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Updated: May 27, 2026

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data

Published on: February 18, 2022

deepBlockAlign: a tool for aligning RNA-seq profiles of read block patterns.

David Langenberger¹, Sachin Pundhir, Claus T Ekstrøm

¹Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, Universität Leipzig, Philipp-Rosenthal-Strasse 27, D-04107 Leipzig, Germany.

Bioinformatics (Oxford, England)

|November 5, 2011

Summary

This summary is machine-generated.

deepBlockAlign identifies novel RNAs by aligning short RNA sequencing patterns. This method merges reads into blocks and groups them to compare processing footprints, aiding in the discovery of microRNAs and transfer RNAs.

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

High-throughput sequencing enables cost-effective transcriptome analysis.
Short RNA sequencing reveals quantitative expression and novel RNA identification.
Post-transcriptional processing of long transcripts generates short fragments with informative patterns.

Purpose of the Study:

To develop a method for aligning RNA-seq read patterns.
To efficiently identify RNAs with similar processing footprints.
To analyze the structural and processing information conveyed by RNA sequence fragments.

Main Methods:

A two-step approach: merging mapped reads into blocks, then combining blocks into block groups.
Modified sequence alignment algorithm to compare blocks and determine similarity scores.
Modified Sankoff algorithm to compare block patterns, considering block similarities and distance patterns within groups.
Hierarchical clustering of block groups for classification.

Main Results:

deepBlockAlign successfully separates most microRNA (miRNA) and transfer RNA (tRNA) clusters.
Identified approximately a dozen tRNAs that cluster with miRNAs.
Observed that these putative Dicer-processed tRNAs often exhibit precise read start positions.

Conclusions:

deepBlockAlign is an effective tool for identifying RNAs based on processing patterns.
The method aids in distinguishing between different types of small RNAs.
Reveals potential novel functions or processing pathways for certain tRNAs.