Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, V5Z 1L3, Canada; Department of Medical Genetics, University of British Columbia, Vancouver V6T 1Z3, Canada.
Trends Genet. 2015 Aug;31(8):465-74. doi: 10.1016/j.tig.2015.04.001. Epub 2015 May 1.
Deep sequencing has impacted on cancer research by enabling routine sequencing of genomes and exomes to identify genetic changes associated with carcinogenesis. Researchers can now use the frequency, type, and context of all mutations in tumor genomes to extract mutation signatures that reflect the driving mutational processes. Identifying mutation signatures, however, may not immediately suggest a mechanism. Consequently, several recent studies have employed deep sequencing of model organisms exposed to discrete genetic or environmental perturbations. These studies exploit the simpler genomes and availability of powerful genetic tools in model organisms to analyze mutation signatures under controlled conditions, forging mechanistic links between mutational processes and signatures. We discuss the power of this approach and suggest that many such studies may be on the horizon.
深度测序通过常规的基因组和外显子组测序来识别与致癌相关的遗传变化，从而对癌症研究产生了影响。研究人员现在可以使用肿瘤基因组中所有突变的频率、类型和上下文来提取反映驱动突变过程的突变特征。然而，确定突变特征并不一定能立即提示机制。因此，最近有几项研究利用深度测序技术对暴露于离散遗传或环境干扰的模式生物进行了研究。这些研究利用模式生物中更简单的基因组和强大的遗传工具的可用性，在受控条件下分析突变特征，在突变过程和特征之间建立了机制联系。我们讨论了这种方法的优势，并认为许多这样的研究可能即将出现。
