OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps

Abstract

Human genomes contain structural variations (SVs) that are associated with various phenotypic variations and diseases. SV detection by sequencing is incomplete due to limited read length.Nanochannel-based optical mapping (OM) allows direct observation of SVs up to hundreds of kilobases in size on individual DNA molecules, making it a promising alternative technology for identifying large SVs. SV detection from optical maps is non-trivial due to complex types of error present in OM data, and no existing methods can simultaneously handle all these complex errors and the wide spectrum of SV types. Here we present a novel method, OMSV, for accurate and comprehensive identification of SVs from optical maps. OMSV detects both homozygous and heterozygous SVs, SVs of various types and sizes, and SVs with and without creating/destroying restriction sites. In an extensive series of tests based on real and simulated data, OMSV achieved both high sensitivity and specificity, with clear performance gains over the latest existing method. Applying OMSV to a human cell line, we identified hundreds of SVs >2kbp, with 65% of them missed by sequencing-based callers. Independent experimental validations confirmed the high accuracy of these SVs. We also demonstrate how OMSV can incorporate sequencing data to determine precise SV break points and novel sequences in the SVs not contained in the reference. We provide OMSV as open-source software to facilitate systematic studies of large SVs.

Determining the impact of uncharacterized inversions in the human genome by droplet digital PCR

“…Therefore, short reads from next generation sequencing technologies (100-150 bp) (Sudmant et al 2015;Hehir-Kwa et al 2016;Collins et al 2019), and even longer reads from single-molecule sequencing technologies (10 kb on average) (Huddleston et al 2017;Shao et al 2018;Audano et al 2019) or paired-end mapping (PEM) data from large fragments (40-kb fosmid clones) (Kidd et al 2008), are often not able to jump across the IRs at inversion breakpoints, precluding the detection of these inversions. New methods like single-cell sequencing of one of the two DNA strands by Strand-seq (Sanders et al 2016;Chaisson et al 2019) or generation 4 of genome maps based on linearized DNA molecules labeled at particular sequences by optical mapping (Li et al 2017;Levy-Sakin et al 2019) have demonstrated their ability to detect inversions despite the presence of long IRs. Nevertheless, these techniques are not suitable for the analysis of large numbers of individuals.…”

Advances in optical mapping for genomic research

“…Researchers cannot directly study or modify the code used in RefAligner and Assembler to improve their performance. Although other tools such as OMTools [47] and OMSV [117] have been developed to assist optical mapping analysis, no other de novo assembly tools are available to compete with Bionano Tools. The direct use of the Bionano pipeline may also introduce false positives and false negatives, particularly in non-human genomes.…”

“…There are two tools used for optical mapping SV detection: Bionano SVCaller and OMSV [117] . OMSV is a tool that identifies SVs by combining molecule-to reference alignments generated from RefAligner and OMBlast.…”

Fast and Efficient Rmap Assembly using the Bi-labelled de Bruijn Graph

“…In 1993 Schwartz et al developed optical mapping [1], a system for creating an ordered, genome wide high resolution restriction map of a given organism's genome. Since this initial development, genome wide optical maps have found numerous applications including discovering structural variations [2,3], scaffolding and validating contigs for several large sequencing projects [4,5], and detecting misassembled regions in draft genomes [6,7,8]. Thus, optical mapping has assisted in the assembly of a variety of species -including various prokaryote species [9,10,11], rice [12], maize [13], mouse [14], goat [15], parrot [4], and amborella trichopoda [5].…”

“…For example, given a genome fragment TTTTAACTGGGGGGGAACTTTTTTTTAACTTTTT and an enzyme that recognizes the site AACT and cleaves in the middle, the resulting Rmap would be [6,11,11,6]. Rmaps by themselves are not traditionally used for analysis -although, they can be [16,3,2] and instead have to be assembled into longer contiguous optical maps corresponding to the genome. Hence, assembly of Rmaps refers to the problem of generating a consensus genome wide optical map from overlapping Rmaps.…”