deFuse: An Algorithm for Gene Fusion Discovery in Tumor RNA-Seq Data

Abstract

Gene fusions created by somatic genomic rearrangements are known to play an important role in the onset and development of some cancers, such as lymphomas and sarcomas. RNA-Seq (whole transcriptome shotgun sequencing) is proving to be a useful tool for the discovery of novel gene fusions in cancer transcriptomes. However, algorithmic methods for the discovery of gene fusions using RNA-Seq data remain underdeveloped. We have developed deFuse, a novel computational method for fusion discovery in tumor RNA-Seq data. Unlike existing methods that use only unique best-hit alignments and consider only fusion boundaries at the ends of known exons, deFuse considers all alignments and all possible locations for fusion boundaries. As a result, deFuse is able to identify fusion sequences with demonstrably better sensitivity than previous approaches. To increase the specificity of our approach, we curated a list of 60 true positive and 61 true negative fusion sequences (as confirmed by RT-PCR), and have trained an adaboost classifier on 11 novel features of the sequence data. The resulting classifier has an estimated value of 0.91 for the area under the ROC curve. We have used deFuse to discover gene fusions in 40 ovarian tumor samples, one ovarian cancer cell line, and three sarcoma samples. We report herein the first gene fusions discovered in ovarian cancer. We conclude that gene fusions are not infrequent events in ovarian cancer and that these events have the potential to substantially alter the expression patterns of the genes involved; gene fusions should therefore be considered in efforts to comprehensively characterize the mutational profiles of ovarian cancer transcriptomes.

14-3-3 fusion oncogenes in high-grade endometrial stromal sarcoma

“…Sequencing was performed against the t(10;17)-containing ESS1, and sequence reads were analyzed by using a custom-written deFuse algorithm designed to identify fusion transcripts in RNA sequencing datasets (13), including those involving members of highly homologous gene families. deFuse analysis identified in-frame YWHAE-FAM22A fusions of YWHAE exon 5 to FAM22A exon 2 ( Fig.…”

Next-generation transcriptome assembly

“…Detection of trans-spliced genes has been shown to be critical for understanding the genetic pathways involved in some cancers 56 , such as prostate cancer 57 .…”

RNA-Seq and human complex diseases: recent accomplishments and future perspectives

“…[68][69] To this purpose, a novel computational method, deFuse, has allowed to discover for the first time gene fusions in ovarian cancer specimen, also showing novel chimeric mRNAs in sarcoma. 66 Novel fusion transcripts have been also discovered, especially in breast cancer (Table 1). 51,61 RNA-Seq revealed that the occurrence of chimeric transcripts in melanoma is a frequent event, also highlighting novel genes and pathways previously not associated to its pathogenesis.…”