Structural variation discovery in the cancer genome using next generation sequencing: computational solutions and perspectives - PubMed (original) (raw)

Review

Structural variation discovery in the cancer genome using next generation sequencing: computational solutions and perspectives

Biao Liu et al. Oncotarget. 2015.

Abstract

Somatic Structural Variations (SVs) are a complex collection of chromosomal mutations that could directly contribute to carcinogenesis. Next Generation Sequencing (NGS) technology has emerged as the primary means of interrogating the SVs of the cancer genome in recent investigations. Sophisticated computational methods are required to accurately identify the SV events and delineate their breakpoints from the massive amounts of reads generated by a NGS experiment. In this review, we provide an overview of current analytic tools used for SV detection in NGS-based cancer studies. We summarize the features of common SV groups and the primary types of NGS signatures that can be used in SV detection methods. We discuss the principles and key similarities and differences of existing computational programs and comment on unresolved issues related to this research field. The aim of this article is to provide a practical guide of relevant concepts, computational methods, software tools and important factors for analyzing and interpreting NGS data for the detection of SVs in the cancer genome.

Keywords: cancer genome analysis; next generation sequencing; somatic mutation; structural variation.

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Figures

Figure 1

Figure 1. Breakpoint signatures of SVs

(a) In each diagram, the up strands are from sample genome, and the lower strand are from reference genome. (b) Depending on the mapping of the inserted strand B, other relationships of coordinates in reference genome can be determined (details not shown). (c) Tandem duplication creates one or multiple breakpoints. NGS is able to detect either 1 (novel tandem duplication) or 0 (non-novel tandem duplication) breakpoint.

Figure 2

Figure 2. Diagram of SV types and NGS signatures, before and after mapping

A) Deletion; B) Insertion; C) Inversion; D) Tandem duplication; E Intra-chromosomal translocation (ITX); F) Inter-chromosomal translocation (CTX).

Figure 3

Figure 3. An exemplary illustration of the impact of SV event sizes and library insert sizes on the NGS signatures

I: length of insertion event (purple strand); r: read length; s: length of un-sequenced part in a read-pair; insert size equals 2r+s, assuming reads are in same length.

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