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Refined detection and phasing of structural aberrations in pediatric acute lymphoblastic leukemia by linked-read whole genome sequencing

ABSTRACT: We evaluated linked-read whole genome sequencing (WGS) for detection of structural chromosomal rearrangements in primary samples of varying DNA quality from 12 patients diagnosed with ALL. Linked-read WGS enabled precise, allele-specific, digital karyotyping at a base-pair resolution for a wide range of structural variants including complex rearrangements, aneuploidy assessment and gene deletions. Additional RNA-sequencing and copy number aberrations (CNA) data from Illumina Infinium arrays were also generated and assessed against the linked-read WGS data. RNA-sequencing data was used to support structural chromosomal rearrangements detected in the linked-read WGS data by detecting expressed fusion genes as a consequence of the rearrangements. Illumina Infinium arrays (450k array and/or SNP array) were used to assess CNA status to further support the findings in the linked-read WGS data. The processed CNA data from the primary ALL patient samples has been deposited to GEO. RNA-sequencing, linked-read WGS data, and raw SNP array data from the primary ALL patient samples will not be deposited because the patient/parent consent does not cover depositing data that may be used for large-scale determination of germline variants in a repository. The ALL samples were collected 10-20 years ago from pediatric patients aged 2-15 years, some whom have deceased. The linked-read WGS data and the RNA-sequencing data sets generated in the study are available upon reasonable request from the corresponding author Jessica.Nordlund@medsci.uu.se.

ORGANISM(S): Homo sapiens

PROVIDER: GSE116057 | GEO | 2020/03/02

REPOSITORIES: GEO

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Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing.

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Refined detection and phasing of structural aberrations in pediatric acute lymphoblastic leukemia by linked-read whole genome sequencing

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