Transcriptomic changes during regeneration of the central nervous system in an echinoderm
© Mashanov et al.; licensee BioMed Central Ltd. 2014
Received: 2 January 2014
Accepted: 6 May 2014
Published: 12 May 2014
Echinoderms are emerging as important models in regenerative biology. Significant amount of data are available on cellular mechanisms of post-traumatic repair in these animals, whereas studies of gene expression are rare. In this study, we employ high-throughput sequencing to analyze the transcriptome of the normal and regenerating radial nerve cord (a homolog of the chordate neural tube), in the sea cucumber Holothuria glaberrima.
Our de novo assembly yielded 70,173 contigs, of which 24,324 showed significant similarity to known protein-coding sequences. Expression profiling revealed large-scale changes in gene expression (4,023 and 3,257 up-regulated and down-regulated transcripts, respectively) associated with regeneration. Functional analysis of sets of differentially expressed genes suggested that among the most extensively over-represented pathways were those involved in the extracellular matrix (ECM) remodeling and ECM-cell interactions, indicating a key role of the ECM in regeneration. We also searched the sea cucumber transcriptome for homologs of factors known to be involved in acquisition and/or control of pluripotency. We identified eleven genes that were expressed both in the normal and regenerating tissues. Of these, only Myc was present at significantly higher levels in regeneration, whereas the expression of Bmi-1 was significantly reduced. We also sought to get insight into which transcription factors may operate at the top of the regulatory hierarchy to control gene expression in regeneration. Our analysis yielded eleven putative transcription factors, which constitute good candidates for further functional studies. The identified candidate transcription factors included not only known regeneration-related genes, but also factors not previously implicated as regulators of post-traumatic tissue regrowth. Functional annotation also suggested that one of the possible adaptations contributing to fast and efficient neural regeneration in echinoderms may be related to suppression of excitotoxicity.
Our transcriptomic analysis corroborates existing data on cellular mechanisms implicated in regeneration in sea cucumbers. More importantly, however, it also illuminates new aspects of echinoderm regeneration, which have been scarcely studied or overlooked altogether. The most significant outcome of the present work is that it lays out a roadmap for future studies of regulatory mechanisms by providing a list of key candidate genes for functional analysis.
KeywordsTranscriptome RNA-seq Gene expression Regeneration Echinoderm Nervous system Transcription factors Injury Extracellular matrix
Echinoderms constitute a phylum of marine invertebrates closely related to chordates. Their phylogenetic position as a non-chordate deuterostome phylum combined with the ability to regenerate various body parts makes them a valuable group, which can give unique insights into fundamental issues of regenerative biology and provide new clues to finding better treatment of human conditions. Recent analyses of cellular events underlying post-traumatic regeneration in echinoderms (reviewed in [1, 2]) identified interesting parallels with corresponding processes in regeneration-competent vertebrates, pointing to reparative mechanisms that might have been evolutionary preserved throughout Deuterostomia and could potentially be re-activated in poorly regenerating vertebrates. However, the paucity of genomic and transcriptomic information has precluded major progress in understanding key regulators of regeneration at the molecular level [3, 4].
Our previous research [1, 6–8] showed that following a transverse cut, the injured organs of the radial organ complex on either side of the wound start growing across the wound gap and eventually reconnect to restore the anatomical continuity (Figure 2). The newly regenerated structures then completely re-acquire their normal tissue architecture and resume their functions. Radial nerve cord regeneration involves extensive dedifferentiation of radial glial cells in the vicinity of the injury. These dedifferentiated glial cells play the key role in subsequent regeneration through extensive proliferation, ECM invasion, and differentiation into new neurons and glial cells. The newly produced neurons are thought to be functionally integrated into the CNS circuitry, as they survive for extended periods of time and form typical synaptic connections [1, 7].
The main goal of the present study is to help understand the molecular basis underlying the extensive regenerative capacity of the central nervous system in the sea cucumber Holothuria glaberrima by providing an outline of the transcriptomic landscape and thus identifying possible directions of future research. To this end, we used deep RNA sequencing on both the 454 and Illumina platforms to analyze changes in the transcriptome that occurred on day 2, day 12, and day 20 after injury. These time points were chosen based on our previous studies of cellular events in the regenerating radial nerve cord of H. glaberrima. Day 2 post-injury (Figure 2C, D) is the early post-injury phase of extensive dedifferentiation of radial glia, axonal degeneration, and programmed cell death in the injured radial nerve. Day 12 post injury (Figure 2E, F) corresponds to a period of active growth across the wound gap; dividing cells are most abundant at this stage. Day 20 (Figure 2G, H) post injury is a late regeneration phase, when the two growing regenerates have restored their anatomical continuity and started to resume their typical histological architecture [1, 7]. The present study provides first insights into gene expression changes that underlie these previously described cellular events.
Results and discussion
Sequencing and assembly: technical information about the assembly
Summary statistics of sequencing runs and read processing
Modal (most frequent)
Total Raw 454 reads
49 – 1,201
Total Cleaned 454 reads
60 – 994
Raw Illimina Norm #1
Raw Illimina Norm #2
Raw Illimina d2 #1
Raw Illimina d2 #2
Raw Illimina d12 #1
Raw Illimina d12 #2
Raw Illimina d20 #1
Raw Illimina d20 #2
Total Raw Illumina
Cleaned Illimina Norm #1
32 – 61
Cleaned Illimina Norm #2
32 – 61
Cleaned Illimina d2 #1
32 – 61
Cleaned Illimina d2 #2
32 – 61
Cleaned Illimina d12 #1
32 – 61
Cleaned Illimina d12 #2
32 – 61
Cleaned Illimina d20 #1
32 – 61
Cleaned Illimina d20 #2
32 – 61
Total Cleaned Illumina
Summary statistics for the intermediate and final assembly steps
Normalized and non-normalized 454 reads combined
100 – 20,566
Velvet (k-mer length=31)
100 – 16,096
Velvet (k-mer length=37)
100 – 27,112
Velvet (k-mer length=41)
100 – 27,083
Velvet (k-mer length=45)
100 – 25,388
Velvet (k-mer length=51)
100 – 23,585
Velvet (k-mer length=55)
100 – 23,018
Reference Assembly (CAP3)
100 – 27,089
Validation of assembled contigs by re-sequencing using Sanger technology
Contig length, bp
Checked by Sanger
both 5’ and 3’ ends are missing
both 5’ and 3’ ends are missing
5’ end is missing
both 5’ and 3’ ends are missing
In order to determine the proportion of the contigs in the reference library, which corresponded to known proteins, we performed a BLASTX search against publicly available protein databases. In the first round of search, the sequences were matched against the Swissprot database. The contigs, which did not produce hits passing the significance threshold corresponding to anE-value < 1e-6 were subsequently subjected to a second round of BLASTX search against the non-redundant (nr) NCBI protein database with the same threshold. Overall, 24,324 (or 33.66%) contigs had significant BLAST hits. The results of the BLAST analysis are listed in Additional file 1.
We also annotated the sea cucumber transcriptome by performing reciprocal best BLAST hit analysis (with a threshold e-value < 1e-6) versus the NCBI’s collection of the sea urchin Strongylocentrotus purpuratus predicted protein sequences , the echinoderm species whose genome has been most thoroughly characterized so far. There were 23,637 one-way BLASTX matches between the H. glaberrima contigs and the S. purpuratus proteins and 19,869 one-way TBLASTN matches between the sea urchin proteins and the contigs of our transcriptome. The number of reciprocal blast matches (putative orthologous sequences) was 8,577. The results of this analysis are listed in Additional file 2.
We, obviously, do not expect all our 70,173 contigs to represent individual sea cucumber genes. It is impossible to give an exact answer on the number of unique genes represented by de novo assembled contigs without having complete genomic information. Thus, we can only provide an educated guess here. The genome of the sea urchin S. purpuratus encodes ∼23,300 genes, of which ∼7,000 are presumed orthologs of mammalian genes. In the course of our analysis, a similar number (8,522) of unique mouse proteins showed significant similarity to sequences contained in the assembled transcriptome of H. glaberrima. If we assume the same level of genomic similarity between mammals and each of the two echinoderm species, the similar number of “mammalian genes” observed in the sea urchin genome and the sea cucumber transcriptome would imply that (i) sea cucumbers have roughly the same number of genes as sea urchins (∼23,000), and (ii) most of these genes are represented in our reference library constructed from mRNA samples from non-injured and regenerating animals. If the above reasoning is correct, there is a ∼3× redundancy in our assembly.
A similar redundancy ratio (∼2.4×) can be obtained, if we consider that, when blasted against the reference mouse proteome, 20,619 of 70,173 contigs of the sea cucumber reference library matched 8,522 unique mouse proteins. Some of this redundancy is part of the “natural” variation that is expected from differences in mRNA processing (such as splicing). In fact, when manually inspecting assembled contigs, we saw polymorphic transcripts, which were especially common among retroelements. Additional variation can be due to the limitations of the sequencing techniques and/or de novo assembly programs.
Differential gene expression in radial organ complex regeneration
At all three time points after the injury, the majority (∼63-85%) of the significant differentially expressed contigs were up- or down-regulated between 2- and 4-fold relative to the normal animals (Additional file 4), suggesting that relatively small changes in transcript abundance of most genes are sufficient for regeneration to occur. Among the most extreme outliers in our differential expression analyses were sequences that were identified as retrotransposon-derived transcripts. Some of them showed an over 50-fold change in expression during regeneration. This unexpected finding prompted us to undertake a separate study of these mobile genetic elements that has already been published elsewhere .
Functional annotation of differentially expressed genes at different time points of regeneration
- 1.Among the most enriched functional categories associated with both up-regulated and down-regulated genes at all time points were those related to synthesis and organization of the extracellular matrix (ECM) components, ECM remodeling, and interaction between cells and the extracellular matrix (see below for a detailed discussion).
Functional annotation terms associated with normal physiology, differentiation, and development of the nervous tissue were over-represented among the down-regulated genes on days 2 and 12 post-injury, and some of those annotation categories were also enriched among negatively regulated genes even as late as after 20 days post-injury. This observation correlates well with previously published morphological studies showing extensive dedifferentiation in the regenerating radial nerve at these time points [1, 7]. Interestingly, annotation categories related to glycolysis were also enriched among the down-regulated genes on day 2 and 12.
Since our tissue samples, in addition to the radial nerve cord per se, also contained some adjacent tissues, including the contractile epithelium of the water-vascular canal and the coelomic myoepithelium of the body wall (see Methods), annotation terms associated with structural components of muscular tissue, as well as with muscle development and physiology, also appeared in the analysis. These terms were enriched in sets of down-regulated genes at all three time points of regeneration corroborating earlier observations of muscular dedifferentiation during body wall regeneration in sea cucumbers .
On day 2 post-injury, the up-regulated genes were associated with over-represented terms related to initiation of DNA replication and protein translation. On day 12, positively regulated genes were characterized by continued over-representation of terms associated with DNA synthesis and cell cycle. These data corroborate our cell proliferation assay, which suggested that the peak of cell division in the regenerating radial nerve cord occurs on days 8 thru 12 after injury . On day 12, up-regulated genes are also enriched in annotation categories associated with activation of the innate immune response. The latter group of functional terms remains over-represented among up-regulated genes on day 20.
All three regeneration time points are characterized by over-representation of annotation categories associated with developmental morphogenesis, indicating involvement of ontogenic processes in regeneration.
Putative regulation of groups of co-expressed genes by transcription factors (TFs)
Among these predicted 11 TFs, there are genes that have been previously implicated in post-traumatic processes and developmental processes in various organisms. For example, NfkB1 is known to affect expression of broad range of downstream genes involved in various biological processes including immunity, differentiation, and programmed cell death. For example, elevated NfkB signaling has been previously shown to activate the Wnt signaling pathway and thus induce dedifferentiation of nonstem cells . Another TF, serum response factor (SRF), was shown to be one of the key genes involved in post-traumatic regeneration initiation in planarians . In gastric ulcer healing, SRF promotes re-epithelialization and muscle regeneration through activation of cell migration and proliferation . Moreover, SRF is also implicated in neuronal cell migration and axonal guidance through regulation of components of the actin cytoskeleton . Still another gene, CCAAT/enhancer binding protein (CEBP) was suggested to be involved in regulation of the innate immune response during tissue injury repair .
Interestingly, the candidate TFs identified in this study included not only previously known regeneration-related genes, but also factors not previously known to act as regulators of post-traumatic tissue regrowth, such as, for example, liver X receptor, Fli1, PLAG1, Ebf3, Esrrb. The potential role of these genes in regeneration deserves further attention in future research.
Discussion of selected functional gene groups
The preceding section provided an overview of unbiased functional characterization of the regeneration-associated genes at the global, transcriptome-wide level. Below, we further zoom in on certain groups of differentially expressed genes, which we picked from our database based on the results of the above analysis, prior biological knowledge, or both.
As revealed by DAVID analysis, the set of differentially expressed genes at the early post-injury stage (day 2) includes many known cancer-related genes (Additional file 6). For example, pathway mapping revealed differential regulation of Wnt receptors (Fzd3 and Fzd4) and ligands (Wnt9, Wnt2, and Wnt6). Another notable observation is down-regulation of survivin (Birc5) (Additional file 8). This gene codes for a multifunctional protein, highly expressed in most human cancers, and implicated in both suppression of programmed cell death  and regulation of cell division [28–30]. We have previously shown that elevated expression of survivin in regenerating sea cucumber intestinal tissues correlated with low levels of apoptosis . Reduced expression of this gene in the regenerating radial nerve cord may thus be at least in part explained as being associated with extensive programmed cells death in the vicinity of the injury .
Differential expression of oncogenes early in regeneration has been also reported for other model systems, including early limb blastema in axolotl  and can be explained by the fact that both regeneration and cancer progression are developmental processes that share a number of key mechanisms including cell division, programmed cell death, and differentiation.
As mentioned above, among the most significantly over-represented pathways associated with differentially expressed genes at all three time points of the radial nerve cord regeneration were those related to the extracellular matrix (ECM) components and ECM-cell interactions (see, for example, Additional file 9 showing mapping of our RNA-seq data to the Focal Adhesion KEGG pathway). One example is significantly reduced expression of genes coding for basal lamina proteins on day 2 (Col4a1, Lama4), but up-regulation of the fibrillar collagens Col5a1 and Col11a2. These data correlate well with previous observations of breakdown of the basal lamina during the early post-injury phase .
Of particular interest is concurrent up-regulation of both matrix metalloproteases (MMPs) and their inhibitors, TIMPs, in the regenerating radial organ complex. By breaking down components of the connective tissue matrix at the injury site and thus affecting cell migration and proliferation, epithelialization, differentiation, and apoptosis, MMPs are known to facilitate wound healing and regeneration [32–34]. However, up-regulation of TIMPs is as important for precise regulation of the regenerative processes, as they protect newly synthesized ECM matrix from degradation .
Proper interactions between cells and the ECM are essential both for correct tissue organization and signal transduction. Among the main cell adhesion molecules mediating these interactions are integrins [35–37]. In regeneration of the radial nerve in the sea cucumber, integrin beta and integrin alpha-8 are significantly up-regulated (Additional file 9). Integrins affect cytoskeletal organization through Cdc42, a member of the Rho family of small GTPases [38, 39]. Expression levels of the Cdc42 transcript were consistently highly elevated in the sea cucumber radial nerve regeneration, suggesting a possible involvement of the integrin-Cdc42 pathway in control of ECM-cell interactions in this animal model.
Besides integrins, other cell adhesion molecules are also up-regulated during the early post-injury phase. These include selectins (Additional file 6). Interestingly, expression of selectins is known to be induced by NF-kB , which was putatively identified as one of the putative key transcription factors driving differential gene expression during the early post-injury stage of neural regeneration in our model (see above).
To our surprise, we also found that expression of the Bmi-1 homolog was significantly reduced in the regenerating tissues on days 2 and 12 post-injury. The remaining 9 genes were expressed at the same level both in the non-injured and regenerating tissues.
A possible explanation that can be proposed to account for the observed data is that although the analyzed pluripotency factors do not show any large scale over-expression in regeneration, most of them are still expressed at a certain level both in the normal and regenerating tissues. Therefore, it may be hypothesized that this basal level constitutes sufficient environment for dedifferentiation to be triggered by Myc upregulation alone. Interestingly, a similar situation has been reported in non-injured and regenerating tissues of lower vertebrates, such as Danio rerio and Xenopus, where pluripotency markers are never shut off completely under normal conditions. Even though the expression level of these genes remained largely at the same level after the injury, it was hypothesized that this basal expression is neverhteless sufficient to facilitate regeneration upon damage .
Genes associated with neurogenesis
To our surprise, homologs of some of the key markers of vertebrate neural stem cells, including nestin and vimentin, were absent from the sea cucumber transcriptome. Likewise, transcripts of some of the important pro-neural factors , such as Mash1 and Neurog2 were also not detected in either the normal or regenerating animals. This may be due to the fact that the program of post-traumatic neurogenesis in sea cucumbers is not known and, obviously, may not entirely consist of the mechanisms that regulate neurogenesis in vertebrates, whose genes were used as the reference.
Prevention of excitotoxic neuronal cell death
This study was conceived as a first stage in exploring molecular mechanisms behind the observed cellular processes in echinoderm CNS regeneration. In general, functional annotations of the differentially expressed genes corroborate well our previous morphological data, but also open up potential new avenues for future research. As mentioned above, our results point out to the important role of the ECM remodeling in regeneration of the radial complex in the sea cucumber. So far, reorganization of the connective tissue in regenerating echinoderms has received little attention. There have been just two experimental studies addressing this issue directly and in both cases they were focused on regeneration of the digestive tube only [33, 34].
Another promising line of future research would be to experimentally test the predictions of this study suggesting the existence of mechanisms suppressing excitotoxicity in the injured CNS. If these mechanisms actually exist, their understanding will be valuable for devising new therapies to prevent excitocytotic neuronal death following, for example, brain and spinal cord injury.
One of the most important outcomes from this study is a predicted list of putative transcription factors, which presumably control differential expression of large groups of downstream genes and thus occupy key positions in regulatory networks controlling regeneration. These genes represent promising candidates for future functional analysis.
Among other interesting findings is that post-traumatic regeneration of the radial nerve cord did not involve large-scale over-expression of pluripotency factors. Many of these genes were already expressed in intact tissues, and only Myc showed up-regulation after injury.
We are well aware of the limitations in our study. For example, by design, our functional annotation was dependent on matching the sea cucumber contigs against a well studied proteome from another organism (in this case, mouse). This approach could have led to many potentially relevant sea cucumber-specific sequences being excluded from the analysis. This issue cannot be resolved without carrying out a separate study aimed at characterization of the ‘new’ or ‘unknown’ sequences, which do not have significant homologs in current databases.
The present paper, like most of other high-throughput studies of gene expression, uses mRNA abundance levels to get insight into how changes in gene expression might affect the phenotype of tissues and cells, although it is largely the quantity of the protein that directly determines the phenotype. However, for the time being, transcriptomic approaches are justified by the fact that the current methodologies for direct quantification of protein expression are either less reliable or more laborious and expensive than mRNA-based studies.
Notwithstanding the limitations, the results and predictions reported above are valuable, because they provide a number of clearly defined testable hypotheses, whereas the associated pitfalls and limitations are well known to many researchers working with ‘non-model’ organisms and are not unresolvable in the future.
Sea cucumber collection, maintenance, and radial nerve cord injury
Adult individuals of the brown rock sea cucumber Holothuria glaberrima Selenka, 1867 were collected from the intertidal zone of the Atlantic coast of Puerto Rico. The reader is referred to our previous publications for detailed description of the injury paradigm and surgical procedures [1, 8, 12]. Briefly, the animals were brought to the laboratory and induced to eviscerate (autotomize their viscera) by injecting 0.35 M KCl into the coelomic cavity. The sea cucumbers needed to be eviscerated, because our surgery involved cutting the radial nerve cord from the inside of the body. In order to perform the transection we needed to get access to the inner side of the body wall. We did so by anesthetizing the animals in 0.2% chlorobutanol (Sigma) for 10–30 min and then exposing the coelomic surface of the body wall through the anus by pushing a glass rod against a radial region of the epidermis at the mid-body level. It was only possible after the animals have been induced to autotomize the viscera. H. glaberrima does not survive penetrating injuries to the body wall (when there is a direct communication between the coelom and the environment). Nevertheless, it readily regenerates if the injury is made from the coelomic side of the body wall without disrupting the epidermis. We thus cut the radial organs of the mid-ventral radius (including the longitudinal muscle band, water-vascular canal, the radial nerve cord, and the underlying connective tissue), but not the epidermis, with a sharp razor blade. The operated animals were returned to the aquaria and kept at room temperature in well-aerated seawater, which was changed regularly. All experiments were conducted in accordance with the NIH and University of Puerto Rico guidelines for the care and use of laboratory animals.
RNA extraction and library preparation
Samples for high-throughput sequencing were prepared as previously described . From each regenerating animal, we excised the region of the injury gap (∼3–4 mm wide) plus ∼3 mm of stump (‘old’) tissue on either side of the injury plane. The wet weight of an individual tissue sample was around 10–15 mg. Tissue samples of comparable size and weight were also excised from uninjured animals. During tissue sampling, every effort was made to separate the radial nerve cord from surrounding tissues. However, isolation of the pure nerve cord by surgical means turned out to be practically impossible. Therefore, our tissue samples also consistently contained small amounts of the surrounding connective tissue, an accompanying segment of the water-vascular canal and a stretch of the contractile coelomic epithelium of the body wall because of close anatomical proximity of these structures to the radial nerve cord (Figure 2). For the 454 platform, we generated three non-normalized libraries representing uninjured animals (38 individuals), days 2 and 6 post-injury (63 and 71 animals, respectively), and days 12 and 20 post-injury (62 and 66 animals, respectively). In addition, equal quantities of the above samples were combined to prepare a normalized library. The samples extracted from the regenerating animals on day 6 post-injury were only used for 454 sequencing to increase transcript diversity in the final assembled transcriptome, and were not subjected to sequencing on the Illumina platform (see below). Total RNA was extracted using TRI reagent (Sigma), assessed for quality on an Agilent 2100 Bioanalyzer with the RNA 6000 Nano chips, and subjected to two rounds of poly(A) selection using Poly(A)Purist technology (Ambion). Normalization procedure was performed with a TRIMMER kit (Evrogen) following the manufacturer’s protocol. The normalized cDNA was amplified using Advantage 2 Polymerase Mix (Clontech).
For Illumina sequencing two non-normalized libraries were prepared for each of the four conditions: (i) uninjured radial organ complex (total RNA samples were pooled from 4 and 3 animals for the first and second libraries, respectively); (ii) day 2 post-injury (20 and 19 animals were used); (iii) day 12 post-injury (20 animals were used for each of the libraries); and (iv) day 20 post-injury (15 animals were used for each of the libraries). The final stages in library preparation and sequencing were performed by sequencing service providers at the DNA Facility of the University of Iowa (Genome Sequencer FLX System, Roche) and the Genome Sequencing and Analysis Core Facility of the Duke Institute for Genome Sciences and Policy (Illumina Genome Analyzer IIx, Illumina). Raw sequencing reads from both the 454 and Illumina platforms were deposited at NCBI Sequence Read Archive (SRA) under accession number NCBI:SRA051990 .
De novo assembly pipeline
The first round of filtering/cleaning of 454 reads was performed with SeqClean  and included removal of synthetic adaptor/primer sequences used in library preparation and screening for E. coli contamination (GenBank:U00096). The reads were then processed with the standalone version of PRINSEQ tool (v 0.14.2)  with the following filtering parameters: minimum length — 60 bases, maximum length — 1100 bases (twice the mean length), maximum allowed percentage of N’s – 1%, minimum mean quality — 17. Also, exact duplicates and reverse complement exact duplicates were removed.
Raw Illumina sequencing reads were quality checked using the FastQC tool (v 0.9.1)  and then trimmed using FASTX-Toolkit (v 0.0.13)  to remove Illumina adapters, discard bases with quality < 20, and reads shorter than 32 bases.
We applied a complex pipeline to assemble the pooled reads from all libraries into a single reference contig set (Figure 3). First, we used MIRA 3.2.1  to assemble all normalized and non-normalized 454 reads. The Illumina reads were assembled with Velvet (v.1.1.03)  and Oases (v.0.1.21). Separate assembly runs were performed at different kmer lengths (31 to 55). Cleaned 454 reads were introduced into each of these runs to improve the assembly. The contigs longer than 100 bp resulting from the Velvet/Oases assemblies were combined together with 454 contigs for the final assembly with CAP3, to produce what we refer to as the reference library. The files containing the contigs, their annotations, and expression values were parsed and analyzed using custom written scripts, which are available from the authors by request.
Differential gene expression in regeneration
For digital expression assay based on RNA-seq data, we used Bowtie 2  to map Illumina reads to the contigs of the reference library. The raw read counts for each of the eight Illumina libraries (four conditions, two biological replicates per condition, see above) were used as input to the DESeq R package  to perform pairwise differential expression analysis between the intact and regenerating animals. The estimateSizeFactors function of the DESeq package was used to normalize gene counts. The resulting P values were adjusted for multiple testing with Benjamini-Hochberg procedure. Genes with an adjusted P value < 0.001 and a fold change greater than 2 were considered differentially expressed.
In order to validate the changes in gene expression determined by RNA-seq, we selected 21 genes with different levels of transcript abundances for real-time PCR analysis. Poly(A) RNA was extracted as described above. PCR primers were designed using Primer Premier 5.0 software (PREMIER Biosoft International). Their sequences are shown in Additional file 10. RNA was reverse transcribed with random hexamer primers and SuperScript II reverse transcriptase (Invitrogen). Template cDNA was diluted 10-fold or 100-fold and used at 2 μl per 25 μl of PCR reaction with Brilliant SYBR Green Master Mix or Brilliant II SYBR Green Master Mix (Agilent) following the manufacturer’s protocol. Real-time PCR reactions were run on Mx3005P qPCR System (Stratagene). The reactions were performed on three independent samples per condition (biological replicates). Each sample was analyzed at least twice, making sure that the difference between technical replicates was less than 0.5 Ct . PCR efficiencies were evaluated by running five 10-fold dilutions of the cDNA template in a PCR reaction and were considered acceptable if the corresponding slope values determined by the MxPro QPCR software (Strategene) lay between -3.2 and -3.5 and the R 2 was above 0.98. All expression values were normalized relative to the ’normalization factor’ calculated with the geNorm Visual Basic Application for Microsoft Excel  from the expression of values of four genes (Rpl18a, Atp6l, Eef2, and Sod), which were identified among the least changing transcripts across the experimental conditions by RNA-seq.
The assembled contigs of the reference library were used as input for the BLASTX homology search. Initially, the sea cucumber sequences were compared with the Swiss-Prot database with a cut-off significance threshold set at 1e-6. Those contigs that lacked matches were then subjected to a second round of BLASTX search against the larger NCBI non-redundant database. In addition, the sea cucumber transcriptome was also annotated versus the NCBI’s collection of the sea urchin predicted protein sequences  by performing reciprocal best BLAST hit analysis (with a threshold e-value < 1e-6).
Functional annotation of differentially expressed genes was performed with DAVID Gene Ontology web server . In order to be able to use this tool, we matched all 70,173 contigs of our assembled transcriptome to the non-redundant reference proteome of the mouse , release 2012_05 using BLASTX with the cut-off e-value of 1e-6. Overall, our assembled contigs showed significant homology to 8,522 mouse genes. We then submitted the annotated lists of differentially expressed genes as an input to DAVID and analyzed them against the background of all annotated genes of our reference library. For pathways of interest, KEGGanim  was used to generate diagrams showing changes in expression level of individual genes. This approach allows to observe expression dynamics in the context of specific pathway interactions.
Expression profile clustering
Unsupervised gene expression profile clustering of differentially expressed genes (i.e., the genes showing more than two-fold change in expression with adjusted P < 0.01) was performed using AutoSOME 2.0 software . Prior to clustering, the original count data were subjected to variance stabilization transformation in the DESeq package. The parameters were set as suggested by the authors of the program (running mode: precision, number of ensemble runs: 500, P-value threshold: 0.05). Unit variance, median centering (rows), and sum squares (both rows and columns) normalization procedures were applied. Eight clusters containing more than 100 contigs were visualized on a heatmap (Figure 7) and considered for further analysis.
Identification of putative regeneration-associated transcription factors
Over-represented transcription factors associated with co-expressed genes were predicted with oPOSSUM v3.0 software . Lists of gene identifiers corresponding to each of the cluster identified by AutoSOME were used as input. The list of gene identifiers corresponding to the entire reference library was used as the background set. The JASPAR CORE collection was used as a set of transcription binding site matrices. The conservation cutoff and the matrix score threshold were left at their default values of 0.4 and 85%, respectively.
In order to select potentially relevant transcription factors, we followed the suggestions of the software’s authors and plotted the Z-score against Fisher score for the transcription factors associated with the genes in each of the cluster. The genes, which showed clear segregation of the scores, were considered for further analysis, if changes in their expression were significant (adjusted P < 0.05) at least at one of the three analyzed time points. If the expression level of the putative transcription factor changed in the same direction as the median gene expression in the gene cluster, this transcription factor was considered a transcriptional activator. If the change in expression was in the reverse direction, the transcription factor was considered a transcriptional repressor.
Availability of supporting data
Raw sequencing reads supporting the results of this article are available in the NCBI SRA repository . The contigs of the reference library, representing the transcriptomic diversity in the normal and regenerating radial organ complex of H. glaberrima are available in the LabArchives notebook . Other data sets are included within the article and its additional files.
Long terminal repeat
Open reading frame
- P adj :
Adjusted P -value
Next-generation sequencing of expressed mRNA
The authors acknowledge the assitance of Rey Rosa in animal collection and maintenance. We also thank Prof. B. Galliot, Prof. L. Moroz, and Prof. H. Ortiz-Zuazaga for stimulating discussions and valuable suggestions. The study was supported by the NIH (Grants 1SC1GM084770-01, 1R03NS065275-01), the NSF (Grants IOS-0842870, IOS-1252679), several NSF and NIH equipment funds for the Sequencing Genomic Facility (SGF UPRRP) and the University of Puerto Rico.
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