Genomics Proteomics & BioinformaticsBioinformaticsPeer-reviewed journal article
DeOri 10.0: An Updated Database of Experimentally Identified Eukaryotic Replication Origins
Abstract
DNA replication is a complex and crucial biological process in eukaryotes. To facilitate the study of eukaryotic replication events, we present database of eukaryotic DNA replication origins (DeOri), a database that collects scattered data and integrates extensive sequencing data on eukaryotic DNA replication origins. With continuous updates of DeOri, the number of datasets in the new release increased from 10 to 151 and the number of sequences increased from 16,145 to 9,742,396. Besides nucleotide sequences and bed files, corresponding annotation files, such as coding sequences (CDS), mRNA, and other biological elements within replication origins, are also provided. The experimental techniques used for each dataset, as well as other statistical data, are also presented on web page. Differences in experimental methods, cell lines, and sequencing technologies have resulted in distinct replication origins, making it challenging to differentiate between cell-specific and non-specific replication. We combined multiple replication origins at the species level, scored them, and screened them. The screened regions were considered as species-conservative origins. They are integrated and presented as reference replication origins (rORIs), including Homo sapiens, Gallus gallus, Mus musculus, Drosophila melanogaster, and Caenorhabditis elegans. Additionally, we analyzed the distribution of relevant genomic elements associated with replication origins at the genome level, such as CpG island (CGI), transcription start site (TSS), and G-quadruplex (G4). These analysis results allow users to select the required data based on it. DeOri is available at http://tubic.tju.edu.cn/deori10/.
- organism: human
- organism: mouse
- organism: zebrafish
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: database / resource
- research focus: gene regulatory network inference
- research focus: variant calling
- approach: statistical model
- Citations
- 3
- FWCI
- 0.41
- Field percentile
- top 46%
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