The ribosome profiling landscape of yeast reveals a high diversity in pervasive translation

IF 10.1 1区 生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Chris Papadopoulos, Hugo Arbes, David Cornu, Nicolas Chevrollier, Sandra Blanchet, Paul Roginski, Camille Rabier, Safiya Atia, Olivier Lespinet, Olivier Namy, Anne Lopes
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引用次数: 0

Abstract

Pervasive translation is a widespread phenomenon that plays a critical role in the emergence of novel microproteins, but the diversity of translation patterns contributing to their generation remains unclear. Based on 54 ribosome profiling (Ribo-Seq) datasets, we investigated the yeast Ribo-Seq landscape using a representation framework that allows the comprehensive inventory and classification of the entire diversity of Ribo-Seq signals, including non-canonical ones. We show that if coding regions occupy specific areas of the Ribo-Seq landscape, noncoding regions encompass a wide diversity of Ribo-Seq signals and, conversely, populate the entire landscape. Our results show that pervasive translation can, nevertheless, be associated with high specificity, with 1055 noncoding ORFs exhibiting canonical Ribo-Seq signals. Using mass spectrometry under standard conditions or proteasome inhibition with an in-house analysis protocol, we report 239 microproteins originating from noncoding ORFs that display canonical but also non-canonical Ribo-Seq signals. Each condition yields dozens of additional microprotein candidates with comparable translation properties, suggesting a larger population of volatile microproteins that are challenging to detect. Our findings suggest that non-canonical translation signals may harbor valuable information and underscore the significance of considering them in proteogenomic studies. Finally, we show that the translation outcome of a noncoding ORF is primarily determined by the initiating codon and the codon distribution in its two alternative frames, rather than features indicative of functionality. Our results enable us to propose a topology of a species’ Ribo-Seq landscape, opening the way to comparative analyses of this translation landscape under different conditions.
酵母核糖体图谱揭示了普遍翻译的高度多样性
普遍翻译是一种普遍现象,在新型微蛋白的出现中起着关键作用,但导致其产生的翻译模式的多样性仍不清楚。基于 54 个核糖体图谱(Ribo-Seq)数据集,我们利用一个表征框架研究了酵母 Ribo-Seq 全景,该框架允许对 Ribo-Seq 信号的整个多样性(包括非经典信号)进行全面清查和分类。我们发现,如果说编码区占据了 Ribo-Seq 图谱的特定区域,那么非编码区则涵盖了 Ribo-Seq 信号的广泛多样性,反之,非编码区则占据了整个图谱。我们的研究结果表明,无处不在的翻译可能与高度特异性有关,有 1055 个非编码 ORF 显示出典型的 Ribo-Seq 信号。利用标准条件下的质谱分析或蛋白酶体抑制与内部分析方案,我们报告了 239 个源自非编码 ORF 的微蛋白,它们显示了规范但也有非规范的 Ribo-Seq 信号。每种情况下都会产生数十种具有相似翻译特性的候选微蛋白,这表明有更多的挥发性微蛋白难以检测。我们的研究结果表明,非规范翻译信号可能蕴藏着有价值的信息,并强调了在蛋白质基因组研究中考虑这些信号的重要性。最后,我们发现非编码 ORF 的翻译结果主要取决于起始密码子及其两个替代框架中的密码子分布,而不是功能性特征。我们的研究结果使我们能够提出一个物种的 Ribo-Seq 图谱拓扑,为在不同条件下对这种翻译图谱进行比较分析开辟了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Genome Biology
Genome Biology Biochemistry, Genetics and Molecular Biology-Genetics
CiteScore
21.00
自引率
3.30%
发文量
241
审稿时长
2 months
期刊介绍: Genome Biology stands as a premier platform for exceptional research across all domains of biology and biomedicine, explored through a genomic and post-genomic lens. With an impressive impact factor of 12.3 (2022),* the journal secures its position as the 3rd-ranked research journal in the Genetics and Heredity category and the 2nd-ranked research journal in the Biotechnology and Applied Microbiology category by Thomson Reuters. Notably, Genome Biology holds the distinction of being the highest-ranked open-access journal in this category. Our dedicated team of highly trained in-house Editors collaborates closely with our esteemed Editorial Board of international experts, ensuring the journal remains on the forefront of scientific advances and community standards. Regular engagement with researchers at conferences and institute visits underscores our commitment to staying abreast of the latest developments in the field.
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