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Overview of Transposition and Recombination

Overview of Transposition and Recombination

Transposons make up a significant part of genomes of various organisms. Therefore, it is believed that transposition played a major evolutionary role in speciation by changing genome sizes and modifying gene expression patterns. For example, in bacteria, transposition can lead to conferring antibiotic resistance. Movement of transposable elements within the genetic pool of pathogenic bacteria can aid in transfer of antibiotic-resistant genetic elements. In eukaryotes, transposons can carry out...

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...

Non-LTR Retrotransposons

Non-LTR Retrotransposons

As the name suggests, non-LTR retrotransposons lack the long terminal repeats characteristic of the LTR retrotransposons. Additionally, both LTR and non-LTR retrotransposons use distinct mechanisms of mobilization. Non-LTR retrotransposons are further divided into two classes - Long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs), both of which occur abundantly in most mammals, including humans. Some of the active non-LTR retrotransposons in humans are L1...

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Related Experiment Video

Updated: Mar 16, 2026

Determination of the Optimal Chromosomal Locations for a DNA Element in Escherichia coli Using a Novel Transposon-mediated Approach

Determination of the Optimal Chromosomal Locations for a DNA Element in Escherichia coli Using a Novel Transposon-mediated Approach

Published on: September 11, 2017

Benchmarking computational tools for polymorphic transposable element detection.

Lavanya Rishishwar, Leonardo Mariño-Ramírez, I King Jordan

Briefings in Bioinformatics

|August 16, 2016

Summary

This summary is machine-generated.

This study benchmarks tools for detecting polymorphic transposable elements (TEs) in human DNA. MELT, Mobster, and RetroSeq showed the best performance, highlighting the need for combined approaches for accurate human genetic variation analysis.

Keywords:

human genome next-generation sequencing polymorphic transposable element detection transposable elements

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Last Updated: Mar 16, 2026

Determination of the Optimal Chromosomal Locations for a DNA Element in Escherichia coli Using a Novel Transposon-mediated Approach

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Published on: September 11, 2017

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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Area of Science:

Genomics
Human Genetics
Bioinformatics

Background:

Transposable elements (TEs) are key drivers of human genetic variation and phenotypic changes.
Computational tools for detecting polymorphic TE (polyTE) insertion sites are crucial for analyzing next-generation sequencing data.
The rapid acceleration of human genome sequencing necessitates reliable polyTE detection methods.

Purpose of the Study:

To benchmark and validate computational tools for detecting polymorphic transposable element insertion sites.
To inform the selection and usage of polyTE detection tools for the research community.
To assess tool performance based on ease of use, detection accuracy, and runtime.

Main Methods:

Comparative analysis of seven core polyTE detection tools.
Validation using an experimentally confirmed set of 893 human polyTE insertions.
Assessment using simulated datasets to evaluate the impact of sequence coverage on performance.

Main Results:

The tool MELT demonstrated the highest overall performance, followed by Mobster and RetroSeq.
PolyTE detection is most reliable for Alu insertions, less reliable for L1, and substantially lower for SVA insertions.
Different polyTE detection tools exhibit complementary strengths in identifying insertion events.

Conclusions:

A combined approach using multiple polyTE detection tools, along with manual inspection, is recommended for optimal results.
Tool performance varies significantly across different TE types (Alu, L1, SVA).
Recommendations for tool installation, usage, and future algorithm development are provided.