Institute for Computational and Data Sciences, Pennsylvania State University, University Park, USA.
Department of Chemistry, Pennsylvania State University, University Park, USA.
BMC Bioinformatics. 2021 Mar 25;22(1):156. doi: 10.1186/s12859-021-04068-w.
Translation is a fundamental process in gene expression. Ribosome profiling is a method that enables the study of transcriptome-wide translation. A fundamental, technical challenge in analyzing Ribo-Seq data is identifying the A-site location on ribosome-protected mRNA fragments. Identification of the A-site is essential as it is at this location on the ribosome where a codon is translated into an amino acid. Incorrect assignment of a read to the A-site can lead to lower signal-to-noise ratio and loss of correlations necessary to understand the molecular factors influencing translation. Therefore, an easy-to-use and accurate analysis tool is needed to accurately identify the A-site locations.
We present RiboA, a web application that identifies the most accurate A-site location on a ribosome-protected mRNA fragment and generates the A-site read density profiles. It uses an Integer Programming method that reflects the biological fact that the A-site of actively translating ribosomes is generally located between the second codon and stop codon of a transcript, and utilizes a wide range of mRNA fragment sizes in and around the coding sequence (CDS). The web application is containerized with Docker, and it can be easily ported across platforms.
The Integer Programming method that RiboA utilizes is the most accurate in identifying the A-site on Ribo-Seq mRNA fragments compared to other methods. RiboA makes it easier for the community to use this method via a user-friendly and portable web application. In addition, RiboA supports reproducible analyses by tracking all the input datasets and parameters, and it provides enhanced visualization to facilitate scientific exploration. RiboA is available as a web service at https://a-site.vmhost.psu.edu/ . The code is publicly available at https://github.com/obrien-lab/aip_web_docker under the MIT license.
翻译是基因表达的基本过程。核糖体谱是一种能够研究转录组范围翻译的方法。在分析核糖体测序 (Ribo-Seq) 数据时，一个基本的技术挑战是确定核糖体保护的 mRNA 片段上的 A 位位置。确定 A 位是至关重要的，因为在核糖体上，密码子就是在这里被翻译成氨基酸的。如果一个读取被错误地分配到 A 位，可能会导致信号噪声比降低，并丢失理解影响翻译的分子因素所必需的相关性。因此，需要一个易于使用且准确的分析工具来准确识别 A 位位置。
我们提出了 RiboA，这是一个 Web 应用程序，可识别核糖体保护的 mRNA 片段上最准确的 A 位位置，并生成 A 位读取密度分布。它使用整数规划方法，反映了这样一个生物学事实，即活跃翻译的核糖体的 A 位通常位于转录本的第二个密码子和终止密码子之间，并利用编码序列 (CDS) 内和周围的各种 mRNA 片段大小。该 Web 应用程序使用 Docker 进行容器化，可以轻松跨平台移植。
与其他方法相比，RiboA 中使用的整数规划方法在识别 Ribo-Seq mRNA 片段上的 A 位方面是最准确的。RiboA 通过用户友好且便携的 Web 应用程序，使社区更容易使用这种方法。此外，RiboA 通过跟踪所有输入数据集和参数，支持可重复分析，并提供增强的可视化功能，以方便科学探索。RiboA 作为 Web 服务可在 https://a-site.vmhost.psu.edu/ 上使用。代码在 MIT 许可证下可在 https://github.com/obrien-lab/aip_web_docker 上获得。
