Academic Journal
Transposable element finder (TEF): finding active transposable elements from next generation sequencing data
| Title: | Transposable element finder (TEF): finding active transposable elements from next generation sequencing data |
|---|---|
| Authors: | Akio Miyao, Utako Yamanouchi |
| Source: | BMC Bioinformatics, Vol 23, Iss 1, Pp 1-17 (2022) |
| Publisher Information: | BMC, 2022. |
| Publication Year: | 2022 |
| Collection: | LCC:Computer applications to medicine. Medical informatics LCC:Biology (General) |
| Subject Terms: | Transposable element, Retrotransposon, Next generation sequence, Target site duplication, Tos17, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5 |
| More Details: | Abstract Background Detection of newly transposed events by transposable elements (TEs) from next generation sequence (NGS) data is difficult, due to their multiple distribution sites over the genome containing older TEs. The previously reported Transposon Insertion Finder (TIF) detects TE transpositions on the reference genome from NGS short reads using end sequences of target TE. TIF requires the sequence of target TE and is not able to detect transpositions for TEs with an unknown sequence. Result The new algorithm Transposable Element Finder (TEF) enables the detection of TE transpositions, even for TEs with an unknown sequence. TEF is a finding tool of transposed TEs, in contrast to TIF as a detection tool of transposed sites for TEs with a known sequence. The transposition event is often accompanied with a target site duplication (TSD). Focusing on TSD, two algorithms to detect both ends of TE, TSDs and target sites are reported here. One is based on the grouping with TSDs and direct comparison of k-mers from NGS without similarity search. The other is based on the junction mapping of TE end sequence candidates. Both methods succeed to detect both ends and TSDs of known active TEs in several tests with rice, Arabidopsis and Drosophila data and discover several new TEs in new locations. PCR confirmed the detected transpositions of TEs in several test cases in rice. Conclusions TEF detects transposed TEs with TSDs as a result of TE transposition, sequences of both ends and their inserted positions of transposed TEs by direct comparison of NGS data between two samples. Genotypes of transpositions are verified by counting of junctions of head and tail, and non-insertion sequences in NGS reads. TEF is easy to run and independent of any TE library, which makes it useful to detect insertions from unknown TEs bypassed by common TE annotation pipelines. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 1471-2105 |
| Relation: | https://doaj.org/toc/1471-2105 |
| DOI: | 10.1186/s12859-022-05011-3 |
| Access URL: | https://doaj.org/article/2490800f02f74a24b385ef08ea9edecb |
| Accession Number: | edsdoj.2490800f02f74a24b385ef08ea9edecb |
| Database: | Directory of Open Access Journals |
| Full text is not displayed to guests. | Login for full access. |
| ISSN: | 14712105 |
|---|---|
| DOI: | 10.1186/s12859-022-05011-3 |
| Published in: | BMC Bioinformatics |
| Language: | English |