Transcriptome sequencing of Atlantic salmon (Salmo salar L.) notochord prior to development of the vertebrae provides clues to regulation of positional fate, chordoblast lineage and mineralisation
© Wang et al.; licensee BioMed Central Ltd. 2014
Received: 12 October 2013
Accepted: 13 February 2014
Published: 19 February 2014
In teleosts such as Atlantic salmon (Salmo salar L.), segmentation and subsequent mineralisation of the notochord during embryonic stages are essential for normal vertebrae formation. However, the molecular mechanisms leading to segmentation and mineralisation of the notochord are poorly understood. The aim of this study was to identify genes/pathways acting in gradients over time and along the anterior-posterior axis during notochord segmentation and immediately prior to mineralisation of the vertebral bodies in Atlantic salmon.
Notochord samples were collected from unsegmented, pre-segmented and segmented developmental stages. In each stage, the cellular core of the notochord was cut into three pieces along the longitudinal axis (anterior, mid, posterior). RNA was sequenced (22 million pair-end 100 bp/ library) and mapped to the salmon genome. 66569 transcripts were predicted and 55775 were annotated. In order to identify possible gradients leading to segmentation of the notochord, all 71 notochord-expressed hox genes were investigated, most of them displaying a typical anterior-posterior expression pattern along the notochord axis. The clustering of hox genes revealed a pattern that could be related to notochord segmentation. We further investigated how mineralisation is initiated in the notochord, and several factors related to chondrogenic lineage were identified (sox9, sox5, sox6, tgfb3, ihhb and col2a1), suggesting a cartilage-like character of the notochord. KEGG analysis of differentially expressed genes between stages revealed down-regulation of pathways associated with ECM, cell division, metabolism and development at onset of notochord segmentation. This implies that inhibitory signals produce segmentation of the notochord. One such potential inhibitory signal was identified, col11a2, which was detected in segments of non-mineralising notochord.
An incomplete salmon genome was successfully used to analyse RNA-seq data from the cellular core of the Atlantic salmon notochord. In transcriptome we found; hox gene patterns possibly linked to segmentation; down-regulation of pathways in the notochord at onset of segmentation; segmented expression of col11a2 in non-mineralised segments of the notochord; and a chondroblast-like footprint in the notochord.
KeywordsAtlantic salmon Notochord RNA-seq col11a2 Hox
The notochord is a midline structure that appears early in the embryo of all vertebrates, and has several important functions. It provides internal hydroskeletal support, until this role is taken over by the vertebral column. It also produces secreted factors during development that provide position and fate signals to adjacent ectoderm, paraxial mesoderm and endoderm along the dorso-ventral axis [1–5]. In recent years, additional functions of the notochord have been unravelled. Segmentation and subsequent mineralisation of the notochord comprise the initial morphogenic process in formation of the vertebral column in Atlantic salmon (Salmo salar L.)  and in zebrafish (Danio rerio) [2, 7]. Segmented mineralisation of the notochord determines the localization of vertebral bodies, and notochord mineralisation is thereby crucial for normal formation of the vertebrae, as the functional study by Willems et al.  has demonstrated. Furthermore, pathological processes that disrupt notochord mineralisation may lead to malformation of vertebrae . However, mechanisms initiating segmentation and mineralisation within the notochord are currently unknown, and further studies of this topic are needed.
The salmon embryo provides a good model for studies of development and differentiation, due to its slow early development and large size, allowing pure samples of the cellular core of the notochord to be isolated. This has facilitated some detailed molecular studies of salmon notochord, and the discovery of notochord-specific molecules such as vimentin and elastin. Moreover, the development of the notochord and the vertebral column of Atlantic salmon embryos and larvae have previously been the subjects of detailed morphological studies [6, 9, 11–13]. This has made it possible to characterize in detail both notochord segmentation and the subsequent mineralisation that nucleates vertebral development.
As development of the salmon notochord proceeds, segmentation is initially observed in the notochord epithelium as metameric bands of cells with alternating cell-axis orientations  concurrent with expression of alkaline phosphatase (ALP) in every second band , both processes defining the future positions of vertebral and intervertebral segments. In the following stage, possibly in order to permit further growth of the vertebrae, sclerotome-derived osteoblasts differentiate on the surface of the notochord centrae to form bone [9, 11].
Despite the importance of the notochord in the initial shaping of the vertebral column, the genes involved and the network of transcriptional regulators controlling them are still incompletely characterized. An overall transcriptome assessment using RNA-seq on critical stages during the early segmentation stage of salmon notochord might reveal pathways associated with the segmentation and subsequent mineralisation processes. Possible factors associated with segmentation of the notochord could be members of the hox gene family, as these molecules are known to confer patterning formation along the anterior-posterior body axis in all vertebrates. In zebrafish, four hox genes have been found to be differentially expressed along the anterior-posterior axis of the notochord , which indicates that these genes may play a role in metameric morphogenic processes within the notochord of teleosts. In Atlantic salmon, 118 hox genes have been identified, including 8 pseudogenes , but none of them have been studied with regard to notochord development. Furthermore, the differentiation of chordocytes, and specific features of notochord mineralisation, might posibly be elucidated via a transcriptome study, as factors typical of chondrogenesis and osteogenesis could be identified. For instance, both the hedgehog and Wnt signalling pathways play important roles in formation of the notochord sheath and the patterning of the vertebral column during early development in the mouse .
The primary objective of the present study was to relate the transcriptome of the notochord to morphological events in un-segmented notochord (510 day), pre-segmented notochord (610 day) and segmented notochord to the ongoing mineralisation of the sheath (710 day). This study employed high-throughput RNA sequencing technology on dissected anterior-posterior notochord segments to explore, at global level, the pathways and genes expressed in the notochord that might contribute to notochord development, segmentation and subsequent mineralisation in salmon and related species.
Rearing of embryos and notochord dissection
Samples of notochord with surrounding tissues for light microscopy, and pure notochord fractions for scanning electron microscopy (SEM), were fixed and processed as described by Grotmol et al. . Histological slides were photographed in an Olympus Vanox X3 microscope (Olympus, Tokyo, Japan), while samples for SEM were studied in a Zeiss FESEM Supra 50 field-emission scanning EM (Oberkochen, Germany).
Total RNA extraction and transcriptome sequencing
Total RNA was extracted from notochord pieces using Rneasy Mini Kit (Qiagen, Hilden, Germany), according to the manufacturer’s instruction. Only RNA samples with A260/280 within 1.9-2.1 and A260/230 > 1.8 measured by Nanodrop (ND-1000, Thermo Scientific, Wilmington, USA), were used for pooling. In total, notochord pieces (anterior, mid-, posterior parts in separate tubes) from 36 fish from T1, 18 fish from T2 and 27 fish from T3 were pooled and prepared for nine total RNA libraries (at least 6 μg RNA/library, labeled as: T1A, T1M, T1P, T2A, T2M, T2P, T3A, T3M, T3P). RNA integrity was checked for each library (RIN value > 9, except for T3M) by Agilent 2100 Bioanalyzer (RIN values for individual library were listed in Additional file 1: Table S1). RNA libraries were prepared by Fasteris Life Science (Geneva, Switzerland). Briefly cDNA libraries were prepared using random hexamer primers and samples were sequenced using 2x100bp paired-end high-throughput mRNA sequencing (RNA-seq) in single lane on Illumina Hiseq 2000 (Illumina, San Diego, CA). Due to the time-consuming dissecting procedures involved and limited tissue mass, single libraries without replicates were sequenced.
Bioinformatical analysis of RNA-seq
The commented java source code based on the Picard API for extracting the read count per Augustus predicted gene is available at https://marineseq.imr.no/salmon/annot2013/. “In silico” gene expression was calculated as: (number of mapped reads*read length)/ (predicted coding sequence length). In cases where the mapped reads overlapped coding sequence and the UTR, only the part of the read that mapped to the coding sequence was counted. If a read mapped to a coding sequence with a 90% match, only 0.9 was added. Reads with an identity match to the genome below 90% were removed from the analysis. Normalization of expression values among libraries was completed by counting the total number of reads from each library and then recalculating, so that each library was given the same number of counts.
Differential gene expression
Differentially expressed genes (DEG) were selected by using NOISeq  with a threshold 0.8. Since we did not have true biological replicates, we either pooled three segments (A, M, P) of each developmental stages (labelled as sumT1, sumT2, sumT3), or three stages (T1, T2, T3) for each segment (sumA, sumM, sumP). We ran NOISeq for both spatial and temporal comparison on pooled libraries, using library-normalized raw read count for each gene. K-mean clustering was used to group genes with similar patterns of expression. Gene Ontology  was used to pick up genes that were annotated with ECM. The output ECM gene list could be cross-checked for DEGs from NOISeq. KEGG pathways analysis  was performed by mapping the KEGG annotated DEGs from NOISeq to KEGG pathways as described in the KEGG Mapper tool. Both raw expressions of genes and DEGs as fold change were plotted in pathways, and the ratio of number of up-regulated genes/number of down-regulated genes, or vice versa, were calculated as a means of ranking up-/down-regulated pathways.
Quantitative real-time PCR
Quantitative real-time PCR (qPCR) was performed using SYBR Green PCR Master Mix (Applied Biosystems Inc., Foster City, CA, USA). Total RNA of all libraries was extracted from dissected notochord, following the same procedure as described for transcriptome sequencing from another batch of salmon embryos . Only RNA samples with A260/280: 1.8-2.0 were pooled from two additional batches of salmon embryos, and they were used for cDNA synthesis with SuperScript VILO cDNA Synthesis Kit (Invitrogen), according to the manufacturer’s guidelines. After TURBO DNA-free kit (Ambion) treatment and sodium acetate precipitation, qPCR reactions were run in a 7900HT Fast Real-Time PCR System (Applied Biosystems Inc.). The conditions for all reactions were 50°C for 2 min, followed by 95°C for 10 min, 40 cycles of 95°C for 15 sec, followed by 60°C for 1 min. Genomic fragments from the draft salmon genome assembly (Acc. No. AGKD00000000.1) were used to design primers and probes, as shown in Additional file 3: Table S2. Primers were designed using Primer Express v2.0 software (Applied Biosystems Inc.) and Primer-BLAST . Elongation factor 1 α (ef1a) was used as reference gene for its stable expression in salmon tissues , including notochord [10, 13, 26]. ef1a was expressed at the same level in all libraries (Gene expression data found at https://marineseq.imr.no/salmon/annot2013/). Three biological replicate cDNAs were made for gene expression analysis. Standard curve analysis was performed to confirm similar amplification efficiency in target genes and the reference gene with a validation step. A no-template-control (NTC) and an RNA sample without reverse transcription (−RT), were used to control for contamination of external and/or genomic DNA in reactions. Melting curve analyses were performed for each primer pair in order to confirm unique amplicon reaction. One-way ANOVA (p < 0.05) and Tukey’s multiple comparison, were performed in GraphPad Prism v5 (GraphPad Software, San Diego, CA. USA) to detect DEG in summed libraries (sumA-P and sumT1-T3) following analysis of the qPCR data.
In situ hybridization
Transcriptome features, annotation and quality
qPCR validation of RNA-seq gene expression values
Expression of Hox genes within the notochord
Expression of key molecules in chondrogenic lineage, ECM formation and mineralisation
Overall activity in the notochord during ontogeny
Spatial expression of col11a2 in the notochord
Building and mineralisation of the notochord sheath
About 65000 salmon gene transcripts were expressed in the notochord during the developmental stages analysed. This is an expected number of transcripts, considering the partial tetraploidy of salmonids . In for example zebrafish, which have undergone only one teleost-specific genome duplication in the course of evolution, ~51000 transcripts were identified in a tissue gene expressional study using a similar genome-mapping method . De novo assembly of the RNA-seq data could have been implemented, but this method may produce a much higher number of predicted transcripts, as has been observed in rainbow trout (Oncorhynchus mykiss) and catfish (Ictalurus punctatus), where de novo assembly produced about ~130000 and ~370000 predicted transcripts respectively [31, 32]. With an average predicted coding sequence length of around 872 bp, the results are comparable to what was predicted using de novo assembly methods in catfish , but much longer than that obtained in rainbow trout . Of the ~65000 predicted transcripts obtained in the present study, annotation was retrieved for ~55000 transcripts (83%), which is a much higher rate compared to rainbow trout, where only 50% transcripts were annotated . However, due to the fragmented structure of the current salmon genome assembly, which consists of a large Sanger-sequenced data-set with a contig N50 of 9342 bp, it was difficult to predict whole protein lengths and therefore also splice variants in a large fraction of the expressed genes. Moreover, due to the recent genome duplication in salmonids, many paralogous genes display high sequence similarity, which may cause cross-mapping, leading to assembly errors.
Quantitative PCR was used to validate gene expression profiles. Twelve out of thirteen DEGs from NOISeq were confirmed by qPCR, which indicates the high reliability of NOISeq for detecting DEGs. qPCR appeared to be more sensitive than RNA-seq in detecting differentially expressed genes, which was expected due to presence of isoforms which share mapping unequally, a fragmented genome and lack of replicate samples in RNA-seq . Interestingly, there was a high correlation in gene expression data among the hox clusters, as they all displayed collinearity in their expression patterns, in spite of some of them being expressed at a very low level. This gene family consist of very well-characterized full-length genes identified by manual cloning ; therefore a fragmented genome might not have affected gene expression profiles of these genes. The lack of replicates also made it difficult to calculate differential gene expression, but by using NOISeq we were able to calculate differential gene expression profiles between stages by combining the expression values of three spatial libraries (A, M, P). NOISeq was chosen mainly because it can simulate technical replicates when few or no replicates are available, which is the case of this study . Since NOISeq does not rely on parametric assumptions, it is also more effective in both identifying differentially expressed transcripts with low read counts and reducing the rate of false discoveries .
Of all the 118 salmon hox genes including 8 pseudogenes, 71 were expressed in the developing notochord, and also collinear expression was observed in corresponding hox clusters along the anterior-posterior axis. Interestingly, our study shows that duplicated Hox cluster pairs in salmon have different gene expression patterns, and also this is most obvious in HoxBa clusters (Figure 5A). This fact could be linked slow evolution of HoxBa, both in number of genes and in their gene and intergenic sequences . Our data may therefore suggest that HoxBa have evolved different functional roles in the notochord. So far, only one study in teleosts have previously identified expression of four hox genes in the notochord, among which hoxb5 displayed the most posterior and highest expression within the notochord . In the notochord, we also found the highest expression in HoxB clusters. Another RNA-seq study of whole eel embryos (Anguilla Anguilla), which includes the notochord, has also shown that the HoxBa has the highest expression . Furthermore, clustering of all hox expression patterns in the notochord indicated that highly-expressed hox genes increase in expression at 610 day, and this expression is retained until 710 day (G5 node, in Figure 5C). Interestingly, the expression levels of all hox genes were more similar in the medial part of the notochord throughout the study period than in other regions, which is in accordance with the observation that the initial chordacentrae develop there [9, 12, 13]. Another point was that several genes found in the A and B clusters show posterior expression patterns. Prince et al.  have observed a similar posteriorisation of hox gene expression in the notochord compared to surrounding tissues, including the CNS and paraxial mesoderm. Here, there are two plausible explanations; either hox genes have a more posterior fate in the notochord, or the posterior end of the notochord represents its own patterning unit. In the latter case, we would not be able to detect collinearity in the posterior notochord, since all this tissue was in the posterior sample. But as most of the hox genes display a posteriorisation of expression, it is likely that the latter assumption is to some extent correct.
A wide search for factors implicated in tissue mineralisation resulted in finding of chondroblast-specific “master genes” expressed in notochord such as sox6, sox5 and sox9, in addition to other genes associated with the fate of chondroblasts, such as tgfb3, ihhb and col2a1. However, no genes associated with the fate of specific osteoblasts, such as runx2, osterix and bgp, were found. The chondrogenic genes Sox5 and Sox6 have previously been shown to be expressed in the zebrafish notochord. Knock-out of both genes in zebrafish inhibits ECM formation in the notochord, which subsequently induces apoptosis in notochord cells . Interestingly, the sox9a/b mutant in zebrafish displays a truncated notochord, supporting the notion of a function of sox9 in chordocytes . Ihhb is essential for chondrogenesis in vertebrates, including teleost fish, where its expression has been associated with chondrogenic tissue . In the same study, ihhb was identified in the notochord, further supporting the concept of evolutionary closeness between chondroblasts and chordoblasts. Tgfb3 was another gene found to be expressed in the notochord, and this is also expressed in a number of cartilage tissues in zebrafish . Tgfb3 is also highly expressed in the notochord during early development in the zebrafish, but as development progresses it ceases to be expressed in the notochord. Similarly, we observed a reduced expression of tgfb3 over time in salmon notochord. One of the most highly expressed genes within the notochord is the major collagen of hyaline cartilage, col2a1. This collagen type displays a much higher level of expression than the major type I collagen (colI) found in bone, further confirming the chondroblast-like nature of chordoblasts . Since the notochord appeared early in chordate evolution, as a key structure characterising the clade, and anticipating by far the emergence of hyaline cartilage, which probably first appeared in jawed fish, it may be fair to say that chondroblasts are chordoblast-like, having co-opted morphogenic pathways that evolved together with the notochord in the pre-chordate lineage, early in the Cambrian (see discussion in ).
Both qPCR and RNA-seq employed in this study show a significant down-regulation of the fibril collagen col11a1 at onset of mineralisation (610dº -710dº), suggesting an overall reduced synthesis and re-modelling of extracellular matrix in the notochord sheath concurrent with segmentation and mineral crystal deposition. Nine other ECM genes were also down-regulated at onset of mineralisation (610dº -710dº); these included bcan, col24a 1, col2a1, crtap, fmod, fn1, lepre1, lox and loxl. It was also shown that at 710dº, col11a2 was spatially expressed in regions not undergoing mineralisation – the sites of the prospective intervertebral joints – which suggests that the overall down-regulation of genes may be due to compartmentalisation of expression (Figure 8C). Likewise, expression of ALP in chordoblasts in segments where mineralisation occurs substantiates such a notion. In the notochord, it has been observed that induction of ECM-specific genes over time (ctgf, efemp2 or fibulin 4, fbln7 and tfpi2), and proteins encoded by these genes, might further contribute to the specificity of the segmentation and mineralisation processes. In the KEGG analysis of differentially expressed genes performed in the present study, we discovered a massive down-regulation of many pathways between 510–710 dayº. However, only the Wnt pathway was found to be down-regulated early, in the period between 610 and 710 day º, which may indicate that the Wnt pathway is involved in the segmentation and subsequent mineralisation of the chordacentrae (Figure 7B). Indeed, key Wnt signaling pathway genes were affected, including fzd2, fosl, nr1c2, wnt2, lrp5/6, fosl, sfrp1 and dkk2 (Additional file 4: Figure S2A).
Experimental manipulations in the chick embryo have excluded the possibility that the notochord plays a role in segmentation of the vertebral column, indicating that subdivision of the sclerotome alone leads to this patterning in avian species, and probably in all amniotes . A study performed on the Japanese medaka (Oryzias latipes), supports the notion that this mechanism is also involved in teleost species . Prior to mineralisation of the notochord sheath in medaka, sclerotome-derived cells, which express col10a1, migrate to surround the notochord at segments where the prospective chordacentrae are to develop. The cells differentiate into osteoblasts, and it has been suggested that they, rather than the notochord epithelium, secrete molecules that induce mineralisation of the sheath, thus forming the chordacentrae and subsequently depositing osteoid to form perichordal vertebral bone. Such a mechanism, in which segmentation is independent of the notochord, would be similar to that described in amniotes . On the other hand, in zebrafish, sclerotomal cells do not migrate to surround the notochord in strictly segmented compartments , and, in salmon, the notochord epithelium expresses ALP – a key enzyme in tissue mineralisation – in a spatio-temporal manner that coincides with development of the chordacentrae; here osteoblast precursor cells surrounding the notochord do not express ALP, and thus do not appear to play a role in the mineralisation of the notochord sheath. In medaka, an alternative mechanism for the accumulation of osteoblast precursors at specific sites along the notochord  may be that the cells respond to unidentified chemoattractant guiding factors that are segmentaly secreted by the notochord epithelium. Indeed, to ensure an uninterrupted development of the vertebrae, these cells need to be in place before the chordacentrae form. Moreover, in zebrafish, when the osteoblasts surrounding the notochord are abolished, the initial development of chordacentrae proceeds normally, but they continue to grow, so that the spaces separating adjacent centrae become reduced, in some cases finally leading to partial fusion . Hence, osteoblasts that are to form perichordal bone may provide signalling factors that inhibit the notochord epithelium in its secretion of molecules that promote mineralisation of the sheath, arresting further growth of the chordacentrae, and, by extension, defining a boundry with non-mineralised segments that correspond to where prospective intervertebral ligaments are to develop. Here, we have identified a metameric expression of col11a2 within the notochord that colocalizes with these segments. Apart from being an extracellular structural matrix protein found in the core of the collagen type II fibril, collagen type XI may inhibit maturation of osteoblasts  in the region where intervertebral ligaments develop – here, instead of osteoblasts, fibroblasts condense around the notochord to form collagenous tissue . One of the end players in the Wnt pathway, which is down-regulated at the onset of segmentation, is collagen type XI. This molecule may act as a downstream inhibitor of mineralisation along the whole notochord prior to segmentation, as expression of col11a2 is, at the onset of segmentation, confined to regions where mineralisation does not occur. Hence, through controlling inhibitory signals, the Wnt pathway may play a key role in notochord segmentation.
The gathering of osteoblast precursors around the notochord, and the inhibitory effect of osteoblasts on growth of the chordacentra, suggests a reciprocal interaction between notochord and surrounding tissue. However, our finding of a complex dynamic regulation of a range of anterior-posterior polarity genes and the segmental expression of col11a2 within the notochord epithelium supports the notion that autonomous segmental patterning processes exist in the teleost notochord.
Sequencing and partial analysis of the notochord transcriptome of salmon, the first dataset of its kind from a vertebrate, has provided new insight into the cellular and molecular genetic mechanisms of this organ. The collinear expressions of 18 hox clusters in the notochord represented by 71 hox genes, suggest a possible role of hox genes in anterior-posterior patterning of the notochord. When notochord segmentation occurs, we find an extensive down-regulation of genes, which may reflect a shutdown of complex regulatory developmental pathways leading up to this event. Expression of col11a2 was detected in segments where prospective intervertebral ligaments develop, and we hypothesise that the Wnt pathway, where collagen type XI is one of the end players, may play a key role in segmental patterning. Furthermore, the expression of genes that determine differentiation of chondroblasts indicates that cartilage may have evolved after the co-option of morphogenic pathways that initially evolved together with the notochord in the pre-chordate lineage.
This work was funded by the Research Council of Norway. We gratefully acknowledge the expert help of Marine Harvest at Tveitevågen, Askøy, EWOS at Lønningdal, Norway and Firda Seafood, Norway in rearing the salmon embryos and larvae. Expert technical assistance was provided by Teresa Cieplinska and Nina Ellingsen. We would also like to thank Dr. Rolf B Edvardsen and Dr. Lene Kleppe for scientific discussions of the analysis of RNA seq data.
- Cleaver O, Krieg PA: Notochord patterning of the endoderm. Dev Biol. 2001, 234: 1-12. 10.1006/dbio.2001.0214.PubMedView ArticleGoogle Scholar
- Fleming A, Keynes R, Tannahill D: A central role for the notochord in vertebral patterning. Development. 2004, 131: 873-880. 10.1242/dev.00952.PubMedView ArticleGoogle Scholar
- Monsoro-Burq A-H: Sclerotome development and morphogenesis: when experimental embryology meets genetics. Int J Dev Biol. 2005, 49: 301-308. 10.1387/ijdb.041953am.PubMedView ArticleGoogle Scholar
- Stemple DL: Structure and function of the notochord: an essential organ for chordate development. Development. 2005, 132: 2503-2512. 10.1242/dev.01812.PubMedView ArticleGoogle Scholar
- Wilson L, Maden M: The mechanisms of dorsoventral patterning in the vertebrate neural tube. Dev Biol. 2005, 282: 1-13. 10.1016/j.ydbio.2005.02.027.PubMedView ArticleGoogle Scholar
- Grotmol S, Kryvi H, Nordvik K, Totland GK: Notochord segmentation may lay down the pathway for the development of the vertebral bodies in the Atlantic salmon. Anat Embryol. 2003, 207: 263-272. 10.1007/s00429-003-0349-y.PubMedView ArticleGoogle Scholar
- Bensimon-Brito A, Cardeira J, Cancela ML, Huysseune A, Witten PE: Distinct patterns of notochord mineralization in zebrafish coincide with the localization of Osteocalcin isoform 1 during early vertebral centra formation. BMC Dev Biol. 2012, 12: 28-10.1186/1471-213X-12-28.PubMed CentralPubMedView ArticleGoogle Scholar
- Willems B, Buttner A, Huysseune A, Renn J, Witten PE, Winkler C: Conditional ablation of osteoblasts in medaka. Dev Biol. 2012, 364: 128-137. 10.1016/j.ydbio.2012.01.023.PubMedView ArticleGoogle Scholar
- Grotmol S, Nordvik K, Kryvi H, Totland GK: A segmental pattern of alkaline phosphatase activity within the notochord coincides with the initial formation of the vertebral bodies. J Anat. 2005, 206: 427-436. 10.1111/j.1469-7580.2005.00408.x.PubMedView ArticleGoogle Scholar
- Sagstad A, Grotmol S, Kryvi H, Krossøy C, Totland GK, Malde K, Wang S, Hansen T, Wargelius A: Identification of vimentin- and elastin-like transcripts specifically expressed in developing notochord of Atlantic salmon (Salmo salar L.). Cell Tissue Res. 2011, 346: 191-202. 10.1007/s00441-011-1262-y.PubMedView ArticleGoogle Scholar
- Nordvik K, Kryvi H, Totland GK, Grotmol S: The salmon vertebral body develops through mineralization of two preformed tissues that are encompassed by two layers of bone. J Anat. 2005, 206: 103-114. 10.1111/j.1469-7580.2005.00372.x.PubMed CentralPubMedView ArticleGoogle Scholar
- Grotmol S, Kryvi H, Keynes R, Krossøy C, Nordvik K, Totland GK: Stepwise enforcement of the notochord and its intersection with the myoseptum: an evolutionary path leading to development of the vertebra?. J Anat. 2006, 209: 339-357. 10.1111/j.1469-7580.2006.00618.x.PubMed CentralPubMedView ArticleGoogle Scholar
- Wang S, Kryvi H, Grotmol S, Wargelius A, Krossøy C, Epple M, Neues F, Furmanek T, Totland GK: Mineralization of the vertebral bodies in Atlantic salmon (Salmo salar L.) is initiated segmentally in the form of hydroxyapatite crystal accretions in the notochord sheath. J Anat. 2013, 223: 159-170. 10.1111/joa.12067.PubMed CentralPubMedView ArticleGoogle Scholar
- Prince VE, Price a L, Ho RK: Hox gene expression reveals regionalization along the anteroposterior axis of the zebrafish notochord. Dev Genes Evol. 1998, 208: 517-522. 10.1007/s004270050210.PubMedView ArticleGoogle Scholar
- Mungpakdee S, Seo H-C, Angotzi AR, Dong X, Akalin A, Chourrout D: Differential evolution of the 13 Atlantic salmon Hox clusters. Mol Biol Evol. 2008, 25: 1333-1343. 10.1093/molbev/msn097.PubMedView ArticleGoogle Scholar
- Choi K-S, Harfe B: Hedgehog signaling is required for formation of the notochord sheath and patterning of nuclei pulposi within the intervertebral discs. Dev Biol. 2011, 356: 160-View ArticleGoogle Scholar
- Hansen KD, Brenner SE, Dudoit S: Biases in Illumina transcriptome sequencing caused by random hexamer priming. Nucleic Acids Res. 2010, 38: e131-10.1093/nar/gkq224.PubMed CentralPubMedView ArticleGoogle Scholar
- Stanke M, Morgenstern B: AUGUSTUS: a web server for gene prediction in eukaryotes that allows user-defined constraints. Nucleic Acids Res. 2005, 33: W465-W467. 10.1093/nar/gki458.PubMed CentralPubMedView ArticleGoogle Scholar
- Haas BJ, Delcher AL, Mount SM, Wortman JR, Smith RK, Hannick LI, Maiti R, Ronning CM, Rusch DB, Town CD, Salzberg SL, White O: Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies. Nucleic Acids Res. 2003, 31: 5654-5666. 10.1093/nar/gkg770.PubMed CentralPubMedView ArticleGoogle Scholar
- Li H, Durbin R: Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009, 25: 1754-1760. 10.1093/bioinformatics/btp324.PubMed CentralPubMedView ArticleGoogle Scholar
- Tarazona S, García-Alcalde F, Dopazo J, Ferrer A, Conesa A: Differential expression in RNA-seq: a matter of depth. Genome Res. 2011, 21: 2213-2223. 10.1101/gr.124321.111.PubMed CentralPubMedView ArticleGoogle Scholar
- Ashburner M, Ball C, Blake J, Botstein D: Gene Ontology: tool for the unification of biology. Nat Genet. 2000, 25: 25-29. 10.1038/75556.PubMed CentralPubMedView ArticleGoogle Scholar
- Kanehisa M, Goto S, Sato Y, Furumichi M, Tanabe M: KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res. 2012, 40: D109-D114. 10.1093/nar/gkr988.PubMed CentralPubMedView ArticleGoogle Scholar
- Ye J, Coulouris G, Zaretskaya I, Cutcutache I, Rozen S, Madden TL: Primer-BLAST: a tool to design target-specific primers for polymerase chain reaction. BMC Bioinforma. 2012, 13: 134-10.1186/1471-2105-13-134.View ArticleGoogle Scholar
- Olsvik P a, Lie KK, Jordal A-EO, Nilsen TO, Hordvik I: Evaluation of potential reference genes in real-time RT-PCR studies of Atlantic salmon. BMC Mol Biol. 2005, 6: 21-10.1186/1471-2199-6-21.PubMed CentralPubMedView ArticleGoogle Scholar
- Wargelius A, Fjelldal PG, Nordgarden U, Hansen T: Continuous light affects mineralisation and delays osteoid incorporation in vertebral bone of Atlantic salmon (Salmo salar L.). J Exp Biol. 2009, 212: 656-661. 10.1242/jeb.024000.PubMedView ArticleGoogle Scholar
- Krossøy C, Ornsrud R, Wargelius A: Differential gene expression of bgp and mgp in trabecular and compact bone of Atlantic salmon (Salmo salar L.) vertebrae. J Anat. 2009, 215: 663-672. 10.1111/j.1469-7580.2009.01153.x.PubMed CentralPubMedView ArticleGoogle Scholar
- Langmead B, Trapnell C, Pop M, Salzberg SL: Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009, 10: R25-10.1186/gb-2009-10-3-r25.PubMed CentralPubMedView ArticleGoogle Scholar
- Gotensparre SM, Andersson E, Wargelius A, Hansen T, Johnston I a: Insight into the complex genetic network of tetraploid Atlantic salmon (Salmo salar L.): description of multiple novel Pax-7 splice variants. Gene. 2006, 373: 8-15.PubMedView ArticleGoogle Scholar
- Collins JE, White S, Searle SMJ, Stemple DL: Incorporating RNA-seq data into the zebrafish Ensembl genebuild. Genome Res. 2012, 22: 2067-2078. 10.1101/gr.137901.112.PubMed CentralPubMedView ArticleGoogle Scholar
- Palstra AP, Beltran S, Burgerhout E, Brittijn S a, Magnoni LJ, Henkel CV, Jansen HJ, van den Thillart GEEJM, Spaink HP, Planas JV: Deep RNA sequencing of the skeletal muscle transcriptome in swimming fish. PLoS One. 2013, 8: e53171-10.1371/journal.pone.0053171.PubMed CentralPubMedView ArticleGoogle Scholar
- Liu S, Zhang Y, Zhou Z, Waldbieser G, Sun F, Lu J, Zhang J, Jiang Y, Zhang H, Wang X, Rajendran KV, Khoo L, Kucuktas H, Peatman E, Liu Z: Efficient assembly and annotation of the transcriptome of catfish by RNA-Seq analysis of a doubled haploid homozygote. BMC Genomics. 2012, 13: 595-10.1186/1471-2164-13-595.PubMed CentralPubMedView ArticleGoogle Scholar
- Kogenaru S, Qing Y, Guo Y, Wang N: RNA-seq and microarray complement each other in transcriptome profiling. BMC Genomics. 2012, 13: 629-10.1186/1471-2164-13-629.PubMed CentralPubMedView ArticleGoogle Scholar
- Henkel CV, Burgerhout E, de Wijze DL, Dirks RP, Minegishi Y, Jansen HJ, Spaink HP, Dufour S, Weltzien F-A, Tsukamoto K, van den Thillart GEEJM: Primitive duplicate Hox clusters in the European eel’s genome. PLoS One. 2012, 7: e32231-10.1371/journal.pone.0032231.PubMed CentralPubMedView ArticleGoogle Scholar
- Akiyama H, Lefebvre V: Unraveling the transcriptional regulatory machinery in chondrogenesis. J Bone Miner Metab. 2011, 29: 390-395. 10.1007/s00774-011-0273-9.PubMed CentralPubMedView ArticleGoogle Scholar
- Smits P, Lefebvre V: Sox5 and Sox6 are required for notochord extracellular matrix sheath formation, notochord cell survival and development of the nucleus pulposus of intervertebral discs. Development. 2003, 130: 1135-1148. 10.1242/dev.00331.PubMedView ArticleGoogle Scholar
- Yan Y-L, Willoughby J, Liu D, Crump JG, Wilson C, Miller CT, Singer A, Kimmel C, Westerfield M, Postlethwait JH: 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.PubMedView ArticleGoogle Scholar
- Avaron F, Hoffman L, Guay D, Akimenko M a: Characterization of two new zebrafish members of the hedgehog family: atypical expression of a zebrafish indian hedgehog gene in skeletal elements of both endochondral and dermal origins. Dev Dyn. 2006, 235: 478-489. 10.1002/dvdy.20619.PubMedView ArticleGoogle Scholar
- Cheah FSH, Jabs EW, Chong SS: Genomic, cDNA, and embryonic expression analysis of zebrafish transforming growth factor beta 3 (tgfbeta3). Dev Dyn. 2005, 232: 1021-1030. 10.1002/dvdy.20282.PubMedView ArticleGoogle Scholar
- Yan YL, Hatta K, Riggleman B, Postlethwait JH: Expression of a type II collagen gene in the zebrafish embryonic axis. Dev Dyn. 1995, 203: 363-376. 10.1002/aja.1002030308.PubMedView ArticleGoogle Scholar
- Senthinathan B, Sousa C, Tannahill D, Keynes R: The generation of vertebral segmental patterning in the chick embryo. J Anat. 2012, 220: 591-602. 10.1111/j.1469-7580.2012.01497.x.PubMed CentralPubMedView ArticleGoogle Scholar
- Renn J, Büttner A, To TT, Chan SJ, Winkler C: A col10a1:nlGFP transgenic line displays putative osteoblast precursors at the medaka notochordal sheath prior to mineralization. Dev Biol. 2013, 381 (1): 134-143. 10.1016/j.ydbio.2013.05.030.PubMedView ArticleGoogle Scholar
- Morin-Kensicki EM, Melancon E, Eisen JS: Segmental relationship between somites and vertebral column in zebrafish. Development. 2002, 129: 3851-3860.PubMedGoogle Scholar
- Kahler R, Yingst SMC, Hoeppner LH, Jensen ED, Krawczak D, Oxford JT, Westendorf JJ: Collagen 11a1 is indirectly activated by lymphocyte enhancer-binding factor 1 (Lef1) and negatively regulates osteoblast maturation. Matrix Biol. 2008, 27: 330-338. 10.1016/j.matbio.2008.01.002.PubMed CentralPubMedView ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.