Title |
Whole genome sequence analysis of BT-474 using complete Genomics’ standard and long fragment read technologies
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Published in |
Giga Science, February 2016
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DOI | 10.1186/s13742-016-0113-x |
Pubmed ID | |
Authors |
Serban Ciotlos, Qing Mao, Rebecca Yu Zhang, Zhenyu Li, Robert Chin, Natali Gulbahce, Sophie Jia Liu, Radoje Drmanac, Brock A. Peters |
Abstract |
The cell line BT-474 is a popular cell line for studying the biology of cancer and developing novel drugs. However, there is no complete, published genome sequence for this highly utilized scientific resource. In this study we sought to provide a comprehensive and useful data set for the scientific community by generating a whole genome sequence for BT-474. Five μg of genomic DNA, isolated from an early passage of the BT-474 cell line, was used to generate a whole genome sequence (114X coverage) using Complete Genomics' standard sequencing process. To provide additional variant phasing and structural variation data we also processed and analyzed two separate libraries of 5 and 6 individual cells to depths of 99X and 87X, respectively, using Complete Genomics' Long Fragment Read (LFR) technology. BT-474 is a highly aneuploid cell line with an extremely complex genome sequence. This ~300X total coverage genome sequence provides a more complete understanding of this highly utilized cell line at the genomic level. |
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Geographical breakdown
Country | Count | As % |
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Germany | 1 | 25% |
France | 1 | 25% |
Hong Kong | 1 | 25% |
Unknown | 1 | 25% |
Demographic breakdown
Type | Count | As % |
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Scientists | 3 | 75% |
Science communicators (journalists, bloggers, editors) | 1 | 25% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 18 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 8 | 44% |
Researcher | 3 | 17% |
Professor | 1 | 6% |
Student > Doctoral Student | 1 | 6% |
Student > Master | 1 | 6% |
Other | 1 | 6% |
Unknown | 3 | 17% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 9 | 50% |
Agricultural and Biological Sciences | 3 | 17% |
Computer Science | 2 | 11% |
Immunology and Microbiology | 1 | 6% |
Unknown | 3 | 17% |