The Interplay Between Translational Efficiency, Poly(A) Tails, MicroRNAs, and Neuronal Activation
<jats:p>Neurons provide a rich setting for studying post-transcriptional control. Here, we investigate the landscape of translational control in neurons and search for mRNA features that explain differences in translational efficiency (TE), considering the interplay between TE, mRNA poly(A)-ta...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Cold Spring Harbor Laboratory
2022
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| Online Access: | https://hdl.handle.net/1721.1/146765 |
| _version_ | 1826212133691457536 |
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| author | Eisen, Timothy J Li, Jingyi Jessica Bartel, David P |
| author2 | Massachusetts Institute of Technology. Department of Biology |
| author_facet | Massachusetts Institute of Technology. Department of Biology Eisen, Timothy J Li, Jingyi Jessica Bartel, David P |
| author_sort | Eisen, Timothy J |
| collection | MIT |
| description | <jats:p>Neurons provide a rich setting for studying post-transcriptional control. Here, we investigate the landscape of translational control in neurons and search for mRNA features that explain differences in translational efficiency (TE), considering the interplay between TE, mRNA poly(A)-tail lengths, microRNAs, and neuronal activation. In neurons and brain tissues, TE correlates with tail length, and a few dozen mRNAs appear to undergo cytoplasmic polyadenylation upon light or chemical stimulation. However, the correlation between TE and tail length is modest, explaining <5% of TE variance, and even this modest relationship diminishes when accounting for other mRNA features. Thus, tail length appears to affect TE only minimally. Accordingly, miRNAs, which accelerate deadenylation of their mRNA targets, primarily influence target mRNA levels, with no detectable effect on either steady-state tail lengths or TE. Larger correlates with TE include codon composition and predicted mRNA folding energy. When combined in a model, the identified correlates explain 38%–45% of TE variance. These results provide a framework for considering the relative impact of factors that contribute to translational control in neurons. They indicate that when examined in bulk, translational control in neurons largely resembles that of other types of post-embryonic cells. Thus, detection of more specialized control might require analyses that can distinguish translation occurring in neuronal processes from that occurring in cell bodies.</jats:p> |
| first_indexed | 2024-09-23T15:16:54Z |
| format | Article |
| id | mit-1721.1/146765 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:16:54Z |
| publishDate | 2022 |
| publisher | Cold Spring Harbor Laboratory |
| record_format | dspace |
| spelling | mit-1721.1/1467652022-12-07T03:07:16Z The Interplay Between Translational Efficiency, Poly(A) Tails, MicroRNAs, and Neuronal Activation Eisen, Timothy J Li, Jingyi Jessica Bartel, David P Massachusetts Institute of Technology. Department of Biology <jats:p>Neurons provide a rich setting for studying post-transcriptional control. Here, we investigate the landscape of translational control in neurons and search for mRNA features that explain differences in translational efficiency (TE), considering the interplay between TE, mRNA poly(A)-tail lengths, microRNAs, and neuronal activation. In neurons and brain tissues, TE correlates with tail length, and a few dozen mRNAs appear to undergo cytoplasmic polyadenylation upon light or chemical stimulation. However, the correlation between TE and tail length is modest, explaining <5% of TE variance, and even this modest relationship diminishes when accounting for other mRNA features. Thus, tail length appears to affect TE only minimally. Accordingly, miRNAs, which accelerate deadenylation of their mRNA targets, primarily influence target mRNA levels, with no detectable effect on either steady-state tail lengths or TE. Larger correlates with TE include codon composition and predicted mRNA folding energy. When combined in a model, the identified correlates explain 38%–45% of TE variance. These results provide a framework for considering the relative impact of factors that contribute to translational control in neurons. They indicate that when examined in bulk, translational control in neurons largely resembles that of other types of post-embryonic cells. Thus, detection of more specialized control might require analyses that can distinguish translation occurring in neuronal processes from that occurring in cell bodies.</jats:p> 2022-12-06T18:12:40Z 2022-12-06T18:12:40Z 2022 2022-12-06T17:15:00Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/146765 Eisen, Timothy J, Li, Jingyi Jessica and Bartel, David P. 2022. "The Interplay Between Translational Efficiency, Poly(A) Tails, MicroRNAs, and Neuronal Activation." RNA, 28 (6). en 10.1261/RNA.079046.121 RNA Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Cold Spring Harbor Laboratory Cold Spring Harbor Laboratory Press |
| spellingShingle | Eisen, Timothy J Li, Jingyi Jessica Bartel, David P The Interplay Between Translational Efficiency, Poly(A) Tails, MicroRNAs, and Neuronal Activation |
| title | The Interplay Between Translational Efficiency, Poly(A) Tails, MicroRNAs, and Neuronal Activation |
| title_full | The Interplay Between Translational Efficiency, Poly(A) Tails, MicroRNAs, and Neuronal Activation |
| title_fullStr | The Interplay Between Translational Efficiency, Poly(A) Tails, MicroRNAs, and Neuronal Activation |
| title_full_unstemmed | The Interplay Between Translational Efficiency, Poly(A) Tails, MicroRNAs, and Neuronal Activation |
| title_short | The Interplay Between Translational Efficiency, Poly(A) Tails, MicroRNAs, and Neuronal Activation |
| title_sort | interplay between translational efficiency poly a tails micrornas and neuronal activation |
| url | https://hdl.handle.net/1721.1/146765 |
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