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RESEARCH ARTICLE

Mapping QTLs for 100-seed weight in an interspecific soybean cross of Williams 82 (Glycine max) and PI 366121 (Glycine soja)

Krishnanand P. Kulkarni A , Sovetgul Asekova A , Dong-Ho Lee A , Kristin Bilyeu B , Jong Tae Song A and Jeong-Dong Lee A C
+ Author Affiliations
- Author Affiliations

A School of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea.

B USDA-ARS, Plant Genetic Research Unit, 110 Waters Hall, University of Missouri-Columbia, Columbia, MO 65211, USA.

C Corresponding author. Email: jdlee@knu.ac.kr

Crop and Pasture Science 68(2) 148-155 https://doi.org/10.1071/CP16246
Submitted: 8 July 2016  Accepted: 31 January 2017   Published: 28 February 2017

Abstract

Seed weight can be an important component for soybean quality and yield. The objective of the present study was to identify quantitative trait loci (QTLs) for 100-seed weight by using 169 recombinant inbred lines (RILs) derived from the cross Williams 82 × PI 366121. The parental lines and RILs were grown for four consecutive years (2012–15) in the field. The seeds were harvested after maturity, dried and used to measure 100-seed weight. Analysis of variance indicated significant differences among the RILs for 100-seed weight. The environment had significant effect on seed-weight expression as indicated by the genotype × environment interaction. QTL analysis employing inclusive composite interval mapping of additive QTLs implemented in QTL IciMapping (Version 4.1) identified nine QTLs (LOD >3) on chromosomes 1, 2, 6, 8, 13, 14, 17 and 20. The individual QTLs explained phenotypic variation in the range 6.1–12.4%. The QTLs were detected in one or two environments, indicating major influence of the growing environment on seed-weight expression. Four QTLs identified in this study, qSW-02_1, qSW-06_1, qSW-13_1 and qSW-14_1, were found to be new QTLs. The findings of the study may be helpful to reveal the molecular genetic basis of the seed-weight trait in soybean.

Additional keywords: QTL mapping, seed quality, wild soybean.


References

Agarwal M, Shrivastava N, Padh H (2008) Advances in molecular marker techniques and their applications in plant sciences. Plant Cell Reports 27, 617–631.
Advances in molecular marker techniques and their applications in plant sciences.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXjsVClt70%3D&md5=51b1aa02559b08e665cb4301bcd3f724CAS |

Akond M, Liu S, Shoener L, Anderson JA, Kantarzi SK, Maksem K, Song Q, Wang D, Wen Z, Lightfoot DA, Kassem MA (2013) SNP-Based genetic linkage map of soybean using the SoySNP6K Illumina Infinium BeadChip genotyping array. Journal of Plant Genome Sciences 1, 80–89.

Brim CA, Cockerham CC (1961) Inheritance of quantitative characters in soybean. Crop Science 1, 187–190.
Inheritance of quantitative characters in soybean.Crossref | GoogleScholarGoogle Scholar |

Burton JW (1987) Quantitative genetics: results relevant to soybean breeding. In ‘Soybeans: improvement, production and uses’. 2nd edn. Agronomy Monograph 16. (Ed. JR Wilcox) pp. 211–247. (ASA, CSSA, SSSA: Madison, WI, USA)

Collard BC, Mackill DJ (2008) Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 363, 557–572.
Marker-assisted selection: an approach for precision plant breeding in the twenty-first century.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXisFCmu7c%3D&md5=8ed9fcf15c96e13693ef8e2b087e91e4CAS |

Cregan PB, Jarvik T, Bush AL, Shoemaker RC, Lara KG, Kahler AL, Kaya N, VanToai TT, Lohnes DG, Chung J, Specht JE (1999) An integrated genetic linkage map of the soybean genome. Crop Science 39, 1464–1490.
An integrated genetic linkage map of the soybean genome.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK1MXmvVWmtb8%3D&md5=22e90c736a9b7c991adc0c487e11af61CAS |

Csanádi G, Vollmann J, Stift G, Lelley T (2001) Seed quality QTLs identified in a molecular map of early maturing soybean. Theoretical and Applied Genetics 103, 912–919.
Seed quality QTLs identified in a molecular map of early maturing soybean.Crossref | GoogleScholarGoogle Scholar |

Davey JW, Hohenlohe PA, Etter PD, Boone JQ, Catchen JM, Blaxter ML (2011) Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nature Reviews. Genetics 12, 499–510.
Genome-wide genetic marker discovery and genotyping using next-generation sequencing.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXnslShu7k%3D&md5=8dc4a71e6590a3ce155e38bbad84bd33CAS |

Dekkers JC, Hospital F (2002) The use of molecular genetics in the improvement of agricultural populations. Nature Reviews. Genetics 3, 22–32.
The use of molecular genetics in the improvement of agricultural populations.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38XhsV2gsbw%3D&md5=4ea3e36c8daa76a4c5067e12a15f942aCAS |

Edwards D, Batley J (2010) Plant genome sequencing: applications for crop improvement. Plant Biotechnology Journal 8, 2–9.
Plant genome sequencing: applications for crop improvement.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXptlaktw%3D%3D&md5=57834288cf46eb674f03737f8be93962CAS |

Ha BK, Kim HJ, Velusamy V, Vuong TD, Nguyen HT, Shannon JG, Lee JD (2014) Identification of quantitative trait loci controlling linolenic acid concentration in PI 483463 (Glycine soja). Theoretical and Applied Genetics 127, 1501–1512.
Identification of quantitative trait loci controlling linolenic acid concentration in PI 483463 (Glycine soja).Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2cXnslejs7k%3D&md5=443471905aa0e2318cf4b173211956d4CAS |

Han Y, Li D, Zhu D, Li H, Li X, Teng W, Li W (2012a) QTL analysis of soybean seed weight across multi-genetic backgrounds and environments. Theoretical and Applied Genetics 125, 671–683.
QTL analysis of soybean seed weight across multi-genetic backgrounds and environments.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38XhtFWhsLfK&md5=670e408ef8c8cbad468f26abd8f30a51CAS |

Han Y, Xie D, Teng W, Sun J, Li W (2012b) QTL underlying developmental behaviour of 100-seed weight of soybean. Plant Breeding 131, 600–606.
QTL underlying developmental behaviour of 100-seed weight of soybean.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38XhsVeitL3O&md5=472241daac97f2d70d8ebccf43030c89CAS |

Hwang TY, Sayama T, Takahashi M, Takada Y, Nakamoto Y, Funatsuki H, Hisano H, Sasamoto S, Sato S, Tabata S (2009) High-density integrated linkage map based on SSR markers in soybean. DNA Research 16, 213–225.
High-density integrated linkage map based on SSR markers in soybean.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXpvF2lsr8%3D&md5=e7e6c7c688eb91c6fb610a71fdde4c99CAS |

Hyten DL, Choi I-Y, Song Q, Specht JE, Carter TE, Shoemaker RC, Hwang E-Y, Matukumalli LK, Cregan PB (2010) A high density integrated genetic linkage map of soybean and the development of a 1536 Universal Soy Linkage Panel for quantitative trait locus mapping. Crop Science 50, 960–968.
A high density integrated genetic linkage map of soybean and the development of a 1536 Universal Soy Linkage Panel for quantitative trait locus mapping.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXmsVWhu74%3D&md5=1bb8a21c327ba2dcdd3a580b2da22fc8CAS |

Kato S, Sayama T, Fujii K, Yumoto S, Kono Y, Hwang TY, Kikuchi A, Takada Y, Tanaka Y, Shiraiwa T, Ishimoto M (2014) A major and stable QTL associated with seed weight in soybean across multiple environments and genetic backgrounds. Theoretical and Applied Genetics 127, 1365–1374.
A major and stable QTL associated with seed weight in soybean across multiple environments and genetic backgrounds.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2cXmsFansL0%3D&md5=fcba6c099bdb12b4b28669f8f30eca0cCAS |

Kim HK, Kim YC, Kim ST, Son BG, Choi YW, Kang JS, Park YH, Young-Son C, In-Soo C (2010) Analysis of quantitative trait loci (QTLs) for seed size and fatty acid composition using recombinant inbred lines in soybean. Journal of Life Science 20, 1186–1192.
Analysis of quantitative trait loci (QTLs) for seed size and fatty acid composition using recombinant inbred lines in soybean.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXhtVOmtrs%3D&md5=adf636283c81e310eafa56b968cff19fCAS |

Kosambi DD (1943) The estimation of map distances from recombination values. Annals of Eugenics 12, 172–175.
The estimation of map distances from recombination values.Crossref | GoogleScholarGoogle Scholar |

Kulkarni KP, Kim M, Shannon JG, Lee JD (2016) Identification of quantitative trait loci controlling soybean seed weight in recombinant inbred lines derived from PI 483463 (Glycine soja) × Hutcheson (G. max). Plant Breeding 135, 614–620.
Identification of quantitative trait loci controlling soybean seed weight in recombinant inbred lines derived from PI 483463 (Glycine soja) × Hutcheson (G. max).Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC28Xhs1SjtrfN&md5=77ca80cf37d834ae3796739e6c10df93CAS |

Lande R, Thompson R (1990) Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124, 743–756.

Lee SH, Bailey MA, Mian MAR, Carter TE, Ashley DA, Hussey RS, Parrott WA, Boerma HR (1996) Molecular markers associated with soybean plant height, lodging, and maturity across locations. Crop Science 36, 728–735.
Molecular markers associated with soybean plant height, lodging, and maturity across locations.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK28XjvVSns7Y%3D&md5=1a4fc9459fd1ddb33981f94ffb8f194cCAS |

Lee JS, Yoo MH, Jung JK, Bilyeu KD, Lee JD, Kang S (2015a) Detection of novel QTLs for foxglove aphid resistance in soybean. Theoretical and Applied Genetics 128, 1481–1488.
Detection of novel QTLs for foxglove aphid resistance in soybean.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2MXntVCiurk%3D&md5=dd1bcb110be301cc19cb0af688d5d7c2CAS |

Lee S, Freewalt KR, McHale LK, Song Q, Jun TH, Michel AP, Dorrance AE, Mian MAR (2015b) A high-resolution genetic linkage map of soybean based on 357 recombinant inbred lines genotyped with BARCSoySNP6K. Molecular Breeding 35, 58
A high-resolution genetic linkage map of soybean based on 357 recombinant inbred lines genotyped with BARCSoySNP6K.Crossref | GoogleScholarGoogle Scholar |

Li ZK, Yu SB, Lafitte HR, Huang N, Courtois B, Hittalmani S, Vijayakumar CHM, Liu GF, Wang GC, Shashidhar HE, Zhuang JY, Zheng KL, Singh VP, Sidhu JS, Srivantaneeyakul S, Khush GS (2003) QTL × environment interactions in rice. I. Heading date and plant height. Theoretical and Applied Genetics 108, 141–153.
QTL × environment interactions in rice. I. Heading date and plant height.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD3srnt1Skug%3D%3D&md5=2e2ac4338342048e0ccb79a2de77987cCAS |

Liu YL, Li YH, Reif JC, Mette MF, Liu ZX, Liu B, Zhang SS, Yan L, Ru-zhen C, Qiu LJ (2013) Identification of quantitative trait loci underlying plant height and seed weight in soybean. The Plant Genome 6,
Identification of quantitative trait loci underlying plant height and seed weight in soybean.Crossref | GoogleScholarGoogle Scholar |

Mohan M, Nair S, Bhagwat A, Krishna T, Yano M, Bhatia C, Sasaki T (1997) Genome mapping, molecular markers and marker-assisted selection in crop plants. Molecular Breeding 3, 87–103.
Genome mapping, molecular markers and marker-assisted selection in crop plants.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK2sXjsVKjsbo%3D&md5=b5cd291494a39013eb8f6254ae99ec2bCAS |

Ribaut JM, Hoisington D (1998) Marker-assisted selection: new tools and strategies. Trends in Plant Science 3, 236–239.
Marker-assisted selection: new tools and strategies.Crossref | GoogleScholarGoogle Scholar |

SAS Institute (2013) ‘SAS/STAT 9.4 user’s guide.’ (SAS Institute: Cary, NC, USA)

Schmutz J, Cannon SB, Schlueter J, Ma J, Mitros T, Nelson W, Hyten DL, Song Q, Thelen JJ, Cheng J, Xu D, Hellsten U, May GD, Yu Y, Sakurai T, Umezawa T, Bhattacharyya MK, Sandhu D, Valliyodan B, Lindquist E, Peto M, Grant D, Shu S, Goodstein D, Barry K, Futrell-Griggs M, Abernathy B, Du J, Tian Z, Zhu L, Gill N, Joshi T, Libault M, Sethuraman A, Zhang XC, Shinozaki K, Nguyen HT, Wing RA, Cregan P, Specht J, Grimwood J, Rokhsar D, Stacey G, Shoemaker RC, Jackson SA (2010) Genome sequence of the palaeopolyploid soybean. Nature 463, 178–183.
Genome sequence of the palaeopolyploid soybean.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXntVClsQ%3D%3D&md5=9863ad42d1783d54d7ff76277cc23f3eCAS |

Sonah H, O’Donoughue L, Cober E, Rajcan I, Belzile F (2015) Identification of loci governing eight agronomic traits using a GBS-GWAS approach and validation by QTL mapping in soya bean. Plant Biotechnology Journal 13, 211–221.
Identification of loci governing eight agronomic traits using a GBS-GWAS approach and validation by QTL mapping in soya bean.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2MXhvV2gtL8%3D&md5=081c5b2f5704b19cdae2fd031052d7c6CAS |

Song QJ, Marek LF, Shoemaker RC, Lark KG, Concibido VC, Delannay X, Specht JE, Cregan PB (2004) A new integrated genetic linkage map of the soybean. Theoretical and Applied Genetics 109, 122–128.
A new integrated genetic linkage map of the soybean.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXkslKgu7w%3D&md5=30ee96bcbbbe3c4acc7077f9ac8c3e94CAS |

Song Q, Jenkins J, Jia G, Hyten DL, Pantalone V, Jackson SA, Schmutz J, Cregan PB (2016) Construction of high resolution genetic linkage maps to improve the soybean genome sequence assembly Glyma1.01. BMC Genomics 17, 33
Construction of high resolution genetic linkage maps to improve the soybean genome sequence assembly Glyma1.01.Crossref | GoogleScholarGoogle Scholar |

Subudhi PK, Parco A, Singh PK, DeLeon T, Karan R, Biradar H, Cohn MA, Brar DS, Sasaki T (2012) Genetic architecture of seed dormancy in US weedy rice in different genetic backgrounds. Crop Science 52, 2564–2575.
Genetic architecture of seed dormancy in US weedy rice in different genetic backgrounds.Crossref | GoogleScholarGoogle Scholar |

Sun YN, Pan JB, Shi XL, Du XY, Wu Q, Qi ZM, Jiang HW, Xin DW, Liu CY, Hu GH, Chen QS (2012) Multi-environment mapping and meta-analysis of 100-seed weight in soybean. Molecular Biology Reports 39, 9435–9443.
Multi-environment mapping and meta-analysis of 100-seed weight in soybean.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38Xht1ynsbvF&md5=80eaa3d150839e3930fd9ce96c7e39bcCAS |

Teng W, Han Y, Du Y, Sun D, Zhang Z, Qiu L, Sun G, Li W (2009) QTL analyses of seed weight during the development of soybean (Glycine max L. Merr.). Heredity 102, 372–380.
QTL analyses of seed weight during the development of soybean (Glycine max L. Merr.).Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXjs1Kjs7g%3D&md5=b665cfd946771a96d6546e7f175f712eCAS |

Tester M, Langridge P (2010) Breeding technologies to increase crop production in a changing world. Science 327, 818–822.
Breeding technologies to increase crop production in a changing world.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXhslWisLg%3D&md5=a4dc597189bd49d7e90bba979060b4b1CAS |

Veldboom LR, Lee M (1996) Genetic mapping of quantitative trait loci in maize in stress and nonstress environments: I. Grain yield and yield components. Crop Science 36, 1310–1319.
Genetic mapping of quantitative trait loci in maize in stress and nonstress environments: I. Grain yield and yield components.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK28XmsFCkur4%3D&md5=56d208c350110e648decc8060d015494CAS |

Voorrips RE (2002) MapChart: software for the graphical presentation of linkage maps and QTLs. The Journal of Heredity 93, 77–78.
MapChart: software for the graphical presentation of linkage maps and QTLs.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38XktlOntrw%3D&md5=87f551f8fb8419ebf58f0b6825253e9dCAS |

Wang J, Li H, Zhang L, Meng L (2016a) ‘User’s manual of QTL IciMapping ver. 4.1.’ (Quantitative Genetics group, Institute of Crop Science, Chinese Academy of Agricultural Sciences (CAAS): Beijing/Genetic Resources Program, International Maize and Wheat Improvement Center (CIMMYT): Mexico City)

Wang J, Chu S, Zhang H, Zhu Y, Cheng H, Yu D (2016b) Development and application of a novel genome-wide SNP array reveals domestication history in soybean. Scientific Reports 6, 20728
Development and application of a novel genome-wide SNP array reveals domestication history in soybean.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC28Xitlymt74%3D&md5=b7d63b9587a78bfd6bb87093691fe346CAS |

Xia Z, Watanabe S, Yamada T, Tsubokura Y, Nakashima H, Zhai H, Anai T, Sato S, Yamazaki T, Lü S, Wu H (2012) Positional cloning and characterization reveal the molecular basis for soybean maturity locus E1 that regulates photoperiodic flowering. Proceedings of the National Academy of Sciences of the United States of America 109, E2155–E2164.
Positional cloning and characterization reveal the molecular basis for soybean maturity locus E1 that regulates photoperiodic flowering.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38XhsVWms77I&md5=c28a2d8b691db39b65b2d3d26af31642CAS |

Xin D, Qi Z, Jiang H, Hu Z, Zhu R, Hu J, Han H, Hu G, Liu C, Chen Q (2016) QTL location and epistatic effect analysis of 100-seed weight using wild soybean (Glycine soja Sieb. & Zucc.) chromosome segment substitution lines. PLoS One 11, e0149380
QTL location and epistatic effect analysis of 100-seed weight using wild soybean (Glycine soja Sieb. & Zucc.) chromosome segment substitution lines.Crossref | GoogleScholarGoogle Scholar |

Xu Y, Li HN, Li GJ, Wang X, Cheng LG, Zhang YM (2011) Mapping quantitative trait loci for seed size traits in soybean (Glycine max L. Merr.). Theoretical and Applied Genetics 122, 581–594.
Mapping quantitative trait loci for seed size traits in soybean (Glycine max L. Merr.).Crossref | GoogleScholarGoogle Scholar |

Zhang J, Song Q, Cregan PB, Jiang G-L (2016) Genome-wide association study, genomic prediction and marker-assisted selection for seed weight in soybean (Glycine max). Theoretical and Applied Genetics 129, 117–130.
Genome-wide association study, genomic prediction and marker-assisted selection for seed weight in soybean (Glycine max).Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2MXhslOgtbzJ&md5=0370f44273270e7ec3b599788e2bfa98CAS |

Zhou Z, Jiang Y, Wang Z, Gou Z, Lyu J, Li W, Yu Y, Shu L, Zhao Y, Ma Y (2015) Resequencing 302 wild and cultivated accessions identifies genes related to domestication and improvement in soybean. Nature Biotechnology 33, 408–414.
Resequencing 302 wild and cultivated accessions identifies genes related to domestication and improvement in soybean.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2MXitVGju7Y%3D&md5=7a809aa641ceab3948865c7dcfd4b8d5CAS |