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BMC Bioinformatics. 2015 Mar 5;16:72. doi: 10.1186/s12859-015-0507-2.

ITIS, a bioinformatics tool for accurate identification of transposon insertion sites using next-generation sequencing data.

Author information

1
Shanghai Center for Plant Stress Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 201602, China. chjiang@sibs.ac.cn.
2
University of Chinese Academy of Sciences, Beijing, 100039, China. chjiang@sibs.ac.cn.
3
Shanghai Center for Plant Stress Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 201602, China. chenchao@sibs.ac.cn.
4
University of Chinese Academy of Sciences, Beijing, 100039, China. chenchao@sibs.ac.cn.
5
Shanghai Center for Plant Stress Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 201602, China. ziyhuang@sibs.ac.cn.
6
Shanghai Center for Plant Stress Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 201602, China. ryliu@sibs.ac.cn.
7
Shanghai Center for Plant Stress Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 201602, China. javerdier@sibs.ac.cn.

Abstract

BACKGROUND:

Transposable elements constitute an important part of the genome and are essential in adaptive mechanisms. Transposition events associated with phenotypic changes occur naturally or are induced in insertional mutant populations. Transposon mutagenesis results in multiple random insertions and recovery of most/all the insertions is critical for forward genetics study. Using genome next-generation sequencing data and appropriate bioinformatics tool, it is plausible to accurately identify transposon insertion sites, which could provide candidate causal mutations for desired phenotypes for further functional validation.

RESULTS:

We developed a novel bioinformatics tool, ITIS (Identification of Transposon Insertion Sites), for localizing transposon insertion sites within a genome. It takes next-generation genome re-sequencing data (NGS data), transposon sequence, and reference genome sequence as input, and generates a list of highly reliable candidate insertion sites as well as zygosity information of each insertion. Using a simulated dataset and a case study based on an insertional mutant line from Medicago truncatula, we showed that ITIS performed better in terms of sensitivity and specificity than other similar algorithms such as RelocaTE, RetroSeq, TEMP and TIF. With the case study data, we demonstrated the efficiency of ITIS by validating the presence and zygosity of predicted insertion sites of the Tnt1 transposon within a complex plant system, M. truncatula.

CONCLUSION:

This study showed that ITIS is a robust and powerful tool for forward genetic studies in identifying transposable element insertions causing phenotypes. ITIS is suitable in various systems such as cell culture, bacteria, yeast, insect, mammal and plant.

PMID:
25887332
PMCID:
PMC4351942
DOI:
10.1186/s12859-015-0507-2
[Indexed for MEDLINE]
Free PMC Article

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