RNAirport : a deep neural network-based database characterizing representative gene models in plants
Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved..
A 5'-leader, known initially as the 5'-untranslated region, contains multiple isoforms due to alternative splicings (aS) and transcription start sites (aTSS). Therefore, a representative 5'-leader is demanded to examine the embedded RNA regulatory elements in controlling translation efficiency. Here, we develop a ranking algorithm and a deep-learning model to annotate representative 5'-leaders for five plant species. We rank the intra- and inter-sample frequency of aS-mediated transcript isoforms using the Kruskal-Wallis test-based algorithm and identify the representative aS-5'-leader. To further assign a representative 5'-end, we train the deep-learning model 5'leaderP to learn aTSS-mediated 5'-end distribution patterns from cap-analysis gene expression (CAGE) data. The model accurately predicts the 5'-end, confirmed experimentally in Arabidopsis and rice. The representative 5'-leader-contained gene models and 5'leaderP can be accessed at RNAirport (http://www.rnairport.com/leader5P/). This stage 1 5'-leader annotation records 5'-leader diversity and will pave the way to Ribo-Seq ORF annotation, identical to the project recently initiated by human GENCODE.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2024 |
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| Enthalten in: |
Journal of genetics and genomics = Yi chuan xue bao - (2024) vom: 20. März |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Zhu, Sitao [VerfasserIn] |
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| Links: |
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| Themen: |
5′-leader |
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| Anmerkungen: |
Date Revised 22.03.2024 published: Print-Electronic Citation Status Publisher |
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| doi: |
10.1016/j.jgg.2024.03.004 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM370085477 |
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| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status Publisher | ||
| 520 | |a Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved. | ||
| 520 | |a A 5'-leader, known initially as the 5'-untranslated region, contains multiple isoforms due to alternative splicings (aS) and transcription start sites (aTSS). Therefore, a representative 5'-leader is demanded to examine the embedded RNA regulatory elements in controlling translation efficiency. Here, we develop a ranking algorithm and a deep-learning model to annotate representative 5'-leaders for five plant species. We rank the intra- and inter-sample frequency of aS-mediated transcript isoforms using the Kruskal-Wallis test-based algorithm and identify the representative aS-5'-leader. To further assign a representative 5'-end, we train the deep-learning model 5'leaderP to learn aTSS-mediated 5'-end distribution patterns from cap-analysis gene expression (CAGE) data. The model accurately predicts the 5'-end, confirmed experimentally in Arabidopsis and rice. The representative 5'-leader-contained gene models and 5'leaderP can be accessed at RNAirport (http://www.rnairport.com/leader5P/). This stage 1 5'-leader annotation records 5'-leader diversity and will pave the way to Ribo-Seq ORF annotation, identical to the project recently initiated by human GENCODE | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a 5′-leader | |
| 650 | 4 | |a Deep learning | |
| 650 | 4 | |a RNA regulatory elements | |
| 650 | 4 | |a Synthetic biology | |
| 650 | 4 | |a Transcript isoforms | |
| 650 | 4 | |a Translational control | |
| 650 | 4 | |a uORF | |
| 700 | 1 | |a Yuan, Shu |e verfasserin |4 aut | |
| 700 | 1 | |a Niu, Ruixia |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Yulu |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Zhao |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Guoyong |e verfasserin |4 aut | |
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