Detecting Novel Structural Variants In Genomes By Leveraging Parent-Child Relatedness

Abstract

Genomic variation shared by members of the same species that are longer than a single nucleotide are commonly called structural variants (SVs). Though relatively rare, they represent an increasingly important class of variation as SVs have been associated with diseases and susceptibility to some types of cancer. Common approaches to SV detection require the sequencing and mapping of fragments from a test genome to a high-quality reference genome. Candidate SVs correspond to fragments with discordant mapped configurations, but because errors in the sequencing and mapping will also create discordant arrangements, many of these predictions will be false. When sequencing coverage is low, distinguishing true SVs from errors is even more complicated. In recent work, we have developed SV detection methods that simultaneously consider the genomes of closely related individuals – parents and children. Our approaches control false positive SVs by requiring children inherit all SVs in their genome from a parent. However, in doing so we may have missed true novel variants acquired by the child. In this work, we generalize our previous approaches to allow the child to carry novel variants but enforce sparsity through an l 1 penalty (since novel SVs in the child should be rare). We present results on both simulated genomes as well as two-sequenced parent-child trios from the 1000 Genomes Project.