3'GAmES: Systematic refinement of gene termini by mRNA 3' end sequencing
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA611785 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11282030.fastq.gz | Fastqsanger.gz |
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Project description:Motivation: Alternative cleavage and polyadenylation generates mRNA 3´ isoforms in a cell type- and tissue-specific manner. Due to finite available RNA sequencing data of organisms with vast cell type complexity, currently available gene annotation resources are incomplete, which poses significant challenges to the comprehensive interpretation and quantification of transcriptomes. Results: We developed 3'GAmES, a stand-alone analysis pipeline to identify and annotate novel (cell-type-specific) mRNA 3´ isoforms from 3' mRNA sequencing datasets. When applied to mouse embryonic stem cells or Zebrafish embryos, 3'GAmES expands currently available mRNA 3' annotations by 47% and 57%, respectively; and the resulting annotations significantly improve comprehensive gene-tag counting by cost-effective 3' mRNA sequencing to more accurately mirror whole-transcriptome RNAseq measurements. As a stand-alone analysis tool, 3'GAmES systematically augments cell type-specific transcript annotations and increases the robustness of quantitative gene expression profiling by 3' mRNA sequencing.
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Project description:Alternative cleavage and polyadenylation generates mRNA 3' isoforms in a cell type-specific manner. Due to finite available RNA sequencing data of organisms with vast cell type complexity, currently available gene annotation resources are incomplete, which poses significant challenges to the comprehensive interpretation and quantification of transcriptomes. In this chapter, we introduce 3'GAmES, a stand-alone computational pipeline for the identification and quantification of novel mRNA 3'end isoforms from 3'mRNA sequencing data. 3'GAmES expands available repositories and improves comprehensive gene-tag counting by cost-effective 3' mRNA sequencing, faithfully mirroring whole-transcriptome RNAseq measurements. By employing R and bash shell scripts (assembled in a Singularity container) 3'GAmES systematically augments cell type-specific 3' ends of RNA polymerase II transcripts and increases the sensitivity of quantitative gene expression profiling by 3' mRNA sequencing. Public access: https://github.com/AmeresLab/3-GAmES.git.
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