e-learning
Differential abundance testing of small RNAs
Abstract
Small, noncoding RNA (sRNA) molecules, typically 18-40nt in length, are key features of post-transcriptional regulatory mechanisms governing gene expression. Through interactions with protein cofactors, these tiny sRNAs typically function by perfectly or imperfectly basepairing with substrate RNA molecules, and then eliciting downstream effects such as translation inhibition or RNA degradation. Different subclasses of sRNAs - e.g. microRNAs (miRNAs), Piwi-interaction RNAs (piRNAs), and endogenous short interferring RNAs (siRNAs) - exhibit unique characteristics, and their relative abundances in biological contexts can indicate whether they are active or not. In this tutorial, we will examine expression of the piRNA subclass of sRNAs and their targets in Drosophila melanogaster.
About This Material
This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.
Questions this will address
- What small RNAs are expressed?
- What RNA features have significantly different numbers of small RNAs targeting them between two conditions?
Learning Objectives
- Process small RNA-seq datasets to determine quality and reproducibility.
- Filter out contaminants (e.g. rRNA reads) in small RNA-seq datasets.
- Differentiate between subclasses of small RNAs based on their characteristics.
- Identify differently abundant small RNAs and their targets.
Licence: Creative Commons Attribution 4.0 International
Keywords: Transcriptomics
Target audience: Students
Resource type: e-learning
Version: 26
Status: Active
Prerequisites:
- Introduction to Galaxy Analyses
- Mapping
- Quality Control
Learning objectives:
- Process small RNA-seq datasets to determine quality and reproducibility.
- Filter out contaminants (e.g. rRNA reads) in small RNA-seq datasets.
- Differentiate between subclasses of small RNAs based on their characteristics.
- Identify differently abundant small RNAs and their targets.
Date modified: 2023-11-09
Date published: 2017-06-29
Contributors: Björn Grüning, Bérénice Batut, Gildas Le Corguillé, Helena Rasche, Mallory Freeberg, Marius van den Beek, Niall Beard, Nicola Soranzo, Saskia Hiltemann, William Durand
Scientific topics: Transcriptomics
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