GEO Logo
   NCBI > GEO > Accession DisplayHelp Not logged in | LoginHelp
GEO help: Mouse over screen elements for information.
Series GSE163491 Query DataSets for GSE163491
Status Public on Jun 05, 2021
Title Deep and accurate detection of m6A RNA modifications in human and mouse cells using miCLIP2 and m6Aboost machine learning [a]
Organisms Homo sapiens; Mus musculus
Experiment type Expression profiling by high throughput sequencing
Summary N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing, such as RNA stability and translation. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based approach to map m6A sites in the transcriptome with single-nucleotide resolution. However, due to broad antibody reactivity, reliable identification of m6A sites from miCLIP data remains challenging. Here, we present several experimental and computational innovations that significantly improve transcriptome-wide detection of m6A sites. Based on the recently developed iCLIP2 protocol, the optimised miCLIP2 results in high-complexity libraries using less input material, leading to a more comprehensive representation of m6A sites. Next, we established a robust computational pipeline to identify true m6A sites from our miCLIP2 data. The analyses are calibrated with data from Mettl3 knockout cells to learn the characteristics of m6A deposition, including a significant number of m6A sites outside of DRACH motifs. In order to make these results universally applicable, we trained a machine learning model, m6Aboost, based on the experimental and RNA sequence features. Importantly, m6Aboost allows prediction of genuine m6A sites in miCLIP data without filtering for DRACH motifs or the need for Mettl3 depletion. Using m6Aboost, we identify thousands of high-confidence m6A sites in different murine and human cell lines, which provide a rich resource for future analysis. Collectively, our combined experimental and computational methodology greatly improves m6A identification.
Overall design miCLIP2 experiments were performed on polyA+ RNA from human and mouse cells, with 3 biological replicates per condition. Mettl3 KO cells served to calibrate the m6A detection.
Contributor(s) Körtel N, Rücklé C, Zhou Y, Busch A, Sutandy FR, Dominissine D, Dieterich C, Zarnack K, König J
Citation(s) 34157120
Submission date Dec 18, 2020
Last update date Sep 08, 2022
Contact name Kathi Zarnack
Organization name Goethe University Frankfurt
Department Buchmann Institute for Molecular Life Sciences (BMLS)
Street address Max-von-Laue-Str. 15
City Frankfurt
ZIP/Postal code 60438
Country Germany
Platforms (2)
GPL18573 Illumina NextSeq 500 (Homo sapiens)
GPL19057 Illumina NextSeq 500 (Mus musculus)
Samples (22)
GSM4980008 miCLIP mESC WT rep1, technical rep1
GSM4980009 miCLIP mESC WT rep1, technical rep2
GSM4980010 miCLIP mESC WT rep2
This SubSeries is part of SuperSeries:
GSE163500 Deep and accurate detection of m6A RNA modifications in human and mouse cells using miCLIP2 and m6Aboost machine learning
BioProject PRJNA686380
SRA SRP298464

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE163491_HEK293T_m6Aboost_predicted_m6A_sites.bed.gz 549.1 Kb (ftp)(http) BED
GSE163491_Mouse_heart_100ng_m6Aboost_predicted_m6A_sites.bed.gz 13.1 Kb (ftp)(http) BED
GSE163491_Mouse_heart_1ug_m6Aboost_predicted_m6A_sites.bed.gz 489.2 Kb (ftp)(http) BED
GSE163491_Mouse_heart_300ng_m6Aboost_predicted_m6A_sites.bed.gz 97.0 Kb (ftp)(http) BED
GSE163491_Mouse_heart_50ng_m6Aboost_predicted_m6A_sites.bed.gz 3.1 Kb (ftp)(http) BED
GSE163491_RAW.tar 600.0 Mb (http)(custom) TAR (of BW, TXT)
GSE163491_mESC_m6Aboost_predicted_m6A_sites.bed.gz 424.8 Kb (ftp)(http) BED 4.0 Mb (ftp)(http) BW 4.1 Mb (ftp)(http) BW 38.6 Mb (ftp)(http) BW 39.3 Mb (ftp)(http) BW 4.7 Mb (ftp)(http) BW 4.8 Mb (ftp)(http) BW 48.5 Mb (ftp)(http) BW 49.6 Mb (ftp)(http) BW
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file
Processed data are available on Series record

| NLM | NIH | GEO Help | Disclaimer | Accessibility |
NCBI Home NCBI Search NCBI SiteMap