Suppr超能文献

采用下一代测序技术检测 DNA 拷贝数,包括端粒和线粒体。

DNA copy number, including telomeres and mitochondria, assayed using next-generation sequencing.

机构信息

Rosetta Inpharmatics LLC, Merck & Co., Inc., Seattle, Washington 98109, USA.

出版信息

BMC Genomics. 2010 Apr 16;11:244. doi: 10.1186/1471-2164-11-244.

Abstract

BACKGROUND

DNA copy number variations occur within populations and aberrations can cause disease. We sought to develop an improved lab-automatable, cost-efficient, accurate platform to profile DNA copy number.

RESULTS

We developed a sequencing-based assay of nuclear, mitochondrial, and telomeric DNA copy number that draws on the unbiased nature of next-generation sequencing and incorporates techniques developed for RNA expression profiling. To demonstrate this platform, we assayed UMC-11 cells using 5 million 33 nt reads and found tremendous copy number variation, including regions of single and homogeneous deletions and amplifications to 29 copies; 5 times more mitochondria and 4 times less telomeric sequence than a pool of non-diseased, blood-derived DNA; and that UMC-11 was derived from a male individual.

CONCLUSION

The described assay outputs absolute copy number, outputs an error estimate (p-value), and is more accurate than array-based platforms at high copy number. The platform enables profiling of mitochondrial levels and telomeric length. The assay is lab-automatable and has a genomic resolution and cost that are tunable based on the number of sequence reads.

摘要

背景

DNA 拷贝数变异存在于人群中,异常可导致疾病。我们试图开发一种改进的实验室自动化、成本效益高、准确的平台来分析 DNA 拷贝数。

结果

我们开发了一种基于测序的核、线粒体和端粒 DNA 拷贝数分析方法,利用下一代测序的无偏性质,并结合了为 RNA 表达谱分析开发的技术。为了验证这个平台,我们使用 500 万个 33nt 读长对 UMC-11 细胞进行了检测,发现了巨大的拷贝数变异,包括单倍体和均匀缺失和扩增到 29 个拷贝的区域;与一组非疾病、血液来源的 DNA 相比,线粒体多 5 倍,端粒序列少 4 倍;而且 UMC-11 来自于一名男性个体。

结论

所描述的测定方法输出绝对拷贝数,输出误差估计值(p 值),并且在高拷贝数时比基于阵列的平台更准确。该平台能够对线粒体水平和端粒长度进行分析。该测定方法可在实验室中自动化进行,其基因组分辨率和成本可根据测序读长的数量进行调整。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4795/2867831/5e3b3ea90b88/1471-2164-11-244-1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验