Scientific ReportsGenomicsPeer-reviewed journal article
Refined detection and phasing of structural aberrations in pediatric acute lymphoblastic leukemia by linked-read whole genome sequencing
Jessica NordlundiD, Yanara Marincevic-ZunigaiD, Lucia B. CavelieriD, Amanda RaineiD, Tom MartiniD, Anders LundmarkiD, Jonas AbrahamssoniD, Ulrika Norén‐NyströmiD, Gudmar Lönnerholm, Ann‐Christine SyväneniD
Abstract
Structural chromosomal rearrangements that may lead to in-frame gene-fusions represent a leading source of information for diagnosis, risk stratification, and prognosis in pediatric acute lymphoblastic leukemia (ALL). However, short-read whole genome sequencing (WGS) technologies struggle to accurately identify and phase such large-scale chromosomal aberrations in cancer genomes. We therefore evaluated linked-read WGS for detection of chromosomal rearrangements in an ALL cell line (REH) and primary samples of varying DNA quality from 12 patients diagnosed with ALL. We assessed the effect of input DNA quality on phased haplotype block size and the detectability of copy number aberrations (CNAs) and structural variants (SVs). Biobanked DNA isolated by standard column-based extraction methods was sufficient to detect chromosomal rearrangements even at low 10x sequencing coverage. Linked-read WGS enabled precise, allele-specific, digital karyotyping at a base-pair resolution for a wide range of structural variants including complex rearrangements and aneuploidy assessment. With use of haplotype information from the linked-reads, we also identified additional structural variants, such as a compound heterozygous deletion of ERG in a patient with the DUX4-IGH fusion gene. Thus, linked-read WGS allows detection of important pathogenic variants in ALL genomes at a resolution beyond that of traditional karyotyping or short-read WGS.
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: variant effect prediction
- approach: experimental assay
- Citations
- 17
- FWCI
- 2.43
- Field percentile
- top 11%
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