Project description:Waterlogging is a major abiotic stress causing oxygen depletion and carbon dioxide accumulation in the rhizosphere. Barley is more susceptible to waterlogging stress than other cereals. To gain a better understanding of the effect of waterlogging stress in barley, we carried out a genome-wide gene expression analysis in roots of Yerong and Deder2 barley genotypes under waterlogging and control (well-watered) conditions by RNA-Sequencing, using Illumina HiSeq™ 4000 platform.
Project description:Chevallier is a heritage english landrace of barley first planted in 1820 while Tipple is modern cultivar of barley released in 2004. Pseudomonas strains were isolated from the rhizospheres of the two varieties and 22 and 20 of the most phylogenetically distinct ones were sequenced to find out the difference in genotypes preferentially selected in the rhizospheres of the two cultivars.
Project description:Pseudomonas fluorescens SBW25 cultures were inoculated into the rhizospheres of barley seedlings of the Chevallier and Tipple varieties growing in axenic cultures. Bacterial cells were collected from the rhizosphere one and five days after inculation and RNA extracted from them. Culture used for inoculation (but not exposed to the rhizospheres) were used as control. The aim of the experiment was to determine the changes in gene expression of P. fluorescens SBW25 upon exposure to barley rhizosphere and also to determine if the rhizospehres of the two varieties of Barley had different effects on gene expression of P. fluorescens SBW25.
Project description:Structure and functions of the bacterial root microbiota in wild and domesticated barley and signatures of positive selection in the rhizosphere metagenome
Project description:Microbial communities in the rhizosphere make significant contributions to crop health and nutrient cycling. However, their ability to perform important biogeochemical processes remains uncharacterized. Important functional genes, which characterize the rhizosphere microbial community, were identified to understand metabolic capabilities in the maize rhizosphere using GeoChip 3.0-based functional gene array method.