Phylogeny and phylogeography of Porites & Siderastrea

Phylogeny and Phylogeography of Porites & Siderastrea (Scleractinia: Cnidaria) Species in The Caribbean and Eastern Pacific; Based on The Nuclear Ribosomal ITS Region

--------------------------------------------- A Dissertation

Presented to

The Faculty of the Department of Biology and Biochemistry

University of Houston

---------------------------------------------

In Partial Fulfillment

Of the Requirements for the Degree

Doctor of Philosophy

---------------------------------------------

by

Zac Forsman

May 2003

ii


____________________________________ Zac H. Forsman

APPROVED:

____________________________________ Dr. Gerard M. Wellington, Chairman

____________________________________ Dr. George E. Fox, Co-Chairman

____________________________________ Dr. Michael Travisano

____________________________________ Dr. Stuart Hall

____________________________________ Dr. Ove Hoegh-Guldberg

____________________________________ Dean, College of Natural Sciences and Mathematics

iii

ACKNOWLEDGEMENTS

This work would not have been possible if it were not for an enormous network of

people, who have helped me in so many ways. I would like to thank my lovely wife Li

Zhang Forsman, for all of her love and support. I would like to thank my advisors Dr.

G. Wellington and Dr. G. Fox for their support and commitment of time and resources.

The following people have contributed samples from far across the globe without asking

anything in return: G. Wellington, M. Takabayashi, E. Neves, R. Johnsson, C. Guevara,

T. Snell, B. Victor, J. Mate, H. Guzman, and A. Fajardo. The following people have

provided technical or lab support: M. Larios-Sanz, U. Nagaswamy, B. Mulder, S. Posey,

S. Hardin, M. Travisano, D. Martinez, and D. Wells. Two undergraduate students

contributed numerous hours of lab work to this project; I would like to thank N.

Nnebuihe, and A. Konshack for their valuable contributions. I have received advice,

insight and comments from: M. van Oppen, J. Veron, H. Lessios, H. Guzman, M.

Takabayashi, T. Snell and O. Hoegh-Guldberg. I also wish to thank E. Bornham, C.

McNutt, J. Felsenstein, T. Hall, S. Kumar, D. Posada, M. Clement, and X. Xia.

Chapter II was made possible by a grant to G.M. Wellington from the

Environmental Institute of Houston, and from the support of G.E. Fox. Chapter III was

made possible by Sigma Xi grant in aid of research, and a grant to G.M. Wellington from

the National Geographic Society #6047-97. Chapter IV was made possible by grants to

Gerard M. Wellington from the Environmental Institute of Houston and the National

Geographic Society #6047-97.

iv


--------------------------------------------- A Dissertation

Presented to

The Faculty of the Department of Biology and Biochemistry

University of Houston

---------------------------------------------

In Partial Fulfillment

Of the Requirements for the Degree

Doctor of Philosophy

---------------------------------------------

by

Zac Forsman

May 2003

v

DISSERTATION ABSTRACT

This study explores the ITS region (ITS-1-5.8S-ITS-2) as a genetic marker in two

prominent Scleractinian genera: Porites and Siderastrea, emphasizing the continuum

between population genetics and phylogenetics. Chapter I is a review and introduction.

Chapter II addresses widely-cited potential problems with the ITS region (intra-individual

heterogeneity and alignment gaps), and demonstrates how they can actually be

informative. Chapter III investigates a putative cryptic species; Porites lobata-Panama,

and examines the genetic structure and morphometric variability in P. lobata samples

collected from the Galápagos, Easter Island, Tahiti, Fiji, Rarotonga, and Australia.

Chapter IV examines shared ITS haplotypes in S. glynni and S. siderea, indicating that S.

glynni originated either from a recent passage through the Panamá canal, or through an

ancient (1-3mya) vicariant event. Both hypotheses have important implications for the

evolution of the ITS region. Chapter V is a summary of the major conclusions.

vi

CONTENTS List of Tables ............................................................................................................................................... vii

List of Figures ............................................................................................................................................. vii

I. Introduction and Background ............................................................................................................. 1 SIGNIFICANCE......................................................................................................................................... 1 PORITES.................................................................................................................................................... 3 RIBOSOMAL SPACERS........................................................................................................................... 5

II. Intra-species Variability And Alignment Gaps In The ITS Region Can Be Informative In Scleractinian Coral Families, Genera And Species; A Case Study In Porites, Siderastrea And Outgroup Taxa............................................................................................................................................ 11

ABSTRACT ............................................................................................................................................. 11 INTRODUCTION .................................................................................................................................... 12

Intragenomic variability ....................................................................................................................... 14 Alignment ambiguity ............................................................................................................................. 16

METHODS............................................................................................................................................... 18 DNA extraction, PCR, Cloning and Sequencing................................................................................... 19 Intra-specific variability ....................................................................................................................... 21 Alignments ............................................................................................................................................ 22 Phylogenetic analysis ........................................................................................................................... 23

RESULTS................................................................................................................................................. 25 Intra-specific comparisons ................................................................................................................... 25 Inter-specific comparisons.................................................................................................................... 26 Alignment permutation ......................................................................................................................... 27

DISCUSSION........................................................................................................................................... 30 III. Phylogeography and Morphological Variation in Porites lobata Across the Pacific: A Cryptic Panamanian species and Isolation Consistent with Ocean Currents. .................................................... 75

ABSTRACT ............................................................................................................................................. 75 INTRODUCTION .................................................................................................................................... 76 METHODS............................................................................................................................................... 78 RESULTS................................................................................................................................................. 84 DISCUSSION........................................................................................................................................... 87 TABLES ................................................................................................................................................... 93 LITERATURE CITED........................................................................................................................... 121

IV. The Siderastrea glynni (Scleractinia: Siderastreidae) Paradox: A Critically Endangered Species Or A Stowaway From The Caribbean? ITS Region Sequences Are Shared With S. siderea. 124

ABSTRACT ........................................................................................................................................... 124 INTRODUCTION .................................................................................................................................. 125 METHODS............................................................................................................................................. 127 RESULTS............................................................................................................................................... 129 DISCUSSION......................................................................................................................................... 132 LITERATURE CITED........................................................................................................................... 150

V. Dissertation Conclusions .............................................................................................................. 152

vii

List of Tables Table II-1.......................................................................................................................................38 Table II-2.......................................................................................................................................40 Table III-1 .....................................................................................................................................93 Table III-2 .....................................................................................................................................95 Table III-3 .....................................................................................................................................97 Table III-4 .....................................................................................................................................99 Table III-5 ...................................................................................................................................101 Table IV-1 ...................................................................................................................................136 Table IV-2 ...................................................................................................................................138 Table IV-3 ...................................................................................................................................140 Table IV-4 ...................................................................................................................................142 List of Figures Figure I-1.........................................................................................................................................7 Figure II-1 .....................................................................................................................................42 Figure II-2 .....................................................................................................................................44 Figure II-3 .....................................................................................................................................46 Figure II-4 .....................................................................................................................................48 Figure II-5 .....................................................................................................................................50 Figure II-6 .....................................................................................................................................52 Figure II-7 .....................................................................................................................................54 Figure II-8 .....................................................................................................................................56 Figure II-9 .....................................................................................................................................58 Figure II-10 ...................................................................................................................................60 Figure II-11 ...................................................................................................................................62 Figure III-1 .................................................................................................................................103 Figure III-2 .................................................................................................................................105 Figure III-3 .................................................................................................................................107 Figure III-4 .................................................................................................................................109 Figure III-5 .................................................................................................................................111 Figure III-6 .................................................................................................................................113 Figure III-7 .................................................................................................................................115 Figure III-8 .................................................................................................................................117 Figure III-9 .................................................................................................................................119 Figure IV-1..................................................................................................................................144 Figure IV-2..................................................................................................................................146 Figure IV-3..................................................................................................................................148

1

I. Introduction and Background

SIGNIFICANCE

Reef-building corals form the structural foundation of one of the most diverse and

productive ecosystems on Earth. Corals have been a major component of reef

ecosystems since the late-Triassic (more than 200 million years ago). They have

persisted through several mass extinctions, as well as major global fluctuations in climate

and sea level. Despite the apparent long-term stability of reef corals, there is

widespread concern that human activity is linked to increasingly frequent episodes of reef

degradation. Hoegh-Guldberg (1999) reviewed widely cited anthropogenic threats to

coral reef ecosystems, including: land runoff, pollution, terrestrial pathogens, over fishing

of herbivores, & coral bleaching (minor increases in ocean temperature dissociates the

coral/algal symbiosis resulting in mortality). Global warming trends are correlated with

mass coral bleaching events and increased levels of atmospheric CO2 may adversely

affect calcification and growth rates.

The sensitivity of corals to minor environmental changes is a valuable source of

information. Corals are indicator species, yielding information about the present status

of ecosystem health. Corals also yield a great deal of information about the past.

Coral are long-lived sedentary clonal organisms that secrete calcium carbonate skeletons

in annual growth bands analogous to tree-rings. Coral proxi-records are central to our

understanding of past climates, changes in sea level, and patterns of biogeography,

(reviewed in Romano et al. 2000). Corals are ancient organisms, descendants of one of

2

the first mulitcellular animals on Earth. Cnidarians (the phylum to which corals are a

member) represent one of the most important transitions in metazoan evolution. They

are the first animals with layers of specialized tissues, which allowed the first appearance

of evolutionary inventions such as: the gastric cavity, movement, muscles, nervous tissue,

and photoreception. Just as the physical skeleton has been a source of proxi-records in

recent geologic history, the genome is a valuable proxi-record of evolutionary

relationships.

Genetic studies have great potential to clarify one of the largest problems in coral

reef studies; many coral species are difficult to identify at the species level. The species

is one of the most fundamental and important units in the study of biology. Without the

ability to distinguish between species, it is impossible to recognize species ranges and

boundaries, dispersal among populations, or interactions between species. With no

ability to recognize species, one cannot determine which populations are endangered, or

even recognize when extinction occurs.

Coral species are difficult to define for several reasons: (1). Convergent

evolution: morphological taxonomic characters are often as variable within a species as

between species. Morphologically indistinguishable species could be closely related

"sibling species", or more distantly related "cryptic species" (after Knowlton 1993, 2000).

(2). Phenotypic plasticity: some species are broadly adapted to a wide range of habitats,

and exhibit different ecomorphs in response to different environmental conditions

(examples in Veron 1995, 2000). (3). Hybridization and reticulate evolution: Mass

spawning produces opportunities for hybridization between species because many corals

3

spawn simultaneously. Some corals are long-lived at the colony level (hundreds of

years or more), and geographically widespread. Changes in ocean circulation may

introduce genetically and morphologically disparate populations, or create opportunities

for hybridization between 'species' vis-à-vis Veron's (1995) theory of reticulate evolution

by sea surface vicariance.

PORITES

The genus Porites Link 1807 has been one of the most important, widespread and

abundant reef-building corals over the last 20 million years (Frost 1977). Porites occurs

worldwide in the tropics, it has the largest range (Veron 1995, 2000) and has one of the

highest estimated dispersal abilities of any extant coral genera (Fadlallah 1983).

Despite the importance of Porites in coral reef ecosystems, relationships between species,

or populations within species remain largely unknown. Progress in Porites systematics

has been slow because it is difficult to determine what constitutes a 'species' within this

genus.

Taxonomy in Porites is based on morphological and skeletal architecture and is

renowned as among the most difficult and in the most need of revision. In Porites,

corallites are very small, irregular, perforated and may be as highly variable within a

single colony as between species. Colony form is also highly variable, for example P.

lobata ranges from encrusting, plate-like or bolder-like forms, to thin protruding lobe, fin

or columner forms. Many morphological differences can be attributed to a

phenotypically plastic response to environmental conditions (available light, water

motion, predation, etc.), while others may be indicative of underlying genetic variation.

4

These highly variable and hard to measure characteristics make it very difficult to divide

Porites into discrete species.

Around 122 Porites species have been named, although many of these names are

considered invalid (Veron 1986). Cairns (1999) recognizes 41 species as valid. Six

species are recognized in the Caribbean; P. porites, P. furcata, P. divaricata, P.

astreoides, P. colonensis and P. branneri. In the far eastern Pacific, 8 species are

currently considered valid; P. lobata, P. panamensis, P. rus, P. arnudi, P. australiensis,

P. lutea, P. lichen and P. sverdrupi. (The latter appears so similar to P. panamensis, that

it may not be a separate species (Veron personal communication)).

Early studies of Porites relied entirely on morphology, (Bernard 1902; Brakel

1977). Bernard (1906) abandoned the Linnean classification system entirely for this

genus, and used a system of numbers. Brakel (1977) concluded that patterns of

morphological Porites are so complex that no simple taxonomic resolution is possible at

the species level. His analysis suggested that P. astreoides and P. porites represented

only the most opposite extremes of recognizable ‘phenons’ in a continual gradient that he

attributed to diversifying selection. The authors maintained that Porites typified a

'species problem' in coral, due to countless intermediate forms.

Garthwaite et al. (1994) used multiple allozyme loci to determine that some

Porites species were genetically distinct. Wiel (1992a, 1992b) through allozymes and

multivariate morphometric statistics distinguished 8 putative species on both sides of the

Isthmus of Panamá. Weil concluded that a large portion of the morphometric variation

5

can be attributed to genetic variation, and that the recognizable species around the

Isthmus of Panamá are likely to be discrete entities.

Hunter (1988) also used allozymes to examine genetic structure in the Hawaiian

endemic P. compressa. Hunter et al. (1997) were among the first to use DNA in a

species level study of Scleractinia. Most molecular techniques are difficult to apply to

corals, because they can be contaminated by symbiotic algae (zooxanthellae). Hunter et

al. (1997) used the Internal Transcribed Spacers of ribosomal RNA genes to examine

Hawaiian and Floridian Porites species and their algal symbionts. The marker

distinguished between species, and revealed species level polymorphisms within

Hawaiian P. lobata.

RIBOSOMAL SPACERS

Nuclear ribosomal genes are a mosaic of variability, and are therefore useful for a

broad range of comparative studies. Regions that have species polymorphisms flank

others that are highly conserved across phyla. This allows studies at different levels of

taxonomic resolution. Primers can be designed from phylogenetically conserved

regions that bridge the gap across highly polymorphic regions. Eukaryotic rDNA

consists of tandemly repeated clusters of the 18S, 5.8S, and 28S genes separated by two

internally transcribed spacers, ITS-1 and ITS-2 (see Figure I-1). Levels of

polymorphism roughly correspond with taxonomic levels ranging from phyla (18S) to

species and below (ITS) (Hillis and Dixon 1991). Studies in a wide variety of

organisms have demonstrated that the spacers are useful for species level phylogeny,

6

species identification, and examining hybridization between species (reviewed in Chapter

II). Ribosomal genes are the largest and most ancient multigene family, occurring in

tandem repeats hundreds or thousands of copies long. The genes and the spacers

between them are usually orders of magnitude less variable within a species than between

species.

The ITS region shows variability within species as well as differences between

them, therefore it has great potential as a genetic marker in a wide variety of studies.

The marker also has serious potential drawbacks, such as polymorphism (sometimes at

high levels) within a single genome. Empirical studies of ribosomal spacers are needed

to further understand the nature of the forces that homogenize them within an

interbreeding lineage, and to determine where population processes such as interbreeding

end and divergence and speciation begin.

7

FIGURES

Figure I-1

A diagram of a Eukaryotic ribosomal operon, which consists of tandem repeats of

ribosomal genes and spacers: IGS, is the intergenic spacer located between each set of

ribosomal genes. The 18S is followed by ITS-1, the 5.8S and the ITS-2, followed by the

28S. Also shown are the relative locations of the 'universal Eukaryotic' PCR primers

used in this study ITS-1, and ITS-4 (White et al. 1990).

8

Figure I-1

9

LITERATURE CITED Bernard, H. M. (1902). The species problem in corals. Nature 65, 560. Brakel, W. H. (1977). Corallite variation in Porites and the species problem in corals. Proc. Third Intl. Coral Reef Symp. Miami, p 457-462. Cairns, S. D., Hoeksema, B. W. and Van Der Land, J. (1999). Appendix: List of Extant Stony Corals. In Atoll Research Bulletin, vol. 459. Washington, D.C.: Smithsonian Institution. Fadlallah, Y. H. (1983). Sexual reproduction, development and larval biology in Scleractinian corals: a review. Coral Reefs 2, 129-150. Frost, S. H. (1977). Miocene and Holocene evolution of Caribbean province reef-building corals. Proc. Third Int. Coral Reef Symp., Maiami 2, 353-359. Garthwaite, R. L., Potts, D. C. and Done, T. J. (1994). Electrophoretic identification of Poritid species (Anthozoa: Scleractinia). Coral Reefs , 49-56. Hillis, D. M. and Dixon, M. T. (1991). Ribosomal DNA: Molecular Evolution and Phylogenetic Inference. Quart. Rev. Bio. 66, 411-453. Hoegh-Guldberg, O. (1999). Climate change coral bleaching and the future of the world's coral reefs. Marine and Freshwater Research 50, 839-66. Hunter, C. L. (1988). Genotypic diversity and population structure of the Hawaiian reef coral Porites compressa, Ph.D. Dissertation. University of Hawaii . Hunter, C. L., Morden, C. W. and Smith, C. M. (1997). The utility of ITS sequences in assessing relationships among zooxanthellae and corals. Proc. 8th int coral reef sym. , 1599-1602. Knowlton, N. (1993). Sibling species in the sea. Annu. Rev. Ecol. Syst 24, 189-216. Knowlton, N. (2000). Molecular genetic analysis of species boundaries in the sea. Hydrobiologia 420, 73-90. Link, H. F. (1807). Bescheibung der Naturalein. Sammlungen der Universaitat Rostock, 3, 161-165.

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Romano, S. L. and Cairns, S. D. (2000). Molecular phylogenetic hypotheses for the evolution of Scleractinian corals. Bull. Mar. Sci. 63, 1043-1068. Veron, J. (1995). Corals in space and time; the biogrography and evolution of the Scleractinia. London: Cornell. Veron, J. E. N. (1986). Corals of Australia and the Indo-Pacific, pp. 644. New York: Angus and Robertsons Publishers. Veron, J. E. N. (2000). Corals of the World, vol. 3 (ed. M. Stafford-Smith). Townsville, Australia: Australian Institute of Marine Science. Weil, E. (1992). Genetic and morphological variation in Caribbean and eastern Pacific Porites (Anthozoa, Scleractinia), preliminary results. Proc 7th Int. Coral Reef Sym. Guam 643-656. Weil, E. F. (1992). Genetic and morphological variation in Porites (Cnidaria, Anthosoa) across the Isthmus of Panama. Ph.D. Dissertation. pp. 327. Austin TX: University of Texas. White, T. J., Gruns, T. L. and Taylor, W. J. (1990). Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In PCR Protocols: A guide to methods and applications (ed. Innis, D.H.;Sninsky,J.J.;White,T.J.). San Diego: Academic Press.

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II. Intra-species Variability And Alignment Gaps In The ITS Region Can Be Informative In Scleractinian Coral Families, Genera And Species; A Case Study In Porites, Siderastrea And Outgroup Taxa.

ABSTRACT In this study, we use an empirical example to examine two of the most widely

acknowledged problems with the ITS region as a phylogenetic marker: intra-species variability, and alignment ambiguities resulting from insertions and deletions. Several sequences from each individual were examined from the following Porites and Siderastrea species; P. lobata, P. lobata-panama (a genetically distinct lineage that may represent a new cryptic species), P. astreoides, P. colonensis, P. sverdrupi, P. panamensis, P. divaricata, P. rus, P. furcata, S. stellata, S. radians, and S. siderea. A phylogeny was then estimated including four outgroup sequences from the GenBank database (Tubastrea, Balanophyllia, Scapophyllia and Montastrea). Intragenomic variation in all species sampled was low. In Porites and Siderastrea sequences, nucleotide diversity was significantly lower within a population, than between populations separated by thousands of kilometers (averaging 0.9%±0.5 and 1.2%±0.5 respectively), indicating that geographic structure may exist. The average difference between species was at least one order of magnitude higher (12.0%±1.2). These results indicate that the ITS region is an informative marker at the species-level and below.

Despite a patchwork of conserved sequence motifs among Scleractinian families, genera and species, numerous insertions and deletions make objective sequence alignment problematic. The effects of alignment gaps on phylogenetic estimates were examined by systematically permuting gap penalties to generate 50 alternative alignments. A maximum likelihood tree was then constructed for each alternative alignment. The trees were remarkably congruent, with the majority of nodes supported by all of the alternative alignments. The same general topology (although much less resolved) was also supported by removing all of the alignment gaps. Alignments at opposite ends of the gap penalty spectrum had unusual ts/tv (transition/transversion) ratios, high discrepancies between substitution and gap distance, and unique nodes. Alignments with mid-range gap penalties had ts/tv ratios similar to conserved portions of the alignment, high character congruence between substitutions and gaps, and the most congruent tree topology. The mid-point alignment was chosen to estimate a phylogeny with maximum likelihood, maximum parsimony, and neighbor-joining methods. The data did not significantly deviate from expectations of a molecular clock at the genus level and below. The phylogeny is consistent with several previous molecular and paleontological studies. This study represents the first molecular phylogeny at the family to species level in Scleractinia.

12

INTRODUCTION

In reef building Scleractinian corals, high levels of genetic and or morphological

variation have resulted in a great deal of taxonomic confusion and controversy.

Intermediate and overlapping morphologies are thought to be due to convergent or

parallel evolution, or by introgression from distinct lineages in 'hybrid species

complexes', resulting in non-discrete patterns of genetic and or morphological variation

(Veron 1995; Lopez and Knowlton 1997; Knowlton 2000; van Oppen et al. 2000, 2002).

This problem is not limited to Scleractinia, but pertains to many of the earliest branches

of the tree of life, where discrete genetic and morphological boundaries are often unclear.

A second major problem in coral systematics is that many of the well-studied and

widely used molecular markers have low levels of polymorphism. Mitochondrial DNA

evolves at a slow rate in corals relative to other Metazoans, such as vertebrates (Romano

and Palumbi 1996,1997; Shearer et al. 2002; van Oppen 1999). DNA repair

mechanisms that are present in free-living relatives of mitochondria appear to be retained

in coral mitochondria, which is a likely explanation for the low levels of polymorphism

(van Oppen 1999). Molecular markers such as the 28S nuclear ribosomal gene, and the

mitochondrial 16S ribosomal gene, have been used for establishing relationships between

orders and families; (Romano and Palumbi 1996,1997; Veron et al. 1996; Chen et al.

1995) however, are not informative at the genus level and below.

The transcribed spacers of nuclear ribosomal genes (ITS-1 and ITS-2), are

becoming one of the most widely used molecular markers at the species level and below

13

in Scleractinian coral (Hunter et al. 1997; Lopez and Knowlton 1997; Odorico and Miller

1997; Medina et al. 1999; van Oppen et al. 2000, 2002; Diekmann at al. 2001;

Takabayashi et al. 1998a, 1998b; Rodriguez-Lanetty and Hoegh-Guldberg 2002;

Márquez et al. in press). There is a considerable precedent for the use of ITS to infer

relationships at or below the species level in a wide variety of other taxonomic groups.

It is widely used for identifying cryptic species of medically or commercially important

fungi (for example; McCullough et. al. 1998; Kuninaga et al. 1997; Arlorio et al. 1999).

It is frequently used in plant systematics (reviewed in Baldwin et al. 1995) and to reveal

relationships in species complexes (Jeandroz et al. 1997; Hsiao et al. 1995; Sang et

al.1995; Wen and Zimmer 1996). It has also been used to reveal geographic

polymorphisms and species relationships in insects (Wesson et al. 1993; Marcilla et al.

2001) and a variety of marine organisms; e.g. deep sea hydrothermal vent polycheates

(Jollivet et al 1995), the globally distributed green algae Chlorophyta (Bakker et al.

1995), the ahermatypic coral Balanophyllia elegans (Beauchamp and Powers 1996) and a

corallimorpharian anemone Rhodactis (Chen and Miller 1996).

Despite the wide use of the ITS region in phylogenetic studies, many authors have

acknowledged two major problems with the marker that can severely confound

phylogenetic studies: (1). Intragenomic variability can be quite large in some species,

pseudogenes or separate chromosomal lineages can make phylogenetic estimation

problematic. (2). hyper-variable portions of ITS-1 and ITS-2 are prone to numerous

insertions and deletions, which can result in alignment ambiguities. Distantly related

species, or species from different genera or families become nearly impossible to align

14

objectively, despite the existence of patches of conserved sequence motifs. These two

problems are addressed in more detail in the following separate sections.

Intragenomic variability

Within a typical Eukaryotic genome there are hundreds, or thousands of copies of

ribosomal genes, which are separated by rapidly evolving spacer sequences. It has been

observed that the spacer sequences tend to be considerably more similar within

reproductive groups, than between separate species (Learn and Schaal 1987, Coleman

and Mai 1997). Concerted evolution, is a process that homogenizes tandem gene

repeats such as ribosomal genes and spacer sequences. Unequal crossover and gene

conversion during crossover are the two most widely accepted mechanisms for concerted

evolution (Dover 1982). Unequal crossover is due to tandem gene repeats occasionally

mis-pairing, resulting in one gamete with extra copies and one with fewer. Gene

conversion is a process whereby one allele is converted to another by cellular repair

mechanisms, which also occurs during recombination. Recombination does not occur

between reproductively isolated individuals; therefore, non-conserved sequences are free

to rapidly diverge after speciation (Elder and Turner 1995). Ribosomal spacer gene

trees usually closely reflect the species tree, provided that the rate of turnover (gene

conversion and unequal crossover) is greater then the rate of speciation (Hillis and Dixon

1991). In other words, the variability within an individual or species must be low

relative to the average difference between closely related species in the taxonomic group

of interest.

15

Intragenomic variability is usually attributed to one of several causes. The

existence of extremely divergent paralogues genes within a genome is usually associated

with the presence of inactive pseudogenes. Divergent pseudogenes have been

associated with ancient hybridization events between separate species, which can result in

polyploidy, followed by chromosomal inactivation (Wendel et al. 1995; Sang et al. 1995;

O'Donnell and Cigelnik 1997; van Oppen et al. 2000; Muir et al. 2000). Some

taxonomic groups have several active arrays of ribosomal genes (nucleolus organizer

regions) located on separate chromosomes. Moderately divergent intra-individual

paralogues have been associated with slower rates of crossover and gene conversion

between these separate chromosomal lineages (Arnheim et al. 1980; Polanco et al. 2000).

Relatively low levels of intra-specific nucleotide diversity make phylogenetic and

population studies much less problematic; however, even if nucleotide diversity is low,

separate species cannot easily be distinguished if speciation occurs faster than the rate of

concerted evolution.

Population level processes are also likely to have an important role in influencing

the homogeneity of ribosomal spacers within a species. A highly subdivided species

with isolated populations might be expected to have higher ribosomal spacer

heterogeneity then a species with no subdivision. Isolated populations are likely to

undergo genetic drift, because concerted evolution is maintained by recombination, and

net recombination will be less frequent between isolated populations. In order for the

ITS region to be useful for population genetic studies, a hierarchy of variability must

exist whereby average nucleotide diversity is significantly lower at the intragenomic level

16

then the intrapopulation level, which is in turn lower than the interpopulation level. If

such patterns exist, then the ITS region could be useful as an indicator of relative gene

flow between populations. Empirical studies that examine the variability of ribosomal

spacers from the population to species level processes are necessary to gain an

understanding of ITS region population and evolutionary dynamics.

Alignment ambiguity

A multiple sequence alignment is a single hypothesis about how a given set of

sequences has evolved. Alignment can have a greater effect on phylogenetic estimation

than the tree making method (Morrison and Ellis 1997). Multiple sequence alignment is

generally not problematic for closely related sequences or highly conserved sequences,

where the majority of mutations are substitutions. In relatively non-conserved

sequences such as introns or ribosomal spacers, a large percentage of the mutations are

likely to be insertions and deletions. Since it is usually not possible to determine

whether an alignment gap between two sequences was the result of an insertion or a

deletion, these events are referred to as indels. Indels generally originate during

replication, recombination, or transposition. The occurrence of gaps in a given set of

sequences usually follows a bimodal distribution consisting of large and small gaps.

Small gaps usually consist of simple repeats resulting from replication slippage, whereas

large gaps tend to result from recombination or transposition (Li 1997). The more gaps

there are in an alignment, the higher the number of possible alternative alignments, and

the higher the number of ambiguous positions. Ambiguous positions provide the

17

opportunity for the subjective judgment of a researcher to consciously or unconsciously

bias the result. The more distantly related the sequences the greater the chance of indel

saturation, resulting in greater homoplasy (contradictory data due to reversals, convergent

evolution, or parallel evolution).

There are several widely employed methods of handling gaps in sequence

alignments. The most commonly applied approach is to "manually improve" an

alignment after its initial construction by a computer algorithm. The goal of manual

"improvement" is to increase the apparent similarity between sequences in the alignment,

however, clear objective criteria for basing such "improvements" are often lacking

(Giribet and Wheeler 1999). This can be especially problematic in hyper-variable

sequences such as introns or transcribed spacers. Although a manually improved

alignment may appear "better" then a computer generated alignment, the appearance

could be misleading, and poorly reflect how the molecule actually evolved. A manual

alignment is unlikely to take into account that some substitutions have higher

probabilities of occurring then others in a given data-set (e.g. the bias for transitions over

transversions).

A second strategy that is often employed is to remove strips of the sequence

alignment that contain alignment gaps altogether (Olsen and Woese 1993). The obvious

setback of this approach is that a great deal of valuable, and potentially informative data

becomes lost. It has been demonstrated that gaps can contain phylogenetic signal

(Giribet and Wheeler 1999), and ignoring characters from a phylogenetic analysis can be

subjective. A third, less widely used, approach is to generate and compare several

18

alternative alignments (Morrison and Ellis 1997; McFadden et al. 2001), or to search for

optimal alignments by parsimony criteria (Wheeler and Gladstein 1988). These

promising approaches are more computationally expensive, and cannot guarantee that the

entire alignment space has been examined, or that the 'correct' alignment can even be

found. However, each approach has the benefit that they are not subjective, and can

give an indication how much homoplasy is present in the data set. Presumably, a strong

underlying phylogenetic signal will reflect the same relationships under a wide variety of

alignment conditions.

The goals of this study are: (1) to examine the hierarchical nature of variability in

the ribosomal spacer region from the individual to species levels. (2) to examine the

phylogenetic signal from species to family level through comparisons of many alternative

alignments generated by the permutation of gap penalties, and (3) to examine the

relationships between several prominent species, genera and families of Scleractinian

coral.

METHODS

Small, fragments, ca. 10-15 grams of tissue and skeleton were removed from

colony edges, branches, or protuberances. Samples were collected at least 10 meters

apart to avoid collecting colonies that originated from fragmentation or budding.

Samples were preserved in 95-100% ethanol. The samples were divided into several

pieces in the laboratory, a small piece was stored in fresh ethanol at -20°C for genetic

analysis, and larger pieces were placed in bleach to dissolve the soft tissue, prior to

19

drying. Voucher specimens, and scaled digital microscope images were collected for the

majority of specimens and will be made available for other studies upon request. Table

II-1 summarizes the geographic location of the samples collected, the collector and the

date of collection.

DNA extraction, PCR, Cloning and Sequencing

Many authors have reported that extracting DNA from Scleractinia can be

problematic. Mucous, polysaccharides, pigments, or other DNA co-precipitates are

often cited as inhibiting the PCR reaction. After a trial of many widely available

extraction protocols, the following protocol consistently yielded the best results. A few

milligrams of tissue and skeleton were dried in a vacuum centrifuge for 20min, the

sample was then homogenized in a solution of 250µl of 50mM tris-HCL (pH 8.0) and

10mM EDTA with a micro-pestle for 2 to 5 minutes. The homogenate was then

frequently inverted during a 5 minute room temperature incubation in 250µl of 20mM

NaOH and 1% SDS. A volume of 350µl of 3.0M potassium acetate (pH 5.5) was added

to the mixture and incubated for 5 minutes on ice followed by centrifugation at maximum

speed. The top 500µl of the cleared lysate was then transferred to a new tube and the

DNA was precipitated by centrifugation in 1ml isopropanol. The sample was then

washed with 70% EtOH, dried and resuspended in 200µl of H2O.

The nuclear ribosomal internal transcribed spacer region (spanning a partial

sequence of the 5’ end of the 18S gene, the complete sequence of ITS-1, 5.8S gene and

ITS-2, and a partial sequence of the 3’ end of the 28S gene) was amplified using the

20

Eukaryotic ‘universal’ primers; ITS-1 (5' -TCC GTA GGT GAA CCT GCG G-3') and

ITS-4 (5' -TCC TCC GCT TAT TGA TAT GC-3') (White et al. 1990) using the

following PCR temperature profile: an initial denaturing period of 96˚C for 2 minutes

followed by 30 of the following cycles: denaturing at 96˚C for 10 seconds, annealing at

50˚C for 30 seconds, and at 70˚C for a 4 minute extension step, followed by a final 5

minute extension step. The PCR reaction consistently produced a single clear band

ranging from approximately 650bp in Siderastrea species, to ca. 700bp in Porites

species. Nearly all samples that did not initially amplify PCR product, successfully

yielded product when the template was diluted either 10 or 100 fold.

PCR products were ligated into the PgemT-EZ cloning vector (Promega Inc.)

and transformed into JM109 competent cells, followed by blue white colony screening.

White colonies were screened for inserts, by colony PCR using the vector primers.

Only two size categories were present; an approximately 750-800bp band indicated an

insert and a 50bp band indicated no insert. Plasmid DNA was then isolated from the

positive colonies using Wizard Preps (Promega Inc.). An average of three molecular

clones from each individual were sequenced using the M13 vector primers, in both the

forward and reverse direction for the sake of complimentary strand conformation.

Sequencing was performed using 1/4 reactions of Dye Terminator Cycle Sequencing kit

(PE Biosystems Inc.). The sequencing reactions were ethanol precipitated and dried

prior to gel loading and running, which was performed commercially (SeqWright, Inc., or

by Lone Star, Inc., both in Houston, TX)

21

To confirm that only the coral ITS region was sequenced, it was compared to

known sequences from P. lobata (Hunter et al. 1997), and other coral ITS sequences in a

BLAST query of the National Center for Biological Information’s (NCBI) sequence

database. Coral specific primers (Takabayashi et al. 1998b) were not used in this study,

because the primers very rarely amplified any PCR product from Porites or Siderastrea

species. This may be due to variability at binding sites for these primers, which is less

likely to occur with the highly conserved 'universal' primers. In Porites and Siderastrea

spp., a single PCR band was consistently amplified, however in Pocillopora species, the

universal primers amplified two bands, one ca~1kb, and one ca~300bp (Z. Forsman et al.

unpublished data). When sequenced and compared to Genbank, these bands correspond

to coral and zooxanthellae respectively. We were unable to observe a zooxanthellae

band in Porites or Siderastrea samples, even under lower annealing temperatures or a

wide variety of other conditions.

Intra-specific variability

There were nearly no alignment ambiguities in intra-specific comparisons.

Intra-individual nucleotide diversity was estimated in MEGA 2.1 (Kumar et al. 2001), by

constructing a distance matrix based on percentage difference (transitions and

transversions) over all positions in the alignment. The matrix was then partitioned into

three subsets: (1) intragenomic; when 2 or more molecular clones were sequenced from

the same individual coral. (2) intrapopulation; when 2 or more individuals were

collected from the same population (reef, island, or general geographic region) and (3)

22

interpopulation, when several individuals were sampled between distant geographic

regions. Statistical tests were calculated in Systat v.9 1998 (SPSS inc.).

Alignments

In order to encompass the large variability within some species (P. lobata, P.

astreoides, and S. siderea), while still being computationally tractable; two representative

sequences were chosen from each 'variable' species that represented the 2 most distinct

haplotypes. The representative sequences were then used to construct 50 separate

permuted alignments generated by systematically altering the alignment parameters in

ClustalW (Thompson et al. 1994) that have a large influence on sequence length: the Gap

Opening Penalty [GOP], and the Gap Extension Penalty [GEP] (after, Morrison and Ellis

1997, and McFadden et al. 2001, see Figure II-3 for an illustration). All pair-wise

combinations of the following values were used: GOP= 0.1, 1, 2, 4, 8, GEP = 0.1, 0.3, 1,

2, 4, as well as ClustalW's default value GOP=10,GEP=5. To avoid input order bias,

the order of taxa was shuffled prior to generating each alignment. Twenty-five

alignments were constructed for the 'ingroup' taxa (containing only Porites sequences),

and twenty-five alignments were constructed for the 'outgroup' taxa, which consisted of

Siderastrea sequences from this study, and the following sequences from GenBank:

Tubastraea coccinea (Dendrophylliidae) (AF180110), Balanophyllia elegans

(Dendrophylliidae) (AF180110), Scapophyllia cylidrica (Faviina; Merulinidae)

(SCU65479), Montastaea faveolata (Faviina; Faviidae)(AB065353). A 'reduced'

alignment was also constructed in which all columns containing gaps were removed.

23

Phylogenetic analysis

For each of the 50 representative alignments, (25 with in-group taxa and 25 with

in-group and out-group taxa), a tree was constructed using the maximum likelihood

method in PHYLIP version 3.6 (Felsenstein 2002) using the default options in the

program DNAML (the default options were chosen in order to increase the speed of this

analysis, as the goal was to examine the sensitivity of the branching order to alternative

alignments, under general conditions with the fewest assumptions about an evolutionary

model). A maximum likelihood tree that imposed the constraints of a molecular clock

was also constructed for each alignment using the program DNAMLK. Consensus trees

were then constructed, using the program CONCENSE in PHYLIP 3.6, using the

majority-rule option. The choice of out-group can greatly influence the tree topology

through long branch attraction (Felsenstein 1988), therefore unrooted phylogenies of the

ingroup (Porites) taxa were estimated first; the addition of outgroup taxa did not alter the

rooting of the ingroup taxa. This procedure, and the addition of multiple ougroup taxa

was employed to avoid inherent problems associated with outgroup choice (see Swofford

et al. 1996 p. 478, Sanderson and Shaffer 2002).

The phylogram for the 'reduced' alignment was constructed using the maximum

likelihood method implemented in the DNAML program in PHYLIP 3.6 (Felsenstien

2002), the alignment was bootstrapped 500 replicates. The program DAMBE v4.1.19

(Xia and Xie 2001) was used to calculate the transition/transversion ratio over Kimura's

24

(1980) estimate of genetic distance graphs in Figure II-6, as well as to calculate the gap

distances of various alignments (Figure II-7).

From the spectrum of alternative alignments generated by permuting gap

penalties, the 'mid-point' (GOP=2.0, GEP=1.0) of the gap penalty range was determined

to be reasonable based on the following criteria: (1) The transition/transversion ratio

did not deviate from alignments where there were no alignment ambiguities (the

alignment of closely related taxa such as Sidereastrea, or an alignment that only included

the 5.8S), see Figure II-6. (2) There was high character congruence between

substitutions and gaps for this alignment, see Figure II-7. In other words, a distance

cladogram based on gap distance would display the exact same topology as a cladogram

based on substitution distance. (3) The tree topology was the same as the majority rule

consensus topology for all alignments.

A phylogram was constructed from the 'mid-point' alignment parameters

GOP=2.0, GEP=1.0, for all 130 sequences using the Neighbor-Joining (Saitou and Nei

1987) method Figure II-9. Genetic distances were calculated using Kimura's (1980)

two-parameter model. The tree was bootstrapped 1000 replicates, implemented in

MEGA 2.0 (Kumar et al. 2001). The likelihood ratio test as described by Felsenstein

(2002) was performed on the Porites taxa separately, and then with the successive

addition of alternative outgroups, the tests were carried out in PHYLIP 3.6 (Felsenstein

2002), and in DAMBE v4.1.19 (Xia and Xie 2001).

25

RESULTS

Intra-specific comparisons

One hundred and thirty sequences from 47 individuals and 12 species were

compared (Table II-1). Sequences were usually similar in length and nucleic acid

content within a species. There were almost no alignment ambiguities between

sequences within a putative species group. Sister-species had very few alignment

ambiguities; however, the number of ambiguous positions rapidly increased among the

more distantly related species. Despite patches of conserved regions in the ITS-1 and

ITS-2, it was extremely difficult to align sequences with the outgroup species with any

confidence. The 5.8S gene was nearly invariant in all the Porites species, although

there were polymorphisms between Porites and the outgroup taxa, there were no

ambiguous positions.

Figure II-1 and II-2 illustrate the nucleotide diversity of the ITS region at several

hierarchical levels. Where comparisons were possible between multiple sequences

collected from the same individual specimen (125 sequences from 33 individuals), intra-

individual per site nucleotide diversity was low, averaging 0.6%±0.5 (percent nucleotide

substitutions), see Figure II-1. A one-way ANOVA with a Bonferroni correction

indicated no significant differences in intragenomic diversity among species, except

between P. lobata and S. radians. S. radians had the lowest intragenomic nucleotide

diversity and P. lobata had the highest. Intragenomic variability is highly skewed

(Figure II-2).

26

Comparisons between separate individuals collected from the same population

were possible using 90 sequences from 34 individuals in 6 species (P .lobata,. P. lobata-

Panama, P. astreoides, P. sverdrupi, P. divaricata, and S. siderea); intra-population

nucleotide diversity averaged 0.9%±0.5. P. sverdrupi, P. lobata-Panama, and P.

divaricata had significantly lower nucleotide diversity at the population level (P<0.05

according to a one-way ANOVA with a Bonferroni correction). Two species (P. lobata

and P. astreoides) were sampled across a large geographic range. The average inter-

population nucleotide diversity in P. lobata and P. astreoides together averaged

1.2%±0.5 (there was no significant difference between means; t-test p=0.33). Intra-

genomic, intra-population, and inter-population nucleotide diversity were significantly

different according to the non-parametric Kruskal-Wallis one-way analysis of variance

(P<0.0001, the values were also highly significant in a one-way ANOVA; however, the

assumption of normality was violated, therefore the non-parametric test used). When

the P. lobata data were examined separately, the same patterns were evident, but the

difference between intrapopulation and interspecies level diversity were slightly less

pronounced (Chapter III).

Inter-specific comparisons

Average inter-specific differences were generally at least an order of magnitude

larger than intra-specific nucleotide diversity (Table II-2); however, differences within P.

lobata, and in P. astreoides, were as large as the average difference between the two

sister species P. panamensis and P. sverdrupi , or nearly as large as between P. furcata

27

and P. divaricata. Surprisingly, all samples that were initially identified as P. lobata

from the Pacific side of Panamá were genetically quite distinct (differing on average

6.2% ±0.9) from P. lobata collected from all other geographic locations (Galápagos,

Tahiti, Easter Island, Fiji, Rarotonga and Australia). Because the groups are

reciprocally monophyletic, P .lobata from Panamá will be treated as a separate, yet

cryptic species, hereafter referred to as P. lobata-panama. A more detailed analysis of

this putative cryptic species will be examined in Chapter III.

Alignment permutation

The stability of the branching order to alternative alignments was evaluated by

systematically altering alignment parameters that have the largest influence on alignment

length, as illustrated in Figure II-3. The majority rule consensus cladograms for each set

of permuted alignments are shown in Figure II-4. The estimated branching order, and

the overall topology was robust, and relatively insensitive to changes in the alignment

parameters. The topology of the tree did not change as outgroup taxa were added,

indicating that the choice of outgroup did not effect the overall topology. The trees

were highly congruent despite major changes in the overall appearance of the alignment.

Under the smallest gap penalties, the alignments appear spread out and scattered whereas

the largest penalties resulted in a clumped appearance, occasionally containing regions

that appeared misaligned. The sum of all branch lengths for the maximum likelihood

phylograms varied approximately 2 fold, with the highest gap penalty alignments

resulting in the longest trees, and the lowest gap penalties resulting in the shortest trees.

28

The lowest gap penalty alignments tended to produce star-like phylogenies, with all long

branch lengths near equidistant, whereas high gap penalties resulted in the opposite

(illustrated in Figure II-5). The overall tree topologies were more consistent if the

assumptions of a molecular clock were enforced (Figure 5a); however, the likelihood

ratio test of the molecular clock hypothesis (described by Felsenstein 2002) could be

rejected for all alignments that contained the 'outgroup' taxa..

Although all alignments generally supported the same topology, a few

alignments at opposite ends of the gap penalty spectrum, resulted in alternative branching

orders. The alternatives were limited to two nodes in particular. In Porites, P. lobata

swapped positions with P. astreoides in a few high gap penalty alignments. Under the

lowest gap penalty alignments, Siderastrea was the closest outgroup to Porites, under

medium gap penalties Siderastrea grouped with Dendrophyllidae, and under high gap

penalties Dendrophyllidae was the closest outgroup to Porites. If the assumptions of a

molecular clock were enforced, the same topology was supported more often (Figure 5).

The 'reduced' alignment Figure II-6, gives an indication of the groupings if all

positions with gaps are removed from the alignment. The general topology is similar to

the tree topology in Figure II-4 b; however, the Porites clade is unresolved (at the level of

60% bootstrap consensus). All nodes that have high bootstrap values are highly

congruent with trees from the permuted alignments.

The ratio of transition to transversions varied between two extremes as illustrated

in Figure II-7; lower gap penalties resulted in very high ts/tv ratios, whereas high gap

penalties resulted in more transversions than transitions. The 'mid-point' alignment was

29

closest to an expected transition transversion ratio, if one assumes that the 'actual' ratio

will be similar to an alignment with no ambiguity (such as in closely related Siderastrea

taxa Figure II-7 D.) or portions of the same alignment that has no ambiguity (such as the

5.8S gene for the same taxa, Figure II-7 C.).

The 'mid-point' alignment had the highest character congruence between gaps and

substitutions, Figure II-8. High gap penalties resulted in more substitution than gaps,

and low penalties resulted in more gaps than substitutions. Cladograms based on Gap

distance were incongruent with those based on substitution distance in both the 'high' and

'low' gap penalty alignments, whereas the 'mid-point' alignment had the exact same

topology. This result is expected if the probability of an insertion or deletion is assumed

the same as that of a substitution. Figure II-9 illustrates that maximum likelihood and

parsimony methods strongly support the same tree topology for the 'mid-point' alignment.

The two nodes with the lowest nonparametric bootstrap values are the same two nodes

that change as a result of alignment permutation.

Figure II-10 is a Neighbor-Joining phylogram of the 'mid-point' alignment

parameters (GOP=2.0, GEP=1.0) applied to all 130 sequences collected for this study and

the four outgroup sequences from the database. Within P. lobata, several additional

clades were supported; however, few of them were monophyletic at the individual level

(in other words, polymorphic sequences from a single individual would be dispersed

among several different clades). There were no clear geographic divisions between

populations in P. lobata, although individuals from neighboring populations tended to

share the same clade. P. astreoides also contained additional clades that were well

30

supported. One clade contained two individuals from Panama, and one from Brazil.

The other clade contained sequences from Texas (Flower Garden National Marine

Sanctuary), Belize and Brazil. Both clades were polypheletic with respect to geographic

region. A morphometric and genetic comparison between P. lobata populations were

investigated in greater detail (see Chapter III). All of the P. sverdrupi sequences were

monophyletic, however, they were nested inside the P. Panamensis clade. The

likelihood ratio test of the molecular clock (Felsenstein 2002) could not be rejected for

the Porites data set, (likelihood ratio chi-square = 14.89,10 d.f., p = 0.136). The

molecular clock was rejected if any of the outgroup taxa were included, or if the 5.8S

gene was evaluated separately. A rate of 0.4% per million years was assumed, based on

previously published rates for birch trees (Savard et al. 1993). The rationale for

choosing this rate over the commonly cited rates established for Drosophila (1.2%,

Schlotterer et al. 1994), is that coral are likely to have a nucleotide generation time closer

to the order of years, rather than days or weeks. A correlation between covariates of

generation time and evolutionary rate has been established (Martin and Palumbi 1993),

and will be discussed in Chapter IV.

DISCUSSION

Intra-individual sequence diversity and variance were low, and do not

significantly differ across most of the Porites and Siderastrea species examined (Figure

II-1). In 130 sequences from 47 individuals, the average within individual difference

was only 0.56%±0.5. The levels of intra-genomic variation were not significantly

31

different among most taxa examined. Intragenomic variability is highly skewed (Figure

II-2); therefore, the probability of collecting nearly identical sequences from the same

individual is many times more likely then the chance of collecting sequences that differ

by more than a few nucleotides. A large number of pseudogenes, or the existence of

several separate chromosomal lineages would probably result in a large intragenomic

nucleotide diversity and variance, and reflect a bimodal distribution. The majority of

the hundreds or thousands of copies of ribosomal spacers within each individual are

therefore likely to be relatively similar. It is possible for cloning or PCR selection or

drift to bias the sampling process; therefore, highly conserved 'universal' Eukaryotic

primers were used. The binding sites for these primers are invariant between very

distantly related organisms, which increases the chance that distinct variants within a

sample will be amplified. Sampling effects alone do not easily account for the

observation that individuals from within a region tend to be more similar then individuals

between regions. The differences between sequences gradually increased as more

populations were sampled. The implication is that there is some degree of geographic

structure, whereby genetic differences increase with geographic distance. This

possibility will be further investigated in greater detail with an examination of the P.

lobata data in the context of morphometrics and population genetics in Chapter III. It is

interesting to note, that species with very large geographic ranges (such as P. lobata and

P. astreoides) tended to have higher then average intrapopulation and intragenomic

nucleotide diversity, (which may be expected for populations undergoing low levels of

gene flow between isolated populations).

32

There are two main conclusions that can be drawn from this survey of ribosomal

spacer diversity: (1) Intragenomic ITS region heterogeneity does not appear to be

extreme in the Porites and Siderastrea species examined. Intraspecific differences were

never larger than and usually an order of magnitude smaller than interspecific

differences. ITS region heterogeneity may not present a major obstacle for phylogenetic

estimation. It is not known to what extent this result can be generalized to other

Scleractinian species; however, similar patterns have been observed in a wide variety of

organisms. (2) The patterns of variability observed may be useful for examining

geographic differences between populations (see Chapter III). The standard error of

intrapopulation and interpopulation nucleotide diversity overlap considerably, therefore

large sample sizes are necessary to detect genetic structure. As the cost of sequencing

decreases and other rapid methods of comparing DNA are developed, examining the

relative proportions of ITS haplotypes between populations will become a more feasible

and highly informative method. The existence of significantly higher levels of intra-

individual nucleotide diversity in species with large geographic ranges and subdivided

populations, may indicate that ITS region nucleotide diversity is proportional to

population heterogeneity; however, further studies are necessary to address this issue.

The overall branching order was quite robust and was rarely influenced by

alternative alignments, despite major changes in the overall appearance of the alignment.

Presumably, the insensitivity of the tree topology to alternative alignments reflects a

strong underlying phylogenetic signal, which overwhelms the potential noise caused by

alignment ambiguities. The two nodes that were sensitive to changes in gap penalties

33

were the same two nodes that had low bootstrap values, or alternative topologies under

Parsimony and likelihood methods (see Figure II-9). The reason that these particular

nodes are sensitive could simply be that, in these instances multiple taxa originated over a

brief period of time, and had similar distances to a node.

The fact that the log-likelihood test of the molecular clock hypothesis could not

be rejected for the 'in group' taxa, but could be rejected for the 'out group' taxa, could be

explained by an exponential increase in mutational saturation (both in terms of

substitutions and gaps) as distance in time increases. The discrepancy between the

shortest and longest trees in Figure II-5 a, appear exponentially larger as distance in time

increases. Theoretical and simulation studies are necessary to determine if corrections

for gap saturation are applicable in this situation.

The consensus and 'mid-point' trees supported relationships at the family level,

which are consistent with previous molecular studies. Veron et al. (1996) examined

255nt of the ribosomal 28S gene, the branching order between families was; ((Poritidae,

Dendrophylliidae) (Siderastreidae)),(Faviidae, Merulinidae), Romano and Cairns (2000),

used the same molecular marker, however they sampled a larger number of separate

species from the same families, they found similar relationships; (Poritidae

(Dendrophylliidae, Siderastreidae)) ,(Faviidae, Merulinidae). The Mitochondrial 16S

ribosomal gene was also consistent, although the molecule had very low levels of

polymorphism, therefore several branches remained unresolved (Romano and Cairns

2000).

34

The fossil record for Scleractinia is one of the most extensive of any organism,

however, there are numerous problems in interpreting this record, especially with

inferring ancient relationships (discussed in Romano and Cairns 2000, Veron et al. 1996).

Because the molecular clock hypothesis can be rejected outside of the Porites genus, we

cannot reliably infer the timings of the origin of families or of genera; however, we can

examine hypotheses about the relative branching order, and approximate placement of

groups. Figure II-11 illustrates a summary of several taxonomic studies by several

authors (based on the fossil record and extant morphology) of Scleractinian families

(Veron 2000, Veron et al. 1996, Roniewicz and Morycowa (1989), and Wells (1956)).

The ITS data significantly deviates from expectations of a clocklike marker beyond the

Eocene, therefore branch lengths beyond this point are likely to be severely

underestimated; nevertheless, the data are superimposed on the geologic record for the

sake of comparison. There are consistencies between the molecular data and the

taxonomic treatments. All authors group Faviidae with Merulinidae; however, there is

disagreement about the timing of the division. Our data is most consistent with Veron

(2000) in this respect. All three authors group Poritidae with either Siderastreidae or

Dendrophyllidae and they place the origin of these families near the same time period

somewhere in the mid to late Cretaceous (100 to 65 million years ago). This is about

1.8 times larger then the distance estimate of our 'mid-point' alignment, which we

acknowledge is likely to be an underestimate.

Species identification in the Porites genus is extremely problematic. Porites is

well renowned for being highly variable, and having convergent morphologic characters.

35

The genus is arguably the single most difficult coral genus to identify at the species level,

and it is in dire need of taxonomic revision. Identifications were made with caution and

consultation to recent taxonomic literature, however we acknowledge the potential for

misidentification as a source of potential error. Digitized and scaled images as well as

skeletal samples are available to interested parties or for future studies.

Within the Porites genus, our findings were generally consistent with previous

studies that have examined Porites in morphological, genetic, and palentological

contexts. Weil (1992), and Weil et al. (1994) examined 11 polymorphic allozyme loci

and morphometrics in several of the same extant Porites species represented in this study.

Weil (1992) found genetic relationships similar to our study. In his study, UPGMA

topology estimated from Roger's modified genetic distances is as follows:

(furcata,divaricata), (panamensis(colonensis,(astreoides, (lobata)))). Our study differs

from this topology, only by grouping panamensis with the furcata-divaricata group

(which is probably related to differences in branch length estimates due to resolution).

Weil's (1992) study also revealed that P. lobata from several populations in Panamá were

more similar to each other then to populations in the Galápagos, although they were not

treated as separate taxa in Weil's analysis. Weil (1992) found high levels of genetic and

morphometric differences between two populations of P. panamensis from Uva and

Saboga Islands in Panamá, and suggested the possibility of the existence of a separate

species. According to our data, P. sverdrupi and P. panamensis are not reciprocally

monophyletic, P. sverdrupi is a well-supported clade nested within the P. panamensis

clade. Some taxonomists note that the species are remarkably similar, and doubt that

36

they are actually separate species (Veron, personal communication.). From these two

observations it seems possible that P. panamensis and sverdrupi are either separate,

sibling species with overlapping ranges, or that they are the same species with large

genetic and morphological differences. Further studies are necessary to distinguish

between these competing hypotheses. Weil (1992) proposed the hypothesis that P.

panamensis and P. colonensis are possible geminate species (resulting from the closure

of the Central American Seaway, 3.5-3.8 million years ago). The rational was based on

extant species ranges on each side of the Isthmus of Panamá (in spite of very large

allozyme differences). This hypothesis is clearly not supported by our data.

The earliest appearance of Porites in the fossil record was in the Eocene in the

Caribbean and the Tethys sea (Veron 2000). Budd et al. (1994) divided the Caribbean

porites into two groups; (1) Porites I, which consists of a primarily mounding colony

morphology, and reproduction by broadcast spawning (P. astreoides is the only extant

member, 6 species underwent extinction between 1 and 4 mya). (2) Porites II, which

consists of a primarily branching colony morphology, and reproduction by brooding

(porites furcata divaricata and colonensis are extant, 4 species underwent extinction

between1 and 4 mya). The Porites I and II groupings appears to be quit consistent with

the ITS data, which indicates that the clades may have some biological significance.

Approximately 3-3.5 million years ago, around 75% of all species in the

Caribbean became extinct (Budd et al. 1996). Shortly after that time, P. divaricata first

appeared in Jamaican formations between 1.6-2.5mya, and in Florida formations between

1.6-1.8mya (Budd et al. 1994). Figure II-9 illustrates the Plio-Pleistocene extinction

37

event and the origin of P. divaricata superimposed on the distance phylogram. The

division between P. astreoides and P. lobata appears to coincide with the complete

closure of the Tethys Sea, which occurred approximately 11-21million years ago. The

hypothesis that this event is responsible for dividing the ancestors to these species would

also coincide with the modern ranges of P. astreoides and P. lobata (both have enormous

geographic ranges; P. astreoides is cosmopolitan in Atlantic, while P. lobata is

cosmopolitan in the Pacific).

Overall, the ITS region data was highly consistent with other molecular markers,

fossil records, and geologic events. The marker differentiated relationships from family,

to species-level and below in the prominent species of Scleractinian coral examined in

this study. The ITS region has been primarily associated with examining relationships

at the genus level and below, however Herzkovitz et al. (1996) found that ITS-2

sequences cluster correctly (relative to an 18S tree) between angiosperms, green algae

and fungi, based on pairwise alignability rather than multiple sequence alignment. They

suggested that the ITS region could be a valuable new paradigm for a wide range of

evolutionary studies. Empirical, theoretical, and simulation studies are necessary to

further explore the properties of the ITS region for use in phylogeny and population

genetics. The marker has the potential to have a very large impact on 'Tree of Life'

research in the near future.

38

Table II-1

Length variation, percent G + C content, number of individuals, number of

sequences, geographic region, collector and date for the ITS-1 and ITS-2 sequences

collected for this study. Abbreviations are as follows: EP, Eastern Pacific; CP, Central

Pacific; ATL, Atlantic; GOM, Gulf of Mexico (Flower Gardens Marine Sanctuary);

GOC, Gulf of California (San Sebastian, and Punta Chivato); WP, Western Pacific; * P.

lobata-Panama was collected from Uva and Saboga Panamá. Collectors and dates are

represented by numbers in superscript: 1 = H. Guzman (01), 2= J. Mate & H. Guzman

(01), 3 = E. Neves (00), 4 =T. Snell (00), 5 = G. Wellington (00), 6=C. Guevara (01),

7=B. Victor (01), 8 = G. Wellington (99), 9 = M. Takabayashi (98), 10 = Z. Forsman

(98). Samples in bold letters indicate that a skeletal voucher specimen was collected.

The 5.8S gene had few polymorphisms, and a nearly constant length of 106-107nt, and a

51% G+C content.

39

Table I

ITS-1 ITS-2 length length No of No of species region (bp) %(G+C) SE (bp) %(G+C) SE individuals sequencesS. siderea Panamá (ATL)2 305 44.22 0.35 192-193 53.41 0.58 3 14 S. radians Panamá (ATL)2 307 43.65 0.12 192 55.70 0.24 2 6 S. stellata Brazil (ATL)3 307-308 44.43 0.12 192 55.60 0.35 1 3 P. astreoides Texas (GOM)4 304 42.40 0.00 234 43.47 0.23 1 3 " " Belize (ATL)5 304 42.30 0.17 231-234 43.53 0.21 1 3 " " Brazil (ATL)3 304-305 42.16 0.55 231-236 44.41 0.72 3 7 " " Panamá (ATL)6 304 41.87 0.40 231-233 44.63 0.40 2 3 P. divaricata Belize (ATL)5 298-300 41.17 0.24 223-228 45.16 0.57 3 7 P. furcata Panamá (ATL)6 300 41.70 0.00 227-230 44.97 0.57 1 3 P. sverdrupi Mexico (GOC)7 317-318 43.23 0.21 229-230 48.37 0.26 3 7 P. panamensis Panamá (EP)1 317-318 43.67 0.45 233-236 49.30 0.10 1 3 P. rus Tahiti (CP)7 310 42.20 0.00 224 44.20 0.00 1 3 P. colonensis Panamá (ATL)2 286 43.00 0.00 248-249 44.15 0.10 2 4 P. lobata-Panama* Panamá* (EP)8 303-311 43.27 0.19 228-229 44.91 0.23 4 7 P. lobata Easter Isl.(CP)8 303-312 42.02 0.47 215-226 43.89 0.22 4 10 " " Australia (WP)9 305-325 42.17 0.43 210-223 43.91 0.75 2 7 " " Rarotonga (WP)8 306-309 42.27 0.26 207-226 44.16 0.45 3 9 " " Tahiti (CP)8 306-309 41.96 0.43 207-231 43.89 0.43 3 9 " " Galápagos (EP )10 306-307 42.29 0.34 209-225 44.04 0.49 4 15 " " Fiji (CP)8 305-309 41.91 0.41 215-223 43.81 0.83 3 7 Total 47 130

40

Table II-2

Matrix of averaged genetic distance between species (in substitutions per site,

calculated by the Kimura 1980 method), and standard errors. The first column

represents average intra-species differences. Distances were calculated including the

entire ITS region (ITS-1, 5.8S, and ITS-2). Standard errors were estimated by 500

bootstrap replicates implemented in MEGA 2.1 (Kumar et al. 2001). Inter-species

distance was calculated from an alignment (GOP=0.2, GEP=0.1) that included all 130

sequences.

41

Table II-2

species Intra-species S. siderea S. radians S. stellata P. astreoides P. divaricata P. furcata P. sverdrupi P. panamensisP. rus P. colonensis P. lobata- Panama

S. siderea 0.008 ±0.002 S. radians 0.001 ±0.001 0.034 ±0.007 S. stellata 0.002 ±0.002 0.035 ±0.007 0.005 ±0.003 P. astreoides 0.011 ±0.002 0.280 ±0.024 0.295 ±0.025 0.297 ±0.025 P. divaricata 0.003 ±0.001 0.311 ±0.026 0.319 ±0.027 0.322 ±0.027 0.202 ±0.019 P. furcata 0.006 ±0.002 0.317 ±0.026 0.326 ±0.027 0.329 ±0.027 0.207 ±0.020 0.013 ±0.004 P. sverdrupi 0.005 ±0.002 0.351 ±0.028 0.355 ±0.028 0.358 ±0.028 0.215 ±0.021 0.133 ±0.014 0.134 ±0.014 P. panamensis0.004 ±0.002 0.361 ±0.028 0.365 ±0.029 0.367 ±0.029 0.219 ±0.021 0.145 ±0.014 0.147 ±0.015 0.011 ±0.003 P. rus 0.001 ±0.001 0.272 ±0.023 0.282 ±0.024 0.284 ±0.024 0.104 ±0.013 0.219 ±0.020 0.215 ±0.020 0.209 ±0.020 0.215 ±0.020 P. colonensis 0.002 ±0.001 0.336 ±0.026 0.346 ±0.027 0.349 ±0.027 0.223 ±0.020 0.190 ±0.018 0.197 ±0.018 0.154 ±0.017 0.163 ±0.017 0.212±0.020 P. lobata-Panama 0.003 ±0.001 0.274 ±0.024 0.281 ±0.024 0.283 ±0.025 0.093 ±0.012 0.210 ±0.020 0.206 ±0.020 0.209 ±0.020 0.215 ±0.021 0.022±0.005 0.223±0.021 P. lobata 0.012 ±0.002 0.270 ±0.024 0.280 ±0.024 0.282 ±0.024 0.094 ±0.012 0.203 ±0.019 0.197 ±0.019 0.202 ±0.020 0.208 ±0.020 0.066±0.010 0.202±0.020 0.062 ±0.009

42

Figure II-1 A summary of the pair-wise comparisons between molecular clones at several

hierarchical levels. A.) The level of differences at the intra-individual, intra-population

and inter-population levels. B.) Inter-species differences were more than an order of

magnitude larger than Inter-population differences. C.) Table of sample sizes, means,

and standard errors for the comparisons.

43

Figure II-1

Number of species

Number of individuals

Molecular clones

Mean Standard error

N n Intragenomic 10 33 125 0.005579 0.004979 Intrapopulation 6 34 90 0.009486 0.005053 Interpopulation 2 21 64 0.011817 0.004501

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

1

per s

ite n

ucle

otid

e di

ffere

nce

intra-individual intra-regional intra-species

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

1

per s

ite n

ucle

otid

e di

ffere

nce

intra-species inter-species

A.

B.

C.

Intragenomic Intrapopulation Interpopulation

Interpopulation Interspecies

44

Figure II-2

Histograms of Pair-wise comparisons of molecular clones at several hierarchical

levels. A.) Intragenomic comparisons approximate a highly skewed distribution,

whereas B.) intrapopulation and C.) interpopulation comparisons are approximately

normally distributed.

45

Figure II-2

0.00 0.01 0.02 0.030

10

20

30

40

50

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

P

B

0.00 0.01 0.02 0.03g

0

50

100

150

200

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.00 0.01 0.02 0.030

10

20

30

40

50

60

70

0.0

0.1

0.2

0.3

0.4

A.

B.

C.

count

Proportion/bar

46

Figure II-3

The effects of gap opening and gap extension penalties on alignment length. A.)

Each line represents a gap opening penalty 0.1, 1, 2, 4, 8. Gap extension penalty is in log

scale. The asterisk represents the default value in ClustalW (Thomson et al. 1994),

GOP=10, GEP=5 B.) The gap opening and extension penalties were averaged, to

illustrate the effects of the average penalty on overall sequence alignment length.

47

Figure II-3

720740760780800820840860880

0.01 0.1 1 10Gap extension penalty

Alig

men

t Len

gth

0.1124810

R2 = 0.9032

700

750

800

850

900

0 2 4 6Average penalty

Alig

nmen

t Len

gth

A.

B.

GOP

r2 = 0.903

48

Figure II-4

Majority rule consensus cladograms of the permuted alignments. Each

alignment was generated by systematically altering alignment parameters as illustrated in

Figure II-3. A maximum likelihood tree was then estimated for each alignment. For

each set of 25 alignments, majority-rule and strict consensus trees were constructed.

The values at each node are not nonparametric bootstrap proportions; rather they

represent the percentage of alignments that yielded the same node (out of 25 alignments

for each analysis). Abbreviations after the species name are as follows; for P. lobata, A

= Australia, G = Galápagos, for P. astreoides, B=Belize, Z=Brazil, for S. siderea, A and

B represent two distinct clades (discussed in further detail in Chapter IV). For other

collection information, see Table II-1. A). Alignment consensus cladogram for the

Porites taxa. B). Consensus cladogram of the 25 permuted alignments for Porites and

outgroup taxa.

49

Figure II-4

Consensus tree of the 25 permuted Porites alignments.

P. divaricata

P. furcata

P. panamensis

P. sverdrupi

P. lobata A

P. lobata G

P. rus

P. lobata-panama

P. astreoides B

P. astreoides Z

P. colonensis

100

100

100

72

100

100

100

100

Scapophyllia

P. colonensis

P. panamensis

P. sverdrupi

P. furcata

P. divaricata

P. lobata A

P. lobata G

P. lobata-panama

P. rus

P. astreoides B

P. astreoides Z

S. siderea A

S. siderea B

S. radians

S. stellata

Tubastrea

Balanophyllia

Montastrea

100

100

100

100

100

100

96

92

72

92

100

100

100

100

72

100

Consensus tree of the 25 permuted Porites and outgroup alignments.

A.

B.

50

Figure II-5 The maximum likelihood phylograms for the 'low' and 'high' gap penalty

alignments. The 'low penalty' phylogram has thick gray branches and is superimposed

underneath the 'high penalty' phylogram. The scale bar for each tree corresponds to 2%

divergence. The entire ITS region was used. (A). Maximum likelihood phylogram

with the molecular clock enforced. (B). Unrooted Maximum likelihood phylograms

with the molecular clock assumption relaxed.

51

Figure II-5

sg1-1

ss2-2

stBR8-3

sr7-1

col3-1

pB4-7

fP1-5

pan75-2

BJ7-3

aP10-2

aB6-6

G3-8

FJ4-2

rus1-8

PP19-6

Montastrae

Scapophyll

Balanophyl

Tubastraea

0.02

sg1-1

ss2-2

stBR8-3

sr7-1

col3-1

pB4-7

fP1-5

pan75-2

BJ7-3

aP10-2

aB6-6

G3-8

FJ4-2

rus1-8

PP19-6

Montastrae

Scapophyll

Balanophyl

Tubastraea

0.02

Porites

Siderastrea

B.

A.

Dendrophylliidae

Faviina

Scapophyll

col3-1

pan75-2BJ7-3

fP1

-5 pB4-7

FJ4-2

G3-8

PP

19-6

rus1

-8

aP10-2

aB6-6

ss

2- 2

sg1-1

sr7-1stBR

8-3

TubastraeaBalanophyl

Montastrae

0.05

Scapophyll

col3-1

pan75-2

BJ7-3

fP1

-5

pB4-7

FJ4-

2

G3-8

PP19-6

rus1

-8

aP10-2

aB6-6

ss2-

2

sg1-1

sr7-1stBR

8-3

Tu

ba

str

ae

a

Bala

noph

yl

Montastrae

0.05

Porites

Siderastrea

Dendrophylliidae

Dendrophylliidae

Faviina

52

Figure II-6

Maximum likelihood condensed topology of the 'reduced alignment' (all sites with

insertions or deletions have been removed from the alignment). The cut off value for the

condensed topology was 60%. Values at the nodes represent values from 500 bootstrap

replicates.

53

Figure II-6

Scapophyllia

S. siderea B

S. siderea A

S. radians

S. stellata

P. divaricata

P. furcata

P. sverdrupi

P. panamensis

P. rus

P. lobata-panama

P. lobata G

P. lobata A

P. colonensis

P. astreoides Z

P. astreoides B

Tubastrea

Balanophyllia

Montastrea

99

94

87

76

100

72

99

86 91

100

54

Figure II-7 The effects of alignment parameter permutation on the ratio of transitions to

transversions. For each graph, transitions and transversions are plotted against Kimura's

(1980) estimate of genetic distance. Transitions are represented by an x, transversions

are represented by a triangle. Dashed lines on each graph represent the overall

transition or transversion mean. The Gap Opening Penalty (GOP) and Gap Extension

Penalty (GEP) values for the permuted alignments are listed below each graph. Figure

(A). is at the 'low' end of the Gap penalty spectrum, ts:tv ratio is high and rapidly

increases with distance. Figure (B). is the 'mid-point' alignment of the gap penalty

spectrum, ts:tv radio is 1.32. Figure (C). is the 'high' end of the spectrum of Gap

penalties, transversions outnumber transitions. Figure (D). is an alignment of the

complete ITS region for Siderastrea taxa only, this alignment has no ambiguities.

Figure (E). is an alignment of the complete 5.8S gene only (ITS 1 and 2 excluded).

Note the similarity in slope and ts:tv ratio between alignments with no ambiguities

(Figure D. and E.), and the mid-point alignment (Figure B.).

55

Figure II-7

B.) GOP 2.0, GEP 1.0 Ts/Tv =1.31A.) GOP=0.01, GEP=0.01 Ts/Tv = 3.38 C.) GOP= 8.0, GEP=4.0 Ts/Tv =0.87

D.) Siderastrea species Ts/Tv 1.72 E.) 5.8S only Ts/Tv= 1.32

56

Figure II-8

The relationship between gap distance and substitution distance between the

permuted alignments. GOP and GEP refer to Gap Opening Penalty and Gap Extension

Penalty. The slope of the line indicates that the alignment with largest gap penalties

(GOP=8.0, GEP=4.0) had approximately 2 substitutions for every alignment gap, the

mid-point alignment (GOP=2.0, GEP=1.0) had 1 substitution for every 1 gap, and the

alignment with lowest gap penalties (GOP=0.01, GEP=0.01) resulted in 0.71

substitutions for every gap. The r2 and p value indicate that the regressions are highly

significant.

57

y = 0.71x + 0.01R2 = 0.84p<0.001

y = 1.14x + 0.02R2 = 0.75p<0.001

y = 1.9x + 0.04R2 = 0.67p<0.001

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4Gap Distance

Subs

titut

ion

Dis

tanc

e (p

)

O 8.0,E 4.0

O 2.0,E 1.0

O .01,E .01

GOP=8.0GEP=4.0

GOP=2.0GEP=1.0

GOP=0.01GEP=0.01 r2

r2

r2

Figure II-8

58

Figure II-9 The 'Mid-point' alignment (GOP=2.0, GEP=1.0), maximum parsimony and

maximum likelihood consensus tree. Abbreviations are as in Figure II-4. Values at the

nodes are bootstrap values (500 replicates); regular script indicates maximum parsimony,

italic script indicates maximum likelihood, and bold script indicates support by both

methods. The alignment had 278 sites that were parsimony informative sites (gaps were

counted as a fifth character state, although if gaps were ignored the same topology

resulted), a heuristic branch and bound search yielded two parsimonious trees, CI=0.77,

RI=0.83. The topology was identical in both methods, with the exception of the node

indicated with an asterisk*. Balanophyllia-Tubastraea were grouped with Siderastrea

in the maximum likelihood topology.

59

Figure II-9

P. rus

P. lobata-panama

P. lobata G

P. lobata A

P. astreoides B

P. astreoides Z

P. colonensis

P. divaricata

P. furcata

P. sverdrupi

P. panamensis

Balanophyllia

Tubastrea

S. stellata

S. radians

S. siderea A

S. siderea B

Montastrea

Scapophyllia

100

10099

10067

5074

100

100 100

100

100

100 73*

100

100

10098

100

10094

60

Figure II-10 A Neighbor-Joining phylogram of all of the sequences collected for this

study (130) and from the database (4), of an alignment constructed using the 'mid-point'

alignment gap penalties. Positions with insertions/deletions were included in the

analysis, the 5.8S gene was invariant among Porites taxa and was therefore excluded,

leaving 981 remaining positions. Distances were calculated with the Kimura (1980)

method, with 1000 bootstrapped replicates in Mega 2.1 (Kumar et al. 2001), bootstrap

values less then 70% are not shown. The width of each triangle base is proportional to

the number of sequences in the clade (approximately 4 pixels/taxon). The height (depth

in time) of the triangle is proportional the variability within the group. The scale is

proportional to number of nucleotide substitutions per site, and estimated time of

divergence assuming a constant rate of 0.004 substitutions per site per million years

(Savard et al. 19993). The large shaded rectangle indicates an area where distance is

likely to be underestimated, Felsenstein's (1988) molecular clock hypothesis can be

rejected for the 'outgroup' taxa. The relationship between substitutions and time do not

significantly deviate from expectations of linearity For the 'ingroup' taxa. A light gray

rectangle represents a period of mass extinction (1-4 mya), dark gray lines indicate

important dates: 3.5-3.8 mya = complete closure of the Isthmus of Panamá (Kegwin

1982) , 1.6-2.5 mya = the first appearance of P. divaricata in the fossil record (Budd et

al. 1994).

61

Figure II-10

Late Cretaceous

Palaeocene

Eocene

Oligocene

Miocene

Pleistocene

P. lobata

P. lobata-panama P. rus

P. astreoides

P. panamensis-sverdrupi

P. furcata P. divaricata

P. colonensis Balanophyllia Tubastrea S. radians S. stellata

S.siderea

Montastrea Scapophyllia

99

99

86

7699

85

99

99

83

75

9999

9999

99

91

9994

83

99

0.00.10.2 0.3 percent divergence

05101520253035404550 55 60 65 70 75 MY

Pliocene

62

Figure II-11

The 'Mid-point' alignment GOP=2.0, GEP=1.0, of the representative sequences

used for examing alignment parameters. Gaps are shaded gray, the relative positions of

the 18S, ITS-1, 5.8S, ITS-2, and 28S are indicated below the alignment.

63

18S 3' end ITS-1 5' begin

Figure II-11

64

Figure II-11 continued

ITS-1 3' end 5.8S 5' begin

5.8S 3' end ITS-2 5' begin

65

Figure II-11 continued

ITS-2 3' end 28S 5' begin

66

Figure II-12

An illustration of several taxonomists (past and present) synthesis of the

Scleractinian fossil record. Abbreviations are as follows: P= Poritidae, D=

Dendrophylliidae, S=Siderastreidae, F=Faviidae, and M=Merulinidae. Bold lines

indicate the depth of the family fossil record; dashed lines represent inferred relationships

with extinct or living families. Brackets indicate that the author placed the taxa in

close proximity. Shaded gray rectangles mark periods of mass extinction and species

turnover in the fossil record. The geologic periods are not drawn to scale. The ITS

data significantly deviates from expectations of a molecular clock at the genus and family

level, and is likely to underestimate divergence times. The data is displayed for the sake

of comparison.

67

Palaeocene

Eocene

Oligocene

Miocene

Late Jurassic

Mid Jurassic

Early Jurassic

Late Triassic

Early Cretaceous

mid Cretaceous

late Cretaceous

(P D ) (M, F) (S)

Veron 2000, 1996

(P ( D, S ) (M, F) (P , S ) (M, F) (D) (P , S ) (M, F) (D)

Wells 1956 Roniewicz and Morycowa (1989)

ITS Region

Figure II -12

68

LITERATURE CITED Arlorio, M., Coisson, J. D. and Martelli, A. (1999). Identification of Saccharomyces cerevisiae in bakery products by PCR amplification of the ITS region of ribosomal DNA. European Food Research and Technology 209, 185-191. Arnheim, N. M., Krystal, M., Shmickel, R., Wilson, G., Ryder, O. and Zimmer, E. (1980). Molecular evidence for genetic exchanges among ribosomal genes on nonhomologous chromosomes in man and apes. Proc. Natl. Acad. Sci. USA 77, 7323-7327. Bakker, F. T., Olsen, J. L. and Stam, S. T. (1995). Evolution of nuclear rDNA ITS sequences in the Caldophora albida/sericiea Clade (Chlorophyta). J Mol Evol 40, 640-651. Baldwin, B. G., Sanderson, M. J., Porter, J. M., Wojciechowski, M. F., Campbel, C. S. and Donoghue, M. J. (1995). The ITS region of nuclear ribosomal DNA - A valuable source of evidence on angiosperm phylogeny. Annuals of the missouri Botanical Garden 82, 247-277. Beauchamp, K. A. and Powers, D. A. (1996). Sequence variation of the first internal spacer (ITS-1) of ribosomal DNA in ahermatypic corals from California. Mol. Mar. Biol. Biotechnol. 5, 357-62. Budd, A. F., Stemann, T. A. and Johnson, K. G. (1994). Stratigraphic Distributions of Genera and Species of Neogene to Recent Caribbean Reef Corals. J. Paleont 68, 951-977. Chen, C. A. and Miller, D. J. (1996). Analysis of ribosomal ITS1 sequences indicates a deep divergence between Rhodactis (Cnidaria: Anthozoa: Corallimorpharia) species from the Caribbean and the Indo-Pacific/Red Sea. Marine Biology , 423-432. Chen, C. A., Odorico, D. M., ten Lohuis, M., Veron, J. E. and Miller, D. J. (1995). Systematic relationships within the Anthozoa (Cnidaria: Anthozoa) using the 5'-end of the 28S rDNA. Mol Phylogenet Evol 4, 175-83. Coleman, A. W., Mai J. C. (1997). Ribosomal DNA ITS-1 and ITS-2 sequence comparisons as a tool for predicting genetic relatedness. J Mol Evol 45, 168-77. Diekmann, O. E., Bak, R. P. M., Stam, W. T. and Olsen, J. L. (2001). Molecular genetic evidence for probable reticulate speciation in the coral genus Madracis from a Caribbean fringing reef slope. Marine Biology 139, 221-233.

69

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III. Phylogeography and Morphological Variation in Porites lobata Across the Pacific: A Cryptic Panamanian species and Isolation Consistent with Ocean Currents.

ABSTRACT Gradual morphologic differences occur between geographic regions in the coral

species P. lobata. This has led to considerable taxonomic controversy; some authors contend that each distinct morphology represents a genetically distinct entity; others suggest that each form is the result of a phenotypic response to environmental conditions. An alternative hypothesis is that genetic and phenotypic cohesiveness are directly related, and maintained by ocean surface currents. Here we examine genetic variability of the ITS region in P. lobata from Panamá, Galápagos, Easter island, Tahiti, Fiji, Rarotonga and Australia. We examine morphometric variability in a subset of these populations (Panamá, Galápagos, Easter Island, Tahiti, and Fiji).

We report a putative cryptic species of P. lobata in Panamá. The species is reciprocally monophyletic according to the ITS region, and morphologically distinct according to a principal component discriminant analysis of corallite level characteristics, which allows 95% of all corallites to be classified as distinct from P. lobata. We designate this putative new species P. lobata-panama. Across the rest of the range of P. lobata, the discriminant analysis indicates that that a large portion of the variance is due to differences between regions, with small differences occurring between neighboring regions, and the largest differences occurring between geographic extremes. An AMOVA (Molecular Analysis of Variance) indicates that a significant portion of the genetic variance is due to differences between populations. Easter Island is the most isolated population, and is the most genetically and morphometrically distinct. A Nested Clade Analysis of the ITS region haplotypes rejects the null hypothesis of no association between phylogenetic and geographic structure. Isolation by distance exists for at least two separate clades that contain the Easter Island haplotypes. The relationships between many of the morphologic traits are significantly correlated to genetic relationships according to Mantel tests of the distance matricies. Gradual genetic and morphometric variation between the geographic regions are consistent with the expectations of recurrent gene flow and isolation by distance. The genetic and morphometric relationships between geographic regions are consistent with observations of Pacific Ocean surface currents derived from satellite data.

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INTRODUCTION

The genus Porites (Link 1807) has been one of the most important, widespread

and abundant reef-building corals over the last 20 million years (Frost 1977). Porites

occurs worldwide in the tropics. Porites species have some of the highest dispersal

potentials (Faldallah 1983) and largest geographic ranges (Veron 1995, 2000). Despite

the importance of Porites in coral reef ecosystems, relationships between species, or

between populations remain largely unknown. Progress in Porites systematics has been

slow because it is difficult to determine what constitutes a 'species' within this genus.

Taxonomy in Porites is based on morphological and skeletal architecture and is

renowned as among the most difficult and in the most need of revision. In Porites,

corallites are very small, irregular, perforated and highly variable. Variability in colony

and corallite level skeletal characteristics is typified in the most cosmopolitan Porites

species P. lobata (Dana 1846). P. lobata occurs in a wide variety of habitats over an

enormous geographic range, spanning across the Pacific and Indian oceans. Colony and

corallite level characteristics have been observed to vary geographically, which has led to

numerous synonyms, and named 'formae' and 'subformae' (Bernard, 1902; Vaughan,

1907; Veron and Pichon, 1982; Veron 1995, 2000). Colony form ranges from

encrusting, plate-like or bolder-like forms, to thin protruding lobe, fin or columner

morphology. Some authors have maintained that these morphological differences are

the result of a phenotypically plastic response to environmental conditions (available

light, water motion, predation, etc.), while others suggest that the variation reflects

isolation between genetically distinct populations, or even separate species.

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It is generally difficult to define coral species for several reasons: (i).

Convergent evolution: morphological characters in Porites are often nearly as variable

within an individual as between species. Morphologically indistinguishable species

could be closely related "sibling species", or more distantly related "cryptic species"

(after Knowlton 1993). (ii). Phenotypic plasticity: some species are broadly adapted to

a wide range of habitats, and exhibit different ecomorphs in response to different

environmental conditions (Veron 1995). (iii). Hybridization and reticulate evolution:

Mass spawning produces opportunities for hybridization between species because many

corals spawn simultaneously. Some corals are long-lived at the colony level (hundreds

of years or more), and geographically widespread. Changes in ocean circulation may

introduce genetically and morphologically disparate populations, or create opportunities

for hybridization between species vis-à-vis Veron's (1995) theory of reticulate evolution

by sea surface vicariance.

The goal of this study is to characterize the genetic relationships between P.

lobata populations collected across a wide geographic range (Panamá, the Galápagos,

Easter Island, Tahiti, Rarotonga, Fiji, and Australia’s Great Barrier Reef). Genetic

relationships were examined with a molecular analysis of variance (AMOVA), which

allows the rejection of the null hypothesis of panmixia, by simulating a null distribution

by permutation of haplotypes (Excoffier, et al. 1992; Weir, 1996). The approach

calculates statistics that partition the covariance between and within groups. The

relationships were further examined with a Nested Clade Analysis (NCA), which

explicitly tests the null hypothesis of no association between geography and phylogenetic

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structure (Templeton 2001). This approach makes use of information contained in

haplotype networks to distinguish between historical population events (such as

fragmentation, long distance colonization, or range expansion), and population structure

(such as low recurrent gene flow due to isolation by distance). The approach has the

additional advantage that the inferences are guided by explicit and objective criteria that

can also indicate a lack of statistical power from inadequate sampling.

A secondary goal of this study is to determine the morphometric relationships

between regions, and to determine if they are similar to the genetic relationships.

Previously (Chapter II), it was discovered that the individuals from Panamá are

genetically distinct from the specimens collected from all other regions. A principal

component discriminant analysis of skeletal measurements was employed to determine if

the Panamá specimens are morphometrically distinct, and to examine the morphometric

relationships between geographic regions. The genetic and morphological relationships

between geographic regions were then examined in the context of satellite data on

prevailing ocean surface currents.

METHODS Genetic analysis

Small, fragments, ca. 10-15 grams of tissue and skeleton were removed from colony

edges, or protuberances. In Rarotonga and Australia populations, small tissue samples

were collected without skeletal vouchers. Samples were collected at least 10 meters

apart to avoid collecting colonies that originated from clonal propagation or

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fragmentation. Samples were preserved in 95-100% ethanol. The samples were

divided into several pieces when returned the laboratory, a small piece was stored in fresh

ethanol at -20°C for genetic analysis, and larger pieces were placed in bleach to dissolve

the soft tissue, prior to drying. Voucher specimens, and scaled digital microscope

images were collected for the majority of specimens and are available upon request.

Table III-1 summarizes the geographic location of the samples collected, the collector

and the date of collection. DNA extraction, PCR, cloning and sequencing are described

in detail in Chapter II. Each sequence of the entire ITS region (ITS-1, 5.8S, ITS-2), was

sequenced in two directions, which allowed for complimentary strand conformation of

the accuracy of each sequence. At least three individuals were genetically sampled from

Panamá, Galápagos, Easter Island, Tahiti, and Fiji. At least 3 molecular clones were

sequenced from most colonies. Sequence alignment was performed in ClustalW

(Thompson et al. 1994) a gap opening penalty [GOP] of 2, and a gap extension penalty

[GEP] of 1, was selected (see Chapter II for more details on sequence alignment).

There were few alignment gaps, and very few positions were ambiguous.

A cladogram was constructed for all 64 sequences using the Neighbor-Joining (Saitou

and Nei 1987) method Figure III-1. Genetic distances were calculated using Kimura's

(1980) two-parameter model. The tree was bootstrapped 1000 replicates, implemented

in MEGA 2.1 (Kumar et al. 2001). The cladogram is intended to indicate relative

similarity between sequences, and not intended as a phylogeny; many of the assumptions

of phylogenetic methods are violated by population level processes. Similarly,

Maximum Likelihood and Parsimony methods implemented in PHYLIP version 3.6

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(Felsenstein 2002), and MEGA 2.1 (Kumar et al. 2001) yielded no clear and consistent

population level relationships. Sequences were grouped according to region, and

average distance within and between regions was calculated separately for the ITS-1 and

ITS-2 region (Table III-2) in MEGA 2.0 (Kumar et al. 2001).

A molecular analysis of variance (AMOVA) was conducted in Arliquin v 2.0

(Schneider et al. 2000), with a transition transversion weight of 2:1 and a gap weight of

one (alternative weighing schemes did not significantly alter the outcome). Distances

were calculated with the Kimura (1980) model, and a 0.2 gamma shape parameter (the

shape parameter was estimated in PHYML v 1.0 (Guindon and Gascuel 2002), by the

maximum likelihood method implemented in the program. A separate AMOVA was

performed on the entire data set (including all molecular clones), and then on separate

subsets of one molecular clone per individual, in order to determine if the analysis was

sensitive to differences in sample size between populations. Each subset reflected

highly significant genetic structure between geographic regions (Table III-4).

Significance tests were carried out with 1000 permutations to generate a null distribution

under the assumption of no genetic structure (Excoffier, et al. 1992; Weir, 1996). Fst

statistics were calculated in Arliquin v 2.0 (Schneider et al. 2000), and tested for

significance by 1000 permutations.

A nested clade analysis (NCA) was performed on a subset of the sequences following

the methods outlined in Templeton et al. (1987), and Templeton and Sing (1993). A

haplotype network of the 95% most probable connections was estimated using the

statistical parsimony method, implemented in the computer program TCS v.1.13

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(Clement et al. 2000). The entire ITS region, and the ITS-1 region alone, contained a

large number of complex reticulations in the haplotype network. Analysis of the ITS-2

resulted in a single network, with no reticulations, which suggests that the levels of

recombination and homoplasy for this data set are relatively low and suitable for the

NCA procedure. Several nearly identical sequences from the same individual have the

potential to severely bias the NCA procedure; therefore, haplotypes from the same

individual that were identical or nearly identical (separated by less than 3 substitutions)

were excluded from the analysis. This resulted in several individual specimens that

contained two disparate haplotypes. The disparate haplotypes did not cluster together,

and therefore should not bias the analysis. The intragenomic variability was quite low,

and many specimens were represented by a single haplotype (see Table III-2 and Figure

III-1). The haplotype network was nested according to rules described in Templeton et

al. (1987), and Templeton and Sing (1993); The procedure joins haplotypes separated by

one mutational event into 1-step clades proceeding from the exterior to the interior of the

network, all 1-step clades separated by one mutational event are then joined into 2-step

clades, and so on, until the entire cladogram is nested in to a single clade (see Figure III-

3). NCA was performed in Geodis v 2.0 (Posada et al. 2000), and the results were

interpreted from the inference key provided with the program.

The geographic distances entered in Geodis, were in the form of a distance matrix of

all possible pairwise distances (in kilometers) between regions, which was estimated by

finding latitude and longitude (accurate only to degrees and minutes) from the Getty

Thesaurus of geographical names online; http://www.getty.edu/. The distances in

82

kilometers between each population were estimated by calculating the great circle

distance between pairs of latitude/longitude co-ordinates using the Lat-Long Converter at

http://www.wcrl.ars.usda.gov/cec/java/lat-long.htm. The GeoDis program calculates

exact permutational contingency tests on two statistics Dc and Dn at each hierarchical

nested level. Dc is a measure of the geographic distribution of a clade, and Dn measures

how widespread a nested clade is relative to other clades in the same nested category,

distances between interior and tip clades (I-T) distances are also calculated (Posada et al.

2000, Templeton et al. 2001). An inference key is provided with the program, with

explicit criteria that allow objective, consistent interpretations of the results, based on

expectations of coalescent theory and computer simulations (Posada et al. 2000,

Templeton et al. 2001). The inference key can also indicate if the sampling design or

the sample size is inadequate to draw conclusions.

Morphometric analysis

For each skeletal voucher, at least 3 Digital images were captured at 18X

magnification using a dissecting microscope attached to a digital CCD videocamera, and

a digital frame-capturing device (ATI all-in-wonder card, ATI technologies Inc.). A

monofilament line of known thickness (0.16mm) was used as a reference for scaling each

image. The images were scaled, and measured using the program Scion Image (Scion

Corporation 2000). Ten corallites for each individual with a voucher specimen (listed in

Table III-1) were measured. The definitions of taxonomic characters are based on Veron

2000, Weil 1992, Weil et al. 1992)

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For each corallite, a series of 29 X-Y point coordinates were digitized according to

prominent skeletal landmarks related to septal length and relative position depicted in

Figure III-5. The distance between any of the landmark coordinates could then be

calculated. For each corallite, the following traits were measured; 41 linear

measurements between selected point coordinates (Table III-5 and Figure III-5), 2 area

measurements (fossa and corallite area), and 3 discrete variables; number of Pali, number

of radi, and ventral triplet margins fused, free, or tridented. Nine measurements were

proportions of several linear measurements, and four were averages.

A forward stepwise discriminate analysis was implemented in Systat v.9 1998 (SPSS

inc.) All variables in Table III-5 were selected initially, and automatic forward stepping

with default options was selected. The aim of the discriminate analysis is to find a

linear combination of morphometric measurements that best discriminates between user-

defined groups.

In order to examine the relationship between morphology and genetic distance

between populations, distance matrices of averaged genetic distance and average

morphological distance were compared using the Mantel test, implemented in Arliquin v

2.0 (Schneider et al. 2000). The significance tests of linear regressions of distance

matrices are not reliable due to violations of assumptions of independence between data-

points. The Mantel test allows for autocorrelation within a matrix and tests for

significant correlations between matrices by a permutation procedure (Mantel, 1967;

Smouse et al. 1986).

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RESULTS

Table III-1 indicates the sample size, collector, date and nucleic acid properties of the

ITS region. Table III-2 indicates the pairwise average genetic distances between

populations. The four individual specimens collected from Panamá, originally

identified as Porites lobata were genetically distinct from the 19 specimens collected

across a wide geographic range (Galápagos, Easter Island, Tahiti, Fiji, Rarotonga and

Australia). The Panamá specimens are reciprocally monophyletic under distance,

parsimony and likelihood methods (Chapter II), and will hereafter be referred to as P.

lobata-panama. The maximum difference between the 57 sequences collected from P.

lobata individuals across a broad geographic range differed by only 1.85%. The seven

P. lobata-panama sequences differed from P. lobata by between 6.03% and 6.63%.

The ITS-2 on average differed more between P. lobata populations than the ITS-1;

however, the ITS-1 was more variable between species (Table III-2, and Figure III-2).

Figure III-2 is a Neighbor-Joining distance cladogram that graphically illustrates the

average differences between geographic regions in the ITS-1 and ITS-2. Most regions

have similar branch lengths; however, Easter Island has longer branch lengths when the

entire ITS region, or only the ITS-2 is considered. Fiji has longer branch lengths when

only the ITS-1 is considered (Figure III-2B). Figure III-1 is a Neighbor-Joining

cladogram between all molecular clones used in this study (intended to show distance

relationships, not as a phylogeny). The majority of molecular clones from the same

specimen were very similar, and clustering most often occurred between sequences from

the same individual. Distance, maximum likelihood and parsimony methods are

85

inconsistent on the proximal placement of Easter Island individuals, and no clear and

consistent geographic patterns are readily apparent (Figure III-1).

In order to determine if any geographic structure between the populations is present, a

molecular analysis of variance (AMOVA) was performed (Excoffier et al. 1992; Weir,

1996). The AMOVA indicates that differences between geographic regions are highly

significant (Table III-4). When all sequences are included, nearly 20% of the variance

is attributed to differences between geographic regions (p <0.0001), and 80% is due to

variance within populations. Highly significant geographic structure between

geographic regions was also evident when one sequence was chosen per individual

(repeated multiple times with alternative molecular clones), or when all Easter Island

sequences were excluded from the analysis (Table III-4). This indicates that the

significant geographic structure is not solely due to the most genetically distant group

(Easter Island), or to problems associated with sampling unequal numbers of sequences

per individual per region. The calculation of Fst statistics confirms the indication by the

averaged distance data that Easter Island is the most genetically distinct geographic

region. Easter Island has the highest and most significant differences according to the

permutation analysis (Table III-3 B).

Phylogeographic Nested clade analysis (Figure III-3 and Table III-4) indicates

that the null hypothesis of no association between phylogenetic structure and geographic

structure can be rejected for two clades; Clade 3-1 and Clade 3-3. An exact contingency

tests of the next highest clade, is highly significant for clade 4-1 (of which 3-1 is a

member); p < 0.01, and clade 4-2 is significant (of which 3-3 is a member); p < 0.05 (see

86

Table III-4). The inference key for NCA (Templeton 1998, Posada et al. 2000)

indicates that the expectations of restricted recurrent gene flow and isolation by distance

are met for both clade 3-1 and 3-3. All sequences from the most geographically isolated

population (Easter Island) are contained in the two significant clades. Clade 3-1

contains sequences from Easter Island and Rarotonga, and Clade 3-3 contains individuals

from Easter Island and the Galápagos. Rarotonga and the Galápagos are the two most

likely candidate source populations for Easter Island, as implied by the ocean surface

current vectors generated from satellite data (Figure III-4 B & C). The satellite data also

indicates a strong unidirectional current flowing west and slightly southwest from the

Galápagos to the south central populations. The current vectors connect the populations

in a way that appears similar to the averaged genetic similarity between populations.

The haplotype network (Figure III-3) indicates that haplotypes are most frequently shared

between the Galápagos and Tahiti followed by Rarotonga.

Morphometric analysis

Corallites generally appear to vary by region, as illustrated in Figure III-6. The

majority of traits measured (Table III-5) exhibited significant differences among

geographic regions. According to a model one ANOVA, and paired comparisons with

Tukey's HSD correction, nearly all measurements showed some significant differences

between regions (Panamá, followed by Easter Island were distinct most frequently).

Examples of some of the significant differences are illustrated in Figure III-7. A

stepwise canonical discriminant analysis, that initially included all the measured variables

87

in Table III-5, indicated that the Panamá individuals were distinguishable from all other

geographic regions; Wilks' lambda = 0.076, p < 0.0001 (Figure III-8). The variables

TRI, NP, SW/L, 23:3/L, PA, and CA had the largest influence on discriminating between

populations. The Jackknifed classification matrix indicates how many corallites were

correctly classified by groupings based on regions, 95% of Panamá region corallites were

classified correctly. The eigenvalues indicate that the first two factors account for the

largest portion of the variance. Neighboring populations, overlap more than populations

at extreme ends of the geographic range (for example, Galápagos and Fiji are nearly

completely non-overlapping).

Linear regressions of average genetic distance between populations with average

morphologic distance between populations were significant for 37 of the 58 variables

measured (64%). Significance values of linear regressions of distance matrices are not

reliable because of violated assumptions of independence; however, the more

conservative Mantel test indicated that 12 of the 58 morphometric variables (21%), were

significantly related to the average genetic distance between regions (Figure III-9).

DISCUSSION

Panmixia is generally assumed in geographically widespread species, especially those

that have long planktonic larval durations (surviving for weeks or more), because ocean

currents are capable of dispersing propagules over enormous distances (Faldallah 1983).

The detection of isolation by distance, in one of the most geographically widespread coral

species suggests that the paradigm of Panmixia is an oversimplification. If gene flow is

88

directly mediated by prevailing ocean currents (which can be strongly unidirectional),

then simple models of isolation by distance are inadequate. Several observations in this

study suggest that an isolation by ocean currents model would fit the data more

accurately than isolation by distance. Easter Island shares haplotypes with the two

populations that are in the direct path of the current vectors in Figure III-4 (Rarotonga

and the Galápagos). The Galápagos is located in the middle of the very strong south

equatorial current, the current vectors flow in order of strength to Tahiti, Rarotonga, Fiji

and Australia (Figure III-4 B & C). According to the haplotype network, Tahiti most

substantially overlaps with the Galápagos haplotypes, followed by Rarotonga and Fiji

(Figure III-3). The average genetic distance between populations reflects a similar

pattern (Figure III-3, and Figure III-2). If we assume that gene flow is mediated by

prevailing currents, then the Galápagos is likely to be an important source population, or

at least a critical stepping stone in the convoluted path of global ocean circulation. P.

lobata is one of the few dominant corals of the Galápagos archipelago, and the only

species of Porites that occurs there (Glynn and Wellington 1983). The fauna is

depauperate with very little reef formation. It is also located at the geographic center of

the El Nino Southern Oscillation, which causes water temperatures to rise and is

associated with mass coral bleaching and mortality. The current vectors in Figure III-4

do not readily suggest a plausible candidate source population for the Galápagos.

Future studies in the Eastern Pacific and the Northern Hemisphere, should address this

issue.

89

The phylogeographic NCA analysis rejects the null hypothesis of no association

between phylogenetic and geographic structure. Under the null hypothesis of panmixia,

all clades have the same geographic center, permutations of the data to generate a null

distribution, allowing for significance testing against random fluctuations expected from

genetic drift, or sample error (Templeton 2001). The technique has explicit criteria for

distinguishing between historical and population level processes, based on expectations

from simulations and coalescent theory (Templeton 1998, 2001). One of the predictions

of coelecent theory is that older haplotypes will be more common in a given sample, and

that interior clades (with multiple connections) are generally younger than tip clades.

The Easter Island haplotypes all occurred in tip clades, and the clade distance (Dc) and

the nested distances were significantly small, while the Dc of the interior clades, and the

I-T distances were significantly large, which are predicted by isolation by distance. The

inference of isolation by distance is strengthened by the fact that for the geographically

restricted clades, the union of the ranges roughly corresponds to the range of the interior

clades (i.e. clade 2-2 and 2-7) within the same nested group, which is predicted by the

inference key (Templeton 2001).

The haplotype network (Figure III-3) appears to have symmetrical properties, and

many of the specimens sampled contain two distinct haplotypes indicating that there may

be two distinct haplotype families that have undergone a parallel history. Two active

arrays of ribosomal genes (nucleolus organizer regions) located on separate

chromosomes, or a gene duplication event could explain this pattern. Moderately

divergent intragenomic paralogues have been associated with slower rates of crossover

90

and gene conversion between separate chromosomal lineages (Arnheim et al. 1980,

Polanco et al. 2000). Alternatively, hybridization and introgression between two coral

species, or incomplete lineage sorting could be invoked as explanations. It is unlikely

that one of the haplotype families (Clade 4-1 or 4-2 in Figure III-3) is a non-functioning

pseudogene. Pseudogenes have been discovered in Acropora species; however, they are

usually associated with substantial levels of intragenomic variation. (Odorico and

Miller 1997; van Oppen 2000). Our survey of other Porites and Siderastrea species

(Chapter II), suggests that levels of intragenomic variability in Porites and Siderastrea

are very low, and relatively low variability have been observed in most Scleractinian

species surveyed to date (reviewed in Marquez et al. in press). We favor the existence

of two nucleolus organizer regions, or hybridization between a species that has not yet

been sampled as the most likely hypotheses.

Inragenomic variation in the ITS region was substantially lower than reported

previously by Hunter et al (1997) in P. lobata from Hawai'i (6%). Hawai’i is an

isolated archipelago with several endemic species of Porites, where an adaptive radiation

may have occurred. It is possible that a cryptic species within the P. lobata complex

was sampled, or that the sequence (AF180115) contains noise, due to absence of

complementary strand confirmation. Mutations appear scattered throughout the

sequence in a manner similar to sequences with high noise or low signal. In our data

set, differences between most Porites species tend to be constrained to several specific

regions of the sequence (Chapter II). Further studies of the Hawai’ian Porites fauna

91

will undoubtedly resolve this issue, as well as clarify the relationships between the many

unique growth forms endemic to the region.

The morphological differences in corallite level characteristics, and differences in

gross colony morphology are consistent with the genetic isolation by distance and low

recurrent gene flow predicted by the nested clade analysis. Many Easter Island P.

lobata colonies are strikingly different in colony appearance from all other geographic

regions, forming tall columnar fins or peaks. The distinctiveness of the population, in

terms of corallite and colony level characteristics, as well as genetic differences, might be

expected as it is located thousands of kilometers away from neighboring populations, and

it is located in the middle of the counter clockwise flowing South Pacific Gyre.

Although Easter Island is the most genetically distinct population (Table III-2), the

genetic differences are on a scale consistent with intraspecies variation (1.5-1.8%). The

nested clade analysis includes explicit criteria that are capable of detecting historical

patterns such as past fragmentation, or range expansion (including long distance

colonization) (Templeton 1998, 2001). The Easter Island clades met the criteria of

recurrent low levels of gene flow. The correlations between morphology and genetics,

and the pattern of morphometric isolation by distance (Figure III-8) lend further support

to this hypothesis.

The reciprocally monophyletic genetic differences between P. lobata and P.

lobata-panama are as high as differences between other Porites species (Chapter II), and

the morphometric data confirm this result. It is possible that both P. lobata-panama and

P. lobata are present in Panamá, and that only P. lobata-panama was sampled due to

92

patchy or habitat specific occurrence, or difference in abundance. Likewise, the small

sample sizes in each region have the potential to exaggerate some differences and

therefore bias the overall result. Nevertheless, each individual was considerably more

similar to other individuals from the same region (Figure III-8) and there was strong

concordance between the molecular and morphometric data that is unlikely to be the

result of chance or sampling artifact.

The overall pattern is one of gradual changes in genetic and morphological

variation between geographical regions. The variation generally increases with

distance, unless overridden by prevailing ocean surface currents. The patterns are best

explained by selection operating on a regional scale, with the cohesive forces of low to

intermediate levels of recurrent gene flow mediated by ocean currents. Although the

samples in this study span more than ten thousand kilometers, only a sparse sampling of a

small portion of P. lobata's geographic range is represented. This study is therefore

only a preliminary view of the complex history of P. lobata in space and time.

93

TABLES

Table III-1

Length variation, percent G + C content, number of individuals, number of sequences, geographic

region, collector and date for the ITS-1 and ITS-2 sequences collected for this study. Abbreviations are as

follows: EP, Pacific; CP, Central Pacific WP, Western Pacific; * P. lobata-panama was collected from Uva

and Saboga Panamá. Collectors and dates are represented by numbers in superscript; 1 = G. Wellington

(99), 2 = M. Takabayashi (98), 3 = Z. Forsman (98). Samples in bold letters indicate that a skeletal

voucher specimen was collected. The 5.8S gene had few polymorphisms, and a nearly constant length of

106-107nt, and a 51% G+C content

94

ITS-1 ITS-2 Length Length No of No of Species Region (bp) %(G+C) SE (bp) %(G+C) SE Individuals Sequences P. lobata-panama* Panama* (EP)1 303-311 43.27 0.19 228-229 44.91 0.23 4 7 P. lobata Easter Isl. (CP)1 303-312 42.02 0.47 215-226 43.89 0.22 4 10 " " Australia (WP)2 305-325 42.17 0.43 210-223 43.91 0.75 2 7 " " Rarotonga (WP)1 306-309 42.27 0.26 207-226 44.16 0.45 3 9 " " Tahiti (CP)1 306-309 41.96 0.43 207-231 43.89 0.43 3 9 " " Galapagos (EP )3 306-307 42.29 0.34 209-225 44.04 0.49 4 15 " " Fiji (CP)1 305-309 41.91 0.41 215-223 43.81 0.83 3 7 Total 23 64

Table III-1

95

Table III-2

Matrix of genetic distance between populations (in substitutions per site,

calculated by the Kimura 1980 method), and standard errors. Numbers in bold script

along the diagonal represent intra-population means. Standard errors are in italic script.

Distances were calculated separately for the ITS-1, and ITS-2. Mean differences

between populations, and net distance between populations are shown. Standard errors

were estimated by 1000 bootstrap replicates implemented in MEGA 2.1 (Kumar et al.

2001). Abbreviations are as follows: A = Australia, E = Easter Isl., F = Fiji, G =

Galápagos, R = Rarotonga, T = Tahiti, P = Panamá.

96

Mean Difference Within and Between Groups Net Difference Between Groups ITS-1 ITS-1

A E F G R T P A E F G R T P A 0.012

±0.005 0.004 0.006 0.005 0.004 0.005 0.009 A ~ 0.001 0.003 0.002 0.002 0.002 0.008

E 0.013 0.010 ±0.004 0.006 0.005 0.004 0.005 0.010 E 0.002 ~ 0.003 0.002 0.002 0.002 0.010

F 0.018 0.019 0.016 ±0.006 0.005 0.005 0.005 0.010 F 0.004 0.006 ~ 0.001 0.002 0.002 0.009

G 0.014 0.014 0.015 0.011 ±0.004 0.004 0.004 0.010 G 0.003 0.004 0.001 ~ 0.001 0.001 0.009

R 0.013 0.012 0.016 0.012 0.009 ±0.004 0.004 0.010 R 0.003 0.003 0.004 0.002 ~ 0.001 0.010

T 0.014 0.013 0.016 0.012 0.012 0.010 ±0.004 0.010 T 0.003 0.003 0.003 0.002 0.002 ~ 0.009

P 0.027 0.033 0.034 0.030 0.033 0.030 0.003 ±0.002 P 0.020 0.027 0.025 0.023 0.027 0.024 ~

ITS-2 ITS-2 A E F G R T P A E F G R T P

A 0.019 ±0.006 0.007 0.004 0.004 0.005 0.004 0.019 A ~ 0.004 0.001 0.001 0.002 0.001 0.019

E 0.029 0.019 ±0.005 0.006 0.006 0.006 0.006 0.019 E 0.011 ~ 0.004 0.002 0.002 0.004 0.018

F 0.016 0.024 0.009 ±0.003 0.004 0.004 0.003 0.018 F 0.002 0.011 ~ 0.001 0.001 0.001 0.019

G 0.020 0.023 0.014 0.016 ±0.004 0.004 0.003 0.019 G 0.002 0.006 0.002 ~ 0.001 0.001 0.018

R 0.019 0.022 0.016 0.018 0.015 ±0.005 0.004 0.019 R 0.002 0.005 0.004 0.003 ~ 0.001 0.019

T 0.014 0.024 0.010 0.013 0.015 0.009 ±0.003 0.019 T 0.001 0.011 0.002 0.001 0.003 ~ 0.019

P 0.110 0.114 0.106 0.108 0.117 0.108 0.005 ±0.002 P 0.110 0.114 0.110 0.110 0.120 0.114 ~

Table III-2

97

Table III-3

AMOVA tables of genetic structure within and between geographic regions. (A).

All sequences included. (B). Table of Pairwise Fst values (below diagonal), and

pairwise significance values (above diagonal), were calculated using Arliquin v 2.0

(Schneider et al. 2000). Significance values were obtained by 1023 permutations of the

data to generate a null distribution. (C). An example of one of the subsets of sequence

per individual (this was repeated several times with alternative sequences/individuals

from a region) -the genetic structure was still highly significant, indicating that the

genetic structure is not an artifact of the sampling method. (D). Significant

differences between regions still occur when all Easter Island sequences were excluded

from the analysis. This indicates that the genetic structure is not solely due to Easter

Island (the most genetically distinct population).

98

E A R T G F E ~ 0.0001 0.0001 0.0001 0.0001 0.0001 A 0.34 ~ 0.06 0.07 0.01 0.15 R 0.32 0.12 ~ 0.01 0.001 0.01 T 0.36 0.09 0.15 ~ 0.05 0.01 G 0.25 0.12 0.16 0.07 ~ 0.05 F 0.38 0.07 0.20 0.15 0.09 ~

Source of Variation d.f. S.S. V.C. % Variation Among Regions 5 36.545 (a) 0.72 12.43 p < 0.02 Within Regions 13 65.75 (b) 5.06 87.57 Total 18 102.296 5.78

Source of Variation d.f. S.S. V.C. % Variation Among Regions 4 29.38 (a) 0.44 11.78 p < 0.0001Within Regions 42 138.64 (b) 3.30 88.22 Total 46 168.02 3.72

Source of Variation d.f. S.S. V.C. % Variation Among Regions 5 59.115 (a) 0.89 19.79 p < 0.0001 Within Regions 50 181.076 (b) 3.62 80.21 Total 55 563.83 10.6

Table III-3

(A) All Sequences Included

(B) Pairwise Fst and significance values between geographic regions

(C) One sequence per individual

(D) Easter Island excluded

99

Table III-4

The results of the nested clade analysis. Clades in gray are interior, others are tip

clades. Significantly large values are denoted by L, small values by S, the level of

significance is indicated as follows: * = p < 0.05 ** = p < 0.01, Dc = Clade distance,

Nc = Nested clade distance. I-T distances are indicated for significant clades only.

The inference chain (according to the inference key of Templeton 1998, and Posada et al.

2000) is indicated underneath the significant clade, IBD is an abbreviation for Isolation

By Distance.

100

Haplotypes 1-step 2-step 3-step 4-step Name Dc Dn Name Dc Dn Name Dc Dn Name Dc Dn Name Dc Dn r1-2 1-1 0 3412 r6-4 0 0

e20-2 0 0 1-2 0 5118 2-1 4094 3839

e121-25 0 0 1-3 0 0 2-2 0 3412 3-1 902 S** 4884 S**

a1-13 0 0 1-4 0 0 2-3 0 6961

g8-8 0 0 1-5 0 0 2-4 0 6961

g3-8 0 0 1-6 0 7008

a2-8 0 6937 1-7 6937 6871 t3-1 0 6937 exact contingency test

4-1 p < 0.01 r1-3 7839 5891 1-8 5241 5362 2-5 6578 6659 3-2 7931 L* 7231 L** 4-1 6365 5909

g66-3 I-T 7029 L** 2348 L** t6-4 0 3942 1-2-3-4

No:IBD

g66-2 t3-2 6756 4504 t2-3 g7-6 6756 4504 1-19 5405 5794 2-10 6762 5717 3-4 5923 6333 4-2 6481 6064

4-2 p <0.05 f7-3 0 0 1-18 0 6766

f4-3 0 0 1-17 0 10142 2-9 10142 6426

g7-8 0 0 1-16 0 10142

r4-17 0 5877 a2-9 0 5877 1-13 5877 3950 2-8 4168 5170

a1-41 0 0 1-12 0 4091

f64 0 0 1-14 0 3210

t6-3 0 0 1-15 0 4598

e48-1 0 0 1-11 0 0 2-7 0 2385 3-3 2862 S* 6328

I-T 3060 L* 4 e47-3 0 3578 1-2-3-4

No:IBD

g3-5 0 3578 1-10 3578 2684 2-6 2862 2684 1-9 0 1789

Table III-4

101

Table III-5

Definitions and descriptions of the morphological variables measured in this study.

See Figure III-1 for an illustration of the point landmarks. The distances between points

were calculated mathematically. Areas were calculated in Scion Image (Scion

Corporation 2000), following a user-defined circumference. *IRR (septal irregularity)

was calculated as the sum of the absolute value of the differences between septal lengths.

102

Name

Points Measured

Description

Name

Description

SL1 1:02 Septa Length NP Number of Pali SL2 3:04 Septa Length TRI Triplet SL3 5:06 Septa Length FA Fossa Area SL4 7:08 Septa Length CA Corallite Area SL5 9:10 Septa Length SL6 11:12 Septa Length Proportional SL7 13:14 Septa Length Variables SL8 15:16 Septa Length FACA FA/CA SL9 17:18 Septa Length X1 20:24+4:10/5:7+19:21 SL10 19:20 Septa Length X2 24:4/23:3 SL11 21:22 Septa Length X3 SW/(1:2:13:14) SL12 23:24 Septa Length X4 12:16/11:15 SW1 25:26 Septa Width X5 13:14/L SW2 27:28 Septa Width X6 1:2/L SD1 1:03 Septa Distance X7 23:3/L SD2 3:05 Septa Distance LAT 3:5+7:9+17:19+21:23/LSD3 5:07 Septa Distance SD4 7:09 Septa Distance SD5 9:11 Septa Distance Averaged SD6 11:13 Septa Distance Variables SD7 13:15 Septa Distance APD Avg (PD) SD8 15:17 Septa Distance ASL Avg (SL) SD9 17:19 Septa Distance ASW Avg (SW) SD10 19:21 Septa Distance IRR * SD11 21:23 Septa Distance SD12 23:01 Septa Distance PD1 2:04 Pali Distance PD2 4:06 Pali Distance PD3 6:08 Pali Distance PD4 8:10 Pali Distance PD5 10:12 Pali Distance PD6 12:14 Pali Distance PD7 14:16 Pali Distance PD8 16:18 Pali Distance PD9 18:20 Pali Distance PD10 20:24 Pali Distance FL1 20:8 Fossa Length FL2 2:14 Fossa Length FW 20:08 Fossa Width W 7:19 Width L 1:15 Length

Table III-5

103

FIGURES Figure III-1

Neighbor-Joining Cladogram of distances between all sequences in this study.

The data was bootstrapped 1000 times in MEGA 2.0 (Kumar et al. 2001). Bootstrap

values lower than 50 are not shown. The colors correspond to population identity; Dark

blue = Galápagos, light blue = Easter Island, periwinkle = Tahiti, Pink = Fiji, Violet

=Rarotonga, Red = Australia. Thick bold lines indicate clades that share multiple

molecular clones from the same individual. P = Panamá population, the triangle is

proportional to the number of sequences; the height or depth in time of the triangle is

proportional to the maximum difference between sequences.

104

F7-1

F7-3 G66-2

G7-6 G8-7

G8-8 A2-8

A2-9 F6-2

F6-4 T6-4

T6-7 T2-7

T2-8 T2-3

G7-5 G7-8

F4-3 F4-2

F4-4 R1-1

R1-3 T3-1

T3-4 A2-10 G3-8

G3-a G66-1 G3-19

G3-28 G3-7

G66-3 T3-2

T6-3 R4-4 R4-9

R4-17 A1-1

A1-41 A1-13 A1-23

E121-25 R6-6

E20-2 E20-7 E20-4

R1-2 R6-4

R6-4b G8-10

E47-3 E47-4 E47-2

G3-5 E48-1 E48-3 E48-5

P

94

73

5767

89

96

89

57

85

99

95

82

8197

54

79

52

69

80

0.012

Figure III-1

105

Figure III-2

Averaged genetic distance (substitutions) between populations Neighbor-Joining

cladogram. Distances were calculated using the Kimura (1980) method. (A). Entire

ITS region. (B). ITS-1 only. (C). ITS-2.

106

A). Entire ITS Region

B). ITS-1

C). ITS-2

ER

G

T

FA

P

0.012

E

R

T

G

FA

P

0.012

E

R G

T

A F

P

0.012

Figure III-2

107

Figure III-3

Haplotype network and nested clade design used for nested clade analysis. The

network was estimated by the statistical parsimony method implemented in TCS v 1.13

(Clement et al. 2001). The network represents the set of 95% probable haplotype

connections. Each rectangular black strip, or small circular node indicate a theoretical

intermediate haplotype, the lines between indicate one mutational distance (insertions and

deletions were treated as missing in this analysis). The nesting algorithm and rules are

outlined in Templeton et al. (1987), and Templeton and Sing (1993). The procedure

joins haplotypes separated by one mutational event into 1-step clades proceeding from

the exterior to the interior of the network, all 1-step clades separated by one mutational

event are joined into 2-step clades, and so on…

108

Figure III-3

G66-2T3-2F7-3

R4-17

T6-3F6-4

G7-8 F4-3

3-4

E48-1

2-9

2-10

2-8

1-17

1-16

1-181-19

1-15

1-13

1-14

A1-411-12

E47-3

G8-10

1-11

1-9

1-10

2-7

2-6

3-3

4-2 4-1

A1-13

G3-8

G8-8

T6-4

G66-3 R1-3

E121-25

R1-2 R6-4

E20-2

T3-1

3-2 3-1

1-1

1-2

1-3

1-5

1-6

1-8

1-7

1-4

2-5

2-3

2-4

2-2

2-1

A2-9

G3-5

G7-6T2-3

A2-8

109

Figure III-4

(A). Genetic distance between populations, the thickness of the lines is inversely

proportional to the average number of nucleotides differing between populations. (B).

Pacific Ocean 10 year mean current vectors, and ocean surface altitude from satellite

data. The large blue arrow represents the scale for current vectors in meters per second.

The blue arrows indicate westward flow, while red arrows indicate Eastward flow. (C).

Monthly mean surface currents, centered on January 15. Summer in the southern

hemisphere results in current vectors that connect the central Pacific to the southeastern

Pacific. A possible means of larval transport from Rarotonga to Easter Island. The

ocean current vectors are derived from satellite altimeter and scatterometer data

(scatterometers measure echoed radar pulses from ripples near the oceans surface). A

java application at http://www.oscar.noaa.gov/datadisplay/latlon-nj.htm, allows users to

define time-frame over which the data is averaged (Bonjean and Lagerloef 2002)

110

E

TRF

A

G

Figure III-4

A). Genetic distance between populations

B). 10 year (1993-2003) mean surface currents from satellite data

C). Monthly (centered on January 15) mean surface currents from satellite data

1.0 meter/sec (0.514 m/s = 1 knot)

111

Figure III-5

An illustration of the corallite morphometric characters used in this study. Left;

a typical digitized microscope image, monofilament line was used as a scale (thickness =

0.16 mm). The 29 points on the image represent septal landmarks, the first point was

always placed on the top of the dorsal directive septa, the numbers then proceed

clockwise. The discrete characters used in this study are indicated on the right; number

of pali, number of radi, ventral tripled fused, free, or tridented. The continuous

characters were based on distances between points, and the area of the fossa (inner

synapticular ring), and the corallite wall. See Table III-3 for a list of measurements

used in this study. The definitions of taxonomic characters are based on Weil 1992;

Weil et al. 1992; Veron 2000.

112

Figure III-5

Wall

Dorsal Directive Lateral Pair

Ventral Triplet

Columella Radi

Pali

Fossa

Free Trident Fused

113

Figure III-6

An example of geographical variation among P. lobata. The images were

photographed at the same scale. Each corallite is generally representative of the

appearance other specimens from the same region, however there is a high level of

apparent variability and overlap between regions. Specimens from Panamá tend to have

more regularly spaced septa, and a more wagon-wheel like appearance.

114

Figure III-6

115

Figure III-7

Box plots of the mean, confidence intervals and standard errors of some of the

measurements from this study. Analysis of variance indicates that significant

differences occur between regions, for almost all of the traits measured (only 4 examples

are shown in this figure). Mean, confidence intervals and standard error are shown.

The matrix below each box plot indicates which comparisons are significant after Tukey's

HSD correction for multiple comparisons has been applied. Generally, Panamá and

Easter Island were significantly different more often than other populations.

116

0.05

0.10

0.15

0.20

FA

0.05

0.10

0.15

0.20

FA

0.05

0.10

0.15

0.20

FA

0.05

0.10

0.15

0.20

FA

0.05

0.10

0.15

0.20

FA

Average Septal Width (SW)

0.1

0.2

0.3

0.4

0.5

0.1

0.2

0.3

0.4

0.5

VAR00068

0.1

0.2

0.3

0.4

0.5

VAR00068

0.1

0.2

0.3

0.4

0.5

VAR00068

0.1

0.2

0.3

0.4

0.5

VAR00068

Average Septal Length (SL)

mm

0

1

2

3

0

1

2

3

VAR00007

0

1

2

3

VAR00007

0

1

2

3

VAR00007

0

1

2

3

VAR00007

Corallite Area (CA)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

FA

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

FA

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

FA

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

FA

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

FA

F T G E PF ~ T ~ ~ G ~ ~ ~ E ~ *** *** ~ P ~ ** *** ~ ~

F T G E PF ~ T ~ ~ G *** ** ~ E *** *** ~ ~ P ~ ~ ~ *** ~

F T G E PF ~ T ~ ~ G ~ ~ ~ E *** *** *** ~ P *** ** *** ~ ~

F T G E PF ~ T ~ ~ G ~ ~ ~ E *** *** *** ~ P *** *** ** * ~

mm

mm2 mm2

Fossa Area (FA)

Figure III-7

117

Figure III-8

Stepwise multivariate canonical discriminant analysis plot of the two factors with

the largest covariance to the variables measured in this study. Wilks' lambda = 0.076, p

< 0.0001. The variables TRI, NP, SW/L, 23:3/L, and, CA had the largest influence on

discriminating between populations. The Jackknifed classification matrix indicates how

many corallites were correctly classified by groupings based on regions. 95% of

Panamá region corallites were classified correctly. The eigenvalues indicate that the

first two factors account for the largest portion of the variance. 95% confidence ellipses

are drawn around the data from each region.

118

-3 -2 -1 0 1 2 3 4SCORE(1)

-5

-4

-3

-2

-1

0

1

2

3

4

5

SCORE(2)

PanamaTahitiGalapagosFijiEaster Island

Region

E F G T P %CorrectE 26 2 5 4 3 65 F 0 19 1 7 3 63 G 7 1 23 4 2 62 T 3 3 3 16 5 53 P 0 0 1 1 38 95

Total 36 25 33 32 51 69 eigenvalues 2.255 1.427 0.351 0.229

Factor (1)

Fact

or (2

)

Jackknifed Classification Matrix

Figure III-8

119

Figure III-9

The relationship between genetic and morphologic distances between P. lobata

populations. The r2 value for a linear regression are indicated, abbreviations are as

follows; * = p < 0.05, ** = p < 0. 01, *** = p < 0.001. The assumptions of

independence are violated in a pairwise distance matrix, therefore a Mantel test with 1000

permutations on the data was implemented in Arliquin v 2.0 (Schneider et al. 2000).

Values highlighted in bold were significant at the alpha = 0.05 level. The abbreviations

of morphologic characters are listed in Table III-3.

120

Variable r2 SL5 0.80* SL6 0.89** SL7 0.83** SL8 0.95*** SL10 0.68* SL11 0.66* SD1 0.88** SD3 0.90** SD4 0.75* SD5 0.90** SD6 0.92** SD7 0.80* SD8 0.98*** SD9 0.85** SD10 0.95*** SD11 0.72* SD12 0.85** PD2 0.85** PD3 0.79* PD4 0.82* PD5 0.97*** PD6 0.87** PD7 0.81* PD8 0.98*** FL1 0.90** FL2 0.75* PD10 0.94*** PD12 0.78* W 0.96*** L 0.92** FA 0.97*** CA 0.95*** X1 0.66* LAT 0.85** APD 0.98***

Figure III-9

121

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Kimura, M. (1980). A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 16, 111-120. Knowlton, N. (1993). Sibling species in the sea. Annu. Rev. Ecol. Syst 24, 189-216. Kumar, S., Tamura, K., Jakobsen, I. and Nei, M. (2001). MEGA2: Molecular Evolutionary Genetics Analysis software Version 2.1. Tempe Arizona: Arizona State University. Link, H. F. (1807). Bescheibung der Naturalein. Sammlungen der Universaitat Rostock, 3, 161-165. Mantel, N. (1967). The detection of disease clustering and a generalized regression approach. Cancer Research 27, 209-220. Marquez, L., Miller, D., MacKenzie, J. and van Oppen, M. J. H. (in press). Psudogenes contribute to the extreme diversity of nuclear ribosomal DNA in the hard coral Acropora. Odorico, D. M. and Miller, D. J. (1997). Variation in the Ribosomal Internal Transcribed Spacers and 5.8S rDNA Among Five Species of Acropora (Cnidaria;Scleractinia): Patterns of Variation Consistent with Reticulate Evolution. Mol. Biol. Evol. 14, 465-473. Polanco, C., Gonzalez, A. I. and Dover, G. A. (2000). Patterns of variation in the intergenic spacers of ribosomal DNA in Drosophila melanogaster support a model for genetic exchanges during X-Y pairing. Genetics 155, 1221-9. Posada, D. (2000). GeoDis: a program for the cladistic nested analysis of the geographical distribution of genetic haplotypes. Molecular Ecology 9, 487-488. Saitou, N. and Nei, M. (1987). The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4, 406-425. Schneider, S., Roessli, D. and Excoffier, L. (2000). Arlequin ver. 2.000: A software for population genetics data analysis. Switzerland: Genetics and Biometry Laboratory, University of Geneva. Smouse, P. E. and Long, J. E. (1986). Multiple regression and correlation extensions of the Mantel Test of matrix correspondence. Systematic Zoology 35, 627-632. Templeton, A. R. (1998). Nested clade analyses of phylogeographic data: testing hypotheses about gene flow and population history. Mol Ecol 7, 381-97. Templeton, A. R. (2001). Using phylogeographic analysis of gene trees to test species status and processes. Molecular Ecology 10, 779-791.

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Templeton, A. R., Boerwinkle, E. and Sing, C. F. (1987). A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping. I. Basic theory and an analysis of alcohol dehydrogenase activity in Drosophila. Genetics 117, 343-351. Templeton, A. R. and Sing, C. F. (1993). A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping. IV. Nested analysis with cladogram uncertainty and recombination. Genetics 134, 659-669. Thompson, J. D., Higgins, D. G. and Gibson, T. J. (1994). CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position specific gap penalties and weight matrix choice. Nucleic Acids Research 22, 4673-4680. van Oppen, M. J. H., Willis, B. L., Van Vugt, H. W. J. A. and Miller, D. J. (2000). Examination of species boundaries in the Acropora cervicornis group (Scleractinia, Cnidaria) using nuclear DNA sequence analyses. Molecular Ecology 9, 1363-1373. Vaughan, T. W. (1907). Recent Madrporaria of the Hawaiian Islands and Lysan. US National Mus Bull 59, 427pp. Veron, J. (1995). Corals in space and time; the biogrography and evolution of the scleractinaia. London: Cornell. Veron, J. E. N. (2000). Corals of the World, vol. 3 (ed. M. Stafford-Smith). Townsville, Australia: Australian Institute of Marine Science. Veron, J. E. N. and Pichon, M. (1982). Scleractinia of Eastern Australia part 4, Family Poritidae. Australian Institute of Marine Science Monograph Series 5, 159. Weil, E. F. (1992). Genetic and morphological variation in Caribbean and eastern Pacific Porites (Anthozoa, Scleractinia), preliminary results. Proc 7th Int. Coral Reef Sym. Guam 643-656. Weil, E. F. (1992). Genetic and morphological variation in Porites (Cnidaria, Anthozoa) across the Isthmus of Panama. In Ph.D. Dissertation, pp. 327. Austin TX: University of Texas. Weir, B. S. (1996). Genetic Data Analysis II: Methods for discrete population genetic data. Sunderland, MA, USA: Sinauer Assoc. Inc.

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IV. The Siderastrea glynni (Scleractinia: Siderastreidae) Paradox: A Critically Endangered Species Or A Stowaway From The Caribbean? ITS Region Sequences Are Shared With S. siderea.

ABSTRACT The extremely rare Panamanian endemic Siderastrea glynni, is one of only two documented critically endangered species of hermatypic coral. S. glynni is the only member of the genus that occurs in the entire eastern Pacific province. Only 5 individuals have been discovered, currently only 4 exist. A comparison of cloned sequences of the Internal Transcribed Spacer (ITS region) reveals that all four S. glynni individuals have extremely low nucleotide diversity, with 15 molecular clones from 4 individuals differing by only 0.17%, -designated as the Clade A haplotype. All individual S.siderea collected from the Caribbean side of Panamá contain the exact same haplotype in roughly equal proportions to an additional haplotype; the Clade B haplotype. The average nucleotide distance between S. glynni and S. siderea is only 0.83%, whereas the maximum distance between the A and B haplotypes is 1.7%. The widely accepted view that S. glynni originated from dispersal from the western Pacific is highly unlikely. There are two remaining alternative hypotheses: (1) A geminate relationship between S. glynni and S. siderea. (2) a more recent colonization through the isthmus of Panamá. Previously published mutation rates of the ITS region were examined in order to determine if the maximum distance between S. glynni and S. siderea haplotypes are consistent with a 3.5 million year divergence. The mutation rates vary by only 5 fold between a wide variety of organisms. The mutation rates cannot reject Hypothesis (1), however this is only if the mutation rate is unusually slow (0.2%), and if the assumptions of a molecular clock are not sufficiently violated. Phylogeographic Nested Clade Analysis was used to make inferences about the information contained in a haplotype network generated by statistical parsimony. The analysis supported the inference of long distance colonization, which is more consistent with a contemporary relationship between S. glynni and S. siderea. Although neither hypothesis can be ruled out, either hypothesis has important implications about population level processes that govern the tandem arrays of ribosomal genes and spacers, such as lineage sorting, genetic drift, founder effect, and concerted evolution. Further study is necessary to solve the S. glynni paradox.

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INTRODUCTION

There are only two documented critically endangered species of coral; S. glynni and

Millepora boschmai. S. glynni, is endemic to Panamá, and extremely rare. Only five

colonies have been discovered, and currently only four exist (Budd and Guzman 1994).

Budd and Guzman (1994) hypothesized that S. glynni may have originated from a small

founding population from the central Pacific, perhaps from a single rare dispersal event.

The hypothesis is based on the rationale that S. glynni is morphometrically distinct from

the Caribbean fauna, and most similar to the central Pacific species S. savignyana. The

alternative hypothesis is that a geminate species may exist in the Caribbean, and S. glynni

is the last relict of a population that was fragmented by the closure of the Tropical

American Seaway, which occurred approximately ~3-3.5 MYA (Kegwin 1982).

A third seemingly unlikely hypothesis is that S. glynni is a non-indigenous species

that has somehow been transported from the Caribbean. The hypothesis would require

that the soft bodied organism survived prolonged passage through the fresh water of the

Panamá canal, perhaps in floating debris, in ships ballast water, as larval spat that settled

on an anchor chain, or some other such mechanism. All five colonies were discovered

within a few square meters of each other, they were small and similar size, and they were

located downstream from the Pacific opening of the Panamá canal. The observed

differences in morphology (Budd and Guzman 1994) could simply be due to phenotypic

plasticity, arising from environmental differences between the Caribbean and Eastern

Pacific.

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We collected all of the extant members of Sidereastrea that occur around the

Isthmus of Panamá in order to determine the possible origin of S. glynni. Siderastrea is

one of the few Scleractinian genera that occur on both sides of the Isthmus. S. glynni is

the only extant Siderastrea species in the eastern Pacific, and Siderastrea siderea, S.

radians and S. stellata are the only species that occur in the Caribbean (Veron 2000).

To examine the possibility of a geminate relationship, an accurate estimate of the

mutation rate of the molecular marker in question is necessary. We surveyed the

estimated ITS region mutation rates from the literature on a wide variety of organisms.

Martin and Palumbi (1993) established that mutation rates covary with a number of

characteristics that are likely to influence 'nucleotide generation time', such as generation

time, metabolic rate, body size, rate of cellular division, and DNA repair efficiency. It

is important therefore to take nucleotide generation time into account, when estimating

divergence rates because small short-lived organisms generally have much higher

mutation rates then large long-lived ones.

We employed a phylogeographic Nested Clade Analysis (NCA), which explicitly

tests the null hypothesis of no association between geography and phylogenetic structure

(Templeton et al. 1987; Templeton and Sing, 1993). This approach makes use of

information contained in haplotype networks to distinguish between historical population

events (such as fragmentation, long distance colonization, or range expansion), and

population structure (such as low recurrent gene flow and isolation by distance). The

approach has the additional advantage that the inferences are guided by explicit and

127

objective criteria that can also indicate lack of statistical power from inadequate

sampling.

METHODS

Very small tissue scrapings (approximately 10-20mg) were collected from each

specimen. S. radians and S. siderea were obtained from Bocas del Toro on the

Caribbean side of Panamá. S. stellata was collected from Pernambuco State Brazil. S.

glynni was originally discovered near Isla Uraba in the Bay of Panamá, near the Pacific

coast; however, after a mass bleaching event during the 1998 El Nino, the colonies were

moved to the Smithsonian Tropical Research Institute (STRI). Extraction of DNA,

PCR, cloning and sequencing are described in detail in Chapter I. Each molecular clone

was sequenced in two directions, which allowed for complementary strand conformation.

S. glynni was processed 2 months before any other samples, therefore the risk of cross

contamination was minimal. Sequence alignment was performed by hand in Bioedit

(Hall 1999). There were few alignment gaps and no ambiguities. All genetic distances

were calculated with the Kimura (1980) method in Mega 2.1 (Kumar et al. 2001)

A plausible range of mutation rates for the ITS region was determined by examining

the relationship between previously published rate estimates for a wide range of

organisms, compared to an approximation of organismal generation time (Figure IV,

Table IV-3). Tajima's (1993) equal rates test was performed in Mega 2.1. The test

detects significant deviations from expectations of a linear relationship between mutation

rate and time, between an outgroup and two other sequences. The Neighbor-Joining

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cladogram was calculated in Mega 2.1, using 1000 bootstrap replicates, it is intended to

show relative distances between sequences not as a phylogeny.

A phylogeographic Nested Clade Analysis (NCA) was performed following the

methods outlined in Templeton et al. (1987), and Templeton and Sing (1993). A

haplotype network of the 95% most probable connections was estimated using the

computer program TCS v.1.13 (Clement et al. 2000). The network had no reticulations,

which indicates that homoplasy and recombination are relatively low. The haplotype

network was nested according to rules described in Templeton et al. (1987), and

Templeton and Sing (1993); the procedure joins haplotypes separated by one mutational

event into 1-step clades proceeding from the exterior to the interior of the network, all 1-

step clades separated by one mutational event are then joined into 2-step clades, and so

on, until the entire cladogram is nested in to a single clade (see Figure IV-3). NCA was

performed in Geodis v 2.0 (Posada et al. 2000), and the results were interpreted from the

inference key provided with the program.

The geographic distances entered in Geodis, were in the form of a categorical

distance matrix: There were only two populations sampled and there were multiple

sequences sampled per individual; therefore, categorical distances were assigned instead

of geographic distances. Either categorical or continuous variables are allowed in the

analysis (Templeton 1998). Each individual specimen was treated as a separate group,

specimens from the same population were assigned an arbitrary 'close' distance of 1. An

arbitrary 'far' distance of 5 was assigned to individuals separated by the Isthmus of

Panamá. The results of the analysis were identical if alternate distances were assigned,

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as long as the interpopulation distances were larger than intrapopulation distance, and

each category was homogeneous.

The GeoDis program calculates exact permutational contingency tests on two

statistics Dc and Dn at each hierarchical nested level. Dc is a measure of the geographic

distribution of a clade, and Dn measures how widespread a nested clade is relative to

other clades in the same nested category, distances between interior and tip clades (I-T)

are also calculated (Posada et al. 2000, Templeton et al. 2001). Significance testing is

based on simulated null distributions under the expectations of panmixia. The null

distributions are generated by permutations of the data, therefore stochastic variation and

the sample sizes per locality are accounted for.

RESULTS

Thirty-eight contiguous sequences for the complete ITS-1, ITS-2 and 5.8S were

assembled, with at least 3 molecular clones for each Siderastrea species (Table IV-1).

The 5.8S rRNA gene was invariant between all sequences. The A-T content, variations

in length and sample sizes are listed in Table IV-1. Table IV-2 is a distance matrix of

all pairwise comparisons between sequences in this study. All four S. glynni individuals

had remarkably low sequence diversity (0.17%, n=16). Surprisingly, the exact same

sequence was present in both S. glynni and S. siderea individuals. All S. siderea

individuals shared at least one identical sequence with S. glynni (designated as clade A).

All S. siderea individuals contained a second sequence, (designated as clade B) which

130

was not present in any of the S. glynni individuals. In other words, all of the S. glynni

haplotypes were nested within the range of S. siderea haplotypes (Figure IV-2).

To examine whether the divergence between the most distinct haplotypes in the

two populations are consistent with a 3.5 million year division it is necessary to have an

accurate estimate of mutation rate for the ITS region. Previously published rate

estimates indicate a strong correlation between approximate generation time and mutation

rate (Figure IV-1 and Table IV-3), a relationship that was established by Martin and

Palumbi (1993). Small short-lived organisms (Algae and Drosophila) have high

mutation rate, where large, long-lived organisms (Birch and Alder trees and primates),

have low mutation rates. The ITS rates across a wide variety of organisms are

surprisingly similar, varying only approximately 6 fold, in contrast mtDNA RFLP data

varies 25 fold in vertebrates (Martin and Palumbi 1993). It would be reasonable to

assume that the minimum possible generation time for a coral colony is on the order of

several years. Hunter (1988) estimated first reproduction in Porites compressa was

approximately 2 years, therefore a plausible maximum and minimum rate based on the

correlation in Figure IV-1 are around 0.6% and 0.2% per million years respectively.

Based on a fossil calibration point in Porites (Chapter II), we estimate the ITS region

substitution rate at approximately 0.4% per million years.

Tajima's relative rate test failed to reject the null hypothesis of equal rates among

the A and B haplotypes, when either S. stellata or S. radians was selected as an outgroup

(chi-square = 1.29, p = 0.257), therefore we assume that mutation rates are proportional

to time, and may be useful for comparing divergences with known historical events.

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Figure IV-2 indicates a Neighbor-Joined cladogram of the substitution distances between

all sequences in this study. Superimposed in the background of the figure is the timing

of the complete closure of the Isthmus of Panamá, which occurred between 3.5 and 3.8

million years ago (Kegwin 1982). The large shaded rectangle indicates the possible

range of the event if the mutation rate for the ITS region in Siderastrea is between 0.2

and 0.6% per million years. The shaded central portion of the rectangle is centered on the

time of the divergence if the rate is 0.4% per million years. It is only possible for the

distance between clade A and B to be 3.5 million years ago if the lowest published rate of

0.2% is assumed. The hypothesis that the distance between clade A and B is 3.5 million

years appears to be unlikely, but it cannot be entirely ruled out.

The results of the phylogeographic NCA analysis are illustrated in Figure IV, and

Table IV-4. The haplotype network had no ambiguous steps or reticulations. All of

the S. glynni haplotypes were nested within the S. siderea clade (Clade A). The NCA

inference key indicates that a long distance colonization event is likely to have occurred.

The clade distances (Dc) are significantly small (p < 0.01), while the nested clade

distances are significantly large (p < 0.01). Significant reversals between Dc and Dn for

a clade generally indicate long distance dispersal events, especially if no intermediate

populations exist (Templeton 1998). The NCA analysis indicated that clade A had the

highest probability of being an older clade, which is based on the predictions of

coalescent theory that older haplotypes will be more frequent in the population, and will

tend to be located in the interior of a network. A separate haplotype network was

constructed that contained only S. siderea samples (data not shown), which also indicated

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that the A clade has the highest outgroup probability. The large numbers of shared

identical sequences, and the NCA inference of long distance colonization suggests a

contemporary relationship between S. glynni and S. siderea.

DISCUSSION

According to our data, the hypothesis that S. glynni originated from dispersal from the

central Pacific can be rejected. Due to the low nucleotide diversity among all four S.

glynni individuals, it is obvious that S. glynni has passed through a population bottleneck;

however, it cannot be determined with certainty if the bottleneck occurred 3.5 million

years ago, or in the last 100 years. Through phylogeographic nested clade analysis, we

can determine that the observed patterns are more consistent with the expectations of a

colonization event by long distance dispersal, than with a historical event such as

allopatric fragmentation. According to the NCA inference key, past fragmentation

events should result at least partially non-overlapping clade ranges, with larger than

average number of intermediate haplotypes (Templeton 1998). The ITS data clearly

nests all of the S. glynni haplotypes as a subset well within the range of the S. siderea

haplotypes. The analysis also indicates that clade A is likely to be older than clade B,

due to its position in the interior of haplotype networks, and its higher frequency in both

populations.

If the two populations were separated for multiple generations, then mutations should

occur independently causing them to become differentiated. It could be argued that

concerted evolution, and high inbreeding in a small population could lead to the fixation

133

and preservation of the most commonly occurring ancestral haplotype (in this case the

clade A haplotype); however, it seems unlikely that stochastic processes such as genetic

drift, concerted evolution, and mutation would all cumulatively fail to alter the A

haplotype in either population for generation after generation for 3.5 million years. The

homogenization of ribosomal arrays occurs at a rate that is even faster than the

substitution rate (James et al. 2001), and genetic drift can occur within generations. If

the process of lineage sorting of ancestral alleles is very slow, then it would be expected

that some ancestral alleles could persist in S. glynni over many generations; however,

some alleles completely unique to S. glynni would also be expected. In Porites, a genus

closely related to Siderastrea, the ITS region clearly separated species that were likely to

have diverged between 1.6 and 2.5 million years ago, therefore incomplete lineage

sorting does not necessarily present a problem over these timescales (Chapter II). Out

of all 16 sequences, S. glynni has only five unique mutations, all of which are singleton

mutations occurring only once and scattered throughout the alignment in a manner

consistent with errors associated with Taq polymerase, or base calling errors.

In the context of previously published rate estimates of the ITS region, the

hypothesis that the distance between clade A and B is 3.5 million years cannot be entirely

ruled out; however, nearly all S. glynni sequences are completely identical to S. siderea

sequences, if the difference between 'species' is measured from the least divergent

haplotypes, or the net or average distance between species, then a 3.5 million year

separation time is clearly incompatible with the data.

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From a survey of Porites species (Chapter II), intraspecific nucleotide diversity

in most species is quite similar to that of S. siderea. Similar levels of nucleotide

diversity in multiple species could be related some fundamental properties of concerted

evolution, or the coalescent process. Alternatively, it could reflect population

bottlenecks that occurred around the Plio-plestocene mass extinction, when up to 75% of

Caribbean species went extinct (around 3 million years ago) (Budd et al. 1994).

Although the available evidence appears to support the larval transport hypothesis,

the vicariance hypothesis cannot be ruled out. Each hypothesis has important

implications regarding the study of multigene families. If the origin of S. glynni was

from transportation across the Isthmus, then a rapid change in the proportion of ITS

haplotypes occurred. Genetic drift is the most likely explanation; however, inbreeding

and homogenization by concerted evolution may have also played a role. On the other

hand, if S. glynni originated by an ancient vicariant event, then the ITS region mutation

rate must be quite low, coalescent times are large and incomplete lineage sorting of

ancestral alleles has occurred.

This study is an illustration of some of the many problems that are associated with

identifying trans-isthmus geminate species pairs (reviewed by Marko 2002), and with

studying the boundary between population and species level processes. Methods such

as the nested clade analysis that are able to distinguish between historical events and

population level processes are necessary and valuable tools for examining these

processes, because it is exactly at this interface that the processes of speciation occurs

(Templeton 1998, 2001). Further empirical studies are necessary to examine how

135

multiple-copy gene families behave within a population, and between recently diverged

species, in order to solve the S. glynni paradox.

136

Table IV-1

Length variation, percent G + C content, number of individuals, number of

sequences, geographic region, collector and date for the ITS-1 and ITS-2 sequences

collected for this study. Abbreviations are as follows: EP, Eastern Pacific; ATL, Atlantic.

Collectors and dates are represented by numbers in superscript: 1 = J. Mate & H. Guzman

(01), 2 = E. Neves (00). The 5.8S gene had few polymorphisms, and a nearly constant

length of 106-107nt, and a 51% G+C content.

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ITS-1 ITS-2 Length Length No of No of Species Region (bp) %(G+C) SE (bp) %(G+C) SE Individuals Sequences S. siderea Panamá (ATL)1 305 44.22 0.35 192-193 53.41 0.58 3 13 S. radians Panamá (ATL)1 307 43.65 0.12 192 55.70 0.24 2 6 S. stellata Brazil (ATL)2 307-308 44.43 0.12 192 55.60 0.35 1 3 S. glynni Panamá (EP)1 304-305 44.67 0.12 192 53.09 0.27 4 16 Total 10 38

Table IV-1

138

Table IV-2

Matrix of averaged genetic distance between all molecular clones (in substitutions

per site, calculated by the Kimura 1980 method). Distances were calculated including

the entire ITS region (ITS-1, 5.8S, and ITS-2) implemented in MEGA 2.1 (Kumar et al.

2001).

139

g1c g1d

g1a, g2a g2d g3c g4d g4c s1a s1b s1d s2b s2d A B s3a r2b R ta tb tc

g1a g1c g1d 0.003

g1a,g2a 0.002 0.002 g2d 0.005 0.005 0.003 g3c 0.003 0.003 0.002 0.005 g4d 0.005 0.005 0.003 0.007 0.005 g4c 0.003 0.003 0.002 0.005 0.003 0.005 s1a 0.012 0.015 0.014 0.017 0.015 0.017 0.015 s1b 0.003 0.003 0.002 0.005 0.003 0.005 0.003 0.015 s1d 0.007 0.010 0.008 0.012 0.010 0.012 0.010 0.009 0.010 s2b 0.005 0.005 0.003 0.007 0.005 0.007 0.005 0.010 0.005 0.008 s2d 0.003 0.003 0.002 0.005 0.003 0.005 0.003 0.015 0.003 0.010 0.005

A 0.012 0.015 0.014 0.017 0.015 0.017 0.015 0.000 0.015 0.008 0.010 0.015 B 0.002 0.002 0.000 0.003 0.002 0.003 0.002 0.014 0.002 0.008 0.003 0.002 0.014

s3a 0.014 0.017 0.015 0.019 0.017 0.019 0.017 0.005 0.017 0.014 0.012 0.017 0.005 0.015 r2b 0.040 0.040 0.038 0.042 0.040 0.042 0.040 0.031 0.040 0.042 0.034 0.040 0.033 0.038 0.033

R 0.038 0.038 0.036 0.040 0.038 0.040 0.038 0.031 0.038 0.040 0.033 0.038 0.031 0.036 0.031 0.002 ta 0.038 0.038 0.036 0.040 0.038 0.040 0.038 0.031 0.038 0.040 0.033 0.038 0.031 0.036 0.031 0.005 0.003 tb 0.040 0.040 0.038 0.042 0.040 0.042 0.040 0.033 0.040 0.042 0.034 0.040 0.033 0.038 0.033 0.007 0.005 0.002 tc 0.040 0.040 0.038 0.042 0.040 0.042 0.040 0.033 0.040 0.042 0.034 0.040 0.033 0.038 0.033 0.007 0.005 0.002 0.003

Table IV-2

140

Table IV-3

Previously published estimated mutation rates of the ITS-1, ITS-2, or both (in

substitutions per site). The generation time estimates are problematic, and in most cases

uncertain. They are only likely to be accurate within an order of magnitude (days,

weeks, months, years, or tens of years).

141

ITS-1 ITS-2 ITS-1 & 2 Organism Aproximate

generation time Reference ~ ~ 0.008-0.020 Cladophora (Green algae) hrs-days Bakker et al. 1995 ~ ~ 0.011-0.012 Drosophila 11-15day Schlotterer et al. 1994 ~ 0.004-0.010 ~ Triatominae (Hemipteran) 5-10months Bargues et al. 2000 ~ ~ .003625-.00725 Cucurbitaceae (cucumber) 1-4 years Jobst et al. 1998 ~ ~ 0.004 Birches and Alders 7-30years Savard et al. 1993

0.0047-0.0060 0.0055-0.0070 0.0039-0.0050 Hawaiian silversword 2-20years Baldwin, (personal communication) 0.0029-0.0018 ~ ~ Primates 4-20 years Gonzalez et al. 1990

Table IV-3

142

Table IV-4

The results of the nested clade analysis. Clades in gray are interior, others are

tip clades. Significantly large values are denoted by L, small values by S, the level of

significance is indicated as follows: * = p < 0.05 ** = p < 0.01 *** = p < 0.001 , Dc =

Clade distance, Nc = Nested clade distance.. I-T distances are indicated for significant

clades only. The chain of inference is from the explicit criteria in the inference key

provided by Posada et al. (2001), and is indicated underneath the significant clade, LDC

is an abbreviation for Long Distance Colonization.

143

Haplotypes 1-step 2-step 3-step 4-step Name Dc Dn Name Dc Dn Name Dc Dn Name Dc Dn

s3a 0 0 1-1 0 1

s1a,s1e,s1f

s2e,s2f 0 0 1-2 0.75 0.81 2-1 0.69 0.62

s2b 0 0 1-3 0 0 2-2 0 0.29 3-1 0.63 S*** 2.91

g2d 0 0 1-4 0 2.26

exact contingencyg4d 0 0 1-5 0 2.42 4-1 test

4-1 p < 0.014 s2c 0 0 1-6 0 3.58

g1a,g1b,s1c,g2a,g2b, g2c,s2a,g3a,g3b,s2c

g4a,g4b,s3b

2.89 2.79 1-7 3 2.9 2-3 0 0 3-2 2.97 S** 3.14 L**

g1-5 0 2.22 I-T 2.34 L*** 0.017 L** g1d g3c g4c s1b s2d

0 0 0 0 0

2.17 2.17 2.22 3.83 3.78

1-2-3-5-6-13-14 Yes:LDC

Table IV-4

144

Figure IV-1

Previously published mutation rate (µ) per million years, for the ITS region of a

wide variety of organisms versus an approximation of generation time. Boxes in gray

indicate the approximate range of uncertainty on the X-axis, and the range of the

minimum and maximum rate estimate provided in the publications listed in Table IV-3.

The r2 value for the linear regression is highly significant (p < 0.01), however the true

placement on the X-axis is unknown.

145

Algae

Hemipteran

Birch Tree

Cucurbitaceae

Silversword

Primates

Drosophila

r 2 = 0.9721

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

0.02

0.1 1 10 100 1000 10000

Generation time (days) in log scale

µ/ 106 years

Figure IV- 1

146

Figure IV-2

A Neighbor-Joining phylogram of Siderastrea species. Distances were

calculated with the Kimura (1980) method, with 1000 bootstrapped replicates in Mega

2.1 (Kumar et al. 2001), bootstrap values less then 60% are not shown. The width of

each triangle base is proportional to the number of sequences in the clade (approximately

4 pixels/taxon). The height (depth in time) of the triangle is proportional the variability

within the group. The scale is proportional to number of nucleotide substitutions per

site. The large shaded rectangle indicates the range of estimates of the complete closure

of the Isthmus of Panamá approximately 3.5 million years ago, assuming that ITS region

mutation rate is between 0.002 and 0.006, and that the assumptions of a molecular clock

are not violated.

147

g3b g4d s2a g3c s3b g1a g2a g1d g4a g3a s2d g4c s2c g3d s1b g1b g2d g4b g2b s1c g2c g1c s2b s3a s1e s2f s1f s1a s2e stellata radians

63

62 100

83

71

97

86

61

0.000 0.0040.0080.0120.016

Clade A

Clade B

Substitutions /site

Figure IV- 2

148

Figure IV-3

A haplotype network calculated by statistical parsimony, and the nested clade

design used for nested clade analysis. The network was estimated by the statistical

parsimony method implemented in TCS v 1.13 (Clement et al. 2000). The network

represents the set of 95% probable haplotype connections. Each rectangular small

circular node indicates a theoretical intermediate haplotype, the lines between indicate

one mutational distance. The nesting algorithm and rules outlined in Templeton et al.

(1987), and Templeton and Sing (1993). The procedure joins haplotypes separated by

one mutational event into 1-step clades proceeding from the exterior to the interior of the

network, all 1-step clades separated by one mutational event are joined into 2-step clades,

and so on…

149

Figure IV-3

3-2 3-1

g3c

g1c

g4c

s1b

s2d

s2c g2d g4d

s2b

s3a

s1a, s1e, s1f s2e, s2f

1-7

1-6 1-5 1-4

1-1

1-21-3

2-12-2

2-3

g1d

g1a, g1b, s1c g2a, g2b, g2c, s2a

g3a, g3b, s2c g4a, g4b, s3b

150

LITERATURE CITED Bakker, F. T., Olsen, J. L. and Stam, S. T. (1995). Evolution of nuclear rDNA ITS sequences in the Caldophora albida/sericiea Clade (Chlorophyta). J Mol Evol 40, 640-651. Bargues, M. D., Marcilla, A., Ramsey, J. M., Dujardin, J. P., Schofield, C. J. and Mas-Coma, S. (2000). Nuclear rDNA-based molecular clock of the evolution of triatominae (Hemiptera: reduviidae), vectors of Chagas disease. Mem Inst Oswaldo Cruz 95, 567-73. Budd, A. F. and Guzman, H. M. (1994). Siderastrea glynni, a new species of scleractinian coral (Cnidaria:Anthozoa) from the eastern Pacific. Proc. Biol. Soc. Wash. 107, 591-599. Budd, A. F., Stemann, T. A. and Johnson, K. G. (1994). Stratigraphic Distributions of Genera and Species of Neogene to Recnet Caribbean Reef Corals. J. Paleont 68, 951-977. Clement, M., Posada, D. and Crandall, K. A. (2000). TCS: a computer program to estimate gene genealogies. Molecular Ecology 9, 1657-1659. Gonzalez, I. L., Sylvester, J. E., Smith, T. F., Stambolian, D. and Schmickel, R. D. (1990). Ribosomal RNA gene seqeunces and Hominoid phylogeny. Mol. Biol. Evol. 7, 203-219. Hall, T. A. (1999). BioEdit: a user-freindly biological sequence alignment program for Windows 95/98/NT. Nucl. Acids Symp 41, 95-98. Hunter, C. L. (1988). Genotypic diversity and population structure of the Hawaiian reef coral Porites compressa, Ph.D. Dissertation. University of Hawaii. James, T. Y., Moncalvo, J. M., Li, S. and Vilgalys, R. (2001). Polymorphism at the ribosomal DNA spacers and its relation to breeding structure of the widespread mushroom Schizophyllum commune. Genetics 157, 149-61. Jobst, J., King, K. and Hemleben, V. (1998). Molecular evolution of the internal transcribed spacers (ITS1 and ITS2) and phylogenetic relationships among species of the family Cucurbitaceae. Mol Phylogenet Evol 9, 204-19. Keigwin. (1982). Isotopic paleoceanography of the Carribean and east Pacific: Role of Panama uplift late Neogene time. Science 217, 350-52.

151

Kimura, M. (1980). A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 16, 111-120. Kumar, S., Tamura, K., Jakobsen, I. and Nei, M. (2001). MEGA2: Molecular Evolutionary Genetics Analysis software Version 2.1. Tempe Arizona: Arizona State University. Marko, P. (2002). Fossil calibration of molecular clocks and the divergence times of geminate species pairs separated by the Isthmus of Panama. Mol. Biol. Evol. 19, 2005-2021. Martin, A. P. P., S.R. (1993). Body size, metabolic rate, generation time, and the molecular clock. Proc. Natl. Acad. Sci 90, 4087-4091. Posada, D. (2000). GeoDis: a program for the cladistic nested analysis of the geographical distribution of genetic haplotypes. Molecular Ecology 9, 487-488. Savard, L., Michaud, M. and Bousquet, J. (1993). Genetic diversity and phylogenetic relationships between birches and alders using ITS, 18S rRNA and rbcL gene sequences. Mol Phylogenet Evol 2, 112-8. Schlotterer, C., Hauser, M. T., von Haeseler, A. and Tautz, D. (1994). Comparative evolutionary analysis of rDNA ITS regions in Drosophila. Mol Biol Evol 11, 513-22. Tajima, F. (1993). Simple methods for testing molecular clock hypothesis. genetics 135, 599-607. Templeton, A. R. (1998). Nested clade analyses of phylogeographic data: testing hypotheses about gene flow and population history. Molecular Ecology 7, 381-397. Templeton, A. R. (2001). Using phylogeographic analysis of gene trees to test species status and processes. Molecular Ecology 10, 779-791. Templeton, A. R., Boerwinkle, E. and Sing, C. F. (1987). A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping. I. Basic thoery and an analysis of alcohol dehydrogenase activity in Drosophila. Genetics 117, 343-351. Templeton, A. R. and Sing, C. F. (1993). A cladistic analysis of phenotypic associations with haplotypes inferred from from restriction endonuclease mapping. IV. Nested analysis with cladogram uncertainty and recombination. Genetics 134, 659-669. Veron, J. E. N. (2000). Corals of the World, vol. 3 (ed. M. Stafford-Smith). Townsville, Australia: Australian Institute of Marine Science.

152

V. Dissertation Conclusions

The ITS region is a promising molecular marker for a wide variety of studies in

Scleractinian coral. The majority of the phylogenetic and population genetic literature

is devoted to mitochondrial DNA, or highly conserved ribosomal genes; therefore, many

of the properties of ribosomal spacers are not well studied. The number of publications

on the subject are rapidly increasing, and the molecular marker has the potential to

revolutionize the fundamental understanding of what species are, how they are related to

each other, and how they change through time. The large technical problems, such as

problems with multiple sequence alignment, or intragenomic variability (due to

pseudogenes, separate chromosomal lineages, or incomplete lineage sorting) have the

potential to confound a study; however, these problems do not arise in many species, and

there are creative ways to overcome them.

A summary of the major conclusions of this dissertation follows: (1). In all species surveyed, intragenomic variation was low (less than 2% in P. lobata,

P. lobata-panama P. astreoides, P. colonensis, P. sverdrupi, P. panamensis, P.

divaricata, P. rus, P. furcata, S. stellata, S. radians, S. siderea, and S. glynni.).

Nucleotide diversity increased as individuals from distant regions were sampled, and

differences between species were at least an order of magnitude larger (12% or higher) in

all but a few closely related species, or species with questionable status.

153

(2). According to alignment permutation: alignment ambiguities do not override the

underlying phylogenetic signal in comparisons between species, genera, and even

families, and the resulting phylogenies are consistent with previous molecular and fossil

studies.

(3). A putative cryptic species of P. lobata named P. lobata-panama was discovered

that is genetically and morphometricaly distinct from individuals collected across the

Pacific ocean from the Galápagos, Easter Island, Tahiti, Rarotonga, Fiji, and Australia.

(4). Patterns of gradual genetic and morphological differences between geographic

regions of P. lobata are consistent with isolation by distance, more specifically isolation

by ocean surface currents.

(5). ITS region mutation rates estimates from a wide variety of previously published

studies are surprisingly consistent, varying only approximately 5 fold. Small short-lived

organisms have much faster rates than large long lived ones.

(6). Due to sequences shared with S. siderea in the Caribbean, S. glynni could not have

originated from the Indo-Pacific. The available evidence, and a nested clade analysis,

suggest that S. glynni may have originated from a contemporary transport across the

Panamá canal. The alternative hypothesis of an ancient vicarient event cannot be

entirely ruled out.

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Phylogeny and phylogeography of Porites & Siderastrea