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Genetic Diversity of Wild Soybean (Glycine soja Sieb. and Zucc.) Accessions from South Korea and Other Countries

^a Univ. of Missouri-Delta Center, P.O. Box 160, Portageville, MO 63873
^b Syngenta Seeds, Inc., 317 330th Street, Stanton, MN 55018
^c Div. of Plant Biosciences, Kyungpook National Univ., Daegu, 702-701, Republic of Korea
^d Div. of Plant Sciences, Univ. of Missouri-Columbia, Columbia, MO 65211
^e Dep. of Agronomy, Iowa State Univ., Ames, IA 50011
^f Korea Atomic Energy Research Institute, 1266 Singjeong-dong Jeong-Eup Jeon-Buk, 580-185, Republic of Korea

^* Corresponding author (shannong{at}missouri.edu).

	ABSTRACT

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
Wild soybean (Glycine soja Sieb. and Zucc.) is an important source of genetic variation for introducing useful traits into cultivated soybeans [Glycine max (L.) Merr.]. Little is known about genetic diversity within South Korean wild soybeans and how they differ genetically from other G. soja lines originating from other regions. Forty-six simple sequence repeat markers covering the 20 soybean linkage groups were used to estimate genetic diversity among 274 wild soybean accessions from South Korea (210), China (34), Japan (25), and eastern Russia (5) and three cultivated checks. Glycine soja populations from South Korea, China, and Japan all had high genetic diversity with indexes of 0.849, 0.818, and 0.804, respectively. Cluster analyses grouped the 274 accessions into three genetic groups. Cluster I and II consisted of 85 accessions, with 79 of 85 from Korea, only one from China, and five from Japan. Cluster III contained 192 of the 274 G. soja accessions. Nearly all of the accessions from China and Japan, all from Russia, and 131 of 210 from South Korea were assigned to Group III. However, there was no difference between populations for genetic diversity for South Korea and China. Although it is a very small country, South Korea is a major center of diversity for wild soybeans and potentially a source of useful genes not found in other parts of the world.

Abbreviations: CB, Chungcheungbuk-do • CN, Chungcheongnam-do • GB, Gyeongsangbuk-do • GG, Gyeonggi-do • GN, Gyeongsangnam-do • GW, Gangwon-do • JB, Jeollabuk-do • JJ, Jeju-do • JN, Jeollanam-do • LG, linkage group • PCR, polymerase chain reaction • SSR, simple sequence repeat

	INTRODUCTION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
WILD SOYBEAN (Glycine soja Sieb. and Zucc.), hypothesized to be the direct progenitor of cultivated soybean [Glycine max (L.) Merr.], is widely distributed in Eastern Asia including Korea, China, Japan, Taiwan, and eastern Russia near the Chinese border (Hymowitz and Singh, 1987). Wild soybean accessions originating from different geographical regions could have important genetic differences. Genetic distance studies among wild soybeans have been conducted for accessions derived from three different gene pools—Korea, China, and Japan. Genetic diversity in wild soybean populations has been evaluated by comparing variation in agronomic traits (Park and Hur, 1979; Dong et al., 2001; Kim et al., 2003; Lee et al., 2005; Kim and Park, 2005; Yoon et al., 2005) and by using molecular markers including random amplified polymorphic DNA, restriction fragment length polymorphism, simple sequence repeat (SSR), and single nucleotide polymorphism (Yu and Kiang, 1993; Chung et al., 1995; Tozuka et al., 1998; Choi et al., 1999; Li and Nelson, 2002; Xu et al., 2002; Hyten et al., 2006).

Restriction fragment length polymorphism analyses of mitochondrial DNA from G. soja genotypes from China (1019 accessions from 349 locations), Japan (753 accessions from 215 locations), and Korea (212 accessions from 102 locations) were classified within 18, 14, and 8 cytoplasmic groups, respectively (Shimamoto et al., 1998; Tozuka et al., 1998; Han and Abe, 1999). Six chloroplast SSRs detected 23 variants (alleles) and disclosed 52 haplotypes among the accessions by comparing chloroplast DNA of 143 wild soybean accessions; 73 from China, 48 from Japan, 14 from South Korea, and 8 from eastern Russia (Xu et al., 2002). Yu and Kiang (1993) compared genetic variation at the 35 loci for 17 isozymes and Kunitz trypsin inhibitor among 172 G. soja soybean accessions from six South Korean regions. They found high polymorphism (77.1%) and high variation among 72 of 94 alleles and concluded that South Korea is a major center of genetic variation for these traits.

The soybean genome is a partially diploidized tetraploid. Approximately half of the soybean genome is repetitive (Shoemaker et al., 2004). The homeologous regions in the soybean genome can make it difficult to study and to construct a map of the genome. However, many SSR markers have been mapped on the 20 linkage groups of the soybean genome. A total of 606 SSR loci were mapped from three populations (Cregan et al., 1999), and 1015 SSR loci were mapped and incorporated into one map (Song et al., 2004). Recently, information for the soybean genome was updated in SoyBase (http://soybase.org; verified 5 Feb. 2008) and in the Soybean GBrowse Database (http://soybeangenome.siu.edu; verified 5 Feb. 2008) for soybean scientists to access current information to conduct their studies.

Several studies have been conducted using SSRs to estimate genetic diversity within wild soybean and determine the genetic relationship among populations of G. max and G. soja. Maughan et al. (1995) reported that five SSRs detected 79 alleles among 94 accessions (62 for G. max and 32 for G. soja). Among the 79 alleles detected, 16 occurred in both subspecies, 10 were observed only in G. max, and 53 were observed only in G. soja. The genetic diversity value (H) of G. max was 0.55 and that of G. soja was 0.87 indicating greater diversity in wild soybeans than cultivated soybeans. Choi et al. (1999) used seven SSR markers to evaluate genetic diversity among 57 wild soybean accessions collected along five major rivers in South Korea. The number of alleles ranged from four to nine per SSR and the genetic diversity index for the population was high, averaging 0.86. Cho et al. (2006) used seven SSRs to compare the genetic variation between 81 G. soja and 130 G. max soybean accessions from South Korea. One hundred forty-four different alleles were detected among accessions in this study. The range in number of different alleles detected at each locus was greater in wild soybean with an average diversity value of 0.88, compared to 0.69 for cultivated soybeans. Previous studies show that genetic diversity of the Korean wild soybean population is high. However, not all linkage groups have been covered in a comprehensive study. No studies have been conducted over all 20 soybean linkage groups to measure genetic diversity among South Korean G. soja accessions. Also, there are few data that compare the diversity and relatedness of wild soybean accessions for South Korea, China, Japan, and eastern Russia.

In this study we used 46 SSR markers covering all 20 linkage groups to evaluate genetic diversity and to compare the genetic relationship among 274 G. soja lines collected from Korea (210 lines), China (34 lines), Japan (25 lines), and eastern Russia (five lines).

	MATERIALS AND METHODS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
Plant Materials and DNA Isolation
Two hundred seventy-four G. soja accessions and three G. max accessions were used in this study (Table 1 ). These accessions (Fig. 1 ) were selected to cover origins from all geographic regions of South Korea (210 lines), China (34 lines), Japan (25 lines), and eastern Russia (five lines).

View larger version (33K): [in this window] [in a new window]   Figure 1. Geographical distribution and number of G. soja accessions collected from South Korea (210 accessions), China (34 including Taiwan), Japan (25), and Russia (5) used in this study. GW, Gangwon-do; GG, Gyeonggi-do; CB, Chungcheongbuk-do; CN, Chungcheongnam-do; GB, Gyeongsangbuk-do; GN, Gyeongsangnam-do; JB, Jeollabuk-do; JN, Jeollanam-do; JJ, Jeju-do; HK, Hokkaido; TK, Tohoku; KT, Kanto; CHB, Chubu; CK, Chugoku; KS, Kansai; SK, Shikoku; KYS, Kyushu. Stars on the map indicate the capital of each country.

Samples of leaf tissue were collected from a single plant of each accession. DNA was extracted from the leaf sample using the CTAB (hexadecyltrimethyl ammonium bromide) method described by Keim et al. (1988).

SSR Analysis
The soybean SSRs used in this study were developed from Williams soybean, then tested on a set of 10 soybean genotypes. Primer sets that produced multi-alleles in any of the 10 genotypes were discarded (Cregan and Quigley, 1997; Cregan et al., 1999). Cregan et al. (1999) developed an integrated genetic linkage map of the soybean genome using 606 SSR markers.

A total 80 SSR markers based on the genetic map (Cregan et al., 1999) covering the 20 soybean linkage groups were selected for genotyping the 277 accessions. An average of four markers with a high genetic diversity index (average = 0.694) were selected per linkage group (LG). Some markers (34 of 80 SSRs) showed poor amplification therefore, 46 SSR markers labeled with 6-FAM (blue), VIC (green), NED (yellow), and PET (red) were used to compare diversity among the G. soja accessions in this study (Table 2 ). Polymerase chain reaction (PCR) amplifications were done using a 10-µL volume containing 30 to 60 ng genomic DNA, 1.5 mM magnesium chloride, 300 µM of each dNTP, 2 µL of GeneScript 10x Taq polymerase buffer (GeneScript Corp., Piscataway, NJ), 0.75 U of GeneScript Taq DNA polymerase, and 0.3 µM forward and reverse primer. Polymerase chain reaction amplifications were conducted on either a GeneAmp model 9700 thermocyclers (AME Bioscience, Toroed, Norway) or Ep Mastercycler384 (Eppendorf, Westbury, NY). The PCR protocol was 95°C for 5 min followed by 35 cycles of 95°C for 30 s, 47°C for 30 s, and 72°C for 45 s, followed by a final extension at 72°C for 15 min.

Data Analysis
Allele size data was used to estimate genetic diversity index (H), number of alleles per locus, number of multi-allele accessions, number of null allele accessions, and frequency of each allele. The genetic diversity index (H) based on allele frequency was calculated for each SSR using Nei's unbiased statistics (Nei, 1973, 1987): H = 1 – P_i², where P_i is the frequency of the ith allele. The genetic distance was calculated from the proportion of shared alleles (Bowcock et al., 1994) and the frequency of each allele for the 46 loci.

Number of alleles detected and genetic diversity index are influenced by sample size (Leberg, 2002). The number of accessions from South Korea in this study was 6.2 times larger than from China. Random repeat sampling was conducted seven times in the South Korean population by the function of RAND of the Microsoft (Redmond, WA) Excel program based on a uniform sample size of n = 34 accessions. Diversity was then compared between each of the seven 34 random accession samples from South Korea and the 34 accessions from China. All analyses of the alleles for the parameters were conducted by the PowerMarker version 3.0 (Liu and Muse, 2005). The genetic distance matrix was subjected to a cluster analysis with the neighbor-joining method. The MEGA version 3.1(Kumar et al., 2004) was used to construct a genetic tree.

	RESULTS AND DISCUSSION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
SSR Variation among Wild Soybean Accessions
A total 1172 alleles were detected among the 274 wild accessions and the allele size of the 46 SSR loci is shown in Table 2. Forty-four SSR markers amplified for the three G. max check varieties were slightly different in size compared to previous studies. Williams, Minsoy, and A81-356022 showed sizes of 260, 260, and 294 bp, respectively, at Satt382 in this study, but amplified at 259, 259, and 295 bp, respectively, in previous reports. The same three genotypes for Satt475 amplified at 248, 235, and 248 bp versus 250, 238, and 250 in previous studies (www.soybase.org). The range in number of alleles for the 46 SSRs across the G. soja genotypes was from 9 to 65 with an average 25.5 alleles per SSR marker (Table 2). The fewest alleles, 9 and 11, were detected at Satt271 and Satt171, respectively on LG D1b. The highest number of alleles, 65 and 64, were detected at Satt226 on LG D2 and Satt590 on LG M, respectively (Table 2). Of the 46 SSRs tested in this study, only nine SSRs used to measure genetic diversity in G. soja were in common with other studies. Three SSRs (Satt242 on LG K, Satt373 on LG L, and Satt565 on LG C1) were in common with the study by Wang and Takahata (2007). Two SSRs, Satt197 on LG B1 and Satt141 on LG D1b, were also used by Cho et al. (2006). Finally, four SSRs used in our study Satt231 on LG E, Satt294 on LG C1, Satt423 on LG F, and Satt509 on LG B1 (Table 2) were examined by Kuroda et al. (2006). We detected more alleles for eight of nine SSRs in common with other reports except for Satt565 on LG C1. Wang and Takahata (2007) found 24 alleles for Satt565 in 105 wild soybean accessions, but we found 19 alleles for the same SSR in this study. Selecting more accessions from a wide range of geographic origins for this study would allow more allele detection per SSR compared to other studies. Leberg (2002) showed that the number of alleles and the genetic diversity index are influenced by sample size.

There were many multi-alleles (two or more alleles per SSR on each accession) and null alleles detected among accessions for the 46 SSRs used in this study (Table 2). Nearly all SSR markers had a null allele (verified by repeat PCRs) in one or more accessions except Satt197, Satt172, Satt268, Satt314, Satt440, and Satt182 (Table 2). The mean number of accessions with a null allele for each SSR was 9.4. Sixty-nine wild soybeans (17 from Korea, 30 from China, 18 from Japan, and 4 from Russia) had a null allele at Satt141 on LG D1b. There were 32 accessions with a null allele at Satt294 on LG C1, and 21 accessions with a null allele at Satt405 (LG J) and Satt584 (LG N). The average number of accessions with null alleles for each SSR varied within the four different countries of origin. An average of 2.7, 6.8, 5.2, and 2.0% of the accessions originating from Korea, China, Japan, and Russia, respectively, had null alleles over all the 46 SSRs. All SSR markers used in this study detected multi-alleles. The range in number of accessions with multi-alleles across the 46 SSRs across all LGs was from eight for Satt184 on LG D1a to 69 for Satt301 on LG D2 with an average of 29.6 (Table 2).

Multi-alleles in SSR genotyping can be detected by (i) extracting DNA from several combined leaf samples in a nonpure line, (ii) amplifying primers at more than one locus, (iii) using contaminated DNA, and (iv) using a heterozygous accessions. Since DNA was extracted from a single plant of each accession, multi-alleles detected in this study are based on the assumption that primers were amplified at more than one locus or some wild soybean accessions were heterozygous from a higher natural cross-pollination rate in G. soja than in G. max (Fujita et al., 1997). In comparative studies with G. max, wild soybean showed more multi-alleles and null alleles among accessions per SSR than G. max. Wang et al. (2006) reported only two accessions with more than one allele at a single locus and the 62 accessions possessed at least one null allele at 32 of 60 SSRs among 129 G. max accessions.

The average genetic diversity index (H) across accessions from all countries for the 46 SSRs was 0.858 and ranged from 0.297 to 0.973 (Table 2). The diversity indexes (H) observed among the 274 wild soybean accessions evaluated in this study were higher than the diversity index reported for Chinese (0.807 for 45 accessions) and Japanese (0.810 for 60 accessions) wild soybeans (Wang and Takahata, 2007). Our results were similar to those of Choi et al. (1999), which showed a genetic diversity value of 0.85, but slightly lower than values H = 0.87 and H = 0.88 reported by Maughan et al. (1995) and Cho et al. (2006), respectively.

Abe et al. (2003) examined genetic diversity of Asian G. max germplasm. Five (Satt236, Satt197, Satt063, Satt038, and Satt431) of the 46 SSRs were in common with our study. In our study with G. soja, four (Satt236, Satt197, Satt063, and Satt431) of five SSRs detected more alleles and had wider allele size ranges and higher genetic diversity than those of G. max. Based on this comparison, there is greater genetic diversity in G. soja than cultivated soybeans. This is consistent with former studies (Maughan et al., 1995; Cho et al., 2006; Kuroda et al., 2006; Hyten et al., 2006).

Our results strongly support that G. soja has more diversity with a greater number of different alleles per locus than cultivated soybeans. Hyten et al. (2006) compared genetic diversity between wild and cultivated soybean using sequence analysis of 111 fragments from 102 genes in four soybean populations. They reported that the landraces (G. max) retained 66% ( = expected heterozygosity per nucleotide site) and 49% ( = the number of polymorphic sites in a genotypic sample corrected for sample size) of the nucleotide diversity found in G. soja. Haplotype diversity was significantly lower in the landraces than in wild soybean. They concluded that during domestication of G. max from G. soja, the low sequence diversity present in the wild soybean species was halved with 81% of the rare alleles being lost and 60% of the genes exhibiting significant change in allele frequency. Similar results were reported for domestication of other species. Buckler et al. (2001) reported domestication has reduced genetic diversity for a number of grass species including Zea mays L., Sorghum bicolor (L.) Moench, Orzya sativa L., and Avena sativa L. to less than 40%.

SSR Variation and Genetic Diversity within South Korean Wild Soybean Accessions
The number of alleles detected from 46 SSR loci across the 210 accessions averaged 23.3 (Table 3 ). This was higher than those from other reports. An average of 16.7 alleles was detected by seven SSR loci from 81 Korean wild soybeans (Cho et al., 2006). Choi et al. (1999) detected an average 11.7 alleles from seven SSR loci in 57 Korean wild soybeans. Among 46 SSR loci used in this study, two SSR loci (Satt197 and Satt141) were included in the research presented by Cho et al. (2006). Cho et al. (2006) found 13 alleles for Satt197 and 12 alleles for Satt141, while we found 32 alleles and 17 alleles for the same SSRs, respectively. The mean number of alleles detected per SSR were similar (9.0 to 11.4) for each Korean province except significantly lower (5.5) for JJ (Table 4 ). The provinces represented by a relatively low number of accessions showed a lower mean number of alleles per SSR (Table 4).

The genetic distance values (data not shown) among the 210 Korean accessions ranged from 0.0111 between K61 and K58 to 1.000 with an average of 0.851 (Table 3). There were 11 pairs of the 210 Korean wild soybean accessions that had a genetic distance score of 1.000 (data not shown). This indicates that all loci detected by these 46 SSR markers are different between these pairs of accessions. The 11 G. soja pairs were K18 and K194, K24 and K181, K42 and K51, K51 and K52, K55 and K195, K64 and K78, K78 and K172, K78 and K194, K105 and K110, K127 and K194, and K127 and K208 (Table 1). An increased number of SSRs are needed to estimate the genetic difference for these 11 G. soja pairs. The genetic distance among accessions between the nine Korean provinces ranged from 0.3803 (CN and GB) to 0.6288 (GW and JJ) with an average of 0.4919 (data not shown).

The geographical features of the nine South Korean provinces consist of mountains in the east region including GW, GB, GN, and some part of GG and CB, and a relatively flat area for the west region including GG, CB, CN, JB, and JN in the Korean peninsula. JJ is an isolated island off the southern coastline of South Korea, which is considered the only subtropical region in South Korea.

A cluster analysis was conducted using the genetic distance matrix among the accessions based on the proportion of shared alleles (Fig. 2 ). The G. soja accessions originating from the nine South Korean provinces were assigned to three groups. Each of the three groups was generally separated according to three geographic regions of South Korea. Group A included accessions generally originating from provinces CB, GG, and GW in northern South Korea. Group B consisted of accessions from GB and CN in central South Korea. Group C included accessions from JB, JJ, JN, and GN in southern South Korea. Cho et al. (2006) divided Korean accessions they studied into two main groups of the five largest provinces excluding JJ. Accessions from Gyeonggi (which is GG in this study) were assigned to Group I and accessions in Group II were assigned to two subgroups. The first subgroup is Jelloa (the combined regions JN and JB in this study) and Chungcheong (the combined regions CN and CB in this study). The second subgroup is Gangwon (GW in this study) and Gyeongsang (the combined regions GN and GB in this study). Clustering of the accessions was consistent with geographical differences of the eastern mountainous and the western plain areas of South Korea. In our study, however, the three different clusters seem to be based on different latitude; northern, central, and southern provinces of South Korea. We derived lines based on nine regions of South Korea. However, Cho et al. (2006) grouped selected lines based on five regions of South Korea for cluster analysis. Thus, different results for cluster analyses between the two studies were likely a result of using different numbers of regions of South Korea. Although our results were different from Cho et al. (2006), it is clear from all studies, that South Korean G. soja accessions show high diversity. Accessions from each province showed a high genetic diversity index (H > 0.8) except JJ (Table 4). Geographically South Korea is a diverse country and G. soja is native to the country. Korea (33°6'–43°1'N, 124°11'–131°52'E) is bordered on the north by China with the other three sides bordered by ocean. The land area of Korea is 70% mountainous and has both large and small rivers. Because of this diverse landscape and lack of intervention by humans, conditions in Korea have been favorable for development and maintenance of genetic diversity among G. soja populations.

View larger version (14K): [in this window] [in a new window]   Figure 2. Dendrogram representing genetic relationships among G. soja accessions originating from nine South Korean provinces: GW, Gangwon-do; GG, Gyeonggi-do; CB, Chungcheongbuk-do; CN, Chungcheongnam-do; GB, Gyeongsangbuk-do; GN, Gyeongsangnam-do; JB, Jeollabuk-do; JN, Jeollanam-do; JJ, Jeju-do. The dendrogram was constructed from the genetic distance values among accessions between and within provinces. Digits on lines represent branch lengths.

It seems that the number of alleles and diversity index were affected by number of accessions studied. This is consistent with previous research in which genetic diversity index was higher where more accessions were compared with fewer accessions (Leberg, 2002). In our study more accessions were studied from Korea (210) than China (34) or Japan (25). If similar numbers of accessions from each country were studied, better comparisons could be made for mean number of alleles and genetic diversity index among wild soybean populations from the three countries.

The Korean G. soja population had a high mean number of alleles per SSR, genetic diversity index, and average genetic distance between accessions compared to the other countries. To contrast diversity among a similar number of accessions from Korea, China, and Japan, the 210 Korean accessions were randomly sampled to select seven sets of 34 accessions which is the number of Chinese accessions evaluated in this study. The seven Korean subpopulations also showed a high mean number of alleles per SSR (13.3) and a high genetic diversity index of 0.829 (Table 3). Although number of alleles per SSR was higher for the Korean population, diversity indexes among accessions were similar for all three countries. Probabilities from a t test showed no significant difference between diversity indexes for each of the seven Korean subpopulations and the index for the Chinese population (Table 3). China is much larger than Korea and the 34 Chinese wild soybean accessions used in this study were collected from a wide geographic area in China. However, the Korean wild soybean subpopulations collected from a much smaller geographic area (Fig. 1) showed as much genetic diversity as the Chinese G. soja accessions.

Cluster Analysis among Wild Soybean Accessions
The dendrogram derived from genetic distance among accessions showed that the 277 accessions formed three major groups (Fig. 3 ). Group I (from J3 to K48) consisted of 54 accessions: one Chinese (C32), four Japanese, and 49 Korean accessions (Table 5 ). Group II (from K102 to K81) contained 31 accessions: one Japanese (J23) and 30 Korean accessions (Table 5). Group III consisted of 192 of 277 accessions (from J14 to K66) (Table 5). Group III showed 131 Korean, 33 Chinese, 20 Japanese, and 5 Russian accessions and the three G. max checks. Group III was divided into seven subgroups. Subgroup III-a (from J14 to C3) contained 22 accessions: 7 Korean, 11 Chinese, and one Japanese and the three G. max checks. The three cultivated soybeans were clustered in Subgroup III-a with K78 and K199. Williams was most closely related to A81-356022 (genetic distance 0.6196). Minsoy was most related to the wild soybean K199. Subgroup III-b (from K165 to R1) had 14 accessions: nine Korean, two Chinese, two Japanese, and one Russian. Only 32 Korean accessions (from K15 to K32) were clustered in Subgroup III-c. Forty-six accessions (from K105 to K45) were in Subgroup III-d: 23 Korean, 9 Chinese, and 14 Japanese. Subgroup III-e (from K25 to K52) had 27 accessions: 22 Korean, 3 Chinese, and 2 Russian. Subgroup III-f had 29 of the 277 accessions: 18 Korean, 7 Chinese, 2 Japanese, and 2 Russian. The last, Subgroup III-g (from C18 to K66), had 23 accessions: 21 Korean, one Chinese, and one Japanese.

View larger version (77K): [in this window] [in a new window]   Figure 3. A dendrogram representing the genetic relationship among 274 G. soja accessions from Korea (210), China (34), Japan (25), and Russia (5) and three G. max cultivars constructed from the genetic distance between accessions. Digits on the lines represent branch lengths.

Even though South Korea is very small in land area compared to China, diversity indexes among G. soja accessions were not significantly different between the two countries. Thus, the small country South Korea, like China, is a major center of diversity for wild soybeans and is a potential source of useful soybean genes not found in other world regions.

Further study is needed to understand the relationship among G. soja accessions from China which is considered the primary soybean center of origin and South Korea, North Korea, and Japan comparing a similar number of accessions from each country.

Because much genetic diversity was lost in the process of domestication of G. max (Hyten et al., 2006), conservation and use of G. soja is very important in finding new genes to improve economically important traits in soybean such as seed yield and resistance to biotic and abiotic stress.

	ACKNOWLEDGMENTS

 
The authors are grateful to Dr. K.U. Kim (Kyungpook Nation University, Korea), Dr. E.G. Cho (Research & Development Bureau, Rural Development Administration, Korea), and Dr. R.L. Nelson (USDA-ARS, USA) for providing the soybean accessions used in this study. We also appreciate Dr. S.K. Park (Kyungpook Nation University, Korea) and Dr. Y.S. Jeong (Soyventure Co. Ltd, Korea) for their suggestions to conduct this study. This study funded by the Missouri Soybean Merchandising Council, the National Center for Soybean Biotechnology, and the National Science Foundation's Major Research Instrumentation program (Award 0526687).

	NOTES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.

Received for publication May 4, 2007.

	REFERENCES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 

• Abe, J., M. Ohara, and Y. Shimamoto. 1992. New electrophoretic mobility variations observed in wild soybean (G. soja) distributed in Japan and Korea. Soybean Genet. Newsl. 9 :63–72.
• Abe, J., D.H. Xu, Y. Suzuki, and A. Kanazawa. 2003. Soybean germplasm pools in Asia revealed by nuclear SSRs. Theor. Appl. Genet. 106 :445–453.[Web of Science][Medline]
• Bowcock, A.M., A. Ruíz-Linares, J. Tomfohrde, E. Minch, J.R. Kidd, and L.L. Cavalli-Sforza. 1994. High resolution human evolutionary trees with polymorphic microsatellites. Nature 368 :455–457.[CrossRef][Medline]
• Buckler, E.S., IV, J.M. Thornsberry, and S. Kresovich. 2001. Molecular diversity, structure, and domestication of grasses. Genet. Res. 77 :213–218.[CrossRef][Web of Science][Medline]
• Cho, Y.H., M.S. Yoon, J. Lee, H.J. Baek, C.Y. King, T.S. Kim, E.G. Cho, and H.B. Lee. 2006. Diversity and geographical relationships by SSR marker in subgenus Soja originated from Korea. Korean J. Crop Sci. 51 :239–247.
• Choi, I.Y., J.H. Kang, H.S. Song, and N.S. Kim. 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 Genet. Syst. 74 :169–177.[CrossRef][Web of Science]
• Chung, S.D., H.W. Huh, and M.G. Chung. 1995. Genetic diversity in Korea populations of Glycine soja (Fabaceae). J. Plant Biol. 38 :39–45.
• Cregan, P.B., T. Jarvik, A.L. Bush, R.C. Shoemaker, K.G. Lark, A.L. Kahler, N. Kaya, T.T. VanToai, D.G. Lohnes, J. Chung, and J.E. Specht. 1999. An integrated genetic linkage map of the soybean genome. Crop Sci. 39 :1464–1490.[Abstract/Free Full Text]
• Cregan, P.B., and C.V. Quigley. 1997. Simple sequence repeat DNA marker analysis. p. 173–185. In G. Caetano-Anolles and P.M. Gresshoff (ed.) DNA markers: Protocols, applications, and overviews. John Wiley & Sons, New York.
• Dong, Y.S., B.C. Zhuang, L.M. Zhao, H. Sun, and M.Y. He. 2001. The genetic diversity of annual wild soybeans grown in China. Theor. Appl. Genet. 103 :98–103.[CrossRef][Web of Science]
• Fujita, R., M. Ohara, K. Okazaki, and Y. Shimamoto. 1997. The extent of natural cross-pollination in wild soybean (Glycine soja). J. Hered. 88 :124–128.[Abstract/Free Full Text]
• Gorman, M.B. 1984. An electrophoretic analysis of the genetic variation in the wild and cultivated soybean germplasm. Diss. Abstr. Int. B 44 :11.
• Han, O.K., and J. Abe. 1999. RFLPs of mitochondrial DNA in Korean wild soybeans. Korean J. Crop Sci. 44 :243–247.
• Hymowitz, T., and R.J. Singh. 1987. Taxonomy and speciation. p. 23–48. In J.R.Wilcox (ed.) Soybeans: Improvement, production, and uses. 2nd ed. ASA, CSSA, SSSA, Madison, WI.
• Hyten, D., Q. Song, Y. Zhu, I.Y. Choi, R.L. Nelson, J.M. Costa, J.E. Specht, R.C. Shoemaker, and P.B. Cregan. 2006. Impacts of genetic bottlenecks on soybean genome diversity. Proc. Natl. Acad. Sci. USA 103 :16666–16671.[Abstract/Free Full Text]
• Keim, P., T.C. Olson, and R.C. Shoemaker. 1988. A rapid protocol for isolating soybean DNA. Soybean Genet. Newsl. 15 :150–152.
• Kim, K.C., and E.H. Park. 2005. Variation of protein, oil contents and fatty acid composition of Korean wild soybean (Glycine soja Sieb. & Zucc.) seeds. (In Korean, with English abstract.) Korean J. Crop Sci. 50 (S):118–122.
• Kim, K.U., T.D. Kang, J.H. Lee, I.J. Lee, D.H. Shin, Y.H. Hwang, S.U. Kim, and H.M. Kim. 2003. Physio-ecological characteristics of wild soybeans (Glycine soja) collected throughout Korea and their response to glyphosate. (In Korean, with English abstract.) Korean J. Weed Sci. 23 :153–159.
• Kumar, S., K. Tamura, and M. Nei. 2004. MEGA3: Integrated software for molecular evolutionary genetics analysis and sequence alignment. Brief. Bioinform. 5 :150–163.[Abstract/Free Full Text]
• Kuroda, Y., A. Kaga, N. Tomooka, and D.A. Vaughan. 2006. Population genetic structure of Japanese wild soybean (Glycine soja) based on microsatellite variation. Mol. Ecol. 15 :959–974.[Medline]
• Leberg, P.L. 2002. Estimating allelic richness: Effects of sample size and bottlenecks. Mol. Ecol. 11 :2445–2449.[CrossRef][Medline]
• Lee, J.D., Y.H. Yoon, I.K. Chung, S.K. Park, and Y.H. Hwang. 2005. A new Glycine soja germplasm accession with green seed-coat color. Breed. Sci. 55 :21–25.[CrossRef]
• Li, Z., and R.L. Nelson. 2002. RAPD marker diversity among cultivated and wild soybean accessions from four Chinese provinces. Crop Sci. 42 :1737–1744.[Abstract/Free Full Text]
• Liu, K., and S.V. Muse. 2005. PowerMarker: An integrated analysis environment for genetic marker analysis. Bioinformatics 21 :2128–2129.[Abstract/Free Full Text]
• Maughan, P.J., M.A. Saghai Maroof, and G.R. Buss. 1995. Microsatellite and amplified sequence length polymorphisms in cultivated and wild soybean. Genome 38 :715–723.[Medline]
• Nei, M. 1973. Analysis of gene diversity in subdivided populations. Proc. Natl. Acad. Sci. USA 70 :3321–3323.[Abstract/Free Full Text]
• Nei, M. 1987. Molecular evolutionary genetics. Columbia Univ. Press, New York.
• Park, H., and S.N. Hur. 1979. Growth habit and protein content of various wild soybean strains. (In Korean, with English abstract.). J. Plant Biol. 22 :1–4.
• Shimamoto, Y., H. Fukushi, J. Abe, A. Kanazawa, J. Gai, Z. Gao, and D. Xu. 1998. RFLPs of chloroplast and mitochondrial DNA in wild soybean, Glycine soja, growing in China. Genet. Resour. Crop Evol. 45 :433–439.[CrossRef]
• Shoemaker, R.C., P.B. Cregan, and L.O. Vodkin. 2004. Soybean genomics. p. 235–263. In H.R. Boerma and J.E. Specht (ed.) Soybeans: Improvement, production, and uses. 3rd ed. ASA, CSSA, SSSA, Madison, WI.
• Song, Q.J., L.F. Marek, R.C. Shoemaker, K.G. Lark, V.C. Concibido, X. Delannay, J.E. Specht, and P.B. Cregan. 2004. A new integrated genetic linkage map of the soybean. Theor. Appl. Genet. 109 :122–128.[CrossRef][Web of Science][Medline]
• Southern, E.M. 1979. Measurement of DNA length by gel electrophoresis. Anal. Biochem. 100 :319–323.[CrossRef][Web of Science][Medline]
• Tozuka, A., H. Fukushi, T. Hirata, M. Ohara, A. Kanazawa, T. Mikami, J. Abe, and Y. Shimamoto. 1998. Composite and clinal distribution of Glycine soja in Japan revealed by RFLP analysis of mitochondrial DNA. Theor. Appl. Genet. 96 :170–176.[CrossRef][Web of Science]
• Wang, K.J., and Y. Takahata. 2007. A preliminary comparative evaluation of genetic diversity between Chinese and Japanese wild soybean (Glycine soja) germplasm pools using SSR markers. Genet. Resour. Crop Evol. 54 :157–165.[CrossRef]
• Wang, L., R. Guan, L. Zhangxiong, R. Chang, and L. Qiu. 2006. Genetic diversity of Chinese cultivated soybean released by SSR markers. Crop Sci. 46 :1032–1038.[Abstract/Free Full Text]
• Xu, D.H., J. Abe, J.Y. Gai, and Y. Shimamoto. 2002. Diversity of chloroplast DNA SSRs in wild and cultivated soybeans: Evidence for multiple origins of cultivated soybean. Theor. Appl. Genet. 105 :645–653.[CrossRef][Web of Science][Medline]
• Yoon, H.T., M.J. Seo, S.L. Kim, S.O. An, and S.J. Kim. 2005. Variation of seed component contents in wild soybean (Glycine soja Sieb. & Zucc.). (In Korean, with English abstract.) Korean J. Crop Sci. 50 (S):108–111.
• Yu, H., and Y.T. Kiang. 1993. Genetic variation in South Korean natural populations of wild soybean (Glycine soja). Euphytica 68 :213–221.[CrossRef][Web of Science]

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