GSE155729
GSE GEORobust single-cell discovery of RNA targets of RNA binding proteins and ribosomes
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Summary
RNA binding proteins (RBPs) are critical regulators of gene expression and RNA processing that are required for gene function. Yet, the dynamics of RBP regulation in single cells is unknown. To address this gap in understanding, we developed STAMP (Surveying Targets by APOBEC Mediated Profiling), which efficiently detects RBP-RNA interactions. STAMP does not rely on UV-crosslinking or immunoprecipitation and, when coupled with single-cell capture, can identify RBP- and cell type-specific RNA-protein interactions for multiple RBPs and cell types in single-pooled experiments. Pairing STAMP with long-read sequencing also yields RBP target sites for full-length isoforms. Finally, conducting STAMP using small ribosomal subunits (Ribo-STAMP) allows analysis of transcriptome-wide ribosome association in single cells. STAMP enables the study of RBP-RNA interactomes and translational landscapes with unprecedented cellular resolution.
Overall Design
Refer to individual Series
Analysis (6 steps)
View Data Processing- Raw reads were trimmed using cutadapt (v1.14) using the following parameters -O 5 -f fastq --match-read-wildcards --times 2 -e 0.0 --quality-cutoff 6 -m 18 -o data.fastqTr.fq -b TCGTATGCCGTCTTCTGCTTG -b ATCTCGTATGCCGTCTTCTGCTTG -b CGACAGGTTCAGAGTTCTACAGTCCGACGATC -b GATCGGAAGAGCACACGTCTGAACTCCAGTCAC -b AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA -b TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT data.fastq.gz
- Trimmed reads were mapped to and filtered of repeat elements (RepBase 18.05) with STAR (2.4.0i) using the following parameters: --alignEndsType EndToEnd --genomeDir repbase --genomeLoad NoSharedMemory --outBAMcompression 10 --outFileNamePrefix data --outFilterMultimapNmax 10 --outFilterMultimapScoreRange 1 --outFilterScoreMin 10 --outFilterType BySJout --outReadsUnmapped Fastx --outSAMattrRGline ID:foo --outSAMattributes All --outSAMmode Full --outSAMtype BAM Unsorted --outSAMunmapped Within --outStd Log --readFilesIn data.fastqTr.fq --runMode alignReads --runThreadN 8
- Reads unmapped to repeat elements were mapped to the human genome with STAR using the same parameters as the previous step, using an hg19 index in place of the repeat element index
- Subread featureCounts (-a gencode.v19.annotation.gtf -s 2 -p -o counts.txt data.bam) was used to count features using human annotations (Gencode v19)
- Edits were called using SAILOR (http://github.com/yeolab/sailor) using default parameters and dbSNP (v147) to remove known SNPs.
- bigwig files were generated from filtered BAM files (intermediates from SAILOR), using the following commands from BedTools (v2.27.1). : bedtools genomecov -split -strand - -g hg19.chrom.sizes -bg -ibam fwd.bam > fwd.bg bedtools sort -I fwd.bg > fwd.sorted.bg bedGraphToBigWig fwd.sorted.bg hg19.chrom.sizes fwd.sorted.bw bedtools genomecov -split -strand + -g hg19.chrom.sizes -bg -ibam rev.bam > rev.bg bedtools sort -I rev.bg > rev.sorted.bg bedGraphToBigWig rev.sorted.bg hg19.chrom.sizes rev.sorted.bw