Identification of expressed resistance gene analog sequences in coconut leaf transcriptome and their evolutionary analysis

Authors : Muliyar Krishna RAJESH, Kaitheri Edathil RACHANA, Sudalaimuthu Asari NAGANEESWARAN, Rahman SHAFEEQ, Regi Jacob THOMAS, Mohammed SHAREEFA, Babu MERIN, Karun ANITHA

Pages : 489-0

Doi:10.3906/tar-1409-75

View : 14 | Download : 7

Publication Date : 2015-06-01

Article Type : Research Paper

Abstract :Coconut, an important crop of the tropics and subtropics, is susceptible to a variety of diseases and enhancing disease resistance has been the major goal of coconut breeding programs all over the world. Information on the presence and distribution of disease resistance ® genes, which play a primary role in the detection of pathogens and the initiation of specific plant defenses, is scarce in coconut. In this study, RNA-Seq was used to generate the transcriptome of leaf samples of coconut root insert ignore into journalissuearticles values(wilt); disease-resistant cultivar Chowghat Green Dwarf. Comprehensive bioinformatics analysis identified 243 resistance gene analog insert ignore into journalissuearticles values(RGA); sequences, comprising 6 classes of RGAs. Domain and conserved motif predictions of clusters were performed to analyze the architectural diversity. Phylogenetic analysis of deduced amino acid sequences revealed that coconut NBS-LRR type RGAs were classified into distinct groups based on the presence of TIR or CC motifs in the N-terminal regions. Furthermore, qRT-PCR analysis validated the expression of randomly selected NBS-LRR type RGAs. The results of this study provide a sequence resource for development of RGA-tagged markers in coconut, which would aid mapping of disease-resistant candidate genes. In addition, we hope that this study will provide a genomic framework for isolation of additional RGAs in coconut via comparative genomics and also contribute to the deciphering of mode of evolution of RGAs in Arecaceae.
Keywords : Coconut, disease, phylogeny, resistance gene analogs, transcriptome