Network‐based visualisation reveals new insights into transposable element diversity. Issue 6 (25th June 2021)

• Record Type: Journal Article
• Authors: Schneider, Lisa; Guo, Yi‐Ke; Birch, David; Sarkies, Peter
• Is Part Of: Molecular systems biology. Volume 17:Issue 6(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-06-25
• Subjects: epigenetics -- evolution -- networks -- piRNAs -- transposable elements; Molecular biology -- Periodicals; Systems biology -- Periodicals; 572.8
• DOI: 10.15252/msb.20209600
• Languages: English
• ISSNs: 1744-4292

Abstract

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. SYNOPSIS: A novel network‐based method is used to study transposable element (TE) evolution, revealing new insights into how epigenetic silencing mechanisms affect TE content across species. Network approaches can be used to reconstruct the evolution of transposable elements. Networks based on sequence similarity between transposable elements reveal unexpected connections between TE families due to convergent evolution. Bipartite networks based on TE content show differences in network properties associated with the different epigenetic TE silencing mechanisms possessed by different species. Abstract : A novel network‐based method is used to study transposable element (TE) evolution, revealing new insights into how epigenetic silencing mechanisms affect TE content across species.