期刊
NATURE GENETICS
卷 50, 期 10, 页码 1474-+出版社
NATURE PORTFOLIO
DOI: 10.1038/s41588-018-0207-8
关键词
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资金
- National Institutes of Health (NIH) [UL1TR002489, GM121806, GM105785]
- Basil O'Connor Award from the March of Dimes Foundation [5100683]
- Eshelman Institute for Innovation
- Lineberger Comprehensive Cancer Center
- UNC Department of Pharmacology
- James S. McDonnell Foundation 21st Century Science Initiative-Complex Systems Scholar Award Grant [220020315]
- NIH MIRA award [R35 GM122532]
- NIH training grant in bioinformatics and computational biology [T32 GM067553]
- NIH training grant in genetics and molecular biology [T32 GM007092]
- NSF [DGE-1144081]
- NIH training grant in molecular and cellular biophysics [T32 GM08570]
- [DGE-1650116]
- NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES [UL1TR002489] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [T32GM067553, R01GM121806, T32GM007092, R01GM105785, T32GM008570, R35GM122532] Funding Source: NIH RePORTER
The functions of most long non-coding RNAs (lncRNAs) are unknown. In contrast to proteins, lncRNAs with similar functions often lack linear sequence homology; thus, the identification of function in one lncRNA rarely informs the identification of function in others. We developed a sequence comparison method to deconstruct linear sequence relationships in lncRNAs and evaluate similarity based on the abundance of short motifs called k-mers. We found that lncRNAs of related function often had similar k-mer profiles despite lacking linear homology, and that k-mer profiles correlated with protein binding to lncRNAs and with their subcellular localization. Using a novel assay to quantify Xist-like regulatory potential, we directly demonstrated that evolutionarily unrelated lncRNAs can encode similar function through different spatial arrangements of related sequence motifs. K-mer-based classification is a powerful approach to detect recurrent relationships between sequence and function in lncRNAs.
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