Dataset Information

ARA-PEPs : a repository of putative sORF-encoded peptides in Arabidopsis thaliana

ABSTRACT: Many eukaryotic RNAs have been considered non-coding as they only contain short open reading frames (sORFs). There is increasing evidence for the translation of these sORFs into bioactive peptides. Yet only a few small peptides are annotated in the model organism Arabidopsis thaliana. To aid the functional annotation of small peptides, we have developed ARA-PEPs, a repository and webserver of putative peptides encoded by sORFs in the Arabidopsis genome from in house Tiling arrays, RNA sequencing and from publicly available datasets. In order to identify novel oxidative stress-induced peptides in Arabidopsis thaliana a tiling array analysis (GeneChip® Arabidopsis Tiling 1.0R Arrays ) was performed on mRNA extracted from leaves inoculated with Botrytis cinerea (BC). Normalized log signals were obtained using the Affymetrix Tiling Analysis Software - Version 1.1, Build 2. ON and OFF probes were selected using a threshold, based on positive controls. Next, groups of 4-13 successive ON probes were combined into short TARs and a selection was made of TARs having an average signal intensity at least 2.6-fold higher after BC treatment compared to the control treatment, resulting in 195 BC induced TARs.

ORGANISM(S): Arabidopsis thaliana

PROVIDER: GSE84002 | GEO | 2016/12/23

SECONDARY ACCESSION(S): PRJNA327795

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Experiments conducted on this tiling array are used to (1) validate the frozen gene sets of the current genome annotation, (2) improve the predicted gene structures by empirically determining UTRs and intron-exon boundaries, identifying missing upstream, internal, and downstream exons and alternative transcripts, (3) propose gene structure models in transcribed regions containing no predicted genes and (4) delineate transcriptionally active regions of the genome from intergenic, intronic and genic regions. Signal to background ratios were determined by first calling probes that fluoresced at intensities greater than 99% of the random probes’ signal intensities; therefore only 1% of fluorescing experimental probes should be false positives. We conducted two-color competitive hybridizations that measure differential expression from three replicates, each using RNA from independent biological extractions. Transcriptional active regions (TARs) were defined by stringing together overlapping probes showing fluorescence above a 1% false positive rate (FPR). Positive probes were joined into a TAR if they were adjacent (maxgap=0, no intermittent non-positive probe) and a TAR’s length had to be at least 45 bp (minrun=45, mid-point first positive probe to mid-point last positive probe, resulting in at least 3 adjacent positive probes for a TAR). Transcriptional active regions (TARs) were defined by stringing together overlapping probes showing fluorescence above a 1% false positive rate (FPR). The data analysis to measure differential expression of genes and of unannotated TARs was performed using the statistical software package R and Bioconductor with additions and modifications. The signal distributions across chips, samples and replicates were adjusted to be equal according to the mean fluorescence of the random probes on each array. All probes including random probes were quantile-normalized across replicates. Expression-level scores were assigned for each predicted gene based on the median log2 fluorescence over background intensity of probes falling within the exon boundaries.

Dataset Information

ARA-PEPs : a repository of putative sORF-encoded peptides in Arabidopsis thaliana

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure