The interactions between crop plants and the endophytic bacteria colonizing them are poorly understood and experimental methods were found to be inadequate to meet the complexities associated with the interaction. Moreover, research on endophytic bacteria was focused at host plant species level and not at cultivar level which is essential for understanding the role played by them on the productivity of specific crop genotype. High throughput genomics offers valuable tools for identification, characterization of endophytic bacteria and understand their interaction with host plants. In this paper we report the use of high throughput plant genomic data for identification of endophytic bacteria colonizing rice plants. Using this novel next generation sequencing based computational method Sphingopyxis granuli and Pseudomonas aeruginosa were identified as endophytes colonizing the elite indica rice cultivar RP Bio-226 and their draft genome sequences were assembled.

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Reference based assembly of genomic reads of the elite indica rice cultivar RP Bio-226 was carried out against 2101 reference bacterial genomes using Bowtie-2 genome assembly tool. Five types of data: Number of paired end reads concordantly aligned exactly only once, number of paired end reads concordantly aligned more than once, number of mates that make the pairs aligned exactly only once, number of mates that make the pairs aligned more than once and overall percentage of alignment were collected. Interpretation of the results and identification of endophytes based on these alignment statistics are described in detail in our research article “L.Battu, M.M. Reddy, B.S.Goud, K.Ulaganathan, K.Ulaganathan, Genome inside genome:NGS based identification and assembly of endophytic Sphingopyxis granuli and Pseudomonas aeruginosa genomes from rice genomic reads, Genomics (in press)”.