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正常组织中的样本内共甲基化模式。

Within-sample co-methylation patterns in normal tissues.

作者信息

Sun Lillian, Sun Shuying

机构信息

1Stanford University, Stanford, CA USA.

2Department of Mathematics, Texas State University, San Marcos, TX USA.

出版信息

BioData Min. 2019 May 9;12:9. doi: 10.1186/s13040-019-0198-8. eCollection 2019.

Abstract

BACKGROUND

DNA methylation is an epigenetic event that may regulate gene expression. Because of this regulation role, aberrant DNA methylation is often associated with many diseases. Within-sample DNA co-methylation is the similarity of methylation in nearby cytosine sites of a chromosome. It is important to study co-methylation patterns. However, it is not well studied yet, and it is unclear to us what co-methylation patterns normal DNA samples have. Are the co-methylation patterns of the same tissue across several samples different? Are the co-methylation patterns of various tissues of the same sample different? To answer these questions, we conduct analyses using two sets of data: 3-sample-1-tissue (3S1T) and 1-sample-8-tissue (1S8T).

RESULTS

To study the co-methylation patterns of the two datasets, 3S1T and 1S8T, we investigate the following questions: How often does one methylation state change to other methylation states and how is this change associated with chromosome distance? Based on the 3S1T data, we find there is not significant co-methylation difference among the same spleen tissues of three different samples. However, the analysis results of 1S8T data show that there were significant differences among eight tissues of one sample. For both 3S1T and 1S8T data, we find that the no/low methylation state A and high/full methylation state D tend to remain the same along a chromosome region. We also find that the low/partial methylation state B and partial/high methylation state C tend to change to higher methylation states along a chromosome. Finally, we find that lengths of most co-methylation regions are very short with only a few hundred base pairs. In fact, only a small proportion of methylated regions are longer than 1000 base pairs.

CONCLUSIONS

In this paper, we have addressed a few questions regarding within-sample co-methylation patterns in normal tissues. Our statistical analysis results and answers may help researchers to better understand the biological process of DNA methylation. This may pave the way to develop better analysis methods for future methylation research.

摘要

背景

DNA甲基化是一种可能调节基因表达的表观遗传事件。由于这种调节作用,异常的DNA甲基化常与多种疾病相关。样本内DNA共甲基化是指染色体上相邻胞嘧啶位点甲基化的相似性。研究共甲基化模式很重要。然而,目前对此研究尚不充分,我们也不清楚正常DNA样本的共甲基化模式是怎样的。同一个组织在多个样本中的共甲基化模式是否不同?同一样本中不同组织的共甲基化模式是否不同?为回答这些问题,我们使用两组数据进行分析:3样本1组织(3S1T)和1样本8组织(1S8T)。

结果

为研究3S1T和1S8T这两个数据集的共甲基化模式,我们研究了以下问题:一种甲基化状态转变为其他甲基化状态的频率如何,以及这种转变与染色体距离有怎样的关联?基于3S1T数据,我们发现三个不同样本的相同脾脏组织之间不存在显著的共甲基化差异。然而,1S8T数据的分析结果表明,一个样本的八个组织之间存在显著差异。对于3S1T和1S8T数据,我们发现无/低甲基化状态A和高/全甲基化状态D倾向于在染色体区域上保持不变。我们还发现低/部分甲基化状态B和部分/高甲基化状态C倾向于沿着染色体转变为更高的甲基化状态。最后,我们发现大多数共甲基化区域的长度非常短,只有几百个碱基对。实际上,只有一小部分甲基化区域长度超过1000个碱基对。

结论

在本文中,我们解决了一些关于正常组织样本内共甲基化模式的问题。我们的统计分析结果和答案可能有助于研究人员更好地理解DNA甲基化的生物学过程。这可能为未来甲基化研究开发更好的分析方法铺平道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be7a/6506960/569809d3ef0a/13040_2019_198_Fig1_HTML.jpg

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