期刊
NUCLEIC ACIDS RESEARCH
卷 46, 期 D1, 页码 D139-D145出版社
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkx895
关键词
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资金
- National Natural Science Foundation of China [31771462, 81772614, 31471252, U1611261]
- National Key Research and Development Program [2017YFA0106700]
- Guangdong Natural Science Foundation [2014TQ01R387, 2014A030313181]
- Science and Technology Program of Guangzhou, China [201604020003]
Identifying disease-causing variants among a large number of single nucleotide variants (SNVs) is still a major challenge. Recently, N-6-methyladenosine (m(6)A) has become a research hotspot because of its critical roles in many fundamental biological processes and a variety of diseases. Therefore, it is important to evaluate the effect of variants on m(6)A modification, in order to gain a better understanding of them. Here, we report m6AVar (http://m6avar.renlab.org), a comprehensive database of m(6)A-associated variants that potentially influence m(6)A modification, which will help to interpret variants by m(6)A function. The m(6)A-associated variants were derived from three different m(6)A sources including miCLIP/PA-m(6)A-seq experiments (high confidence), MeRIP-Seq experiments (medium confidence) and transcriptome-wide predictions (low confidence). Currently, m6AVar contains 16 132 high, 71 321 medium and 326 915 low confidence level m(6)A-associated variants. We also integrated the RBP-binding regions, miRNA-targets and splicing sites associated with variants to help users investigate the effect of m(6)A-associated variants on post-transcriptional regulation. Because it integrates the data from genome-wide association studies (GWAS) and ClinVar, m6AVar is also a useful resource for investigating the relationship between the m(6)A-associated variants and disease. Overall, m6AVar will serve as a useful resource for annotating variants and identifying disease-causing variants.
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