BackgroundBisulfite sequencing (BS-seq) has become a standard technology to profile genome-wide DNA methylation at single-base resolution. It allows researchers to conduct genome-wise cytosine methylation analyses on issues about genomic imprinting, transcriptional regulation, cellular development and differentiation. One single data from a BS-Seq experiment is resolved into many features according to the sequence contexts, making methylome data analysis and data visualization a complex task.ResultsWe developed a streamlined platform, TEA, for analyzing and visualizing data from whole-genome BS-Seq (WGBS) experiments conducted in the model plant Arabidopsis thaliana. To capture the essence of the genome methylation level and to meet the efficiency for running online, we introduce a straightforward method for measuring genome methylation in each sequence context by gene. The method is scripted in Java to process BS-Seq mapping results. Through a simple data uploading process, the TEA server deploys a web-based platform for deep analysis by linking data to an updated Arabidopsis annotation database and toolkits.ConclusionsTEA is an intuitive and efficient online platform for analyzing the Arabidopsis genomic DNA methylation landscape. It provides several ways to help users exploit WGBS data.TEA is freely accessible for academic users at: http://tea.iis.sinica.edu.tw.

Formerly, dimensionality reduction techniques are effective ways for extracting statistical significance of features from their original dimensions. However, the dimensionality reduction also induces an additional complexity burden which may encumber the real efficiency. In this paper, a technique is proposed for the reduction of the dimension of samples rather than the features in the former schemes, and it is able to additionally reduce the computational complexity of the applied systems during the reduction process. This method effectively reduces the redundancies of a sample, in particular for those objects which possess partially symmetric property, such as human face, pedestrian, and license plate. As demonstrated in the experiments, based upon the premises of faster speeds in training and detection by a factor of 4.06 and 1.24, respectively, similar accuracies to the ones without considering the proposed method are achieved. The performance verifies that the proposed technique can offer competitive practical values in pattern recognition related fields.

Background: DNA methylation is a crucial epigenomic mechanism in various biological processes. Using wholegenome bisulfite sequencing (WGBS) technology, methylated cytosine sites can be revealed at the single nucleotide level. However, the WGBS data analysis process is usually complicated and challenging. Results: To alleviate the associated difficulties, we integrated the WGBS data processing steps and downstream analysis into a two-phase approach. First, we set up the required tools in Galaxy and developed workflows to calculate the methylation level from raw WGBS data and generate a methylation status summary, the mtable. This computation environment is wrapped into the Docker container image DocMethyl, which allows users to rapidly deploy an executable environment without tedious software installation and library dependency problems. Next, the mtable files were uploaded to the web server EpiMOLAS_web to link with the gene annotation databases that enable rapid data retrieval and analyses. Conclusion: To our knowledge, the EpiMOLAS framework, consisting of DocMethyl and EpiMOLAS_web, is the first approach to include containerization technology and a web-based system for WGBS data analysis from raw data processing to downstream analysis. EpiMOLAS will help users cope with their WGBS data and also conduct reproducible analyses of publicly available data, thereby gaining insights into the mechanisms underlying complex biological phenomenon.

e14199 Background: Prior study stratified Taiwanese oral cancer specimens (n = 40) and cell lines (n = 7) into three distinct molecular subtypes, namely classical (CL), mesenchymal (MS), and basal (BA). In a cell line derived xenograft (CDX) model, we observed MS grew at least 10-fold slower than CL did in immunodeficient mice. By using RNA-seq to portrait the transcriptomes of human tumor and mouse stroma simultaneously, contribution of mouse innate immunity in restricting the growth of human oral cancer cells was assessed. Methods: A half millions of mycoplasma-free OC3 (MS) or TW2.6 (CL) cells with matrigel were subcutaneously implanted into the flank of 10 to 16 weeks old NOG (NOD/SCID/Il2rgtm). RNAs of CDX tissues from OC3-NOG (n = 7) and TW2.6-NOG (n = 5) were extracted and subjected to stranded mRNA sequencing. Clean reads were aligned to GRCh38 (human) and GRCm38 (mouse), respectively, followed by identifying differentially expressed genes and gene set enrichment analysis. Results: Up-regulation of signature genes for dendritic cells and macrophages and enrichment of innate immunity, including Tnfa-Nfkb signaling, interferon alpha response, interferon gamma response and inflammation were detected in OC3- but not in TW2.6-CDXs. These results suggested that OC3 (MS) was more immunogenic than TW2.6 (CL), which is reminiscent of the inflammatory MS (IMS) subtype of head and neck cancer recently described by Keck et al (n = 938, Clin Cancer Res 2015, 21: p870. PMID: 25492084). Conclusions: By RNA-seq/xenome analysis of CDXs, we provide evidence that compared to CL, MS subtype of oral cancer cells elicited a stronger innate immunity in NOG mouse. Alternatively, CL subtype might have evolved as a prototype with superiority in immune escape.