First published online January 30, 2003; 10.1104/pp.012492
Plant Physiol, March 2003, Vol. 131, pp. 1294-1301
Genetic Diversity of Eurycoma longifolia Inferred
from Single Nucleotide
Polymorphisms1,[w]
Asiah
Osman,
Barbara
Jordan,2
Philip A.
Lessard,
Norwati
Muhammad,
M.
Rosli
Haron,
Norifiza Mat
Riffin,
Anthony J.
Sinskey,
ChoKyun
Rha,* and
David E.
Housman
Malaysia-MIT Biotechnology Partnership Programme (A.O., B.J.,
P.A.L., N.M., M.R.H., N.M.R., A.J.S., C.R., D.E.H.), Center for Cancer
Research (A.O., B.J., D.E.H.), Department of Biology (P.A.L., A.J.S.),
and Biomaterials Science and Engineering Laboratory (C.R.),
Massachusetts Institute of Technology, 77 Massachusetts Avenue,
Cambridge Massachusetts 02139; and Forest Research Institute of
Malaysia, Kepong, 52109 Kuala Lumpur, Malaysia (A.O., N.M., M.R.H.,
N.M.R.)
 |
ABSTRACT |
Eurycoma longifolia Jack. is a treelet that grows in
the forests of Southeast Asia and is widely used throughout the region because of its reported medicinal properties. Widespread harvesting of
wild-grown trees has led to rapid thinning of natural populations, causing a potential decrease in genetic diversity among
E. longifolia. Suitable genetic markers
would be very useful for propagation and breeding programs to support
conservation of this species, although no such markers currently exist.
To meet this need, we have applied a genome complexity reduction
strategy to identify a series of single nucleotide polymorphisms (SNPs)
within the genomes of several E.
longifolia accessions. We have found that the occurrence
of these SNPs reflects the geographic origins of individual plants and
can distinguish different natural populations. This work demonstrates
the rapid development of molecular genetic markers in species for which
little or no genomic sequence information is available. The SNP markers
that we have developed in this study will also be useful for
identifying genetic fingerprints that correlate with other properties
of E. longifolia, such as high regenerability or the appearance of bioactive metabolites.
 |
INTRODUCTION |
Eurycoma longifolia
Jack., from the family of Simaroubaceae is commonly distributed in
South East Asia including Myanmar, Thailand, Laos, Cambodia,
Indo-China, and Malaysia. This tree has achieved considerable attention
from the public for its medicinal properties and is used traditionally
as a blood coagulant for complications during childbirth, as a
treatment for dysentery, and as an aphrodisiac, among other
applications. Extracts from E. longifolia also
contain biologically active compounds with antiplasmodial activity
(Chan et al., 1986 ). Increased harvesting of wild-grown
trees for their medicinal use has led to rapid thinning of natural
populations and a potential loss of genetic diversity in this species.
Genetic diversity studies are essential for providing information for
propagation, domestication, and breeding programs as well as
conservation of genetic resources for this species.
Molecular markers have proven to be powerful tools for assessing
genetic variation within and between populations of plants. Several
criteria should be considered in choosing molecular techniques for
genetic diversity studies including the following: whether the
techniques are highly reproducible between laboratories and whether the
data that is generated can be reliably transferred; whether markers are
dominant or codominant, allowing homozygotes and heterozygotes to be
distinguished; the amount of genomic sequence information required; and
whether the markers detect highly polymorphic loci. At present, various
molecular techniques are available for assessing genetic diversity in
plants including identification of isozymes (Gomory et al.,
2001 ; Nassar et al., 2001 ); amplified fragment
length polymorphisms (Creswell et al., 2001 ;
Quagliaro et al., 2001 ), random amplified polymorphic
DNA, RFLP, and microsatellites (Maguire et al., 2000 ;
Walter and Epperson, 2001 ). However, the limitations of
these techniques include low numbers of polymorphic loci, their
requirements for large amounts of DNA, or their poor reproducibility
and labor intensity.
Because little or no information on genetic diversity in E. longifolia has been generated, we have tested a highly
polymorphic marker to investigate the level of genetic diversity
between and within populations of this species using single nucleotide
polymorphism (SNPs). SNPs have become popular tools for identifying
genetic loci that contribute to phenotypic variation based on linkage disequilibrium. Compared with other genetic markers, SNPs are more
abundant in the genome and are much more stably inherited. Another
advantage of SNP-based genotyping is that SNP detection does not
involve gel electrophoresis, which is relatively slow and labor
intensive. Many different strategies have been developed for high
throughput detection of SNPs including high-density oligonucleotide hybridization arrays (Wang et al., 1998 ), dynamic
allele-specific hybridization (Pennisi, 1998 ), and the
Taqman assay (Livak et al., 1995 ). In this study, we use
allele-specific oligonucleotide hybridization (Jordan et al.,
2002 ) to detect polymorphisms among many different accessions
of E. longifolia. The goal of this study is to
assess the genetic relationships between and within different geographical populations of E. longifolia.
 |
RESULTS |
E. longifolia plants were
collected from six geographically distinct locations in peninsular
Malaysia, and genomic DNA was extracted from each of the 47 plants
(Fig. 1A; Table
I). Five degenerate
oligonucleotide-primed (DOP)-PCR primers, each with 3'
sequences of different lengths and composition, were used
to amplify fragments from genomic DNA of one of these individual plants. According to Jordan et al. (2002) , increasing
the length of the specific sequence at the 3' end of the primer should
decrease the complexity of the PCR product mixture. Lowering the
annealing temperature and/or shortening extension times should also
reduce the size of PCR products. In the present, experiment we used
DOP-PCR primers with nine to 12 nucleotides at their 3' ends and lower annealing temperature (42°C) than have been reported for DOP-PCR with
Arabidopsis, mouse, and human (Jordan et al., 2002 ).
DOP-PCR products were ligated into pCR2.1-TOPO plasmid for further
analysis.

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Figure 1.
A, Peninsular Malaysia depicting geographic
distribution of populations from which E. longifolia
accessions were collected. The geographic origin of materials
propagated in tissue culture was not known. Although domesticated
populations were similarly maintained on a plantation in southwest
Malaysia, the geographic origins of the founders of this population
were not known. B, Summary of SNP data for individual plants from six
collections. Homozygosity and heterozygosity are indicated by color:
blue, homozygous for the major allele; red, homozygous for the minor
allele, green, heterozygous; white, no/inconclusive data, except in the
final (summary) column for each population, where white indicates the
presence of polymorphic loci within that population. C, Dendrogram from
unweighted pair group method (UPGMA) cluster analysis based on the
unbiased genetic distance in E. longifolia
populations of Nei (1978) . Color coding corresponds to
populations as shown in A. D, Dendrogram from UPGMA cluster analysis
based on the unbiased genetic distance between individuals of
Nei (1978) . Annotations indicate populations from which
individuals originated: J, Johor, M, plantation grown; P, Pahang, TC,
tissue culture collection; T, Terengganu; and L, Langkawi. E,
Dendrogram from Ward's analysis of genetic distance between
individuals.
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Locus-Specific (LS) Primer
A total of 480 clones (96 from each of the five DOP-PCRs) were
characterized by end sequencing with universal primers that anneal to
the common vector sequences. Terminal sequences were obtained from 263 of these clones, of which 132 (55%) were unique (Table
II). DOP-PCR primer 2 produced the
highest percentage of unique sequences (68%), whereas the lowest
percentage of unique sequences was obtained from DOP-PCR 1 (30%).
SNP Identification and Validation
One hundred and thirty-two sets of LS primers were made and used
for the PCR amplification of fragments from the genomic DNA of three
E. longifolia individuals representing three locations (one
each from Johor [J1], Langkawi [L9], and Terengganu [T17]). One
hundred and twenty-three (95%) of the LS primers produced a single
product of the same length from at least two individuals (Table II).
The resulting PCR products were sequenced directly (without first
cloning into plasmid vectors). From the sequence data of these
products, a visual comparison of aligned sequences revealed 144 putative SNPs.
Putative SNPs were validated using allele-specific oligonucleotide
(ASO) hybridization. A polymorphism was considered to be an
ASO-validated SNP (true SNP) if the LS products hybridized to its
corresponding ASO, matching the pattern of the sequencing results. A
total of 98 SNPs (71%) were validated (Table
III).
Using the same method, we then scored 47 individuals with respect to 58 ASO-validated SNPs (two of which are shown in Fig. 2). The genotyping results from seven of
the SNPs were eliminated because the data were difficult to score due
to weak hybridization signal or failure of the ASO to hybridize in most
of the samples tested.

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Figure 2.
Examples of SNP genotyping of 47 E. longifolia samples. In each case, identical blots were
prepared carrying LS-PCR products from each of the different
accessions; then one blot was hybridized with the ASO for the first
allele, and the second blot was hybridized with the ASO for the second
allele. The circle indicates an individual that is homozygous for the
second allele, whereas the box adjacent to it demonstrates that another
accession was heterozygous for these two alleles. The lack of
heterozygosity detected with SNP98 illustrates how some SNPs reported
starkly different results.
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SNP Genotyping Data
Data generated from SNP genotyping showed a high degree of
polymorphism between individuals (Fig. 1B). We categorized the SNP data
according to the alleles observed, homozygous (minor and major)
alleles, and heterozygous alleles. For each SNP, the more commonly
occurring alleles were called major alleles, and the less common
alleles found were categorized as minor (rare) alleles. Samples that
contained both alleles were scored as heterozygous.
Genetic Diversity
Overall, of all the loci tested 49% to 75% (average = 64%)
were polymorphic within a population (Fig. 1B; Table
IV). The lowest number of polymorphic
loci (and therefore presumably the least genetic diversity) was
observed in tissue culture samples, and the highest frequency of
polymorphic loci was observed in the Melaka (plantation) population.
Nei's (1978) mean expected heterozygosity was higher
than observed with an average of He = 0.216 (±0.029) and Ho = 0.182 (±0.035), respectively. The Pahang population had the lowest
heterozygosity, He = 0.177 (±0.028), whereas the highest heterozygosity was from the Johor population, He = 0.246 (±0.028). In four of the populations, the value of Ho was lower than
He, indicating an excess of homozygotes in these groups. However, in
the cases of the Pahang and tissue culture populations, the differences
between the observed and the expected heterozygosities were not
significantly different.
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Table IV.
Summary of genetic diversity in E. longifolia
populations
Na, Mean sample size per locus; Aa, average no. of alleles per
polymorphic locus; P, percentage of polymorphic loci (95% criterion);
Ho, observed heterozygosity; and He, expected heterozygosity. Values in
parentheses are SES.
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Total genetic diversity (Ht) and gene diversity within populations at
polymorphic loci averaged 0.288 and 0.219, respectively (Table
V). The mean genetic differentiation
between populations (Gst) was 0.240 indicating that about 24% of the
observed genetic diversity was due to variation between E. longifolia populations and the remaining 76% was a function
of genetic differentiation among plants within populations.
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Table V.
Summary of G-statistic (Nei, 1978 )
calculated from 51 polymorphic loci over six populations
Hs, Within population genetic diversity. Dst, Average gene diversity
among populations.
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Genetic Distance
The mean genetic distances D (Nei, 1978 ) between
populations was 0.119, with a range of 0.012 to 0.229 (Table
VI). UPGMA cluster analysis between
populations using Nei's unbiased genetic distance revealed two
distinct clusters (Fig. 1C). The first cluster comprised Johor, Pahang,
tissue culture samples, and the more distantly related individuals from
the Terengganu population. The Langkawi and Melaka populations
clustered in a second group, suggesting that the plantation material
was derived from the island population. Similar results were obtained
when cluster analysis was performed on the individual plants (Fig. 1, D
and E). With very few exceptions (e.g. M34), these plants clustered
into cohesive groups corresponding to their distinct geographic
origins. When Ward's method was used for cluster analysis, all of the
plantation-grown individuals clustered with the Langkawi
population.
 |
DISCUSSION |
In general, the present study shows that populations of
E. longifolia possess a high level of genetic
diversity (P = 64%, He = 0.216 ± 0.029).
The mean heterozygosity between populations of
E. longifolia was higher compared with other
regional, tropical, long-lived trees reported from isozyme studies
(He = 0.125+0.012; Hamrick et al., 1992 ), conifers
(He = 0.145+0.008; Hamrick et al., 1992 ),
eucalyptus (He = 0.182; Moran and Hopper,
1987 ), and Acacia auriculformis (He = 0.081, Wickneswari and Norwati, 1993 ). However, the value for
E. longifolia is lower than for timber species such as
Shorea leprosula (He = 0.369+0.025; Lee et al., 2000b ), Stemonoporous oblingifolius (He = 0.297+0.039; Murawski and Bawa, 1994 ), and
Dryobalanops aromatica (He = 0.459+0.117; Lee et
al., 2000a ). The validity of this comparison may be questioned because the studies were made using different molecular markers, i.e.
SNPs versus isozymes. In isozyme studies, the level of genetic diversity between populations is determined by allele frequency, mean
number of alleles, heterozygosity, percentage of polymorphic loci, etc.
In the present study, the level of genetic diversity was determined by
the mean of heterozygosity and percentage of polymorphic loci. Allele
frequency and mean number of polymorphic alleles were excluded from our
calculation because the technique was developed to detect only two
different alleles.
The perceived diversity within E. longifolia might also be
affected by the small number of individuals per population used in the
study. According to electrophoretic surveys by Nei and Roychoudhury (1974) , Nei (1978) , and
Gorman and Renzi (1979) , a large number of loci should
be examined if the number of individuals per locus is small. In fact, a
few individuals are sufficient for estimating heterozygosity if a
sufficiently large number of loci are examined (Gorman and
Renzi, 1979 ). Although it is difficult to compare the data from
electrophoretic and SNP-based studies (the former being a protein-based
assay and the latter focusing on DNA), preliminary data from recent
electrophoretic assays (Norfiza et al., 2001 ) support
the conclusion that SNP markers provide more sensitive assays of
genetic diversity.
The mean degree of population differentiation in E. longifolia (Gst = 0.24) is higher than wind-pollinated
species such as conifers (Gst = 0.05; Matheson et al.,
1989 ) and S. leprosula (Gst = 0.085;
Lee et al., 2000b ), and insect-pollinated
eucalyptus (Gst = 0.10-0.12; Moran and Hopper,
1987 ). Low values for population differentiation suggest that
effective and extensive seed migration in these species minimizes
fragmentation of these populations. In contrast, a high Gst value in
E. longifolia might reflect poor pollen movement
and the limitations of gravity-based seed dispersal in this species,
both of which would be expected to genetically isolate individual populations.
Cluster analysis between populations of E. longifolia revealed two major groups, with the plantation
population being closely related to that from Langkawi, suggesting that
individuals or seedlings from plantation might have originated from
Langkawi. The populations from Pahang and the tissue culture collection are closely related to the population from Johor, whereas the population from Terengganu forms a somewhat more distantly related subpopulation within the second group. The distinction between the
population from Langkawi and the other two groups could be explained by
its geographical isolation (it is an island population), which is
expected to limit gene exchange between populations.
Similar results were observed in cluster analysis among individuals
(Fig. 1, D and E). An interesting finding was observed with tissue
culture samples, where callus samples that are capable of producing
somatic embryos cluster together (TC42, TC43, TC44, TC45, and TC46),
whereas a nonembryogenic callus line (TC47) did not (data
on regenerability not shown). Although many more individuals should be
tested in this regard before a firm correlation can be drawn, this
observation suggests that SNPs could be employed as molecular markers
for predicting whether a particular accession of E. longifolia will be amenable to regeneration via somatic embryogenesis. This result would be very valuable for micropropagation of this sought-after forest species.
Another strategy to identify SNPs among the genomes of
undercharacterized species might be to collect sequence information from the 3' ends of cloned expressed sequence tags (ESTs; e.g. Ching and Rafalski, 2002 ). SNPs identified in this
manner would offer the advantages of (a) the sequences not being
anonymous (i.e. the expressed genes with which they are associated may
be identified by a BLAST search [Altschul et al.,
1997 ]); and (b) a higher likelihood that the SNPs initially
identified are allelic. Although such a method might be useful for
identifying SNPs in E. longifolia, the lack of a suitable
EST library or for that matter a reliable RNA extraction
protocol made the DOP-PCR strategy preferable because it requires only
vanishingly small amounts of genomic DNA. Other advantages of the
DOP-PCR method include (a) the fact that it provides a simple method
for PCR amplification of all of the markers in a single batch, thus
providing a template for genotyping; and (b) the fact that DOP-PCR may
also allow for identification of SNPs from regions of the genome that
are not particularly gene rich, enabling more complete coverage of the genome. Although an EST-based strategy might have the benefit of
permitting gene identification, this would still not allow the
assignment of the newly discovered SNPs to a map location in E. longifolia because gene locations are completely uncataloged in
this species, and very few assumptions could be made about synteny
between E. longifolia and other species. Nonetheless, some
caveats associated with the DOP-PCR technique should be acknowledged. Because no controlled segregating populations of these primarily wild-grown plants were available at the time of this study, we were
unable to carry out allelism tests for the SNPs identified by the
DOP-PCR method. We hope to work with controlled populations in the
future to address this issue and to begin constructing genetic maps for
this species. From previous results with human, mouse, and Arabidopsis
DNA (Jordan et al., 2002 ), we found the DOP-PCR
technique favors the identification of DNA fragments and SNPs that are
present in single copies. These studies also showed that the SNPs
identified through DOP-PCR segregated in a Mendelian manner. However,
the assumption that these trends hold true in E. longifolia
has not yet been tested.
From this study, we have identified 51 SNPs that can be used as genetic
markers in E. longifolia. Cluster analysis showed that diversity among the different accessions of E. longifolia corresponds well with the geographic origins of
each population. These markers should prove useful in preserving
genetic diversity among domesticated populations of E. longifolia. These SNPS may also be developed as
predictive markers for useful phenotypes such as regenerability.
 |
MATERIALS AND METHODS |
Plant Material
A total of 47 Eurycoma longifolia Jack.
individuals representing four natural populations, one domesticated
population, and materials that had been propagated in tissue culture
were collected in Peninsular Malaysia. Leaf materials from six to nine
trees were collected from each population as shown in Figure 1A. The locations of each population are listed in Table I. Total genomic DNA
from leaf tissue was extracted using a modified
cetyl-trimethyl-ammonium bromide method (Doyle and Doyle,
1987 ).
DOP-PCR Reactions
DOP-PCR primers for whole genome amplification used in the
experiments were designed as described by Telenius et al.
(1992) . The primer includes a C/G rich 5' anchor (CTCGAG), six
"N" where N is A, C, G, or T (4,096-fold degeneracy) and nine to 12 arbitrary, specified nucleotides at the 3' end of each primer. The
DOP-PCR reaction mix was as follows: 50 ng of genomic DNA, 0.2 mM dNTPs, 2.5 units of Amplitaq DNA polymerase (Applied
Biosystems, Foster City, CA), 3.0 µM degenerate primer,
and 10× PCR buffer in a total of 50-µL reaction volume. The cycling
profile was as follows: 94°C for 1 min; five cycles of 94°C for
30 s, 42°C for 45 s, and 72°C for 1.5 min; 35 cycles of
94°C for 30 s, 58°C for 45 s, and 72°C for 1.5 min;
72°C for 10 min; and hold at 4°C. The sequences of the DOP-PCR
primers are given in Table II. All degenerate primers were purchased
from Invitrogen (Carlsbad, CA). Fifty microliters (250-1,500 bp) of
five DOP-PCR mixtures were gel purified using Qiaquick PCR purification
kit (Qiagen USA, Valencia, CA) and shotgun cloned according to the
protocol of the TOPO XL cloning kit (Invitrogen).
End Sequencing of Cloned DOP-PCR Products
The termini of 480 cloned DOP-PCR products inserts were
sequenced with the universal primers (M13 Forward and M13 reverse) in
50-µL reactions: 0.2 mM dNTPs, 2.0 µL of overnight
culture, 1.25 units of Amplitaq DNA polymerase, 0.4 µM
each primer, and 5.0 µL of 10× buffer. The PCR cycles were 94°C
for 5 min; 35 cycles of 94°C for 30 s, 55°C for 30 s, and
72°C for 1 min; 72°C for 10 min; and hold at 4°C. The entire
products were loaded onto 1.1% (w/v) agarose gel,
electrophoresed, and gel purified using Qiaquick 96 PCR purification
kit (Qiagen USA). The purified PCR products were sent for automated
sequencing at MWG Biotech Inc. (High Point, NC).
LS Primer Design
After sequencing of the cloned DOP-PCR products, the 20 bp of
sequence immediately adjacent to the DOP-PCR primer sequences at either
end of all clones were tabulated and sorted. Duplicate clones were
eliminated, producing a list of unique loci. Pairs of LS primers were
designed based on these unique sequences such that one primer of each
pair contained a 5' M13 forward tag (TGT AAA ACG ACG GCC AGT) and the
other primer contained a 5' M13 reverse tag (CAG GAA ACA GCT ATG ACC).
Primers were synthesized by MWG Biotech Inc.
SNP Identification
The LS primer pairs were used for PCR amplification of fragments
from three individuals representing different E.
longifolia populations. PCR was carried out in 50-µL
reactions: 1 µL of appropriate DOP-PCR products as a template DNA,
0.2 mM dNTPs, 2.5 units of Amplitaq DNA polymerase, 0.4 µM each primer, and 5 µL of 10× buffer. A touch down
cycling profile was as follows: 94°C for 1 min; 40 cycles of 94°C
for 30 s, 65°C for 30 s, and 72°C for 1 min; 10 cycles of
94°C for 30 s, 50°C for 30 s, and 72°C for 1 min;
72°C for 10 min; and hold at 4°C. The entire PCR products were
separated on 1.1% (w/v) agarose gels and purified with Qiaquick
96 PCR purification kit (Qiagen USA). The purified PCR products were
sequenced by MWG Biotech Inc. using the M13 forward and reverse
primers. Sequence data was analyzed with the Lasergene Seq-Man II
program (DNASTAR, Inc., Madison, WI) to find putative SNPs.
SNP Validation and Genotyping
For each allele of each putative SNP, a 17-mer oligonucleotide
(MWG Biotech, Inc.) centered on the putative polymorphic nucleotide was
made. Each putative SNP was validated by ASO hybridization to the
LS-PCR product and DOP-PCR product mixtures from three individuals
following the method of Jordan et al. (2002) . These ASO-validated SNPs were used to genotype 47 individuals of
E. longifolia (supplemental data,
available at www.plantphysiol.org).
Data Analysis: SNP Genotyping
Data generated from 47 individuals were entered in an Excel
spreadsheet (Microsoft, Redmond, WA) and were categorized as homozygous (minor and major) and heterozygous alleles. These are depicted in
Figure 1B. In a small number of cases, data for individual SNPs were inconclusive.
Genetic Diversity
Data were scored as presence and absence of major and minor
alleles (homozygous) or presence of both alleles (heterozygous) for
each sample. The level of genetic diversity and cluster analysis was
conducted with the program GENEPOP v.3.2a (Raymond and Rousset, 1995 ). Percentage polymorphic loci and mean heterozygosity
between populations were estimated using Biosys-1 (Swofford and
Selander, 1981 ). The Ht at the polymorphic loci and the Gst
were determined following the G-statistic of Nei (1978)
with the assistance of the FSTAT computer program (v2.1.9;
http://www.unil.ch/izea/softwares/fstat.html). Nei's
(1978) unbiased distance (D) was estimated
between populations and individuals to generate average linkage
clustering using the UPGMA. A phenogram of Nei's (1978)
genetic distance was prepared using Biosys-1. Cluster analysis using
Ward's method was also carried out on data from individual plants
using the StatGraphics Software package (Manugistics, Rockville, MD).
Distribution of Materials
Upon request, all novel materials described in this publication
will be made available in a timely manner for noncommercial research
purposes, subject to the requisite permission from any third-party
owners of all or parts of the material. Obtaining any permissions will
be the responsibility of the requestor.
 |
ACKNOWLEDGMENTS |
We thank Fadhilah Zainudin and Nor Hasnida for providing samples
of cultured E. longifolia and Dr. Azizol
Abdul Kadir, Dr. Mohd. Ilham Adenan, and colleagues at the Forest
Research Institute of Malaysia for supplying plant material for this
study and for technical assistance.
 |
FOOTNOTES |
Received August 6, 2002; returned for revision September 25, 2002; accepted December 9, 2002.
1
This work was supported by the Government of
Malaysia and the Malaysia-Massachusetts Institute of Technology
Biotechnology Partnership Program.
2
Genomics Collaborative, Inc., 99 Erie Street, Cambridge,
MA 02139.
[w]
The online version of this article contains Web-only
data. The supplemental material is available at
www.plantphysiol.org.
*
Corresponding author; e-mail ckrha{at}mit.edu; fax
617-253- 6358.
Article, publication date, and citation information can be found at
www.plantphysiol.org/cgi/doi/10.1104/pp.012492.
 |
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