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The PARA-suite: PAR-CLIP specific sequence read simulation and processing.

Andreas Kloetgen¹, Arndt Borkhardt², Jessica I Hoell²

¹Department for Algorithmic Bioinformatics, Heinrich-Heine Universität Düsseldorf, Düsseldorf, Germany; Department of Pediatric Oncology, Hematology and Clinical Immunology, Medical Faculty, Heinrich-Heine Universität Düsseldorf, Düsseldorf, Germany; Computational Biology of Infection Research, Helmholtz Center for Infection Research, Braunschweig, Germany.

|November 5, 2016

Summary

Analyzing photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation (PAR-CLIP) sequencing reads reveals distinct properties. A new toolkit, PARA-suite, improves read alignment and binding site detection accuracy for PAR-CLIP data analysis.

Keywords:

Cross-linking and immunoprecipitation (CLIP)Next-generation sequencing Posttranscriptional regulation RNA-binding proteins Read alignment Read simulation

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Area of Science:

Genomics and Molecular Biology
Bioinformatics and Computational Biology

Background:

Next-generation sequencing (NGS) is crucial in modern biology.
Photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation (PAR-CLIP) identifies genome-wide protein-RNA interactions using deep sequencing.
PAR-CLIP involves specific nucleotide conversions during reverse transcription, influencing sequencing read properties.

Purpose of the Study:

To assess the distinctive properties of PAR-CLIP sequencing reads.
To compare PAR-CLIP reads with regular transcriptome sequencing (RNA-Seq) reads for alignment relevance.
To develop and evaluate tools for improved PAR-CLIP data analysis.

Main Methods:

Developed the PAR-CLIP analyzer suite (PARA-suite) for data analysis.
Included error model inference and PAR-CLIP read simulation within PARA-suite.
Implemented a modified Burrows-Wheeler Aligner for read alignment and CLIP read clustering for binding site detection.

Main Results:

Identified distinct error profiles in PAR-CLIP reads compared to RNA-Seq reads.
Evaluated alignment accuracy of various aligners on simulated PAR-CLIP datasets, identifying optimal settings.
Demonstrated improved alignment and binding site detection accuracy using the PARA-suite on real PAR-CLIP and HITS-CLIP datasets.

Conclusions:

Differences in PAR-CLIP read error profiles necessitate specialized processing.
The PARA-suite enhances the accuracy of both read alignment and binding site detection for PAR-CLIP data.
The developed tools offer significant improvements for analyzing protein-RNA interactions.