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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...
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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.
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Transposons, or "jumping genes," are small mobile genetic elements (MGEs) that range from 700 to 40,000 base pairs in length. They are found in all organisms and can move within the same chromosome or transfer to different chromosomes. In some cases, transposons can also jump between different host DNA molecules, such as plasmids or viruses, contributing to genetic variability.Barbara McClintock first discovered these mobile genetic elements in the 1940s while studying maize genetics, and she...
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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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LTR retrotransposons are class I transposable elements with long terminal repeats flanking an internal coding region. These elements are less abundant in mammals compared to other class I transposable elements. About 8 percent of human genomic DNA comprises LTR retrotransposons. Some of the common examples of LTR retrotransposons are Ty elements in yeast and Copia elements in Drosophila.
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Transposable element detection from whole genome sequence data.

Adam D Ewing1

  • 1Mater Research Institute - University of Queensland, 37 Kent St Level 4, Woolloongabba, QLD 4102 Australia.

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|January 1, 2016
PubMed
Summary
This summary is machine-generated.

New software tools for detecting transposable element insertions are emerging rapidly. However, current methods lack concordance, highlighting the need for improved computational approaches in whole genome sequencing analysis.

Keywords:
BioinformaticsMethodsSequencing

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • The increasing availability of whole genome sequencing data has led to a surge in software tools for transposable element (TE) detection.
  • Existing TE detection methods employ various computational strategies, often based on common underlying approaches.

Purpose of the Study:

  • To review current transposable element detection and filtering strategies in the context of TE biology and whole genome sequencing.
  • To assess the concordance of state-of-the-art TE detection methods.
  • To provide resources for advancing future TE detection tool development.

Main Methods:

  • Review of existing computational approaches for transposable element insertion detection.
  • Analysis of detection and filtering strategies based on transposable element biology.
  • Evaluation of current whole genome sequencing technologies and their impact on TE detection.

Main Results:

  • A wide array of software tools for transposable element detection exists, with diverse methodologies.
  • Current state-of-the-art transposable element detection tools exhibit limited concordance in their results.
  • Significant challenges remain in accurately identifying transposable element insertions across different datasets.

Conclusions:

  • The field of transposable element detection requires further methodological refinement to improve accuracy and consistency.
  • Future development should focus on enhancing concordance among different detection algorithms.
  • Resources and insights are provided to guide the next generation of transposable element detection software.