Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A spectral analysis approach to detects actively translated open reading frames in high resolution ribosome profiling data

ABSTRACT: RNA sequencing protocols allow for quantifying gene expression regulation at each individual step, from transcription to protein synthesis. Ribosome Profiling (Ribo-seq) maps the positions of translating ribosomes over the entire transcriptome. Despite its great potential, a rigorous statistical approach to identify translated regions from Ribo-seq data is not yet available. To fill this gap, we developed RiboTaper, which quantifies the significance of the three-nucleotide periodicity of Ribo-seq reads via spectral analysis methods.

ORGANISM(S): Homo sapiens

PROVIDER: GSE73136 | GEO | 2015/11/12

SECONDARY ACCESSION(S): PRJNA296059

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

A spectral analysis approach to detects actively translated open reading frames in high resolution ribosome profiling data

Project description:RNA sequencing protocols allow for quantifying gene expression regulation at each individual step, from transcription to protein synthesis. Ribosome Profiling (Ribo-seq) maps the positions of translating ribosomes over the entire transcriptome. Despite its great potential, a rigorous statistical approach to identify translated regions from Ribo-seq data is not yet available. To fill this gap, we developed RiboTaper, which quantifies the significance of the three-nucleotide periodicity of Ribo-seq reads via spectral analysis methods. Examination of RNA fragments protected by ribosome

2015-11-12 | E-GEOD-73136 | biostudies-arrayexpress

SPECtre: a spectral coherence-based classifier of actively translated transcripts from ribosome profiling sequence data

Project description:Active protein translation can be assessed and measured using ribosome profiling sequencing strategies. Existing approaches make use of sequence fragment length or frame occupancy to differentiate between active translation and background noise, however they do not consider additional characteristics inherent to the technology which limits their overall accuracy. Here, we present an analytical tool that models the overall tri-nucleotide periodicity of ribosomal occupancy using a classifier based on spectral coherence. Our software, SPECtre, examines the relationship of normalized ribosome profiling read coverage over a rolling series of windows along a transcript against an idealized reference signal. A comparison of SPECtre against current methods on existing and new data shows a marked improvement in accuracy for detecting active translation and exhibits overall high sensitivity at a low false discovery rate.

2016-07-01 | GSE75947 | GEO

SPECtre: a spectral coherence-based classifier of actively translated transcripts from ribosome profiling sequence data

2016-07-01 | E-GEOD-75947 | biostudies-arrayexpress

Standardized annotation of translated open reading frames.

Project description: Not available

| S-EPMC9757701 | biostudies-literature

Identification of translated small open reading frames in lymphocytes

Project description:Open reading frames (ORFs) are the genomic DNA sequences that have the potential to be translated. Genome annotation pipelines dismiss translation products of small ORFs (smORFs) of less than 100 codons (<300 nucleotides) as being unlikely to have a biological function. In this study, we systematically characterized smORFs in mouse B and T cells under different conditions and predicted a total of 5744 unique actively translated smORFs. We then extended our analysis to ORFs of 101-200 codons in length and predicted 945 of such longer translation products. Additionally, our results have suggested the existence of candidate secreted micropeptides. Furthermore, verifying their existence and identifying their functions will be essential and potentially lead to useful applications.

2021-04-28 | GSE154491 | GEO

RiboReport - Benchmarking ribosome profiling based identification of open reading frames in bacteria.

Project description:Generation of a Ribo-seq dataset for E. coli MG1655 for benchmarking Ribo-seq analysis tools

2022-05-20 | GSE131514 | GEO

RibORF: Identifying Genome-Wide Translated Open Reading Frames Using Ribosome Profiling.

Project description:Ribosome profiling identifies RNA fragments associated with translating ribosomes. The technology provides an opportunity to examine genome-wide translation events at single-nucleotide resolution and in an unbiased manner. Here I present a computational pipeline named RibORF to systematically identify translated open reading frames (ORFs), based on read distribution features representing active translation, including 3-nt periodicity and uniformness across codons. Analyses using the computational tool revealed pervasive translation in putative 'noncoding' regions, such as lncRNAs, pseudogenes, and 5'UTRs. The computational tool is useful for studying functional roles of non-canonical translation events in various biological processes. © 2018 by John Wiley & Sons, Inc.

| S-EPMC6168376 | biostudies-literature

Distinct types of short open reading frames are translated in plant cells.

Project description:Genomes contain millions of short (<100 codons) open reading frames (sORFs), which are usually dismissed during gene annotation. Nevertheless, peptides encoded by such sORFs can play important biological roles, and their impact on cellular processes has long been underestimated. Here, we analyzed approximately 70,000 transcribed sORFs in the model plant Physcomitrella patens (moss). Several distinct classes of sORFs that differ in terms of their position on transcripts and the level of evolutionary conservation are present in the moss genome. Over 5000 sORFs were conserved in at least one of 10 plant species examined. Mass spectrometry analysis of proteomic and peptidomic data sets suggested that tens of sORFs located on distinct parts of mRNAs and long noncoding RNAs (lncRNAs) are translated, including conserved sORFs. Translational analysis of the sORFs and main ORFs at a single locus suggested the existence of genes that code for multiple proteins and peptides with tissue-specific expression. Functional analysis of four lncRNA-encoded peptides showed that sORFs-encoded peptides are involved in regulation of growth and differentiation in moss. Knocking out lncRNA-encoded peptides resulted in a decrease of moss growth. In contrast, the overexpression of these peptides resulted in a diverse range of phenotypic effects. Our results thus open new avenues for discovering novel, biologically active peptides in the plant kingdom.

| S-EPMC6724668 | biostudies-literature

Thousands of novel translated open reading frames in humans inferred by ribosome footprint profiling.

Project description:Accurate annotation of protein coding regions is essential for understanding how genetic information is translated into function. We describe riboHMM, a new method that uses ribosome footprint data to accurately infer translated sequences. Applying riboHMM to human lymphoblastoid cell lines, we identified 7273 novel coding sequences, including 2442 translated upstream open reading frames. We observed an enrichment of footprints at inferred initiation sites after drug-induced arrest of translation initiation, validating many of the novel coding sequences. The novel proteins exhibit significant selective constraint in the inferred reading frames, suggesting that many are functional. Moreover, ~40% of bicistronic transcripts showed negative correlation in the translation levels of their two coding sequences, suggesting a potential regulatory role for these novel regions. Despite known limitations of mass spectrometry to detect protein expressed at low level, we estimated a 14% validation rate. Our work significantly expands the set of known coding regions in humans.

| S-EPMC4940163 | biostudies-literature

Thousands of novel translated open reading frames in humans inferred by ribosome footprint profiling.

Project description:Accurate annotations of protein coding regions are essential for understanding how genetic information is translated into biological functions. The recent development of ribosome footprint profiling provides an important new tool for measuring translation. Here we describe riboHMM, a new method that uses ribosome footprint data along with gene expression and sequence information to accurately infer translated sequences. We applied our method to human lymphoblastoid cell lines and identified 7,863 previously unannotated coding sequences, including 445 translated sequences in pseudogenes and 2,442 translated upstream open reading frames. We observed an enrichment of harringtonine-treated ribosome footprints at the inferred initiation sites, validating many of the novel coding sequences. In aggregate, the novel sequences exhibit significant signatures of purifying selection indicative of protein-coding function, suggesting that many of the novel sequences are functional. We observed that nearly 40% of bicistronic transcripts showed significant negative correlation in the levels of translation of their two coding sequences, suggesting a key regulatory role for these novel translated sequences. Despite evidence for their functional importance, the novel peptide sequences were detected by mass spectrometry at a lower rate than predicted based on data from annotated proteins, thus suggesting that many of the novel peptide products may be relatively short-lived. Our work illustrates the value of ribosome profiling for improving coding annotations, and significantly expands the set of known coding regions.

2015-12-25 | GSE75290 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data