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Cell Syst. 2016 Jul;3(1):62-70. doi: 10.1016/j.cels.2016.07.003.

AptaTRACE Elucidates RNA Sequence-Structure Motifs from Selection Trends in HT-SELEX Experiments.

Author information

1
National Center of Biotechnology Information, National Library of Medicine, NIH, Bethesda, MD 20894, USA.
2
Department of Molecular and Cellular Biology, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA.
3
Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg 79110, Germany.
4
National Center of Biotechnology Information, National Library of Medicine, NIH, Bethesda, MD 20894, USA. Electronic address: przytyck@ncbi.nlm.nih.gov.

Abstract

Aptamers, short RNA or DNA molecules that bind distinct targets with high affinity and specificity, can be identified using high-throughput systematic evolution of ligands by exponential enrichment (HT-SELEX), but scalable analytic tools for understanding sequence-function relationships from diverse HT-SELEX data are not available. Here we present AptaTRACE, a computational approach that leverages the experimental design of the HT-SELEX protocol, RNA secondary structure, and the potential presence of many secondary motifs to identify sequence-structure motifs that show a signature of selection. We apply AptaTRACE to identify nine motifs in C-C chemokine receptor type 7 targeted by aptamers in an in vitro cell-SELEX experiment. We experimentally validate two aptamers whose binding required both sequence and structural features. AptaTRACE can identify low-abundance motifs, and we show through simulations that, because of this, it could lower HT-SELEX cost and time by reducing the number of selection cycles required.

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