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Fine-mapping of QTLs for individual and total isoflavone content in soybean (Glycine max L.) using a high-density genetic map

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Abstract

Key message

Fifteen stable QTLs were identified using a high-density soybean genetic map across multiple environments. One major QTL, qIF5-1, contributing to total isoflavone content explained phenotypic variance 49.38, 43.27, 46.59, 45.15 and 52.50%, respectively.

Abstract

Soybeans (Glycine max L.) are a major source of dietary isoflavones. To identify novel quantitative trait loci (QTL) underlying isoflavone content, and to improve the accuracy of marker-assisted breeding in soybean, a valuable mapping population comprised of 196 F7:8–10 recombinant inbred lines (RILs, Huachun 2 × Wayao) was utilized to evaluate individual and total isoflavone content in plants grown in four different environments in Guangdong. A high-density genetic linkage map containing 3469 recombination bin markers based on 0.2 × restriction site-associated DNA tag sequencing (RAD-seq) technology was used to finely map QTLs for both individual and total isoflavone contents. Correlation analyses showed that total isoflavone content, and that of five individual isoflavone, was significantly correlated across the four environments. Based on the high-density genetic linkage map, a total of 15 stable quantitative trait loci (QTLs) associated with isoflavone content across multiple environments were mapped onto chromosomes 02, 05, 07, 09, 10, 11, 13, 16, 17, and 19. Further, one of them, qIF5-1, localized to chromosomes 05 (38,434,171–39,045,620 bp) contributed to almost all isoflavone components across all environments, and explained 6.37–59.95% of the phenotypic variance, especially explained 49.38, 43.27, 46.59, 45.15 and 52.50% for total isoflavone. The results obtained in the present study will pave the way for a better understanding of the genetics of isoflavone accumulation and reveals the scope available for improvement of isoflavone content through marker-assisted selection.

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Abbreviations

cv.:

Cultivar

CIM:

Composite interval mapping method

LOD:

Log-likelihood

QTL:

Quantitative trait loci

RIL:

Recombinant inbred line

RAD-seq:

Restriction site-associated DNA sequencing

SLAF-seq:

Specific length amplified fragment sequencing

SNP:

Single nucleotide polymorphism

MAS:

Marker-assisted selection

References

  • Akond M, Liu S, Kantartzi SK et al (2014) Quantitative trait loci for seed isoflavone contents in ‘MD96-5722’ by ‘Spencer’ recombinant inbred lines of soybean. J Agric Food Chem 62(7):1464–1468

    Article  CAS  PubMed  Google Scholar 

  • Bargsten JW, Nap JP, Sanchez-Perez GF et al (2014) Prioritization of candidate genes in QTL regions based on associations between traits and biological processes. BMC Plant Biol 14(1):330

    Article  PubMed  PubMed Central  Google Scholar 

  • Cheng Y, Ma Q, Ren H et al (2017) Fine mapping of a Phytophthora-resistance gene RpsWY in soybean (Glycine max L.) by high-throughput genome-wide sequencing. Theor Appl Genet 130(5):1041–1051

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Chiari L, Piovesan ND, Naoe LK et al (2004) Genetic parameters relating isoflavone and protein content in soybean seeds. Euphytica 138(1):55–60

    Article  CAS  Google Scholar 

  • Cho MJ, Harper JE (1991) Effect of inoculation and nitrogen on isoflavonoid concentration in wild-type and nodulation-mutant soybean roots. Plant Physiol 95(2):435–442

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Du Z, Zhou X, Ling Y et al (2010) agriGO: a GO analysis toolkit for the agricultural community. Nucleic Acids Research 38(Web server issue):W64–W70

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Eldridge AC, Kwolek WF (1983) Soybean isoflavones: effect of environment and variety on composition. J Agric Food Chem 31(2):394–396

    Article  CAS  PubMed  Google Scholar 

  • Elshire RJ, Glaubitz JC, Sun Q et al (2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS one 6(5):e19379

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Graham TL, Graham MY, Subramanian S et al (2007) RNAi silencing of genes for elicitation or biosynthesis of 5-deoxyisoflavonoids suppresses race-specific resistance and hypersensitive cell death in Phytophthora sojae infected tissues. Plant Physiol 144(2):728–740

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Gutierrez-Gonzalez JJ, Wu X, Zhang J et al (2009) Genetic control of soybean seed isoflavone content: importance of statistical model and epistasis in complex traits. Theor Appl Genet 119(6):1069–1083

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Gutierrez-Gonzalez JJ, Wu X, Gillman JD et al (2010) Intricate environment-modulated genetic networks control isoflavone accumulation in soybean seeds. BMC Plant Biol 10(1):1

    Article  Google Scholar 

  • Gutierrez-Gonzalez JJ, Vuong TD, Zhong R et al (2011) Major locus and other novel additive and epistatic loci involved in modulation of isoflavone concentration in soybean seeds. Theor Appl Genet 123(8):1375–1385

    Article  CAS  PubMed  Google Scholar 

  • Han Y, Teng W, Wang Y et al (2015) Unconditional and conditional QTL underlying the genetic interrelationships between soybean seed isoflavone, and protein or oil contents. Plant Breeding 134(3):300–309

    Article  CAS  Google Scholar 

  • Hoeck JA, Fehr WR, Murphy PA et al (2000) Influence of genotype and environment on isoflavone contents of soybean. Crop Sci 40(1):48–51

    Article  CAS  Google Scholar 

  • Hyten DL, Cannon SB, Song Q et al (2010) High-throughput SNP discovery through deep resequencing of a reduced representation library to anchor and orient scaffolds in the soybean whole genome sequence. BMC Genom 11(1):38

    Article  Google Scholar 

  • Kassem MA, Meksem K, Iqbal MJ et al (2004) Definition of soybean genomic regions that control seed phytoestrogen amounts. Biomed Biotechnol 1:52–60

    Article  Google Scholar 

  • Kassem MA, Shultz J, Meksem K et al (2006) An updated ‘Essex’ by ‘Forrest’ linkage map and first composite interval map of QTL underlying six soybean traits. Theor Appl Genet 113(6):1015–1026

    Article  CAS  PubMed  Google Scholar 

  • Kumar J, Gupta DS, Gupta S et al (2017) Quantitative trait loci from identification to exploitation for crop improvement. Plant Cell Rep 36(8):1187–1213

    Article  CAS  PubMed  Google Scholar 

  • Lee SJ, Yan W, Ahn JK et al (2003) Effects of year, site, genotype and their interactions on various soybean isoflavones. Field Crops Res 81(2):181–192

    Article  Google Scholar 

  • Lee MJ, Chung IM, Kim H et al (2015) High resolution LC–ESI–TOF-mass spectrometry method for fast separation, identification, and quantification of 12 isoflavones in soybeans and soybean products. Food Chem 176:254–262

    Article  CAS  PubMed  Google Scholar 

  • Li R, Yu C, Li Y et al (2009a) SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics 25(15):1966–1967

    Article  CAS  PubMed  Google Scholar 

  • Li H, Handsaker B, Wysoker A et al (2009b) The sequence alignment/map format and SAMtools. Bioinformatics 25(16):2078–2079

    Article  PubMed  PubMed Central  Google Scholar 

  • Li B, Tian L, Zhang J et al (2014) Construction of a high-density genetic map based on large-scale markers developed by specific length amplified fragment sequencing (SLAF-seq) and its application to QTL analysis for isoflavone content in Glycine max. BMC Genom 15(1):1

    Article  Google Scholar 

  • Liang HZ, Yu YL, Wang SF et al (2010) QTL mapping of isoflavone, oil and protein contents in soybean (Glycine max L. Merr.). Agric Sci China 9(8):1108–1116

    Article  CAS  Google Scholar 

  • Ma B, Liao L, Peng Q et al (2017) Reduced representation genome sequencing reveals patterns of genetic diversity and selection in apple. J Integr Plant Biol 59(3):190–204

    Article  CAS  PubMed  Google Scholar 

  • Mabrouk Y, Zourgui L, Sifi B et al (2007) Some compatible Rhizobium leguminosarum strains in peas decrease infections when parasitised by Orobanche crenata. Weed Res 47(1):44–53

    Article  Google Scholar 

  • McCouch S, Cho Y, Yano M et al (1997) Report on QTL nomenclature. Rice Genet Newsl 14:11–12

    Google Scholar 

  • Meksem K, Njiti VN, Banz WJ et al (2001) Genomic regions that underlie soybean seed isoflavone content. J Biomed Biotechnol 1(1):38

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Meng S, He J, Zhao T et al (2016) Detecting the QTL-allele system of seed isoflavone content in Chinese soybean landrace population for optimal cross design and gene system exploration. Theor Appl Genet 129(8):1–20

    Article  Google Scholar 

  • Messina MJ (1999) Legumes and soybeans: overview of their nutritional profiles and health effects. Am J Clin Nutr 70(3):439s–450s

    CAS  PubMed  Google Scholar 

  • Miller MR, Dunham JP, Amores A et al (2007) Rapid and cost-effective polymorphism identification and genotyping using restriction site associated DNA (RAD) markers. Genome Res 17(2):240–248

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Njiti VN, Meksem K, Yuan J et al (1999) DNA markers associated with loci underlying seed phytoestrogen content in soybeans. J Med Food 2(3–4):185–187

    Article  CAS  PubMed  Google Scholar 

  • Peng Y, Hu Y, Mao B et al (2016) Genetic analysis for rice grain quality traits in the YVB stable variant line using RAD-seq. Mol Genet Genom 291(1):297–307

    Article  CAS  Google Scholar 

  • Pfender WF, Saha MC, Johnson EA et al (2011) Mapping with RAD (restriction-site associated DNA) markers to rapidly identify QTL for stem rust resistance in Lolium perenne. Theor Appl Genet 122(8):1467–1480

    Article  CAS  PubMed  Google Scholar 

  • Primomo VS, Poysa V, Ablett GR et al (2005a) Agronomic performance of recombinant inbred line populations segregating for isoflavone content in soybean seeds. Crop Sci 45(6):2203–2211

    Article  CAS  Google Scholar 

  • Primomo VS, Poysa V, Ablett GR et al (2005b) Mapping QTL for individual and total isoflavone content in soybean seeds. Crop Sci 45(6):2454–2464

    Article  CAS  Google Scholar 

  • Smallwood CJ (2012) Detection of quantitative trait loci for marker-assisted selection of soybean isoflavone genistein. Dissertation, University of Tennessee

  • Subramanian S, Hu X, Lu G et al (2004) The promoters of two isoflavone synthase genes respond differentially to nodulation and defense signals in transgenic soybean roots. Plant Mol Biol 54(5):623–639

    Article  CAS  PubMed  Google Scholar 

  • Subramanian S, Graham MY, Yu O et al (2005) RNA interference of soybean isoflavone synthase genes leads to silencing in tissues distal to the transformation site and to enhanced susceptibility to Phytophthora sojae. Plant Physiol 137(4):1345–1353

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sun JM, Sun BL, Han FX et al (2011) Rapid HPLC method for determination of 12 isoflavone components in soybean seeds. Agric Sci China 10(1):70–77

    Article  CAS  Google Scholar 

  • Sun X, Liu D, Zhang X et al (2013) SLAF-seq: an efficient method of large-scale de novo SNP discovery and genotyping using high-throughput sequencing. PLoS One 8(3):e58700

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Unamba CIN, Nag A, Sharma RK (2015) Next generation sequencing technologies: the doorway to the unexplored genomics of non-model plants. Front Plant Sci 6:1074

    Article  PubMed  PubMed Central  Google Scholar 

  • Voorrips RE (2002) MapChart: software for the graphical presentation of linkage maps and QTLs. J Hered 93(1):77–78

    Article  CAS  PubMed  Google Scholar 

  • Vyn TJ, Yin X, Bruulsema TW et al (2002) Potassium fertilization effects on isoflavone concentrations in soybean [Glycine max (L.) Merr.]. J Agric Food Chem 50(12):3501–3506

    Article  CAS  PubMed  Google Scholar 

  • Wang HJ, Murphy PA (1994) Isoflavone composition of American and Japanese soybeans in Iowa: effects of variety, crop year, and location. J Agric Food Chem 42(8):1674–1677

    Article  CAS  Google Scholar 

  • Wang S, Meyer E, McKay JK et al (2012) 2b-RAD: a simple and flexible method for genome-wide genotyping. Nat Methods 9(8):808–810

    Article  CAS  PubMed  Google Scholar 

  • Wang Y, Han Y, Teng W et al (2014) Expression quantitative trait loci infer the regulation of isoflavone accumulation in soybean (Glycine max L. Merr.) seed. BMC Genom 15(1):680

    Article  Google Scholar 

  • Wang Y, Han Y, Zhao X et al (2015) Mapping isoflavone QTL with main, epistatic and QTL × environment effects in recombinant inbred lines of soybean. PLoS One 10(3):e0118447

    Article  PubMed  PubMed Central  Google Scholar 

  • Wu K, Liu H, Yang M et al (2014) High-density genetic map construction and QTLs analysis of grain yield-related traits in Sesame (Sesamum indicum L.) based on RAD-seq techonology. BMC Plant Biol 14(1):1

    Article  CAS  Google Scholar 

  • Yang K, Moon JK, Jeong N et al (2011) Novel major quantitative trait loci regulating the content of isoflavone in soybean seeds. Genes Genom 33(6):685–692

    Article  CAS  Google Scholar 

  • Yoshikawa T, Okumoto Y, Ogata D et al (2010) Transgressive segregation of isoflavone contents under the control of four QTLs in a cross between distantly related soybean varieties. Breed Sci 60(3):243–254

    Article  CAS  Google Scholar 

  • Zeng G, Li D, Han Y et al (2009) Identification of QTL underlying isoflavone contents in soybean seeds among multiple environments. Theor Appl Genet 118(8):1455–1463

    Article  CAS  PubMed  Google Scholar 

  • Zhang HJ, Li JW, Liu YJ et al (2014a) Quantitative trait loci analysis of individual and total isoflavone contents in soybean seeds. J Genet 93(2):331–338

    Article  CAS  PubMed  Google Scholar 

  • Zhang J, Ge Y, Han F et al (2014b) Isoflavone content of soybean cultivars from maturity group 0 to VI grown in northern and southern China. J Am Oil Chem Soc 91(6):1019–1028

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhou L, Wang SB, Jian J et al (2015) Identification of domestication-related loci associated with flowering time and seed size in soybean with the RAD-seq genotyping method. Sci Rep 5:9350

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zou G, Zhai G, Feng Q et al (2012) Identification of QTLs for eight agronomically important traits using an ultra-high-density map based on SNPs generated from high-throughput sequencing in sorghum under contrasting photoperiods. J Exp Bot 63(15):5451

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We wish to thank Professor Junming Sun (Chinese Academy of Agricultural Sciences, People’s Republic of China) for kindly supplying the 12 standards of isoflavone components. This work was supported by the National Natural Sciences Foundation of China (31401398); the China Agricultural Research System (CARS-04-PS09); the Project of Molecular Design Breeding for Major Economic Crops (2016yfd0101901) and the Research Project of the State Key Laboratory of Agricultural and Biological Resources Protection and Utilization in Subtropics.

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  1. Zhandong Cai, Yanbo Cheng and Zhuwen Ma are contributed equally to this work.

Authors and Affiliations

  1. The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, 510642, Guangdong, People’s Republic of China

    Zhandong Cai, Yanbo Cheng, Zhuwen Ma, Xinguo Liu, Qibin Ma, Yinghui Mu & Hai Nian

  2. The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, 510642, Guangdong, People’s Republic of China

    Zhandong Cai, Yanbo Cheng, Zhuwen Ma, Xinguo Liu, Qibin Ma, Yinghui Mu & Hai Nian

  3. Shofine Seed Technology Co., Ltd., Jiaxiang, 272400, Shandong, People’s Republic of China

    Zhandong Cai, Yanbo Cheng, Qibin Ma, Yinghui Mu & Hai Nian

  4. Guangdong Provincial Key Laboratory of Crops Genetics and Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, Guangdong, People’s Republic of China

    Zhuwen Ma

  5. Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518086, People’s Republic of China

    Qiuju Xia & Gengyun Zhang

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  1. Zhandong Cai
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Correspondence to Yinghui Mu or Hai Nian.

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Communicated by David A Lightfoot.

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Cai, Z., Cheng, Y., Ma, Z. et al. Fine-mapping of QTLs for individual and total isoflavone content in soybean (Glycine max L.) using a high-density genetic map. Theor Appl Genet 131, 555–568 (2018). https://doi.org/10.1007/s00122-017-3018-x

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