Title | Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair. |
Publication Type | Journal Article |
Year of Publication | 2024 |
Authors | McDaniel, JH, Patel, V, Olson, ND, He, H-J, He, Z, Cole, KD, Schmitt, A, Sikkink, K, Sedlazeck, FJ, Doddapaneni, H, Jhangiani, SN, Muzny, DM, Gingras, M-C, Mehta, H, Paulin, LF, Hastie, AR, Yu, H-C, Weigman, V, Rojas, A, Kennedy, K, Remington, J, Gonzalez, I, Sudkamp, M, Wiseman, K, Lajoie, BR, Levy, S, Jain, M, Akeson, S, Narzisi, G, Steinsnyder, Z, Reeves, C, Shelton, J, Kingan, SB, Lambert, C, Bayabyan, P, Wenger, AM, McLaughlin, IJ, Adamson, A, Kingsley, C, Wescott, M, Kim, Y, Paten, B, Park, J, Violich, I, Miga, KH, Gardner, J, McNulty, B, Rosen, G, McCoy, R, Brundu, F, Sayyari, E, Scheffler, K, Truong, S, Catreux, S, Hannah, LChapman, Lipson, D, Benjamin, H, Iremadze, N, Soifer, I, Eacker, S, Wood, M, Cross, E, Husar, G, Gross, S, Vernich, M, Kolmogorov, M, Ahmad, T, Keskus, A, Bryant, A, Thibaud-Nissen, F, Trow, J, Proszynski, J, Hirschberg, JW, Ryon, K, Mason, CE, Wagner, J, Xiao, C, Liss, AS, Zook, JM |
Journal | bioRxiv |
Date Published | 2024 Oct 18 |
ISSN | 2692-8205 |
Abstract | The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first to be explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from thirteen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, and Hi-C, and karyotyping. These data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic mutations. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology. |
DOI | 10.1101/2024.09.18.613544 |
Alternate Journal | bioRxiv |
PubMed ID | 39345378 |
PubMed Central ID | PMC11429686 |
Grant List | R35 GM133747 / GM / NIGMS NIH HHS / United States OT2 OD034190 / OD / NIH HHS / United States U01 CA253405 / CA / NCI NIH HHS / United States R01 HG011274 / HG / NHGRI NIH HHS / United States U24 HG011853 / HG / NHGRI NIH HHS / United States |