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MOLECULAR PHYLOGENETICS AND DIVERSITY OF THE ACACIA KOA
COMPLEX BASED ON DNA SEQUENCES AND MICROSATELITIE MARKERS
A THESIS SUBMITIED TO THE GRADUATE DIVISION OF THE UNIVERSITY OF HA WAI'I IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
IN
MOLECULAR BIOSCIENCES AND BIOENGINEERING
MAY 2008
By Daniel Adamski
Thesis committee:
Dulal Borthakur Chairperson Clifford Morden Chifumi Nagai
We certify that we have read this thesis and that, in our opinion, it is satisfactory in scope
and quality as a thesis for the degree of Master of Science in Molecular Biosciences and
Bioengineering.
THESIS COMMI1TEE
Chairperson
tktJJtJ~-c4f' n~
ii
ACKNOWLEDGEMENTS
I would like to recognize the people who have guided me throughout my
educational journey. First and foremost, a great deal of thanks to my advisor Dr. Dulal
Borthakur for giving me the opportunity and freedom to shape my research project to my
interests, and always making time to provide insight on both research and life. I am
grateful to my committee members Dr. Cliff Morden and Dr. Chifumi Nagai for investing
a great amount of time and energy to help me achieve my research goals. I would also
like to thank my lab mates, especially Sandro Jube and Rudolf Fredua-Agyeman, for their
guidance and patience in the lab, and friendship. This project would not have been
possible without the help of Nick Dudley, Steve Smith, Dr. James Brewbaker, and Dr.
James Leary, who assisted me with numerous field collections and provided a wealth of
knowledge concerning koa Finally I would like to thank my family and my parents,
Susan and Thomas Adamski, for their support and encouragement throughout the years.
iii
ABSTRACT
The Acacia koa complex, commonly referred to as koa, is a group of nitrogen
fixing legumes native to the Hawaiian Islands. Within the complex, A. koa and A. koaia
are accepted nomenclature. Intermediate forms ofkoa, described in this study as 'group
three', include individuals with the tree structure of A. koa and seed pod structure of A.
koala, or vise versa, which is similar to populations described as A. kauaiensis Hillebrand
(St. John, 1979; Wagner et at., 1999). These three groups of the koa complex, A. koa, A.
koaia, and 'group three', were characterized using molecular techniques. DNA
sequencing from nuclear (ITSl I 5.8S I ITS2) and chloroplast (trnK I matK) regions
placed koa within the subgenus Phyllodineae, and showed a close relationship with
Acacia melanoxylon. Differentiation among groups of koa based on sequencing results
was inconclusive. A total of 106 alleles were detected among koa groups using 12
different rnicrosatellite markers, with an average of 8.8 alleles per polymorphic locus
(AP). 'Group three' had the highest genetic diversity (H = 1.578), average alleles per
locus (AP = 7.9), and number of unique alleles (21). The A. koaia group showed the
lowest diversity (H = 0.960), and was differentiated from A. koa and 'group three' in
analysis using an unweighted pair group method with arithmetic mean (upGMA)
dendogram and principle coordinate analysis. An analysis of molecular variance
(AMOVA) found genetic variation partitioned within populations (72.2%) rather than
among populations (27.8%). Clustering in the UPGMA dendogram, principle coordinate
analysis, and genetic differentiation revealed three distinct groups among the populations.
Koa-specific rnicrosatellite markers showed little success in cross-amplification of non
native acacias found in Hawaii. This study provides molecular evidence distinguishing
three groups of the A. koa complex; A. koa, A. koaia, and 'group three', found only on
Kauai and similar to A. kauaiensis.
iv
TABLE OF CONTENTS
Acknowledgements ................................................................................... iii Abstract. ..................................................................................................... .iv List of Tables ............................................................................................. vii List of Figures .......................................................................................... viii List of Abbreviations ................................................................................... x Chapter I: Introduction ................................................................................ I Chapter 2: Literature Review ..................................................................... .5
Acacia ..................................................................................................... 5 Koa Origin .............................................................................................. 5 Ploidy I Cytology .................................................................................... 6 Classification I Morphology ................................................................... 7 Distribution ........................................................................................... 14 Conservation Status .............................................................................. 14 Island Characteristics I Genetic Variability .......................................... 15 Koa Decline and Disease ...................................................................... 16 Reproduction ........................................................................................ 19 Plant Development ............................................................................... 19 Field Experiments ................................................................................. 21 Phylogenetics ........................................................................................ 22 Molecular Genetic Markers .................................................................. 23 Isozymes ............ " ................................................................................. 23 AFLPs ................................................................................................... 24 RAPDs .................................................................................................. 24 RFLPs ................................................................................................... 25 Microsatellite Markers .......................................................................... 25 DNA sequencing ................................................................................... 28
Chloroplast trnK intron and matK coding sequence ...................... 29 Internal transcribed spacer regions (ITS 1 and ITS2) of nuclear ribosomal DNA .............................................................................. 30
Chapter 3: Experimental Methods ............................................................. 32 Plant material sampling and DNA isolation ......................................... 32 Sequence amplification and analysis .................................................... 36
Chloroplast trnK intron and matK coding sequence ........................ 36 Interoal transcribed spacer regions (ITS) of nuclear ribosomal
DNA ......................................................................................... 39 Microsatellite marker amplification and analysis ................................. 41 Data Analysis ....................................................................................... .42
trnK I matK and ITS1/5.8S I ITS2 sequencing ............................. .42 Microsatellite marker analysis ......................................................... 46
Cross-species amplification .................................................................. 51 Chapter 4: Results ...................................................................................... 53
Chloroplast trnK intron and matK coding sequence ............................. 53 Internal transcribed spacer regions (ITS) of nuclear ribosomal
DNA ......................................................................................... 55
v
Multiplexing of microsatellite markers ................................................ 57 Microsatellite markers ......................................................... ................. 57 Cross-species amplification .................................................................. 69
Chapter 5: Discussion ................................................................................ 74 DNA sequencing ................................................................................... 75 Molecular studies .................................................................................. 76 Microsatellite markers / Diversity ........................................................ 76 Microsatellite markers / Population differentiation .............................. 77 Cross-species amplification .................................................................. 80 Koa groups ............................................................................................ 80 Conclusions / Applications ................................................................... 81
References ................................................... : ............................................. 83
vi
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LIST OF TABLES
1. Variation in morphological characteristics among groups ofkoa .... 33
2. Population description for koa samples ............................................ 33
3. Species used for trnK / matK analysis .............................................. 44
4. Species used for ITS 11 5.8S I ITS 2 analysis .................................. .45
5. Microsatellite marker primer sequences, annealing temperature, and allele sizes ............................................................................. 47
6. Total number of alleles at each locus for groups ofkoa ................... 59
7. Diversity statistics over all loci for groups in the A. fwa complex ... 61
8. Genetic diversity of 11 populations in the A. fwa complex .............. 61
9. Matrix of pairwise differentiation between II populations of koa, based on microsatellite allele scoring .................................. 63
10. Cross species amplification ofkoa-specific markers by non-native acacias from Hawaii .................................................................... 71
vii
LIST OF FIGURES
Figure
1. A. koaia tree with domed canopy .................................................... 8
2. A. koaia tree displaying gnarled habit ............................................. 8
3. Narrow seed pods and longitudinally arranged seeds found on A. koaia ....................................................................................... 9
4. A. koaia phyllode shape, generally long and narrow ....................... 9
5. Large tree size of A. koa ................................................................ 10
6. High branching pattern of A. koa ................................................... l 0
7. Wide seed pods and transversely arranged seeds of A. koa ........... II
8. Wide phyllodes of A .. koa .............................................................. 11
9 . Variation of wood color found in koa ........................................... 11
10. Variation in koa tree form on Kauai and Oahu for 'group three' .. 12
11. Phyllode variation in 'group three' ................................................ 13
12. Seed pod variation in 'group three' ............................................... 13
13. Crown thinning in koa tree ............................................................ 18
14. Complete defoliation ofkoa tree ................................................... 18
15. Koa wilt symptoms of cankers (left) and sap bleeding (right) ...... 18
16. Bipinnately compound tree leaves ofkoa seedlings ...................... 20
17. Transition from producing true leaves to phyllodes in koa ........... 21
18. Stutter bands produced during amplification ofDNA ................... 27
19. Map of sample populations on the islands ofKauai, Oahu, and Hawaii ................................................................................ 34
20. Terminology used to describe koa ................................................. 35
viii
21. Diagram of the chloroplast trnK intron I matK coding regions .... 37
22. Diagram of rDNA cistron for the ITS region in Acacia .............. .40
23. Majority rule consensus tree of 10,000 most parsimonious trees from trnK I matK sequence analysis .............................. 54
24. Majority rule consensus tree of 10,000 most parsimonious trees from ITSl/5.8S I ITS2 sequence analysis ................... 56
25. Electropherogram of allelic scoring for A. koa, A. koaia, and 'group three' for primer AmS02 .............................................. 60
26. Total alleles, unique alleles, and genetic diversity in koa ............ 60
27. Comparison of genetic differentiation and geographic distance between populations ............................................................... 63
28. Dendogram of 11 populations of the A. koa complex revealed by UPGMA cluster analysis based on pairwise differentiation ......................................................................... 64
29. Principle coordinate analysis for micro satellite analysis ofkoa populations .............................................................................. 65
30. Principle coordinate analysis for individuals, labeled for each group ....................................................................................... 67
31. Principle coordinate analysis for individuals, labeled for each population ............................................................................... 68
32. Principle coordinate analysis for individuals, labeled according to population and group ......................................... 70
33. Cross-species amplification results from microsate11ite marker Ak37, with expected fragment size of21 0 bp ........................ 72
34. Cross-species amplification results from microsate11ite marker Ak284, with expected fragment size of242 bp ...................... 72
ix
A AFLP Ak Am AMOVA AN AP AR bp C CON cpDNA DBH DNA Dst ETS FAM FDASH Fst g GBIF GTHR H h Ff'w
H HG HT IGS INUC
ms ITS KANA KHAN KKA KMC KNT KOA KOAA KOAB KOAlA KTSA KTSB
LIST OF ABBREVIATIONS
(Acacia) (amplified fragment length polymorphism) (Acacia koa) (Acacia mangium) (analysis of molecular variance) (Acacia angustissirna) (average alleles per polymorphic locus) (Acacia auriculiformis) (basepair) ( degree celsius) (Acacia confusa) (chloroplast deoxyribonucleic acid) (diameter at breast height) (deoxyribonucleic acid) (average diversity among populations of each group) (external transcribed spacer) (fluorescent dye color) (statistics software) (FDASH genetic differentiation) (gram) (Global Biodiversity Information Facility) ('group three') (Nei's genetic diversity) (hour) (Shannon-Weaver diversity index) (FDASH diversity) (FDASH average diversity within populations of each group) (FDASH total genetic diversity) (intergenic spacer) (International Union for the Conservation of Nature and Natural Resources) (Integrated Taxonomic Information System) (internal transcribed spacer) (Anahola) (Hanalei) (Awa'awapuhi Trail) (Kokee-Mohihi) (Nounou Ridge) (AcaCia koa group) (Hakalau Wildlife Refuge)
. (Pua Akala) (AcaCia koaia group) (Koaia Tree Sanctuary) (Kohala Road)
x
KV (Kahana Valley) L (liter) LSU (large subunit) M (Mimoseae) m (meter) MAC-PR (microsatellite allele counting-peak ratios) matK (maturase encoding gene) MO (Acacia mangium) min (minute) ML (Acacia melanoxylon) mmol (millimole) MR (Acacia mearnsil) N (negative control) NCBI BLAST (National Center for Biotechnology Information Basic Local Alignment
NED ng p PCR PET pmol RAPD rbcL rDNA RFLP RFU SO SSLP SSR SSU STR trnK uL UPOMA VIC
Seach Tool) (fluorescent dye color) (nanogram) (percent polymorphic locus) (polymerase chain reaction) (fluorescent dye color) (picomole) (random amplification of polymorphic DNA) (large subunit of ribulose bisphosphate carboxylase/oxygenase) (ribosomal deoxyribonucleic acid) (restriction fragment length polymorphism) (relative fluorescent units) (Waimea) (simple sequence length polymorphism) (simple sequence repeat) (small subunit) (simple tandem repeat) (transfer RNA gene for lysine) (microliter) (unweighted pair grouping of arithmetic average) (fluorescent dye color)
xi
CHAPTERl INTRODUCTION
The Acacia koa complex (koa) is a group of both shrubby and arboreal nitrogen-
fixing tree-legumes native to the Hawaiian Islands (pedley, 1975; Wagner et al., 1999).
Koa thrives on well-drained, volcanic soils at elevations predominantly between 800-
1600 m, although populations can be found as low as 100 m and up to 2300 m (Whitesell,
1990; Sun, 1996a; Elevitch, 2006). In addition to providing high value timber for
Hawaii's $29 million/annum forest industry, koa plays a vital role in Hawaii's watershed
ecosystem, serving as habitat for endangered birds and epiphytic plants (Whitesell, 1990,
Elevitch, 2006; HFIA, 2007). Koa is a polyploid species with an outcrossed breeding
system, and is thought to be self-incompatible because of unsuccessful self-pol1ination
studies (Sun, 1996a). However, this classification is speculative and only the tetraploid
nature ofkoa has been supported by ploidy analysis (Shi, 2003; Hipkins, 2004).
Morphologically, koa is similar to species from the largely Australian subgenus
Phyllodineae (Miller et aI., 2003). At lower taxonomic levels, koa is classified into many
different types based on island origin and morphological characteristics, but only two
types, A. koa A. Gray and A. koaia Hillebrand, are formally accepted (GBIF Data Portal,
2007). There are also descriptions of groups that are argued to be distinct subspecies or
varieties, although they are not formally recognized (St John, 1979, Wagner et al., 1999,
GBIF Data Portal, 2007; ms, 2007). These include: A. kauaiensis Hillebrand, A.
hawaiiensis Rock, A. Ianaiensis Rock, A. lati/olia Bentham, A. waianaeensis St. John,
and variant populations exhibiting hybrid morphological characteristics. Differences
1
among groups are most evident in tree size, seed alignment within the pod, and phyllode
size and shape.
Common garden studies have shown that families from Hawaii, when compared
to those from Oahu and Kauai, have significant differences in seed width and mass, as
well as phyllode length and width (Daehler et al., 1999). Variations in isozyme loci have
been shown for koa populations on different islands in the State of Hawaii (Brewbaker,
1977; Conkle, 1996). Koa from Maui, Oahu, and Kauai are closely related, and their
isozyme allele profiles differ greatly from koa on Hawaii (Conkle, 1996).
Distinguishing characteristics of A. koala include shrubby form, tree height up to
5 m, longitudinally arranged seeds, and various phyllode shapes which are usually short
and narrow. Acacia koa, on the other hand, has a large tree height reaching up to 35 m,
transversely arranged seeds, and phyllodes that are generally wide and long (Wagner et
al., 1999).
Among the groups of informal taxa are populations that have morphological
characteristics that are a mixture of those found in A. koa and A. koaia, that will be
referred to as 'group three'. These morphologically variable populations are influenced
by environmental conditions, animal grazing, and genetics (Harrington et al., 1997;
Daehler, et al., 1999; Elevitch, 2006). Koa found on Kauai are especially difficult to
classify based on morphological characteristics because different ecotypes are thought to
2
exist due to extreme changes in elevation, rainfaII, and soil types over short geographical
distances (St. John, 1979; Smith, S., personal communication).
In addition to koa, other non-native acacias are found in Hawaii that have been
planted over the past 100 years as windbreaks, biomass for energy, and for scientific
research (Friday, J., personal communication). Many of these non-native acacias have
become naturalized and include: A. angustissima, A. auriculiformis, A. confosa, A.
mangium, A. mearnsii, and A. melanoxylon.
Koa forests have been reduced over the past 100 years due to land clearing for
agriculture, ranching, and a devastating koa wilt disease caused by the fungal pathogen
Fusarium oxysporum f sp. koae (Anderson et al., 2002). However, A. koa is still
commonly found throughout Hawaii. On the other hand, A. koaia is on The World List 0/
Threatened Trees (Oldfield et aI., 1998) and the International Union for Conservation of
Nature and Natural Resources (lNUC) Red List o/Threatened Species (Bruegmann et al.,
2003). SmaIl population size accompanied with a low total number of trees makes A.
koaia vulnerable to extinction if it is not protected from disease and habitat degradation
(Bruegmann et al., 2003).
As koa are morphologically variable within populations that comprise each
described group, it is difficnlt to differentiate populations as common (A. koa), rare (A.
koaia), or unknown ('group three'). For conservation of rare taxa, the genetic and
evolutionary distinctiveness of populations are essential priorities. Genetic studies are
3
needed to determine distinctness, phylogenetic status, and diversity in koa, especially in
small and fragmented populations. Molecular tools such as DNA sequencing and
microsatellite markers are useful for conservation and population genetic studies, as they
resolve differences at the genus and species levels (Murphy et al., 2003; Doyle and
Luckow, 2003).
The objectives of this investigation are to determine the phylogenetic placement
ofkoa within the Acacia genus using DNA sequencing (S.8s rDNA and ITS regions, and
chloroplast trnK / matK regions). The utility of microsatellite markers for analyzing koa
groups will also be assessed, and polymorphic microsatellite loci will be used to
determine population distinctiveness and genetic diversity between three groups of koa;
A. koa. A. koaia. and 'group three'. Finally, microsatellite markers will be tested for
cross-species amplification of DNA from non-native Acacia species found in the Hawaii
Islands. I expect to find highest levels of genetic diversity in the A. koa group, as it is
most common and widely distributed in the Hawaiian Islands. The distinctiveness
between populations is expected to be greatest between populations in the A. koa group
from Hawaii and 'group three' populations from Kauai as they are geographically
isolated and morphologically variable. The success of cross-species amplification is
expected to be low, based on amplification of DNA from Australian Acacia species using
microsatellite markers from A. mangium (Butcher et al., 2000).
4
Acacia
CHAPTER 2 LITERATURE REVIEW
The genus Acacia (Fabaceae:Mimosoideae) is non-monophyletic, having several
lineages among the species (Wagner et al., 1999; Clarke et al., 2000; Miller and Bayer,
2001, 2003). Encompassing over 1380 species found in Asia, Africa, North and South
America, and Australia, Acacia is classified into three subgenera: Acacia, Aculeiferum,
and Phyllodineae (Heterophyllum) (Maslin, 2003; Murphey et al., 2003). Koa,
morphologically classified in the largely Australian subgenus Phyllodineae, is native to
the Hawaiian Islands and includes A. koa and A. koaia (pedley, 1975; Wagner et al.,
1999). Traditionally, Hawaiians carved seafaring canoes from the bole of large koa trees,
and presently koa is used to produce high value furniture, crafts, and instruments because
of its distinct grain and wood color (Cuddihy and Stone, 1990; Whitesell, 1990; Daehler,
et at., 1999). Koa also plays a vital role in Hawaii's watershed ecosystem, and is
important habitat for epiphytic plants and birds, some of which are endangered (Rock,
1913; Whitesell, 1990; Elevitch, 2006).
KoaOrigin
Koa is thought to be a descendent of seed that floated into the Indian and Pacific
Oceans (Carlquist, 1965). Acacia heterophylla, endemic to Reunion and the Mascarene
Islands in the Indian Ocean, is morphologically similar to koa (Whitesell, 1990).
Differences between the two include larger pods and seeds for A. koa, and also racemes
5
with more heads, and distinct petals (Vassa1, 1969; Pedley, 1975; and Wagner et oJ.,
1999). It is also suggested that both A. koa and A. heterophylla share a common ancestor
in A. melanoxylon (Coulaud et al., 1995, Wagner et aZ., 1999).
Ploidy I cytology
The genus Acacia has a base chromosome number x=13, and counts 2n=26,
2n=52, 2n=78, and 2n=104 have been reported (Atchison, 1948; Darlington and Wylie,
1955; Carr, 1978; Bennett and Leitch, 1995). Different ploidy levels (diploids to
octaploids) can be found within species in Acacia, as is the case with A. torti/is, which
has both tetraploid and octaploid individuals (Bukhari, 1997). Blakesley et aZ. (2002)
reported naturally occurring triploid and tetraploid genotypes of A. dealbata, but no
tetraploids of A. mangium. It has been suggested that koa is an allotetraploid from
species hybridization (Brewbaker, 1996; Shi, 2003). A past study suggests A.
heterophylla, which is a koa relative, may be an autotetraploid of A. melanoxyZon
(Couland et aZ., 1995), though this relationship is based on morphological similarities, not
chromosome experiments. While not studied in depth, koa is known to be tetraploid
(2n=4x=52) (Atchison, 1948; Pedley, 1975; Carr, 1978; Conkle, 1996; Shi, 2003).
Ploidy analysis of A. koa seed from the island of Hawaii and Kauai showed no variation
in ploidy levels, although one sample appeared to have a variable chromosome number
(Hipkins, 2004). In plant biology, variable chromosome number can be caused by
chromosome fragmentation, imbalance, fusion, or aneuploidy (Briggs and Walters,
1997). Shi (2003) also showed individuals from A. koa, A. koaia, and intermediate
('group three') populations having 2n=52 chromosomes and no variation in chromosome
6
number. It has been proposed that koa is an allotetraploid due to the fact that it is self
sterile, and because secondary constrictions are found in some pairs of chromosomes
(Shi, 2003). This characterization is based on chromosome studies by Shi (2003), and no
further studies have been undertaken to confirm this origin.
Classification I Morphology
Hawaiian koa is generally separated into three groups, that constitute either
distinct species or subspecies/varieties. These groups include A. /coa Gray, A. /coaia
Hillebrand, and A. /couaiensis Hillebrand. Additionally, A. hawaiiensis Rock, A.
lanaiensis Rock, A. lati/oUa Bentham, and A. waianaeensis St. John have been used to
characterize varieties of koa (St. John, 1979, Gardner, 1980, and Wagner et al., 1999).
Only A. /coa and A. /coaia are currently accepted as taxonomic classifications for
Hawaiian koa (The PLANTS Database, 2000; NatureServe. 2006, GBIF Data Portal,
2007). Therefore, morphological descriptions will be concentrated on these two types,
along with a brief description of A. kouaiensis.
Differences are most evident in tree size, seed alignment within the pod, and
phyllode size and shape. Acacia /coaia is a small tree with a domed canopy (Figure 1),
gnarled habit (Figure 2), and reaches heights up to 5 m (Wagner et al., 1999, Elevitch,
2006). Seed pods are narrow with longitudinally arranged seeds (Figure 3), that are
smaller than those produced by A. /coa. Additional distinctions include phyllodes that are
shorter and narrower than A. /coa (Figure 4). although this characteristic varies widely by
island and habitat. Furthermore, A. /coaia has denser wood, and usually grows in drier
7
Figure 1. A. koaia tree with domed canopy.
Figure 2. A. koaia tree displaying gnarled habit.
8
Figure 3. Narrow seed pods and longitudinally arranged seeds found on A. koaia.
Figure 4. A. koaia phyllode shape, generally long and narrow.
9
and more open habitats than A. koa, although a few populations have been found in mesic
habitats (Wagner et al., 1999).
A. koa is a large tree (Figure 5) reaching heights up to 35 m, with tree form
including both high (Figure 6) and low branching patterns (Wagner et aI. , 1999, Elevitch,
2006). Seed pods are wider than those of A. koaia and have the distinction of
transversely arranged seeds (Figure 7). Phyllode shape varies greatly, but generally is
long, wide, and curved (Figure 8). Acacia koa is found in a variety of habitats, including
both wet and dry forests (Wagner et al., 1999). Koa wood color varies widely, spanning
colors from blond to red to dark brown (Figure 9), and will rarely display an
economically valuable curl, known as fiddleback. Both A. koa and A. koaia have
expansive lateral root systems that are exposed on the so il surface, that makes them
susceptible to suckering when damaged or stressed (Elevitch, 2006).
Figure 5. Large tree size of A. koa. Figure 6. High branching pattern.
10
Figure 7. Wide seed pods and transversely arranged seeds of A. koa.
Figure 8. Wide phyllodes of A. koa.
Figure 9. Variation of wood color found in koa.
I 1
Acacia kauaiensis (similar to 'group three') is distinct to Kauai above elevations
of 1,000 m, has a short habit, and pods like those of A. koa. However, populations are
also found on Kauai with the habit and phyllodes associated with A. koa, but seed pods
characteristic of A. koaia (Wagner et al., 1999). Additional populations found below
1,000 m on Kauai and Oahu have similar variations in morphological traits. 'Group
three' consists of koa that cannot be accurately characterized based on morphological
characteristics due to wide variation in tree form (Figures 10), phyllodes (Figure 11), and
seed pods (Figure 12). While A. kauaiensis is not officially recognized, evidence
suggests further investigation could reveal species divergence or hybridization, especially
in populations fitting the morphological profile of A. kauaiensis.
Figure 10. Variation in koa tree form on Kauai and Oahu for 'group three'.
12
Figure II . Phyllode variation in 'group three' .
13
Figure 12. Seed pod variation in 'group three'.
Distribution
Koa grows on a variety of volcanic soils, being most productive on those that are
well drained (Whitesell, 1990, Elevitch, 2006). The distribution of koa is influenced by
rainfall and elevation. Koa thrives at elevations ranging 800-1600 m and receiving
between 1,900 and 5,100 mm of annual rainfall (Whitesell, 1990; Sun, 1996a). Acacia
koa is common, and found on the Hawaiian Islands of Hawaii, Molokai, Maui, Lanai,
Oahu, and Kauai at elevations ranging from 100-2300 m. Acacia koaia is rare and
usually found as fragmented populations on the islands of Hawaii, Molokai, Maui, Lanai,
and Kauai (Elevitch, 2006). In addition, A. koaia generally grows at lower elevations in
open, drier habitats than A. koa (Wagner et al., 1999).
Conservation status
Acacia koa has been negatively impacted by ranching, but is still widely
distributed throughout the major Hawaii Islands. Its conservation status is presently
secure.
Acacia koaia was categorized as vulnerable on The World List of Threatened
Trees (Oldfield et al., 1998) and the INUC (International Union for Conservation of
Nature and Natural Resources) also included A. koaia on the Red List of Threatened
Species (Bruegmann et. aI., 2003). It currently has a global status ranking of 02, which is
described as imperiled (NatureServe, 2006). Specific characteristics of these rankings
include rare species with limited habitats that are often fragmented. Threatened trees are
14
also vulnerable to hybridization, inbreeding, and various pathogens. Small population
size accompanied with a low total number of trees leaves A. koaia vulnerable to
extinction if not protected and reforestation efforts implemented (Oldfield et al., 1998;
Bruegmann et al., 2003). One preservation area is the Koaia Tree Sanctuary on the island
of Hawaii, an enclosed area for preservation of A. koaia approximately 70 acres in size.
Island Charaeteristics I Genetic Variability
Acacia koa has wide variation in phenotypic characteristics across the Hawaiian
Islands. Differences in phyllode width and shape. seed size. branch color. and nectary
characters are most pronounced (St. John, 1979; Daehler et al., 1999). These differences
are proposed to be a result of environmental conditions, genetic profile, or a combination
of the two (Lamoureux, 1971; Sun et al., 1996b; Daehler et al., 1999). Sun (1996a)
showed significant differences in tree height, DBH (Diameter at Breast Height), and
phyllode development among koa using progeny tests. Common garden studies have
shown that families from the island of Hawaii, when compared to those from Oahu and
Kauai, have significant differences in seed width and mass, as well as phyllode length
and width. These differences include longer, wider phyllodes with greater area, and
seeds that have a greater mass and width for Hawaii families. Additionally, nectary
diameter and branch color were also significantly different when compared to Oahu and
Kauai families (St. John, 1979; Daehler et al., 1999). These results suggest a genetic
basis in phenotypic variation between island families, and that Hawaii families are
distinguishable from those of Oahu and Kauai (Daehler et al., 1999).
15
Variations in isozyme loci have been shown for koa populations on different
islands in the state of Hawaii (Brewbaker. 1977: Conkle. 1996). Conkle (1996) showed
the number of alleles per gene in samples of koa populations ranged from three to seven
alleles for six polymorphic genes analyzed. Koa from Maui, Oahu, and Kauai are closely
related, and their enzyme allele profiles differ greatly from those of Hawaii (Conkle,
1996). These results also support the conclusions of Daehler et al. (1999) that koa from
Hawaii is genetically distinct from koa growing on Oahu and KauaL
Koa Decline and Disease
The decline of koa can be attributed to a number of factors: land clearing for
agriculture, fire, insects, fungi, and animal grazing (Scowcroft and Hobdy, 1987,
Brewbaker, 1996; Daehler et aI., 1999; Anderson et al., 2002; Shi, 2003). Most recently,
fungal pathogens and the black twig borer (Xylosandrus compactus) have been the main
cause of damage to koa trees (Anderson et al., 2002; Elevitch, 2006; Dudley et aI, 2007).
In Hawaii Volcanoes National Park, Gardner (1980) observed wilt disease
occurring in established stands of older koa trees. Root and stem tissues from wilted A.
koa. A. koaia. and A. confusa trees were used as sample material and the fungal pathogen
Fusarium oxysporum f sp. koae was isolated. The fungus was determined to be seed
born and the probable cause of premature decline in koa (Gardner, 1980), although other
Fusarium species may also playa role (Elevitch, 2006; Dudley et aI, 2007). Recently,
Anderson et al. (2002) reported that koa ranging in size from small saplings to mature
trees are affected by this fungus which causes a vascular wilt infection. Trees less than
16
fifteen years old and occurring at elevations lower than 760 m are most frequently
affected, although koa wilt occurs at elevations up to 1650 m (Elevitch, 2006).
Various symptoms are associated with koa wilt disease, beginning with yellowing
ofphyllodes, followed by thinning of the tree's crown (Figure 13). Eventually the entire
crown displays a chlorotic condition; necrosis of phyllodes ensues, leading to complete
defoliation of the tree (Figure 14) (Anderson et al., 2002). Accompanying symptoms
may include the development of cankers on bark, sap bleeding, and dark staining of
sapwood (Figure 15). The fungus appears to originate in the roots and spreads upward,
blocking vascular vessels, and causing canopy loss and tree death (Elevitch, 2006).
Although infection throughout the entire tree is common, sometimes only one or a few
branches are affected. Trees can survive with dead crowns for variable periods of time
(Anderson et al., 2002; Elevitch, 2006). As a response to crown death, trees produce
epicormic shoots on remaining healthy sections of the stem. A cycle of epicormic shoot
production and eventual shoot death progresses downward along the stem until no
healthy parts of the stem remains, and the infection kills the entire tree (Anderson et al.,
2002).
The presence of Fusarium pathogens in soil does not automatically cause disease
unless conditions for infection are favorable (Elevitch, 2006). Anderson et al. (2002)
observed koa stands with healthy trees in close proximity, 50-100 m, to stands with wilt
symptoms. Localized infections spread in a radial pattern from a central infection area,
17
T ,
Figure 13. Crown thinning in koa tree. Figure 14. Complete defoliation ofkoa tree.
Figure 15. Koa wilt symptoms ofcankers (left) and sap bleeding (right).
18
but are usually contained to defined stands of trees. Favorable conditions of high
humidity, heavy rain, and low elevation seem to enhance fungal infection and symptoms
of wilt disease. These characteristics make it difficult to determine if healthy-looking
trees are indeed disease free.
Reproduction
The dichogamous nature of koa, where the anthers mature before the stigma on a
single flower, favors an entirely outcrossed breeding system (Brewbaker. 1977). This
system is enhanced by insects cross-pollinating koa (Sakai, 1995). Some polyploid
acacias are able to reproduce by self-pollination, however, pollination studies have
indicated koa is not likely one of them (Brewbaker, 1996; Sun, 1996a). Koa is also able
to regenerate from seed banks and vegetatively from root suckers and stump sprouts, but
tall grass may inhibit growth. (Spatz and Mueller-Dombois. 1973; Hatfield et al .• 1996;
Elevitch. 2006). Recently, Nelson (2006) reported intraspecific grafting of A. koa, as
well as grafting onto rootstocks of A. mangium and A. confosa with success rates ranging
from 20-70%. This data suggests koa may be compatible with a variety of Acacia species
for grafting.
Plant Development
Koa is fast-growing during the first five years, potentially averaging more than
1.5 m/year, after which growth slows. Growth rates, especially stem diameter, are
influenced by soil type, adequate rainfall, elevation, and stand density (Whitesell, 1990;
Elevitch, 2006). As koa begins to grow it initially forms true leaves that consist of 12-15
19
bipinnately compound leaflets (Figure 16) (Whitesel~ 1990; Wagner, 1999). Plants
transition from producing true leaves to sickle-shaped phyllodes (Figure 17), usually
before the sapling reaches 2 m (Whitesell, 1990). Hansen (i 986) suggested that true
leaves are better adapted to early plant growth when moisture is sufficient, while
phyllodes provide better protection against drought once koa is established. This is a
reasonable presumption considering phyllodes close their stomata in 14 the time as true
leaves during darkness, as well as transpiring only about 20 percent as much as true
leaves during moisture stress (Walters et al. , 1984). While mature trees usually display
only phyllodes, true leaves may appear on the trunk, or protruding from roots, following
injury or infection (Whitesell, 1990).
Figure 16. Bipinnately compound tree leaves characteristic ofkoa seedlings.
20
Figure 17. Transition from producing true leaves to phyllodes in koa.
Field Experiments
Variation of quantitative traits m tree populations is often studied usmg the
common-garden approach. These studies focus on traits that are economically important
such as tree growth, surviva~ and disease tolerance (Krutovsky and Neale, 2005).
Corrunon-garden studies can identifY families that are adapted to either a specific
environment or broad range of environments (Krutovsky and Neale, 2005). This method
has been used in Hawaii to evaluate phenotypic variation in koa from different islands.
Significant differences were shown in seed, phyllode, and nectary characteristics among
families from Oahu, Kauai, and Hawaii, suggesting phenotypic variation in koa is under
genetic control (Daehler et al., 1999). While common garden approaches are useful for
determining variation in measurable traits, they have many disadvantages. Field
21
experiments are very time consuming, dependent on consistent seedling establishment,
and constrained by the long reproductive cycles of tree species (Nehra et at., 2005).
Additionally, these studies are relatively expensive and based solely on phenotypes
(Gonzalez-Martinez et al., 2006). Finally, the common-garden approach cannot explain
how much phenotypic variation can be accounted for by genetic diversity and population
structure.
Phylogenetics
Phylogenetics is the evolutionary relatedness of groups, and treats species as a
group of lineage connected individuals over time (Doyle and Luckow, 2003). There are
many approaches to reveal relationships among different species, most notably DNA
sequences and molecular markers. Both nuclear and chloroplast DNA sequences have
been used to explain phylogenetic relationships, while molecular markers such as
isozymes, restriction fragment length polymorphisms (RFLPs), random amplification of
polymorphic DNA (RAPDs), amplified fragment length polymorphisms (AFLPs), and
microsatellite markers have been used to determine diversity and distinctiveness for
Acacia species (Butcher et at., 2000; Broadhurst and Coates, 2002; Miller and Bayer,
2003; Murphey et al., 2003; Hemeida et al., 2004; Nanda et al., 2004; Millar and Byrne;
2007). The effectiveness of a particular marker depends on its polymorphism within and
among species. Among molecular markers, microsatellites have broad applications in the
field of genetics because it is a co-dominant marker and is highly variable (Rakoczy
Trojanowslqi and Bolibok, 2004).
22
Molecular Genetic Markers
Genetic markers are useful tools to estimate genetic diversity, phylogenetic
relationships, population structure, and kinship (Krutovsky and Neale, 2005; Varshney et
al., 2005; Selkoe and Toonen, 2006). As mentioned previously, the most common
markers include: isozymes, RFLPs, RAPDs, AFLPs, chloroplast and nuclear DNA
sequences, and microsatellite markers. Determining genetic variation within natural
populations is essential for effective conservation and tree improvement programs, and
molecular markers have proven useful for these applications (Mohammadi and Prasanna,
2003). Each type of marker is useful for different studies, with advantages and
disadvantages as listed below.
Isozymes
Isozymes are co-dominant (although sometimes markers exist as present and
null), genic markers where polymorphism is revealed by variations in a few amino acid
differences. Isozyme markers are inexpensive to develop and have high reproducibility,
however large amounts of fresh sample tissue are required compared to AFLPs and
microsatellite markers, and some enzymes are tissue-specific (Krutovsky and Neale,
2005). An isozyme study on koa using six polymorphic genes revealed differences in
koa populations from Hawaii, but was unable to differentiate populations from Maui,
Oahu, and Kauai (Conkle, 1996). Isozyme studies have been widely used in the past for
population genetic studies, but presently more powerful and versatile DNA-based
23
markers such as AFLPs and simple sequence repeats (SSRs) are commonly used
(Gonzalez-Martinez et al., 2006; Selkoe et al., 2006).
AFLPs
AFLPs are dominant, non-coding markers where genomic DNA is digested by
restriction endonuc1eases, followed by selective amplification of DNA (V os et al., 1995;
Gonzalez-Martinez et al., 2006). Compared to isozyme markers, AFLPs are generally
more expensive and difficult to assay. However, less tissue is needed per sample and
multiplexing is possible (Krutovsky and Neale, 2005). AFLPs have been used to identify
different Acacia species, and also combined with RAPD markers for higher resolution of
relationships among species (Hemeida et al., 2004).
RAPDs
RAPDs are dominant, non-coding markers that utilize a single 10-mer
oligonucleotide to amplify DNA (phillips and Vasil, 2001). These markers are easy and
inexpensive to develop, useful for multiplexing, and the amount of DNA required for
each sample is low compared to other molecular marker techniques. RAPDs have been
used successfully to differentiate Acacia species, both independently and in combination
with AFLP markers (Hemeida et al., 2004; Nanda et al., 2004). The major disadvantage
of RAPDs is the reproducibility of results is not as robust as RFLPs, AFLPs, and SSRs
(Krutovsky and Neale, 2005).
24
RFLPs
RFLPs are co-dominant, non-coding markers where endonucleases cut pieces of
DNA into different length restriction fragments. There are two types of RFLPs based on
either complementary DNA or genomic DNA (Gonzalez-Martinez et aI., 2006). RFLPs
have very high reproducibility and are usually transferable across genera, however, they
are difficult to develop, are not suitable for multiplexing, and are expensive to assay
compared to other markers (Krutovsky and Neale, 2005).
MicrosateIlite Markers
Microsatellite markers are co-dominant, non-coding markers found throughout
the nuclear genome, often referred to as simple sequence repeats (SSRs), short tandem
repeats (STRs), or simple sequence length polymorphism (SSLP) (Rakoczy-Trojanowska
and Bolibok, 2004). They consist of tandem repeats of 1-6 nucleotides, with the number
of repeats varying from five to 100, although repeats between 10 and 40 are most
common (Selkoe and Toonen, 2006). The effectiveness of microsatellites in determining
complex relationships across taxa depends on the variability of a given locus, and the
level of polymorphism in microsatellite loci has been shown to be positively related to
the overall length of the repeating sequence (Le. number of repeats, not repeat length
such as dinucleotide and trinucleotide) (Dayanandan et al., 1997; Butcher et al., 2000).
The variation in repeat length for microsatellites is due to frequent mutations
(between 10-2 and 10-6 mutations per locus per generation) during DNA replication
25
caused by slippage of DNA polymerase and slipped-strand mispairing, and also
proofreading errors (Bruvo et al., 2004; Rakoczy-Trojanowska and Bolibok. 2004:
Selkoe and Toonen, 2006). These high mutation rates make microsateIIites effective
markers for genetic studies as they reveal high levels of allelic diversity among plants
(Schlotterer, 2000). The flanking region surrounding a microsateIIite locus consists of
conserved sequences that are identical for individuals of the same or closely related
species (Seikoe and Toonen. 2006). This allows some microsateIIites developed for a
specific species to cross-amplifY in another, although the efficiency of cross
amplification decreases with increasing genetic distance between species (Dayanandan et
al., 1997; Butcher et al., 2000; Selkoe and Toonen, 2006).
The most common microsateIIites used for molecular genetic studies include
dinucleotide, trinucleotide, and tetranucleotide repeats (Rakoczy-Trojanowska and
Bolibok, 2004). Mononucleotide repeats are generally avoided due to their poor
amplification reliability and lack of long repeats (Li et al., 2002). Dinucleotide repeats
are generally most variable and account for the majority of microsateIlites, but sometimes
produce stutter bands due to slippage in DNA polymerase during amplification (Figure
18), which make allelic scoring difficult (Butcher et al., 2000; Holton, 2001; Li et al.,
2002; Lacape et al., 2007). Trinucleotide and tetranucleotide repeats eliminate this
problem, but have been shown to be less variable (Holton, 2001).
26
90 100 110 120
1,500 .
1,000
500
Ol~---.-v
Figure 18. Stutter bands produced during amplification of DNA, making allele scroring difficult.
In Acacia, micro satellites have been shown to be less transferable among species
than AFLP markers, and are relatively expensive and difficult to develop (Butcher et aI. ,
2000; Krutovsky and Neale, 2005). However, the advantages of microsatellites
compensate for the difficult and expensive process of developing these markers.
Microsatellite markers are advantageous compared to other molecular markers
because they are highly polymorphic, polymerase chain reaction (PCR)-based, provide
reproducible results, require small amounts of sample DNA, and are relatively abundant
throughout the genome (Dayanandan el al. , 1997; Butcher et al., 2000; He et aI., 2003;
Otero-Amaiz et aI. , 2005; Varshney et al., 2005; Selkoe and Toonen, 2006). Previous
studies in Acacia species found that genetic diversity detected using just five
microsatellite loci, was three times higher than that found using 58 RFLP loci (Butcher et
al., 2000). Microsatellites are DNA-based and use PCR to amplifY the marker with a
27
very small amount of sample tissue. Additionally, DNA is more stable than working with
enzymes, can be easily preserved for future use, and microsateIlites can often be
amplified by PCR even after some amount of DNA degradation (Taberlet et al., 1999;
Selkoe and Toonen, 2006).
DNA Sequencing
DNA sequencing has been used to infer phylogenetic relationships for many
different plant taxa. One major advantage of DNA sequencing as a molecular tool is that
it is easy to expand datasets to include additional plant species and provide phylogenetic
resolution (Maslin et al., 2003). The utility of a specific gene region used for sequencing
depends upon the rate of evolution of the gene relative to the taxonomic group being
investigated (Doyle and Luckow, 2003). Nuclear and chloroplast are both useful, but
they reveal relationships at different levels among taxa.
When selecting a gene or spacer region for constructing phylogenies, gene
function is not as important as characteristics such as copy number and rate of gene
evolution. The gene region needs to have sufficient sequence variation to differentiate
taxa-splitting events while still preserving relationships at higher taxonomic levels (Doyle
and Luckow, 2003). The high copy number of chloroplast and ribosomal genes in the
genome allows successful amplification from total DNA (Baldwin et al., 1995).
Chloroplast DNA sequences have frequently been used for plant molecular
studies at different taxonomic levels (Shaw ef aI, 2005). To reveal relationships at the
28
family level, the slow evolving gene rbcL (large subunit of ribulose bisphosphate
carboxylase) is commonly used. while genera and species are differentiated by more
rapidly evolving spacer regions (Doyle and Luckow, 2003). The large amount of data
available for Acacia and other genera for the chloroplast trnK (transfer gene for lysine)
intron spacer region make it useful for phylogenetic and comparative studies with other
taxa (Miller and Bayer, 2001; Shaw et al., 2005). While this region is sufficient to
resolve species relationships in some taxa, it is sometimes combined with other sequence
data for better phylogenetic resolution at low taxonomic levels (Shaw et al., 2005).
The nuclear ribosomal cistron is also commonly used for genetic studies, with
different portions used to reveal various relationships among taxa. The small subunit,
5.8S rDNA. and large subunit genes are highly conserved and utilized at high taxonomic
levels. The internal transcribed spacer regions (ITS), on the other hand, are more
variable non-coding regions that are used at the genus and species level (Murphy et al.,
2003; Doyle and Luckow, 2003).
Chloroplast trnK intron and matK coding sequence
The use of multiple approaches to infer phylogeny, along with a measure of
internal support such as bootstrap or jackknife, reveals more robust phylogenetic trees
(Doyle and Gaut, 2000; Soltis and Soltis, 2003). Along with ribosomal ITS sequences,
chloroplast DNA sequences are primarily used to infer phylogeny at the intergeneric and
interspecific levels (Shaw et al., 2005). The chloroplast matK (maturase encoding gene)
sequence, along with its flanking trnK intron region has been extensively used to resolve
29
discrepancies regarding the interrelationships of the three subgenera of the genus Acacia
(Miller and Bayer. 2001; Miller et al .• 2003). The matK evolves faster than rbcL. and is
useful at the infrageneric level, while the trnK intron is noncoding and is used at lower
taxonomic levels (Johnson and Soltis, 1994; Miller and Bayer, 2001). While little
sequence variation is expected for this region within the koa complex, sequence variation
between koa and non-native Acacia species found in Hawaii is expected. This
chloroplast region will be most useful for determining the placement of koa within one of
the three subgenera of Acacia.
Internal transcribed spacer regions (ITS1 and ITS2) of nuclear ribosomal DNA
Traditionally genetic relatedness has been inferred through morphological
similarities at the genus and species levels (Coleman and Mai, 1997). However, a
combination of molecular approaches, such as nuclear and chloroplast DNA sequencing,
can answer the question of genetic relatedness among taxa that are difficult to distinguish
morphologically, as is the case with koa. The internal transcribed spacer regions (ITS I
and 2) separating the nuclear ribosomal genes have been shown to be highly variable in
the Leguminosae family, and have been used to reconstruct plant phylogeny in the
subgenus Phyllodineae (Murphey et aI., 2003; Varela et aI., 2004; Choi et al., 2006).
While the internal transcribed spacer regions allow discrimination among different
species within the subgenus, the 5.8S gene region separating these spacer regions is
highly conserved within the subgenus with no length variation observed (Murphey et al.,
2003). This allows for easy alignment of DNA sequences from previously
uncharacterized samples. Sequencing near the 5' end oflTS I has been reported to be
30
problematic for some Acacia species, where only partial sequences are obtained
(Murphey et aZ., 2003). However, the combined length of approximately 700 bp for the
entire region allows for easy amplification and successful sequencing from only one pair
of primers (Kress et aZ., 2005). Additionally, the ITS region is the most commonly used
locus at the species level, which allows comparison with sequence data from many
different taxa (Kress el at., 2005; Kress and Erickson, 2007).
31
CHAPTER 3 EXPERIMENTAL METHODS
Plant material sampling and DNA Isolation
Mature koa phyllodes and seed pods were collected from Hawaii, Oahu, and
KauaL Sampling included representatives of various forms of koa based on
morphological distinctions (Table 1). A total of 215 samples were collected, from
populations comprising three groups characterized by morphological distinctions: A. koa,
A. koaia, and populations with characteristics intermediate of A. koa and A. koaia, termed
'group three' (See Table 2, Figures 19 and 20). Acacia species non-native to the state of
Hawaii were collected from Oahu and Hawaii for DNA isolation and included: A.
angustissima, A. auriculiformis, A. confosa, A. mangium, A. mearnsii, and A.
melanoxylon. Plant samples were transported on ice and frozen at -20°C until processed.
Three to four phyllodes from each individual tree sample were pulverized in liquid
nitrogen, and total DNA was isolated from 5 g samples using DNeasy® Plant Mini Kit
(Qiagen Inc., Valencia, CA). The DNeasy® Plant System purified total cellular DNA
from plant tissue samples using the following isolation procedure according to the kit
manual. First, tissue was lysed and RNase A treated while incubated at 65°C. Next,
polysaccharides, detergents, and proteins were precipitated with depleting buffer during
centrifugation. After, the supernatant was collected and centrifuged through a
QIAshredder spin column to remove cell debris and precipitates. DNA was then
precipitated with ethanol buffer and this solution was loaded onto the DNeasy spin
column and centrifuged, leaving the DNA bound to a silica gel membrane. DNA bound
32
Table 1. Variation in morphological characteristics among groups ofkoa.
Habitat Tree Height Seed Pods Seed Phyllodes
Arrangement
A. koa WetlMesic Large Wide Transversely Wide variation
forest 10-35 m generally long and wide
A. koaia Dry, open Small 3-5 m Narrow Longitudinal Wide variation
woodland generally short
and narrow
'group WetlMesic Variable Wide Transversely Wide variation
three' forest and 3-IOm Narrow Longitudinal
open Intermediate Diagonal
woodland
Table 2. Population descriptions for koa samples.
Population Label/Location Island Morphological Group Individuals KANA- Anahola Kauai 'group three' 20
SG- Waimea Kauai 'group three' 15
KHAN- Hanalei Kauai 'group three' 20
KV- Kahana Valley Oahu 'group three' 20
KOAB- Pua Akala Hawaii A. koa 20
KOAA- Hakalau Wildlife Refuge Hawaii A. koa 20
KKA- Awa'awapuhi Trail Kauai A.koa 20
KMC- Kokee-Mohihi Kauai A.koa 20
KTSB- Kohala Road Hawaii A. koaia 20
KTSA- Koaia Tree Sanctuary Hawaii A. koaia 20
KNT - Nounou Ridge Kauai A. koaia 20
33
Figure 19. Map of sample populations on the islands of Kauai, Oahu, and Hawaii. Images copyright Google, 2007; DigitalGlobe, 2008.
Figure 20. Tenninology used to describe koa.
35
to the membrane was washed and then eluted from the membrane using elution buffer.
DNA concentration and purity was checked for each sample using a Nanodrop NO-I 000
spectrophotometer (Nanodrop Technologies, Wilmington, DE).
Sequence amplification and analysis
Chloroplast trnK intron and matK coding sequence
To determine phylogentic relationships of koa within the broader context of
Acacia subgenera, chloroplast and nuclear DNA sequences were investigated. A total of
33 samples were sequenced including 10 each from. the groups A. koa, A. koaia, and
'group three'. Additional sequencing for the chloroplast region included non-native
Acacia species A. auriculiformis and A. mearnsii. while A. melanoxylon was sequenced
for both DNA regions. For chloroplast analysis the cpDNA intron spacer of trnK was
sequenced. This region includes matK, a maturase encoding gene, in addition to flanking
noncoding regions (Figure 21). The coding region of matK is approximately 1500 bp,
while the entire intron is approximately 2300 bp (Miller and Bayer, 2001, 2003).
Techniques for PCR amplification were adapted and modified from those previously
published. Initial DNA amplification by PCR used primers trnK-39 14 (GOG GTT GCT
AAC TCA ACG G) and trnK-2R (AAC TAG TCG GAT GGA GTA G) described for
Saxifragaceae (Johnson and Soltis, 1994). Subsequent reactions used Acacia specific
primers internal to trnK- 2R including: Ac283R (CAC TGA CGG CAA GCC CCT
CTG), Acl2F (GGT GCA (A/C)AA TCT AGG TTA TGA C), Acl290R (AAT ACA
AGA AAG CCG AAG), Ac II 04F (CCT CTA A TT AGA TCA TTG GC), and Acl707R
36
trnKlmatK
trnK-3914~ .trnK-2R, Ac1707R
Ac1290R
Acll04~
5' trnK 724 bp .--___ ----=::--__ ::-::-:-::-:-___ --, 47 bp
----L __ ~m~a~tK~ __ .:15~4::.5~bp~ __ JF trnK 3'
Figure 21. Diagram (not to scale) oftbe chloroplast trnK intron region and matK coding sequence region (Miller and Bayer, 2001). Arrows represent primer direction.
37
(TOC ACA COO crr TCC CTA TO) (Miller and Bayer, 2001). Primers were
synthesized by Integrated DNA Technologies, INC. (Coralville, lA, USA). The PCR
reaction mixture consisted of: 4 ilL of 25 mmollL magnesium chloride solution; 10 !tL of
5x Colorless OoTaq® Flexi Buffer; 1.0 unit of OoTaq® Flexi DNA polymerase
(Promega Corp., Madison, WI); 25 pmol primer; 6-10 ng template DNA; and 1.0 !tL of
25 mmollL dNTP solution (Bioline USA Inc., Taunton, MA) in equimolar ratio. The
total volume of each PCR reaction was 50!tL. Total DNA was amplified using a MJ
Research PTC-200 Peltier Thermal Cycler (San Francisco, CA) with the following
program: initial denaturation at 94°C for 5 minutes; followed by 30 cycles of
denaturation (I min. at 94°C), primer annealing (I min. at 46-53°C), and extension (2
min. at 72°C). A final extension of 72°C for 10 minutes followed the 30th cycle and PCR
products were stored at 4°C. Annealing temperatures for each primer pair were optimized
using a temperature gradient between 42-60°C. PCR amplification was confirmed by
electrophoresis using 15 ilL of PCR product in 1.0% agarose gels for 2 h at
approximately 6SV. Double stranded PCR products were cleaned using the QIAquick®
PCR Purification Kit (Qiagen Inc., Valencia, CA). Purified PCR samples were
sequenced on an Applied Biosystems 3730XL capillary-based DNA sequencer (Applied
Biosystems, Foster City, CA) by University of Hawaii at Manoa ASOPB. Sequencing
used 2 !tL of a 10 !tL solution consisting of 3.2 pmol of primer and 20 ng PCR product
per 100 bp sequenced.
38
Internal transcribed spacer regions (ITS) o/nuclear ribosomal DNA
For nuclear ribosomal analysis the ITS regions and 5.8S rDNA was sequenced
(Figure 22). This region includes ITS 1 [between the SSU (small-subunit rDNA) and
5.8S rDNA], the 5.8S rDNA gene, and ITS 2 [between the 5.8S rDNA and the LSU
(large-subunit rDNA)]. The coding region of the 5.8S rDNA gene is 159 bp, while the
entire rDNA cistron region is approximately 700 bp (Murphey et al .• 2003). Techniques
for PCR amplification were adapted from those previously published. DNA
amplification by PCR used an Acacia specific primer, ACF (GGA GAA GTC GTA ACA
AGG TIT CCG) (Murphey et al., 2003) and 26SE (TAG AAT TCC CCG GTT CGC
TCG CCG TTA C) (Sun et al., 1994) for initial amplification. The ITS regions were
further amplified using nested PCR with primers S3 (AAC CTG CGGA AGG ATC ATT
G), S4 (TAG CCC CGC CTG ACC TGA GG), S5 (TTC GGG CGC AAC TTG CGr
TC) and S6 (AT A TCT CGG CTC TTG CAT CG) (Kiiss and Wink, 1997). Primers were
synthesized by Integrated DNA Technologies, INC. (Coralville, IA). The PCR reaction
mixture consisted of: 4 III of 25 mmollL magnesium chloride solution; 10 III of 5x
Colorless GoTaq® Flexi Buffer; 1.0 unit of GoTaq® Flexi DNA polymerase (Promega
Corp., Madison, WI); 25 pmol primer; 6-10 ng template DNA; and 1.0 III of25 mmollL
dNTP solution (Bioline USA Inc., Taunton, MA) in equimolar ratio. The total volume of
each PCR reaction was 50 Ill. Total DNA was amplified using a MJ Research PTC-200
Peltier Thermal Cycler (San Francisco, CA) with the following program: initial
denaturation at 94°C for 3 minutes; followed by 30 cycles of denaturation (I min. at
94°C), primer annealing (I min. at 55°C), and extension (2 min. at 72°C). A final
39
S3 •
SSIJ
ITS regions of 5.8S rDNA
S6 ~
• S5
ITS 1 r--------,
S.8S rONA
• 26SE
• S4
ITS 2
LSIJ
Figure 22. Diagram (not to scale) ofrDNA cistron for the ITS region in Acacia. SSU =
small-subunit rDNA; ITS = internal transcribed spacer; LSU = large-subunit rDNA (Murphey et al., 2003). Arrows represent primer direction.
40
extension of 72°C for 7 minutes followed the 30th cycle and PCR products were stored at
4°C. Nested PCR reactions were carried out using the following program: initial
denaturation at 95°C for 15 min; followed by 30 cycles of denaturation (30 sec. at 94°C),
primer annealing (30 sec. at 63.8°C), and extension (20 sec. at 72°C). A final extension
of 72°C for 5 minutes followed the 30th cycle and PCR products were stored at 4°C
(Murphey et aI., 2003). PCR amplification was confirmed by electrophoresis using 15
ilL of PCR product in 1.0% agarose gels for 2 h at approximately 65V. Double stranded
PCR products were cleaned using the QIAquick® PCR Purification Kit (Qiagen Inc.,
Valencia, CA). Purified PCR products were sequenced on an Applied Biosystems
3730XL capillary-based DNA sequencer (Applied Biosystems, Foster City, CA) by
University of Hawaii at Manoa ASGPB. Sequencing used 2 ilL of a 10 !!L solution
consisting of3.2 pmol of primer and 20 ng PCR product per 100 bp sequenced.
MicrosateUite marker amplification and analysis
A total of 20 microsatellite markers were tested, six that were A. mangium
specific, and 14 that were A. koa-specific. The six A. mangium-specific markers were
chosen on the basis of cross-species amplification of species closely related to A. koa in
the subg. Phyllodineae, section Plurinerves (Butcher et al., 2000). Phylogenetic trees
and sequence analysis indicated high sequence similarity between A. koa and A.
melanoxylon, indicating likely amplification of A. koa samples using microsatellite
markers developed for A. mangium. The PCR reaction mixture followed the same
protocol used in PCR reactions for sequencing analysis and the forward primer of each
primer pair was fluorescently labeled with one of four fluorescent dyes; VIC, PET, FAM,
41
or NED (Applied Biosystems Custom Oligonucleotides, Foster City, CA, USA). PCR
amplification was as follows: initial denaturation at 94°C for 5 min; followed by 35
cycles of denaturation (I min. at 94°C), primer annealing (I min. at 48-60°C), and
extension (Imin. 30 sec. at 72°C). Annealing temperatures for each primer pair were
optimized using a temperature gradient between 46-64°C. A final extension of 72°C for
30 minutes followed the 35th cycle and PCR products were stored at 4°c' Initially,
samples were individually genotyped for allele size determination. Additional test
samples were genotyped using multiplexes involving four microsateIlite markers, each
with a unique dye color. Multiplexes consisting of between five and eight microsateIlite
amplification products were evaluated, but resulted in poor separation of PCR products
during capillary electrophoresis. This caused problems with allele scoring, so only four
markers were multiplexed at a time. Amplification products were separated by capillary
electrophoresis on an ABI Prism 377XL DNA sequencer. Fragment sizes were
determined using GeneMarker V1.6 software (Softgenetics LLC, State College, PA).
Data analysis
trnK / matK and ITS] / 5.BS / ITS2 sequencing
Boundaries of the chloroplast trnK / matK and the nuclear ITS I I 5.8S I ITS2
regions were determined by comparison to those of published Acacia species (MiIler and
Bayer, 2001; MiIler and Bayer, 2003; Miller et al., 2003; Murphey et aZ., 2003). A set of
homologous Acacia sequences were assembled using NCBI BLAST (Basic Local
Alignment Search Tool), and combined with koa sequence data for the trnK / matK
42
(Table 3) and the nuclear ITSI I 5.8S I ITS2 regions (Table 4). DNA sequences were
initially aligned using the Clustal X package with all multiple alignment characters used
at default settings (Thompson et aI., 1997), and further edited by hand. Indels were
scored as separate characters and manual alignments were with minimal gaps. Sequence
alignments with missing data were excluded from analysis and all characters were un
weighted. For the trnK I matK region, 47 nucleotide positions were excluded from
further analysis because of ambiguous alignments at these positions. A total aligned
sequence length of 805 bp including the trnK intron region and partial matK coding
region was used for further analysis. For the ITS spacer region, 85 nucleotide positions
were excluded because of ambiguous alignments. A total aligned sequence length of 582
bp including partial ITS I region, complete 5.8S gene, and partial ITS 2 region was used
for further analysis. Phylogenetic analysis was performed using PHYLIP (phylogeny
Inference Package) v3.6 phylogentic programs (Felsenstein, 1989; 2005). Parsimony
analysis was performed using DNAPENNY where the branch and bound algorithm was
used to find most parsimonious trees. Mimosa tenuiflora and Lysiloma divaricata were
used as outgroups for all phylogenetic analysis of the trnK I matK and ITS I I 5.8S IITS2
regions, respectively, based on their close morphological and genetic similarity to Acacia
(Miller and Bayer, 2001; Murphey et af., 2003). Multiple random data sets were
generated using SEQBOOT for use in parsimony analysis to eliminate bias associated
with the order of data entry. Bootstrap data sets and consensus trees were created using
SEQBOOT and CONSENSE programs. A majority rules consensus tree was created
with 100 bootstrap replicates. Phylogenetic trees were created using
43
Table 3. Species used for trnK / matK analysis. (Species with GenBank accession numbers are from Miller and Ba~er, 2001; Miller and Bayer, 2003; Miller et al., 2003)
Tribe Subgenus Species GenBank accession number
Mimoseae Outgroup Mimosa tenuiflora AF274120
Acacieae Acacia A. caven AF274131
Acacieae Acacia A. cochliacantha AF274133
Acacieae Acacia A. constricta AF274135
Acacieae Acacia A. pennatula AF274134
Acacieae Acacia A. schaffneri AF274132
Acacieae Acacia A. schottii AF274136
Acacieae Aculeiferum A. berlandieri AF274145
Acacieae Aculeiferum A. bonariensis AF274146
Acacieae Aculeiferum A. glomerosa AF274147
Acacieae Aculeiferum A. modesta AF274142
Acacieae Aculeiferum A. senegal AF274143
Acacieae Aculeiforum A. wrightii AF274148
Acacieae Phyllodineae A. auriculiformis
Acacieae Phyllodineae A. cognata AF523167
Acacieae Phyllodineae A. myrtifolia AF274160
Acacieae Phyllodineae A. melanoxylon
Acacieae Phyllodineae A. pulchella AF523087
Acacieae Phyllodineae A. translucens AF523087
Acacieae A. koa
Acacieae A. koaia
Acacieae 'group three'
44
Table 4. Species used for ITS 11 S.8S / ITS 2 analysis. (Sequences with GenBank
accession numbers are from Murphey et al., 2003) Subgenus Group I Section Species I Sample GenBank accession
number Phyllodineae A.koa KOA2
Phyllodineae A. koa KOA7
Phyllodineae A.koa KOAI2
Phyllodineae A. koa KOAI6
Phyllodineae A. koa KOAI9
Phyllodineae A. koaia KOAIA2
Phyllodineae A. koaia KOAIA4
Phyllodineae A. koaia KOAlAS
Phyllodineae A. koaia KOAlA I 4
Phyllodineae A. koaia KOAIA18
Phyllodineae 'group three' GTHR2
Phyllodineae 'group three' GTHRS
Phyllodineae 'group three' GTHRIO
Phyllodineae 'group three' GTHR12
Phyllodineae 'group three' GTHR19
Phyllodineae Alalae A. alata AF360699
Phyllodineae Juiijlorae A. acuminata AF360708
Phyllodineae Juiijlorae A. denticuiosa AF487763
Phyllodineae Lycopodiifoliae A. adoxa AF36071S
Phyllodineae Lycopodiifoliae A. iycopodiifolia AF360716
Phyllodineae Piurinerves A. melanoxylon
Phyllodineae Piurinerves A. translucens AF360722
Phyllodineae Pulchellae A. leteriticola AF487774
Phyllodineae Pulchellae A. pentadenia AF487773
Phyllodineae Pulchellae A. pulchella AF360726
Outgroup Ingeae Lysiloma divaricata AF4877SS
KOA = A. koa; KOAlA = A. koaia; GTHR = 'group three'
45
DRAWGRAM, and TreeView (page, 1996) was used to view the PHYLIP format tree
data.
Microsatellite marker analysis
Twelve of the 20 microsatellite markers tested were utilized for data analysis
(Table 5). The other eight markers were excluded due to poor quality of amplification,
ambiguities in allele assignment, and stutter bands. Variation in allele sizes and
frequency were scored for 12 microsatellite markers using GeneMarker V1.51 software.
Four of these markers were developed for A. mangium (Am030, Am465, Am502, and
Am770; Butcher et al., 2000), and the other eight were developed for A. koa (Ak05,
Ak37, Ak44, Ak84, Ak89, Ak180, Ak196, and Ak284; Fredua-Agyeman, unpublished).
A data matrix of allele sizes was created in Microsoft Excel and used to calculate genetic
parameters of populations and groups (subscripts P and G, respectively) for the average
number of alleles per polymorphic locus (AP) and percentage of polymorphic loci (P,
eriterion 99%). At the population level, the average number of alleles per polymorphic
locus (APp) was calculated by summing the alleles detected at polymorphic loci in a
population and dividing by the number of polymorphic loci. At the group level, APo was
calculated by summing the alleles detected at polymorphic loci in all populations
representing a group, and dividing by the number of polymorphic loci. The same
approach was used to determine percentage of polymorphic loci, where the number of
loci polymorphic within a group/population was divided by the total number ofloci.
46
Table 5. Microsatellite marker primer sequences, annealing temperature, and allele sizes.
Name Repeat Mofit(s) Primer Sequence (5' - 3') Allele Range (bp)
Am030 (AT)9(GT)ls GAGGTAATATTTTGAATTCCTTGAAC 51-82 GGTGTATACCTCTTTCCTGTGG
Am465 (ACb TGGGTATCACTTCCACCATT 133 -181 AGGCTGCTTCTTTGTGCAGG
Am502 (TTC)3-(GGA)8,AGA(GGAh CAAATGGCCAAGTTACGACTG 105-133 TTCTGGTAATCCAAACTTATGTGG
Am770 CTC(CAC)sCGC(CAC)3 CAGAGGTGGCAGATGATGTC 86-96 AAGCCTTTAGTTGGGCGTTC
Ak05 (AC)s(AT)s unpublished 164-195
Ak37 (CTC)4 unpublished 195-218
Ak44 (CT)\3 unpublished 131-184
Ak84 (TTTA)4 unpublished 237-259
Ak89 (AC), unpublished 158-193
Ak180 (GTT)4 unpublished 188-198
Ak196 (TA), unpublished 234-360
Ak284 (AG)3A(AG)11 unpublished 233-274
47
The polyploid nature of plants is believed to contribute advantages to their growth
within an environment. It has been shown to increase their ability to survive in extreme
habitats (Soltis and Soltis, 2001). Polyploid plants are not as well studied as diploids,
especially using molecular markers such as allozyrnes and microsatellite markers
(Esselink et ai., 2004). Analysis of tetraploids using these two molecular tools is
inherently difficult due to variation in allele dosage.
Tetraploid plants may have up to four alleles present at each locus, and allele
scoring can be recorded as one copy of each allele (eg. A:B:C:D). However, in the case
of two or three alleles being present at a specific locus, different genotypes can account
for the same band pattern, (eg. A:A:A:B; A:B:B:B; A:A:B:C; A:B:B:C; A:B:C:C;
A:B:C:null allele: etc.) referred to as 'partial heterozygotes' (Bruvo et aI., 2004). To
account for this potential genotypic variation, the MAC-PR (microsatellite allele
counting-peak ratios) method can be used, which utilizes calculations of the area under
each microsatellite allele peak to infer allele dosage and distribution (Esselink et al.,
2004; Babaei et ai., 2007). However, the success of the MAC-PR approach is dependent
on having consistent allele amplification and limited stutter bands (Esselink et al., 2004).
Considering all koa samples cannot be analyzed from the same PCR reaction, variation in
allele intensity was to be expected, and it makes this approach impractical. Additionally,
MAC-PR is not commonly applied to studies where genetic relationships are unknown
(Esselink et at., 2004).
48
A more common approach to analyze molecular data is to score the presence or
absence of each allele at a particular locus and infer diversity statistics from allele
phenotype patterns (Hormaza, 2002; Wang et at., 2004; Medini et at., 2005; Segarra
Moragues et at., 2005; Obbard et at., 2006a; Obbard et at., 2006b; Yifru et at., 2006;
Hamilton and Eckert, 2007). Phenotype frequency measures such as ;then and Jtw only
take into account whether allele band patterns are identical or different. On the other
hand, H, calculated using the software FDASH, takes into account the fact that
phenotypes sharing a high number of bands are more similar, even though the band
patterns are not identical (Obbard et ai., 2006b). Although this approach is intended for
allotetraploids, which koa is thought to be, it also captures essential information from
polyploids with alternative inheritance (eg. polysomic polyploids) and when common
ancestry may not relate to allele sharing (Obbard et aI., 2006b). These factors made
FDASH the most reasonable approach for tetraploid data analysis.
Allele scoring revealed individuals with one, two, three, and four alleles present.
Multilocus scoring was done where the presence or absence of each allele was scored for
each microsatellite locus (Hormaza, 2002; Wang et at., 2004; Medini et at., 2005;
Segarra-Moragues et at., 2005; Yifru et at., 2006). To measure popUlation diversity and
differentiation, the software FDASH was used, which allows analysis of polyploid data
by comparing allelic phenotypes. The diversity measure calculated by FDASH is similar
to Nei's gene diversity (H), and the Shannon-Weaver diversity index of phenotypes
(Jtw), and is termed H. H measures diversity by accounting for different numbers of
unshared alleles between individuals, calculated by the following formula:
49
n n
H = 11 n(n-l) ~ ~ ~ Xijk leJ j=J k£{alJeJes}
where n is the number of individuals sampled and XUk is a variable that is equal to one if
allele k it carried by individual i or individual j, but not both, and otherwise equal to zero
(Obbard et at., 2006). While some information is lost compared to analysis using allele
dosage frequencies, this method includes more information than other phenotypic
diversity measures because it takes into account band sharing between different
phenotypes instead of treating each phenotype separately (Obbard et at., 2006b).
Significant differences in diversity between groups were tested using a randomization test
(\000 permutations) in FDASH, and differences in H between groups was considered
significant if it was greater than 95% of aU randomized differences.
Based on diversity calculated by H, genetic differentiation, F ST, was also
calculated using FDASH by the foUowing formula:
F ST = (HT - Hs) / HT
where Hs is the average diversity (H) within populations and HT is the total genetic
diversity (8) for both populations pooled (Obbard et ai., 2006b).
50
The relatedness of populations was evaluated by an unweighted pair grouping of
arithmetic average (UPGMA) cluster method based on pairwise genetic distances
between populations, calculated as PST in FDASH. The dendogram of these relationships
as well as principle coordinate analysis (pCOORDA) of populations was computed using
the software NTSYSpc version 2.2 (Rohlf, 2007). PCOORDA was also carried out for
individuals to assess their inclusion in each group.
Regression analysis was used to assess the correlation between population
differentiation, measured as PST, and geographic distance between populations to
determine isolation by distance effects. The significance of this effect was measured
using Mantel tests implemented in NTSYSpc version 2.2 (Rohlf, 2007).
To describe the partitioning of genetic variation within and among populations, an
analysis of molecular variance (AMOVA) was performed using Arlequin 2.0 (Schneider
et ai., 2000), based on the same matrix of presence (1) or absence (0) of alleles used for
the diversity statistics. For this binary data, AMOVA is based on allelic differences
between individuals defined as Euclidean distance (Mengoni and Bazzicalupo, 2002;
Excoffier et ai., 1992, 2005).
Cross-species ampUfication
To assess the utility of microsatellite markers for cross-species amplification,
three individuals from the following acacias were tested for positive amplification using
peR: A. angustissima, A. auriculiformis, A. confusa, A. mangium, A. mearnsii, and A.
51
melanoxylon. PCR amplification cycles were the same as those used for koa samples.
Markers were considered successful to cross-amplify if all three samples showed sharp
PCR products.
52
CHAPTER 4 RESULTS
Chloroplast trnK intron and matK coding sequence
The aligned length of the trnK / matK region was 805 bp, of which 29% of the
sequence was variable. The region contained 82 potentially informative base
substitutions, however, only four informative substitutions were observed among the
three koa groups. The occurrence of relatively small sequence variation within species
for the trnK / matK region is the reason for its application at the genus and subgenus
levels (Miller et al., 2003). The two non-native acacias that were also sequenced, A.
auriculiformis and A. melanoxylon, were more variable from individuals in the koa
groups, as expected. Ten individuals representing each koa group, a total of 30
individuals, were sequenced. However, no more than I bp was variable within each
group. Therefore, one consensus sequence was created from the 10 individuals of each
group and used for further phylogenetic analysis.
A majority rules consensus tree was created from 10,000 most parsimonious trees
to reveal the placement of each koa group within the Acacia genus (Figure 23). The koa
groups were closely related to species in the Australian subgenus Phyllodineae,
especially A. melanoxylon. Sequence comparison revealed that A. froa had over 98%
sequence homology with A. melanoxylon. The two non-native Acacia species sampled
from Hawaii (A. auriculiformis and A. melanoxylon) were also clustered within
Phyllodineae (P). Bootstrap values based on 100 replicates showed strong support for
relationships among species within each subgenus, in the phylogenetic tree. Within
53
10.0.
86 35
92 97
11 8
15
99 1 8 A. schaffnernii A
6 2
99 1
4 3
7
9
~ 1
~ 2
100 1 5
4
A.caven A
A. cochliacantha A
A. pennatula A
A. schottii A
A. constricta A
A. berlandii L
A. wrightii L
A. glomerosa L
A. bonariens L
A. modesta
A. senegal
New World
Asia! Africa
89 99-1
A. koaia
A.koa
'group three' /"
11
.-
- 97 7
14
15
6
43
64
4 1
I 2
100 3
2
A. melanoxylon P
A. cognata P
A. auriculiformis P
A.puchella P
A. translucens P
A. myrtifolia P
Mimosa tenuiflora
Hawaii
Australia
New World
Figure 23. Majority rule consensus tree of 10,000 most parsimonious trees from trnK / matK sequence analysis with a length of 341 steps. Bold numbers above lines are bootstrap support values. The second column indicates subgenus classification within Acacia: A= Acacia; L=Aculeiferum; P= Phyllodineae; Outgroup represented by M= Mimoseae. The third column represents each species native origin (Miller and Bayer, 2001). Italicized numbers represent the number of steps for each branch.
54
subgenus Aculeiferum (L), bootstrap support was strongest for A. modesta and A. senegal,
the two species with Asia! Africa origin, although relationships of aU species in the
subgenus were strongly supported based on bootstrap analysis.
Internal transcribed spacer regions (ITS) of nuclear ribosomal DNA
The aligned length of the ITS region was 582 bp, of which 37% of the sequence
was variable. The region contained 88 potentially informative base substitutions,
including nine among the three koa groups. Five individuals from each group, including
at least one from each of the sample populations, were included in the phylogentic
analysis. A majority rules consensus tree was created from 10,000 most parsimonious
trees to determine the relationship of koa groups within the subgenus Phyllodineae
(Figure 24). Based on trnK / matK sequence analysis, koa groups should be closely
related to species in the section Plurinerves. Bootstrap replicates (100) were used to
analyze the strength of relationships determined from parsimony analysis.
While sequencing from the ITS region revealed more than twice as many
informative sites among koa groups as the trnK / matK region, no conclusive
relationships among koa were supported by the parsimony analysis. AU koa samples
used for analysis formed a single clade with A. melanoxylon as the closest related sister
taxon (consistent with results from analysis of the trnK / matK region). A total of 17
characters were variable among individuals within this clade, but there were no patterns
of association evident among samples of koa populations. Individuals from the three koa
groups were most related to A. melanoxylon of the section Plurinerves. However,
55
3 5 KOA7
3 5 KOA16
Hawaii
3 KOAlAS
2 4 GTHRIO
2 2 KOAIA14
78 1 KOA12
6 KOAIA4 1
GTHR2 1
KOA1A2 6 1
3 KOA19
76 KOA2
7 2 1
1 GTHR12
A. melanoxylon I Plurinerves 18
25 10 2 A. lateriticola I PulcheUae 14 lA. pentadenia
24 A. pulchella
59 A. alata I Alatae
22 98 5 A. adoxa I .. 80 22 2 A. Iycopodiifolia Lycopodii/oliae
11 78 2 A. denticulosa I Julijlorae 90 7 5 A. acuminate 11 A. translucens I Plurinerves
11
11 Lysoma
devaricata
I Ingeae
Figure 24. Majority rule consensus tree of 10,000 most parsimonious trees from ITS 1 I 5.8S I ITS2 sequence analysis. Bold numbers above lines are bootstrap support values. Classifications into sections (right side in bold) for taxa are after Vassal and Pedley (Murphey et al., 2003). KOA = A. koa; KOAlA = A. koaia; GTHR = 'group three'. Italicized numbers represent the number of steps for each branch.
56
A. translucens. also classified in the section Plurinerve8, was clustered with species from
other sections in subgenus Phyllodineae. Bootstrap values were highest between species
in both the Pulchellae and Lycopodiifoliae sections, which is consistent with reported
data (Murphey et al., 2003).
Multiplexing of microsateIIite markers
Theoretically, any four fluorescent-labeled microsatellite markers could have
been multiplexed, as long as the markers were each labeled with a different dye, such as
VIC, PET, FAM, or NED. Markers of the same dye color could also have been analyzed
together if the expected base pair sizes are known for each marker, and they do not
overlap. Groups were designed to keep the A. mangium-specific markers and the koa
specific markers in separate groups. Multiplexing with more than four markers proved to
be problematic, as amplified products were not as intense and allele scoring was difficult
Therefore multiple combinations using four markers were tested as multiplex groups.
Analysis with these multiplex groups produced easily identifiable allele patterns for all
samples. The multiplex groups used for all microsatellite allele scoring were as follows:
Group I; Am030, Am465, Am502, and Am770; Group 2; Ak05, Ak44, Ak84, and
Ak284; and Group 3; Ak37, Ak89, Akl80, and Ak196.
MicrosateUite markers
All 12 microsatellite loci were polymorphic for each group, and resulted in a total
of 106 alleles that were detected across all populations. Allelic variation for each locus
57
ranged from three (Ak180, Am770) to 17 (Ak44), with an average of8.8 alleles per locus
(AP) for all samples combined (Table 6). Of all alleles detected, 29% (31 of 106) were
unique to a particular group ('Group three', 21 unique alleles; A. koa, 7; andA. koaia, 3).
Although all loci were polymorphic, there were wide variations in the APo for each group
of the koa complex. Acacia koaia had the lowest APo with 4.3, while 'group three' had
the highestAPo with 7.9. This group also had the most unique alleles, 21, and contained
a combination of alleles found exclusively in the A. koa or A. koaia groups (Figure 25).
Results for APp were consistent with those seen for each group, as KANA ('group
three'), had the highest APp with 5.7, while two populations of A. koaia (KTSA and
KNT) had the lowest APp (2.7 and 3.1, respectively).
Genetic diversity measures for each group, based on allele phenotypes, were not
significantly different and were correlated with the total number of alleles per group
(Figure 26). Diversity was strongly partitioned within populations of each group (Ito)
rather than among (D'ST), which explains the low levels of differentiation between groups
(PST) (Table 7). Diversity and differentiation statistics over all loci showed the A. koaia
group as the least diverse (Table 7). At the population level, total diversity (HT) showed
an A. koaia population on Kauai (KNT) was the least diverse (Table 8). Population
statistics were consistent with those for groups, as the highest levels of diversity were
found in 'group three' populations. The two most diverse populations were KANA and
SG, but surprisingly, 'group three' also contained one of the least diverse popUlations,
KV (Table 8). An AMOV A for the microsatellite data reaffirmed differentiation
58
Table 6. Total number of alleles at each locus for groups ofkoa.
Marker Total Alleles A. koa alleles A. koaia alleles 'group three'
Alleles
Am030 6 4 4 6**
Am465 7 6 5 7"
Am502 10 6 4 10****
Am770 3 2 2 3'"
Ak05 8 6 7" 6
Ak37 4 3 3 4*
Ak44 17 \3 ••• 4 14"' .....
Ak84 9 6··· 4* 5*·
Ak89 13 II 6 13"''''
Akl80 3 3 2 3
Akl96 10 6* 2'" 8"'*
Ak284 16 14 9 16"'"
Total 106 80 52 95
AP 8.8 6.7 4.3 7.9
·Unique Allele
59
,~. '00 I.ot It .. "~ I ~ ," ' " 1" 1:.9 1.1 ).I ", ... ' A I ~ 1)0
~[ A. koaia
~ I~ "a ,~ I ', ' . I "' 1"1 '" ~ ~ ~ ~ ~ • , ~ I~
:: ~ 'group ~ ~ ~ m Jv \ three' ,'J \ /\}', jv • _ '. __ ---..-l '- ____ _
"" '" ."
m ,~ ~ ,~ 1°) I ") ' 1' ",. "' . ". , ~ I~ ~ ,~ ,~ 1 ~ 1)0
,. A. koa .. 'Ill It' ,,.. 'M "t ' ll ", ,,' " . ",.. "t,: I" . ;0& , ~ 11) -» " 4
: 'group A
~ thre~')J\ I •
-;
Figure 25. Electropherogram of allelic scoring for A. koa, A. koaia, and 'group three' for primer Am502. Numbers below peaks represent allele sizes (bp); y axis measurement is relative fluorescent units (RFU). 'Group three' has: allele 115, only fo und in A. koa; allele 118, only found in A. koaia; as well as alleles 105, 109, 127, and 133, unique to 'group three' .
100
90
III 80 .. ]! 70
<i 60 .... 0 50 ... .. 40 J:l E 30 :::l Z 20
10
0
Akoaia Akoa
Group Name
1.6
1.4 j:
1.2 .~ ~ .. >
0.8 i5 u
0.6 :;
0.4 5i C)
0.2
--'---+ 0
'group three'
_ Total Alleles
c::::::::JUnique Alleles
..... Genetic Di;ersity H'
Figure 26. Total alleles, unique alleles, and genetic diversity (H T) among three groups ofkoa.
60
Table 7. Diversity statistics over all loci for groups in the A. koa complex.
Group Ho D'ST
A.koa 1.206 1.065 0.141 0.098
A. koaia 0.960 .848 0.112 0.082
'group three' 1.578 1.360 0.218 0.141
HT. total diversity; Ho, average diversity within populations of each group; D'ST, average diversity among populations of each group; PST, differentiation between popUlations of each group.
Table 8. Genetic diversity of 11 populations in the A. koa complex arranged according to morphological group. Population Group HT
KANA 'group three' 1.682
SG 'group three' 1.662
KHAN 'group three' 1.455
·KV 'group three' 0.778
KOAB A. koa 1.318
KOAA A. koa 1.180
KKA A. koa 0.939
KMC A. koa 0.828
KTSB A: koaia 0.977
KTSA A. koaia 0.954
KNT A. koaia 0.613
61
statistics, showing that most of the genetic variation, 72.2% was found within populations
rather than among populations, 27.8%.
Pairwise differentiation (PST) between populations is shown in Table 9. Two
populations from Hawaii representing the A. koa group (KOAA and KOAB) were most
closely related, with a PST of 0.007. KTSA and KTSB, A. koaia populations from
Hawaii, were also very similar, with a PST of 0.010. The most dissimilar populations
were all from Kauai and in the groups A. koa and 'group three'. KNT (A. koaia) and SO
('group three') were most differentiated (PST = 0.207), followed by KMC (A. koa) and
KANA ('group three'), with a PST = 0.190. These results were a not expected,
considering that these populations were all from the same island and in close proximity to
one another. As the above results would suggest there was no correlation observed
between genetic distance and geographic distance between populations as revealed by the
Mantel test (Figure 27).
A dendogram based on the UPOMA cluster method (Figure 28), as well as a plot
from principle coordinate analysis (Figure 29) were constructed using average pairwise
differentiation (PST), to analyze the relatedness of populations. Three populations
representing 'group three' (KANA, KHAN, SO) clustered together and were distinct
from other populations in both the UPOMA dendogram and principle coordinate analysis.
Another distinct cluster seen in both analyses was KTSA and KTSB, both from Hawaii
and in the A. koaia group. One unexpected placement in the cladogram was KV, a 'group
62
Table 9. Matrix of pairwise differentiation between 11 populations of koa, based on micro satellite allele scoring. Populations arranged according to morphological group.
SO KHAN KV KOAB KOAA KKA KMC KTSB KTSA KNT
KANA 0.076 0.047 0.154 0.122 0.134 0.11910.190 1 0.143 0.128 0.156
SO 0.101 0.168 0.098 0.130 0.119 0.149 0.175 0.173 1
0.207
1
KHAN 0.176 0.094 0.119 0.092 0.122 0.152 0.136 0.131
KV 0.084 0.122 0.064 0.029 0.181 0.163 0.113
KOAB I 0.007 1 0.057 0.076 0.083 0.077 0.091
KOAA 0.082 0.112 0.114 0.091 0.117
KKA 0.086 0.109 0.092 0.046
KMC 0.175 0.164 0.110
KTSB 1 0.010 1 0.113
KTSA 0.097
KNT
go 0.25 .'11 I!:.. C 02 0
i 0.15
I II! 0.1 c
~=0.0334 • • •
• • • • f • •• • • ..... • • • • .. . l • .. ••• • ,
u 0.05 11 c
• • •
~ 0 o 100 200 300 400 500 600
Geographic Distance (Ion)
Figure 27. Comparison of genetic differentiation and geographic distance between populations. The blue diamond symbol represents a pair on populations.
63
KANA I I KHAN 'group three'
SG
I KKA
I KNT -
I KOAA
I KOAB A. koa
I KMC I KV
KTSA
KTSB A. koaia I • , ii' I I j , ii , I ' , t
0.14 0. 10 0.07 0.04 0.01 Differentiation Coefficient
Figure 28. Dendogram of II populations of the A. koa complex revealed by UPGMA cluster analysis based on pairwise differentiation.
64
0.16
-D.07 Axis 3
Axis 2
0.31
0.54
Figure 29. Principle coordinate analysis for micro satellite analysis of koa populations. The plot explains 59.5% of the total variability, 27.4% for the first principle coordinate axis, 18.3% for the second, and 13.8% for the third.
65
three' population from Oahu clustered with KMC, an A. koa population from Kauai.
These two populations also displayed a close association in the principle coordinate
analysis. While both A. koa populations from Hawaii were clustered together, they also
displayed a close association with Kauai populations KKA (A. koa) and KNT (A. koaia).
All three microsatellite analyses showed the close association of KNT and KV with
populations from the A. koa group. Although KNT and KV were originally classified in
different groups based on morphological characteristics, molecular results indicate they
should correctly be classified as A. koa (Figures 28, and 29). The plot from principle
coordinate analysis explained 59.5% of the total variability, 27.4% for the first principle
coordinate axis, 18.3% for the second, and 13.8% for the third (Figure 29).
Principle coordinate analysis for individual samples showed clustering among
individuals from each group, although overlapping of individuals (red circle) from some
populations was observed (Figure 30). When individuals were categorized according to
populations rather than groups, several trends in clustering were observed. Individuals
from KMC and KV showed a close association (Figure 31, red circle). Additionally, KV
individuals were also clustered closer to individuals from the A. koa groups from Hawaii,
KOAA and KOAB, than they were to any of the 'group three' populations (Figure 31,
pink circle). Based on pairwise differentiation, the two closest related populations to KV
were also A. koa groups, KMC and KKA, while 'group three' populations SG, KANA,
and KHAN were among the most distantly related (Table 9). The combination of these
molecular data again show that KV, although morphologically classified in 'group three',
is actually in the A. koa group. Molecular analysis also showed a similar relationship for
66
• A. koaia
• A. koa
• 'group three'
020
020
0.09 Axis 3 ·0.03
-0 -0.14
-02Q -C.26
~--\
-0.08
0.05 Axis 2
0.19
032
Figure 30. Principle coordinate analysis for individuals, categorized into groups according to morphological characteristics.
67
----......... Axis 1
-<l20
68
020 0.09
-<l.03 Ax is 3 -<l./4
-{1.2(j
0./9
• KTSA Q KTSB
• I<OAA Q I<OAB
- KANA - K1iAN - KI<A
• KMc - I<Ny
- sa I: Kv
population KNT. Principle coordinate analysis of individuals (Figure 31, blue circle) and
the differentiation dendogram (Figure 28) showed KNT should be categorized in the A.
koa group. While a few individuals from each population were still found intermixed,
three distinct clusters were observed when the KV and KNT individuals were
appropriately assigned to the A. koa group (Figure 32). The inclusion of populations into
one of three groups was consistent with the UPGMA dendogram showing average
differentiation between populations (Figure 28).
Cross-species amplification
Cross-species marker-amplification for A. mangium microsateJlite markers was
previously reported by Butcher et al. (2000), but was tested again using Acacia species
collected from Hawaii. All Acacia samples cross-amplified using A. mangium-specific
markers Am030, Am465, Am502, and Am770, as expected. This step was done to
confirm that DNA extracted from non-native acacias was of sufficient quality for testing
on koa-specific markers.
Five of the six non-native acacias amplified at least one koa-specific marker, with
only A. angustissima failing to amplifY any of the eight markers. Overall success was
low, with A. auriculiformis and A. mangium amplifYing only one marker, and A. confosa,
A. mearnsii, and A. melanoxylon amplifYing just two markers each (Table 10, Figures 33,
and 34). DNA from all non-native acacias successfully amplified universal primer
69
Figure 32. Principle coordinate analysis for individuals, labeled according to population and group. All individuals colored green are from 'group three'; pink individuals are from the A. koa group and blue individuals are from the A. koaia group. Population KV and KNT are categorized in the A. koa group according to molecular data, resulting in three distinct groups.
70
Table 10. Cross species amplification of koa-specific markers by non-native acacias from
Hawaii. Successful amplification denoted by X, unsuccessful amplification denoted by -. Non-native Acacia species
Marker A.angustissima A.ariculijormis A.confosa A.mangium A.mearnsii A.melanoxylon
AkOS X
~7 X
Ak44
Ak84
Ak89
Akl80
Ak196
Ak284
X
X
71
X
X
X
X
500 bp
250 bp 100 bp
CON AR MAN I 23123
AN 123
ML 2 3
MR MG I 2 3 I 2
Figure 33 . Cross-species amplification results from microsatellite marker Ak37, with expected fragment size of 210 bp. Successful amplification or two A. mangium individuals (third individual not shown). Codes for each species are as follows : M=Standard Marker; A= A. koa positive control; =negative control; CO = A. con/usa; AR= A. auricilliformis; AN= A. anguslissima; ML= A. melanoxy lon; MR= A. mearnsii; MG= A. mangium. Numbers below species codes represent an individual of each species.
SOO bp
250 bp
CON MAN I 2 3
AR 2 3
AN ML MR MG 2 3 I 2 3 I 2 3 I 2
Figure 34. Cross-species amplification resu lts from microsatell ite marker Ak284, with expected fragment size of 242 bp. 0 cross-amplification for any non-native Acacia. Codes for each species are as fo llows : M=Standard Marker; A=A. koa positive control; N=negative control; CON= A. conjilsa; AR= A. auriculiformis; AN= A. anguslissima; ML= A. melanoxy lon; MR= A. mearnsii; MG= A. mangium. umbers below species codes represent an individual of each species.
72
ccSSR9 (Chung and Staub, 2003), confirming that failure to cross-amplifY was not the
result of poor DNA quality.
73
CHAPTERS DISCUSSION
Morphological variations among populations of the A. koa complex provide a
basis for comparison between different groups. While some characteristics such a seed
alignment within the pod and tree height are useful to distinguish different groups, other
variables such as phyllode size and shape, seed size, and branching patterns are more
variable and not effective at differentiating populations. Another problem with
identification using seed pod or seed characteristics is that seed production occurs over a
relatively short three month period usually between August and December, or whenever
the tree is stressed. Wood density has been shown to be significantly different between
A. koa and A. koaia, but destructive sampling is required to analyze this property, which
is not practical for threatened plant taxa such as A. koaia (Oldfield et aI., 1998; Wagner et
al., 1999).
In the case of Hawaii's diverse ecosystems where rainfall, topography, and soils
are variable over short geographic distances, environmental conditions may allow for
development of morphologically variable ecotypes (St. John, 1979). These factors make
characterization based on phenotype difficult. The advantage of molecular analysis of
DNA from individual samples is that it is at the genotypic level, not phenotypic analysis
which may be influenced by environmental factors. Also, molecular analysis requires
only a small amount of phyllode tissue per tree for DNA extraction, therefore it is a non-
destructive sampling procedure. These characteristics of molecular methods make them
valuable for studies of diversity and population genetics.
74
DNA sequencing
The molecular approaches used to assess the A. koa complex revealed general
relationships regarding placement within the Acacia genera, as well as specific
associations between populations from different islands and groups. Little variation was
observed between groups using chloroplast DNA sequencing, although the trnK / matK
region was still informative as it revealed the placement of koa groups within the Acacia
genus.
Compared to the nuclear genome, the chloroplast genome is highly conserved and
has a lower mutation rate (Johnson and Soltis, 1994). Generally the chloroplast genome
has a uniparental (maternal) mode of transmission in plants, and may exhibit patterns of
genetic variation different than that of the nuclear genome (Basu et al., 2004). The
possibility of genetic variation between the two genomes was the basis for utilizing both
nuclear and chloroplast gene regions. The clustering of subgenera Acacia and
Aculeiferum, and relative isolation of Phyllodineae in the phylogenetic tree (Figure 23),
support the proposed independent evolution of Phyllodineae from Acacia (Maslin and
Stirton, 1997).
Neither the trnK / matK region, nor the ITS region was able to clearly
differentiate the three koa groups, although this comprehensive analysis using two gene
regions had been shown to differentiate Australian Acacia species (Miller and Bayer,
2001; Miller and Bayer. 2003; Miller et al .• 2003; Murphey et al .• 2003). As the nuclear
ITS region contains more variable internal spacers, it was expected to provide resolution
75
below the genus level (Murphey et al., 2003). The ITS region contained more than twice
as many potentially informative characters within koa groups as the trnK / matK region;
however, the characterization of distinct groups was inconclusive based on the
sequencing results. Both sequencing analyses supported the close relationship between
koa and A. melanoxylon as seen in the phylogenetic trees based on parsimony analysis
(Figures 23 and 24). The trnK / matK sequencing confirmed a close association of koa to
Australian acacias. However. the placement of koa within the sections of subgenus
Phyllodineae was not further revealed from the ITS region sequencing results.
Molecular Studies
Conkle (1996) showed high polymorphism in koa using isozymes and that allele
profiles ofkoa from Hawaii were very different than those from Maui, Oahu, and Kauai.
Koa from the latter islands were not differentiated. Other than this study, little
information is known about molecular characteristics of koa populations in the Hawaiian
Islands.
MicrosateUite markers I Diversity
Due to its relatively restricted geographic range and distribution in fragmented
habitats, it was expected that the A. koaia group contained the fewest total alleles and
showed the lowest level of diversity (H) compared to the other two groups. Furthermore,
the A. koaia populations from Hawaii (KTSA and KTSB) were among the least
differentiated (PST) among all population pairs. This was expected because the two
76
populations were very close geographically. However, no support for isolation by
distance was observed for all populations, as there was no correlation between
geographic and genetic distance (Figure 27).
Acacia koa was expected to have more alleles and higher diversity than A. koaia,
and it was hypothesized that 'group three' would have values between the two. This is
because 'group three' individuals were more common than A. koaia, but still not as
widely distributed as A. koa. It is noteworthy that 'group three' had the most alleles, but
more unexpected was the high number of unique alleles found in 'group three' as well.
Both total diversity and differentiation between populations were highest for 'group
three', and diversity of all groups was higher within popUlations than among populations.
The diversity measures were confirmed by the AMOV A, which found 72.2% of genetic
variation was within populations and only 27.8% was among populations of each group.
This may be due to the high percentage of unique alleles present in each group.
MicrosatelIite markers I Population differentiation
The total genetic diversity of each population reflected the overall group diversity
measures. The three most diverse populations were from 'group three' (KANA, KHAN,
SG), and the three populations with the lowest diversity were all from the A. koa group
(KMe, KNT, and KV). Genetic differentiation shown in the UPGMA dendogram and
clustering in the principle coordinate analysis suggests that KV and KNT should be
included in the A. kaa group, although individuals from KV are morphologically similar
to those in 'group three', and KNT individuals where morphologically similar to A.
77
koaia. These results show that phenotypic variation among populations is not consistent
with molecular differences. Differentiation among populations in each group was low
(Table 7). It was similar to interpopulation differentiation reported for the A. acuminata
complex in Australia (Broadhurst and Coates, 2002).
The range of 'group three' is restricted to populations on Kauai (KANA, KHAN,
SG), but the diversity found in these populations was higher than A. koa populations
found on different islands. Studies on Australian acacias have shown that genetic
diversity of restricted or rare species is often close to that of widespread species, but
generally is lower (Gitzendanner and Soltis, 2000; Broadhurst and Coates, 2002; Elliot et
al., 2002). The genetic diversity of A. koaia populations is similar to that of populations
in the widespread A. koa group. However, all populations of 'group three' have higher
diversity than any of the A. koa populations.
Clustering in the UPGMA dendogram shows some relatedness between
populations from the same island. However, the close association of A. koa populations
from Kauai, Oahu, and Hawaii reveal clustering of populations according to groups rather
than island of origin (Figure 28). The highest differentiation among all populations was
between KNT (A. koa) and SG ('group three'), which are found in close proximity to one
another on Kauai. This observation also supports clustering by groups rather than by
island (Table 9).
78
Principle coordinate analysis based on variation in allele patterns between koa
individuals showed that most populations clustered according to group with very few
individuals overlapping (Figure 32). The separation of populations into three groups was
similar to relationships shown in the UPGMA dendograrn. Aside from the Kauai
populations KMC and KNT (A. koa) which had a few individual outliers, individuals
from each population clustered into one of three groups (Figures 32).
Genetic differentiation among populations of 'group three' (KHAN, KANA, and
SG) and those of A. koa or A. koaia, was greater than differentiation among populations
of A. koa and A. koaia (Table 9), which are recognized as distinct groups. These results
were also confirmed by both the UPGMA dendogram and the principle coordinate
analysis, suggesting that 'group three' Kauai populations form a group that is
independent of A. koa and A. koaia.
The results of microsatellite marker analyses show that 'group three' is distinct
from A. koa and A. koaia. This characterization is based on the large amount of unique
alleles observed, as well as clear differentiation from A. koa and A. koaia in both the
UPGMA dendograrn and principle coordinate analysis. The results also show that the
Oahu population (KV) and Kauai population (KNn are classified in the A. koa group.
'Group three' is restricted to just three populations, but diversity levels were higher than
those found in any population of A. koa.
79
Cross-species amplification
The conservation of microsateIlite markers across non-native acacias was
relatively low, having at most 25% amplification success. This was similar to results
from cross-species amplification of other acacias in the subgenus Phyllodineae, where
one-third of markers were conserved (Butcher et al., 2000). It was expected that more A.
koa-specific markers would be amplified by A. melanoxylon than the other non-native
Acacia because DNA sequencing results showed A. melanoxylon was most closely
related to koa compared to non-native acacias in Hawaii. Since the efficiency of cross
amplification decreases with increasing genetic distance between species, limited cross
amplification was expected between koa-specific markers and the other non-native
acacias. (Dayanandan et al., 1997; Butcher et al., 2000; Selkoe and Toonen, 2006).
Therefore, it was unexpected that A. confusa and A. mearnsii amplified the same number
of markers as A. melanoxylon. It is difficult to relate the success of cross-species
amplification to genetic distance between these Acacia species with only eight markers
tested. The eight koa-specific microsateIlite markers would be of limited use for
molecular studies of non-native acacias found in Hawaii, based on these results.
Koagroups
The classification of the A. koa complex often includes descriptions ofkoa based
on island origin and have been argued to be distinct species based on variations in
morphological characteristics. Acacia koa and A. koaia are accepted as distinct groups,
but A. kauaiensis is often grouped together with either A. koa or A. koaia (St. John, 1979,
80
Wagner et al., 1999, GBIF Data Portal, 2007; ITIS, 2007). Phenotypic variation in the
'group three' populations included individuals with the tree structure of A. koa and seed
pods of A. koaia, and also individuals with the tree structure of A. koaia and seed pods of
A. koa. These are similar to characteristics of taxa described by Wagner e/ al. (1999) as
A. kauaiensis Hillebrand, and it is proposed that these populations be classified as such.
The phenotypic similarity of 'group three' populations to those described by Wagner e/
al. (1999), accompanied with molecular analysis from this study supports the inclusion of
'group three' (similar to A. kouaiensis) with A. koa and A. koaia, as distinct groups of
koa. Whether this distinction is at the species, subspecies, or variety level remains
unclear, due to inconclusive sequencing results. These results suggest that the genetic
differentiation between 'group three' (similar to A. kauaiensis) and either A. koa or A.
koaia, is equal to the differentiation between A. koa and A. koaia.
Conclusions I Applications
Several conclusions can be made based on the results of molecular analysis of the
A. koa complex. The three koa groups are closely related to Acacia species found in
Australia, rather than those native to Asia and the Americas. Within the subgenus
Phyllodineae, koa is most similar to A. melanoxylon based on the high similarity of
nuclear and chloroplast DNA sequences. Among the koa groups, populations comprising
the A. koaia group have the lowest diversity and 'group three' has the highest diversity
and most unique alleles based on microsatellite marker analysis. It can be concluded that
three distinct groups exist in the koa complex, A. koa, A. koaia, and 'group three'(similar
to A. kouaiensis).
81
The primary objectives of this study were to determine the placement of koa in
the broader genus of Acacia, to reveal associations between groups ofkoa, and to analyze
diversity in populations from common and rare species. Many koa populations have been
described by island for morphological variations, but limited genetic diversity studies
using molecular approaches have been done. DNA sequencing of koa populations using
gene and spacer regions revealed a close association with A. melanoxylon. It did not
provide conclusive evidence for differentiation of the three koa groups. MicrosateIlite
marker analysis, on the other hand, showed evidence of three clearly distinct groups of
koa, described here as A. koa, A. koaia, and 'group three'. Diversity and differentiation
between uncharacterized populations are understood more clearly by utilizing
microsateIlite markers, as shown in this study. Among molecular markers, the variability
of microsateIlite markers allowed greater differentiation of groups of koa than studies
utilizing isozymes (Conkle, 1996).
The degree of differentiation and diversity in populations provides insight for
conservation and disease resistance questions by providing a genetic framework on which
to base future studies. By determining the level and partitioning of diversity in koa, a
greater understanding of conservation needs can be developed. This study provides a
molecular determination of koa population diversity that can be utilized for conservation,
and has application for selecting germplasm to be used in disease resistance and breeding
studies.
82
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