SNPs, InDels, and Microsatellites within and Near to Rice NBS-LRR Resistance Gene Candidates

被引:1
|
作者
Quinton-Tulloch, Mark J. [1 ]
Steele, Katherine A. [1 ]
机构
[1] Bangor Univ, Sch Nat Sci, Bangor LL57 2UW, Gwynedd, Wales
来源
AGRONOMY-BASEL | 2021年 / 11卷 / 11期
基金
“创新英国”项目;
关键词
pathogen; resistance; NBS-LRR; NLR; Oryza sativa; rice blast; bacterial blight; NUCLEOTIDE-BINDING SITE; GENOME-WIDE IDENTIFICATION; DISEASE RESISTANCE; ENCODING GENES; WILD-RICE; READ ALIGNMENT; ANNOTATION; EVOLUTION; VARIETIES; FAMILY;
D O I
10.3390/agronomy11112297
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Plant resistance genes (R-genes) drive the immune responses of crops against specific pathotypes of disease-causing organisms. Over time, genetic diversity in R-genes and R-pseudogenes has arisen among different rice varieties. This bioinformatics study was carried out to (i) predict the full sets of candidate nucleotide-binding site leucine-rich repeat (NLR) R-genes present in six rice genomes; (ii) detect variation within candidate R-genes; (iii) identify potential selectable markers within and near to LRR genes among 75 diverse indica rice genomes. Four high quality indica genomes, plus the standard japonica and indica reference genomes, were analysed with widely available bioinformatic tools to identify candidate R-genes and R-pseudogenes. They were detected in clusters, consistent with previous studies. BLAST analysis of cloned protein sequences of 31 R-gene loci gave confidence in this approach for detection of cloned NLR R-genes. Approximately 10% of candidate R-genes were located within 1 kb of a microsatellite (SSR) marker. Sequence comparisons among indica rice genomes detected SNPs or InDels in 334 candidate rice R-genes. There were significantly more SNPs and InDels within the identified NLR R-gene candidates than in other types of gene. The genome-wide locations of candidate R-genes and their associated markers are presented here for the potential future development of improved disease-resistant varieties. Limitations of in silico approaches used for R-gene discovery are discussed.
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页数:19
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