m6Acomet: large-scale functional prediction of individual m6A RNA methylation sites from an RNA co-methylation network
Abstract Background Over one hundred different types of post-transcriptional RNA modifications have been identified in human. Researchers discovered that RNA modifications can regulate various biological processes, and RNA methylation, especially N6-methyladenosine, has become one of the most resear...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2019-05-01
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| Series: | BMC Bioinformatics |
| Online Access: | http://link.springer.com/article/10.1186/s12859-019-2840-3 |
| _version_ | 1811208257230864384 |
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| author | Xiangyu Wu Zhen Wei Kunqi Chen Qing Zhang Jionglong Su Hui Liu Lin Zhang Jia Meng |
| author_facet | Xiangyu Wu Zhen Wei Kunqi Chen Qing Zhang Jionglong Su Hui Liu Lin Zhang Jia Meng |
| author_sort | Xiangyu Wu |
| collection | DOAJ |
| description | Abstract Background Over one hundred different types of post-transcriptional RNA modifications have been identified in human. Researchers discovered that RNA modifications can regulate various biological processes, and RNA methylation, especially N6-methyladenosine, has become one of the most researched topics in epigenetics. Results To date, the study of epitranscriptome layer gene regulation is mostly focused on the function of mediator proteins of RNA methylation, i.e., the readers, writers and erasers. There is limited investigation of the functional relevance of individual m6A RNA methylation site. To address this, we annotated human m6A sites in large-scale based on the guilt-by-association principle from an RNA co-methylation network. It is constructed based on public human MeRIP-Seq datasets profiling the m6A epitranscriptome under 32 independent experimental conditions. By systematically examining the network characteristics obtained from the RNA methylation profiles, a total of 339,158 putative gene ontology functions associated with 1446 human m6A sites were identified. These are biological functions that may be regulated at epitranscriptome layer via reversible m6A RNA methylation. The results were further validated on a soft benchmark by comparing to a random predictor. Conclusions An online web server m6Acomet was constructed to support direct query for the predicted biological functions of m6A sites as well as the sites exhibiting co-methylated patterns at the epitranscriptome layer. The m6Acomet web server is freely available at: www.xjtlu.edu.cn/biologicalsciences/m6acomet. |
| first_indexed | 2024-04-12T04:18:45Z |
| format | Article |
| id | doaj.art-520df5f049174b37a047981646795a6e |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-04-12T04:18:45Z |
| publishDate | 2019-05-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-520df5f049174b37a047981646795a6e2022-12-22T03:48:19ZengBMCBMC Bioinformatics1471-21052019-05-0120111210.1186/s12859-019-2840-3m6Acomet: large-scale functional prediction of individual m6A RNA methylation sites from an RNA co-methylation networkXiangyu Wu0Zhen Wei1Kunqi Chen2Qing Zhang3Jionglong Su4Hui Liu5Lin Zhang6Jia Meng7Department of Biological Sciences, Xi’an Jiaotong-Liverpool UniversityDepartment of Biological Sciences, Xi’an Jiaotong-Liverpool UniversityDepartment of Biological Sciences, Xi’an Jiaotong-Liverpool UniversityDepartment of Biological Sciences, Xi’an Jiaotong-Liverpool UniversityDepartment of Mathematical Sciences, Xi’an Jiaotong-Liverpool UniversitySchool of Information and Control Engineering, China University of Mining and TechnologySchool of Information and Control Engineering, China University of Mining and TechnologyDepartment of Biological Sciences, Xi’an Jiaotong-Liverpool UniversityAbstract Background Over one hundred different types of post-transcriptional RNA modifications have been identified in human. Researchers discovered that RNA modifications can regulate various biological processes, and RNA methylation, especially N6-methyladenosine, has become one of the most researched topics in epigenetics. Results To date, the study of epitranscriptome layer gene regulation is mostly focused on the function of mediator proteins of RNA methylation, i.e., the readers, writers and erasers. There is limited investigation of the functional relevance of individual m6A RNA methylation site. To address this, we annotated human m6A sites in large-scale based on the guilt-by-association principle from an RNA co-methylation network. It is constructed based on public human MeRIP-Seq datasets profiling the m6A epitranscriptome under 32 independent experimental conditions. By systematically examining the network characteristics obtained from the RNA methylation profiles, a total of 339,158 putative gene ontology functions associated with 1446 human m6A sites were identified. These are biological functions that may be regulated at epitranscriptome layer via reversible m6A RNA methylation. The results were further validated on a soft benchmark by comparing to a random predictor. Conclusions An online web server m6Acomet was constructed to support direct query for the predicted biological functions of m6A sites as well as the sites exhibiting co-methylated patterns at the epitranscriptome layer. The m6Acomet web server is freely available at: www.xjtlu.edu.cn/biologicalsciences/m6acomet.http://link.springer.com/article/10.1186/s12859-019-2840-3 |
| spellingShingle | Xiangyu Wu Zhen Wei Kunqi Chen Qing Zhang Jionglong Su Hui Liu Lin Zhang Jia Meng m6Acomet: large-scale functional prediction of individual m6A RNA methylation sites from an RNA co-methylation network BMC Bioinformatics |
| title | m6Acomet: large-scale functional prediction of individual m6A RNA methylation sites from an RNA co-methylation network |
| title_full | m6Acomet: large-scale functional prediction of individual m6A RNA methylation sites from an RNA co-methylation network |
| title_fullStr | m6Acomet: large-scale functional prediction of individual m6A RNA methylation sites from an RNA co-methylation network |
| title_full_unstemmed | m6Acomet: large-scale functional prediction of individual m6A RNA methylation sites from an RNA co-methylation network |
| title_short | m6Acomet: large-scale functional prediction of individual m6A RNA methylation sites from an RNA co-methylation network |
| title_sort | m6acomet large scale functional prediction of individual m6a rna methylation sites from an rna co methylation network |
| url | http://link.springer.com/article/10.1186/s12859-019-2840-3 |
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