Resistance gene analogs in the Brassicaceae: Identification, characterization, distribution, and evolution

Soodeh Tirnaz, Philipp Bayer, Fabian Inturrisi, Fangning Zhang, Hua Yang, Aria Dolatabadian, Ting X Neik, Anita Severn-Ellis, Dhwani Patel, Muhammad I Ibrahim, Aneeta Pradhan, David Edwards, Jacqueline Batley

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)

Abstract

The Brassicaceae consists of a wide range of species, including important Brassica crop species and the model plant Arabidopsis thaliana. Brassica crop diseases impose significant yield losses annually. A major way to reduce susceptibility to disease is the selection in breeding for resistance gene analogs (RGAs). Nucleotide-binding site-leucine-rich repeat (NLR), receptor-like kinases (RLK), and receptor-like proteins (RLP) are the main types of RGAs; they contain conserved domains and motifs and play specific roles in resistance to pathogens. Here, all classes of RGAs have been identified using annotation and assembly-based pipelines in all available genome annotations from the Brassicaceae, including multiple genome assemblies of the same species where available (total of 32 genomes). The number of RGAs, based on genome annotations, varies within and between species. In total 34,065 RGAs were identified with the majority being RLKs (21,691), then NLRs (8,588) and RLPs (3,786). Analysis of the RGA protein sequences revealed a high level of sequence identity, whereby 99.43% of RGAs fell in several orthogroups. This study establishes a resource for the identification and characterization of RGAs in the Brassicaceae and provides a framework for further studies of RGAs for an ultimate goal of assisting breeders in improving resistance to plant disease.

Original languageEnglish
Pages (from-to)909–922
Number of pages14
JournalPlant Physiology
Volume184
Issue number2
DOIs
Publication statusPublished - Oct 2020

Fingerprint

Dive into the research topics of 'Resistance gene analogs in the Brassicaceae: Identification, characterization, distribution, and evolution'. Together they form a unique fingerprint.

Cite this