University of Massachusetts Medical School Faculty Publications

UMMS Affiliation

Program in Bioinformatics and Integrative Biology; Program in Molecular Medicine

Publication Date

2021-01-28

Document Type

Article

Disciplines

Bioinformatics | Computational Biology | Genetics and Genomics | Nucleic Acids, Nucleotides, and Nucleosides

Abstract

Transposons are genomic parasites, and their new insertions can cause instability and spur the evolution of their host genomes. Rapid accumulation of short-read whole-genome sequencing data provides a great opportunity for studying new transposon insertions and their impacts on the host genome. Although many algorithms are available for detecting transposon insertions, the task remains challenging and existing tools are not designed for identifying de novo insertions. Here, we present a new benchmark fly dataset based on PacBio long-read sequencing and a new method TEMP2 for detecting germline insertions and measuring de novo 'singleton' insertion frequencies in eukaryotic genomes. TEMP2 achieves high sensitivity and precision for detecting germline insertions when compared with existing tools using both simulated data in fly and experimental data in fly and human. Furthermore, TEMP2 can accurately assess the frequencies of de novo transposon insertions even with high levels of chimeric reads in simulated datasets; such chimeric reads often occur during the construction of short-read sequencing libraries. By applying TEMP2 to published data on hybrid dysgenic flies inflicted by de-repressed P-elements, we confirmed the continuous new insertions of P-elements in dysgenic offspring before they regain piRNAs for P-element repression. TEMP2 is freely available at Github: https://github.com/weng-lab/TEMP2.

Keywords

Computational Methods, Genomics

Rights and Permissions

© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

DOI of Published Version

10.1093/nar/gkab010

Source

Yu T, Huang X, Dou S, Tang X, Luo S, Theurkauf WE, Lu J, Weng Z. A benchmark and an algorithm for detecting germline transposon insertions and measuring de novo transposon insertion frequencies. Nucleic Acids Res. 2021 Jan 28:gkab010. doi: 10.1093/nar/gkab010. Epub ahead of print. PMID: 33511407. Link to article on publisher's site

Related Resources

Link to Article in PubMed

Journal/Book/Conference Title

Nucleic acids research

PubMed ID

33511407

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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