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DNA-only Transposons

DNA-only Transposons

DNA-only transposons are called autonomous transposons since they code for the enzyme transposase that is required for the transposition mechanism. Insertion of transposons can alter gene functions in multiple ways. They can mutate the gene, alter gene expression by introducing a novel promoter or insulator sequence, introduce new splice sites, and change the mRNA transcripts produced, or remodel chromatin structure.
The donor site from where the transposon is excised is either degraded or...

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Detection of Retrotransposition Activity of Hot LINE-1s by Long-Distance Inverse PCR

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Published on: July 27, 2019

Detecting Medium and Large Insertions and Deletions with transIndel.

Ting-You Wang¹, Rendong Yang²

¹The Hormel Institute, University of Minnesota, Austin, MN, USA.

Methods in Molecular Biology (Clifton, N.J.)

|June 25, 2022

Summary

We developed transIndel, a new algorithm to detect medium and large insertions and deletions (indels) from RNA sequencing data. This method helps explore the transcriptional consequences of indels, previously challenging to identify.

Keywords:

Chimeric alignment DNA-seq Indel detection RNA-seq Split reads

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Last Updated: Sep 6, 2025

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Published on: October 18, 2013

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Insertions and deletions (indels) are common genetic variations.
Detecting indels from DNA sequencing (DNA-seq) is established, but their impact on transcription is less understood.
Distinguishing medium- and large-sized indels from RNA splicing events in RNA sequencing (RNA-seq) data presents a significant challenge.

Purpose of the Study:

To introduce transIndel, a novel splice-aware algorithm for indel detection.
To enable the exploration of transcriptional consequences of indels using RNA-seq data.
To provide a method for reconstructing mid-sized insertions and large deletions from sequencing data.

Main Methods:

Developed transIndel, a splice-aware bioinformatics algorithm.
The algorithm parses chimeric alignments predicted by short read aligners.
Reconstructs mid-sized insertions and large deletions using linear alignments of split reads from DNA-seq or RNA-seq data.

Main Results:

Successfully developed a method to distinguish indels from splicing events in RNA-seq.
Demonstrated the capability to reconstruct medium- and large-sized indels.
Provided a tutorial for transIndel installation and application.

Conclusions:

transIndel offers a robust solution for identifying indels and their transcriptional effects from RNA-seq data.
The algorithm overcomes previous limitations in distinguishing indels from splicing.
Facilitates deeper understanding of genetic variation impact on gene expression.