Predicting cell-type-specific non-coding RNA transcription from genome sequence
Predicting cell-type-specific non-coding RNA transcription from genome sequence
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DOI：
10.1101/2020.03.29.011205
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发表时间：
2020-03
期刊：
影响因子：
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通讯作者：
Masaru Koido;C. Hon;S. Koyama;H. Kawaji;Y. Murakawa;K. Ishigaki;K. Ito;J. Sese;Y. Kamatani;Piero Carninci;C. Terao
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文献类型：
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作者：
Masaru Koido;C. Hon;S. Koyama;H. Kawaji;Y. Murakawa;K. Ishigaki;K. Ito;J. Sese;Y. Kamatani;Piero Carninci;C. Terao
转录是通过涉及非编码rna （ncRNAs）的复杂机制进行调控的。然而，由于ncrna，特别是增强rna的转录通常是低水平的，并且具有细胞类型特异性，因此其对基因型的依赖性在很大程度上仍未被探索。在这里，我们开发了ncRNA转录的突变效应预测（MENTR），这是一个定量的机器学习框架，可靠地将遗传关联与ncRNA表达联系起来，并解决了细胞类型水平。mentr预测的突变对ncRNA转录的影响与以前的基因研究的估计一致，以细胞类型依赖的方式。我们从41223个GWAS变异中推断出可靠的因果变异，并提出了7775个增强子和3548个长ncrna作为348个主要人类原细胞和组织中的复杂性状相关的ncrna，包括在克罗恩病的单变异解决中貌似增强子介导的功能改变。总之，我们为发现因果变异、驱动复杂性状的生物学机制以及相关细胞类型中ncRNA调控的序列依赖性提供了新的资源。
Transcription is regulated through complex mechanisms involving non-coding RNAs (ncRNAs). However, because transcription of ncRNAs, especially enhancer RNAs, is often low and cell type-specific, its dependency on genotype remains largely unexplored. Here, we developed mutation effect prediction on ncRNA transcription (MENTR), a quantitative machine learning framework reliably connecting genetic associations with expression of ncRNAs, resolved to the level of cell type. MENTR-predicted mutation effects on ncRNA transcription were concordant with estimates from previous genetic studies in a cell type-dependent manner. We inferred reliable causal variants from 41,223 GWAS variants, and proposed 7,775 enhancers and 3,548 long-ncRNAs as complex trait-associated ncRNAs in 348 major human primary cells and tissues, including plausible enhancer-mediated functional alterations in single-variant resolution in Crohn’s disease. In summary, we present new resources for discovering causal variants, the biological mechanisms driving complex traits, and the sequence-dependency of ncRNA regulation in relevant cell types.