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CpG Island microarray probe sequences derived
from a physical library are representative of
CpG Islands annotated on the human genome
Lawrence E. Heisler
1
, Dax Torti
1
, Paul C. Boutros
2,3,8
, John Watson
2,3
,
Charles Chan
1
, Neil Winegarden
4
, Mark Takahashi
4
, Patrick Yau
4
, Tim H.-M. Huang
5
,
Peggy J. Farnham
6
, Igor Jurisica
3,7,8
, James R. Woodgett
3,4,8
, Rod Bremner
1,9
,
Linda Z. Penn
2,3
and Sandy D. Der
1,
*
1
Department of Laboratory Medicine and Pathobiology, Program in Proteomics and Bioinformatics,
University of Toronto, Toronto, ON M5S 1A8, Canada,
2
Division of Cancer Genomics and Proteomics,
Ontario Cancer Institute, University Health Network, Toronto, ON M5G 2M9, Canada,
3
Department of Medical
Biophysics, University of Toronto, Toronto, ON M5G 2M9, Canada,
4
University Health Network Microarray Centre,
Toronto, ON M5G 2C4, Canada,
5
Human Cancer Genetics Program, Department of Molecular Virology,
Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus,
OH 43210, USA,
6
Department of Medical Pharmacology and Toxicology, University of California-Davis,
Davis, CA 95616, USA,
7
Department of Computer Science, University of Toronto, Toronto, ON M5S 2M9, Canada,
8
Division of Signaling Biology, Ontario Cancer Institute, Toronto, ON M5G 2M9, Canada and
9
Toronto Western Research Institute, Toronto, ON M5T 2S8, Canada
Received March 15, 2005; Revised and Accepted April 28, 2005
ABSTRACT
An effective tool for the global analysis of both DNA
methylation status and protein–chromatin interac-
tions is a microarray constructed with sequences
containing regulatory elements. One type of array sui-
ted for this purpose takes advantage of the strong
association between CpG Islands (CGIs) and gene
regulatory regions. We have obtained 20 736 clones
from a CGI Library and used these to construct CGI
arrays. The utility of this library requires proper
annotation and assessment of the clones, including
CpG content, genomic origin and proximity to neigh-
boring genes. Alignment of clone sequences to the
human genome (UCSC hg17) identified 9595 distinct
genomic loci; 64% were defined by a single clone
while the remaining 36% were represented by mul-
tiple, redundant clones. Approximately 68% of the loci
were located near a transcription start site. The dis-
tribution of these loci covered all 23 chromosomes,
with 63% overlapping a bioinformatically identified
CGI. The high representation of genomic CGI in
this rich collection of clones supports the utilization
of microarrays produced with this library for the
study of global epigenetic mechanisms and protein–
chromatin interactions. A browsable database is
available on-line to facilitate exploration of the CGIs
in this library and their association with annotated
genes or promoter elements.
INTRODUCTION
An understanding of the epigenetic mechanisms and protein–
DNA interactions that affect gene expression is an important
component of functional genomics research. Chromatin-
immunoprecipitation (ChIP) has been used to study these
interactions by allowing the isolation of genomic fragments
targeted by an antibody or bound by a specific protein in vivo
(1–4). The presence of a specific chromosomal target in the
immunoprecipitated fragments can be determined by amplify-
ing the region of interest with appropriately designed primers.
This approach is limiting in that it depends on prior knowledge
of the expected gene targets, knowledge of the precise chro-
mosomal location to which a protein binds near the gene, and
requires separate PCR for each target. Global analysis of the
DNA products from a ChIP assay is possible by hybridizing
the fragments against a microarray of chromosomal regions,
an approach that has been called ChIP-chip (5–7).
*To whom correspondence should be addressed. Tel: +1 416 978 8878; Fax: +1 416 978 5959; Email: sandy.der@utoronto.ca
The Author 2005. Published by Oxford University Press. All rights reserved.
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access
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2952–2961 Nucleic Acids Research, 2005, Vol. 33, No. 9
doi:10.1093/nar/gki582
Microarray analysis of ChIP samples requires the con-
struction of arrays using probes against regulatory regions
with which the protein might interact. The first ChIP-chip
experiments were performed in yeast, using intergenic regions
as probes on the microarray (6). ChIP-chip experiments in
humans have been conducted using array sequences derived
from regions directly upstream of the genes and into the
first exon (8,9). This approach assumes that the majority of
protein–DNA interactions that affect RNA transcription occur
in regions near the transcription start site (TSS). A more com-
prehensive approach has been to use arrays with a set of probes
that represent all regions within a given locus (10), chromo-
some (11) or genome (12,13).
An alternate approach to designing a microarray for ChIP-
chip studies has been to use CpG Island (CGI) sequences.
CGIs are genomic regions that are thought to have escaped
the gradual loss of CpG dinucleotides that results from the
transition of methylated cytosine to thymidine and is respons-
ible for the CpG scarcity through most vertebrate genomes
(14,15). It has been estimated that 60% of all human genes
are associated with a CGI usually in the 5
0
end (16), and 85%
of CGIs have been determined to be within 500 to +1500 bp
of a TSS. (17). Furthermore, a strong correlation has been
noted between CGIs and clusters of transcription factor bind-
ing sites (18). This association of CGIs with promoter regions
suggests that trans-acting factors bound to these sites pre-
vent cytosine methylation and subsequent degradation (19).
Supporting this idea is the observation that de novo methy-
lation of CGIs can result in transcriptional repression
and X-chromosome inactivation while demethylation with
5-azacytidine can remove gene repression (20).
The first large-scale effort to computationally identify CGIs
was performed using GenBank sequences (14). With the com-
pletion of the human genome-sequencing project, bioinform-
atic approaches have been applied to identifying CGIs across
the human genome (21) and CGI tracks are available on the
major publicly accessible, genome browsers (NCBI, UCSC).
The criteria and algorithms used to determine the bounds of
the islands vary, but generally it is accepted that CGIs are 200
bp or greater in length with a G + C content >50% and a CpG
percentage that exceeds 60% of that expected in random
sequence (1/16) (14).
In contrast to bioinformatic identification of CGIs, a phys-
ical CGI library was constructed using a two-step cloning
strategy involving isolation of GC-rich chromosomal frag-
ments based on their lack of methylation in vivo and followed
by reselecting fragments that could be methylated in vitro (22).
After analysis of 113 clones in this library, it was concluded
that 77% of the clones were derived from CpG-rich regions.
The first array constructed from this clone library was utilized
to determine the methylation status of CGIs in breast cancer
cells (23). These arrays have since been used effectively for
analysis of E2F (5) and c-myc targets (24) using a ChIP-chip
approach. We have recently constructed microarrays con-
taining probes derived from the clones isolated from this
library. To better understand the nature of the CGI library
and to facilitate analysis of CGI arrays, we have sequenced
20 736 clones and conducted a large-scale characterization
that includes identification of the genomic origins of each
clone as well as other potential hybridization targets in the
genome.
MATERIALS AND METHODS
CGI library and sequence data
The CGI Library had been prepared and described (25).
From this Library, 12 192 clones (12k Set) were obtained
from the Wellcome Trust Sanger Institute (Cambridge, UK).
Sequencing of these clones had been done previously at the
Sanger Institute and this information is publicly available
(http://www.sanger.ac.uk/HGP/cgi.shtml). A second set of
8544 clones (9k Set), derived from the same library but
screened with human Cot1 DNA to remove clones with repet-
itive elements, was obtained from T. H. Huang (Ohio State
University). Subsets of these clones had been used previously
in the construction of several arrays (23,26), including the CGI
Promoter arrays available through the UHN Microarray Centre
in Toronto (www.microarray.ca). The complete set of 20 736
clones was replicated and sent for sequencing to the Genome
Sciences Centre (Vancouver, BC).
Sequence alignment
BLAT (Blast-like Alignment Tool) (27) was obtained from
UCSC Genome Bioinformatics (http://genome.ucsc.edu/FAQ/
FAQblat). The May 2004 build (Hg17) of the human genome
was obtained from the UCSC Genome Bioinformatics site
(http://hgdownload.cse.ucsc.edu/downloads.html#human) (28)
and formatted for local BLAT alignments. Annotated CGIs,
Refseq and Known Gene positions from this build were
obtained from UCSC and used for analysis of clone alignments.
End reads from each clone were aligned to the genomic
sequence using BLAT (‘-fastmap’ option), masking out repet-
itive elements and low-complexity regions. Base-calls in the
end read with a PHRED score <20 were also masked. Align-
ments to the genome for each clone were constructed by com-
bining the BLAT alignment from each end read when within
5000 bp of each other. In cases where only a single read was
available, clone alignments were constructed from a single
BLAT alignment, but marked as incomplete. In cases where
sequence reads for a single clone aligned independent of each
other, alignment information was stored and this was noted.
Once all clone sequences had been aligned, genomic loci were
defined by combining overlapping alignments resulting from
redundant clones in the collection. These loci were evaluated for
chromosomal distribution, CpG content and proximity to TSS.
Two sets of loci were generated from the human genomic
sequence for comparison with the CGI Library loci. To model
the expected contents of the CGI Library, MseI fragments
containing complete or partial annotated CGIs were identified.
In addition, a set of random loci was created by selection of
5000 random positions distributed across all 23 chromosomes
proportional to chromosome length, and extracting a 1000 bp
downstream from each position.
CGI library sequence and alignment data has been stored in
a MySQL database and made publicly available. Queryable
web-based forms have been constructed (http://derlab.med.
utoronto.ca/CpGIslands/) to facilitate analysis of this library,
as well as retrieval of information associated with specific
probe identifiers on the CGI Promoter arrays.
CGI array hybridization
Two samples of 100 ng of genomic DNA, prepared from
2ftgh fibrosarcoma cells, were spiked with 2 ng arabidopsis
Nucleic Acids Research, 2005, Vol. 33, No. 9 2953
DNA control and random-primed with a final 50 ml mixture
of 1· Sequenase buffer, 0.12 mM amino-allyl-dUTP/dNTP
[0.12 mM dATP/dGTP/dCTP, 0.048 mM dTTP (Invitrogen,
10297-018) and 0.072 mM aminoallyl-dUTP (Sigma, A0410)]
and 1 ml (13 U) of Sequenase T7 DNA polymerase (USB,
70775Y/Z) for 4 h at 37
C. The resulting product was purified
using the Cyscribe GFX purification kit (Amersham Bio-
sciences, 27-9606-01) according to manufacturer’s directions.
Recovered DNA was reduced to a final volume of 8 ml, and
incubated with DMSO reconstituted Alexa 647 or Alexa 555
dyes (Molecular Probes, A32755), in a final volume of 10 ml
for 1 h at room temperature. The labeled DNA was again
purified using the Cyscribe GFX purification kit. Both 100 ng
samples were pooled and added to 85 ml of hybridization
cocktail [0.5 mg/ml calf thymus DNA (Sigma, D8661) and
0.5 m g/ml yeast tRNA (Invitrogen, 15401-029) in DIG Easy
Hyb solution (Roche, 1603558)] and hybridized to the array
for 18 h. After washing (1· SCC and 0.1% SDS solution at
50
C), the arrays were scanned using the GenePix 4000A
microarray scanner (Axon Instruments) at PMT voltages
between 750 and 800 at 100% laser power.
Background subtraction was done using an algorithm that
fits a convolution of exponential and normal distributions
to foreground intensities (normexp) with an offset of 50 for
low-intensity shrinkage. Data were normalized with a robust-
spline algorithm (29). All algorithms were implemented in the
limma package (v1.8.21) (30) of the BioConductor library (31)
for the R statistical package.
RESULTS
Sequence information was obtained for two sets of CGI clones.
The 12k set (12 192 clones) was a portion of the original clone
selection that had been deposited at the Wellcome Trust
Sanger Institute (22). A second 9k set (8544 clones) had
been isolated from the same CGI Library by the Huang labor-
atory (32). Vector-trimmed sequences that were longer than
50 bp and had a PHRED score >20 were used for alignment
to the genome. A summary of the available sequence and
alignment to the human genome is presented in Table 1 for
each set and for the combined set of 20 736 clones. The 9k
set was generally of better quality, with 95% having accept-
able sequence versus 78% of the 12k set (Table 1, CGI
Library sequence information). Combined, 85% of the clone
sequences were considered suitable for alignment to the
human genomic sequence. The 9k set had a median sequence
length of 499 bp with 2% of the reads <100 bp in length. In
contrast, 11% of the 12k set reads were <100 bp in length,
contributing to the shorter median sequence length of 307 bp.
A second round of sequencing performed on 768 blinded
clones confirmed the sequence data obtained in the first
round (data not shown).
Of the 17 645 clones with sequence, 14 901 (84%) aligned
to the human genome using BLAT (Table 1, Genomic align-
ment). The proportion of clones aligning was higher for the
9k set (92%) versus the 12k set (79%) as expected due to the
longer reads in this set. Overall, 90% of the clones with
sequence aligned at a single position in the genome. While
many partial alignments were observed, the majority of seq-
uences showed nearly full-length alignments to the genome.
The average alignment length was 90% of the sequence length.
The median sequence length for clones that did align was 480
bp versus only 217 bp for clones that did not align. Although it
appears likely that read length affected the ability to align
sequence, some sequences that did not align to genomic
DNA were as long as 962 bp.
Alignments which overlapped each other on the genomic
scaffold were combined to define 9595 distinct genomic loci
(Table 1, Genomic loci). The 9k set generated 4937 loci while
the 12k set generated 5411 loci. Interestingly, only 753 loci
(8%) were shared, indicating that the two sets were very dis-
tinct from each other. The majority of loci (65%) were defined
by a single clone (Figure 1, upper panel), although these
accounted for only 30% of all clones which aligned (Figure 1,
lower panel). Therefore, 70% of the clones showed some
degree of redundancy within the combined sets. Approxim-
ately 39% had a low degree of redundancy (2–5 per locus)
while 15% were highly redundant (11+ per locus). This last
group consists of 2958 clones defining only 118 loci and
includes a single locus defined by 582 clones.
Genomic loci ranged in size between 50 and 2589 bp, with a
mean locus length of 511 bp. Many of the shorter loci result
from partial sequence alignments and often these sequences
align to a greater degree elsewhere in the genome. The per-
centage of each sequence contributing to the total alignment
length is shown in Figure 2 (upper panel). Most alignments
<200 bp tend to be due to partial alignments and this trend
Table 1. CGI Library sequence information, genomic alignment and
genomic loci
12k 9k 21k
CGI Library sequence information
a
Number of clones derived
from CGI Library
12 192 8544 20 736
Clones with sequence 9552 (78%) 8093 (95%) 17 645 (85%)
Both end reads 7786 (63%) 7508 (88%) 15 294 (74%)
Single end reads 1766 (14%) 585 (7%) 2351 (11%)
Median read length (bp) 307 499 414
Genomic alignment
b
Clones with sequence 9552 8093 17 645
Number aligning 7495 (79%) 7446 (92%) 14 901 (84%)
Align once 6754 (71%) 6692 (83%) 13 410 (76%)
Multiple aligns 741 (8%) 754 (9%) 1495 (8%)
Non-aligning 2041 (21%) 646 (8%) 2751 (16%)
Genomic loci
c
Clones aligning 7495 7446 14 901
Loci 5411 4937 9595
Distinct loci (exclusive of
the other clone set)
4658 4184
Common loci
(from both clone sets)
753
Loci defined by 1 clone 3171 3008 6179
Loci defined by multiple
redundant clones
2240 1929 3416
Statistics is shown for the 12k clone set, the 9k clone set and the combined
21k set.
a
The number of clones sent for sequencing, the number with usable sequence.
b
The number of clones with usable sequence that aligned to the Human Genome
build. The number of clones aligning at a single versus multiple positions is also
indicated.
c
The number of loci generated from alignments in each clone set. The overlap
between the two clone sets is indicated, along with the number of loci unique to
each clone set. Also indicated are the number of loci generated by a single clone
alignment and multiple clone alignments.
2954 Nucleic Acids Research, 2005, Vol. 33, No. 9
diminishes as the total aligned length increases. When the loci
defined from these alignments are examined (Figure 2, lower
panel), shorter loci are usually defined by partially aligning
clones while loci 200 bp in size and greater generally result
from nearly complete sequence alignments. Accordingly, we
have not included loci <200 bp in length in the subsequent
analysis, reducing the number from 9595 to 7184.
To evaluate the overall quality of the loci defined by the
physical CGI Library, we calculated two metrics, the G + C
content and CpG dinucleotide frequency, and compared this to
the computationally annotated CGIs. To make the appropriate
comparison, we modeled in silico the library construction
undertaken by Cross et al. (22) by identifying MseI sites
in the genomic sequence and generating fragments between
MseI sites within or immediately flanking annotated CGIs
(MseI-CGIs). Starting with the 27 801 computationally annot-
ated CGIs from hg17, 42 450 MseI-CGIs were identified
having an average length of 1106 bp (range 5–51, 939 bp).
For additional comparison, a set of 5000 random loci, each
1000 bp in length and proportionally distributed across all
23 chromosomes, was also generated in silico. These three
sets were then evaluated for the two above-mentioned metrics
(Figure 3). Both criteria were met (CpG ratio > 0.6, G + C
content > 0.5) for 64% of the physical loci. Although this was
less than the 87% observed in the MseI-CGIs, this stood in
stark contrast to the 2% observed in the random loci. Annot-
ated CGI will, by definition, exceed both criteria but 13% of
the MseI-CGIs do not, and this can be directly attributed to the
non-CGI-containing flanking sequences imposed by the MseI
positions. Given this, it is likely that the 36% of the physical
CGIs not exceeding both criteria includes authentic CGI
sequences. In contrast, 98% of the random loci fail to exceed
both criteria.
We next determined the chromosomal distribution of the
physical CGI loci and compared this to the distribution of
MseI-CGIs (Figure 4). In total, 63% of the physical CGI
loci show overlap with an MseI-CGI. The proportional rep-
resentation of both sets relative to chromosome size were
similar (Figure 4, right-hand side), suggesting that the clones
isolated from the library are generally representative of
annotated CGI. A similar over-representation (chromosomes
16,17 and 19) or under-representation (chromosomes 13, X, Y)
of CGI on particular chromosomes was also observed in
both sets.
Given that CGIs have been demonstrated to have a close
relationship with the 5
0
upstream region of genes, we next
examined the distance of each CGI Library locus from the
nearest TSS. Distance from a TSS to the annotated CGIs as
well as to the random loci was also calculated and these results
are summarized in Figure 5. For the CGI-derived MseI frag-
ments, 47% are in the proximal promoter region (+200 bp to
1 kb), 41% of which directly overlap a TSS. An additional
12% are found in more distal promoter regions (+1kbto
10 kb) and 14% are found further into the gene sequence,
>1000 bp downstream from the TSS. Less than 10% of the
annotated CGIs are found in regions far upstream of a TSS
(100k) in contrast to the randomly generated loci which are
predominantly in these regions.
The CGI Library loci that overlapped a CGI-derived MseI
fragment showed a similar preferential localization around the
TSS and in promoter regions. The CGI Library loci that were
not associated with the annotated CGI also showed a stronger
association with TSSs than observed with the random loci.
Although few were directly at a TSS, 25% were within the
distal promoter region, compared to only 10% of the random
loci. Furthermore, 43% of the random loci were >100 kb away
from a TSS compared to only 25% of this subset of the CGI
library loci.
To verify the overall ability to align these sequences to
the human genome, a 12k microarray constructed from the
CGI clones was hybridized with DNA fragments generated by
sonication of isolated human genomic DNA. Fluorescence
measurements from non-human probes on this array were
Figure 1. Clone composition of genomic loci. Each genomic locus is defined
by one or more CGI library clone alignments. The majority of loci (6179/9552)
are each defined by a single, non-redundant clone (upper panel, left-most bar).
Fewer loci are represented by redundant clones with 1782 loci each defined
by a pair of clones, 1240 by 3–5 clones, 235 by 6–10 clones and 118 loci each
represented by 11 or more clones (range 11–582 clones). In the lower panel,
the total number of clones represented in each group is indicated. The most
redundant group consisting of 2958 clones defines only 118 loci.
Figure 2. Percentage of sequence aligning. In the upper panel, the percentage of
the sequence length aligning is plotted against the total number of bases aligned
(alignment length). The shorter alignments generally result from partial
sequence alignments and as the total length of the alignment increases, so does
the % aligning. The lower panel shows the % sequence alignment for loci of
various size ranges. Loci <100 bp in length are generated mostly from these
partial alignments, while the longer loci (200 bp) are derived from nearly
complete sequence alignments.
Nucleic Acids Research, 2005, Vol. 33, No. 9 2955
used as a measure of non-specific binding since the corres-
ponding spike-in cDNA was not included in the hybridization
mixture (Figure 6A). Signal from only 396 of the 12 196 CGI
probes were within 2 SD of the mean signal intensity of the
non-human DNA probes, suggesting that genomic DNA bound
specifically to >97% of the CGI probes.
The array was hybridized with two independently labeled
aliquots (100 ng each) of sonicated genomic DNA. An MA plot
Figure 3. Evaluation of GC and CpG dinucleotide content. CGI Library Loci (right panel) were evaluated for G + C content and CpG dinucleotide content (expressed
as a ratio of the expected frequency of 1/16). For comparison, MseI fragments containing annotated CGIs (left panel) and random loci (center panel) were also
evaluated. Dotted lines indicate the values frequently used for assessment of CGIs (G + C > 0.5, CpG observed/expected > 0.6). The percentage of Loci in each
quadrant is indicated.
Figure 4. Distribution of CGIs across the human genome. A schematic diagram of the 23 human chromosomes is shown with Giemsa staining patterns in grayscale.
Annotated CGIs are indicated in green (top of schematic diagram) and the number identified on each chromosome is indicated to the right (CGI). The position of each
mapped locus is indicated in red (bottom of schematic diagram). The number identified on each chromosome is indicated to the right (Loci). The first column is the
number of loci with a position that overlaps an Annotated CGI/MseI. The second column is the number of loci that do not overlap an annotated CGI/MseI. To the far
right is indicated the proportional representation of the number of loci or annotated CGIs relative to chromosome length. Loci were also identified on mitochondrial
DNA (14 loci) as well as on undesignated chromosome sequence collected into UCSC random sequence files (94 loci).
2956 Nucleic Acids Research, 2005, Vol. 33, No. 9
of background-corrected and normalized log
2
signal versus
log
2
differential expression is shown in Figure 6B. Signal
consistency is very strong between the two channels with
>99.5% of CGI probes showing <2-fold differential expression
(|M| < 1) and signal from the two channels showing a correla-
tion (Pearson) of 0.99. The mean log
2
signal intensity for all
probes was 10.9 – 1.9; in total 85% of CGI probes had signals
within two orders of magnitude range.
To facilitate examination of the CGI Library clone align-
ments to the genome, a CGI Library Browser has been
constructed and is available at http://derlab.med.utoronto.ca/
CpGIslands/ (Figure 7) Clone identifiers corresponding to
Figure 5. Position of Loci relative to gene TSSs. The distance to the nearest annotated TSS is shown for three sets of loci: the annotated CGI in the current build of the
human genome (Hg17, May 2004); the random loci; and the loci derived from the CGI Library. The last set has been subdivided into loci which overlap an annotated
CGI (solid) and those that do not (speckled). The percentage of loci in each set at various positions relative to the TSS is shown. (i) Promoter regions. Percentage of
loci overlapping an annotated TSS, in the proximal promoter region (+200 to 1000 bp) and in the distal promoter region (+1000 to 10000 bp). (ii) Downstream
(1000 bp or greater within a gene). (iii) Upstream between 10 and 100 kb upstream of a TSS or >100 kb upstream of a TSS.
B
Figure 6. 12k CGI microarray. (A) A representative block from the CGI array after hybridization with 100 ng sonicated human genomic DNA. The faint spots in the
lower left are the non-human DNA control probes. The corresponding spike-in controls were not added to the hybridization mixture. Arabidopsis controls were added
to the hybridization and the Arabidopsis probes are in the lower right. (B) MA plot of differential expression (M) versus mean signal intensity (A) in log
2
-space for
all CGI probes on the array. Only 32 of 12 196 probes display >2-fold differential expression (|M| > 1).
Nucleic Acids Research, 2005, Vol. 33, No. 9 2957
spots on the 12k CGI Microarray can be entered to obtain
a graphical view of the genomic alignment, as well as the
relative positions of upstream and downstream genes. Other
features of the browser include the ability to view other clones
aligning to the same locus and to identify clones aligning near
a specified gene. Links have been created to map directly to
the UCSC genome browser (33) to allow exploration of other
genomic features near the locus of interest.
DISCUSSION
Arrays constructed from a CGI library (22) have been applied
successfully to study DNA methylation status and to identify
genomic fragments immunoprecipitated with antibodies
against several target proteins (5,24,32,34–36). The rationale
for using a CGI array to analyze ChIP DNA is based on the
association between CGIs and gene TSSs (16,17) as well as the
hypothesis that CpG conservation in these regions results from
protein–chromatin interactions which prevent methylation
and subsequent CpG degeneration (19). The CGI library from
which the probes for the array were selected was created by
isolating genomic fragments that have a high G + C content,
are rich in CpG dinucleotides, but are poorly methylated (22).
The clones used as probes on earlier arrays were selected
randomly from this library and therefore their sequence and
identity was unknown. In contrast to arrays constructed from
defined genomic fragments, it had been necessary to identify
probes of interest post-hybridization by sequencing the clone,
aligning to known sequences, then identifying associated
genes. This study provides a comprehensive analysis of a
set of 20 736 clones isolated from the CGI library validating
the approach taken by Cross et al. (22) in construction of the
library as well as the use of this library for construction of a
microarray suitable for ChIP-chip analysis.
Initial attempts to align clone sequences to genomic DNA
utilized the sequence information which was publicly avail-
able for the 12k set (http://www.sanger.ac.uk/HGP/cgi.shtml).
While sequence information was available for only 60% of the
clones in this data set, nearly 85% of the clones had usable
sequence following resequencing in this study. Furthermore,
the average read length in the original data set was 215 bp
compared to 414 bp in our sequences. The higher quality of
sequence data probably contributed to a higher percentage of
successful alignments. More importantly though, since dis-
crepancies were observed between the two data sets (data
not shown) and our sequence data is known to directly cor-
respond to the clones used for array construction, this ensures
an accurate annotation of the probes on the microarray.
Despite resequencing, 15% of the clones did not have
adequate sequence information to generate genomic align-
ments. This included clones in which no sequence information
was obtained as well as clones with <50 bp of quality sequence
(PHRED score >20), which would generate short, less inform-
ative alignments. This was not unexpected and may be due to
lack of an insert in the clone, or to the presence of multiple
clones in some wells, preventing proper sequencing of the
inserts.
Two sets of clones were sequenced and analyzed. The first
set of 12 192 clones (12k set) was obtained directly from
the Sanger Institute. The second subset of 8544 clones
(9k set) had been previously isolated by Huang et al. (23)
from the same library. The clones from this set have been
used in the construction of various CGI arrays (5,24,32).
The quality of the sequence information in the 9k set was
superior to the 12k set. Fewer clones in the 9k set returned
no sequence, and the read lengths were generally longer. This
is probably due to the fact that this set had been prescreened
with human Cot-1 DNA to remove sequences with a high
degree of repeat elements. Consequently, a higher percentage
of clones in the 9k set aligned to genomic sequence than in
the 12k set. CGI arrays constructed from the 12k set have been
available through the UHN Microarray Centre (http://
www.microarray.ca/) since 2003. Arrays constructed from
the full set of 20 736 clones are now being produced.
Figure 7. CGI library browser. An online CGI Library Browser (http://derlab.med.utoronto.ca/CpGIslands/) has been constructed to allow users of the CGI Promoter
Microarrays as well as users interested in the CGI Library to explore alignments of the clones to the human genome. For each clone, alignments to the genome are
listed and displayed diagrammatically, including the relative positions of annotated CGI and nearby genes.
2958 Nucleic Acids Research, 2005, Vol. 33, No. 9
We have used the BLAT software (27) to align sequences to
genomic DNA, both for its speed and because it is well-suited
for identifying highly similar sequences. Some post-alignment
processing was necessary to separate out partial alignments on
a single chromosome that had been combined by BLAT’s
stitching routine. Using BLAT, it was possible to align 84%
of all sequences. The 16% that did not align can be partially
accounted for by their shorter sequence lengths although
there did exist long sequences that did not align. In addition,
sequences that did not have long contiguous stretches of qual-
ity sequence may have not aligned due to masking of the poor
quality bases. Use of other alignment algorithms may be more
suitable for these sequences, but the results would include
similar or homologous regions that would not necessarily rep-
resent either the genomic origin of a clone, nor an area that
would hybridize against the clone on an array.
Clone alignments were constructed after aligning each read
separately, allowing the genomic sequence to act as a scaffold
to determine the positioning of the two reads with respect to
each other. In clones with non-overlapping ends, the gap was
therefore defined by the genomic scaffold. There were also
instances of alignments of one read in the absence of a nearby
alignment of the other read. Although these alignments may
not represent the genomic origin of a particular clone, they
do indicate a potential hybridization target in genomic DNA
against the clone when acting as a probe on a microarray. Such
clones may have arisen by ligation of two or more distinct
fragments into the same plasmid. Evidence suggesting this is
observed in 2% of the clones (213 clones), where the end reads
align to distinct genomic positions, often on different chro-
mosome. The absence of the other read’s contribution to the
alignment is noted in the annotation available through the web
browser.
The genomic scaffold was also used to identify redundancy
in the clones derived from the CGI Library. CGI Library Loci
were generated by combining overlapping alignments and
identifying all clones contributing to each locus. There is the
possibility also that a locus might capture contiguous clones in
cases where incompletely digested fragments were captured,
but in the absence of this, contiguous clones will be repres-
ented by adjacent loci. In this way, 9595 loci were defined,
slightly less than one-half of the total number of clones
available and slightly more than one-half of the clones with
sequence. This number is reduced to 7184 when eliminating
shorter loci resulting from partial sequence alignments. In this
way, it was determined that only 30% of the clones were
unique, the other 70% showing some degree of redundancy.
Interestingly, the 12k and 9k sets show only a small degree
of overlap which was not expected given the degree of redund-
ancy in each set. Of the 9595 loci, only 753 were present in
both sets. This finding suggests there may be value in con-
tinuing to isolate clones from the library. Approximately 60%
of the loci that we have identified are within the MseI restric-
tion fragments associated with the annotated CGI. This num-
ber corresponds well with the observation that 64% of the loci
evaluate as a CGI based on G + C content and CpG dinuc-
leotide frequency. CGIs by definition are regions of CpG
conservation due to the absence of methylation and will
therefore have high G + C content and a CpG frequency
that approaches the expected random frequency of 1/16.
Identification of CGI in promoter regions or in genomic
sequence exploits algorithms that evaluate when these para-
meters exceed arbitrary values designed to minimize signal-to-
noise. Within the 40% of the loci that do not correspond to the
annotated CGI-associated MseI restriction fragments, there
may exist CGIs not identified by these algorithms. Alternately,
some of these loci may represent noise in the original library
due to capture of fragments not expected from the selection
procedure.
The documented association of CGIs with regions upstream
of genes is based on bioinformatic analysis of the genome
(14,17,21) and is dependent on the analysis of the nucleotide
sequence alone. We have approached this from a different
direction, mapping the CGI library clones that were selected
based on sequence characteristics and methylation status, to
the genomic sequence. Approximately 60% of the CGI Library
loci in the subset that overlap annotated CpG sites are in the
distal promoter region or closer to a TSS. This is nearly ident-
ical to the distribution of the annotated CGIs, supporting the
idea that CGIs are associated with TSSs.
In addition to collecting CGIs near the TSS, the CGI library
also contains fragments representing CGIs that are distant
from a gene. Potentially these islands may represent regions
to which transcriptional enhancers and repressors may bind
outside the proximal or distal promoter regions. Alternately,
they may be a part of promoter regions in proximity to an
unknown TSS and may ultimately play a role in identifying
new genes (37).
Nearly 25% of the loci in the subset that does not overlap
annotated CpG sites are within the distal promoter region or
closer. This is a significant enrichment relative to random loci
in this region (10%). Furthermore, while >40% of random
loci are 100 kb or further from a TSS, only 25% of this
second subset is found here. Despite not being associated with
annotated CGIs, this suggests that these loci are not simply due
to non-specific collection of random fragments into the library.
Possibly, the CpG content is too low to characterize these
regions as CGIs by the established criteria, but still high
enough to have been effectively methylated and isolated
during the procedure used to create the CGI library.
There have been a variety of approaches taken towards the
design of microarrays suitable for analysis of ChIP DNA.
Proximal promoter arrays constructed using regions directly
upstream of known TSSs (8,9) can identify binding to tran-
scriptional regulatory elements which exist close to the gene.
It has been well established though that regulatory factors can
bind at more distal regions, and even within introns, exons or
downstream of a gene (10,11,38). More comprehensive tiling
arrays have been constructed targeting intergenic regions (6),
distinct loci (10,11) and the full genome (12,13). The CGI
array approach is based primarily on the association of CGIs
with regulatory activity (16,17), but in contrast to the proximal
promoter arrays the location of CGIs relative to the TSS is not
limited to 1000 bp upstream. While many of the loci identified
in this study are still within 10 kb of a TSS, they also occur at
far more distant regions. Although full genome tiling arrays
obviously represent the most comprehensive tool for global
methylation or protein–chromatin interaction studies, tech-
nical issues such as costs, multiple array platforms and data
analysis software, represent aspects which currently preclude
widespread use of these arrays for a typical molecular biology
laboratory. However, it is likely that all these array types
Nucleic Acids Research, 2005, Vol. 33, No. 9 2959
represent complementary approaches to studying global
epigenetic mechanisms and transcription factor binding sites.
The primary focus of this study is to annotate clones isolated
from the CGI library and the CGI arrays which use these
clones as probes. While more extensive studies are in progress
to further evaluate these arrays, we conducted a straight-
forward experiment to examine probe hybridization to the
12k CGI array. At least 97% of the probes bound sonicated
genomic DNA. Furthermore, the degree of binding observed
after hybridization with equal amounts of genomic DNA in
both channels was highly consistent, with only 32 of 12 192
CGI probes showing differential hybridization. The signal
obtained from each probe varied over 2 orders of magnitude,
probably due to differences in hybridization strength, dye
incorporation and hybridization specificity between different
DNA fragments.
The data produced in this analysis is available online
through the CpG Island Library browser (http://derlab.med.
utoronto.ca/CpGIslands/). This has been designed to allow
detailed examination of individual probes on the CGI array
as well as providing a means to summarize information for a
list of probes. The alignments detailed in this browser include
complete and near-complete alignments of clone sequences to
genomic loci, as well as partial alignments that may require
consideration when analyzing hybridization results. This inter-
active tool will facilitate analysis of ChIP-chip experiments by
allowing faster identification of targets. In addition, redundant
probes on the array have been identified and probes that align
near a gene of interest as well as the spatial relationship of the
alignment to the gene can be easily determined.
The CGI library is expected to contain only a subset of all
genomic CGI, those that are unmethylated in whole blood
genomic DNA from which the library was constructed (22).
The analysis presented here will contribute to the production
of next generation CGI arrays by allowing removal of redund-
ant probes, enrichment with unique clones, and the inclusion
of probes designed against other regulatory regions which
complement this CGI approach. A clearer understanding of
the nature of the CGI probes will also facilitate the design of
coordinated expression arrays that can be used in conjunction
with ChIP-chip studies with CGI arrays to study and define
transcriptional networks. Furthermore, the development of
high quality CGI arrays will contribute to more accurate
analysis of global methylation status and the relationship of
epigenetic mechanisms to these networks.
ACKNOWLEDGEMENTS
This project has been funded in part with Federal funds from
the National Cancer Institute and National Institutes of Health,
under Contract No. N01-C0-12400. The content of this pub-
lication does not necessarily reflect the views or policies of
the Department of Health and Human Services, nor does
mention of trade names, commercial products, or organization
imply endorsement by the US Government. This study was
funded by grants from CIHR and Genome Canada to S.D.D.
Computational analysis was in part supported by NSERC and
IRIS grants to I.J. Sequencing was carried out by the British
Columbia Genome Sciences Centre, Suite 100, 570 West
7th Ave, Vancouver, BC V5Z 4S6, Canada. Funding to pay
the Open Access publication charges for this article was
provided by Genome Canada.
Conflict of interest statement. None declared.
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