Welcome to KERO.
To support transcriptional regulation studies, we have constructed the KERO, which represents exact positions of transcriptional start sites (TSSs) in the genome based on our unique experimentally validated TSS sequencing method, TSS-seq.
This database includes TSS data of a major part of human adult and embryonic tissues are covered. KERO now contains 491 million TSS tag sequences for collected from a total of 20 tissues and 7 cell cultures. We also integrated our newly generated RNA-seq data of subcellular- fractionated RNAs and ChIP-seq data of histone modifications, RNA polymerase II and several transcriptional regulatory factors in cultured cell lines. We also included recently accumulating external epigenomic data, such as chromatin map of the ENCODE project.
In this update, we further associated those TSS information with public and original SNV data, in order to identify single nucleotide variations (SNVs) in the regulatory regions.
It is believed that single nucleotide variations (SNVs) in the transcriptional regulatory regions are responsible for many human diseases, including cancers. However, it remains difficult to identify functionally relevant SNVs from those having no explicit biological consequences. In this version of KERO, we attempt to associate SNVs with the omics information of the surrounding regions. We used SNVs which we identified from genomic analyses of various types of cancers, including somatic mutations of 100 lung adenocarcinoma and lung small cell carcinoma. For germline variations, we used SNVs in dbSNP as well as our unique dataset of variations in 1000 Japanese individuals. We integrated those SNV information with our original datasets of TSS-seq, RNA-seq, ChIP-seq of representative histone modifications and Bisulfite Sequencing of cytosine methylations of DNA. Particular, we present multi-omics data of 26 lung adenocarcinoma cells line for which TSS-seq, RNA-seq, ChIP-seq and BS-seq together with whole genome sequencing are collected from the same materials. We further connected the multi-omics data of model organisms by genome-genome alignment. We provide a unique data resource to investigate what genomic features are observed in a particular genomic coordinates in a wide variety of samples.
These data can be browsed in our new viewer which also supports versatile search conditions of users. We believe new KERO is helpful to understand biological consequences of the massively identified TSSs and identify human genetic valuations which are associated with disordered transcriptional regulations.