Top-ranked expressed gene transcripts of human protein-coding genes investigated with GTEx dataset.

Top-ranked expressed gene transcripts of human protein-coding genes investigated with GTEx dataset.
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DOI:
10.1038/s41598-020-73081-5
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发表时间:
2020-10-01
期刊:
影响因子:
4.6
通讯作者:
Lin WC
Lin WC
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Tung KF;Pan CY;Chen CH;Lin WC

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随着大量RNA-Seq转录组数据的积累,我们已经扩展了我们对蛋白质编码基因转录本组成的理解。然而,人类蛋白质编码基因转录本的替代复合模式将使基因表达数据处理和解释复杂化。用统一的数据资源详尽地询问蛋白质编码基因的复杂mRNA亚型是至关重要的。为了研究作为转录组分析参考的代表性mRNA转录异构体,我们利用GTEx数据建立了人类蛋白质编码基因的顶级转录异构体表达数据资源。独特的组织特异性表达谱和调制可以观察到个别排名靠前的转录蛋白质编码基因。蛋白质编码转录本或基因在转录组数据中确实占据了更高的表达分数。此外,排名靠前的转录本是在各种正常组织中占优势表达的转录本。有趣的是,一些排名靠前的转录本是非编码剪接异构体,这意味着不同的基因调控机制。对顶级转录异构体的组织表达模式的全面研究至关重要。因此,我们建立了一个网络工具来检查各种人类正常组织类型中排名靠前的转录异构体,它提供了简洁的转录信息和易于使用的图形用户界面。研究排名靠前的转录异构体将有助于理解独特的选择性剪接转录异构体的功能意义。
With considerable accumulation of RNA-Seq transcriptome data, we have extended our understanding about protein-coding gene transcript compositions. However, alternatively compounded patterns of human protein-coding gene transcripts would complicate gene expression data processing and interpretation. It is essential to exhaustively interrogate complex mRNA isoforms of protein-coding genes with an unified data resource. In order to investigate representative mRNA transcript isoforms to be utilized as transcriptome analysis references, we utilized GTEx data to establish a top-ranked transcript isoform expression data resource for human protein-coding genes. Distinctive tissue specific expression profiles and modulations could be observed for individual top-ranked transcripts of protein-coding genes. Protein-coding transcripts or genes do occupy much higher expression fraction in transcriptome data. In addition, top-ranked transcripts are the dominantly expressed ones in various normal tissues. Intriguingly, some of the top-ranked transcripts are noncoding splicing isoforms, which imply diverse gene regulation mechanisms. Comprehensive investigation on the tissue expression patterns of top-ranked transcript isoforms is crucial. Thus, we established a web tool to examine top-ranked transcript isoforms in various human normal tissue types, which provides concise transcript information and easy-to-use graphical user interfaces. Investigation of top-ranked transcript isoforms would contribute understanding on the functional significance of distinctive alternatively spliced transcript isoforms.
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