J Caroli1, C Taccioli1, A De La Fuente2, P Serafini2, S Bicciato1. 1. Center for Genome Research, Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy and. 2. Department of Microbiology & Immunology, UM/Sylvester Comprehensive Cancer Center, Leonard M. Miller School of Medicine, University of Miami, Miami, FL 33136, USA.
Abstract
MOTIVATION: Aptamers are synthetic nucleic acid molecules that can bind biological targets in virtue of both their sequence and three-dimensional structure. Aptamers are selected using SELEX, Systematic Evolution of Ligands by EXponential enrichment, a technique that exploits aptamer-target binding affinity. The SELEX procedure, coupled with high-throughput sequencing (HT-SELEX), creates billions of random sequences capable of binding different epitopes on specific targets. Since this technique produces enormous amounts of data, computational analysis represents a critical step to screen and select the most biologically relevant sequences. RESULTS: Here, we present APTANI, a computational tool to identify target-specific aptamers from HT-SELEX data and secondary structure information. APTANI builds on AptaMotif algorithm, originally implemented to analyze SELEX data; extends the applicability of AptaMotif to HT-SELEX data and introduces new functionalities, as the possibility to identify binding motifs, to cluster aptamer families or to compare output results from different HT-SELEX cycles. Tabular and graphical representations facilitate the downstream biological interpretation of results. AVAILABILITY AND IMPLEMENTATION: APTANI is available at http://aptani.unimore.it. CONTACT: silvio.bicciato@unimore.it SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Aptamers are synthetic nucleic acid molecules that can bind biological targets in virtue of both their sequence and three-dimensional structure. Aptamers are selected using SELEX, Systematic Evolution of Ligands by EXponential enrichment, a technique that exploits aptamer-target binding affinity. The SELEX procedure, coupled with high-throughput sequencing (HT-SELEX), creates billions of random sequences capable of binding different epitopes on specific targets. Since this technique produces enormous amounts of data, computational analysis represents a critical step to screen and select the most biologically relevant sequences. RESULTS: Here, we present APTANI, a computational tool to identify target-specific aptamers from HT-SELEX data and secondary structure information. APTANI builds on AptaMotif algorithm, originally implemented to analyze SELEX data; extends the applicability of AptaMotif to HT-SELEX data and introduces new functionalities, as the possibility to identify binding motifs, to cluster aptamer families or to compare output results from different HT-SELEX cycles. Tabular and graphical representations facilitate the downstream biological interpretation of results. AVAILABILITY AND IMPLEMENTATION: APTANI is available at http://aptani.unimore.it. CONTACT: silvio.bicciato@unimore.it SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Adriana De La Fuente; Serena Zilio; Jimmy Caroli; Dimitri Van Simaeys; Emilia M C Mazza; Tan A Ince; Vincenzo Bronte; Silvio Bicciato; Donald T Weed; Paolo Serafini Journal: Sci Transl Med Date: 2020-06-17 Impact factor: 19.319
Authors: Khalid K Alam; Jonathan L Chang; Margaret J Lange; Phuong D M Nguyen; Andrew W Sawyer; Donald H Burke Journal: Mol Ther Nucleic Acids Date: 2018-10-24 Impact factor: 8.886