Unraveling the influences of sequence and position on yeast uORF activity using massively parallel reporter systems and machine learning.
Unraveling the influences of sequence and position on yeast uORF activity using massively parallel reporter systems and machine learning.
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DOI：
10.7554/elife.69611
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发表时间：
2023-05-25
期刊：
影响因子：
7.7
通讯作者：
McManus J
中科院分区：
文献类型：
--
作者：
May GE;Akirtava C;Agar-Johnson M;Micic J;Woolford J;McManus J
上游开放阅读框架(UORF)是mRNA翻译和无义介导的衰变(NMD)的有效顺式调节因子。虽然8月和非8月启动的uORF在核糖体图谱研究中普遍存在，但很少有uORF被实验测试。因此，序列、结构和位置特征对uORF活性的相对影响尚未确定。我们在野生型和∆酵母中使用大规模平行报告分析量化了数以千计的酵母uORFs。虽然几乎所有的AUG uORF都是强大的抑制因子，但大多数非AUG uORF对表达的影响相对较弱。机器学习回归模型显示，uORF序列和转录本前导中的位置都可以预测它们对基因表达的影响。事实上，选择性转录起始点对uORF活性有很大影响。这些结果定义了自然uORF活性的范围，识别了与翻译抑制和NMD相关的特征，并表明uORF在转录本前导中的位置几乎与uORF序列一样具有预测性。
Upstream open-reading frames (uORFs) are potent cis-acting regulators of mRNA translation and nonsense-mediated decay (NMD). While both AUG- and non-AUG initiated uORFs are ubiquitous in ribosome profiling studies, few uORFs have been experimentally tested. Consequently, the relative influences of sequence, structural, and positional features on uORF activity have not been determined. We quantified thousands of yeast uORFs using massively parallel reporter assays in wildtype and ∆upf1 yeast. While nearly all AUG uORFs were robust repressors, most non-AUG uORFs had relatively weak impacts on expression. Machine learning regression modeling revealed that both uORF sequences and locations within transcript leaders predict their effect on gene expression. Indeed, alternative transcription start sites highly influenced uORF activity. These results define the scope of natural uORF activity, identify features associated with translational repression and NMD, and suggest that the locations of uORFs in transcript leaders are nearly as predictive as uORF sequences.
p53 mRNA的5'-末端区域的变体影响核糖体扫描和翻译效率。
影响因子：
4.6
作者：
Zydowicz-Machtel P;Swiatkowska A;Popenda Ł;Gorska A;Ciesiołka J
通讯作者：
Ciesiołka J