Neonate and Adult Human Platelet RNA-seq and Ribo-seq Data

Published: 21 June 2022| Version 1 | DOI: 10.17632/337m3ppw46.1
Contributor:
Zhaoyan Liu

Description

To compare the neonatal platelet transcriptome and translatome changes during development, RNA-seq and Ribo-seq were performed in platelet obtained from adult and cord blood (CB). For RNA-seq, there are 11 CB samples and 9 adult samples. For Ribo-seq, 3 CB samples and 3 adult samples are studied. The sequencing details are shown below. Raw expression data, preprocessed (normalized, filtered) data, and Differential Expression Gene lists are included. The study were completed using trizol-isolated RNA, and microarray analysis using the ~20,000 annotated gene set human ClariomTM S Array (Applied Biosystems);2,8 RNASeq and RiboSeq transcriptomic studies were completed using the NovoSeq 6000 platform. RNASeq (100 ng/sample) was completed using previously-established protocols for mRNA capture, cDNA synthesis, library generation, and DNA Sequencing.9 Ribosome footprint profiling (RiboSEq) was completed as previously described,10,11 starting with 5 X 108 platelets incubated with 100 g mL-1 cycloheximide for 1 minute at 250C to preserve ribosome-attached mRNAs. Following lysis, prepared lysates were used for RNase I digestion of polysomes, size selection and purification of monosme-bound RNA, followed by cDNA synthesis, PCR amplification, and single-read pooled sequencing (>90 million reads/library). For both RNASeq and RiboSeq, FASTQ sequences truncated as 50 mer pair-end reads were mapped to the human genome Hg38 GRCh38 build,12 and normalized mRNA abundance for each transcript was calculated using the RPKM (reads per kilobase/106) score. For all samples, fragment alignment ranged between 94% – 96%.

Files

Steps to reproduce

RNAseq_reads.csv and RIBOseq_reads.csv are the raw data; RNAseq_rpkm.csv and RIBOseq_rpkm.csv are the RPKM normalized data; RNAseq_DGEList.RDS and RIBOseq_DGEList.RDS are the DEGList objects generated from edgeR, containing the group labels, library sizes and normalization factors. The workflow and R code that used to process the data are introduced in details at Github (see Related links)

Institutions

Stony Brook University

Categories

RNA Sequencing, Platelet, High-Throughput Sequencing

License