Project description:Purpose:we aimed to demonstrate the effects of cycloastragenol on the different plant signaling mechanisms and analyze microRNAomic responses in order to demonstrate its potential as a new key molecule to help plants overcome different environmental stresses. Methods: smallRNA-seq was employed to give a quantitative profile of microRNA expression and to identify new micro RNAs and in treated and non-treated A. thaliana calli. We sequenced two cDNA libraries developed from A. thaliana (wild type Col-0) calli, one non-treated and the other is treated with 1µM cycloatragenol. Reads were filtered, mapped, aligned and then compared to the reference annotation (miRBase database). Clean data was analyzed using different software in order to identify differentilly expressed miRNAs and their target genes. Results were validated by qRT-PCR using TaqMan and SYBER green assays. Results: We mapped more than 31 and 30 million tags from, respectively, control and CAG-treated samples. After filtration and mapping, a total of 273 known micro RNAs, 298 novels expressed miRNAs and 6160 target genes were identified, among which a total of 119 miRNAs and 961 target genes showed differential expression between control and treated sample with a p value < 0.05. Nine miRNAs, which have been chosen randomly, were validated with qRT-PCR. SmallRNA-seq data had a linear relationship with qRT-PCR for a goodness of fit (R2) of 0.938.
Project description:Purpose: we aimed to demonstrate the effects of Cycloastragenol on the different plant signaling mechanisms and analyze genome-wide transcriptional responses in order to demonstrate its potential as a new key molecule to help plants overcome different environmental stresses. Methods: RNA-seq was employed to assess transcriptional profiles in treated and non-treated A. thaliana calli. We sequenced two cDNA libraries developed from A. thaliana (wild type Col-0) calli treated with 1µM Cycloatragenol and without. The sequence reads that was filtered, were mapped, aligned and then compared to the reference annotation (the known genes of A. thaliana genome) using Cufflinks tools. Clean data was analyzed using CPC software and results were validated by qRT-PCR using TaqMan and SYBER green assays. Results: We mapped around 63 and 70 million sequence reads from, respectively, control and CAG-treated samples. After filtration and mapping about 21 thousands genes corresponding to an average of 34 thousands transcripts, for each sample were identified. 1045 genes showed differential expression between control and treated sample with a p value < 0.05. Seven genes, which have been chosen randomly, were validated with qRT-PCR. RNA-seq data had a linear relationship with qRT-PCR for a goodness of fit (R2) of 0.959.
Project description:Small RNA sequences from Arabidopsis thaliana Col-0 inflorescence tissues of three biological replicates. The data were analyzed to identify non-templated nucleotides in Arabidopsis small RNAs.
Project description:Small RNA diversity and function has been widely characterized in various tissues of the sporophytic generation of the angiosperm model Arabidopsis thaliana. In contrast, there is limited knowledge about small RNA diversity and their roles in developing male gametophytes. We thus carried out small RNA sequencing on RNA isolated from four stages of developing Arabidopsis thaliana pollen.
Project description:High-throughput sequencing of Arabidopsis thaliana endogenous small RNAs by 454 pyrosequencing. Keywords: high-throughput sequencing
Project description:microRNA dysregulation is a common feature of cancer cells, but the complex roles of microRNAs in cancer are not fully elucidated. Here we used functional genomics to identify oncogenic microRNAs in non-small cell lung cancer and to evaluate their impact on response to EGFR targeting therapy. Our data demonstrate that microRNAs with an AAGUGC-motif in their seed-sequence increase both cancer cell proliferation and sensitivity to EGFR inhibitors. Global transcriptomics, proteomics and target prediction resulted in the identification of several tumor suppressors involved in the G1/S transition as targets of AAGUGC-microRNAs. The clinical implications of our findings were evaluated by analysis of public domain data supporting the link between this microRNA seed-family, their tumor suppressor targets and cancer cell proliferation. In conclusion we propose that AAGUGC-microRNAs are an integral part of an oncogenic signaling network, and that these findings have potential therapeutic implications, especially in selecting patients for EGFR-targeting therapy.
Project description:Small RNA sequences from Arabidopsis thaliana Col-0 inflorescence tissues of three biological replicates. The data were analyzed to identify non-templated nucleotides in Arabidopsis small RNAs. Inflorescence samples are collected from three biological replicates of Col-0 wild-type Arabidopsis plants.
Project description:WUS is the key regulator in stem cell induction and maintenance. We performed the small RNA high throughput sequencing to test whether WUS is involved in stabilizing RNA structure in Arabidopsis thaliana.
Project description:Like protein coding genes, loci that produce microRNAs (miRNAs) are generally considered to be under purifying selection, consistent with miRNA polymorphisms being able to cause disease. Nevertheless, it has been hypothesized that variation in miRNA genes may contribute to phenotypic diversity. Here we demonstrate that a naturally occurring polymorphism in the MIR164A gene interacts epistatically with an unlinked locus to affect leaf shape and shoot architecture in Arabidopsis thaliana. A single-base pair substitution in the miRNA complementary sequence alters the stability of the miRNA:miRNA* duplex. It thereby interferes with processing of the precursor and greatly reduces miRNA accumulation. We demonstrate that this is not a rare exception, but that natural strains of Arabidopsis thaliana harbor dozens of similar polymorphisms that affect processing of a wide range of miRNA precursors. Our results suggest that natural variation in miRNA processability due to cis mutations is a common contributor to phenotypic variation in plants.