A high-resolution map of segmental DNA copy number variation in the mouse genome.

Abstract

Submicroscopic (less than 2 Mb) segmental DNA copy number changes are a recently recognized source of genetic variability between individuals. The biological consequences of copy number variants (CNVs) are largely undefined. In some cases, CNVs that cause gene dosage effects have been implicated in phenotypic variation. CNVs have been detected in diverse species, including mice and humans. Published studies in mice have been limited by resolution and strain selection. We chose to study 21 well-characterized inbred mouse strains that are the focus of an international effort to measure, catalog, and disseminate phenotype data. We performed comparative genomic hybridization using long oligomer arrays to characterize CNVs in these strains. This technique increased the resolution of CNV detection by more than an order of magnitude over previous methodologies. The CNVs range in size from 21 to 2,002 kb. Clustering strains by CNV profile recapitulates aspects of the known ancestry of these strains. Most of the CNVs (77.5%) contain annotated genes, and many (47.5%) colocalize with previously mapped segmental duplications in the mouse genome. We demonstrate that this technique can identify copy number differences associated with known polymorphic traits. The phenotype of previously uncharacterized strains can be predicted based on their copy number at these loci. Annotation of CNVs in the mouse genome combined with sequence-based analysis provides an important resource that will help define the genetic basis of complex traits.

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A High-Resolution Map of Segmental DNA
Copy Number Variation in the Mouse Genome
Timothy A. Graubert1*, Patrick Cahan1[, Deepa Edwin1[, Rebecca R. Selzer2, Todd A. Richmond2, Peggy S. Eis2,
William D. Shannon3, Xia Li3, Howard L. McLeod4, James M. Cheverud5, Timothy J. Ley1
1 Department of Medicine, Division of Oncology, Stem Cell Biology Section, Washington University, St. Louis, Missouri, United States of America, 2 NimbleGen Systems, Inc.,
Madison, Wisconsin, United States of America, 3 Department of Medicine, Division of General Medical Science, Washington University, St. Louis, Missouri, United States of
America, 4 Department of Medicine, Division of Oncology, Molecular Oncology Section, Washington University, St. Louis, Missouri, United States of America, 5 Department of
Anatomy and Neurobiology, Washington University, St. Louis, Missouri, United States of America
Submicroscopic (less than 2 Mb) segmental DNA copy number changes are a recently recognized source of genetic
variability between individuals. The biological consequences of copy number variants (CNVs) are largely undefined. In
some cases, CNVs that cause gene dosage effects have been implicated in phenotypic variation. CNVs have been
detected in diverse species, including mice and humans. Published studies in mice have been limited by resolution and
strain selection. We chose to study 21 well-characterized inbred mouse strains that are the focus of an international
effort to measure, catalog, and disseminate phenotype data. We performed comparative genomic hybridization using
long oligomer arrays to characterize CNVs in these strains. This technique increased the resolution of CNV detection by
more than an order of magnitude over previous methodologies. The CNVs range in size from 21 to 2,002 kb. Clustering
strains by CNV profile recapitulates aspects of the known ancestry of these strains. Most of the CNVs (77.5%) contain
annotated genes, and many (47.5%) colocalize with previously mapped segmental duplications in the mouse genome.
We demonstrate that this technique can identify copy number differences associated with known polymorphic traits.
The phenotype of previously uncharacterized strains can be predicted based on their copy number at these loci.
Annotation of CNVs in the mouse genome combined with sequence-based analysis provides an important resource
that will help define the genetic basis of complex traits.
Citation: Graubert TA, Cahan P, Edwin D, Selzer RR, Richmond TA, et al. (2007) A high-resolution map of segmental DNA copy number variation in the mouse genome. PLoS
Genet 3(1): e3. doi:10.1371/journal.pgen.0030003
Introduction
Inbred mice are the model organisms of choice for
studying the genetic basis of complex traits such as diabetes,
heart disease, and cancer. A large and diverse set of traits has
been systematically organized in the publicly accessible
Mouse Phenome Database (MPD; www.jax.org/phenome),
housed at The Jackson Laboratory (Bar Harbor, Maine,
United States). The priority strains designated by the MPD
serve as a standard set chosen by the genetics community to
represent commonly used and genetically disparate inbred
strains of Mus musculus and wild-derived subspecies. Current
efforts are directed at identifying the full complement of
genetic variants that influence heritable traits.
Sequence-based studies have begun to define the genetic
differences that exist between these strains at the nucleotide
level. The prevailing model is that the mouse genome is a
mosaic of sequence blocks derived from ancestral popula-
tions, reflecting the unique breeding history of each strain
[1,2]. Recently, variation in segmental DNA copy number has
emerged as an additional dimension of genetic diversity that
exists in the germline of rodents and primates. Copy number
variants (CNVs) have been detected in humans, chimpanzees,
and mice [3–7]. Germline CNVs affecting gene expression or
function could contribute to heritable differences for many
traits. More than 3,800 human CNVs have been identified and
cataloged (http://projects.tcag.ca/variation). These CNVs ex-
tend the spectrum of genetic changes that contribute to
phenotypic differences in mammalian species. In addition to
effects on normal traits, CNVs are also likely to influence
disease susceptibility [8]. Published studies of CNVs in mice
have been limited by resolution and strain selection [6,7]. The
aim of this study was to define the extent of CNV in the
genomes of 21 well-characterized MPD strains. Using a high-
density, tiling-path whole genome-long oligomer array, we
identified CNVs in all strains and found that most of these
segments contain annotated genes. The CNV profiles of these
strains recapitulate aspects of their known ancestry. This
high-resolution map of mouse CNVs in diverse strains will
facilitate ongoing efforts to map phenotypes to genes.
Editor: David Beier, Harvard Medical School, United States of America
Received July 10, 2006; Accepted November 21, 2006; Published January 5, 2007
A previous version of this article appeared as an Early Online Release on November
22, 2006 (doi:10.1371/journal.pgen.0030003.eor).
Copyright: ? 2007 Graubert et al. This is an open-access article distributed under
the terms of the Creative Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the original author
and source are credited.
Abbreviations: BHC, BLAT hit count; CNV, copy number variant; CT, comparative
threshold cycle; GO, Gene Ontology; MPD, Mouse Phenome Database; NCBI,
National Center for Biotechnology Information; oligo-aCGH, long oligonucleotide
array comparative genomic hybridization; qPCR, quantitative PCR; SNP, single
nucleotide polymorphism
* To whom correspondence should be addressed. E-mail: graubert@medicine.
wustl.edu
[ These authors contributed equally to this work.
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Results/Discussion
High-Resolution Comparative Genomic Hybridization
Analysis of MPD Strains
We performed comparative genomic hybridization using
long oligonucleotide arrays (oligo-aCGH) containing 388,352
probes spanning the mouse reference genome with a median
spacing of 5 kb. Germline DNA from 20 high-priority MPD
strains was tested against the C57BL/6J reference strain.
Segmental germline DNA copy number gains and losses were
evident in all strains (Figure 1). By using a set of stringent
criteria (see Materials and Methods), 80 ‘‘high confidence’’
CNVs were identified. CNVs were detected on all 19 mouse
autosomes (Figure 2). Changes on the X and Y chromosomes
were not considered in this analysis because of lower probe
density and greater mapping uncertainty for these regions in
the current assembly. The segments vary in size (range, 21.4
kb to 2.0 Mb; mean, 271.5 kb) and number per strain (range,
two CNVs per genome in C57BL/6Tac to 38 CNVs per
genome in NOD/LtJ; mean, 22 CNVs per genome) (Table S1).
As expected, no segments were identified in the C57BL/6J
self–self hybridization. While the tiling-path design used in
this study enables systematic detection of CNVs in genic and
intergenic regions, we note that repeat-masking yields a
Figure 1. Representative Germline CNVs in Mice Identified by High-Resolution aCGH
The log2ratios of signal intensity for C57BL/6J (reference) versus 20 test strains are shown. Inset, an expanded view of the CNVs in NOD/LtJ and A/J from
(A) and (B). Scale, 500 kb.
(A) A 135.6-kb segment of reduced copy number (mean log2¼?1.02) on Chromosome 14 is present in most strains.
(B) A 61.7-kb amplified segment (mean log2¼þ1.01) on Chromosome 1 is present in most strains.
doi:10.1371/journal.pgen.0030003.g001
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Copy Number Variation in Mice
Author Summary
A major goal of genetics and genomics is to understand how
genetic differences between individuals (genotypes) translate into
variation in disease susceptibility, behavior, and many other
organism-level characteristics (phenotypes). While the sizes of
genetic variants range from a single base to whole chromosomes,
historically, only the extreme ends of this spectrum have been
explored. DNA copy number variants (CNVs) lie between these two
extremes, ranging in size from hundreds to millions of bases. The
recent application of microarray technology to detect genetic
variation in humans has led to the realization that CNVs are
common. In fact, rough estimates indicate that CNVs and small-scale
variants may constitute similar proportions of total genomic DNA. In
this report, the authors characterize 80 CNVs across the genomes of
21 inbred strains of mice. The identification and characterization of
mouse CNVs are important because inbred strains of mice are the
most widely used model system to explore biomedical genetics.
These CNVs are located near another class of genomic features,
segmental duplications, more often than would be expected by
chance, which supports the hypothesis that CNVs and segmental
duplications are causally linked. Importantly, many of the CNVs
contain known genes and thus may underlie both gene expression
and phenotypic variation between strains.

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subset of regions (e.g., the centromeres) with lower probe
density, which could affect the CNV detection rate. Despite
the lower probe coverage in these regions, several high
confidence CNVs were detected in areas of relatively low
probe coverage (Figure S1).
These CNVs were identified by comparing the ratio of
signal intensity between the reference and test samples.
Additional information can be extracted by analyzing the raw
signal intensity of the reference (C57BL/6J) channel alone.
For 94.6% of the probes on the array, the absolute signal
intensity for C57BL/6J varies by less than one order of
magnitude. Most of the high confidence CNV calls fall in
these areas (Table S1 and Figure S2). Because the array design
is based on the C57BL/6J reference genome (National Center
for Biotechnology Information [NCBI] Build 34), sequences
absent in C57BL/6J and present in other strains are not
detected in this analysis. Segments amplified in C57BL/6J may
appear as relative copy number loss in comparison strains or
may be missed if these strains contain similar amplifications.
To identify these duplicated regions, the average absolute
signal intensity values for the reference strain were scanned
using a statistical process control algorithm (see Materials
and Methods). Sixty-seven high signal intensity locations were
flagged, of which 13 overlapped CNVs (Table S2 and Figure
S2). Twelve of these segments were also identified in an
independent set of 20 CGH experiments using the same array
design (unpublished data). To determine whether probe
sequence redundancy might underlie the high reference
signal in these regions, we searched the genome (NCBI Build
36) for nearly perfect matches to each probe using BLAT [9].
A measure of probe redundancy, BLAT hit count (BHC), was
defined as the number of matches in which the sequence
identity normalized to the length of the probe is greater than
or equal to 0.90. There is a linear relationship (p , 10?15)
between the BHC and the average signal of the reference
channel across all 21 arrays (Figure 3). The BHC in regions of
normal signal intensity (Figure 3, mean¼1.46) is significantly
less than the BHC in regions with high reference signal
(Figure 3, mean¼6.27). The strong association between BHC
and signal intensity suggests that the high signal intensity
segments are amplified regions in the C57BL/6J genome.
Although their structure is clearly different than that of
CNVs falling in areas of lower reference signal intensity, these
segments are also sites of genomic variability between the
MPD strains (Figure S2 and Table S2). This idea reinforces the
recent report that the distribution of some human CNVs is
not bimodal between populations but rather a continuous
variable with properties of quantitative traits [10].
PCR Validation of Oligo-aCGH Results
Quantitative PCR (qPCR) was used to validate several high
confidence CNVs. Primer/probe assays were designed that are
fully contained within CNVs. The results were normalized to
segments that are not altered in any of the strains included in
this study. Copy number assessed by qPCR was concordant
with oligo-aCGH in unaffected strains (Figure 4). DNA from
strains with copy number loss (e.g., Figure 4A) by oligo-aCGH
yielded only background level amplification by PCR, implying
that the target sequences for the assay were not present in
these strains (Figure 4B). These results were confirmed using
a second, independent qPCR assay within the same segment
(unpublished data). Finally, no amplicon was generated in
qualitative PCRs using a third set of primer pairs in this
region (Figure 4C). Amplified segments (e.g., Figure 4D)
detected by oligo-aCGH were confirmed by qPCR using the
relative comparative threshold cycle (CT) method [11]
(Figures 4E and S3). Regression analysis demonstrated a
linear relationship between copy number determined by both
platforms (Figure 4F) (p , 0.0001). All high confidence CNVs
subjected to qPCR validation to date (n ¼ 9) have been
confirmed (Figures 4, S3, and S4).
Relationship between CNV Profiles and Strain Histories
Hierarchical clustering was performed to identify structure
in the CNV profiles for these 21 strains. Unsupervised
clustering of the 80 high confidence CNVs (Figure 5)
illustrates three distinct groups of CNVs: segments deleted
in more than one strain, segments amplified in more than one
strain, and a third cluster containing singleton CNVs (CNVs
occurring in only one strain) and ‘‘mixed’’ CNVs (CNVs that
are both deleted and amplified, nine in total). The CNV
profiles from replicate hybridizations were highly correlated
(Figure S5), demonstrating the reproducibility of CNV
detection by this platform. The cophenetic correlation of
the dendrogram is 0.851, indicating that the distance matrix
is appropriately represented as a tree. Unsupervised cluster-
ing by Pearson correlations between CNV profiles recapit-
Figure 2. Genome-wide Distribution of CNVs
The ideograms depict chromosomal locations of copy number gains
(green arrows), losses (red arrows), and gains or losses (blue arrows)
relative to C57BL/6J in autosomes from 20 inbred strains.
doi:10.1371/journal.pgen.0030003.g002
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Copy Number Variation in Mice

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ulates some aspects of known mouse genealogy [12]. Strains
129X1/SvJ and 129S1/SvImJ stably cluster (bootstrap value ¼
0.80) in agreement with their known recent shared ancestry
[13]. Swiss-derived strains FVB/NJ, SJL/J, and SWR/J cluster
together and with another Swiss-derived strain, NOD/LtJ,
although the bootstrap values (0.60 and 0.26, respectively) are
not significant. Although C57BL/6J and C57BL/6Tac are very
closely related, they do not cluster together. This is an artifact
of the measurements being based on a C57BL/6J standard.
When Euclidean distance is used as the metric, C57BL/6J and
C57BL/6Tac group together, reflecting their genealogical
relationship. The remainder of the tree lacks resolution,
indicating that, for the most part, the relationships between
strains can be considered a star phylogeny, with only a little
structure at the tips of the tree. This is also consistent with
the breeding history of the strains [12]. A single nucleotide
polymorphism (SNP)-derived tree differs mainly in a strong
cluster composed of only the wild-derived strains CAST/EiJ
and MOLF/EiJ, possibly reflecting ascertainment bias in the
SNP panel [14]. This acknowledged limitation of the current
mouse SNP database [14] will be remedied as data emerge
from the ongoing Mouse Genome Resequencing and SNP
Discovery Project (http://www.niehs.nih.gov/crg/cprc.htm).
Comparison of Low-Resolution and High-Resolution aCGH
Analyses
A systematic comparison of the 80 CNVs in this report to
previously described mouse CNVs uncovered 17 of 238
overlapping CNVs from one study [6] and three of 74 from
another [7] (Table S4). A single CNV located between 63 Mb
and 64 Mb on Chromosome 14 was identified in all three
studies. This CNV is amplified in C57BL/6J in one report [7],
deleted in 12 strains in the present study including FVB/NJ
(the reference strain used in the previous study [7]), and
deleted in five strains in another study [6]. It is likely that this
CNV is an amplification in C57BL/6J, resulting in an apparent
deletion in multiple strains with normal copy number in our
study. This cross-study comparison was limited to the small
number of strains overlapping between the current study and
the prior reports and to those previously reported CNVs
whose genome position in Build 34 could be determined
(85.9% and 62.9% of CNVs, respectively) [6,7]. Differences in
Figure 3. Relationship between Signal Intensity and Probe Uniqueness
(A) Absolute signal intensity of the reference strain increases as a function of BHC (p , 10?15); 97.9% of autosomal probe sequences are present at
single copy in the C57BL/6J genome.
(B) Probes falling in ‘‘high confidence’’ CNVs are unique (1,005 of 1,313 probes with BHC ¼ 1).
(C) Probes falling in high signal CNVs are duplicated (356 of 420 probes with BHC . 1).
doi:10.1371/journal.pgen.0030003.g003
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the analytical techniques and the reference genome used also
contribute to the relatively low overlap between these studies.
The use of oligo-aCGH overcomes several limitations of the
BAC array platform used in prior studies. Whereas CNV calls
are frequently made on the basis of a single BAC hybrid-
ization event, 15 to 20 probes cover an interval of similar size
on the 5-kb tiling-path oligo-aCGH platform used here. More
important, the increased resolving power of oligo-aCGH can
discern complex CNV structures such as adjacent amplifica-
tions and deletions (e.g., Chromosome 6 at 130.7 and 130.9
Mb) and identify smaller-sized CNVs, as have been found in
the human genome [15]. Since our analytical approach was
weighted to minimize false positives, our results are an
underestimate of the total number of CNVs in the mouse
genome. Using a relaxed set of criteria (i.e., called by process
control and circular binary segmentation but not subjected to
manual curation or qPCR validation), the number of
potential CNVs detected by oligo-aCGH in these strains
increases to 463 (unpublished data). Ongoing studies using
higher probe density (e.g., 200-bp median spacing for an
effective resolution of approximately 1 kb) are needed for
validation of these apparent copy number changes.
Segmental Duplications Colocalize with CNVs in the
Mouse Genome
Although the complete set of mechanisms responsible for
generating CNVs is unknown, previous studies have noted the
enrichment of CNVs near segmental duplications in the
human [3,4,16–18] and mouse [6] genomes. Segmental
duplications are genomic regions of high sequence identity
(greater than or equal to 90%) to more than one genomic
locus and have been mapped in both the human [19] and
mouse [20,21] genomes. They may mediate CNV genesis by
acting as a substrate for nonallelic homologous recombina-
tion. A nonallelic homologous recombination event may
result in amplification, deletion, inversion, or no copy
number change. To test whether the nonrandom association
between CNVs and segmental duplications is preserved in our
high-resolution data, we determined the overlap of CNVs
with segmental duplications (distances from CNV to nearest
segmental duplication shown in Tables S1 and S2). Thirty-
eight of 80 (47.5%; p , 0.001 by permutation testing) CNVs
directly overlapped segmental duplications obtained from
the Non-Human Segmental Duplication Database (http://
projects.tcag.ca/xenodup/data.php) [21].
We also tested a range of margin sizes, defined as the
number of base pairs flanking a CNV in either direction,
since a direct overlap between a CNV and segmental
duplication may not be necessary for CNV genesis. The
association remained significant (p , 0.01) up to 2 Mb,
providing an estimate of the upper limit at which segmental
duplications may affect CNVs (Figure 6). The high proportion
of CNVs colocalizing with segmental duplications (94% at 2
Mb) can be interpreted as a bias in our CNV identification
methodology or as support for a strong, almost necessary,
role of segmental duplications in CNV generation. The
distance between CNVs and segmental duplications is an
Figure 4. Validation of Copy Number Changes Identified by aCGH
(A) Log2ratio plot demonstrates a 109.2-kb segment of copy number loss on Chromosome 6 in C57L/J, compared to C57BL/6J.
(B) qPCR using a primer/probe set in the altered region demonstrates normal copy number (normalized to a relative copy number of one in C57BL/6J) in
unaffected strains and significantly reduced copy number in four affected strains (inset, zoom-in view of y-axis).
(C) qPCR fails to generate an amplicon of expected size in the altered region from affected strains. B6, C57BL/6J reference strain.
(D) Log2ratio plot demonstrates a 473.7-kb segment of copy number gain on Chromosome 17 in BALB/cByJ compared to C57BL/6J.
(E) qPCR demonstrates heterogeneity of copy number (normalized to a relative copy number of one in C57BL/6J) in this region among 20 strains.
(F) Copy number estimates from aCGH and qPCR are highly concordant (p , 0.0001).
doi:10.1371/journal.pgen.0030003.g004
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important parameter of the mechanism driving segmental
duplication–mediated CNV creation. Because some exper-
imental approaches search for CNVs only in segmental
duplication regions [18], it is also important to know the
distribution of CNV–to–segmental duplication distances so
that all potential CNV-containing regions can be screened.
Successful detection of these overlaps is dependent on both
the precise definition of a segmental duplication (in this case,
a length of 5 kb or greater with at least 90% sequence
identity) and the accuracy of the segmental duplication
database. Because the genomic coordinates of segmental
duplications were determined with a previous build of the
genome, we used liftOver (http://genome.ucsc.edu/cgi-bin/
hgLiftOver) to map the coordinates to Build 34. In this
process, 7,748 of 44,851 (17%) segmental duplications failed
to remap. It is unlikely that a larger proportion of the 80 high
confidence CNVs colocalizes with segmental duplications,
because the majority of the unmapped segmental duplica-
tions were originally localized to sex chromosomes, which
were excluded from our analysis.
Gene Content of Mouse CNVs
We asked whether the gene content of CNVs is representa-
tive of the whole mouse genome. In the 80 high confidence
CNVs reported here, 62 (77.5%) contain or overlap at least
one gene. Genomic regions with lengths drawn from the
distribution of detected CNVs were randomly selected, and
the number of segments overlapping at least one gene was
counted. The probability of 62 or more CNVs overlapping at
least one gene each is 0.12 based on 1,000 randomizations,
indicating that the gene content of these CNVs is not
significantly different from the whole mouse genome.
We next asked if genes overlapping CNVs are enriched in
Gene Ontology (GO) annotations. Several GO categories
were significantly (p , 0.001) overrepresented in our mouse
CNV data (Table 1). The term ‘‘carbohydrate binding’’ is
overrepresented in concordance with a previous GO analysis
of mouse CNVs [22]. We also found several annotations to
be overrepresented that were previously reported to be
significantly underrepresented: G protein–coupled receptor
activity, rhodopsin-like receptor activity, and olfactory
receptor activity. The discrepancy in GO enrichment may
be attributable to the fact that the prior analysis was based
on data covering fewer strains. Several terms overrepre-
sented in our analysis of mouse CNVs were also found to be
overrepresented in an analysis of human CNV data (e.g.,
transmembrane receptor activity, olfactory receptor activity)
[22].
The human orthologs of several of the genes contained
within the mouse CNVs identified in this study (Immp2l, Birc1,
Cfh, Sirpb1, and Btbd9) have had reported germline copy
number polymorphisms (http://projects.tcag.ca/variation).
Conservation of CNVs across species suggests that selective
pressure may drive acquisition or retention of specific gene
dosage alterations. One of these genes (CFH) is of particular
Figure 5. Heatmap Representation of Copy Number Changes in Mice
Unsupervised clustering of segmental gains (green) and losses (red) yields a dendrogram that recapitulates features of the known genealogy of these
strains. Clustering in the vertical axis demonstrates three clusters: segments amplified in most strains, segments reduced in most strains, and a third
cluster containing either singleton CNVs or mixtures of amplifications and deletions.
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interest because, in addition to germline CNV, an SNP
(Y402H) was recently shown to account for a substantial
proportion of the heritable risk for age-related macular
degeneration in humans [23–25].
Two high confidence mouse CNVs reported here include
portions of the Klra gene cluster on Chromosome 6. The
large Klra (Ly49) family of C-type lectin transmembrane
proteins are the functional analogs of the human natural
killer cell immunoglobulin-related receptors (KIR). In the
current genome assembly (Build 36), these two segments on
Chromosome 6 contain 12 Klra family members, including
Klra8. Concordant with our oligo-aCGH results, sequence
analysis in BALB/c and DBA/2 mice demonstrated loss of
Klra8 (Ly49H) [26], a critical resistance factor for mouse
cytomegalovirus infection [27,28]. Our data predict that
AKR/J, C3H/HeJ, and PL/J should also be susceptible to
mouse cytomegalovirus infection and that the remaining
strains should be resistant. Similarly, the intelectins are
intestinal epithelial cell surface proteins involved in innate
immunity to parasitic infection. We found copy number
increase in the locus encoding intelectin-1 (Intlna) on
Chromosome 1 in several strains, including BALB/cByJ.
These results confirm previous reports of intelectin gene
duplication in BALB/c and an associated increase in
Figure 6. Relationship between Genomic Distance and Overlap between Segmental Duplications and CNVs
The number of CNVs that overlap at least one segmental duplication was calculated for a range of margin sizes. At a margin size of zero (complete
overlap with CNV), 38 of 80 observed CNVs overlap segmental duplications. The extent of overlap between CNVs and segmental duplications (black
solid line) increases with margin size. The red dotted line (expected CNVs) indicates the colocalization of segmental duplications with randomly
permuted genomic regions of lengths equal to the observed CNVs. Each point of the permuted data was calculated by determining the 95th percentile
of the overlap counts. The association between CNVs and segmental duplications remains significant to the 2-Mb window size (p , 0.01) and is
highlighted in the yellow rectangle.
doi:10.1371/journal.pgen.0030003.g006
Table 1. GO Categories Significantly Overrepresented in Mouse
CNVs
GO Termp-ValueCount
Receptor activity
Signal transducer activity
Carbohydrate bindinga
Response to stimulus
G protein–coupled receptor activityb
Response to biotic stimulusc
Defense responsec
Transmembrane receptor activityc
Rhodopsin-like receptor activityb
Response to other organism
Olfactory receptor activitybc
Response to pest, pathogen, or parasite
G protein–coupled receptor protein signaling pathway
Chitinase activity
1.32E?010
1.40E?008
8.01E?007
3.88E?006
1.53E?005
2.50E?005
5.64E?005
6.40E?005
9.81E?005
2.79E?004
7.08E?004
7.32E?004
7.33E?004
9.16E?004
47
49
12
42
27
21
20
29
24
14
18
13
26
3
aGO term overrepresented in previous report of mouse CNVs [22].
bGO term underrepresented in previous report of mouse CNVs [22].
cGO term overrepresented in previous report of human CNVs [22].
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resistance to Trichinella infection compared to C57BL/6 [29].
These examples independently validate this CNV discovery
platform and provide proof of principle that CNVs may
underlie many phenotypic differences between mouse
strains.
A recent comprehensive study of copy number variation in
the human genome [36] revealed many findings concordant
with our study of the mouse genome. Using SNP arrays and
CGH with a large insert clone array, extensive CNV was
detected in apparently normal individuals from the HapMap
collection. The human CNVs are associated with segmental
duplications and contain genes enriched for sensory percep-
tion GO categories. Taken together, these studies demon-
strate the extent and significance of CNV in the mammalian
genome.
Materials and Methods
Oligonucleotide array construction. A tiling-path CGH array for
whole-genome analysis in mouse (NCBI Build 34) was designed and
constructed by NimbleGen Systems (http://www.nimblegen.com).
Probes were selected with a minimum probe spacing of 4.5 kb, and
the resulting array had a median probe spacing of 5.2 kb. Probes were
synthesized using an isothermal format (Tm¼ 76 8C) and varied in
length from 45 to 75 bp.
Sample processing. Male mice aged 8 to 10 wk were obtained from
the research colony at The Jackson Laboratory or Taconic (http://
www.taconic.com). Genomic DNA was prepared from spleen and tail
specimens (DNeasy; Qiagen, http://www.qiagen.com). Unamplified
genomic DNA (1 lg) was labeled with Cy3 (test strains) or Cy5
(reference strain, C57BL/6J), and hybridizations were performed by
NimbleGen Systems in a two-color format according to Selzer et al.
[30].
Statistical analysis. Each array data set was imported into R [31]
for normalization. The normalize.qspline method from the Bio-
conductor package [32] was used to normalize the signal intensities
of the sample versus reference. A Statistical Process Control
algorithm (X. Li, A. Allred, M. Walter, R. Ries, T. Ley, W. Shannon,
unpublished data) was used to flag log2(test/reference) values that
deviate significantly from baseline. The segment boundaries were
defined using circular binary segmentation [33] across the flagged
region. A set of conservative criteria (five or more probes in a
segment, mean amplitude of log2shift across segment ¼ 60.5) were
used to define the final set of high confidence CNV calls. CNV
profiles and strains were clustered with hierarchical clustering using
average linkage and the Pearson correlation coefficient as the
distance. The probe density was computed by counting the number
of probes within each 500-kb window of the genome. The BLAT hit
count was defined as the number of matches in which the probe
sequence identity 3 length of matching sequence/length of the
probe was greater than or equal to 0.90. Gene annotation and
overlap were determined using Ensembl Genebuild July 2005,
database version 32.34 [34]. Gene enrichment was tested by
randomly selecting a segment length from the distribution of high
confidence CNV lengths, randomly selecting a valid chromosomal
location, and determining if the segment overlapped at least one
gene. A similar approach was used to test for association between
CNVs and segmental duplications. GO analysis was performed using
DAVID Bioinformatic Resources 2006 (http://david.abcc.ncifcrf.gov/
home.jsp) [35]. Comparison of CNVs to previous publications was
assessed by remapping CNVs from the appropriate NCBI assembly
version (Builds 30 and 32) using liftOver and determining the
overlap of reported CNVs.
PCR validation. To validate CNVs detected by oligo-aCGH, qPCR
assayswereusedto measure copynumberin alteredregionsrelative to
a control region of invariant copy number across all 21 strains
(selected based on aCGH profiles). Relative copy numbers were
determined by real-time PCR (qPCR) using TaqMan detection
chemistry and the ABI Prism 7300 Sequence Detection System
(Applied Biosystems, http://www.appliedbiosystems.org). Primers and
TaqMan probes were designed using ABI Primer Express Software
(version 2.0) and the NCBI Mouse Build 34 (primer and probe
sequences provided in Table S3). All probes were dual-labeled with 6-
carboxyfluorescein and 6-carboxytetramethyl-rhodamine. Each assay
was performed in triplicate using 25-ll reactions containing 12.5 ll of
TaqMan 23 PCR master mix (Applied Biosystems), 280 nM TaqMan
probe, 900 nM concentration of forward and reverse primer, and 100
ng of genomic DNA. Amplification was performed according to the
followingconditions:onecycleat508Cfor2min,onecycleat958Cfor
10min, and 50 cyclesat 958C for 15 s and 60 8C for1 min. Experiments
were performed on the test and control primers to verify comparable
efficiency in amplification prior to analysis of copy number in the
strains. The CTmethod was used for quantification of copy number in
the test strains relative to the reference strain (C57BL/6J). The CT
values for each set of triplicates were averaged and were normalized
against the control primer. The relative copy number for each strain
wascalculatedas2?(normalized CTfor the test strain?normalized CTfor C57BL/6).
A linear regression model was used to compare the copy number
estimates from aCGH and qPCR.
CNVs were also assessed by non-qPCR. Amplification reactions
contained 20 ll of Jumpstart Ready Mix Taq (Sigma, http://
www.sigmaaldrich.com), 2.5 ng of each primer, and 100 ng of
genomic DNA in a final volume of 40 ll. Amplifications were
performed on a Gene Amp 9700 (PE Applied Biosystems) at standard
conditions for 35 cycles, and the product was run on a 1.5% agarose
gel, stained with ethidium bromide, and visualized on a UV
transilluminator.
Supporting Information
Figure S1. Relationship between CNVs and Genome-Wide Probe
Coverage by Oligo-aCGH
Segmental gains and losses are shown to the left of each chromosome
(as in Figure 2). The probe density in 500-kb windows across the
genome is shown to the right of each ideogram.
Found at doi:10.1371/journal.pgen.0030003.sg001 (1.3MB TIF).
Figure S2. Detection of CNV Is Affected by Reference DNA Signal
Intensity
(A) CNV in a region of normal reference DNA signal on Chromosome
6. The mean signal intensity (n ¼ 21 arrays) for the reference sample
(C57BL/6J) ranges from 1 to 10,000 across this region (inset).
(B) CNV in a region of high reference DNA signal on Chromosome 8.
The segment boundaries coincide with a region of high mean signal
intensity for the reference DNA (inset).
Found at doi:10.1371/journal.pgen.0030003.sg002 (4.2 MB TIF).
Figure S3. Additional Validation of aCGH Results Using qPCR: Part I
Log2plot and qPCR data from (A) an 82.8-kb amplified region on
Chromosome 18 in AKR/J and PL/J, (B) a 93.8-kb deleted region on
Chromosome 3 in NOD/LtJ, (C) a 51.8-kb deleted region on
Chromosome 19 in CAST/EiJ, FVB/NJ, and MOLF/EiJ, and (D) a
110.6-kb segment deleted on Chromosome 11 in MOLF/EiJ (inset,
zoom-in view of y-axis). The start site of each CNV is shown next to
the log2plots.
Found at doi:10.1371/journal.pgen.0030003.sg003 (1.7 MB TIF).
Figure S4. Additional Validation of aCGH Results Using qPCR: Part II
Log2plot and qPCR data from (E) a 47.0-kb segment deleted on
Chromosome 1 in BALB/cByJ, C3H/HeJ, and PL/J, (F) a 1.1-Mb
segment deleted on Chromosome 4 in MOLF/EiJ, CAST/EiJ, and SM/J,
and (G) a 42.0-kb segment on Chromosome 6 amplified in SWR/J and
deleted in C3H/HeJ and PL/J (inset, zoom-in view of y-axis).
Found at doi:10.1371/journal.pgen.0030003.sg004 (3.6 MB TIF).
Figure S5. Unsupervised Clustering of CNVs in 21 MPD Strains with
Replicates
Ten replicates were studied, including repeat hybridizations with the
same sample or a different tissue from the same animal (spleen versus
tail DNA). The Pearson correlation coefficient was computed for the
log2signal for all probes for each pairwise chip–chip comparison.
The probe signal correlation coefficients are low since there is no
global normalization among arrays. However, there is a strong
correlation among the CNV profiles of replicate samples (mean
correlation, 0.92; range, 0.84 to 0.96). Replicate number is indicated
in parentheses. Sp, spleen.
Found at doi:10.1371/journal.pgen.0030003.sg005 (3.9 MB TIF).
Table S1. Segmental Variation in Areas Not Amplified in Reference
Strain (C57BL/6J)
Found at doi:10.1371/journal.pgen.0030003.st001 (102 KB XLS).
PLoS Genetics | www.plosgenetics.org January 2007 | Volume 3 | Issue 1 | e30028
Copy Number Variation in Mice

Page 9

Table S2. Segmental Variation in Regions Amplified in Reference
Strain (C57BL/6J)
Found at doi:10.1371/journal.pgen.0030003.st002 (74 KB XLS).
Table S3. Primers Used for CNV Validation
Found at doi:10.1371/journal.pgen.0030003.st003 (15 KB XLS).
Table S4. Comparison of CNVs in This Study with Previous
Publications
Found at doi:10.1371/journal.pgen.0030003.st004 (65 KB XLS).
Accession Numbers
Primary data from the oligo-aCGH experiments can be found in the
NCBI Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/
geo) under accession number GSE5805.
Acknowledgments
Matt Walter and Dan Link provided helpful discussion and critique of
the manuscript. Mice were kindly provided through collaboration
with the Mouse Phenome Project (The Jackson Laboratory, Bar
Harbor, Maine, United States).
Author contributions. TAG and TJL conceived and designed the
experiments. DE, RRS, TAR, and PSE performed the experiments.
TAG, PC, DE, WDS, XL, HLM, and JMC analyzed the data. TAG, PC,
and DE wrote the paper.
Funding. Supported by the National Cancer Institute (P01
CA101937) and the National Human Genome Research Institute
(T32 HG000045).
Competing interests. RRA, TAR, and PSE are employees of
NimbleGen Systems, Inc.
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Copy Number Variation in Mice