TEISER

TEISER decodes post-transcriptional regulatory elements by identifying informative RNA sequence and secondary-structure motifs that influence transcript stability, alternative splicing, and localization.

Key Features:

• Context-free grammars and mutual information: TEISER employs context-free grammars combined with mutual information to systematically search for small structural elements within RNA sequences.
• Integration of structural and sequence data: TEISER captures and combines local RNA secondary-structure information with underlying sequence to characterize regulatory elements.
• Discovery of significant elements: Applied to genome-wide human mRNA stability data, TEISER identified eight highly significant structural elements, including one with a major role in global mRNA regulation.
• Identification of key regulators: TEISER facilitated discovery of HNRPA2B1 as a regulator binding one identified element, supported by biochemistry, mass spectrometry, and in vivo binding studies.
• Global regulatory mapping: TEISER enables mapping of linear and structural cis-regulatory elements, their interactions, and associated target pathways to define post-transcriptional regulatory programs.

Scientific Applications:

• Predictive modeling of cellular behavior: Use TEISER-derived elements to build models linking post-transcriptional regulation to cellular phenotypes.
• Analysis of mRNA stability and processing: Apply TEISER to study mechanisms controlling transcript stability, alternative splicing, and localization.
• Identification of RNA-binding protein targets: Use TEISER outputs to discover and validate RNA-binding proteins (for example HNRPA2B1) and their target repertoires.
• Regulatory network and pathway mapping: Integrate TEISER-identified cis-regulatory elements into pathway analyses to reveal affected target pathways.

Methodology:

TEISER uses context-free grammars combined with mutual information to detect informative small structural RNA motifs and integrates local secondary-structure information with sequence data, applied to genome-wide human mRNA stability datasets.