ID
45645
Beschreibung
Principal Investigator: Arend Sidow, PhD, Stanford University, Stanford, CA, USA MeSH: Liposarcoma https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001255 Recently developed methods that utilize partitioning of long genomic DNA fragments, and barcoding of shorter fragments derived from them, have succeeded in retaining long-range information in short sequencing reads. These so-called read cloud approaches represent a powerful, accurate, and cost-effective alternative to single-molecule long-read sequencing. We developed software, GROC-SVs, that takes advantage of read clouds for structural variant detection and assembly. We apply the method to two 10x Genomics data sets, one chromothriptic sarcoma with several spatially separated samples, and one breast cancer cell line, all Illumina-sequenced to high coverage. Comparison to short-fragment data from the same samples, and validation by mate-pair data from a subset of the sarcoma samples, demonstrate substantial improvement in specificity of breakpoint detection compared to short-fragment sequencing, at comparable sensitivity, and vice versa. The embedded long-range information also facilitates sequence assembly of a large fraction of the breakpoints; importantly, consecutive breakpoints that are closer than the average length of the input DNA molecules can be assembled together and their order and arrangement reconstructed, with some events exhibiting remarkable complexity. These features facilitated an analysis of the structural evolution of the sarcoma. In the chromothripsis, rearrangements occurred before copy number amplifications, and using the phylogenetic tree built from point mutation data, we show that single nucleotide variants and structural variants are not correlated. We predict significant future advances in structural variant science using 10x data analyzed with GROC-SVs and other read cloud-specific methods.
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- 14.03.23 14.03.23 - Simon Heim
Rechteinhaber
Arend Sidow, PhD, Stanford University, Stanford, CA, USA
Hochgeladen am
14. März 2023
DOI
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Lizenz
Creative Commons BY 4.0
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dbGaP phs001255 Molecular Evolution of Cancer
The subject consent file includes subject IDs, consent information, and case control status of the subject for chromothripsis.
- StudyEvent: SEV1
- The subject consent file includes subject IDs, consent information, and case control status of the subject for chromothripsis.
- This data table contains a mapping of study subject IDs to sample IDs. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs. The data table also includes sample use.
- This sample attributes table contains sample IDs, body site, analyte type, tumor status, and histological type.
Ähnliche Modelle
The subject consent file includes subject IDs, consent information, and case control status of the subject for chromothripsis.
- StudyEvent: SEV1
- The subject consent file includes subject IDs, consent information, and case control status of the subject for chromothripsis.
- This data table contains a mapping of study subject IDs to sample IDs. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs. The data table also includes sample use.
- This sample attributes table contains sample IDs, body site, analyte type, tumor status, and histological type.
C0441833 (UMLS CUI [1,2])