Detection of Genomic Structural Variants from Next-Generation Sequencing Data

Abstract

Structural variants are genomic rearrangements larger than 50 bp accounting for around 1% of the variation among human genomes. They impact on phenotypic diversity and play a role in various diseases including neurological/neurocognitive disorders and cancer development and progression. Dissecting structural variants from next-generation sequencing data presents several challenges and a number of approaches have been proposed in the literature. In this mini review, we describe and summarize the latest tools - and their underlying algorithms - designed for the analysis of whole-genome sequencing, whole-exome sequencing, custom captures, and amplicon sequencing data, pointing out the major advantages/drawbacks. We also report a summary of the most recent applications of third-generation sequencing platforms. This assessment provides a guided indication - with particular emphasis on human genetics and copy number variants - for researchers involved in the investigation of these genomic events.

Keywords: amplicon sequencing; copy number variants; next generation sequencing; statistical methods; structural variants; whole-exome sequencing; whole-genome sequencing.

Figure 1

Signatures and patterns of SVs for deletion (A), novel sequence insertion (B), inversion (C), and tandem duplication (D) in read count (RC), read-pair (RP), split-read (SR), and de novo assembly (AS) methods.