scUTRquant

scUTRquant quantifies alternative 3′ untranslated region (3′UTR) isoforms from single-cell RNA sequencing (scRNA-seq) data to characterize post-transcriptional regulation and 3′ end cleavage site usage.


Key Features:

  • Enhanced 3′ end cleavage site annotations: Incorporates mRNA 3′ end cleavage site (CS) annotations derived from over 200 primary human and mouse cell types, increasing CS annotations by approximately 40% compared to GENCODE.
  • Precision in isoform quantification: Provides rapid, precise, and accurate quantification of gene expression and 3′UTR isoform expression at single-cell resolution using novel computational methodologies.
  • Comprehensive analysis across cell types: Applied to data from 474 distinct cell types and 2,134 perturbations, revealing extensive and variable changes in 3′UTR length that are comparable in prevalence to gene expression changes.

Scientific Applications:

  • Gene regulation insights: Characterizes the dual axes of gene regulation—mRNA abundance and mRNA length—to inform how these factors collectively influence protein synthesis.
  • Single-cell resolution studies: Enables investigation of cell-type-specific regulatory mechanisms and the impact of perturbations on 3′UTR dynamics at single-cell resolution.
  • Biomedical research applications: Maps and quantifies 3′UTR isoforms relevant to diseases where post-transcriptional regulation is critical, such as cancer and genetic disorders.

Methodology:

Integrates enhanced CS annotations with computational algorithms for isoform quantification, processes scRNA-seq data to map 3′ end cleavage sites and categorize distinct isoforms per gene, and analyzes isoform usage across cell types and conditions to identify 3′UTR length variation.

Topics

Details

License:
GPL-3.0
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Mac, Linux, Windows
Programming Languages:
R, Python
Added:
3/28/2022
Last Updated:
3/28/2022

Operations

Publications

Fansler MM, Mitschka S, Mayr C. Comprehensive annotation of 3′UTRs from primary cells and their quantification from scRNA-seq data. Unknown Journal. 2021. doi:10.1101/2021.11.22.469635.

Documentation