Differential analysis of gene regulation at transcript resolution with RNA-seq

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• High-throughput RNA sequencing (RNA-seq) presents statistical challenges for differential expression analysis due to measurement variability.
• Accurate transcript-level expression estimation and control for replicate variability are crucial for reliable RNA-seq analysis.

Purpose of the Study:

• To introduce Cuffdiff 2, an algorithm for robust differential analysis of gene and transcript expression from RNA-seq data.
• To demonstrate Cuffdiff 2's capability in identifying differential expression, splicing, and promoter-preference changes at transcript resolution.

Main Methods:

• Development and application of the Cuffdiff 2 algorithm for RNA-seq data analysis.
• Differential analysis of lung fibroblasts and HeLa cells following HOXA1 knockdown.

Main Results:

• Cuffdiff 2 accurately estimates transcript-level expression and controls for library variability.
• The algorithm robustly identifies differentially expressed transcripts and genes, as well as differential splicing and promoter-usage.
• Loss of HOXA1 in lung fibroblasts leads to widespread transcriptomic changes and isoform switching in cell cycle regulators.

Conclusions:

• Cuffdiff 2 provides robust differential analysis for RNA-seq experiments at transcript resolution.
• The algorithm reveals regulatory layers not easily detected by other high-throughput methods.
• HOXA1 is essential for cell cycle progression in lung fibroblasts and HeLa cells.