使用高分辨率全基因组寡核苷酸阵列对癌症的拷贝数改变和RNA表达谱进行综合分析。
Integrated analysis of copy number alteration and RNA expression profiles of cancer using a high-resolution whole-genome oligonucleotide array.
作者信息
Jung Seung-Hyun, Shin Seung-Hun, Yim Seon-Hee, Choi Hye-Sun, Lee Sug-Hyung, Chung Yeun-Jun
机构信息
Department of Microbiology, Integrated Research Center for Genome Polymorphism, Korea.
出版信息
Exp Mol Med. 2009 Jul 31;41(7):462-70. doi: 10.3858/emm.2009.41.7.051.
Recently, microarray-based comparative genomic hybridization (array-CGH) has emerged as a very efficient technology with higher resolution for the genome-wide identification of copy number alterations (CNA). Although CNAs are thought to affect gene expression, there is no platform currently available for the integrated CNA-expression analysis. To achieve high-resolution copy number analysis integrated with expression profiles, we established human 30k oligoarray-based genome-wide copy number analysis system and explored the applicability of this system for integrated genome and transcriptome analysis using MDA-MB-231 cell line. We compared the CNAs detected by the oligoarray with those detected by the 3k BAC array for validation. The oligoarray identified the single copy difference more accurately and sensitively than the BAC array. Seventeen CNAs detected by both platforms in MDA-MB-231 such as gains of 5p15.33-13.1, 8q11.22-8q21.13, 17p11.2, and losses of 1p32.3, 8p23.3-8p11.21, and 9p21 were consistently identified in previous studies on breast cancer. There were 122 other small CNAs (mean size 1.79 mb) that were detected by oligoarray only, not by BAC-array. We performed genomic qPCR targeting 7 CNA regions, detected by oligoarray only, and one non-CNA region to validate the oligoarray CNA detection. All qPCR results were consistent with the oligoarray-CGH results. When we explored the possibility of combined interpretation of both DNA copy number and RNA expression profiles, mean DNA copy number and RNA expression levels showed a significant correlation. In conclusion, this 30k oligoarray-CGH system can be a reasonable choice for analyzing whole genome CNAs and RNA expression profiles at a lower cost.
最近,基于微阵列的比较基因组杂交技术(array-CGH)已成为一种非常有效的技术,它在全基因组范围内识别拷贝数改变(CNA)方面具有更高的分辨率。尽管人们认为CNA会影响基因表达,但目前尚无用于整合CNA-表达分析的平台。为了实现与表达谱相结合的高分辨率拷贝数分析,我们建立了基于人类30k寡核苷酸阵列的全基因组拷贝数分析系统,并探索了该系统在使用MDA-MB-231细胞系进行整合基因组和转录组分析中的适用性。我们将寡核苷酸阵列检测到的CNA与3k BAC阵列检测到的CNA进行比较以进行验证。寡核苷酸阵列比BAC阵列更准确、更灵敏地识别单拷贝差异。在MDA-MB-231中,两个平台均检测到的17个CNA,例如5p15.33-13.1、8q11.22-8q21.13、17p11.2的增益以及1p32.3、8p23.3-8p11.21和9p21的缺失,在先前关于乳腺癌的研究中得到了一致确认。还有122个其他小的CNA(平均大小1.79 mb)仅由寡核苷酸阵列检测到,而不是由BAC阵列检测到。我们针对仅由寡核苷酸阵列检测到的7个CNA区域和一个非CNA区域进行了基因组qPCR,以验证寡核苷酸阵列CNA检测。所有qPCR结果均与寡核苷酸阵列-CGH结果一致。当我们探索将DNA拷贝数和RNA表达谱进行联合解释的可能性时,平均DNA拷贝数和RNA表达水平显示出显著相关性。总之,这种30k寡核苷酸阵列-CGH系统可以成为以较低成本分析全基因组CNA和RNA表达谱的合理选择。