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Proposing Institution

Institut für Bioinformatik, Universität Leipzig
Project Manager

Dr. Stephan Bernhart
Haertelstr 16-18
04107 Leipzig
Fusion Transcripts in Malignant LymphomaFusion transcripts play an important role in many cancer types. As a part of the german ICGC MMMLSeq and ICGC Data Mining projects, we will use transcriptome data and a state-of-the-art transcriptome mapping tool (segemehl 0.2) to identify fusion transcripts with a low false positive rate. We hope not only to characterize in detail fusion transcripts whose existence has been predicted by genomic methods, but also to find new, bona-fide fusion transcripts that eluded discovery with genomic tools. Previous methods for high throughput sequencing transcriptome analysis suffer from high false positive rates, with typically hundreds of putative fusion transcripts per dataset. Reducing this false positive rate will make it possible to pick candidate fusion genes for further wet-lab analysis. The segemehl 0.2 mapping tool combines threaded alignment techniques that can find splice events (and fusions) between all places in the genome with several approaches that strongly prefer splicing in cis if at all possible, which reduces the false-positive rate.We will look for fusion transcripts in 259 next-generation-sequencing data sets, 249 lymphoma data sets representing 5 main types of malignant lymphoma and several sub-types, and 10 control datasets which are split into 5 germinal center B-cell datasets, thought to be the direct precursor of many malignant lymphoma types, and 5 naive B-cell data sets, which are. Besides lists of putative fusion transcripts, segemehl 0.2 provides mappings and lists of normal splice sites that can and will be used for furhter analysis.

Impressum, Conny Wendler