Differential Expression Analysis of Nothobranchius furzeri Transposable Elements from RNA-seq Data

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Transposable elements (TEs) constitute significant portions of eukaryotic genomes.
• Analyzing TEs is challenging due to their repetitive nature and high copy numbers.
• Standard bioinformatic pipelines often require adaptation for TE analysis.

Purpose of the Study:

• To establish robust pipelines for analyzing transposable element (TE) expression from RNA-seq data.
• To provide adaptable protocols for non-model organisms, specifically the African turquoise killifish (Nothobranchius furzeri).
• To offer solutions for varying computational resource availability, including memory constraints.

Main Methods:

• Development of three distinct bioinformatic pipelines for TE expression analysis.
• Utilization of standard RNA-seq analysis software combined with TE-specialized tools.
• Adaptation for both genomic and transcriptomic references, accommodating single-end and paired-end Illumina RNA-seq data.
• Inclusion of adapter trimming, read alignment, counting, and differential expression analysis steps.

Main Results:

• Successful implementation of three versatile pipelines for TE expression analysis.
• Demonstration of protocol applicability using publicly available RNA-seq data from aging killifish.
• Validation of the pipelines' ability to handle complex genomic data from a non-model organism.

Conclusions:

• The presented pipelines provide a flexible and robust framework for analyzing transposable element expression in eukaryotic genomes.
• These methods facilitate TE research in non-model organisms with limited genomic resources or computational power.
• The protocol enables differential expression analysis of TEs, contributing to a deeper understanding of their role in biological processes like aging.