important papers

Name:
Location: Kyoto, Kansai, Japan

60 kg, 5'7", Red white, Slim face slender body, small laughs and big smiles, Atleast you wont be frightened even if you encounter me in dusk and dawn.

Wednesday, July 19, 2006

DBGET search result KEGG soybean

http://www.genome.ad.jp/dbget-bin/www_bfind_sub?mode=bfind&max_hit=1000&dbkey=kegg&keywords=soybean

Reverse complement ClastalW

Here: http://bioinformatics.org/sms/rev_comp.html

Multiple sequence Allignment by CLUSTALW

IMP: http://align.genome.jp/

Plant tizzue culture Micropopagation

click
http://aggie-horticulture.tamu.edu/tisscult/microprop/microprop.html

Plant transformation Technologies

good:
http://www.univie.ac.at/planttranstech/frameset.html

Agrobacterium-mediated transformation

Agrobacterium-mediated transformation
of soybean and recovery of transgenic
soybean plants


web page: http://www.agron.iastate.edu/ptf/protocol/Soybean.pdf



Agrobacterium-mediated transformation
of soybean and recovery of transgenic
soybean plants
Paz et al. (2005) Improved cotyledonary node method using an alternative explant derived from mature
seed for efficient Agrobacterium-mediated soybean transformation. Plant Cell Reports 2005.
Materials
a Plasmid
Different plant transformation constructs that were derivatives of base vector pTF101.1
were introduced into Agrobacterium tumefaciens strain EHA101 (Hood et al. 1986). The
base vector pTF101.1 is a derivative of the pPZP binary vector (Hajdukiewicz et al.,
1994) that includes the right and left T-DNA border fragments from a nopaline strain of
A. tumefaciens, a broad host origin of replication (pVS1) and a spectinomycin-resistant
marker gene (aadA) for bacterial selection. The plant selectable marker gene cassette
consists of (1) double 35S promoter (2x P35S) of cauliflower mosaic virus (CaMV)
(Odell et al. 1985), (2) tobacco etch virus translational enhancer (Carrington and Freed
1990), (3) the phosphinothricin acetyl transferase (bar) gene from Streptomyces
hygroscopicus that confers resistance to the herbicide phosphinothricin and its
derivatives.). pTF101.1 contains a multiple cloning site (MCS) for facilitating
subcloning of the gene of interest in between the right border region and the plant
selectable marker cassette. The soybean vegetative storage protein terminator (Mason et
al., 1993) was cloned to the 3’ end of the bar gene. The vector pTF102 was derived from
pTF101.1 by inserting the P35S GUS intron cassette (Vancanneyt et al. 1990) into the
Hind III site of pTF101.1 The gus gene contained a portable intron in its codon region
(Vancanneyt et al., 1990) to prevent GUS activity in Agrobacterium cells.
a Plant material
Soybean cultivars Thorne, Williams, Williams79, and Williams82
Media
a YEP Solid Medium:
5 g/L Yeast extract, 10 g/L Peptone, 5 g/L NaCl2, 12 g/L Bacto-agar. pH to 7.0 with
NaOH. Appropriate antibiotics should be added to the medium after autoclaving. Pour
into sterile 100x15 plates (~25ml per plate).
a YEP Liquid Medium:
5 g/L Yeast extract, 10 g/L Peptone, 5 g/L NaCl2. pH to 7.0 with NaOH. Appropriate
antibiotics should be added to the medium prior to inoculation.

a Co-cultivation Medium:
1/10X B5 major salts, 1/10X B5 minor salts, 2.8 mg/L Ferrous, 3.8 mg/L NaEDTA, 30
g/L Sucrose, 3.9 g/L MES, and 4.25 g/L Noble agar (pH 5.4). Filter sterilized 1X B5
vitamins, GA3 (0.25 mg/L), BAP (1.67 mg/L), Cysteine (400 mg/L), Dithiothrietol (154.2
mg/L), and 40 mg/L acetosyringone are added to this medium after autoclaving. Pour
into sterile 100x15 mm plates (~88 plates/L). When solidified, overlay the co-cultivation
medium with sterile filter paper to reduce bacterial overgrowth during co-cultivation
(Whatman #1, 70 mm).
a Infection Medium:
1/10X B5 major salts, 1/10X B5 minor salts, 2.8 mg/L Ferrous, 3.8 mg/L NaEDTA, 30
g/L Sucrose, 3.9 g/L MES (pH 5.4). Filter sterilized 1X B5 vitamins, GA3 (0.25 mg/L),
BAP (1.67 mg/L), and 40 mg/L acetosyringone are added to this medium after
autoclaving.
a Shoot Induction Washing Medium:
1X B5 major salts, 1X B5 minor salts, 28 mg/L Ferrous, 38 mg/L NaEDTA, 30 g/L
Sucrose, and 0.59 g/L MES (pH 5.7). Filter sterilized 1X B5 vitamins, BAP (1.11 mg/L),
Timentin (100 mg/L), Cefotaxime (200 mg/L), and Vancomycin (50 mg/L) are added to
this medium after autoclaving.
a Shoot Induction Medium I:
1X B5 major salts, 1X B5 minor salts, 28 mg/L Ferrous, 38 mg/L NaEDTA, 30 g/L
Sucrose, 0.59 g/L MES, and 7 g/L Noble agar (pH 5.7). Filter sterilized 1X B5 vitamins,
BAP (1.11 mg/L), Timentin (50 mg/L), Cefotaxime (200 mg/L), and Vancomycin (50
mg/L) are added to this medium after autoclaving. Pour into sterile 100x20 mm plates
(26 plates/L).
a Shoot Induction Medium II:
1X B5 major salts, 1X B5 minor salts, 28 mg/L Ferrous, 38 mg/L NaEDTA, 30 g/L
Sucrose, 0.59 g/L MES, and 7 g/L Noble agar (pH 5.7). Filter sterilized 1X B5 vitamins,
BAP (1.11 mg/L), Timentin (50 mg/L), Cefotaxime (200 mg/L), Vancomycin (50 mg/L)
and Glufosinate (6 mg/L) are added to this medium after autoclaving. Pour into sterile
100x20 mm plates (26 plates/L).
a Shoot Elongation Medium:
1X MS major salts, 1X MS minor salts, 28 mg/L Ferrous, 38 mg/L NaEDTA, 30 g/L
Sucrose, 0.59 g/L MES, and 7 g/L Noble agar (pH 5.7). Filter sterilized 1X B5 vitamins,
Asparagine (50 mg/L), L-Pyroglutamic Acid (100 mg/L), IAA (0.1 mg/L), GA3 (0.5
mg/L), Zeatin-R (1 mg/L), Timentin (50 mg/L), Cefotaxime (200 mg/L), Vancomycin
(50 mg/L), and Glufosinate (6 mg/L) are added to this medium after autoclaving. Pour
into sterile 100x25 mm plates (22 plates/L).
a Rooting Medium:
1X MS major salts, 1X MS minor salts, 28 mg/L Ferrous, 38 mg/L NaEDTA, 20 g/L
Sucrose, 0.59 g/L MES, and 7 g/L Noble agar (pH 5.6). Filter sterilized 1X B5 vitamins,
Asparagine (50 mg/L), and L-Pyroglutamic Acid (100 mg/L) are added to this medium
after autoclaving. Pour into sterile 150x25 mm vial (10ml/vial).
Methods
a Seed Sterilization
1. Place mature soybean seeds in 100x15 mm petri plates in a single layer (about 130 seeds
per plate).
2. Arrange 3-4 plates in a bell jar desiccator within a fume hood in such a way that all
interior plate surfaces are exposed and allow enough space to accommodate a 250 ml
beaker.
3. Using appropriate hand protection, fill the 250 ml beaker with 100ml of bleach and add
3.5 ml of concentrated (12N) HCl drop wise along the side of the beaker.
4. Close the desiccator immediately and let stand overnight (16 hours).
5. After overnight exposure to chlorine gas, close the petri plates and remove them to a
laminar flow hood. Open the plates and allow them to air out for about 30 minutes to
remove the excessive chlorine gas.
a Agrobacterium Preparation
1. Bacteria cultures for weekly experiments are initiated from –80ºC glycerol stocks three
days prior to an experiment. The vector system, pTF102 in EHA101, is cultured on YEP
medium (An et al., 1988) containing 100 mg/L spectinomycin (for pTF102), 50 mg/L
kanamycin (for EHA101), and 25 mg/L chloramphenicol (for EHA101).
2. 24 hours prior to the experiment start a 2 ml culture of Agrobacterium by inoculating a
loop of bacteria from the fresh YEP plate in YEP liquid medium amended with
antibiotics.
3. Allow the culture to grow to saturation (8-10 hours) at 28oC in a shaker incubator (~250
rpm). At the end of the day, transfer 0.2 ml of starter culture to a 1 L flask containing
250 ml of YEP medium amended with antibiotics.
4. Allow the culture to grow overnight at 28°C, 250 rpm to log phase (OD650 = 0.3 – 0.6 for
EHA105) or late log phase (OD650 = 1.0 – 1.2 for EHA101).
5. Collect Agrobacterium culture by pelleting at 3,500 rpm for 10 minutes at 20°C.
6. Resuspend the pellets in infection medium by pipetting through the pellet. Bacterial cell
densities are adjusted to a final OD650=0.6 (for EHA105) or OD650=0.6 to 1.0 (for
EHA101).
7. Gently shake the resulting infection medium at 60 rpm for at least 30 minutes before use.
a Seed Imbibition
1. Under the laminar flow hood, approximately 20 hours prior to the experiment, add deionized
sterile water to the sterilized seeds until the water is ¼ cm from the top of the plate.
2. Completely cover plate with aluminum foil to block out light.

a Explant Preparation and Infection
1. Remove aluminum foil from the imbibed soybean seeds. Transfer ~20 seeds to a sterile
100x15 petri plate for dissection.
2. Using a #15 scalpel blade, make a longitudinal cut along the hilum to separate the
cotyledons and remove the seed coat. Excise the embryonic axis found at the nodal end
of the cotyledons, and remove any remaining axial shoots/buds attached to the
cotyledonary node.
3. Dissect 60 half-seed explants (30 seeds) into a 100 x 25 mm petri plate and add 30 ml of
Agrobacterium infection media. Make sure the explants are completely covered by the
infection media. Allow the explants to incubate at room temperature for 30 minutes with
occasional gentle agitation.
a Co-Cultivation
1. After infection, remove excess infection media by gently grasping the explant with sterile
forceps and tapping the forceps on the rim of the infection media plate. Transfer halfseed
explants to co-cultivation medium (6 per plate) so the flat, adaxial side is touching
the filter paper.
2. Wrap the plates with parafilm and place them at 24oC under an 18:6 photoperiod (140
µmoles s-1 m-2) for 5 days.
a Shoot induction
1. After five days of co-cultivation, briefly wash the half-seed explants in shoot induction
washing medium (~50ml in a 100 x 25 sterile petri plate, room temperature). 30 halfseed
explants may be washed for each plate of washing medium.
2. Place the explants on shoot induction medium I (5 explants per plate). Half-seed explants
should be oriented with the nodal end of the cotyledon imbedded in the medium and the
regeneration region flush to the surface with flat side up at a 30–45o angle.
3. Wrap each plate with vent tape and incubate at 24oC, 18:6 photoperiod for 14 days (if
plates are stacked, by the end of the first week, rearrange each plate in each stack so that
the top and bottom plates are switched and explants are exposed to light).
4. Explants should be transferred to shoot induction medium II after 14 days. Cut and
discard large shoots and make a fresh cut at the base of the shoot pad flush to the
medium. Orient the tissue in such a way that the freshly cut surface is imbedded into the
fresh shoot induction medium, with the differentiating region flush to the surface.
5. Maintain cultures in the Percival incubator under the same conditions described above for
another 14 days.
a Shoot Elongation
1. After 4 weeks on shoot induction medium, remove the cotyledons from the explants and
make a fresh cut at the base of the shoot pad flush to the medium.
2. Transfer the explants to fresh shoot elongation medium and incubate the tissue at 24°C,
18:6 photoperiod for 2-8 weeks.

3. Transfer the tissue to fresh shoot elongation medium every 2 weeks. At each transfer
make a fresh horizontal slice at the base of the shoot pad.
a Rooting of transgenic plants
1. When shoots surviving glufosinate selection reach at least 3 cm, excise them from the
shoot pad.
2. Soak the cut end of the shoots in filter sterilized Indole-3-butyric acid (IBA), 1 mg/ml,
for 1–2 minutes. Then transfer shoots to rooting medium in 150 x 25 mm glass vials with
the stems of the shoots embedded approximately ½ cm into the media.
3. Incubate at 24°C, 18:6 photoperiod for 1-2 weeks.
a Plant Acclimatization and Liberty Screening
1. After 1-2 weeks, when the shoot develops more than two roots, transplant it into soil.
Gently remove the plant from the rooting medium and wash off the roots with tap water
to remove any excess medium.
2. Soak 2.5 inch jiffy pots in tap water to assist in even hydration. Place each soaked jiffy
pot into an individual 2.5 inch plastic pot (cut from a four-pack) and fill with moistened
Redi-Earth Peat-Lite soil mix (Hummert Cat. # 10-2030-1). Transplant plantlets to the
soil and place them in a flat without holes, covered with a humidome. Allow the plantlets
to grow at 24oC, 18:6 photoperiod for at least one week, watering as needed.
3. When the plantlets have at least two healthy trifoliates, an herbicide paint assay may be
applied to confirm resistance to glufosinate. Using a cotton swab, apply Liberty
herbicide (150mg l-1), to the upper leaf surface along the midrib of two leaves on two
different trifoliates. Transfer painted plants to the greenhouse and cover with a
humidome. Score plantlets 3-5 days after painting. Resistant plantlets may be
transplanted immediately to 2-gallon pots.
4. Fill 50% of a 2-gallon nursery pot with 4 drainage holes with Sunshine Universal Mix
SB300. Add 1 (15 g per 2 gal. pot) Sierra 16-8-12 controlled release fertilizer tablet with
trace elements to each pot.
5. Add additional Universal Mix to bring the soil volume to 80% of the pot (~2” from top
edge of pot). Too little does not hold enough water between watering, and too much does
not allow enough water to be added at watering.
6. Transplant Liberty resistant plantlets, including the jiffy pots, to the middle of the 2-
gallon pot. The soil should cover all the roots. Be sure to plant the young plants deep
enough or they will tip over when they grow taller.
7. Fill with water to the top edge of the pot. Let it drain completely, and water once more
until the water reaches the top of the pot. The plants will not need to be watered until 7-
14 days after transplant. After this time, water as needed.

Department of Agronomy
Agrobacterium - Soybean 6 Updated 01-27-06
a Plant Care
1. Marathon, for aphid control, may be added as part of the transplant step during summer
months. If white flies or fungus gnats hover over pots, yellow sticky sheets may be used
to reduce or eliminate the insects.
2. As plants grow, staking will be required to prevent plants from intertwining. Loosely
bind elongated soybean branches to long bamboo stakes using twist ties.
3. Soybean pods on the same plant will dry at variable rates. To prevent pod shatter and
consequent seed loss due to over drying, remove dry pods and store them in a paper bag
until all pods on the plant are harvested.
References
An G, Ebert PR, Mitra A, Ha SB (1988) Binary vectors. In: Gelvin SB and Schilperoort RA
(eds) Plant Molecular Biology Manual. Kluwer Academic Publishers, Great Britain, pp 1-19.
Carrington JC, Freed DD (1990) Cap-independent enhancement of translation by a plant
potyvirus 5’ nontranslated region. J of Virology 64: 1590-1597.
Hajdukiewicz, P., Svab, Z., and Maliga, P. (1994) The small, versatile pPZP family of
Agrobacterium binary vectors for plant transformation. Plant Mol. Biol. 25:989-994.
Hood, E. E., Helmer, G. L., Fraley, R. T., and Chilton, M.-D. (1986) The hypervirulence of
Agrobacterium tumefaciens A281 is encoded in a region of pTiBo542 outside of T-DNA. J.
Bacteriol. 168:1291-1301.
Mason HS, DeWald D, Mullet JE (1993) Identification of a methyl jasmonate-responsive
domain in the soybean vspB promoter. Plant Cell 5: 241-251.
Odell, J. T., Nagy, F. & Chua, N.H. (1985) Identification of DNA sequences required for
activity of the cauliflower mosaic virus 35S promoter. Nature 313, 810-812.
Olhoft PM, Somers DA (2001) L-cysteine increases Agrobacterium-mediated T-DNA
delivery into soybean cotyledonary-node cells. Plant Cell Rep 20: 706-711.
Vancanneyt G, Schmidt R, O’Connor-Sanchez A, Willmitzer L, Rocha-Sosa M (1990)
Construction of an intron-containing marker gene: Splicing of the intron in transgenic plants
and its use in monitoring early events in Agrobacterium-mediated plant transformation. Mol
Gen Genet 220: 245-250.
Zhang et al. (1999) Tissue and Organ Culture. Plant Cell 56: 37-46.

Gibberalic Acid

Web:

http://www.jlhudsonseeds.net/GibberellicAcid.htm

The Lab rat

all the site is here:
http://www.thelabrat.com/protocols/reagents.shtml

SCREENING OF SOYBEAN, GLYCINE MAX (L.) MERRILL, LINES FOR SOMATIC EMBRYO INDUCTION AND

Click:
http://plantsciences.utk.edu/pdf/tomlin.pdf



In Vitro Cell. Dev. Biol.-Plant 38:543-548, November-December 2002
@ 2002 Society for In Vitro Biology
1054-5476/02 810.00+0.00
DOl: lO.IO79/IVP2002326
SCREENING OF SOYBEAN, GLYCINE MAX (L.) MERRILL, LINES FOR SOMATIC EMBRYO INDUCTION AND
MATURATION CAPABILITY FROM IMMATURE COTYLEDONS
EUZABETH S. TOMUN1*, SHEILA R. BRANCWt, DEAN CHAMBERLAIN1t, HOWARD GABE2, MARTHA S. WRIGH~§, AND
C. NEAL STEWART JR.1,
IDepartment of Biology, University of North Carolina, Greensboro, NC 27402
2Syngenta Seeds Ltd., Caixa Postal 585, Uberlandia, MG 38405-232, Brazil
3Syngenta Biotechnology Inc., Research Triangle Park, NC 27709
(Received 27 February 2002; accepted 9 May 2002; editor C.C. Phillips)
SUMMARY
Seventeen breeding lines of soybean, Glycine max (L.) Merrill, and cv. Jack, from relative maturity groups 0.3- 7.5 were
assessed for their ability to undergo somatic embryogenesis. The goal of this study was to determine which lines had high
embryogenic capacity. We also sought to understand the relationship between relative maturity and embryogenesis.
Embryos from immature cotyledons were initiated on solid MS medium with varying levels of 2,4-dichlorophenoxyacetic
acid (2,4-D). Qualitative and quantitative measures of initiation, proliferation, differentiation, and maturation were
recorded. The breeding lines differed significantly with respect to percent induction, number of embryos induced, and
quality of induced embryos. Mter 1 mo. of proliferation, two early maturing lines, the control, Jack, and NK-5, had the best
overall performance. High percent response of proliferating embryos was positively associated with lower maturity groups.
Relatively high concentrations of 2,4-D (compared with that used in proliferating medium, e.g., 226JjM; 50mgl-l) in the
illitiating medium reduced numbers of embryo clusters per cotyledon initiated and percent initiation, and the
concentration of 2,4-D affected the proliferation of somatic embryos in a breeding line-dependent manner. The breeding
lines differed significantly in the time to produce mature somatic embryos. There was a positive correlation between
immature embryo quality and number of differentiated somatic embryos produced.
Key words: soybean; somatic embryogenesis; breeding lines.
!NTRODUcrION maize (Parrott et al., 1991). Differences in capacity for somatic
embryogenesis in soybean were found by Komatsuda and Ohyama
(1988), Parrott et al. (1989), Komatsuda (1990), Bailey et al.
(1993a, b), Tian et al. (1994), Simmonds and Donaldson (2000), and
Meurer et al. (2001). A number of genes have been identified that
control different aspects of somatic embryogenesis in soybean and
other plants (Hernandez-Fernandez and Christie, 1989; Parrott
et al., 1991; Tar'an and Bowley, 1997).
Soybean lines are divided into different maturity groups based on
photoperiod requirements and time to produce flowers. The lower
the maturity group number, the more northern-adapted the
germplasm, i.e., flowers under longer day lengths. Although
northern and southern maturity groups evolved from different
germplasms, the gene pool within each group is small (Delannay
et al., 1983). The goal of this study was to screen a number of elite
lines of soybean from different maturity groups to assess their
capacity for somatic embryogenesis.
Soybean has proven amenable to genetic transformation by
microprojectile bombardment of somatic embryos (Finer and
McMullen, 1991; Parrott et al., 1991, 1994; Finer et al., 1996;
Stewart et al., 1996; Hazel et al., 1998; Santarem and Finer, ~999).
Unfortunately, soybean embryogenesis is inefficient compared to
other crops (Santarem et al., 1997; Samoylov et al., 1998), and the
development of genetically engineered soybeans has been limited to
lines that respond well in tissue culture.
The capacity for somatic embryogenesis is a heritable trait,
varying with genotype in many systems such as peanut
(Chengalrayan et al., 1998), orchardgrass (Tar'an and Bowley,
1997), alfalfa (Hernandez-Fernandez and Christie, 1989), and
MATERIALS AND METHODS
Fifty breeding lines of soybean, and cv. Jack, the control, grown under
field conditions in various locations (Arkansas, Iowa, and Minnesota), from
maturity groups 0-8, were initially screened for their capacity to produce
somatic embryos. Maturity group 0 flowers the earliest, and maturity group 8
flowers the latest. From these, 18 of the lines that had apparent superior
*Current address: Department of Biology, Bennett College Box # 53, 900
E. Washington St., Greensboro, NC 2741)1-3239.
tCurrent address: Stockhausen, Inc., 241)1 Doyle St., Greensboro, NC
274()6.
:j:Current address: Department of Medicine, Division of Cardiology, Duke
University Medical Center, DUMC 3104, Durham, NC 27710.
§Retired.
1 Author to whom correspondence should be addressed (present address):
Department of Plant Sciences and Landscape Systems, 2431 Center Drive,
Rm 252 Ellington Plant Sciences, University of Tennessee, Knoxville, TN
37996-4561; Email nealstewart@Utk.edu
543

Population genetic structure of Japanese wild soybean (Glycine soja) based on microsatellite variation.

For original print: http://www.blackwell-synergy.com/doi/full/10.1111/j.1365-294X.2006.02854.x

or





Population genetic structure of Japanese wild soybean (Glycine soja) based on microsatellite variation
Y. KURODA*, A. KAGA*, N. TOMOOKA and D. A. VAUGHAN

Abstract

The research objectives were to determine aspects of the population dynamics relevant to effective monitoring of gene flow in the soybean crop complex in Japan. Using 20 microsatellite primers, 616 individuals from 77 wild soybean (Glycine soja) populations were analysed. All samples were of small seed size (< 0.03 g), were directly collected in the field and came from all parts of Japan where wild soybeans grow, except Hokkaido. Japanese wild soybean showed significant reduction in observed heterozygosity, low outcrossing rate (mean 3.4%) and strong genetic differentiation among populations. However, the individual assignment test revealed evidence of rare long-distance seed dispersal (> 10 km) events among populations, and spatial autocorrelation analysis revealed that populations within a radius of 100 km showed a close genetic relationship to one another. When analysis of graphical ordination was applied to compare the microsatellite variation of wild soybean with that of 53 widely grown Japanese varieties of cultivated soybean (Glycine max), the primary factor of genetic differentiation was based on differences between wild and cultivated soybeans and the secondary factor was geographical differentiation of wild soybean populations. Admixture analysis revealed that 6.8% of individuals appear to show introgression from cultivated soybeans. These results indicated that population genetic structure of Japanese wild soybean is (i) strongly affected by the founder effect due to seed dispersal and inbreeding strategy, (ii) generally well differentiated from cultivated soybean, but (iii) introgression from cultivated soybean occurs. The implications of the results for the release of transgenic soybeans where wild soybeans grow are discussed.

Introduction Go to: ChooseTop of pageIntroduction <
Soybean [Glycine max (L.) Merrill] is the world's most important grain legume crop in terms of total production and international trade (Smil 2000). Transgenic soybean is grown on a larger area globally than any other transgenic crop but is not currently grown in Asia where the wild progenitor of soybean (Glycine soja Sieb. & Zucc.) grows (http://www.colostate.edu/programs/lifesciences/TransgenicCrops/current.html).

To date, the main transgene incorporated into widely grown soybeans confers herbicide resistance. There are concerns that transgenes from soybeans cultivated in the same area as its cross compatible wild relative, G. soja, could lead to wild soybeans having herbicide resistance. Currently, policy regarding growing transgenic soybeans is awaiting risk assessment. Consequently the research reported here addresses frequency and extent of gene flow from soybean to its wild relative, to assist policy makers' deliberations on the potential impact of growing transgenic soybean in Japan.

Wild soybean is a strictly annual plant species with high seed production, and is one of the aggressive colonizers of disturbed habitats. It is considered the direct progenitor of cultivated soybean based on morphology (Broich & Palmer 1980), cytogenetics (Hymowitz & Singh 1987; Palmer et al. 1987) and molecular analyses (e.g. Kollipara et al. 1997; Abe et al. 1999). There is no agreement on whether soybean was domesticated in southern China, the Yellow River valley of central China or northeast China, or more than once (Carter et al. 2004). The natural distribution of wild soybeans is far eastern Russia, eastern China including Taiwan, Japan and the Korean Peninsula (Lu 2004). In Japan, wild soybean is widely distributed across the Japanese archipelago from the northern island of Hokkaido (42°N) to the southern island of Kyushu (31°N).

The safe release of transgenic soybeans is contingent on the transgene not being able to escape. A further consideration is whether transgenes become established in wild populations. Knowledge of gene flow, the combined effect of cross-pollination and seed dispersal, is necessary to evaluate environmental impact of transgenic soybeans. The outcrossing rate of wild soybeans has been reported to range from 2.4% to 19% (Kiang et al. 1992; Fujita et al. 1997). The high outcrossing rates (9.3–19%) recorded by Fujita et al. (1997) were considered to be due to frequent visits to wild soybean flowers by pollinators (honeybees and carpenter bees) in the study area, Akita prefecture, in the northern part of Japan. The average and maximum distance wild soybean pollen is dispersed has been estimated at 10 m and 60 m, respectively (Jin et al. 2003). Most seeds are naturally dispersed by pod dehiscence within 4.5 m of the mother plant (Oka 1983), but long-distance seed dispersal of wild soybeans down rivers has been inferred on the basis of genetic diversity and genetic differentiation (Kiang et al. 1992; Choi et al. 1999). Long-distance seed dispersal may result in plants with the same genotype being introduced into widely separated areas. However, evidence of long-distance seed dispersal has not been demonstrated.

Introgression from crops to their wild relatives is a common phenomenon (Ellstrand et al. 1999; Ellstrand 2003a), but information on the basis of molecular analysis is limited for soybean (Abe et al. 1999). Wild soybeans have generally smaller leaves, smaller flowers, smaller seeds (1–3 g/100 seeds) that are black, and stronger stem-twinning compared with cultivated soybeans. In natural habitats, morphologically intermediate plants between wild and cultivated soybean showing phenotypic traits such as large leaves, large grains and yellow seed coat are reported to be quite common in China (Dong et al. 2001) and but are rare in Japan (Sekizuka & Yoshiyama 1960; Kuroda et al. 2005). Outcrossing between G. soja and G. max can occur where these two species are sympatric, since these two species share the same genome and no obvious reproductive barriers have been observed in experimental crosses (Hymowitz & Singh 1987). Outcrossing in cultivated soybeans has been reported to be less than 3% (Dorokhov et al. 2004). Natural outcrossing rates range from 0% to 5.9% when G. soja and G. max were alternately planted at a distance of 50 cm (Nakayama & Yamaguchi 2002). G. soja and G. max hybrids can survive in seminatural conditions for at least 3 years without intervention (Oka 1983).

While direct measurements of gene flow are generally difficult (Bossart & Prowell 1998; Cain et al. 2000), indirect approaches based on theories of population genetics such as analyses of Hardy–Weinberg equilibrium (e.g. Wright 1965; Weir & Cockerham 1984), genetic distance (e.g. Takezaki & Nei 1996), genetic differentiation (e.g. Weir & Cockerham 1984), model-based genetic mixture (Pritchard et al. 2000) and spatial autocorrelation (Smouse & Peakall 1999) are commonly employed. Microsatellites or simple sequence repeats (SSRs) are widely distributed across all eukaryotic genomes and have high sensitivity to detect polymorphisms (Haig 1998; Parker et al. 1998). Many soybean microsatellite markers have been mapped on the 20 linkage groups of the soybean genome (Song et al. 2004). Therefore, microsatellite markers can be used to assess population genetic structure and gene flow between cultivated and wild soybeans.

The objectives of this study, using microsatellite analysis of the nuclear genome, were to (i) evaluate population genetic structure of wild soybeans sampled from throughout most of their natural range in Japan; (ii) determine the potential contribution of long-distance seed dispersal on wild soybean population structure; (iii) estimate outcrossing in wild soybean populations; (iv) compare the genetic diversity of wild and cultivated soybeans; and (v) estimate the extent of natural introgression from cultivated soybeans to the wild soybeans. Based on the results, issues related to gene flow in the Japanese soybean gene pool in relation to biosafety are discussed.

Materials and methods Go to: ChooseTop of pageIntroductionMaterials and methods <
Collection of materials

Six hundred sixteen seeds from a total of 77 populations of wild soybean (Soja01–Soja77, Fig. 1, Appendix I) were analysed in this study. Populations ranged in proximity from about 0.2 km (Soja44 and Soja45) to about 1330 km (Soja07 and Soja72). The authors directly surveyed these wild populations between 1996 and 2003. The habitats of wild soybeans were riverbanks, abandoned paddies and roadside ditches where human and natural disturbances are frequent. Individual plant samples were collected from throughout each population between October and November. Based on a survey of 100 seed weight of 3531 accessions of cultivated soybean and 439 accessions of wild soybean in the National Institute of Agrobiological Sciences (NIAS) gene bank, the mean and range for each species was 27.8 g (range: 3.50–73.9 g) and 2.20 g (range: 0.85–7.43 g), respectively (Kaga et al. 2005). The cultivated accessions with a seed size range overlapping with wild accessions are lines for fodder. One-seed weight of each wild individual surveyed in this experiment had less than 0.03 g and were all considered to represent wild soybeans. Seeds from these individuals, totalling 616 seeds from 77 populations, were used for microsatellite analysis.

Fifty-three varieties of cultivated soybean (Max01–Max53, Appendix II) that covered more than 95% of the soybean planting area in Japan over the last 5 years were selected for analysis (http://www.maff.go.jp/soshiki/nousan/hatashin/daizu/siryo/kenbetuhinsyu.html). These cultivars have different cultivation histories, 10 were landraces, 17 varieties were released 20–40 years ago, 14 varieties were released 10–20 years ago and 12 were recently released varieties (< 10 years).

DNA extraction, primer screening and genotyping

Total DNA was extracted from 616 seeds of wild soybean collected directly from the field and single seed samples of 53 cultivars using the method of Kamiya & Kiguchi (2003) with modifications. The seed coat was removed prior to DNA extraction in order to prevent contamination with maternal DNA. Using three wild soybeans (collected from northern, central and southern parts of Japan) and three cultivated soybeans (major varieties of northern, central and southern parts of Japan) 714 genome-wide soybean primers, which included ATT repeat motif (71%) and AT repeat motif (13%) and other repeat motifs such as CTT, CT, CAA, and TAGA, were screened (Table 1, primer information is available from http://129.186.26.94/ssr.html). In the primer screening process, PCR amplification was performed using a thermal cycler (GeneAmp PCR system 9700, Applied Biosystems) under the conditions of one cycle of 2 min at 94 °C, followed by 40 cycles for 30 s at 94 °C, 30 s at about 50 °C and 30 s at 68 °C and finally maintained at 4 °C in a volume of 10 µL [1 × buffer, 0.2 mm of dNTP, 1 mm of MgSO4, 0.3 µm of primer pairs, 0.01 U of polymerase (KOD-plus, Toyobo) and 1–5 ng of total DNA]. Two hundred forty-two primers, which were composed of ATT (85%) and AT (9%) motif primers (ranged from 7 to 17 per linkage group), showed stable and polymorphic banding patterns among the samples based on electrophoresis in 2.5% agarose gel under the condition of 100 V for 15 min. From those primers, one was randomly selected from each soybean chromosome.

For the analysis of all samples, forward primers were labelled with different dyes, 6-FAM, VIC, NED or PET dyes (Applied Biosystems). Polymerase chain reaction (PCR) was carried out under the same conditions as primer screening. Two microlitre of PCR product was denatured in 13 µL of Hi-Di formamide with 0.2 µL of GeneScan-500LIZ size standard (Applied Biosystems). PCR products were separated on an AB3100 capillary sequencer for allele detection. Allelic data were scored using genemapper 3.0 software and the genotype of each sample was determined.

Data analysis

Intrapopulation variation and breeding systems. Genetic variability of each wild soybean population was estimated as the total number of alleles (A), expected and observed heterozygosities (HE and HO), fixation index (FIS) using the fstat program (Goudet 2001). HE is equal to HO in randomly mating populations. Fixation index (Wright 1965) shows deviation from the Hardy–Weinberg expectation. The testing to evaluate either excess or deficit of heterozygotes was computed using the fstat program. Outcrossing rate (t) was calculated from the fixation index using the equation t = (1 –FIS)/(1 + FIS) (Weir 1996).

Seed dispersal. An assignment test was performed on multilocus data to determine whether it is possible to assign individuals to their original population or another wild soybean population using geneclass 2 software (Piry et al. 2004). The DA (Nei et al. 1983) distance-based method was used to calculate the likelihood values for each individual belonging to the sampled population. This distance method does not require Hardy–Weinberg equilibrium or absence of linkage disequilibrium among loci and the DA distance showed higher percentage of individuals assigned to the correct population than other distance methods such as standard genetic distance (DS) and minimum genetic distance (Dm) (Cornuet et al. 1999).

Spatial structure of genetic variation. Spatial autocorrelation analysis for multiallelic codominant loci was used to assess population structure of the 77 wild soybean populations (Smouse & Peakall 1999). A coefficient (r) was calculated from pairwise geographical and a pairwise squared genetic distance matrix (Φ) using the genealex version 5 program (Peakall & Smouse 2001). The coefficient r is a correlation coefficient with a mean of '0' when there is no correlation between geographical and genetic distances, and bounded by [−1, +1] (Smouse & Peakall 1999). The test for statistical significance was performed based on 999 random permutations. This generates an estimate of r about the null hypothesis of no spatial genetic structure (rp). After 999 permutations, the rp values are sorted and the 25th and 975th rp values taken to define the upper and lower bounds of the 95% confidence interval.

Genetic admixture. The Bayesian clustering algorithm was applied to identify clusters of genetically similar individuals and to test the proportion of genetic admixture among the clusters at the individual level using structure version 2.1 (Pritchard et al. 2000). One to 50 K (number of clusters) was applied to infer the number of clusters for wild soybean (including and excluding cultivated soybeans). The value of K maximizes the posterior probability of wild soybean clusters (Pritchard et al. 2000). In addition, genetic admixture between cultivated soybeans and wild soybeans was estimated using prior population information (migration rate ν= 0.05) in order to infer introgression between the species. For each run, a Markov chain Monte Carlo (MCMC) method was used to estimate allele frequencies in each K populations and the degree of admixture in each individual under the condition of 10 000 burn-in (process required to prepare for running MCMC) period and 10 000 MCMC replications.

Genetic differentiation. Analysis of molecular variance (amova, Excoffier et al. 1992) was performed to partition the observed genetic variability among populations of wild soybean, among varieties of cultivated soybean, and between wild and cultivated soybean using arlequin software (Schneider et al. 2000). To detect genetic differentiation between wild and cultivated soybean for each microsatellite locus, amovas were performed for each locus separately. amova creates a genetic distance matrix (Φ) between samples in order to measure the genetic structure of the population from which the samples are drawn. F-statistics were tested by 1000 permutations, and significant differences between groups declared if measured variance is lower than 95% of the variance in the null distribution (Excoffier et al. 1992). Genetic distances (DA, Nei et al. 1983) for all possible pairs of wild and cultivated soybean samples were computed using populations version 1.2.28 software (available at http://www.cnrs-gif.fr/pge/bioinfo/populations). Reproducibility of tree topology with the neighbour-joining method can be obtained based on DA (Takezaki & Nei 1996). Principal coordinate analysis was used to display genetic divergence among samples in a multidimensional space. The DA distances computed among all samples (including cultivated soybeans) were ordinated in two dimensions using ntsys (Rohlf 2000).

Results Go to: ChooseTop of pageIntroductionMaterials and methodsResults <
Microsatellite variation

In total, 405 and 109 alleles were detected from 20 microsatellite loci in Japanese wild and cultivated soybeans, respectively (Table 1). Wild soybeans showed much higher values for A and HE than cultivated soybeans. The number of alleles per locus (A) in wild soybean ranged from 9 (Satt581) to 39 (Satt277) and in cultivated soybeans ranged from 2 (Satt509, Satt555 and Satt581) to 13 (Satt277 and Satt288). Expected heterozygosity (HE) averaged over 20 loci was 0.870 (range from 0.691 to 0.956 for each locus) in wild soybeans, and was 0.496 (range from 0.109 to 0.850 for each locus) in cultivated soybeans. Eleven alleles were found only in cultivars (Table 2), but their frequencies were very low accounting for only 2.55% of alleles in cultivated soybean. In contrast, several alleles that were observed frequently in cultivated soybean were rare in wild soybean (Table 2).

FST value, which is an index of genetic differentiation, between cultivated soybean and wild soybeans ranged from 0.053 (Satt215) to 0.352 (Satt423) and was significant at all loci (P < 1.0 × 105, Table 1). Figure 2 shows typical examples of allele distribution where differentiation was not clear (e.g. Satt288, FST = 0.066, Fig. 2a), and where it was high (e.g. Satt076, FST = 0.336, Fig. 2b).

Intrapopulation variation and breeding system

Forty-one out of 77 wild soybean populations deviated significantly from Hardy–Weinberg equilibrium (P < 0.0003) due to lower level of observed heterozygosity (mean 0.018, range 0.000–0.131) compared with expected level of heterozygosity (mean 0.228, range 0.000–0.822). Therefore the average value of the fixation index was very high (mean 0.933, range 0.456–1.000; Table 3). Among the other 36 populations, the fixation index for 24 populations could not be evaluated because all plants in each population had an identical genotype. The indices for the remaining 12 populations did not deviate from Hardy–Weinberg equilibrium due to low levels of expected and observed heterozygosities. Mean outcrossing rate (%) estimated from the fixation indices in 77 populations was low (mean 3.4%, range 0.0–37.4%), suggesting that wild soybeans are predominantly inbreeding. However, seven populations had an outcrossing rate estimated at more than 10%. These populations came from all regions, north (2), central (1) and southern Japan (4). Larger populations had higher outcrossing rates than smaller populations (r = 0.428, P < 0.05).

Assignment test and spatial genetic structure

The individual assignment test revealed that 613 samples out of 616 samples (99.5%) were assigned to their original populations (i.e. having the highest likelihood value of belonging to the populations they came from), and the remaining three samples were assigned to another population: one Soja08 sample assigned to Soja07 (12.4 km from Soja08) and two Soja44 samples assigned to Soja45 (0.2 km from Soja44). These three samples showed identical genotypes over 20 microsatellite markers to five Soja07 and six Soja45 individuals.

Results of spatial autocorrelation are shown as a correlograms (Fig. 3a, b). Japanese wild soybean populations were divided by distance classes of 100 km and 50 km. There was a general decline in the correlation coefficient (r) among populations with distance. Each locus showed the same tendency that the correlation coefficient was highest at the first distance class (range r = 0.096–0.179, when Japanese populations were divided by 14 distance classes) and then it rapidly decreased to around zero within a few distance classes. The correlation values are positive and significant up to 200 km, with an x-intercept at 350 to 400 km, and negative and significant from 450 to 500 km and beyond. Spatial autocorrelation at the smallest distance class was highest, indicating the relationship between geographical proximity and genetic relatedness. Since rapid decline in the first two distance classes followed by moderate decline of genetic relatedness with distance was observed, the spatial pattern observed in relation to overall genetic distance can be explained by both short-distance similarity and long-distance differentiation.

Genetic differentiation within and between wild and cultivated soybean

amova showed strong genetic differentiation among populations of wild soybean (FST = 0.76, P < 1.0 × 105). Genetic admixture analysis without prior information about geographical origin of populations revealed that the highest likelihood value (ln PrX|K) was obtained when the number of clusters (K) was 38 (Fig. 4). At K = 38, 77 wild soybean populations were classified into 38 groups, which had only one to three wild populations. When 53 varieties of cultivated soybean were added to the analysis, the highest likelihood value was 39 (Fig. 4). In both of these analyses, populations of wild soybeans showed weak clustering of neighbouring populations. However, cultivated soybeans always formed a single group. These results reflect the high differentiation that exists in populations of Japanese wild soybeans. In contrast, Japanese cultivated soybeans are less divergent than wild soybeans and form a single group.

Genetic differentiation between wild and cultivated soybeans for the 20 microsatellite loci analysed was significant (FST = 0.203, P < 1.0 × 105). Graphical ordination of the first two axes in the plane for wild and cultivated soybean samples are shown (Fig. 5a–d). The first axis, accounting for 7.4% of the variation, reflects wild–cultivated soybean differentiation. In the axis, wild soybeans were located at values of less than 0.3; in contrast, cultivated soybeans were located at values of more than 0.3 (Fig. 5a). The second axis (accounting for 5.7% of the variation) showed that wild soybean samples were widely scattered compared to cultivated soybean. Samples on this axis for wild soybean reflected the geographical origin of samples. Samples from northern Japan were mainly found to the right of axis 1 and samples from the south to the left of axis 1, while samples from central Japan were about equally to the left and right of axis 1 (Fig. 5b–d). No cline was observed in relation to cultivation regions or years after release in cultivated soybeans.

Introgression from cultivated soybean to wild soybean

Since genetic differentiation between wild and cultivated soybeans was significant, as described in the previous section, genetic admixture analysis was performed using prior population information on the status of cultivation (wild or cultivated soybean, K = 2). This resulted in samples forming two clusters, wild and cultivated soybeans, respectively (Fig. 6). Forty-two samples from seven wild populations showed less than a 75% probability that the individual in question was correctly assigned to the given wild soybean population because these samples had some alleles which were common to cultivated soybeans but rare in wild soybeans. These samples came from populations Soja27 (7 individuals), Soja31 (8), Soja32 (4), Soja34 (3), Soja35 (4), Soja70 (8) and Soja71 (8) (Fig. 6). From these results, introgression from cultivated soybeans to wild soybeans was inferred. The presumed introgressed individuals were located at the interface between wild and cultivated soybean on the ordination plot (Fig. 5).

Discussion Go to: ChooseTop of pageIntroductionMaterials and methodsResultsDiscussion <
Gene flow between cultivars and their wild relatives commonly occurs in many plant species (Ellstrand 2003b). For soybeans in Japan, however, despite its long history of cultivation, phenotypic intermediate types between wild and cultivated soybeans are rarely found (Kuroda et al. 2005). To determine the population dynamics of the soybean crop complex in Japan for effective monitoring of gene flow, this study evaluated genetic structure of wild and cultivated soybeans, with samples from a wide range of natural and disturbed areas in Japan, using 20 nuclear microsatellite markers. The result revealed sufficient allelic variation to enable the genetic structure of wild soybean populations to be analysed. The data enable the following factors related to potential gene flow from transgenic soybean to be discussed: (i) geographical structure of genetic variation in wild soybean; (ii) long-distance dispersal of wild soybean seeds; (iii) natural outcrossing rate in wild soybean; (iv) genetic diversity of Japanese wild and cultivated soybeans; and (v) introgression from cultivated soybean to wild soybean. This is the first large-scale population genetic analysis based on nuclear genome diversity in relation to wild and cultivated soybeans.

Geographical structure of genetic variation in wild soybean

Spatial autocorrelation analysis revealed clinal spatial structure of genetic variation in Japanese wild soybeans. A positive correlation was found within a range of about 200 km and a negative correlation was found from about 350–400 km. Past studies on the basis of several molecular analyses have reported a geographical cline in genetic variation of Japanese wild soybeans (Kiang et al. 1992; Fujita et al. 1997). Kiang et al. (1992) analysed polymorphic patterns of 15 isozyme and one nonenzyme protein (Ti) in four populations of wild soybean collected in Iwate prefecture (120 km range), and found a relationship between genetic distance and latitude in several populations. Fujita et al. (1997) analysed nine allozyme and one nonenzyme protein (Ti) in four wild soybean populations collected in Akita prefecture (50 km range), and found a significant simple correlation between genetic distance and geographical distance (r = 0.86). These two previous studies only dealt with wild soybean from northern parts of Japan. The present study used samples of wild soybean from almost all parts of Japan, and found spatial correlation over the whole range of Japanese wild soybean.

On the basis of graphical ordination analysis, nuclear microsatellite variation of wild soybeans in northern Japan is distinct from southern Japan. Wild soybeans of central Japan had variation from both regions. These results suggest that wild soybean populations can be dispersed within a range of about 200 km regions and there is a lack of seed migration between regions. Such geographical cline was also observed in organelle genome studies (Tozuka et al. 1998; Xu et al. 2002). Tozuka et al. (1998) analysed RFLP (restriction fragment length polymorphism) patterns of mitochondrial DNA using 1097 individuals of wild soybean collected from throughout Japan and found genetic differentiation between southern and northern parts of Japan. Xu et al. (2002) analysed microsatellite haplotypes of chloroplast DNA using 143 wild soybean accessions from throughout Japan and showed regional distribution for most of the haplotypes.

Long-distance dispersal of wild soybean seeds

Seed dispersal from 0.2 to 12.4 km was inferred from three samples out of 616 based on identical genotypes being found in different populations. Although genetic structure among wild soybean populations was highly differentiated, a reflection of inbreeding in this annual plant species (Hamrick & Godt 1989), seed dispersal over more than 0.2 km can occur for wild soybeans. There are some data to support the result of seed dispersal. First, 41 populations out of 77 had only one or two genotypes among eight samples in this study, indicating that founder plants in new habitats produce large numbers of seeds resulting in populations with few genotypes. Second, autocorrelation analysis showed a rapid decline in the first distance class (100–200 km), suggesting gene flow between populations within 200 km occurred significantly more frequently than those farther than 200 km. Third, individual wild soybean plants produce between 472 and 3570 seeds under cultivated conditions in Tsukuba, central Japan (authors' unpublished data), indicating that large seed numbers per individual would provide the chance for seed dispersal. Long-distance seed dispersal can occur as a result of dispersal in water or when seeds are carried by animals or humans (Cain et al. 2000). Pollen has only been reported to be carried short-distances (< 60 m) by bees (Jin et al. 2003), and most seeds of wild soybean are naturally dispersed to a distance of up to 4.5 m when pods dehisce (Oka 1983). These results indicate that long-distance seed dispersal and founder effect may be an important factor in determining population genetic structure and the establishment of new populations within a range of 200 km.

Natural outcrossing rate in wild soybean

Wild soybeans have a variable level of outcrossing in Japan. In this study, most populations showed a low rate of outcrossing (mean 3.4%). However, seven populations from different parts of Japan had an estimated outcrossing rate of more than 10%. The wide variation in outcrossing rate probably reflects variation in the abundance of pollinators, population size and their interaction. Population size of wild soybeans varies greatly. In this study, some wild soybean populations consist of a few plants, others cover hectares of land, and larger populations have higher outcrossing rates than smaller populations. In the wild soybean populations studied by Fujita et al. (1997), frequent visits of pollinators were reported to be the main factor in the high levels of outcrossing (9.3–19%). They recorded 37 honeybees (Apis cerana) and 5 carpenter bees (Xylocopa appendiculata circumvolans) in a 4-m2 plot in 2 h (11:00–13:00 h). Their study site was relatively large in size (900–40 000 m2). Large populations would be expected to attract larger numbers of pollinators and hence have high outcrossing rate (Fujita et al. 1997).

Genetic diversity of Japanese wild and cultivated soybeans

Our results support the view that domestication of soybean involved a genetic bottleneck. Microsatellite variation in 53 major Japanese cultivated soybean varieties, which account for more than 95% of the planting area in Japan, is much less than that of Japanese wild soybeans. Cultivated soybeans had only 57% of the Nei's diversity value (HE) of wild soybeans analysed (0.870 and 0.496 for wild and cultivated soybeans, respectively). The higher variation in wild soybeans than that of cultivated soybeans is consistent with past studies using germplasm from many countries. Maughan et al. (1995) analysed 67 soybean cultivars and 32 wild samples from China, Japan, Korea, Taiwan and the former Soviet Union using five nuclear microsatellites, and found that cultivated soybeans had 63% of the HE value of wild soybeans (0.87 and 0.55 for wild and cultivated soybeans, respectively). Xu et al. (2002) evaluated 143 wild soybean accessions from Russia, China, Korea and Japan and 183 cultivated soybeans from Russia, China, Korea, Japan, Vietnam, Thailand, Indonesia, India, Myanmar, Bhutan, Nepal, Pakistan and Kyrgyzstan using six chloroplast microsatellites, and found that cultivated soybeans had 54% of the HE value of wild soybeans (0.496 and 0.269 for wild and cultivated soybeans, respectively). A loss of diversity between cultivated soybean and wild soybeans is reported here (57%) despite the narrow genetic base of Japanese cultivated soybeans that were used in the study. Most cereals for example have been shown to have 78% (maize), 60% (sorghum), 71% (rice), 65% (oat), 71% (wheat) and 67% (peal millet) of the nucleotide variation (i.e. nucleotide level of HE, Nei 1987) found in wild progenitors based on broad sampling of the crop and its wild relatives (Buckler et al. 2001).

Although genetic variation in cultivated soybean is much lower than wild soybean, some alleles were found only in cultivated soybean and other alleles with high frequency in cultivated soybeans and low frequency in wild soybeans. In this study, 11 microsatellite alleles that were only found in cultivars, were at low frequencies (0.02–0.09). This could be the result of mutation after domestication of soybean (Li & Nelson 2002) or the samples of wild soybean were insufficient for these alleles to be detected. For example, wild soybean in China, a centre of diversity for the soybean crop complex, may have these alleles. Seven alleles were observed at a much higher frequency in cultivated soybeans than wild soybeans. This suggests that the soybean was domesticated from a part or parts of the wild soybean gene pool.

Natural introgression from cultivated soybean to wild soybean

Ordination analysis clearly differentiated between Japanese wild soybeans and cultivated soybeans. Since most cultivated soybean alleles were also present in wild soybeans, the differentiation in these two species is explained by genotypic differences in microsatellite allele combinations. Such genetic differentiation between wild and cultivated soybeans has previously been reported (Powell et al. 1996; Xu & Gai 2003). Xu & Gai (2003) found no cultivar-specific RAPD (random amplified polymorphic DNA) bands when comparing 48 wild (21) and cultivated (27) soybean accessions from China but did find clear differentiation between cultivated and wild soybean.

Although none of the wild soybeans analysed had morphological characteristics of intermediate soybeans, genetic admixture and principal coordinate analyses suggest introgression between cultivated and wild soybean in all regions of Japan. Forty-two wild individuals (6.8%) from the northern, central and southern parts of Japan were found with presumed introgressed genomic segments from cultivated soybeans. The wild soybean populations with individuals having membership to the cultivated soybean class were Soja27, Soja31, Soja34, Soja70 and Soja71. These samples had alleles which were observed frequently in cultivated soybeans and rarely in wild soybeans. Among these populations, Soja31 and Soja34 were found in Nagano prefecture, and Soja70 and Soja71 were found in Miyazaki prefecture. It is possible that wild soybean growing there originally had such alleles. However, we believe that those populations were hybrid derivatives, because the composition of such cultivar-predominant alleles differed among populations and among individuals within populations. Such cultivar-predominant alleles in wild soybean were distributed across Japan at a low frequency. These populations were found in different habitats such as wasteland beside paddies, fields or roadside. Japanese farmers have sometimes utilized such habitats for planting soybeans. It seems that pollen flow from soybean cultivars to wild soybeans occurs where they are sympatric. In artificial hybrids between wild and cultivated soybeans it is difficult to recover cultivated characteristics (Carter et al. 2004). Thus, introgressed genes from cultivated soybean may persist in wild soybean populations cryptically. The lack of intermediate morphological characteristics in presumed introgressed samples analysed suggests that hybrid progenies between wild and cultivated soybeans revert to wild soybean characteristics in natural conditions.

Implications for biosafety of soybean gene pool in Japan

In Japan the two conditions required for genes from transgenic soybean to be dispersed to wild soybeans, sympatric habitats and synchronous flowering, exist (Kuroda et al. 2005). Despite the small size of wild soybean seeds (> 0.03 g) used for microsatellite analysis in this study, it is inferred that pollen flow from cultivated soybeans to wild soybeans occurs across Japan and long-distance seed dispersal also occasionally occurs. Seven microsatellite markers alleles, which are predominant in cultivated soybean and rare in wild soybean, are likely to be useful to monitor gene flow from the widely grown Japanese cultivars to the wild soybean in Japan.

Our research team has searched for phenotypic wild–cultivated intermediate soybean in natural habitats throughout Japan for 2 years, and we have confirmed that such intermediate soybeans exist in natural habitats. However, such intermediate individuals are rare. Based on field surveys of more than 50 wild soybean populations that were adjacent to fields of cultivated soybeans, only 12 intermediate individuals having large seed size (0.06–0.12 g) in three populations were found in the northern and southern parts of Japan (Kaga et al. 2005; Kuroda et al. 2005). Results presented here and field observations indicate that some genomic regions of cultivated soybean are neutral or a disadvantage in natural conditions. A genetically modified (GM) gene may persist in the natural habitat when it is closely linked with the neutral genomic regions. In contrast, a GM gene may disappear when it is linked with genomic regions, which are at a disadvantage in the natural habitat. Therefore, to identify such genomic regions in soybean genome may offer important information for the safe release of GM soybeans in the field. Research directed to the issue of fitness in wild and cultivated soybean hybrids is currently underway.


Acknowledgements Go to: ChooseTop of pageIntroductionMaterials and methodsResultsDiscussionAcknowledgements <
Support from Global Environment Research Fund of the Japanese Ministry of the Environment to author A.K. is acknowledged. The authors would like to thank the following Japanese institutes for the supply of some of the materials used in the experiments: National Agricultural Research Center for Kyushu Okinawa Region (KONARC), National Agricultural Research Center for Tohoku Region (NARCT), Hokkaido Prefectural Tokachi Agricultural Experimental Station, Nagano Chushin Agricultural Experimental Station, and Saga Prefectural Agricultural Experimental Center.

References Go to: ChooseTop of pageIntroductionMaterials and methodsResultsDiscussionAcknowledgementsReferences <• Abe J, Hasegawa A, Fukushi H et al. (1999) Introgression between wild and cultivated soybeans of Japan revealed by RFLP analysis for chloroplast DNAs. Economic Botany, 53, 285–291.

• Bossart JL, Prowell DP (1998) Genetic estimates of population structure and gene flow: limitations, lessons and new directions. Trends in Ecology & Evolution, 13, 202–206.

• Broich SL, Palmer RG (1980) A cluster analysis of wild and domesticated soybean phenotypes. Euphytica, 29, 23–32.

• Buckler ESIV, Thornsberry JM, Kresovich S (2001) Molecular diversity and domestication of grasses. Genetical Research, 77, 213–218.

• Cain ML, Milligan BG, Sterand AE (2000) Long-distance seed dispersal in plant populations. American Journal of Botany, 87, 1217–1227.

• Carter TE Jr, Nelson RL, Sneller CH, Cui Z (2004) Genetic diversity in soybean. In: Soybean Monograph (eds Boerma HR, Specht JE), 3rd edn. pp. 303–416. American Society of Agronomy, Madison, Wisconsin.

• Carter TE Jr, Nelson RL, Sneller CH, Cui Z (2004) Genetic diversity in soybean. In: Soybeans: Improvement, Production, and Uses (eds Boerma HR, Specht JE), pp. 303–416. American Society of Agronomy, Crop Science Society of America and Soil Science Society of America, Madison, Wisconsin.

• Chen YW, Nelson RL (2004) Identification and characterization of a white-flowered wild soybean plant. Crop Science, 44, 339–342.

• Choi IY, Kang JH, Song HS, Kim NS (1999) Genetic diversity measured by simple sequence repeat variations among the wild soybean, Glycine soja, collected along the riverside of five major rivers in Korea. Genes and Genetic Systems, 74, 169–177.

• Cornuet JM, Piry S, Luikart G, Estoup A, Solignac M (1999) New methods employing multilocus genotypes to select or exclude population as origin of individuals. Genetics, 153, 1989–2000.

• Dong YS, Zhuang BC, Zhao LM, Sun H, He MY (2001) The genetic diversity of annual wild soybeans grown in China. Theoretical and Applied Genetics, 103, 98–103.

• Dorokhov D, Ignatov A, Deineko E et al. (2004) Potential for gene flow from herbicide-resistant GM soybeans to wild soybeans in the Russian Far East. In: Introgression from Genetically Modified Plants into Wild Relatives (eds den Nijs HCM, Bartsch D, Sweet J), pp. 151–161. CAB International, Wallingford, UK.

• Ellstrand NC (2003a) Current knowledge of gene flow in plants: implications for transgene flow. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 358, 1163–1170.

• Ellstrand NC (2003b) Dangerous Liaisons? When Cultivated Plants Mate with Their Wild Relatives. Johns Hopkins University Press, Baltimore, Maryland.

• Ellstrand NC, Prentice HC, Hancock JF (1999) Gene flow and introgression from cultivated plants into their wild relatives. Annual Review of Ecology, Evolution, and Systematics, 30, 539–563.

• Excoffier L, Smouse P, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics, 131, 479–491.

• Fujita R, Ohara M, Okazaki K, Shimamoto Y (1997) The extent of natural cross-pollination in wild soybean (Glycine soja). Journal of Heredity, 88, 124–128.

• Goudet J (2001) fstat, A program to estimate and test gene diversities and fixation indices (version 2.9.3). Available from http://www.unil.ch/izea/softwares/fstat.html Updated from Goudet (1995).

• Haig SM (1998) Molecular contributions to conservation. Ecology, 79, 413–425.

• Hamrick JL, Godt MJW (1989) Allozyme diversity in plant species. In: Plant Population Genetics, Breeding and Genetic Resources (eds Brown AHD, Clegg MT, Kahler AL, Weir BS), pp. 43–63. Sinauer Associates, Sunderland, Massachusetts.

• Hymowitz T, Singh RJ (1987) Taxonomy and speciation. In: Soybeans, Improvement, Production, and Uses (ed. Wilcox JR), pp. 23–48. American Society of Agronomy and Crop Science Society of America, Madison, Wisconsin.

• Jin Y, He T, Lu BR (2003) Fine scale genetic structure in a wild soybean (Glycine soja) population and the implications for conservation. New Phytologist, 159, 513–519.

• Kaga A, Tomooka N, Phuntsho U et al. (2005) Exploration and collection for hybrid derivatives between wild and cultivated soybean: preliminary survey in Akita and Hiroshima Prefectures, Japan. Annual Report on Exploration and Introduction of Plant Genetic Resources, in press (In Japanese with English summary).

• Kamiya M, Kiguchi T (2003) Rapid DNA extraction method from soybean seeds. Breeding Science, 53, 277–279.

• Kiang YI, Chiang YC, Kaizuma N (1992) Genetic diversity in natural populations of wild soybean in Iwate prefecture, Japan. Journal of Heredity, 83, 325–329.

• Kollipara KP, Singh RJ, Hymowitz T (1997) Phylogenetic and genomic relationships in the genus Glycine Willd. based on sequences from the ITS region of nuclear rDNA. Genome, 40, 57–68.

• Kuroda Y, Kaga A, Apa A et al. (2005) Exploration, collection and monitoring of wild soybean and hybrid derivatives between wild soybean and cultivated soybean: based on field surveys at Akita, Ibaraki, Aichi, Hiroshima and Saga Prefectures. Annual Report on Exploration and Introduction of Plant Genetic Resources, in press (In Japanese with English summary).

• Li ZL, Nelson RL (2002) RAPD marker diversity among cultivated and wild soybean accessions from four Chinese provinces. Crop Science, 42, 1737–1744.

• Lu BR (2004) Conserving biodiversity of soybean gene pool in the biotechnology era. Plant Species Biology, 19, 115–125.

• Maughan PJ, Saghai MA, Buss GR (1995) Microsatellite and amplified sequence length polymorphisms in cultivated and wild soybean. Genome, 38, 715–723.

• Nakayama Y, Yamaguchi H (2002) Natural hybridization in wild soybean (Glycine max ssp. soja) by pollen flow from cultivated soybean (Glycine max ssp. max) in a designed population. Weed Biology and Management, 2, 25–30.

• Nei M (1987) Molecular Evolutionary Genetics. Columbia University Press, New York.

• Nei M, Tajima N, Tateno Y (1983) Accuracy of estimated phylogenetic trees from molecular data. Journal of Molecular Evolution, 19, 153–170.

• Oka HI (1983) Genetic control of regenerating success in semi-natural conditions observed among lines derived from a cultivated × wild soybean hybrid. Journal of Applied Ecology, 20, 937–949.

• Palmer RG, Newhouse KE, Graybosch RA, Delannay X (1987) Chromosome structure of wild soybean (Glycine soja Sieb. & Zucc.) accessions from China and the Soviet Union. Journal of Heredity, 78, 243–247.

• Parker PG, Snow AA, Schug MD, Booton GC, Fuerst PA (1998) What molecules can tell us about populations: choosing and using a molecular marker. Ecology, 79, 361–382.

• Peakall R, Smouse PE (2001) genalex version 5: Genetic analysis in Excel. Population genetic software for teaching and research. Australian National University, Canberra, Australia. http://www.anu.edu.au/BoZo/GenAlEx.

• Piry S, Alapetite A, Cornuet JM et al. (2004) geneclass2: a software for genetic assignment and first-generation migrant detection. Journal of Heredity, 95, 536–539.

• Powell W, Morgante M, Doyle JJ et al. (1996) Gene pool variation in genus Glycine subgenus soja revealed by polymorphic nuclear and chloroplast microsatellites. Genetics, 144, 793–803.

• Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics, 155, 945–959.

• Rohlf FJ (2000) ntsys pc, Version 2.02j. Exeter Software, Setauket, New York.

• Schneider S, Roessli D, Excoffier L (2000) arlequin: A software for population genetics data analysis. Genetics and Biometry Laboratory, Department of Anthropology, University of Geneva, Geneva, Switzerland.

• Sekizuka S, Yoshiyama T (1960) Studies on the native wild grasses for fodder. (IV) crop-scientific studies on wild species of Glycine soja. Japan. Journal of Kanto-Tosan Agricultural Experimental Station, 15, 57–73 (in Japanese with English summary).

• Smil V (2000) Magic beans. Nature, 407, 567.

• Smouse PE, Peakall R (1999) Spatial autocorrelation analysis of individual multiallele and multilocus genetic structure. Heredity, 82, 561–573.

• Song QJ, Marek LF, Shoemaker RC et al. (2004) A new integrated genetic linkage map of the soybean. Theoretical and Applied Genetics, 109, 122–128.

• Takezaki N, Nei M (1996) Genetic distances and reconstruction of phylogenetic trees from microsatellite DNA. Genetics, 144, 389–399.

• Tozuka A, Fukushi H, Hirata T et al. (1998) Composite and clinal distribution of Glycine soja. Japan revealed by RFLP analysis of mitochondrial DNA. Theoretical and Applied Genetics, 96, 170–176.

• Weir BS (1996) Methods for discrete population genetic data. In: Genetic Data Analysis II. Sinauer Associates, Sunderland, Massachusetts.

• Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution, 38, 1358–1370.

• Wright S (1965) The interpretation of population structure by F-statistics with special regard to systems of mating. Evolution, 19, 395–420.

• Xu DH, Gai JY (2003) Genetic diversity of wild and cultivated soybeans growing in China revealed by RAPD analysis. Plant Breeding, 122, 503–506.

• Xu DH, Abe J, Gai JY, Shimamoto Y (2002) Diversity of chloroplast DNA SSRs in wild and cultivated soybeans: evidence for multiple origins of cultivated soybean. Theoretical and Applied Genetics, 105, 645–653.


The authors have focused their research on the legume genetic resources for which there is a genetic resources comparative advantage in Japan. Their initial studies focused on the azuki bean (Vigna angularis complex) for which they developed SSR markers and they have used these in population and genome studies. Their genome studies have focused on the domestication syndrome.



Appendix I Go to: ChooseTop of pageIntroductionMaterials and methodsResultsDiscussionAcknowledgementsReferencesAppendix I <
Passport data of wild soybean (Glycine soja) used in this study

Population District, Prefecture Latitude/Longitude Altitude Collection no. Population size Habitat
Soja01 Tohoku, Akita 39°03'01.9"N, 140°25'32.8"E 240 m CED97017 50 m2 Riverbank of Omono river beside paddy
Soja02 Tohoku, Akita 39°33'41.4"N, 140°17'30.0"E 27 m CED2003-35 20 m2 Abandoned paddy
Soja03 Tohoku, Akita 40°11'08.3"N, 140°24'03.9"E 50 m CED97014 16 m2 Roadside beside paddy
Soja04 Tohoku, Akita 39°20'00.2"N, 140°33'38.1"E 110 m CED97016 100 m2 Riverbank of Yokote river
Soja05 Tohoku, Akita 39°38'57.0"N, 140°09'09.6"E 20 m CED2003-32 80 m2 Wasteland beside paddy
Soja06 Tohoku, Akita 39°23'57.0"N, 140°27'49.2"E 41 m CED2003-31 1250 m2 Paddy bund in riverbank of Omono river
Soja07 Tohoku, Aomori 40°38'04.7"N, 140°34'37.7"E 110 m CED97009 50 m2 Wasteland along road (R102)
Soja08 Tohoku, Aomori 40°31'24.8"N, 140°35'02.4"E 90 m CED97012 10 m2 Wasteland along road (R7)
Soja09 Tohoku, Fukushima 37°35'40.3"N, 140°07'51.7"E 645 m CED96101404 — Roadside (R2)
Soja10 Tohoku, Fukushima 36°42'55.3"N, 140°23'06.2"E 145 m CED96100704 — Roadside (R118)
Soja11 Tohoku, Fukushima 37°34'53.1"N, 139°39'33.0"E 265 m CED96101503 — Roadside (R49) beside riverbank and paddy
Soja12 Tohoku, Fukushima 37°19'20.0"N, 139°20'16.4"E 400 m CED96101611 — Roadside (R289)
Soja13 Tohoku, Fukushima 37°33'13.1"N, 139°45'22.5"E 305 m CED96101501 — Roadside (R49), disturbed habitat
Soja14 Tohoku, Fukushima 37°17'16.2"N, 139°28'51.0"E 475 m CED96101613 — Riverbank of Inami river along road (R289)
Soja15 Tohoku, Iwate 39°55'05.3"N, 141°11'41.5"E 300 m CED97007 6 m2 Paddy in fallow
Soja16 Tohoku, Miyagi 38°09'01.5"N, 140°52'24.8"E 25 m CED97003 60 m2 Wasteland along road
Soja17 Tohoku, Yamagata 37°57'02.0"N, 140°12'40.0"E 375 m CED97019 — Roadside beside home garden
Soja18 Hokuriku, Niigata 37°02'38.6"N, 137°55'29.0"E 80 m CED97062 10 m2 Wasteland along river
Soja19 Hokuriku, Niigata 37°50'40.5"N, 139°12'05.0"E 10 m CED97065 1 m2 Paddy bund
Soja20 Hokuriku, Niigata 37°07'35.7"N, 138°23'31.5"E 80 m CED97064 10 m2 Abandoned paddy
Soja21 Hokuriku, Niigata 37°28'07.5"N, 139°00'14.0"E 120 m CED96101607 — Roadside (R290)
Soja22 Kanto, Chiba 35°05'53.0"N, 140°02'31.8"E 170 m CED97206 10 m2 Paddy in fallow
Soja23 Kanto, Chiba 35°14'25.5"N, 139°59'43.9"E 140 m CED97208 (few) Wasteland beside paddy
Soja24 Kanto, Chiba 35°57'58.4"N, 139°52'46.0"E 100 m CED97207 5 m2 Wasteland beside paddy
Soja25 Kanto, Ibaraki 36°30'14.6"N, 140°14'59.2"E 120 m CED96101201 — Roadside (R51), disturbed habitat
Soja26 Kanto, Tochigi 36°43'23.4"N, 140°11'27.3"E 105 m CED96101711 — Riverbank of Yamata river along road (R293)
Soja27 Kanto, Tochigi 36°56'38.1"N, 139°57'52.0"E 370 m CED96101702 — Wasteland along road
Soja28 Kanto, Tokyo 35°38'55.0"N, 139°27'30.9"E 45 m CED96103101 — Riverside of Tama river
Soja29 Chubu, Aichi 34°55'03.2"N, 137°12'47.4"E 40 m CED98081 100 m2 Paddy bund
Soja30 Chubu, Nagano 35°30'50.6"N, 137°48'30.2"E 498 m CED2001-27 200 m2 Wasteland
Soja31 Chubu, Nagano 36°28'36.6"N, 137°51'05.1"E 490 m CED2001-107 120 m2 Wasteland besides field and paddy
Soja32 Chubu, Nagano 36°19'50.8"N, 138°20'50.5"E 611 m CED97023 100 m2 Rocky riverside
Soja33 Chubu, Nagano 35°34'35.7"N, 138°02'57.3"E 715 m CED2001-110 — Beside field
Soja34 Chubu, Nagano 36°15'19.9"N, 138°25'32.7"E 699 m CED97022 (scattered) Rocky riverside
Soja35 Chubu, Nagano 36°05'53.2"N, 137°58'32.3"E 466 m CED97028 (scattered) Roadside beside paddy along canal
Soja36 Chubu, Shizuoka 35°03'51.7"N, 138°56'14.6"E 30 m CED98086 200 m2 Field bund on riverbank
Soja37 Kansai, Hyogo 34°51'45.0"N, 134°22'03.4"E 150 m CED97067 1 m2 Road embarkment
Soja38 Kansai, Hyogo 35°19'48.7"N, 134°52'06.7"E 80 m CED97050 — Wasteland along road
Soja39 Kansai, Kyoto 35°11'02.1"N, 135°20'22.3"E 200 m CED97039 2 m2 Abandoned land beside small road
Soja40 Kansai, Mie 34°04'03.1"N, 136°11'26.9"E 20 m CED97093 15000 m2 Waste riverside
Soja41 Kansai, Mie 34°28'47.3"N, 136°32'41.6"E 100 m CED97098 5 m2 Wasteland beside paddy
Soja42 Kansai, Mie 34°43'47.1"N, 136°28'05.3"E 100 m CED97099 (large pop) Wasteland beside paddy and river
Soja43 Kansai, Nara 34°22'41.2"N, 135°45'54.9"E 90 m CED97073 40 m2 Wasteland beside paddy
Soja44 Kansai, Shiga 35°29'44.8"N, 136°12'17.1"E 125 m CED98007 — Roadside beside paddy and field (soybean)
Soja45 Kansai, Shiga 35°29'51.9"N, 136°12'15.5"E 30 m CED97054 50 m2 Paddy edge slope
Soja46 Kansai, Shiga 35°21'24.6"N, 136°22'14.7"E 135 m CED97037 1000 m2 Riverbank of Amano river
Soja47 Kansai, Wakayama 33°31'53.8"N, 135°48'54.3"E 4 m CED97087 > 300 m2 Riverbank
Soja48 Kansai, Wakayama 33°41'04.3"N, 135°24'52.6"E 12 m CED97084 > 500 m2 Wasteland beside field and road
Soja49 Chugoku Tottori 35°28'50"N, 134°11'24.0"E 10 m CED2002-28 — —
Soja50 Chugoku Tottori 35°26'53.7"N, 134°12'11.2"E 11 m CED2002-29 — —
Soja51 Chugoku, Hiroshima 34°28'30.3"N, 133°18'23.6"E 19 m CED2003-41 60 m2 Abandoned field
Soja52 Chugoku, Hiroshima 34°26'57.3"N, 132°57'47.5"E 45 m CED2003-19 45 m2 Paddy bund
Soja53 Chugoku, Okayama 35°17'27.4"N, 133°41'04.1"E 465 m CED98011 25 m2 Abandoned paddy with black soil
Soja54 Chugoku, Okayama 35°05'08.9"N, 134°01'42.2"E 10 m CED97072 2500 m2 Abandoned paddy
Soja55 Chugoku, Tottori 35°33'32.8"N, 134°16'34.0"E 4 m CED98010 50 m2 Sandy wasteland beside field (scallion)
Soja56 Chugoku, Yamaguchi 34°07'38.6"N, 130°55'36.8"E 50 m CED98018 — Paddy bund
Soja57 Chugoku, Yamaguchi 34°03'38.4"N, 131°17'34.7"E 14 m CED98071 5 m2 —
Soja58 Chugoku, Yamaguchi 34°02'57.4"N, 131°55'31.0"E 30 m CED98075 10 m2 Wasteland along road (R2)
Soja59 Chugoku, Yamaguchi 34°04'11.5"N, 131°02'45.9"E 3 m CED98069 100 m2 Wasteland
Soja60 Shikoku, Ehime 33°22'54.8"N, 132°30'00.6"E 64 m CED98103 — Wasteland along road
Soja61 Shikoku, Ehime 33°11'18.5"N, 132°32'45.6"E 25 m CED98106 20 m2 Paddy bund
Soja62 Shikoku, Kochi 33°01'47.0"N, 132°51'28.5"E 17 m CED98109 > 30 000 m2 Paddy bund
Soja63 Shikoku, Kochi 33°24'29.5"N, 133°16'58.9"E 3 m CED98117 10 000 m2 Wasteland
Soja64 Shikoku, Kochi 33°32'48.4"N, 133°46'17.6"E 11 m CED98126 30 000 m2 Paddy bund
Soja65 Kyushu, Fukuoka 33°21'38.7"N, 130°40'23.6"E 14 m CED98033 — Wasteland along river
Soja66 Kyushu, Fukuoka 33°39'47.0"N, 131°01'36.5"E 10 m CED98068 10 000 m2 Riverbank
Soja67 Kyushu, Fukuoka 33°04'44.3"N, 130°26'06.2"E 25 m CED96111101 — Roadside (R18)
Soja68 Kyushu, Kagoshima 31°45'26.8"N, 130°40'35.2"E 140 m CED98042 — —
Soja69 Kyushu, Kumamoto 32°46'52.6"N, 130°49'08.3"E 80 m CED98038 1000 m2 Riverside beside paddy
Soja70 Kyushu, Miyazaki 32°21'24.4"N, 131°37'12.7"E 8 m CED98054 500 m2 Roadside (R10)
Soja71 Kyushu, Miyazaki 32°00'43.8"N, 131°27'33.7"E 4 m CED98051 10 000 m2 Roadside along field
Soja72 Kyushu, Nagasaki 32°58'45.1"N, 129°07'34.5"E 25 m CED98025 400 m2 Wasteland beside paddy
Soja73 Kyushu, Nagasaki 33°03'15.1"N, 129°05'24.8"E 60 m CED98023 75 m2 Wasteland surrounded by mountains
Soja74 Kyushu, Ohita 33°31'47.9"N, 131°18'02.7"E 8 m CED98061 8 m2 Wasteland beside farmland (soybean)
Soja75 Kyushu, Ohita 33°09'13.6"N, 131°31'08.0"E 40 m CED98059 100 m2 Wasteland beside paddy
Soja76 Kyushu, Saga 33°21'07.1"N, 129°56'00.2"E 50 m CED96111105 — Roadside (R202)
Soja77 Kyushu, Saga 33°18'47.0"N, 130°04'08.0"E 90 m CED96111104 — Roadside (R203)
Appendix II Go to: ChooseTop of pageIntroductionMaterials and methodsResultsDiscussionAcknowledgementsReferencesAppendix IAppendix II <<

Cultivated soybean (Glycine max) used in this study

Abbreviation Cultivated regions‡ (%§) Name of variety History* JP no.†
Max01 Hkk (28) Toyomusume TN 27541
Max02 Hkk (14) Suzumaru TN 67771
Max03 Hkk (23) Toyokomachi TN 53275
Max04 Hkk (6) Otofuke Ousode LR 49455
Max05 Hkk (4) Chuusei Hikarikuro LR 49453
Max06 Hok (0.01) Aonyuudou LR 28311
Max07 Hkk (6) Kitamusume TW 27449
Max08 Hkk (1) Yuuzuru TW 27533
Max09 Hkk (2) Tokachikuro TW 27539
Max10 Hkk (5) Kariyutaka TN (1)
Max11 Hkk (4) Toyohomare TN (1)
Max12 Hkk (2) Yukihomare NW (1)
Max13 Hkk (1) Hayahikari NW 200328
Max14 T (4) Okushirome TW 28030
Max15 T (8) Ohsuzu NW (2)
Max16 T (9) Tanrei TW 29206
Max17 T (23), Hok (0.06) Suzuyutaka TW 68385
Max18 T (19), Hok (0.01) Ryuhou NW (2)
Max19 T (6) Suzukari TN 68386
Max20 T (8) Tachiyutaka TN 68387
Max21 T (13) Miyagi Shirome TW 27886
Max22 T (3), Hok (0.2) Kosuzu TN 68389
Max23 T (0.5), Hok (0.3) Ayakogane NW (3)
Max24 Hok (98), Kt (3), Cb (0.1), Ks (5), CS (1) Enrei TW 28862
Max25 Hok (0.02) Tohoku 41 TN 28151
Max26 Hok (0.03), CS (0.04) Ao Daizu LR 28748
Max27 Kt (15) Nattou Kotsubu TW 29161
Max28 T (3), Kt (56), Cb (0.2), CS (0.4) Tosan 135 TN 49761
Max29 Kt (0.2) Hakkou LR 28954
Max30 Kt (13) Nakasennari TW 29183
Max31 Kt (0.4) Hatayutaka NW (2)
Max32 Kt (2) Ginrei NW (3)
Max33 Kt (4), Cb (92), Ks (5), CS (14), Ky (76) Fukuyutaka TW 29668
Max34 Cb (0.1) Chuu Teppou LR 29207
Max35 Cb (0.1), Ks (16), CS (25), Ky (0.002) Tanba Kuro LR 29359
Max36 Kt (1), Hok (0.7), Cb (0.04), Ks (23) Ohtsuru TN (3)
Max37 Kt (2), Cb (3), Ks (34), CS (33) Tamahomare TW 29184
Max38 Ks (7), CS (0.2), Ky (0.02) Kuro Daizu LR 29535
Max39 Ks (1) Mochi Daizu LR 70093
Max40 Ks (6) Shintanbakuro TW 49594
Max41 Ks (0.1) Tamamasari NW (3)
Max42 Ks (3), CS (8) Nishimusume TW 76377
Max43 Cb (3), Ks (0.01), CS (12), Ky (0.03) Akishirome TW 29669
Max44 CS (0.1) Gin Daizu LR 27579
Max45 CS (0.04) Shirotae TW 28859
Max46 CS (0.004) Akiyoshi TW 29578
Max47 CS (0.03) Sayanami NW (3)
Max48 CS (0.8) Suzukogane NW (3)
Max49 CS (3), Ky (1) Toyoshirome TN 29681
Max50 Ky (0.001) Kyushu 134 TN
Max51 Ky (22) Murayutaka TN (5)
Max52 Ky (0.04) Erusuta NW (4)
Max53 Ky (0.03) Kiyomidori NW (4)
*LR [landrace], TW [varieties released more than 20 (40) years ago], TN [varieties released more than 10 (20) years ago] and NW [newly developed varieties released less than 10 years ago].
†Materials conserved in the gene bank at National Agricultural Research Institute.
(1)(5)Materials obtained from (1)Tokachi Agricultural Experimental Station, (2)National Agricultural Research Center for Tohoku Region, (3)Chushin Agricultural Experimental Station, (4)National Agricultural Research Center for Kyushu Okinawa Region and (5)Saga Agricultural Experimental Center.
‡Hkk (Hokkaido, main northern island), T (Tohoku, northern Honshu), Hok (Hokuriku, Niigata and surrounding regions),
Kt (Kanto, Tokyo and surrounding regions), Cb (Chubu, Nagoya and surrounding regions), Ks (Kansai, Osaka and surrounding regions), CS [Chugoku (southern Honshu) & Shikoku (Shikoku island)], and Ky (Kyushu, main southern island).
§Frequencies in parentheses indicate average percentage of planting area in each region from 1998 to 2002 according to the National Agricultural Statistics of Japan.

Influence of media components and PH on somatic embryo induction in soybean

Click here

http://korban.nres.uiuc.edu/pub8.pdf

Mutagenesis of Embryogenic Cultures of Soybean and Detecting Polymorphisms Using RAPD Markers

Details : http://www.springerlink.com/media/mm8xd75n4l5jujc80evl/contributions/g/7/4/7/g74736267h7mg131.pdf





In short:

Mutagenesis of Embryogenic Cultures of Soybean and Detecting Polymorphisms Using RAPD Markers
N.E. Hofmann1, R. Raja2, R.L. Nelson2, 3 and S.S. Korban1

(1) Department of Natural Resources and Environmental Sciences, University of Illinois, 1201 W. Gregory, Urbana, IL 61801, USA
(2) Department of Crop Science, University of Illinois, Urbana, IL 61801, USA
(3) USDA/ARS, Urbana, IL 61801, USA


Abstract Embryogenic suspension cultures of soybean (Glycine max L. cv. Iroquois) were subjected to mutagenesis using varying concentrations (1, 3, 10, and 30 mM) of ethyl methanesulfonate (EMS). Depending on the concentration of EMS used, the mean survival rate of embryogenic cultures decreased from 74 % (1 mM EMS) to 43 % after 30 mM EMS treatment. Random amplified polymorphic DNA (RAPD) analysis was used to determine whether induction of genetic variability in embryogenic cultures in response to the different EMS treatments may result in identification of polymorphic markers. Two of 35 core primers tested revealed polymorphisms. One of the primers, OPO-01/1150, revealed polymorphism in tissue treated with 10 mM EMS, while the other primer, OPO-05/1200, revealed polymorphism in tissue treated with either 1 or 30 mM EMS. These results suggest that RAPD markers are useful in detecting mutations in embryogenic cultures of soybean.
chemical mutagenesis - Glycine max - molecular markers - somatic embryogenesis


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

Histology of embryogenic responses in soybean anther culture

In details: http://www.springerlink.com/media/bd1bm4803l5jujda3bq6/contributions/k/4/2/6/k426tk6888146024.pdf




In Short:

Histology of embryogenic responses in soybean anther culture
Lia R. Rodrigues1 , João Marcelo S. Oliveira2, Jorge E.A. Mariath2 and Maria Helena Bodanese-Zanettini1

(1) Departamento de Genética, Universidade Federal do Rio Grande do Sul, P.O. Box 15053, CEP 91501-970 Porto Alegre, RS, Brazil
(2) Departamento de Botânica, Universidade Federal do Rio Grande do Sul, Porto Alegre,, Porto Alegre, RS, Brazil

Received: 21 January 2004 Accepted: 28 April 2004

Abstract In order to clarify the embryogenic responses in soybean anther culture, anthers of four cultivars were cultured under known conditions to trigger androgenic response. A histological study was performed with anthers in vivo and with approximately 100 explants sampled after 9, 12, 15, 18, 21, 30 and 45 days of culture. In vitro culture triggered the frequent accumulation of phenolic compounds on the locular and anther surfaces, and also caused the destruction of cells and tissues in complex structure such as the tapetum, microspores and pollen grains. Somatic embryogenesis of unicellular origin was observed from the epidermis and the middle layer, and of multicellular origin from connective calluses. No androgenic response could be observed in the anthers of these four soybean genotypes, in the medium and conditions indicated. We point out to the need of changing the approach to the study of androgenesis in soybean, either by using culture conditions unfavourable to the proliferation of diploid tissues, or by culturing isolated microspores.
Keywords anther anatomy - anther culture - Glycine max - histology - somatic embryogenesis

Somaclonal variation in soybean plants regenerated from tissue culture

Source: http://www.springerlink.com/media/5g0gxvrylqc570lxgndm/contributions/k/8/4/2/k842257101q0582m.pdf






In Short

Somaclonal variation in soybean plants regenerated from tissue cultureA. H. Freytag1 , A. P. Rao-Arelli1, S. C. Anand1, J. A. Wrather1 and L. D. Owens2

(1) Department of Agronomy and Department of Plant Pathology, University of Missouri, Delta Center, MO 63873 Portageville, Missouri, USA
(2) Plant Molecular Biology Laboratory, USDA-ARS, MD 20705 Beltsville, Maryland, USA


Abstract Callus cultures of soybean (Glycine max (L.) Merr.) genotypes PI 88788, PI 438489B, and cultivar Bedford were initiated in vitro from seedling explants consisting of the cotyledonary node plus epicotyl from germinated mature seed. Plants were regenerated from these callus cultures and subsequently evaluated for qualitative variation in three to four subsequent generations. Variant phenotypes observed that have not been previously reported from tissue culture include lanceolate leaves, leaf variegation (chimeral variegated plants), pod variegation on otherwise normal plants, and change in growth habit from indeterminate to determinate. The lanceolate leaf, chimeral variegated plant, and change from indeterminate to determinate growth habit characters were inherited through at least three generations (R0-R2), and segregation occurred in each generation. Pod variegation was inherited through the two generations tested thus far and segregation occurred in each generation. No variation was observed in control plants derived from normal seed. Variants appeared more frequently in regenerants from PI 88788 and PI 438489B than from Bedford. These results confirm and extend the finding that certain tissue culture techniques may be used to induce novel plant formation from somatic tissue of soybean.
Missouri Agricultural Experiment Station, University of Missouri, Columbia, Missouri, USA
Mention of tradenames does not constitute a guarantee or warranty of the product by University of Missouri or USDA-ARS and does not imply their approval to the exclusion of other products.

Genetic variation for quantitative traits in soybean lines derived from tissue culture

Details/source; http://www.springerlink.com/media/2l5gxvryum15c9j3kg0v/contributions/m/v/6/1/mv6112744345n648.pdf





In short

Genetic variation for quantitative traits in soybean lines derived from tissue culture
M. S. Hawbaker1, W. R. Fehr2, L. M. Mansur3, R. C. Shoemaker4 and R. G. Palmer4

(1) Department of Crop Science, North Carolina State University, 27695-7620 Raleigh, NC, USA
(2) Department of Agronomy, Iowa State University, 50011 Ames, IA, USA
(3) Department of Biology, University of Utah, 84110 Salt Lake City, UT, USA
(4) Department of Agronomy, Zoology, and Genetics, USDA-ARS-FCR, Iowa State University, 50011 Ames, IA, USA

Received: 31 October 1992 Accepted: 1 March 1993

Communicated by A. R. Hallauer
Abstract Tissue culture may generate useful genetic variation for quantitative traits. The objective of this study was to analyze genetic variation for ten quantitative traits of soybean [Glycine max (L.) Merr.] among lines derived from the tissue culture of three cultivars. The three cultivars used to obtain R0 plants from tissue culture were BSR 101, Hodgson 78, and Jilin 3. A total of 63 R0-derived lines of BSR 101, eight of Hodgson 78, and 42 of Jilin 3 was planted with the untreated controls in row plots in a randomized complete-block design with three replications at two locations for each of 2 years. The traits evaluated were days to beginning bloom (R1), beginning seed (R5), beginning maturity (R7), full maturity (R8), height, lodging, seed yield, seed weight, protein content, and oil content. Significant (P < 0.05) variation was observed among lines for each of the ten quantitative traits. There was 57.1% of the BSR 101 lines, 87.5% of the Hodgson 78 lines, and 76.2% of the Jilin 3 lines that were significantly different from the controls for at least one trait. The percentages of lines that were significantly different from the control for an individual trait ranged from 2.7% for oil content to 25.7% for R7. The magnitude of the changes was relatively small. Although this genetic variation may be useful for cultivar development, greater variability at less expense would be expected with conventional artificial hybridization.
Key words Tissue culture - Somaclonal variation - Embryogenesis - Glycine max (L.) Merr.

Journal Paper No. J-14958 of the Iowa Agriculture and Home Economics Experiment Station, Ames, IOWA, USA Project No. 2475.

Cell division and differentiation in protoplasts from cell cultures of Glycine species and leaf tissue of soybean

Full paper:
http://www.springerlink.com/media/e3lmnhtvukvf73yyrqau/contributions/h/1/u/7/h1u727772574w772.pdf




In short;

Cell division and differentiation in protoplasts from cell cultures of Glycine species and leaf tissue of soybean
O. L. Gamborg1, 4, B. P. Davis1, 2 and R. W. Stahlhut1, 3

(1) International Plant Research Institute, 94070 San Carlos, CA, USA
(2) Health Science Center, University of Texas, Dallas, TX, USA
(3) Department of Agronomy, University of Illinois, Urbana, IL, USA
(4) Genentech Inc., 460 Point San Bruno Blvd., 94080 South San Francisco, CA, USA

Received: 5 July 1983

Abstract Protoplasts were isolated from cell cultures of G. soja and G. tabacina, respectively. The isolation procedure employed Percoll for the separation and concentration of protoplasts. The cultured protoplasts formed cells which developed into embryo-like structures. Protoplasts also were isolated from leaf tissue of soybean cv. Williams 82. Upon culture, the protoplasts regenerated cell walls and divided to form cell cultures.
Abbreviations 2,4-D 2,4-Dichlorophenoxyacetic acid BA|Benzyladenine - BA Benzyladenine

Agronomic evaluation of tissue-culture-derived soybean plants

Origibnal : http://www.springerlink.com/(x4uisc3effmqwa55tuvxkr55)/app/home/contribution.asp?referrer=parent&backto=searcharticlesresults,2,88;


In pdf:
http://www.springerlink.com/media/64cr5a4mgl5juke15ywv/contributions/g/5/5/6/g556h24852456564.pdf

References for soybean

details in original:
http://www.cropsoil.uga.edu/soy-engineering/Species.html


Species references:
Last modified July 2, 1996; no new known references to add as of 19 October, 2004

Grant, J.E. 1984. Regeneration from cotyledonary tissue of Glycine canescens, a perennial relative of the soybean. Plant Cell Tissue Organ Cult. 3:169-173.

Hammatt, N., H.-I. Kim, M.R. Davey, R.S. Nelson, and E.C. Cocking. 1987a. Plant regeneration from cotyledon protoplasts of Glycine canescens and G. clandestina. Plant Sci. 48:129-135.

Hammatt, N., R.S. Nelson, and M.R. Davey. 1987b. Plant regeneration from seedling cotyledons, petioles and leaves of Glycine clandestina. Plant Physiol. 68:125-128.

Hammatt, N., R.S. Nelson, and M.R. Davey. 1987c. Plant regeneration from seedling explants of perennial Glycine species. Plant Cell Tissue Organ Cult. 11:3-11.

Hammatt, N., B. Jones, and M.R. Davey. 1989. Plant regeneration from seedling explants and cotyledon protoplasts of Glycine argyrea Tind. In Vitro Cell. Dev. Biol. 25:669-672.

Hymowitz, T., N.L. Chalmers, S.H. Constanza, and M.M. Saam. 1986. Plant regeneration from leaf explants of Glycine clandestina Wendl. Plant Cell Rep. 3:192-194.

Kameya, T. and J. Widholm. 1981. Plant regeneration from hypocotyl sections of Glycine species. Plant Sci. Lett. 21:289-294.

Kumar, V., B. Jones, and M.R. Davey. 1991. Transformation by Agrobacterium rhizogenes and regeneration of transgenic shoots of the wild soybean Glycine argyrea. Plant Cell Rep. 10:135-138.

Myers, J.R., P.A. Lazzeri, and G.B. Collins. 1989. Plant regeneration of wild Glycine species from suspension culture-derived protoplasts. Plant Cell Rep. 8:112-115.

Newell, C.A. and H.T. Luu. 1985. Protoplast culture and plant regeneration in Glycine canescens F.J. Herm. Plant Cell Tissue Organ Cult. 4:145-149.

Pandey, P. and Y.K. Bansal. 1992. Plant regeneration from leaf and hypocotyl explants fo Glycine wightii (W. and A.) Verdc. var longicauda. Japan J. Breed. 42:1-5.

Rech, E.L., T.J. Golds, N. Hammatt, B.J. Mulligan, and M.R. Davey. 1988. Agrobacterium rhizogenes mediated transformation of the wild soybeans Glycine canescens and G. clandestina: production of transgenic plants of G. canescens. J. Exp. Bot. 39:1275-1285.

Sellars, R.M., G.M. Southward, and G.C. Phillips. 1990. Adventitious somatic embryogenesis from cultured immature zygotic embryos of peanut using soybean as a model system. Crop Sci. 30:408-414.

Widholm, J.M. and S. Rick. 1983. Shoot regeneration from Glycine canescens tissue culture. Plant Cell Rep. 2:19-20.

Yeh, M.-S. 1990. In vitro culture of immature soybean embryos II. The abilities of organogenesis and plantlet regeneration from different aged immature embryo in Glycine species. J. Agric. Assoc. China 39:73-87.

Population genetic structure of Japanese wild soybean (Glycine soja) based on microsatellite variation

For original test click : http://www.blackwell-synergy.com/doi/full/10.1111/j.1365-294X.2006.02854.x


Population genetic structure of Japanese wild soybean (Glycine soja) based on microsatellite variation
Y. KURODA*, A. KAGA*, N. TOMOOKA and D. A. VAUGHAN

Abstract

The research objectives were to determine aspects of the population dynamics relevant to effective monitoring of gene flow in the soybean crop complex in Japan. Using 20 microsatellite primers, 616 individuals from 77 wild soybean (Glycine soja) populations were analysed. All samples were of small seed size (< 0.03 g), were directly collected in the field and came from all parts of Japan where wild soybeans grow, except Hokkaido. Japanese wild soybean showed significant reduction in observed heterozygosity, low outcrossing rate (mean 3.4%) and strong genetic differentiation among populations. However, the individual assignment test revealed evidence of rare long-distance seed dispersal (> 10 km) events among populations, and spatial autocorrelation analysis revealed that populations within a radius of 100 km showed a close genetic relationship to one another. When analysis of graphical ordination was applied to compare the microsatellite variation of wild soybean with that of 53 widely grown Japanese varieties of cultivated soybean (Glycine max), the primary factor of genetic differentiation was based on differences between wild and cultivated soybeans and the secondary factor was geographical differentiation of wild soybean populations. Admixture analysis revealed that 6.8% of individuals appear to show introgression from cultivated soybeans. These results indicated that population genetic structure of Japanese wild soybean is (i) strongly affected by the founder effect due to seed dispersal and inbreeding strategy, (ii) generally well differentiated from cultivated soybean, but (iii) introgression from cultivated soybean occurs. The implications of the results for the release of transgenic soybeans where wild soybeans grow are discussed.

Introduction Go to: ChooseTop of pageIntroduction <
Soybean [Glycine max (L.) Merrill] is the world's most important grain legume crop in terms of total production and international trade (Smil 2000). Transgenic soybean is grown on a larger area globally than any other transgenic crop but is not currently grown in Asia where the wild progenitor of soybean (Glycine soja Sieb. & Zucc.) grows (http://www.colostate.edu/programs/lifesciences/TransgenicCrops/current.html).

To date, the main transgene incorporated into widely grown soybeans confers herbicide resistance. There are concerns that transgenes from soybeans cultivated in the same area as its cross compatible wild relative, G. soja, could lead to wild soybeans having herbicide resistance. Currently, policy regarding growing transgenic soybeans is awaiting risk assessment. Consequently the research reported here addresses frequency and extent of gene flow from soybean to its wild relative, to assist policy makers' deliberations on the potential impact of growing transgenic soybean in Japan.

Wild soybean is a strictly annual plant species with high seed production, and is one of the aggressive colonizers of disturbed habitats. It is considered the direct progenitor of cultivated soybean based on morphology (Broich & Palmer 1980), cytogenetics (Hymowitz & Singh 1987; Palmer et al. 1987) and molecular analyses (e.g. Kollipara et al. 1997; Abe et al. 1999). There is no agreement on whether soybean was domesticated in southern China, the Yellow River valley of central China or northeast China, or more than once (Carter et al. 2004). The natural distribution of wild soybeans is far eastern Russia, eastern China including Taiwan, Japan and the Korean Peninsula (Lu 2004). In Japan, wild soybean is widely distributed across the Japanese archipelago from the northern island of Hokkaido (42°N) to the southern island of Kyushu (31°N).

The safe release of transgenic soybeans is contingent on the transgene not being able to escape. A further consideration is whether transgenes become established in wild populations. Knowledge of gene flow, the combined effect of cross-pollination and seed dispersal, is necessary to evaluate environmental impact of transgenic soybeans. The outcrossing rate of wild soybeans has been reported to range from 2.4% to 19% (Kiang et al. 1992; Fujita et al. 1997). The high outcrossing rates (9.3–19%) recorded by Fujita et al. (1997) were considered to be due to frequent visits to wild soybean flowers by pollinators (honeybees and carpenter bees) in the study area, Akita prefecture, in the northern part of Japan. The average and maximum distance wild soybean pollen is dispersed has been estimated at 10 m and 60 m, respectively (Jin et al. 2003). Most seeds are naturally dispersed by pod dehiscence within 4.5 m of the mother plant (Oka 1983), but long-distance seed dispersal of wild soybeans down rivers has been inferred on the basis of genetic diversity and genetic differentiation (Kiang et al. 1992; Choi et al. 1999). Long-distance seed dispersal may result in plants with the same genotype being introduced into widely separated areas. However, evidence of long-distance seed dispersal has not been demonstrated.

Introgression from crops to their wild relatives is a common phenomenon (Ellstrand et al. 1999; Ellstrand 2003a), but information on the basis of molecular analysis is limited for soybean (Abe et al. 1999). Wild soybeans have generally smaller leaves, smaller flowers, smaller seeds (1–3 g/100 seeds) that are black, and stronger stem-twinning compared with cultivated soybeans. In natural habitats, morphologically intermediate plants between wild and cultivated soybean showing phenotypic traits such as large leaves, large grains and yellow seed coat are reported to be quite common in China (Dong et al. 2001) and but are rare in Japan (Sekizuka & Yoshiyama 1960; Kuroda et al. 2005). Outcrossing between G. soja and G. max can occur where these two species are sympatric, since these two species share the same genome and no obvious reproductive barriers have been observed in experimental crosses (Hymowitz & Singh 1987). Outcrossing in cultivated soybeans has been reported to be less than 3% (Dorokhov et al. 2004). Natural outcrossing rates range from 0% to 5.9% when G. soja and G. max were alternately planted at a distance of 50 cm (Nakayama & Yamaguchi 2002). G. soja and G. max hybrids can survive in seminatural conditions for at least 3 years without intervention (Oka 1983).

While direct measurements of gene flow are generally difficult (Bossart & Prowell 1998; Cain et al. 2000), indirect approaches based on theories of population genetics such as analyses of Hardy–Weinberg equilibrium (e.g. Wright 1965; Weir & Cockerham 1984), genetic distance (e.g. Takezaki & Nei 1996), genetic differentiation (e.g. Weir & Cockerham 1984), model-based genetic mixture (Pritchard et al. 2000) and spatial autocorrelation (Smouse & Peakall 1999) are commonly employed. Microsatellites or simple sequence repeats (SSRs) are widely distributed across all eukaryotic genomes and have high sensitivity to detect polymorphisms (Haig 1998; Parker et al. 1998). Many soybean microsatellite markers have been mapped on the 20 linkage groups of the soybean genome (Song et al. 2004). Therefore, microsatellite markers can be used to assess population genetic structure and gene flow between cultivated and wild soybeans.

The objectives of this study, using microsatellite analysis of the nuclear genome, were to (i) evaluate population genetic structure of wild soybeans sampled from throughout most of their natural range in Japan; (ii) determine the potential contribution of long-distance seed dispersal on wild soybean population structure; (iii) estimate outcrossing in wild soybean populations; (iv) compare the genetic diversity of wild and cultivated soybeans; and (v) estimate the extent of natural introgression from cultivated soybeans to the wild soybeans. Based on the results, issues related to gene flow in the Japanese soybean gene pool in relation to biosafety are discussed.

Materials and methods Go to: ChooseTop of pageIntroductionMaterials and methods <
Collection of materials

Six hundred sixteen seeds from a total of 77 populations of wild soybean (Soja01–Soja77, Fig. 1, Appendix I) were analysed in this study. Populations ranged in proximity from about 0.2 km (Soja44 and Soja45) to about 1330 km (Soja07 and Soja72). The authors directly surveyed these wild populations between 1996 and 2003. The habitats of wild soybeans were riverbanks, abandoned paddies and roadside ditches where human and natural disturbances are frequent. Individual plant samples were collected from throughout each population between October and November. Based on a survey of 100 seed weight of 3531 accessions of cultivated soybean and 439 accessions of wild soybean in the National Institute of Agrobiological Sciences (NIAS) gene bank, the mean and range for each species was 27.8 g (range: 3.50–73.9 g) and 2.20 g (range: 0.85–7.43 g), respectively (Kaga et al. 2005). The cultivated accessions with a seed size range overlapping with wild accessions are lines for fodder. One-seed weight of each wild individual surveyed in this experiment had less than 0.03 g and were all considered to represent wild soybeans. Seeds from these individuals, totalling 616 seeds from 77 populations, were used for microsatellite analysis.

Fifty-three varieties of cultivated soybean (Max01–Max53, Appendix II) that covered more than 95% of the soybean planting area in Japan over the last 5 years were selected for analysis (http://www.maff.go.jp/soshiki/nousan/hatashin/daizu/siryo/kenbetuhinsyu.html). These cultivars have different cultivation histories, 10 were landraces, 17 varieties were released 20–40 years ago, 14 varieties were released 10–20 years ago and 12 were recently released varieties (< 10 years).

DNA extraction, primer screening and genotyping

Total DNA was extracted from 616 seeds of wild soybean collected directly from the field and single seed samples of 53 cultivars using the method of Kamiya & Kiguchi (2003) with modifications. The seed coat was removed prior to DNA extraction in order to prevent contamination with maternal DNA. Using three wild soybeans (collected from northern, central and southern parts of Japan) and three cultivated soybeans (major varieties of northern, central and southern parts of Japan) 714 genome-wide soybean primers, which included ATT repeat motif (71%) and AT repeat motif (13%) and other repeat motifs such as CTT, CT, CAA, and TAGA, were screened (Table 1, primer information is available from http://129.186.26.94/ssr.html). In the primer screening process, PCR amplification was performed using a thermal cycler (GeneAmp PCR system 9700, Applied Biosystems) under the conditions of one cycle of 2 min at 94 °C, followed by 40 cycles for 30 s at 94 °C, 30 s at about 50 °C and 30 s at 68 °C and finally maintained at 4 °C in a volume of 10 µL [1 × buffer, 0.2 mm of dNTP, 1 mm of MgSO4, 0.3 µm of primer pairs, 0.01 U of polymerase (KOD-plus, Toyobo) and 1–5 ng of total DNA]. Two hundred forty-two primers, which were composed of ATT (85%) and AT (9%) motif primers (ranged from 7 to 17 per linkage group), showed stable and polymorphic banding patterns among the samples based on electrophoresis in 2.5% agarose gel under the condition of 100 V for 15 min. From those primers, one was randomly selected from each soybean chromosome.

For the analysis of all samples, forward primers were labelled with different dyes, 6-FAM, VIC, NED or PET dyes (Applied Biosystems). Polymerase chain reaction (PCR) was carried out under the same conditions as primer screening. Two microlitre of PCR product was denatured in 13 µL of Hi-Di formamide with 0.2 µL of GeneScan-500LIZ size standard (Applied Biosystems). PCR products were separated on an AB3100 capillary sequencer for allele detection. Allelic data were scored using genemapper 3.0 software and the genotype of each sample was determined.

Data analysis

Intrapopulation variation and breeding systems. Genetic variability of each wild soybean population was estimated as the total number of alleles (A), expected and observed heterozygosities (HE and HO), fixation index (FIS) using the fstat program (Goudet 2001). HE is equal to HO in randomly mating populations. Fixation index (Wright 1965) shows deviation from the Hardy–Weinberg expectation. The testing to evaluate either excess or deficit of heterozygotes was computed using the fstat program. Outcrossing rate (t) was calculated from the fixation index using the equation t = (1 –FIS)/(1 + FIS) (Weir 1996).

Seed dispersal. An assignment test was performed on multilocus data to determine whether it is possible to assign individuals to their original population or another wild soybean population using geneclass 2 software (Piry et al. 2004). The DA (Nei et al. 1983) distance-based method was used to calculate the likelihood values for each individual belonging to the sampled population. This distance method does not require Hardy–Weinberg equilibrium or absence of linkage disequilibrium among loci and the DA distance showed higher percentage of individuals assigned to the correct population than other distance methods such as standard genetic distance (DS) and minimum genetic distance (Dm) (Cornuet et al. 1999).

Spatial structure of genetic variation. Spatial autocorrelation analysis for multiallelic codominant loci was used to assess population structure of the 77 wild soybean populations (Smouse & Peakall 1999). A coefficient (r) was calculated from pairwise geographical and a pairwise squared genetic distance matrix (Φ) using the genealex version 5 program (Peakall & Smouse 2001). The coefficient r is a correlation coefficient with a mean of '0' when there is no correlation between geographical and genetic distances, and bounded by [−1, +1] (Smouse & Peakall 1999). The test for statistical significance was performed based on 999 random permutations. This generates an estimate of r about the null hypothesis of no spatial genetic structure (rp). After 999 permutations, the rp values are sorted and the 25th and 975th rp values taken to define the upper and lower bounds of the 95% confidence interval.

Genetic admixture. The Bayesian clustering algorithm was applied to identify clusters of genetically similar individuals and to test the proportion of genetic admixture among the clusters at the individual level using structure version 2.1 (Pritchard et al. 2000). One to 50 K (number of clusters) was applied to infer the number of clusters for wild soybean (including and excluding cultivated soybeans). The value of K maximizes the posterior probability of wild soybean clusters (Pritchard et al. 2000). In addition, genetic admixture between cultivated soybeans and wild soybeans was estimated using prior population information (migration rate ν= 0.05) in order to infer introgression between the species. For each run, a Markov chain Monte Carlo (MCMC) method was used to estimate allele frequencies in each K populations and the degree of admixture in each individual under the condition of 10 000 burn-in (process required to prepare for running MCMC) period and 10 000 MCMC replications.

Genetic differentiation. Analysis of molecular variance (amova, Excoffier et al. 1992) was performed to partition the observed genetic variability among populations of wild soybean, among varieties of cultivated soybean, and between wild and cultivated soybean using arlequin software (Schneider et al. 2000). To detect genetic differentiation between wild and cultivated soybean for each microsatellite locus, amovas were performed for each locus separately. amova creates a genetic distance matrix (Φ) between samples in order to measure the genetic structure of the population from which the samples are drawn. F-statistics were tested by 1000 permutations, and significant differences between groups declared if measured variance is lower than 95% of the variance in the null distribution (Excoffier et al. 1992). Genetic distances (DA, Nei et al. 1983) for all possible pairs of wild and cultivated soybean samples were computed using populations version 1.2.28 software (available at http://www.cnrs-gif.fr/pge/bioinfo/populations). Reproducibility of tree topology with the neighbour-joining method can be obtained based on DA (Takezaki & Nei 1996). Principal coordinate analysis was used to display genetic divergence among samples in a multidimensional space. The DA distances computed among all samples (including cultivated soybeans) were ordinated in two dimensions using ntsys (Rohlf 2000).

Results Go to: ChooseTop of pageIntroductionMaterials and methodsResults <
Microsatellite variation

In total, 405 and 109 alleles were detected from 20 microsatellite loci in Japanese wild and cultivated soybeans, respectively (Table 1). Wild soybeans showed much higher values for A and HE than cultivated soybeans. The number of alleles per locus (A) in wild soybean ranged from 9 (Satt581) to 39 (Satt277) and in cultivated soybeans ranged from 2 (Satt509, Satt555 and Satt581) to 13 (Satt277 and Satt288). Expected heterozygosity (HE) averaged over 20 loci was 0.870 (range from 0.691 to 0.956 for each locus) in wild soybeans, and was 0.496 (range from 0.109 to 0.850 for each locus) in cultivated soybeans. Eleven alleles were found only in cultivars (Table 2), but their frequencies were very low accounting for only 2.55% of alleles in cultivated soybean. In contrast, several alleles that were observed frequently in cultivated soybean were rare in wild soybean (Table 2).

FST value, which is an index of genetic differentiation, between cultivated soybean and wild soybeans ranged from 0.053 (Satt215) to 0.352 (Satt423) and was significant at all loci (P < 1.0 × 105, Table 1). Figure 2 shows typical examples of allele distribution where differentiation was not clear (e.g. Satt288, FST = 0.066, Fig. 2a), and where it was high (e.g. Satt076, FST = 0.336, Fig. 2b).

Intrapopulation variation and breeding system

Forty-one out of 77 wild soybean populations deviated significantly from Hardy–Weinberg equilibrium (P < 0.0003) due to lower level of observed heterozygosity (mean 0.018, range 0.000–0.131) compared with expected level of heterozygosity (mean 0.228, range 0.000–0.822). Therefore the average value of the fixation index was very high (mean 0.933, range 0.456–1.000; Table 3). Among the other 36 populations, the fixation index for 24 populations could not be evaluated because all plants in each population had an identical genotype. The indices for the remaining 12 populations did not deviate from Hardy–Weinberg equilibrium due to low levels of expected and observed heterozygosities. Mean outcrossing rate (%) estimated from the fixation indices in 77 populations was low (mean 3.4%, range 0.0–37.4%), suggesting that wild soybeans are predominantly inbreeding. However, seven populations had an outcrossing rate estimated at more than 10%. These populations came from all regions, north (2), central (1) and southern Japan (4). Larger populations had higher outcrossing rates than smaller populations (r = 0.428, P < 0.05).

Assignment test and spatial genetic structure

The individual assignment test revealed that 613 samples out of 616 samples (99.5%) were assigned to their original populations (i.e. having the highest likelihood value of belonging to the populations they came from), and the remaining three samples were assigned to another population: one Soja08 sample assigned to Soja07 (12.4 km from Soja08) and two Soja44 samples assigned to Soja45 (0.2 km from Soja44). These three samples showed identical genotypes over 20 microsatellite markers to five Soja07 and six Soja45 individuals.

Results of spatial autocorrelation are shown as a correlograms (Fig. 3a, b). Japanese wild soybean populations were divided by distance classes of 100 km and 50 km. There was a general decline in the correlation coefficient (r) among populations with distance. Each locus showed the same tendency that the correlation coefficient was highest at the first distance class (range r = 0.096–0.179, when Japanese populations were divided by 14 distance classes) and then it rapidly decreased to around zero within a few distance classes. The correlation values are positive and significant up to 200 km, with an x-intercept at 350 to 400 km, and negative and significant from 450 to 500 km and beyond. Spatial autocorrelation at the smallest distance class was highest, indicating the relationship between geographical proximity and genetic relatedness. Since rapid decline in the first two distance classes followed by moderate decline of genetic relatedness with distance was observed, the spatial pattern observed in relation to overall genetic distance can be explained by both short-distance similarity and long-distance differentiation.

Genetic differentiation within and between wild and cultivated soybean

amova showed strong genetic differentiation among populations of wild soybean (FST = 0.76, P < 1.0 × 105). Genetic admixture analysis without prior information about geographical origin of populations revealed that the highest likelihood value (ln PrX|K) was obtained when the number of clusters (K) was 38 (Fig. 4). At K = 38, 77 wild soybean populations were classified into 38 groups, which had only one to three wild populations. When 53 varieties of cultivated soybean were added to the analysis, the highest likelihood value was 39 (Fig. 4). In both of these analyses, populations of wild soybeans showed weak clustering of neighbouring populations. However, cultivated soybeans always formed a single group. These results reflect the high differentiation that exists in populations of Japanese wild soybeans. In contrast, Japanese cultivated soybeans are less divergent than wild soybeans and form a single group.

Genetic differentiation between wild and cultivated soybeans for the 20 microsatellite loci analysed was significant (FST = 0.203, P < 1.0 × 105). Graphical ordination of the first two axes in the plane for wild and cultivated soybean samples are shown (Fig. 5a–d). The first axis, accounting for 7.4% of the variation, reflects wild–cultivated soybean differentiation. In the axis, wild soybeans were located at values of less than 0.3; in contrast, cultivated soybeans were located at values of more than 0.3 (Fig. 5a). The second axis (accounting for 5.7% of the variation) showed that wild soybean samples were widely scattered compared to cultivated soybean. Samples on this axis for wild soybean reflected the geographical origin of samples. Samples from northern Japan were mainly found to the right of axis 1 and samples from the south to the left of axis 1, while samples from central Japan were about equally to the left and right of axis 1 (Fig. 5b–d). No cline was observed in relation to cultivation regions or years after release in cultivated soybeans.

Introgression from cultivated soybean to wild soybean

Since genetic differentiation between wild and cultivated soybeans was significant, as described in the previous section, genetic admixture analysis was performed using prior population information on the status of cultivation (wild or cultivated soybean, K = 2). This resulted in samples forming two clusters, wild and cultivated soybeans, respectively (Fig. 6). Forty-two samples from seven wild populations showed less than a 75% probability that the individual in question was correctly assigned to the given wild soybean population because these samples had some alleles which were common to cultivated soybeans but rare in wild soybeans. These samples came from populations Soja27 (7 individuals), Soja31 (8), Soja32 (4), Soja34 (3), Soja35 (4), Soja70 (8) and Soja71 (8) (Fig. 6). From these results, introgression from cultivated soybeans to wild soybeans was inferred. The presumed introgressed individuals were located at the interface between wild and cultivated soybean on the ordination plot (Fig. 5).

Discussion Go to: ChooseTop of pageIntroductionMaterials and methodsResultsDiscussion <
Gene flow between cultivars and their wild relatives commonly occurs in many plant species (Ellstrand 2003b). For soybeans in Japan, however, despite its long history of cultivation, phenotypic intermediate types between wild and cultivated soybeans are rarely found (Kuroda et al. 2005). To determine the population dynamics of the soybean crop complex in Japan for effective monitoring of gene flow, this study evaluated genetic structure of wild and cultivated soybeans, with samples from a wide range of natural and disturbed areas in Japan, using 20 nuclear microsatellite markers. The result revealed sufficient allelic variation to enable the genetic structure of wild soybean populations to be analysed. The data enable the following factors related to potential gene flow from transgenic soybean to be discussed: (i) geographical structure of genetic variation in wild soybean; (ii) long-distance dispersal of wild soybean seeds; (iii) natural outcrossing rate in wild soybean; (iv) genetic diversity of Japanese wild and cultivated soybeans; and (v) introgression from cultivated soybean to wild soybean. This is the first large-scale population genetic analysis based on nuclear genome diversity in relation to wild and cultivated soybeans.

Geographical structure of genetic variation in wild soybean

Spatial autocorrelation analysis revealed clinal spatial structure of genetic variation in Japanese wild soybeans. A positive correlation was found within a range of about 200 km and a negative correlation was found from about 350–400 km. Past studies on the basis of several molecular analyses have reported a geographical cline in genetic variation of Japanese wild soybeans (Kiang et al. 1992; Fujita et al. 1997). Kiang et al. (1992) analysed polymorphic patterns of 15 isozyme and one nonenzyme protein (Ti) in four populations of wild soybean collected in Iwate prefecture (120 km range), and found a relationship between genetic distance and latitude in several populations. Fujita et al. (1997) analysed nine allozyme and one nonenzyme protein (Ti) in four wild soybean populations collected in Akita prefecture (50 km range), and found a significant simple correlation between genetic distance and geographical distance (r = 0.86). These two previous studies only dealt with wild soybean from northern parts of Japan. The present study used samples of wild soybean from almost all parts of Japan, and found spatial correlation over the whole range of Japanese wild soybean.

On the basis of graphical ordination analysis, nuclear microsatellite variation of wild soybeans in northern Japan is distinct from southern Japan. Wild soybeans of central Japan had variation from both regions. These results suggest that wild soybean populations can be dispersed within a range of about 200 km regions and there is a lack of seed migration between regions. Such geographical cline was also observed in organelle genome studies (Tozuka et al. 1998; Xu et al. 2002). Tozuka et al. (1998) analysed RFLP (restriction fragment length polymorphism) patterns of mitochondrial DNA using 1097 individuals of wild soybean collected from throughout Japan and found genetic differentiation between southern and northern parts of Japan. Xu et al. (2002) analysed microsatellite haplotypes of chloroplast DNA using 143 wild soybean accessions from throughout Japan and showed regional distribution for most of the haplotypes.

Long-distance dispersal of wild soybean seeds

Seed dispersal from 0.2 to 12.4 km was inferred from three samples out of 616 based on identical genotypes being found in different populations. Although genetic structure among wild soybean populations was highly differentiated, a reflection of inbreeding in this annual plant species (Hamrick & Godt 1989), seed dispersal over more than 0.2 km can occur for wild soybeans. There are some data to support the result of seed dispersal. First, 41 populations out of 77 had only one or two genotypes among eight samples in this study, indicating that founder plants in new habitats produce large numbers of seeds resulting in populations with few genotypes. Second, autocorrelation analysis showed a rapid decline in the first distance class (100–200 km), suggesting gene flow between populations within 200 km occurred significantly more frequently than those farther than 200 km. Third, individual wild soybean plants produce between 472 and 3570 seeds under cultivated conditions in Tsukuba, central Japan (authors' unpublished data), indicating that large seed numbers per individual would provide the chance for seed dispersal. Long-distance seed dispersal can occur as a result of dispersal in water or when seeds are carried by animals or humans (Cain et al. 2000). Pollen has only been reported to be carried short-distances (< 60 m) by bees (Jin et al. 2003), and most seeds of wild soybean are naturally dispersed to a distance of up to 4.5 m when pods dehisce (Oka 1983). These results indicate that long-distance seed dispersal and founder effect may be an important factor in determining population genetic structure and the establishment of new populations within a range of 200 km.

Natural outcrossing rate in wild soybean

Wild soybeans have a variable level of outcrossing in Japan. In this study, most populations showed a low rate of outcrossing (mean 3.4%). However, seven populations from different parts of Japan had an estimated outcrossing rate of more than 10%. The wide variation in outcrossing rate probably reflects variation in the abundance of pollinators, population size and their interaction. Population size of wild soybeans varies greatly. In this study, some wild soybean populations consist of a few plants, others cover hectares of land, and larger populations have higher outcrossing rates than smaller populations. In the wild soybean populations studied by Fujita et al. (1997), frequent visits of pollinators were reported to be the main factor in the high levels of outcrossing (9.3–19%). They recorded 37 honeybees (Apis cerana) and 5 carpenter bees (Xylocopa appendiculata circumvolans) in a 4-m2 plot in 2 h (11:00–13:00 h). Their study site was relatively large in size (900–40 000 m2). Large populations would be expected to attract larger numbers of pollinators and hence have high outcrossing rate (Fujita et al. 1997).

Genetic diversity of Japanese wild and cultivated soybeans

Our results support the view that domestication of soybean involved a genetic bottleneck. Microsatellite variation in 53 major Japanese cultivated soybean varieties, which account for more than 95% of the planting area in Japan, is much less than that of Japanese wild soybeans. Cultivated soybeans had only 57% of the Nei's diversity value (HE) of wild soybeans analysed (0.870 and 0.496 for wild and cultivated soybeans, respectively). The higher variation in wild soybeans than that of cultivated soybeans is consistent with past studies using germplasm from many countries. Maughan et al. (1995) analysed 67 soybean cultivars and 32 wild samples from China, Japan, Korea, Taiwan and the former Soviet Union using five nuclear microsatellites, and found that cultivated soybeans had 63% of the HE value of wild soybeans (0.87 and 0.55 for wild and cultivated soybeans, respectively). Xu et al. (2002) evaluated 143 wild soybean accessions from Russia, China, Korea and Japan and 183 cultivated soybeans from Russia, China, Korea, Japan, Vietnam, Thailand, Indonesia, India, Myanmar, Bhutan, Nepal, Pakistan and Kyrgyzstan using six chloroplast microsatellites, and found that cultivated soybeans had 54% of the HE value of wild soybeans (0.496 and 0.269 for wild and cultivated soybeans, respectively). A loss of diversity between cultivated soybean and wild soybeans is reported here (57%) despite the narrow genetic base of Japanese cultivated soybeans that were used in the study. Most cereals for example have been shown to have 78% (maize), 60% (sorghum), 71% (rice), 65% (oat), 71% (wheat) and 67% (peal millet) of the nucleotide variation (i.e. nucleotide level of HE, Nei 1987) found in wild progenitors based on broad sampling of the crop and its wild relatives (Buckler et al. 2001).

Although genetic variation in cultivated soybean is much lower than wild soybean, some alleles were found only in cultivated soybean and other alleles with high frequency in cultivated soybeans and low frequency in wild soybeans. In this study, 11 microsatellite alleles that were only found in cultivars, were at low frequencies (0.02–0.09). This could be the result of mutation after domestication of soybean (Li & Nelson 2002) or the samples of wild soybean were insufficient for these alleles to be detected. For example, wild soybean in China, a centre of diversity for the soybean crop complex, may have these alleles. Seven alleles were observed at a much higher frequency in cultivated soybeans than wild soybeans. This suggests that the soybean was domesticated from a part or parts of the wild soybean gene pool.

Natural introgression from cultivated soybean to wild soybean

Ordination analysis clearly differentiated between Japanese wild soybeans and cultivated soybeans. Since most cultivated soybean alleles were also present in wild soybeans, the differentiation in these two species is explained by genotypic differences in microsatellite allele combinations. Such genetic differentiation between wild and cultivated soybeans has previously been reported (Powell et al. 1996; Xu & Gai 2003). Xu & Gai (2003) found no cultivar-specific RAPD (random amplified polymorphic DNA) bands when comparing 48 wild (21) and cultivated (27) soybean accessions from China but did find clear differentiation between cultivated and wild soybean.

Although none of the wild soybeans analysed had morphological characteristics of intermediate soybeans, genetic admixture and principal coordinate analyses suggest introgression between cultivated and wild soybean in all regions of Japan. Forty-two wild individuals (6.8%) from the northern, central and southern parts of Japan were found with presumed introgressed genomic segments from cultivated soybeans. The wild soybean populations with individuals having membership to the cultivated soybean class were Soja27, Soja31, Soja34, Soja70 and Soja71. These samples had alleles which were observed frequently in cultivated soybeans and rarely in wild soybeans. Among these populations, Soja31 and Soja34 were found in Nagano prefecture, and Soja70 and Soja71 were found in Miyazaki prefecture. It is possible that wild soybean growing there originally had such alleles. However, we believe that those populations were hybrid derivatives, because the composition of such cultivar-predominant alleles differed among populations and among individuals within populations. Such cultivar-predominant alleles in wild soybean were distributed across Japan at a low frequency. These populations were found in different habitats such as wasteland beside paddies, fields or roadside. Japanese farmers have sometimes utilized such habitats for planting soybeans. It seems that pollen flow from soybean cultivars to wild soybeans occurs where they are sympatric. In artificial hybrids between wild and cultivated soybeans it is difficult to recover cultivated characteristics (Carter et al. 2004). Thus, introgressed genes from cultivated soybean may persist in wild soybean populations cryptically. The lack of intermediate morphological characteristics in presumed introgressed samples analysed suggests that hybrid progenies between wild and cultivated soybeans revert to wild soybean characteristics in natural conditions.

Implications for biosafety of soybean gene pool in Japan

In Japan the two conditions required for genes from transgenic soybean to be dispersed to wild soybeans, sympatric habitats and synchronous flowering, exist (Kuroda et al. 2005). Despite the small size of wild soybean seeds (> 0.03 g) used for microsatellite analysis in this study, it is inferred that pollen flow from cultivated soybeans to wild soybeans occurs across Japan and long-distance seed dispersal also occasionally occurs. Seven microsatellite markers alleles, which are predominant in cultivated soybean and rare in wild soybean, are likely to be useful to monitor gene flow from the widely grown Japanese cultivars to the wild soybean in Japan.

Our research team has searched for phenotypic wild–cultivated intermediate soybean in natural habitats throughout Japan for 2 years, and we have confirmed that such intermediate soybeans exist in natural habitats. However, such intermediate individuals are rare. Based on field surveys of more than 50 wild soybean populations that were adjacent to fields of cultivated soybeans, only 12 intermediate individuals having large seed size (0.06–0.12 g) in three populations were found in the northern and southern parts of Japan (Kaga et al. 2005; Kuroda et al. 2005). Results presented here and field observations indicate that some genomic regions of cultivated soybean are neutral or a disadvantage in natural conditions. A genetically modified (GM) gene may persist in the natural habitat when it is closely linked with the neutral genomic regions. In contrast, a GM gene may disappear when it is linked with genomic regions, which are at a disadvantage in the natural habitat. Therefore, to identify such genomic regions in soybean genome may offer important information for the safe release of GM soybeans in the field. Research directed to the issue of fitness in wild and cultivated soybean hybrids is currently underway.


Acknowledgements Go to: ChooseTop of pageIntroductionMaterials and methodsResultsDiscussionAcknowledgements <
Support from Global Environment Research Fund of the Japanese Ministry of the Environment to author A.K. is acknowledged. The authors would like to thank the following Japanese institutes for the supply of some of the materials used in the experiments: National Agricultural Research Center for Kyushu Okinawa Region (KONARC), National Agricultural Research Center for Tohoku Region (NARCT), Hokkaido Prefectural Tokachi Agricultural Experimental Station, Nagano Chushin Agricultural Experimental Station, and Saga Prefectural Agricultural Experimental Center.

References Go to: ChooseTop of pageIntroductionMaterials and methodsResultsDiscussionAcknowledgementsReferences <• Abe J, Hasegawa A, Fukushi H et al. (1999) Introgression between wild and cultivated soybeans of Japan revealed by RFLP analysis for chloroplast DNAs. Economic Botany, 53, 285–291.

• Bossart JL, Prowell DP (1998) Genetic estimates of population structure and gene flow: limitations, lessons and new directions. Trends in Ecology & Evolution, 13, 202–206.

• Broich SL, Palmer RG (1980) A cluster analysis of wild and domesticated soybean phenotypes. Euphytica, 29, 23–32.

• Buckler ESIV, Thornsberry JM, Kresovich S (2001) Molecular diversity and domestication of grasses. Genetical Research, 77, 213–218.

• Cain ML, Milligan BG, Sterand AE (2000) Long-distance seed dispersal in plant populations. American Journal of Botany, 87, 1217–1227.

• Carter TE Jr, Nelson RL, Sneller CH, Cui Z (2004) Genetic diversity in soybean. In: Soybean Monograph (eds Boerma HR, Specht JE), 3rd edn. pp. 303–416. American Society of Agronomy, Madison, Wisconsin.

• Carter TE Jr, Nelson RL, Sneller CH, Cui Z (2004) Genetic diversity in soybean. In: Soybeans: Improvement, Production, and Uses (eds Boerma HR, Specht JE), pp. 303–416. American Society of Agronomy, Crop Science Society of America and Soil Science Society of America, Madison, Wisconsin.

• Chen YW, Nelson RL (2004) Identification and characterization of a white-flowered wild soybean plant. Crop Science, 44, 339–342.

• Choi IY, Kang JH, Song HS, Kim NS (1999) Genetic diversity measured by simple sequence repeat variations among the wild soybean, Glycine soja, collected along the riverside of five major rivers in Korea. Genes and Genetic Systems, 74, 169–177.

• Cornuet JM, Piry S, Luikart G, Estoup A, Solignac M (1999) New methods employing multilocus genotypes to select or exclude population as origin of individuals. Genetics, 153, 1989–2000.

• Dong YS, Zhuang BC, Zhao LM, Sun H, He MY (2001) The genetic diversity of annual wild soybeans grown in China. Theoretical and Applied Genetics, 103, 98–103.

• Dorokhov D, Ignatov A, Deineko E et al. (2004) Potential for gene flow from herbicide-resistant GM soybeans to wild soybeans in the Russian Far East. In: Introgression from Genetically Modified Plants into Wild Relatives (eds den Nijs HCM, Bartsch D, Sweet J), pp. 151–161. CAB International, Wallingford, UK.

• Ellstrand NC (2003a) Current knowledge of gene flow in plants: implications for transgene flow. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 358, 1163–1170.

• Ellstrand NC (2003b) Dangerous Liaisons? When Cultivated Plants Mate with Their Wild Relatives. Johns Hopkins University Press, Baltimore, Maryland.

• Ellstrand NC, Prentice HC, Hancock JF (1999) Gene flow and introgression from cultivated plants into their wild relatives. Annual Review of Ecology, Evolution, and Systematics, 30, 539–563.

• Excoffier L, Smouse P, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics, 131, 479–491.

• Fujita R, Ohara M, Okazaki K, Shimamoto Y (1997) The extent of natural cross-pollination in wild soybean (Glycine soja). Journal of Heredity, 88, 124–128.

• Goudet J (2001) fstat, A program to estimate and test gene diversities and fixation indices (version 2.9.3). Available from http://www.unil.ch/izea/softwares/fstat.html Updated from Goudet (1995).

• Haig SM (1998) Molecular contributions to conservation. Ecology, 79, 413–425.

• Hamrick JL, Godt MJW (1989) Allozyme diversity in plant species. In: Plant Population Genetics, Breeding and Genetic Resources (eds Brown AHD, Clegg MT, Kahler AL, Weir BS), pp. 43–63. Sinauer Associates, Sunderland, Massachusetts.

• Hymowitz T, Singh RJ (1987) Taxonomy and speciation. In: Soybeans, Improvement, Production, and Uses (ed. Wilcox JR), pp. 23–48. American Society of Agronomy and Crop Science Society of America, Madison, Wisconsin.

• Jin Y, He T, Lu BR (2003) Fine scale genetic structure in a wild soybean (Glycine soja) population and the implications for conservation. New Phytologist, 159, 513–519.

• Kaga A, Tomooka N, Phuntsho U et al. (2005) Exploration and collection for hybrid derivatives between wild and cultivated soybean: preliminary survey in Akita and Hiroshima Prefectures, Japan. Annual Report on Exploration and Introduction of Plant Genetic Resources, in press (In Japanese with English summary).

• Kamiya M, Kiguchi T (2003) Rapid DNA extraction method from soybean seeds. Breeding Science, 53, 277–279.

• Kiang YI, Chiang YC, Kaizuma N (1992) Genetic diversity in natural populations of wild soybean in Iwate prefecture, Japan. Journal of Heredity, 83, 325–329.

• Kollipara KP, Singh RJ, Hymowitz T (1997) Phylogenetic and genomic relationships in the genus Glycine Willd. based on sequences from the ITS region of nuclear rDNA. Genome, 40, 57–68.

• Kuroda Y, Kaga A, Apa A et al. (2005) Exploration, collection and monitoring of wild soybean and hybrid derivatives between wild soybean and cultivated soybean: based on field surveys at Akita, Ibaraki, Aichi, Hiroshima and Saga Prefectures. Annual Report on Exploration and Introduction of Plant Genetic Resources, in press (In Japanese with English summary).

• Li ZL, Nelson RL (2002) RAPD marker diversity among cultivated and wild soybean accessions from four Chinese provinces. Crop Science, 42, 1737–1744.

• Lu BR (2004) Conserving biodiversity of soybean gene pool in the biotechnology era. Plant Species Biology, 19, 115–125.

• Maughan PJ, Saghai MA, Buss GR (1995) Microsatellite and amplified sequence length polymorphisms in cultivated and wild soybean. Genome, 38, 715–723.

• Nakayama Y, Yamaguchi H (2002) Natural hybridization in wild soybean (Glycine max ssp. soja) by pollen flow from cultivated soybean (Glycine max ssp. max) in a designed population. Weed Biology and Management, 2, 25–30.

• Nei M (1987) Molecular Evolutionary Genetics. Columbia University Press, New York.

• Nei M, Tajima N, Tateno Y (1983) Accuracy of estimated phylogenetic trees from molecular data. Journal of Molecular Evolution, 19, 153–170.

• Oka HI (1983) Genetic control of regenerating success in semi-natural conditions observed among lines derived from a cultivated × wild soybean hybrid. Journal of Applied Ecology, 20, 937–949.

• Palmer RG, Newhouse KE, Graybosch RA, Delannay X (1987) Chromosome structure of wild soybean (Glycine soja Sieb. & Zucc.) accessions from China and the Soviet Union. Journal of Heredity, 78, 243–247.

• Parker PG, Snow AA, Schug MD, Booton GC, Fuerst PA (1998) What molecules can tell us about populations: choosing and using a molecular marker. Ecology, 79, 361–382.

• Peakall R, Smouse PE (2001) genalex version 5: Genetic analysis in Excel. Population genetic software for teaching and research. Australian National University, Canberra, Australia. http://www.anu.edu.au/BoZo/GenAlEx.

• Piry S, Alapetite A, Cornuet JM et al. (2004) geneclass2: a software for genetic assignment and first-generation migrant detection. Journal of Heredity, 95, 536–539.

• Powell W, Morgante M, Doyle JJ et al. (1996) Gene pool variation in genus Glycine subgenus soja revealed by polymorphic nuclear and chloroplast microsatellites. Genetics, 144, 793–803.

• Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics, 155, 945–959.

• Rohlf FJ (2000) ntsys pc, Version 2.02j. Exeter Software, Setauket, New York.

• Schneider S, Roessli D, Excoffier L (2000) arlequin: A software for population genetics data analysis. Genetics and Biometry Laboratory, Department of Anthropology, University of Geneva, Geneva, Switzerland.

• Sekizuka S, Yoshiyama T (1960) Studies on the native wild grasses for fodder. (IV) crop-scientific studies on wild species of Glycine soja. Japan. Journal of Kanto-Tosan Agricultural Experimental Station, 15, 57–73 (in Japanese with English summary).

• Smil V (2000) Magic beans. Nature, 407, 567.

• Smouse PE, Peakall R (1999) Spatial autocorrelation analysis of individual multiallele and multilocus genetic structure. Heredity, 82, 561–573.

• Song QJ, Marek LF, Shoemaker RC et al. (2004) A new integrated genetic linkage map of the soybean. Theoretical and Applied Genetics, 109, 122–128.

• Takezaki N, Nei M (1996) Genetic distances and reconstruction of phylogenetic trees from microsatellite DNA. Genetics, 144, 389–399.

• Tozuka A, Fukushi H, Hirata T et al. (1998) Composite and clinal distribution of Glycine soja. Japan revealed by RFLP analysis of mitochondrial DNA. Theoretical and Applied Genetics, 96, 170–176.

• Weir BS (1996) Methods for discrete population genetic data. In: Genetic Data Analysis II. Sinauer Associates, Sunderland, Massachusetts.

• Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution, 38, 1358–1370.

• Wright S (1965) The interpretation of population structure by F-statistics with special regard to systems of mating. Evolution, 19, 395–420.

• Xu DH, Gai JY (2003) Genetic diversity of wild and cultivated soybeans growing in China revealed by RAPD analysis. Plant Breeding, 122, 503–506.

• Xu DH, Abe J, Gai JY, Shimamoto Y (2002) Diversity of chloroplast DNA SSRs in wild and cultivated soybeans: evidence for multiple origins of cultivated soybean. Theoretical and Applied Genetics, 105, 645–653.


The authors have focused their research on the legume genetic resources for which there is a genetic resources comparative advantage in Japan. Their initial studies focused on the azuki bean (Vigna angularis complex) for which they developed SSR markers and they have used these in population and genome studies. Their genome studies have focused on the domestication syndrome.



Appendix I Go to: ChooseTop of pageIntroductionMaterials and methodsResultsDiscussionAcknowledgementsReferencesAppendix I <
Passport data of wild soybean (Glycine soja) used in this study

Population District, Prefecture Latitude/Longitude Altitude Collection no. Population size Habitat
Soja01 Tohoku, Akita 39°03'01.9"N, 140°25'32.8"E 240 m CED97017 50 m2 Riverbank of Omono river beside paddy
Soja02 Tohoku, Akita 39°33'41.4"N, 140°17'30.0"E 27 m CED2003-35 20 m2 Abandoned paddy
Soja03 Tohoku, Akita 40°11'08.3"N, 140°24'03.9"E 50 m CED97014 16 m2 Roadside beside paddy
Soja04 Tohoku, Akita 39°20'00.2"N, 140°33'38.1"E 110 m CED97016 100 m2 Riverbank of Yokote river
Soja05 Tohoku, Akita 39°38'57.0"N, 140°09'09.6"E 20 m CED2003-32 80 m2 Wasteland beside paddy
Soja06 Tohoku, Akita 39°23'57.0"N, 140°27'49.2"E 41 m CED2003-31 1250 m2 Paddy bund in riverbank of Omono river
Soja07 Tohoku, Aomori 40°38'04.7"N, 140°34'37.7"E 110 m CED97009 50 m2 Wasteland along road (R102)
Soja08 Tohoku, Aomori 40°31'24.8"N, 140°35'02.4"E 90 m CED97012 10 m2 Wasteland along road (R7)
Soja09 Tohoku, Fukushima 37°35'40.3"N, 140°07'51.7"E 645 m CED96101404 — Roadside (R2)
Soja10 Tohoku, Fukushima 36°42'55.3"N, 140°23'06.2"E 145 m CED96100704 — Roadside (R118)
Soja11 Tohoku, Fukushima 37°34'53.1"N, 139°39'33.0"E 265 m CED96101503 — Roadside (R49) beside riverbank and paddy
Soja12 Tohoku, Fukushima 37°19'20.0"N, 139°20'16.4"E 400 m CED96101611 — Roadside (R289)
Soja13 Tohoku, Fukushima 37°33'13.1"N, 139°45'22.5"E 305 m CED96101501 — Roadside (R49), disturbed habitat
Soja14 Tohoku, Fukushima 37°17'16.2"N, 139°28'51.0"E 475 m CED96101613 — Riverbank of Inami river along road (R289)
Soja15 Tohoku, Iwate 39°55'05.3"N, 141°11'41.5"E 300 m CED97007 6 m2 Paddy in fallow
Soja16 Tohoku, Miyagi 38°09'01.5"N, 140°52'24.8"E 25 m CED97003 60 m2 Wasteland along road
Soja17 Tohoku, Yamagata 37°57'02.0"N, 140°12'40.0"E 375 m CED97019 — Roadside beside home garden
Soja18 Hokuriku, Niigata 37°02'38.6"N, 137°55'29.0"E 80 m CED97062 10 m2 Wasteland along river
Soja19 Hokuriku, Niigata 37°50'40.5"N, 139°12'05.0"E 10 m CED97065 1 m2 Paddy bund
Soja20 Hokuriku, Niigata 37°07'35.7"N, 138°23'31.5"E 80 m CED97064 10 m2 Abandoned paddy
Soja21 Hokuriku, Niigata 37°28'07.5"N, 139°00'14.0"E 120 m CED96101607 — Roadside (R290)
Soja22 Kanto, Chiba 35°05'53.0"N, 140°02'31.8"E 170 m CED97206 10 m2 Paddy in fallow
Soja23 Kanto, Chiba 35°14'25.5"N, 139°59'43.9"E 140 m CED97208 (few) Wasteland beside paddy
Soja24 Kanto, Chiba 35°57'58.4"N, 139°52'46.0"E 100 m CED97207 5 m2 Wasteland beside paddy
Soja25 Kanto, Ibaraki 36°30'14.6"N, 140°14'59.2"E 120 m CED96101201 — Roadside (R51), disturbed habitat
Soja26 Kanto, Tochigi 36°43'23.4"N, 140°11'27.3"E 105 m CED96101711 — Riverbank of Yamata river along road (R293)
Soja27 Kanto, Tochigi 36°56'38.1"N, 139°57'52.0"E 370 m CED96101702 — Wasteland along road
Soja28 Kanto, Tokyo 35°38'55.0"N, 139°27'30.9"E 45 m CED96103101 — Riverside of Tama river
Soja29 Chubu, Aichi 34°55'03.2"N, 137°12'47.4"E 40 m CED98081 100 m2 Paddy bund
Soja30 Chubu, Nagano 35°30'50.6"N, 137°48'30.2"E 498 m CED2001-27 200 m2 Wasteland
Soja31 Chubu, Nagano 36°28'36.6"N, 137°51'05.1"E 490 m CED2001-107 120 m2 Wasteland besides field and paddy
Soja32 Chubu, Nagano 36°19'50.8"N, 138°20'50.5"E 611 m CED97023 100 m2 Rocky riverside
Soja33 Chubu, Nagano 35°34'35.7"N, 138°02'57.3"E 715 m CED2001-110 — Beside field
Soja34 Chubu, Nagano 36°15'19.9"N, 138°25'32.7"E 699 m CED97022 (scattered) Rocky riverside
Soja35 Chubu, Nagano 36°05'53.2"N, 137°58'32.3"E 466 m CED97028 (scattered) Roadside beside paddy along canal
Soja36 Chubu, Shizuoka 35°03'51.7"N, 138°56'14.6"E 30 m CED98086 200 m2 Field bund on riverbank
Soja37 Kansai, Hyogo 34°51'45.0"N, 134°22'03.4"E 150 m CED97067 1 m2 Road embarkment
Soja38 Kansai, Hyogo 35°19'48.7"N, 134°52'06.7"E 80 m CED97050 — Wasteland along road
Soja39 Kansai, Kyoto 35°11'02.1"N, 135°20'22.3"E 200 m CED97039 2 m2 Abandoned land beside small road
Soja40 Kansai, Mie 34°04'03.1"N, 136°11'26.9"E 20 m CED97093 15000 m2 Waste riverside
Soja41 Kansai, Mie 34°28'47.3"N, 136°32'41.6"E 100 m CED97098 5 m2 Wasteland beside paddy
Soja42 Kansai, Mie 34°43'47.1"N, 136°28'05.3"E 100 m CED97099 (large pop) Wasteland beside paddy and river
Soja43 Kansai, Nara 34°22'41.2"N, 135°45'54.9"E 90 m CED97073 40 m2 Wasteland beside paddy
Soja44 Kansai, Shiga 35°29'44.8"N, 136°12'17.1"E 125 m CED98007 — Roadside beside paddy and field (soybean)
Soja45 Kansai, Shiga 35°29'51.9"N, 136°12'15.5"E 30 m CED97054 50 m2 Paddy edge slope
Soja46 Kansai, Shiga 35°21'24.6"N, 136°22'14.7"E 135 m CED97037 1000 m2 Riverbank of Amano river
Soja47 Kansai, Wakayama 33°31'53.8"N, 135°48'54.3"E 4 m CED97087 > 300 m2 Riverbank
Soja48 Kansai, Wakayama 33°41'04.3"N, 135°24'52.6"E 12 m CED97084 > 500 m2 Wasteland beside field and road
Soja49 Chugoku Tottori 35°28'50"N, 134°11'24.0"E 10 m CED2002-28 — —
Soja50 Chugoku Tottori 35°26'53.7"N, 134°12'11.2"E 11 m CED2002-29 — —
Soja51 Chugoku, Hiroshima 34°28'30.3"N, 133°18'23.6"E 19 m CED2003-41 60 m2 Abandoned field
Soja52 Chugoku, Hiroshima 34°26'57.3"N, 132°57'47.5"E 45 m CED2003-19 45 m2 Paddy bund
Soja53 Chugoku, Okayama 35°17'27.4"N, 133°41'04.1"E 465 m CED98011 25 m2 Abandoned paddy with black soil
Soja54 Chugoku, Okayama 35°05'08.9"N, 134°01'42.2"E 10 m CED97072 2500 m2 Abandoned paddy
Soja55 Chugoku, Tottori 35°33'32.8"N, 134°16'34.0"E 4 m CED98010 50 m2 Sandy wasteland beside field (scallion)
Soja56 Chugoku, Yamaguchi 34°07'38.6"N, 130°55'36.8"E 50 m CED98018 — Paddy bund
Soja57 Chugoku, Yamaguchi 34°03'38.4"N, 131°17'34.7"E 14 m CED98071 5 m2 —
Soja58 Chugoku, Yamaguchi 34°02'57.4"N, 131°55'31.0"E 30 m CED98075 10 m2 Wasteland along road (R2)
Soja59 Chugoku, Yamaguchi 34°04'11.5"N, 131°02'45.9"E 3 m CED98069 100 m2 Wasteland
Soja60 Shikoku, Ehime 33°22'54.8"N, 132°30'00.6"E 64 m CED98103 — Wasteland along road
Soja61 Shikoku, Ehime 33°11'18.5"N, 132°32'45.6"E 25 m CED98106 20 m2 Paddy bund
Soja62 Shikoku, Kochi 33°01'47.0"N, 132°51'28.5"E 17 m CED98109 > 30 000 m2 Paddy bund
Soja63 Shikoku, Kochi 33°24'29.5"N, 133°16'58.9"E 3 m CED98117 10 000 m2 Wasteland
Soja64 Shikoku, Kochi 33°32'48.4"N, 133°46'17.6"E 11 m CED98126 30 000 m2 Paddy bund
Soja65 Kyushu, Fukuoka 33°21'38.7"N, 130°40'23.6"E 14 m CED98033 — Wasteland along river
Soja66 Kyushu, Fukuoka 33°39'47.0"N, 131°01'36.5"E 10 m CED98068 10 000 m2 Riverbank
Soja67 Kyushu, Fukuoka 33°04'44.3"N, 130°26'06.2"E 25 m CED96111101 — Roadside (R18)
Soja68 Kyushu, Kagoshima 31°45'26.8"N, 130°40'35.2"E 140 m CED98042 — —
Soja69 Kyushu, Kumamoto 32°46'52.6"N, 130°49'08.3"E 80 m CED98038 1000 m2 Riverside beside paddy
Soja70 Kyushu, Miyazaki 32°21'24.4"N, 131°37'12.7"E 8 m CED98054 500 m2 Roadside (R10)
Soja71 Kyushu, Miyazaki 32°00'43.8"N, 131°27'33.7"E 4 m CED98051 10 000 m2 Roadside along field
Soja72 Kyushu, Nagasaki 32°58'45.1"N, 129°07'34.5"E 25 m CED98025 400 m2 Wasteland beside paddy
Soja73 Kyushu, Nagasaki 33°03'15.1"N, 129°05'24.8"E 60 m CED98023 75 m2 Wasteland surrounded by mountains
Soja74 Kyushu, Ohita 33°31'47.9"N, 131°18'02.7"E 8 m CED98061 8 m2 Wasteland beside farmland (soybean)
Soja75 Kyushu, Ohita 33°09'13.6"N, 131°31'08.0"E 40 m CED98059 100 m2 Wasteland beside paddy
Soja76 Kyushu, Saga 33°21'07.1"N, 129°56'00.2"E 50 m CED96111105 — Roadside (R202)
Soja77 Kyushu, Saga 33°18'47.0"N, 130°04'08.0"E 90 m CED96111104 — Roadside (R203)
Appendix II Go to: ChooseTop of pageIntroductionMaterials and methodsResultsDiscussionAcknowledgementsReferencesAppendix IAppendix II <<

Cultivated soybean (Glycine max) used in this study

Abbreviation Cultivated regions‡ (%§) Name of variety History* JP no.†
Max01 Hkk (28) Toyomusume TN 27541
Max02 Hkk (14) Suzumaru TN 67771
Max03 Hkk (23) Toyokomachi TN 53275
Max04 Hkk (6) Otofuke Ousode LR 49455
Max05 Hkk (4) Chuusei Hikarikuro LR 49453
Max06 Hok (0.01) Aonyuudou LR 28311
Max07 Hkk (6) Kitamusume TW 27449
Max08 Hkk (1) Yuuzuru TW 27533
Max09 Hkk (2) Tokachikuro TW 27539
Max10 Hkk (5) Kariyutaka TN (1)
Max11 Hkk (4) Toyohomare TN (1)
Max12 Hkk (2) Yukihomare NW (1)
Max13 Hkk (1) Hayahikari NW 200328
Max14 T (4) Okushirome TW 28030
Max15 T (8) Ohsuzu NW (2)
Max16 T (9) Tanrei TW 29206
Max17 T (23), Hok (0.06) Suzuyutaka TW 68385
Max18 T (19), Hok (0.01) Ryuhou NW (2)
Max19 T (6) Suzukari TN 68386
Max20 T (8) Tachiyutaka TN 68387
Max21 T (13) Miyagi Shirome TW 27886
Max22 T (3), Hok (0.2) Kosuzu TN 68389
Max23 T (0.5), Hok (0.3) Ayakogane NW (3)
Max24 Hok (98), Kt (3), Cb (0.1), Ks (5), CS (1) Enrei TW 28862
Max25 Hok (0.02) Tohoku 41 TN 28151
Max26 Hok (0.03), CS (0.04) Ao Daizu LR 28748
Max27 Kt (15) Nattou Kotsubu TW 29161
Max28 T (3), Kt (56), Cb (0.2), CS (0.4) Tosan 135 TN 49761
Max29 Kt (0.2) Hakkou LR 28954
Max30 Kt (13) Nakasennari TW 29183
Max31 Kt (0.4) Hatayutaka NW (2)
Max32 Kt (2) Ginrei NW (3)
Max33 Kt (4), Cb (92), Ks (5), CS (14), Ky (76) Fukuyutaka TW 29668
Max34 Cb (0.1) Chuu Teppou LR 29207
Max35 Cb (0.1), Ks (16), CS (25), Ky (0.002) Tanba Kuro LR 29359
Max36 Kt (1), Hok (0.7), Cb (0.04), Ks (23) Ohtsuru TN (3)
Max37 Kt (2), Cb (3), Ks (34), CS (33) Tamahomare TW 29184
Max38 Ks (7), CS (0.2), Ky (0.02) Kuro Daizu LR 29535
Max39 Ks (1) Mochi Daizu LR 70093
Max40 Ks (6) Shintanbakuro TW 49594
Max41 Ks (0.1) Tamamasari NW (3)
Max42 Ks (3), CS (8) Nishimusume TW 76377
Max43 Cb (3), Ks (0.01), CS (12), Ky (0.03) Akishirome TW 29669
Max44 CS (0.1) Gin Daizu LR 27579
Max45 CS (0.04) Shirotae TW 28859
Max46 CS (0.004) Akiyoshi TW 29578
Max47 CS (0.03) Sayanami NW (3)
Max48 CS (0.8) Suzukogane NW (3)
Max49 CS (3), Ky (1) Toyoshirome TN 29681
Max50 Ky (0.001) Kyushu 134 TN
Max51 Ky (22) Murayutaka TN (5)
Max52 Ky (0.04) Erusuta NW (4)
Max53 Ky (0.03) Kiyomidori NW (4)
*LR [landrace], TW [varieties released more than 20 (40) years ago], TN [varieties released more than 10 (20) years ago] and NW [newly developed varieties released less than 10 years ago].
†Materials conserved in the gene bank at National Agricultural Research Institute.
(1)(5)Materials obtained from (1)Tokachi Agricultural Experimental Station, (2)National Agricultural Research Center for Tohoku Region, (3)Chushin Agricultural Experimental Station, (4)National Agricultural Research Center for Kyushu Okinawa Region and (5)Saga Agricultural Experimental Center.
‡Hkk (Hokkaido, main northern island), T (Tohoku, northern Honshu), Hok (Hokuriku, Niigata and surrounding regions),
Kt (Kanto, Tokyo and surrounding regions), Cb (Chubu, Nagoya and surrounding regions), Ks (Kansai, Osaka and surrounding regions), CS [Chugoku (southern Honshu) & Shikoku (Shikoku island)], and Ky (Kyushu, main southern island).
§Frequencies in parentheses indicate average percentage of planting area in each region from 1998 to 2002 according to the National Agricultural Statistics of Japan.




--------------------------------------------------------------------------------
Footnotes
*These authors contributed equally to this research.


Molecular Ecology
Volume 15 Page 959 - April 2006














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

QuickSearch in:

Synergy
PubMed (MEDLINE)
CrossRef
for
Authors:
Y. KURODA
A. KAGA
N. TOMOOKA
D. A. VAUGHAN

Keywords:

autocorrelation
cultivated soybean
gene flow
introgression
spatial diversity





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


Received 27 July 2005; revision received 31 October 2005; accepted 22 November 2005


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

Issue online 16 Feb 2006

Affiliations

Crop Evolutionary Dynamics Team, National Institute of Agrobiological Sciences, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8602, Japan


Correspondence

Correspondence: Duncan A. Vaughan, Fax: 81 298 387408; E-mail: duncan@affrc.go.jp


Image Previews


[Full Size]

Fig. 1 Origin in Japan of 77 populations of wild soybean (Glycine soja) analysed.




[Full Size]
Fig. 2 Distribution of allele frequencies between wild and cultivated soybeans for (a) Satt288 showing...




[Full Size]
Fig. 3 Correlograms for spatial pattern of Japanese wild soybeans based on microsatellite variation. ...r...




[Full Size]
Fig. 4 Estimated posterior probability of K (2–45), for wild soybeans (n = 616) and wild and cultivated s...




[Full Size]
Fig. 5 Distribution of individuals consisting of (a) wild and cultivated soybeans, (b) wild soybeans f...




[Full Size]
Fig. 6 Genetic admixture analysis of the nuclear SSR variation between wild and cultivated soybeans. E...




[Full Size]
Table 1 Variation at 20 microsatellite loci in wild and cultivated soybeans




[Full Size]
Table 2 Glycine max specific alleles and G. max predominant alleles in 20 microsatellite loci




[Full Size]
Table 3 Microsatellite variation within populations of Japanese wild soybeans





To cite this article
KURODA, Y., KAGA, A., TOMOOKA, N. & VAUGHAN, D. A. (2006)
Population genetic structure of Japanese wild soybean (Glycine soja) based on microsatellite variation.
Molecular Ecology 15 (4), 959-974.
doi: 10.1111/
j.1365-294X.2006.02854.x

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