AptaCluster - A method to cluster HT-SELEX aptamer pools and lessons from its application

Jan Hoinka, Alexey Berezhnoy, Zuben E. Sauna, Eli Gilboa, Teresa M. Przytycka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

37 Scopus citations

Abstract

Systematic Evolution of Ligands by EXponential Enrichment (SELEX) is a well established experimental procedure to identify aptamers - synthetic single-stranded (ribo)nucleic molecules that bind to a given molecular target. Recently, new sequencing technologies have revolutionized the SELEX protocol by allowing for deep sequencing of the selection pools after each cycle. The emergence of High Throughput SELEX (HT-SELEX) has opened the field to new computational opportunities and challenges that are yet to be addressed. To aid the analysis of the results of HT-SELEX and to advance the understanding of the selection process itself, we developed AptaCluster. This algorithm allows for an efficient clustering of whole HT-SELEX aptamer pools; a task that could not be accomplished with traditional clustering algorithms due to the enormous size of such datasets. We performed HT-SELEX with Interleukin 10 receptor alpha chain (IL-10RA) as the target molecule and used AptaCluster to analyze the resulting sequences. AptaCluster allowed for the first survey of the relationships between sequences in different selection rounds and revealed previously not appreciated properties of the SELEX protocol. As the first tool of this kind, AptaCluster enables novel ways to analyze and to optimize the HT-SELEX procedure. Our AptaCluster algorithm is available as a very fast multiprocessor implementation upon request.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages115-128
Number of pages14
Volume8394 LNBI
ISBN (Print)9783319052687
DOIs
StatePublished - 2014
Event18th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2014 - Pittsburgh, PA, United States
Duration: Apr 2 2014Apr 5 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8394 LNBI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other18th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2014
CountryUnited States
CityPittsburgh, PA
Period4/2/144/5/14

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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    Hoinka, J., Berezhnoy, A., Sauna, Z. E., Gilboa, E., & Przytycka, T. M. (2014). AptaCluster - A method to cluster HT-SELEX aptamer pools and lessons from its application. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8394 LNBI, pp. 115-128). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8394 LNBI). Springer Verlag. https://doi.org/10.1007/978-3-319-05269-4_9