Browsing by Author "Naganeeswaran Sudalaimuthu Asari"

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    Identification of expressed resistance gene analog sequences in coconut leaf transcriptome and their evolutionary analysis
    (2015) Rajesh, M.K.; Rachana, K.E.; Naganeeswaran Sudalaimuthu Asari; Shafeeq Rahman; Regi J. Thomas; Shareefa, M.; Merin Babu; Anitha Karun
    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 (R) 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 (wilt) disease-resistant cultivar Chowghat Green Dwarf. Comprehensive bioinformatics analysis identified 243 resistance gene analog (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.
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    Standalone EST microsatellite mining and analysis tool (SEMAT): for automated EST-SSR analysis in plants
    (2014) Naganeeswaran Sudalaimuthu Asari; Manimekalai Ramaswamy; Elain Apshara Subbian; Manju Kalathil Palliyarakkal; Malhotra, S.K.; Anitha Karun
    Public databases contain large datasets of plant expressed sequence tags (ESTs) that can be used for mining microsatellite/simple sequence repeat markers. The identification and annotation of these markers take considerable time. Here, we describe an efficient, high-throughput microsatellite mining, and analysis pipeline, standalone EST microsatellite mining and analysis tool (SEMAT). The pipeline bundles sequence trimming, assembly, microsatellite identification, primer selection, and blast annotation, for which it consecutively uses SeqClean, CAP3, MISA, Primer3, and Blast. SEMAT is written using Perl scripts, and it runs under Ubuntu and Fedora Linux. SEMAT is an efficient and timesaving bioinformatics tool to accomplish the high throughput EST-SSR analysis. It is freely available from http://semat. cpcribioinformatics.in/.