Multi-gene phylogenetic analysis reveals the multiple origin and evolution of mangrove physiological traits through exaptation

Accepted Manuscript Multi-gene phylogenetic analysis reveals the multiple origin and evolution of mangrove physiological traits through exaptation Sunil Kumar Sahu, Reena Singh, Kandasamy Kathiresan PII:

S0272-7714(16)30476-0

DOI:

10.1016/j.ecss.2016.10.021

Reference:

YECSS 5280

To appear in:

Estuarine, Coastal and Shelf Science

Received Date: 1 April 2015 Revised Date:

20 August 2016

Accepted Date: 16 October 2016

Please cite this article as: Sahu, S.K., Singh, R., Kathiresan, K., Multi-gene phylogenetic analysis reveals the multiple origin and evolution of mangrove physiological traits through exaptation, Estuarine, Coastal and Shelf Science (2016), doi: 10.1016/j.ecss.2016.10.021. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT

Multi-gene phylogenetic analysis reveals the multiple origin and evolution of mangrove physiological traits through exaptation Sunil Kumar Sahu1, 2*, Reena Singh1,3 and Kandasamy Kathiresan1

Centre of Advanced Study in Marine Biology, Faculty of Marine Sciences, Annamalai

University, Parangipettai, Tamil Nadu - 608502, India 2 Present address

RI PT

1

State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant

Resources, School of Life Science, Sun Yat-Sen University, Guangzhou - 510275, P. R. China Central Island Agricultural Research Institute, Port Blair - 744101, India

SC

3

*Corresponding author: Email: [email protected]; Tel: +86 13535124942; Fax no.

M AN U

+86 (20) 84110712 Abstract

Mangroves are taxonomically diverse group of salt-tolerant, mainly arboreal, flowering plants that grow in tropical and sub-tropical regions and have adapted themselves to thrive in such obdurate surroundings. While evolution is often understood exclusively in terms of

TE D

adaptation, innovation often begins when a feature adapted for one function is co-opted for a different purpose and the co-opted features are called exaptations. Thus, one of the fundamental issues is what features of mangroves have evolved through exaptation. We attempt to address these questions through molecular phylogenetic approach using chloroplast and nuclear markers.

EP

First, we determined if these mangroves specific traits have evolved multiple times in the phylogeny. Once the multiple origins were established, we then looked at related non-mangrove

AC C

species for characters that could have been co-opted by mangrove species. We also assessed the efficacy of these molecular sequences in distinguishing mangroves at the species level. This study revealed the multiple origin of mangroves and shed light on the ancestral characters that might have led certain lineages of plants to adapt to estuarine conditions and also traces the evolutionary history of mangroves and hitherto unexplained theory that mangroves traits (aerial roots and viviparous propagules) evolved as a result of exaptation rather than adaptation to saline habitats. Key words: Adaptations; Evolution; Mangroves; molecular markers; Phylogenetics; Physiology 1

ACCEPTED MANUSCRIPT

1. Introduction One of the most profound questions in evolutionary biology is "how evolutionary adaptations and innovations originate?" A narrow focus exclusively on immediate adaptation fails to

RI PT

satisfactorily explain the origin of many important traits (Barve and Wagner, 2013). Darwin (1877) suggested that there are at least two distinct processes that can generate evolutionary novelty. One is natural selection acting directly on genetic variation generated by mutation to create new features and relationships (adaptation). The second is by selection or other processes

SC

having generated, in a prior context, features with a different function than at present (exaptation). In other words, exaptation is a feature that performs a function but that was not produced by natural selection for its current use. Perhaps the feature was produced by natural

M AN U

selection for a function other than the one it currently performs and was then co-opted for its current function. For example, feathers might have originally arisen in the context of selection for insulation, and only later were they co-opted for flight. In this case, the general form of feathers is an adaptation for insulation and an exaptation for flight. This has been called evolution by "exaptation" (Gould and Vrba, 1982; Arnold 1994). Exaptations have been reported to occur from the macroscopic to the molecular scale, but still the knowledge on the importance

TE D

of exaptations in the origin of adaptations is obscure (Tomarev and Piatigorsky 1996; True et al., 1999; Keys et al., 1999; True and Carroll 2002; Brancalion et al., 2010; Pievani and Serrelli 2011; Barve and Wagner, 2013). This limitation of case studies could be overcome in those biological systems where it is possible to study systematically many genotypes and phenotypes

EP

in which they seem to occur (Ferrada and Wagner 2012; Samal et al., 2010). Plants provide unique opportunities to study the mechanistic basis and evolutionary

AC C

processes of adaptation to diverse environmental conditions. Adaptation of plants is one of the most important areas of study in evolutionary biology especially given the fact that they are fixed to a substratum. Among the experimental systems in biology, plants provide excellent opportunities to study the interaction between genetic and environmental variation, which produces the complex traits observed in nature (Anderson et al., 2011). Plants in habitats with periodic or permanent flooding are challenged by several stresses, particularly the rapid depletion of soil oxygen following the onset of flooding (due to the much slower rates of oxygen diffusion in liquid compared to the gas phase (Blom, 1999). The resulting oxygen deficiency in 2

ACCEPTED MANUSCRIPT

the root of non-adapted species is considered to be the major factor negatively affecting the survival and growth of submerged plants (Colmer, 2003; Voesenek et al., 2004). Therefore, the possibility exists that the occurrence of mangrove species in unfavorable intertidal zones may have evolved through exaptation, a scenario where a morphological structure evolved in related

RI PT

plant groups have been utilized for a special function in these saline aquatic environments.

Mangroves are an ideal system to study adaptations in plants. Mangroves are a taxonomically diverse group of flowering plants that grow primarily in tropical and sub-tropical

SC

regions in the intertidal zone (Kathiresan and Bingham, 2001; Alongi, 2008). Mangrove forests are among the most productive and biologically important ecosystems of the world (Polidoro et al., 2010). Mangroves are spread in about 20 families, 27 genera, and 69 species among

M AN U

flowering plants (Spalding, 2010; Polidoro et al., 2010). Mangrove plants grow in soils which are highly waterlogged and with a salinity as high as that of the open sea (Kathiresan et al., 2013). They provide an impressive instance of trait evolution and a combination of diverse morphological and physiological adaptations (Shi et al., 2005). The adaptations of these mangrove plants’ root system well-defined types of aerial roots namely stilt roots, pneumatophores, knee roots, cable roots and buttress/plank roots which play three distinct roles:

TE D

aeration, anchorage, and nutrient absorption (Gill and Tomlinson, 1975; Tomlinson, 1986). These morphological components apparently have different origins in different species (Tomlinson, 1986). Black mangroves (Avicennia sp.) live on higher ground and have large numbers of pneumatophores (specialised root-like structures which emerge out of the soil like

EP

straws for breathing) which are also covered with pores (lenticels). All species in the genera Aegiceras, Avicennia, Acanthus and Aegialitis have salt glands and species in Laguncularia and

AC C

Conocarpus have structures analogous to salt glands (Tomlinson, 1986). Among seed plants, vivipary is most well developed in mangroves (Tomlinson, 1986). Vivipary can be divided into two types known as ‘‘true vivipary’’ and ‘‘cryptovivipary,’’ representing the two situations in which the embryo grows to break through the fruit wall or the seed coat, respectively (Tomlinson and Cox, 1986). Thus, one of the fundamental issues is what features of mangroves have evolved through exaptation? We attempt to address this by building a broad phylogeny of the mangrove species along with their sister taxa among their respective families. First, we determined if these mangroves specific traits have evolved multiple times in the multigene phylogeny. Once the 3

ACCEPTED MANUSCRIPT

multiple origins were established, we then looked at related non-mangrove species for characters that could have been co-opted by mangrove species for specialization in estuarine habitats. Previously the independent evolutionary origins of vivipary and salt secretion has been postulated in mangroves based on 18S rRNA, rbcL, and matR sequences of mangroves plants

RI PT

only (Shi et al., 2005). However, the evolution and origin of other adaptive features like aerial roots and salinity tolerant mechanisms among mangrove are still unexplored. Therefore, in the present study by taking advantage of molecular systematics and the recent methodological advances in analyzing character evolution in a given phylogeny, we have tried to address the

SC

following questions: (1) Whether molecular phylogeny supports the multiple origins of various adaptive features (aerial roots, viviparity and salt tolerant mechanisms) among mangroves? ; (2)

M AN U

Whether different types of aerial roots, and vivipary in mangroves is an exaptation, and are these traits also seen in non-mangrove sister species?; (3) How efficient are these chloroplast (matK and rbcL) and nuclear (ITS) markers in differentiating mangroves at species level? 2. Materials and Methods 2.1. Ethics Statement

The study does not require an ethics statement. However, for mangrove leaf sampling prior

forests.

TE D

written permissions were taken from the district forest officer (DFO) of the respective mangrove

2.2. Taxon sampling and study area

The leaf samples of mangroves species belonging to 14 families (17 genera and 37 species)

EP

were collected from various estuarine habitats of east and west coast of India (Fig.1). The field identifications were made by morphological observation by referring the mangrove identification

AC C

manuals (Naskar and Mandal, 1999; Banerjee et al., 1989). 2.3. DNA extraction, PCR and sequencing Genomic DNA from mangrove leaves was isolated by using the CTAB (Cetyl Trimethyl Ammonium Bromide) DNA extraction method (Sahu et al., 2012). Two chloroplast gene matK and rbcL were amplified using the universal primers (Wicke and Quandt, 2009) and the nuclear ITS locus (Internal Transcribed spacers) was amplified by using the primers described by White et al. (1990) (Table 2). Polymerase chain reactions (PCR) were performed in the following condition in TechGeneTM, thermal cycler. PCR reactions included 1-2 µl of template DNA (10– 4

ACCEPTED MANUSCRIPT

100 ng), 2.5 µl 10x MgCl2 Buffer (15 mM), 2 µl dNTPs (2.5 mM), 0.5 µl Taq DNA polymerase (1.0 U), 0.5 µl of each primer (10 mM), and 18 µl H2O (total volume, 25 µl). The PCR reaction for the matK gene was carried out in a one-step touchdown PCR-program (1 cycle at 90 s at 96ºC, 60 s at 50ºC, 120 s at 68ºC, 35 cycles at 30 s at 95ºC, 60 s at 48ºC, 120 s at 68ºC,

RI PT

subsequent final elongation of 20 min at 68ºC). However, the PCR cycling profile for rbcL and ITS locus included initial denaturation at 94ºC for 5 min, followed by 35 cycles of 30 s at 94ºC, 60 s at 60ºC (rbcL)/ 60 s at 54ºC (ITS) and 90 s at 72ºC. The successfully amplified gene products were sequenced by Sanger’s dideoxy method in an automated ABI sequencer at

SC

Macrogen Inc, Korea. An extensive literature survey was made to assess the presence of similar morphological characters/traits among all the representative mangrove families. Therefore, 63

2.4.

M AN U

sequences of non-mangroves and associated species were also retrieved from Genbank (Table 1). Sequence alignment and phylogenetic analysis

Sequences of matK, rbcL and ITS were aligned using the program MUSCLE (Edgar, 2004) and manually adjusted using BioEdit (Hall, 1999). Tree searches were performed using maximum likelihood and Bayesian approaches. Prior to these analyses, the best-fit substitution model was determined using Modeltest 3.7 (Posada and Crandall, 1998). Based on the Akaike

TE D

Information Criterion (AIC), GTR + I + G substitution model was selected. Maximum likelihood analyses were carried out using RAxML GUI 1.3 (Silvestro and Michalak, 2011), setting partitions for each region, the model to GTR+GAMMA+I and the bootstrap (BS) analysis with 1000 replicates.

EP

For the Bayesian analysis of the concatenated data, the same partitions were defined as for the RAxML analysis. Analyses were performed with MrBayes, version 3.1.2 (Huelsenbeck

AC C

and Ronquist, 2001; Ronquist et al., 2012), employing a Markov chain Monte Carlo (MCMC) procedure in order to simultaneously estimate an optimal phylogenetic tree and the posterior probabilities (PP) of interior branches (Rannala and Yang, 1996; Li et al., 2000). Four parallel Markov chains were run for five million generations, sampling every thousand generations. Convergence of runs was tested by inspecting whether the standard deviation of split frequencies of the runs was <0.01 and by using the effective sample sizes (ESS) as calculated with Tracer 1.4, considering ESS values >200 as good evidence (Rambaut and Drummond, 2007). Majority rule (>50%) consensus trees were constructed after removing the ‘‘burn-in period’’ samples (the first 25% of the sampled trees). The evolutionary history was also inferred using the Maximum 5

ACCEPTED MANUSCRIPT

Parsimony method MEGA6 based on the Subtree-Pruning-Regrafting (SPR) algorithm with search level 1 in which the initial trees were obtained by the random addition of sequences (10 replicates). To test if the various adaptive features such as buttress root, stilt root, pneumatophores,

RI PT

aerial roots, vivipary and salt tolerant mechanisms have originated multiple times among the mangroves, likelihood-based on Shimodaira-Hasegawa (SH) test was carried. For various traits listed in table 3, first a constraint tree was built wherein species exhibiting a particular trait was placed in a monophyletic group. The Log likelihood scores of constrained trees were compared

SC

with the best tree by implementing SH-test in PAUP v4.0b10 (Swofford, 2002). The null distribution was generated by using the RELL method with 1000 bootstrap replicates (Kishino

M AN U

and Hasegawa, 1989). In all the analysis Nypa fruticans, Phoenix paludosa, P. dactylifera and P. canariensis were taken as an outgroup taxon.

2.5. Ancestral state reconstruction

To reconstruct the physiological traits of mangroves such as vivipary and aerial roots (stilt roots, buttress roots, knee roots, pneumatophores) including salt tolerant mechanisms (salt

TE D

exclusion; salt excretion, and salt accumulation) using the R package ‘diversitree’ (FitzJohn, 2012). To infer patterns of character evolution, the most parsimonious tree on the combined molecular dataset was employed. The ‘subplex’ model was used for the optimization and construction of ancestral state in diversitree (FitzJohn, 2012). The main syntax was “fit <-

Estimation of genetic distance

AC C

2.6.

EP

find.mle(lik, c(.1, .1), method="subplex") coef(fit)”.

Overall genetic distance among the mangrove and non-mangrove species was estimated

using the Kimura 2-parameter model in MEGA 6 (Kimura, 1980). All positions containing gaps and missing data were eliminated. Sequence statistics such as nucleotide frequencies and variability in different regions of the sequences were also computed. The transitions (Purine ↔ purine; pyrimidine ↔ pyrimidine) and transversions (purine ↔ pyrimidine) were also estimated using maximum composite likelihood method.

6

ACCEPTED MANUSCRIPT

3. Results Our phylogeny cements the backbone topology of complex mangrove lineages, providing the phylogenetic framework required to assess the evolutionary patterns of major physiological traits of mangroves such as vivipary and aerial roots (stilt roots, buttress roots, knee roots,

RI PT

pneumatophores) including salt tolerant mechanisms (salt exclusion; salt excretion, and salt accumulation) (Fig. 2). These major defining characters of the mangroves presumably enabled them to form a distinct identity as evident in the phylogenetic tree and ancestral state mapping (Supplementary figs.1-9). All the collected samples were vouchered and deposited in Annamalai

SC

University, Faculty of Marine Science (AUFMS) Herbarium with voucher number AUFMS1 to AUFMS256. The successfully amplified gene sequences showed good length ranging from 729

M AN U

to 1433 bp for matK; 1164 to 1433 bp for rbcL, and 566 to 742 bp for ITS. All the sequences were submitted to Genbank and accession numbers KJ784544-KJ784654 were obtained (Table 2)

3.1.

Phylogeny and ancestral state of physiological traits

Out of 1037 bases in matK sequence, 310 conserved bases, 701 variable sites, 475

TE D

parsimony informative sites and 224 singleton sites were found. For rbcL 101 conserved bases, 259 variable sites, 171 parsim informative sites and 88 singleton sites were found out of 1097 bases. In the case of ITS sequences out 765 bases 185 conserved bases, 530 variable sites, 439

EP

parsim informative sites and 89 singleton sites were observed. The phylogeny was constructed with a particular emphasis on the origin and evolution of

AC C

various adaptive characters in mangroves by using Bayesian inference (BI), Maximum Likelihood (ML) and Maximum Parsimony (MP) from the combined data of two chloroplast gene (matK and rbcL) and the nuclear locus ITS. Fig. 2 shows a similar, but more highly resolved phylogenetic pattern for mangroves than documented by the Shi et al. (2005). Topologically two major clades were formed; which was further divided into subclades showing clear distinction at genera and family level. The first major clade was comprised of six families namely

Rhizophoraceae,

Euphorbiaceae,

Lythraceae,

Combretaceae,

Meliaceae

and

Sterculiaceae. However, the second major clade was represented by Primulaceae, Sapotaceae, 7

ACCEPTED MANUSCRIPT

Rubiaceae, Bignoniaceae and Acanthaceae. Stilt root, the characteristic feature of Rhizophoraceae is not restricted within the family but it is also found in the members of Acanthaceae. Similarly, the presence of pneumatophores can also be seen among various families viz. Lythraceae, Combretaceae and Acanthaceae. Buttress root is another example of

RI PT

multiple origin where this character is found in Sterculiaceae, Meliaceae and Sapotaceae families. Hence, it is quite evident from the phylogenetic tree that all the characters are polyphyletic in origin and nested within other mangrove and non-mangrove species that lack the similar traits. The best tree had significantly higher likelihood than the trees where species were

SC

constrained based on various traits (P>0.05, Shimodaira–Hasegawa one-tail test) and thus the alternate hypothesis of the single origin of these traits was rejected (Table 3).

M AN U

As expected, the ancestral-state reconstructions using model-based estimates suggest the multiple origin of the physiological traits. Trait reconstructions also suggest that these typical mangrove traits are primarily present in other non-mangrove species (indicated by the red box, Supplementary figs.1-9). Based on accumulating illustrations from the fields of biology and technology, one can infer that evolutionary change need not always occur because of adaptation. Instead, change can occur because of exaptation, defined as “a feature, now useful to an

TE D

organism, which did not arise as an adaptation for its present role, but was subsequently co-opted for its current function” (Gould and Vrba, 1982). Plasticity of traits is a key feature of mangroves that allows them to acclimate to

EP

changing conditions. Vivipary, the precocious germination of seeds within the parent plant, is a specialized feature of evolutionary and biological importance that ensures the survival of several

AC C

mangrove species (Tomlinson and Cox, 2000). The trait reconstruction clearly shows that viviparous mangroves are mainly dominated by Rhizophoraceae members which include Ceriops, Rhizophora, Bruguiera and Kandelia candel (Supplementary fig.1 and 2). Sexual reproduction and regeneration events are annual in these plants and are dependent on local insects, tidal currents and nutrient content in the estuarine environment (Tomlinson, 1986). For the reproductive success of these viviparous mangroves, it is crucial that their seeds be adapted to survive the extreme environmental conditions in which they disperse and establish. The buoyant dispersal units (propagules) seem perfect exaptation for dispersal and establishment 8

ACCEPTED MANUSCRIPT

within the mangrove environment. However, interestingly N. fruticans is the only monocot species that has adapted to intertidal zones. It has also developed many adaptive traits (such as vivipary and floating fruits) to survive in high-saline and hypoxic habitats (He et al., 2015). Natural selection under different ecological environments would have driven the evolution of N.

RI PT

fruticans and its divergence from terraneous palms as evident in the phylogenetic tree.

The physiological trait, aerial root is linked to inundation tolerance cum exaptation in mangroves. The phylogenetic tree and the ancestral state reconstruction corroborate the multiple

SC

origin and parallel evolution of aerial roots such as stilt roots (Rhizophora), pneumatophores (Avicennia, Sonneratia), knee roots (Bruguiera), and cable roots (Xylocarpus, Heritiera), prompting much early speculation into their role in aerating sub-soil roots and soils

M AN U

(Supplementary figs. 3-6). Lenticels or gas exchange pores are prominent on these aerial root structures and stems. The differences in mangrove species in the structure, growth and physiology of roots, including their ability to transport and retain oxygen within their roots, are likely to lead to differences in species responses to changing inundation regimes and associated hydrological change with sea level rise (Kathiresan and Bingham, 2001). Mangroves interact with sediment deposits through their complex and diversified roots system that varies for

TE D

different mangrove species. Aerial roots are a common adaptation of mangrove trees to their saline environment, allowing root respiration despite the anaerobic substrate (Nardin et al., 2016). However, the presence of the aerial roots is also evident in non-mangrove species Crossostylis biflora, Trapa maximowczii and Lagerstroemia speciosa but we couldn’t see any

EP

sort of mechanical/external support by the roots to the plant (Fig. 2). Hence, we speculate that with the advent of time these aerial roots further evolved and apparently provide strong

AC C

mechanical support to the plant to stand erect in the muddy sediment, thus leading to exaptation of these traits.

Growth in saline environments necessitates adaptations to maintain the low tissue water

potentials needed to extract water from highly saline soils, and to limit the loss of extracted water from leaves. The ancestral state reconstruction of three important salt tolerant mechanisms of mangroves further demonstrates the multiple origin and parallel evolution (Supplementary figs.7-9). Mangrove species exclude the majority of salt ions during water absorption by the 9

ACCEPTED MANUSCRIPT

roots. Casparian bands and suberin lamellae provide barriers to apoplastic water flow through the root endodermis. The topology reveals the considerable difference in the root traits and salinity tolerance among mangrove species (Kathiresan et al., 2013). For example, Rhizophoraceae family members possess a large root cap, high levels of phenolic deposits in cells and rapid

RI PT

development of vasculature to prevent salts from entering xylem vessels through this pathway (Gill and Tomlinson, 1975), and hence show “salt exclusion” characteristics. In contrast, Avicennia marina has a smaller root cap and vascular development is delayed, which may allow greater salt and water uptake which leads to “salt excretion” through leaves. Interestingly,

SC

Lythraceae family members especially Sonneretia Spp. shows both salt exclusion and salt excretion type of salt tolerance as evident in the (Supplementary figs.7-9) Genetic distance

M AN U

3.2.

The lower level of variation in the genetic distance was observed between all the studied mangrove species based on the matK and rbcL gene. The K2P genetic distance ranged from 0.01 to 0.89 for the matK gene. The distance was much lower within same genus and family. For instance among the genera - Rhizophora, Sonneratia, Avicennia and Bruguiera - the least

TE D

distance was observed based on chloroplast genes. Whereas, for the rbcL gene, the difference was much lower ranging from 0.01 to 0.25 only. However, ITS locus showed the comparatively

0.508. 4. Discussion

EP

higher level of variation among mangrove species, the K2P value was in the range of 0.01 to

AC C

4.1. Phylogenetic analysis and character evolution Mangroves possess a complex suite of traits that are required for growth in intertidal environments and have fascinated physiologists for decades. The highly saline, tidally flooded environments of mangrove forests seem unlikely to support tree growth, yet mangroves are some of the most productive forests on the planet (Naskar and Mandal, 1999; Polidoro et al., 2010; Sahu et al., 2015). Our combined phylogeny of mangroves based on Bayesian inference (BI), Maximum Likelihood (ML) and Maximum Parsimony (MP) presented a well resolved phylogenetic pattern for mangroves and favours the polyphyletic origin of mangroves and its 10

ACCEPTED MANUSCRIPT

various morphological characters. Topologically two major clades were formed comprising six and five families respectively. All the clades were well resolved at family and genera level with strong bootstrap support values. From the tree (Fig. 2), it is evident that stilt root, vivipary, and salt exclusion are the most distinct feature among Rhizophoraceae members with the exception of

RI PT

Bruguiera sp. where knee roots are present. The genus Carallia was found to be the sister species of Rhizophora, Ceriops, Kandelia and Bruguiera. This is in accordance with the previous findings of Schwarzbach and Ricklefs (2000). It was also intriguing to see that the Rhizophora species of Atlantic East Pacific (AEP, new world) i.e. R. mangle and R. harrisonii clustered

SC

independently with respect to Indo-West Pacific (IWP, old world) mangrove taxa. It was also worth noting that Rhizophora samoensis, the only species found naturally in both regions was

M AN U

clustered with the new old Rhizophora mangroves indicating its possible dispersion from AEP to IWP (Duke et al., 2002). This is also congruent with the findings based on cpDNA and microsatellite analyses (Takayama et al., 2013). In addition to the presence of major disjunctions in Rhizophora species distributions, the extant populations are not morphologically uniform and continuous at the intraspecific level (Duke et al., 2002), partly due to persistent introgressive hybridization, for example, among the New World Rhizophora (Ceron-Souza et al., 2010). While

TE D

the reason for these disjunct occurrences might be complex, once created most discontinuities were persistent over millions of years – as evidenced by Wallace’s Line in the IWP region (Lo et al., 2014).

Exaptation: Aerial roots

EP

4.2.

Conquering the harsh saline marshes by mangrove plants has been through innovation of

AC C

special structures such as pneumatophores, salt glands and vivipary. But, the fact that already evolved features from sister taxa might have been co-adapted to suit the mangrove environment, cannot be ruled out. The present phylogenetic examination of mangrove plants and their closely related sister taxa provides excellent examples for exaptation. Here we postulate that aerial roots might have originally arisen in the context of selection for breathing and nutrients uptake in saline and flooded harsh estuarine habitat, and only later it was co-opted to provide strength and support to the mangroves (mainly in Rhizophora species). However, in the case of non-mangrove

11

ACCEPTED MANUSCRIPT

species, the aerial roots act as an adaptive feature only; it doesn’t provide any sort of strength and support to these plants. Among the various features mangrove plants have acquired to inhabit salt marshes, the

RI PT

following are prominent and essential: Aerial breathing roots (pneumatophores), supporting roots (stilt roots, buttresses, knee roots and cable roots), vivipary and salt exudation. Among these characters the ancestral characters among related taxa were traced. In the mangrove family Rhizophoraceae, true mangrove genera such as Rhizophora, Bruguiera, Ceriops and Kandelia

SC

which possess stilt roots are sister to non-mangrove species such as Crossostylis biflora. The red star in Fig. 2 indicates the presence of primary/similar morphological structure in non-mangrove taxa. Similarly, Crossostylis biflora a non-mangrove species occurring in evergreen forests has

M AN U

been also reported to develop abundant aerial roots at the base of the stem (Setoguchi et al., 2007). Within Lythraceae, genus Trapa comprises of floating aquatic plants. Trapa maximowczii is also known to have adapted to both wet and dry conditions (Choudhury, 2005). Lagerstroemia speciosa another sister species to Sonneratia species has been reported to exhibit locally spreading hairy root. These features such as aquatic habitat and spreading hairy aerial roots non-

TE D

mangrove taxa have led to adaptations in mangrove genera of Lythraceae (Haggett, 2001). Similarly, in family Meliaceae the presence of primary buttress roots has been observed in non-mangrove species Khaya senegalensis (Nikiema and Pasternak, 2008). These primary structures could be linked to the development of secondary buttress/aerial roots among the

EP

mangrove taxa Xylocarpus granatum and X. mekonensis. Among Sterculiaceae members Bombax ceiba and Adansonia digitata possess well-developed buttress roots to support their

AC C

massive trunks (Smith et al., 2004). This character has been adapted in sister genus to Heritiera as an adaptation to mangroves. Buttress roots have also been well developed in other mangrove associates (Manilkara littoralis and Terminalia catappa) and non-mangrove species of Sapotaceae family indicating the recruitment of buttress roots from non-mangrove species into mangrove species.

4.3. Exaptation: Vivipary Vivipary is the condition found in some species of mangroves in which the sexually produced embryo of the seed continues its development without dormancy into a seedling, while 12

ACCEPTED MANUSCRIPT

still attached to the mother plant (Elmqvist and Cox, 1996). Vivipary in mangroves was initially considered as an adaptive characteristic permitting avoidance of high salinity at germination (Henkel, 1979). Precocious germination, including vivipary and pseudovivipary, is rare in seed plants. However, the occurrence of terrestrial vivipary in Ardisia japonica (Hornsted) Blume

RI PT

(Myrsinaceae), a species growing in humid warm-temperate forests has been also reported (KunYuan et al., 2009). Aegiceras corniculatum (Myrsinaceae) also exhibits cryptovivipary similar to that of Ardisia (Myrsinaceae) providing clues that this feature might be a carried over feature in mangroves to fight salinity. Exaptation in vivipary also helps to ensure the viability of

SC

propagules even after detachment from the mother plant. Based on the previous literature we also postulate that the buoyant propagules and long-term seed coat impermeability enable the

M AN U

dispersion/drifting of the propagules to very long distances, and this putative protection could be considered as an exaptation to increase the effective dispersal period of the viviparous propagules (De Ryck et al., 2012).

Therefore, aerial roots and vivipary are the two characters which might have evolved through exaptation of related characters from evolutionary close relatives. The other features such as pneumatophores and salt exudation have been evolved multiple times, especially in

TE D

mangroves as evident by the ancestral state reconstruction (Supplementary figs. 1-9). 4.4. Multiple origins of key physiological traits

EP

Evolution of pneumatophores is an important adaptive feature of mangroves and several lineages have evolved this key character independently. Mangroves species of Avicennia (Acanthaceae), Sonneratia (Lythraceae) and Lumnitzera (Combretaceae) which have different

AC C

phylogenetic histories have evolved this structure repeatedly. Similarly supporting root systems have also evolved multiple times as reported by previous workers. Recently presence of stilt roots usually present in Rhizophoraceae has also been reported among Avicennia (Acanthaceae) species in Sundarbans Delta, West Bengal (Barik and Chowdhury, 2014). Thus, the phylogenetic analysis strongly supports the multiple origins of aerial roots in mangroves. Knee roots are mainly observed among Bruguiera, Ceriops (both Rhizophoraceae) and occasionally in Xylocarpus (Meliaceae) species indicating the multiple origins of these traits. 13

ACCEPTED MANUSCRIPT

But, interestingly knee roots have only been observed in mangrove species indicating the evolution of this structure only in true mangrove species. Similarly, the presence of distinct snake like (cable) roots has been witnessed only in Excoecaria agallocha signifying the single origin of this particular trait. Though of different phylogenetic origin, Xylocarpus and Heritiera

RI PT

species have evolved plank buttresses (modified flattened stilt roots that are joined to the stem to base, which extend away from the main trunk in a sinuous manner on soft, loose substrate to attain mechanical stability (Floyd, 1977).

Vivipary is the characteristic feature of Rhizophoraceae members namely Bruguiera,

SC

Kandelia, Rhizophora and Ceriops (Tomlinson, 1986) which are also clustered together in a single clade (Fig. 2). Vivipary has also been reported in Nypa fruticans (Arecaceae) (Tomlinson

M AN U

and Cox, 2000) which is a palm and distinctly related to the rest of the mangroves included in the study. Cryptovivipary has been comprehended in the phylogenetically diverse Avicennia sp. and Aegiceras corniculatum representing Acanthaceae and Myrsinaceae family respectively (Fig. 2). This further signifies the multiple origin of vivipary among mangroves. Depending on the salt eliminating mechanism mangroves and their associates have been classified into three groups: (1) salt excluders, (2) salt secretors (having salt glands) and (3) salt

TE D

accumulators. The salt-excluding mangrove species (e.g. Rhizophora spp., Ceriops spp., Bruguiera spp., Lumnitzera spp., Excoecaria spp.) eliminate excess salt by an ultrafiltration mechanism occurring at the root cell membranes of cortical cells (Wang et al., 2002). Salt secretors regulate internal salt levels by secreting excess salt through foliar glands and are

EP

represented by Acanthus spp., Avicennia marina, A. officinalis, A. alba, Aegiceras corniculatum and Aegialitis spp. (Aziz and Khan, 2001; Selvam, 2003). Salt accumulators accumulate high

AC C

concentration of salts in their cells and tissues and avoid salt damage by efficient sequestering of ions to the vacuoles in the leaf, translocation outside the leaf, possible cuticular transpiration and efficient leaf turnover to salt shedding (Tomlinson, 1986; Daru et al., 2013). Species of Lumnitzera and Excoecaria accumulate salts in leaf vacuoles and become succulent. From the phylogenetic tree (Fig. 2) the multiple origin of these salt tolerant mechanisms could be attributed and it further substantiates the hypothesis of Shi et al. (2005) where the study was carried out in salt secretion mechanism only.

14

ACCEPTED MANUSCRIPT

4.5. Efficacy of molecular markers in distinguishing mangrove taxa and DNA barcoding To date, traditional taxonomy relies mostly on diagnostic morphological characters and molecular tools are increasingly recognized for delineating species boundaries, quantifying

RI PT

diversity, and clarifying distributions in understudied groups especially mangroves (Yakovchuk et al., 2006; Sahu and Kathiresan, 2012). matK gene sequences were most conserved (310 bases out of 1037) followed by rbcL gene where 101 bases were found conserved out of 1097 bases. The nucleotide compositions of all the studied samples based on matK, rbcL and ITS sequences

SC

revealed that chloroplast genes retained the higher content of A+T, whereas ITS had a higher content of G+C. DNA with high GC-content is more stable than DNA with low GC-content (Chase et al., 2005).

M AN U

The lower level of variation in the genetic distance was observed between all the studied mangrove species based on matK and rbcL (chloroplast gene). This could be attributed to highly conserved nature of these genes. ITS locus showed comparatively higher level of variation among mangrove species, the K2P value was in the range of 0.01 to 0.508. Pillon et al. (2013) have favoured the use of nuclear ribosomal Internal Transcribed Spacers (nrITS) in conjunction with one or two plastid regions. The use of two regions, one from the nuclear and one from the

TE D

plastid genome, allows for the detection of genetic differences inherited from both parents, as the plastid genome is usually maternally inherited (Sahu et al., 2015). DNA barcoding of land plants has relied traditionally on a small number of markers from

EP

the plastid genome. In contrast, low-copy nuclear genes have received little attention as DNA barcodes because of the absence of universal primers for PCR amplification (Costion, 2011). The

AC C

present study performed a comparative assessment of the discriminative powers of two chloroplast genes and one nuclear gene for the authentication of mangroves and associated plant species. The rbcL locus was the easiest to sequence and align but showed too little variation to enable identifying all species tested. These results are in line with recent reports on barcoding efforts in plants (Hollingsworth et al., 2009). Although rbcL and matK are the two recommended DNA barcodes that can resolve 72% of land plants when used in combination (Li et al., 2011). However, in the present study, matK and rbcL provided the lower intraspecific and interspecific divergences. It was also found that 15

ACCEPTED MANUSCRIPT

matK was the least divergent locus among three DNA barcode candidates for differentiating species in mangroves. But, the chloroplast gene was proficient enough to differentiate genera. However despite the modest lengths of the nuclear locus (ITS), it was found highly variable relative to plastid genes. The greater variability of nuclear loci and many other differences with

RI PT

plastid genes can be explained by the greater coalescence times of nuclear genes compared to organelle genes (Sass et al., 2007). Nevertheless, the higher percentage of variable sites in these genes compared to plastid genes allowed differentiation of closely related species (Rhizophora, Sonneratia and Avicennia). Contrary to the published problems encountered with the nrITS

SC

region (variation and alignment difficulties) by Sass et al. (2007), the present study is in agreement with Crockett et al. (2007) that the ITS is an effective region for identification of plant

M AN U

species. This region was readily amplified and the published DNA sequences aligned for all of the Hypericum species tested, and are a suitable target for the design of DNA-based assays. In a recent review of the most optimal barcode for plants, Hollingsworth et al. (2011) indicate that none of the barcodes proposed is perfect in every respect and that matK still needs optimization of primer combinations, probably to be adapted to specific taxonomic groups. This hypothesis was very much applicable in the present study where the combination of matK and

TE D

rbcL suggested by the CBOL plant workgroup doesn’t work well (CBOL Plant Working group et al., 2009). However, the combined phylogenetic analysis based on chloroplast (matK and rbcL) and nuclear (ITS) locus revealed a better resolution to differentiate and identify the closely related mangrove species. Intriguingly, the ITS locus showed more substantial results than

EP

chloroplast markers which is in accordance with Chen et al. (2010) who proposed the ITS2

AC C

sequence of the nrITS region as a barcode for Chinese Medicinal Plants. 5. Conclusions

This study revealed the multiple origin of mangroves and shed light on the ancestral characters that might have led certain lineages of plants to adapt to estuarine conditions, and also traces the evolutionary history of mangroves and hitherto unexplained theory that mangroves traits namely aerial roots and vivipary evolved as a result of exaptation rather than adaptation to saline habitats. The combined phylogeny of mangroves based on Bayesian inference (BI), Maximum Likelihood (ML) and Maximum Parsimony (MP) presented a well resolved 16

ACCEPTED MANUSCRIPT

phylogenetic pattern for mangroves and favours the polyphyletic origin of mangroves and its various morphological characters. We postulate that the aerial roots and viviparous propagules are the two traits which might have evolved through exaptation of related characters from evolutionary close relatives. The other features such as pneumatophores and salt exudation

RI PT

mechanism have been evolved multiple times in mangroves. The lower level of variation in the genetic distance was observed between all the studied mangrove species based on matK and rbcL (chloroplast gene). However, the combined phylogenetic analysis based on chloroplast (matK and rbcL) and nuclear (ITS) locus revealed a better resolution to differentiate and identify the

SC

closely related mangrove species. In future, the inclusion of more number of molecular markers and design of species-specific primers may enable to obtain more resolved phylogenetic trees

M AN U

and will shed more light on the evolution of mangrove traits. Acknowledgements

Authors are thankful to the authorities of Annamalai University for providing necessary facilities to carry out this work, and Department of Science and Technology, Govt. of India, New Delhi for providing INSPIRE fellowship to Sunil Kumar Sahu (Grant number: DST/INSPIRE

TE D

Fellowship/2010/220). Authors also acknowledge Dr. M. Thangaraj for extending Lab facilities; Dr. P. Karanth and Dr. S. Siddharthan for their valuable help in phylogenetic analyses. We express our gratitude to Dr. P. Ragavan for his kind assistance in Mangrove sampling in Andaman & Nicobar Islands. We also thank Prof. Shi Suhua and Dr. Ziwen He for their prompt

EP

help in the analysis of ancestral rate reconstruction. We thank the anonymous reviewers and

AC C

editor for their valuable and useful comments on an earlier version of the manuscript.

References

Alongi, D.M., 2008. Mangrove forests: resilience, protection from tsunamis, and responses to global climate change. Estuarine Coastal and Shelf Science 76, 1-13.

Anderson, J.T., Willis, J.H., Mitchell–Olds, T., 2011. Evolutionary genetics of plant adaptation. Trends in Genetics 27, 258–266. Arnold, E.N., 1994. Investigating the origins of performance advantage: adaptation, exaptation and lineage effects. Phylogenetics and ecology. Academic Press, London, pp. 123-168. 17

ACCEPTED MANUSCRIPT

Aziz, I., Khan, M.A., 2001. Effect of seawater on the growth, ion content and water potential of Rhizophora mucronata Lam. Journal of Plant Research 114, 369–373. Banerjee, L.K., Sastry, A.R.K., Nayar, M.P., 1989. Mangroves of India: Identification Manual. Botanical Survey of India, Calcutta.

Eastern India. Check List 10, 329–334.

RI PT

Barik, J., Chowdhury, S., 2014. True Mangrove Species of Sundarbans Delta, West Bengal,

Barve, A.,Wagner, A., 2013. A latent capacity for evolutionary innovation through exaptation in metabolic systems. Nature 500, 203–206.

SC

Blom, C.W.P.M., 1999. Adaptations to flooding stress: from plant community to molecule. Plant Biology 1, 261–273.

M AN U

Brancalion, F., Marcos, P.H.S., Ana, D.L., Novembre, C., Ricardo, R.R., 2010. Dormancy as exaptation to protect mimetic seeds against deterioration before dispersal. Annals of Botany 105, 991–998.

Ceron-Souza, I., Rivera-Ocasio, E., Medina, E., Jimenez, J.A., McMillan, W.O., Bermingham, E., 2010. Hybridization and introgression in New World red mangroves, Rhizophora (Rhizophoraceae). American Journal of Botany 97, 945-957.

TE D

Chase, M.W., Salamin, N., Wilkinson, M., Dunwell, J.M., Kesanakurthi, R.P., Haidar, N. and Savolainen, V., 2005. Land plants and DNA barcodes: short-term and long-term goals. Philosophical Transactions of the Royal Society B: Biological Sciences 360, 1889–1895. Chen, S., Yao, H., Han, J., Liu, C., Song, J., Shi, L., Zhu, Y., Ma, X., Gao, T., Pang, X. and Luo,

EP

K., 2010. Validation of the ITS2 region as a novel DNA barcode for identifying medicinal plant species. PloS one 5, e8613.

AC C

Choudhury, J.K., Faisal, A.M., Irfanullah, H.M., Ahmed, R., Nishat, A., 2005. Plant resources of Haors and floodplains: an overview. IUCN–The World Conservation Union, Bangladesh Country Office.

Colmer, T.D., 2003. Long–distance transport of gases in plants: a perspective on internal aeration and radial oxygen loss from roots. Plant Cell and Environment 26, 17–36.

Costion, C., Ford, A., Cross, H., Crayn, D., Harrington, M., Lowe, A., 2011. Plant DNA barcodes can accurately estimate species richness in poorly known floras. PloS one 6, e26841. 18

ACCEPTED MANUSCRIPT

Crockett, S.L., Demirci, B., Başer, K.H.C., Khan, I.A., 2007. Analysis of the volatile constituents of five African and Mediterranean Hypericum L. (Clusiaceae, Hypericoideae) species. Journal of Essential Oil Research 19, 302–306. Daru, B.H., Yessoufou, K., Mankga, L.T., Davies, T.J., 2013. A global trend towards the loss of

RI PT

evolutionarily unique species in mangrove ecosystems. PloS one 8, e66686.

Darwin, C., 1877. The different forms of flowers on plants of the same species John Murray. Arnold EN (1994) Investigating the origins of performance advantage: adaptation, exaptation and lineage effects. Phylogenetics and ecology. Academic Press, London, pp.

SC

123-168.

De Ryck, D.J., Robert, E.M., Schmitz, N., Van der Stocken, T., Di Nitto, D., Dahdouh–Guebas,

M AN U

F., Koedam, N., 2012. Size does matter, but not only size: Two alternative dispersal strategies for viviparous mangrove propagules. Aquatic Botany 103, 66–73. Duke, N., 2006. Australia’s Mangroves–The Authoritative Guide to Australia's Mangrove Plants. University of Queensland, 200pp.

Duke, N.C., Lo, E.Y.Y., Sun, M., 2002. Global distribution and genetic discontinuities of mangroves - emerging patterns in the evolution of Rhizophora. Trees Structure and

TE D

Functions 16, 65-79.

Edgar, R.C., 2004. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Research 32, 1792–1797. Elmqvist, T., Cox, P.A., 1996. The evolution of vivipary in flowering plants. Oikos 3–9.

EP

Ferrada, E., Wagner, A.A., 2012. Comparison of genotype–phenotype maps for RNA and proteins. Biophysics Journal 102, 1916–1925.

AC C

FitzJohn, R.G., 2012. Diversitree: comparative phylogenetic analyses of diversification in R. Methods in Ecology and Evolution 3, 1084-1092.

Floyd, A.G., 1977. Ecology of the tidal forests in the Kikori–Romilly Sound area, Gulf of Papua. Office of Forests, Division of Botany, Ecology Report No. 4, 1–59.

Gill, A.M., Tomlinson, P.B., 1975. Aerial roots: an array of forms and functions. In: Torrey, J.G., Clarkson, D.T., (Eds.), The Development and Function of Roots. 3. Cabot Symposium Academic Press, London. Gould, S.J., Vrba, E.S., 1982. Exaptation: a missing term in the science of form. Paleobiology 8, 4–15. 19

ACCEPTED MANUSCRIPT

Haggett, P., (Ed) 2001. Encyclopedia of World Geography (Vol. 24). Marshall Cavendish. Hall, T.A., 1999. BioEdit: a user–friendly biological sequence alignment editor and analysis program for Windows 95/98/ NT. Nucleic Acids Symposium Series 41, 95–98. He, Z., Zhang, Z., Guo, W., Zhang, Y., Zhou, R., Shi, S., 2015. De Novo Assembly of Coding

RI PT

Sequences of the Mangrove Palm (Nypa fruticans) Using RNA-Seq and Discovery of Whole-Genome Duplications in the Ancestor of Palms. PloS one 10, e0145385.

Henkel, P.A., 1979. The concept of vivipary in the plant world. Zh Obshch Biology 40, 60–66. Group, C.P.W., Hollingsworth, P.M., Forrest, L.L., Spouge, J.L., Hajibabaei, M., Ratnasingham,

SC

S., van der Bank, M., Chase, M.W., Cowan, R.S., Erickson, D.L. and Fazekas, A.J., 2009. A DNA barcode for land plants. Proceedings of the National Academy of Sciences

M AN U

106,12794–12797.

Hollingsworth, P.M., Graham, S.W., Little, D.P., 2011. Choosing and using a plant DNA barcode. PloS one 6, e19254.

Huelsenbeck, J.P., Ronquist, F., 2001. MrBAYES: Bayesian inference of phylogenetic trees. Bioinformatics 17, 754–755.

Kathiresan, K., Bingham, B.L., 2001. Biology of mangroves and mangroves ecosystems.

TE D

Advances in Marine Biology 40, 84–251.

Kathiresan, K., Moorthy, P., Rajendran, N., 2013. Mangroves and its associate’s diversity. In Mangroves of India – Their Biology and Uses. JR Bhatt et al. (eds). Zoological Survey of India, Prani Vigyan Bhawan, M–Block, New Alipore, Kolkata 700 053. 2013. XIV, 640

EP

pp.

Keys, D.N., Lewis, D.L., Selegue, J.E., Pearson, B.J., Goodrich, L.V., Johnson, R.L., Gates, J.,

AC C

Scott, M.P. and Carroll, S.B., 1999. Recruitment of a hedgehog regulatory circuit in butterfly eyespot evolution. Science 283, 532–534.

Kimura, M., 1980. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. Journal of molecular evolution 16, 111–120.

Kishino, H., Hasegawa, M., 1989. Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in Hominoidea. Journal of Molecular Evolution 29, 170–179. 20

ACCEPTED MANUSCRIPT

KunYuan, H., PeiHua, J., ChingChu, T., ChouHsuan, H., HsinHui, W., 2009. Precocious germination in Ardisia japonica (Myrsinaceae). J Exp Forest of National Taiwan University 23, 329–335. Li, D.Z., Liu, J.Q., Chen, Z.D., Wang, H., Ge, X.J., Zhou, S.L., Gao, L.M., Fu, C.X., CHEN,

RI PT

S.L., 2011. Plant DNA barcoding in China. Journal of Systematics and Evolution 49,165– 168.

Li, S., Pearl, D.K., Doss, H., 2000. Phylogenetic tree construction using Markov chain Monte Carlo. Journal of American Statistical Association 95, 493–508.

N.C., Mei, S., 2014. Phylogeographic pattern of Rhizophora

SC

Lo, E.Y.Y., Duke,

(Rhizophoraceae) reveals the importance of both vicariance and long-distance oceanic

M AN U

dispersal to modern mangrove distribution. BMC Evolutionary Biology 14, 83. Meher–Homji, V.M., 1988. The Pichavaram mangroves. Blackbuck 4, 1–12. Nardin, W., Woodcock, C.E., Fagherazzi, S., 2016. Bottom sediments affect Sonneratia mangrove forests in the prograding Mekong delta, Vietnam. Estuarine Coastal and Shelf Science 177, 60-70.

Naskar, K., Mandal, R., 1999. Ecology and Biodiversity of Indian mangroves. Daya Publishing

TE D

House, New Delhi.

Nikiema, A., Pasternak, D., 2008. Khaya senegalensis (Desr.) A. Juss. Plant resources of tropical Africa. PROTA Foundation 7, 339–344.

Pievani, T., Serrelli, E., 2011. Exaptation in human evolution: how to test adaptive vs exaptive

EP

evolutionary hypotheses. Journal of Anthropological Sciences 89, 9–23. Pillon, Y., Johansen, J., Sakishima, T., Chamala, S., Barbazuk, W.B., Roalson, E.H., Price, D.K.,

AC C

Stacy, E.A., 2013. Potential use of low–copy nuclear genes in DNA barcoding: a comparison with plastid genes in two Hawaiian plant radiations. BMC Evolutionary Biology 13, 1–35.

Polidoro, B.A., Carpenter, K.E., Collins, L., Duke, N.C., Ellison, A.M., Ellison, J.C., Farnsworth, E.J., Fernando, E.S., Kathiresan, K., Koedam, N.E., Livingstone, S.R., 2010. The loss of species: mangrove extinction risk and geographic areas of global concern. PLoS ONE 5, e10095. Posada, D., Crandall, K.A., 1998. Modeltest: testing the model of DNA substitution; Bioinformation 14, 817–818. 21

ACCEPTED MANUSCRIPT

Rambaut, A., Drummond, A.J., 2007. Tracer v1. 4. Rannala, B., Yang, Z., 1996. Probability distribution of molecular evolutinary trees: a new method of phylogenetic inference. Journal of molecular evolution 43, 304–311. Ronquist, F., Teslenko, M., van der Mark, P., Ayres, D.L., Darling, A., Höhna, S., Larget, B.,

RI PT

Liu, L., Suchard, M.A., Huelsenbeck, J.P., 2012. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. System Biology 61, 539–542.

Sahu, S.K., Kathiresan, K., 2012. Molecular Markers: An intricate tool for new insights in

SC

mangrove genetics. International Journal of Advanced Biotechnology and Research 3, 847-863.

M AN U

Sahu, S.K., Singh, R., Kathiresan, K., 2015. Deciphering the taxonomical controversies of Rhizophora hybrids using AFLP, plastid and nuclear markers. Aquatic Botany 125, 4856.

Sahu, S.K., Thangaraj, M., Kathiresan, K., 2012. DNA extraction protocol for plants with high levels of secondary metabolites and polysaccharides without using liquid nitrogen and phenol. ISRN Molecular Biology 2012, 1–6.

TE D

Samal, A., Matias Rodrigues, J.F., Jost, J., Martin, O.C., Wagner, A., 2010. Genotype networks in metabolic reaction spaces. BMC System Biology 4, 1– 30. Sass, C., Little, D.P., Stevenson, D.W., Specht, C.D., 2007. DNA barcoding in the cycadales: testing the potential of proposed barcoding markers for species identification of cycads.

EP

PloS one 2, e1154.

Schwarzbach, A.E., Ricklefs, R,E., 2000. Systematic affinities of Rhizophoraceae and

AC C

Anisophylleaceae, and intergeneric relationships within Rhizophoraceae, based on chloroplast DNA, nuclear ribosomal DNA, and morphology. American Journal of Botany 87, 547-564.

Selvam, V., 2003. Environmental classification of mangrove wetlands of India. Current Science 84, 757–765.

Setoguchi, H., Ohba, H., Tobe, H., 2007. Evolution in Crossostylis (Rhizophoraceae) on the South Pacific Islands. Evolution and Speciation of Island Plants 203 pp.

22

ACCEPTED MANUSCRIPT

Shi, S., Huang, Y., Zeng, K., Tan, F., He, H., Huang, J., Fu, Y., 2005. Molecular phylogenetic analysis of mangroves: independent evolutionary origins of vivipary and salt secretion. Molecular Phylogenetics and Evoluion 40, 298–304. Silvestro, D., Michalak, I., 2011. RaxmlGUI: a graphical front–end for RAxML. Organisms

RI PT

Diversity and Evolution 12, 335–337.

Smith, N., Mori, S., Henderson, A., Stevenson, D., Heal, D.S., editors 2004. Flowering Plants of the Neotropics. Princeton University Press. Spalding, M., 2010. World atlas of mangroves. Routledge.

SC

Swofford, D.L., 2002. PAUP Phylogenetic analysis using parsimony. Version 4. Sunderland, MA: Sinauer Associates.

M AN U

Takayama. K., Tamura, M., Tateishi, Y., Webb, E.L., Kajita, T., 2013. Strong genetic structure over the American continents and transoceanic dispersal in the mangrove genus Rhizophora (Rhizophoraceae) revealed by broad-scale nuclear and chloroplast DNA analysis. American Journal of Botany 100, 1191-1201.

Tomarev, S.I., Piatigorsky, J., 1996. Lens crystallins of invertebrates. Diversity and recruitment from detoxification enzymes andnovel proteins. European Journal of Biochemistry 235,

TE D

449–465.

Tomlinson, P.B., 1986. The Botany of Mangroves. Cambridge University Press, Cambridge. Tomlinson, P.B., Cox, P.A., 2000. Systematic and functional anatomy of seedlings in mangrove Rhizophoraceae: vivipary explained? Botanical Journal of Linnaean Society 134, 215–

EP

231.

Troll, W., Dragendorff, O., 1931. Ueber die Luftwurzeln von Sonneratia L. und ihre biologische

AC C

Bedeutung. Planta 13, 311–473. True, J.R., Carroll, S.B., 2002. Gene co–option in physiological and morphological evolution. Annual Reviews on Cell and Developmental Biology 18, 53–80.

True, J.R., Edwards, K.A., Yamamoto, D., Carroll, S.B., 1999. Drosophila wing melanin patterns form by vein-dependent elaboration of enzymatic prepatterns. Current Biology 9, 13821391. Voesenek, L., Rijnders, J., Peeters, A.J.M., VandeSteeg, H.M.V., DeKroon, H., 2004. Plant hormones regulate fast shoot elongation under water: from genes to communities. Ecology 85, 16–27. 23

ACCEPTED MANUSCRIPT

Wang, W.Q., Ke, L., Tam, N.F.Y., Wong, Y.S., 2002. Changes in the main osmotica during the development of Kandelia candel hypocotyls and after mature hypocotyls were transplanted in solutions with different salinities. Marine Biology 141, 1029–1034. White, T.J., Bruns, T., Lee, S.J.W.T., Taylor, J.W., 1990. Amplification and direct sequencing of

applications 18, 315-322.

RI PT

fungal ribosomal RNA genes for phylogenetics. PCR protocols: a guide to methods and

Wicke, S., Quandt, D., 2009. Universal primers for amplification of the trnK/matK region in land plants. Anales del Jardín Botánico de Madrid 66, 285–288.

SC

Yakovchuk, P., Protozanova, E., Frank–Kamenetskii, M.D., 2006. Base–stacking and base– pairing contributions into thermal stability of the DNA double helix. Nucleic Acids

M AN U

Research 34, 564–574.

Zheng, W.J., Wang, W.Q., Lin, P., 1999. Dynamics of elemental contents during the development of hypocotyls and leaves of certain mangrove species. Journal of

AC C

EP

TE D

Experimental Marine Biology and Ecology 233, 247–257.

24

ACCEPTED MANUSCRIPT

Legends Fig. 1. Map showing the mangrove sampling sites

M AN U

SC

RI PT

Fig. 2. Maximum likelihood (ML) tree of mangrove and non-mangrove species constructed by using Bayesian inference (BI) with the combined data set of rbcL, matK and ITS regions. Characters of aerial roots vivipary and salt tolerance mechanisms are mapped on to the tree. Numbers near branches represent the bootstrap supports: Bayesian posterior probability (Black), RaxML maximum likelihood (red) and Parsimony bootstrap in MEGA analysis (blue) respectively. ( -Stilt root; -Buttress root; - Knee root; -Pneumatophores; V-Vivipary; CV-Crypto vivipary; SE-Salt exclusion; SG-Salt excretion/salt gland; SA-Salt accumulation. The red star indicates the presence of primary/similar morphological structure in non-mangrove taxa. Names in red font represent mangroves whereas blue colored represents non-mangrove species. Table 1. Accession details of mangroves and non-mangroves species used in the study Table 2. List of primers used for amplification of target regions

Table 3. Multiple origin analysis of mangrove physiological traits by likelihood-based Shimodaira-Hasegawa (SH) test

TE D

Supplementary Fig 1. Ancestral state reconstruction of “Vivipary” in the maximum likelihood (ML) tree of mangroves based on the combined data set of rbcL, matK and ITS regions. Red and black color boxes represent the presence and absence of characters respectively.

EP

Supplementary Fig 2. Ancestral state reconstruction of “cryptovivipary” in the maximum likelihood (ML) tree of mangroves based on the combined data set of rbcL, matK and ITS regions. Red and black color boxes represent the presence and absence of characters respectively.

AC C

Supplementary Fig 3. Ancestral state reconstruction of “stilt roots” in the maximum likelihood (ML) tree of mangroves based on the combined data set of rbcL, matK and ITS regions. Red and black color boxes represent the presence and absence of characters respectively. Supplementary Fig 4. Ancestral state reconstruction of “buttress roots” in the maximum likelihood (ML) tree of mangroves based on the combined data set of rbcL, matK and ITS regions. Red and black color boxes represent the presence and absence of characters respectively. Supplementary Fig 5. Ancestral state reconstruction of “Knee roots” in the maximum likelihood (ML) tree of mangroves based on the combined data set of rbcL, matK and ITS 25

ACCEPTED MANUSCRIPT

regions. Red and black color boxes represent the presence and absence of characters respectively.

RI PT

Supplementary Fig 6. Ancestral state reconstruction of “Pneumatophores” in the maximum likelihood (ML) tree of mangroves based on the combined data set of rbcL, matK and ITS regions. Red and black color boxes represent the presence and absence of characters respectively.

SC

Supplementary Fig 7. Ancestral state reconstruction of “salt exclusion” in the maximum likelihood (ML) tree of mangroves based on the combined data set of rbcL, matK and ITS regions. Red and black color boxes represent the presence and absence of characters respectively.

M AN U

Supplementary Fig 8. Ancestral state reconstruction of “salt excretion” in the maximum likelihood (ML) tree of mangroves based on the combined data set of rbcL, matK and ITS regions. Red and black color boxes represent the presence and absence of characters respectively.

AC C

EP

TE D

Supplementary Fig 9. Ancestral state reconstruction of “salt accumulation” in the maximum likelihood (ML) tree of mangroves based on the combined data set of rbcL, matK and ITS regions. Red and black color boxes represent the presence and absence of characters respectively.

26

TE D

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

AC C

EP

Fig. 1. Map showing the mangrove sampling sites

27

AC C

EP

TE D

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

28

AC C

EP

TE D

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

29

EP

TE D

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

AC C

Fig. 2. Maximum likelihood (ML) tree of mangrove and non-mangrove species constructed by using Bayesian inference (BI) with the combined data set of rbcL, matK and ITS regions. Characters of aerial roots vivipary and salt tolerance mechanisms are mapped on to the tree. Numbers near branches represent the bootstrap supports: Bayesian posterior probability (Black), RaxML maximum likelihood (red) and Parsimony bootstrap in MEGA analysis (blue) respectively. ( -Stilt root; -Buttress root; - Knee root; -Pneumatophores; V-Vivipary; CV-Crypto vivipary; SE-Salt exclusion; SG-Salt excretion/salt gland; SA-Salt accumulation. The red star indicates the presence of primary/similar morphological structure in non-mangrove taxa. Names in red font represent mangroves whereas blue colored represents non-mangrove species. 30

ACCEPTED MANUSCRIPT

Table 1. Accession details of mangroves and non-mangroves species used in the study

AC C

EP

TE D

Rhizophoraceae

Euphorbiaceae

RI PT

Genbank Accession number rbcL matK ITS KJ784621 NA KJ784549 HM849737 HE967332 NA GU135172 GU135009 NA L12592 HQ384511 AF169756 KJ784624 KJ784590 KJ784551 AY008829 JQ589417 EF540989 U28868 JQ589991 EF540990 KJ784625 KJ784591 KJ784552 KJ784626 KJ784592 KJ784553 KF890169 KF890175 NA HQ384878 HQ384512 AF169850 JQ590086 AB649971 NA KJ784627 KJ784593 KJ784554 AF127695 NA NA KJ784628 KJ784594 KJ784555 NA NA EU000399 KJ784629 KJ784595 KJ784556 NA NA HM366121 NA AF105091 AF006757 AF105086 AF130320 AF127372 AF329467 AF105079 AF127679 NA AF130323 AF127681 NA AF130325 AF127680 NA AF130324 KJ784643 KJ784609 KJ784546 KJ784644 KJ784610 KJ784544 AB668367 NA NA KJ784645 KJ784611 KJ784548 AB668356 JX661962 KJ194270 KJ784646 KJ784612 KJ784545 AB668365 NA HQ337960 AB668368 NA HQ337959 KJ784647 KJ784613 KJ784547 KJ784632 KJ784598 KJ784557 KJ784633 KJ784599 KJ784558 NA NA EF119069 KJ784637 KJ784603 KJ784561 JQ952128 JQ951977 AF537468

SC

Species Acanthus ilicifolius Acanthus mollis Asystasia gangetica Acanthus montanus Avicennia alba Avicennia bicolor Avicennia germinans Avicennia marina Avicennia officinalis Barleria cuspidata Thunbergia alata Thunbergia grandiflora Bruguiera cylindrica Bruguiera exaristata Bruguiera gymnorrhiza Bruguiera hainesii Bruguiera parviflora Bruguiera rhynchopetala Bruguiera sexangula Carallia brachiata Carallia pectinifolia Crossostylis biflora Pellacalyx axillaris Pellacalyx saccardians Rhizophora annamalayana Rhizophora apiculata Rhizophora harrisonii Rhizophora lamarckii Rhizophora mangle Rhizophora mucronata Rhizophora racemosa Rhizophora samoensis Rhizophora stylosa Ceriops decandra Ceriops tagal Ceriops zippeliana Kandelia candel Euphorbia alluaudii

M AN U

Family Acanthaceae

31

ACCEPTED MANUSCRIPT

KJ784601 JX518133

KJ784559 NA

AB233885 GU441782 NA AB267957 AB267961 AF421496 AY036138 AY036142 L10226 KJ784649 KJ784650 KJ784651 NA NA KJ784652 JX856722 AY036149 JQ592418 NA KJ784638 KJ784639 KC158546 NA U26338 AF425712 AY128234 KJ784653 KJ784654 JX982144 AB925375 KJ735966 JQ626164 AY082357 AB925312 KJ784636 AY328191 AY328192 JQ594220 JQ625993

AB233781 GU441800 NA AB268061 AB268065 HQ593354 NA NA NA KJ784615 KJ784616 KJ784617 NA NA KJ784618 NA NA JQ588161 NA KJ784604 KJ784605 KC130323 NA GU135057 GU135121 EF489117 KJ784619 KJ784620 JX982143 AB924764 EF489115 KC627567 NA AB924701 KJ784602 NA NA GQ982103 JQ626433

GU441816 GU441822 JN250092 JN250093 GQ396671 AF334772 KJ784566 AY035757 FM887019 KJ784567 KJ784568 KJ784565 AY680948 AY680909 KJ784569 JX856469 AF420218 AY910705 AF425685 KJ784562 KJ784563 JX840569 AY050562 JX856522 JX856525 AY695595 KJ784570 KJ784571 JX982145 FJ518898 KJ784572 NA NA NA KJ784560 AF460186 AY083657 NA NA

SC

RI PT

KJ784635 JX572593

AC C

Meliaceae

EP

Combretacea

TE D

M AN U

Lythraceae

Excoecaria agallocha Excoecaria bussei Excoecaria cochinchinensis Excoecaria formosana Gymnanthes albicans Homalanthus nutans Triadica sebifera Lythrum salicaria Pemphis acidula Trapa maximowiczii Trapa natans Sonneratia alba Sonneratia apetala Sonneratia caseolaris Sonneratia gulngai Sonneratia hainanensis Sonneratia ovata Lagerstroemia hirsuta Lagerstroemia speciosa Cuphea carthagenensis Laguncularia racemosa Lumnitzera littorea Lumnitzera racemosa Combretum apiculatum Conocarpus erectus Terminalia catappa Terminalia muelleri Melia azedarach Xylocarpus granatum Xylocarpus mekongensis Dysoxylum binectariferum Khaya senegalensis Azadirachta indica Carapa procera Heritiera angustata Heritiera javanica Heritiera littoralis Firmiana major Firmiana platanifolia Sterculia apetala Sterculia pruriens

Sterculiaceae

32

ACCEPTED MANUSCRIPT

AY083663 NA AJ277463 JN400317 HQ658377 EF436999 KJ784550 AY275090 FJ037872 NA FJ037874 KJ784564 JX856474

KJ784614 JF954664 AM412468 KJ784600 KJ784607 FJ514757 JX903671 KJ784608

NA JF977113 JN115026 KJ161167 NA NA NA NA

RI PT

NA JX495761 NA AY321168 JX495673 HM850731 KJ784589 DQ378429 FJ514757 JQ589181 JQ626390 KJ784606 GU135011

SC

AY082361 GU981722 AY082351 AY328180 JN114787 HM849771 KJ784623 KF602221 JQ626263 JQ594068 JQ625936 KJ784640 EU980807 KJ784648 JF942573 HM164167 KJ784634 KJ784641 AM110194 AY012468 KJ784642

AC C

EP

TE D

M AN U

Scaphium lychnophorum Brachychiton acerifolius Brachychiton populneus Adansonia digitata Bombax ceiba Primulaceae Anagallis foemina Aegiceras corniculatum Androsace chamaejasme Sapotaceae Manilkara bidentata Manilkara chicle Manilkara huberi Manilkara littoralis Manilkara zapota Scyphiphora Rubiaceae hydrophyllacea Mussaenda macrophylla Ixora coccinea Bignoniaceae Dolichandrone spathacea Arecaceae Nypa fruticans Phoenix canariensis Phoenix dactylifera Phoenix paludosa *NA: Sequence not available

33

ACCEPTED MANUSCRIPT

Table 2. List of primers used for amplification of target genes S. No. Primer Name Primer sequence rbcL-F

5’- TGTCACCAAAAACAGAGACT - 3’

2

rbcL-R

5’ - TTCCATACTTCACAAGCAGC - 3’

3

matK-F

5’- GGGTTGCTAACTCAATGGTAGAG - 3’

4

matK-R

5’ - TGGGTTGCCCGGGGCCGAAC - 3’

5

ITS-4

5’ - TCCTCCGCTTATTGATATGC - 3’

6

ITS-5

5’ - GGAAGGAGAAGTCGTAACAAGG -3’

SC

RI PT

1

M AN U

Table 3 Multiple origin analysis of mangrove physiological traits by likelihood-based Shimodaira-Hasegawa (SH) test

-ln L

Diff -ln L

Best tree

54937.75308

(best)

Buttress root

56378.34538

1440.592 0.000*

Stilt root

56950.59672

2012.844 0.000*

Pneumatophores

56129.07789

1191.325 0.000*

Viviparous

55865.77155

928.0185 0.000*

Crypto viviparous

55450.998

513.2449 0.000*

Salt exclusion

57401.18801

2463.435 0.000*

Salt excretion

57043.27861

2105.526 0.000*

Salt accumulation

57401.18801

2463.435 0.000*

AC C

EP

TE D

Tree

P

34

ACCEPTED MANUSCRIPT

Highlights

Multi-gene markers deciphered the multiple origin of mangrove physiological traits We hypothesize that aerial roots and vivipary are evolved as a result of exaptation

AC C

EP

TE D

M AN U

SC

RI PT

Combination of rbcL, matK and ITS is proposed to identify mangroves at species level