figure 4B). HepG2 specific target genes were sig-
nificantly enriched for ubiquitin cycle, nucleosome,
chromatin assembly and metabolic processes, particularly
those involving organic acid, carbohydrates, and lipids.
Interestingly, a few previous studies have suggested a role
for TR4 in gluconeogenesis [16]. Furthermore, TR4 may
exert its function by sensing lipids and the presence of
fatty acids was found to enhance cofactor recruitment to
TR4 [26] suggesting an important role for lipids in TR4
function.
In recent years it has become evident that transcrip-
tion factors often play dual roles, affecting activation as
well as repression of target genes. Previous studies have
implicated TR4 in both activation and repression of cel-
lular target genes [7]. TR4 binds to DNA as a homodi-
mer, but preferentially forms heterodimers with the
orphan receptor TR2 [27]. Recently, a global atlas for
transcription factor networks has been assembled based
on physical protein-protein interactions using mamma-
lian two hybrid data [28]. This study identified TR4
(NR2C2), Nuclear Receptor Interacting Protein 1 NRIP1
(RIP140), and histone deacetylases HDAC 3 and
HDAC4 as proteins interacting with TR2 (NR2C1).
NRIP1 may function as a corepressor or coactivator
depending on the interacting protein [29]. Furthermore,
post translational modifications of TR4 influence its
interaction with cofactors [30]. Phosphorylation of TR4
is accomplished by MAP kinases and results in recruit-
ment of NRIP1. On the other hand, dephosphorylated
TR4 recruits the coactivator pCAF. We wanted to deter-
mine whether TR4 target genes are expressed or
silenced. For this purpose, we matched TR4 target genes
in HeLa and HepG2 cells (1,135 and 1,688 respectively)
to their RNA expression values from Illumina expres-
sion arrays (Figure 5). The median expression value of
TR4 target genes in HeLa and HepG2 cells (median
expression value 535 and 504, respectively) is higher
than the median expression value of all genes from the
HepG2 expression array (median expression value 219).
TR4 target genes are also expressed at higher levels
than a set of 3000 randomly selected genes from the
HepG2 expression array (median expression value 228).
Based on RNA expression analysis, TR4 target genes are
generally expressed.
The correlation between TR4 binding and expression
of target genes suggests that TR4 binds to open accessi-
ble chromatin regions. To test this hypothesis, we exam-
ined the epigenetic signature at TR4 binding sites using
ChIP-seq data of various histone marks in K562 cells.
Overlap of TR4 binding sites with histone marks typical
for open and repressed chromatin was determined using
the gffOverlap tool from Sole-search (http://chipseq.gen-
omecenter.ucdavis.edu/cgi-bin/chipseq.cgi; [21]). A dis-
tance of 200 base pairs between peaks was allowed to
take nucleosome positioning into account. A remarkable
534 of the 537 TR4 target sites in K562 cells were also
occupied by H3K4me3, which is a mark for accessible
A
B
Spliceosome
Structural constituent of ribosome
Macromolecule biosynthetic process
Translation
RNA binding
RNA processing
RNA splicing
mRNA metabolic process
Cellular biosynthetic process
1E01E-21E-41E-61E-8
Significance of enrichment
Ubiquitin cycle
Cellular biosynthetic process
Macromolecular complex assembly
Chromatin assembly
Macromolecule biosynthetic process
Nucleosome assembly
Pyrimidine metabolism
Organic acid metabolic process
Translation
Lipid biosynthetic process
Cell cycle
Carbohydrate metabolic process
1E0 1E-2 1E-41E-6
Significance of enrichment
Figure 4 Functional enrichment analysis of TR4 target genes.
(A) Targets common to all 4 cell types and (B) targets unique to
HepG2 cells. Significantly enriched gene ontology terms for
biological processes are shown on the y axis; the x axis represents
p-values for each enriched category.
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chromatin. No significant overlap with the repressive
chromatin marks H3K27me3 or H3K9me3 was found
(2 and 5 peaks, respectively). It has been shown in yeast
and also human cells that transcription factors often
bind in the linker region between nucleosomes [3,31].
To determine whether TR4 binding occurs in nucleo-
some depleted regions, we analyzed sequence tag density
for TR4 and H3K4me3 binding relative to the transcrip-
tion start sites (Figure 6). TR4 binding was highest
within 100 base pairs upstream of the TSS while the his-
tone mark H3K4me3 is lowest in this region and reach-
ing maximum where TR4 binding tails off, suggesting
predisposition of TR4 binding sites to the linker region.
Motif analysis suggests the importance of ETS family
members in TR4 action
In vitro experiments have shown that TR4 binds to the
direct repeat (DR) of AGGTCA, which is the consensus
binding site for a number of nuclear hormone receptors
including estrogen receptor alpha and PPAR. Further
studies have indicated that TR4 can bind to direct
repeats separated by zero to five nucleotides (DR0 -
DR5) [11,13,17,32]. However, all previous studies were
performed using in vitro assays. We used the de novo
motif discovery program MEME to identify motifs over-
represented in TR4 binding sites to determine if TR4
has the same specificity in vivo. To allow identification
of DR elements and its spacing and flanking nucleotides,
the minimum motif length was set between 12 (length
of two half sites with no spacing in between) and 20
nucleotides (length of two half sites with up to 8 nucleo-
tides in between). The canonical DR motif with one
nucleotide spacing (DR1) was significantly overrepre-
sented in all four cell types with the preferred spacing
nucleotide being an A or G (Figure 7A). The canonical
DR1 motif accounts for about 150 TR4 binding sites
(28% in K562, 9% in HepG2, 13% in HeLa, and 35% in
GM12878 cells). Interestingly, the % of peaks having a
DR1 motif is much higher in the blood cell lines (K562
and GM12878) than in the other two cell types. The
lack of the DR1 motif in the remaining peaks may indi-
cate that TR4 associates with some sites only indirectly
by binding to a different transcription factor.
Transcription factors often regulate expression of
nearby genes in combination with other transcription
factors through complex cis regulatory modules [33].
Our initial motif analysis revealed the significant recur-
rence of an ETS motif in addition to the DR1 element.
Members of the ETS transcription factor family such as
ELK4, E74A, and GABPA recognize the ETS core motif
GGAA. Using 13,010 human promoter sequences, the
ETS motif has been identified as one of those motifs
exhibiting statistically significant clustering near the
transcription start site [34]. The ETS motif was predo-
minantly found in the promoters of genes with essential
cellular functions, such as ribosomal genes, mitochon-
drial ribosomal genes, basal transcription factor genes
and proteosomal genes. The ETS motif is not only
found at genes regulating similar processes as TR4 tar-
get genes, but also preferentially occurs 100 base pairs
Distance from TSS
Tags (xe+04)
−3000−2000
−1000
0
100020003000
0
2
4
6
8
10
TR4
H3K4me3
Figure 6 TR4 binding relative to nucleosomes. Positions of the
histone mark H3K4me3 and TR4 occupancy are plotted for the 735
genes bound by TR4 in K562 cells. Sequence tags in bins of 100
base pairs are plotted on the y axis; distance to transcription start
site is shown on the x axis.
Average expression values
0
1000
2000
3000
TR4
HeLA
TR4
HepG2
All
genes
Random
Figure 5 Expression analysis of TR4 target genes. Box-and-
whisker diagrams show the range of expression values of TR4
bound genes in HeLa and HepG2 cells in comparison to expression
values of all genes present on the HepG2 expression array and to
the set of 3000 randomly selected genes. Expression values are
plotted on the y axis. The central line in the box-and-whisker plots
shows the position of the median, the upper and lower boundaries
of the box represent the location of the upper (75th percentile) and
the lower (25th percentile) quartiles, respectively. Data outliers are
not shown.
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upstream of a transcription start site. The ETS motif
occurs in a significant portion of TR4 binding sites
(35% in K562, 57% in HepG2, 53% in HeLa, and 24%
in GM12878 cells). Only about 10% of target genes
contain both the DR1 and the ETS motif (Figure 7A).
Combining both motifs can account for 67-78% of
TR4 peaks (70% in K562, 78% in HepG2, 74% in
HeLa, and 67% in GM12878 cells) suggesting a
combinatorial role for ETS family members in TR4
function. Similar results were obtained using other de
novo motif discovery programs such as NHR-Scan [5]
and W-ChIPMotifs [35].
It has been postulated that the true binding site for
transcription factors should be located under the center
of the peak [36]. We analyzed the distribution of both
motifs relative to the center of the TR4 binding sites
K562 (537)
DR1
ETS
DR1 (28%)
ETS (35%)
DR1+ETS
(7%)
neither (30%)
neither (22%)
DR1+ETS
(12%)
DR1 (9%)
ETS (57%)
DR1
6e-288
ETS
2e-233
HepG2 (1,732)
ETS Core Motif
GGAA
or
CCTT
CCTT
DR1 Consensus
AGGTCAnAGGTCA
or
TCCAGTnTCCAGT
TnTCCAGTTCCAGT T
HeLa (1,154)
DR1
ETS
DR1 (13%)
ETS (53%)
DR1+ETS
(8%)
neither (26%)
neither (33%)
DR1+ETS
(8%)
DR1 (35%)
ETS (24%)
DR1
ETS
GM12878 (535)
B
A
3e-208
3e-242
1e-142
1e-385
2e-263
1e-117
DR1 Conse
AGGTCAnA
ETS Co
GGAA
nsus
AGGTCAA
e
Frequency
0
20
40
60
0.0
DR1 distribution
0.2 0.4 0.60.8 1.0
ETS distribution
Frequency
0.00.2 0.40.60.81.0
150
100
50
0
Figure 7 Motif analysis of TR4 binding sites. (A) Sequences for TR4 binding sites located within 1 kb upstream and downstream of a TSS
were retrieved. Significantly overrepresented motifs within TR4 binding sites were identified by MEME. The number of targets is indicated in
parenthesis. E-values indicate significance of a given motif. Pie charts show occurrence of DR1 alone, ETS alone, DR1 and ETS, and neither of
these motifs within TR4 binding sites. (B) DR1 motif and ETS core motif are depicted in either orientation. Occurrence of DR1 and ETS motifs
relative to TR4 peak center in HeLa cells is shown in a histogram. Peak frequency is plotted along the y axis; distance from the peak center is
plotted on the x axis. Similar results were obtained with the other 3 cell types, histograms are not shown.
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and found that the DR1 as well as the ETS motif are
located under the peak center (Figure 7B). The close
proximity of these binding sites suggests a cis regulatory
network involving TR4 and ETS family members.
ETS transcription factor ELK4 co-occupies TR4 target sites
We wanted to test the hypothesis that TR4 and a mem-
ber of the ETS family co-localize with TR4 in vivo using
ChIP-seq. Motif analysis implicates the ETS family, but
does not provide information as to which family mem-
ber might bind to TR4 target sites. There is a high
degree of functional redundancy between different
members of the ETS transcription factors. Comparison
of ELK1 and GABPA binding regions revealed redun-
dant as well as unique targets between the two ETS
family members [37,38]. It has also been shown that
ETS transcription factors interact with other transcrip-
tion factors to regulate gene expression. For example,
ELK1 is thought to function through cooperation with
the serum response factor SRF [37,39]. ChIP-chip analy-
sis showed that 22% of all ELK1 binding regions were
also bound by SRF, while the majority of ELK1 targets
is SRF-independent.
To explore the possibility that ETS transcription fac-
tors might cooperate with TR4, we performed ChIP-seq
analysis of ELK1 as well as ELK4 in HeLa cells and bind-
ing sites were determined using Sole-search. 2,312 ELK4
peaks were identified from 21 million reads and 702
ELK1 peaks were identified from 13 million reads, with
86% of the ELK1 sites also being ELK4 binding sites (see
Additional file 4). When we compared the 1,135 TR4 tar-
gets present within 1 kb of a TSS with 1,715 ELK4 targets
found within 1 kb of a TSS, a significant overlap of 30%
was observed (Figure 8A; see Figure 9A for ChIP-seq
binding pattern). To identify the motifs utilized for TR4
recruitment at the 346 TR4 binding sites that are also
occupied by ELK4, we performed motif analysis using
MEME. The ETS motif was highly overrepresented
(E-value 3.3e-310), while the DR1 motif was not (E-value
2.5e + 4) (Figure 8B). We have thus identified a TR4-
ELK4 cis module that accounts for 30% of TR4 binding
sites. These sites are characterized by overrepresentation
of the ETS motif in 96% of the sites and the lack of a
DR1 element typically thought to recruit TR4. Therefore,
TR4 does not directly bind to DNA via a DR1 element at
these sites, but appears to be recruited through an ETS
factor. We also analyzed the localization of binding rela-
tive to gene structure and found that TR4 and ELK4
display very similar patterns, with maximum binding
between 500 bp upstream and downstream of a tran-
scription start site (Figure 8C). The occurrence of
both factors at common binding sites was confirmed by
quantitative PCR using independent biological replicates
(Figure 9B). Although we experimentally identified a cis
regulatory module involving ELK4 at ~30% of TR4 bind-
ing sites, the ETS core motif was identified using bioin-
formatics to be within 53% of TR4 binding regions. It is
possible that other ETS family members occupy these
sites. It has been shown that the ETS family members
ELK and GABPA shared half of their binding sites, while
the other half were specific for a particular ETS factor
[37]. Although further studies are needed, it is possible
that ELK4 facilitates TR4 binding to promoter regions
1,154 TR4
1,715 ELK4
346
(30%)
A
B
TR4
ELK4
0
500
1000
-1000
-500
Distance to TSS
0
100
200
300
Number of peaks
ETS motif: E-value 3e-310
C
ETS (96%)
346 sites bound by TR4 and ELK4
Figure 8 Overlap of TR4 and ELK4 binding sites in HeLa cells.
(A) Venn diagram shows the overlap of TR4 and ELK4 binding sites
within ± 1 kb of transcription start site. (B) Motif analysis was
performed on the 346 sites bound by both factors; the
overrepresented ETS motif is shown. Pie chart shows the occurrence
of the DR1 motif, ETS motif and neither of these motifs. (C)
Histogram shows binding of TR4 and ELK4 relative to the
transcription start sites. Binding sites were binned into 50 base pair
bins. Number of peaks is shown on the y axis; distance relative to
transcription start site is plotted on the x axis.
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that do not contain the DR1 motif, suggesting the pre-
sence of ELK4 dependent and ELK4 independent modes
of TR4 action (Figure 10).
Conclusions
While it had been established that TR4 plays a critical
role in embryonic development, differentiation and lipid
metabolism, the modes by which it functions were pre-
viously unclear. To obtain a better understanding of the
TR4 modes of action, we used ChIP-seq technology to
identify TR4 target genes in vivo in multiple cell lines.
This allowed us to confirm TR4 binding in vivo to the
direct repeat of AGGTCA separated by one nucleotide
(also known as a DR1 element) at endogenous target
sites in all four cell types examined. Using de novo motif
discovery, we found that the ETS motif CCGGAA was
significantly overrepresented in TR4 binding sites, sug-
gesting a role for ETS family members in TR4 action.
To confirm the co-occurrence of these two factors
in vivo, we performed ChIP-seq for the ETS transcrip-
tion factor ELK4 and we found that about one third of
TR4 target sites were indeed bound by ELK4. Sites that
are bound by both factors contain an ETS motif, but
lack the DR1 element typically thought to recruit TR4.
These data suggest that TR4 may regulate specific sub-
sets of target genes through ETS dependent as well as
ETS independent pathways. Future studies will focus on
the interdependence of these two transcription factors.
Thus our approach of defining genome-wide binding
patterns for a factor, followed by motif analysis to sug-
gest possible cis modules, and then genome-wide analy-
sis of the putative co-localizing factor has worked well
to identify a TR4-ELK4 cis module.
Interestingly, we identified TR4 target genes that are
common to quite diverse cell types (representatives of
blood, liver, and epidermal cells). These genes were
involved in fundamental biological processes such as
RNA metabolism and protein translation. In addition,
TR4 also binds near genes that are highly cell type-
specific. For example, in HepG2 cells TR4 binds near
genes that are involved in organic acid, lipid and carbo-
hydrate metabolism. TR4 knockout mice show insulin
hypersensitivity [16] and TR4 can be induced by cer-
tain essential fatty acids resulting in TR4 activation fol-
lowed by the up-regulation of the apolipoprotein E
precursor (ApoE) and cytosolic phosphoenolpyruvate
carboxykinase 1 PEPCK gene [30], which is thought to
contribute to diabetics-induced hyperglycemia [40,41].
Knowing the direct TR4 binding sites, it will be an
interesting focus of future studies to evaluate the path-
ways underlying TR4 action and its possible role in
metabolic diseases.
A
B
FOS
200
0
200
0
ELK4
TR4
200
0
200
0
TAF1A
200
0
200
0
SNRPE
200
0
200
0
VPS72
ELK4
TR4
TR4
ELK4
ELK4
TR4
0
20
40
TNFAIP1
NR2C1
PCNXL3
TAF1A
FOS
GABPA
EXOC2
VPS72
SNRPE
SLC25A44
CDH1
Fold enrichment over input
TR4
Elk4
IgG
IgG
TR4TR4+ELK4ELK4
neg
control
Elk4
100
60
80
EME1
COX19
BLZF1
CDH10
Figure 9 TR4 and ELK4 bind to common target genes. (A) ChIP-
seq signal track of TR4 and ELK4 enrichment at common and
unique target sites in HeLa cells. TAF1A promoter region is bound
by TR4 only; C-FOS promoter region is occupied by ELK4 only, while
EXOC2, SNRPE and VPS72 gene promoters are occupied by TR4 and
ELK4. Number of sequence tags representing enrichment is plotted
on the y axis. (B) ChIP validation of TR4 and ELK4 binding sites
using qPCR. Relative enrichment was calculated over input DNA and
plotted on the y axis. Each data point represents the average of
triplicate ChIP experiments. Rabbit IgG was used as a non-specific
control ChIP. Promoter regions tested for ChIP enrichment are
shown on the x axis. The C-FOS promoter region is used as a
positive control for ELK4 binding, CDH1 and CDH10 promoter
regions were used as negative control regions for both, TR4 and
ELK4 binding.
TR4
ELK4
CCGGAA
?
Figure 10 Model of TR4-ELK4 cis module. Gene promoters
bound by both transcription factors, TR4 and ELK4, lack the DR1
element, but contain an ETS motif. This suggests that TR4 binding
at these sites is facilitated through an ETS family member such as
ELK4, possibly with the help of a bridging protein. TR4 may then
augment ELK4 binding through non-specific DNA association, as
depicted, or by serving as a non-DNA binding scaffold for additional
accessory proteins.
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Methods
Cell culture and crosslinking
K562, HeLa, HepG2, and GM12878 cells for ChIP-seq
were grown and crosslinked by the National Cell Cul-
ture Center (NCCC) as part of the ENCODE project.
K562 and GM12878 cells were grown in RPMI supple-
mented with 10% fetal bovine serum (FBS), 2 mM L-
Glutamine, 100 U/mL penicillin-streptomycin. HeLa and
HepG2 cells were grown in DMEM medium supplemen-
ted with 10% FBS, 2 mM L-Glutamine, 100 U/mL peni-
cillin-streptomycin. Cells were either processed for RNA
isolation or crosslinked 10 minutes at a concentration of
1% formaldehyde, snap frozen and stored at -80C.
Chromatin immunoprecipitation (ChIP) assay and library
preparation
ChIP assays and the libraries for Illumina sequencing
were prepared as described in detail in O’Geen et al.
2010 [42]. Briefly, chromatin from 108cells was diluted
with 5 volumes IP dilution buffer (50 mM Tris pH7.4,
150 mM NaCl, 1% (v/v) igepal, 0.25% (w/v) deoxycholic
acid, 1 mM EDTA pH8) and incubated at 4C over night
with either 50 μl of rabbit anti-TR4 antibody [15]. 300
μl protein A agarose beads were added for 2 hours to
capture the immune complexes. Beads were washed
three times with IP dilution buffer and once with phos-
phate-buffered saline. ChIP assays using 20 μl rabbit
anti-ELK4 (Santa Cruz Biotechnology sc-13030X) or 20
μl of monoclonal rabbit anti-ELK1 (Epitomics #1277-1)
were performed using StaphA cells as described on the
Farnham lab web site (http://www.genomecenter.ucda-
vis.edu/farnham/pdf/FarnhamLabChIP%20Protocol.pdf).
For sequencing experiments, StaphA cells were only
blocked with BSA and the preclearing step was omitted.
After reversal of crosslinks and RNase treatment,
ChIP DNA was purified and used directly for library
preparation.
Sequencing and data analysis
Libraries were sequenced using the Illumina GA2 plat-
form by the DNA Technologies Core Facility at the Uni-
versity of California-Davis (http://genomecenter.ucdavis.
edu/dna_technologies/). The ChIP-seq data has been
deposited in the NCBI Gene Expression Omnibus
(accession number GSE24685). In addition, all TR4
ChIP-seq data can be visualized and downloaded from
the UCSC browser at http://www.genome.ucsc.edu/cgi-
bin/hgTrackUi?hgsid=169984430&c=chr9&g=wgEnco-
deYaleChIPseq. Peaks were called using the Sole-search
software with default parameters (FDR0.0001, alpha
value 0.001) using sequenced libraries of matched Input
DNA for each cell type [21]. Peak overlap analysis based
on chromosomal coordinates as well as location analysis
were also performed using the Sole-search software.
Gene Ontology analysis was performed using Concept-
Gen to identify the functional categories enriched in the
overlapping targets in 4 cell types. (p-value < 0.05, mod-
ified Fisher’s exact test). In addition to GO terms, other
concepts were tested for significant enrichment in the
gene set. All Entrez Genes were used as background to
determine the significance of over-representation.
Motif Analysis
In vivo binding sequences from TR4 peak files were
retrieved from UCSC Genome Database (hg18, March
2006). Unbiased motif analysis was performed using
MEME to identify statistically overrepresented motifs in
the TR4 peak sequences present in 4 cell types. The follow-
ing parameters were used “-dna -nmotifs 5 -mod zoops
-minw 12 -maxw 20 -maxsize 2000000 -revcomp”, which
specify the number of motifs to search for, the zoops
assumption (zero or one occurrence per peak sequence),
the minimum motif length of 12 (length of a repeat element
with no spacing between two half sites), the maximum
motif length of 20 (length of a repeat element with 8 spa-
cing nucleotides between two half sites), the maximum
dataset size of 2,000,000 characters. Sequences were
searched in forward and reverse orientation.
RNA preparation and Illumina expression arrays
RNA was prepared from three independent cultures of
106HeLa or HepG2 cells using Invitrogen Trizol
according to the manufacture’s recommendations. The
Illumina TotalPrep RNA amplification kit from Ambion
(AMIL1791) was used to generate biotinylated, amplified
RNA for hybridization with the Illumina Sentrix Expres-
sion Beadchips, HumanHt-12. The Sentrix gene expres-
sion beadchips used for this study consisted of a 12-
array, 2 stripe format comprising approximately 48 k
probes/array. In this collection 24,000 probes were from
RefSeq sequences and 24,000 from other Genbank
sequences (see http://www.illumina.com/pages.ilmn?
ID=197 for more details). Arrays were processed as per
manufacturer’s instructions, scanned at medium PMT
settings as recommended by the manufacturer, and ana-
lyzed using Bead Studio Software v. 2.3.41. Data was
normalized using the “average” method, which simply
adjusts the intensities of two populations of gene
expression values such that the means of the popula-
tions become equal. Relative expression values were cal-
culated using an algorithm provided by Bead Studio.
The expression array data has been deposited in the
NCBI Gene Expression Omnibus (accession numbers
GSE24419 for HepG2 and GSE19146 for HeLa data).
ChIP assay and quantitative PCR (qPCR)
To confirm targets identified by ChIP-seq, all ChIP
assays were performed using StaphA cells. 107cells were
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used per ChIP experiment and adjusted amounts of the
same antibodies and pre-immune serum (rabbit IgG) as
described above. Immunoprecipitated DNA was purified
and eluted in 50 μl water. 1 μl of ChIP DNA or 3 ng of
Input DNA were used for qPCR analysis. Quantitative
PCR experiments were performed at least in duplicates,
from at least two independent ChIP assays on a Bio-Rad
DNA Engine Opticon Real-Time PCR System using
SYBR® Green Master PCR Mix (SIGMA) according to
the manufacturer’s instructions. Results were analyzed
relative to input. Each target site was calculated as 2 to
the power of the cycle threshold (cT) difference between
input DNA and ChIP samples. Enrichments at target
sites are compared to negative/unbound control regions
CDH1 and CDH10 (see Additional file 2 for primer
sequences).
Additional material
Additional file 1: Validation of TR4 expression in four different cell
types. Western blot analysis to validate expression of TR4 protein. 10 μg
nuclear extract were loaded per lane. Cell types used are indicated
above each lane.
Additional file 2: Primer sequences for standard and qPCR
validation of TR4 ChIP samples.
Additional file 3: PCR anaslysis of three TR4 binding sites. ChIP
assays were performed in K562 and HepG2 cells using TR4 antibody. PCR
was performed using primers to TR4 binding sites identified by ChIP-seq
(see Additional file 2 for oligo sequences). The enrichment of TR4 is
shown in comparison to 0.1% Input chromatin. IgG ChIPs were used as
negative controls. PCR analysis confirmed presence of TR4 at TNFIAP1,
ECSIT and SCAP, but showed no significant enrichment when using
negative control primers to ZNF333.
Additional file 4: ChIP-seq data and analysis summary
Acknowledgements
We thank members of the Farnham lab for helpful discussion and Charles
Nicolet of the DNA Technologies and Expression Analysis Core Facilities of
the UC Davis Genome Center for assistance with sequencing the ChIP
samples. We thank K. Bradnam for help with motif analysis, C. Sershen, G.
Euskirchen, H. Monahan, M. Shi and P. Lacroute for help with DNA
sequencing and P. Cayting and M. Wilson for help with database
submission. This work was funded in part by Public Health Service grant
1U54HG004558 and NIH grants HL24415 and DK86956.
Author details
1Genome Center, University of California at Davis, Davis, CA 95616, USA.
2Department of Cell and Developmental Biology, University of Michigan
Medical School, Ann Arbor, MI 48109, USA.3Center for Computational
Medicine and Bioinformatics, University of Michigan Medical School, Ann
Arbor, MI 48109, USA.
Authors’ contributions
HOG designed, performed and analyzed experiments and drafted the
manuscript. YHL performed bioinformatics analysis, provided figures and text
for the manuscript. XX performed ChIP-seq experiments and data analysis.
LE performed ChIP-seq experiments and data analysis. VMK helped with RNA
and ChIP-seq data analysis and provided figures and text for the manuscript.
DH performed QPCR experiments and data analysis. SF performed RNA
experiments and data analysis. OT and LS generated and purified anti-TR4
antisera. MAS assisted with bioinformatics analysis. JDE and PJF helped with
experimental design and writing of manuscript. All authors read and
approved the final manuscript.
Received: 12 July 2010 Accepted: 2 December 2010
Published: 2 December 2010
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doi:10.1186/1471-2164-11-689
Cite this article as: O’Geen et al.: Genome-wide binding of the orphan
nuclear receptor TR4 suggests its general role in fundamental biological
processes. BMC Genomics 2010 11:689.
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