Abstract
Key message
Two independent variant raffinose synthase 3 ( RS3 ) alleles produced an equivalent phenotype and implicated the gene as a key contributor to soybean seed carbohydrate phenotype.
Abstract
Soybean is an important crop because the processed seed is utilized as a vegetable oil and a high protein meal typically used in livestock feeds. Raffinose and stachyose, the raffinose family of oligosaccharides (RFO) carbohydrate components of the seed, are synthesized in developing soybean seeds from sucrose and galactinol. Sucrose is considered positive for metabolizable energy, while RFO are anti-nutritional factors in diets of monogastric animals such as humans, poultry, and swine. To increase metabolizable energy available in soybean seed meal, prior research has been successful in deploying variant alleles of key soybean raffinose synthase (RS) genes leading to reductions or near elimination of seed RFO, with significant increases in seed sucrose. The objective of this research was to investigate the specific role of variants of the RS3 gene in a genomic context and improve molecular marker-assisted selection for the ultra-low (UL) RFO phenotype in soybean seeds. The results revealed a new variant of the RS3 allele (rs3 snp5, rs3 snp6) contributed to the UL RFO phenotype when mutant alleles of RS2 were present. The variant RS3 allele identified was present in about 15% of a small set of soybean cultivars released in North America. A missense allele of the RS3 gene (rs3 G75E) also produced the UL RFO phenotype when combined with mutant alleles of RS2. The discoveries reported here enable direct marker-assisted selection for an improved soybean meal trait that has the potential to add value to soybean by improving the metabolizable energy of the meal.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Bellaloui N, Smith JR, Gillen AM, Ray JD (2010) Effect of maturity on seed sugars as measured on near-isogenic soybean (glycine max) lines. Crop Sci 50:1978–1987. https://doi.org/10.2135/cropsci2009.10.0596
Bernard RL, Cremeens CR (1988) Registration of ‘Williams 82’ soybean. Crop Sci 28:1027–1028. https://doi.org/10.2135/cropsci1988.0011183X002800060049x
Bilyeu KD, Wiebold WJ (2016) Environmental stability of seed carbohydrate profiles in soybeans containing different alleles of the raffinose synthase 2 (RS2) gene. J Agric Food Chem 64:1071–1078. https://doi.org/10.1021/acs.jafc.5b04779
Coon CN, Leske KL, Akavanichan O, Cheng TK (1990) Effect of oligosaccharide-free soybean meal on true metabolizable energy and fiber digestion in adult roosters1. Poult Sci 69:787–793. https://doi.org/10.3382/ps.0690787
Dierking EC, Bilyeu KD (2008) Association of a soybean raffinose synthase gene with low raffinose and stachyose seed phenotype. Plant Genome 1:135–145. https://doi.org/10.3835/plantgenome2008.06.0321
Dierking EC, Bilyeu KD (2009) New sources of soybean seed meal and oil composition traits identified through TILLING. BMC Plant Biol 9:89. https://doi.org/10.1186/1471-2229-9-89
Gitzelmann R, Auriccio S (1965) The handling of soya alpha-galactosides by a normal and a galactosemic child. Pediatrics 36:231–235
Hagely KB, Palmquist D, Bilyeu KD (2013) Classification of distinct seed carbohydrate profiles in soybean. J Agric Food Chem 61:1105–1111. https://doi.org/10.1021/jf303985q
Hitz WD, Carlson TJ, Kerr PS, Sebastian SA (2002) Biochemical and molecular characterization of a mutation that confers a decreased raffinosaccharide and phytic acid phenotype on soybean seeds. Plant Physiol 128:650. https://doi.org/10.1104/pp.010585
Hsu SH, Hadley HH, Hymowitz T (1973) Changes in carbohydrate contents of germinating soybean seeds1. Crop Sci 13:407–410. https://doi.org/10.2135/cropsci1973.0011183X001300040004x
Jo H, Lee J-D, Bilyeu KD (2018) Environmental stability of carbohydrate profiles in different soybean genotypes. Crop Sci 58:773–782. https://doi.org/10.2135/cropsci2017.08.0497
Jo H, Lorenz AJ, Rainey KM et al (2019) Environmental stability study of soybeans with modified carbohydrate profiles in maturity groups 0 to V. Crop Sci 59:1531–1543. https://doi.org/10.2135/cropsci2018.09.0600
Karr-Lilienthal LK, Kadzere CT, Grieshop CM, Fahey GC (2005) Chemical and nutritional properties of soybean carbohydrates as related to nonruminants: a review. Livest Prod Sci 97:1–12. https://doi.org/10.1016/j.livprodsci.2005.01.015
Kerr PS, Sebastian SA (2000) Soybean products with improved carbohydrate composition and soybean plants. US Patent 5,710,365A
Keunen E, Peshev D, Vangronsveld J et al (2013) Plant sugars are crucial players in the oxidative challenge during abiotic stress: extending the traditional concept. Plant Cell Environ 36:1242–1255. https://doi.org/10.1111/pce.12061
Kumar V, Rani A, Goyal L et al (2010) Sucrose and raffinose family oligosaccharides (RFOs) in soybean seeds as influenced by genotype and growing location. J Agric Food Chem 58:5081–5085. https://doi.org/10.1021/jf903141s
Lam H-M, Xu X, Liu X et al (2010) Resequencing of 31 wild and cultivated soybean genomes identifies patterns of genetic diversity and selection. Nat Genet 42:1053–1059. https://doi.org/10.1038/ng.715
Langewisch T, Zhang H, Vincent R et al (2014) Major soybean maturity gene haplotypes revealed by SNPViz analysis of 72 sequenced soybean genomes. PLoS ONE 9:e94150. https://doi.org/10.1371/journal.pone.0094150
Neus JD, Fehr WR, Schnebly SR (2005) Agronomic and seed characteristics of soybean with reduced raffinose and stachyose. Crop Sci 45:589–592. https://doi.org/10.2135/cropsci2005.0589
Nickell CD, Noel GR, Thomas DJ, Waller R (1990) Registration of “Jack” soybean. Crop Sci 30:1365. https://doi.org/10.2135/cropsci1990.0011183X003000060059x
Nickell CD, Thomas DJ, Cary TR, Stephens PA (1996) Registration of “Macon” soybean. Crop Sci 36:1410
Obendorf RL, Górecki RJ (2012) Soluble carbohydrates in legume seeds. Seed Sci Res 22:219–242. https://doi.org/10.1017/S0960258512000104
Obendorf RL, Zimmerman AD, Ortiz PA et al (2008) Imbibitional chilling sensitivity and soluble carbohydrate composition of low raffinose, low stachyose soybean seed. Crop Sci 48:2396–2403. https://doi.org/10.2135/cropsci2007.12.0706
Openshaw SJ, Hadley HH (1978) Maternal effects on sugar content in soybean seeds1. Crop Sci 18:581–584. https://doi.org/10.2135/cropsci1978.0011183X001800040014x
Parsons CM, Zhang Y, Araba M (2000) Nutritional evaluation of soybean meals varying in oligosaccharide content. Poult Sci 79:1127–1131. https://doi.org/10.1093/ps/79.8.1127
Perryman KR, Dozier WA III (2012) Apparent metabolizable energy and apparent ileal amino acid digestibility of low and ultra-low oligosaccharide soybean meals fed to broiler chickens1. Poult Sci 91:2556–2563. https://doi.org/10.3382/ps.2012-02379
Peterbauer T, Richter A (2001) Biochemistry and physiology of raffinose family oligosaccharides and galactosyl cyclitols in seeds. Seed Sci Res 11:185–197. https://doi.org/10.1079/SSR200175
Ren C, Bilyeu KD, Beuselinck PR (2009) Composition, vigor, and proteome of mature soybean seeds developed under high temperature. Crop Sci 49:1010–1022. https://doi.org/10.2135/cropsci2008.05.0247
SAS Institute (2016) The SAS system for windows. Cary, NC. https://www.sas.com
Schillinger JA, Dierking EC, Bilyeu KD (2013) Soybeans having high germination rates and ultra-low raffinose and stachyose content. US Patent 8,471,107
Schillinger JA, Dierking EC, Bilyeu KD (2018) Soybeans having high germination rates and ultra-low raffinose and stachyose content. US Patent 10,081,814
Schmutz J, Cannon SB, Schlueter J et al (2010) Genome sequence of the palaeopolyploid soybean. Nature 463:178–183. https://doi.org/10.1038/nature08670
Smiricky MR, Grieshop CM, Albin DM et al (2002) The influence of soy oligosaccharides on apparent and true ileal amino acid digestibilities and fecal consistency in growing pigs12. J Anim Sci 80:2433–2441. https://doi.org/10.1093/ansci/80.9.2433
Song Q, Yan L, Quigley C et al (2017) Genetic characterization of the soybean nested association mapping population. Plant Genome. https://doi.org/10.3835/plantgenome2016.10.0109
SoyStats® (2019) 2018 soy highlights. The American Soybean Association. http://soystats.com/2018-highlights/. Accessed 11 Aug 2019
State College, PA (2010) Minitab 17 statistical software. Minitab, Inc. www.minitab.com
Thapa R, Carrero-Colón M, Rainey KM, Hudson K (2019) Tilling by sequencing: a successful approach to identify rare alleles in soybean populations. Genes 10:1003
USDA (2019) Statistics by subject, national statistics for soybeans. National Agricultural Statistics Service. https://www.nass.usda.gov/Statistics_by_Subject/result.php?64D20FB3-8DF5-35B9-A9AA-1A2FF7F7B232§or=CROPS&group=FIELD%20CROPS&comm=SOYBEANS Accessed 25 Sept 2019
Valliyodan B, Qiu Dan, Patil G et al (2016) Landscape of genomic diversity and trait discovery in soybean. Sci Rep 6:23598. https://doi.org/10.1038/srep23598
Wolf RB, Cavins JF, Kleiman R, Black LT (1982) Effect of temperature on soybean seed constituents: oil, protein, moisture, fatty acids, amino acids and sugars. J Am Oil Chem Soc 59:230–232. https://doi.org/10.1007/BF02582182
Zabala G, Vodkin L (2003) Cloning of the pleiotropic locus in soybean and two recessive alleles that differentially affect structure and expression of the encoded flavonoid 3′ hydroxylase. Genetics 163:295
Zhou Z, Jiang Y, Wang Z et al (2015) Resequencing 302 wild and cultivated accessions identifies genes related to domestication and improvement in soybean. Nat Biotechnol 33:408. https://doi.org/10.1038/nbt.3096
Acknowledgements
The authors greatly acknowledge the technical assistance of Paul Little, Christine Cole, and Mark Johnston in both the laboratory and soybean field. Funding for this project was provided in part by the United Soybean Board (USB). Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture. The USDA is an equal opportunity provider and employer.
Author information
Authors and Affiliations
Contributions
KBH and HJ contributed equally to this work and share co-first authorship. KBH, HJ, and JK conducted experiments and analyzed results. KAH and KB conceived and designed the experiments, analyzed the results, and developed soybean germplasm. KBH, HJ, and KB drafted the manuscript. All authors read and approved the manuscript.
Corresponding author
Ethics declarations
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Additional information
Communicated by Albrecht E. Melchinger.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Hagely, K.B., Jo, H., Kim, JH. et al. Molecular-assisted breeding for improved carbohydrate profiles in soybean seed. Theor Appl Genet 133, 1189–1200 (2020). https://doi.org/10.1007/s00122-020-03541-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00122-020-03541-z