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ARS Home » Southeast Area » Stuttgart, Arkansas » Dale Bumpers National Rice Research Center » Research » Publications at this Location » Publication #354448

Research Project: Gene Discovery and Crop Design for Current and New Rice Management Practices and Market Opportunities

Location: Dale Bumpers National Rice Research Center

Title: Using high-throughput genotyping and phenotyping to dissect rice-soil microbiome interactions affecting GHG emissions and identify candidate genes affecting rice grain quality

Author
item Barnaby, Jinyoung
item Mcclung, Anna
item Mcclung, Anna
item Kim, Woojae - Rural Development Administration - Korea

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 6/21/2018
Publication Date: 6/25/2018
Citation: Barnaby, J.Y., McClung, A.M., Kim, W. 2018. Using high-throughput genotyping and phenotyping to dissect rice-soil microbiome interactions affecting GHG emissions and identify candidate genes affecting rice grain quality [abstract].RDA-USDA Collaborative Meeting.

Interpretive Summary:

Technical Abstract: As the national research center for rice, USDA-ARS-Dale Bumpers National Rice Research Center (DBNRRC) offers unique genetic resources that are invaluable to sustain and improve U.S. rice production. Dr. Jinyoung Barnaby’s long-term research goal is to develop an integrated multi-omics platform (genetics, genomics, transcriptomics, proteomics, metabolomics, and phenomics) to optimize genetic selection for producing cultivars with high grain quality and/or enhanced tolerance to stresses due to changes in the environment. In this talk, Dr. Barnaby’s ongoing research activities related to rice systems will be discussed: understanding the genetic variation in methane emissions and dissecting the rice rhizosphere soil microbiome affecting methane emissions using next generation sequencing; using high throughput genotyping and phenotyping (GWAS) to identify candidate genes affecting grain quality; examining the genotypic and phenotypic variation to identify the most adaptive rice lines to climate uncertainty using transcriptomics and metabolomics.