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

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.