Integrated analysis of whole-genome paired-end and mate-pair sequencing data for identifying genomic structural variations in multiple myeloma.

Abstract

We present a pipeline to perform integrative analysis of mate-pair (MP) and paired-end (PE) genomic DNA sequencing data. Our pipeline detects structural variations (SVs) by taking aligned sequencing read pairs as input and classifying these reads into properly paired and discordantly paired categories based on their orientation and inferred insert sizes. Recurrent SV was identified from the discordant read pairs. Our pipeline takes into account genomic annotation and genome repetitive element information to increase detection specificity. Application of our pipeline to whole-genome MP and PE sequencing data from three multiple myeloma cell lines (KMS11, MM.1S, and RPMI8226) recovered known SVs, such as heterozygous TRAF3 deletion, as well as a novel experimentally validated SPI1 – ZNF287 inter-chromosomal rearrangement in the RPMI8226 cell line.