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GSE155649

GSE GEO
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Robust single-cell discovery of RNA targets of RNA binding proteins and ribosomes [RNA-seq]

Organism: Homo sapiens
Platform: GPL20301
Samples: 77
Experiment Types:
Other
Submitted: Aug 04 2020
Last Updated: Jan 24 2025
Status: Public on May 09 2021
Contact: Gene,,Yeo (UCSD)

Relations

SubSeries of: GSE155729 BioProject: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA655121 SRA: https://www.ncbi.nlm.nih.gov/sra?term=SRP275758

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 (RiboSTAMP) 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

strategy for immunoprecipitation-free detection of protein-RNA interactions by fusion of RNA binding proteins and ribosomal subunits to the C-to-U RNA edtiing enzyme APOBEC1 and quantification of interaction-driven edits by sequencing, to allow interaction detection on long-read and single-cell platforms

Analysis (6 steps)

View Data Processing
Processing steps for GSE155649
  1. 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
  2. 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
  3. 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
  4. 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)
  5. Edits were called using SAILOR (http://github.com/yeolab/sailor) using default parameters and dbSNP (v147) to remove known SNPs.
  6. 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

Supplementary Files (10)

GSE155649_RAW.tar Download
GSE155649_SLBP_0_72hr_merged_a0_b0_e0.01.bed.gz Download
GSE155649_SLBP_0_72hr_merged_a0_b0_e0.01.fwd.sorted.rmdup.readfiltered.sorted.bw Download
GSE155649_SLBP_0_72hr_merged_a0_b0_e0.01.rev.sorted.rmdup.readfiltered.sorted.bw Download
GSE155649_SLBP_1000_48hr_merged_a0_b0_e0.01.bed.gz Download
GSE155649_SLBP_1000_48hr_merged_a0_b0_e0.01.fwd.sorted.rmdup.readfiltered.sorted.bw Download
GSE155649_SLBP_1000_48hr_merged_a0_b0_e0.01.rev.sorted.rmdup.readfiltered.sorted.bw Download
GSE155649_SLBP_1000_72hr_merged_a0_b0_e0.01.bed.gz Download
GSE155649_SLBP_1000_72hr_merged_a0_b0_e0.01.fwd.sorted.rmdup.readfiltered.sorted.bw Download
GSE155649_SLBP_1000_72hr_merged_a0_b0_e0.01.rev.sorted.rmdup.readfiltered.sorted.bw Download
GEO Samples (77)
GSM4709474 GSM4709475 GSM4709476 GSM4709477 GSM4709478 GSM4709479 GSM4709480 GSM4709481 GSM4709482 GSM4709483 GSM4709484 GSM4709485 GSM4709486 GSM4709487 GSM4709488 GSM4709489 GSM4709490 GSM4709491 GSM4709492 GSM4709493 GSM4709494 GSM4709495 GSM4709496 GSM4709497 GSM4709498 GSM4709499 GSM4709500 GSM4709501 GSM4709502 GSM4709503 GSM4709504 GSM4709505 GSM4709506 GSM4709507 GSM4709508 GSM4709509 GSM4709510 GSM4709511 GSM4709512 GSM4709513 GSM4709514 GSM4709515 GSM4709516 GSM4709517 GSM4709518 GSM4709519 GSM4709520 GSM4709521 GSM4709522 GSM4709523 GSM4709524 GSM4709525 GSM4709526 GSM4709527 GSM4709528 GSM4709529 GSM4709530 GSM4709531 GSM4709532 GSM4709533 GSM4709534 GSM4709535 GSM4709536 GSM4709537 GSM4709538 GSM4709539 GSM4709540 GSM4709541 GSM4709542 GSM4709543 GSM4709544 GSM4709545 GSM4709546 GSM4709547 GSM4709548 GSM4709549 GSM4818032

Dataset Citations (2)

Robust single-cell discovery of RNA targets of RNA-binding proteins and ribosomes.
PMID 33963355 · 2021 · Nature methods
Kristopher W Brannan, Isaac A Chaim, Ryan J Marina, Brian A Yee, Eric R Kofman, Daniel A Lorenz, Pratibha Jagannatha, Kevin D Dong, Assael A Madrigal, Jason G Underwood, Gene W Yeo
Long-read Ribo-STAMP simultaneously measures transcription and translation with isoform resolution.
PMID 38906680 · 2024 · Genome research
Pratibha Jagannatha, Alexandra T Tankka, Daniel A Lorenz, Tao Yu, Brian A Yee, Kristopher W Brannan, Cathy J Zhou, Jason G Underwood, Gene W Yeo

Linked Publications (2)

Robust single-cell discovery of RNA targets of RNA-binding proteins and ribosomes.
Nature methods · 2021
Long-read Ribo-STAMP simultaneously measures transcription and translation with isoform resolution.
Genome research · 2024

Data Files (10)

Accession File Name Stored Type Output Type Mapping Assembly Size Download
— RPS3-0_S5_L001_R1_001.fastq.gz OTHER 1.8 GB link
— RPS3-1000_S19_L002_R1_001.fastq.gz OTHER 1.8 GB link
— Sample_40_S68_L006_R1_001.fastq.gz OTHER 730.7 MB link
— Sample41_S41_merged.fastq.gz OTHER 63.0 MB link
— Sample42_S42_merged.fastq.gz OTHER 124.1 MB link
— TI_55_S13_L001_R1_001.fastq.gz OTHER 883.8 MB link
— TI_56_S14_L001_R1_001.fastq.gz OTHER 241.8 MB link
— TI_58_S15_L001_R1_001.fastq.gz OTHER 262.8 MB link
— TI_59_S16_L001_R1_001.fastq.gz OTHER 718.1 MB link
— TI_8_S6_L001_R1_001.fastq.gz RNA-Seq 958.8 MB link