Suppr超能文献

建立人类大脑皮层中重复元件表达的基线水平。

Establishing the baseline level of repetitive element expression in the human cortex.

机构信息

Department of Biostatistics and Computational Biology, Dana-Farber CancerInstitute, 450 Brookline Ave, Boston, 02115, USA.

出版信息

BMC Genomics. 2011 Oct 10;12:495. doi: 10.1186/1471-2164-12-495.

Abstract

BACKGROUND

Although nearly half of the human genome is comprised of repetitive sequences, the expression profile of these elements remains largely uncharacterized. Recently developed high throughput sequencing technologies provide us with a powerful new set of tools to study repeat elements. Hence, we performed whole transcriptome sequencing to investigate the expression of repetitive elements in human frontal cortex using postmortem tissue obtained from the Stanley Medical Research Institute.

RESULTS

We found a significant amount of reads from the human frontal cortex originate from repeat elements. We also noticed that Alu elements were expressed at levels higher than expected by random or background transcription. In contrast, L1 elements were expressed at lower than expected amounts.

CONCLUSIONS

Repetitive elements are expressed abundantly in the human brain. This expression pattern appears to be element specific and can not be explained by random or background transcription. These results demonstrate that our knowledge about repetitive elements is far from complete. Further characterization is required to determine the mechanism, the control, and the effects of repeat element expression.

摘要

背景

尽管人类基因组的近一半由重复序列组成,但这些元件的表达谱在很大程度上仍未被描述。最近开发的高通量测序技术为我们提供了一组强大的新工具来研究重复元件。因此,我们使用来自斯坦利医学研究所的死后组织进行了全转录组测序,以研究人类额叶皮质中重复元件的表达。

结果

我们发现大量来自人类额叶皮质的reads 来源于重复元件。我们还注意到,Alu 元件的表达水平高于随机或背景转录的预期水平。相比之下,L1 元件的表达量低于预期。

结论

重复元件在人类大脑中大量表达。这种表达模式似乎是特定于元件的,不能用随机或背景转录来解释。这些结果表明,我们对重复元件的了解还远远不够。需要进一步的表征来确定重复元件表达的机制、控制和影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/3207997/0951631d523e/1471-2164-12-495-1.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