一个巨大的进化瞬时易位体对表型和适应性做出了贡献。

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Cell Systems Pub Date : 2023-05-17 Epub Date: 2023-05-09 DOI:10.1016/j.cels.2023.04.002
Aaron Wacholder, Saurin Bipin Parikh, Nelson Castilho Coelho, Omer Acar, Carly Houghton, Lin Chou, Anne-Ruxandra Carvunis
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引用次数: 0

摘要

翻译是核糖体合成蛋白质的过程。核糖体剖面分析最近发现,许多以前被认为是非编码的短序列被普遍翻译。为了在这种非典型的翻译组中识别蛋白质编码基因,我们将一个用于高灵敏度核糖体图谱分析的综合框架 iRibo 与专为短序列定制的高能选择推断相结合。我们为酿酒酵母构建了一个参考翻译组,包括 5,400 个规范翻译元件和近 19,000 个非规范翻译元件。在可检测到的纯化选择下,只有 14 个非规范元素在进化。缺乏选择特征的代表性翻译元件子集显示,它们参与了 DNA 修复、应激反应和转录后调控等过程。我们的研究结果表明,大多数翻译元件并不是保守的蛋白质编码基因,而是通过快速进化的分子机制促成了基因型与表型之间的关系。
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A vast evolutionarily transient translatome contributes to phenotype and fitness.

Translation is the process by which ribosomes synthesize proteins. Ribosome profiling recently revealed that many short sequences previously thought to be noncoding are pervasively translated. To identify protein-coding genes in this noncanonical translatome, we combine an integrative framework for extremely sensitive ribosome profiling analysis, iRibo, with high-powered selection inferences tailored for short sequences. We construct a reference translatome for Saccharomyces cerevisiae comprising 5,400 canonical and almost 19,000 noncanonical translated elements. Only 14 noncanonical elements were evolving under detectable purifying selection. A representative subset of translated elements lacking signatures of selection demonstrated involvement in processes including DNA repair, stress response, and post-transcriptional regulation. Our results suggest that most translated elements are not conserved protein-coding genes and contribute to genotype-phenotype relationships through fast-evolving molecular mechanisms.

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来源期刊
Cell Systems
Cell Systems Medicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍: In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.
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