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A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

Published on: October 28, 2025

GeneExt: a gene model extension tool for enhanced single-cell RNA-seq analysis.

Grygoriy Zolotarov^1,2, Xavier Grau-Bové¹, Arnau Sebé-Pedrós^1,2,3,4

¹Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.

Bioinformatics (Oxford, England)

|March 2, 2026

Summary

This summary is machine-generated.

GeneExt refines gene annotations using single-cell RNA sequencing (scRNA-seq) data, improving gene detection in non-model organisms. This enhances biological interpretation and cross-species comparisons of single-cell atlases.

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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Inaccurate gene annotations, especially 3' end transcriptions, hinder single-cell gene expression quantification.
This issue is pronounced in non-model species, leading to undetected or misquantified genes.
Current single-cell RNA sequencing (scRNA-seq) methods primarily capture the 3' transcript region, exacerbating annotation problems.

Purpose of the Study:

To introduce GeneExt, a novel tool for refining gene annotations using scRNA-seq data.
To demonstrate the utility of GeneExt in improving gene expression quantification.
To enhance biological interpretation and facilitate cross-species comparisons of single-cell atlases.

Main Methods:

GeneExt utilizes scRNA-seq data to extend and homogenize gene annotations.
The tool's application was exemplified across eight non-model organism single-cell atlases.
Performance was evaluated based on improvements in gene detection and quantification.

Main Results:

GeneExt successfully refined gene annotations in multiple non-model organisms.
The tool demonstrated significant improvements in gene expression quantification.
Extended and homogenized annotations facilitated better biological insights.

Conclusions:

GeneExt effectively addresses limitations in gene annotation for scRNA-seq analysis.
The tool enhances the accuracy and comparability of single-cell expression data, particularly for non-model species.
GeneExt is a valuable resource for advancing single-cell genomics research.