GRIP-seq

Welcome to our research article published in Nature Chemistry, where we introduced an innovative technique called GRIP-seq (GECX-RNA with immunoprecipitation). This method paves the way for in vivo identification of unknown N⁶-methyladenosine on RNA with single-nucleotide resolution throughout the transcriptome using unnatural amino acids (UAAs).

To facilitate the analysis of GRIP-seq data, we have outlined a comprehensive pipeline below. By following these steps, you can gain valuable insights from GRIP-seq experiments.

Additionally, for those interested in exploring further, our raw sequencing data is accessible on NCBI's Sequence Read Archive (SRA): PRJNA797913.

Install

1. Clone the repository.

git clone https://github.com/Shall-We-Dance/GRIP-seq.git
cd GRIP-seq

2. Create a new conda environment using GRIP-seq.yml.

# create a new conda environment for GRIP-seq
conda env create -f GRIP-seq.yml

# activate the conda evironment - GRIP-seq
conda activate GRIP-seq

3. Install clipper.

# create a conda environment for clipper3
conda env create -f clipper3.yml

# for test
conda activate clipper3
clipper -h

Pipeline

1. Create directories.

• Create a directory named ANALYSIS_DIR for this analysis, and place your raw data in the ANALYSIS_DIR/raw_data folder.

• Create a directory named GENOME_DIR for STAR to generate the genome index.

• Create a directory named TOOLS_DIR, and install the following four tools: STAR, meme, clipper, metaPlotR . (Note: STAR and meme could also be installed using conda)

  Please ensure the directory structure follows the format:

${TOOLS_DIR}/
    meme/
        #Using meme to find motif
    STAR/
        #Using STAR to map reads
    clipper/
        #Using clipper to call peaks
    metaPlotR/
        #Using clipper to create metagene plots
${ANALYSIS_DIR}/
    raw_data/
        # Your reads files
${GENOME_DIR}/

2. Generate the genome indexes for STAR

#basic usage
cd scripts
bash generate_genome_index.sh ${GENOME_DIR}

This command will generate an hg19 genome index using default settings, including --sjdbOverhang=100 and utilizing 8 threads for processing.

To specify the number of threads used for generation, execute the following command:

#specify CPU threads
bash generate_genome_index.sh ${GENOME_DIR} ${CPU_THREADS}

The ideal value of --sjdbOverhang is max(ReadLength)-1, to specify, run:

#specify CPU threads & index length
bash generate_genome_index.sh ${GENOME_DIR} ${CPU_THREADS} ${INDEX_LENGTH}

3. Preprocess the raw data

Please specify the name of your repeats in scripts/repeats.txt.

#basic usage
conda activate GRIP-seq
cd scripts
bash preprocess.sh ${ANALYSIS_DIR} ${GENOME_DIR}

This script processes the FASTQ files using fastp and then maps the reads to the genome using STAR.

We will use an ID called current by defalut, to specify, run:

bash preprocess.sh ${ANALYSIS_DIR} ${GENOME_DIR} ${ID}

This script will run on 8 threads (CPU) by defalut, to specify, run:

bash preprocess.sh ${ANALYSIS_DIR} ${GENOME_DIR} ${ID} ${THREAD}

4. Clipper

#basic usage
conda activate clipper3
cd scripts
bash clipper.sh ${ANALYSIS_DIR} 

This script utilizes the mapping results from STAR to call peaks using clipper.

⚠️NOTE: This is not the final peak results.

We will use an ID called current by defalut, to specify, run:

bash clipper.sh ${ANALYSIS_DIR} ${ID}

This script will run on 8 threads (CPU) by defalut, to specify, run:

bash clipper.sh ${ANALYSIS_DIR} ${ID} ${THREAD}

5. Call peaks

#basic usage
conda activate GRIP-seq
cd scripts
bash GRIP_peak.sh ${ANALYSIS_DIR} 

This script utilizes the clipper results to call N⁶-methyladenosine sites.

We will use an ID called current by defalut, to specify, run:

bash GRIP_peak.sh ${ANALYSIS_DIR} ${ID}

This script will run on 8 threads (CPU) by defalut, to specify, run:

bash GRIP_peak.sh ${ANALYSIS_DIR} ${ID} ${THREAD}

Citing this work

If you use our code or data, please cite:

@article{sun2022genetically,
  author = {Sun, Wei and Wang, Nanxi and Liu, Hongjiang and Yu, Bingchen and Jin, Ling and Ren, Xingjie and Shen, Yin and Wang, Lei},
  title = {Genetically encoded chemical crosslinking of RNA in vivo},
  journal = {Nature Chemistry},
  pages = {1--12},
  year = {2022},
  publisher = {Nature Publishing Group UK London},
  doi = {10.1038/s41557-022-01038-4}
}