Visual genome 3D structure and long-distance chromosomal action are realized

Title: The 3D Genome Browser: a web-based browser for visualizing 3D genome organization and long-range chromatin interactions
Journal:
Yanli Wang, Fan Song, Bo Zhang, Lijun Zhang, Jie Xu, Da Kuang, Daofeng Li, Mayank N. K. Choudhary, Yun Li, Ming Hu, Ross Hardison, Ting Wang and Feng Yue
Published: 2018/10/4
Digital ID: 10.1186/s13059-018-1519-9
original link:
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In the mammalian genome, the three-dimensional structure of chromosomes plays an important role in gene expression regulation. At the DNA level, distant regulatory originals, such as enhancers, can regulate the expression of target genes through the proximity of spatial structures. At a higher level of chromosomal structure, the topological domain found in recent years is considered to be the basic unit of mammalian chromosomal structure. Topological domain is one of the advanced structures of chromosomes of mega-base size, which was first revealed by Hi-C technology. The topology domain provides a very good explanation for gene regulation of remote enhancers. In addition to the topological domain, other chromosomal structures such as A/B structures, chromatin loops, etc. are also revealed by Hi-C derivative techniques. These Hi-C derivative technologies, such as Hi-C, ChIA-PET, Capture Hi-C, PLAC-seq, and HiChIP, provide unprecedented opportunities and challenges for the study of chromosomal spatial structures. However, with the rapid growth of Hi-C data, efficient and convenient data visualization technology becomes urgent. At the same time, efficient visualization plays an important role in revealing the biological significance hidden behind Hi-C data. However, because the data is often large and complex, it can be inefficient and time-consuming for independent researchers to visualize the data themselves.
recently published a methodology article entitled "The 3D Genome Browser: a web-based browser for visualizing 3D genome organization and long-range chromatin interactions" in
by Yue Feng, a member of the Yuefeng Task Force at Penn State University in the United States, and the Wang Boat Task Force at the University of Washington. This article describes the web-based 3D Genome Browser () they developed. It is currently the most popular 3D genome browser and has so far been visited by tens of thousands of users from more than 120 countries, with more than hundreds of thousands of page hits. The site has a number of chromosomal structure-related data types, including Hi-C, GAM, SPRITE, DNase Hi-C, ChIA-PET PLAC, seq, HiChIP and Capital Hi-C. The data included dozens of tissue and cell line in humans and mice, with a total of more than 300 data. The site data loads quickly and opens a 10Mb heat map in less than 5 seconds.
the browser makes it easier and faster for researchers to visualize data from high-volume chromosomal structure capture technology (Hi-C). Its main functions are as follows:
use heat maps to visualize Hi-C data and Hi-C-type technologies such as GAM, SPRITE, and
DNase Hi-C;
compares chromosomal 3D configurations between different tissues or species;
converts Hi-C data into virtual 4C (virtual 4C) to make it easier to see interactions at specific points and other locations on chromosomes; and
visualizes Hi-C derivative technologies based on chromosomal immunosuppression binding or chromosomal region capture (e.g. ChIA-PET, PLAC-seq, HiChip, HiCh-C).
project, researchers proposed a new binary format (BUTLR) to hold Hi-C data, greatly reducing file size and speeding up queries. In addition, the Browser provides convenient chromosomal area scaling. Hi-C data can be queried by gene, chromosome location, and SNP number. More importantly, users can seamlessly interface their own UCSC or WashU track and Hi-C heatmaps, greatly expanding the type of data that can be displayed.
we'll use a few examples to illustrate how to use 3D Genome Browser for Hi-C data mining.First, open the Hi-C query page (Figure 1), where we can select the Hi-C method, species, reference genome, tissue or cell line, and data resolution. For example, we can query the Hi-C heat map of the SHH gene in the GM12878 cell line. From the Hi-C heat map (Figure 2), we can see that the gene is located in the same TAD as a known enhancer region upstream of it, and that the enhancer has a high interaction with the SHH promoter, thus confirming the promoter's regulatory role in SHH. We can also click on the bar chart at the top right of the page to see how the gene is expressed in more than 100 tissues in ENCODE.Hi-C could also reveal the SNP's potential target genes. We looked at rs12740374 using virtual 4C, which is associated with elevated LDL in the population. Virtual 4C shows that the SNP has a higher role to play with its downstream SORT1 promoters, a finding supported by DNA highly sensitive point chains (DHS linkage) and ChIA-PET data (Figure 3). Histoprotein data below also show that the SNP is located in a possible enhancement sub-region. This evidence suggests that SORT1 may be the target gene for rs12740374.In Figure 4, we use Capture Hi-C data to analyze the governance mechanism of PAX5. We first found interactions between the promoter of PAX5 in the original B cell and its upstream ZCCHC7 region. Using DNA enzyme hypersensitive bit (DHS) data and histogene modification data, we also found that the region that functions with the promoter is a possible enhancer. Similarly, on the Hi-C heat map, we also found strong interactions between the two regions. All this evidence suggests that this enhancer upstream of ZCCHC7 may be the key to regulating the expression of the PAX5 gene. Interestingly, previous studies have reported that the removal of the enhancer lowered PAX5 expression and led to leukemia. This example shows that we can use 3D Genome Browser and Capture Hi-C data to study fine-grained promoter-enhancer roles.We can also use the Hi-C comparison model to study the conservatism of chromatin configurations between different species. Figure 5 shows the Hi-C heat map of the BCL6 region in the human lymphocyte line (GM12878) and the mouse cell line (CH12). From the similarity of Hi-C heat map, it can be seen that the chromatin configuration in this area is more conservative in humans and mice.Many studies have found that Hi-C can be used to detect structural variations in chromosomes. Different types of structural variations, such as deletion, insertion, dislocation, and inverting, can cause corresponding changes in the Hi-C heat map. BCR-ABL gene fusion is a disease-caused variant of chronic granulocytic leukemia. This mutation is caused by hetero-variation of chromosome 9 and chromosome 22. We can detect this allogeneic variation with the Hi-C heat map (Figure 6). K562 is a cell line grown from patients with chronic granulocytic leukemia. Figure 6a shows the Hi-C heat map of chromosome 9 of chromosome 22 in K562. The intermediate diamond region shows that chromosome 9 of chromosome 22 has strong intersectings, and in normal cells, the interaction between the chromosomes is minimal and much smaller than the interaction within the chromosome. Therefore, we can infer that chromosome 9 of chromosome 22 has merged, resulting in increased interaction between different chromosomes. And in the fusion break point area, we can see that the BCR and ABL genes have merged. In contrast, in normal GM12878 lymphocyte line, we did not see an increase in interaction between similar different chromosomes (Figure 6b). By querying the function between chromosomes in 3D Genome Browser, the researchers were able to identify structural variations in the genome and the changes in gene regulation that could result.
3D Genome Browser also has a number of features that are not covered in this article, such as virtual 4C (virtual 4C) and difference analysis of different Hi-C data, which also helps to mine the biological significance behind Hi-C data. We welcome researchers interested in learning about the 3D genome to use and explore our 3D Genome Browser.





Here, we introduce the 3D Genome Browser, which allows users to conveniently explore both their own and over 300 publicly available chromatin interaction data of different types. We design a new binary data format for Hi-C data that reduces the file size by at least a magnitude and allows users to visualize chromatin interactions over millions of base pairs within seconds. Our browser provides multiple methods linking distal cis-regulatory elements with their potential target genes. Users can seamlessly integrate thousands of other omics data to gain a comprehensive view of both regulatory landscape and 3D genome structure.:(
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The current impact factor is 13.214* and the journal is ranked 4th among research journals in the Genetics and Heredity category by Thomson Reuters. Genome Biology is the highest ranked open access journal in the category.
2017 Journal Metrics
Citation Impact
13.2 - 2-year Impact Factor
16.5 - 5-year Impact Factor
3.1 - Source Normalized Impact Per Paper (SNIP)
12.7 - SCImago Journal (Rank SJR)
(Source: ScienceDaily)