The Interplay Between Translational Efficiency, Poly(A) Tails, MicroRNAs, and Neuronal Activation
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https://www.ncbi.nlm.nih.gov/sra/SRP356162
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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 38â45% 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. Overall design: The experiments consist of 12 matched samples of ribosome profiling libraries (small RNA-seq and RPF reads, 24 files in total) from primary neuronal cortical culture or mouse tissues. These samples have matched PAL-seq V2 or TAIL-seq data. In addition, there are eight samples (light stimulated mouse visual cortex samples) that have PAL-seq V2 data but no matched ribosome profiling data.
创建时间:
2022-03-17



