ArticleMolecular systems biology2021
Network-based visualisation reveals new insights into transposable element diversity.
Article in Molecular systems biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Host-transposable element coexistence: a matter of resistance, tolerance and trade-off.The EMBO journal · 2026Review
- Article
- Overview of methods for characterization and visualization of a protein-protein interaction network in a multi-omics integration context.Frontiers in molecular biosciences · 2022Review
- Network-based visualisation reveals new insights into transposable element diversity.Molecular systems biology · 2021Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Transposable elements (TEs) are widespread across eukaryotic genomes, yet their content varies widely between different species. Factors shaping the diversity of TEs are poorly understood. Understanding the evolution of TEs is difficult because their sequences diversify rapidly and TEs are often transferred through non-conventional means such as horizontal gene transfer. We developed a method to track TE evolution using network analysis to visualise TE sequence and TE content across different genomes. We illustrate our method by first using a monopartite network to study the sequence evolution of Tc1/mariner elements across focal species. We identify a connection between two subfamilies associated with convergent acquisition of a domain from a protein-coding gene. Second, we use a bipartite network to study how TE content across species is shaped by epigenetic silencing mechanisms. We show that the presence of Piwi-interacting RNAs is associated with differences in network topology after controlling for phylogenetic effects. Together, our method demonstrates how a network-based approach can identify hitherto unknown properties of TE evolution across species.
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Registered trials
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