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Deep RNA sequencing of the human placental transcriptome

ABSTRACT: The goal of this study was to conduct an in-depth analysis of the human placental transcriptome. RNA was extracted from 16 placental samples using TRIzol following the manufacturer’s protocol. All samples were spiked with 96 External RNA Controls Consortium (ERCC) ExFold RNA transcripts. Ribosomal RNAs were depleted from samples using Ribo-Zero Gold and sequencing libraries were prepared using Illumina TruSeq Stranded Total RNA Sample Preparation kits. Sequencing was performed on the Illumina Hi-Seq 2500 using a 100bp paired-end protocol. Sequence adapters were trimmed using AdapterRemoval with options --trimns, --minlength 20. Trimmed RNA-Seq reads were aligned to known UCSC hg19 genes and the hg19 genome using Bowtie 2 v2.1.0 and TopHat v2.0.9 with options --library-type=fr-firststrand --mate-inner-dist -20 --mate-std-dev 180. UCSC hg19 reference genome and transcriptome was obtained through Illumina iGenomes (https://support.illumina.com/sequencing/sequencing_software/igenome.html). Aligned RNA-Seq reads were summarised using the summarizeOverlaps algorithm with the UCSC known genes hg19 GTF file using the the options overlapMode=``Union'', ignoreStrand=FALSE, singleEnd=FALSE, fragments=TRUE to generate a table of unique read counts per gene for each sample. All samples were processed in the same way, with all sequencing libraries created in the same batch and sequenced together.

ORGANISM(S): Homo sapiens

PROVIDER: GSE77085 | GEO | 2016/08/31

SECONDARY ACCESSION(S): PRJNA309411

REPOSITORIES: GEO

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Project description:Purpose: Memory T cells has been studied to improve vaccine design and develop adaptive immunotherapy. The goal of this study is to identify specific genes to memory T cells by analysis different types of T cells using transcriptome (RNA-seq) data. Methods: CD3 positive T cells were isolated from PBMC separated from blood taken from 2 healthy donors (PBMC17003 and PBMC17006). IL-7 and IL-15 were used for differentiation from CD3 positive T cells to memory type T cells. The transcriptome data of memory type T cells was generated by next generation sequencing using Illumina TruSeq Stranded mRNA LT Sample Prep Kit and HiSeq 2500 System. RNA-seq reads were trimmed and aligned to UCSC hg19 reference genome using Bowtie2 aligner. The transcripts were assembled with known transcript and abundance of the transcripts was measured as FPKM value using StringTie program. Filtration was processed by excluding genes with a FPKM value of zero and artifacts such as adaptor sequence, contaminant DNA and PCR duplicates. Differentially expressed genes (DEG) among samples were analyzed with FPKM of each gene. Results: Four type T cells were sorted after differentiation from CD3 positive T cells to memory type T cells for transcriptome analysis. They are CD8 positive T cells (sample number-1), stem memory T cells (Tscm, sample number-2), central memory T cells (Tcm, sample number-3) and effector memory T cells (Tem, sample number-4). At least 65 million sequence reads per sample were mapped to the human genomic DNA reference (UCSC hg19). More than 15,000 genes were identified after filtration, Log2 transformation of FPKM+1 and quantile normalization. Significant genes in each memory T cells were analyzed by comparing with CD8 T cells in PBMC17003 or PBMC17006. Tscm specific genes were identified 176 in PBMC17003 and 108 in PBMC 17006. Tcm specific genes were 117 in PBMC17003 and 62 in PBMC 17006. DEG of Tem were 191 in PBMC17003 and 109 in PBMC 17006. Conclusions: This study represents the transcriptomes analysis of different memory T cell using RNA-seq technology. PBMCs obtained from 2 healthy donors were used for differentiation to memory T cells followed by analysis of transcriptome. These RNA-seq data are useful for developing improved vaccine or immunotherapy.

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Deep RNA sequencing of the human placental transcriptome

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