Dataset Information

Improved structural variant interpretation for hereditary cancer susceptibility using long-read sequencing.

ABSTRACT: PURPOSE:Structural variants (SVs) may be an underestimated cause of hereditary cancer syndromes given the current limitations of short-read next-generation sequencing. Here we investigated the utility of long-read sequencing in resolving germline SVs in cancer susceptibility genes detected through short-read genome sequencing. METHODS:Known or suspected deleterious germline SVs were identified using Illumina genome sequencing across a cohort of 669 advanced cancer patients with paired tumor genome and transcriptome sequencing. Candidate SVs were subsequently assessed by Oxford Nanopore long-read sequencing. RESULTS:Nanopore sequencing confirmed eight simple pathogenic or likely pathogenic SVs, resolving three additional variants whose impact could not be fully elucidated through short-read sequencing. A recurrent sequencing artifact on chromosome 16p13 and one complex rearrangement on chromosome 5q35 were subsequently classified as likely benign, obviating the need for further clinical assessment. Variant configuration was further resolved in one case with a complex pathogenic rearrangement affecting TSC2. CONCLUSION:Our findings demonstrate that long-read sequencing can improve the validation, resolution, and classification of germline SVs. This has important implications for return of results, cascade carrier testing, cancer screening, and prophylactic interventions.

SUBMITTER: Thibodeau ML

PROVIDER: S-EPMC7605438 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Improved structural variant interpretation for hereditary cancer susceptibility using long-read sequencing.

Thibodeau My Linh ML O'Neill Kieran K Dixon Katherine K Reisle Caralyn C Mungall Karen L KL Krzywinski Martin M Shen Yaoqing Y Lim Howard J HJ Cheng Dean D Tse Kane K Wong Tina T Chuah Eric E Fok Alexandra A Sun Sophie S Renouf Daniel D Schaeffer David F DF Cremin Carol C Chia Stephen S Young Sean S Pandoh Pawan P Pleasance Stephen S Pleasance Erin E Mungall Andrew J AJ Moore Richard R Yip Stephen S Karsan Aly A Laskin Janessa J Marra Marco A MA Schrader Kasmintan A KA Jones Steven J M SJM

Genetics in medicine : official journal of the American College of Medical Genetics 20200706 11

<h4>Purpose</h4>Structural variants (SVs) may be an underestimated cause of hereditary cancer syndromes given the current limitations of short-read next-generation sequencing. Here we investigated the utility of long-read sequencing in resolving germline SVs in cancer susceptibility genes detected through short-read genome sequencing.<h4>Methods</h4>Known or suspected deleterious germline SVs were identified using Illumina genome sequencing across a cohort of 669 advanced cancer patients with pa ...[more]

PMID: 32624572

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Project description:BackgroundStructural variant (SV) calling from DNA sequencing data has been challenging due to several factors, including the ambiguity of short-read alignments, multiple complex SVs in the same genomic region, and the lack of "truth" datasets for benchmarking. Additionally, caller choice, parameter settings, and alignment method are known to affect SV calling. However, the impact of FASTQ read order on SV calling has not been explored for long-read data.ResultsHere, we used PacBio DNA sequencing data from 15 Caenorhabditis elegans strains and four Arabidopsis thaliana ecotypes to evaluate the sensitivity of different SV callers on FASTQ read order. Comparisons of variant call format files generated from the original and permutated FASTQ files demonstrated that the order of input data affected the SVs predicted by each caller. In particular, pbsv was highly sensitive to the order of the input data, especially at the highest depths where over 70% of the SV calls generated from pairs of differently ordered FASTQ files were in disagreement. These demonstrate that read order sensitivity is a complex, multifactorial process, as the differences observed both within and between species varied considerably according to the specific combination of aligner, SV caller, and sequencing depth. In addition to the SV callers being sensitive to the input data order, the SAMtools alignment sorting algorithm was identified as a source of variability following read order randomization.ConclusionThe results of this study highlight the sensitivity of SV calling on the order of reads encoded in FASTQ files, which has not been recognized in long-read approaches. These findings have implications for the replication of SV studies and the development of consistent SV calling protocols. Our study suggests that researchers should pay attention to the input order sensitivity of read alignment sorting methods when analyzing long-read sequencing data for SV calling, as mitigating a source of variability could facilitate future replication work. These results also raise important questions surrounding the relationship between SV caller read order sensitivity and tool performance. Therefore, tool developers should also consider input order sensitivity as a potential source of variability during the development and benchmarking of new and improved methods for SV calling.

Dataset Information

Improved structural variant interpretation for hereditary cancer susceptibility using long-read sequencing.

Publications

Improved structural variant interpretation for hereditary cancer susceptibility using long-read sequencing.

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