CSCS:中国春面包小麦的染色质状态界面

IF 4.6 4区 农林科学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY aBIOTECH Pub Date : 2021-05-31 DOI:10.1007/s42994-021-00048-z
Xiaojuan Ran, Tengfei Tang, Meiyue Wang, Luhuan Ye, Yili Zhuang, Fei Zhao, Yijing Zhang
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引用次数: 3

摘要

面包小麦品种中国春(CS)的染色体水平基因组组装最近发表。负责调节基因活性的调控元件(RE)的全基因组鉴定是进一步机制研究的关键。由于表观遗传学活性可以反映RE活性,因此基于表观基因组特征定义染色质状态是检测RE的有效方法。在这里,我们提出了基于网络的平台Chinese Spring染色质状态(CSCS),它提供CS染色质特征信息。CSCS包括15个最近发表的表观基因组数据集,包括开放染色质和主要染色质标记,这些数据集被进一步划分为15种不同的染色质状态。CSCS通过对所有染色质状态片段的训练自组织映射(SOM)和对基因组区域或基因的JBrowse可视化,来策划有关这些染色质状态的详细信息。基因组区域或基因的Motif分析、基因的GO分析和新的表观基因组数据集的SOM分析也被整合到CSCS中。总之,CSCS数据库包含小麦染色质特征的组合模式,有助于检测功能元件和进一步阐明调节活性。我们通过一个例子说明了CSCS如何实现生物学见解,证明CSCS是密集数据挖掘的一种非常有用的资源。CSCS可在http://bioinfo.cemps.ac.cn/CSCS/.
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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CSCS: a chromatin state interface for Chinese Spring bread wheat

A chromosome-level genome assembly of the bread wheat variety Chinese Spring (CS) has recently been published. Genome-wide identification of regulatory elements (REs) responsible for regulating gene activity is key to further mechanistic studies. Because epigenetic activity can reflect RE activity, defining chromatin states based on epigenomic features is an effective way to detect REs. Here, we present the web-based platform Chinese Spring chromatin state (CSCS), which provides CS chromatin signature information. CSCS includes 15 recently published epigenomic data sets including open chromatin and major chromatin marks, which are further partitioned into 15 distinct chromatin states. CSCS curates detailed information about these chromatin states, with trained self-organization mapping (SOM) for segments in all chromatin states and JBrowse visualization for genomic regions or genes. Motif analysis for genomic regions or genes, GO analysis for genes and SOM analysis for new epigenomic data sets are also integrated into CSCS. In summary, the CSCS database contains the combinatorial patterns of chromatin signatures in wheat and facilitates the detection of functional elements and further clarification of regulatory activities. We illustrate how CSCS enables biological insights using one example, demonstrating that CSCS is a highly useful resource for intensive data mining. CSCS is available at http://bioinfo.cemps.ac.cn/CSCS/.

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CiteScore
7.70
自引率
2.80%
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