2021
DOI: 10.21203/rs.3.pex-1336/v1
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3’ RNA sequencing for robust and low-cost gene expression profiling

Abstract: 3’seq-RNA Profiling (3’SRP) approach is based on multiplexing samples and molecular indexing mRNA in order to drive genome-wide transcriptional profiling at reasonable cost in comparison to standard RNA-sequencing. The protocol is performed according to the 3′-digital gene expression (3′-DGE) approach developed by the Broad institute. The libraries are prepared from small amounts of total RNA where the mRNA poly(A) tails are tagged with universal adapters, well-specific barcodes and unique molecular identifier… Show more

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Cited by 17 publications
(21 citation statements)
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“…Samples were demultiplexed and aligned on the hg19 genome using the 3' SRP pipeline. The primary analysis of DGEseq data including, quality controls of reads, demultiplexing, read mapping, and quantification of gene expression, was carried out as described in Charpentier et al 20 Normalization of gene expression and differential expression analysis were both performed with DESeq2. 21 pvalues were adjusted with the False Discovery Rate method and genes with an adjusted p-value less than 0.05 were considered as differentially expressed (DEG).…”
Section: Discussionmentioning
confidence: 99%
“…Samples were demultiplexed and aligned on the hg19 genome using the 3' SRP pipeline. The primary analysis of DGEseq data including, quality controls of reads, demultiplexing, read mapping, and quantification of gene expression, was carried out as described in Charpentier et al 20 Normalization of gene expression and differential expression analysis were both performed with DESeq2. 21 pvalues were adjusted with the False Discovery Rate method and genes with an adjusted p-value less than 0.05 were considered as differentially expressed (DEG).…”
Section: Discussionmentioning
confidence: 99%
“…Retro-transcription was achieved using the cDNA Reverse Transcription High-Capacity kit (Applied Biosystem, Courtaboeuf, France). Sample preparation, the verification of sample quality and quantity, and transcriptomics were performed according to the protocol explained and detailed by Charpentier et al [ 61 ]. The identification and selection of differentially expressed genes was performed with the R package “DESeq2”, and “clusterProfiler” was used for enrichment analyses and associated graphical representation [ 62 ].…”
Section: Methodsmentioning
confidence: 99%
“…The primary analysis of DGEseq data including, quality controls of reads, demultiplexing, read mapping, and quantification of gene expression, was carried out as described in Charpentier et al [ 20 ] Normalization of gene expression and differential expression analysis were both performed with DESeq2 [ 21 ]. p -values were adjusted with the False Discovery Rate method and genes with an adjusted p -value less than 0.05 were considered as differentially expressed (DEG).…”
Section: Methodsmentioning
confidence: 99%