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
Phylogeny and Phylogeography of Porites & Siderastrea (Scleractinia: Cnidaria)
Species in The Caribbean and Eastern Pacific;
Based on The Nuclear Ribosomal ITS Region
____________________________________
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
ii
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.
Zhang Forsman, for all of her love and support.
I would like to thank my lovely wife Li
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.
iii
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
iv
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.
v
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
vi
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
vii
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
1
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
2
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.
3
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
4
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.
taxonomic resolution.
This allows studies at different levels of
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,
5
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.
6
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).
7
Figure I-1
8
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.
9
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.
10
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.
11
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
12
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
13
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.
14
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
15
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.
16
Ambiguous positions provide the
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
17
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
18
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
19
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)
20
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)
21
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)
(Dendrophylliidae)
(AF180110),
(AF180110),
Scapophyllia
cylidrica
Balanophyllia
elegans
(Faviina;
Merulinidae)
(SCU65479), Montastaea faveolata (Faviina; Faviidae)(AB065353).
A 'reduced'
alignment was also constructed in which all columns containing gaps were removed.
22
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
23
(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).
24
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), intraindividual 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).
25
Comparisons between separate individuals collected from the same population
were possible using 90 sequences from 34 individuals in 6 species (P .lobata,. P. lobataPanama, 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
26
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.
27
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.
28
The 'mid-point' alignment was
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
29
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
30
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).
31
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 intraindividual 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
32
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).
33
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.
(2000) in this respect.
Our data is most consistent with Veron
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.
34
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
35
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
36
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.
37
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.
38
Table I
39
species
S. siderea
S. radians
S. stellata
P. astreoides
"
"
"
"
"
"
P. divaricata
P. furcata
P. sverdrupi
P. panamensis
P. rus
P. colonensis
P. lobata-Panama*
P. lobata
"
"
"
"
"
"
"
"
"
"
region
2
Panamá (ATL)
2
Panamá (ATL)
3
Brazil (ATL)
4
Texas (GOM)
5
Belize (ATL)
3
Brazil (ATL)
6
Panamá (ATL)
5
Belize (ATL)
6
Panamá (ATL)
7
Mexico (GOC)
1
Panamá (EP)
7
Tahiti (CP)
2
Panamá (ATL)
8
Panamá* (EP)
8
Easter Isl.(CP)
9
Australia (WP)
8
Rarotonga (WP)
8
Tahiti (CP)
10
Galápagos (EP )
8
Fiji (CP)
ITS-1
length
(bp) %(G+C) SE
305
44.22 0.35
307
43.65 0.12
307-308 44.43 0.12
304
42.40 0.00
304
42.30 0.17
304-305 42.16 0.55
304
41.87 0.40
298-300 41.17 0.24
300
41.70 0.00
317-318 43.23 0.21
317-318 43.67 0.45
310
42.20 0.00
286
43.00 0.00
303-311 43.27 0.19
303-312 42.02 0.47
305-325 42.17 0.43
306-309 42.27 0.26
306-309 41.96 0.43
306-307 42.29 0.34
305-309 41.91 0.41
ITS-2
length
(bp)
192-193
192
192
234
231-234
231-236
231-233
223-228
227-230
229-230
233-236
224
248-249
228-229
215-226
210-223
207-226
207-231
209-225
215-223
%(G+C)
53.41
55.70
55.60
43.47
43.53
44.41
44.63
45.16
44.97
48.37
49.30
44.20
44.15
44.91
43.89
43.91
44.16
43.89
44.04
43.81
SE
0.58
0.24
0.35
0.23
0.21
0.72
0.40
0.57
0.57
0.26
0.10
0.00
0.10
0.23
0.22
0.75
0.45
0.43
0.49
0.83
Total
No of
No of
individuals sequences
3
14
2
6
1
3
1
3
1
3
3
7
2
3
3
7
1
3
3
7
1
3
1
3
2
4
4
7
4
10
2
7
3
9
3
9
4
15
3
7
47
130
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.
40
Table II-2
species
Intra-species S. siderea
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
S. radians
S. stellata
P. astreoides P. divaricata P. furcata
P. sverdrupi
P. panamensisP. rus
P. lobataP. colonensis Panama
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
41
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. panamensis 0.004 ±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. lobataPanama
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
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.
42
Figure II-1
A.
per site nucleotide difference
0.018
0.016
0.014
0.012
0.01
0.008
0.006
0.004
0.002
0
intra-individual
Intragenomic
B.
1
intra-regional
Intrapopulation
Interpopulation
intra-species
per site nucleotide difference
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
1
intra-species
inter-species
Interpopulation
Interspecies
C.
Number of Number of
species
individuals
N
Intragenomic
10
33
Intrapopulation
6
34
Interpopulation
2
21
43
Molecular
clones
n
125
90
64
Mean
Standard
error
0.005579
0.009486
0.011817
0.004979
0.005053
0.004501
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.
44
Figure II-2
A.
70
60
0.4
50
30
0.2
20
0.1
10
0
0.00
0.01
0.02
0.0
0.03
50
B.
0.14
40
0.12
0.10
30
0.08
20
0.06
0.04
10
0.02
0
0.00
0.01
0.02
0.00
0.03
200
C.
0.18
0.16
150
P
0.14
100
0.10
0.12
0.08
B
0.06
50
0.04
0.02
0
0.00
0.01
0.02
g
45
0.00
0.03
Proportion/bar
count
0.3
40
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.
46
Figure II-3
GOP
0.1
1
2
4
8
10
A. 880
Aligment Length
860
840
820
800
780
760
740
720
0.01
0.1
1
10
Gap extension penalty
B.
Alignment Length
900
0.9032
rR22== 0.903
850
800
750
700
0
2
4
Average penalty
47
6
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).
collection information, see Table II-1.
For other
A). Alignment consensus cladogram for the
Porites taxa. B). Consensus cladogram of the 25 permuted alignments for Porites and
outgroup taxa.
48
Figure II-4
A. Consensus tree of the 25 permuted Porites alignments.
100
P. lobata A
P. lobata G
72
P. lobata-panama
100
100
P. rus
P. astreoides B
100
P. astreoides Z
100
P. sverdrupi
P. panamensis
100
P. divaricata
100
P. furcata
P. colonensis
B. Consensus tree of the 25 permuted Porites and outgroup alignments.
92
P. lobata A
P. lobata G
72
P. lobata-panama
92
100
P. rus
P. astreoides B
100
100
P. astreoides Z
100
P. sverdrupi
72
P. panamensis
100
100
P. furcata
96
100
P. divaricata
P. colonensis
Tubastrea
100
Balanophyllia
100
S. siderea A
S. siderea B
100
S. radians
100
S. stellata
Scapophyllia
Montastrea
49
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.
with the molecular clock enforced.
(A). Maximum likelihood phylogram
(B). Unrooted Maximum likelihood phylograms
with the molecular clock assumption relaxed.
50
Figure II-5
PP19-6
rus
rus1-8
1-8
FJ4-2
G3-8
A.
aB6-6
aP10-2
Porites
BJ7-3
pan75-2
fP1-5
pB4-7
col3-1
ssr7-1
r7-1
sstBR8-3
tBR8-3
sss2-2
s2-2
Siderastrea
ssg1-1
g1-1
Tubastraea
Tubas traea
Balanophyl
Scapophyll
Montastrae
0.02
0.02
Dendrophylliidae
op
la n
pB4
-7
fP1-5
BJ7-3
pan75-2
Ba
B.
hy
l
Tubas traea
Porites
pan
-7
7-3
pB4
-1
fP1-5
BJ
7 5 -2
col3
co
l3
-1
-2
sg
1 -1
s r7 -1
1 9-6
PP
rus
Siderastrea
sg1-1
R 8-3
s tB
1-8
G3
-
-3
8
ss
FJ4
-2
2
0-
22
sr7-1
6
R8
s tB
2
4FJ
G3-8
Tu
b
a s tr
ae
a
op
9-6
ru
hyl
s1
lan
-8
Ba
PP1
1
aP
s s 2-2
6-6
aB
a P10
aB
6-
Mo n
Sc a
pop
ta s tr
ae
Dendrophylliidae
hyll
0.05
Faviina
Mon
ta
s tra
e
ap
Sc
op
hyll
0.05
51
Dendrophylliidae
Faviina
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.
52
Figure II-6
P. astreoides B
P. astreoides Z
87
P. lobata A
P. lobata G
94
100
86
P. lobata-panama
P. rus
91
P. colonensis
P. sverdrupi
100
99
P. panamensis
P. furcata
76
P. divaricata
Tubastrea
Balanophyllia
S. siderea A
S. siderea B
99
S. radians
72
S. stellata
Scapophyllia
Montastrea
53
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.).
54
Figure II-7
55
A.) GOP=0.01, GEP=0.01
Ts/Tv = 3.38
D.) Siderastrea species Ts/Tv 1.72
C.) GOP= 8.0, GEP=4.0
B.) GOP 2.0, GEP 1.0 Ts/Tv =1.31
E.)
5.8S only Ts/Tv= 1.32
Ts/Tv =0.87
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.
56
Figure II-8
0.4
GOP=8.0
OGEP=4.0
8.0,E 4.0 y = 1.9x + 0.04
2
2
= 0.67
rR
0.35
p<0.001
GOP=2.0
0.3
OGEP=1.0
2.0,E 1.0 y = 1.14x + 0.02
57
Substitution Distance (p)
2 2
rR
= 0.75
p<0.001
0.25
OGOP=0.01
.01,E .01
GEP=0.01
0.2
y = 0.71x + 0.01
2 2
rR
= 0.84
p<0.001
0.15
0.1
0.05
0
0
0.05
0.1
0.15
0.2
Gap Distance
0.25
0.3
0.35
0.4
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.
58
Figure II-9
100
99
50
74
100
P. lobata G
P. lobata A
P. lobata-panama
100
P. rus
P. astreoides B
100
100
P. astreoides Z
100
73*
P. colonensis
P. divaricata
100
67
100
P. furcata
P. sverdrupi
100
P. panamensis
Balanophyllia
100
100
94
100
100
98
Tubastrea
S. siderea A
S. siderea B
S. stellata
S. radians
Montastrea
100
59
Scapophyllia
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).
60
Figure II-10
P. lobata
99
83
91
94
P. lobata-panama
99
P. rus
99
P. astreoides
99
99
P. panamensis-sverdrupi
99
75
99
99
P. furcata
76
99
P. divaricata
86
P. colonensis
Balanophyllia
Tubastrea
S. radians
S. stellata
99
99
83
85
99
S.siderea
Scapophyllia
Montastrea
75
70
65
60
0.3
Late
Cretaceous
55
50
45
40
35
30
0.2
Palaeocene
Eocene
25
20
15
0.1
Oligocene
61
10
5
0
0.0
Miocene
MY
percent divergence
Pliocene Pleistocene
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.
62
Figure II-11
18S 3' end
ITS-1 5' begin
63
Figure II-11 continued
ITS-1 3' end
5.8S 5' begin
5.8S 3' end
ITS-2 5' begin
64
Figure II-11 continued
ITS-2 3' end
65
28S 5' begin
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.
close proximity.
Brackets indicate that the author placed the taxa in
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.
66
ITS Region
(P ( D, S )
(M, F)
Veron 2000, 1996
Roniewicz and
Morycowa (1989)
(P
(P , S )
D ) (M, F) (S)
Miocene
Oligocene
Eocene
67
Palaeocene
late Cretaceous
mid Cretaceous
Early Cretaceous
Late Jurassic
Mid Jurassic
Early Jurassic
Late Triassic
Figure II -12
(M, F)
Wells 1956
(D)
(P , S )
(M, F)
(D)
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.
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74
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.
75
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.
corallites are very small, irregular, perforated and highly variable.
In Porites,
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.
76
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
77
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
78
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
79
(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
80
(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 III3). 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/.
81
The distances in
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)
82
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 userdefined 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 datapoints.
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).
83
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
84
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
85
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
86
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
87
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.
88
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
89
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
90
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
91
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.
92
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
93
Table III-1
94
Species
P. lobata-panama*
P. lobata
"
"
"
"
"
"
"
"
"
"
Region
Panama* (EP)1
Easter Isl. (CP)1
Australia (WP)2
Rarotonga (WP)1
Tahiti (CP)1
Galapagos (EP )3
Fiji (CP)1
ITS-1
Length
(bp) %(G+C)
303-311
43.27
303-312
42.02
305-325
42.17
306-309
42.27
306-309
41.96
306-307
42.29
305-309
41.91
SE
0.19
0.47
0.43
0.26
0.43
0.34
0.41
ITS-2
Length
No of
No of
(bp) %(G+C) SE Individuals Sequences
228-229
44.91
0.23
4
7
215-226
43.89
0.22
4
10
210-223
43.91
0.75
2
7
207-226
44.16
0.45
3
9
207-231
43.89
0.43
3
9
209-225
44.04
0.49
4
15
215-223
43.81
0.83
3
7
Total
23
64
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.
95
Table III-2
Mean Difference Within and Between Groups
A
E
F
A
0.012
±0.005
0.004
0.006
E
0.013
0.010
±0.004
0.019
F
G
96
R
0.018
0.014
0.013
0.014
0.012
ITS-1
G
Net Difference Between Groups
A
E
F
ITS-1
G
R
~
0.001
0.003
0.002
0.002
0.002 0.008
~
0.003
0.002
0.002
0.002 0.010
~
0.001
0.002
0.002 0.009
G 0.003 0.004
0.001
~
0.001
0.001 0.009
0.010
R 0.003 0.003
0.004
0.002
~
0.001 0.010
0.010
T
0.003 0.003
0.003
0.002
0.002
~
0.009
P 0.020 0.027
0.025
0.023
0.027
0.024
~
T
P
R
T
P
0.005
0.004
0.005
0.009
A
0.006
0.005
0.004
0.005
0.010
E 0.002
0.016
±0.006
0.005
0.005
0.005
0.010
F
0.015
0.011
±0.004
0.004
0.004
0.010
0.012
0.009
±0.004
0.004
0.016
0.004 0.006
T
0.014
0.013
0.016
0.012
0.012
0.010
±0.004
P
0.027
0.033
0.034
0.030
0.033
0.030
0.003
±0.002
A
E
F
ITS-2
G
R
T
P
0.019
±0.006
0.007
0.004
0.004
0.005
0.004
0.019
A
E
0.029
0.019
±0.005
0.006
0.006
0.006
0.006
0.019
E 0.011
F
0.016
0.024
0.009
±0.003
0.004
0.004
0.003
0.018
F
0.004
0.003
0.019
0.015
±0.005
0.004
0.015
0.009
±0.003
0.108
A
G
0.020
0.023
0.014
0.016
±0.004
R
0.019
0.022
0.016
0.018
T
P
0.014
0.110
0.024
0.114
0.010
0.106
0.013
0.108
0.117
T
P
A
E
F
ITS-2
G
R
~
0.004
0.001
0.001
0.002
0.001 0.019
~
0.004
0.002
0.002
0.004 0.018
~
0.001
0.001
0.001 0.019
G 0.002 0.006
0.002
~
0.001
0.001 0.018
0.019
R 0.002 0.005
0.004
0.003
~
0.001 0.019
0.019
T
0.001 0.011
0.002
0.001
0.003
~
0.019
0.005
±0.002
P 0.110 0.114
0.110
0.110
0.120
0.114
~
0.002 0.011
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).
97
Table III-3
(A) All Sequences Included
Source of Variation
d.f.
S.S.
V.C.
% Variation
Among Regions
Within Regions
5
50
59.115
181.076
(a) 0.89
(b) 3.62
19.79
80.21
Total
55
563.83
10.6
p < 0.0001
(B) Pairwise Fst and significance values between geographic regions
E
A
R
T
G
F
E
~
0.34
0.32
0.36
0.25
0.38
A
0.0001
~
0.12
0.09
0.12
0.07
R
0.0001
0.06
~
0.15
0.16
0.20
T
0.0001
0.07
0.01
~
0.07
0.15
G
0.0001
0.01
0.001
0.05
~
0.09
F
0.0001
0.15
0.01
0.01
0.05
~
(C) One sequence per individual
Source of Variation
Among Regions
Within Regions
Total
d.f.
5
13
18
S.S.
36.545
65.75
102.296
V.C.
(a) 0.72
(b) 5.06
5.78
% Variation
12.43
p < 0.02
87.57
(D) Easter Island excluded
Source of Variation
Among Regions
Within Regions
Total
d.f.
4
42
46
S.S.
29.38
138.64
168.02
98
V.C.
(a) 0.44
(b) 3.30
3.72
% Variation
11.78
p < 0.0001
88.22
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
Nc = Nested clade distance.
** = p < 0.01, Dc = 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.
99
Table III-4
Name
Haplotypes
Dc
Dn
Name
1-step
Dc
Dn
1-1
0
3412
Name
2-step
Dc
Dn
Name
3-step
Dc
Dn
r1-2
r6-4
0
0
e20-2
0
0
1-2
0
5118
2-1
e121-25
0
0
1-3
0
0
2-2
0
3412
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
t3-1
0
0
6937
6937
1-7
r1-3
g66-3
t6-4
7839
5891
1-8
5241 5362
2-5
6578 6659
0
3942
3-2 7931 L* 7231 L**
I-T 7029 L** 2348 L**
1-2-3-4
No:IBD
5405 5794
2-10
6762 5717
3-4
2-9
10142 6426
2-8
4168 5170
4-step
Dc
Dn
4094 3839
3-1 902 S** 4884 S**
6937 6871
g66-2
t3-2
t2-3
g7-6
6756
4504
6756
4504 1-19
f7-3
0
0
1-18
0
6766
f4-3
0
0
1-17
0
10142
g7-8
0
0
1-16
0
10142
r4-17
a2-9
0
0
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
e47-3
0
3578
g3-5
0
3578 1-10
1-9
5877
5877 1-13
Name
5877 3950
3578 2684
0
1789
2-7
2-6
0
2385
2862 2684
100
5923
3-3 2862 S*
I-T 3060 L*
1-2-3-4
No:IBD
6333
6328
4
exact contingency test
4-1 p < 0.01
4-1 6365
5909
4-2
6481
6064
4-2 p <0.05
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.
were calculated mathematically.
The distances between points
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.
101
Table III-5
Name
Points
Measured
SL1
SL2
SL3
SL4
SL5
SL6
SL7
SL8
SL9
SL10
SL11
SL12
SW1
SW2
SD1
SD2
SD3
SD4
SD5
SD6
SD7
SD8
SD9
SD10
SD11
SD12
PD1
PD2
PD3
PD4
PD5
PD6
PD7
PD8
PD9
PD10
FL1
FL2
FW
W
L
1:02
3:04
5:06
7:08
9:10
11:12
13:14
15:16
17:18
19:20
21:22
23:24
25:26
27:28
1:03
3:05
5:07
7:09
9:11
11:13
13:15
15:17
17:19
19:21
21:23
23:01
2:04
4:06
6:08
8:10
10:12
12:14
14:16
16:18
18:20
20:24
20:8
2:14
20:08
7:19
1:15
Description
Name
Description
Septa Length
Septa Length
Septa Length
Septa Length
Septa Length
Septa Length
Septa Length
Septa Length
Septa Length
Septa Length
Septa Length
Septa Length
Septa Width
Septa Width
Septa Distance
Septa Distance
Septa Distance
Septa Distance
Septa Distance
Septa Distance
Septa Distance
Septa Distance
Septa Distance
Septa Distance
Septa Distance
Septa Distance
Pali Distance
Pali Distance
Pali Distance
Pali Distance
Pali Distance
Pali Distance
Pali Distance
Pali Distance
Pali Distance
Pali Distance
Fossa Length
Fossa Length
Fossa Width
Width
Length
NP
TRI
FA
CA
Number of Pali
Triplet
Fossa Area
Corallite Area
102
Proportional
Variables
FACA
X1
X2
X3
X4
X5
X6
X7
LAT
FA/CA
20:24+4:10/5:7+19:21
24:4/23:3
SW/(1:2:13:14)
12:16/11:15
13:14/L
1:2/L
23:3/L
3:5+7:9+17:19+21:23/L
Averaged
Variables
APD
ASL
ASW
IRR *
Avg (PD)
Avg (SL)
Avg (SW)
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.
103
Figure III-1
99
F7-1
F7-3
G66-2
8 2 G7-6
G8-7
G8-8
95
A2-8
A2-9
F6-2
97
F6-4
81
80
T6-4
T6-7
T2-7
T2-8
T2-3
G7-5
G7-8
F4-3
F4-2
F4-4
R1-1
R1-3
69
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
79
A1-1
A1-41
96
A1-13
A1-23
E121-25
54
R6-6
7 3 E20-2
89
E20-7
E20-4
R1-2
R6-4
85
R6-4b
94
G8-10
E47-3
57
E47-4
67
E47-2
57
G3-5
E48-1
E48-3
89
E48-5
P
52
0 .0 1 2
104
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.
105
Figure III-2
A).
Entire ITS Region
R
G
E
P
T
A
0.012
B).
F
ITS-1
R
T
E
P
G
A
0.012
C).
F
ITS-2
R
G
E
T
P
F
0.012
106
A
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…
107
Figure III-3
4-2
4-1
3-4
3-1
3-2
2-1
2-9
3-3
G7-8
F4-3
R6-4
1-5
1-16
2-6
G8-10
R1-2
1-1
G8-8
1-17
1-9
2-10
E47-3
G3-5
1-2
2-4
1-10
G66-2
T3-2
F7-3
E20-2
G3-8
108
1-6
1-19
1-18
2-7
2-2
G7-6
T2-3
E48-1
G66-3
R1-3
E121-25
2-3
1-11
1-8
T6-4
A2-9
1-14
F6-4
1-4
1-15
1-13
T6-3
1-7
T3-1
R4-17
A2-8
2-8
A1-41
1-12
2-5
A1-13
1-3
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)
109
Figure III-4
A).
Genetic distance between populations
G
A
R
F
B).
C).
T
E
10 year (1993-2003) mean surface currents from satellite data
Monthly (centered on January 15) mean surface currents from satellite data
1.0 meter/sec (0.514 m/s = 1 knot)
110
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.
used in this study.
See Table III-3 for a list of measurements
The definitions of taxonomic characters are based on Weil 1992;
Weil et al. 1992; Veron 2000.
111
Figure III-5
Dorsal Directive
Lateral Pair
Fossa
Pali
Wall
112
Radi
Columella
Ventral Triplet
Free
Fused
Trident
Figure III-6
An example of geographical variation among P. lobata.
photographed at the same scale.
The images were
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.
113
Figure III-6
114
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.
115
Figure III-7
0.5
0.5
0.5
0.5
0.5
Average Septal Length (SL)
0.4
mm 0.3
0.4
8
6
0
0
0
R
A
V
0.3
0.2
116
3
1
0
F
T
G
E
P
F
~
~
~
***
***
1
~
~
***
**
8
6
0
0
0
R
A
V
0.1
Corallite Area (CA)
7
0
0
0
0
R
A
V
1
~
***
***
2
2
0
G
3
3
7
0
0
0
0
R
A
V
1
7
0
0
0
0
R
A
V
~
~
2
mm
A
F
1
0
0
E
0.20
0.20
0.20
0.15
0.15
0.15
P
~
A
F
F
T
G
E
P
F
~
~
~
***
***
A
F
0.10
0.05
F
~
~
***
***
~
F
T
G
E
P
~
A
F
0.10
P
~
~
2
0.15
A
F
mm
0.1
3
0.15
Average Septal Width (SW)
0.3
0.2
E
~
***
***
0
T
0.3
0.20
0.4
0.2
0.1
2
7
0
0
0
0
R
A
V
8
6
0
0
0
R
A
V
G
~
~
***
**
2
0.4
0.2
T
3
mm
0.3
0.1
F
~
~
~
~
~
2
8
6
0
0
0
R
A
V
0.2
0.1
F
T
G
E
P
0.4
0.20
A
F
0.10
0.05
0.10
0.05
0.10
0.05
0.05
T
G
E
P
~
**
***
~
~
~
~
~
***
~
Fossa Area (FA)
1.0
1.0
1.0
1.0
1.0
0.9
0.9
0.9
0.9
0.9
0.8
0.8
0.8
0.8
0.8
0.7
0.7
0.7
0.7
0.7
0.6
0.6
0.6
0.6
0.5
0.4
A
F
0.5
0.4
0.5
A
F
0.4
0.5
A
F
0.4
0.6
0.5
A
F
0.4
0.3
0.3
0.3
0.3
0.3
0.2
0.2
0.2
0.2
0.2
0.1
0.1
0.1
0.1
0.1
0.0
0.0
0.0
0.0
0.0
T
G
E
P
~
~
***
***
~
***
**
~
*
~
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.
Panamá region corallites were classified correctly.
95% of
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.
117
Figure III-8
5
4
3
2
Factor (2)
)
2(
E
R
O
C
S
Region
1
Easter Island
Fiji
Galapagos
Tahiti
Panama
0
-1
-2
-3
-4
-5
-3
-2
-1
0
1
2
SCORE(1)
Factor
(1)
3
Jackknifed Classification Matrix
E
F
G
T
P
Total
E
26
0
7
3
0
36
F
2
19
1
3
0
25
G
5
1
23
3
1
33
T
4
7
4
16
1
32
P
3
3
2
5
38
51
eigenvalues
2.255 1.427 0.351 0.229
118
%Correct
65
63
62
53
95
69
4
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.
119
Figure III-9
Variable
SL5
SL6
SL7
SL8
SL10
SL11
SD1
SD3
SD4
SD5
SD6
SD7
SD8
SD9
SD10
SD11
SD12
PD2
PD3
PD4
PD5
PD6
PD7
PD8
FL1
FL2
PD10
PD12
W
L
FA
CA
X1
LAT
APD
2
r
0.80 *
0.89**
0.83**
0.95***
0.68*
0.66*
0.88**
0.90**
0.75*
0.90**
0.92**
0.80*
0.98***
0.85**
0.95***
0.72*
0.85**
0.85**
0.79*
0.82*
0.97***
0.87**
0.81*
0.98***
0.90**
0.75*
0.94***
0.78*
0.96***
0.92**
0.97***
0.95***
0.66*
0.85**
0.98***
120
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123
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.
124
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.
125
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
126
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
127
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 1step 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,
128
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
129
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.
130
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
131
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
132
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.
133
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
134
multiple-copy gene families behave within a population, and between recently diverged
species, in order to solve the S. glynni paradox.
135
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.
136
Table IV-1
137
Species
Region
S. siderea
S. radians
S. stellata
S. glynni
Panamá (ATL)
1
Panamá (ATL)
2
Brazil (ATL)
1
Panamá (EP)
1
ITS-1
Length
(bp) %(G+C)
305
307
307-308
304-305
44.22
43.65
44.43
44.67
SE
ITS-2
Length
(bp) %(G+C)
No of
No of
SE Individuals Sequences
0.35
0.12
0.12
0.12
192-193
192
192
192
0.58
0.24
0.35
0.27
53.41
55.70
55.60
53.09
Total
3
2
1
4
13
6
3
16
10
38
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).
138
Table IV-2
g1c
139
g1a
g1c
g1d
g1a,g2a
g2d
g3c
g4d
g4c
s1a
s1b
s1d
s2b
s2d
A
B
s3a
r2b
R
ta
tb
tc
0.003
0.002
0.005
0.003
0.005
0.003
0.012
0.003
0.007
0.005
0.003
0.012
0.002
0.014
0.040
0.038
0.038
0.040
0.040
g1a,
g1d g2a g2d g3c g4d g4c s1a
s1b s1d s2b s2d
A
B
s3a
r2b
R
ta
tb
0.002
0.005 0.003
0.003 0.002 0.005
0.005 0.003 0.007 0.005
0.003 0.002 0.005 0.003 0.005
0.015 0.014 0.017 0.015 0.017 0.015
0.003 0.002 0.005 0.003 0.005 0.003 0.015
0.010 0.008 0.012 0.010 0.012 0.010 0.009 0.010
0.005 0.003 0.007 0.005 0.007 0.005 0.010 0.005 0.008
0.003 0.002 0.005 0.003 0.005 0.003 0.015 0.003 0.010 0.005
0.015 0.014 0.017 0.015 0.017 0.015 0.000 0.015 0.008 0.010 0.015
0.002 0.000 0.003 0.002 0.003 0.002 0.014 0.002 0.008 0.003 0.002 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
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
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
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
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
0.040 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
tc
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).
140
Table IV-3
141
ITS-1
ITS-2
~
~
~
~
~
0.004-0.010
~
~
~
~
0.0047-0.0060 0.0055-0.0070
0.0029-0.0018
~
ITS-1 & 2
0.008-0.020
0.011-0.012
~
.003625-.00725
0.004
0.0039-0.0050
~
Organism
Cladophora (Green algae)
Drosophila
Triatominae (Hemipteran)
Cucurbitaceae (cucumber)
Birches and Alders
Hawaiian silversword
Primates
Aproximate
generation time
hrs-days
11-15day
5-10months
1-4 years
7-30years
2-20years
4-20 years
Reference
Bakker et al. 1995
Schlotterer et al. 1994
Bargues et al. 2000
Jobst et al. 1998
Savard et al. 1993
Baldwin, (personal communication)
Gonzalez et al. 1990
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.
142
Table IV-4
Name
Haplotypes
Dc
Dn
1-step
Name
Dc
Dn
2-step
Name
Dc
Dn
143
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
g2d
0
0
1-4
0
2.26
g4d
0
0
1-5
0
2.42
s2c
0
0
1-6
0
3.58
g1a,g1b,s1c,g2a,g2b,
g2c,s2a,g3a,g3b,s2c
g4a,g4b,s3b
g1-5
g1d
g3c
g4c
s1b
s2d
2.89
2.79
1-7
3
2.9
0
0
0
0
0
0
2.22
2.17
2.17
2.22
3.83
3.78
Name
3-step
Dc
4-step
Dn
3-1
0.63 S***
2.91
4-1
2-3
0
0
3-2
2.97 S** 3.14 L**
I-T
2.34 L*** 0.017 L**
1-2-3-5-6-13-14
Yes:LDC
exact contingency
test
4-1 p < 0.014
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.
144
Figure IV- 1
Algae
0.02
Drosophila
0.018
Hemipteran
145
0.016
Cucurbitaceae
0.014
µ/
106 years 0.012
Primates
Silversword
0.01
Birch Tree
0.008
0.006
2
r = 0.9721
0.004
0.002
0
0.1
1
10
100
1000
Generation time (days) in log scale
10000
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.
site.
The scale is proportional to number of nucleotide substitutions per
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.
146
Figure IV- 2
61
86
97
71
83
63
1 00
62
0.01 6
0.012
0.008
Substitutions /site
147
0.004
g3b
g4d
s2a
g3c
s3b
g1a
g2a
g1d
g4a
g3a Clade A
s2d
g4c
s2c
g3d
s1b
g1b
g2d
g4b
g2b
s1c
g2c
g1c
s2b
s3a
s1e
s2f Clade B
s1f
s1a
s2e
stellata
radians
0.000
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…
148
Figure IV-3
3-2
3-1
2-3
1-7
2-2
g3c
g4c
g1d
s2b
149
s1b
2-1
s1a, s1e, s1f
s2e, s2f
1-3
g1a, g1b, s1c
g2a, g2b, g2c, s2a
g3a, g3b, s2c
g4a, g4b, s3b
1-2
g1c
s2d
1-1
s3a
1-6
s2c
1-5
g4d
1-4
g2d
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151
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.
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(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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