2018
Molecular Quantification of Soybean Cyst Nematodes in Soil in North Dakota
Contributor/Checkoff:
Category:
Sustainable Production
Keywords:
Biotic stressCrop protectionField management Pest
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Guiping Yan, North Dakota State University
Co-Principal Investigators:
Project Code:
QSSB
Contributing Organization (Checkoff):
Institution Funded:
Brief Project Summary:

Soybean cyst nematode (SCN; Heterodera glycines) is a major pathogen posing greater disease threat to soybean production than any other pathogen in the USA. This nematode was first found in North Dakota in 2003 and quickly spread within the state and is currently found in at least 19 counties. SCN is a soil-borne pathogen and hence is readily transported from field to field on any equipment carrying soil and poses the greatest threat to soybean production in North Dakota. The severity of the disease caused by SCN varies depending on population densities of the nematode present in the soil. Therefore, it is important to determine the population levels of the nematode in soil to assess soil...

Unique Keywords:
#insects and pests
Information And Results
Project Deliverables

The molecular assay we propose to develop would improve SCN detection and quantification efficiency in soybean fields in North Dakota, prevent false positive detections for soil samples submitted by growers, and allow growers to rapidly assess fields to determine the level and risk of SCN prior to planting. Reliable differentiation and quantification of SCN are critical for management of the nematode to improve soil health and soybean yield.

Final Project Results

Update:

View uploaded report Word file

MOLECULAR QUANTIFICATION OF SOYBEAN CYST NEMATODES IN SOIL IN NORTH DAKOTA

EXECUTIVE SUMMARY
NORTH DAKOTA SOYBEAN COUNCIL
JUNE, 2018

Principal Investigator:
Dr. Guiping Yan, Dept. Plant Pathology, NDSU

The soybean cyst nematode (SCN) continues to be a major threat to soybean production in North Dakota (ND). Other nematodes including sugar beet cyst nematode (SBCN), clover cyst nematode and cereal cyst nematode may occur in ND fields. These nematodes are traditionally differentiated based on morphology. However, distinction between SCN and these nematodes using the traditional method is not only difficult and time-consuming but also requires expertise in nematode taxonomy. The primary goal of this project was to develop a molecular identification and quantification tool for SCN alternative to the traditional method. The specific objectives were to design real-time PCR (qPCR) primers to detect SCN in soil and discriminate it from SBCN and other species, and to develop a qPCR assay to quantify SCN from DNA extracts of field soils.

In this project, we 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. The assay was validated by quantifying different SCN numbers artificially added to a sterilized soil.

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. We also designed another primer pair (CLE2F/CLE2R) specific to both SCN and SBCN but are able to separate them simultaneously. Finally, we found that different soil textural classes may have effects on quantification efficiency as soils with more clay content may inhibit qPCR amplification.

The developed molecular assay provides a platform to detect and quantify SCN specifically and directly from DNA extracts of field soils obviating the time-consuming steps of nematode extraction, microscopic identification and counting. The qPCR assay is highly specific to SCN and will improve SCN detection efficiency in soybean fields in ND and help prevent false positive or negative detection results for soil samples submitted by growers. Further, this assay provides a distinction method between SCN and other closely related cyst nematodes for effective SCN management using crop rotation.

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.