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This article mainly introduces the use of iMETHYL database, the article is very detailed, has a certain reference value, interested friends must read it!

In the era of rapid development of NGS, there are a large number of studies on the relationship between SNP and disease through the method of GSWA, and some scholars use WGBS,RRBS, methylation chip and other ways to study the relationship between DNA methylation and disease. However, for SNP and DNA methylation, there are many independent databases to store and organize related information, but there is a lack of open databases that integrate multi-group data such as SNP and DNA methylation.

Three types of cells were extracted from nearly 100 volunteers and sequenced by WGS, WGBS and RNA_seq, and the final data were stored in iMETHYL database. IMETHYL integrated the data of SNP, DNA methylation and RNA expression profile, and analyzed the correlation between them.

The website is as follows:

Http://imethyl.iwate-megabank.org/index.html

On the STATISTICS page, two basic pieces of information are provided.

The distribution of three kinds of combinatorial data

You can see the basic information about the sex and age of the volunteers, as well as summary information about DNA methylation, gene expression and SNV.

In the above table, it is worth noting that the number of autosomal CpG is about 23m, while the methylation chip is 450K or 850K, which shows the advantage of WGBS over methylation chip.

Distribution of CpG loci on each chromosome

Only the distribution on autosomal chromosomes is given here, and we can see that the number of CpG loci on chromosome 1 is the most.

On the HOME page, three retrieval methods are provided

Gene Symbol

DbSNP rsID

Chr Position

The results of the search are displayed through the genome browser:

Take a look at how DNA methylation, transcriptome data, and SNV data are displayed in the genome browser.

IMM:3 cell-types is used to show the methylation, gene expression and SNV results of each cell line.

The RNA_seq data, displayed through FPKM, will show the transcripts detected by each cell in the genome browser.

The results of SNV are displayed with dots. Each | represents a SNV site.

After hovering over the mouse, you can see the corresponding rs number and base mutation.

The display of methylation sites is similar to that of SNV.

For the three groups of data, imethy also uses QTL to analyze the relationship between the two groups.

The association analysis between genotype and gene expression profile is realized by cis-eQTL, the association analysis between DNA methylation and gene expression profile is realized by cis-eQTM, and the association analysis between DNA methylation and genotype is realized by cis-mQTL.

Both eQTL and mQTL are listed in the SNP sites associated with the gene, and eQTM lists the methylation sites associated with the gene.

IMETHYL database represents a trend, the trend of multi-group data integration and analysis. With the reduction of sequencing cost and the maturity of analysis technology, a large number of single-group data emerge, but for such a complex event of life activities, the influencing factors must be in many aspects. The integrated analysis of multi-group data allows us to conduct multi-faceted, more comprehensive and more in-depth research and exploration, which is bound to be a trend.

This database also gives us an example. DNA methylation can be analyzed jointly with transcriptome and genomic SNV data. The specific methods of analysis can be used for reference and reference to this database, which makes our research results more abundant.

The above is all the contents of the article "what is the use of iMETHYL database". Thank you for reading! Hope to share the content to help you, more related knowledge, welcome to follow the industry information channel!

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