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Disease Resistance Gene Analogs (RGAs) in Plants.

Sekhwal MK, Li P, Lam I, Wang X, Cloutier S, You FM - Int J Mol Sci (2015)

Bottom Line: Thousands of RGAs have been identified from sequenced plant genomes.High-density genome-wide RGA genetic maps are useful for designing diagnostic markers and identifying quantitative trait loci (QTL) or markers associated with plant disease resistance.Applications in enhancing fine mapping and cloning of plant disease resistance genes are also discussed.

View Article: PubMed Central - PubMed

Affiliation: Cereal Research Centre, Agriculture and Agri-Food Canada, Morden, MB R6M 1Y5, Canada. manoj.sekhwal@agr.gc.ca.

ABSTRACT
Plants have developed effective mechanisms to recognize and respond to infections caused by pathogens. Plant resistance gene analogs (RGAs), as resistance (R) gene candidates, have conserved domains and motifs that play specific roles in pathogens' resistance. Well-known RGAs are nucleotide binding site leucine rich repeats, receptor like kinases, and receptor like proteins. Others include pentatricopeptide repeats and apoplastic peroxidases. RGAs can be detected using bioinformatics tools based on their conserved structural features. Thousands of RGAs have been identified from sequenced plant genomes. High-density genome-wide RGA genetic maps are useful for designing diagnostic markers and identifying quantitative trait loci (QTL) or markers associated with plant disease resistance. This review focuses on recent advances in structures and mechanisms of RGAs, and their identification from sequenced genomes using bioinformatics tools. Applications in enhancing fine mapping and cloning of plant disease resistance genes are also discussed.

No MeSH data available.


Related in: MedlinePlus

A common procedure for identification and characterization of plant RGAs.
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ijms-16-19248-f003: A common procedure for identification and characterization of plant RGAs.

Mentions: Based on previously used approaches, the identification and characterization of RGAs usually follow a common procedure of four steps (Figure 3). First, a plant RGA database including all known plant RGA gene and protein sequences is generated. GenBank [234] and PRGdb [235] are two important sources of well curated RGA sequences. Second, BLAST searches against the RGA database are performed using a loose E-value cut-off (from 1e-5 to 1 depending on the genome size) to identify RGA candidates. Third, using the RGA candidates as input, a variety of software tools (Table 4) are employed to detect various conserved domains and motifs and produce alignments. Some programs like pfam_scan.pl (developed by Sanger) and InterproScan can be run in a parallel mode. In the last step, a dedicated sorting script is needed to group the RGA candidates into classes as per their domain and motif structures or a combination thereof. For example, to be classified as a gene encoding a TNL protein, an RGA must have a 5′ TIR and an NB-ARC followed by an LRR domain.


Disease Resistance Gene Analogs (RGAs) in Plants.

Sekhwal MK, Li P, Lam I, Wang X, Cloutier S, You FM - Int J Mol Sci (2015)

A common procedure for identification and characterization of plant RGAs.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4581296&req=5

ijms-16-19248-f003: A common procedure for identification and characterization of plant RGAs.
Mentions: Based on previously used approaches, the identification and characterization of RGAs usually follow a common procedure of four steps (Figure 3). First, a plant RGA database including all known plant RGA gene and protein sequences is generated. GenBank [234] and PRGdb [235] are two important sources of well curated RGA sequences. Second, BLAST searches against the RGA database are performed using a loose E-value cut-off (from 1e-5 to 1 depending on the genome size) to identify RGA candidates. Third, using the RGA candidates as input, a variety of software tools (Table 4) are employed to detect various conserved domains and motifs and produce alignments. Some programs like pfam_scan.pl (developed by Sanger) and InterproScan can be run in a parallel mode. In the last step, a dedicated sorting script is needed to group the RGA candidates into classes as per their domain and motif structures or a combination thereof. For example, to be classified as a gene encoding a TNL protein, an RGA must have a 5′ TIR and an NB-ARC followed by an LRR domain.

Bottom Line: Thousands of RGAs have been identified from sequenced plant genomes.High-density genome-wide RGA genetic maps are useful for designing diagnostic markers and identifying quantitative trait loci (QTL) or markers associated with plant disease resistance.Applications in enhancing fine mapping and cloning of plant disease resistance genes are also discussed.

View Article: PubMed Central - PubMed

Affiliation: Cereal Research Centre, Agriculture and Agri-Food Canada, Morden, MB R6M 1Y5, Canada. manoj.sekhwal@agr.gc.ca.

ABSTRACT
Plants have developed effective mechanisms to recognize and respond to infections caused by pathogens. Plant resistance gene analogs (RGAs), as resistance (R) gene candidates, have conserved domains and motifs that play specific roles in pathogens' resistance. Well-known RGAs are nucleotide binding site leucine rich repeats, receptor like kinases, and receptor like proteins. Others include pentatricopeptide repeats and apoplastic peroxidases. RGAs can be detected using bioinformatics tools based on their conserved structural features. Thousands of RGAs have been identified from sequenced plant genomes. High-density genome-wide RGA genetic maps are useful for designing diagnostic markers and identifying quantitative trait loci (QTL) or markers associated with plant disease resistance. This review focuses on recent advances in structures and mechanisms of RGAs, and their identification from sequenced genomes using bioinformatics tools. Applications in enhancing fine mapping and cloning of plant disease resistance genes are also discussed.

No MeSH data available.


Related in: MedlinePlus