Jitterbug: somatic and germline transposon insertion detection at single-nucleotide resolution

BMC Genomics

Methodology Article

Josep M. Casacuberta¹  Elizabeth Hénaff²  Luís Zapata³  Stephan Ossowski³ 

[1] Center for Research in Agricultural Genomics, CRAG (CSIC-IRTA-UAB-UB), Barcelona, Spain;Genomic and Epigenomic Variation in Disease Group, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, 08003, Barcelona, Spain;Center for Research in Agricultural Genomics, CRAG (CSIC-IRTA-UAB-UB), Barcelona, Spain;current address: Weill Cornell Medical College, Institute for Computational Biomedicine, 1305 York Avenue, 10021, New York, NY, USA;Genomic and Epigenomic Variation in Disease Group, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, 08003, Barcelona, Spain;Universitat Pompeu Fabra (UPF), Barcelona, Spain;

关键词: Transposons;    Mobile elements;    NGS;    Somatic mutation;    Cancer;    Structural variation;    Genomics;    Evolution;   

DOI  :  10.1186/s12864-015-1975-5

 received in 2015-05-13, accepted in 2015-10-02,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundTransposable elements are major players in genome evolution. Transposon insertion polymorphisms can translate into phenotypic differences in plants and animals and are linked to different diseases including human cancer, making their characterization highly relevant to the study of genome evolution and genetic diseases.ResultsHere we present Jitterbug, a novel tool that identifies transposable element insertion sites at single-nucleotide resolution based on the pairedend mapping and clipped-read signatures produced by NGS alignments. Jitterbug can be easily integrated into existing NGS analysis pipelines, using the standard BAM format produced by frequently applied alignment tools (e.g. bwa, bowtie2), with no need to realign reads to a set of consensus transposon sequences. Jitterbug is highly sensitive and able to recall transposon insertions with a very high specificity, as demonstrated by benchmarks in the human and Arabidopsis genomes, and validation using long PacBio reads. In addition, Jitterbug estimates the zygosity of transposon insertions with high accuracy and can also identify somatic insertions.ConclusionsWe demonstrate that Jitterbug can identify mosaic somatic transposon movement using sequenced tumor-normal sample pairs and allows for estimating the cancer cell fraction of clones containing a somatic TE insertion. We suggest that the independent methods we use to evaluate performance are a step towards creating a gold standard dataset for benchmarking structural variant prediction tools.

【 授权许可】

CC BY   
© Hénaff et al. 2015