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Detecting differential transcript usage in complex diseases with SPIT.

Beril Erdogdu¹, Ales Varabyou², Stephanie C Hicks³

¹Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA.

Cell Reports Methods

|March 20, 2024

Summary

This summary is machine-generated.

Differential transcript usage (DTU) analysis is crucial for understanding gene expression complexity. A new tool, SPIT, identifies subgroups and their unique DTU events, revealing new insights in schizophrenia.

Keywords:

CP: systems biology DTU RNA-seq alternative splicing complex diseases heterogeneity schizophrenia

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Last Updated: Jun 30, 2025

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Area of Science:

Genomics
Molecular Biology
Computational Biology

Background:

Differential transcript usage (DTU) influences biological diversity and disease pathogenesis.
Analyzing DTU in complex diseases is challenging due to genetic heterogeneity.
Current DTU methods often fail to account for population heterogeneity.

Purpose of the Study:

To develop a statistical tool, SPIT, for identifying subgroups with distinct DTU events.
To address the limitations of existing DTU analysis methods in complex diseases.
To apply SPIT to analyze transcriptomic data from schizophrenia patients.

Main Methods:

Development of the SPIT statistical tool for subgroup identification in DTU.
Comprehensive assessment of SPIT's methodology and performance.
Application of SPIT to RNA sequencing data from human brain samples.

Main Results:

SPIT successfully identifies predominant subgroups within transcript usage data.
The tool reveals distinct sets of DTU events specific to identified subgroups.
Analysis of schizophrenia brain samples uncovered novel DTU events in six candidate genes.

Conclusions:

SPIT provides a robust method for analyzing DTU in heterogeneous populations.
The tool enhances our understanding of transcriptomic complexity in diseases like schizophrenia.
SPIT facilitates the discovery of novel disease-associated molecular mechanisms.