1. Genetic Diversity and Association Analysis of Protein and Oil Content in Food-type Soybean Ainong Shi, Pengyin Chen, Bo Zhang, and Anfu Hou University of Arkansas

2. Food-type soybean has generated tremendous public interests in various soyfoods - Large seeds for tofu, soymilk, and edamame - Small seeds for natto and bean sprouts Background

3. Few have reported the genetic structure and diversity of food-type soybean. Seed protein and oil contents are two main quality traits in soybean breeding effort. Association analysis based on linkage disequilibrium (LD) has recently become an alternative approach to map QTL in plants. SSR markers have been widely used to analyze genetic diversity and detect QTLs through linkage mapping and association analysis in many crops including soybean.

4. Objective To analyze genetic diversity in 105 food-type soybeans using 65 SSRs To conduct association analysis of protein and oil content in soybean

5. 105 food-type soybeans collected from Japan, South Korea, and 6 states of USA 65 SSRs located on 20 soybean MLGs used for genotying in the 105 soybeans Allele diversity including allele number, allele frequency, gene diversity, and PIC value calculated by PowerMarker 3.25 AMOVA implemented in Arlequin 3.11 Genetic structure analyzed by Structure 2.2 Association tests run with the mixed linear model method in TASSEL 2.0.1 Materials and Methods

6. Phenotypic and genotypic data Protein: 42.9% (36.96-50.0%) Oil: 19.0% (13.8-22.5%) r = -0.67 (protein-oil) Allele number: 10 (5-16) Gene diversity: 0.82 (0.57-0.91) PIC: 0.79 (0.42-0.89) Results

7. 105 food-type soybeans divided into three clusters (I, II and III), and further into six groups Cluster I: S. Korea and Japan Cluster II: USA lines Cluster III: S. Korea The genetic background in USA food-type lines were different from those lines from Japan and South Korea. Genetic Diversity

8. Cluster I: I-S and I-SJ Cluster II: II-N, II-MK and II-IO Group I-S: 7 Southern Korea lines Group I-SJ: 10 South Korea, 3 Japan, and 1 Missouri lines Group II-N: 3 North Dakota, 2 South Korea, and 1 Virginia lines. Group II-MK: 8 Missouri, 3 Kansas, and 1 Virginia lines Group II-IO: 18 Iowa, 12 Ohio, 1 Missouri and 1 Virginia lines Cluster III: 26 South Korea, 2 Japan, and 2 Virginia. Two lines, K32 (KS4302sp) and O105 (HF-AG5381) not clustered into any group

9. 18 Iowa + 12 (out of 14) lines clustered into the group II-IO 3 (4) Kansas + 10 Missouri lines into II-MK 3 North Dakota lines into II-N 5 Virginia lines into III, II-MK, II-N, and II-IO. 5 Japanese lines into I-SJ and III 46 Korean lines into four groups: 8 to I-S, 10 to I-SJ, 2 to II-N, and 26 to III

10. AMOVA for geographic origin in the 105 soybeans Source of variation d.f.Sum of squares Variance components Percentage variation P value Among Countries2237.840.3800.99< 0.001 Among states within USA 5337.834.05610.60< 0.001 Within lines973281.3433.8388.410.327 Total1043857.0038.26 The largest variance due to within soybean lines (88.41%) Little variance due to among countries (less than 1%) The variance among the six states of USA (10.60%) indicated genetic diversity existed among the states

11. Linkage disequlibrium (LD) value (R 2, above diagonal line) and probability value (P, below diagonal line) for 65 markers in 105 soybean lines LD parameter R 2 was significant for most of the pairwise comparisons among 65 SSR markers.

12. SSR marker LGPos a (cM) PR2R2 Marker/QTL reported in around the region MarkerPos (cM)Reference Satt300 A130.937.37E-050.191A329_230.30Mansur et al. (1996) Satt187 A254.922.09E-060.456Prot 17-448.5 – 49.5SoyBase Satt228 A2154.116.85E-050.244A505_1132.30Brummer et al. (1997) Satt453 B1123.967.06E-050.227 - - - Satt577 B26.058.55E-040.093A352_129.20Lee et al. (1996) Satt556 B273.214.49E-050.229B142_143.60Lee et al. (1996) Satt281 C240.303.43E-070.424 - - - Satt147 D1a108.893.24E-040.237Satt07777.50Csanadi et al. (2001) Satt459 D1b118.621.64E-060.303Satt459118.62Hyten et al. (2004) Satt268 E44.251.56E-050.258Satt26844.27Jun et al. (2007) Satt146 F1.922.44E-070.359 - - - Satt586 F3.636.42E-040.189 - - - Satt352 G50.534.61E-040.353Satt56457.32Jun et al. (2007) Satt571 I18.501.01E-110.433Satt57118.50Jun et al. (2007) Satt49636.40Chung et al. (2003) Satt523 L27.923.42E-060.169A023_136.70Diers et al. (1992) Satt229 L93.893.54E-040.276Satt00692.00Mansur et al. (1996) Satt306 M80.021.23E-040.143Satt55195.45Jun et al. (2007) Satt358 O5.441.66E-040.233Prot 21-54.44 – 6.44SoyBase Satt345 O59.439.30E-050.337Satt47871.10Speeht et al. (2001) 19 putative QTLs for protein content (15 previously mapped using linkage analysis and 4 new identified)

13. SSR marker LGPos (cM) PR2R2 Marker/QTL reported in around the region MarkerPos (cM)Reference Satt300 A130.931.53E-070.388A329_230.30Mansur et al. (1996) Satt59131.10Hyten et al. (2003) Satt187 A254.922.66E-040.194T153_1 A111_1 50.42 67.33 Mansur et al. (1993) Satt228 A2154.117.78E-080.365A505_1132.30Brummer et al. (1997) Satt453 B1123.969.73E-040.144 - - - Satt577 B26.055.23E-070.275A242_133.10Diers et al. (1992) Satt281 C240.301.15E-070.344Satt43238.00Orf et al. (1999) Satt147 D1a108.894.92E-050.311Satt147108.89Hyten et al. (2003) Satt459 D1b118.627.32E-050.169Satt274116.35Panthee et al. (2005) Satt146 F1.921.94E-080.395 - - - Satt114 F63.698.17E-040.280Satt51071.40Specht et al. (2001) Satt571 I18.509.95E-080.315Satt57118.50Jun et al. (2007) Satt23936.94Nichols et al. (2006) Satt49636.40Chung et al. (2003) Satt229 L93.892.89E-080.435Satt22993.89Hyten et al. (2003) Satt358 O5.446.62E-040.242 - - - 13 putative QTLs for oil content (10 previously mapped using linkage analysis and 3 new identified)

14. Summary 105 soybean lines were divided into three clusters and further clustered into six groups. A negative correlation was obtained between protein and oil contents (r = -0.67). 13 SSR markers distributed on 11 MLGs were identified to be significantly associated with oil content (p < 0.001 and R 2 % = 14.4 – 43.5). 19 SSR markers distributed on 14 MLGs were identified with protein content (P < 0.001, R 2 % = 14.3 – 45.6).

15. Thank you!