The gene regulatory basis of genetic compensation during neural crest induction

Christopher M Dooley; Neha Wali; Ian M Sealy; Richard J White; Derek L Stemple; John E Collins; Elisabeth M Busch-Nentwich

doi:10.1371/journal.pgen.1008213

. 2019 Jun 14;15(6):e1008213. doi: 10.1371/journal.pgen.1008213

The gene regulatory basis of genetic compensation during neural crest induction

Christopher M Dooley ¹, Neha Wali ¹, Ian M Sealy ^1,², Richard J White ^1,², Derek L Stemple ¹, John E Collins ¹, Elisabeth M Busch-Nentwich ^1,^2,^*

Editor: Mary C Mullins³

PMCID: PMC6594659 PMID: 31199790

Abstract

The neural crest (NC) is a vertebrate-specific cell type that contributes to a wide range of different tissues across all three germ layers. The gene regulatory network (GRN) responsible for the formation of neural crest is conserved across vertebrates. Central to the induction of the NC GRN are AP-2 and SoxE transcription factors. NC induction robustness is ensured through the ability of some of these transcription factors to compensate loss of function of gene family members. However the gene regulatory events underlying compensation are poorly understood. We have used gene knockout and RNA sequencing strategies to dissect NC induction and compensation in zebrafish. We genetically ablate the NC using double mutants of tfap2a;tfap2c or remove specific subsets of the NC with sox10 and mitfa knockouts and characterise genome-wide gene expression levels across multiple time points. We find that compensation through a single wild-type allele of tfap2c is capable of maintaining early NC induction and differentiation in the absence of tfap2a function, but many target genes have abnormal expression levels and therefore show sensitivity to the reduced tfap2 dosage. This separation of morphological and molecular phenotypes identifies a core set of genes required for early NC development. We also identify the 15 somites stage as the peak of the molecular phenotype which strongly diminishes at 24 hpf even as the morphological phenotype becomes more apparent. Using gene knockouts, we associate previously uncharacterised genes with pigment cell development and establish a role for maternal Hippo signalling in melanocyte differentiation. This work extends and refines the NC GRN while also uncovering the transcriptional basis of genetic compensation via paralogues.

Author summary

Embryonic development is an intricate process that requires genes to be active at the right time and place. Organisms have evolved mechanisms that ensure faithful execution of developmental programmes even if genes fail to function. For example, in a process called genetic compensation, one or more genes become activated in response to loss of function of another. In this work we use the zebrafish model to investigate how two related genes, tfap2a and tfap2c, interact to ensure establishment of the neural crest, a vertebrate-specific cell type that contributes to many different tissues. Losing tfap2a activity causes mild morphological defects and losing tfap2c has no visible effect. Yet when both are inactive, embryos are severely abnormal due to lack of neural crest-derived tissues. Here we show that loss of tfap2a triggers upregulation of tfap2c which prevents the loss of neural crest tissue. However, the genes normally regulated by tfap2a respond differently to tfap2c allowing us to identify the first tier of the Ap2 network and new players in neural crest biology. Our work demonstrates that the expression signature of partial, but morphologically sufficient, genetic compensation provides an opportunity to dissect gene regulatory networks.

Introduction

Development from a single fertilised cell to the complex adult form requires a simultaneously robust and plastic gene regulatory program. The neural crest is a transient pluripotent stem cell population capable of crossing germ layer boundaries and differentiating into highly diverse tissue types while migrating long distances in the developing embryo. The establishment of the neural crest and its subsequent tissue derivatives is specific to vertebrates and has played a fundamental role in their variation and evolutionary success [1–4]. Neural crest cells require a complex combination of external inductive signals such as Wnts, Fgfs, Notch/delta and Bmps (Fig 1A). These extrinsic signals can be considered the first phase of the neural crest gene regulatory network (GRN) followed by a second phase of tightly controlled intrinsic gene expression. In this context foxd3 initially promotes neural crest fates by acting as a transcriptional repressor whereas later in development foxd3 promotes neural crest fates as a transcriptional activator [5]. Two other intrinsic signals of fundamental importance for evolution and development of the neural crest that set vertebrates apart from other chordates such as amphioxus and tunicates are the AP-2 and SoxE genes families [6–10].

Fig 1 — (A) The NC is induced by different morphogens, for example Wnt, BMP and FGF acting on ectoderm. Non-vertebrate chordates lack NC cells but are capable of producing pigmented cells and otoliths via *mitf*. AP-2 and SoxE family genes are required in vertebrates to form the NC and these also contribute to the differentiation of specific NC tissues types. (B-G) 3’ end transcriptome sequencing (DeTCT) of six key neural crest transcription factors (*tfap2a*, *tfap2c*, *foxd3*, *sox9b*, *sox10*, *mitfa*) across 18 developmental time points covering zygote to 5 dpf. Normalised counts of individual embryos (dots) are plotted for each stage. The mapped GRCz10 genomic positions of each 3’ end are at the top of the plots next to the gene names. ZFS numbers are labelled with their corresponding stage names and representative colouring. (H) FACS of dissociated *sox10*:mg was sorted based on mCherry and GFP signals at 22–23 hpf and were either sorted as whole embryos or separated heads and tails. Multiple replicates of each cell population were harvested and sequenced via RNA-seq. (I) FACS transgenic populations were compared to non-transgenic populations using DESeq2 to produce gene enrichment lists for each population. The enriched gene lists for the mCherry and mCherry/GFP population from whole embryos and mCherry and/or GFP positive populations from the head or trunk were then compared to each other as a Venn diagram. (J) An overview of the transcriptomics loss of function analysis comparing mutants to WT siblings, using 3’ tag sequencing, carried out at stages of premigratory, migratory and differentiating neural crest cells. The phases of NC differentiation are noted at the bottom. Differentially expressed genes at adj. p-value <0.05 when compared to wild-type siblings are represented with up and down arrows for increased and decreased abundance, respectively. The *sox10* downstream target *mitfa* (*) is first detected as reduced (adj. p-value 0.019, log₂ FC -1.775) at 19 hpf.

Mutations in neural crest genes lead to disease in humans, highlighting the importance of this cell population for human health. Animal models faithfully recapitulate these defects demonstrating functional conservation. In humans and mice, mutations in TFAP2A lead to branchio-oculo-facial syndrome presenting as defects in cranial development and cranial closure [11,12]. Similarly, mutations in zebrafish tfap2a lead to craniofacial defects in addition to a reduction in melanocytes [13,14]. The Tfap2 family arose from a single gene in a chordate ancestor that underwent gene duplication resulting in five family members (tfap2a, tfap2b, tfap2c, tfap2d and tfap2e) in zebrafish. Removing combinations of tfap2 family members results in a wide array of phenotypes. For example, the neural crest is completely ablated in tfap2a;tfap2c double homozygous zebrafish whereas there is a dramatic and specific reduction of melanocytes in tfap2a;tfap2e double homozygous zebrafish embryos [15–20]. Furthermore, melanomas, squamous cell carcinomas, most skin and breast cancers and a few cervical and urothelial cancers have strong nuclear immunoreactivity for TFAP2A. [21,22].

Haploinsufficiency in one of the AP-2 targets, the SoxE family member SOX10, results in Waardenburg syndrome; patients exhibit defects in the peripheral and enteric nervous systems and also pigmentation defects [23,24]. In zebrafish the known SoxE family members consist of sox8a/b sox9a/b and sox10. The expression of sox10 is first detectable in premigratory neural crest cells and expression is maintained in certain neural crest linages, for example, glia, but reduced in many other neural crest-derived tissues in zebrafish [25–27] and mouse [28–30]. Following neural crest induction, sox10 plays a vital role in the establishment of non-ectomesenchymal neural crest cells in zebrafish and driving mitfa expression. Knockouts in zebrafish sox10 behave in a recessive manner and lead to the absence of enteric neurons, chromatophores, Schwann cells, sensory neurons and other trunk crest cell types [31,25,27]. Craniofacial features appear to be largely unaffected in zebrafish sox10 mutants, which is thought to be due to compensation by sox9b in ectomesenchymal neural crest [32,33]. Mutations in mitfa lead to the total lack of body melanocytes in zebrafish due to a failure in melanocyte differentiation and as such mitfa is considered to be the melanocyte master regulator transcription factor [34].

Many crucial transcription factors involved in the neural crest GRN have been identified and studied in depth across a number of different species [10,35,36] and are largely conserved across vertebrates [37], but many of their downstream targets and interaction partners still remain to be elucidated. For example, AP-2A ChIP-seq analysis using human neural crest cells has identified over 4,000 potential AP-2A binding sites and established AP-2A as a chromatin initiating factor [38]. This large number of putative AP-2A downstream targets now requires functional validation.

In this work we use transcriptional profiling of zebrafish mutants in genes required at different levels of neural crest induction and differentiation to dissect the GRN downstream of tfap2. Specifically, by using individual genotyped embryos and many biological replicates, we can identify molecular neural crest signatures before a morphological phenotype arises. Stepwise genetic ablation of tfap2 levels reveals in detail the gene regulatory basis of dose-dependent genetic compensation between two AP-2 paralogues. By analysing the dosage compensation we have identified a subset of genes required to rescue the neural crest. To validate a small subset of novel candidates emerging from this analysis we applied a reverse genetics approach to knock out genes of interest using both ENU and CRISPR/Cas9 mutagenesis [39–41]. Taken together, this work has identified early activation of members of the neural crest GRN and the core gene set underlying genetic compensation of tfap2a or tfap2c perturbations. Our screen has also identified novel downstream neural crest genes and a role for maternal expression of the Hippo signalling member yap1 in the differentiation of melanocytes. All resources are publicly available and we envisage that this will lead to a deeper understanding of neural crest biology.

Results

Our collection of mutations in previously well studied zebrafish mutants (tfap2a, tfap2c, sox10 and mitfa) as well as a newly associated neural crest mutant (yap1–this study) encompasses an early undifferentiated, premigratory neural crest state through to terminal differentiation of different crest cell types, in particular the melanocytes.

Neural crest GRN members are expressed at genome activation

Neural crest cells can be readily identified as the first somites begin to form, however it is not clear when the neural crest GRN becomes active in the zebrafish embryo. We used a wild-type developmental time course we had published previously [42] encompassing 18 stages from zygote to 5 dpf to identify the specific time points at which relevant transcripts are activated and their expression over time. In addition, the use of single embryos reveals the natural variation across individuals (Fig 1B–1G). In zebrafish, the genome first becomes transcriptionally active between the 1K-Cell and Dome stage [43–45]. A number of early neural crest transcription factors—foxd3, tfap2a, tfap2c - can be detected at the Dome stage. This is much earlier than neural crest cells are formed, but our data suggest that the top tier of the neural crest GRN has already commenced at these early developmental time points and is expressed in relevant ectoderm-forming regions (Fig 1B–1D) [2,46]. Their downstream targets sox9b and sox10 begin to be expressed between 75% epiboly and when the first somites appear (Fig 1E and 1F). Both sox9b and sox10 have been shown to be robust markers for premigratory neural crest cells in zebrafish [47].

Identification of a neural crest–enriched gene set

We first created a catalogue of genes enriched in premigratory and differentiating neural crest cells as a reference set for the subsequent transcriptional analysis of the neural crest mutants. We used Fluorescence-Activated Cell Sorting (FACS) on dissociated cells from whole embryos of the sox10:mg line [48] at 22–23 hours post fertilisation (hpf). The transgenic reporter labels neural crest nuclei (mCherry) and crest cell membranes (GFP). At 22–23 hpf neural crest cells are migrating in a dorsal to ventral direction and their differentiation is more advanced at the rostral than caudal part of the embryo. We therefore reasoned that this stage would provide us with a comprehensive mixture of neural crest differentiation states. We compared transcripts detected in the transgenic neural crest cell populations to the non-crest cells using DESeq2 to produce neural crest-enriched gene sets (Fig 1I). For comparison to our whole embryo data we aggregated the resulting gene lists from the individual FACS experiments to produce a set of 4995 genes enriched in any FACS neural crest cell population (Table 1).

Table 1. Sequencing data and pairwise comparison gene lists.

Figure Location	Data Source	FigShare DOI
Fig 1I	FACS RNA-Seq gene lists	https://doi.org/10.6084/m9.figshare.6106082
Fig 1J	DeTCT gene lists (sox10, mitfa, yap1)	https://doi.org/10.6084/m9.figshare.6106091
Fig 2F	DeTCT tfap2a;tfap2c gene lists	https://doi.org/10.6084/m9.figshare.6106091
Fig 2F	UpSet gene subsets & ZFA Enrichment	https://doi.org/10.6084/m9.figshare.6170417
S2B Fig	RNA-Seq tfap2a;tfap2c gene lists	https://doi.org/10.6084/m9.figshare.6106079
Fig 4D	UpSet gene subset lists	https://doi.org/10.6084/m9.figshare.6170474
Fig 4I	Homer Results	https://doi.org/10.6084/m9.figshare.8131664
Fig 5B–5G	MCL cluster gene lists	https://doi.org/10.6084/m9.figshare.6170651
Fig 5B–5G	MCL cluster gene lists w/ genotype as sample name	https://doi.org/10.6084/m9.figshare.8131220

Open in a new tab

sox10 knockout mutants diverge from siblings transcriptionally at 19 hpf

In order to establish the initiation of the sox10 GRN, a direct transcriptional target of tfap2a;tfap2c[49], we first created a transcriptional loss of function time course of sox10 and its target, mitfa, by comparing gene expression of homozygous mutants and siblings. Zebrafish sox10^t3/baz1 mutant embryos form premigratory neural crest cells in the trunk but these cells fail to migrate and properly differentiate while cranial crest remains largely unaffected [25]. Mutants of the sox10^t3/baz1 downstream target mitfa have mostly correctly differentiated neural crest but specifically lack melanocytes of the body while showing mild differences in the numbers of the other two pigment cell types, xanthophores and iridophores [34].

Fig 1J is an overview of all experiments carried out using DeTCT (differential expression transcript counting technique) 3’ tag sequencing [50]. Although sox10 is appreciably expressed at the 1–4 somites stage (~10 hpf) (Fig 1F) it is only at the 19 somite stage (19 hpf) where we detected a reduction in the abundance of one of its downstream targets, mitfa, in sox10^t3/baz1 embryos (Fig 1J). The majority of genes appearing differentially expressed in the sox10 4 somite, 15 somite and 19 somite stages are localised on chromosome 3, the same chromosome as sox10 (Fig 1J, Table 1). We also found similar signals for the mitfa^w2/w2 mutants at 4 somites, with a very strong enrichment for chromosome 6 at 24 hpf (Table 1). This enrichment is either due to differential read mapping between the haplotypes owing to the high genetic variation in zebrafish [51] or reflects true expression differences between the two haplotypes, i.e. allele-specific expression [52]. When embryos homozygous for a specific genomic locus, in these cases the areas around the sox10 or the mitfa mutation, are compared to embryos heterozygous and homozygous for the other haplotype, either possibility will cause an enrichment of DE genes on the chromosome carrying the mutation.

We next analysed enrichments of terms from the Zebrafish Anatomy Ontology (ZFA) associated with differentially expressed genes and plotted all time points with significant enrichments (S1 Fig). As expected, we found a strong and specific melanocyte signal in both mutants across all time points, with sox10 mutants also showing a strong enrichment at 24 hpf for xanthophores and iridophores. By 36 hpf we also found an enrichment for the terms peripheral nervous system and nervous system which is consistent with an established role for sox10 in peripheral nervous system development [25]. Previous data [25] and our developmental time course show that the expression of sox10 begins early, following the establishment of the first neural crest cells at about 4 somites. It is only at the 19 somite stage, however, in which we detect the first molecular signal via the reduction of mitfa transcript, and only at 24 hpf do we see the first ZFA enrichments.

Transcriptomic profiling of neural crest genetic ablation at three developmental stages using 3’ tag sequencing

Based on the wild-type expression of tfap2a and tfap2c, the morphological double mutant phenotype and the sox10 molecular phenotype we chose three time points, 4 somites, 15 somites and 24 hpf, for the transcriptomic screen of tfap2a;tfap2c mutants. At the 4 somite stage pluripotent neural crest stem cells should be well established based on snail1b expression [33] and detectable with a whole embryo transcriptomic approach.

To genetically ablate the neural crest, we created double carrier fish for tfap2a^+/sa24445;tfap2c^+/sa18857 (denoted as tfap2a^+/-;tfap2c^+/- from here on) alleles, using mutants produced by the Zebrafish Mutation Project (ZMP https://www.sanger.ac.uk/resources/zebrafish/zmp/) [39]. We confirmed the phenotypes previously described in tfap2a;tfap2c depletion experiments [17,20]. Double homozygous embryos were indistinguishable from wild-type siblings at the 4 somite stage but were slightly elongated/dorsalised by the 15 somite stage and were clearly discernible by 24 hpf (Fig 2A and 2B). Notably, we also identified a specific pattern of reduction of dorsal tail melanocytes in tfap2a^-/-;tfap2c^+/- embryos at 48 hpf (Fig 2C) in addition to the melanocyte reduction previously noted in tfap2a^-/- embryos which demonstrates a dosage effect of tfap2c heterozygosity on tfap2a homozygous mutants (Fig 2D). Conversely, all other genotypic combinations were indistinguishable from their wild-type siblings at 48 hpf with only tfap2a^-/- carriers progressing to present craniofacial defects at 72 hpf as previously described [16]. This phenotypic diversity shows that tfap2a and tfap2c do not act in a simple redundant fashion.

Fig 2 — (A) *tfap2a*^-/-;*tfap2c*^-/- mutants present the first morphological phenotypes at the 15 somite stage. (B) By 28 hpf the morphological phenotype leads to an overall dorsalised form, bifurcation of the forming eye, heart oedema, and complete lack of neural crest cells. All other genotypes appear normal. (C) At 48 hpf the previously described reduction of melanocytes can be noted in *tfap2a*^-/-*;tfap2c*^+/+ embryos and a modest reduction of melanocytes can be identified in the dorsal tail (red arrow heads) in *tfap2a*^-/-*;tfap2c*^+/- mutants. (D) Quantification of melanocytes in the three corresponding genotypes at 36 hpf. (E) Chart indicating the number of differentially expressed gene 3’ ends identified with an adjusted p-value of <0.05 for each pairwise comparison of genotypes *tfap2a*^-/-*;tfap2c*^-/-, *tfap2a*^-/-*;tfap2c*^+/-, *tfap2a*^-/-*;tfap2c*^+/+ and *tfap2a*^+/+*;tfap2c*^-/- to *tfap2a*^+/+*;tfap2c*^+/+ siblings at 4 somites, 15 somites and 24 hpf (F) An UpSet[53] diagram to compare multiple pairwise DE gene lists derived from the *tfap2a*^-/-*;tfap2c*^-/- vs wild-type siblings (adj. p-value <0.05) for the 4 somite, 15 somite and 24 hpf stages and the list of neural crest-enriched genes derived from sorted neural crest cells at 22–23 hpf. The horizontal black bars represent the size of the gene lists. Individual subsets are marked with a black dot and overlaps with a connecting line. The number of genes in each subset is shown above each vertical bar. The vertical bars are numbered consecutively along the x-axis. GO/ZFA enrichment was carried out on the subset of the 4 and 15 somite stages (blue box), the subsets indicated with the orange boxes and on all genes contained in the neural crest FACS enrichment and in at least one of the three different double knockout time points (magenta box). The developmental time course nature of the data allows for the grouping of the subsets into timing based on neural crest development starting with *early* neural crest-specific gene expression and then moving towards *early-mid*, *mid*, *mid-later* and *later*. The complete list of the 26 genes in group 13 can be found in S2 Table.

In light of the observed phenotypes stemming from a dosage effect of tfap2c heterozygosity in tfap2a homozygous mutants our primary aim was to systematically investigate the genetic interactions of tfap2a and tfap2c. We therefore sequenced up to 10 embryos for all 9 genotypes at the three different stages to enable comparison of all genotypic combinations. We crossed double heterozygous tfap2a;tfap2c parents and collected embryos at the three developmental time points as single embryos. Following nucleic acid extraction and genotyping, single embryos were processed and global mRNA transcript levels determined using 3’ tag sequencing (Fig 1J). After quality control and the removal of outlier samples we carried out pairwise analysis using DESeq2.

Transcriptional phenotypes in tfap2a and tfap2c mutants differ greatly in magnitude when compared to their morphological outcomes

Our transcriptomic profiling uses whole embryos, therefore tissue-specific gene expression changes tend to be reflected in smaller log₂ fold changes than would be expected from tissue dissection or FACS-derived cell populations. However, using high numbers of biological replicates enables us to faithfully detect smaller, but meaningful, effect sizes. We first assessed how the transcriptomes of the different genotypic conditions behaved across time. Comparing the absolute numbers of differentially expressed (DE) genes of the four most relevant knockout genotypes over the three developmental time points revealed three major findings (Fig 2E). Firstly, when compared to wild-type siblings, the number of genes differentially expressed in both tfap2a or tfap2c single homozygous embryos is very small in contrast to the double homozygous knockout and the tfap2a^-/-;tfap2c^+/- mutants indicating genetic compensation. Secondly, despite the severe morphological phenotype of double mutants at 24 hpf the number of DE genes was less than half of that at the 15 somite stage. Conversely, while only beginning to display a mild morphological phenotype at 48 hpf, the tfap2a^-/-;tfap2c^+/- mutants showed a strong molecular phenotype at 4 and 15 somites, with a longer DE list at 4 somites than the double mutants. This molecular signature was strongly diminished by 24 hpf. Taken together this demonstrates that the complexity of transcriptional changes is not necessarily mirrored in the morphological phenotype, and vice versa.

Overlapping multiple expression profiles groups genes by biological function

Next we analysed the transcriptional profile of complete ablation of the neural crest in tfap2a^-/-;tfap2c^-/- knockouts. A role for tfap2a has been previously described in both neural and non-neural ectoderm tissues which lead to the formation of the neural crest, epidermis, and cranial placodes [17,54,55]. To separate transcripts into subsets specific to the neural crest or the epidermis we filtered the DE genes from the three developmental time points in tfap2a^-/-;tfap2c^-/- knockouts relative to wild-type siblings with the list of 4995 FACS-identified neural crest genes (Fig 2F). When all genes which appear in at least one of the developmental stages and the neural crest FACS list are analysed together with their associated GO terms, there is an enrichment for pigment cells and melanocytes but no other neural crest subtypes (magenta box Fig 2F). However, zebrafish anatomy enrichment (ZFA) returns a strong enrichment for the neural crest (Fig 2F, S1 Table). This finding highlights the current limitations of zebrafish GO annotation which has a bias for genes linked to pigmentation and lacks annotation for genes associated with earlier neural crest states.

A relatively small group of 26 genes (S2 Table) appearing in all four data sets included tfap2a, sox10 and many keratins. This could potentially signify an epidermal/neural crest precursor cell type which is in the process of committing to one of the lineages.

Comparison of the three developmental time points places genes into “early,” “mid,” and “later” neural crest-specific groups. Each of these groups (Fig 2F) contain numerous examples of previously characterised neural crest-specific genes common across many studied species [37] which helps to validate this approach, but also many unannotated genes or genes previously not associated with the neural crest (Table 1).

The gene lists shared between the different stages but not found in the neural crest FACS data set (orange boxes Fig 2F) and their Gene Ontology (GO) term annotation revealed an enrichment for epidermal-related terms. Another subset from the 4 somite and 15 somite stages that is not present in the NC-enriched gene list is a group of genes enriched for expression, translation and RNA processing (blue box Fig 2F).

tfap2a;tfap2c genetic compensation

Our next question was how the transcript levels of tfap2a and tfap2c, along with three well characterised neural crest-specific genes (foxd3, sox10 and sox9b), behaved across all nine genotypes and the three developmental stages (Fig 3A–3O). At 4 somites, embryos homozygous for either tfap2a or tfap2c had significantly lower transcript abundances for their respective genes, indicating that nonsense-mediated decay [56] had most likely occurred (Fig 3A and 3B). A genetic interaction is evident in tfap2a^-/-;tfap2c^+/+ embryos between tfap2a and tfap2c with higher levels of wild-type tfap2c transcripts than in wild-type siblings (Fig 3B) while tfap2a is not increased in the inverse case of tfap2a^+/+;tfap2c^-/- mutants (Fig 3A). This indicates that, by the 4 somite stage, the neural crest GRN is able to detect reduced levels of tfap2a in knockouts and compensation through upregulation of tfap2c is established. Interestingly, at 4 somites and partially at 15 somites, in homozygous tfap2a mutants transcript levels of the three NC genes follow the tfap2c expression pattern. For example, among embryos homozygous for tfap2a, sox9b expression at 4 and 15 somites is highest in tfap2a^-/-;tfap2c^+/+ embryos, but drops to half in tfap2a^-/-;tfap2c^+/- embryos (Fig 3E and 3J). This suggests a direct quantitative relationship between tfap2 transcript abundance and that of its targets.

By 24 hpf the abundance of tfap2a and tfap2c across the nine genotypes remains much the same as at the previous developmental stages (Fig 3K and 3L). Interestingly, foxd3 and sox9b levels are no longer significantly different in tfap2a^-/-;tfap2c^-/- embryos, which is suggestive of their exit from the neural crest GRN or initiation of expression in non-neural crest tissues, but levels of sox10 remain strongly reduced in the double mutants (Fig 3M–3O). Also, tfap2a^-/-;tfap2c^+/- embryos now have levels of foxd3, sox9b and sox10 comparable to wild type which suggests a general recovery of the neural crest GRN by this stage. These data show that the time point of the strongest molecular phenotype and tfap2c compensation is at around 4–15 somites with the morphological phenotypes beginning to emerge by 15 somites.

RNA-seq on tfap2a;tfap2c knockouts at 15 somites confirms 3’ tag sequencing data and produces a more detailed transcriptional landscape

To further investigate the dose-dependent compensation while also creating a more detailed transcriptomic profile of pluripotent and differentiating neural crest cells, we carried out RNA-seq on tfap2a;tfap2c knockouts at the 15 somite stage. All 9 genotypes were assessed using a total of 90 single embryos. Principal component analysis highlights that tfap2a^-/-;tfap2c^-/- and tfap2a^-/-;tfap2c^+/- are most similar on a molecular level in spite of their vastly different morphological phenotypes (S2A Fig). Pairwise comparisons of four different genotypes to their wild-type siblings shows high numbers of genes changing in both tfap2a^-/-;tfap2c^-/- and tfap2a^-/-;tfap2c^+/- groups (S2B Fig, Table 1). The majority of significant genes have reduced transcript levels in double mutants with robust p-values (S2C Fig). The 15 somite 3’ tag sequencing and RNA-Seq data sets showed good correlation of the detected DE genes at an adjusted p-value < 0.01 (S2D Fig)

Hierarchical clustering on the significantly changed genes from the tfap2a^-/-;tfap2c^-/- versus wild type pairwise comparison and ZFA enrichment placed genes into functional groups. While loss of both tfap2a and tfap2c leads to a reduction in genes involved in neural crest and epidermis development it also leads to an upregulation of genes associated with neural terms (S2E Fig).

Identifying genes required for tfap2a;tfap2c knockout compensation / neural crest rescue

The 3’ tag sequencing analysis had highlighted that both tfap2a^-/-;tfap2c^-/-and tfap2a^-/-;tfap2c^+/- gave the most extensive molecular phenotypes even though tfap2a^-/-;tfap2c^+/- were morphologically indistinguishable from wild-type siblings at 15 somites whereas tfap2a^-/-;tfap2c^-/- presented obvious morphological phenotypes by that stage. Hence a single wild-type allele of tfap2c is sufficient to rescue the morphological tfap2a^-/-;tfap2c^-/- neural crest specification and differentiation phenotype despite the observed effect on the transcriptional level. We were therefore keen to understand which genes are involved and may be required for the rescue of the morphological phenotype.

First, we assessed expression of tfap2c in the 15 somites RNA-seq data and found that the levels of tfap2c were significantly higher in tfap2a^-/- embryos when compared to wild-type embryos (Fig 4A) demonstrating active regulatory compensation rather than redundancy. We then compared the sets of DE genes derived from the pairwise comparisons of wild type with tfap2a^-/-;tfap2c^-/- and tfap2a^-/-;tfap2c^+/-. The vast majority of DE genes in the tfap2a^-/-;tfap2c^+/- condition were also changed in the tfap2a^-/-;tfap2c^-/- embryos (Fig 4B). Crucially, this set is enriched for genes with a dose-dependent response to successive loss of tfap2a/c alleles where for each gene the log₂ fold change in tfap2a^-/-;tfap2c^+/- is about half that in tfap2a^-/-;tfap2c^-/- (Fig 4C). This demonstrates that loss of a third tfap2a/c allele affects the neural crest GRN, however the transcriptional changes are not sufficient to derail neural crest specification and differentiation. Together this identifies a core set of tfap2a/tfap2c-responding genes, separate from secondary downstream events caused by differentiation failure and tissue loss.

As a single wild-type allele of tfap2c is able to maintain neural crest specification we sought to identify genes that are sensitive to different levels of tfap2c by dissecting the full ablation response (tfap2a^-/-;tfap2c^-/-) using the partial ablation profiles (tfap2a^-/-;tfap2c^+/+ and tfap2a^-/-;tfap2c^+/-). To this end we ran four differential gene expression (DGE) analyses: double homozygous embryos against embryos with one or two wild-type alleles of tfap2c, and wild-type embryos against tfap2a^-/-;tfap2c^-/- or tfap2a^-/-;tfap2c^+/-. Next we overlapped the four lists to produce 14 subsets (Fig 4D). This identified groups of genes that share distinct expression profiles. Subset one contains genes where tfap2a^-/-;tfap2c^-/- knockout resulted in a mild, but significant, change from wild-type siblings but there is no significant difference between tfap2a^-/-;tfapc^+/- and tfap2a^-/-;tfap2c^-/- or wild-type siblings (Fig 4E). For genes in subset three a complete tfap2a^-/-;tfap2c^-/- knockout resulted in a significant change from wild-type siblings while a single allele of tfap2c was sufficient to return the expression to wild-type levels. An example of this case would be lef1 (Fig 4F). Subset five contained genes that are only partially rescued, for example sox10, pax7a, ednrab, kctd15a and erbb3b, all of which play vital roles in neural crest development across vertebrates [37]. A single wild-type allele of tfap2c, or even both wild-type alleles, is unable to return expression to wild-type levels but the expression is still significantly different from the tfap2a^-/-;tfap2c^-/- condition, as exemplified by mmp28 (Fig 4G). Finally, subset seven contained genes that are only rescued by two alleles of tfap2c, such as krt222 (Fig 4H).

We next analysed the gene sets for transcription factor motif enrichment using HOMER[57] (Fig 4I, see Table 1 for figshare link to all significant results). The full DGE list for tfap2a^-/-;tfap2c^-/- against wild type (Fig 4B) had 31 enriched known motifs (q-value < 0.05), which included Ap2gamma and Ap2alpha. These motifs also appeared in the top three of 13 enriched motifs for the DGE list for tfap2a^-/-;tfap2c^+/- against wild type, suggesting that this profile reflects a core set of Ap2 targets. Analysis of the subsets in Fig 4D revealed that only subset five, which contains genes showing dosage sensitivity and partial rescue in tfap2a^-/-;tfap2c^+/- embryos, had an enrichment for Ap2 targets. Subset three, the set of genes fully rescued by one or two wild-type copies of tfap2c, was enriched mostly for binding sites of zinc-finger domain-containing transcription factors such as KLFs, but also Tead2, a transcription factor involved in Yap/Taz Hippo signalling[58,59].

ZFA enrichment confirms specific neural crest signatures

For a functional gene analysis, we carried out ZFA enrichment on all 14 gene subset lists which yielded significant enrichments for subsets 1–8 (Fig 4J, S3 Fig). Subset three, the genes fully rescued by either one or two alleles of tfap2c, showed the strongest enrichment for terms associated with the neural crest, head and cranial crest and also fin. While fin enrichment may seem nonsensical for a 15 somite embryo, this is due to the fact that many genes annotated for fin development are also involved in craniofacial development. A similar enrichment profile resulted from subset five, the genes where either one or two alleles of tfap2c rescued expression levels to a significant extent, but not completely. By contrast, the two largest subsets, containing genes that change in double homozygous embryos with respect to wild types, but not compared to tfap2a^-/-;tfapc^+/-, showed a bias towards nervous system and ectoderm enrichment. Crucially, subsets six and seven with genes that failed to be rescued by either one (subset seven) or two (subset six) wild-type tfap2c alleles, had no or very little neural crest enrichment. This suggests these genes represent tfap2a targets outside of neural crest differentiation.

Taken together the enrichment analysis breaks down the full tfap2a/tfap2c knockout response into separate expression classes with different functional profiles. Subsets three and five contain genes that are fully or partially rescued by tfap2c, show the strongest neural crest enrichment and are thus most likely to represent the core of the tfap2 neural crest GRN. Interestingly, only the partial rescue gene list (subset five) is enriched for direct Ap2 targets, suggesting that the full rescue list (subset three), which shows the strongest neural crest signature, contains more genes that are further downstream in the network.

Markov clustering reveals tfap2a and tfap2c-specific gene clusters

Next we applied an expression correlation network and Markov clustering approach using Biolayout Express^3D [60,61] to identify co-expression profiles independent from condition-driven differential expression analysis. We constructed a network graph with genes as nodes and their Pearson correlation as edges from the tfap2a;tfap2c 15 somite RNA-seq dataset and used Markov clustering (MCL) to divide the network into discrete sets of co-expressed genes. The network clusters isolated co-expression groups of genes that share a genomic locus (Fig 5A’ and S4 Fig) similar to our observation in the sox10 and mitfa mutants, but also identified tfap2a and tfap2c-specific components (Fig 5A) within the larger co-expression network.

In total 30 clusters containing a total of 600 genes were driven by changes in the tfap2a or tfap2c genotypes (Fig 5B). It is important to point out that in the previous analysis we compared lists derived from pairwise DGE comparisons, whereas MCL clusters genes based on their expression similarity across all samples. Therefore, these clusters might exclude genes that are identified in the DESeq2 analysis because of low expression correlation with other genes, but also include highly correlated genes which did not produce a significant adjusted p-value in the DESeq2 analysis.

The unsupervised clustering confirmed the strong signal in the double homozygous fish (clusters one and two) and dose-dependent compensation by tfap2c (cluster three). However, in addition it provided increased functional resolution. For example, cluster 17 (Fig 5E) was highly specific to neural crest effectors containing the soxE paralogues sox10 and sox9b, the micropthalmia bHLH transcription factor tfec, as well as the Pak4 kinase inhibitor fam212aa, and one uncharacterised gene (si:ch211-243g18.2; ENSDARG00000044261).

The differentiation of the neural crest also requires the down-regulation of specific groups of genes, for example to repress a neural fate. Cluster five (Fig 5F) contains a collection of soxB family genes (sox3, sox19a, sox19b, sox21b), one of which (sox19) is one of the earliest CNS markers in vertebrates [47]. Cluster five also includes another example of paralogues of oct-related transcription factors pou3f2b (Oct-2) and pou3f3a, which are associated with controlling CNS development. Cluster 29 (Fig 5G) contains a collection of genes (pax7a, eng2b, mapk12b and enfa2a) which, based on the midbrain/hindbrain expression patterns of pax7a and eng2b, also suggests a developmental CNS role. All gene lists of individual clusters, along with GO and ZFA enrichments, can be found in (Table 1).

Using many replicates of single, genotyped embryos from the same clutch has allowed us to show how a single allele of tfap2c is sufficient to maintain a minimal neural crest GRN. Based on this we have compiled functional subsets of maintained genes, many of which are still poorly described and previously have never been associated with the neural crest. We have identified multiple cases where gene families or paralogues behave in the same manner, highlighting more potential examples of the compensatory nature of the GRN in general. To validate the association of novel genes with neural crest biology, we next analysed a set of candidates using a knockout approach.

Validation of novel neural crest transcripts

Our transcriptional profiles from mutants and FACS enriched neural crest cells contain a large number of novel neural crest candidate genes with poor or no functional annotation (Table 1). We chose a subset of these for further analysis based on lack of functional annotation and their differential expression across the different datasets (Table 2). To validate their involvement in neural crest biology, we analysed the expression patterns or screened for knockout phenotypes in zebrafish embryos. For example, transcripts of the gene wu:fc46h12; ENSDARG00000114516 were strongly reduced in several sox10 mutant experiments (Table 1). At 24 hpf wu:fc46h12 has an identical expression pattern to the xanthophore marker gch2 in wild-type and sox10 mutants (S5A, S5D, S5G and S5H Fig), but diverges at 48 hpf in wild types as wu:fc46h12’s expression domain becomes more specific to a ventral crest population (S5E and S5F Fig), heart and dorsal aorta (S5E’ and S5F’ Fig). The majority of these expression domains are also lost at 48 hpf in sox10 mutants (S5G and S5H Fig). A CRISPR/Cas9 knockout allele, wu:fc46h12^sa30572, was homozygous viable. Maternal-zygotic (MZ) mutant wu:fc46h12^sa30572 embryos from intercrosses of homozygous females with heterozygous males showed heart oedema at 36 hpf (S5I and S5J Fig). By 5 dpf most larvae formed swim bladders and had grossly normal hearts. A more detailed analysis will be required to ascertain the role of wu:fc46h12 in heart development.

Table 2. Knockouts investigated in this study.

Gene	Allele	Gene_ID	DGE Experiment	Phenotype	Notes
add3b	sa10508	ENSDARG00000056250	FACS	NP	Hom-Viable
akr1b1	sa30578	ENSDARG00000006215	sox10 & tfap2a;tfap2c	PT
anxa2a	sa24716	ENSDARG00000003216	FACS	NP
c10orf11	sa12051	ENSDARG00000057166	FACS	NP	Hom-Viable
cax1	sa10712	ENSDARG00000045601	sox10 & tfap2a;tfap2c	PT	Hom-Viable MZ-PT
defbl1	sa30573	ENSDARG00000075161	sox10	NP
Hipk2	sa23245	ENSDARG00000042518	FACS	NP
itga6a	sa21422	ENSDARG00000042282	tfap2a;tfap2c	NP
itga6b	sa16239	ENSDARG00000069946	tfap2a;tfap2c	NP
si:ch211-155k24.6	sa13099	ENSDARG00000062688	sox10	NP
si:ch211-155k24.6	sa13185	ENSDARG00000062688	sox10	NP
slc27a4	sa21677	ENSDARG00000017047	FACS	NP
smarca4	sa12514	ENSDARG00000077226	tfap2a;tfap2c	PT
tspan36	sa21320	ENSDARG00000024540	sox10	NP
wu:fc46h12	sa30572	ENSDARG00000104814	sox10 & yap1	PT	Hom-Viable
yap1	sa25458	ENSDARG00000068401	tfap2a;tfap2c	PT	Hom-Viable MZ-PT
yap1	sa25474	ENSDARG00000068401	tfap2a;tfap2c	PT	Hom-Viable MZ-PT

Open in a new tab

Two genes, akr1b1 and cax1, were differentially expressed in the tfap2a;tfap2c and sox10 mutant data sets (Table 1). The former, akr1b1, is ubiquitously expressed [47] and, using CRISPR/Cas9, we created a premature stop, akr1b1^sa30579. Homozygous akr1b1^sa30579 fish develop normally but presented pale xanthophores (S5K Fig).

A premature stop in cax1 was already available from the Zebrafish Mutation Project. A previous report has shown expression in xanthophores and upon morpholino knockdown a reduction in neural crest tissues of the jaw as well as xanthophores [62]. While zygotic cax1^sa10712 homozygotes present a dulling in the colouring of xanthophores (S5L Fig) and rounding up of the normally highly dendritic cells, they lack obvious craniofacial phenotypes. Homozygous cax1^sa10712 adults are viable and fertile, but MZcax1^sa10712 embryos appear ventralised at somitogenesis pointing to a role for cax1 during early embryonic development (S5M Fig).

A role for maternally supplied yap1 in melanocytes

Expression of the transcriptional regulator yap1 was reduced in double homozygous embryos in our 4 somite tfap2a;tfap2c 3’ tag sequencing data (Table 1) and yap1 was also enriched in neural crest FACS-sorted cells (Fig 2E). We also found that three members of the Hippo signalling pathway, fat2, lats2 and yap1, had significant negative log₂ fold changes in the 15 somite tfap2a;tfap2c knockout versus wild type RNA-seq dataset (Fig 6A). Furthermore, subset three from the tfap2a/tfap2c analysis was enriched for genes with a Tead2 binding site, an interactor of Yap/Taz transcription factors. These data suggest a very early role for Hippo signalling in neural crest cells. Previous work has identified Hippo signalling as a coactivator of Pax3, involved in melanocyte gene expression [63], and in vitro studies suggest that YAP is involved in neural crest fate and migration [64].

Fig 6 — (A) Transcripts of members of the Hippo signalling pathway *fat2*, *lats2* and *yap1* were less abundant in *tfap2a;tfap2c* mutants when compared to wild-type siblings. A schematic showing their role in signal transduction and transcription inside a cell. (B) CRISPR/Cas9 mutations were made in the first exon of *yap1* leading to the two alleles described. The exon-intron structure of the *yap1* transcript is shown in gold. The exact deletions are displayed below. (C) Embryos from a single clutch were split and raised at 24C and 31.5C. Bars indicate the absolute number of fish forming a swim bladder at 5 dpf for each *yap1*^sa25458 genotype (D) Normalised counts of 3’ tag sequencing data at 24 hpf comparing *yap1*^sa25458 mutants to wild-type siblings. All four genes, *yap1*, *gch2*, wu:*fc46h12* and *padi2*, have an adj. p-value <0.05. (E) Maternal zygotic *yap1* mutants present a strong reduction in melanocyte numbers at 36 hpf at both dorsal (arrow head) and ventral tail regions (arrow). (F) Quantification of melanocytes with the quantities on the left and then broken down into the regions of the head, yolk, ventral tail and dorsal tail. Each dot represents a region in a single larva, siblings in blue and MZyap1^sa25458 in red. A statistical significance of <0.05 is indicated with “*”.

yap1 knockouts are temperature sensitive, homozygous viable and reduced in body size

To investigate the role of yap1 in neural crest we targeted its first exon using CRISPR/Cas9 and created two alleles, yap1^sa25458 and yap1^sa25474, leading to frame shifts and premature stops (Fig 6B). When heterozygous carriers for either yap1^sa25458 or yap1^sa25474 were intercrossed and embryos raised at 28.5°C we found the previously described ocular phenotypes at 48–72 hpf in approximately 25% of embryos [65], albeit with variable penetrance depending on incubator temperature. We therefore tested whether these two yap1 mutants were temperature sensitive by splitting a single clutch and raising the embryos at two different temperatures. When raised at 24°C, by 5 dpf just under a quarter (22 of 116) of larvae with normal morphology and a filled swim bladder were homozygous yap1 mutant. By contrast, when raised at 31.5°C none of the larvae with a swim bladder (108) were homozygous mutant for yap1 leaving a 1:2 ratio of 38 wild-type and 70 heterozygous fish (Fig 6C).

We raised intercrosses of yap1 carriers for each allele (yap1^sa25458 & yap1^sa25474) at a permissive temperature of 24°C until 5 dpf then transferred them to our standard fish nursery to test for adult viability of homozygotes. At two months post fertilisation, a subset of these fish seemed smaller than their siblings (S6A Fig). We measured and genotyped intercrosses from both yap1 alleles and confirmed that yap1 homozygous fish were viable, but smaller than their wild-type siblings (S6B Fig).

Zygotic yap1 mutants show signs of neural crest GRN disruption

Although zygotic yap1 mutants did not display obvious morphological phenotypes in neural crest cell types, we investigated potential neural crest GRN changes. We intercrossed yap1^+/sa25458 carriers, raised them at 28.5°C and collected embryos for 3’ tag sequencing at 4 somites, 15 somites and 24 hpf. The transcriptome profiles were normal at 4 somite and 15 somite stages, with the majority of the changed genes on the same chromosome as yap1 (Fig 1J, Table 1). However, at 24 hpf the early xanthophore pigment cell marker gch2 and wu:fc46h12, the newly identified pigment marker described above, were significantly reduced in yap1 mutants (Fig 6D). Interestingly, the early epidermis marker padi2 was also reduced (Fig 6D).

Loss of maternal yap1 mRNA causes reduced melanocyte numbers at 30 hpf

Previous studies have shown a role for yap1 in very early development of zebrafish and medaka [66–68]. In zebrafish, this precedes zygotic genome activation and thus highlights a role for maternally deposited transcripts. The developmental time course data of yap1 expression confirmed high levels of maternally deposited polyadenylated yap1 (E-ERAD-475, www.ebi.ac.uk/gxa/home/).

Given the maternal deposition of yap1 transcripts in the egg, we crossed heterozygous male yap1^+/sa25458 carriers to homozygous female yap1^sa25458 fish and evaluated the resulting MZyap1^sa25458 larvae at the restrictive temperature of 31.5C. At approximately 30 hpf we observed a strong reduction in the number of melanocytes in roughly half of the embryos. The previously described ocular phenotype [65] was also apparent in addition to a mild pericardial oedema (Fig 6E). These larvae are otherwise morphologically stage matched. To quantify the melanocyte reduction we counted melanocytes in four different sections (head, yolk, ventral trunk and dorsal trunk) of each larva and then genotyped them. A significant melanocyte reduction of about 50% in the yolk, ventral tail and dorsal tail was found, with no major difference in the number of melanocytes in the head (Fig 6F). This demonstrates that maternally deposited mRNA is able to rescue a melanocyte phenotype at 30 hpf further highlighting the very early induction of the neural crest GRN.

Discussion

We have used transcriptional profiling of mutants affecting different steps of neural crest specification and differentiation to dissect the zebrafish neural crest GRN. We have used 3’ tag sequencing as a first pass screening method to then hone in with more detailed RNA-seq. To make our data easily accessible to the research community we have made the tfap2a;tfap2c 15 somite RNA-seq experiment available for browsing and downloading in Expression Atlas (https://www.ebi.ac.uk/gxa/experiments/E-MTAB-6106/Results). The analysis of genotyped single embryos, independent from a visible phenotype, has allowed us to separate transcriptional responses from morphological outcomes. This approach is complementary to cell type-specific assays which require tissue manipulation and/or dissociation, much like the neural crest FACS RNA-seq data set described here. It is important to keep in mind that RNA-seq measures absolute differences in transcript abundance, rather than up- and down-regulation of genes. In whole embryos these abundances can be changed by altered tissue size as well as a change in mRNA levels in an otherwise unaffected tissue. Recently, elegant methods have been developed to biotag specific cells in vivo and isolate their nuclei for further processing [69]. However, currently, these require the pooling of embryos which would be challenging to apply to non-phenotypic embryos in loss of function analyses.

Initiation of neural crest GRN expression before gastrulation, shortly after zygotic genome activation

The neural crest is typically described as being induced at the lateral edges of the neural plate after gastrulation. However, using wild-type developmental time course data we can place the activation of the neural crest transcription factors tfap2a, tfap2c and foxd3 at the Dome stage, which follows zygotic genome activation and precedes gastrulation. In zebrafish, simultaneous loss of tfap2a and foxd3 has been shown to genetically ablate the neural crest [70,71] with tfap2a and foxd3 expressed in mutually exclusive compartments of the embryo at the shield stage, midway through gastrulation. The overlap of these expression domains forms the presumptive neural crest [71]. In Xenopus laevis a high degree of overlap exists in the blastula pluripotent GRN and the neural crest GRN with the neural crest retaining the pluripotency of cells in the blastula stage rather than being induced later on in development [72]. Interestingly, the activation of the neural crest marker crestin also coincides with the Dome stage (E-ERAD-475, www.ebi.ac.uk/gxa/home/). This suggests that the establishment of the proto-neural crest GRN comes shortly after zygotic genome activation and places its initiation much earlier than previously shown in zebrafish and other vertebrates. This also raises the possibility of maternal mRNAs playing a larger role than previously thought in early neural crest initiation. Nevertheless we do not dispute that the neural crest cell lineage is likely to pass through a well-defined ectodermal state as elegantly shown in single cell studies [73].

Genetic ablation of the neural crest

In addition to tfap2a;foxd3 loss of function, a combined knockout of tfap2a and tfap2c genetically ablates the neural crest in zebrafish [17,71]. In the case of tfap2a;foxd3, tfap2a is thought to have an activator function whereas foxd3 has been shown to act both as a repressor and an activator [5]. Knockouts of tfap2a fail to form normal jaws and have reduced numbers of melanocytes, but still form neural crest cells. On a transcriptional level, using 3’ tag sequencing, the number of genes which are differentially abundant in the tfap2a or tfap2c mutants alone are modest, 39 and 5 genes respectively at the 15 somite stage (Fig 2E). At the 4 somite stage tfap2c acts in a compensatory manner as its overall abundance is increased by almost 50% in tfap2a^-/- embryos (Fig 3B and Fig 5A). By removing a single wild-type tfap2c allele in tfap2a^-/- embryos the number of changing genes jumps from 39 to 1152 (Fig 2E), although this extensive change in gene expression is marked morphologically by only a mild decrease in the numbers of melanocytes in the tail at a much later stage. Using RNA-seq at the 15 somite stage increases the total numbers of changing genes detected but the general trends remain much the same. tfap2 family proteins are thought to form both homodimers as well as heterodimers [74]. This stepwise genetic ablation implies that tfap2c does not require tfap2a to initiate the early neural crest GRN and that either homodimers of tfap2c alone or potentially heterodimers with other tfap2 family members are sufficient; however, we do not see upregulation of any other tfap2 genes.

Dissection of the neural crest transcriptional network

Previous work in mouse, frog, chick and fish have identified the important role of AP-2 to initiate the neural crest and drive its downstream targets such as msx1, sox9/10 and snail. [12,75,35,16]. Most previous analysis of AP-2 downstream targets have taken a gene by gene approach or, in the case of ChIP-seq, return thousands of putative targets. With our large-scale screen our intent is to identify the bulk of relevant AP-2 downstream targets and to make these available for further analysis. For example, Msx1 is a well-defined AP-2 target and our analysis shows transcripts for both paralogues, msx1a and msx1b, are less abundant in the tfap2a/c double knockouts, suggesting that a double knockout is necessary to abolish msx1 function. A further aspect is that AP-2 has been shown to play an important role in epidermis in addition to neural crest. Both of these tissues arise at similar time points from ectoderm, and it is therefore crucial to separate the neural crest from the ectoderm signal. By combining multiple mutant data sets over developmental time along with the neural crest FACS data set we could establish the timing of when different levels of the neural crest GRN begin. Along with a large number of known downstream targets the subsets contain many uncharacterised genes, suggesting a role for these in pigmentation. We can further group genes which are more likely to not be specific to the neural crest but rather involved in epidermis development (Fig 2F). Using the overlaps across the three different time points we have classified groups of genes from an “early” role to “mid” and then “later.” We appreciate that both tfap2a and tfap2c have broad expression domains and our attempts to separate out neural crest and epidermal-specific signals will have limitations. Due to the shared lineage of neural crest and dorsal epidermis cells, it is also possible that GRN overlap exists before the lineage splits. Single cell studies will be better able to address these issues. We have also further characterised trunk neural crest and melanocyte-specific downstream targets by analysing sox10 and mitfa knockouts. Similar approaches could be used in the future to address different neural crest sub lineages, for example, in sox9b mutants.

Neural crest identity requires repression of a neural fate

The 15 somite stage had the highest number of differentially expressed genes in the tfap2a;tfap2c loss of function model and therefore we chose to investigate this stage in more detail using RNA-seq. Using different subsetting approaches we have characterised distinct groups of neural crest genes and also have identified the core neural crest GRN that is maintained via tfap2c. The hierarchical clustered heatmap (S2E Fig) highlights an enrichment of neural genes that are increased in the mutant samples. Considering the emerging model that neural crest cells are not actually induced in situ but rather a refinement of pluripotent blastula cells [72], our data support the notion that not only is the activation of the neural crest GRN important but also the repression of non-neural crest-specific GRNs.

Compensation of tfap2a knockout phenotypes via tfap2c and identification of genes involved in the neural crest rescue

Both our 3’ tag sequencing time course and RNA-seq reveal a great disparity between the severity of molecular phenotypes and morphological phenotypes. This data set allows us to identify the genes required to maintain neural crest induction but also what levels of expression are sufficient. RNA-seq analysis of tfap2a;tfap2c knockouts and their siblings revealed an increase of tfap2c mRNA expression in tfap2a mutants at 15 somites. Although not addressed in this study, an interesting question now is: what is the molecular machinery which identifies the need for genetic compensation and how is it carried out? We find that whereas a single allele of tfap2c is able to rescue the early morphological neural crest ablation phenotype the expression of a core set of downstream effectors cannot be restored to wild-type levels. This separates the morphological phenotype, and its secondary molecular effects, from the primary gene regulatory effect of tfap2 loss of function. We have used this differential behaviour of downstream targets to identify genes which tfap2c is able to return to wild-type levels or to only partially rescue from the tfap2a/c double knockout. This has confirmed known neural crest players but has also added new genes to the neural crest GRN. The genes in subsets three and five (Fig 4C–4H) represent a core set of 371 and 162 genes, respectively, of the neural crest GRN required for early neural crest initiation and are most likely to be of high developmental and evolutionary importance. An enrichment for AP-2 transcription factor binding sites in the partially rescued gene subset is consistent with the first tier nature of the genes.

Genetic compensation via paralogues

Humans are particularly susceptible to haploinsufficient mutations in a number of neural crest-specific genes, including sox10, leading to Waardenburg syndrome or Hirschsprung disease, whereas this is less the case in zebrafish [76]. sox10^+/- fish are adult viable and are phenotypically normal. Based on the developmental timing and clustering behaviour of the soxE family paralogues sox10 and sox9b, there is a good probability that these two genes are able to compensate for each other in early neural crest cells. Similarly, fish with mutations in tfap2c are homozygous viable and tfap2a^+/-;tfap2c^-/- fish are indistinguishable from their wild-type siblings. By contrast, alterations of TFAP2A, acting in a dominant negative manner, lead to a number of developmental phenotypes in humans.

Phenotype-driven forward genetics screens [77,78] are very successful in identifying mutations affecting a multitude of processes across the zebrafish lifespan. By contrast, reverse genetics screens have demonstrated, against expectations, that many presumably protein-disrupting mutations fail to lead to an obvious morphological phenotype in the first five days zebrafish of development [39,79]. Although more sensitive screening assays across different life stages and conditions are required to identify more subtle phenotypes, a multi-gene loss of function approach may be required to counteract as of yet poorly characterised mechanisms of compensation. Here, using the neural crest as a model, we dissect the relationship between transcriptional robustness and morphological outcomes. Our study has also begun to reveal more evidence of genetic compensation in other paralogous genes. Unsupervised clustering has highlighted that entire gene families clustered together across development [42] and behaved in a similar manner in different genetic combinations in the tfap2a;tfap2c loss of function experiments (Fig 5B–5E, Table 1).

Another example of possible paralogous compensation can be observed in the relatively mild developmental phenotypes of the yap1 knockouts. Recently double knockouts of yap1 and taz (wwtr1), its paralogue, have shown much stronger early developmental phenotypes and are embryonic lethal [67]. A deeper understanding of genetic and functional paralogues with respect to mutual compensation versus division of function will provide mechanistic insight into gene function evolution.

A role for Hippo signalling in the neural crest

We have identified a reduction in the abundance of some Hippo signalling members in both our 3’ tag sequencing and RNA-seq data sets. Previously, a role for Hippo signalling has been suggested in the neural crest using conditional mouse knockout models and in cell culture [80,63,64]. However, in the case of the mouse, complete yap1 knockouts are not viable and in human iPS neural crest cell models both YAP1 and TAZ (WWTR) require modulation. Yap1 itself is not capable of binding DNA but requires TEAD elements also identified in our studies (Table 1 gene lists). A role for TEADs in both melanocytes and melanoma has been previously documented [81] and placing yap1 downstream of Ap2 signalling adds an interesting aspect to Hippo signalling in melanocytes. In zebrafish we show a role for maternally deposited yap1 in the differentiation of melanocytes, however the effect on other neural crest subtypes remains to be investigated. It is also likely that the yap1 paralogue taz could be playing a compensatory role. Furthermore, transcriptional analysis of non-phenotypic zygotic mutant embryos raised at permissive temperatures shows dis-regulation of several neural crest and epidermis genes. This is a further example of a transcriptional phenotype in the absence of morphological changes. Over the past few years post-embryonic neural crest stem cells have been identified in mouse and zebrafish [26,82,83]. The temperature sensitive yap1 signalling model described here allows for the conditional inactivation of Hippo signalling and could also be combined with taz heterozygous fish. This would allow for the investigation of Hippo-dependent processes in post-embryonic neural crest stem cells, but also growth, pattern formation and regeneration later in development and in adults.

Conclusions

Taken together, we have used transcriptional profiling and stepwise genetic ablation of the neural crest to divide the neural crest GRN into temporal and functional units containing new candidate genes alongside well known factors. The analysis of paralogue compensation separates the morphological neural crest ablation phenotype from the first expression changes to the core tfap2 GRN. We confirm association of previously uncharacterised genes through knockout experiments and demonstrate a role for maternal transcripts in pigment cell development. Future studies of the functional gene clusters described here will help to further refine their role in neural crest development as well as their involvement in human genetic disorders and diseases such as neuroblastoma and melanoma.

Materials and methods

Ethics statement

Zebrafish were maintained in accordance with UK Home Office regulations, UK Animals (Scientific Procedures) Act 1986, under project licences 80/2192, 70/7606 and P597E5E82. All animal work was reviewed by The Wellcome Trust Sanger Institute Ethical Review Committee.

Zebrafish husbandry and phenotyping of mutants

Zebrafish were maintained at 23.5°C on a 14 h light/10 h dark cycle. Male and female zebrafish from genotyped heterozygous fish carrying mutations were separated overnight before letting them spawn naturally the next day. Fertilised eggs were grown at 28°C and single or multi-allelic phenotyping was carried out as previously described [39,84]. The sox10^t3 and sox10^baz1 alleles were a gift from Robert Kelsh and mitfa^w2 was previously a gift from Jim Lister [25,34].

Embryo collection

Embryos were either morphologically sorted into phenotypically abnormal and normal (sox10^t3/baz1 collected at 28 hpf, 36 hpf and 48 hpf) or collected blind at the stage of interest. Single embryos were placed individually into the wells of a 2 ml deep well block (Axygen, Cat number P-DW-20-C-S), snap frozen on dry ice and then stored at -80°C.

FACS

22–23 hpf embryos were collected from the zebrafish transgenic sox10:mg line which labels neural crest nuclei with mCherry and crest cell membranes with GFP. We observed a delay in the membrane-bound GFP signal causing two separate neural crest populations; one labelled only with the nuclear mCherry marker, and a second labelled both with mCherry and the membrane-bound GFP (Fig 1H). We sorted these two populations separately along with a third non-transgenic population for pairwise differential expression analysis, however for the purposes of this study we pooled the neural crest cell data. We also generated transcriptional profiles of cranial crest and trunk crest separately to capture lowly expressed genes specific to those cell types. We therefore separated heads and tails of embryos from the same stage and isolated individual cranial and trunk neural crest populations from each tissue comprising both mCherry+ and mCherry+/GFP+ cells as well as an unlabelled non-crest population. All cell populations were processed to produce polyA RNA-seq libraries and sequenced. Dissociated cells from about 30–50 larvae were collected for FACS as previously described (Manoli et al., 2012). Briefly, embryos were dechorionated using 33 mg/ml pronase (Sigma) and pooled either as whole embryos or as pools of heads and tails. The yolks were removed using deyolking buffer (55 mM NaCl, 1.8 mM KCl, 1.25 mM NaHCO₃) followed by digestion with trypsin-EDTA. Finally, the pellet was resuspended in FACSmax Cell Dissociation solution (AMS Biotechnology) and dissociated cells collected by passing the suspension through a 20 μm cell strainer (Sysmex Partec). Using appropriate gating, dissociated cells were sorted into mCherry positive, mCherry and GFP positive and unlabelled non-crest cells on the BD INFLUX. The data was analysed using FlowJo.

Sorted cells were collected and lysed in 110 μl of RLT buffer (Qiagen) containing 1 μl of 14.3M beta mercaptoethanol (Sigma). The lysate was allowed to bind to 1.8 volumes of Agencourt RNAClean XP (Beckman Coulter) beads for 10 min and RNA was eluted from the beads as per the manufacturer’s instructions. Total RNA was converted into cDNA libraries using the SMART-Seq V4 Ultra Low Input RNA kit (Clontech) followed by Nextera DNA Library Prep kit (Illumina) as per manufacturer’s instructions. Libraries were pooled and sequenced on Illumina HiSeq 2000 in 75 bp paired-end mode.

Nucleic acid extraction

Frozen embryos were lysed in 100 μl RLT buffer (Qiagen) containing 1 μl of 14.3M beta mercaptoethanol (Sigma). The lysate was allowed to bind to 1.8 volumes of Agencourt RNAClean XP (Beckman Coulter) beads for 10 min. The plate was then applied to a plate magnet (Invitrogen) until the solution cleared and the supernatant was removed without disturbing the beads. While still on the magnet the beads were washed three times with 70% ethanol and RNA was eluted from the beads as per the manufacturer’s instructions. RNA was quantified using either Qubit RNA HS assay or Quant-iT RNA assay (Invitrogen).

Genotype confirmation

Genotyping was carried out as described previously [40]. Briefly, 1 μl of DNA from the extracted total nucleic acid was used to confirm the genotype of each sample using KASP SNP and InDel identification assays (LGC group) designed against our allele of interest. The genotyped plates were read on a plate reader (Pherastar, BMG Labtech) and 10–12 samples per genotype were selected for making libraries.

Transcript counting

DeTCT libraries were generated as described previously [50]. Briefly, 300 ng of RNA from each genotyped sample were DNAse treated, fragmented and bound to streptavidin beads. The 3’ ends of the fragmented RNA were pulled down using a biotinylated polyT primer. An RNA oligo containing the partial Illumina adapter 2 was ligated to the 5’ end of the bound fragment. The RNA fragment was eluted and reverse transcribed using an anchored oligo dT reverse transcriptase primer containing one of the 96 unique index sequences and part of the Illumina adapter 1. The Illumina adapters were completed during a library amplification step and the libraries were quantified using either the BioPhotometer (Eppendorf) or Pherastar (BMG Labtech). This was followed by size selection for an insert size of 70–270 bases. Equal quantities of libraries for each experiment were pooled, quantified by qPCR and sequenced on either HiSeq 2000 or HiSeq 2500.

Sequencing data were analysed as described previously [50]. Briefly, sequencing reads were processed with the DeTCT detag_fastq.pl script and aligned to the GRCz10 reference genome with BWA 0.5.10. The resulting BAM files were processed using the DeTCT pipeline, which results in a list of regions representing 3’ ends, together with a count for each sample. These counts were used for differential expression analysis with DESeq2 on pairwise combinations of samples. Each region was associated with Ensembl 86 gene annotation based on the nearest transcript in the appropriate orientation. False positive 3’ ends, representing, for example, polyA-rich regions of the genome, were filtered using the DeTCT filter_output.pl script with the—strict option, reducing the number of 3’ ends from 439,367 to 53943. Gene sets were analysed using topgo-wrapper for GO enrichment and Ontologizer for ZFA enrichment.

RNA-seq

Total nucleic acid was isolated from tfap2a^+/sa24445;tfap2c^+/sa18857 intercrosses at 15 somites. KASP genotyping was used to identify all nine possible genotypes. Total nucleic acid was treated with DNAseI (NEB, Catalogue number M0303L) and 10 replicates per genotype were processed. Ambion ERCC spike-in mix 2 (Cat. No. 4456740) was added to 200 ng RNA according to the manufacturer’s instructions and sequencing libraries were prepared using the Illumina TruSeq Stranded mRNA Sample Prep Kit. Libraries were pooled and sequenced on Illumina HiSeq 2500 in 75 bp paired-end mode.

Sequencing data were assessed using FastQC and aligned to the GRCz10 reference genome and Ensembl 86 transcriptome using TopHat2. Read counts per gene were generated using htseq-count and used as input for pairwise differential expression analysis with DESeq2. Gene sets were analysed using topgo-wrapper for GO enrichment and Ontologizer for ZFA enrichment. Custom R scripts were used for hierarchical clustering and principal component analysis.

Transcription factor motif analysis

Transcription factor motif enrichment was performed using HOMER's findMotifs.pl tool (v4.10.3) with default settings. The GRCz10 promoter set used was created with HOMER's updatePromoters.pl tool based on RefSeq genes from -2000 bp to 2000 bp relative to the TSS.

Graph based Pearson correlation and Markov clustering of RNA-Seq data

Count data were clustered using Biolayout Express^3D. Graph based network visualization with a Pearson correlation of above 0.7 and Markov clustering was carried out using Biolayout Express^3D (https://www.ebi.ac.uk/about/news/service-news/BioLayoutExpress3D). Markov clusters were visually inspected and extracted for display as a heatmap using the geneExpr (https://github.com/richysix/geneExpr) Shiny App (Fig 5).

Embryo and fin clip genotyping

Genotyping of embryos and fin clips was performed as previously described [39,40]. A schematic of all genes with the positions of their respected mutations can be found in S6 Fig. Previously unpublished alleles used in this study are listed in Table 3.

Table 3. New alleles used in this study.

Allele name	Pos(Assembly:Chr:Pos)	WT	MUT
cax1^sa10712	GRCz11:4:14984215	T	A
tfap2c^sa18857	GRCz11:6:56171775	G	T
tfap2a^sa24445	GRCz11:24:8725695	T	A
yap1^sa25474	GRCz11:18:37355128	AT	A
yap1^sa25458	GRCz11:18:37355126	TCATCGGCA	T
wu:fc46h12^sa30572	GRCz11:2:7638034	ATCAGGGTGAAGGTCAGCAGCAAT	A
akr1b1^sa30578	GRCz11:4:14901038	GTCCGGCTACCGGCACA	G

Open in a new tab

Zebrafish anatomy enrichment

Zebrafish anatomy enrichment is a similar approach to the widely used Gene Ontology enrichment but instead uses zebrafish anatomical terms linked to zebrafish genes. The enrichment is performed using ontologizer (http://ontologizer.de/) with the ontology from http://ontologies.berkeleybop.org/zfa.obo. ZFIN gene IDs are linked to ZFA terms using http://zfin.org/downloads/phenoGeneCleanData_fish.txt and http://zfin.org/downloads/wildtype-expression_fish.txt and Ensembl IDs are converted to ZFIN IDs using Ensembl. Ontologizer is then run with the Parent-Child-Union calculation and Bonferroni multiple testing correction.

RNA whole mount in situ hybridisation

RNA DIG-labelled probes were generated from cDNA libraries (Transcriptor High Fidelity cDNA Synthesis Kit, Roche) covering all relevant embryonic stages. PCR was performed and then TA cloned using TOPO-TA (Invitrogen). RNA riboprobes were produced using the T7- and SP6-promoter sequence, enabling in vitro transcription of the plasmid using T7- and SP6-RNA polymerase (Roche). All oligonucleotide sequences are listed here:

wu:fc46h12_left1:CTGCTGACCTTCACCCTGATTCTG, wu:fc46h12_right1:GGTGTATTGCCTAAAACCCTCAGC wu:fc46h12_left2:ATTGCTGCTGACCTTCACCCTGAT, wu:fc46h12_right2:ATTGCCTAAAACCCTCAGCTTCCA.

CRISPR/Cas9

Creation and identification of CRISPR/Cas9 zebrafish alleles were conducted as previously described using the zebrafish codon optimised double NLS Cas9 [85,41].

Supporting information

S1 Fig. Zebrafish anatomy enrichment of sox10 and mitfa mutant profiles across time.

ZFA enrichment was tested for all sox10 and mitfa mutants compared to wild-type siblings at all time points shown in Fig 1J but only time points at 24 hpf or later returned significantly enriched terms (adj. p-value <0.05).

(TIF)

Click here for additional data file.^{(498.9KB, tif)}

S2 Fig. RNA-seq transcriptomic analysis of tfap2a;tfap2c mutants at 15 somite stage.

(A) Principal component analysis of replicates of all 9 tfap2a;tfap2c genotypes showing the first two principal components. Dots represent a single embryo and genotype is denoted by colour. (B) Bars denote the numbers of genes for four most relevant pairwise combinations (adj. p-value <0.05) with the numbers of genes with a positive log₂ fold change in green (above the line) and negative in red (below the line). The specific genotypes of tfap2a and tfap2c are listed across the top for each bar. (C) A pairwise comparison of RNA-seq of tfap2a^-/-;tfap2c^-/- versus their wild-type siblings at 15 somites. The adj p-value is on the y-axis and the log₂ fold change on the x-axis. (D) Comparison of 3’ tag sequencing (y-axis) and RNA-seq (x-axis) log₂ fold change of genes with an adj p-value <0.01 in the tfap2a^-/-;tfap2c^-/- versus wild-type siblings pairwise comparison showing an overall linear correlation. (E) Heatmap of gene expression with an adj p-value <0.05 from tfap2a^-/-;tfap2c^-/- to wild-type siblings pairwise comparison. Genes are hierarchically clustered with the samples organised by genotype. ZFA enrichment analysis was carried out on clusters as indicated by the black boxes. ZFA enrichments with their corresponding significances are depicted on the right. ZFA terms were further broadly categorised into epidermis, neural crest and neuronal.

(TIF)

Click here for additional data file.^{(2.4MB, tif)}

S3 Fig. Enlargement of zebrafish anatomy enrichment from Fig 4H.

(TIF)

Click here for additional data file.^{(1.8MB, tif)}

S4 Fig. Examples of haplotype-specific signals from the tfap2a;tfap2c 15 somite RNA-seq data set.

(A, D, F) Markov clusters from BioLayout Express^3D expression analysis shown in Fig 5 A’ which contain genes linked to a specific region on a particular chromosome. A bar indicating the genotypes of the embryos is at the bottom. (A) A cluster of genes located on chromosome 24 linked to tfap2a. Genes behave in three groups depending on whether tfap2a is heterozygous, homozygous or wild type. A recombination has occurred in one embryo (circled in red) in the tfap2a homozygous group and that cluster of genes now behaves as the wild-type condition. (B) A list of genes and their chromosomal positions which make up the cluster in (A). (C) A karyotype map of chromosome 24 showing the location of tfap2a (blue arrow head right) and the positions of the genes contained in the cluster (red arrow heads left). (D) A cluster of genes on chromosome 15 where genes fall into two different groups, indicating one of the parents would have been heterozygous for the region. (E) A list of the genes contained in the cluster which are mostly on chromosome 15 and potentially two incorrectly mapped genes. (F-G) A third example of a haplotype-specific region located on chromosome 16 where both parents are presumably heterozygous for the region leading to three different groups.

(TIF)

Click here for additional data file.^{(1.2MB, tif)}

S5 Fig. Functional analysis of pigment cell-specific genes.

(A-H) Whole mount in situ analysis of wu:fc46h12 and gch2 as a pigment cell comparison. sox10^baz/+ heterozygotes embryos as sibling controls (A-B) and mutant sox10^baz1 embryos at 24 hpf (C-D). At 48 hpf in situs were carried out on albino embryos to serve as wild-type controls (E-F) with arrows indicating the heart and arrow heads the dorsal aorta. A blow up of this region can be found in E’-F’. (G-H) Expression of gch2 and wu:fc46h12 at 48 hpf in sox10^baz1 mutants. I-J Wild-type and MZwu:fc46h12^sa30587 embryos at 36 hpf with oedema around the forming heart (J). (K) Wild-type sibling and mutant akr1b1^sa30579 at 4 dpf with mutant larvae presenting a reduction of yellow colour produced by xanthophores. Magnifications indicated with a black box. (L) Wild-type sibling and mutant cax1^sa10712 larvae at 5 dpf. Close ups indicated by black boxes around the head show dull yellow colour and abnormal cell morphology in mutants (arrow head). (M) MZcax1^sa10712 phenotype at 19 somite stage.

(TIF)

Click here for additional data file.^{(5.3MB, tif)}

S6 Fig. Adult yap1 mutant fish are smaller than wild-type siblings.

(A) Homozygous yap1 mutants are viable but present with a variation in size. (B) Quantification of size at two months of age with the corresponding genotypes for both yap1 alleles. A statistically significant difference with p-val <0.05 is indicated by “*”.

(TIF)

Click here for additional data file.^{(2MB, tif)}

S7 Fig. Structure of genes and position of mutations used in this study.

Filled boxes represent coding sequence, unfilled ones denote untranslated regions.

(TIF)

Click here for additional data file.^{(344.9KB, tif)}

S1 Table. Complete list of ZFA enrichments from Fig 2F.

(TSV)

Click here for additional data file.^{(181KB, tsv)}

S2 Table. List of 26 genes from Fig 2F group 13.

(TXT)

Click here for additional data file.^{(826B, txt)}

S3 Table. Metadata IDs for all sequencing data.

(TXT)

Click here for additional data file.^{(57.8KB, txt)}

Acknowledgments

The authors would like to thank Robert Kelsh for sharing the sox10^t3 and sox10^baz1 mutants and Claudia Linker for the sox10:mg transgenic line. The authors would also like to thank Rob Cornell and lab for discussions about the project along the way. We are grateful to all current and past Vertebrate Genetics and Genomics group members for advice and help, and Catherine Scahill and Nicole Staudt for manuscript feedback. The authors would also like to thank Nicola Goodwin and the RSF as well as sequencing pipelines at the Wellcome Sanger Institute for their excellent support and zebrafish care.

Data Availability

The datasets supporting the conclusions of this article are available in ENA (https://www.ebi.ac.uk/ena). Accessions for all sequencing can be found in the S3 Table Sequence Archive Metadata.txt. DGE lists, clusters etc. described in this manuscript are deposited in a figshare collection (See Table 1).

Funding Statement

This work was supported by core funding to the Sanger Institute by the Wellcome Trust [098051 and 206194]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1.Gans C, Northcutt RG. Neural Crest and the Origin of Vertebrates: A New Head. Science. 1983;220: 268–273. 10.1126/science.220.4594.268 [DOI] [PubMed] [Google Scholar]
2.Hall BK. The neural crest and neural crest cells in vertebrate development and evolution 2nd ed. New York: Springer; 2009. [Google Scholar]
3.Le Douarin N, Kalcheim C. The neural crest 2. ed., digitally printed version. Cambridge: Cambridge Univ. Press; 2009. [Google Scholar]
4.Simoes-Costa M, Bronner ME. Reprogramming of avian neural crest axial identity and cell fate. Science. 2016;352: 1570–1573. 10.1126/science.aaf2729 [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Lukoseviciute M, Gavriouchkina D, Williams RM, Hochgreb-Hagele T, Senanayake U, Chong-Morrison V, et al. From Pioneer to Repressor: Bimodal foxd3 Activity Dynamically Remodels Neural Crest Regulatory Landscape In Vivo. Dev Cell. 2018;47: 608–628.e6. 10.1016/j.devcel.2018.11.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Meulemans D, Bronner-Fraser M. Gene-Regulatory Interactions in Neural Crest Evolution and Development. Dev Cell. 2004;7: 291–299. 10.1016/j.devcel.2004.08.007 [DOI] [PubMed] [Google Scholar]
7.Sauka-Spengler T, Meulemans D, Jones M, Bronner-Fraser M. Ancient Evolutionary Origin of the Neural Crest Gene Regulatory Network. Dev Cell. 2007;13: 405–420. 10.1016/j.devcel.2007.08.005 [DOI] [PubMed] [Google Scholar]
8.Barlow AJ, Dixon J, Dixon MJ, Trainor PA. Balancing neural crest cell intrinsic processes with those of the microenvironment in Tcof1 haploinsufficient mice enables complete enteric nervous system formation. Hum Mol Genet. 2012;21: 1782–1793. 10.1093/hmg/ddr611 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Simoes-Costa M, Bronner ME. Establishing neural crest identity: a gene regulatory recipe. Development. 2015;142: 242–257. 10.1242/dev.105445 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Green SA, Simoes-Costa M, Bronner ME. Evolution of vertebrates as viewed from the crest. Nature. 2015;520: 474–482. 10.1038/nature14436 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Milunsky JM, Maher TA, Zhao G, Roberts AE, Stalker HJ, Zori RT, et al. TFAP2A Mutations Result in Branchio-Oculo-Facial Syndrome. Am J Hum Genet. 2008;82: 1171–1177. 10.1016/j.ajhg.2008.03.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Schorle H, Meier P, Buchert M, Jaenisch R, Mitchell PJ. Transcription factor AP-2 essential for cranial closure and craniofacial development. Nature. 1996;381: 235–238. 10.1038/381235a0 [DOI] [PubMed] [Google Scholar]
13.Holzschuh J. Noradrenergic neurons in the zebrafish hindbrain are induced by retinoic acid and require tfap2a for expression of the neurotransmitter phenotype. Development. 2003;130: 5741–5754. 10.1242/dev.00816 [DOI] [PubMed] [Google Scholar]
14.Knight RD, Javidan Y, Nelson S, Zhang T, Schilling T. Skeletal and pigment cell defects in the lockjaw mutant reveal multiple roles for zebrafish tfap2a in neural crest development. Dev Dyn Off Publ Am Assoc Anat. 2004;229: 87–98. 10.1002/dvdy.10494 [DOI] [PubMed] [Google Scholar]
15.Barrallo-Gimeno A, Holzschuh J, Driever W, Knapik EW. Neural crest survival and differentiation in zebrafish depends on mont blanc/tfap2a gene function. Development. 2004;131: 1463–1477. 10.1242/dev.01033 [DOI] [PubMed] [Google Scholar]
16.Knight RD, Nair S, Nelson SS, Afshar A, Javidan Y, Geisler R, et al. lockjaw encodes a zebrafish tfap2a required for early neural crest development. Development. 2003;130: 5755–5768. 10.1242/dev.00575 [DOI] [PubMed] [Google Scholar]
17.Li W, Cornell RA. Redundant activities of Tfap2a and Tfap2c are required for neural crest induction and development of other non-neural ectoderm derivatives in zebrafish embryos. Dev Biol. 2007;304: 338–354. 10.1016/j.ydbio.2006.12.042 [DOI] [PMC free article] [PubMed] [Google Scholar]
18.O’Brien EK, d’Alençon C, Bonde G, Li W, Schoenebeck J, Allende ML, et al. Transcription factor Ap-2alpha is necessary for development of embryonic melanophores, autonomic neurons and pharyngeal skeleton in zebrafish. Dev Biol. 2004;265: 246–261. [DOI] [PubMed] [Google Scholar]
19.Van Otterloo E, Li W, Bonde G, Day KM, Hsu M-Y, Cornell RA. Differentiation of zebrafish melanophores depends on transcription factors AP2 alpha and AP2 epsilon. PLoS Genet. 2010;6: e1001122 10.1371/journal.pgen.1001122 [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Van Otterloo E, Li W, Garnett A, Cattell M, Medeiros DM, Cornell RA. Novel Tfap2-mediated control of soxE expression facilitated the evolutionary emergence of the neural crest. Development. 2012;139: 720–730. 10.1242/dev.071308 [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Hilger-Eversheim K, Moser M, Schorle H, Buettner R. Regulatory roles of AP-2 transcription factors in vertebrate development, apoptosis and cell-cycle control. Gene. 2000;260: 1–12. 10.1016/S0378-1119(00)00454-6 [DOI] [PubMed] [Google Scholar]
22.Uhlen M, Zhang C, Lee S, Sjöstedt E, Fagerberg L, Bidkhori G, et al. A pathology atlas of the human cancer transcriptome. Science. 2017;357: eaan2507 10.1126/science.aan2507 [DOI] [PubMed] [Google Scholar]
23.Pingault V, Bondurand N, Kuhlbrodt K, Goerich DE, Préhu M-O, Puliti A, et al. SOX10 mutations in patients with Waardenburg-Hirschsprung disease. Nat Genet. 1998;18: 171–173. 10.1038/ng0298-171 [DOI] [PubMed] [Google Scholar]
24.Waardenburg PJ. A new syndrome combining developmental anomalies of the eyelids, eyebrows and nose root with pigmentary defects of the iris and head hair and with congenital deafness. Am J Hum Genet. 1951;3: 195–253. [PMC free article] [PubMed] [Google Scholar]
25.Dutton KA, Pauliny A, Lopes SS, Elworthy S, Carney TJ, Rauch J, et al. Zebrafish colourless encodes sox10 and specifies non-ectomesenchymal neural crest fates. Development. 2001;128: 4113–4125. [DOI] [PubMed] [Google Scholar]
26.Dooley CM, Mongera A, Walderich B, Nüsslein-Volhard C. On the embryonic origin of adult melanophores: the role of ErbB and Kit signalling in establishing melanophore stem cells in zebrafish. Development. 2013;140: 1003–1013. 10.1242/dev.087007 [DOI] [PubMed] [Google Scholar]
27.Carney TJ, Dutton KA, Greenhill E, Delfino-Machin M, Dufourcq P, Blader P, et al. A direct role for Sox10 in specification of neural crest-derived sensory neurons. Development. 2006;133: 4619–4630. 10.1242/dev.02668 [DOI] [PubMed] [Google Scholar]
28.Herbarth B, Pingault V, Bondurand N, Kuhlbrodt K, Hermans-Borgmeyer I, Puliti A, et al. Mutation of the Sry-related Sox10 gene in Dominant megacolon, a mouse model for human Hirschsprung disease. Proc Natl Acad Sci U S A. 1998;95: 5161–5165. 10.1073/pnas.95.9.5161 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Kuhlbrodt K, Herbarth B, Sock E, Hermans-Borgmeyer I, Wegner M. Sox10, a novel transcriptional modulator in glial cells. J Neurosci Off J Soc Neurosci. 1998;18: 237–250. [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Pusch C, Hustert E, Pfeifer D, Südbeck P, Kist R, Roe B, et al. The SOX10/Sox10 gene from human and mouse: sequence, expression, and transactivation by the encoded HMG domain transcription factor. Hum Genet. 1998;103: 115–123. [DOI] [PubMed] [Google Scholar]
31.Kelsh RN, Brand M, Jiang YJ, Heisenberg CP, Lin S, Haffter P, et al. Zebrafish pigmentation mutations and the processes of neural crest development. Development. 1996;123: 369–389. [DOI] [PubMed] [Google Scholar]
32.Cheung M, Briscoe J. Neural crest development is regulated by the transcription factor Sox9. Development. 2003;130: 5681–5693. 10.1242/dev.00808 [DOI] [PubMed] [Google Scholar]
33.Yan Y-L, Willoughby J, Liu D, Crump JG, Wilson C, Miller CT, et al. A pair of Sox: distinct and overlapping functions of zebrafish sox9 co-orthologs in craniofacial and pectoral fin development. Development. 2005;132: 1069–1083. 10.1242/dev.01674 [DOI] [PubMed] [Google Scholar]
34.Lister JA, Robertson CP, Lepage T, Johnson SL, Raible DW. nacre encodes a zebrafish microphthalmia-related protein that regulates neural-crest-derived pigment cell fate. Development. 1999;126: 3757–3767. [DOI] [PubMed] [Google Scholar]
35.Martik ML, Bronner ME. Regulatory Logic Underlying Diversification of the Neural Crest. Trends Genet. 2017;33: 715–727. 10.1016/j.tig.2017.07.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Sauka-Spengler T, Bronner-Fraser M. A gene regulatory network orchestrates neural crest formation. Nat Rev Mol Cell Biol. 2008;9: 557–568. 10.1038/nrm2428 [DOI] [PubMed] [Google Scholar]
37.Betancur P, Bronner-Fraser M, Sauka-Spengler T. Assembling neural crest regulatory circuits into a gene regulatory network. Annu Rev Cell Dev Biol. 2010;26: 581–603. 10.1146/annurev.cellbio.042308.113245 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Rada-Iglesias A, Bajpai R, Prescott S, Brugmann SA, Swigut T, Wysocka J. Epigenomic Annotation of Enhancers Predicts Transcriptional Regulators of Human Neural Crest. Cell Stem Cell. 2012;11: 633–648. 10.1016/j.stem.2012.07.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Kettleborough RNW, Busch-Nentwich EM, Harvey SA, Dooley CM, de Bruijn E, van Eeden F, et al. A systematic genome-wide analysis of zebrafish protein-coding gene function. Nature. 2013;496: 494–497. 10.1038/nature11992 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Dooley CM, Scahill C, Fényes F, Kettleborough RNW, Stemple DL, Busch-Nentwich EM. Multi-allelic phenotyping—a systematic approach for the simultaneous analysis of multiple induced mutations. Methods San Diego Calif. 2013;62: 197–206. 10.1016/j.ymeth.2013.04.013 [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Brocal I, White RJ, Dooley CM, Carruthers SN, Clark R, Hall A, et al. Efficient identification of CRISPR/Cas9-induced insertions/deletions by direct germline screening in zebrafish. BMC Genomics. 2016;17: 259 10.1186/s12864-016-2563-z [DOI] [PMC free article] [PubMed] [Google Scholar]
42.White RJ, Collins JE, Sealy IM, Wali N, Dooley CM, Digby Z, et al. A high-resolution mRNA expression time course of embryonic development in zebrafish. eLife. 2017;6 10.7554/eLife.30860 [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Newport J, Kirschner M. A major developmental transition in early Xenopus embryos: II. Control of the onset of transcription. Cell. 1982;30: 687–696. [DOI] [PubMed] [Google Scholar]
44.Schier AF. The Maternal-Zygotic Transition: Death and Birth of RNAs. Science. 2007;316: 406–407. 10.1126/science.1140693 [DOI] [PubMed] [Google Scholar]
45.Tadros W, Lipshitz HD. The maternal-to-zygotic transition: a play in two acts. Development. 2009;136: 3033–3042. 10.1242/dev.033183 [DOI] [PubMed] [Google Scholar]
46.Kwon H-J, Bhat N, Sweet EM, Cornell RA, Riley BB. Identification of Early Requirements for Preplacodal Ectoderm and Sensory Organ Development. Mullins MC, editor. PLoS Genet. 2010;6: e1001133 10.1371/journal.pgen.1001133 [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Thisse B, Thisse C. Fast Release Clones: A High Throughput Expression Analysis. ZFIN Direct Data Submission. [Internet]. ZFIN; 2004. Available: http://zfin.org [Google Scholar]
48.Richardson J, Gauert A, Briones Montecinos L, Fanlo L, Alhashem ZM, Assar R, et al. Leader Cells Define Directionality of Trunk, but Not Cranial, Neural Crest Cell Migration. Cell Rep. 2016;15: 2076–2088. 10.1016/j.celrep.2016.04.067 [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Seberg HE, Van Otterloo E, Loftus SK, Liu H, Bonde G, Sompallae R, et al. TFAP2 paralogs regulate melanocyte differentiation in parallel with MITF. PLoS Genet. 2017;13: e1006636 10.1371/journal.pgen.1006636 [DOI] [PMC free article] [PubMed] [Google Scholar]
50.Collins JE, Wali N, Sealy IM, Morris JA, White RJ, Leonard SR, et al. High-throughput and quantitative genome-wide messenger RNA sequencing for molecular phenotyping. BMC Genomics. 2015;16 10.1186/s12864-015-1788-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Saha A, Battle A. False positives in trans-eQTL and co-expression analyses arising from RNA-sequencing alignment errors. F1000Research. 2018;7: 1860 10.12688/f1000research.17145.2 [DOI] [PMC free article] [PubMed] [Google Scholar]
52.Knight JC. Allele-specific gene expression uncovered. Trends Genet. 2004;20: 113–116. 10.1016/j.tig.2004.01.001 [DOI] [PubMed] [Google Scholar]
53.Lex A, Gehlenborg N, Strobelt H, Vuillemot R, Pfister H. UpSet: Visualization of Intersecting Sets. IEEE Trans Vis Comput Graph. 2014;20: 1983–1992. 10.1109/TVCG.2014.2346248 [DOI] [PMC free article] [PubMed] [Google Scholar]
54.Leask A, Byrne C, Fuchs E. Transcription factor AP2 and its role in epidermal-specific gene expression. Proc Natl Acad Sci U S A. 1991;88: 7948–7952. 10.1073/pnas.88.18.7948 [DOI] [PMC free article] [PubMed] [Google Scholar]
55.Pieper M, Ahrens K, Rink E, Peter A, Schlosser G. Differential distribution of competence for panplacodal and neural crest induction to non-neural and neural ectoderm. Development. 2012;139: 1175–1187. 10.1242/dev.074468 [DOI] [PubMed] [Google Scholar]
56.Wittkopp N, Huntzinger E, Weiler C, Saulière J, Schmidt S, Sonawane M, et al. Nonsense-mediated mRNA decay effectors are essential for zebrafish embryonic development and survival. Mol Cell Biol. 2009;29: 3517–3528. 10.1128/MCB.00177-09 [DOI] [PMC free article] [PubMed] [Google Scholar]
57.Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010;38: 576–589. 10.1016/j.molcel.2010.05.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
58.Tian W, Yu J, Tomchick DR, Pan D, Luo X. Structural and functional analysis of the YAP-binding domain of human TEAD2. Proc Natl Acad Sci U S A. 2010;107: 7293–7298. 10.1073/pnas.1000293107 [DOI] [PMC free article] [PubMed] [Google Scholar]
59.Ota M, Sasaki H. Mammalian Tead proteins regulate cell proliferation and contact inhibition as transcriptional mediators of Hippo signaling. Dev Camb Engl. 2008;135: 4059–4069. 10.1242/dev.027151 [DOI] [PubMed] [Google Scholar]
60.Enright AJ, Ouzounis CA. BioLayout—an automatic graph layout algorithm for similarity visualization. Bioinforma Oxf Engl. 2001;17: 853–854. [DOI] [PubMed] [Google Scholar]
61.Theocharidis A, van Dongen S, Enright AJ, Freeman TC. Network visualization and analysis of gene expression data using BioLayout Express(3D). Nat Protoc. 2009;4: 1535–1550. 10.1038/nprot.2009.177 [DOI] [PubMed] [Google Scholar]
62.Manohar M, Mei H, Franklin AJ, Sweet EM, Shigaki T, Riley BB, et al. Zebrafish (Danio rerio) endomembrane antiporter similar to a yeast cation/H(+) transporter is required for neural crest development. Biochemistry. 2010;49: 6557–6566. 10.1021/bi100362k [DOI] [PubMed] [Google Scholar]
63.Manderfield LJ, Engleka KA, Aghajanian H, Gupta M, Yang S, Li L, et al. Pax3 and hippo signaling coordinate melanocyte gene expression in neural crest. Cell Rep. 2014;9: 1885–1895. 10.1016/j.celrep.2014.10.061 [DOI] [PMC free article] [PubMed] [Google Scholar]
64.Hindley CJ, Condurat AL, Menon V, Thomas R, Azmitia LM, Davis JA, et al. The Hippo pathway member YAP enhances human neural crest cell fate and migration. Sci Rep. 2016;6: 23208 10.1038/srep23208 [DOI] [PMC free article] [PubMed] [Google Scholar]
65.Miesfeld JB, Gestri G, Clark BS, Flinn MA, Poole RJ, Bader JR, et al. Yap and Taz regulate retinal pigment epithelial cell fate. Development. 2015;142: 3021–3032. 10.1242/dev.119008 [DOI] [PMC free article] [PubMed] [Google Scholar]
66.Agarwala S, Duquesne S, Liu K, Boehm A, Grimm L, Link S, et al. Amotl2a interacts with the Hippo effector Yap1 and the Wnt/β-catenin effector Lef1 to control tissue size in zebrafish. eLife. 2015;4: e08201 10.7554/eLife.08201 [DOI] [PMC free article] [PubMed] [Google Scholar]
67.Kimelman D, Smith NL, Lai JKH, Stainier DY. Regulation of posterior body and epidermal morphogenesis in zebrafish by localized Yap1 and Wwtr1. eLife. 2017;6 10.7554/eLife.31065 [DOI] [PMC free article] [PubMed] [Google Scholar]
68.Porazinski S, Wang H, Asaoka Y, Behrndt M, Miyamoto T, Morita H, et al. YAP is essential for tissue tension to ensure vertebrate 3D body shape. Nature. 2015;521: 217–221. 10.1038/nature14215 [DOI] [PMC free article] [PubMed] [Google Scholar]
69.Trinh LA, Chong-Morrison V, Gavriouchkina D, Hochgreb-Hägele T, Senanayake U, Fraser SE, et al. Biotagging of Specific Cell Populations in Zebrafish Reveals Gene Regulatory Logic Encoded in the Nuclear Transcriptome. Cell Rep. 2017;19: 425–440. 10.1016/j.celrep.2017.03.045 [DOI] [PMC free article] [PubMed] [Google Scholar]
70.Arduini BL, Bosse KM, Henion PD. Genetic ablation of neural crest cell diversification. Development. 2009;136: 1987–1994. 10.1242/dev.033209 [DOI] [PMC free article] [PubMed] [Google Scholar]
71.Wang W-D, Melville DB, Montero-Balaguer M, Hatzopoulos AK, Knapik EW. Tfap2a and Foxd3 regulate early steps in the development of the neural crest progenitor population. Dev Biol. 2011;360: 173–185. 10.1016/j.ydbio.2011.09.019 [DOI] [PMC free article] [PubMed] [Google Scholar]
72.Buitrago-Delgado E, Nordin K, Rao A, Geary L, LaBonne C. Shared regulatory programs suggest retention of blastula-stage potential in neural crest cells. Science. 2015;348: 1332–1335. 10.1126/science.aaa3655 [DOI] [PMC free article] [PubMed] [Google Scholar]
73.Briggs JA, Weinreb C, Wagner DE, Megason S, Peshkin L, Kirschner MW, et al. The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution. Science. 2018; 10.1126/science.aar5780 [DOI] [PMC free article] [PubMed] [Google Scholar]
74.Williams T, Tjian R. Analysis of the DNA-binding and activation properties of the human transcription factor AP-2. Genes Dev. 1991;5: 670–682. 10.1101/gad.5.4.670 [DOI] [PubMed] [Google Scholar]
75.de Crozé N, Maczkowiak F, Monsoro-Burq AH. Reiterative AP2a activity controls sequential steps in the neural crest gene regulatory network. Proc Natl Acad Sci U S A. 2011;108: 155–160. 10.1073/pnas.1010740107 [DOI] [PMC free article] [PubMed] [Google Scholar]
76.Pingault V, Ente D, Dastot-Le Moal F, Goossens M, Marlin S, Bondurand N. Review and update of mutations causing Waardenburg syndrome. Hum Mutat. 2010;31: 391–406. 10.1002/humu.21211 [DOI] [PubMed] [Google Scholar]
77.Haffter P, Granato M, Brand M, Mullins MC, Hammerschmidt M, Kane DA, et al. The identification of genes with unique and essential functions in the development of the zebrafish, Danio rerio. Dev Camb Engl. 1996;123: 1–36. [DOI] [PubMed] [Google Scholar]
78.Driever W, Solnica-Krezel L, Schier AF, Neuhauss SC, Malicki J, Stemple DL, et al. A genetic screen for mutations affecting embryogenesis in zebrafish. Development. 1996;123: 37–46. [DOI] [PubMed] [Google Scholar]
79.Kok FO, Shin M, Ni C-W, Gupta A, Grosse AS, van Impel A, et al. Reverse genetic screening reveals poor correlation between morpholino-induced and mutant phenotypes in zebrafish. Dev Cell. 2015;32: 97–108. 10.1016/j.devcel.2014.11.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
80.Wang J, Xiao Y, Hsu C-W, Martinez-Traverso IM, Zhang M, Bai Y, et al. Yap and Taz play a crucial role in neural crest-derived craniofacial development. Development. 2016;143: 504–515. 10.1242/dev.126920 [DOI] [PMC free article] [PubMed] [Google Scholar]
81.Nallet-Staub F, Marsaud V, Li L, Gilbert C, Dodier S, Bataille V, et al. Pro-invasive activity of the Hippo pathway effectors YAP and TAZ in cutaneous melanoma. J Invest Dermatol. 2014;134: 123–132. 10.1038/jid.2013.319 [DOI] [PMC free article] [PubMed] [Google Scholar]
82.Adameyko I, Lallemend F, Aquino JB, Pereira JA, Topilko P, Müller T, et al. Schwann Cell Precursors from Nerve Innervation Are a Cellular Origin of Melanocytes in Skin. Cell. 2009;139: 366–379. 10.1016/j.cell.2009.07.049 [DOI] [PubMed] [Google Scholar]
83.Budi EH, Patterson LB, Parichy DM. Post-Embryonic Nerve-Associated Precursors to Adult Pigment Cells: Genetic Requirements and Dynamics of Morphogenesis and Differentiation. Barsh GS, editor. PLoS Genet. 2011;7: e1002044 10.1371/journal.pgen.1002044 [DOI] [PMC free article] [PubMed] [Google Scholar]
84.Westerfield M. The Zebrafish Book: A Guide for Laboratory Use of Zebrafish (Danio Rerio)—See more at: http://elifesciences.org/content/5/e11813#ref-80. 4th ed. Eugene, USA: University of Oregon Press; 2000. [Google Scholar]
85.Jao L-E, Wente SR, Chen W. Efficient multiplex biallelic zebrafish genome editing using a CRISPR nuclease system. Proc Natl Acad Sci. 2013;110: 13904–13909. 10.1073/pnas.1308335110 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. Zebrafish anatomy enrichment of sox10 and mitfa mutant profiles across time.

(TIF)

Click here for additional data file.^{(498.9KB, tif)}

S2 Fig. RNA-seq transcriptomic analysis of tfap2a;tfap2c mutants at 15 somite stage.

(TIF)

Click here for additional data file.^{(2.4MB, tif)}

S3 Fig. Enlargement of zebrafish anatomy enrichment from Fig 4H.

(TIF)

Click here for additional data file.^{(1.8MB, tif)}

S4 Fig. Examples of haplotype-specific signals from the tfap2a;tfap2c 15 somite RNA-seq data set.

(TIF)

Click here for additional data file.^{(1.2MB, tif)}

S5 Fig. Functional analysis of pigment cell-specific genes.

(TIF)

Click here for additional data file.^{(5.3MB, tif)}

S6 Fig. Adult yap1 mutant fish are smaller than wild-type siblings.

(TIF)

Click here for additional data file.^{(2MB, tif)}

S7 Fig. Structure of genes and position of mutations used in this study.

Filled boxes represent coding sequence, unfilled ones denote untranslated regions.

(TIF)

Click here for additional data file.^{(344.9KB, tif)}

S1 Table. Complete list of ZFA enrichments from Fig 2F.

(TSV)

Click here for additional data file.^{(181KB, tsv)}

S2 Table. List of 26 genes from Fig 2F group 13.

(TXT)

Click here for additional data file.^{(826B, txt)}

S3 Table. Metadata IDs for all sequencing data.

(TXT)

Click here for additional data file.^{(57.8KB, txt)}

Data Availability Statement

[pgen.1008213.ref001] 1.Gans C, Northcutt RG. Neural Crest and the Origin of Vertebrates: A New Head. Science. 1983;220: 268–273. 10.1126/science.220.4594.268 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref002] 2.Hall BK. The neural crest and neural crest cells in vertebrate development and evolution 2nd ed. New York: Springer; 2009. [Google Scholar]

[pgen.1008213.ref003] 3.Le Douarin N, Kalcheim C. The neural crest 2. ed., digitally printed version. Cambridge: Cambridge Univ. Press; 2009. [Google Scholar]

[pgen.1008213.ref004] 4.Simoes-Costa M, Bronner ME. Reprogramming of avian neural crest axial identity and cell fate. Science. 2016;352: 1570–1573. 10.1126/science.aaf2729 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref005] 5.Lukoseviciute M, Gavriouchkina D, Williams RM, Hochgreb-Hagele T, Senanayake U, Chong-Morrison V, et al. From Pioneer to Repressor: Bimodal foxd3 Activity Dynamically Remodels Neural Crest Regulatory Landscape In Vivo. Dev Cell. 2018;47: 608–628.e6. 10.1016/j.devcel.2018.11.009 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref006] 6.Meulemans D, Bronner-Fraser M. Gene-Regulatory Interactions in Neural Crest Evolution and Development. Dev Cell. 2004;7: 291–299. 10.1016/j.devcel.2004.08.007 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref007] 7.Sauka-Spengler T, Meulemans D, Jones M, Bronner-Fraser M. Ancient Evolutionary Origin of the Neural Crest Gene Regulatory Network. Dev Cell. 2007;13: 405–420. 10.1016/j.devcel.2007.08.005 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref008] 8.Barlow AJ, Dixon J, Dixon MJ, Trainor PA. Balancing neural crest cell intrinsic processes with those of the microenvironment in Tcof1 haploinsufficient mice enables complete enteric nervous system formation. Hum Mol Genet. 2012;21: 1782–1793. 10.1093/hmg/ddr611 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref009] 9.Simoes-Costa M, Bronner ME. Establishing neural crest identity: a gene regulatory recipe. Development. 2015;142: 242–257. 10.1242/dev.105445 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref010] 10.Green SA, Simoes-Costa M, Bronner ME. Evolution of vertebrates as viewed from the crest. Nature. 2015;520: 474–482. 10.1038/nature14436 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref011] 11.Milunsky JM, Maher TA, Zhao G, Roberts AE, Stalker HJ, Zori RT, et al. TFAP2A Mutations Result in Branchio-Oculo-Facial Syndrome. Am J Hum Genet. 2008;82: 1171–1177. 10.1016/j.ajhg.2008.03.005 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref012] 12.Schorle H, Meier P, Buchert M, Jaenisch R, Mitchell PJ. Transcription factor AP-2 essential for cranial closure and craniofacial development. Nature. 1996;381: 235–238. 10.1038/381235a0 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref013] 13.Holzschuh J. Noradrenergic neurons in the zebrafish hindbrain are induced by retinoic acid and require tfap2a for expression of the neurotransmitter phenotype. Development. 2003;130: 5741–5754. 10.1242/dev.00816 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref014] 14.Knight RD, Javidan Y, Nelson S, Zhang T, Schilling T. Skeletal and pigment cell defects in the lockjaw mutant reveal multiple roles for zebrafish tfap2a in neural crest development. Dev Dyn Off Publ Am Assoc Anat. 2004;229: 87–98. 10.1002/dvdy.10494 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref015] 15.Barrallo-Gimeno A, Holzschuh J, Driever W, Knapik EW. Neural crest survival and differentiation in zebrafish depends on mont blanc/tfap2a gene function. Development. 2004;131: 1463–1477. 10.1242/dev.01033 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref016] 16.Knight RD, Nair S, Nelson SS, Afshar A, Javidan Y, Geisler R, et al. lockjaw encodes a zebrafish tfap2a required for early neural crest development. Development. 2003;130: 5755–5768. 10.1242/dev.00575 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref017] 17.Li W, Cornell RA. Redundant activities of Tfap2a and Tfap2c are required for neural crest induction and development of other non-neural ectoderm derivatives in zebrafish embryos. Dev Biol. 2007;304: 338–354. 10.1016/j.ydbio.2006.12.042 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref018] 18.O’Brien EK, d’Alençon C, Bonde G, Li W, Schoenebeck J, Allende ML, et al. Transcription factor Ap-2alpha is necessary for development of embryonic melanophores, autonomic neurons and pharyngeal skeleton in zebrafish. Dev Biol. 2004;265: 246–261. [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref019] 19.Van Otterloo E, Li W, Bonde G, Day KM, Hsu M-Y, Cornell RA. Differentiation of zebrafish melanophores depends on transcription factors AP2 alpha and AP2 epsilon. PLoS Genet. 2010;6: e1001122 10.1371/journal.pgen.1001122 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref020] 20.Van Otterloo E, Li W, Garnett A, Cattell M, Medeiros DM, Cornell RA. Novel Tfap2-mediated control of soxE expression facilitated the evolutionary emergence of the neural crest. Development. 2012;139: 720–730. 10.1242/dev.071308 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref021] 21.Hilger-Eversheim K, Moser M, Schorle H, Buettner R. Regulatory roles of AP-2 transcription factors in vertebrate development, apoptosis and cell-cycle control. Gene. 2000;260: 1–12. 10.1016/S0378-1119(00)00454-6 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref022] 22.Uhlen M, Zhang C, Lee S, Sjöstedt E, Fagerberg L, Bidkhori G, et al. A pathology atlas of the human cancer transcriptome. Science. 2017;357: eaan2507 10.1126/science.aan2507 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref023] 23.Pingault V, Bondurand N, Kuhlbrodt K, Goerich DE, Préhu M-O, Puliti A, et al. SOX10 mutations in patients with Waardenburg-Hirschsprung disease. Nat Genet. 1998;18: 171–173. 10.1038/ng0298-171 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref024] 24.Waardenburg PJ. A new syndrome combining developmental anomalies of the eyelids, eyebrows and nose root with pigmentary defects of the iris and head hair and with congenital deafness. Am J Hum Genet. 1951;3: 195–253. [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref025] 25.Dutton KA, Pauliny A, Lopes SS, Elworthy S, Carney TJ, Rauch J, et al. Zebrafish colourless encodes sox10 and specifies non-ectomesenchymal neural crest fates. Development. 2001;128: 4113–4125. [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref026] 26.Dooley CM, Mongera A, Walderich B, Nüsslein-Volhard C. On the embryonic origin of adult melanophores: the role of ErbB and Kit signalling in establishing melanophore stem cells in zebrafish. Development. 2013;140: 1003–1013. 10.1242/dev.087007 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref027] 27.Carney TJ, Dutton KA, Greenhill E, Delfino-Machin M, Dufourcq P, Blader P, et al. A direct role for Sox10 in specification of neural crest-derived sensory neurons. Development. 2006;133: 4619–4630. 10.1242/dev.02668 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref028] 28.Herbarth B, Pingault V, Bondurand N, Kuhlbrodt K, Hermans-Borgmeyer I, Puliti A, et al. Mutation of the Sry-related Sox10 gene in Dominant megacolon, a mouse model for human Hirschsprung disease. Proc Natl Acad Sci U S A. 1998;95: 5161–5165. 10.1073/pnas.95.9.5161 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref029] 29.Kuhlbrodt K, Herbarth B, Sock E, Hermans-Borgmeyer I, Wegner M. Sox10, a novel transcriptional modulator in glial cells. J Neurosci Off J Soc Neurosci. 1998;18: 237–250. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref030] 30.Pusch C, Hustert E, Pfeifer D, Südbeck P, Kist R, Roe B, et al. The SOX10/Sox10 gene from human and mouse: sequence, expression, and transactivation by the encoded HMG domain transcription factor. Hum Genet. 1998;103: 115–123. [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref031] 31.Kelsh RN, Brand M, Jiang YJ, Heisenberg CP, Lin S, Haffter P, et al. Zebrafish pigmentation mutations and the processes of neural crest development. Development. 1996;123: 369–389. [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref032] 32.Cheung M, Briscoe J. Neural crest development is regulated by the transcription factor Sox9. Development. 2003;130: 5681–5693. 10.1242/dev.00808 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref033] 33.Yan Y-L, Willoughby J, Liu D, Crump JG, Wilson C, Miller CT, et al. A pair of Sox: distinct and overlapping functions of zebrafish sox9 co-orthologs in craniofacial and pectoral fin development. Development. 2005;132: 1069–1083. 10.1242/dev.01674 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref034] 34.Lister JA, Robertson CP, Lepage T, Johnson SL, Raible DW. nacre encodes a zebrafish microphthalmia-related protein that regulates neural-crest-derived pigment cell fate. Development. 1999;126: 3757–3767. [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref035] 35.Martik ML, Bronner ME. Regulatory Logic Underlying Diversification of the Neural Crest. Trends Genet. 2017;33: 715–727. 10.1016/j.tig.2017.07.015 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref036] 36.Sauka-Spengler T, Bronner-Fraser M. A gene regulatory network orchestrates neural crest formation. Nat Rev Mol Cell Biol. 2008;9: 557–568. 10.1038/nrm2428 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref037] 37.Betancur P, Bronner-Fraser M, Sauka-Spengler T. Assembling neural crest regulatory circuits into a gene regulatory network. Annu Rev Cell Dev Biol. 2010;26: 581–603. 10.1146/annurev.cellbio.042308.113245 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref038] 38.Rada-Iglesias A, Bajpai R, Prescott S, Brugmann SA, Swigut T, Wysocka J. Epigenomic Annotation of Enhancers Predicts Transcriptional Regulators of Human Neural Crest. Cell Stem Cell. 2012;11: 633–648. 10.1016/j.stem.2012.07.006 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref039] 39.Kettleborough RNW, Busch-Nentwich EM, Harvey SA, Dooley CM, de Bruijn E, van Eeden F, et al. A systematic genome-wide analysis of zebrafish protein-coding gene function. Nature. 2013;496: 494–497. 10.1038/nature11992 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref040] 40.Dooley CM, Scahill C, Fényes F, Kettleborough RNW, Stemple DL, Busch-Nentwich EM. Multi-allelic phenotyping—a systematic approach for the simultaneous analysis of multiple induced mutations. Methods San Diego Calif. 2013;62: 197–206. 10.1016/j.ymeth.2013.04.013 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref041] 41.Brocal I, White RJ, Dooley CM, Carruthers SN, Clark R, Hall A, et al. Efficient identification of CRISPR/Cas9-induced insertions/deletions by direct germline screening in zebrafish. BMC Genomics. 2016;17: 259 10.1186/s12864-016-2563-z [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref042] 42.White RJ, Collins JE, Sealy IM, Wali N, Dooley CM, Digby Z, et al. A high-resolution mRNA expression time course of embryonic development in zebrafish. eLife. 2017;6 10.7554/eLife.30860 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref043] 43.Newport J, Kirschner M. A major developmental transition in early Xenopus embryos: II. Control of the onset of transcription. Cell. 1982;30: 687–696. [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref044] 44.Schier AF. The Maternal-Zygotic Transition: Death and Birth of RNAs. Science. 2007;316: 406–407. 10.1126/science.1140693 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref045] 45.Tadros W, Lipshitz HD. The maternal-to-zygotic transition: a play in two acts. Development. 2009;136: 3033–3042. 10.1242/dev.033183 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref046] 46.Kwon H-J, Bhat N, Sweet EM, Cornell RA, Riley BB. Identification of Early Requirements for Preplacodal Ectoderm and Sensory Organ Development. Mullins MC, editor. PLoS Genet. 2010;6: e1001133 10.1371/journal.pgen.1001133 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref047] 47.Thisse B, Thisse C. Fast Release Clones: A High Throughput Expression Analysis. ZFIN Direct Data Submission. [Internet]. ZFIN; 2004. Available: http://zfin.org [Google Scholar]

[pgen.1008213.ref048] 48.Richardson J, Gauert A, Briones Montecinos L, Fanlo L, Alhashem ZM, Assar R, et al. Leader Cells Define Directionality of Trunk, but Not Cranial, Neural Crest Cell Migration. Cell Rep. 2016;15: 2076–2088. 10.1016/j.celrep.2016.04.067 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref049] 49.Seberg HE, Van Otterloo E, Loftus SK, Liu H, Bonde G, Sompallae R, et al. TFAP2 paralogs regulate melanocyte differentiation in parallel with MITF. PLoS Genet. 2017;13: e1006636 10.1371/journal.pgen.1006636 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref050] 50.Collins JE, Wali N, Sealy IM, Morris JA, White RJ, Leonard SR, et al. High-throughput and quantitative genome-wide messenger RNA sequencing for molecular phenotyping. BMC Genomics. 2015;16 10.1186/s12864-015-1788-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref051] 51.Saha A, Battle A. False positives in trans-eQTL and co-expression analyses arising from RNA-sequencing alignment errors. F1000Research. 2018;7: 1860 10.12688/f1000research.17145.2 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref052] 52.Knight JC. Allele-specific gene expression uncovered. Trends Genet. 2004;20: 113–116. 10.1016/j.tig.2004.01.001 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref053] 53.Lex A, Gehlenborg N, Strobelt H, Vuillemot R, Pfister H. UpSet: Visualization of Intersecting Sets. IEEE Trans Vis Comput Graph. 2014;20: 1983–1992. 10.1109/TVCG.2014.2346248 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref054] 54.Leask A, Byrne C, Fuchs E. Transcription factor AP2 and its role in epidermal-specific gene expression. Proc Natl Acad Sci U S A. 1991;88: 7948–7952. 10.1073/pnas.88.18.7948 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref055] 55.Pieper M, Ahrens K, Rink E, Peter A, Schlosser G. Differential distribution of competence for panplacodal and neural crest induction to non-neural and neural ectoderm. Development. 2012;139: 1175–1187. 10.1242/dev.074468 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref056] 56.Wittkopp N, Huntzinger E, Weiler C, Saulière J, Schmidt S, Sonawane M, et al. Nonsense-mediated mRNA decay effectors are essential for zebrafish embryonic development and survival. Mol Cell Biol. 2009;29: 3517–3528. 10.1128/MCB.00177-09 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref057] 57.Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010;38: 576–589. 10.1016/j.molcel.2010.05.004 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref058] 58.Tian W, Yu J, Tomchick DR, Pan D, Luo X. Structural and functional analysis of the YAP-binding domain of human TEAD2. Proc Natl Acad Sci U S A. 2010;107: 7293–7298. 10.1073/pnas.1000293107 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref059] 59.Ota M, Sasaki H. Mammalian Tead proteins regulate cell proliferation and contact inhibition as transcriptional mediators of Hippo signaling. Dev Camb Engl. 2008;135: 4059–4069. 10.1242/dev.027151 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref060] 60.Enright AJ, Ouzounis CA. BioLayout—an automatic graph layout algorithm for similarity visualization. Bioinforma Oxf Engl. 2001;17: 853–854. [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref061] 61.Theocharidis A, van Dongen S, Enright AJ, Freeman TC. Network visualization and analysis of gene expression data using BioLayout Express(3D). Nat Protoc. 2009;4: 1535–1550. 10.1038/nprot.2009.177 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref062] 62.Manohar M, Mei H, Franklin AJ, Sweet EM, Shigaki T, Riley BB, et al. Zebrafish (Danio rerio) endomembrane antiporter similar to a yeast cation/H(+) transporter is required for neural crest development. Biochemistry. 2010;49: 6557–6566. 10.1021/bi100362k [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref063] 63.Manderfield LJ, Engleka KA, Aghajanian H, Gupta M, Yang S, Li L, et al. Pax3 and hippo signaling coordinate melanocyte gene expression in neural crest. Cell Rep. 2014;9: 1885–1895. 10.1016/j.celrep.2014.10.061 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref064] 64.Hindley CJ, Condurat AL, Menon V, Thomas R, Azmitia LM, Davis JA, et al. The Hippo pathway member YAP enhances human neural crest cell fate and migration. Sci Rep. 2016;6: 23208 10.1038/srep23208 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref065] 65.Miesfeld JB, Gestri G, Clark BS, Flinn MA, Poole RJ, Bader JR, et al. Yap and Taz regulate retinal pigment epithelial cell fate. Development. 2015;142: 3021–3032. 10.1242/dev.119008 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref066] 66.Agarwala S, Duquesne S, Liu K, Boehm A, Grimm L, Link S, et al. Amotl2a interacts with the Hippo effector Yap1 and the Wnt/β-catenin effector Lef1 to control tissue size in zebrafish. eLife. 2015;4: e08201 10.7554/eLife.08201 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref067] 67.Kimelman D, Smith NL, Lai JKH, Stainier DY. Regulation of posterior body and epidermal morphogenesis in zebrafish by localized Yap1 and Wwtr1. eLife. 2017;6 10.7554/eLife.31065 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref068] 68.Porazinski S, Wang H, Asaoka Y, Behrndt M, Miyamoto T, Morita H, et al. YAP is essential for tissue tension to ensure vertebrate 3D body shape. Nature. 2015;521: 217–221. 10.1038/nature14215 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref069] 69.Trinh LA, Chong-Morrison V, Gavriouchkina D, Hochgreb-Hägele T, Senanayake U, Fraser SE, et al. Biotagging of Specific Cell Populations in Zebrafish Reveals Gene Regulatory Logic Encoded in the Nuclear Transcriptome. Cell Rep. 2017;19: 425–440. 10.1016/j.celrep.2017.03.045 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref070] 70.Arduini BL, Bosse KM, Henion PD. Genetic ablation of neural crest cell diversification. Development. 2009;136: 1987–1994. 10.1242/dev.033209 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref071] 71.Wang W-D, Melville DB, Montero-Balaguer M, Hatzopoulos AK, Knapik EW. Tfap2a and Foxd3 regulate early steps in the development of the neural crest progenitor population. Dev Biol. 2011;360: 173–185. 10.1016/j.ydbio.2011.09.019 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref072] 72.Buitrago-Delgado E, Nordin K, Rao A, Geary L, LaBonne C. Shared regulatory programs suggest retention of blastula-stage potential in neural crest cells. Science. 2015;348: 1332–1335. 10.1126/science.aaa3655 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref073] 73.Briggs JA, Weinreb C, Wagner DE, Megason S, Peshkin L, Kirschner MW, et al. The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution. Science. 2018; 10.1126/science.aar5780 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref074] 74.Williams T, Tjian R. Analysis of the DNA-binding and activation properties of the human transcription factor AP-2. Genes Dev. 1991;5: 670–682. 10.1101/gad.5.4.670 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref075] 75.de Crozé N, Maczkowiak F, Monsoro-Burq AH. Reiterative AP2a activity controls sequential steps in the neural crest gene regulatory network. Proc Natl Acad Sci U S A. 2011;108: 155–160. 10.1073/pnas.1010740107 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref076] 76.Pingault V, Ente D, Dastot-Le Moal F, Goossens M, Marlin S, Bondurand N. Review and update of mutations causing Waardenburg syndrome. Hum Mutat. 2010;31: 391–406. 10.1002/humu.21211 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref077] 77.Haffter P, Granato M, Brand M, Mullins MC, Hammerschmidt M, Kane DA, et al. The identification of genes with unique and essential functions in the development of the zebrafish, Danio rerio. Dev Camb Engl. 1996;123: 1–36. [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref078] 78.Driever W, Solnica-Krezel L, Schier AF, Neuhauss SC, Malicki J, Stemple DL, et al. A genetic screen for mutations affecting embryogenesis in zebrafish. Development. 1996;123: 37–46. [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref079] 79.Kok FO, Shin M, Ni C-W, Gupta A, Grosse AS, van Impel A, et al. Reverse genetic screening reveals poor correlation between morpholino-induced and mutant phenotypes in zebrafish. Dev Cell. 2015;32: 97–108. 10.1016/j.devcel.2014.11.018 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref080] 80.Wang J, Xiao Y, Hsu C-W, Martinez-Traverso IM, Zhang M, Bai Y, et al. Yap and Taz play a crucial role in neural crest-derived craniofacial development. Development. 2016;143: 504–515. 10.1242/dev.126920 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref081] 81.Nallet-Staub F, Marsaud V, Li L, Gilbert C, Dodier S, Bataille V, et al. Pro-invasive activity of the Hippo pathway effectors YAP and TAZ in cutaneous melanoma. J Invest Dermatol. 2014;134: 123–132. 10.1038/jid.2013.319 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref082] 82.Adameyko I, Lallemend F, Aquino JB, Pereira JA, Topilko P, Müller T, et al. Schwann Cell Precursors from Nerve Innervation Are a Cellular Origin of Melanocytes in Skin. Cell. 2009;139: 366–379. 10.1016/j.cell.2009.07.049 [DOI] [PubMed] [Google Scholar]

[pgen.1008213.ref083] 83.Budi EH, Patterson LB, Parichy DM. Post-Embryonic Nerve-Associated Precursors to Adult Pigment Cells: Genetic Requirements and Dynamics of Morphogenesis and Differentiation. Barsh GS, editor. PLoS Genet. 2011;7: e1002044 10.1371/journal.pgen.1002044 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pgen.1008213.ref084] 84.Westerfield M. The Zebrafish Book: A Guide for Laboratory Use of Zebrafish (Danio Rerio)—See more at: http://elifesciences.org/content/5/e11813#ref-80. 4th ed. Eugene, USA: University of Oregon Press; 2000. [Google Scholar]

[pgen.1008213.ref085] 85.Jao L-E, Wente SR, Chen W. Efficient multiplex biallelic zebrafish genome editing using a CRISPR nuclease system. Proc Natl Acad Sci. 2013;110: 13904–13909. 10.1073/pnas.1308335110 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

The gene regulatory basis of genetic compensation during neural crest induction

Christopher M Dooley

Neha Wali

Ian M Sealy

Richard J White

Derek L Stemple

John E Collins

Elisabeth M Busch-Nentwich

Roles

Abstract

Author summary

Introduction

Fig 1. Analysis of the zebrafish NC GRN using gene expression data, knockouts and tissue-specific sequencing.

Results

Neural crest GRN members are expressed at genome activation

Identification of a neural crest–enriched gene set

Table 1. Sequencing data and pairwise comparison gene lists.

sox10 knockout mutants diverge from siblings transcriptionally at 19 hpf

Transcriptomic profiling of neural crest genetic ablation at three developmental stages using 3’ tag sequencing

Fig 2. Molecular profiling of tfap2a;tfap2c mutants across multiple time points using 3’ tag sequencing.

Transcriptional phenotypes in tfap2a and tfap2c mutants differ greatly in magnitude when compared to their morphological outcomes

Overlapping multiple expression profiles groups genes by biological function

tfap2a;tfap2c genetic compensation

Fig 3. Expression of sox10, sox9b and foxd3 in tfap2a;tfap2c mutants across three developmental time points.

RNA-seq on tfap2a;tfap2c knockouts at 15 somites confirms 3’ tag sequencing data and produces a more detailed transcriptional landscape

Identifying genes required for tfap2a;tfap2c knockout compensation / neural crest rescue

Fig 4. Identification of NC-specific gene subsets in tfap2a;tfap2c mutant RNA-seq 15 somite data.

ZFA enrichment confirms specific neural crest signatures

Markov clustering reveals tfap2a and tfap2c-specific gene clusters

Fig 5. Network analysis and Markov clustering of RNA-seq 15 somite data set.

Validation of novel neural crest transcripts

Table 2. Knockouts investigated in this study.

A role for maternally supplied yap1 in melanocytes

Fig 6. yap1 mutants are temperature sensitive and yap1 plays a role in melanocyte development.

yap1 knockouts are temperature sensitive, homozygous viable and reduced in body size

Zygotic yap1 mutants show signs of neural crest GRN disruption

Loss of maternal yap1 mRNA causes reduced melanocyte numbers at 30 hpf

Discussion

Initiation of neural crest GRN expression before gastrulation, shortly after zygotic genome activation

Genetic ablation of the neural crest

Dissection of the neural crest transcriptional network

Neural crest identity requires repression of a neural fate

Compensation of tfap2a knockout phenotypes via tfap2c and identification of genes involved in the neural crest rescue

Genetic compensation via paralogues

A role for Hippo signalling in the neural crest

Conclusions

Materials and methods

Ethics statement

Zebrafish husbandry and phenotyping of mutants

Embryo collection

FACS

Nucleic acid extraction

Genotype confirmation

Transcript counting

RNA-seq

Transcription factor motif analysis

Graph based Pearson correlation and Markov clustering of RNA-Seq data

Embryo and fin clip genotyping

Table 3. New alleles used in this study.

Zebrafish anatomy enrichment

RNA whole mount in situ hybridisation

CRISPR/Cas9

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases