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accession-icon SRP151817
Genome-wide identification of putative translation regulator cis-Natural Antisense Transcripts in Arabidopsis thaliana
  • organism-icon Arabidopsis thaliana
  • sample-icon 69 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

The development of high-throughput genomic technologies has revealed that a large fraction of the genomes of eukaryotes is associated with the expression of noncoding RNAs. One class of noncoding RNA, the cis-natural antisense transcripts (cis-NATs), are particularly interesting as they are at least partially complementary to the protein-coding mRNAs. Although most studies described cis-NATs involved in the regulation of transcription, a few reports have shown recently that cis-NATs can also regulate translation of the cognate sense coding genes in plants and mammals. In order to identify novel examples of translation regulator cis-NATs in Arabidopsis thaliana, we designed a high-throughput experiment based on polysome profiling and RNA-sequencing. Expression of cis-NATs and translation efficiency of the cognate coding mRNAs were measured in roots and shoots in response to various conditions, including phosphate deficiency and treatment with phytohormones. We identified several promising candidates, and validated a few of them experimentally, in Arabidopsis thaliana transgenic lines over-expressing in trans the translation regulator candidate cis-NATs. Overall design: total RNA and polysomal RNA was sequenced from Arabidopsis thaliana whole seedlings grown in high or low pohsphate content, or from roots or shoots from seedlings treated or not with different phytohormones (Ctrl, IAA, ABA,MeJA and ACC). 3 biological replicates were analyzed for each of the 12 experimental conditions.

Publication Title

Prediction of regulatory long intergenic non-coding RNAs acting in trans through base-pairing interactions.

Sample Metadata Fields

Specimen part, Treatment, Subject

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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