Project description:Purpose: Transcriptional profiling of Oryza sativa japonica Nipponbare roots after one, three and seven days post inoculation with Azoarcus olearius BH72 (vs. non-inoculated controls) to understand the changes in transcriptomic response of rice roots to colonization by bacterial endophyte at initial stages of interaction; Additional set-up was included in which bacterial growth was boosted (through increasing 20-times carbon source - malic acid in the plant's hydroponic medium) to study rice roots transcriptome during enhanced colonization by the endophyte after three days post inoculation. Methods: Rice root mRNA profiles after one day, three days (including additional set-ups for boosted colonization), and seven days post inoculation with Azoarcus olearius BH72 and corresponding non-inoculated controls were generated by RNA sequencing, in triplicates, using Illumina NextSeq 500. Raw reads were then filtered, trimmed (PHRED > 33) and mapped onto IRGSP-1 version of Oryza sativa ssp. japonica cv. Nipponbare genome using CLC Genomics Workbench 8.5.1 (Qiagen, Germany). Expression of 17 selected genes was confirmed via RT-qPCR. Results: Using the RNA-Seq technology we obtained transcriptomic data from 24 sequencing libraries, with an average 46,181,160 clean reads per library, of which 87% or more were mapped onto the Oryza sativa ssp. japonica cv. Nipponbare IRGSP-1.0 genome (Fig. S3). We considered genes as differentially regulated (DEG) that exhibited at least 1.5-fold-change in expression level between Azo-colonized and non-colonized roots and FDR<0.05. Conclusions: Bacteria appeared to short-circuit the initial root defense responses for a compatible interaction during endophytic establishment, involving previously unknown putative rice candidate genes.
Project description:Bacterial panicle blight caused by the bacterium Burkholderia glumae is an emerging disease of rice in the United States. Not much is known about this disease, the disease cycle or any source of disease resistance. To understand the interaction between rice and Burkholderia glumae, we used transcriptomics via next-generation sequencing (RNA-Seq) and bioinformatics to identify differentially expressed transcripts between resistant and susceptible interactions and formulate a model for rice resistance to the disease. There was a total of 36 tissue samples that included 2 rice genotypes (CL 151 and CL 161) à 2 treatment groups (water control and bacterium inoculated) à 3 time points à 3 biological replicates. Note: Samples in SRA were assigned the same sample accession. This is incorrect as there are different samples, hence âSource Nameâ was replaced with new values. Comment[ENA_SAMPLE] contains the original SRA sample accessions.
