Structural variant analysis of a cancer reference cell line sample using multiple sequencing technologies.

Autor:	Talsania K; Sequencing Facility Bioinformatics Group, Advanced Biomedical and Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.; Bioinformatics and Computational Science Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD, USA., Shen TW; Sequencing Facility Bioinformatics Group, Advanced Biomedical and Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.; Bioinformatics and Computational Science Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD, USA., Chen X; Sequencing Facility Bioinformatics Group, Advanced Biomedical and Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.; Bioinformatics and Computational Science Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD, USA., Jaeger E; Illumina Inc, Foster City, CA, USA., Li Z; Sentieon Inc, Mountain View, CA, USA., Chen Z; Center for Genomics, Loma Linda University School of Medicine, Loma Linda, CA, USA., Chen W; Center for Genomics, Loma Linda University School of Medicine, Loma Linda, CA, USA., Tran B; Sequencing Facility, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, USA., Kusko R; Immuneering Corp, Cambridge, MA, USA., Wang L; Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA., Pang AWC; Bionano Genomics, San Diego, CA92121, USA., Yang Z; Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China., Choudhari S; Sequencing Facility Bioinformatics Group, Advanced Biomedical and Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.; Bioinformatics and Computational Science Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD, USA., Colgan M; Center for Drug Evaluation and Research, FDA, Silver Spring, MD, USA., Fang LT; Bioinformatics Research & Early Development, Roche Sequencing Solutions Inc, 1301 Shoreway Road, Belmont, CA, 94002, USA., Carroll A; DNAnexus, Mountain View, CA, USA., Shetty J; Sequencing Facility, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, USA., Kriga Y; Sequencing Facility, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, USA., German O; Sequencing Facility, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, USA., Smirnova T; Sequencing Facility, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, USA., Liu T; Center for Genomics, Loma Linda University School of Medicine, Loma Linda, CA, USA., Li J; Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China., Kellman B; Bionano Genomics, San Diego, CA92121, USA., Hong K; Bionano Genomics, San Diego, CA92121, USA., Hastie AR; Bionano Genomics, San Diego, CA92121, USA., Natarajan A; Illumina Inc, Foster City, CA, USA., Moshrefi A; Illumina Inc, Foster City, CA, USA., Granat A; Illumina Inc, Foster City, CA, USA., Truong T; Illumina Inc, Foster City, CA, USA., Bombardi R; Illumina Inc, Foster City, CA, USA., Mankinen V; Dovetail Genomics, Scotts Valley, CA, USA., Meerzaman D; Computational Genomics and Bioinformatics Branch, Center for Biomedical Informatics and Information Technology (CBIIT), National Cancer Institute, Rockville, MD, USA., Mason CE; Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA., Collins J; Sequencing Facility Bioinformatics Group, Advanced Biomedical and Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.; Bioinformatics and Computational Science Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD, USA., Stahlberg E; Bioinformatics and Computational Science Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD, USA., Xiao C; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA., Wang C; Center for Genomics, Loma Linda University School of Medicine, Loma Linda, CA, USA. chwang@llu.edu., Xiao W; Center for Drug Evaluation and Research, FDA, Silver Spring, MD, USA. Wenming.Xiao@fda.hhs.gov., Zhao Y; Sequencing Facility Bioinformatics Group, Advanced Biomedical and Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD, USA. Yongmei.Zhao@nih.gov.; Bioinformatics and Computational Science Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD, USA. Yongmei.Zhao@nih.gov.
Jazyk:	angličtina
Zdroj:	Genome biology [Genome Biol] 2022 Dec 13; Vol. 23 (1), pp. 255. Date of Electronic Publication: 2022 Dec 13.
DOI:	10.1186/s13059-022-02816-6
Abstrakt:	Background: The cancer genome is commonly altered with thousands of structural rearrangements including insertions, deletions, translocation, inversions, duplications, and copy number variations. Thus, structural variant (SV) characterization plays a paramount role in cancer target identification, oncology diagnostics, and personalized medicine. As part of the SEQC2 Consortium effort, the present study established and evaluated a consensus SV call set using a breast cancer reference cell line and matched normal control derived from the same donor, which were used in our companion benchmarking studies as reference samples. Results: We systematically investigated somatic SVs in the reference cancer cell line by comparing to a matched normal cell line using multiple NGS platforms including Illumina short-read, 10X Genomics linked reads, PacBio long reads, Oxford Nanopore long reads, and high-throughput chromosome conformation capture (Hi-C). We established a consensus SV call set of a total of 1788 SVs including 717 deletions, 230 duplications, 551 insertions, 133 inversions, 146 translocations, and 11 breakends for the reference cancer cell line. To independently evaluate and cross-validate the accuracy of our consensus SV call set, we used orthogonal methods including PCR-based validation, Affymetrix arrays, Bionano optical mapping, and identification of fusion genes detected from RNA-seq. We evaluated the strengths and weaknesses of each NGS technology for SV determination, and our findings provide an actionable guide to improve cancer genome SV detection sensitivity and accuracy. Conclusions: A high-confidence consensus SV call set was established for the reference cancer cell line. A large subset of the variants identified was validated by multiple orthogonal methods. (© 2022. The Author(s).)
Databáze:	MEDLINE
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