Normalization of a chromosomal contact map.

Normalization of a chromosomal contact map.
复制标题

染色体接触图的标准化。

DOI:
10.1186/1471-2164-13-436
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发表时间:
2012-08-30
期刊:
影响因子:
4.4
通讯作者:
Mozziconacci J
Mozziconacci J
中科院分区:
生物学2区
文献类型:
--
作者:
Cournac A;Marie-Nelly H;Marbouty M;Koszul R;Mozziconacci J

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染色质组织已经越来越多地被研究与其对DNA相关的代谢过程的重要影响,如复制或基因表达的调节。自十年前首次设计以来,染色体构象捕获(3C)已成为研究染色体整体构象的重要工具。它依赖于捕获染色体片段的长程反式和顺式相互作用,这些片段在最终库中的相对比例反映了它们的相互作用频率,因此反映了它们在细胞群体中的空间接近性。最近的3C与深度测序方法的结合现在允许产生高分辨率的全基因组染色体接触图。不同的协议已被用于在各种生物体中生成这样的地图。这包括哺乳动物、果蝇和酵母。基因组3C产生的大量原始数据必须经过仔细处理,以减轻实验产生的各种偏差和副产品。我们的研究旨在提出一个简单的标准化程序,以尽量减少这些不必要的,但不可避免的事件对最终结果的影响。仔细分析了以前产生的芽殖酵母S。酿酒酵母导致三个主要的偏见影响最终的数据集,包括以前未知的偏见导致的DNA分子的环化。然后,我们开发了一个简单的标准化程序来处理数据,并允许生成标准化的,高度对比的,S染色体接触图。啤酒。同样的方法随后被扩展到第一个人类基因组接触图。使用归一化的数据,我们重新审视了最初描述的离散染色体特征子集之间的优先相互作用。值得注意的是,酵母中的tRNA与人类中的CTCF、PolII结合位点之间的优先相互作用的检测可以随着所使用的标准化程序而变化。我们对获得的S.酿酒,确定了一些固有的偏见的技术,并提出了一个简单的归一化程序来分析它们。这种方法可以很容易地推广到其他生物的基因组3C实验。需要进行更多的实验和分析,以达到通过这些方法生成的地图的最佳分辨率和精度。与呈现最高水平的同质性的细胞群体一起工作将证明在这方面是有用的。
Chromatin organization has been increasingly studied in relation with its important influence on DNA-related metabolic processes such as replication or regulation of gene expression. Since its original design ten years ago, capture of chromosome conformation (3C) has become an essential tool to investigate the overall conformation of chromosomes. It relies on the capture of long-range trans and cis interactions of chromosomal segments whose relative proportions in the final bank reflect their frequencies of interactions, hence their spatial proximity in a population of cells. The recent coupling of 3C with deep sequencing approaches now allows the generation of high resolution genome-wide chromosomal contact maps. Different protocols have been used to generate such maps in various organisms. This includes mammals, drosophila and yeast. The massive amount of raw data generated by the genomic 3C has to be carefully processed to alleviate the various biases and byproducts generated by the experiments. Our study aims at proposing a simple normalization procedure to minimize the influence of these unwanted but inevitable events on the final results. Careful analysis of the raw data generated previously for budding yeast S. cerevisiae led to the identification of three main biases affecting the final datasets, including a previously unknown bias resulting from the circularization of DNA molecules. We then developed a simple normalization procedure to process the data and allow the generation of a normalized, highly contrasted, chromosomal contact map for S. cerevisiae. The same method was then extended to the first human genome contact map. Using the normalized data, we revisited the preferential interactions originally described between subsets of discrete chromosomal features. Notably, the detection of preferential interactions between tRNA in yeast and CTCF, PolII binding sites in human can vary with the normalization procedure used. We quantitatively reanalyzed the genomic 3C data obtained for S. cerevisiae, identified some of the biases inherent to the technique and proposed a simple normalization procedure to analyse them. Such an approach can be easily generalized for genomic 3C experiments in other organisms. More experiments and analysis will be necessary to reach optimal resolution and accuracies of the maps generated through these approaches. Working with cell population presenting highest levels of homogeneity will prove useful in this regards.
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