| TetraRNA, a tetra-class machine learning model for deciphering the coding potential derivation of RNA world | |
Bai, Hanrui1; Wang, Jie2; Jiang, Xiaoke1; Guo, Zhen3; Yang, Wenjing1; Yang, Zitian1; Li, Jing1 ; Liu, Changning1
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| 2025 | |
| Source Publication | COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
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| ISSN | 2001-0370 |
| Volume | 27Issue:xPages:1305-1317 |
| Abstract | CncRNAs (coding and noncoding RNAs) are a class of bifunctional RNAs that that has both coding and noncoding biological activity. An increasing number of cncRNAs are being identified, prompting reassessment of our knowledge of RNA. However, most existing RNA classification tools are based on binary classification models which are not effective in distinguishing cncRNAs from mRNAs or long noncoding RNAs (lncRNAs). Our statistical analysis demonstrated that mRNA-derived cncRNAs (untranslated mRNAs, untr-mRNAs) and lncRNAderived cncRNAs (translated ncRNAs, tr-ncRNAs) do not fall in the same cluster. Therefore, in this study, we devised a novel tetra-class RNA classification model that is systematically optimized for RNA feature extraction. According to our model, all human RNAs can be reclassified into one of four categories - mRNA, untr-mRNA, lncRNA, and tr-ncRNA - representing a novel RNA classification system and allowing the discovery of more potential cncRNAs. Further analysis revealed significant differences among the four types of RNAs in tissuespecific expression, functional annotation, sequence composition, and other factors, providing insights into their divergent evolution trajectories. Moreover, investigation of the small tr-ncRNA peptides demonstrated that their evolution is coordinated with that of the the conserved functional small RNAs associated with them. All analysis results have been integrated into a database - TetraRNADB accessible online (http://tetrarnadb.liu-lab. com/). |
| Keyword | Translated ncRNA Untranslated mRNA CncRNA Tetra-class classification model TetraRNADB database |
| Subject Area | Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology |
| DOI | 10.1016/j.csbj.2025.03.039 |
| Indexed By | SCI |
| Language | 英语 |
| WOS ID | WOS:001458289100001 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | https://ir.xtbg.ac.cn/handle/353005/14685 |
| Collection | 2012年后新成立研究组 |
| Affiliation | 1.Univ Sci & Technol China, Coll Life Sci, Div Life Sci & Med, Hefei 230026, Peoples R China 2.Chinese Acad Sci, CAS Key Lab Trop Plant Resources & Sustainable Use, Yunnan Key Lab Crop Wild Relat Omics, Xishuangbanna Trop Bot Garden, Kunming 650223, Peoples R China 3.Max Planck Inst Plant Breeding Res, Dept Chromosome Biol, Carl von Linne Weg 10, D-50829 Cologne, Germany 4.St Louis Univ, Coll Sci & Engn, St Louis, MO 63103 USA |
| Recommended Citation GB/T 7714 | Bai, Hanrui,Wang, Jie,Jiang, Xiaoke,et al. TetraRNA, a tetra-class machine learning model for deciphering the coding potential derivation of RNA world[J]. COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL,2025,27(x):1305-1317. |
| APA | Bai, Hanrui.,Wang, Jie.,Jiang, Xiaoke.,Guo, Zhen.,Yang, Wenjing.,...&Liu, Changning.(2025).TetraRNA, a tetra-class machine learning model for deciphering the coding potential derivation of RNA world.COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL,27(x),1305-1317. |
| MLA | Bai, Hanrui,et al."TetraRNA, a tetra-class machine learning model for deciphering the coding potential derivation of RNA world".COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL 27.x(2025):1305-1317. |
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| TetraRNA, a tetra-cl（7282KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Download | |
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