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Abstract Transposable elements (TEs) are dynamic components of genomes that often vary in copy number among members of the same species. With the advent of next-generation sequencing TE insertion-site polymorphism can be examined at an unprecedented level of detail when combined with easy-to-use bioinformatics software. Here we report a new tool, RelocaTE, that rapidly identifies specific TE insertions that are either polymorphic or shared between a reference and unassembled next-generation sequencing reads. Furthermore, a novel companion tool, CharacTErizer, exploits the depth of coverage to classify genotypes of nonreference insertions as homozygous, heterozygous or, when analyzing an active TE family, as rare somatic insertion or excision events. It does this by comparing the numbers of RelocaTE aligned reads to reads that map to the same genomic position without the TE. Although RelocaTE and CharacTErizer can be used for any TE, they were developed to analyze the very active mPing element which is undergoing massive amplification in specific strains of Oryza sativa (rice). Three individuals of one of these strains, A123, were resequenced and analyzed for mPing insertion site polymorphisms. The majority of mPing insertions found (~97%) are not present in the reference, and two siblings from a self-crossed of this strain were found to share only ~90% of their insertions. Private insertions are primarily heterozygous but include both homozygous and predicted somatic insertions. The reliability of the predicted genotypes was validated by polymerase chain reaction.
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RelocaTE2: a high resolution transposable element insertion site mapping tool for population resequencing
Background Transposable element (TE) polymorphisms are important components of population genetic variation. The functional impacts of TEs in gene regulation and generating genetic diversity have been observed in multiple species, but the frequency and magnitude of TE variation is under appreciated. Inexpensive and deep sequencing technology has made it affordable to apply population genetic methods to whole genomes with methods that identify single nucleotide and insertion/deletion polymorphisms. However, identifying TE polymorphisms, particularly transposition events or non-reference insertion sites can be challenging due to the repetitive nature of these sequences, which hamper both the sensitivity and specificity of analysis tools. Methods We have developed the tool RelocaTE2 for identification of TE insertion sites at high sensitivity and specificity. RelocaTE2 searches for known TE sequences in whole genome sequencing reads from second generation sequencing platforms such as Illumina. These sequence reads are used as seeds to pinpoint chromosome locations where TEs have transposed. RelocaTE2 detects target site duplication (TSD) of TE insertions allowing it to report TE polymorphism loci with single base pair precision. Results and Discussion The performance of RelocaTE2 is evaluated using both simulated and real sequence data. RelocaTE2 demonstrate high level of sensitivity and specificity, particularly when the sequence coverage is not shallow. In comparison to other tools tested, RelocaTE2 achieves the best balance between sensitivity and specificity. In particular, RelocaTE2 performs best in prediction of TSDs for TE insertions. Even in highly repetitive regions, such as those tested on rice chromosome 4, RelocaTE2 is able to report up to 95% of simulated TE insertions with less than 0.1% false positive rate using 10-fold genome coverage resequencing data. RelocaTE2 provides a robust solution to identify TE insertion sites and can be incorporated into analysis workflows in support of describing the complete genotype from light coverage genome sequencing.
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- Award ID(s):
- 1027542
- PAR ID:
- 10395973
- Date Published:
- Journal Name:
- PeerJ
- Volume:
- 5
- ISSN:
- 2167-8359
- Page Range / eLocation ID:
- e2942
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)Transposable elements (TEs) are mobile elements capable of introducing genetic changes rapidly. Their importance has been documented in many biological processes, such as introducing genetic instability, altering patterns of gene expression, and accelerating genome evolution. Increasing appreciation of TEs has resulted in a growing number of bioinformatics software to identify insertion events. However, the application of existing tools is limited by either narrow-focused design of the package, too many dependencies on other tools, or prior knowledge required as input files that may not be readily available to all users. Here, we reported a simple pipeline, TEfinder, developed for the detection of new TE insertions with minimal software and input file dependencies. The external software requirements are BEDTools, SAMtools, and Picard. Necessary input files include the reference genome sequence in FASTA format, an alignment file from paired-end reads, existing TEs in GTF format, and a text file of TE names. We tested TEfinder among several evolving populations of Fusarium oxysporum generated through a short-term adaptation study. Our results demonstrate that this easy-to-use tool can effectively detect new TE insertion events, making it accessible and practical for TE analysis.more » « less
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.7717/peerj.2942
