Systematic refinement of gene annotations by parsing mRNA 3' end sequencing datasets.

Autor:	Bhat P; Institute of Molecular Biotechnology (IMBA), Vienna BioCenter (VBC), Vienna, Austria; Vienna BioCenter PhD Program, Doctoral School of the University at Vienna and Medical University of Vienna, Vienna, Austria., Burkard TR; Institute of Molecular Biotechnology (IMBA), Vienna BioCenter (VBC), Vienna, Austria., Herzog VA; Institute of Molecular Biotechnology (IMBA), Vienna BioCenter (VBC), Vienna, Austria., Pauli A; Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria., Ameres SL; Institute of Molecular Biotechnology (IMBA), Vienna BioCenter (VBC), Vienna, Austria; Max Perutz Labs, University of Vienna, Vienna BioCenter (VBC), Vienna, Austria. Electronic address: stefan.ameres@univie.ac.at.
Jazyk:	angličtina
Zdroj:	Methods in enzymology [Methods Enzymol] 2021; Vol. 655, pp. 205-223. Date of Electronic Publication: 2021 Apr 28.
DOI:	10.1016/bs.mie.2021.03.016
Abstrakt:	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. (Copyright © 2021 Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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