HAMR

HAMR detects and annotates modified ribonucleotides from RNA sequencing (RNA-seq) data to identify epitranscriptomic sites that alter RNA base pairing, structure, and function.

Key Features:

• Detection and classification: Detects and classifies modified nucleotides within RNA sequencing (RNA-seq) datasets.
• Error-exploitation approach: Exploits disruptions of base pairing during RNA sequencing library preparation that induce errors in complementary DNA (cDNA) synthesis to infer modified sites.
• Computational identification: Computationally identifies and analyzes sequencing-induced errors and sequence anomalies to pinpoint candidate nucleotide modifications.
• Retroactive analysis: Applies the computational analysis to various RNA sequencing techniques to re-examine existing datasets.
• High-throughput processing: Performs high-throughput analysis to provide comprehensive coverage across RNA classes, including messenger RNAs.

Scientific Applications:

• Epitranscriptome mapping: Enables genome-wide annotation of RNA modifications across diverse RNA classes from RNA-seq data.
• Posttranscriptional regulation studies: Facilitates investigation of how nucleotide modifications influence RNA structure, stability, and function in gene expression regulation.
• Molecular biology and genetics research: Supports studies in molecular biology and genetics that require identification of modified ribonucleotides.
• Disease mechanism and systems biology: Provides data to explore roles of RNA modifications in cellular function and disease mechanisms within systems biology contexts.

Methodology:

HAMR exploits base-pairing disruptions caused by modified ribonucleotides during RNA sequencing library preparation that generate errors in cDNA synthesis; these sequencing-induced errors are computationally identified and analyzed to infer nucleotide modifications.