Nucleotide‐binding resistance gene signatures in sugar beet, insights from a new reference genome. (25th June 2018) - Funk, Andrew; Galewski, Paul; McGrath, J. Mitchell
Summary: Nucleotide‐binding (NB‐ARC), leucine‐rich‐repeat genes (NLRs) account for 60.8% of resistance ( R ) genes molecularly characterized from plants. NLRs exist as large gene families prone to tandem duplication and transposition, with high sequence diversity among crops and their wild relatives. This diversity can be a source of new disease resistance, but difficulty in distinguishing specific sequences from homologous gene family members hinders characterization of resistance for improving crop varieties. Current genome sequencing and assembly technologies, especially those using long‐read sequencing, are improving resolution of repeat‐rich genomic regions and clarifying locations of duplicated genes, such as NLRs. Using the conserved NB‐ARC domain as a model, 231 tentative NB‐ARC loci were identified in a highly contiguous genome assembly of sugar beet, revealing diverged and truncated NB‐ARC signatures as well as full‐length sequences. The NB‐ARC‐associated proteins contained NLR resistance gene domains, including TIR, CC and LRR, as well as other integrated domains. Phylogenetic relationships of partial and complete domains were determined, and patterns of physical clustering in the genome were evaluated. Comparison of sugar beet NB‐ARC domains to validated R ‐genes from monocots and eudicots suggested extensive Beta vulgaris ‐specific subfamily expansions. The NLR landscape in the rhizomania resistance conferring Rz region of Chromosome 3 was characterized, identifying 26 NLR‐like sequences spanning 20 MB. This work presents the first detailed view of NLR family composition in a member of the Caryophyllales, builds a foundation for additional disease resistance work in B. vulgaris, and demonstrates an additional nucleic‐acid‐based method for NLR prediction in non‐model plant species. Significance Statement: This work explores signatures of a nucleotide‐binding class of resistance genes in a well‐resolved genome, using a strategy capable of detecting full‐length, fragmented and diverged sequences to identify candidate loci for additional components of disease resistance.