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A genome-wide comparison of NB-LRR type of resistance gene analogs (RGA) in the plant kingdom.


ABSTRACT: Plants express resistance (R) genes to recognize invaders and prevent the spread of pathogens. To analyze nucleotide binding site, leucine-rich repeat (NB-LRR) genes, we constructed a fast pipeline to predict and classify the R gene analogs (RGAs) by applying in-house matrices. With predicted ~37,000 RGAs, we can directly compare RGA contents across entire plant lineages, from green algae to flowering plants. We focused on the highly divergent NBLRRs in land plants following the emergence of mosses. We identified entire loss of Toll/Interleukin-1 receptor, NBLRR (TNL) in Poaceae family of monocots and interestingly from Mimulus guttatus (a dicot), which leads to the possibility of species-specific TNL loss in other sequenced flowering plants. Using RGA maps, we have elucidated a positive correlation between the cluster sizes of NB-LRRs and their numbers. The cluster members were observed to consist of the same class of NB-LRRs or their variants, which were probably generated from a single locus for an R gene. Our website ( http://sol.kribb.re.kr/PRGA/ ), called plant resistance gene analog (PRGA), provides useful information, such as RGA annotations, tools for predicting RGAs, and analyzing domain profiles. Therefore, PRGA provides new insights into R-gene evolution and is useful in applying RGA as markers in breeding and or systematic studies.

SUBMITTER: Kim J 

PROVIDER: S-EPMC3887800 | biostudies-other | 2012 Apr

REPOSITORIES: biostudies-other

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A genome-wide comparison of NB-LRR type of resistance gene analogs (RGA) in the plant kingdom.

Kim Jungeun J   Lim Chan Ju CJ   Lee Bong-Woo BW   Choi Jae-Pil JP   Oh Sang-Keun SK   Ahmad Raza R   Kwon Suk-Yoon SY   Ahn Jisook J   Hur Cheol-Goo CG  

Molecules and cells 20120326 4


Plants express resistance (R) genes to recognize invaders and prevent the spread of pathogens. To analyze nucleotide binding site, leucine-rich repeat (NB-LRR) genes, we constructed a fast pipeline to predict and classify the R gene analogs (RGAs) by applying in-house matrices. With predicted ~37,000 RGAs, we can directly compare RGA contents across entire plant lineages, from green algae to flowering plants. We focused on the highly divergent NBLRRs in land plants following the emergence of mos  ...[more]

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