Database Research Summaries
2018 Molecular Quantification of Soybean Cyst Nematodes in Soil in North Dakota

calendar_today Year of Research: 2018
update Posted On: 12/05/2019
group Guiping Yan (Principal Investigator, North Dakota State University)
bookmark North Dakota Soybean Council

Research Focus

The focus of this project is to develop new real-time PCR primers and procedures (DNA-based) for specific and sensitive detection and quantification of SCN directly from soybean field soils and to differentiate SCN from other closely related nematode species.


  • Design new highly specific real-time PCR primers to detect SCN in soil and to discriminate it from sugar beet cyst nematode and other nematode species that are known to occur or may occur in ND.
  • Develop a real-time PCR assay to quantify SCN directly from DNA extracts of field soils and validate that assay using artificially inoculated and naturally infested soils.


  1. They designed qPCR primers (SCNF/SCNR), which showed high specificity to SCN. The specificity of the primers was evaluated using seven isolates of SCN and 31 other nematode species. Varying numbers of SCN eggs or juveniles (0, 1, 4, 16, 64, 256) were inoculated into 0.25 g sterilized soil from which soil DNA was extracted. A standard curve relating threshold cycle and log values of nematode number was generated. Quantifying different SCN numbers artificially added to a sterilized soil validated the assay.
  2. The validated assay was used to estimate SCN numbers in 34 field soil samples from ND naturally infested with the nematode at varying levels. For each soil sample, 400 g of soil was collected and divided in half for molecular quantification, and traditional SCN extraction and microscopic enumeration.
  3. Another primer pair was developed (CLE2F/CLE2R) specific to both SCN and SBCN but are able to separate them simultaneously. Finally, they found that different soil textural classes might have effects on quantification efficiency as soils with more clay content may inhibit qPCR amplification.



  • Results of this research will allow farmers to avoid time-consuming steps for manual nematode extractions, microscopic identification and counting of the nematodes from field samples with mixed populations of other nematode species.
  • This research provides a distinction method between SCN and other closely related cyst nematodes for effective SCN management using crop rotation.

For more information about this research project, please visit the National Soybean Checkoff Research Database.

Funded in part by the soybean checkoff.