Abstract
Long non-coding RNAs (lncRNAs) have been shown to play regulatory roles
in a diverse range of biological processes and are associated with the
outcomes of various diseases. The majority of studies about lncRNAs
focus on model organisms, with lessened investigation in non-model
organisms to date. Herein, we have undertaken an investigation on
lncRNA in two zoanthids (cnidarian): Protolpalythoa varibilis and
Palythoa caribaeorum. A total of 11,206 and 13,240 lncRNAs were
detected in P. variabilis and P. caribaeorum transcriptome,
respectively. Comparison using NONCODE database indicated that the
majority of these lncRNAs is taxonomically species-restricted with no
identifiable orthologs. Even so, we found cases in which short regions
of P. caribaeorum’s lncRNAs were similar to vertebrate species’
lncRNAs, and could be associated with lncRNA conserved regulatory
functions. Consequently, some high-confidence lncRNA-mRNA interactions
were predicted based on such conserved regions, therefore revealing
possible involvement of lncRNAs in posttranscriptional processing and
regulation in anthozoans. Moreover, investigation of differentially
expressed lncRNAs, in healthy colonies and colonial individuals
undergoing natural bleaching, indicated that some up-regulated lncRNAs
in P. caribaeorum could posttranscriptionally regulate the mRNAs
encoding proteins of Ras-mediated signal transduction pathway and
components of innate immune-system, which could contribute to the
molecular response of coral bleaching.
Introduction
Advancement of high throughput sequencing technologies has allowed wide
characterization of an increasing number of RNA repertoires from
diverse organisms; however, only a small proportion of these
effectively code for proteins and the majority remains to be studied in
depth. For instance, around 1% of the human genome correlates to
protein-coding transcripts, while around 4% to 9% of genome are
estimated to be transcribed of which the functions are still poorly
understood^[40]1. Due to the lack of protein-coding capacity and
relatively low conservation, some of these transcripts are referred to
as non-coding RNAs (ncRNAs) and at the time of their identification
they were considered as “junk transcripts”^[41]2. Nevertheless,
up-to-date in-depth analyses of ncRNAs indicated that a small
proportion of these ncRNAs are implicated in a variety of biological
regulations cascades and pathways, and correlated strongly with a wide
range of developmental processes and diseases^[42]3, [43]4. Notably,
the majority of ncRNAs discovered in recent studies had a length
>200 nt, namely long noncoding RNAs (lncRNAs). Evidence has accumulated
that lncRNAs could serve as key transcriptional regulators in numerous
biological processes, one of the best-characterized examples of which
is their role in genomic imprinting. The lncRNA namely X-inactive
specific transcript (XIST) is responsible for inactivating the X
chromosome in mammals by recruiting PRC2 (Polycomb repressive complex).
In mice, XIST deletion causes aberrant expression of the X chromosome
and female-specific lethality^[44]5. Another example includes
p53-regulated lncRNAs in mammalian cells, i.e. lincRNA-p21 and PANDA,
which are capable of interacting with DNA-binding proteins and nuclear
transcription factor Y alpha and suppress transcription of the target
gene^[45]6. In addition, some investigation implicates the
participation of lncRNAs in the regulation of gene expression at the
posttranscriptional level. For example, an lncRNA known as cytoplasmic
1/2-sbsRNA was shown to promote mRNA decay by partial base-pairing with
its specific target mRNA^[46]7. In another case, it was demonstrated
that lincRNA-p21 represses the translation of mRNA encoding β-catenin
and JunB by partial base-pairing and recruitment of translation^[47]8.
Apart from these examples on the function of lncRNAs at the
transcriptional level of gene regulation, lncRNAs appear to serve as
multi-target regulators of posttranscriptional processes, including
control of mRNA splicing, degradation and translation.
Corals are among the most valuable ecosystems on Earth, providing a
natural oceanic habitat for an abundance of species, ranging from
microbes to vertebrates. However, over the past few decades, coral reef
ecosystems worldwide are in danger due to climate changes,
consequently, they are facing an unprecedented level of degradation due
to the phenomena of bleaching. Bleaching is essentially defined as the
loss of color, mainly caused by severe dissociation from the coral
tissue of symbionts, like Symbiodinium ^[48]9–[49]11. There are a
number of factors that can trigger Symbiodinium escape, thus disrupting
the functionality of holobionts, such as an increase in sea water
temperature (global warming), marine pollution, ocean acidification and
bacterial infections among others^[50]10–[51]12. Several recent studies
relied on massive RNA sequencing data to investigate the
transcriptional changes that occur in corals in response to
bleaching^[52]13–[53]17. For example, Barshis and collaborators^[54]17
compared the gene expression among conspecific thermally sensitive and
resilient corals via RNA sequencing, and found hundreds of differential
expression genes (DEGs), including thermal tolerance genes and genes
involved in apoptosis regulation, tumor suppression, the innate immune
response, and cell adhesion. Pinzon and colleagues^[55]13 revealed by
means of the whole transcriptome analysis that immune-related genes
were differentially expressed during and after a coral bleaching event.
These transcriptomic studies on the coral bleaching response focused on
the changes in protein-coding RNAs, no study until now has taken into
account the implication of noncoding RNAs.
In the first part of present study, we sought to identify lncRNAs in
two purported congeneric species of soft coral, the zoanthids
Protopalythoa variabilis and Palythoa caribaeorum. P. caribaeorum
occurs in shallow waters in the western Atlantic and are relatively
abundant on most coastal reefs in northeast Brazil, where they
cohabits^[56]18. As a first step to in our survey of anthozoan lncRNAs,
we employed a stringent computational filtering pipeline of
transcriptomic data from deep RNA sequencing to predict with
high-confidence subsets of lncRNA repertoires in these two zoanthid
species. In the second part of the study, a careful examination of
genes that are differentially expressed, comprising mRNAs and lncRNAs
from P. caribaeorum under two physiological conditions, i.e., from
healthy P. caribaeorum and from colonial individuals undergoing
bleaching, was done. It is now known that episodes of bleaching occur
in P. caribaeorum in the geographical localities that this species
inhabit^[57]19. Moreover, P. caribaeorum is considered a good indicator
of bleaching, since it is the first species to display the symptoms of
deterioration caused by bleaching events^[58]20. Analytical data
revealed a pattern of expression suggestive of a regulatory circuitry
that operates posttranscriptionally with the participation of mRNAs and
some of these novel anthozoan lncRNAs. To our knowledge, the present
work is the first investigation of lncRNAs in zoanthids and their
presumed regulatory role in response to coral bleaching, based on
transcriptome analysis.
Materials and Methods
Coral sampling and sequencing
Two species of anthozoan (family Sphenopidae, order Zoantharia,
subclass Hexacorallia, class Anthozoa) were investigated in the present
study: Protopalythoa variabilis and Palythoa caribaeorum. Detailed
sampling and sequencing information of P. variabilis were like
described in our previous study (Huang et al.)^[59]21. The samples of
P. caribaeorum were from healthy colonies and from colonies in the
process of being bleached (Fig. [60]1). The tissue samples of P.
caribaeorum were collected in the same geographical region and
coordinate as P. variabilis, that is, they were collected in the
beach-rock bands of Porto de Galinhas, Pernambuco, Brazil (8°30′20″S,
35°00′34″W). All samples were quickly chopped, transferred to 10
volumes of RNAlater (Life Technologies, USA) and preserved at 4 °C for
48 h; subsequently, the RNA-preserving solution was then drained off
for tissue storage (−80 °C) before processing. The minced tissues were
powdered with a porcelain mortar and pestle under liquid nitrogen and
total RNA was purified using TRIzol reagent (Life Technologies)
according to the manufacturer’s protocol. The strand-specific libraries
for 90 bp paired-end sequencing were prepared. Briefly, the
polyadenylated RNAs (poly (A)^+ RNAs) were isolated using oligo(dT)
affinity chromatography. Single-stranded 5′-end RNA adaptors were
covalently linked to mRNA fragments using T4 RNA ligase (Ambion,
Austin, TX, USA) and then reversely transcribed into cDNA using
Superscript III reverse transcriptase (Invitrogen, Carlsbad, CA, USA).
The 3′-end DNA adaptor was ligated to the digested DNA fragments after
digestion with Mmel and the products were amplified using PCR. Finally,
RNA deep sequencing (RNA-seq) was conducted on a HiSeq 2500 instrument
(Illumina, San Diego – CA, USA). The P. variabilis Transcriptome
Shotgun Assembly (TSA) project was deposited at DDBJ/EMBL/GenBank under
the accession [61]GCVI00000000, associated with the BioProject
PRJNA279783 and BioSample SAMN03450566. The TSA projects concerning to
healthy P. caribaeorum and colonies undergoing bleaching were deposited
under the accession [62]GESO00000000, associated with the BioProject
PRJNA320984 and BioSamples SAMN04961660 and SAMN4961665, respectively.
Figure 1.
Figure 1
[63]Open in a new tab
Representative images of Palythoa caribaeorum colonies sampled in the
present study. (a) Healthy Palythoa caribaeorum colonies. (b) Colonies
of P. caribaeorum experiencing bleaching. Both colonies were
photographed on reefs of Porto de Galinhas Beach, PE, Brazil (Photo by
Dr. C. D. Perez’s research group).
Data processing, de novo transcriptome assembly and assessment
RNA sequencing, assembly and assessment of P. variabilis were as
recently published (Huang et al.)^[64]21. In the case of the
transcriptome analysis of P. caribaeorum, an individual RNA sequencing
dataset (from tissue samples of healthy colonies and undergoing
bleaching) and, an in-house C++ script was used to process the raw
sequencing data, in order to remove low quality data (>50% of bases
whose Phred scores were <5%, containing over 10% of poly-N), and the
Illumina software was used to eliminate the adaptor sequences. Raw data
and clean data were subjected to FastQC^[65]22 to evaluate sequence
quality (Supplementary Figures [66]S1–[67]S3). Then, clean reads were
used for the subsequent de novo transcriptome assembly process by means
of Trinity^[68]23 with default parameters. The TIGR Gene Indices
Clustering Tools (TGICL) software^[69]24 was used to obtain the longest
and most complete consensus transcripts by clustering the assembled
datasets of the two samples. Transcripts shorter than 200 nt were
discarded. Furthermore, for the purpose of assessing transcriptome
assembly quality as well, all reads were initially aligned to the
assembled transcripts using Burrows-Wheeler Aligner (BWA) (Ver.
0.7.7-r441)^[70]25. Then SAMtools (Ver. 0.1.19–44428cd)^[71]26 and
BEDTools (Ver. 2.17.0)^[72]27 were applied to evaluate the depth and
coverage of alignment.
Filtering pipeline for the identification of anthozoan lncRNAs
A stringent stepwise filtering pipeline was proposed to detect
transcribed lncRNAs in both anthozoan species (Fig. [73]2). This
pipeline is very similar to the procedures reported for the systematic
screening of lncRNAs from RNA sequencing of other species, such as from
the sponge Amphimedon ^[74]28 and from the plant Panax ginseng ^[75]29.
Initially, all assembled transcripts were align to transcripts
previously reported for the photosynthetic endosymbiont, Symbiodinium
spp.^[76]14. Hits that aligned length longer than 50% of query
sequences and subject sequences with an e-value less than 1E-3 were
removed. This step aimed at excluding the contaminating transcriptomic
sequences from endosymbiont, i.e., Symbiodinium minutum. It should be
noted at this point that we decide not to remove endosymbiont
transcriptomic sequences in the data processing step, since these
sequences could be used to investigate the impact of coral bleaching on
the symbiont content. Then, the remaining transcripts were subjected to
the NCBI non-redundant (nr) protein database, Pfam database (both
Pfam-A and Pfam-B)^[77]30 and Signal P4.0^[78]31 to search for
potential protein coding transcripts. BLASTx^[79]32 was used to search
against the non-redundant (nr) database, the E-value was set to 1e-4.
For Pfam scanning and SignalP analyses, all transcripts were translated
(stop-to-stop codon) using in-house perl script, and the longest ORF
for each transcript was retained. Transcripts returning at least one
hit by one of the three search methods were removed. To reduce the
number of potential spurious transcripts found in transcriptome
assemblies, transcripts shorter than 300nt were also removed^[80]28. In
addition, only the remaining transcripts for which the largest
predicted ORF corresponded to precursors of no more than 75 amino acid
residues (aa) were considered as lncRNA candidates. Next, transcripts
annotated as housekeeping non-protein coding RNAs (npcRNAs), such as
tRNAs and rRNA were excluded from the remaining lncRNA candidates by
subjecting them to the Rfam database^[81]33. Additionally, only lncRNA
candidates with an overall expression of at least 10 raw read counts
were retained. Finally, a tool for predicting lncRNAs and mRNAs,
PLEK^[82]34 was used to evaluate the sensitivity of the bioinformatic
pipeline. Only transcripts that were classified as noncoding by PLEK
(Ver. 1.2 were identified as high-confidence lncRNAs.
Figure 2.
Figure 2
[83]Open in a new tab
The filtering pipeline used for the identification of lncRNAs in the
transcriptomes of Protopalythoa variabilis and Palythoa caribaeorum.
Differential expression analysis of anthozoan lncRNAs and mRNAs
Clean reads from one-stranded paired-end libraries of P. variabilis and
two-stranded paired-end libraries of P. caribaeorum were mapped to the
corresponding assembled transcripts using the Burrows-Wheeler
transform, BWA (-o 1 -e 50 -i 15 -L -l 31 -k 2 -t 4)^[84]35. The number
of reads that mapped to each transcript were calculated using in-house
Perl script, and fragments per kilobase of transcript per million
mapped reads (FPKM)^[85]36 of transcripts of each sample were also
calculated by in-house Perl script. The transcripts were identified as
differential expression genes when the absolute value of Log[2]
(FPKM1/FPKM2) ≧1, at a 5% false discovery rate (P value adjusted for
multiple testing using the Benjamini–Hochberg correction).
KEGG pathway analysi
Ingenuity pathway analysis was used to identify enriched metabolic
and/or signal transduction pathways related to significantly
differentially expressed mRNAs of P. caribaeorum, according to the
Kyoto Encyclopedia of Genes and Genomes (KEGG). This approach mapped
firstly all DGEs concerned with the proteins of KEGG, and then found
significantly enriched pathways. A strict algorithm was proposed,
described as follows,
[MATH:
P=1−∑i=0m−1<
/mrow>(Mi
)(N−M
n−i)(Nn
) :MATH]
where N is the total number of genes with KEGG annotation, n is the
number of DEGs in N, M is the total number of genes annotated to
specific pathways, and m is the number of DEGs in M. The calculated
p-value was subjected to the Bonferroni Correction, with the taking
corrected p-value ≧ 0.05 taken as the threshold for significane.
GO annotation analysis
All of the differential expression mRNAs were first searched using
BLASTx against the NCBI non-redundant (nr) protein database with a
cut-off E-value of 10^−3. Then, all the blast results were subjected to
the GO database to retrieve GO annotation information using
Blast2GO^[86]37. Finally, the annotation results were visualized using
the WEGO (Web Gene Ontology Annotation Plot) tool^[87]38.
Target mRNAs for prediction of P. caribaeorum lncRNAs
In this study, which aimed to identify target mRNAs for novel anthozoan
lncRNAs, as well as to correlate lncRNA functions to physiopathological
responses to coral bleaching at the molecular level, we focused our
analysis on the lncRNA repertoire of P. caribaeorum. Firstly, all P.
caribaeorum lncRNAs were compared with known lncRNAs of the NONCODE
database using BLASTn, the E-value was set to 1e-3 (for differentially
expressed lncRNAs, E-value = 1.0). Aligned regions between queried
lncRNAs and target lncRNA sequences in NONCODE were regarded as
putative functional conservative regions. Secondly, the aligned lncRNAs
were subjected to RNAplex to search for probable lncRNA-mRNA
interactions among the 54,699 known mRNAs of P. caribaeorum
transcriptome, using default parameters, but with the exception that
the temperature of simulative hybridization was set to 25 °C. RNAplex
is a tool especially designed to search for short segments of
interactions between two long RNAs^[88]39. It can rapidly compute
optimal secondary structures for their hybridization based on free
energy minimization. The mRNA-lncRNA interactions in which
hybridization sites were located in conservative regions were selected
for further investigation. Finally, the mRNAs that were shown to
interact with P. caribaeorum lncRNAs in a relatively perfect
complementary base-pairing manner on the conservative regions, and
having lower interaction energy (≤−20) requirements, were considered as
being high-confidence target mRNAs for their corresponding lncRNAs.
More specific details of lncRNAs and mRNAs interactions in P.
caribaeorum are presented in the results.
Statistical analysis
The Kolmogorov-Smirnov test (KS test), a nonparametric test of the
equality of continuous, one-dimensional probability distributions, is
one of the most useful and widely used nonparametric methods for
comparing two samples, as it is sensitive to differences in both the
location and shape of the empirical cumulative distribution functions
of two samples. In the present study, we used the two-sample KS test to
evaluate the significance of differences between mRNAs and lncRNAs
among two coral species. The whole statistical analyses are performed
using the R package.
Results
Data processing, transcriptome assembly and identification of lncRNAs in P.
variabilis and P. caribaeorum transcriptomes
RNA sequencing data processing, and assembly and assessment of P.
variabilis transcriptome were conducted as detailed in our previous
study^[89]21. Briefly, a total of 60,891,368 clean reads were assembled
into 126,441 transcripts. Sequence alignment of clean reads against
assembled transcripts using BWA indicated that 58,916,865 (87.22%)
reads could be mapped to the assembled transcripts. Furthermore,
assessment of the depth and coverage of alignment, done using SAMtools
and BEDTools showed that 121,877 transcripts were mapped to at least 10
reads, in which more than 80% of the sequences were covered by reads.
In the case of P. caribaeorum transcriptomes, deep RNA sequencing of
paired-end 90 nt was conducted with samples from the tissues of healthy
colonies and from individuals undergoing bleaching, resulted in a total
of 63,914,343 and 55,523,043 reads, respectively. The sequence quality
analysis of clean data for both samples is presented in Figures [90]S2
and [91]S3. Following this assessment, the transcripts of each sample
were firstly assembled using Trinity and then clustered together using
TGICL to obtain the consensus transcript sequences. At the end of the
process, a dataset of 136,654 transcripts with a mean sequence length
of 874 nt, was obtained for the combined transcriptomes of healthy P.
caribaeorum tissue and tissue undergoing bleaching. Sequence alignment
of clean reads of healthy P. caribaeorum against assembled transcripts
using BWA indicated that 57,291,678 (89.63%) reads could be mapped back
to the assembled transcripts. Furthermore, the depth and coverage
assessment of alignment using SAMtools and BEDTools showed that 123,675
transcripts were mapped to at least 10 reads, in which more than 80% of
sequences were covered by reads. On the other hand, 48,678,012 (86.90%)
of the reads of P. caribaeorum experiencing bleaching could be aligned
to the assembled transcripts and 118,345 transcripts were mapped at
least ten reads and in which more than 80% of sequences were covered by
reads.
In order to identify the putative lncRNAs transcribed in P. variabilis
and P. caribaeorum, all assembled transcripts were subjected to a
stringent stepwise filtering pipeline (Fig. [92]2). Three core
filtering criteria were applied to screen these anthozoan lncRNAs: (1)
the potential of encoding proteins; (2) the length of transcripts; and
(3) the size of the open reading frames (ORFs). Taking the dataset from
P. variabilis as an example of our detailed filtering process, a total
of 20,400 transcripts that aligned to Symbiodinium transcript sequences
were initially removed. Thereafter, the remaining zoanthid (P.
variabilis) transcripts were searched for sequence similarity with
known proteins in the NCBI non-redundant database, for finding
functional domains in the Pfam database and predicted leader sequences
(signal peptides), which were also removed. Subsequently, transcripts
shorter than 300 nucleotides, a stricter cutoff than the 200 nt
commonly used, were filtered out. By means of these steps, 32,028
(ncRNAs) were retained. Next, the ncRNAs were subjected to the ORF
prediction and subsequently filtered by removing the transcripts of
protein-coding potential, based on a maximum ORF size of 75 amino
acids.
The remaining ncRNAs were again filtered to eliminate housekeeping
ncRNAs, like tRNAs and rRNAs, based on Rfam scanning. This approach led
to the retention of 11,453 lncRNA candidates. Subsequently, to reduce
noise without losing low-abundance transcripts, the lncRNA candidates
with an overall expression of less than 10 raw read counts were removed
as in a previous study by Gaiti et al.^[93]28. The cross-validation of
these lncRNA candidates, using PLEK software and a comprehensive
stringent pipeline, identified a final set of 11,206 lncRNAs in the P.
variabilis transcriptomic dataset. A similar number of lncRNA
candidates, i.e., 13,240 lncRNAs, were also identified in healthy P.
caribaeorum transcriptomes.
Features and functional analysis of lncRNAs from P. variabilis and P.
caribaeorum transcriptomes
As mentioned above, a total of 11,206 and 13,240 lncRNAs were
identified in the transcriptome of P. variabilis and healthy P.
caribaeorum, respectively. In order to comprehensively examine the
differences and similarities between mRNAs and lncRNAs, comparative
analysis was performed based on the lengths and structures of
transcripts, as well as their expression levels. The results showed
that the length of mRNAs of both species of anthozoan was greater than
that of their respective lncRNAs (Kolmogorov-Smirnov test, P < 0.0005)
(Fig. [94]3A). Moreover, lncRNAs in both anthozoans showed a lower
level of expression when compared to the respective levels of mRNA
expression (Kolmogorov-Smirnov test, P < 0.0005) (Fig. [95]3B).
Additionally, we assessed the similarity of the mRNAs and lncRNAs
repertoires of P. variabilis and healthy P. caribaeorum using BLASTn.
For this purpose, a relatively strict criterion to indexing similarity
was defined: the matching regions should be longer than half the size
of any compared lncRNAs. The results indicated that 3,469 lncRNAs
(about a third of the predicted lncRNAs) shared a high similarity
(79~100% identities) between lncRNAs from P. variabilis and healthy P.
caribaeorum (Fig. [96]3C). By contrast, 38,802 mRNAs (more than 50% of
the predicted coding transcripts) of P. variabilis were shown to be
homologous to their transcript counterparts in P. caribaeorum
(Fig. [97]3C). The sequence conservation observed in the collection of
lncRNAs and mRNAs from both anthozoans is justifiable and corroborated
by the fact that both species are suggested to be congeneric^[98]40.
Importantly, some lncRNAs from these two anthozoan repertoires, as the
long intervening non-coding RNAs (lincRNAs), were found to have
sequences less conserved than mRNA sequences, consequently being more
lineage-specific as observed for other species^[99]41.
Figure 3.
Figure 3
[100]Open in a new tab
General characteristics of mRNAs and lncRNAs in Protopalythoa
variabilis and Palythoa caribaeorum. (A) Distribution of transcript
length by log[10] (Length) in mRNAs and lncRNAs in Protopalythoa
variabilis and Palythoa caribaeorum. (B) Expression level indicated by
log[10] (FPKM + 1) in mRNAs and lncRNAs in Protopalythoa variabilis and
Palythoa caribaeorum. (C) Comparison of mRNAs and lncRNAs from
P.variabilis and P. caribaeorum.
Ultra-conserved regions exist in lncRNAs from P. variabilis, P. caribaeorum
and model species in the NONCODE database
To address the functionality of lncRNAs, all putative lncRNAs of P.
variabilis and P. caribaeorum were compared with known lncRNA sequences
in the NONCODE v3.0 database using BLASTn, with the E-value adjusted to
1e-3. The result showed that approximately 1% of P. variabilis and P.
caribaeorum lncRNAs are structurally comparable with lncRNA sequences
from diverse vertebrate species (Figure [101]S4). This low percentage
was actually expected, since a low number of lncRNA sequences are
shared among species, as observed in zebrafish and human (6%)^[102]42.
Noteworthy, among the compared lncRNA sequences and in contrast to
protein-coding RNAs, in which long segments are typically very similar
to their homologues, most of lncRNAs shared a common sequence only for
short stretches of 10 bp to 50 bp. For instance, comparison of a lncRNA
of P. caribaeorum, namely CL4490. Contig 2, to lncRNA sequences from
human, chimpanzee and mouse, showed that lncRNA CL4490. Contig 2
displays relatively low similarity with the corresponding short
(divergent) regions of lncRNAs from these higher vertebrate species
(Figure [103]S5). A possible explanation for this structural
characteristic of lncRNAs is that they are quite distinct from mRNAs in
that mRNAs have to conserve codon integrity and prevent frameshift
mutations in a single long ORF. In addition, lncRNAs are subjected to a
relatively low number of evolutionary constraints, with the exception
of a selective pressure to strictly conserve the short lncRNA regions,
responsible either for sequence-specific interactions or structural
organization. Indeed, in previous studies on lncRNAs, it was
demonstrated that a small proportion of lncRNAs from mammals and
zebrafish retains interspecies short and highly conserved
regions^[104]42, [105]43. Moreover, antisense reagents targeting these
conserved regions in zebrafish lncRNAs resulted in developmental
defects^[106]42, suggesting that the conserved regions play a crucial
role in lncRNAs functions, i.e., in the regulation of gene expression,
via hybridizing with transcriptional elements, such as promoter,
transcription factor, repressor, and/or enhancer.
Prediction of P. caribaeorum lncRNAs function based on ultra-conserved
regions
It is rationally and intuitive to suggest that conserved regions in
lncRNAs would be retained over the long course of the evolutionary
history of distant parental organisms only if those conserved
sequences, if altered, could critically affect key components of
cellular processes. Several current studies about lncRNAs have
elucidated the diverse range of functions mediated by lncRNA, based
mainly on the intermolecular RNA-RNA and RNA-DNA interactions,
complementary base-pairing, or the formation of an RNA-protein complex
via recruitment of specific proteins^[107]6. Hence, we reasoned that
such conserved regions in anthozoan lncRNAs could interact with RNA,
DNA or protein target and also exert their regulatory effects also in
zoanthids. To assess this, a total of 145 lncRNAs from healthy P.
caribaeorum, with conserved regions highly comparable to those of
lncRNAs found in other organisms were considered here for further
investigation. Those lncRNAs were subjected to RNAplex to search for
probable lncRNA-mRNA interaction with 54,699 identified P. caribaeorum
mRNAs. RNAplex tools are allowed identification of the optimal
hybridization sites for each queried lncRNA-mRNA pair, taking into
account the minimization of free energy. The aim of this step was to
examine if conserved regions tend to be located in the hybridization
sites of lncRNA-mRNA interaction. The results of the predictive
analysis showed that a large proportion of lncRNAs (around 90%) could
hybridize and interact with target mRNAs in their respective matched
conserved regions (Supplementary Table [108]1), lending support to a
possible regulatory role of these lncRNAs in P. caribaeorum tissue. Of
all of these possible interactions, 29 lncRNAs, in particular, have
been shown to interact with the conserved region of 371 target mRNAs in
a complementary base-pairing manner and with a low predicted energy
(≤−20) (Fig. [109]4, example in Figure [110]S6), which forms a 402
mRNAs-lncRNAs interaction network. The majority of the mRNA-lncRNA
interactions were, however, predicted to hybridize defectively in terms
of base complementarity (Supplementary Table [111]1). In fact, it is
not surprising to see such defective base pairing, since most of the
ncRNAs essentially tend to interact in an intricate way which does not
necessarily involves accurate hybridization^[112]44. Furthermore,
around 10% lncRNAs were found to not predictively any kind of
interaction with the same set of mRNAs (Supplementary Table [113]1),
probably because conserved regions of these lncRNAs might specifically
bind to special elements other than target mRNAs, such as certain DNAs
or proteins. Obviously, for definitive conclusions about lncRNA
target-interactions and functionality to be drawn, further ingenious
experimental design and validation is required.
Figure 4.
Figure 4
[114]Open in a new tab
Inter-species conserved region of 29 lncRNAs from Palythoa caribaeorum,
involved in the predicted lncRNA-mRNA interactions. Different color
bars below the conserved region sequence show each nucleotide’s
frequency of binding to all target mRNAs, blue: 0–19%, green: 20–39%,
yellow: 40–59%, orange: 60–79%, red: 80–100%.
Functional classification of target mRNAs potentially regulated by P.
caribaeorum lncRNAs
Based on the annotation by BLASTx against the nr database, target mRNAs
that could be posttranscriptionally regulated by the novel 29 lncRNAs
of P. caribaeorum were classified into eight categories (Fig. [115]5).
Specifically, these 29 lncRNAs were predicted to interact with, and
potentially regulate mRNAs encoding proteins that are involved in
multiple processing networks of biological activity and cellular
metabolism (Fig. [116]6 and Table [117]S2). For instance, some of these
interactions were observed to predictively target mRNAs encoding
various enzymes involved in RNA transcription, and DNA assembly,
replication and modification, including enzymatic components such as
transcriptase, exoribonuclease, DNA polymerase, and nuclease, etc. In
addition, around 6% of lncRNAs were predicted to interact with mRNAs
encoding regulatory proteins (Fig. [118]5), such as transcription
elongation regulator, translation initiation factor, nuclear factor,
transcription factor, splicing factor, nonsense transcript regulator
and transcription complex subunits. Concerning this aspect of DNA and
RNA metabolism, it is now known and accepted that lncRNAs can work as
transcriptional regulators by interacting directly with transcription
factors, acting on promoters and repressors for activation or
inactivation of gene expression^[119]45. Our findings reveal that
lncRNAs in P. caribaeorum may be involved in regulation at the
posttranscriptional level of key proteins involved in RNA metabolism in
P. caribaeorum cells. Another small set of 29 P. caribaeorum lncRNAs
(Table [120]S2) was predicted and found to only target mRNA sequences
encoding several unknown or hypothetical proteins, although they were
specifically encoded by a marine cnidarian model, the starlet sea
anemone Nematostella vectensis. It is worthy of noting that the
predicted interaction of P. caribaeorum lncRNAs with mRNAs encoding
unknown/hypothetical protein sequences in N. vectensis, suggests a
cross-species regulation of a common group of target transcripts in
these distant but closely related species of cnidarians.
Figure 5.
Figure 5
[121]Open in a new tab
Functional classification of interacting mRNAs targeted by 29 lncRNAs
from P. caribaeorum. Functions of target mRNAs were extracted based on
the annotation information of BLAST alignment against the NR database.
The lncRNA-mRNA interactions not only contain relatively perfect
complementary base-pairing, but also require low interaction energy
(≤−20) for hybridization.
Figure 6.
Figure 6
[122]Open in a new tab
lncRNA-mRNA interaction network constructed based on the 29 lncRNA-mRNA
interaction pairs. Target mRNAs were classified based on coding
proteins annotated from BLAST alignment against the NR database. The
lncRNA-mRNA interactions not only contain relatively perfect
complementary base-pairing, but also require low interaction energy
(≤−20) for hybridization.
Differential expression of mRNAs and lncRNAs in P. caribaeorum: a clue to the
possible implications of coral bleaching?
Identification of differentially expressed mRNAs and lncRNAs in healthy P.
caribaeorum tissues and those undergoing bleaching
Comparison of the transcriptomes of P. caribaeorum in two different
physiological states, i.e., from tissues of a healthy colony and from a
colony going through the process of bleaching, has allowed us to
disclose transcribed genes and pathways seemingly associated with the
coral bleaching response. A total of 1,684 mRNAs and 200 lncRNAs were
identified in P. caribaeorum by DGEs analysis after transcriptome
assembly and sequence alignments (Fig. [123]7). Of 1,684 identified
mRNAs, 723 were up-regulated and 961 were down-regulated (fold-change
>2, P < 0.05) in P. caribaeorum undergoing bleaching compared to
healthy P. caribaeorum, respectively (Fig. [124]7a). Of 200 differently
expressed lncRNAs, 65 were up-regulated and 135 were down-regulated
(fold-change >2, P < 0.05), in P. caribaeorum undergoing bleaching
versus healthy P. caribaeorum, respectively (Fig. [125]7a). The
distinguishable mRNA and lncRNA expression profiles of healthy P.
caribaeorum and those undergoing bleaching are depicted in
Figure [126]7b,c.
Figure 7.
Figure 7
[127]Open in a new tab
Comparison of differentially expressed mRNAs and lncRNAs identified in
healthy P. caribaeorum and in colonial individuals undergoing
bleaching. (a) Histogram plot of significantly differentially regulated
mRNAs and lncRNAs in P. caribaeorum tissue undergoing bleaching
compared to healthy tissue. (b,c) Hierarchical clustering and scatter
plot of overall mRNAs (b) and lncRNAs (c) differentially expressed in
P. caribaeorum tissue undergoing bleaching compared to healthy tissue.
Red: lower expression levels, green: higher expression levels.
KEGG pathway enrichment analysis of differentially expressed mRNAs
KEGG enrichment analysis indicated that the major pathways via which
transcripts were differentially expressed in P. caribaeorum going
through the process of bleaching are associated with energy metabolism,
cell adhesion and immunity, including photosynthesis, protein digestion
and absorption, focal adhesion, ribosome biogenesis, carbon fixation in
photosynthetic organisms and photosynthesis-antenna proteins, among
others (Table [128]1). Indeed, the overall expression level of
differentially expressed mRNAs mapped to KEGG pathways was found to
decrease by different amounts in P. caribaeorum in undergoing bleaching
(Fig. [129]8), particularly in respect to pathways related to energy
metabolism, like photosynthesis and energy capture by antenna proteins,
and photosynthetic carbon fixation (Table [130]1 and Fig. [131]9).
These findings could be reasonably explained by the fact that coral
host undergoing bleaching is losing its symbionts, compromising the
ability of the holobiont to cope with the physiological demand of
photosynthesis. Two other pathways enriched by differentially expressed
mRNAs were correlated with cell adhesion and the innate immune
response, which comprises transcripts encoding focal adhesion proteins,
cell adhesion molecules (CAMs) and primary immunodeficiency responsive
components. Indeed, these results are corroborated by the work of
Pinzon and coworkers who reported that the expression of immune-related
genes would change during and after bleaching of a reef-building coral
Orbicella faveolata ^[132]13.
Table 1.
Top thirteen enriched KEGG pathways involving differentially expressed
mRNAs in P. caribaeorum.
Pathway Pathway ID Number Up/Down(Bleaching-vs-Healthy) P value
P-corrected value
Photosynthesis ko00195 20 0/20 5.367164e-11 1.406197e-08
Protein digestion and absorption ko04974 34 7/27 1.039168e-08
1.361310e-06
Focal adhesion ko04510 51 15/36 3.220733e-08 2.812773e-06
Ribosome ko03010 41 16/25 4.539063e-08 2.973086e-06
Carbon fixation in photosynthetic organisms ko00710 15 1/14
1.641190e-07 8.599836e-06
Photosynthesis - antenna proteins ko00196 13 0/13 2.355030e-07
1.028363e-05
ECM-receptor interaction ko04512 31 6/25 7.57104e-07 2.833732e-05
Cell adhesion molecules (CAMs) ko04514 19 7/12 1.250847e-05
4.096524e-04
Amoebiasis ko05146 26 8/18 1.733519e-05 5.046466e-04
Dilated cardiomyopathy ko05414 36 5/31 0.0001710962 4.259353e-03
Hypertrophic cardiomyopathy (HCM) ko05410 35 4/31 0.0001788278
4.259353e-03
Primary immunodeficiency ko05340 9 0/9 0.0002033226 4.439210e-03
Pancreatic secretion ko04972 17 8/9 0.0002288780 4.612772e-03
[133]Open in a new tab
Figure 8.
Figure 8
[134]Open in a new tab
Heatmap of 347 differentially expressed mRNAs enriched to 13 KEGG
pathways in P. caribaeorum tissue undergoing bleaching compared to
healthy tissue. Expression levels were normalized by logarithmic base
2.
Figure 9.
Figure 9
[135]Open in a new tab
Visualization of differentially expressed mRNAs enriched in the
metabolic pathways of P. caribaeorum. All differentially expressed
mRNAs were subjected to the web-based tool, IPath2.0^[136]69 for
visualization. Up-regulated genes are highlighted in red,
down-regulated genes are highlighted in green.
GO Annotation analysis of differentially expressed mRNAs in healthy and
diseased (undergoing bleaching) P. caribaeorum
Based on nr annotation, all of the differential expression mRNAs were
mapped using the international standardized gene functional
classification (GO) system. Concretely, Of the 1,119 most significant
BLASTx hits against the nr database, a total of 222 differential
expression mRNAs were annotated to at least one GO term, which could be
categorized into 56 functional groups (Fig. [137]10). Among these, 134
(60.36%), 114 (51.35%) and 185 (83.33%) differential expression mRNAs
were grouped into main categories comprising biological processes,
cellular components and molecular functions, respectively. In each of
the three main categories of GO classification, the terms “metabolic
process”, “cell”, and “binding” account for the largest proportion. GO
analysis revealed the functions of differential expression (both
up-regulated and down-regulated) mRNAs in bleaching samples versus
healthy samples. The functions of these mRNAs are probably related with
many processes that are important in the bleaching response.
Figure 10.
Figure 10
[138]Open in a new tab
GO Annotation analysis of differentially expressed mRNAs in healthy and
diseased (undergoing bleaching) P. caribaeorum.
Predicted lncRNA-mRNA interactions in P. caribaeorum possibly implicated in
coral bleaching
Previous studies from other researchers have shown that lncRNAs could
play a regulatory role in diverse molecular pathways and processes of
cells, in both healthy and disease states, being a determinant of the
disease outcome in vertebrates, including humans. In the present study,
a total of 200 significant differentially expressed lncRNAs (DELs) were
identified by comparing the lncRNA expression level of healthy P.
caribaeorum and individuals experiencing bleaching. As reported in the
first part of this investigation regarding the prediction of lncRNA and
their effect on the regulation of transcript translation and protein
activity, we predicted target mRNAs for 29 lncRNAs in P. caribaeorum.
However, none of them were DELs. This was not surprise for two main
reasons: we adopted an extremely stringent strategy to screen the most
reliable lncRNA-mRNA interactions, and mRNAs may not be necessarily be
the principal target for lncRNAs, since even proteins may act as
interplayers in lncRNA-mediated regulatory pathways^[139]46. In order
to understand whether P. caribaeorum lncRNAs are implicated in coral
bleaching and whether changes in the expression levels of lncRNAs
correlate with the bleaching response, all of the DELs were compared to
lncRNA sequences available in the NONCODE database, to search for
probable conserved regions using a loose parameter (the E-value was
adjusted to 10) by BLASTn. Interestingly, this analysis revealed
numerous DELs that share short conserved regions (ranging from 19 bps
to 50 bps) with lncRNAs deposited in NONCODE. Likewise, we adopted the
same strategy that was mentioned in a previous section to search for
probable target mRNAs. In total, 200 DELs were subjected to RNAplex to
detect probable lncRNA-mRNA interactions among the 54,699 P.
caribaeorum candidate mRNAs. By means of this strategy, one can verify
that these mRNAs predictively interact with lncRNAs that tend to
hybridize to conserved regions through almost-perfect complementary
base pairing. These interacting partners were then annotated as
candidate target mRNAs of DELs. Eventually, 89 lncRNA-mRNA interactions
associated with the bleaching response in P. caribaeorum were
identified, which involved interactions between 17 lncRNAs and 89
mRNAs. Annotation of the 89 target mRNAs by BLASTx against the nr
database revealed that most DELs could act on the mRNAs encoding
various enzymes correlated to DNA and RNA metabolism, including, for
example, DNA-dependent RNA polymerase III, histone acetyltransferase
and RNA-dependent DNA polymerase (Table [140]2). Additionally, some of
these lncRNAs could also act on the mRNAs encoding regulatory proteins,
such as transcription factor, splicing factor, THO complex, integrator
complex subunit, elongator complex protein, and GTP-binding protein.
Particularly, one P. caribaeorum lncRNA (ID: Unigene72046) is
potentially able to interact with an mRNA encoding Ras-related protein.
The Ras protein members have been reported to be ubiquitously expressed
in all cell lineages and organs and generally they are involved in
transmitting signals that would result in cell growth and division. It
is well known that aberrant expression of Ras protein in human would be
associated with proliferative diseases and over activity of ras
signaling can lead to cancer^[141]47. Actually, genome annotation of
the coral A. digitifera by Dunlap and coworkers has allowed disclosure
of a large number of genes encoding putative Rab homologues of the Ras
superfamily of proteins^[142]48. Differential expression analysis
indicated that lncRNA Unigene72046 would be up-regulated in response to
P. caribaeorum bleaching. Overexpression of lncRNA Unigene72046 might
affect the transcriptional regulation of Ras-related protein, resulting
in a disruption of intracellular signaling in P. caribaeorum
individuals undergoing bleaching, that might culminate with a tentative
recovery in cell growth, differentiation and survival.
Table 2.
Detailed information of differentially expressed lncRNAs and predicted
target mRNAs in Palythoa caribaeorum.
lncRNA ID Target mRNAs number Target mRNAs annotation information
Unigene72046^↑ 24 Aminotransferase; uncharacterized protein;
trypsin-3-like; retinoic acid receptor; islet cell autoantigen;
carbonic anhydrase; histone acetyltransferase; ranBP-type and
C3HC4-type zinc finger-containing protein; epidermal growth factor
receptor substrate; putative acyl-coenzyme A oxidase; ras-related
protein Rab-24; probable UDP-sugar transporter protein; ubiquitin-like
protein fubi and ribosomal protein; hypothetical protein; hypothetical
protein*; NEDD8-conjugating enzyme; protease regulatory subunit;
transmembrane protease;
Unigene69139^↑ 11 uncharacterized protein;stimulator of interferon
genes protein; THO complex 1; complement factor B; transmembrane
protein 181; charged multivesicular body protein; hypothetical protein;
UDP-glucuronosyltransferase; elongator complex protein; histamine
N-methyltransferase; integrator complex subunit;
Unigene57713^↓ 10 agglutinin biogenesis protein MshQ; hypothetical
protein; predicted protein*; glutamate 5-kinase; methionine synthase;
membrane protein metalloendopeptidase; unknown protein; MSHA biogenesis
protein; GTP-binding protein;
Unigene7497^↓ 9 glycerol-3-phosphate acyltransferase; hypothetical
protein; uncharacterized protein;
N-acetylglucosaminyl-phosphatidylinositol de-N-acetylase;
ubiquitin-conjugating enzyme; thiosulfate
sulfurtransferase/rhodanese-like domain-containing protein; ubiquitin
carboxyl-terminal hydrolase; RNA-directed DNA polymerase;
Unigene1657^↓ 6 enolase-like protein;predicted protein*; poly
[ADP-ribose] polymerase isoform X2; poly(A) polymerase central domain
protein; hypothetical protein; motile sperm domain-containing protein;
Unigene62981^↓ 6 cGMP-dependent 3′,5′-cyclic
phosphodiesterase;chitinase 3-like; fibropellin-1-like; probable
serine-O-acetyltransferase; phosphatidate cytidylyltransferase;
uncharacterized protein;
Unigene83429^↓ 5 arginine/serine-rich protein PNISR isoform;protein
kinase; splicing factor, arginine/serine-rich 18-like;
Unigene16589^↓ 4 uncharacterized protein; hypothetical protein;
mannose-binding lectin associated serine protease; phytanoyl-CoA
dioxygenase;
CL1738.Contig1^↑ 3 DNA-directed RNA polymerase III; uncharacterized
protein*; predicted protein*;
CL7909.Contig1^↑ 3 predicted protein*; steroid 17-alpha-hydroxylase;
CL1253.Contig5^↑ 2 transcription factor MYTF; mitochondrial inner
membrane protease subunit;
CL1417.Contig2^↑ 1 hypothetical protein;
CL4186.Contig1^↑ 1 uncharacterized protein;
Unigene55440^↓ 1 rab3 GTPase-activating protein catalytic subunit;
Unigene69919^↑ 1 glucose transporter;
Unigene70419^↑ 1 predicted protein*;
Unigene81587^↓ 1 predicted protein*;
[143]Open in a new tab
^*Represents protein uniquely annotated in cnidarian, i.e.,
Nematostella vectensis, Hydra vulgaris.
^↑Represents up-regulated in Bleaching P. caribaeorum versus Healthy P.
caribaeorum.
^↓Represents down-regulated in Bleaching P. caribaeorum versus Healthy
P. caribaeorum.
Intriguingly, one up-regulated P. caribaeorum lncRNA (ID: Unigene69139)
was predicted to interact with mRNAs coding for immune-associated
proteins, namely, the complement factor B and the stimulator of
interferon genes protein (STING). Complement factor B is a component of
an alternative pathway of complement activation, involved in the
regulation of the innate immune response, and the stimulator of STING
has been demonstrated to play an important role in innate immunity by
inducing cells to produce immunomulators and, consequently, signalizing
to control infection^[144]49. It is hypothesized here that the lncRNA
(Unigene69139) would be able to posttranscriptionally regulate
immune-related genes via direct interaction and that the up-regulation
of this kind of lncRNA in P. caribaeorum undergoing bleaching, might
severely impact the coral immune system in a tentative bid to control
not only the lost beneficial symbionts, but also host susceptibility to
pathogenic microbes. The KEGG analysis of differential expression
mRNAs, presented in the previous section, indicates that components
related to the immune response pathway were overall repressed in P.
variabilis experiencing bleaching. Accordingly, Pinzon and
collaborators also demonstrated that the coral immune response appears
to be suppressed after a bleaching event^[145]13. It is well known and
accepted that the immune system is a complex network that associated
with numerous interconnected biological processes and pathways that
play a crucial role in maintaining the balance of an organism,
particularly in fighting disease. Furthermore, in the case of corals,
immune system interplayers also participate in the colonization of self
(species-specific)-beneficial microscopic dwellers to the detriment of
infectious microbes. Our findings indicated that overexpression of
lncRNAs that potentially regulate immune-related mRNAs could contribute
to the host immunosuppression in response to coral bleaching.
Discussion
The rapid development of sequencing technologies has allowed the
discovery of tens of thousands of lncRNAs in recent years^[146]4,
[147]50. They were initially thought of as being “transcriptional
noise”, due to the incompetence of encoding proteins^[148]4, [149]51.
However, cumulative studies now indicate that lncRNAs comprise a novel
class of significant biological regulators, which has been implicated
in a range of biological processes, including development and
differentiation. Additionally, lncRNAs have emerged as another class of
cellular components that influences the disease outcome. However, most
studies about lncRNAs were until now restricted to few established
model organisms^[150]52–[151]54. For instance, the NONCODE database
integrates sets of data with ncRNAs of 16 species, including human,
mouse, cow, rat, chicken, fruitfly, zebrafish, nematode (C. elegans)
and yeast^[152]55. Commonly, lncRNAs possess a low level of structural
and sequence conservation among species^[153]46. Hence, the fact that
most lncRNAs diverge considerably among species, and that they have
been found in a limited number of model organisms, causes some
difficulties in straightforwardly identifying lncRNAs from unusual
non-model organism by means of comparative homology sequence searches
and multi-alignments. Moreover, with the exception of their functions,
lncRNAs are paradoxically very similar to mRNAs in several structural
aspects, such as the overall organization of precursor structures and
regions of base-pairing complementarity. Compared to mRNAs, the
majority of mature lncRNAs are generated by the same histone
modifications; that is, the same RNA polymerase II transcriptional
machinery and they also are accordingly polyadenylated^[154]45,
[155]56, suggesting that a priori lncRNAs are indistinguishable from
functional mRNAs. However, this is exactly the reason why a relatively
large number of lncRNA sequences can be retrieved when one conducts RNA
sequencing merely based on the RNA ‘Poly (A)’ library. In the present
work, aiming at the identification of lncRNAs in the transcriptomes of
two anthozoan species, we initiated our survey by taking data from
next-generation RNA sequencing performed in accordance with our
previously published studies^[156]28, [157]29, but now including an
adapted filtering pipeline step for analytical identification of
subsets of lncRNAs. In this way, we were able to predict a large number
of lncRNAs in the transcriptomes of two species of zoanthids one of
which undergoing bleaching. The number of predicted lncRNAs in these
species of cnidarians exceeded that which was initially expected. This
could be attributable to several differences in our experimental
designs and from those of other researchers. For instance, Wang and
collaborators^[158]29 predicted lncRNAs in Panax ginseng from EST
sequences, and not from deep RNA sequencing. In a work by Gaiti and
colleagues^[159]28, they combined genome data to filter for lncRNAs,
creating potentially more chances to eliminate not only false-positive
lncRNA candidates, but also true positives. Indeed, lncRNAs in some
ways are regarded as a moniker until they are better characterized; a
small percentage of transcripts originally reported as lncRNAs have
later been found to have the capacity to encode new (usually small)
proteins^[160]50, [161]57. We believe that our in silico prediction of
lncRNA repertoires from the transcriptomes of understudied living
organisms could in the future be further optimized, along with specific
and constant improvement in sequencing data handling and
bioinformatics, particularly concerning to ncRNA analysis.
In the light of lncRNA functions, besides their well-characterized
effects as regulators of transcription, a small proportion of lncRNAs
have been known for their roles as posttranscriptional regulators,
involved in pre-mRNA splicing, RNA editing, mRNA decay, translation and
abrogation of miRNA-induced repression^[162]6, [163]58. However,
functional characterization of identified lncRNAs has been great
challenge so far. On the one hand, effective experimental approaches
for validating lncRNA functions cannot deal with the increasing amount
of transcriptional data generated. On the other hand, bioinformatics
methods utilized to predict lncRNA functions are still in the early
stage. Certainly, a large number of studies have successfully
elucidated the functional role of some lncRNAs in the molecular biology
of cancer and chronic diseases^[164]59–[165]62. Wang and his
collaborators, for example, revealed that approximately 40% of lncRNAs,
named mRNA-like ncRNAs, are the precursors of microRNAs in P. ginseng
that mature to produce multi-function–associated elements responsive to
jasmonate (–a plant signaling molecule)^[166]29. Ren and
coworkers^[167]63 investigated the target genes regulated by lncRNAs in
the process of skin pigmentation and development based on the deep
RNA-sequencing data of dark and white goats.
Several studies have suggested that a great number of lncRNAs exert
their effects via base-paring with complementary DNAs and RNAs^[168]6,
[169]58, [170]64. In fact, purely sequence-based methods like BLAST and
FASTA, which search for long stretches of perfect complementarity
between two queried RNAs, have been used for detecting probable
RNA-DNA/RNA interactions. For instance, Szcześniak and collaborators
predicted a large number of lncRNA-RNA interactions in human
transcriptome using a similarity-search method^[171]58. As an
alternative, He et al. developed a tool named LongTarget to predict
lncRNA-DNA interactions via base-pairing analysis^[172]65. In our
present study, we initially investigated the content of lncRNAs and the
pattern of expression in the transcriptomes of two marine basal
organisms – the anthozoans P. variabilis and P. caribaeorum, parentally
related to the first metazoans that arose in the oceans more than 500
million years ago. Since P. caribaeorum, in the coral reefs that it
inhabits, is the first species to display the symptoms of bleaching, we
predicted a possible network of lncRNAs interactions in this zoanthid
species under two physiological conditions: healthy tissue and colonial
individuals undergoing bleaching. As shown here, we found that a few P.
caribaeorum lncRNAs shared relatively short but highly conserved
regions with known lncRNAs derived from higher organisms. Based on this
finding, we reasoned that these conserved regions could be associated
with P. caribaeorum lncRNA target-interaction and regulatory functions.
Concurrently, the lncRNA-mRNA interactions were predicted using RNAplex
and indicated that the majority of the putative hybridization sites
were restricted to conserved lncRNA segments (regions). Therefore, we
proposed an alternative strategy to potentially screen more
lncRNAs-mRNAs interactions in P. caribaeorum transcriptomes, and
hypothesized that such lncRNA interactions are implicated in
posttranscriptional regulation in P. caribaeorum according to
differences in metabolic status.
The fact that coral bleaching, a sort of ‘disease outbreak’ of
anthozoans, has increased in frequency in recent decades has pushed
many researchers to investigate the mechanism(s) of coral bleaching
response and holobiont collapse. A number of biological processes and
pathways, as well as DGEs related to bleaching have been revealed by
means of deep RNA sequencing of distinct unrelated coral species.
Nevertheless, the implication for lncRNAs in corals, in general, and
for anthozoan transcriptomes, of coral bleaching in particular were not
taken into account prior to the present study.
Altogether, interesting data emerged from our analysis: firstly, the
repertoires of lncRNAs in P. variabilis and P. caribaeorum are
quantitatively and qualitatively more homogeneous than among organisms
of distinct phyla; secondly, cross-interaction of lncRNAs of P.
caribaeorum with a group of mRNAs from a phylogenetically close species
of cnidarians, like the starlet sea anemone, suggested conservation
with respect to the target-drive function of lncRNAs. Another
remarkable discovery is the variation in the expression level of
certain lncRNAs in the transcriptomes of healthy P. caribaeorum versus
colonial individuals undergoing bleaching, as well as identification of
their potential target mRNAs, which also displayed variable levels of
expression and are probably implicated in the underlying molecular
response to bleaching. As can be observed here, our analysis suggests
that some up-regulated DELs might be involved in the
posttranscriptional regulation of mRNAs encoding two important groups
of protein effectors: one related to immune responses and another to
Ras intracellular signaling. Acting in concert in the bleaching
response of P. caribaeorum, these groups of multi-effector polypeptides
(and their mRNA precursors) are recruited and modulated in a tentative
bid to mitigate pathogenic microbial assault and control infection and
promote tissue remodeling to maintain symbionts and the functionality
of the holobiont. It is known that allorecognition, xenorecognition and
restriction (killing reaction) are inherent abilities of anthozoans,
allowing them to thrive in harsh aquatic environments. In fact, the
mechanism of underlying interaction between host and symbiont relies on
distinction by organisms and cells of self from non-self, which in turn
depends on proteins and signaling pathways concerned with the innate
immune response and molecular patterns of cell recognition and
adhesion^[173]66, [174]67. Furthermore, there is an increasing number
of examples showing that cross-kingdom RNA trans-regulation is a
process that triggers gene silencing and regulation mediated by small
RNA and double-stranded long RNA that translocate bi-directionally from
the host to the partner symbiont/pathogen^[175]68. In this context, one
can conceive that lncRNAs might act as additional interplayers in the
array of molecular dispositive to discriminate self (symbionts) from
non-self (pathogens) and regulate the residence of beneficial
microorganisms that are detrimental to pathogens. To our knowledge, our
findings disclose for the first time the presence of lncRNAs in the
transcriptomes of two species of zoanthids, and pave the way for a new
perspective on the molecular mechanisms of coral bleaching, as
demonstrated in healthy and diseased (undergoing bleaching) P.
caribaeorum by transcriptome analysis.
Electronic supplementary material
[176]Supplementary information^ (2MB, pdf)
Acknowledgements