A Caltech Library Service

Modeling and automation of sequencing-based characterization of RNA structure

Aviran, Sharon and Trapnell, Cole and Lucks, Julius B. and Mortimer, Stefanie A. and Luo, Shujun and Schroth, Gary P. and Doudna, Jennifer A. and Arkin, Adam P. and Pachter, Lior (2011) Modeling and automation of sequencing-based characterization of RNA structure. Proceedings of the National Academy of Sciences of the United States of America, 108 (27). pp. 11069-11074. ISSN 0027-8424. PMCID PMC3131376.

[img] PDF - Published Version
See Usage Policy.

[img] PDF - Supplemental Material
See Usage Policy.


Use this Persistent URL to link to this item:


Sequence census methods reduce molecular measurements such as transcript abundance and protein-nucleic acid interactions to counting problems via DNA sequencing. We focus on a novel assay utilizing this approach, called selective 2′-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq), that can be used to characterize RNA secondary and tertiary structure. We describe a fully automated data analysis pipeline for SHAPE-Seq analysis that includes read processing, mapping, and structural inference based on a model of the experiment. Our methods rely on the solution of a series of convex optimization problems for which we develop efficient and effective numerical algorithms. Our results can be easily extended to other chemical probes of RNA structure, and also generalized to modeling polymerase drop-off in other sequence census-based experiments.

Item Type:Article
Related URLs:
URLURL TypeDescription CentralArticle Information
Pachter, Lior0000-0002-9164-6231
Additional Information:© 2011 National Academy of Sciences. Freely available online through the PNAS open access option. Contributed by Jennifer A. Doudna, April 29, 2011 (sent for review February 13, 2011) S.A., J.B.L., and A.P.A. acknowledge support from the Synthetic Biology Engineering Research Center under NSF Grant 04-570/0540879. J.A.D. is an Howard Hughes Medical Institute (HHMI) Investigator, and this work was supported in part by the HHMI. S.A.M. is a fellow of the Leukemia and Lymphoma Society. J.B.L. and L.P. thank the Miller Institute for financial support and a stimulating environment in which this work was conceived. Author contributions: S.A., C.T., J.B.L., S.A.M., S.L., G.P.S., J.A.D., A.P.A., and L.P. designed research; S.A., C.T., J.B.L., S.A.M., and L.P. performed research; S.A., C.T., J.B.L., and L.P. contributed new reagents/analytic tools; S.A., C.T., J.B.L., S.A.M., S.L., and L.P. analyzed data; and S.A., C.T., J.B.L., S.A.M., S.L., G.P.S., J.A.D., A.P.A., and L.P. wrote the paper. This article contains supporting information online at The authors declare no conflict of interest.
Funding AgencyGrant Number
Howard Hughes Medical Institute (HHMI)UNSPECIFIED
Leukemia and Lymphoma SocietyUNSPECIFIED
Miller Institute for Basic Research in ScienceUNSPECIFIED
Subject Keywords:signal processing; next generation sequencing; chemical mapping; RNA sequencing; RNA folding
Issue or Number:27
PubMed Central ID:PMC3131376
Record Number:CaltechAUTHORS:20170306-103050792
Persistent URL:
Official Citation:Sharon Aviran, Cole Trapnell, Julius B. Lucks, Stefanie A. Mortimer, Shujun Luo, Gary P. Schroth, Jennifer A. Doudna, Adam P. Arkin, and Lior Pachter Modeling and automation of sequencing-based characterization of RNA structure PNAS 2011 108 (27) 11069-11074; published ahead of print June 3, 2011, doi:10.1073/pnas.1106541108
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:74776
Deposited By: George Porter
Deposited On:06 Mar 2017 18:48
Last Modified:24 Feb 2020 10:30

Repository Staff Only: item control page