Skip to main content
ARS Home » Midwest Area » East Lansing, Michigan » Sugarbeet and Bean Research » Research » Publications at this Location » Publication #325304

Title: Leveraging long sequencing reads to investigate R-gene clustering and variation in sugar beet

item FUNK, ANDREW - Michigan State University
item McGrath, Jon

Submitted to: Plant and Animal Genome Conference
Publication Type: Abstract Only
Publication Acceptance Date: 1/8/2016
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Host-pathogen interactions are of prime importance to modern agriculture. Plants utilize various types of resistance genes to mitigate pathogen damage. Identification of the specific gene responsible for a specific resistance can be difficult due to duplication and clustering within R-gene families. Furthermore, non-model species suffer from less-developed genomic resources than model crops, leading to additional uncertainty in location and copy number of closely-related genes. Here we utilize a new genome assembly of Beta vulgaris generated with the PacBio sequencing platform to clarify R-gene localization and clustering in sugar beet. Special attention is given to the resistance locus Rz1, which confers resistance to the disease rhizomania induced by beet necrotic yellow vein virus (BNYVV). This locus was identified and mapped over 15 years ago but the underlying gene has yet to be identified. As a step toward identifying the gene or genes responsible for rhizomania resistance, Hidden Markov Models were constructed from resistance genes of model systems as well as B. vulgaris. These models were used to interrogate the new genomic sequences and identify resistance genes in the region of the Rz1 locus. Phylogenetic analysis of the underlying genes reveals possible paralogs and provides candidate genes for further characterization of rhizomania resistance.