GSE255844 Processing Pipeline

Publication

Genome research (2024) — PMID 38906680

Dataset

Long-read Ribo-STAMP simultaneously measures transcription and translation at full length isoform resolution

1. 1

   Sequencing data was processed using the Isoseq v4 pipeline with lima (parameter: --isoseq) to generate full-length non-concatemer reads and isoseq refine (parameter: --require-polya) to generate refined reads.

   IsoSeq vv4 GitHub

   $ Bash example

   # Install PacBio SMRT Tools (pbbioconda) if not already installed
   # conda create -n isoseq_env pbbioconda
   # conda activate isoseq_env
   
   # Assuming 'input.ccs.bam' are circular consensus (CCS) reads and 'primers.fasta' contains IsoSeq primers (e.g., SMRTbell adapters)
   # Generate full-length non-concatemer (FLNC) reads using lima
   lima --isoseq input.ccs.bam primers.fasta output.flnc.bam
   
   # Refine FLNC reads, requiring a polyA tail
   isoseq refine --require-polya output.flnc.bam output.refined.bam

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2. 2

   HEK293T APOBEC1-only and Ribo-STAMP data were aligned to hg19 reference and MDA-MB-231 Ribo-STAMP data (NT and CoCl2) were aligned to hg38 reference using pbmm2 align (parameter: --preset ISOSEQ).

   IsoSeq vNot specified (Inferred with models/gemini-2.5-flash) GitHub

   $ Bash example

   # Install pbmm2 (part of pbtools)
   # conda install -c bioconda pbmm2
   
   # Define reference genomes
   # Download hg19 reference FASTA from UCSC
   # wget -O hg19.fasta.gz http://hgdownload.soe.ucsc.edu/goldenPath/hg19/bigZips/hg19.fa.gz
   # gunzip hg19.fasta.gz
   HG19_REF="hg19.fasta" # Path to hg19 reference FASTA
   
   # Download hg38 reference FASTA from UCSC
   # wget -O hg38.fasta.gz http://hgdownload.soe.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz
   # gunzip hg38.fasta.gz
   HG38_REF="hg38.fasta" # Path to hg38 reference FASTA
   
   # Input data placeholders (assuming FASTQ files as input for alignment)
   HEK293T_INPUT="hek293t_apobec1_ribostamp.fastq"
   MDAMB231_NT_INPUT="mdamb231_ribostamp_nt.fastq"
   MDAMB231_COCL2_INPUT="mdamb231_ribostamp_cocl2.fastq"
   
   # Align HEK293T APOBEC1-only and Ribo-STAMP data to hg19
   pbmm2 align "$HG19_REF" "$HEK293T_INPUT" "hek293t_apobec1_ribostamp_hg19.bam" --preset ISOSEQ
   
   # Align MDA-MB-231 Ribo-STAMP NT data to hg38
   pbmm2 align "$HG38_REF" "$MDAMB231_NT_INPUT" "mdamb231_ribostamp_nt_hg38.bam" --preset ISOSEQ
   
   # Align MDA-MB-231 Ribo-STAMP CoCl2 data to hg38
   pbmm2 align "$HG38_REF" "$MDAMB231_COCL2_INPUT" "mdamb231_ribostamp_cocl2_hg38.bam" --preset ISOSEQ

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3. 3

   QC was completed using NanoPlot (parameters: --raw and --tsv_stats).

   NanoPlot v1.41.0 (Inferred with models/gemini-2.5-flash) GitHub

   $ Bash example

   # Install NanoPlot (example using conda)
   # conda create -n nanopore_qc nanopore-qc
   # conda activate nanopore_qc
   # conda install -c bioconda nanopore-qc
   
   # Example NanoPlot command for QC of raw Nanopore reads
   # Assuming 'nanopore_reads.fastq' is the input raw FASTQ file
   # Output will be generated in the 'nanoplot_output' directory
   
   mkdir -p nanoplot_output
   NanoPlot --raw --tsv_stats --fastq nanopore_reads.fastq --outdir nanoplot_output

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4. 4

   Reads were filtered for uniquely mapped reads and read counts obtained using IsoQuant (parameters: --data_type pacbio, --transcript_quantification unique_only, and --gene_quantification unique_only)

   PacBio sequencing vv2.0.0 GitHub

   $ Bash example

   # Install IsoQuant (example using pip)
   # pip install IsoQuant
   # Or using conda
   # conda create -n isoquant_env python=3.8
   # conda activate isoquant_env
   # pip install IsoQuant
   
   # Placeholder for input PacBio aligned reads (BAM)
   INPUT_BAM="path/to/your/pacbio_aligned_reads.bam"
   # Placeholder for reference genome FASTA (e.g., hg38.fa)
   GENOME_FASTA="path/to/your/reference_genome.fasta"
   # Placeholder for gene annotation GTF/GFF3 (e.g., gencode.v38.annotation.gtf)
   ANNOTATION_GTF="path/to/your/annotation.gtf"
   # Output directory for IsoQuant results
   OUTPUT_DIR="isoquant_output"
   
   # Create output directory if it doesn't exist
   mkdir -p "${OUTPUT_DIR}"
   
   # Execute IsoQuant for read quantification
   isoquant \
       --data_type pacbio \
       --transcript_quantification unique_only \
       --gene_quantification unique_only \
       --genome "${GENOME_FASTA}" \
       --gtf "${ANNOTATION_GTF}" \
       --bam "${INPUT_BAM}" \
       --output "${OUTPUT_DIR}"

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5. 5

   Edits were identified and filtered using custom scripts.

   RNA_Edit_Filter_Script (Inferred with models/gemini-2.5-flash) vCustom GitHub

   $ Bash example

   # This step identifies and filters RNA editing sites using custom scripts.
   # The specific script and parameters would depend on the custom implementation.
   # Input is typically a VCF file containing potential RNA editing sites identified from aligned RNA-seq data.
   # Output is a filtered VCF file with high-confidence RNA editing sites.
   
   # Define input and output files (placeholders)
   INPUT_VCF="identified_rna_edits.vcf"
   OUTPUT_VCF="filtered_rna_edits.vcf"
   
   # Define reference genome (using hg38 as a common latest assembly placeholder)
   # The actual reference genome used should match the one used for alignment.
   REFERENCE_GENOME="/path/to/human_genome/hg38.fa"
   
   # Placeholder for custom script execution.
   # The script would typically take parameters for filtering criteria such as:
   # - Minimum read depth at the editing site
   # - Minimum allele frequency of the edited base
   # - Exclusion of known SNPs (e.g., from dbSNP)
   # - Exclusion of sites in repetitive regions or low-complexity regions
   
   # Example command for a hypothetical custom script:
   # Replace 'custom_rna_edit_filter.sh' with the actual script name.
   # Replace parameters with those used in the specific custom script.
   custom_rna_edit_filter.sh \
       --input ${INPUT_VCF} \
       --output ${OUTPUT_VCF} \
       --reference ${REFERENCE_GENOME} \
       --min_depth 10 \
       --min_allele_frequency 0.1 \
       --exclude_snps "/path/to/dbSNP/common_snps.vcf.gz" \
       --filter_criteria "custom_filter_settings.txt"

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Tools Used