Browse > Article
http://dx.doi.org/10.5808/GI.2013.11.1.24

Bioinformatics Interpretation of Exome Sequencing: Blood Cancer  

Kim, Jiwoong (Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology)
Lee, Yun-Gyeong (Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology)
Kim, Namshin (Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology)
Abstract
We had analyzed 10 exome sequencing data and single nucleotide polymorphism chips for blood cancer provided by the PGM21 (The National Project for Personalized Genomic Medicine) Award program. We had removed sample G06 because the pair is not correct and G10 because of possible contamination. In-house software somatic copy-number and heterozygosity alteration estimation (SCHALE) was used to detect one loss of heterozygosity region in G05. We had discovered 27 functionally important mutations. Network and pathway analyses gave us clues that NPM1, GATA2, and CEBPA were major driver genes. By comparing with previous somatic mutation profiles, we had concluded that the provided data originated from acute myeloid leukemia. Protein structure modeling showed that somatic mutations in IDH2, RASGEF1B, and MSH4 can affect protein structures.
Keywords
acute myeloid leukemia; computational biology; exome; mutation;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009;25:1754- 1760.   DOI   ScienceOn
2 Koboldt DC, Zhang Q, Larson DE, Shen D, McLellan MD, Lin L, et al. VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res 2012;22:568-576.   DOI   ScienceOn
3 Godley LA. Profiles in leukemia. N Engl J Med 2012;366: 1152-1153.   DOI   ScienceOn
4 Patel RK, Jain M. NGS QC Toolkit: a toolkit for quality control of next generation sequencing data. PLoS One 2012;7:e30619.   DOI
5 McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The Genome Analysis Toolkit: a Map- Reduce framework for analyzing next-generation DNA sequencing data. Genome Res 2010;20:1297-1303.   DOI   ScienceOn
6 Liu X, Jian X, Boerwinkle E. dbNSFP: a lightweight database of human nonsynonymous SNPs and their functional predictions. Hum Mutat 2011;32:894-899.   DOI   ScienceOn
7 Futreal PA, Coin L, Marshall M, Down T, Hubbard T, Wooster R, et al. A census of human cancer genes. Nat Rev Cancer 2004;4:177-183.   DOI   ScienceOn
8 Ingenuity Systems. Redwood City: Ingenuity Systems. Accessed 2013 Jan 1. Available from: http://www.ingenuity.com/.
9 Grossmann V, Kohlmann A, Zenger M, Schindela S, Eder C, Weissmann S, et al. A deep-sequencing study of chronic myeloid leukemia patients in blast crisis (BC-CML) detects mutations in 76.9% of cases. Leukemia 2011;25:557-560.   DOI   ScienceOn
10 Wang L, Lawrence MS, Wan Y, Stojanov P, Sougnez C, Stevenson K, et al. SF3B1 and other novel cancer genes in chronic lymphocytic leukemia. N Engl J Med 2011;365: 2497-2506.   DOI   ScienceOn