Identifying RNA contacts from SHAPE-MaP by partial correlation analysis

Journal Article · Mon Jun 24 04:00:00 EDT 2019 · arXiv.org Repository

OSTI ID:1633236

Tambe, Akshay ^[1]; Doudna, Jennifer ^[1]; Pachter, Lior ^[1]

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1. Univ. of California, Berkeley, CA (United States)

In a recent paper Siegfried et al. published a new sequence-based structural RNA assay that utilizes mutational profiling to detect base pairing (MaP). Output from MaP provides information about both pairing (via reactivities) and contact (via correlations). Reactivities can be coupled to partition function folding models for structural inference, while correlations can reveal pairs of sites that may be in structural proximity. The possibility for inference of 3D contacts via MaP suggests a novel approach to structural prediction for RNA analogous to covariance structural prediction for proteins. We explore this approach and show that partial correlation analysis outperforms na\"ive correlation analysis. Our results should be applicable to a wide range of high-throughput sequencing based RNA structural assays that are under development.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC)
• DOE Contract Number: AC02-05CH11231
• OSTI ID: 1633236
• Journal Information: arXiv.org Repository, Journal Name: arXiv.org Repository Vol. 2014; ISSN 9999-0017
• Publisher: Cornell University
• Country of Publication: United States
• Language: English