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Molecular Breeding

, 39:27 | Cite as

Molecular tools for detecting Pdh1 can improve soybean breeding efficiency by reducing yield losses due to pod shatter

  • Carrie Miranda
  • Carolyn Culp
  • Mária Škrabišová
  • Trupti Joshi
  • François Belzile
  • David M. Grant
  • Kristin BilyeuEmail author
Article
  • 2 Downloads

Abstract

Pod shattering is an ancestral trait that promotes seed dispersal; however, shattering can have substantial yield losses in cultivated soybean. During the improvement process, American soybean breeders virtually eliminated the shatter phenotype for released varieties, but in other countries, such as Ghana, shatter persists. The objective of our research was to find a molecular tool to implicate genetic shatter susceptibility, validate its usefulness, and apply this knowledge to identify shattering potential in parental lines. Previous research revealed the gene Pdh1 on chromosome 16 plays a crucial role in determining the shatter phenotype. A perfect molecular marker assay was developed to detect alleles of the Pdh1 gene. A genome-wide association study (GWAS) was performed using the Pdh1 allele status as a phenotype and identified a highly associated marker in the SoySNP50K array. Soybean accessions from the National Plant Germplasm System (GRIN-NPGS) with shatter score and SoySNP50K data were evaluated to determine the impact of the predicted Pdh1 alleles on early and late pod shattering. An online tool was developed to enable researchers to query the GRIN collection for the predicted Pdh1 allele status. Lines from an African soybean germplasm collection were analyzed, and it was determined that 22.5% of lines had the shatter-susceptible alleles of Pdh1; two of seven Ghanaian released soybean varieties had the shatter-susceptible alleles of Pdh1. Soybean breeding programs that access germplasm from the GRIN or the African collection can utilize these resources to eliminate the Pdh1 effects on pod shatter and thus improve yield potential.

Keywords

Soybean Breeding Domestication Molecular tools Pod shatter 

Notes

Funding information

This work was supported by the US Department of Agriculture-Agricultural Research Service. This research is in part funded by the USAID Feed the Future Lab for Soybean Value Chain Research. The award number is Cooperative Agreement Number AID OAA-L-14-00001.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

11032_2019_935_MOESM1_ESM.xlsx (23 kb)
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11032_2019_935_MOESM2_ESM.xlsx (15 kb)
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References

  1. Anderson JE, Kantar MB, Kono TY, Fu F, Stec AO, Song Q, Cregan PB, Specht JE, Diers BW, CAnnon SB, McHale LK, Stupar RM (2014) A roadmap for functional structural variants in the soybean genome. G3: Genes|Genomes|Genetics 4:1307–1318CrossRefGoogle Scholar
  2. Bailey M, Mian M, Carter T, Ashley D, Boerma H (1997) Pod dehiscence of soybean: identification of quantitative trait loci. J Hered 88:152–154CrossRefGoogle Scholar
  3. Bandillo NB, Anderson JE, Kantar MB, Stupar RM, Specht JE, Graef GL, Lorenz AJ (2017) Dissecting the genetic basis of local adaptation in soybean. Sci Rep 7:17195CrossRefGoogle Scholar
  4. 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 23:2633–2635CrossRefGoogle Scholar
  5. Carter TE, Nelson RL, Sneller CH, Cui Z (2004) Genetic diversity in soybean. Soybeans: Improvement, production, and uses:303–416Google Scholar
  6. Chen Y, Nelson RL (2004) Genetic variation and relationships among cultivated, wild, and semiwild soybean. Crop Sci 44:316–325CrossRefGoogle Scholar
  7. Dong Y, Yang X, Liu J, Wang B-H, Liu B-L, Wang Y-Z (2014) Pod shattering resistance associated with domestication is mediated by a NAC gene in soybean. Nat Commun 5:3352CrossRefGoogle Scholar
  8. Fang C, Ma Y, Wu S, Liu Z, Wang Z, Yang R, Hu G, Zhou Z, Yu H, Zhang M, Pan Y, Zhou G, Ren H, du W, Yan H, Wang Y, Han D, Shen Y, Liu S, Liu T, Zhang J, Qin H, Yuan J, Yuan X, Kong F, Liu B, Li J, Zhang Z, Wang G, Zhu B, Tian Z (2017) Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean. Genome Biol 18:161CrossRefGoogle Scholar
  9. Food and Agriculture Organization of the United Nations (2014) FAOSTAT statistics database. http://www.fao.org/faostat. Accessed 5 Feb 2019
  10. Fuller DQ, Denham T, Arroyo-Kalin M, Lucas L, Stevens CJ, Qin L, Allaby RG, Purugganan MD (2014) Convergent evolution and parallelism in plant domestication revealed by an expanding archaeological record. Proc Natl Acad Sci 111:6147–6152CrossRefGoogle Scholar
  11. Funatsuki H, Suzuki M, Hirose A, Inaba H, Yamada T, Hajika M, Komatsu K, Katayama T, Sayama T, Ishimoto M, Fujino K (2014) Molecular basis of a shattering resistance boosting global dissemination of soybean. Proc Natl Acad Sci 111:17797–17802CrossRefGoogle Scholar
  12. Gao M, Zhu H (2013) Fine mapping of a major quantitative trait locus that regulates pod shattering in soybean. Mol Breed 32:485–491CrossRefGoogle Scholar
  13. Goldsmith PD (2008) Economics of soybean production, marketing and utilization. Soybeans Chemistry, Production, Processing, and Utilization:117–150Google Scholar
  14. Grant D, Nelson RT, Cannon SB, Shoemaker RC (2009) SoyBase, the USDA-ARS soybean genetics and genomics database. Nucleic Acids Res 38:D843–D846CrossRefGoogle Scholar
  15. Hymowitz T (1970) On the domestication of the soybean. Econ Bot 24:408–421CrossRefGoogle Scholar
  16. Hyten DL, Song Q, Zhu Y, Choi IY, Nelson RL, Costa JM, Specht JE, Shoemaker RC, Cregan PB (2006) Impacts of genetic bottlenecks on soybean genome diversity. Proc Natl Acad Sci 103:16666–16671CrossRefGoogle Scholar
  17. Joshi T, Patil K, Fitzpatrick MR, Franklin LD, Yao Q, Cook JR, Wang Z, Libault M, Brechenmacher L, Valliyodan B, Wu X, Cheng J, Stacey G, Nguyen HT, Xu D (2012) Soybean Knowledge Base (SoyKB): a web resource for soybean translational genomics. BMC Genomics 13(Suppl 1):S15.  https://doi.org/10.1186/1471-2164-13-S1-S15 CrossRefPubMedPubMedCentralGoogle Scholar
  18. Joshi T et al (2013) Soybean knowledge base (SoyKB): a web resource for integration of soybean translational genomics and molecular breeding. Nucleic Acids Res 42:D1245–D1252CrossRefGoogle Scholar
  19. Joshi T, Wang J, Zhang H, Chen S, Zeng S, Xu B, Xu D (2017) The evolution of soybean Knowledge Base (SoyKB). In: Plant Genomics Databases. Springer, pp 149–159Google Scholar
  20. Kong F, Liu B, Xia Z, Sato S, Kim BM, Watanabe S, Yamada T, Tabata S, Kanazawa A, Harada K, Abe J (2010) Two coordinately regulated homologs of FLOWERING LOCUS T are involved in the control of photoperiodic flowering in soybean. Plant Physiol 154:1220–1231.  https://doi.org/10.1104/pp.110.160796 CrossRefPubMedPubMedCentralGoogle Scholar
  21. Lam HM, Xu X, Liu X, Chen W, Yang G, Wong F-L, Li M-W, He W, Qin N, Wang B, Li J, Jian M, Wang J, Shao G, Wang J, Sun SS-M, Zhang G (2010) Resequencing of 31 wild and cultivated soybean genomes identifies patterns of genetic diversity and selection. Nat Genet 42:1053–1059CrossRefGoogle Scholar
  22. Liu B, Fujita T, Yan Z-H, Sakamoto S, Xu D, Abe J (2007) QTL mapping of domestication-related traits in soybean (Glycine max). Ann Bot 100:1027–1038CrossRefGoogle Scholar
  23. Liu Y, Khan SM, Wang J, Rynge M, Zhang Y, Zeng S et al (2016) PGen: large-scale genomic variations analysis workflow and browser in SoyKB. BMC Bioinformatics 17(Suppl 13):337Google Scholar
  24. Masuda T, Goldsmith PD (2009) World soybean production: area harvested, yield, and long-term projections. Int Food Agribusiness Manag Rev 12:143–162Google Scholar
  25. Nguyen H, et al. (2018) Large scale soybean genome re-sequencing consortium, pre-publication. https://soybase.org/projects/SoyBase.B2014.02/resequencing%20data%20usage%20policy.htm. Accessed May 2018
  26. Saxe L, Clark C, Lin S, Lumpkin T (1996) Mapping the pod-shattering trait in soybean. Soybean Genetics Newsletter (USA)Google Scholar
  27. Singh U, Singh B (1992) Tropical grain legumes as important human foods. Econ Bot 46:310–321CrossRefGoogle Scholar
  28. Song Q, Hyten DL, Jia G, Quigley CV, Fickus EW, Nelson RL, Cregan PB (2013) Development and evaluation of SoySNP50K, a high-density genotyping array for soybean. PLoS One 8:e54985CrossRefGoogle Scholar
  29. Suzuki M, Fujino K, Funatsuki H (2009) A major soybean QTL, qPDH1, controls pod dehiscence without marked morphological change. Plant Prod Sci 12:217–223CrossRefGoogle Scholar
  30. Tefera H, Asafo-Adjei B, Dashiell KE (2010) Breeding progress for grain yield and associated traits in medium and late maturing promiscuous soybeans in Nigeria. Euphytica 175:251–260CrossRefGoogle Scholar
  31. Wansink B, Cheong J (2002) Taste profiles that correlate with soy consumption in developing countries. Pak J Nutr 1:276–278CrossRefGoogle Scholar
  32. Zhou Z, Jiang Y, Wang Z, Gou Z, Lyu J, Li W, Yu Y, Shu L, Zhao Y, Ma Y, Fang C, Shen Y, Liu T, Li C, Li Q, Wu M, Wang M, Wu Y, Dong Y, Wan W, Wang X, Ding Z, Gao Y, Xiang H, Zhu B, Lee SH, Wang W, Tian Z (2015) Resequencing 302 wild and cultivated accessions identifies genes related to domestication and improvement in soybean. Nat Biotechnol 33:408–414CrossRefGoogle Scholar

Copyright information

© This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2019

Authors and Affiliations

  1. 1.Division of Plant SciencesUniversity of MissouriColumbiaUSA
  2. 2.Division of BiochemistryUniversity of MissouriColumbiaUSA
  3. 3.Department of Molecular Biology, Centre of the Region Haná for Biotechnological and Agricultural Research, Faculty of SciencePalacký University in OlomoucOlomoucCzech Republic
  4. 4.Department of Health Management and Informatics and MU Informatics InstituteUniversity of MissouriColumbiaUSA
  5. 5.Département de Phytologie and Institut de Biologie Intégrative et des Systèmes (IBIS)Université LavalQuébecCanada
  6. 6.USDA/ARS Corn Insects and Crop Genetics ResearchAmesUSA
  7. 7.USDA/ARS Plant Genetics Research UnitColumbiaUSA

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