Full-length ribosome density prediction by a multi-input and multi-output model.
Translation elongation is regulated by a series of complicated mechanisms in both prokaryotes and eukaryotes. Although recent advance in ribosome profiling techniques has enabled one to capture the genome-wide ribosome footprints along transcripts at codon resolution, the regulatory codes of elongat...
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| Language: | English |
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Public Library of Science (PLoS)
2021-03-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008842&type=printable |
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| author | Tingzhong Tian Shuya Li Peng Lang Dan Zhao Jianyang Zeng |
| author_facet | Tingzhong Tian Shuya Li Peng Lang Dan Zhao Jianyang Zeng |
| author_sort | Tingzhong Tian |
| collection | DOAJ |
| description | Translation elongation is regulated by a series of complicated mechanisms in both prokaryotes and eukaryotes. Although recent advance in ribosome profiling techniques has enabled one to capture the genome-wide ribosome footprints along transcripts at codon resolution, the regulatory codes of elongation dynamics are still not fully understood. Most of the existing computational approaches for modeling translation elongation from ribosome profiling data mainly focus on local contextual patterns, while ignoring the continuity of the elongation process and relations between ribosome densities of remote codons. Modeling the translation elongation process in full-length coding sequence (CDS) level has not been studied to the best of our knowledge. In this paper, we developed a deep learning based approach with a multi-input and multi-output framework, named RiboMIMO, for modeling the ribosome density distributions of full-length mRNA CDS regions. Through considering the underlying correlations in translation efficiency among neighboring and remote codons and extracting hidden features from the input full-length coding sequence, RiboMIMO can greatly outperform the state-of-the-art baseline approaches and accurately predict the ribosome density distributions along the whole mRNA CDS regions. In addition, RiboMIMO explores the contributions of individual input codons to the predictions of output ribosome densities, which thus can help reveal important biological factors influencing the translation elongation process. The analyses, based on our interpretable metric named codon impact score, not only identified several patterns consistent with the previously-published literatures, but also for the first time (to the best of our knowledge) revealed that the codons located at a long distance from the ribosomal A site may also have an association on the translation elongation rate. This finding of long-range impact on translation elongation velocity may shed new light on the regulatory mechanisms of protein synthesis. Overall, these results indicated that RiboMIMO can provide a useful tool for studying the regulation of translation elongation in the range of full-length CDS. |
| format | Article |
| id | doaj-art-99c0101d8448448d9b9aa3d81c36629a |
| institution | OA Journals |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2021-03-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-99c0101d8448448d9b9aa3d81c36629a2025-08-20T02:18:04ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-03-01173e100884210.1371/journal.pcbi.1008842Full-length ribosome density prediction by a multi-input and multi-output model.Tingzhong TianShuya LiPeng LangDan ZhaoJianyang ZengTranslation elongation is regulated by a series of complicated mechanisms in both prokaryotes and eukaryotes. Although recent advance in ribosome profiling techniques has enabled one to capture the genome-wide ribosome footprints along transcripts at codon resolution, the regulatory codes of elongation dynamics are still not fully understood. Most of the existing computational approaches for modeling translation elongation from ribosome profiling data mainly focus on local contextual patterns, while ignoring the continuity of the elongation process and relations between ribosome densities of remote codons. Modeling the translation elongation process in full-length coding sequence (CDS) level has not been studied to the best of our knowledge. In this paper, we developed a deep learning based approach with a multi-input and multi-output framework, named RiboMIMO, for modeling the ribosome density distributions of full-length mRNA CDS regions. Through considering the underlying correlations in translation efficiency among neighboring and remote codons and extracting hidden features from the input full-length coding sequence, RiboMIMO can greatly outperform the state-of-the-art baseline approaches and accurately predict the ribosome density distributions along the whole mRNA CDS regions. In addition, RiboMIMO explores the contributions of individual input codons to the predictions of output ribosome densities, which thus can help reveal important biological factors influencing the translation elongation process. The analyses, based on our interpretable metric named codon impact score, not only identified several patterns consistent with the previously-published literatures, but also for the first time (to the best of our knowledge) revealed that the codons located at a long distance from the ribosomal A site may also have an association on the translation elongation rate. This finding of long-range impact on translation elongation velocity may shed new light on the regulatory mechanisms of protein synthesis. Overall, these results indicated that RiboMIMO can provide a useful tool for studying the regulation of translation elongation in the range of full-length CDS.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008842&type=printable |
| spellingShingle | Tingzhong Tian Shuya Li Peng Lang Dan Zhao Jianyang Zeng Full-length ribosome density prediction by a multi-input and multi-output model. PLoS Computational Biology |
| title | Full-length ribosome density prediction by a multi-input and multi-output model. |
| title_full | Full-length ribosome density prediction by a multi-input and multi-output model. |
| title_fullStr | Full-length ribosome density prediction by a multi-input and multi-output model. |
| title_full_unstemmed | Full-length ribosome density prediction by a multi-input and multi-output model. |
| title_short | Full-length ribosome density prediction by a multi-input and multi-output model. |
| title_sort | full length ribosome density prediction by a multi input and multi output model |
| url | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008842&type=printable |
| work_keys_str_mv | AT tingzhongtian fulllengthribosomedensitypredictionbyamultiinputandmultioutputmodel AT shuyali fulllengthribosomedensitypredictionbyamultiinputandmultioutputmodel AT penglang fulllengthribosomedensitypredictionbyamultiinputandmultioutputmodel AT danzhao fulllengthribosomedensitypredictionbyamultiinputandmultioutputmodel AT jianyangzeng fulllengthribosomedensitypredictionbyamultiinputandmultioutputmodel |