IDP-ASE: haplotyping and quantifying allele-specific expression at the gene and gene isoform level by hybrid sequencing.

IDP-ASE: haplotyping and quantifying allele-specific expression at the gene and gene isoform level by hybrid sequencing.
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IDP-ASE:通过混合测序在基因和基因亚型水平上对等位基因特异性表达进行单倍型分析和定量

DOI:
10.1093/nar/gkw1076
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发表时间:
2017-03-17
影响因子:
14.9
通讯作者:
Au KF
Au KF
中科院分区:
生物学2区
文献类型:
--
作者:
Deonovic B;Wang Y;Weirather J;Wang XJ;Au KF

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摘要等位基因特异性表达(ASE)是研究基因调控和二倍体转录组谱的一个基本问题,有两个关键挑战:(i)单倍型和(ii)在基因亚型水平上估计ASE。现有的ASE分析方法受限于依赖于来自费力实验或额外基因组/家族三重数据的单体型分析。此外,缺乏基因亚型水平ASE分析的方法。我们开发了一个工具,IDP-ASE,完整的ASE分析。通过第三代测序(TGS)长读段与第二代测序(SGS)短读段的创新整合,在基因和基因异构体水平上的单倍型分型和ASE定量的准确性大大提高,如金标准数据GM 12878数据和半模拟数据所证明的。除了方法学的发展,IDP-ASE在人胚胎干细胞和乳腺癌细胞中的应用表明ASE的不平衡和基因异构体ASE的不均一性是普遍的,包括肿瘤发生相关基因和多能性标记。这些结果表明,基因亚型表达和等位基因特异性表达合作,提供了高度的多样性和复杂性的基因调控和表达,突出了在基因亚型水平上研究ASE的重要性。我们的研究提供了一个强大的生物信息学解决方案,仅使用RNA测序数据来理解ASE。
Abstract Allele-specific expression (ASE) is a fundamental problem in studying gene regulation and diploid transcriptome profiles, with two key challenges: (i) haplotyping and (ii) estimation of ASE at the gene isoform level. Existing ASE analysis methods are limited by a dependence on haplotyping from laborious experiments or extra genome/family trio data. In addition, there is a lack of methods for gene isoform level ASE analysis. We developed a tool, IDP-ASE, for full ASE analysis. By innovative integration of Third Generation Sequencing (TGS) long reads with Second Generation Sequencing (SGS) short reads, the accuracy of haplotyping and ASE quantification at the gene and gene isoform level was greatly improved as demonstrated by the gold standard data GM12878 data and semi-simulation data. In addition to methodology development, applications of IDP-ASE to human embryonic stem cells and breast cancer cells indicate that the imbalance of ASE and non-uniformity of gene isoform ASE is widespread, including tumorigenesis relevant genes and pluripotency markers. These results show that gene isoform expression and allele-specific expression cooperate to provide high diversity and complexity of gene regulation and expression, highlighting the importance of studying ASE at the gene isoform level. Our study provides a robust bioinformatics solution to understand ASE using RNA sequencing data only.
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