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ARS Home » Northeast Area » Ithaca, New York » Robert W. Holley Center for Agriculture & Health » Emerging Pests and Pathogens Research » Research » Publications at this Location » Publication #417343

Research Project: Management and Biology of Arthropod Pests and Arthropod-borne Plant Pathogens

Location: Emerging Pests and Pathogens Research

Title: Investigating the soybean cyst nematode microbiome for biocontrol organisms

Author
item GREEN, EMILY - ARS Postdoctoral Research Associate
item Bushley, Kathryn

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 3/6/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Heterodera glycines, the soybean cyst nematode (SCN), is a pathogen damaging soybean crops across the globe. Soybean plant resistance to SCN has been weakening over the last few decades. While plant breeders are working on identifying new resistance loci and for breeding, this process is slow. Other treatments, like nematicides, are extremely harmful to the environment and many have been banned over environmental or health concerns. Therefore, identifying novel biocontrol and biopesticide solutions is urgently needed. We have focused our research on microbial biocontrol organisms, bacteria and fungi, to kill or control SCN populations. We collected samples in Waseca, Minnesota from different field treatments that included long-term (40 year) monoculture of SCN-resistant soybeans, SCN-susceptible soybeans, and soybean fields with an annual rotation of corn and soy, and a field that had grown soybeans for 3 years. The long-term SCN-susceptible field has shown decreases in overall SCN populations over time, potentially a result of the buildup of nematode antagonistic microorganisms in the soil. We sequenced the microbiome of SCN, soybean roots, bulk soil and rhizosphere soil with community amplicon 16S & ITS. Illumina short read metagenomes were generated from SCN cyst samples and PacBio metagenomes from bulk and rhizosphere soil. Through this sampling, we have identified taxa are conserved across sample types, as well as taxa differ between treatments. Future metagenomic analysis will be used to search for differential abundance of taxa across treatments and identify genes of interest of potential biocontrol organisms in metagenomes.