Yasuyuki Ohkawa | Search bioRxiv

bioRxiv2014

SraTailor: GUI software for visualizing high-throughput sequence read archives

Raw high-throughput sequence data are deposited in public databases as SRAs (Sequence Read Archives) and are publically available to every researcher. However, in order to graphically visualize the sequence data of interest, the corresponding SRAs must be downloaded and converted into BigWig format through complicated command-line processing. This task requires users to possess skill with script languages and sequence data processing, a requirement that prevents a wide range of biologists from exploiting SRAs. To address these challenges, we developed SraTailor, a GUI (Graphical User Interface) software package that automatically converts an SRA into a BigWig-formatted file. Simplicity of use is one of the most notable features of SraTailor: entering an accession number of an SRA and clicking the mouse are the only steps required in order to obtain BigWig-formatted files and to graphically visualize the extents of reads at given loci. SraTailor is also able to make peak calls and files of other formats, and the software also accepts various command-line-like options. Therefore, this software makes SRAs fully exploitable by a wide range of biologists. SraTailor is freely available at http://www.dev.med.kyushu-u.ac.jp/sra_tailor/.

Bioinformatics↗

bioRxiv2014

Identification of five patterns of nucleosome positioning that globally describe transcription factor function

Following the binding of transcription factors (TF) to specific regions, chromatin remodeling including alterations in nucleosome positioning (NP) occurs. These changes in NP cause selective gene expression to determine cell function. However whether specific NP patterns upon TF binding determine the transcriptional regulation such as gene activation or suppression is unclear. Here we identified five patterns of NP around TF binding sites (TFBSs) using fixed MNase-Seq analysis. The most frequently observed NP pattern described the transcription state. The five patterns explained approximately 80% of the whole NP pattern on the genome in mouse C2C12 cells. We further performed ChIP-Seq using the input obtained from the fixed MNase-Seq. The result showed that a single trial of ChIP-Seq could visualize the NP patterns around the TFBS and predict the function of the transcriptional regulation at the same time. These findings indicate that NP can directly predict the function of TFs.

Molecular Biology↗