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tRFtarget:一个转移 RNA 衍生片段靶标的数据库。

tRFtarget: a database for transfer RNA-derived fragment targets.

机构信息

SJTU-Yale Joint Center for Biostatistics and Data Science, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.

Department of Biostatistics, Yale School of Public Health, New Haven, CT 06520, USA.

出版信息

Nucleic Acids Res. 2021 Jan 8;49(D1):D254-D260. doi: 10.1093/nar/gkaa831.

Abstract

Transfer RNA-derived fragments (tRFs) are a new class of small non-coding RNAs and play important roles in biological and physiological processes. Prediction of tRF target genes and binding sites is crucial in understanding the biological functions of tRFs in the molecular mechanisms of human diseases. We developed a publicly accessible web-based database, tRFtarget (http://trftarget.net), for tRF target prediction. It contains the computationally predicted interactions between tRFs and mRNA transcripts using the two state-of-the-art prediction tools RNAhybrid and IntaRNA, including location of the binding sites on the target, the binding region, and free energy of the binding stability with graphic illustration. tRFtarget covers 936 tRFs and 135 thousand predicted targets in eight species. It allows researchers to search either target genes by tRF IDs or tRFs by gene symbols/transcript names. We also integrated the manually curated experimental evidence of the predicted interactions into the database. Furthermore, we provided a convenient link to the DAVID® web server to perform downstream functional pathway analysis and gene ontology annotation on the predicted target genes. This database provides useful information for the scientific community to experimentally validate tRF target genes and facilitate the investigation of the molecular functions and mechanisms of tRFs.

摘要

转移 RNA 衍生片段 (tRFs) 是一类新的小非编码 RNA,在生物和生理过程中发挥重要作用。tRF 靶基因和结合位点的预测对于理解 tRF 在人类疾病的分子机制中的生物学功能至关重要。我们开发了一个可公开访问的基于网络的数据库 tRFtarget(http://trftarget.net),用于 tRF 靶标预测。它使用两种最先进的预测工具 RNAhybrid 和 IntaRNA,包含计算预测的 tRF 与 mRNA 转录物之间的相互作用,包括结合位点在靶标上的位置、结合区域和结合稳定性的自由能,并以图形说明。tRFtarget 涵盖了 8 个物种中的 936 个 tRF 和 13.5 万个预测靶标。它允许研究人员通过 tRF ID 搜索靶基因,或通过基因符号/转录本名称搜索 tRF。我们还将预测相互作用的经过人工整理的实验证据整合到数据库中。此外,我们提供了一个方便的链接到 DAVID®网络服务器,以便对预测靶基因进行下游功能途径分析和基因本体注释。该数据库为科学界提供了有用的信息,以实验验证 tRF 靶基因,并促进对 tRF 分子功能和机制的研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7ee/7779015/e42b184b44f5/gkaa831fig1.jpg

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