Unexpected effects of different genetic backgrounds on identification of genomic rearrangements via whole-genome next generation sequencing
| Autor: | Jing Wang, Katherine Gowan, Sawanee S. Viboolsittiseri, Zhangguo Chen, Kenneth L. Jones, Bifeng Gao, Sonia M. Leach, Tanya Kadoishi, Ameet K. Mishra, Katrina Diener |
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| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Genomic instability Lymphoma Sequence assembly Genomics Mice Transgenic Biology de novo assembly Whole genome next generation sequencing Genome DNA sequencing Translocation Genetic 03 medical and health sciences Mice Genetics Animals Comparative genomics Gene Rearrangement B-Lymphocytes Computational Biology High-Throughput Nucleotide Sequencing Reproducibility of Results Gene rearrangement Different genetic background 3. Good health B cell lymphoma 030104 developmental biology Genetic Background Personal genomics Reference genome Biotechnology Research Article |
| Zdroj: | BMC Genomics |
| ISSN: | 1471-2164 |
| Popis: | Background Whole genome next generation sequencing (NGS) is increasingly employed to detect genomic rearrangements in cancer genomes, especially in lymphoid malignancies. We recently established a unique mouse model by specifically deleting a key non-homologous end-joining DNA repair gene, Xrcc4, and a cell cycle checkpoint gene, Trp53, in germinal center B cells. This mouse model spontaneously develops mature B cell lymphomas (termed G1XP lymphomas). Results Here, we attempt to employ whole genome NGS to identify novel structural rearrangements, in particular inter-chromosomal translocations (CTXs), in these G1XP lymphomas. We sequenced six lymphoma samples, aligned our NGS data with mouse reference genome (in C57BL/6J (B6) background) and identified CTXs using CREST algorithm. Surprisingly, we detected widespread CTXs in both lymphomas and wildtype control samples, majority of which were false positive and attributable to different genetic backgrounds. In addition, we validated our NGS pipeline by sequencing multiple control samples from distinct tissues of different genetic backgrounds of mouse (B6 vs non-B6). Lastly, our studies showed that widespread false positive CTXs can be generated by simply aligning sequences from different genetic backgrounds of mouse. Conclusions We conclude that mapping and alignment with reference genome might not be a preferred method for analyzing whole-genome NGS data obtained from a genetic background different from reference genome. Given the complex genetic background of different mouse strains or the heterogeneity of cancer genomes in human patients, in order to minimize such systematic artifacts and uncover novel CTXs, a preferred method might be de novo assembly of personalized normal control genome and cancer cell genome, instead of mapping and aligning NGS data to mouse or human reference genome. Thus, our studies have critical impact on the manner of data analysis for cancer genomics. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3153-9) contains supplementary material, which is available to authorized users. |
| Databáze: | OpenAIRE |
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