转录组
基因表达
基因
生物
基因表达谱
计算生物学
基因表达调控
生物信息学
作者
Mahashweta Basu,Kun Wang,Eytan Ruppin,Sridhar Hannenhalli
出处
期刊:Science Advances
[American Association for the Advancement of Science (AAAS)]
日期:2021-04-02
卷期号:7 (14)
被引量:46
标识
DOI:10.1126/sciadv.abd6991
摘要
Complex diseases are mediated via transcriptional dysregulation in multiple tissues. Thus, knowing an individual's tissue-specific gene expression can provide critical information about her health. Unfortunately, for most tissues, the transcriptome cannot be obtained without invasive procedures. Could we, however, infer an individual's tissue-specific expression from her whole blood transcriptome? Here, we rigorously address this question. We find that an individual's whole blood transcriptome can significantly predict tissue-specific expression levels for ~60% of the genes on average across 32 tissues, with up to 81% of the genes in skeletal muscle. The tissue-specific expression inferred from the blood transcriptome is almost as good as the actual measured tissue expression in predicting disease state for six different complex disorders, including hypertension and type 2 diabetes, substantially surpassing the blood transcriptome. The code for tissue-specific gene expression prediction, TEEBoT, is provided, enabling others to study its potential translational value in other indications.
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