Project description:Transcript profile of 10 days-old seedlings over expressing miR396 Experiment Overall Design: 2 samples from 35S:miR396 plants vs 2 samples of wild type plants
Project description:A first line of defense against pathogen infections is the recognition of pathogen-associated molecular patterns (PAMPs), leading to PAMP-triggered immunity (PTI). MicroRNAs (miRNAs) are primarily known as central regulators of plant development, but a few have also been connected to immunity. We have found that several fungal pathogens lead to a reduction in miR396 levels, suggesting that miR396 are negative regulators of downstream defense responses. In agreement with such as scenario, constitutive attenuation of miR396 activity enhances resistance to infection by fungal pathogens, while increased miR396 activity reduces pathogen resistance. We conclude that constitutive reduction of miR396 levels confer a primed state for enhanced defense reactions
Project description:Arabidopsis Affymetrix ATH1 GeneChips were used to compare the mRNA profiles of root tissues of the grf1/grf2/grf3 triple mutant and transgenic plants overexpressing miR396-resistant variants of GRF1 (P35S:rGRF1) or GRF3 (P35S:rGRF3) with those of the corresponding wild-type (Col-0 or WS). Wild-type (Arabidopsis thaliana ecotypes Col-0 and Ws), the triple mutant grf1/grf2/grf3, and transgenic plants overexpressing rGRF1 or rGRF3 were grown in vertical culture dishes on modified Knop’s medium for 2 weeks and then root tissues were collected for RNA extraction. ****[PLEXdb(http://www.plexdb.org) has submitted this series at GEO on behalf of the original contributor, Tarek Hewezi. The equivalent experiment is AT109 at PLEXdb.]
Project description:The root apex is an important section of the plant root, involved in environmental sensing and cellular development. Analyzing the gene profile of root apex in diverse environments is important and challenging, especially when the samples are limiting and precious, such as in spaceflight. The feasibility of using tiny root sections for transcriptome analysis was examined in this study.To understand the gene expression profiles of the root apex, Arabidopsis thaliana Col-0 roots were sectioned into Zone-I (0.5 mm, root cap and meristematic zone) and Zone-II (1.5 mm, transition, elongation and growth terminating zone). Gene expression was analyzed using microarray and RNA seq.Both the techniques, arrays and RNA-Seq identified 4180 common genes as differentially expressed (with > two-fold changes) between the zones. In addition, 771 unique genes and 19 novel TARs were identified by RNA-Seq as differentially expressed which were not detected in the arrays. Single root tip zones can be used for full transcriptome analysis; further, the root apex zones are functionally very distinct from each other. RNA-Seq provided novel information about the transcripts compared to the arrays. These data will help optimize transcriptome techniques for dealing with small, rare samples.
Project description:The root apex is an important section of the plant root, involved in environmental sensing and cellular development. Analyzing the gene profile of root apex in diverse environments is important and challenging, especially when the samples are limiting and precious, such as in spaceflight. The feasibility of using tiny root sections for transcriptome analysis was examined in this study.To understand the gene expression profiles of the root apex, Arabidopsis thaliana Col-0 roots were sectioned into Zone-I (0.5 mm, root cap and meristematic zone) and Zone-II (1.5 mm, transition, elongation and growth terminating zone). Gene expression was analyzed using microarray and RNA seq.Both the techniques, arrays and RNA-Seq identified 4180 common genes as differentially expressed (with > two-fold changes) between the zones. In addition, 771 unique genes and 19 novel TARs were identified by RNA-Seq as differentially expressed which were not detected in the arrays. Single root tip zones can be used for full transcriptome analysis; further, the root apex zones are functionally very distinct from each other. RNA-Seq provided novel information about the transcripts compared to the arrays. These data will help optimize transcriptome techniques for dealing with small, rare samples.