6.1.RNA Editing

1) Background

Pre-mRNA molecules transcribed from the genome may fold to form double-stranded RNA (dsRNA) secondary structures. dsRNA-specific adenosine deaminase (ADAR) enzymes bind these structures and deaminate some adenosines to inosines. If these inosines are located in an exon, they will be present in the mature mRNA.

Reverse transcription replaces inosines in mRNA with guanosines in the cDNA. Thus, the hallmark of RNA editing is a consistent A → G mismatch between RNA sequencing (RNA-seq) data and the reference genomic sequence to which it is aligned.

Four main types of mRNA editing have been studied in recent decades. A-to-I RNA editing is the most common in terms of the range of organisms affected, the breadth of tissues edited and the number of editing sites.

Editing can modify protein function, generate new protein products and alter gene regulation.

2) Paper

RNAEditor: easy detection of RNA editing events and the introduction of editing islands

3) Pipeline

4) Website


5) Running steps (RNAEditor)

请首先启动相应 Docker,进入工作目录。

(1) input files

We need a configuration file to assign the input files to the RNAeditor, here is a brief look of configuration file

# This file is used to configure the behaviour of RNAeditor
# Standard input files
refGenome = /home/test/data/Homo_sapiens.GRCh38.ch1.fa
gtfFile = /home/test/data/Homo_sapiens.GRCh38.chr1.gtf
dbSNP = /home/test/data/dbSNP.vcf.new
hapmap = /home/test/data/HAPMAP.vcf
omni = /home/test/data/1000GenomeProject.vcf
esp = /home/test/data/ESP.chr1.vcf
aluRegions = /home/test/data/Repeats.chr1.bed
output = /apps/RNAEditor/output/chr1
sourceDir = /usr/local/bin/
maxDiff = 0.04
seedDiff = 2
standCall = 0
standEmit = 0
edgeDistance = 3
intronDistance = 5
minPts = 5
eps = 50
paired = False
keepTemp = True
overwrite = False
threads = 1

(2) starting analysis

rm -rf /apps/RNAEditor/output
mkdir /apps/RNAEditor/output
cd /apps/RNAEditor
RNAEditor.py -i /home/test/chr1.fq -c /home/test/config_new
mv /apps/RNAEditor/output/ /home/test/out_new

6) Homework

  • 参照RNAEditor网页上Documentation页面,理解示例文件运行完的输出结果中sample.vcf和sample.gvf的含义。根据sample.gvf文件,统计RNA编辑位点在基因组上的分布(3‘UTR,intron等各不同区域各有多少RNA editing sites,用柱形图展示);在sample.gvf最后添加一列,计算每个RNA编辑位点的editing ratio。

7) References

  • A-to-I RNA editing — immune protector and transcriptome diversifier. Eli Eisenberg, et al. Nature Reviews, 2018.

  • RNAEditor: easy detection of RNA editing events andthe introduction of editing islands. David John, et al. Briefings in Bioinformatics, 2017.