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基于 TCP-seq 数据对酿酒酵母核糖体小亚基动态的建模。

Modeling the ribosomal small subunit dynamic in Saccharomyces cerevisiae based on TCP-seq data.

机构信息

Department of Biomedical Engineering, Tel Aviv University, Tel Aviv 6997801, Israel.

The Sagol School of Neuroscience, Tel-Aviv University, Tel Aviv 6997801, Israel.

出版信息

Nucleic Acids Res. 2022 Feb 22;50(3):1297-1316. doi: 10.1093/nar/gkac021.

Abstract

Translation Complex Profile Sequencing (TCP-seq), a protocol that was developed and implemented on Saccharomyces cerevisiae, provides the footprints of the small subunit (SSU) of the ribosome (with additional factors) across the entire transcriptome of the analyzed organism. In this study, based on the TCP-seq data, we developed for the first-time a predictive model of the SSU density and analyzed the effect of transcript features on the dynamics of the SSU scan in the 5'UTR. Among others, our model is based on novel tools for detecting complex statistical relations tailored to TCP-seq. We quantitatively estimated the effect of several important features, including the context of the upstream AUG, the upstream ORF length and the mRNA folding strength. Specifically, we suggest that around 50% of the variance related to the read counts (RC) distribution near a start codon can be attributed to the AUG context score. We provide the first large scale direct quantitative evidence that shows that indeed AUG context affects the small sub-unit movement. In addition, we suggest that strong folding may cause the detachment of the SSU from the mRNA. We also identified a number of novel sequence motifs that can affect the SSU scan; some of these motifs affect transcription factors and RNA binding proteins. The results presented in this study provide a better understanding of the biophysical aspects related to the SSU scan along the 5'UTR and of translation initiation in S. cerevisiae, a fundamental step toward a comprehensive modeling of initiation.

摘要

翻译复合物谱测序(TCP-seq)是一种在酿酒酵母上开发和实施的方法,它提供了核糖体小亚基(SSU)在被分析生物的整个转录组上的足迹(带有额外的因素)。在这项研究中,我们首次基于 TCP-seq 数据开发了 SSU 密度的预测模型,并分析了转录物特征对 5'UTR 中 SSU 扫描动力学的影响。除其他外,我们的模型基于针对 TCP-seq 定制的检测复杂统计关系的新工具。我们定量估计了几个重要特征的影响,包括上游 AUG 的上下文、上游 ORF 长度和 mRNA 折叠强度。具体来说,我们认为大约 50%的与起始密码子附近的读取计数 (RC) 分布相关的方差可以归因于 AUG 上下文评分。我们提供了第一个大规模的直接定量证据,表明 AUG 上下文确实会影响小亚基的运动。此外,我们认为强烈的折叠可能导致 SSU 与 mRNA 分离。我们还鉴定了一些可能影响 SSU 扫描的新序列基序;其中一些基序影响转录因子和 RNA 结合蛋白。本研究的结果提供了对与 5'UTR 中 SSU 扫描和酿酒酵母中翻译起始相关的生物物理方面的更好理解,这是对起始进行全面建模的重要一步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdf0/8860609/d6362dad7b1a/gkac021fig1.jpg

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