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Related Concept Videos

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Ribosome synthesis is a highly complex and coordinated process involving more than 200 assembly factors. The synthesis and processing of ribosomal components occurs not only in the nucleolus but also in the nucleoplasm and the cytoplasm of eukaryotic cells.
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Updated: Apr 21, 2026

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data
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Robust identification of noncoding RNA from transcriptomes requires phylogenetically-informed sampling.

Stinus Lindgreen1, Sinan Uğur Umu2, Alicia Sook-Wei Lai3

  • 1Department of Biology, University of Copenhagen, Copenhagen, Denmark; School of Biological Sciences, University of Canterbury, Christchurch, New Zealand.

Plos Computational Biology
|October 31, 2014
PubMed
Summary
This summary is machine-generated.

Identifying functional noncoding RNAs in bacteria and archaea is challenging. New transcriptomics methods require phylogeny-aware sampling to distinguish true biological signals from transcriptional noise.

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Area of Science:

  • Microbiology
  • Genomics
  • Molecular Biology

Background:

  • Noncoding RNAs (ncRNAs) play crucial roles in essential biological processes.
  • Identifying ncRNAs in bacterial and archaeal genomes is difficult due to de novo identification challenges.
  • RNA sequencing (RNA-seq) improves ncRNA identification but distinguishing functional ncRNAs from transcriptional noise remains a hurdle.

Purpose of the Study:

  • To assess the effectiveness of current transcriptome data annotation for capturing all functional noncoding RNA outputs.
  • To evaluate the utility of comparative genomics approaches for noncoding RNA discovery in prokaryotes.
  • To determine the impact of phylogenetic sampling on the identification of noncoding RNAs.

Main Methods:

  • Analysis of over 400 publicly available RNA-seq datasets from 37 bacterial and archaeal species.
  • Application of comparative genomic tools to identify highly-expressed candidate noncoding RNAs.
  • Evaluation of phylogenetic dependency in noncoding RNA identification methods.

Main Results:

  • Identification of nearly a thousand highly-expressed candidate noncoding RNAs.
  • Demonstration that noncoding RNA identification capacity is highly dependent on phylogenetic sampling.
  • Discovery that comparative methods for distinguishing functional ncRNAs from noise have a narrow phylogenetic window, often requiring phylogeny-aware sampling.

Conclusions:

  • Current transcriptomics data and annotation methods may not fully capture all functional noncoding RNA outputs in prokaryotes.
  • Effective identification of noncoding RNAs necessitates careful, phylogeny-aware experimental design and data sampling.
  • Future transcriptomics studies should incorporate phylogenetic considerations to maximize the discovery of functional ncRNAs.