Genome-wide identification and differential analysis of translational initiation.
Genome-wide identification and differential analysis of translational initiation.
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DOI：
10.1038/s41467-017-01981-8
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发表时间：
2017-11-23
影响因子：
16.6
通讯作者：
Chen Y
中科院分区：
文献类型：
--
作者：
Zhang P;He D;Xu Y;Hou J;Pan BF;Wang Y;Liu T;Davis CM;Ehli EA;Tan L;Zhou F;Hu J;Yu Y;Chen X;Nguyen TM;Rosen JM;Hawke DH;Ji Z;Chen Y
翻译主要是在初始阶段进行调节。翻译起始（TI）测序（TI-seq）技术的发展，使全球映射的TI，并揭示了意想不到的复杂的翻译景观后生动物。尽管TI-seq被广泛采用，但目前还没有可用于分析TI-seq数据的计算工具。为了填补这一空白，我们开发了一个名为Ribo-TISH的综合工具包，它允许从TI-seq数据中检测和定量比较各种条件下的TI。Ribo-TISH还可以从常规核糖体分析（rRibo-seq）数据预测新的开放阅读框架（ORF），并且在计算效率和预测准确性方面优于几种已建立的方法。应用于已发表的TI-seq/rRibo-seq数据集，Ribo-TISH揭示了氨基酸剥夺期间线粒体翻译升高的新特征，并预测了5′ UTR，长非编码RNA和内含子中的新ORF。这些成功的应用证明了Ribo-TISH在从TI-seq/rRibo-seq数据中提取生物学见解方面的能力。翻译起始测序（TI-seq）揭示了蛋白质亚型的意外多样性。在这里，Zhang等人提出了Ribo-TISH，这是一种计算工具包，可以检测和比较各种条件下的TI，并根据不同类型的核糖体分析数据改进开放阅读框架预测。
Translation is principally regulated at the initiation stage. The development of the translation initiation (TI) sequencing (TI-seq) technique has enabled the global mapping of TIs and revealed unanticipated complex translational landscapes in metazoans. Despite the wide adoption of TI-seq, there is no computational tool currently available for analyzing TI-seq data. To fill this gap, we develop a comprehensive toolkit named Ribo-TISH, which allows for detecting and quantitatively comparing TIs across conditions from TI-seq data. Ribo-TISH can also predict novel open reading frames (ORFs) from regular ribosome profiling (rRibo-seq) data and outperform several established methods in both computational efficiency and prediction accuracy. Applied to published TI-seq/rRibo-seq data sets, Ribo-TISH uncovers a novel signature of elevated mitochondrial translation during amino-acid deprivation and predicts novel ORFs in 5′UTRs, long noncoding RNAs, and introns. These successful applications demonstrate the power of Ribo-TISH in extracting biological insights from TI-seq/rRibo-seq data. Translation initiation sequencing (TI-seq) has revealed unexpected diversity in protein isoforms. Here, Zhang et al. present Ribo-TISH, a computational toolkit that can detect and compare TIs across conditions and improve open reading frame prediction from different types of ribosome profiling data.
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DOI：
10.1038/nrm4069
发表时间：
2015-11
期刊：
Nature reviews. Molecular cell biology
影响因子：
--
作者：
Brar GA;Weissman JS
通讯作者：
Weissman JS
DOI：
10.1261/rna.052548.115
发表时间：
2015-10
期刊：
RNA (New York, N.Y.)
影响因子：
--
作者：
Chung BY;Hardcastle TJ;Jones JD;Irigoyen N;Firth AE;Baulcombe DC;Brierley I
通讯作者：
Brierley I
影响因子：
46.9
作者：
通讯作者：
--
DOI：
10.1261/rna.049908.115
发表时间：
2015-04
期刊：
RNA (New York, N.Y.)
影响因子：
--
作者：
Jackson R;Standart N
通讯作者：
Standart N
影响因子：
14.9
作者：
Andreev DE;O'Connor PB;Loughran G;Dmitriev SE;Baranov PV;Shatsky IN
通讯作者：
Shatsky IN