Characterization of disease resistance genes in the Brassica napus pangenome reveals significant structural variation. Issue 4 (10th October 2019)

• Record Type: Journal Article
• Authors: Dolatabadian, Aria; Bayer, Philipp E.; Tirnaz, Soodeh; Hurgobin, Bhavna; Edwards, David; Batley, Jacqueline
• Is Part Of: Plant biotechnology journal. Volume 18:Issue 4(2020)
• Page Start: 969
• Page End: 982
• Publication Date: 2019-10-10
• Subjects: Brassica napus -- pangenome -- RGAugury -- presence/absence variation -- resistance gene; Plant biotechnology -- Periodicals; Plant genetic engineering -- Periodicals; 630.272
• DOI: 10.1111/pbi.13262
• Languages: English
• ISSNs: 1467-7644

Abstract

Summary: Methods based on single nucleotide polymorphism (SNP), copy number variation (CNV) and presence/absence variation (PAV) discovery provide a valuable resource to study gene structure and evolution. However, as a result of these structural variations, a single reference genome is unable to cover the entire gene content of a species. Therefore, pangenomics analysis is needed to ensure that the genomic diversity within a species is fully represented. Brassica napus is one of the most important oilseed crops in the world and exhibits variability in its resistance genes across different cultivars. Here, we characterized resistance gene distribution across 50 B. napus lines. We identified a total of 1749 resistance gene analogs (RGAs), of which 996 are core and 753 are variable, 368 of which are not present in the reference genome (cv. Darmor‐ bzh ). In addition, a total of 15 318 SNPs were predicted within 1030 of the RGAs. The results showed that core R‐genes harbour more SNPs than variable genes. More nucleotide binding site‐leucine‐rich repeat (NBS‐LRR) genes were located in clusters than as singletons, with variable genes more likely to be found in clusters. We identified 106 RGA candidates linked to blackleg resistance quantitative trait locus (QTL). This study provides a better understanding of resistance genes to target for genomics‐based improvement and improved disease resistance.