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Systems Analysis Implicates WAVE2 Complex in the Pathogenesis of Developmental Left-Sided Obstructive Heart Defects

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Genetic variants are the primary driver of congenital heart disease (CHD) pathogenesis. However, our ability to identify causative variants is limited. To identify causal CHD genes that are associated with specific molecular functions, the study used prior knowledge to filter de novo variants from 2,881 probands with sporadic severe CHD. This approach enabled the authors to identify an association between left ventricular outflow tract obstruction lesions and genes associated with the WAVE2 complex and regulation of small GTPase-mediated signal transduction. Using CRISPR zebrafish knockdowns, the study confirmed that WAVE2 complex proteins brk1, nckap1, and wasf2 and the regulators of small GTPase signaling cul3a and racgap1 are critical to cardiac development.
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PRECLINICAL RESEARCH
SystemsAnalysisImplicatesWAVE2
ComplexinthePathogenesisof
Developmental Left-Sided Obstructive
Heart Defects
Jonathan J. Edwards, MD,
a
Andrew D. Rouillard, PHD,
b
Nicolas F. Fernandez, PHD,
b
Zichen Wang, PHD,
b
Alexander Lachmann, PHD,
b
Sunita S. Shankaran, PHD,
c
Brent W. Bisgrove, PHD,
d
Bradley Demarest, MS,
d
Nahid Turan, PHD,
e
Deepak Srivastava, MD,
f
Daniel Bernstein, MD,
g
John Deaneld, MD,
h
Alessandro Giardini, MD, PHD,
h
George Porter, MD, PHD,
i
Richard Kim, MD,
j
Amy E. Roberts, MD,
k
Jane W. Newburger, MD, MPH,
k
Elizabeth Goldmuntz, MD,
l
Martina Brueckner, MD,
m
Richard P. Lifton, MD, PHD,
m,n
Christine E. Seidman, MD,
o,p,q
Wendy K. Chung, MD, PHD,
r,s
Martin Tristani-Firouzi, MD,
t
H. Joseph Yost, PHD,
d
Avi Maayan, PHD,
b
Bruce D. Gelb, MD
u,v
VISUAL ABSTRACT
Edwards, J.J. et al. J Am Coll Cardiol Basic Trans Science. 2020;-(-):--.
ISSN 2452-302X https://doi.org/10.1016/j.jacbts.2020.01.012
JACC: BASIC TO TRANSLATIONAL SCIENCE VOL. -,NO.-,2020
ª2020 THE AUTHORS. PUBLISHED BY ELSEVIER ON BEHALF OF THE AMERICAN
COLLEGE OF CARDIOLOGY FOUNDATION. THIS IS AN OPEN ACCESS ARTICLE UNDER
THE CC BY-NC-ND LICENSE (http://creativecommons.org/licenses/by-nc-nd/4.0/).
HIGHLIGHTS
Combining CHD phenotypedriven gene set enrichment and CRISPR knockdown screening in zebrash is an
effective approach to identifying novel CHD genes.
Mutations affecting genes coding for the WAVE2 protein complex and small GTPase-mediated signaling are
associated with LVOTO lesions.
WAVE2 complex genes brk1,nckap1,andwasf2 and regulators of small GTPase signaling cul3a and racgap1 are
critical to zebrash heart development.
SUMMARY
Genetic variants are the primary driver of congenital heart disease (CHD) pathogenesis. However, our ability to
identify causative variants is limited. To identify causal CHD genes that are associated with specic molecular
functions, the study used prior knowledge to lter de novo variants from 2,881 probands with sporadic severe
CHD. This approach enabled the authors to identify an association between left ventricular outow tract
obstruction lesions and genes associated with the WAVE2 complex and regulation of small GTPase-mediated
signal transduction. Using CRISPR zebrash knockdowns, the study conrmed that WAVE2 complex proteins
brk1,nckap1, and wasf2 and the regulators of small GTPase signaling cul3a and racgap1 are critical to cardiac
development. (J Am Coll Cardiol Basic Trans Science 2020;-:--) © 2020 The Authors. Published by Elsevier
on behalf of the American College of Cardiology Foundation. This is an open access article under the CC BY-NC-ND
license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
ABBREVIATIONS
AND ACRONYMS
CHD =congenital heart disease
CORUM =Comprehensive
Resource of Mammalian
Protein Complexes
CRISPR =clustered regularly
interspaced short palindromic
repeats
CTD =conotruncal defect
GOBP =Gene Ontology
biological processes
HHE =high heart expression
HLHS =hypoplastic left heart
syndrome
HTX =heterotaxy
LVOTO =left ventricular
outow tract obstruction
MGI =Mouse Genome
Informatics
PCGC =Pediatric Cardiac
Genomics Consortium
PPI =protein-protein
interaction
From the
a
Department of Pediatrics, Division of Pediatric Cardiology, Childrens Hospital of Philadelphia, Philadelphia, Penn-
sylvania;
b
Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, LINCS-BD2K DCIC, Icahn School of
Medicine at Mount Sinai, New York, New York;
c
Department of Molecular Physiology and Biophysics, Vanderbilt School of
Medicine, Nashville, Tennessee;
d
Molecular Medicine Program, University of Utah School of Medicine, Salt Lake City, Utah;
e
Coriell Institute, Camden, New Jersey;
f
Gladstone Institute of Cardiovascular Disease, San Francisco, California;
g
Division of
Pediatric Cardiology, Stanford University School of Medicine, Stanford University, Stanford, California;
h
Department of Cardiol-
ogy, Great Ormond Street Hospital, University College London, London, United Kingdom;
i
Department of Pediatrics, University of
Rochester Medical Center, University of Rochester School of Medicine and Dentistry, Rochester, New York;
j
Section of Cardio-
thoracic Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, California;
k
Department of
Cardiology, Childrens Hospital Boston, Boston, Massachusetts;
l
Department of Pediatrics, Perelman School of Medicine, Uni-
versity of Pennsylvania, Philadelphia, Pennsylvania;
m
Department of Genetics, Yale School of Medicine, New Haven, Connecticut;
n
Howard Hughes Medical Institute, Yale University, New Haven, Connecticut;
o
Department of Genetics, Harvard Medical School,
Boston, Massachusetts;
p
Howard Hughes Medical Institute, Harvard University, Boston, Massachusetts;
q
Cardiovascular Division,
Brigham and Womens Hospital, Harvard University, Boston, Massachusetts;
r
Department of Pediatrics, Columbia University
Medical Center, New York, New York;
s
Department of Medicine, Columbia University Medical Center, New York, New York;
t
Nora
Eccles Harrison Cardiovascular Research and Training Institute, University of Utah School of Medicine, Salt Lake City, Utah;
u
Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York; and the
v
Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, New York. This work was supported by a grant
from the National Center for Research Resources and the National Center for Advancing Translational Sciences (U01 HL098153),
National Institutes of Health grants to the Pediatric Cardiac Genomics Consortium (U01-HL098188, U01-HL098147, U01-HL098153,
U01-HL098163, U01-HL098123, U01-HL098162, and U01-HL098160), and the National Institutes of Health Centers for Mendelian
Genomics (5U54HG006504). Dr. Edwards was supported by National Institutes of Health Grant No. 5T32HL007915.Drs. Lifton and
Seidman were supported by the Howard Hughes Medical Institute. Dr. Chung was supported by the Simons Foundation. Dr.
Srivastava is co-founder and has served on the scientic advisory board for Tenaya Therapeutics. Dr. Lifton is director of Roche;
has served on the scientic advisory board for Regeneron; and has served as a consultant for Johnson and Johnson. All other
authors have reported that they have no relationships relevant to the contents of this paper to disclose.
The authors attest they are in compliance with human studies committees and animal welfare regulations of the authorsin-
stitutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit
the JACC: Basic to Translational Science author instructions page.
Manuscript received November 19, 2019; revised manuscript received January 23, 2020, accepted January 24, 2020.
Edwards et al.JACC: BASIC TO TRANSLATIONAL SCIENCE VOL. -,NO.-,2020
WAVE2 Complex in LVOTO -2020:--
2
Congenital heart disease (CHD) is the most
common clinically devastating birth defect
(1). Among the multiple factors that drive
CHD pathogenesis, genetic variants appear to be a
primary driver (2,3). Despite greater understanding
of the molecular mechanisms of heart development,
our ability to denitively identify specic genetic
causes for most patients has progressed more slowly.
A barrier to unraveling genotype-phenotype asso-
ciations is the high degree of genetic heterogeneity,
such that analysis of even a moderate-sized cohort
results in a relatively low number of genes observed
to be mutated recurrently (4,5). Hence, identifying
novel CHD genes is well suited for network analysis,
wherein discrete mutations and affected genes can be
connected based on prior knowledge of gene-gene
functional networks such as associations with devel-
opmental pathways and known protein-protein
interactions. Together, these functional data can
provide a platform to identify molecular pathways
that link variants to prioritize identication and lead
to the discovery of novel candidate causal CHD genes.
Validation of selected genes in model systems will
ultimately expand our ability to detect genetic
etiologies for patients.
Initial whole exome sequencing from the Pediatric
Cardiac Genomics Consortium (PCGC) identied a
burden of de novo exonic mutations in genes with
higher fetal heart expression (HHE) in sporadic,
severe CHD accounting for 10% of cases (4). Gene
Ontology enrichment analyses identied altered
epigenetic regulators, particularly histone modiers,
as important for CHD pathogenesis. Subsequent PCGC
whole exome sequencing studies have identied a
signicant overlap between HHE and high fetal brain
expression for mutated genes identied in CHD pro-
bandsthus providing a potential mechanism for the
frequent co-occurrence of extracardiac anomalies or
neurodevelopmental delays (6). More recently, whole
exome sequencing of this growing cohort of sporadic,
severe CHD characterized the contribution of reces-
sive variants in genes well established to cause
CHD in human and mouse studies (7). To expand on
these, we performed unbiased global analyses of
phenotype-specic CHD-associated variants to prior-
itize candidate causal genes and identify pathways
relevant for CHD pathogenesis.
METHODS
EXOME SEQUENCING AND VARIANT FILTERING.
Whole exome sequencing results from 2,881 sporadic,
severe CHD trios enrolled in the PCGC or Pediatric
Heart Network were compared with whole exome
sequencing from 900 control trios in SimonsFoun-
dation Autism Research Initiative Simplex Collection
(6). The research protocols were approved by the
Institutional Review Boards at each participating
centerBostonsChildrens Hospital, Brigham and
WomensHospital,GreatOrmondStreetHospital,
Childrens Hospital of Los Angeles, ChildrensHos-
pital of Philadelphia, Columbia University Irving
Medical Center, Icahn School of Medicine at Mount
Sinai, Rochester School of Medicine and Dentistry,
Steven and Alexandra Cohen ChildrensMedical
Center of New York, and Yale School of Medicine.
Briey, sequencing for case and control trios was
performed at Yale Center for Genome Analysis using
NimbleGen v2.0 exome capture reagent (Roche,
Basel, Switzerland) and Illumina HiSeq 2000, 75-bp
paired-end reads (Illumina, San Diego, California).
Three independent analysis pipelines were used to
process reads and were mapped to hg19 using
Novoalign (Novocraft Technologies, Selangor,
Malaysia) and Genome Analysis Toolkit 3.0 (Broad
Institute, Cambridge, Massachusetts) best practices at
HarvardMedicalSchoolandBWA-mematYaleSchool
of Medicine and Columbia University Medical Center
(8,9), Variant calls were made using GATK Hap-
lotypeCaller (8). De novo variants not meeting the
following criteria after pooling from the 3 pipelines
were ltered out: depth (minimum 10 reads total and
5 alternate allele reads), alternate allele balance
(minimum 20% if alternate read depth $10 or mini-
mum 28% if alternate read depth <10), and parental
read characteristics (minimum depth of 10 reference
reads and alternate allele balance <3.5%).
Variant pathogenicity was assessed using in silico
prediction from PredictSNP2 (Loschmidt Labora-
tories, Brno, Czech Republic), which employs an
ensemble approach by integrating data from multiple
in silico tools, for all variants other than frameshift
mutations (10). As PredictSNP2 does not score
frameshift mutations, we used Combined Annotation
Dependent Depletion v1.4 for these variants (11).
Combined Annotation Dependent Depletion, 1 of the
tools which contributes to PredictSNP2, yields
PHRED-scaled C scores, such that a score of $30
correlates to the top 0.1% of all possible variants and
in prior studies has been used to discriminate
pathogenic from tolerated frameshift variants (11).
Variants were also ltered for those affecting HHE
genes (4). The HHE gene set was previously identied
using RNA sequencing of isolated strain 129/SvEV
mouse hearts including atria, ventricles, and all 4
valves at embryonic day 14.5 to dichotomize 16,676
genes with identied human-mouse orthologues with
a minimum of 40 reads per million mapped reads into
JACC: BASIC TO TRANSLATIONAL SCIENCE VOL. -,NO.-,2020 Edwards et al.
-2020:--WAVE2 Complex in LVOTO
3
the top quartile of expression (4). The HHE gene list
consists of 4,169 genes, and the low heart expression
list consists of 12,507 genes.
We considered that the low heart expression genes
may contain some genes critical to cardiogenesis, so
in an orthogonal variant ltering, we excluded genes
unlikely to have a role in cardiovascular development
based on knockout mouse phenotypes using the
Mouse Genome Informatics (MGI) knockout pheno-
type gene library (12). Specically, a gene was
excluded if its knockout had been phenotyped, and
the knockout was not found to cause any cardiovas-
cular related phenotype, embryogenesis phenotype,
or embryonic or postnatal lethality.
Cardiac diagnoses were obtained from the PCGC
Data Hub (13). Left ventricular outow tract obstruc-
tion (LVOTO) (n ¼802) included hypoplastic left heart
syndrome, aortic coarctation, and aortic stenosis.
Conotruncal defects (CTDs) (n ¼1120) included
D-transposition of the great arteries, tetralogy of Fal-
lot, double outlet right ventricle, truncus arteriosus,
ventricular septal defects, and abnormalities of the
aortic arch patterning. Heterotaxy (HTX) (n ¼274)
included patients with left-right isomerism as the
primary defect. The remaining patients not included in
1 of the 3 phenotype categories consisted of a hetero-
geneous group of defects including atrial septal de-
fects and anomalous pulmonary venous connections,
pulmonary valve lesions, atrioventricular canal de-
fects, double inlet left ventricle, and tricuspid atresia.
GENE SET ENRICHMENT ANALYSIS. We performed
gene set enrichment analysis for Gene Ontology bio-
logical processes (GOBP) terms and Comprehensive
Resource of Mammalian Protein Complexes (CORUM)
using HHE in silicoand MGI library in silicoltered
variants and the hypergeometric test. Enrichment
analyses were performed with Enrichr (Icahn School
of Medicine at Mount Sinai, New York, New York),
which, in addition to implementing the hypergeo-
metric test, also employs a ranking method that
combines the adjusted p value with a deviation from
the expected rank based on enrichment analysis
applied to random gene sets (z-score) (14). In addi-
tion, we repeated the enrichment analysis with the
loading of 2 different background reference lists;
1 made of the 4,169 HHE genes and the other made of
the entire human genome excluding the MGI library
phenotype negative genes using WebGestalt
(Vanderbilt University Medical Center, Nashville,
Tennessee) with the default settings (15). The refer-
enceandbackgroundgenelistsareavailablein
supplemental information. A Benjamini-Hochberg
adjusted p <0.05 using both tools, Enrichr and
WebGestalt, was used for signicance with signicant
terms ranked by Enrichrscombinedscore.Gene
Ontology enrichment analysis was performed for
controls, all cases, and LVOTO, CTD, and HTX
gene lists.
Given that among the CHD phenotypespecic
groups, signicant enrichment was only observed
for the LVOTO group, we performed a protein-protein
interaction (PPI) network analysis only for this group
to prioritize candidate genes. We generated an
LVOTO-specic PPI network, using GeNets (Broad
Institute, Cambridge, Massachusetts), by inputting all
LVOTO genes associated with all GOBP and CORUM
terms identied as enriched including terms which
were observed as enriched when using only Enrichr
or WebGestalt enrichment analyses. Then we ranked
genes associated with the consistently enriched terms
bytheirnumberofconnectionsidentied in the
LVOTO-specicPPInetwork.
Aow diagram of the variant ltering and enrich-
ment analyses is provided in Supplemental Figure 1.
MODELING LOSS O F CANDIDATE GENES IN ZEB RAFISH
EMBRYOS. Clustered regularly interspaced short
palindromic repeats (CRISPR)mediated knockdown
experiments were performed for candidate genes in
zebrash F0 embryos to assess morphological
phenotypes, as described previously (16). Briey,
wild-type AB strain zebrash embryos were injected
at the 1- to 2-cell stage with zebrash-optimized Cas9
protein and CRISPR RNAs targeting abi1,brk1,cyp1
cul3a,nckap1,racgap1,orwasf2.CRISPRdesignand
construction were performed by the University of
Utah Mutation Generation and Detection Core using
standard best practice procedures. Single guide RNAs
were designed for high efciency and low off-target
effects, and concentrations for single guide RNA and
cas9 protein were also titrated for optimal impact.
The mutagenic efciency of each CRISPR and vali-
dation of double-stand breaks was assessed using
high-resolution melting analysis performed on
genomic DNA from individual injected embryos (17).
CRISPR target sequences and high-resolution melting
analysis primer sequences are listed in Supplemental
Table 1.Zebrash embryos were phenotyped at 2 days
past fertilization. To evaluate cardiac morphology
and function, wild-type and mutant lines of zebrash
were evaluated on a cmlc2-GFP background and
visualized with a uorescent microscope.
STATISTICS. The burden of de novo mutations in
controls was compared with that found in all CHD
cases and then separately for the LVOTO, CTD, and
HTX phenotype groups. A 2-tailed chi-square analysis
was performed to generate the odds ratio with 95%
Edwards et al.JACC: BASIC TO TRANSLATIONAL SCIENCE VOL. -,NO.-,2020
WAVE2 Complex in LVOTO -2020:--
4
condence interval comparing the number of lter-
selected variants (in silico, HHE in silico, or MGI
library in silico) to ltered-out variants for each group
comparedwithcontrols.Asdescribedpreviously,gene
set enrichment was assessed using a hypergeometric
test. All reported p values were adjusted using the
Benjamini-Hochberg method. A p value <0.05 was
considered statistically signicant and R software
version 3.5.2 (R Foundation for Statistical Computing,
Vienna, Austria) was used for all statistical analyses.
DATA AVAILABILITY. Whole exome sequencing data
have been previously deposited in the database of
Genotypes and Phenotypes (dbGaP) under accession
number phs000571.v1.p1, phs000571.v2.p1,
and phs000571.v3.p2.
RESULTS
EXOME SEQUENCING AND VARIANT FILTERING. Consistent
with the initial PCGC cohort and as published for this
expanded PCGC cohort, the rate for all de novo vari-
ants in patients with CHD was not signicantly
different from healthy controls (1.04 vs. 1.05 variants/
individual) (4,6,7).ThiswasalsotruefortheLVOTO
(n ¼802), CTD (n ¼1120), and HTX (n ¼274) groups
(1.08, 1.03, and 0.90 de novo variants per individual,
respectively). Variant pathogenicity was assessed us-
ing in silico prediction from PredictSNP2 and Com-
bined Annotation Dependent Depletion (10,11). With
the exception of HTX, which did not demonstrate
signicant burden with any combination of lters, all
cases, LVOTOs, and CTDs exhibited increasing burden
with each layer of ltering (Table 1). The HHE in silico
lter demonstrated the greatest burden, with odds
ratios of 1.7, 2.0, and 1.7 (p <0.001, for all) for all cases,
LVOTOs, and CTDs, respectively, with comparable
burden identied using the MGI library in silico.
GENE SET ENRICHMENT ANALYSES. We performed
GOBPandCORUMgenesetenrichmentanalyses
using the hypergeometric test with the MGI library in
silicoand HHE in silicoltered gene lists derived
from all cases, CHD phenotypes, and control groups.
Hypergeometric tests were performed using Enrichr
and WebGestalt as described in the Methods (14,15).
Using the MGI library in silicoltered gene set from
all cases, we identied 181 GOBP and 4 CORUM
enriched terms. Similarly, using WebGestalt, we
identied 140 GOBP and 3 CORUM enriched terms, of
which 17 common GOBP and 2 common CORUM terms
identied as signicant with both tools (Supplemental
Table 2). The relatively low overlap in enriched terms
between Enrichr and WebGestalt is likely due to
different methods to convert the Gene Ontology tree
into a gene set library and different versions of the
Gene Ontology tree. Notable enriched terms included
the following developmental pathways and processes:
heart morphogenesis, vasculogenesis, VEGF receptor
signaling, beta-catenin-TCF complex, and regulation
of actin lamentbased processes. Using the same
approach for the LVOTO phenotype genes, we identi-
ed enrichment for 23 GOBP and 3 CORUM enriched
terms using Enrichr and 39 GOBP and 2 CORUM
enriched terms using WebGestalt, with 2 from each li-
brary consistently enriched using both tools: regula-
tion of actin lament-based processes, VEGF receptor
signaling, WAVE2 complex, and ITGA6-ITGB4-
Laminin 10/12 complex (Table 2).
Similar themes emerged from enrichment results
using HHE in silicoltered gene sets for all cases and
LVOTO groups but with overall narrower overlapping
results. From all cases, 4 GOBP and 1 CORUM term
were consistently identied as enriched: heart
morphogenesis, ephrin receptor signaling, regulation
of small GTPase-mediated signal transduction, acto-
myosin structure organization, and BAF complex
(Supplemental Table 3). For LVOTO, the highest-
ranked CORUM protein complex identied by
Enrichr was WAVE2. One GOBP term was consistently
enriched using both tools: regulation of small
GTPase-mediated signal transduction (Table 2).
TABLE 1 Mutation Burden by Variant Filter and Phenotype
Mutation Type
Controls
(n ¼900) Cases (n ¼2,881) LVOTO (n ¼802) CTD (n ¼1,120) HTX (n ¼274)
Var Var
OR
(95% CI)
Adjusted
pValue Var
OR
(95% CI)
Adjusted
pValue Var OR(95%CI)
Adjusted
pValue Var OR(95% CI)
Adjusted
pValue
All 945 3010 863 1,150 247
In silico 362 1,237 1.12 (0.961.30) 0.145 375 1.24 (1.031.45) 0.051 473 1.13 (0.941.34) 0.273 89 0.91 (0.681.21) 0.560
HHE in silico 116 583 1.73 (1.392.13) <0.001 185 1.96 (1.512.51) <0.001 223 1.73 (1.352.19) <0.001 36 1.23 (0.81- 1.83) 0.469
MGI library
in silico
178 819 1.61 (1.341.93) <0.001 252 1.78 (1.432.21) <0.001 304 1.55 (1.261.91) <0.001 52 1.15 (0.811.63) 0.531
Odds ratios (ORs) calculated comparing lter-selected with ltered-out variants between controls and cases or phenotype groups. All p values adjusted using Benjamini-Hochberg p <0.05 for signicance.
CI ¼condence interval; CTD ¼conotruncal defect; HHE ¼high fetal heart expression; HTX ¼heterotaxy; MGI ¼Mouse Genome Informatics; Var ¼variants.
JACC: BASIC TO TRANSLATIONAL SCIENCE VOL. -,NO.-,2020 Edwards et al.
-2020:--WAVE2 Complex in LVOTO
5
Much less enrichment was observed for the CTD,
HTX, and control gene lists, with no terms reaching
statistical signicance for the control or the HTX MGI
library in silico or HHE in silico gene lists using either
tool. For CTDs, only 1 GOBP termpericardium
developmentwas consistently enriched using the
MGI library in silicoltered genes. No term
was consistently enriched using HHE in silico
ltered CTD genes. Complete results of patient phe-
notypes and variants and complete enrichment
analyses results are included in the supplemental
information.
Across all enrichment analyses, LVOTO-driven
WAVE2 complex enrichment demonstrated the high-
est Enrichr combined score and WebGestalt fold
enrichment. Variants affecting 3 of the 5 genes
encoding proteins within the WAVE2 complex and
the direct regulator of WAVE2 (RAC1)wereidentied
in LVOTO probands with none identied in other
phenotypes: nonsense variants in ABI1 (p. R106X) and
NCKAP1 (p. E1057X) and damaging missense variants
in CYFIP1 (p. S35L) and RAC1 (p.R68C).PredictSNP2
scores ranged from 0.69 to 1.0 (maximum) and C
scores were $32 (0.06% most damaging variants) for
these 4 variants. The WAVE2 complex functions
downstream of the small GTPase RAC1 to regulate
branched actin synthesis and inuence actin cyto-
skeleton organization in multiple cellular processes,
including cell migration through formation of lamel-
lipodia (18,19). In this context, it is notable that in
addition to consistent enrichment observed for actin
lamentbasedprocessesandregulationofsmall
GTPase signaling, terms related to lamellipodium and
actin cytoskeleton development were identied as
enriched in at least 1 context.
We considered that visualizing protein network
interactions between genes associated with the
LVOTO enriched terms would allow us to better pri-
oritize candidate genes for downstream validation. To
that end, we used Metanetwork v1.0 (Broad Institute,
Cambridge, Massachusetts) predicted protein-protein
interactions available from GeNets to interrogate for
interactions between the 35 genes associated with the
5 consistently enriched GOBP and CORUM terms and
all genes associated with all LVOTO enriched terms
(Figure 1)(20). These 35 genes had a median of 3 con-
nections in this LVOTO-specic protein network with
CUL3,CDC42,CYFIP1,NCKAP1,NF1,NOTCH1,RAC1,
RACGAP1,andRAF1 being in the top quartile with 7 to
14 connections each. Unsurprisingly, most of these
genes are already strongly implicated in cardiac
development and CHD (2125). Notably, both Cul3
/
and Racgap1
/
result in embryonic lethality, suggest-
ing a possible role in heart development, which is
further supported by a more recent cardiomyocyte-
specicCul3
/
demonstrating a developmental
cardiomyopathy and postnatal lethality (2628).
The role of the WAVE2 complex, which consists of
the 3 previously mentioned genes as well as BRICK1
and WASF2, in cardiogenesis is mostly unknown.
Mouse knockout studies of Abi1,Brick1,andCyp1
resulted in embryonic lethality, with the only
reported cardiac phenotype being hemorrhagic peri-
cardial edema or discontinuous cardiac tissue layers
from loss of Abi1 (2932). Additionally, loss of Wasf2
resulted in reversed cardiac looping in 1 of 2 mouse
models and loss of Nckap1 resulted in cardia bida in
mice (3335). Therefore, we selected the 5 WAVE2
complex genes, cul3a,andracgap1 for further
validation in zebrash embryos.
TABLE 2 LVOTO Gene Set Enrichment
Gene List Library Term Combined*Fold
Adjusted
pValueGenes
MGI library in silico CORUM Wave-2 complex 1709.0 32.6 0.011 ABI1;CYFIP1;NCKAP1
MGI library in silico CORUM ITGA6-ITGB4-Laminin10/12 complex 692.9 32.6 0.011 LAMA5;LAMB1;LAMC1
MGI library in silico GOBP Regulation of actin lamentbased process 77.1 3.5 0.003 ABL2;DLC1;TENM1;ASAP3;
SPTA1;SSH2;ANK2;TSC1;SMAD4;
CYFIP1;NCKAP1;LRP1;RAC1;
CDC42;RYR2;MTOR;ROCK1
HHE in silico GOBP Regulation of small GTPase-mediated
signal transduction
73.6 3.8 0.002 FOXM1;NF1;NOTCH2;NOTCH1;
ARAP3;DLC1;CUL3;SIPA1L1;
ITSN2;KALRN;TNFAIP1;RHOT2;
RACGAP1;RAF1;RAC1;CDC42
MGI library in silico GOBP Vascular endothelial growth factor
receptor signaling pathway
63.5 5.3 0.017 MYOF;ABI1;CYFIP1;NCKAP1;
RAC1;CDC42;ROCK1
Gene set enrichment was performed using HHE and MGI library in silicoltered genes with the hypergeometric overrepresentation test implemented using Enrichr and
WebGestalt. Terms were ltered for statistical signicance if Benjamini-Hochbergadjusted p <0.05 using both tools. *Combined score derived from Enrichr, which is a unique
ranking system that combines the adjusted p value with a deviation from expected ranking for each term based on inputting random gene sets. Fold enrichment and adjusted
p values presented from WebGestalt using background gene list correction.
CORUM ¼Comprehensive Resource of Mammalian Protein Complexes; GOBP ¼Gene Ontology biological processes; other abbreviations as in Table 1.
Edwards et al.JACC: BASIC TO TRANSLATIONAL SCIENCE VOL. -,NO.-,2020
WAVE2 Complex in LVOTO -2020:--
6
MODELING LOSS OF CANDIDATE GENES IN ZEBRAFISH
EMBRYOS. Zebrash was selected for gene knock-
down as its ability to survive via oxygen diffusion in
the absence of a functional cardiovascular system
permits the study of lethal cardiac defects later in
development (36). Using CRISPR-guided knockdown,
we observed cardiac phenotypes in F0 embryos with
mosaic loss of brk1,cul3a,nckap1,racgap1,andwasf2
(Table 3). Reversed cardiac looping was observed in
brk1,cul3a,nckap1,andwasf2 knockdown embryos,
while racgap1 knockdown resulted in zebrash em-
bryos with a small, poorly contractile ventricle often
FIGURE 1 LVOTO Disease Gene Network
Bipartite graphgenerated using GeNets Metanetwork v1.0 protein-protein interactionsconnecting left ventricular outow tract obstruction(LVOTO) genes associated with
enriched terms using either high fetal heart expression (HHE) in silico or Mouse Genome Informatics (MGI) library in silicoltered genes and either Enrichr or WebGestalt.
Of the genes associated with consistently enriched terms and not previously implicated in structural heart defects, CUL3 and RACGAP1 are the most strongly connected.
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7
with associated atrial dilation (Figure 2). Notably, all 7
of these genes are both highly expressed in the
developing heart and brain of the mouse, but a brain
phenotype was only observed in racgap1 knockdown
embryos (6).
DISCUSSION
HUMAN GENETICS. In this study, we used whole
exome sequencing of 2,881 well-phenotyped, spo-
radic CHD trios and compared these with 900 control
trios to identify de novo predicted damaging muta-
tions using in silico, developmental heart expression,
and previous implications in development or cardiac
disease in knockout mouse phenotypes. As gene set
enrichment analyses are sensitive to both the length
of the genes list associated with each term and the
background gene list, we performed enrichment
analysis with different methods and considered not
only statistical signicance, but also consistency
across tools and algorithms.
Through phenotype-driven elaborate gene set
enrichment analyses, we identied a novel associa-
tion between the LVOTO phenotype and genes asso-
ciated with the WAVE2 complex, actin-lament based
processes, and small GTPase signal transduction. The
WAVE2 complex comprises 5 proteins (gene symbols
in parentheses when different)WAVE2 (WASF2),
TABLE 3 Phenotypes of CRISPR Gene Knockdown F0 Zebrash
Target
Gene
Reversed Heart
Looping Atrial and Ventricular Size Circulation
Head/Brain/Eye
Structures
cul3a 8/64 (13) Normal Normal Normal
wasf2 19/102 (19) Normal Normal Normal
racgap1 6/105 (6) Dilated atria and small
ventricle 42/105 (42)
Normal Hypoplastic
99/105 (95)
brk1 23/122 (19) Normal Normal Normal
nckap1 16/83 (19) Normal Normal Normal
cyfpl1 1/75 (1.3) Normal Normal Normal
abi1 1/72 (1.4) Normal Normal Normal
Values are n/n (%). Most (5 of 7) candidate genes demonstrate abnormal cardiac development in
CRISPR-mediated knockdown, including reversed cardiac looping in 3 WAVE2 complex genes
(brk1,nckap1, and wasf2) and cul3a. Loss of racgap1 also demonstrated extracardiac anomalies in
addition to a small ventricle and atrial dilation.
CRISPR ¼clustered regularly interspaced short palindromic repeats.
FIGURE 2 Crispr-Mediated Candidate Gene Knockdown in Zebrash
(A, C) Wild-type (WT), (C) cul3a, and (D) racgap1 knockout (KO) zebrash at 2 days past fertilization. Reversed cardiac looping illustrated in
cul3a KO as compared with WT, both on a cmlc2-GFP background. The racgap1 KO zebrash demonstrate atrial dilation and pericardial
edema. At ¼atria; CRISPR ¼clustered regularly interspaced short palindromic repeats; Ve ¼ventricle.
Edwards et al.JACC: BASIC TO TRANSLATIONAL SCIENCE VOL. -,NO.-,2020
WAVE2 Complex in LVOTO -2020:--
8
HSPC300 (BRK1), CYFIP1, NCKAP1, and ABI1and is
regulated by the small GTPase RAC1 to mediate
branched actin synthesis, a key contributor to actin
cytoskeleton organization, via Arp2/3-mediated actin
polymerization (18). Enrichment analyses also iden-
tied CUL3 and RACGAP1 as mediators of small
GTPase signaling. Placing the protein products of
these genes within a PPI network we further highlight
their strong connections within an LVOTO-specic
network.
In contrast to LVOTO, the other phenotype groups
demonstrated signicantly less term enrichment.
Although CTDs had similar variant burden to LVOTO,
we hypothesize that genetic and phenotypic hetero-
geneity within this group may have limited our ability
to identify consistent term enrichment with our
approach. For HTX, we failed to identify a burden of
mutations or identify any signicant term enrichment
using any combination of enrichment tools or gene
lter. The smaller size of the HTX cohort compared
with the other phenotypes may have limited our
power for enrichment analysis, but limiting to de novo
variants may also have missed signicant genetic
contributors. Recent results from the PCGC highlight
that recessively inherited variants contribute
substantially to pathogenesis of patients with CHD and
laterality defects, suggesting that this model of in-
heritance needs to be incorporated into all future gene
pathway enrichment studies for patients with HTX (7).
CANDIDATE GENE VALIDATION IN ZEBRAFISH. Given
consistency of LVOTO gene set enrichment, we
selected candidate genes from this group for valida-
tion. We identied reversed cardiac looping with loss
of brk1,cul3a,nckap1,andwasf2 andasmallventricle
with atrial dilation and pericardial edema with loss of
racgap1 in F0 zebrash embryos. It is difcult to
directly compare reversed cardiac looping in zebra-
sh with LVOTO defects in humans. Being comprised
of only 2 chambers renders the developing zebrash
heart vulnerable to looping defects from mechanisms
other than perturbed sidedness including altered
myocardial cell polarity, cell number, or blood ow
(37). Thus, while these results in zebrash cannot
denitively implicate these genes in LVOTO, we can
conclude their critical nature to cardiac development
and establish an association with mutations in these
genes and LVOTO in humans.
PROPOSED MOLECULAR MECHANISMS. Recently,
the Lo lab has developed a mouse forward genetics
screen coupled with fetal imaging and whole exome
sequencing of founder mice exhibiting a cardiovas-
cular malformation to identify recessively inherited
variants in novel CHD genes (38). This model has
illustrated a role for complex genetic inheritance in
multiple CHD phenotypes including the severest form
of LVOTO, hypoplastic left heart syndrome, in the
Ohia mouse line (Sap130
m/m
/Pcdha9
m/m
)(39). These
genes were further validated in LVOTO pathogenesis
after identifying mutations affecting SAP130 and a
related gene, PCDHA13, in patients with hypoplastic
left heart syndrome. Kyoto Encyclopedia of Genes
and Genomes network analysis of differentially
expressed genes in the Ohia right and left ventricular
tissue by RNA sequencing and chromatin immuno-
precipitation sequencing implicated multiple devel-
opmental pathways including Notch,Wnt,Tgf
b
,and
hedgehog signaling, as well as biological processes
including extracellular matrix receptors, regulation of
actin cytoskeleton, axon guidance, and metabolism.
WAVE2 is a highly conserved regulator of actin cyto-
skeleton and cell morphology during development, a
process that is critical to regulating cell polarity, cell
migration, cytokinesis, and tissue architecture
(35,40,41). Interestingly, the noncanonical Wnt
planar cell polarity pathway, which regulates cell
polarity during development via small RhoGTPase
regulation including RAC1, was identied as enriched
using Enrichr with both MGI library in silicoand HHE
in silicoltered LVOTO gene lists and could provide a
mechanistic link between altered WAVE2 complex
activity and CHD (42).
Knockout studies in mouse and zebrash demon-
strate that planar cell polarity genes inuence heart
development by regulating directional migration of
progenitor cells, septation of the primitive heart
tube, and patterning of cardiac structures (43). In
loss of Wnt5a and mutants of Vangl2andDvl2 (which
connect planar cell polarity to RhoGTPase signaling),
abnormal outow tract development, reduced
cardiomyocyte polarity, and actin polymerization
defects in cardiac progenitor cells are observed (44).
The direct link between planar cell polarity and
WAVE2 complex signalingistheRhoGTPaseRAC1.
Early lethality has prohibited studying global loss of
Rac1, but second heart eld-specicknockdownof
Rac1 resulted in abnormal right ventricular
cardiomyocyte polarity with inhibited second heart
eld progenitor cell migration and concomitant
decreased expression of WAVE2 complex genes and
Arp2/3 in embryonic right ventricular tissue (22).
Taken together, these studies illustrate how
altered signaling via planar cell polarity/Rac1/
WAVE2 can disrupt normal mammalian heart
development.
In addition to contributing to small GTPase-
mediated signaling, loss of CUL3 may also
contribute to CHD through its role in ubiquitination
JACC: BASIC TO TRANSLATIONAL SCIENCE VOL. -,NO.-,2020 Edwards et al.
-2020:--WAVE2 Complex in LVOTO
9
(45). In HEK293 cells, SAP130, a regulator of ubiq-
uitination via cullin-RING ligases and 1 of 2 proteins
implicated in the mouse Ohia line, binds CUL3 with
higher afnity than other CUL proteins (46).
Additionally, Lztr1 knockout in the mouse and loss of
function LZTR1 mutations in humans have been
implicated in Noonan syndrome through decreased
CUL3-mediated RAS ubiquitination and ultimately
increased RAS/MAPK signaling (47,48). Further, in
the LVOTO-specic protein network generated in
this study, the canonical ubiquitination regulator
UBC demonstrated the highest number of
connections including with CUL3.Thus,themecha-
nism of CUL3 loss leading to developmental cardiac
defects might also be related to dysregulated
ubiquitination.
Finally, loss of cyp1 and abi1a, unlike the other
WAVE2 complex genes, was not found to impact
zebrash heart development. Zebrash, unlike mouse
or human, have 2 orthologs for ABI1 (abi1a and abi1b)
with abi1b likely compensating to maintain normal
cardiac development. Similarly, loss of cyp1 may be
compensated by irsp53, which in mice has been
shown to also facilitate binding of activated Rac1 to
WAVE2 (49).
CONCLUSIONS
Despite rigorous efforts to unravel the genetic
mechanisms for severe forms of LVOTO pathogenesis,
the etiology for most patients has largely remained
elusive with only recent evidence conrming a role
for SAP130 and PCDHA13 (39). Here, we exploited the
strength of gene pathway enrichment analyses from
whole exome sequencing results of sporadic, complex
CHD trios to identify an association with LVOTO in
humans and WAVE2 complex, actin-lament regula-
tion, and small GTPase signaling genes. Furthermore,
we conrmed a role for brk1,cul3a,nckap1,racgap1,
and wasf2 in cardiac development using CRISPR
mediated knockdown in zebrash. Ultimately, we
illustrate that combining phenotype-driven gene set
enrichment analyses with validation in zebrash is
as an effective approach for identifying novel CHD
genes. Given evidence linking planar cell polarity
pathway to WAVE2 complex activity via small GTPase
signaling, we propose this as a promising framework
for future mechanistic investigation into LVOTO.
ADDRESS FOR CORRESPONDENCE: Dr. Bruce D.
Gelb, Mindich Child Health and Development Insti-
tute, Icahn School of Medicine at Mount Sinai, 1
Gustave L. Levy Place, Box 1040, New York, New
York 10029. E-mail: bruce.gelb@mssm.edu.
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APPENDIX For supplemental databases,
tables, and Figure, please see the online version
of this paper.
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... The human gene mutations database has enlisted a total of 37 variations. The missense variations develop diverse phenotypes including premature ovarian insufficiency (25), tetralogy of Fallot (26), mitochondrial respiratory chain complex IV deficiency (27), Leigh syndrome, French-Canadian type (28), cytochrome c oxidase deficiency (9), infantile mitochondrial disease, lethal type (16), congenital heart disease (29), autism (30), inborn errors of metabolism (31), failure to thrive, microcephaly, global developmental delay, intellectual disability, hypotonia, and seizures (25). There are only two nonsense variations that result in developing Leigh syndrome French-Canadian type and mitochondrial disorder with intellectual disability (17,28). ...
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Background The mitochondria are a cellular power house. Tissues are involved in frequent energy consumption, and any failure or irregularity in the continuous energy production could lead to abnormalities. The leucine-rich pentatricopeptide repeat ( LRPPRC ) gene is one of the mitochondrial-related functions genes; variations in these genes are responsible for complex phenotypes that affect many organs such as the brain, liver, and muscles. Materials and methods This study enrolled a family with Leigh syndrome-like phenotype. The molecular diagnosis was conducted by first performing whole exome sequencing (WES), followed by Sanger sequencing. Results A novel splice-site variant (c.469 + 2T > A) at the exon–intron boundary in the LRPPRC gene was identified using the WES data analysis. Sanger validation confirmed the autosomal recessive inheritance of the identified variant. Based on the ACMG criteria for variant classification, PVS1 and PM2 suggest that the identified variant in the LRPPRC gene is likely to be pathogenic. Conclusion To the best of our knowledge, there have been no previous reports of this variant in the LRPPRC gene. Our research not only identifies a novel variant in the LRPPRC gene, but also confirms the unresolved molecular diagnosis of the family. WES can be used as a first-line diagnostic tool in familial cases, particularly in those cases when detailed clinical phenotyping is not possible. Once the molecular diagnosis is confirmed in a family, it is necessary to conduct a thorough re-evaluation of the patients’ specific clinical phenotypes in order to establish a clear genotype–phenotype correlation.
... 8 Studies using cellular and animal models suggest that LYST plays a role in the biogenesis and maturation of lysosomes and LROs, as well as in the vesicular transport of proteins in the endo-lysosomal system. [9][10][11][12][13][14][15][16][17][18][19][20] The advent of next-generation sequencing has revolutionised the analysis of genetic data, enabling rapid identification of pathogenic variants for rare disorders like CHS. Although variant interpretation remains a challenge, it serves as a powerful tool for molecular diagnosis when paired with a comprehensive clinical evaluation and clinical acumen. ...
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Introduction Chediak-Higashi syndrome (CHS) is a rare autosomal recessive disorder characterised by partial oculocutaneous albinism, a bleeding diathesis, immunological dysfunction and neurological impairment. Bi-allelic loss-of-function variants in LYST cause CHS. LYST encodes the lysosomal trafficking regulator, a highly conserved 429 kDa cytoplasmic protein with an unknown function. Methods To further our understanding of the pathogenesis of CHS, we conducted clinical evaluations on individuals with CHS enrolled in our natural history study. Using genomic DNA Sanger sequencing, we identified novel pathogenic LYST variants. Additionally, we performed an extensive literature review to curate reported LYST variants and classified these novel and reported variants according to the American College of Medical Genetics/Association for Molecular Pathology variant interpretation guidelines. Results Our investigation unveiled 11 novel pathogenic LYST variants in eight patients with a clinical diagnosis of CHS, substantiated by the presence of pathognomonic giant intracellular granules. From these novel variants, together with a comprehensive review of the literature, we compiled a total of 147 variants in LYST , including 61 frameshift variants (41%), 44 nonsense variants (30%), 23 missense variants (16%), 13 splice site variants or small genomic deletions for which the coding effect is unknown (9%), 5 in-frame variants (3%) and 1 start-loss variant (1%). Notably, a genotype–phenotype correlation emerged, whereby individuals harbouring at least one missense or in-frame variant generally resulted in milder disease, while those with two nonsense or frameshift variants generally had more severe disease. Conclusion The identification of novel pathogenic LYST variants and improvements in variant classification will provide earlier diagnoses and improved care to individuals with CHS.
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Congenital heart disease (CHD) is the most prevalent hereditary disorder, affecting approximately 1% of all live births. A reduction in morbidity and mortality has been achieved with advancements in surgical intervention, yet challenges in managing complications, extracardiac abnormalities, and comorbidities still exist. To address these, a more comprehensive understanding of the genetic basis underlying CHD is required to establish how certain variants are associated with the clinical outcomes. This will enable clinicians to provide personalized treatments by predicting the risk and prognosis, which might improve the therapeutic results and the patient’s quality of life. We review how advancements in genome sequencing are changing our understanding of the genetic basis of CHD, discuss experimental approaches to determine the significance of novel variants, and identify barriers to use this knowledge in the clinics. Next-generation sequencing technologies are unravelling the role of oligogenic inheritance, epigenetic modification, genetic mosaicism, and noncoding variants in controlling the expression of candidate CHD-associated genes. However, clinical risk prediction based on these factors remains challenging. Therefore, studies involving human-induced pluripotent stem cells and single-cell sequencing help create preclinical frameworks for determining the significance of novel genetic variants. Clinicians should be aware of the benefits and implications of the responsible use of genomics. To facilitate and accelerate the clinical integration of these novel technologies, clinicians should actively engage in the latest scientific and technical developments to provide better, more personalized management plans for patients.
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Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to compare the signal-to-noise ratios of different networks and to identify the optimal network with which to interpret a particular genetic dataset. We present GeNets, a platform in which users can train a machine-learning model (Quack) to carry out these comparisons and execute, store, and share analyses of genetic and RNA-sequencing datasets. The GeNets web platform can identify the most informative network, as well as execute, store and share network-based analyses of RNA-seq or genomic datasets.
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Exome sequencing has markedly enhanced the discovery of genes implicated in Mendelian disorders, particularly for individuals in whom a known clinical entity could not be assigned. This has led to the recognition that phenotypic heterogeneity resulting from allelic mutations occurs more commonly than previously appreciated. Here, we report that missense variants in CDC42, a gene encoding a small GTPase functioning as an intracellular signaling node, underlie a clinically heterogeneous group of phenotypes characterized by variable growth dysregulation, facial dysmorphism, and neurodevelopmental, immunological, and hematological anomalies, including a phenotype resembling Noonan syndrome, a developmental disorder caused by dysregulated RAS signaling. In silico, in vitro, and in vivo analyses demonstrate that mutations variably perturb CDC42 function by altering the switch between the active and inactive states of the GTPase and/or affecting CDC42 interaction with effectors, and differentially disturb cellular and developmental processes. These findings reveal the remarkably variable impact that dominantly acting CDC42 mutations have on cell function and development, creating challenges in syndrome definition, and exemplify the importance of functional profiling for syndrome recognition and delineation.
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Background: Cdc42 is a member of the Rho GTPase family and functions as a molecular switch in regulating cytoskeleton remodeling and cell polarity establishment. Inactivating Cdc42 in cardiomyocytes resulted in embryonic lethality with heart developmental defects, including ventricular septum defects and thin ventricle wall syndrome. Findings: In this study, we have generated a Cdc42 cardiomyocyte knockout mouse line by crossing Cdc42/flox mice with myosin light chain 2a (MLC2a)-Cre mice. We found that the deletion of Cdc42 in embryonic cardiomyocytes resulted in an underdeveloped right ventricle. Microarray analysis and real-time PCR data analysis displayed that the deletion of Cdc42 decreased dHand expression level. In addition, we found evaginations in the ventricle walls of Cdc42 knockout hearts. Conclusion: We concluded that Cdc42 plays an essential role in right ventricle growth.
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Congenital heart disease (CHD) is the leading cause of mortality from birth defects. Here, exome sequencing of a single cohort of 2,871 CHD probands, including 2,645 parent–offspring trios, implicated rare inherited mutations in 1.8%, including a recessive founder mutation in GDF1 accounting for ~5% of severe CHD in Ashkenazim, recessive genotypes in MYH6 accounting for ~11% of Shone complex, and dominant FLT4 mutations accounting for 2.3% of Tetralogy of Fallot. De novo mutations (DNMs) accounted for 8% of cases, including ~3% of isolated CHD patients and ~28% with both neurodevelopmental and extra-cardiac congenital anomalies. Seven genes surpassed thresholds for genome-wide significance, and 12 genes not previously implicated in CHD had >70% probability of being disease related. DNMs in ~440 genes were inferred to contribute to CHD. Striking overlap between genes with damaging DNMs in probands with CHD and autism was also found.
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Congenital heart disease (CHD) affects up to 1% of live births. Although a genetic etiology is indicated by an increased recurrence risk, sporadic occurrence suggests that CHD genetics is complex. Here, we show that hypoplastic left heart syndrome (HLHS), a severe CHD, is multigenic and genetically heterogeneous. Using mouse forward genetics, we report what is, to our knowledge, the first isolation of HLHS mutant mice and identification of genes causing HLHS. Mutations from seven HLHS mouse lines showed multigenic enrichment in ten human chromosome regions linked to HLHS. Mutations in Sap130 and Pcdha9, genes not previously associated with CHD, were validated by CRISPR-Cas9 genome editing in mice as being digenic causes of HLHS. We also identified one subject with HLHS with SAP130 and PCDHA13 mutations. Mouse and zebrafish modeling showed that Sap130 mediates left ventricular hypoplasia, whereas Pcdha9 increases penetrance of aortic valve abnormalities, both signature HLHS defects. These findings show that HLHS can arise genetically in a combinatorial fashion, thus providing a new paradigm for the complex genetics of CHD.
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Regulation of RAS by ubiquitination The protein LZTR1 is mutated in human cancers and developmental diseases. Work from two groups now converges to implicate the protein in regulating signaling by the small guanosine triphosphatase RAS. Steklov et al. showed that mice haploinsufficient for LZTR1 recapitulated aspects of the human disease Noonan syndrome. Their biochemical studies showed that LZTR1 associated with RAS. LZTR1 appears to function as an adaptor that promotes ubiquitination of RAS, thus inhibiting its signaling functions. Bigenzahn et al. found LZTR1 in a screen for proteins whose absence led to resistance to the tyrosine kinase inhibitors used to treat cancers caused by the BCR-ABL oncogene product. Their biochemical studies and genetic studies in fruitflies also showed that loss of LZTR1 led to increased activity of RAS and signaling through the mitogen-activated protein kinase pathway. Science , this issue p. 1177 , p. 1171
Chapter
The ability to perform reverse genetics in the zebrafish model organism has been greatly advanced with the advent of the CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 (CRISPR-associated) system. The high level of efficiency in generating mutations when using the CRISPR/Cas9 system combined with the rapid generation time of the zebrafish model organism has made the possibility of performing F0 screens in this organism a reality. This unit describes a detailed protocol for performing an F0 screen using the CRISPR/Cas9 system in zebrafish starting with the design and production of custom CRISPR/Cas9 reagents for injection. Next, two approaches for determining the efficiency of mutation induction by the custom CRISPR/Cas9 reagents that are easily performed using standard molecular biology protocols are detailed. Finally, screening for F0 induced phenotypes using the zebrafish flh gene as an example is discussed.