PHYLOGENETIC INFERENCES ON CARIBBEAN SCLERACTINIAN CORALS

BASED ON ITS2 SECONDARY STRUCTURES PREDICTION

Gisselle Rivera Cárdenas

Running head: Phylogenetic relationships in Scleractinia based on ITS2 secondary

structure

Keywords: Scleractinia, Caribbean, coral reefs, ITS2, secondary structure, phylogenetic

analysis.

ABSTRACT

Most of reef-building corals belong to the Scleractinia order. Historically, the taxonomic

classification of this order has been subject to a lot of controversy, given that it has been

mostly based on morphological features and the lack of robust molecular markers to

elucidate true monophyletic relationships among species. The ITS2 nuclear marker has

demonstrated to be very useful in order to reconstruct well-supported phylogenetic

relationships, because primary alignments can be corrected according to the secondary

structure folding. This study presents the most complete phylogenetic reconstruction for

Caribbean scleractinian corals (44 species) through this method. ITS2 sequences for all

Caribbean coral species were amplified by PCR, then folded using the secondary structure

prediction and considering the higher free negative energy available and finally analyzed

through maximum likelihood and Bayesian inference methods. Results show the

divergence between the two major clades reported previously in literature (robust and

complex). Support scores obtained for many species included in the phylogenetic analysis

showed to be very high; however, there are some specific cases (A. cervicornis, S. hyades,

F. fragum) that could not be established satisfactorily. Further analysis are recommended,

in which both morphological and genetic features are combined, in order to try to elucidate

the phylogenetic signal of challenging species and identify the most plausible hypothesis

that can explain the evolutionary processes underwent by this order.

INTRODUCTION

Coral reefs constitute the marine ecosystem displaying the highest biodiversity around the

world, which provide ecological services for millions of people that depend on them

(Cinner, 2014; Hughes et al., 2017). This astonishing environment, which structural basis

is composed mainly by corals, has been able to maintain itself on the planet for millions of

years. Corals have shown an amazing ability to adapt to an environment that has been

constantly changing lately at both global (e.g. climate change) and local scales (e.g.

pollution, overfishing, lack of conservation policies) (Harborne, Rogers, Bozec, &

Mumby, 2017; Hoegh-Guldberg, 2014). Highly reaffirmed in the literature, climate change

leads to events on the ocean, such as acidification and coral bleaching due to the increasing

temperature, and there has been a lot of concern on the last years about the future of coral

reefs (Donner, Skirving, Little, Oppenheimer, & Hoegh-Gulberg, 2005; Eyre et al., 2018;

Kitahara, Fukami, Benzoni, & Huang, 2016; Stolarski et al., 2011). Thus, scientists have

recently increased their interest on achieving a thorough understanding of how corals have

evolved and adapted to their environment throughout Earth’s History, given that now at

the Anthropocene era, corals are believed to change and display a brand new range of

arrangements and characteristics that have not been observed before (Eyre et al., 2018;

Hughes et al., 2017).

Most of reef-building corals belong to the order Scleractinia, which is an order that has

shown to be very difficult to define regarding its classification (Budd, Romano, Smith, &

Barbeitos, 2010; Fukami, 2008; Kitahara et al., 2016; Romano & Palumbi, 1996, 1997).

Several reasons are attributed to this fact: historically, its taxonomic classification has

relied on morphological features. However, many of these characteristics can be influenced

by different variables, such as the environmental ones (growth rate, exposition to waves,

mass spawning in the Acropora genus, among others), that can produce a great deal of

variation or even hybridization within a single coral colony (Fukami, 2008; Kitahara et al.,

2016; Odorico & Miller, 1997). Different studies have demonstrated as well that there can

be greater differences on morphological features (such as septal teeth, corallite walls, etc.)

between Atlantic and Pacific species (Budd et al., 2010). Therefore, taxonomic

relationships can be confusing and hard to establish (producing topologies with low

resolution) when based solely on morphological features, since it can be very hard to

establish which characteristics are synapomorphic at higher classification levels. This does

not mean that morphological features should be excluded from such classification studies,

but rather these should be extendedly analyzed along with molecular data; however, this

approach is often challenging and hard to implement (Fukami, 2008; Kitahara et al., 2016).

Molecular methods have been greatly developed in the last decades and have helped

scientist to improve the establishment of evolutionary relationships for this order (Fukami,

2008). However, phylogenetically speaking, it has not been clearly distinguished and most

of the studies are focused on establishing relationships at the family or genus level

(Kitahara et al., 2016), but higher levels have been difficult to determine. Scleractinian

corals have been believed to be subject to two different hypothesis in order to explain how

their evolutionary relationships occur: the first one is the reticulate hypothesis theory stated

by Veron in 1995 and supported by different studies, in which corals repeat speciation and

hybridization processes in an evolutionary time scale (mostly studied and identified for the

Acropora genus, although hybridization processes are much simpler to explain than

reticulate evolution, according to recent data) (Fukami, 2008; Kitahara et al., 2016; Odorico

& Miller, 1997; J. Veron, 1995; J. E. N. Veron, Odorico, Chen, & Miller, 1996). The second

corresponds to the two-clade hypothesis (stated first by Romano and Palumbi in 1996), in

which the order is separated into two major clades (“Robust” and “Complex”) based on

mitochondrial 16S and 12S rDNA studies (Chen, Wallace, & Wolstenholme, 2002;

Romano & Palumbi, 1996, 1997). Kitahara and coworkers in 2010 also reported two

families diverging greatly from the major two clades mentioned before and that are

believed to have emerged before in time, which were classified as the “basal” clade and are

composed by solitary, deep-water and azooxanthellate corals (Kitahara, Cairns, Stolarski,

Blair, & Miller, 2010). Strikingly, members from these families shown to have

monophyletic relationships (Kitahara et al., 2016; Stolarski et al., 2011)

Different arrangements have been proposed in the last century in an attempt to classify the

Scleractinia order, but many of these relationships remain uncertain to date, as mentioned

before. Current data analysis have shown that many Scleractinian families reported display

very chaotic and unorganized arrangements in the resulting topologies; moreover, some

species have not been able to be located in either of the two major clades (Fukami et al.,

2008; Kitahara et al., 2016). Overall, 5 families currently present uncertainty on their tree

positions (members can be located in both clades), 14 species from different genera have

not been able to be located in an accurate way in the topologies and many genera display

para or polyphyletic relationships (6 genera with at least 13 species among them) (Kitahara

et al., 2016) (see Table 1). The most recent classification states that the order is composed

by at least 30 different clades at the family level that are subdivided among the three major

clades mentioned, 11 for the “complex” clade, 15 for the “robust” clade and 2 for the

“basal” clade (Kitahara et al., 2016).

Table 1. Scleractinian coral families and genera that have shown uncertain or poorly defined

relationships, according to literature (Fukami et al., 2008; Kitahara et al., 2016)

Family Genera Acroporidae Acropora

Agariciidae Leptoseris and Pavona

Anthemiphylliidae

Anthemiphyllia

Astrocoeniidae

Stephanocoenia

Caryophylliidae

Phyllangia, Cladocora and Rhizosmilia

Dendrophyilliidae Balanophylia, Clapdopsammia, Dendrophyllia and Rhizopsammia

Euphylliidae Euphyllia, Gyrosmilia, Catalaphyllia, Montigyra, Simplastrea and Galaxea

Faviidae Solenastrea

Flabellidae Flabellum and Truncatoflabellum

Rhizangiidae Astrangia and Culicia

Oculinidae

Oculina

Siderastreidae Siderastrea

Under study Indophyllia, Leptastrea, Paracyathus, Polycyathus and Stephanocyatus

Different nuclear and mitochondrial molecular markers often used for phylogenetical

analysis in Eukaryotes have been used as well for phylogenetical analysis in Scleractinia.

Nuclear examples include 28s, 5.8S, 18s, ITS-1 and -2, minicollagen, PaxC, Calmodulin

and ß-tubulin gene. Mitochondrial examples include 12 and 16s, cytochrome b, ATPase 6,

cox1, among others. Nevertheless, it has been difficult to identify which genes or set of

genes can actually work for most genera in all geographical locations, in order to elucidate

well-supported relationships based on topologies with the highest resolution possible

(Fukami, 2008; Kitahara et al., 2016).

Most studies reported for the Scleractinia order rely on mitochondrial genes, but these

suppose a difficulty for the analysis, since it was identified that the evolutionary rates of

coding genes are much more slower than others in different species, so it is hard to identify

differences in the sequences at the species level because the variation percentage is very

low (Fukami, 2008). Many large coral phylogenies have been using these markers

effectively, but still many evolutionary relationships remain unclear (too many

paraphyletic and polyphyletic groups); likewise, it has also been identified that major

clades display different patterns of evolution in mitochondrial gene sequences, that cannot

be aligned properly or might not be orthologous between species (applies mostly for non-

coding regions) (Kitahara et al., 2016).

Several studies have suggested that nuclear markers can provide low resolution for

phylogenetic inferences given its intragenomic variation, percentage of INDELS and

saturation, but this can be corrected through secondary structure folding (Aguilar &

Sánchez, 2007; Chen et al., 2004). Moreover, nuclear markers can provide a better

resolution since they are single-copy genes and even though the evolutionary rates are

conservative and similar among scleractinian coral species, they can display enough

nucleotide differences that can be analyzed and provide useful information (Coleman,

2007; Fukami et al., 2008). One of the nuclear markers most commonly used is ITS2

(Internal Transcribed Spacer) because it possesses very unique advantages: it has enough

variation to be able to identify a species sequence as unique (gives information about the

level of the biological species), there are no cases of horizontal transfer (as opposed to

mitochondrial sequences), and they are common to every known taxa, unlike some

mitochondrial sequence segments as has been mentioned before (Coleman, 2007) which

means it is universally common. ITS2 has another great advantage, that is its secondary

structure. The folding prediction of its transcript secondary structure allows identifying the

most conserved and variable motifs among taxa in order to suggest the formation of helixes,

loops or bulges by considering base pair compensation (Chen et al., 2004) and providing

correct alignments that can enhance phylogenetic tree topologies.

The main objectives to be fulfilled in the present study are: (1) to establish the most

complete phylogeny up to date for Caribbean species belonging to the Scleractinia order

using the ITS2 nuclear marker and (2) provide an adequate and high resolution and support

for the resulting topology by correcting sequences alignment through ITS2 secondary

structure folding.

MATERIALS AND METHODS

Samples collection

Scleractinia coral samples were collected from different locations in Cartagena and Islas

del Rosario y San Bernardo, Colombia (Table 2 and Figures 2 and 2a) during experimental

fieldwork carried out by Grajales and coworkers in 2016 and López-Angarita and

coworkers in 2014 (Grajales & Sanchez, 2016; López-Angarita, Moreno-Sánchez,

Maldonado, & Sánchez, 2014). Tissue samples of symbiotic corals smaller than 1cm2 were

collected through Scuba or CCR diving at different depths, both in the upper slope regions

or coral mixed zones (Sánchez et al., 2019). Initially, samples for 46 different scleractinian

species were obtained and stored for further identification. Data such as depth for each site,

coordinates, as well as ecological traits, were recorded in several databases in order to have

the most complete information available for each tissue sample collected and further

analyzed in this study.

Table 2. List of scleractinian coral species sampled in the area of study.

SAMPLE CODES SPECIES SAMPLE CODES SPECIES

B493, C14, C278, X12 Agaricia agaricites AC1-AC52-AC56 Acropora palmata

A5C, B269, B38C, I21, I23, I24, I25 Agaricia fragilis C165, C211 Montastraea cavernosa

A3C Agaricia franskii A673 Mussa angulosa

A11C, A8C, B36C Agaricia grahamae B459, C18 Mycetophyllia aliciae

A4C Agaricia humilis B470 Mycetophyllia ferox

A10C, A2C, C107, C35, C8, I22 Agaricia lamarcki B462 Mycetophyllia danaana

A161, B31C, C5 Agaricia tenuifolia A131, A162, C274, CTG16 Orbicella annularis

A9C, B32C, B35C, C261 Agaricia undata C279, C3, C50, CTG15 Orbicella faveolata

B33C, C49 Colpophyllia natans CTG1 Orbicella franskii

C116 Dichocoenia stokesii S112, S114, S115, M1, M2, M3 Orbicella sp. C172 Diploria clivosa

C19, C4 Diploria labyrinthiformis A154, C16, C2 Porites astreoides

C273 Pseudodiploria strigosa C270, X24 Porites colonensis

A198 Eusmillia fastigiata A159, B34C, C256, CTG15 Porites furcata

C27 Favia fragum P1 Porites porites

X35, X7, CTG20 Isophyllia rigida B260, B263, C25 Scolymia cubensis

CTG14 Isophyllia sinuosa B256 Scolymia lacera

A6C, B40C, X29 Helioseris cucullata

A114C, B34C, B39, I17, I18, I19,I20, S1, S2, S20, S3, S4, S5, S6, S7 Scolymia sp.

C30, C34, X6 Madracis decactis

C17, C9 Siderastrea siderea

C32, C37, X37 Madracis aurentera

CTG22 Solenastra buornoni

I16 Madracis sp.

A170, C174, C267 Solenastrea hyades

B423, B429 Meandrina meandrites

CTG8 Stephanocoenia intercepta AC5-AC6 Acropora cervicornis

B681 Tubastrea coccinea

Figure 2. Sampling locations marked with a yellow label (Cartagena and Islas del Rosario andSan Bernardo, Colombia). Red lines show the distance from each point sampled to the nearesthuman settlement.Distances were calculated in km using Google Maps. Sites names are: 1. Burbujas, 2. Boya, 3. Caño Ratón, 4. Isla Gloria, 5. Juan Guerra, 6. Latifundio, 7. Montañita, 8. Niko, 9. Playita, 10.Punta Brava, 11. Pavitos, 12. Rosario, 13. Salmedina, 14. Tesoro.

Figure 2a. Close-up of sites sampled in the Archipelago of Corales del Rosario and SanBernando, showing all the sites sampled.

DNA extraction

ITS2 sequences from scleractinian corals were obtained by following several steps. The

first one was a DNA extraction, following a CTAB protocol (Coffroth, Lasker, Diamond,

Bruenn, & Bermingham, 1992). A small fraction of coral sample (0.5 cm) was transferred

into an Eppendorf vial and 500 µl CTAB (Cetyl trimethylammonium bromide) were added.

Afterwards, two µl of proteinase K were added and samples were incubated for 24 hours

at 65ºC. For DNA digestion, 300 µl FCIA (phenol, chloroform and isoamyl alcohol) were

included to each sample and then, all samples were centrifugated for 5 minutes at 12000

rpm. The supernatant was transferred into another Eppendorf and 300 µl CIA (chloroform,

isoamyl) were added in order to completely separate residues from DNA and then, another

centrifugation was carried out (5 minutes at 12000 rpm). The upper layer obtained was

transferred into a new tube and 800 µl alcohol (96%) were included; after this procedure,

samples were stored at -20ºC for 12 hours. A new centrifugation was carried out (30

minutes at 12000 rpm) and the subsequent supernatant was discarded, maintaining the

DNA pellet in the tube. After adding 300 µl alcohol (70%) and carrying out a centrifugation

for 15 minutes at 12000 rpm, the upper layer of the samples was discarded again and these

were dried out and re-suspended in 100 µl TE buffer. Finally, all samples were read in the

Nanodrop spectrophotometer in order to confirm the correct outcome for the extractions

and assess both the DNA concentration (ng/ µl) and quality from all the samples extracted.

ITS2 Amplification

After the DNA extraction, ITS2 amplification was carrying out a PCR using two primers

designed by Aguilar & Sánchez (Aguilar & Sánchez, 2007), 5.8S 5’-

AGCATGTCTGTCTGAGTGTTGG-3’ and 28S 5’ GGGTAATCTTGCCTGATCTGAG-

3’, in order to amplify the nuclear ITS2 region for the scleractinian corals assessed. These

primers amplify a fragment that can be variable according to the coral species, but can

range between 110 and 250 bp. Approximately, 20 bp from flanking sequences (5.8 and

28s) were included because they have been identified to be very important in order to

correctly fold the ITS2 secondary structure (Chen et al., 2004). The PCR profile used for

all samples was: 5x Buffer, 10mM dNTPs, 25mM MgCl2, 20 µg/mL BSA, 5 U/µL Taq,

0,10 µM per each primer, 1 µL DNA and ddH2O (1/50), in order to achieve a final volume

of 15µL. PCR thermal conditions were followed according to the protocol described by

Chen and coworkers in 2004 (Chen et al., 2004). Samples were transferred for reading into

a PCR electrophoresis stained gel using ethidium bromide and containing 1.3% agarose

and 0.5 TBE buffer, which was configured to run for 60 min at 60V and 400 mV. The final

product was visualized in a gel documentation system through the QuantityOne software

(Bio-Rad Laboratories, n.d.). PRC products for the initial 46 coral species were cleaned

using the Exo-SAP-IT protocol (Applied Biosystems™) and then, these were sent for

sequencing at Macrogen biotechnology company (Seoul, Korea). After retrieving the

results from the samples processed in Macrogen, both forward and reverse ITS2 sequences

obtained were analyzed using the Geneious 2 Basic software (Kearse et al., 2012), based

on the resulting chromatograms. This procedure allows obtaining contigs based on the

quality and identity percentage for each pair of sequences. In consequence, it was possible

to identify which consensus sequences displayed the highest identity or which showed to

be heterozygous (those showing low identity, which are common to be found in nuclear

loci) (Kitahara et al., 2016). Therefore, sequences showing low identity would need to be

discarded. After analyzing and selecting all the ITS2 contigs with the proper quality and

identity, these were translated in order to obtain the corresponding RNA sequences for

further analysis.

ITS2 Secondary structures folding

In order to determine the ITS2 secondary structure from the scleractinian coral sequences

included in the analysis, both RNA sequences and structures were compared to those

reported by Chen and coworkers in 2004, Coleman in 2007 and Odorico & Miller in 1997

(Chen et al., 2004; Coleman, 2007; Odorico & Miller, 1997) including additional parts of

both 5.8s and 28S regions, given that they have shown to be important for the structure

stability during folding by forming canonical bonds (Chen et al., 2004). Sequences were

then folded manually through the MFOLD software (Zuker, 2003) taking into account their

corresponding restrictions and constraints, in order to form helices and loops for each

sequence. Default parameters were used during the structure’s folding. The structures used

in this analysis were the ones more similar to the reference structures found in previous

literature, trying to choose those with the higher negative free energy available. After

sequences folding, the corresponding Vienna formats produced were used along with RNA

primary sequences in order to be edited and aligned using the 4SALE software (Seibel,

Müller, Dandekar, Schultz, & Wolf, 2006). This software uses ClustalW2 as the resource

for carrying out the multiple sequence alignments (Larkin et al., 2007). Sequences aligned

and corrected by their secondary structure were used to carry out the phylogenetic analysis,

which will be described in the following section. After retrieving the secondary structures,

these were edited through the VARNA software for better visualization (Darty, Denise, &

Ponty, 2009).

Phylogenetic analysis

Two phylogenetic analyses were carried out using the alignments corrected by ITS2

secondary structures. The first one is a Maximum Likelihood analysis (ML), using the

RaxML-HPC Blackbox software v.8 (Stamatakis, 2014) through the CIPRES Science

Gateway portal (Miller, Pfeiffer, & Schwartz, 2010). The Blackbox interface includes

support for RNA secondary structures and provides branch bipartition scores. This analysis

was carried out using default parameters: heuristic search, parameters for the nucleotide

model of substitution GTRGAMMA and branch support with 1.000 bootstrap replicates.

The second analysis consisted on a Bayesian inference using Mr. Bayes software (Ronquist

et al., 2012), using the parameters of substitution model (GTRGAMMA) according to the

AIC selection results inferred by the JModelTest software (run through the CIPRES portal)

(Posada, 2008). Mr. Bayes analysis was carried out using the following parameters:

1.000.000 MCMC, 4 chains repetitions and a burn-in of 1.000.000, being sure to obtain the

proper PSRF and EES values for each run to ensure that the analysis was run long enough

to provide the best possible support. The NEXUS conservative file used to run the

sequences was created using the MESQUITE software (Maddison & Maddison, 2001). The

generated trees were further observed and edited for its correct displaying (i.e. format and

branch labels and post-probability Bayesian and ML scores, correspondingly) using the

FigTree software v.1.4.4 (Rambaut, 2018).

RESULTS AND DISCUSSION

ITS2 amplification for coral species

ITS2 amplification was achieved for all 46 coral species through the PRC method described

in the previous section (Figure 1, supplementary material). Nevertheless, at the time of

carrying out the contigs analysis, two species had to be removed according to the selection

criteria for high quality and identity, and there were no more samples available to be

analyzed. The species removed from the study at this point were A. palmata and E.

fastigiata. Therefore, only 44 species were included for the subsequent analysis.

It was noted the importance of having several samples corresponding to different coral

species, so that if any ITS2 sequence cannot be amplified from a given sample, there are

other options of samples to be sequenced and thus, the dataset included in the study is as

complete as possible. Another aspect that must be considered is that sometimes the physical

integrity of the tissue samples is not the best (stored for far too long time, degraded over

time, etc.) and therefore, these variables can affect the results obtained for the PCR

amplification.

ITS2 Secondary Structures

ITS2 secondary structures obtained for all the scleractinian coral species analyzed

exhibited a 5-domain structure, except for the following species: D. labyrinthiformis, F.

fragum, I. rigida, I. sinuosa, P. strigosa, S. siderea and all the Mycetophyllia species

included, which displayed the 4-domain model typically described for many Eukaryotes.

The presence of the fifth helix for these sequences corresponds to a bifurcation of helix I

(Ia and Ib). There was one exception: sequences from Acropora species were folded as

described by Chen and coworkers in 2004 and Odorico and Miller in 1997 (Chen et al.,

2004; Odorico & Miller, 1997). This configuration corresponds to a 5-domain model,

where domain III is divided in 2 (helices IIIa and IIIb). For every species, the motif ‘5 –

CRCG-GYC – 3’ on the second helix was conserved, as well as the motif ‘5 –

GCGRAGGC – 3’ on helix III (Figure 4, 5 and 6), which are well supported from results

obtained in previous studies (Chen et al., 2004; Coleman, 2007). The inclusion of part of

both 5.8s and 28S regions in the sequence showed to be very important, since these regions

form canonical bonds among them as has been previously suggested by literature and

allows the structure to fold correctly (Chen et al., 2004; Coleman, 2007).

Figure 4. Example of secondary structures folded for D. labyrinthiformis and I. sinuosa, which showthe common 4-finger hand model exhibited by most of eukaryotes (Chen et al., 2004). Both figures show the conserved motifs in Helices II and II (outlined with a red line).

Figure 5. Example of secondary structures folded for L. cucullata and M. cavernosa, which showthe 5-domain model exhibited for most Scleractinian corals included in this study, with the bifurcation of Helix I in Helix Ia and b (Chen et al., 2004). Both figures show the conserved motifs in Helices II and III (outlined with a red line).

Figure 6. Example of the secondary structure folded for A. cervicornis, showing the 5-domain model suggested by Chen and coworkers in 2004 and Odorico and Miller in 1997, with the bifurcation of Helix III in IIIa and b (Chen et al., 2004; Odorico & Miller, 1997). The figure show the conserved motifs in Helices II and IIIa (outlined with a red line).

It is already known that Acropora displays a different behavior regarding its evolutionary

history, because of the hybridization and different patterns that are consistent with

reticulate evolution; moreover, it has been reported that the ITS2 sequence for this species

is also shorter than the other scleractinian corals (Kitahara et al., 2016; Odorico & Miller,

1997). However, for this study the sequence length was similar to the other scleractinian

species, a fact that should be reviewed further in the light of the particular characteristics

displayed by the Acropora genus. At the time of carrying out the secondary structure

folding for all the species and under default parameters set by the MFOLD software, the

ITS2 sequence for Acropora tended to display a 5-domain model obtained for the

remaining sequences analyzed here. However, since the first phylogenetic analysis, it was

observed that this configuration didn’t allow the sequence to be placed accordingly to what

has been previously described in literature (Chen et al., 2004; Kitahara et al., 2016; Odorico

& Miller, 1997). Therefore, the sequence folding was changed to the type with the

bifurcation in helix III, so it would fit in the further analysis and be placed correctly.

Anyhow, this configuration didn’t allow either the species to place in the position that it is

supposed to according to previous studies when carrying out the phylogenetic analysis, so

the suggestion here is to broaden and carry out further studies for ITS2 sequences in

Acropora.

Phylogenetic analyses

The resulting phylogenetic construction for Caribbean scleractinian coral species based on

maximum likelihood and Bayesian inference analysis is shown in Figure 7. Posterior

Bayesian probabilities and bootstrap support for branches are indicated in each case. The

outgroups chosen for the analysis were: Epizoanthus sp., Savalia sp. and Parazoanthus sp.,

three octocoral species.

Overall,the resulting tree topology for the Scleractinia order showed to have a very good

support for both types of analysis (ML and Bayes), given that most of the scores went

greater than 0.75 or 70. Thus, it is possible to affirm that the methods used in this study in

order to implement ITS2 gene sequences for providing a robust phylogenetic signal is

appropriate and that it gives an important insight of intragenomic variation among closely-

related species. The secondary structure folding for the ITS2 sequences had allowed to

provide an excellent support for the primary alignment, which can be demonstrated based

on the ML and posterior Bayesian probabilities obtained for the trees’ phylogenetic

reconstruction (Figure 7). Therefore, results from previous studies where different authors

suggest the use of ITS2 sequences corrected by their secondary structure are reaffirmed

(Chen et al., 2004; Coleman, 2007; Grajales, Aguilar, & Sánchez, 2007; Odorico & Miller,

1997; J. E. N. Veron et al., 1996). This nuclear marker then, constitutes an excellent option

to be included in phylogenetic analysis for scleractinian corals and should be considered in

a greater proportion when choosing the appropriate markers to carry out such types of

phylogenetic analysis.

Figure 7. Phylogenetic relationships obtained for Caribbean Scleractinian coral species analyzed.

Tree topology shows both posterior probabilities for each branch obtained by Bayesian inference

(left score) and bootstrap support obtained by ML (right score). The tree structure chosen was the

one corresponding to the Bayesian inference analysis. Important remarks regarding evolutionary

relationships between species found in different ML and Bayesian analysis run are shown in red

and further discussed (squares, species name, scores or segmented lines).

The topology showed to diverge in two major clades (“robust” and “complex”), as has been

previously reported and mentioned at the beginning of this study (Chen et al., 2004;

Fukami, 2008; Kitahara et al., 2016; Stolarski et al., 2011; J. E. N. Veron et al., 1996) and

most of the species analyzed here happened to be located in the corresponding position

according to literature, but italso showed to have some inconsistencies. The use of the

secondary structures to correctthe primary alignment definitively showed to help defining

better relationships among taxa; however,statistical support was not enough to unravel

definitive reciprocal monophyletic groupsfor this order and therefore, it needs to continue

to be improved (Figure 7). The analysis was run several times, including or excluding taxa

depending on how the relationships among species were shown to be grouped, so at the

end two greater analysis were considered. The first one included all the species after folding

their corresponding secondary structures (not shown in this study, only some relevant data

of the analysis was included overlapped in Figure 7, either squaring coral species, showing

score supports or positioning coral species on the topology, which are outlined in red). On

the other hand, the second one showed the greatest statistical support, presumably because

some samples were excluded from the analysis, as well as F. fragum (shown in Figure 7).

These excluded samples did not have an impact on the number of species sampled, since

there were other samples representatives on the dataset.

Regarding the relationships that needs to be further reviewed, FamilySiderastreidae and

Poritidae grouped together; but F. fragum showed to group within the Siderastreidae

family, when it should be grouping with the Diploria genus, within the “robust” clade. That

was the reason why it was excluded from the second analysis. On the other hand, A.

cervicornis showed to group with D. labyrinthiformis, P. strigosa and C. natans, inside the

“complex” clade, when it should be grouped on the “robust” one. Even though this was

evidenced, the tree topology lost all scores and resolution when A. cervicornis was

excluded from the analysis, so it was decided to be left on the position it was clustered. The

same situation happened with S. hyades, which appeared to be grouped along with S.

intercepta and the Agaricia complex, when according to literature it should be grouped in

the “robust” clade, ideally next to S. bournoni. However, these were the most critical

species that could not be excluded from the analysis, due to the loss of high support

branches scores and resolution for the tree topology. But undoubtedly, more studies on this

regard are needed.

In spite of obtaining excellent support for branches scores, since there is not enough

information regarding other nuclear or mitochondrial genes that can support the data

obtained for the tree topology presented in this study, more studies would be needed in

order to confirm these positions. It is important, as well, under this scope, to test the

methods used in this study in order to analyze biogeographical patters (that is, to include

both Atlantic and Pacific species in a same study) and determine whether these analysis

provide a good support for the tree topologies produced, since differences have been

detected between species samples coming from different locations in previous studies

(Fukami, 2008; Kitahara et al., 2016).

Since scleractinian corals have shown to be very difficult and complicated to analyze and

understand from their evolutionary perspective, and as has been suggested before by

several authors (Fukami, 2008; Kitahara et al., 2016), the ideal scenario in order to

elucidate scleractinian corals evolutionary relationships with the maximum scores and

resolution would be to carry out analysis considering both morphological and genetic data

(best if different genes or sequences are included, both mitochondrial and nuclear), in order

to provide the most complete dataset available and rely on more complete information

regarding every species to be sampled. Therefore, it would be very interesting to carry out

phylogenetic community structure analysis on such type of studies, because it allows to

implement both types of datasets.

Biotic and abiotic variables suggested to be included for these analysis can be depth

(Bongaerts et al., 2011; T. C. LaJeunesse, 2002; Todd C. LaJeunesse et al., 2004), distance

to the nearest human settlement (human impact over coral reefs are supported by studies

showing that terrestrial run-off could affect marine environments, as a source of increased

sedimentation rates and organic and inorganic dissolved matter into the water (Fabricius,

2005)), holobiont assemblages (coral and Symbiodinium species combined), off-shore vs.

in-shore locations, water exposure, temperature, coral coverage, morphological

characteristics of coral species (being the coral skeleton the most important one according

to recent data (Kitahara et al., 2016; Stolarski et al., 2011)), among others. It would be

important as well to analyze local and regional processes affecting particular species in an

area, since ecological variables have demonstrated to be affected at different scales (Cooper

et al., 2011; Todd C. LaJeunesse et al., 2010).

Other unpublished data (Rivera G., preliminary data) suggest that biotic narrow

relationships such as the presence of different types of zooxanthellae within the coralmight

give them the opportunity to colonize other sites and develop different nicheoccupancies,

allowing similar species to coexist and avoid competition. These types of observations can

be particularly important in order to consider different variables and ecological processes

than might be affecting the species plasticity or adaptation ability and therefore, the way in

which they converge or diverge over time. Thus, all of these variables would needed to be

considered when carrying out further analysis and studies on this matter.

In conclusion, ITS2 sequences provide an excellent support for phylogenetic analysis,

allowing the correction of the primary alignment with the use of the secondary structure

prediction. This analysis allowed constructing a very complete phylogeny for the

Scleractinia order, which showed to possess very high scores and resolution for the tree

topology and therefore, many closely-related species relationships can be reaffirmed or

confirmed according to previous studies. However, there are still some relationships

between species that were not completely established in this study, which is why further

studies are needed in order to solve these queries. The use of different molecular markers

(both mitochondrial and nuclear) is suggested in order to improve the phylogenetic signal

for the relationships found within this order. Another important point is to consider

conducting further studies by correlating ecological and genetic data at the same time, in

order to consider many variables (environmental mostly) that can be affecting scleractinian

corals adaptation to their environment and in consequence, can provide a more complete

insight on how the evolutionary processes and relationships among this order occurs.

ACKNOWLEDGEMENTS

I would like to gratefully thank first of all Juan Armando, for his great patience and

guidance throughout the research development and the process of reviewing and correcting

this manuscript and the opportunity to carry out this research, Maylin González, Andrés

Link, Julio Andrade, Natalia Jiménez, Mauricio Buitrago, Adriana Sarmiento, Fabio

Casas, Lina Gutiérrez, Luisa Dueñas, Fanny González and colleagues from BIOMMAR

(Laboratorio de Biología Molecular Marina, Universidad de los Andes) for their invaluable

field and lab assistance, as well as for helpful ideas, discussions and reviews in order to

develop the present study. I would also like to thank my family and friends, whose support,

love and patience was extremely important. Also, my work mates (Nico, Jaime and Mao)

for their continuous support and help during this time. Finally, I would like to dedicate the

efforts made through this research to the loving memory of my dad. This study was funded

by the Science Faculty (Biological Sciences Department) from Universidad de los Andes,

through its “Proyecto Semilla” grant and Ecoral SAS (Medellín, Antioquia, CEO Federico

Botero) that funded some field trips, in which Juan Armando Sánchez collected some

samples. The Natural History Museum from Universidad de los Andes also provided some

samples for this study.

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SUPPLEMENTARY MATERIAL

Figure 1. Example of PCR electrophoresis, in which the ITS2 PCR products were amplified

according to the parameters set and explained in the Materials and Methods section for this study.

Each cell on the electrophoresis gel corresponds to a different scleractinian coral species.