Skip to main content
Log in

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

  • Published:
Molecular Breeding Aims and scope Submit manuscript

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.

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

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /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.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • 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 4:1307–1318

    Article  CAS  Google Scholar 

  • Bailey M, Mian M, Carter T, Ashley D, Boerma H (1997) Pod dehiscence of soybean: identification of quantitative trait loci. J Hered 88:152–154

    Article  CAS  Google Scholar 

  • 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 7:17195

    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  Google Scholar 

  • Carter TE, Nelson RL, Sneller CH, Cui Z (2004) Genetic diversity in soybean. Soybeans: Improvement, production, and uses:303–416

  • Chen Y, Nelson RL (2004) Genetic variation and relationships among cultivated, wild, and semiwild soybean. Crop Sci 44:316–325

    Article  CAS  Google Scholar 

  • 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 5:3352

    Article  Google Scholar 

  • 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 18:161

    Article  Google Scholar 

  • Food and Agriculture Organization of the United Nations (2014) FAOSTAT statistics database. http://www.fao.org/faostat. Accessed 5 Feb 2019

  • 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 111:6147–6152

    Article  CAS  Google Scholar 

  • 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 111:17797–17802

    Article  CAS  Google Scholar 

  • Gao M, Zhu H (2013) Fine mapping of a major quantitative trait locus that regulates pod shattering in soybean. Mol Breed 32:485–491

    Article  Google Scholar 

  • Goldsmith PD (2008) Economics of soybean production, marketing and utilization. Soybeans Chemistry, Production, Processing, and Utilization:117–150

  • Grant D, Nelson RT, Cannon SB, Shoemaker RC (2009) SoyBase, the USDA-ARS soybean genetics and genomics database. Nucleic Acids Res 38:D843–D846

    Article  Google Scholar 

  • Hymowitz T (1970) On the domestication of the soybean. Econ Bot 24:408–421

    Article  Google Scholar 

  • 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 103:16666–16671

    Article  CAS  Google Scholar 

  • 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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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–D1252

    Article  Google Scholar 

  • 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 149–159

  • 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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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 42:1053–1059

    Article  CAS  Google Scholar 

  • 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 100:1027–1038

    Article  CAS  Google Scholar 

  • 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):337

  • Masuda T, Goldsmith PD (2009) World soybean production: area harvested, yield, and long-term projections. Int Food Agribusiness Manag Rev 12:143–162

    Google Scholar 

  • 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

  • Saxe L, Clark C, Lin S, Lumpkin T (1996) Mapping the pod-shattering trait in soybean. Soybean Genetics Newsletter (USA)

  • Singh U, Singh B (1992) Tropical grain legumes as important human foods. Econ Bot 46:310–321

    Article  Google Scholar 

  • 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:e54985

    Article  CAS  Google Scholar 

  • Suzuki M, Fujino K, Funatsuki H (2009) A major soybean QTL, qPDH1, controls pod dehiscence without marked morphological change. Plant Prod Sci 12:217–223

    Article  CAS  Google Scholar 

  • 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 175:251–260

    Article  Google Scholar 

  • Wansink B, Cheong J (2002) Taste profiles that correlate with soy consumption in developing countries. Pak J Nutr 1:276–278

    Article  Google Scholar 

  • 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 33:408–414

    Article  CAS  Google Scholar 

Download references

Funding

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.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kristin Bilyeu.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(XLSX 23 kb)

ESM 2

(XLSX 15 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Miranda, C., Culp, C., Škrabišová, M. et al. Molecular tools for detecting Pdh1 can improve soybean breeding efficiency by reducing yield losses due to pod shatter. Mol Breeding 39, 27 (2019). https://doi.org/10.1007/s11032-019-0935-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11032-019-0935-1

Keywords

Navigation