Abstract
BackgroundMany genetic/genomic disorders are caused by genomic rearrangements. Standard methods can often characterize these variations only partly, e.g., copy number changes or breakpoints. It is important to fully understand the order and orientation of rearranged fragments, with precise breakpoints, to know the pathogenicity of the rearrangements.MethodsWe performed whole-genome-coverage nanopore sequencing of long DNA reads from four patients with chromosomal translocations. We identified rearrangements relative to a reference human genome, subtracted rearrangements shared by any of 33 control individuals, and determined the order and orientation of rearranged fragments, with our newly developed analysis pipeline.ResultsWe describe the full characterization of complex chromosomal rearrangements, by filtering out genomic rearrangements seen in controls without the same disease, reducing the number of loci per patient from a few thousand to a few dozen. Breakpoint detection was very accurate; we usually see ~ 0 ± 1 base difference from Sanger sequencing-confirmed breakpoints. For one patient with two reciprocal chromosomal translocations, we find that the translocation points have complex rearrangements of multiple DNA fragments involving 5 chromosomes, which we could order and orient by an automatic algorithm, thereby fully reconstructing the rearrangement. A rearrangement is more than the sum of its parts: some properties, such as sequence loss, can be inferred only after reconstructing the whole rearrangement. In this patient, the rearrangements were evidently caused by shattering of the chromosomes into multiple fragments, which rejoined in a different order and orientation with loss of some fragments.ConclusionsWe developed an effective analytic pipeline to find chromosomal aberration in congenital diseases by filtering benign changes, only from long read sequencing. Our algorithm for reconstruction of complex rearrangements is useful to interpret rearrangements with many breakpoints, e.g., chromothripsis. Our approach promises to fully characterize many congenital germline rearrangements, provided they do not involve poorly understood loci such as centromeric repeats.
Highlights
Many genetic/genomic disorders are caused by genomic rearrangements
It filtered out rearrangements that are seen in any of 33 control individuals (Fig. 3, Additional file 1: Table S1)
Because we are not interested in simple deletions, we ignored gaps < 10 kb; we tested a lower gap threshold (100 bp) which produced vastly more output at first, but after discarding rearrangements shared with the controls, the output size became closer to the default (g = 10 kb), suggesting that many of these gaps are shared with controls (Additional file 1: Fig. S5)
Summary
Many genetic/genomic disorders are caused by genomic rearrangements. Standard methods can often characterize these variations only partly, e.g., copy number changes or breakpoints. Many small nucleotidelevel changes (one to a few bases) in 4209 genes have been reported in OMIM (https://www.omim.org/) (as of Jan 21, 2020), which are known as single gene disorders In addition to these small changes, large structural variations of the chromosomes can cause diseases. Previous studies on pathogenic structural changes in patients with genetic/genomic disorders found chromosomal abnormalities by microscopy, by detecting copy number variations (CNVs) using microarrays [1], or by detecting both CNVs and breakpoints using highthroughput short read sequencing [2]. Long read sequencing (PacBio or nanopore) is advantageous for characterizing rearrangements in such cases and is recently beginning to be used for patient genome analysis to identify pathogenic variations [4,5,6]. Detection and reconstruction methods for complex rearrangements are needed to characterize pathogenic variations from whole genome sequencing data
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