- Research article
- Open Access
Transcriptome profiling reveals expression signatures of cranial neural crest cells arising from different axial levels
© The Author(s). 2017
- Received: 17 November 2016
- Accepted: 3 April 2017
- Published: 13 April 2017
Cranial neural crest cells (NCCs) are a unique embryonic cell type which give rise to a diverse array of derivatives extending from neurons and glia through to bone and cartilage. Depending on their point of origin along the antero-posterior axis cranial NCCs are rapidly sorted into distinct migratory streams that give rise to axial specific structures. These migratory streams mirror the underlying segmentation of the brain with NCCs exiting the diencephalon and midbrain following distinct paths compared to those exiting the hindbrain rhombomeres (r). The genetic landscape of cranial NCCs arising at different axial levels remains unknown.
Here we have used RNA sequencing to uncover the transcriptional profiles of mouse cranial NCCs arising at different axial levels. Whole transcriptome analysis identified over 120 transcripts differentially expressed between NCCs arising anterior to r3 (referred to as r1-r2 migratory stream for simplicity) and the r4 migratory stream. Eight of the genes differentially expressed between these populations were validated by RT-PCR with 2 being further validated by in situ hybridisation. We also explored the expression of the Neuropilins (Nrp1 and Nrp2) and their co-receptors and show that the A-type Plexins are differentially expressed in different cranial NCC streams.
Our analyses identify a large number of genes differentially regulated between cranial NCCs arising at different axial levels. This data provides a comprehensive description of the genetic landscape driving diversity of distinct cranial NCC streams and provides novel insight into the regulatory networks controlling the formation of specific skeletal elements and the mechanisms promoting migration along different paths.
- Neural crest
- Cranial neural crest
Neural crest cells (NCCs) are a multipotent population of cells that arise from dorsal regions of the neural tube during early stages of embryonic development . Due to their critical importance to a wide variety of tissues, deficiencies of NCCs underlie a highly prevalent group of congenital disorders termed neurocristopathies that include craniofacial anomalies and cardiac outflow tract defects . Understanding the genetic programs controlling NCC development is therefore essential to provide insight to the origins and potential treatment of a large number of birth defects.
Different populations of NCCs are defined by the position at which they arise along the antero-posterior axis. Cranial NCCs arise anterior to somite 5 and give rise to bone, cartilage and tendons of the head, as well as sensory and sympathetic neurons of the peripheral nervous system. Vagal NCCs arise between somites 1–7 and give rise to the neurons and glia of the enteric nervous system and to cardiac NCCs which form vascular smooth muscle lining the pharyngeal arch arteries and also contribute to the aortic-pulmonary septum. Trunk NCCs arise posterior to the 4th somite and give rise to neurons and glia of the sensory and sympathetic nervous system, schwann cells and melanocytes .
Within these broad axially defined regions, NCCs can be further divided into sub-populations based on their migratory path and developmental fate. For example, cranial NCCs spanning the region between the mid-diencephalon and 5th somite are segregated into distinct migratory streams which mirror the transient segmentation of the neural tube into lineage-restricted units such as the diencephalon, midbrain and the hindbrain rhombomeres (r) [4, 5]. Cranial NCCs emigrating from each axial level follow distinct paths that drive segregation into distinct migratory streams that are maintained as these cells navigate the cranial mesenchyme. Thus, cranial NCCs arising anterior to r3, including those from the diencephaplon, midbrain and r1-r2, migrate into the frontonasal process, maxilla and first pharyngeal arch (PA1), whereas r4-derived NCCs migrate into PA2. NCCs populating these regions also give rise to specific structures such as Meckel’s cartilage, incus, malleus and trigeminal ganglia (Vth) in PA1, and middle ear ossicle and stapes, hyoid bone and facioacoustic ganglia (VIIth/VIIIth) in PA2 .
Migration of cranial NCCs within these distinct streams is under control of cell intrinsic and environmental cues that include several ligand-receptor pairs from the Eph/Ephrin [7–9], ERBB/Neuregulin , SDF/CXCR  and VEGFA/Semaphorin/Neuropilin signalling pathways [12–17]. Neuropilins (NRP1 and NRP2) are transmembrane co-receptors for guidance molecules of the class 3 semaphorin (SEMA3) family and for heparin binding isoforms of the vascular endothelial growth factor VEGFA . During early stages of cranial NCC development NRP1 expression is restricted to NCCs within the r4 migratory stream while NRP2 is restricted to NCCs within the r1-r2 migratory stream . Using an inducible Cre/LoxP lineage tracing system the Nrp2 expressing cranial NCCs were further found to give rise to r1-r2 derived structures such as the trigeminal ganglia (Vth cranial ganglia) . Mouse knockouts of Nrp1 and Nrp2 further demonstrate an essential requirement for these receptors in promoting migration of NCCs within different streams. Thus, r4-derived NCCs migrate aberrantly in Nrp1 knockout mice, and r1-r2-derived NCCs migrate aberrantly in Nrp2 knockout mice [12, 16]. In chick, Nrp1 is also expressed by NCCs in the r4 migratory stream and controls migration toward VEGFA secreted by the surface ectoderm . Although Neuropilins recruit signalling co-receptors such as the A-type plexins (PLXNA1-4) and VEGF receptors (VEGFR1-R2) to control axonal guidance , vascular growth  and motor neuron migration , the signalling co-receptors recruited in NCCs remain unknown.
Positional identity of NCCs along the antero-posterior axis is thought to be acquired prior to migration and to be under control of homeodomain transcription factors that promote segmentation and patterning of the rhombomeres from which the NCCs arise [4, 24, 25]. Thus, the unique combination of Homeobox (HOX) genes along the antero-posterior axis is likely to underlie the molecular differences of the distinct migratory streams. Indeed, distinct Hox expression profiles have also been identified in NCCs arising at different axial levels. However, as Hox expression in NCCs is under control of distinct enhancers, the Hox genetic code in NCCs differs from their original rhombomeric tissue [5, 24, 25]. While the distinct expression profiles of the Hox genes and Neuropilins demonstrate that NCCs of different migratory streams are molecularly distinct, the extent of these differences and the regulatory networks controlling their unique identity remain unknown.
Here we have uncovered the transcriptional profiles of cranial NCCs arising anterior to r3 (termed r1-r2 migratory stream) and r4 migratory streams by performing RNA sequencing (RNA-seq) on purified populations of cranial NCCs. Our RNA-seq, RT-PCR and in situ hybridisation analyses reveal many previously unappreciated transcripts showing differential expression between these distinct streams of cells. We also explored the expression of potential Neuropilin co-receptors and show that A-type Plexins are differentially expressed between these cranial NCC streams. Our analyses identify a large number of genes differentially expressed between cranial NCCs arising at different axial levels, providing a comprehensive resource for future analysis of these cellular populations.
Isolation of cranial NCC streams
Dynamic expression of Neuropilins in cranial NCCs
RNA Sequencing reveals the expression profiles of r1-r2 and r4-derived NCCs
Genes up-regulated in r1-r2-derived NCCs. Top 25 genes significantly up-regulated in the r1-r2 NCC migratory stream as defined via Cuffdiff and EdgeR. Inf refers to an infinite Log2 fold change due to a value of 0 in r4-derived NCCs
Genes up-regulated in r4-derived NCCs. Top 25 genes significantly up-regulated in the r4 NCC migratory stream as defined via Cuffdiff and EdgeR. Inf refers to an infinite Log2 fold change due to a value of 0 in r1-r2-derived NCCs
Validation of differentially expressed genes
Differential expression of Neuropilin coreceptors in cranial NCCs
In this study we have used whole transcriptome profiling to reveal the genetic signatures of cranial NCCs arising from different axial levels. A large body of work in chick and zebrafish has previously defined gene regulatory networks that sequentially control: 1) specification of NCC precursors at the neural plate border, 2) specification of bona fide NCCs from the neuroepithelium, and 3) diversification of NCCs post delamination . Under this model, a hierarchy of transcription factor combinations are proposed to drive different developmental stages, with neural crest specifier genes inducing formation of bona fide NCCs from their neuroepithelial precursors, and neural crest effector genes instructing NCC proliferation, migration and differentiation. Our current study shows that cranial NCCs from mice express a similar repertoire of specifier and effector genes to that seen in chick [27, 28, 46] and demonstrates that conserved genetic networks control NCC development across multiple species. In chick, SOX9 and ETS1 have also been shown to act as common enhancers of cranial NCC identity . In further support of this notion, we identified SOX9 binding sites within the promoter regions of 77% and 82% of genes up-regulated in r4 and r1-r2, respectively.
Our findings also support the notion that different combinations of neural crest effector genes orchestrate the diverse developmental fates and migration paths of NCCs arising at different axial levels. Thus, our analysis identified distinct expression signatures for each NCC stream, including 10 transcription factors specific for r1-r2, and 14 transcription factors specific for r4-derived NCCs. Enrichment of the Aristaless-like homeobox gene transcription factors Alx1, Alx3 and Alx4 within r1-r2-derived NCCs is in strong agreement with previous findings linking these genes to early NCC development and craniofacial disorders [33, 47–50]. Moreover, identification of genes previously found enriched in NCCs arising anterior to r3 provides confidence that our dataset uncovers genetic networks underlying the diversity of NCCs arising at different axial levels. Amongst the other transcription factors specific to the r1-r2 stream Ferd3l has also been implicated in the craniofacial disorder Saethre-Chotzen syndrome , however, the remaining transcription factors have unknown roles in cranial NCCs. Sp8 and Sp9 are both members of the Sp/KLF transcription factor family that have essential roles in organising craniofacial, limb and interneuron development [52, 53]. Although Sp8 is primarily required by the anterior neural ridge and olfactory pit to regulate craniofacial development , it’s expression pattern is also consistent with a putative role in the frontonasal process at E9.5 in mice . Expression of Sp9, on the other hand, is thought to be restricted to the ganglionic eminences and developing limb of mice post E10.5 . While this is inconsistent with our data set, it is possible that prior analyses have not been sensitive enough to detect low levels of expression in NCCs at E9.5, as would be predicted by our data. The identification of Sox21, which is known to regulate neurogenesis, also suggests that our data set uncovers genetic networks at play in the differentiation phase of NCC development . Indeed, this is further highlighted by the over-representation of genes regulating skeletal development in the r1-r2 data set, including Alx1, Alx3, Alx4, Shh and Pax5.
In contrast to NCCs that populate PA1, NCCs contributing to the second and more posterior pharyngeal arches are known to express various combinations of Hox genes. Accordingly, our analysis uncovered numerous Hox family members specific to r4-derived NCCs. Hoxa2 was the most abundant member of this family and has well established roles in patterning second arch derivatives through regulating expression of effector genes such as Meox1 , which was also enriched in r4-derived NCCs. Hoxb1 is exclusively expressed in r4 derived NCCs  and has essential roles in controlling formation of the facioacoustic ganglia . Hoxc11 and Hoxc5 were enriched in r4-derived NCCs but have unknown functions in this stream. Hoxc5 is predicted to have overlapping functions with its paralogue Hoxb5 that has been shown to regulate expression of Ret in vagal NCCs . Ret was also identified in our data set and previously shown to be enriched in r4-derived NCCs . Another notable observation with the r4 data set is the over-representation of retinoic acid responsive genes including Hsd17b2, Pparg, Abca1, Ret, Hoxa2 and Rbp4. Taken together with the finding that retinoic acid preferentially affects migration of r4-derived NCCs in chick , this suggests that this population of NCCs are more responsive to retinoic acid than NCCs arising anterior to r3.
Previous expression profiling and phenotypic analysis of Nrp1 and Nrp2 knockout mice supports the proposal that Nrp1 guides r4-derived NCCs into PA2, and that Nrp2 guides r1-r2-derived NCCs into PA1 [12, 16, 19]. Indeed, complete fusion of the trigeminal and facioacoustic ganglia in compound Nrp1; Nrp2 knockout embryos highlights a critical role for these receptors in guiding neuroglial fated cranial NCCs . While these receptors are expressed in exclusive domains at the earliest stages of NCC migration, our current analysis shows that they become co-expressed in the same populations of NCCs and NCC derivatives as they condense into the cranial ganglia. Taken in context, the knockout phenotypes suggest that the Neuropilins are required for promoting migration into distinct streams at the initial stages of NCC migration and in controlling axonal guidance after the cranial ganglia differentiate [16, 21].
Although none of the Neuropilin co-receptors were identified in our comparative transcriptome analysis, in situ hybridisation suggests that PlxnA1-A4 are differentially expressed in NCCs arising at different axial levels. PlxnA1-A4 are archetypical Neuropilin co-receptors that predominantly convey signals upon binding of SEMA3 during peripheral and central nervous system development . Given their overlapping expression profiles it will now be of interest to address the roles of these receptors in controlling cranial NCC migration. In searching for additional mechanisms that may be involved in controlling cranial NCC migration it was notable that the receptor tyrosine kinase Ret and the GABA receptor Gabre were the only membrane receptors identified in our analysis. Ret is essential for migration of enteric NCCs within the gut but additional roles in controlling migration of r4-derived NCCs are currently unknown . GABA receptors are also known to modulate the proliferation and differentiation of NCC derived boundary cap cells . It will now be of interest to test if Ret or Gabre have specific roles in the r1-r2 or r4 population of NCCs.
In conclusion, our studies uncover the transcriptional landscape that underpins diversity of cranial NCCs arising from different axial levels. This gene list provides novel insight to the regulatory networks controlling the formation of specific skeletal elements and to the mechanisms promoting migration along different paths.
All experimentation was approved by and conducted in accordance with the guidelines of the Animal Ethics Committee of SA Pathology/Central Adelaide Local Area Health Network and followed the Australian code of practice for the care and use of animals for scientific purposes. To obtain embryos of defined gestational ages, animals were mated in the evening, and the morning of vaginal plug formation was counted as embryonic day (E) 0.5. To label NCCs with GFP we crossed Wnt1Cre  mice to Z/EG mice . All Wnt1Cre mice were maintained and used in the heterozygous state to minimise any off-target effects of aberrant expression of Wnt1 that has been reported in this line .
In situ hybridisation
Whole-mount in situ hybridisation was performed as described . Riboprobes were transcribed from plasmids containing the cDNA sequence for Nrp1 and Nrp2 [64, 65]. Fragments of Nkx2-9, Lmx1B and AnxA2 were amplified by PCR from whole embryo cDNA, cloned to pGEMT (Promega) and verified by sequencing. Primers used for PCR amplification are detailed in the RT-PCR methods section.
Microdissection of NCC migratory streams
Somites were counted and GFP positive embryos with less than 25 somites were further dissected for fluorescent activated cells sorting (FACS). To isolate pure populations of r1-r2 and r4-derived cranial NCCs these regions were carefully dissected by first removing the GFP expressing forebrain which was discarded. The vagal and trunk NCCs were then removed by slicing the embryos through the otic vesicle. Finally, the r1-r2 and r4 streams were sliced apart using 26 gauge needles. GFP negative littermates were sliced into fragments and added evenly across the dissected r1-r2, r4 and trunk regions to boost cell numbers for further analyses.
FACS sorting primary NCCs
Primary NCCs were isolated from E9.5 Wnt1Cre; Z/EG embryos as previously described . To dissociate the dissected tissue Tryple Express (Life Technologies) was warmed to 37°C and 2mls added per tube. Tissue was incubated at room temperature for 10mins. Cells were gently triturated with a fire blown glass pipette until no clumps of cells could be seen, washed twice with Dulbecco’s modified Eagle’s media (DMEM) containing 1% Fetal Calf Serum (FCS) and strained through a 40μm filter. Cell sorting was performed on Beckman Coulter Epics Altra HyperSort using Expo MultiComp Software version 1.2B (Beckman Coulter) equipped with Innova 300C water-cooled 488nm argon laser at 100mW. Sorting was conducted at room temperature, with the instrument pressurised to 12psi and a 100um nozzle. Linear forward scatter (FSC) height (pk), width (TOF) and area (INT) signals were collected to allow for standard scatter and doublet discrimination. Linear side scatter (SSC) area (INT) signal was collected with a 488/10 band pass filter in PMT1. Log GFP signal was collected in PMT2 with a 525/25 band pass filter behind a 488nm long pass dichroic mirror. A gate was drawn on a FSC (INT) vs SSC (INT) plot to exclude debris and dead cells as discriminated by scatter properties alone. Following this a FSC pk vs FSC INT plot was examined to allow distinction of single cells. Linearly related cells were gated for further analysis on a GFP vs SSC plot. Cells were collected into DMEM with 1% FCS.
FACS isolated cells were sorted into DMEM containing 1% FCS, pelleted and then resuspended in 500ul of trizol before being frozen at −80°C. Upon thawing 100ul of chloroform was added and the samples mixed. Samples were centrifuged at 14,000rpm. The top aqueous phase was transferred into a new tube and an equivalent volume of ethanol was added and gently mixed. RNA was extracted from the ethanol mixed samples using a RNeasy Micro Kit (Qiagen). Half of the extracted RNA (6ul) was used for qRT-PCR and half used for RNAseq.
Single stranded cDNA was made using a Quantitect Reverse Transcription kit (Qiagen). qRT-PCR was performed with SYBR Green reagent (Qiagen) using Rotor-Gene-6000 real-time PCR system (Corbett Life Science). Semi-quantitative PCR was also performed for a number of genes to compare the relative expression levels in the different NCC sub-populations. For this, go taq green (Promega) was used with a low number of cycles ranging from 20 to 25 and annealing temperature of 55°C. Primers used were as follows: Sox10 fwd: GGAGGCAGAATGCCCAGGCG, rev: TGGCTCTGGCCTGAGGGGTG; Nrp1 fwd: AAAGGTTCCTCCAATTGCTG, rev: TGGCTTCCTGGAGATGTTCT; Nrp2 fwd: TGCATGGAGTTCCAGTACCA, rev: CCCTATCACTCCCTCGAACA; β-Actin fwd: GATCATTGCTCCTCCTGAGC, rev: GTCATAGTCCGCCTAGAAGCAT; Sp8 fwd: GCGCACACTTGCACCATATC, rev: GTTCTTCTCGCGTTCCCCTT; Hoxa2 fwd: CCTTTTGAGCAGACCATTCC, rev: AAAGCTGAGTGTTGGTGTACG; AnxA2 fwd: CTTCAAGGGAGGCTCTCAGC, rev: GTAGAATGATCACCCTCCAGGC, Nkx2-9 Fwd: GCGCAGCCTCCTGAATTTAC, rev: TCTCGTCCGAGGACAGGTAG; Alx1 fwd: CAAGTGGAGAAAAAGAGGAACG, rev: ATTCTGGTGGTTCGAAAACC; Pax5 fwd: CTGTGACAATGACACTGTGC, rev: ACTGATGGAGTATGAGGAGC; Tgfbi fwd: ACAAACTGGAAGTCAAGCTCG rev: CTAATGCTTCATCCTCTCCAG; Efhd2 fwd: GATTTCGACAGCAAACTCAGC, rev: GAAAGTAGCTGGTACCAAAGG; GFP fwd: GCACGACTTCTTCAAGTCCGCCATGCC rev: GCGGATCTTGAAGTTCACCTTGATGCC. Relative mRNA levels were quantified using the comparative quantitation method in the Rotor-Gene −6000 software. Relative mRNA levels were then normalised to β-Actin. Each PCR was performed in triplicate across 4 biological replicates. Error bars represent standard error of the mean (SEM) between biological replicates.
Embryos were fixed in 4% paraformaldehyde in PBS. Sections were cut to a thickness of 18μm on a CM1850 cryostat (Leica, North Ryde, NSW, Australia) and air dried for a minimum of 60min prior to staining. For immunolabelling, whole-mount or sections were blocked in PBS containing 0.2% BSA and 0.5% Triton X-100 and stained with indicated primary antibodies: chicken anti-GFP 1:1000 (Sigma Aldrich, Sydney, NSW, Australia), rabbit anti-P75-NTR/NGRF 1:200 (Epitomics, Burlingame, CA, USA).
RNA was enriched for polyadenylated transcripts before library construction with NEBNext RNA library preparation kit and sequenced on an Illumina HiSeq 2500 at the ACRF Cancer Genomics Facility (SA Pathology, Adelaide, Australia) to obtain 51 base single-end reads. Reads were trimmed for the NEB single end adapter “AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC” with Cutadapt v1.3 , requiring a minimum overlap of 5, allowing a 20% error rate and discarding trimmed sequences shorter than 18 bases. The trimmed reads were then mapped to the UCSC mm10 mouse genome with Tophat 2.0.9  using default parameters. Differential expression between r1-r2 and r4 was performed using Cuffdiff v2.1.1 or edgeR. For edgeR analysis, gene counts were obtained with HTSeq-count v0.6.1p1, and differential expression performed according to the protocol described in Anders 2013. Genes with FDR < 0.05 or Q < 0.05 were considered to be differentially expressed in edgeR and Cuffdiff, respectively. Prior to multiple testing correction 1353 differentially expressed genes were identified with a p < 0.05 in both programs, with 511 (37.7%) significant in both. After multiple testing correction, a total of 131 genes met criteria for differential expression in one of the analysis programs, with 6 identified in both. Here we have taken identification in either analysis program to represent differentially expressed genes. The multidimensional scaling plot was produced by the Limma plotMDS function, using the BCV method. The scatterplot shows the mean of normalised A and B replicates for both conditions.
This work was supported by an NHMRC grant APP1067848 and National Heart Foundation Fellowship awarded to Q.S.
Availability of data and materials
All data are available on request to the corresponding author.
R.L., G.S and Q.S completed all experiments and wrote the manuscript. D.L. and S.B. completed all bioinformatics analyses. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Consent for publication
All experimentation was approved by and conducted in accordance with the guidelines of the Animal Ethics Committee of SA Pathology/Central Adelaide Local Area Health Network and followed the Australian code of practice for the care and use of animals for scientific purposes.
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