An Accurate Method for mRNA 3'End Identification and Gene Expression Analysis

3′READS+ protocol with optimized RNase H digestion and ligation steps

Invention Summary:

Most mRNA genes in eukaryotes contain multiple cleavage and polyadenylation sites (PAS), resulting in alternative cleavage and polyadenylation isoforms with different coding sequences and/or variable 3' untranslated regions. Alternative polyadenylation (APA) is widespread across all eukaryotic species and is recognized as a major mechanism of gene regulation. Correct PAS identification is critical for gene expression analysis and understanding dynamics of gene regulation, including mRNA metabolism, protein expression, protein localization, etc.

While APA can be analyzed by regular RNA-seq methods, they are not designed to identify PASs, leading to incomplete transcriptome analysis. Deep sequencing methods using primers containing oligo(dT) sequence for reverse transcription lead to false PAS identification due to priming at internal regions of transcripts (internal priming problem).

Dr. Tian's team has developed the 3′ region extraction and deep sequencing (3′READS+) method, which is not affected by internal priming. This method reveals the 3' end position of each transcript and is a cost-effective approach to study gene expression.

Using 3′READS and its updated version 3’READS+, Dr. Tian's team has successfully uncovered a sizable fraction of previously overlooked PASs in mammalian genomes and accurately assessed the frequency of APA in different cell types, e.g., HeLa cells (∼50%).


  • Efficient capture of all RNAs with a poly(A) tail ≥10 nt
  • Reliably sequencing of a small amount of total RNA (as low as 100 ng) with high reproducibility
  • Generation of reads with an optimal number of T's (∼13) for accurate identification of genuine PASs avoiding the homopolymer problem in sequencing.

Market Application:

A useful tool to accurately study APA and to analyze gene expression using 3' end reads counting.

Intellectual Property:

Patent pending. Available for licensing or collaboration.

Rutgers ID: S2016-143
Life Sciences
Research Tools
Yong Zhang
Licensing Manager
Bin Tian
Dinghai Zheng