SEGF: A Novel Method for Gene Fusion Detection from Single-End Next-Generation Sequencing Data.

Hai Xu,Miao Teng,Siwen Zhang,Xizhe Zhang,Jidong Lang,Shijun Li,Geng Tian,Huixin Lin,Bo Meng,Dawei Yuan,Dawei Sun,Xiaojin Wu,Weitao Wang,Shidong Xu,Jianlong Bu

doi:10.3390/genes9070331

Abstract

With the development and application of next-generation sequencing (NGS) and target capture technology, the demand for an effective analysis method to accurately detect gene fusion from high-throughput data is growing. Hence, we developed a novel fusion gene analyzing method called single-end gene fusion (SEGF) by starting with single-end DNA-seq data. This approach takes raw sequencing data as input, and integrates the commonly used alignment approach basic local alignment search tool (BLAST) and short oligonucleotide analysis package (SOAP) with stringent passing filters to achieve successful fusion gene detection. To evaluate SEGF, we compared it with four other fusion gene discovery analysis methods by analyzing sequencing results of 23 standard DNA samples and DNA extracted from 286 lung cancer formalin fixed paraffin embedded (FFPE) samples. The results generated by SEGF indicated that it not only detected the fusion genes from standard samples and clinical samples, but also had the highest accuracy and sensitivity among the five compared methods. In addition, SEGF was capable of detecting complex gene fusion types from single-end NGS sequencing data compared with other methods. By using SEGF to acquire gene fusion information at DNA level, more useful information can be retrieved from the DNA panel or other DNA sequencing methods without generating RNA sequencing information to benefit clinical diagnosis or medication instruction. It was a timely and cost-effective measure with regard to research or diagnosis. Considering all the above, SEGF is a straightforward method without manipulating complicated arguments, providing a useful approach for the precise detection of gene fusion variation.

Highlights

Gene fusion occurs due to chromosomal breakage and rearrangement, and plays a critical role in oncogenesis
It was worth mentioning that single-end gene fusion (SEGF) successfully validated three 12-diluted standard samples, whose ROS1–SLC34A2 fusion frequency was decreased from 5% to 0.42%
This study proposed a novel method called SEGF for gene fusion detection from next-generation sequencing (NGS) data, wherein single-end reads were used to predict the gene fusion at DNA level

Summary

Introduction

Gene fusion occurs due to chromosomal breakage and rearrangement, and plays a critical role in oncogenesis. Advances in next-generation sequencing (NGS) technology have provided a new approach to systematically identify genomic alterations. Compared to the traditional methods, NGS technology has many advantages, such as in sample throughput, cost-effectiveness, and detection sensitivities. Many companies proceeded fusion gene detection tools for sequencing DNA and RNA to ensure accuracy, while this experimental design is both time- as well as money-consuming. Companies prefer gene fusion analysis at the genomic level over the transcriptional level, because DNA capture enrichment technology is cost-effective and faster, and both single nucleotide variation (SNV) and gene fusion can be interrogated simultaneously. A proper method for precisely detecting gene fusion from DNA high-throughput sequencing is needed, and this subsequently increases the difficulty and complexity of data analysis. There are four predominant approaches for detecting structural variation: De novo assembly: it detects structure variation in a more straightforward manner [4], but it is difficult to assemble the NGS short reads due to the influence of repetitive regions in the genome, as well as its high price

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Conclusion