Human Molecular Genetics, 2013, Vol. 22, No. 6
doi:10.1093/hmg/dds515
Advance Access published on December 7, 2012
1097–1111
Copy number variation analysis implicates the cell
polarity gene glypican 5 as a human spina bifida
candidate gene
Alexander G. Bassuk1,{, Lakshmi B. Muthuswamy5,{, Riley Boland2, Tiffany L. Smith3,
Alissa M. Hulstrand2, Hope Northrup6, Matthew Hakeman2, Jason M. Dierdorff2,
Christina K. Yung5, Abby Long2, Rachel B. Brouillette2, Kit Sing Au6, Christina Gurnett7,
Douglas W. Houston2, Robert A. Cornell3 and J. Robert Manak1,2,4,∗
1
Department of Pediatrics, University of Iowa Carver College of Medicine, 2Department of Biology, 3Department of
Anatomy and Cell Biology, and 4Carver Center for Genomics, University of Iowa, Iowa City, IA 52242, USA 5Ontario
Institute for Cancer Research, Toronto, ON, Canada M5G 0A3 6Department of Pediatrics, University of Texas Med
School at Houston, Houston, TX 77030, USA and 7Department of Neurology, Washington University School of Med,
St Louis, MO 63110, USA
Received August 8, 2012; Revised November 5, 2012; Accepted December 3, 2012
Neural tube defects (NTDs) are common birth defects of complex etiology. Family and population-based studies have confirmed a genetic component to NTDs. However, despite more than three decades of research, the
genes involved in human NTDs remain largely unknown. We tested the hypothesis that rare copy number variants (CNVs), especially de novo germline CNVs, are a significant risk factor for NTDs. We used array-based
comparative genomic hybridization (aCGH) to identify rare CNVs in 128 Caucasian and 61 Hispanic patients
with non-syndromic lumbar-sacral myelomeningocele. We also performed aCGH analysis on the parents of
affected individuals with rare CNVs where parental DNA was available (42 sets). Among the eight de novo
CNVs that we identified, three generated copy number changes of entire genes. One large heterozygous deletion removed 27 genes, including PAX3, a known spina bifida-associated gene. A second CNV altered
genes (PGPD8, ZC3H6) for which little is known regarding function or expression. A third heterozygous deletion removed GPC5 and part of GPC6, genes encoding glypicans. Glypicans are proteoglycans that modulate the activity of morphogens such as Sonic Hedgehog (SHH) and bone morphogenetic proteins (BMPs),
both of which have been implicated in NTDs. Additionally, glypicans function in the planar cell polarity
(PCP) pathway, and several PCP genes have been associated with NTDs. Here, we show that GPC5 orthologs
are expressed in the neural tube, and that inhibiting their expression in frog and fish embryos results
in NTDs. These results implicate GPC5 as a gene required for normal neural tube development.
INTRODUCTION
Neural tube defects (NTDs) arise from a failed or disordered
closure of the neural tube during embryogenesis. These congenital disorders occur with a frequency of 1/1000– 1/5000
worldwide and therefore, are among the most common birth
defects (together with congenital heart abnormalities and craniofacial anomalies) (1 – 4). While environmental factors have
been implicated in NTDs, these factors alone fail to explain
most cases. Studies in mice have described over 200 (5) monogenic mutant lines with NTDs and have shown that the genes
involved play multiple distinct roles in neurulation (1,6).
Mouse studies also show that NTDs may be caused by multigenic influences, as revealed by the differing severities
produced when genetic defects are combined (7). However,
despite decades of research and hundreds of studies, we do
∗
To whom correspondence should be addressed. Tel: +1 3193350180; Fax: +1 3193351069; Email: [email protected]
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.
†
# The Author 2012. Published by Oxford University Press. All rights reserved.
For Permissions, please email: [email protected]
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Human Molecular Genetics, 2013, Vol. 22, No. 6
not yet understand the genetic contribution to human NTDs.
In humans, genetic etiologies for NTDs were first identified
30 years ago, when it was shown that the family members
of a person with an NTD have an increased risk (from 2 to
5%) of having an NTD themselves (8 – 12). In addition,
NTDs have been linked to several genes in the folatehomocysteine metabolic axis, consistent with epidemiological
evidence that between 30 and 70% of NTDs can be prevented
by prenatal folate (2– 4). Polymorphisms in these genes,
however, are not significantly associated with NTDs in all
populations, suggesting that polygenic and environmental
factors are important. Our groups and others have described
NTDs in chromosomal and inherited syndromes, including
trisomy 13 (13– 16), trisomy 18 (16 – 19), trisomy 21, and
22q11.2 and 13q deletion syndromes (20– 23). In rare cases,
syndromes that variably present with NTDs have been associated with a mutation in a single gene (24– 36). Using traditional linkage disequilibrium, patient studies of individual
(non-folate-related) candidate genes, including jumonji (JMJ)
(37), apolipoprotein E (ApoE), apolipoprotein B (ApoB)
(38), bone morphogenetic protein-4 (BMP4) (39), CITED2
(40), transcription factor AP2 (TFAP2) (41), multiple sequence homeobox-2 (MSX2) (41), PAX3 (42) and noggin
(NOG) (43), have only rarely succeeded in ascribing attributable risk for NTDs to specific genes.
More recently, several genes in the planar cell polarity
(PCP) signaling pathway have been implicated in NTDs.
PCP, also called tissue polarity, is the process by which
cells become polarized within the plane of an epithelium.
This form of polarization has been well studied in the adult
epithelial tissues of Drosophila where phenotypes are observed
in the form of altered orientation of hairs and bristles (44),
among other defects. In the fly, genetic studies of a wide
range of mutations affecting these highly organized structures
identified a group of so-called ‘core’ PCP genes, required for
PCP signaling in all tissues. These include Frizzled (Fz), Dishevelled (Dsh), Strabismus/Van Gogh (Stbm/Vang), Flamingo
(Fmi), Prickle (Pk) and Diego (Dgo) (44– 46). Members of
the PCP pathway are highly conserved in vertebrates where
they are also implicated in controlling tissue polarity in
several epithelia. Additionally, many of these proteins regulate
cell adhesion or cytoskeletal organization in non-polarized
cells to regulate morphogenesis. PCP regulators are essential
for controlling convergent extension (CE) of tissues during
gastrulation and neurulation in the embryo (47– 49), a
process that requires cell shape changes and cell intercalation.
In this context, regulation of core PCP components occurs
through b-catenin-independent Wnt signaling (47,48), whereas
PCP in Drosophila is not controlled by Wnt/Wg ligands.
The importance for CE in neural tube closure was first demonstrated by molecular disruption of CE following expression of
dominant-negative Dishevelled (Dvl) in the frog embryo (50).
In these studies, failure of CE in the midline caused the neural
folds to form too widely apart, preventing them from fusing
at the midline (50). Genetic studies in mouse have further
implicated core PCP pathway components in NTDs (e.g.,
Vangl2 (51– 53), Celsr1 [an Fmi ortholog] (54), Scribble
(Scrib) (55) and combined mutations of either Dvl1/Dvl2
(56) or Fz3/Fz6 (57)). A recent paper demonstrated that two
key morphogenetic processes required for neural tube closure
(CE and neural plate apical constriction) are linked by PCP
signaling (58). PCP components are also likely to contribute
to NTDs in humans. Genetic studies of human craniorachischisis
suggest an association with mutations in CELSR1 and SCRIB
(59). Recently, PRICKLE1 and PRICKLE2 mutations were
implicated as predisposing factors or risk modifiers for
human spina bifida (60,61). Two reviews summarize the compelling evidence for PCP gene involvement in NTDs (62,63).
The glypican family of heparin sulfate proteoglycan core
proteins has recently been implicated in regulating PCP signaling and CE in vertebrates. Zebrafish knypek/gpc4 mutants
exhibit abnormal convergence and extension during gastrulation and embryonic cells have abnormal PCP (64). Additionally, knockdown of gpc4 in frog embryos generates NTDs
(65,66). Glypicans can modulate the activity of bone morphogenetic proteins (BMPs) and Sonic Hedgehog (SHH) (67,68),
morphogens that regulate the bending of neural folds during
closure of the neural tube (69– 71). During mouse embryogenesis, high levels of Glypican 5 are expressed in the neural tube
(72). Consistent with a potential role of glypicans in spina
bifida, patients with 13q deletions that sometimes remove
GPC5 and GPC6 can present with NTDs (23,73). Collectively,
these results implicate the glypican gene family in promoting
normal neural tube development.
An extensive body of literature now shows that changes in
copy number variants (CNVs) play a substantial role in human
disease (74– 79) including birth defects (80,81). However,
with the exception of a few small-scale genomic rearrangement studies (20,82,83), almost all association studies regarding human NTDs have focused on either single-nucleotide
polymorphisms or gene mutations. To address this deficit, we
identified three independent cohorts of non-syndromic myelomeningocele, the most commonly observed form of spina
bifida, and performed whole-genome comparative genomic hybridization analysis. This study aimed to (1) identify rare copy
number events directly affecting coding genes in cases; (2)
determine whether any of these rare CNVs were de novo
events and (3) test whether candidate genes affected by such
CNVs were required for neural tube development in frogs and
zebrafish. These analyses identified GPC5 as a human spina
bifida candidate gene and demonstrated that reducing the expression of GPC5 orthologs in frogs or fish resulted in NTDs
consistent with spina bifida. This work demonstrates that
birth-defect-associated genes can be identified by CNV analysis
and functionally validated in vertebrate model systems.
RESULTS
We performed array-based comparative genomic hybridization (aCGH on 189 spina bifida patients (128 Caucasians, 61
Mexicans) to identify rare CNVs. Only variants that affected
coding sequences of genes were considered for further analysis (Supplementary Material, Table S1). For these cases, parental DNA was obtained when available and the variants were
analyzed to determine whether they were de novo. Any variants that affected entire genes were considered for further
functional analysis in vertebrate model systems.
Human Molecular Genetics, 2013, Vol. 22, No. 6
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Figure 1. Network analysis of coding genes overlapping rare CNVs. Module annotations are done with false discovery rate (FDR) , 0.05. Solid line—annotated
interaction; dashed line—predicted interaction; arrow end—activating interaction; straight end—inhibiting interaction. Sources for annotations come from: K,
KEGG, P, Panther, R, Reactome, N, NCI Pathways, B, BioCarta, C, CellMap.
Rare copy number variations
We defined a CNV in affected cohorts to be ‘rare’ if the
segment has no overlap with any of the CNVs in the Database
of Genomic Variants, or if the overlap with such variants was
less than or equal to 50% of its genomic length. To identify
coding regions of genes within those events, we further
refined boundaries of the rare CNVs. The length and boundaries of a given CNV reflect the resolution of the array. Two
CNV intervals from different individuals may have the same
boundaries. Frequently, however, CNV intervals have
varying extents of overlap with other CNV intervals in a
given population. We define the ‘maximum frequency’ of
any given CNV as the number of overlaps with other CNVs,
and used the ‘minimal overlapping region’ to be the boundaries of rare events.
We identified a total of 1976 rare genomic variant events
containing at least one exon of a coding gene, giving an
average of 10 rare events per individual (all the events
are detailed individually in Supplementary Material,
Table S1). In these 1976 CNVs, a total of 2269 genes
were affected. Interestingly, a subset of such CNV-altered
genes have previously been implicated in neural tube formation; for instance, JMJD5 (‘jumonji’ domain containing 5
(37), HES1 and HES3 (84); PAX3 (27,85); and both
BRD3 and BRD4 (bromodomain-containing 3 and 4) (86).
Although it is reasonable to assume that this subset of
CNVs contributed to the NTD in these patients, the majority
of CNVs identified in this study could not readily be associated with NTDs without further analysis. Hence, we
tested the hypothesis that rare coding genes with altered
number of copies may have a common functional impact
using network and pathway analysis.
We used the reactome functional interaction (FI) network
(which consists of curated pathways and high-confidence predicted interactions identified from non-curated sources by
machine-learning techniques) to identify the significantly
enriched pathways that are interconnected by FI of genes
affected by rare CNV events. The combined network contains
nearly 9400 SwissProt proteins and 210 000 FIs. Of the 2269
coding genes affected by rare copy number aberrations, 44%
were projected onto the FI network. Using hierarchical clustering based on the network, we identified 567 genes that were
more highly interconnected with each other than by chance
(P , 0.001). A subnetwork was built from these 567 genes.
Spectral partitioning clustering algorithm revealed 15 functionally related network modules (0 – 14) as illustrated in
Figure 1, 8 of which contain 15 or more genes (Supplementary
Material, Table S2 lists the genes forming the modules). Each
of the functional modules is then annotated for pathways using
KEGG, Panther, Reactome, NCI pathways, BioCarta and
CellMap, and the 47 statistically significant pathways with a
NFE2L3
GPC5, GPC6
RGPD8, ZC3H6
NPAS3
0
0
0
1
0
0
0
0
0
3
0
0
0
0
0
1
1
1
1
0
0
0
0
1
1
0
0
0
Dup
Del
Del
Dup
Dup
Dup
Del
158.79
18.06
4470.27
112.93
37.00
32.47
21.87
2:142717141-142875928
7:26162685-26180745
13:88695918-93166192
2:112809127-112922053
14:32461626-32498630
19:37026054-37058521
10:128208296-128230163
SB2223
SB2223
SB2223
SB147
SB147
SB147
SB287
2q22.2
7p15.2
13q31.2-q31.3
2q13
14q13.1
19q12
10q26.2
TMEM198,RESP18, EPHA4, SGPP2,
AP1S3, SPEG, CHPF, FARSB,
SLC4A3, GMPPA, OBSL, SERPINE2,
MRPL44, KCNE4, STK11IP, DNPEP,
ACSL3, DES, FAM124B, PAX3,
MOGAT1, ACCN4, CUL3, CCDC140,
WDFY, SCG2, INHA, DOCK10
0
2
1
27
Del
5649.80
2:219889913-225539715
2q35-q36.2
Number of
non-coding,
partially
overlapping
genes
Number of
non-coding,
overlapping
genes
Number of
coding, partially
overlapping
genes
Number of
coding,
overlapping
genes
Copy
number
polarity
Genomic
length (kb)
Cyto-band
SB111
To test the hypothesis that a proportion of the rare CNVs in the
cases are de novo germline variations, we obtained parental
DNA from 42 cases and performed CGH analysis. We identified eight rare CNVs that were present in a case but not in
either parent (i.e. de novo; Table 1). Out of the eight, three
completely encompass at least one gene in the region. One
Genomic location
De novo variations
Family
ID
false discovery rate (FDR) , 0.05 are listed in Supplementary
Material, Table S3 (note that some pathways are indicated
multiple times; thus, 47 pathways is the coalesced number).
It is interesting to note that a subset of the pathways contained
within the modules have been previously implicated in NTDs,
including integrin signaling (FDR , 3e24), 3) cell cycle
(FDR , 1e23), Wnt signaling (FDR , 5e24), Hedgehog
signaling (FDR , 3e24) and glypican pathway (FDR ¼
4.4e23). Notably, although only 8 modules contained 15 or
more genes, both the Wnt signaling and Glypican pathway
modules were among them (see Supplementary Material,
Figs S2 and S3). We further tested whether these pathways
were truly enriched due to their disease association or
whether they were simply the result of copy number variation
normally affecting the genes in these pathways. We analyzed
CNPs generated for 2026 healthy genomes as reported by
Shaik et al. (87). We found 1938 genes overlapping CNPs,
out of which 721 were highly interconnected. The FI network
analysis revealed a total of 174 statistically significant pathways (after coalescing pathways listed multiple times;
FDR , 0.05; Supplementary Material, Table S4), which is
in contrast to the much smaller group (47) of statistically significant and functionally relevant pathways observed in our
spina bifida cohort (Supplementary Material, Table S3). This
suggests that CNPs in healthy populations do not selectively
target particular functional pathways, while ‘Rare CNVs’ in
the spina bifida cohort specifically target pathways involved
in neural tube development.
We then asked how the functional gene pathways associated
with recurrent CNPs compared with the spina bifida functional
pathways. We defined a CNP to be recurrent if it was observed
in .0.5% of the population. FI network analysis on 476 recurrent genes revealed three statistically significant modules consisting of eight pathways which can be categorized into three
functionally independent pathways (Supplementary Material,
Table S4). While two of the functional pathways, olfactory
signaling (module 2) and immune response-related (module
6), may be targeted due to normal genomic variation, Wnt
and Cadherin signaling (module 3) overlaps one of the pathways identified in the spina bifida cohort. However, the annotated genes within the Wnt signaling pathway do not overlap
between the two datasets, suggesting that a specific subset of
Wnt pathway genes may be more tightly associated with the
disease process. In summary, the set of genes contained in
the CNVs found in patients with NTDs, in comparison to a
random set of genes or genes overlapping recurrent copy
number polymorphisms, is enriched for those that participate
in cellular processes important for neural tube formation.
This supports the hypothesis that the rare CNVs we have identified in the disease cohorts are pathogenic in at least a subset
of patients.
Coding genes
Human Molecular Genetics, 2013, Vol. 22, No. 6
Table 1. List of de novo CNVs observed in 42 cases based on trio analysis. Counts of genes that are (a) partially over-lapping and coding, over-lapping and coding, partially over-lapping and non-coding,
over-lapping and non-coding genes are listed. Genes whose CDS are within the copy number altered regions are considered potential candidates associated with the disorder and are listed
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Human Molecular Genetics, 2013, Vol. 22, No. 6
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Figure 2. Identification of a de novo heterozygous deletion in a spina bifida proband which removes the polarity genes glypicans GPC5 and GPC6. Segmentation
plots of aCGH data generated by Roche NimbleGen software of mother (top), father (middle) and proband (bottom). Genes within this region are indicated below
the segmentation plots. Note that the entire GPC5 gene is removed by the deletion, whereas only the first two exons of GPC6 are removed.
heterozygous deletion removed 27 genes, including PAX3, a
gene known to be in the deleted region in Wardenburg syndrome type 1 patients with spina bifida (although the patient
in this case did not have other features of Wardenburg syndrome type 1) (88). Additionally, mouse model evidence
implicates Pax3 in NTDs (89). A second CNV altered genes
whose function or expression is mostly unknown (RGPD8,
ZC3H6). These genes were not pursued further in the
present study. A third CNV, a heterozygous deletion,
removed GPC5 and two exons of GPC6, both of which
encode glypicans (Fig. 2). We identified the specific breakpoints of this deletion by a long-range PCR (chr13:
88,692,539 (build hg18) and chr13: 93,166,512; see Materials
and Methods) and found 49 bp of a LINE element of the L1
family inserted between them. Given the multitude of connections between glypicans and neural tube development (see
Introduction), we considered GPC5 and GPC6 as potential
spina bifida candidate genes.
Glypican 5 is required for neural tube closure in Xenopus
embryos
To test whether GPC5 or GPC6 were reasonable spina bifida
candidates, we examined their expression in the frog, Xenopus
tropicalis. Using an organism resource database (www.xenba
se.org) we identified a full-length expressed sequence tag
(EST) for a X. tropicalis glypican 5-like gene. This transcript
encodes a predicted protein with 40% identity/60% similarity
to human GPC5 at the amino acid level. For gpc6, there is no
available EST sequence data, although there is a predicted
transcript present in the X. tropicalis genome. This putative
transcript encodes a predicted protein with 87% similarity
at the amino acid level. As shown in Figure 2, GPC5,
GPC6 and DCT (dopachrome tautomerase) are sequentially
organized on human chromosome 13. In the X. tropicalis
genome, gpc5 is located on a separate genomic scaffold
from the gpc6/dct pair. Together with analysis of fish (discussed below) and chick genomes, these observations reveal
that there have been genomic rearrangements in this region
in the course of evolution.
Using in situ hybridization on X. tropicalis embryos, we
detected gpc5 expression diffusely throughout the neural
plate during early neural-fold stage embryos (stage 15/16;
Supplementary Material, Fig. S4). In mid-late neural-fold
stage embryos, expression became enriched in the floorplate
of the spinal cord, and by the early tailbud stage (stage
30), expression was prominent in the floorplate, and evident
in the somites and optic vesicles (Supplementary Material,
Fig. S4). Expression was not detectable by in situ hybridization during the cleavage or gastrula stages. These data are consistent with potential functions for Gpc5 during neurulation in
this organism. In contrast, our efforts to detect expression of
gpc6 at embryonic stages were unsuccessful, consistent with
the lack of EST evidence for expression of this gene. Therefore, we pursued functional studies of gpc5. We designed antisense morpholino oligonucleotides (MOs) complementary to
the gpc5 start codon to inhibit translation of this mRNA. We
injected gpc5-MO, or a negative control MO, into fertilized
X. tropicalis eggs and analyzed the resulting embryos for
NTDs. Embryos injected with a 10-ng gpc5-MO developed
normally through cleavage and gastrulation with no overt
defects in early morphogenetic movements. However, more
than half of these embryos went on to show neural tube
closure defects (Fig. 3 and Table 2). Phenotypic inspection
of gross morphology showed an open neural tube (spina
bifida) particularly in the posterior neural tube. This effect
was substantiated by in situ hybridization against pax6, to delineate the dorsal margin of the neural tube. Affected embryos
showed gaps in the fusion of the dorsal neural tube margins
along the midline, particularly in the posterior neural tube
(Fig. 3F and G). These data support a role of Gpc5 in tetrapod
neurulation.
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Human Molecular Genetics, 2013, Vol. 22, No. 6
Figure 3. gpc5 morpholinos inhibit neural tube closure in X. tropicalis embryos. (A and B) Tailbud stage X. tropicalis embryos injected with gpc5-MOs (B) or
left uninjected (A). (C and D) Stage 22/23 embryos injected with control morpholino (co-MO; C) or 10 ng gpc5-MO (D). Arrow in (D) indicates open neural
tube. (E– G) Embryos injected with a co-MO (E) or gpc5-MO (F and G) were stained for pax6 by in situ hybridization. Arrow in (G) indicates open neural tube.
Dorsal views, anterior is toward the top in (C, D) and toward the left in (A, B; E –G).
Table 2. Summary of NTDs in gpc5-MO-injected X. tropicalis embryos
Normal
(%)
Uninjected/control MO
(20 ng)
gpc5-MO (10 ng + 10 ng
co-MO)∗∗
47/47 (96)
NTDs (%) Other/blastopore
closure defects (%)
0/27 (0)
0/27 (0)
22/69 (32) 44/69 (64) 3/69 (4)
Summary of three experiments (∗∗ P , 0.0001, chi-square)
Glypican 5 is required for morphogenesis of the trunk
in zebrafish embryos
To further test whether mutation in GPC5 or GPC6 might
cause spina bifida, we examined expression of their orthologs
in zebrafish (Danio rerio) embryos. In contrast to neurulation
of the rostral central nervous system (CNS) in mammals and
amphibians, in zebrafish the neuroectoderm initially forms a
solid neural keel, which subsequently gains a lumen (90).
Nonetheless, because morphogenesis of the neural tube in zebrafish embryos results from the folding of a neural epithelium,
it is considered primary neurulation (91) rather than secondary
neurulation, in which the neural rod derives from a condensation of a mesenchymal mass (92). Searching the zebrafish
genome (Ensembl, Zv9), we identified an apparent GPC5
ortholog (i.e., gpc5) on chromosome 1 (see Methods). The predicted protein encoded by this transcript is 40% identical/58%
similar to human GPC5. We also detected two orthologs of
GPC6, gpc6a and gpc6b, which are 69% and 60% identical
to human GPC6, respectively. Similar to the arrangement of
GPC5 and GPC6 in the human genome, zebrafish gpc6a is adjacent to gpc5 (on chromosome 1), but in contrast to humans,
no ortholog of dct is present nearby. Interestingly, gpc6b is
adjacent to dct on chromosome 9, but no ortholog of gpc5
is nearby. We isolated RNA from 24 h post-fertilization
(hpf) embryos and amplified pieces of gpc5 and gpc6a. We
were unable to amplify gpc6b from complementary DNA
(cDNA), similar to our experience with Xenopus gpc6.
We performed in situ hybridization to assess expression of
gpc5 and gpc6a. In 12 hpf embryos (late somitogenesis
stage) processed with an antisense gpc5 probe signal was
detected broadly, including in the brain and spinal cord (Supplementary Material, Fig. S5A). In contrast, embryos hybridized with a sense gpc5 control probe exhibited no signal
(Supplementary Material, Fig. S5B). At 36 hpf, expression
of gpc5 was clearly present in the floor plate (Supplementary
Human Molecular Genetics, 2013, Vol. 22, No. 6
Material, Fig. S5C and D). In contrast, gpc6b expression at
12 hpf was undetected, and at 24 hpf was diffuse and barely
detectable by in situ hybridization, even after extended developing (not shown). Based on the pattern of mRNA expression,
Gpc5 was considered a good candidate to participate in zebrafish neurulation.
To inhibit gpc5 expression, we injected zebrafish embryos
with an antisense MO that overlaps the junction of intron
5 and exon 6 in gpc5 mRNA (hereafter, gpc5 MO). We confirmed by RT– PCR that the levels of correctly spliced gpc5
are diminished in such embryos at 24 hpf (Supplementary
Material, Fig. S6). In gpc5 MO-injected embryos at 30 hpf,
we observed morphological phenotypes. Whereas in uninjected or control MO-injected embryos, the notochord was
readily visible (Supplementary Material, Fig. S7A), in strongly
affected gpc5 MO-injected embryos, the somite boundaries
were indistinct and, remarkably, the notochord was not
readily visible, especially in the tail (Supplementary Material,
Fig. S7C and F). In less strongly affected embryos, the notochord appeared diminished in size and there was a downward
bend at the end of the hindyolk (Supplementary Material,
Fig. S7B and E). The fraction of injected embryos in these
phenotypic categories correlated with the dose of MO injected
(Supplementary Material, Fig. S7G).
To more clearly reveal the effects of gpc5 knockdown on
the mesoderm, we fixed MO-injected embryos at 14 hpf
(Fig. 4A and B) or 24 hpf (Fig. 4C and D) and processed
them to reveal expression of myod, a marker of somatic mesoderm (Fig. 4A– D) or ntl (Fig. 4I and J), a marker of the notochord. In gpc5 MO-injected embryos at 14 hpf, somite
boundaries were less distinct than normal; in addition, the
length of the axis appeared shortened at this stage (Fig. 4A
and B). At 24 hpf, the somite boundaries in gpc5 MO injected
are much less distinct than normal, and the length of the
embryos was clearly shorter than normal (Fig. 4C and D). Processing embryos to reveal ntl expression confirmed the observation that in strongly affected gpc5 MO-injected embryos,
the notochord is absent (Fig. 4I and J) or fragmented (not
shown). To highlight the CNS, we processed gpc5
MO-injected embryos to reveal elavl3, a marker of differentiated neurons (93). The CNS of gpc5 MO-injected embryos
was clearly abnormally shaped and mispatterned in comparison to control MO-injected embryos (hereafter, controls)
(Fig. 4E and F). The sections of these embryos showed widening of the neural tube and loss of neural tube organization following gpc5 knockdown (Fig. 4G and H). To confirm the
specificity of this phenotype, we tested a second MO targeting
the splice site of exon 1 and intron 1 of gpc5. This MO (gpc5
MO e1i1) also disrupted morphogenesis of somites, notochord
and neural tube, although with lower penetrance than the gpc5
MO (Table 3). These phenotypes were not observed in
embryos injected with a negative control MO (Table 3). In
summary, inhibition of Gpc5 expression is sufficient to
perturb morphogenesis of the trunk in zebrafish, resulting in
an abnormally shaped neural tube which is significantly
widened, reducing the likelihood of forming a properly
closed neural tube. Taken together with the frog studies
described above, these findings support the hypothesis that
decreased expression of GPC5 predisposes human patients
to spina bifida.
1103
DISCUSSION
Here, we have used aCGH analysis to screen 189 patients with
spina bifida for potentially etiologic CNVs that are not found
in a database of common CNVs (or have minimal overlap with
CNVs found there). Our principal findings were 2-fold: first,
we found that the list of 2269 genes contained within the
boundaries of these CNVs is enriched for those that participate
in regulatory pathways involved in neurulation, relative to a
random list of genes of this length. This finding supports the
notion that the CNVs contribute to the etiology in at least a
subset of spina bifida patients. Second, we identified eight
CNVs that are present in patients and not parents; such ‘de
novo’ mutations are particularly likely to be involved in
disease pathogenesis (94) and are thus worthy of special consideration. Of the eight de novo variants we discovered, only
five altered gene exons (see Table 1). As discussed below,
one of these removed a known spina bifida gene (PAX3),
three contained genes with no known role in neural tube formation, and the final one contained two genes that seemed
good candidates to contribute to this process (GPC5 and
GPC6). We subjected these genes to functional tests in
vertebrate model systems and found evidence that GPC5 is
important for neural tube formation. Together this work has
served both to identify a new spina bifida candidate gene
and to provide a pipeline for future CNV analyses where
confirmation by replication is not readily feasible due to
small cohort sizes or the rarity of the etiologic chromosomal
aberration.
Network-based pathway analysis suggests CNVs contribute
to spina bifida
Our pathway annotation analysis of genes found within the
CNV boundaries in the spina bifida patients revealed enrichment for key biological functional groups. Interestingly, six
out of the eight high-confidence functional modules (represented by ≥15 genes) identified in our network analysis
contain pathways that have been hypothesized or proven to
be essential for neural tube closure (95) (for example, cell
cycle, extra cellular matrix – receptor interaction, Wnt and
Hedgehog signaling, calcium signaling pathway and glypican
pathway). The two remaining functional modules were (1) signaling via Rho GTPases and (2) transcription, spliceosome,
and formation and maturation of mRNA transcript. Although
not explicitly hypothesized to be involved in neural tube
closure, the first of these pathways is nonetheless represented
in the NTD literature since the mice mutant for p190 RhoGAP,
a Rho GTPase-activating protein, present with NTDs (96). The
second of these pathways is generic for transcriptional processes and thus cannot persuasively be ruled in or out for its
involvement in neural tube closure. Although further studies
will be required to explain the contributions of the genes in
these pathways to the development of this disorder, the
results of our pathway analysis support the model that multiple
susceptibility genes are functionally convergent and that alteration in copy numbers in any one of them can predispose
humans to spina bifida. Importantly, these results underscore
the utility of pathway analysis to uncover candidate genes
for complex, multigenic disorders.
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Human Molecular Genetics, 2013, Vol. 22, No. 6
Figure 4. gpc5 MO disrupt morphogenesis of the trunk in zebrafish embryos. Abnormal morphogenesis of the neural tube and surrounding tissue in gpc5
MO-injected embryos compared with controls, (A–J). Embryos fixed at 14 hpf (A and B) or 24 hpf (C–J) were stained for myod (A –D), a marker of
somatic mesoderm; elavl3 (E– H), a marker of differentiated neurons; or ntl (I,J), a marker of the notochord. In comparison to (E) control MO-injected
embryos, the hindbrain is broader and neurons appear disorganized in (F) gpc5 MO-injected embryos. This is highlighted in transverse trunk cross sections
of (G) control and (H) gpc5 MO-injected embryos. In (A) control MO-injected embryos, somites exhibit a classic chevron shape, while in (B) gpc5 MO-injected
embryos, myod expression is compressed. (I and J) In lateral view, the notohord is clear in (I) control MO-injected embryos, while it is absent in (J) gpc5
MO-injected embryos.
Human Molecular Genetics, 2013, Vol. 22, No. 6
Table 3. Summary of NTDs in gpc5-MO-injected D. rerio embryos
Normal (%)
Trunk Defects
(%)
Control MO
99/104 (95)
0/104 (0)
(2 mg/ml) + p53
(1.5 mg/ml)
gpc5-MO (2 mg/ml) + p53 131/410 (32) 243/410 (59)
(1.5 mg/ml)∗
156/258 (61) 196/258 (37)
gpc5 MO e1i1
(2 mg/ml) + p53
(1.5 mg/ml)∗
Gastrulation
failure (%)
5/104 (5)
36/410 (9)
6/258 (2)
Summary of two to four experiments for each group (∗ P , 0.0001, chi-square)
Analysis of de novo CNVs identifies potential genes that
may contribute to spina bifida
We analyzed a subset of spina bifida patients for de novo
CNVs, given that this class of CNV is especially likely to etiologic when both parents are unaffected. Of the five we found
that disrupted genes (either in their entirety or in part), one
affected PAX3 (a gene required for neural tube closure in
mice and humans (97)), supporting the validity of our approach. Three of the other de novo CNVs altered genes for
which little is known regarding function, or for which evidence suggests that they are less likely to be involved in
neural tube development (see Table 1). For example,
NFE2L3 is a cap ‘n’ collar transcription factor that, when
knocked out in the mouse, does not display any obvious phenotypes (98). Furthermore, two genes (RGPD8 and ZC3H6)
have protein domains with predicted functions (Golgi-targeted
Ran GTPase-binding protein and zinc finger transcription
factor, respectively) but no reported function in development.
Additionally, genomic alterations in the NPAS3 gene have
been associated with schizophrenia and mental retardation,
but no NTDs were reported in these patients (99). In
summary, we identified several de novo CNVs in patients
with spina bifida that contain genes not previously implicated
in neural tube closure. Whether these genes play a role in this
process awaits further study.
Knockdown of gpc5 in frog and fish support the model that
GPC5 is a spina bifida gene
The remaining de novo CNV directly altering a coding gene
deleted GPC5 and part of GPC6 (Fig. 2), both of which
encode glypicans. Substantial evidence implicates glypicans
in neural tube development. First, in the mouse embryo, Gpc5
is prominently expressed in the neural tube (as well as in
limbs and kidney) during embryogenesis (72). Second, the activity of morphogens implicated in NTDs (such as SHH and
BMPs) is known to be modulated by glypicans (67,68,100),
which are localized to the outer surface of the plasma membrane of cells and are thought to work by stabilizing the interaction of morphogens with their receptors (67). Third, glypican
4 morpholino knockdowns in frogs resulted in NTDs (65,66),
1105
and a zebrafish gpc4 mutant exhibits defects in convergence
and extension consistent with disruption of the PCP pathway
(64). Fourth, glypicans are classified as cell polarity genes,
and several genes in this class have already been implicated
in NTDs and neural tube closure (including Vangl2, Celsr1,
Dishevelled, and Prickle1 and 2; see Introduction for references). These published findings, coupled with the identification
of a de novo deletion in a spina bifida case that altered two glypican genes, prompted us to investigate the expression and role
in neurulation of gpc5 and gpc6 orthologs in two vertebrate
models, X. tropicalis and D. rerio. We did not detect expression
of gpc6 orthologs in either species, suggesting that this gene
does not play an obvious role in neurulation. On the other
hand, we discovered that at neurulation stages in embryos of
both species, gpc5 is expressed broadly and with clear expression in the presumptive neural ectoderm (where it is maintained
at later stages, mainly in the ventral spinal cord). There were
differences in the phenotype of embryos of the two species
after gpc5 knockdown; for instance, a strong effect on notochord formation was only observed in zebrafish. Nonetheless,
in both species morphogenesis of the neural tube was clearly
abnormal upon depletion of gpc5 expression. The mechanistic
basis of the requirement for GPC5 in spinal cord morphogenesis
awaits further investigation; however, it is intriguing that GPC5
is specifically required for the binding of Shh (an important
morphogen in the developing CNS) to its receptor Ptc1 (100).
In summary, identification of a de novo deletion in a spina
bifida patient that affects GPC5, as well as functional validation
in two vertebrate model systems, supports the hypothesis
that mutation of GPC5 predisposes humans to spina bifida. Intriguingly, our FI network analysis of genes altered by rare
CNVs (Fig. 1) identified multiple statistically enriched pathways which are directly linked to glypicans (Wnt signaling,
glypican pathway, Hedgehog signaling, TGF-beta receptor signaling), further underscoring the connection between GPC5 and
spina bifida.
Final confirmation that GPC5 contributes to the pathogenesis of spina bifida awaits the identification of additional
GPC5 mutations in spina bifida patients. In the cohort of
189 such patients, we identified only a single patient with a
GPC5 deletion. This observation, combined with the dramatic
effect of gpc5 knockdown in frogs and fish, suggests that
GPC5 mutations are rare but of high impact, the class of
variant that may help explain some of the missing heritability
in polygenic complex disorders (101,102). However, it should
be noted that GPC5 mutations do not necessarily lead to spina
bifida; for example, a recent report identified two Feingold
syndrome patients with heterozygous deletions of one or
more exons of GPC5 which did not present with NTDs (103).
In these cases, deletion of a microRNA cluster (miR-17 –92)
immediately upstream of GPC5 was shown to be the likely
cause of the syndrome (which presents with microcephaly,
short stature and digital anomalies (103)). Conversely, the
patient with the GPC5 deletion reported here had no apparent
Feingold syndrome phenotypes, even though this deletion also
removes the miR-17 – 92 cluster. These observations underscore the significant role played by the genetic background
in promoting the disease state in these cases.
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Human Molecular Genetics, 2013, Vol. 22, No. 6
MATERIALS AND METHODS
Clinical cohort
We used three independent non-syndromic myelomeningocele
spina bifida cohorts assembled in three different centers.
DNA samples from spina bifida patients and parents were
collected following Internal Review Board approved protocols
from the Northwestern University (Dr Bassuk), Washington
University St Louis (Dr Gurnett) and the University of
Texas Health Sciences Center at Houston (UTHSC; Dr
Northrup) and were isolated using standard commercially available genomic DNA purification kits. One hundred and
twenty-eight patients were Caucasians from the Northwestern
University, Washington University and UTHSC, while 61
were Hispanics from the UTHSC (104). All patients were
examined by a neurosurgeon, and a neurologist or geneticist,
and all patients had evidence of non-syndromic lumbar–
sacral myelomeningocele. All patient samples were obtained
with informed consents following the local Internal Review
Board criteria and the Declaration of Helsinki criteria. All
samples were de-identified as per these criteria.
Comparative genomic hybridization
Copy number profiles were generated in all affected cases and,
when available, unaffected parents, using an aCGH technology
from Roche NimbleGen following the protocol recommended
by the manufacturer. The array used is the 2.1 million feature
whole-genome human tiling array with a median probe
spacing of 1169 bp (catalog number 05541921001, Human
CGH 2.1M Whole-Genome Tiling v2.0D Array). In brief, the
sample cohorts were labeled with Cy3 and the reference
genome was labeled with Cy5. All samples were hybridized
with a population-matched male reference genome. Additional
information can be accessed in the Supplementary Material
section.
hybridization. The details of the CNV detection algorithm
are described in the following section.
CNVs from 20 experiments were clustered using single
linkage hierarchical clustering. Because of the greedy nature
of this algorithm, the Jaccard index is used to separate
loosely linked nodes of large clusters into tightly linked subclusters (106). The Jaccard index is a measure of the similarity
of two object sets, in this case the observed number of shared
branches between two nodes of a cluster in relation to the
number of possible shared branches. All intact clusters of
CNVs are thus obligated to show a minimum degree of similarity among all members. We identified 250 gain and 148
deletion clusters. Repeatability measures for all array hybridizations (whether comparisons are made for the same or different array usage) are then estimated based on 398 CNV events
using a three-way ANOVA statistical test for three independent variables, namely ‘usage’, ‘arrays’ and ‘copy number
type’. The CNV type was included as an independent variable
in order to separate the effect due to gains and losses. Each
event is weighted as inversely proportional to its genomic
length. The results of the analysis, shown in Supplementary
Material, Table S5, yielded statistically insignificant
P-values of 0.82, 0.99 and 0.99 for both the main and interaction effects. The results suggest a very high reproducibility
of detecting CN events across arrays of the same use or across
arrays of different uses. To reconfirm, we further calculated
Spearman’s rank correlation coefficient, r, for all possible
pair-wise combinations which is shown in Supplementary
Material, Figure S9. Eighteen out of 20 experiments gave a
Spearman rho of .0.95, strongly suggesting a high correlation
amongst all datasets. One array from reuse 2 and one array
from reuse 3 produced a rho of 0.92. This is due to a moderate
reduction in signal to noise as observed by an increase in
median absolute deviation by 15% compared with the rest of
the data. In summary, we conclude that, using our reuse strategy, Roche NimbleGen microarrays can generate qualitatively
similar data across at least five array uses.
Array reuse procedure
We employed an array reuse procedure for this study, which
we developed in-house. In short, we used a glycerol – salt
denaturation buffer to strip arrays of labeled, hybridized DNA
fragments (105), followed by hybridization with another
sample; up to five uses were employed per array. A detailed
protocol of the reuse procedure is provided in Supplementary
Material, Figure S8. In order to qualitatively assess the data
quality and reproducibility from the reuse procedure, we performed aCGH experiments using the same pair of ‘Reuse Test’
and ‘Reuse Reference’ human genomic DNA on seven different arrays for uses 1, 3 and 5, and various experimental and
reference samples from other studies for uses 2 and 4; these
intermediate hybridizations were performed to eliminate the
possibility that the same hybridization patterns generated by
the Reuse Test and Reference samples were carried over
from one use to another. To estimate the statistical significance
of repeatability, we compared CNV calls for array uses 1, 3
and 5. Microarray hybridization data underwent a series of
steps including ‘normalization’ and ‘segmentation’ to detect
break points of copy number changes. The third use of array
number 7 was not included due to a mixer leak during
Data analysis of spina bifida hybridizations
Microarray hybridization data underwent two major steps
before it was interpreted as demonstrating copy number
changes (Supplementary Material, Fig. S1): (a) quality
control and (b) normalization. We have employed quality
measures at various stages of the process to achieve uniform
data quality. We extracted 40 different parameters associated
with every hybridization in order to identify any scores
beyond acceptable thresholds. Additionally, all scores are
stored in a database to facilitate a comprehensive review and
analysis of trends and batch effects. These parameters
include measure of DNA quality, various signal and noise
measures, estimation of statistical parameters on the copy
neutral state using an expectation – maximization algorithm,
which is further used to define ‘Copy Number Altered’ state.
The results obtained with poor quality DNA manifest themselves as a trend (low frequency components) in the ratio of
intensities in the two channels, which can result in a lowamplitude false signal. We have developed a mathematical
algorithm to detect the trends based on the integrated power
of the Fourier-transformed signal. The experiments with a
Human Molecular Genetics, 2013, Vol. 22, No. 6
1107
trend measure higher than a threshold value were repeated.
Quality-controlled data are subjected to normalization procedures to adjust for uneven hybridization, unbalanced fluorescent
signals in two channels and other systemic variations with no
biological relevance. We employed two normalization procedures: local and LOWESS normalization. Local normalization
corrects for nonuniform intensities across the array due to experimental procedures and LOWESS normalization adjusts for
the expectation that the genome is diploid.
The normalized ratios of intensities (referred to as LRR) are
readily modeled as segmental deletions and duplications or
amplifications. The method utilizes minimization of variance
with a Kolmogorov – Smirnov (KS) test to determine significance; segments are defined as non-overlapping, genomic
regions where the copy number has changed from the baseline.
The algorithm consists of two components. The first part is
based on the minimization of variance. Initially, we search
for breakpoints that may be boundaries of segments. The
profile is divided into 100 probe-long windows. Within a
window, the first local minimum of variance is identified
and accepted as a new breakpoint. Whenever a new breakpoint
is found, the algorithm recursively breaks the said region until
no breakpoints can be found therein. If no breakpoints are
found, the window is shifted by half its size, and the recursive
procedure continues until the end of the chromosome is
reached. Once the initial breakpoints are identified, each
breakpoint is validated for statistical significance by comparing the distributions of segments on either side of the breakpoint using the KS null hypothesis test. If the P-value is
,1025, then the breakpoint is accepted. If not, the segments
are merged. For each hybridization, the LRR is modeled as
three modes corresponding to ‘No-Copy change’, ‘Gain’ or
‘Loss’ and estimates the modal parameters using an expectation – maximization algorithm. A CNV segment is then
defined to be a ‘Duplication’ if LRR . (mu + sigma) of
two-copy state and LRR ≥ 0.32 and as ‘Deletion’ if LRR ,
(mu 2 sigma) of two-copy state) and LRR ≤ 20.6. For each
segment of gain (or loss), both boundaries are further tested
for statistical significance using the KS null hypothesis test
and then an estimate of the likelihood that a segment of gain
(loss) deviates from a two-copy state is calculated.
and the Takara LA Taq kit (0.1 ml LA Taq, 2.5 ml LA PCR
buffer, 1.6 ml dNTPs, 5.9 ml PCR grade water) at 988C for
10 s, 668C for 15 min and 728C for 10 min for 30 cycles.
PCR products were run on a 1% gel at 100 V for 90 min.
Primers 500 bp outside the estimated location of the deletion
yielded a 6 kb fragment. Additional primers were designed
(Primer3) to move closer to the breakpoints (CACCAGTAA
CAAGTTTAAGCCTCTG, ATTATCTCTCGATACCACAG
ACACA, TTCTAACAATTCATCCCTTCTCTTAGT, GCAA
TTTACTCAAGGACACACAAC, TTAACTGCACAAACTG
TAGAGCAT, CATTTTTCTTAGCATCACATAGCACT, CT
CCCAGGCTTAGGAAAAGGA, CCAAACCAAGAAGAAG
TCAAATCC, AATATCTTCAAATCTCCCCTTAAAT, AGA
GAAATAAATAAAGCATGTTCAAA, AAACAGCCCGTA
TAGCCAAAACAG, ATCATGGGCAGATTTACTGCTTG
CT). A 10 ml PCR was performed using DNA from the 6 kb
PCR product and the Takara LA Taq kit. PCR products
were run on a 1% gel at 100 V for 90 min. Primers CACCAG
TAACAAGTTTAAGCCTCTG and AAACAGCCCGTATA
GCCAAAACAG yielded a 3 kb fragment. More primers
were designed (Primer 3) and a 10 ml PCR was performed
using DNA from the 3 kb PCR fragment and the Takara LA
Taq kit. PCR products were run on a 1% gel at 100 V for
75 min. Primers GAAAGGAGGGTAGGAGTAGGTCAG
and TTCAAGGACATTCAGGTAGATTTTATT yielded a
1 kb fragment. This fragment was purified using a PCR purification kit (Qiagen), and A tails were added with Taq DNA
polymerase (Roche). A TOPO TA cloning kit (Invitrogen)
was used to clone and transform the 1 kb DNA fragment
into competent E. coli cells. DNA from competent cells was
purified using a QIAprep Miniprep kit (Qiagen). DNA was
subjected to Sanger sequencing (CCG) using a primer
125 bp from the deletion on the left side (TATAAC
AAGGGCTATGGGTGTTAGG) and a primer 170 bp from
the deletion on the right side (GGCCTACACCTGGTCAGA
ATTATC). The leftmost breakpoint was determined to occur
just after chr13: 88 692 539 (build hg18) to the left of
GPC5, and the rightmost breakpoint was determined to
occur just before chr13: 93 166 512, removing exons 1 and 2
of GPC6. In between both breakpoints, 49 bp of a LINE
element of the L1 family was identified.
Sequencing of glypican deletion breakpoints
Expression and functional analysis of frog gpc5 and gpc6
orthologs
To sequence the breakpoints of the deletion, GFF segmentation files were generated for data from sample SB2223 using
the default CGH settings and then loaded into SignalMap
v1.9 (Roche NimbleGen). The breakpoints of the deletion
were then estimated based on the 5′ -most and 3′ -most positions of the array probes that generated a deletion shift
value. Primers (obtained from Integrated DNA Technologies)
were designed (using Primer3; http://frodo.wi.mit.edu/) 500,
1000, 1500 and 2000 bp outside the estimated breakpoints of
the deletion (CACCAGTAACAAGTTTAAGCCTCT, GTCA
AAAATTCCAAGACACTGAATAAT, CAAGAGCAGTAG
CAAGGATTTACC, TCTAAGGGCTAATACATACACTTC
GTT, ATCTCATGTGTCCTGTTTTTATACCA, TAGCAAT
ATCAGCTCTACCTACAACA, AAAAGACAGTAGCTTAG
AACAAGATTCC, ATTTACAATGGGTAGAGGTTGCAG).
A 10 ml PCR was performed using DNA from sample 22.23
Genomic sequences for X. tropicalis gpc5 (GenBank: XM
002933375) and gpc6 (XM 002939284) were identified, and
a gpc5 plasmid was obtained commercially (GenBank:
ES678878, Open Biosystems, Huntsville, AL). Morpholino
oligo 25 mers were designed against the start codons and
obtained from GeneTools (start codons are italics/underlined):
gpc5-MO: 5′ -AGCAAGAGAGAGCGGCTCATTTCAC-3′
(nt 176 – 200)
gpc6-MO: 5′ -TAACTGTGATCTCCCTTAAGCACAT-3′
(nt 1 – 25)
Morpholinos were dissolved in nuclease-free water to a stock
concentration of 1 mM and stored at 48C. Prior to injection,
MOs were diluted to 1 mg/ml and centrifuged. A fluoresceinlabeled control MO (GeneTools, LLC, Philomath, OR, USA)
1108
Human Molecular Genetics, 2013, Vol. 22, No. 6
was added to bring the total MO dose to 20 ng per embryo. Frog
husbandry was performed essentially as described (107). X. tropicalis eggs were obtained from females stimulated with human
chorionic gonadotropin (200 U per frog) and fertilized using a
testis homogenized in L15 medium. Embryos were rinsed in 1/
9× Marc’s modified Ringers (MMR) (1× MMR: 0.1 M NaCl,
1.8 mM KCl, 2.0 mM CaCl2, 1.0 mM MgCl2, 15.0 mM HEPES,
pH 7.6), dejellied in 3% cysteine in 1/9× MMR and rinsed extensively in 1/9× MMR. For injection, embryos at the one- to
two-cell stage were placed in 2% Ficoll in 0.3× MMR and
injected with oligo. After several hours, the embryos were transferred to 1/9× MMR and then to 1/20× MMR (with 1 mg/ml
gentamicin) for overnight culture. Vitelline membranes were
removed and the embryos fixed in MEMFA at the neurula stage
and processed for in situ hybridization as described (108).
Expression and functional analysis of zebrafish gpc5
and gpc6 orthologs
We searched EST databases for close homologs of human
GPC5 and GPC6. We detected what appeared to be two
halves of a gpc5 ortholog, one mapped to chromosome 1
(ENSDART00000129557, chr1: 2 809 161–2 821 811) and the
other to an unassembled contig (ENSDART00000125684,
NA503:37 227– 160 006). We isolated mRNAs from wild-type
zebrafish embryos at 24 hpf, synthesized first-strand cDNA as
described (109) and conducted PCR with primers in these two
pieces (f—CGATCCGTGGAATTTTGTTT, r—ACCCAGTT
GGCTGACGTTAC) and amplified a band of 1695 bases.
This confirms that the two pieces are indeed part of a single
transcript, presumably found on chromosome 1. We cloned
this PCR product, made a DIG-labeled antisense RNA probe
and conducted RNA in situ hybridization using standard
methods as described (110).
We detected two apparent orthologs of GPC6 (i.e. gpc6a
and gpc6b). Like gpc5, the two halves of gpc6a map to different genomic positions. Interestingly, the first half of gpc6a
(ENSDART00000126093) is located on chromosome 1
(chr1: 2641199 – 2673283), within 200 kb of gpc5. The
second half of gpc6a maps to chromosome 12
(ENSDART00000090338, chr12: 50004532 – 50075404). We
designed primers to these two regions (f—CAACTCGCA
GTTCACCTTCA, r—CAGTGCAGGGATGCTCAGTA) and
amplified from 24 hpf first-strand cDNA a band of 1131 bp,
confirming that the two regions contribute to a single transcript. The most likely interpretation of these findings is that
gpc6a lies within a region of chromosome 1 that is difficult
to assemble, leading to mis-assignment of half of it to chromosome 12. Of note, human GPC5 is also 200 kb from GPC6.
Thus, allowing for the errors in genome assembly, it appears
that gpc6a has shared synteny with human GPC6. The other
predicted ortholog of GPC6, gpc6b, maps to chromosome
9 (chr9: 55 348 132 –55 406 016), adjacent to dct. Thus,
gpc6b has shared synteny with the gpc6 ortholog we examined
in X. tropicalis. Similar to Xenopus gpc6, there are no EST
data to indicate that gpc6b is expressed. We tested several
primer pairs and were not able to amplify it from cDNA prepared from embryos at embryonic stages. This gene was not
pursued further.
To test the efficacy of the gpc5 MO (which targets the
intron 5/exon 5 boundary, sequence below), we injected
embryos at the one-cell stage with 10 ng of gpc5 MO.
When MO-injected embryos reached 24 hpf, we harvested
RNA, and conducted RT– PCR with primers in exons 4 and
7 of gpc5 (gpc5 RT – PCR primers: forward, gaggagcacagcgaggatac; reverse, attaaagcgcaggctgaaaa). RNA loading was
assessed comparably by RT – PCR to beta actin (beta actin
primer sequences: forward, GAGATGATGCCCCTCGTG;
reverse, GCTCAATGGGGTATTTGAGG). This analysis confirmed that in such embryos, the levels of correctly spliced
gpc5 mRNA were strongly reduced in comparison to uninjected embryos. The negative control MO, supplied by GeneTools (Philomath), has no known target in the zebrafish
genome.
To test the specificity of the gpc5 MO, we initially
attempted to reverse its effects by co-injecting gpc5 mRNA
but were not successful. However, we found that embryos
injected with gpc5 mRNA without a gpc5 MO developed
with abnormal morphogenesis of the trunk, similar to gpc5
MO-injected embryos. This result suggests that morphogenesis of the trunk is sensitive to overexpression of gpc5, as
well as deficiency of expression, although this issue merits
further investigation. As an alternate test of specificity, we
ordered a second gpc5 MO, gpc5 e1i1 MO (sequence
below), and found it to elicit the same phenotypes as gpc5 MO.
gpc5 MO: TGCACCTGCAACACACCAACACACA
gpc5 e1i1 MO: CCAGCACATCACATTCTTACCTGTT
negative control MO: CCTCTTACCTCAGTTACAATTTATA
p53 MO: GCGCCATTGCTTTGCAAGAATTG
SUPPLEMENTARY MATERIAL
Supplementary Material is available at HMG online.
ACKNOWLEDGEMENTS
We thank Jacek Topczewski for alerting us to the fact that the
apparent zebrafish gpc5 orthologs of chromosome 1 and an
unassembled contig were potentially part of the same gene.
We are grateful to Greg Bonde for excellent technical assistance in the fish experiments. We also thank Irina Kalatskaya
for helpful discussions on network analysis.
Conflict of Interest statement. None declared.
FUNDING
This work was supported by the National Institutes of Health
(1R01DE021071-01 to J.R.M., GM083999 to D.W.H.) and the
National Science Foundation (grant number IOS-1147221
to R.A.C.).
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