| Literature DB >> 33048844 |
Xiangbo Ruan1, Ping Li1, Yonghe Ma1, Cheng-Fei Jiang1, Yi Chen1, Yu Shi1, Nikhil Gupta1, Fayaz Seifuddin2, Mehdi Pirooznia2, Yasuyuki Ohnishi3, Nao Yoneda3, Megumi Nishiwaki3,4, Gabrijela Dumbovic5, John L Rinn5, Yuichiro Higuchi3, Kenji Kawai6, Hiroshi Suemizu3, Haiming Cao1.
Abstract
A growing number of long noncoding RNAs (lncRNAs) have emerged as vital metabolic regulators. However, most human lncRNAs are nonconserved and highly tissue specific, vastly limiting our ability to identify human lncRNA metabolic regulators (hLMRs). In this study, we established a pipeline to identify putative hLMRs that are metabolically sensitive, disease relevant, and population applicable. We first progressively processed multilevel human transcriptome data to select liver lncRNAs that exhibit highly dynamic expression in the general population, show differential expression in a nonalcoholic fatty liver disease (NAFLD) population, and respond to dietary intervention in a small NAFLD cohort. We then experimentally demonstrated the responsiveness of selected hepatic lncRNAs to defined metabolic milieus in a liver-specific humanized mouse model. Furthermore, by extracting a concise list of protein-coding genes that are persistently correlated with lncRNAs in general and NAFLD populations, we predicted the specific function for each hLMR. Using gain- and loss-of-function approaches in humanized mice as well as ectopic expression in conventional mice, we validated the regulatory role of one nonconserved hLMR in cholesterol metabolism by coordinating with an RNA-binding protein, PTBP1, to modulate the transcription of cholesterol synthesis genes. Our work overcame the heterogeneity intrinsic to human data to enable the efficient identification and functional definition of disease-relevant human lncRNAs in metabolic homeostasis.Entities:
Keywords: Gastroenterology; Hepatitis; Metabolism; Noncoding RNAs; Obesity
Year: 2021 PMID: 33048844 PMCID: PMC7773374 DOI: 10.1172/JCI136336
Source DB: PubMed Journal: J Clin Invest ISSN: 0021-9738 Impact factor: 14.808