Literature DB >> 27467247

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

Phuong Dao1, Jan Hoinka1, Mayumi Takahashi2, Jiehua Zhou2, Michelle Ho2, Yijie Wang1, Fabrizio Costa3, John J Rossi2, Rolf Backofen3, John Burnett2, Teresa M Przytycka4.   

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. Published by Elsevier Inc.

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Year:  2016        PMID: 27467247      PMCID: PMC5042215          DOI: 10.1016/j.cels.2016.07.003

Source DB:  PubMed          Journal:  Cell Syst        ISSN: 2405-4712            Impact factor:   10.304


  30 in total

1.  Identification of sequence-structure RNA binding motifs for SELEX-derived aptamers.

Authors:  Jan Hoinka; Elena Zotenko; Adam Friedman; Zuben E Sauna; Teresa M Przytycka
Journal:  Bioinformatics       Date:  2012-06-15       Impact factor: 6.937

2.  APTANI: a computational tool to select aptamers through sequence-structure motif analysis of HT-SELEX data.

Authors:  J Caroli; C Taccioli; A De La Fuente; P Serafini; S Bicciato
Journal:  Bioinformatics       Date:  2015-09-22       Impact factor: 6.937

3.  Large scale analysis of the mutational landscape in HT-SELEX improves aptamer discovery.

Authors:  Jan Hoinka; Alexey Berezhnoy; Phuong Dao; Zuben E Sauna; Eli Gilboa; Teresa M Przytycka
Journal:  Nucleic Acids Res       Date:  2015-04-13       Impact factor: 16.971

4.  RNA recognition by the Vts1p SAM domain.

Authors:  Philip E Johnson; Logan W Donaldson
Journal:  Nat Struct Mol Biol       Date:  2006-01-22       Impact factor: 15.369

Review 5.  Advances in aptamer screening and small molecule aptasensors.

Authors:  Yeon Seok Kim; Man Bock Gu
Journal:  Adv Biochem Eng Biotechnol       Date:  2014       Impact factor: 2.635

6.  High affinity ligands from in vitro selection: complex targets.

Authors:  K N Morris; K B Jensen; C M Julin; M Weil; L Gold
Journal:  Proc Natl Acad Sci U S A       Date:  1998-03-17       Impact factor: 11.205

7.  Multiplexed massively parallel SELEX for characterization of human transcription factor binding specificities.

Authors:  Arttu Jolma; Teemu Kivioja; Jarkko Toivonen; Lu Cheng; Gonghong Wei; Martin Enge; Mikko Taipale; Juan M Vaquerizas; Jian Yan; Mikko J Sillanpää; Martin Bonke; Kimmo Palin; Shaheynoor Talukder; Timothy R Hughes; Nicholas M Luscombe; Esko Ukkonen; Jussi Taipale
Journal:  Genome Res       Date:  2010-04-08       Impact factor: 9.043

8.  AptaCluster - A Method to Cluster HT-SELEX Aptamer Pools and Lessons from its Application.

Authors:  Jan Hoinka; Alexey Berezhnoy; Zuben E Sauna; Eli Gilboa; Teresa M Przytycka
Journal:  Res Comput Mol Biol       Date:  2014

9.  Inferring binding energies from selected binding sites.

Authors:  Yue Zhao; David Granas; Gary D Stormo
Journal:  PLoS Comput Biol       Date:  2009-12-04       Impact factor: 4.475

10.  Evaluation of methods for modeling transcription factor sequence specificity.

Authors:  Matthew T Weirauch; Atina Cote; Raquel Norel; Matti Annala; Yue Zhao; Todd R Riley; Julio Saez-Rodriguez; Thomas Cokelaer; Anastasia Vedenko; Shaheynoor Talukder; Harmen J Bussemaker; Quaid D Morris; Martha L Bulyk; Gustavo Stolovitzky; Timothy R Hughes
Journal:  Nat Biotechnol       Date:  2013-01-27       Impact factor: 54.908

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  16 in total

1.  ssHMM: extracting intuitive sequence-structure motifs from high-throughput RNA-binding protein data.

Authors:  David Heller; Ralf Krestel; Uwe Ohler; Martin Vingron; Annalisa Marsico
Journal:  Nucleic Acids Res       Date:  2017-11-02       Impact factor: 16.971

2.  RaptRanker: in silico RNA aptamer selection from HT-SELEX experiment based on local sequence and structure information.

Authors:  Ryoga Ishida; Tatsuo Adachi; Aya Yokota; Hidehito Yoshihara; Kazuteru Aoki; Yoshikazu Nakamura; Michiaki Hamada
Journal:  Nucleic Acids Res       Date:  2020-08-20       Impact factor: 16.971

Review 3.  In silico design of novel aptamers utilizing a hybrid method of machine learning and genetic algorithm.

Authors:  Mahsa Torkamanian-Afshar; Sajjad Nematzadeh; Maryam Tabarzad; Ali Najafi; Hossein Lanjanian; Ali Masoudi-Nejad
Journal:  Mol Divers       Date:  2021-02-07       Impact factor: 2.943

Review 4.  Applications of High-Throughput Sequencing for In Vitro Selection and Characterization of Aptamers.

Authors:  Nam Nguyen Quang; Gérald Perret; Frédéric Ducongé
Journal:  Pharmaceuticals (Basel)       Date:  2016-12-10

Review 5.  Aptamer Bioinformatics.

Authors:  Andrew B Kinghorn; Lewis A Fraser; Shaolin Lang; Simon Chi-Chin Shiu; Julian A Tanner
Journal:  Int J Mol Sci       Date:  2017-11-24       Impact factor: 5.923

6.  SARNAclust: Semi-automatic detection of RNA protein binding motifs from immunoprecipitation data.

Authors:  Ivan Dotu; Scott I Adamson; Benjamin Coleman; Cyril Fournier; Emma Ricart-Altimiras; Eduardo Eyras; Jeffrey H Chuang
Journal:  PLoS Comput Biol       Date:  2018-03-29       Impact factor: 4.475

7.  Recognizing RNA structural motifs in HT-SELEX data for ribosomal protein S15.

Authors:  Shermin Pei; Betty L Slinger; Michelle M Meyer
Journal:  BMC Bioinformatics       Date:  2017-06-06       Impact factor: 3.169

8.  AptaSUITE: A Full-Featured Bioinformatics Framework for the Comprehensive Analysis of Aptamers from HT-SELEX Experiments.

Authors:  Jan Hoinka; Rolf Backofen; Teresa M Przytycka
Journal:  Mol Ther Nucleic Acids       Date:  2018-04-22       Impact factor: 8.886

9.  SMARTIV: combined sequence and structure de-novo motif discovery for in-vivo RNA binding data.

Authors:  Maya Polishchuk; Inbal Paz; Zohar Yakhini; Yael Mandel-Gutfreund
Journal:  Nucleic Acids Res       Date:  2018-07-02       Impact factor: 16.971

Review 10.  Aptamers: A Review of Their Chemical Properties and Modifications for Therapeutic Application.

Authors:  Tatsuo Adachi; Yoshikazu Nakamura
Journal:  Molecules       Date:  2019-11-21       Impact factor: 4.411

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