Genetic diversity and population structure of Korean wild soybean (Glycine soja Sieb. and Zucc.) inferred from microsatellite markers

Biochemical Systematics and Ecology 71 (2017) 87e96

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Genetic diversity and population structure of Korean wild soybean (Glycine soja Sieb. and Zucc.) inferred from microsatellite markers Muhammad Amjad Nawaz a, Seung Hwan Yang a, Hafiz Mamoon Rehman a, Faheem Shehzad Baloch b, Jeong Dong Lee c, Jong Hyun Park d, **, Gyuhwa Chung a, * a

Department of Biotechnology, Chonnam National University, Chonnam 59626, Republic of Korea Department of Field Crops, Faculty of Agricultural and Natural Science, Abant Izzet Baysal University, 14280 Bolu, Turkey Division of Plant Biosciences, Kyungpook National University, Daegu 702-701, Republic of Korea d National College of Agriculture and Fisheries, Jeonju 54874, Republic of Korea b c

a r t i c l e i n f o

a b s t r a c t

Article history: Received 22 November 2016 Received in revised form 27 January 2017 Accepted 4 February 2017

Korea is considered one of the centers of genetic diversity for cultivated as well as wild soybeans. Natural habitats of wild soybeans are distributed across the Korean mainland and the islands surrounding the Korean peninsula. In this study, the genetic diversity of 100 mainland Korean wild soybean accessions was evaluated by using 42 simple sequence repeat markers covering 17 soybean chromosomes. All analyzed loci were polymorphic and a total of 114 alleles were found. The observed average genetic diversity was low (0.4). The results showed that the 100 selected accessions did not exactly follow the geographical distribution. These results were further confirmed by the phylogeny inferred from five morphological characteristics (i.e., leaf shape, leaf area, plant shape, seed area, and 100-seed weight). Together, the genetic and morphological evaluations suggested conclusively that the selected population did not follow the geographical distribution pattern. The present study could provide useful information for the ex situ conservation and exploitation of wild soybean accessions in soybean improvement stratagems, and will aid in further understanding about the phylogeography of the species in the Korean center of diversity. © 2017 Elsevier Ltd. All rights reserved.

Keywords: Genetic diversity Geographical distribution pattern Microsatellite markers Population structure Wild soybean

1. Introduction Morphological, cytogenetic, and molecular studies have revealed that the wild soybean (Glycine soja Sieb. & Zucc.) is the direct progenitor of domesticated soybeans (Doebley et al., 2006), with the geographical distribution being restricted to East Asia, especially China, the Russian Far East, the Korean Peninsula, and Japan (Singh and Hymowitz, 1999; Boerma and Specht, 2004; Baloch et al., 2010). There is intense debate over whether the domestication of soybeans had occurred as a single event

* Corresponding author. ** Corresponding author. E-mail addresses: [email protected] (J.H. Park), [email protected] (G. Chung). http://dx.doi.org/10.1016/j.bse.2017.02.002 0305-1978/© 2017 Elsevier Ltd. All rights reserved.

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in China or through multiple events in East Asia. Archaeological records, as well as recent genome sequencing data, support a complex domestication history of soybeans (Kim et al., 2010; Lee et al., 2011). However, it is a well-established fact that wild soybeans had originated in the eastern Huanghe Basin in North China (Zhao, 2010). Other reports have also suggested Korea be one of the major centers of soybean origin as well as the center of diversity. Such a diverse area could help in finding useful alleles that might not be available in other regions (Lee et al., 2014). Much of Korean literature dating from the middle of the third century AD has been referenced to have mentioned soybeans. The Nam River Valley and Daundong site near Ulsan are sources of soybean seeds preserved during the Three Kingdom period (Lee et al., 2011). However, these records are mostly associated with cultivated soybeans rather than their wild counterparts. Furthermore, all the archaeological records are mostly a supplementation to the determination of domestication events rather than of origin and dissemination. The mechanism of dispersion of wild soybeans in Korea has not yet been fully explored. Genetic diversity is regarded as the strategic mainstay of biodiversity and diversity within and among wild populations inhabiting an ecosystem (Govindaraj et al., 2015). Clear knowledge about genetic variation could lead to further comprehensive and better understanding of the evolution, natural dissemination, and history of crops, and provide valuable information not only for the selection of most diverse populations but also of suggestions on how the crop could have spread and evolved through an area (Lee et al., 2010). Deciphering the genetic diversity of wild soybeans would provide the push needed for population assessment and monitoring, and thereby support conservation and planning efforts for these valuable wild assets (Govindaraj et al., 2015). Recently, molecular markers have been used to investigate the origin and domestication history of various crops (Baloch et al., 2010, 2016; Guo et al., 2010). Whereas direct measurements of crop dissemination are generally difficult (Bossart and Prowell, 1998; Cain et al., 2000), indirect approaches based on theories of population genetics, such as genetic distance, genetic differentiation, model-based genetic mixture, and spatial autocorrelation, are commonly used (Takezaki and Nei, 1996; Smouse and Peakall, 1999; Pritchard et al., 2000). Simple sequence repeats (SSRs), which are dispersed across all eukaryotic genomes, are considered highly sensitive for the detection of polymorphisms (Cho et al., 2008; He et al., 2012; Alsaleh et al., 2015). Many SSR markers have been mapped to the 20 linkage groups of the soybean genome (Song et al., 2004). Therefore, microsatellite markers can be used to determine genetic diversity as an indirect measure of the natural dissemination and gene flow between cultivated and wild soybeans. The genetic diversity and population structure of Korean wild soybeans have been reported in many studies (He et al., 2012; Kim et al., 2014; Lee et al., 2014). All the reported studies included some representative accessions or populations of a particular area or island(s). In the current study, we selected 100 wild soybean accessions located across the South Korean territory, including all major and minor wild soybean habitats. This selection makes the study unique, and elaborates the natural dissemination of wild soybeans across the land of South Korea via measurement of their genetic diversity.

2. Materials and methods 2.1. Plant material and DNA isolation One hundred Korean germplasm accessions were selected from Chung's Wild Legume Germplasm Collection (Chonnam National University, Korea). The accessions were chosen on the basis of collection sites from all natural habitats of wild soybeans in South Korea. Special care was taken to choose a maximum number of accessions covering all major and minor wild habitats (Table 1, Fig. 1). Young leaf tissues were collected from a single plant of each accession and genomic DNA was extracted by using a modified cetyltrimethylammonium bromide method (Nawaz et al., 2016). The DNA was quantified with the ACTGene ASP-2680 spectrophotometer (CellTAGen, Korea) and was further diluted to a final concentration of 20e30 ng/ mL for SSR-PCR analysis.

2.2. SSR-PCR analysis To investigate the genetic diversity among the selected wild soybean accessions, 50 SSR markers were chosen that spanned all soybean genetic linkage groups. Because of poor amplification and/or no polymorphisms, 8 of the SSR markers were deleted and the remaining 42 were further processed to compare the genetic relationships among the 100 selected accessions (Table 2). The SSR markers were chosen based on a soybean genetic map obtained from SoyBase.org (http:// soybase.org/BARCSOYSSR/index.php). The PCR master mix was prepared as described by Lee et al. (2008). In brief, PCRs were carried out in 0.7 mL tubes in a final 20 mL volume of reaction mixture containing 30e60 ng gDNA, 1
PCR buffer, 0.3 mM of both forward and reverse primers, 0.25 mmol/L dNTPs, and 0.5 U TransTaq-T DNA polymerase (TransGen Biotech, Korea). PCR amplification was conducted on the Takara PCR thermal cycler dice-TP600 device (Takara, Japan) under the conditions of an initial degradation at 95  C (5 min), followed by 35 cycles of 98  C (30 s), X C (30 s), and 72  C (90 s), with a final extension at 72  C 9 (10 min), and thereafter maintaining at 4  C. The amplified PCR products were separated on 2% agarose (w/v) prepared in 0.5
TAE buffer, together with a 100 bp ladder (Bioneer Inc., Korea), and visualized in a UV transilluminator (Davinch Gel Imager; Labplus, Korea).

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Table 1 Selected wild soybean accessions and their collection sites. No.

Accession

Collection site

No.

Accession

Collection site

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

CW13193 CW01012 CW10110 CW10118 CW10336 CW10846 CW10917 CW11065 CW11288 CW11386 CW11977 CW12208 CW12345 CW12376 CW12393 CW12450 CW12497 CW12511 CW12521 CW12586 CW12636 CW12709 CW12731 CW12878 CW12899 CW13139 CW13183 CW13230 CW13274 CW13285 CW13295 CW13319 CW13348 CW13367 CW13385 CW13400 CW13411 CW13440 CW13454 CW13714 CW13749 CW13766 CW13798 CW13818 CW13848 CW13938 CW14131 CW14177 CW14201 CW14210

Gyeongi, Seongnam Jeonnam, Sinan Jeju Jeju Gyeongnam, Sacheon Jeonnam, Goheung Jeonnam, Haenam Jeonnam, Jindo Jeonnam, Gurye Gyeongnam, Goseong Gyeongnam, Hamyang Jeonnam, Muan Jeonnam, Yeongam Jeonnam, Gwangju Jeonbuk, Gochang Jeonbuk, Jeongeup Jeonbuk, Gimje Jeonbuk, Iksan Jeonnam, Hwasun Chungnam, Cheonan Chungnam, Gongju Chungnam, Seocheon Chungnam, Buyeo Jeonnam, Gangjin Jeonbuk, Sunchang Gyeongnam, Geoje Gyeongnam, Namhae Gangwon, Gangneung Gangwon, Samcheok Gyeongbuk, Uljin Gyeongbuk, Yeongdeok Gyeongbuk, Pohang Gyeongbuk, Gyeongju Gyeongi, Hwaseong Gyeongi, Pyeongtaek Chungnam, Yesan Chungnam, Boryeong Jeonbuk, Buan Jeonnam, Yeonggwang Gangwon, Wongju Gangwon, Hwacheon Gangwon, Yanggu Gangwon, Chuncheon Gangwon, Hongcheon Gangwon, Hoengseong Gangwon, Pyeongchang Gyeongi, Ansan Jeonbuk, Namwon Jeonbuk, Wanju Chungnam, Geumsan

51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100

CW14220 CW14237 CW14273 CW14286 CW14293 CW14502 CW14526 CW14549 CW14568 CW14645 CW14672 CW14688 CW14713 CW14730 CW14869 CW14911 CW14926 CW14954 CW14967 CW15002 CW15036 CW15052 CW15090 CW15109 CW15172 CW15188 CW15200 CW15212 CW15370 CW15742 CW15747 CW15820 CW15838 CW15879 CW15929 CW16185 CW16257 CW16307 CW16343 CW16521 CW16532 CW16564 CW16605 CW16640 CW16666 CW16966 CW16981 CW17008 CW17031 CW17192

Chungbuk, Okcheon Chungbuk, Boeun Chungbuk, Goesan Chungbuk, Jeungpyeong Chungbuk, Cheongwon Chungnam, Taean Chungnam, Seosan Chungnam, Dangjin Chungnam, Asan Gyeongbuk, Andong Gyeongbuk, Cheongdo Gyeongnam, Sancheong Gyeongnam, Uiryeong Jeonnam, Jangseong Gyeongnam, Haman Gyeongi, Osan Gyeongi, Yongin Chungbuk, Eumseong Chungbuk, Chungju Chungbuk, Jecheon Chungbuk, Danyang Gangwon, Yeongwol Gyeongi, Gwangju Gyeongi, Namyangju Gyeongi, Paju Gyeongi, Goyang Jeonbuk, Jansu Jeonbuk, Jinan Gangwon, Wonseong Jeonbuk, Jeonju Gyeongnam, Geochang Jeonbuk, Nunsan Jeonnam, Boseong Chungbuk, Jincheon Jeju Gyeongnam, Yangsan Gyeongbuk, Seongju Chungbuk, Chungwon Gyeongnam, Changwon Gyeongnam, Changwon Jeju Chungnam, Daejeon Gyeongbuk, Yeongyang Gyeongbuk, Bonghwa Chungbuk, Yeongdong Gyeongbuk, Sangju Gyeongbuk, Gumi Jeonnam, Gwangyang Gyeongi, Gwangmyeong Gyeongnam, Jinju

2.3. Data analysis The strong, clear, and reproducible amplification products of variable size were considered as different alleles. Those belonging to all accessions under study, amplified by a given primer, were scored as present (1) or absent (0). The utility of the used markers was determined by recording the number of alleles amplified per marker, allelic frequency, polymorphic information content (PIC), resolution power (Rp), Nei's gene diversity, effective number of alleles, and Shannon's information index (SII). PIC values for each locus were measured according to the formula PICi ¼ 2fi (1 e fi), as reported by Guo and Elston (1999), and averaged for all loci of the individual marker. The Rp value of the individual allele was calculated according to the P formula Rp ¼ Ib, where Ib ¼ 1 e {2
(0.5 e p)}, in which p is the proportion of 100 accessions showing the amplified fragments (Prevost and Wilkinson, 1999). The genetic distance among the collected accessions was measured according to the Jaccard index (Jaccard, 1987) for pairwise comparison, based on the proportion of shared bands produced by all primers. A neighbor-joining (NJ) tree was constructed using the computer software program “R.”

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Fig. 1. Geographical distribution of Korean wild soybean accessions used in this study.

2.4. Structure analysis The classical principal coordinate analysis technique was used to evaluate the population structure for polymorphic SSR markers, using the program STRUCTURE (v.2.3.4), and the principal coordinates were visualized by plotting in twodimensional plots. The model-based cluster analysis for the 100 accessions was recorded in STRUCTURE for each value of K (number of subpopulations) from 2 to 9, without prior information of the population. A total of 10,000 iterations were run, of which only successful iterations were recorded by assuming an admixture model in correlation to allelic frequencies. The true K value was measured by an ad hoc quantity constructed on the second order of DK (rate of change of the likelihood function), as given by Evanno et al. (2005); in other words, true K is shown by DK. Grouping on the basis of genetic distance was calculated by R (v.3.1.3).

2.5. Morphological characterization The 100 selected Korean wild soybean accessions were grown in four replications during the growing season of 2015 and 2016. Four mature plants were selected randomly for each accession to record five morphological characteristics (two qualitative and three quantitative) at a particular stage (Table 3). In brief, the leaf shape and plant shape were recorded on a visual basis. The leaf area and seed size were recorded using a commercially available scanner (ScanJet 5370C; Hewlett Packard, USA) at a resolution of 1200 dpi, combined with ImageJ software (Abramoff et al., 2004). The 100-seed weight was recorded using a weighing balance (Mettler Toledo, Switzerland). The phenotypic descriptors for the leaf and plant shapes are provided in Table 3. The mean values of data from four accessions were used for further analysis. The qualitative traits were transformed into binary data, and Jaccard's similarity coefficient was estimated. The morphological data were used to

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Table 2 SSR primers used in the study. No.

Primer

ID

Ch ID

LG

Motif

Tm ( C)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

GlySSR1 GlySSR2 GlySSR3 GlySSR4 GlySSR5 GlySSR7 GlySSR8 GlySSR9 GlySSR10 GlySSR11 GlySSR12 GlySSR13 GlySSR14 GlySSR15 GlySSR16 GlySSR17 GlySSR18 GlySSR19 GlySSR21 GlySSR22 GlySSR26 GlySSR27 GlySSR28 GlySSR29 GlySSR31 GlySSR33 GlySSR34 GlySSR35 GlySSR36 GlySSR37 GlySSR38 GlySSR39 GlySSR40 GlySSR41 GlySSR42 GlySSR43 GlySSR44 GlySSR45 GlySSR46 GlySSR47 GlySSR48 GlySSR49

BARCSOYSSR_02_1330 BARCSOYSSR_03_0222 BARCSOYSSR_03_0471 BARCSOYSSR_04_0002 BARCSOYSSR_04_0264 BARCSOYSSR_04_1025 BARCSOYSSR_05_0393 BARCSOYSSR_06_1422 BARCSOYSSR_08_1257 BARCSOYSSR_09_1411 BARCSOYSSR_10_0465 BARCSOYSSR_10_0519 BARCSOYSSR_10_0562 BARCSOYSSR_10_0680 BARCSOYSSR_11_0719 BARCSOYSSR_11_0948 BARCSOYSSR_11_1441 BARCSOYSSR_12_0525 BARCSOYSSR_16_0355 BARCSOYSSR_17_1573 BARCSOYSSR_20_0274 BARCSOYSSR_20_0348 BARCSOYSSR_20_0413 BARCSOYSSR_12_0986 BARCSOYSSR_10_0717 BARCSOYSSR_13_0527 BARCSOYSSR_14_0827 BARCSOYSSR_10_0394 BARCSOYSSR_08_1076 BARCSOYSSR_10_0968 BARCSOYSSR_17_1205 BARCSOYSSR_07_1003 BARCSOYSSR_02_0076 BARCSOYSSR_04_1461 BARCSOYSSR_08_1029 BARCSOYSSR_13_1796 BARCSOYSSR_17_1337 BARCSOYSSR_01_0740 BARCSOYSSR_11_0008 BARCSOYSSR_01_0206 BARCSOYSSR_01_0362 BARCSOYSSR_01_0907

Gm2 Gm3 Gm3 Gm4 Gm4 Gm4 Gm5 Gm6 Gm8 Gm9 Gm10 Gm10 Gm10 Gm10 Gm11 Gm11 Gm11 Gm12 Gm16 Gm17 Gm20 Gm20 Gm20 Gm12 Gm10 Gm13 Gm14 Gm10 Gm8 Gm10 Gm17 Gm7 Gm2 Gm4 Gm8 Gm13 Gm17 Gm1 Gm11 Gm1 Gm1 Gm1

D1b D1b N N N C1 A1 C2 A2 K O O O O B1 B1 B1 H J D2 I I I H O F B2 O A2 O D2 M D1b C1 A2 F D2 D1a B1 D1a D1a D1a

(AT)26 (TA)21 (AAT)10 (TA)26 (ATT)8 (AGT)5(AAT)15 (AT)18 (AT)11 (ATA)26 (TAA)10 (ATT)16 (TAA)14 (CA)11 (TGT)7g(ATT)20 (TTA)24 (AT)33 (GT)15 (TC)15 (ACA)10 (TAT)20 (ATA)20 (TAT)23tg(TTA)5 (TTA)22 (AAAT)7 (AAT)10 (AAT)10 (AAT)10 (AAT)10g(ATA)6 (AAT)11 (AAT)11 (AAT)11 (AAT)11 (AAT)12 (AAT)12 (AAT)12 (AAT)12 (AAT)12 (AAT)12(AAG)5 (AAT)12(TAA)13 (ATT)14 (TTA)26 (TTA)23

63.2 62.8 63.4 63.1 61 63 63.7 63 64.1 63.7 64.1 62.6 64.6 63.5 63.8 63 68.8 63.9 63.1 63.9 64.1 63.8 64.6 63.8 63.6 63.4 62.4 62.5 64.2 64.4 64.7 64.1 63.7 64.1 64.4 64.7 64.1 63.7 64.6 63.8 63.6 63.4

ID ¼ Microsatellite identity number; Ch ID ¼ Chromosome identity number; LG ¼ Linkage group; Tm ¼ Annealing temperature.

Table 3 Morphological characteristics along with their descriptors. Qualitative traits

Descriptors/Observed phenotypic class

Evaluation phase

Leaf shape Plant shape

1 (oval), 2 (ovate), 3 (elliptical), 4 (lanceolate), 5 (oblanceolate), 6 (oblong), 7 (linear) 1 (complete climbing type), 2 (semi-climbing type), 3 (spreading type), 4 (bushy type)

Ripening stage Ripening stage

Quantitative traits Leaf area Seed size 100-Seed weight

Arithmetic means of four samples Arithmetic means of four samples Arithmetic means of four samples

Ripening stage Ripening stage Ripening stage

construct the phylogenetic tree with DendroUPGMA, a dendogram construction utility that applies the unweighted pair group method with arithmetic mean (http://genomes.urv.cat/UPGMA/). 3. Results Fifty microsatellites primers were applied to 100 Korean wild soybean accessions for initial screening. Three markers did not amplify any product and five SSR markers were non-polymorphic. Therefore, only 42 SSR markers were subjected to further evaluation of the selected germplasm. The number of alleles observed among the 42 SSR primers ranged from 1 (from primer GlySSR17) to 9 (from primers GlySSR9, GlySSR31, GlySSR34, GlySSR37, GlySSR38, GlySSR44, GlySSR45, GlySSR47, and

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GlySSR49) in total, and 114 polymorphic alleles were observed, with an average of 2.71 (Table 4). The observed polymorphism rate was 100%. The genetic diversity per SSR marker varied from 0.13 (GlySSR16 and GlySSR37) to 0.55 (GlySSR38), with an average of 0.4. Mean values of SII per SSR marker ranged from 0.25 (GlySSR37) to 0.69 (GlySSR45), with an average of 0.6. Maximum and minimum PIC values of 0.98 and 0.33 were revealed using GlySSR16 and GlySSR37, respectively, with an average of 0.77. The discriminatory potential of the marker, as represented by Rp, ranged from 0.3 (GlySSR47) to 5.6 (GlySSR8), with an average of 2.29. The allelic frequency ranged from 0.05 to 0.81. Moreover, 43.85% of the alleles exhibited allelic frequencies of 0.25e0.50, whereas 1.75%, 21.81%, and 32.45% exhibited allelic frequencies of 0.75e1.0, 0e0.25, and 0.50e0.75, respectively (Table 4). A pairwise genetic distance matrix was deliberated according to Jaccard's similarity coefficient. The NJ tree was developed by using Jaccard's genetic distance, as shown in Fig. 2A. The 100 Korean wild soybean accessions were divided into three clusters, colored brown, green, and blue according to NJ analysis. The two large clusters (green and blue) were further subdivided into a different number of subgroups. The first cluster (highlighted brown) comprised three accessions, whereas the other two clusters comprised 41 (highlighted green) and 56 (highlighted blue) accessions. The constructed NJ tree indicated that the Korean wild soybean does not strictly obey the geographical distribution pattern between and among the groups and subgroups. In the STRUCTURE analysis, the number of subgroups varied from 1 to 9 and the highest K value was 2. Analysis of the 100 accessions revealed that there were

Table 4 Diversity parameters revealed by 42 simple sequence repeat (SSR) markers. Primer

A

Allelic frequency

Diversity parameters PIC

Rp

H

SII

GlySSR1 GlySSR2 GlySSR3 GlySSR4 GlySSR5 GlySSR7 GlySSR8 GlySSR9 GlySSR10 GlySSR11 GlySSR12 GlySSR13 GlySSR14 GlySSR15 GlySSR16 GlySSR17 GlySSR18 GlySSR19 GlySSR21 GlySSR22 GlySSR26 GlySSR27 GlySSR28 GlySSR29 GlySSR31 GlySSR33 GlySSR34 GlySSR35 GlySSR36 GlySSR37 GlySSR38 GlySSR39 GlySSR40 GlySSR41 GlySSR42 GlySSR43 GlySSR44 GlySSR45 GlySSR46 GlySSR47 GlySSR48 GlySSR49

3 3 6 3 3 2 7 1 2 5 2 3 2 4 2 9 3 3 3 2 2 3 2 6 1 2 1 3 2 1 1 4 4 2 2 2 1 1 2 1 2 1

0.66, 0.38, 0.54 0.57, 0.50, 0.38 0.55, 0.62, 0.40, 0.28, 0.23, 0.50 0.55, 0.54, 0.50 0.64, 0.31 0.09, 0.66, 0.28, 0.57 0.66, 0.17 0.37, 0.36, 0.54, 00.72, 0.05 0.54, 0.52, 0.72 0.28, 0.29 0.28, 0.64, 0.76, 0.09, 0.14 0.44, 0.12, 0.12, 0.34, 0.48, 0.19 0.76, 0.34, 0.44 0.21, 0.51, 0.06 0.66, 0.36 0.55, 0.35 0.07, 0.67, 0.36 0.34, 0.44 0.48, 0.28, 0.28, 0.36 0.28, 0.38 0.4 0.27, 0.23, 0.31 0.36, 0.67 0.81 0.74 0.48, 0.81, 0.51, 0.21, 0.34, 0.44, 0.42, 0.51 0.5, 0.35 0.57, 0.24 0.6 0.48 0.27, 0.36 0.16 0.62, 0.44 0.59

0.70 0.75 0.80 0.87 0.71 0.75 0.81 0.66 0.76 0.83 0.73 0.63 0.91 0.70 0.98 0.89 0.87 0.70 0.89 0.71 0.78 0.80 0.84 0.78 0.86 0.88 0.84 0.92 0.70 0.33 0.44 0.66 0.84 0.77 0.81 0.81 0.63 0.77 0.89 0.97 0.71 0.64

3.19 2.95 4.7 2.03 3.19 1.91 5.6 1.2 1.7 3.7 1.6 3.6 1.8 4.1 0.5 4.8 2 3.1 1.6 2.1 1.8 2.4 1.6 5.35 0.73 1.35 0.81 1.65 2.1 1.6 1.5 4.5 3 1.9 1.7 1.6 1.2 1 1.3 0.3 2.1 1.2

0.44 0.48 0.39 0.45 0.48 0.37 0.46 0.45 0.34 0.41 0.20 0.41 0.45 0.38 0.24 0.13 0.44 0.40 0.33 0.43 0.48 0.34 0.49 0.45 0.49 0.47 0.50 0.43 0.42 0.13 0.55 0.40 0.46 0.49 0.49 0.42 0.43 0.50 0.46 0.31 0.46 0.44

0.64 0.67 0.57 0.64 0.67 0.55 0.66 0.64 0.53 0.59 0.34 0.60 0.64 0.56 0.40 0.48 0.63 0.58 0.50 0.62 0.67 0.51 0.68 0.64 0.68 0.66 0.62 0.62 0.61 0.25 0.42 0.58 0.65 0.68 0.68 0.62 0.62 0.69 0.65 0.49 0.65 0.63

Total Average

114 2.71

e 0.77

e 2.29

0.4

0.6

0.09, 0.14, 0.52

0.30, 0.40, 0.62, 0.40

0.52, 0.052

0.34 0.66, 0.17, 0.21, 0.51, 0.061, 0.07

0.38, 0.63, 0.60

0.42 0.51

PIC ¼ Polymorphism information content; Rp ¼ Resolution power; H ¼ Genetic diversity; SII ¼ Shannon's information index.

Fig. 2. (A) Neighbor-joining analysis of 100 Korean wild soybean accessions. All accessions were divided into three clusters; represented in different colors. (B) UPGMA Dendrogram of selected accessions for five morphological characteristics. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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primarily two basic gene pools in South Korea (Supplementary Fig. 1). A maximum number of Korean wild soybean accessions showed admixture from two populations, as presented in the structure analysis. The phylogenetic tree based on morphological data showed that the selected accessions did not follow the geographical distribution (Fig. 2B). The UPGMA tree divided all selected accessions into two clusters, which further formed seven wellresolved clades.

4. Discussion Genetic diversity is a reliable tool for inferring the history, gene flow, and domestication time of any crop and its wild ancestors (Baloch et al., 2015). The other objectives of studying genetic diversity are the identification of genetic groups for germplasm retention, and identification of genes responsible for important phenotypes that are useful in breeding (Li et al., 2010). Genetic diversity can reveal useful information about the biodiversity and diversity of a species, and greatly helps in maintaining the wild reservoir for use in future systematic studies and for understanding evolutionary relationships (Govindaraj et al., 2015). The fundamental assignment in genetic diversity is to act as a key for the survival of any species in ever-changing environments. Furthermore, the genetic diversity of landraces/germplasms collected from wild habitats and centers of domestication can reveal useful information regarding patterns of evolutions, genetic structure, and geographical and socioeconomic factors that affected the crop during its evolution and domestication. Apart from this, wild accessions possess high variations at inter/intra-population levels, which ultimately provides a buffering capacity against ever-growing stochastic variations in the environment (Baloch et al., 2015). The wild soybean is considered as the direct progenitor of cultivated soybeans, and there has been a reduction in genetic diversity during the events of domestication (Lam et al., 2010). This situation renders the wild soybean as an excellent genetic resource, and implies its usefulness in providing knowledge about the phylogenetics and evolution of other species in the genera as well as in soybean improvement breeding programs. The molecular diversity of the wild soybean has been studied by using available molecular markers such as random amplified polymorphic DNAs, amplified fragment length polymorphisms, SSRs, and single nucleotide polymorphisms (Li et al., 2010; Lee et al., 2010; Chung et al., 2014). We used 42 SSR markers to find the genetic diversity among 100 wild soybean accessions in order to gain additional understanding of soybean domestication and guiding collection for ex situ conservation. The selected population makes our study unique, in that we considered all the natural wild habitats of soybean in mainland Korea. Previous studies on the topic used different sample sizes located in the mainland and islands of South Korea. For example, Choi et al. (1999) used a sample population (57 accessions) collected from riverbanks in South Korea. Such population can only reveal the structure and diversity of the selected locations and cannot be generalized to Korean wild soybeans. Similarly, two studies (Lee et al., 2008, 2010) that dissected the genetic diversity of the Korean wild soybean used wild accessions from the mainland and southern islands of Korea, respectively. Both these studies used rather random populations and lacked a complete representative population from South Korea. We underpinned the diversity parameters of 100 Korean wild soybean accessions collected from mainland natural habitats. The wild soybean population in our study showed a lower genetic diversity value (H ¼ 0.4) than that obtained in previous investigations reported by Cho et al. (2008) (0.65), Lee et al. (2008) (H ¼ 0.85), Lee et al. (2010, 2014) (0.71), and Kim et al. (2014) (0.882). The lower genetic diversity in our report may be attributed to genetic drift (Gao and Gao, 2016) in wild soybean populations in the Korean peninsula, as the geographical pattern of this peninsula does not greatly help in gene flow. The lower number of alleles (114) detected in this study is another possible reason for the lower genetic diversity. A different number of markers, use of differently located markers, different accessions, and different locations could also possibly affect the differences observed in the genetic diversity values. Pairwise genetic distance scores were used for the construction of phylogeny among the 100 selected wild soybean accessions. NJ and principal coordinate analysis did not cluster the data into geographical locations in a specific manner (Fig. 2A and Supplementary Fig. 1). The 100 accessions were assigned to three clusters that were further divided into subgroups. This clustering is in line with all previously carried out studies, except for the one conducted by Kim et al. (2014) that reported two main clusters in the Korean wild soybean. There was no exact pattern in subgrouping of the accessions according to the area or collection site. However, most of the accessions followed the geographical pattern slightly in subgrouping (Fig. 2). The distinct genetic diversity in the Korean territory may not essentially follow the latitudinal or longitudinal gradient, and may behave differently than their geographical locations (Burnham et al., 2002). The somewhat disturbed subgrouping pattern reveals that there was human intervention during the natural dissemination of wild soybeans in the Korean mainland natural habitats (Wichmann et al., 2009). The morphological data also confirmed that the selected Korean wild soybean accessions do not exactly follow the geographical pattern. The low level of genetic diversity revealed by SSR markers in this study reveals that the Korean wild soybean has been spread both naturally and by humans. Lee et al. (2010) also explained that the geographical distribution was not perfectly associated with the accession. Similar reports were observed for peas, mung beans, chickpeas, lentils, and maize (Sangiri et al., 2007; Baloch et al., 2015). Hence, we report that Korean mainland wild soybean have low genetic diversity and do not follow geographical distribution pattern. This study will greatly help in ex situ conservation of wild soybean.

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Ethical statement We testify that this work has not been published in whole or in part elsewhere and the manuscript is not currently being considered for publication in another journal. All authors have been personally and actively involved in substantive work leading to the manuscript, and will hold themselves jointly and individually responsible for its content. All authors have explicitly consented to submit the aforementioned work to Biochemical Systematics and Ecology. Acknowledgements This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2015R1D1A1A09060925). Appendix A. Supplementary data Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.bse.2017.02.002. References Abramoff, M.D., Magelhaes, P.J., Ram, S.J., 2004. Image processing with image. J. Biophot. Int. 11, 36e42. € Alsaleh, A., Baloch, F.S., Derya, M., Azrak, M., Kilian, B., Ozkan, H., Nachit, M., 2015. Genetic linkage map of Anatolian durum wheat derived from a cross of Kunduru-1149
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