EXPRSS: an Illumina based high-throughput expression-profiling method to reveal transcriptional dynamics.

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Next Generation Sequencing (NGS) enables gene expression analysis via RNA-seq and Tag-seq.
• RNA-seq faces challenges with transcript length bias, non-uniform coverage, and high read requirements.
• Existing Tag-seq methods often suffer from biases, low throughput, or reliance on enzymatic manipulation and RNA ligations.

Purpose of the Study:

• To develop a novel, high-throughput, and bias-free method for gene expression profiling.
• To overcome limitations of current RNA-seq and Tag-seq technologies.
• To introduce a cost-effective and reliable gene expression analysis technique.

Main Methods:

• Developed EXpression Profiling through Randomly Sheared cDNA tag Sequencing (EXPRSS).
• Utilizes acoustic waves for random cDNA shearing, generating sequence tags near the 3' end of mRNA (~150-200 bp).
• EXPRSS is strand-specific, restriction enzyme-independent, and does not require cDNA length normalization.

Main Results:

• EXPRSS demonstrated high reproducibility and throughput.
• Comparative analysis validated EXPRSS against NlaIII-DGE, Affymetrix microarray, and qPCR.
• The method identified alternative polyadenylation and polyadenylated antisense transcripts.
• EXPRSS is cost-effective through barcoded multiplexing and avoids biases of SAGE-like methods.

Conclusions:

• EXPRSS Tag-seq provides sensitive and reliable gene expression data.
• Enables high-throughput expression profiling with simplified downstream analysis.
• Offers a robust alternative for accurate gene expression studies.