Skip to main content
Springer Nature Link
Log in

Identification of quantitative trait loci associated with soyasaponin I concentration in soybean seed

  • Original Article
  • Published:
Theoretical and Applied Genetics Aims and scope Submit manuscript

Abstract

Key message Significant QTL for soyasaponin I, as the major component of the soyasaponin B, have been identified using an RIL soybean population, which could facilitate the development of functional food soybean cultivars.

Abstract

Soyasaponin B forms that are naturally found in soybean (Glycine max [L.] Merr.) seed, have been of interest to the food industry because of their functional food properties. The predominant form soyasaponin B is soyasaponin I. While some of the genes in the biosynthesis of soyasaponins have been characterized, the underlying genetics of soyasaponins as a quantitative trait is still poorly understood. The objective of this study was to identify quantitative trait loci (QTL) associated with the accumulation of soyasaponin I using a genetic mapping population. The population consisting of 186 F4:7 recombinant inbred lines derived from the cross of ‘OAC Glencoe’ and ‘OAC Wallace’ was grown in two Southern Ontario locations in 2015 and 2016. The concentration of soyasaponin I was determined using high-performance liquid chromatography. Putative QTL associated with the accumulation of soyasaponin I were identified through simple interval mapping and composite interval mapping on chromosomes 10 and 16, which explained up to 11% of the total phenotypic variation per QTL for the trait. A significant positive correlation was observed between soyasaponin I and seed protein concentration in the mapping population, which may be advantageous for the development of soybean lines with improved soyasaponin I profiles. QTL identified in this study may facilitate marker-assisted selection for the development of food-grade soybean lines with improved functional properties.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

References

  • Agronomix Software, Inc (1999) Agrobase 99 user’s guide and reference manual. Agronomix Software, Inc., Winnipeg, p 428

    Google Scholar 

  • Bartlett MS (1937) Properties of sufficiency and statistical tests. Proc. R. Soc. London. Ser. A 160:268–282

    Article  Google Scholar 

  • Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23:2633–2635

    Article  CAS  PubMed  Google Scholar 

  • Browning SR, Browning BL (2007) Rapid and accurate haplotype phasing and missing data inference for whole genome association studies by use of localized haplotype clustering. Am J Hum Genet 81:1084–1097. https://doi.org/10.1086/521987

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Collard BCY, Jahufer MZZ, Brouwer JB, Pang ECK (2005) An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: the basic concepts. Euphytica 142:169–196

    Article  CAS  Google Scholar 

  • Concibido VC, La Vallee B, McLaird P, Pineda N, Meyer J, Hummel L, Yang J (2003) Introgression of a quantitative trait locus for yield from Glycine soja into commercial soybean cultivars. Theor Appl Genet 106:575–582

    Article  CAS  PubMed  Google Scholar 

  • Dreher K, Khairallah M, Ribaut J, Morris M (2003) Money matters (I): costs of field and laboratory procedures associated with conventional and marker-assisted maize breeding at CIMMYT. Mol Breed 11:221–234

    Article  Google Scholar 

  • Eskandari M, Cober ER, Rajcan I (2013) Genetic control of soybean seed oil: I. QTL and genes associated with seed oil concentration in RIL populations derived from crossing moderately high-oil parents. Theor Appl Genet 126(2):483–495

    Article  CAS  PubMed  Google Scholar 

  • Fehr WR, Caviness CE, Burmood DT, Pennington JS (1971) Stage of development descriptions for soybeans, Glycine max (L.) Merrill. Crop Sci 11:929–931

    Article  Google Scholar 

  • Francis G, Kerem Z, Makkar H, Becker K (2002) The biological action of saponins in animal systems: a review. Brit J Nutr 88(6):587–605

    Article  CAS  PubMed  Google Scholar 

  • Holland JB, Nyquist WE, Cervantes-Martinez CT (2003) Estimating and Interpreting Heritability for Plant Breeding: an Update. Plant Breed Rev 22:9–112

    Google Scholar 

  • Huang S, Han YP, Li CS, Tian J, Li WB, Wang JA (2012) Identification of QTLs associated with total soyasaponin content in soybean (Glycine max (L.) Merr.). J Integr Agric 11:1976–1984

    Article  Google Scholar 

  • Hubert J, Berger M, Daydé J (2005) Use of a simplified HPLC—UV analysis for soyasaponin B determination: study of saponin and isoflavone variability in soybean cultivars and soy-based health food products. J Agric Food Chem 53:3923–3930

    Article  CAS  PubMed  Google Scholar 

  • Hwang E-Y, Song Q, Jia G, Specht JE, Hyten DL, Costa J, Cregan PB (2014) A genome-wide association study of seed protein and oil content in soybean. BMC Genom 15:1. https://doi.org/10.1186/1471-2164-15-1

    Article  CAS  Google Scholar 

  • Kosambi DD (1943) The estimation of map distances from recombination values. Ann Eugen 12(1):172–175

    Article  Google Scholar 

  • Levene H (1960) Robust tests for equality of variances. In: Olkin J, Ghurye S, Hoeffding W, Madow W, Mann H (eds) Contributions to probability and statistics: essays in honor of harold hotelling. Stanford University Press, Stanford, pp 278–292

    Google Scholar 

  • OSACC (2017) Ontario soybean and canola committee. Available online: http://www.oopscc.org/index.php, reports 2000, 2001, and 2010. Accessed 5 July 2017

  • Qin P, Song W, Yang X, Sun S, Zhou X, Yang R, Li N, Hou W, Wu C, Han T, Ren G (2014) Regional distribution of protein and oil compositions o of soybean cultivars in China. Crop Sci 54:1139–1146. https://doi.org/10.2135/cropsci2013.05.0314

    Article  CAS  Google Scholar 

  • Salyer J, Eswaranandam S, Lee S-O (2013) Soyasaponin I, III, and soyasapogenol B inhibit proliferation and modulate PKC expression in caco-2 human colon cancer cells. J Food Res 2:81

    Article  CAS  Google Scholar 

  • Sayama T, Ono E, Takagi K, Takada Y, Horikawa M, Nakamoto Y, Hirose A, Sasama H, Ohashi M, Hasegawa H, Terakawa T, Kikuchi A, Kato S, Tatsuzaki N, Tsukamoto C, Ishimoto M (2012) The Sg-1 glycosyltransferase locus regulates structural diversity of triterpenoid saponins of soybean. Plant Cell 24:2123–2138

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Seguin P, Chennupati P, Tremblay G, Wucheng L (2014) Crop management, genotypes, and environmental factors affect soyasaponin b concentration in soybean. J Agric Food Chem 62:7160–7165

    Article  CAS  PubMed  Google Scholar 

  • Shapiro SS, Wilk MB (1965) An analysis of variance test for normality (complete series). Biometrika 52(3/4):591–611

    Article  Google Scholar 

  • Takada Y, Tayama I, Sayama T, Sasama H, Saruta M, Kikuchi A, Ishimoto M, Tsukamoto C (2012) Genetic analysis of variations in the sugar chain composition at the C-3 position of soybean seed saponins. Breed Sci 61:639–645

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Takada Y, Sasama H, Sayama T, Kikuchi A, Kato S, Ishimoto M, Tsukamoto C (2013) Genetic and chemical analysis of a key biosynthetic step for soyasapogenol A, an aglycone of group A saponins that influence soymilk flavor. Theor Appl Genet 126:721–731

    Article  CAS  PubMed  Google Scholar 

  • Teraishi M, Tojo Y, Yamada N, Okumoto Y (2017) Identification of environmentally stable QTLs controlling Saponin content in Glycine max. Breed Sci 67:123–128

    Article  PubMed  PubMed Central  Google Scholar 

  • Torkamenah D, Laroche J, Bastien M, Abed A, Belzile F (2017) Fast-GBS: a new pipeline for the efficient and highly accurate calling of SNPs from genotyping-by-sequencing data. BMC Bioinform 18:5

    Article  CAS  Google Scholar 

  • Van Ooijen JW (2006) JoinMap 4.0: Software for the Calculation of Genetic Linkage Maps in Experimental Populations. Kyazma B.V., Wageningen, Netherlands

  • Van Ooijen JW (2009) MapQTL 6: Software for the mapping of quantitative trait loci in experimental populations of diploid species. Kyazma B.V., Wageningen, Netherlands

  • Xu XP, Liu H, Tian L, Dong XB, Shen SH, Qu LQ (2015) Integrated and comparative proteomics of high-oil and high-protein soybean seeds. Food Chem 172:105–116

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Drs. Barry J. Shelp and Alireza Navabi (Univ. of Guelph) for their valuable suggestions on the manuscript. Authors are also grateful for the technical assistance of Chris Grainger, Colbey Templeman Sebben, Cory Schilling, and Drs. Gordon Hoover and André Passianotto, as well as the entire soybean crew at the University of Guelph. We would like to acknowledge Weather INnovations Consulting LP and Mr. Ian Nichols for generously providing us with the weather data for Welburn, Ontario. This project was funded with generous contributions from the Canadian Field Crop Research Alliance/Alliance de Recherche sur les Cultures Commerciales du Canada, Project # AIP-CL2, under the Growing Forward 2 Program of Agriculture and Agri-food Canada.

Author information

Authors and Affiliations

  1. Department of Plant Agriculture, Crop Science Building, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada

    Edward C. MacDonell & Istvan Rajcan

Authors
  1. Edward C. MacDonell
    View author publications

    Search author on:PubMed Google Scholar

  2. Istvan Rajcan
    View author publications

    Search author on:PubMed Google Scholar

Corresponding author

Correspondence to Istvan Rajcan.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Additional information

Communicated by Henry T. Nguyen.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

MacDonell, E.C., Rajcan, I. Identification of quantitative trait loci associated with soyasaponin I concentration in soybean seed. Theor Appl Genet 131, 2157–2165 (2018). https://doi.org/10.1007/s00122-018-3144-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00122-018-3144-0