Evidence map›Paper›PMID 35119670›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Anota2seq Analysis for Transcriptome-Wide Studies of mRNA Translation.

Christian Oertlin, Kathleen Watt, Johannes Ristau, Ola Larsson

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
8.0field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 14 citations in OpenAlex.

  1. Capturing Translation in Action with Protein Synthesis Profiling.bioRxiv : the preprint server for biology · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Translational control byRNA (New York, N.Y.) · 2023
    Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Christian OertlinDepartment of Oncology-Pathology, Science for Life Laboratory, Karolinska Institute, Stockholm, Sweden.
Kathleen WattDepartment of Oncology-Pathology, Science for Life Laboratory, Karolinska Institute, Stockholm, Sweden.
Johannes RistauDepartment of Oncology-Pathology, Science for Life Laboratory, Karolinska Institute, Stockholm, Sweden.
Ola LarssonDepartment of Oncology-Pathology, Science for Life Laboratory, Karolinska Institute, Stockholm, Sweden. Ola.Larsson@ki.se.
Karolinska Institutet · SEScience for Life Laboratory · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

mRNA translation plays a critical role in determining proteome composition. In health, regulation of mRNA translation facilitates rapid gene expression responses to intra- and extracellular signals. Moreover, dysregulated mRNA translation is a common feature in disease states, including neurological disorders and cancer. Yet, most studies of gene expression focus on analysis of mRNA levels, leaving variations in translational efficiencies largely uncharacterized. Here, we outline procedures to identify mRNA-selective alterations in translational efficiencies on a transcriptome-wide scale using the anota2seq package. Anota2seq compares expression data originating from translated mRNA to data from matched total mRNA to identify changes in translated mRNA not paralleled by corresponding changes in total mRNA (interpreted as changes in translational efficiencies impacting protein levels), congruent changes in total and translated mRNA (interpreted as changes in transcription and/or mRNA stability), and changes in total mRNA not paralleled by corresponding alterations in translated mRNA (interpreted as translational buffering). To illustrate the functionality of the anota2seq analysis package, we demonstrate a detailed analysis using a polysome-profiling data set quantified by RNA sequencing, revealing that estrogen receptor α modulates gene expression via a type of translational buffering termed offsetting. Notably, this anota2seq analysis procedure is also applicable to ribosome-profiling (RiboSeq) data sets and can be adapted to a variety of other data types and experimental contexts. Finally, we provide guidance for extending anota2seq analysis to examine associations between untranslated regions and altered translational efficiencies as well as targeted cellular functions to gain insights into mechanisms and phenotypic consequences of altered mRNA translation. Thus, this step-by-step manual allows users to interrogate selective changes in mRNA translation on a transcriptome-wide scale using the Bioconductor package anota2seq.

Indexed as

Protein BiosynthesisTranscriptomePolyribosomesRibosomesRNA, MessengerRNA, MessengerData analysisEstrogen receptor alphaGene expressionmRNA translationPolysome profilingRiboseqRibosome profilingRNA sequencingTranslatome

Identifiers

PMID35119670
OpenAlexW4210358195

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.