Hoinka Jan, Berezhnoy Alexey, Sauna Zuben E, Gilboa Eli, Przytycka Teresa M
National Center of Biotechnology Information, National Library of Medicine, NIH, Bethesda MD 20894, USA.
Department of Microbiology & Immunology, University of Miami Miller School of Medicine, Miami, Florida 33101, USA.
Res Comput Mol Biol. 2014;8394:115-128. doi: 10.1007/978-3-319-05269-4_9.
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.
指数富集配体系统进化技术（SELEX）是一种成熟的实验方法，用于鉴定适配体——与特定分子靶标结合的合成单链（核糖）核酸分子。最近，新的测序技术彻底改变了SELEX方案，允许在每个循环后对选择池进行深度测序。高通量SELEX（HT-SELEX）的出现为新的计算机遇和挑战开辟了领域，这些机遇和挑战尚待解决。为了辅助分析HT-SELEX的结果并增进对选择过程本身的理解，我们开发了AptaCluster算法。该算法能够对整个HT-SELEX适配体池进行高效聚类；由于此类数据集规模巨大，传统聚类算法无法完成这项任务。我们以白细胞介素10受体α链（IL-10RA）作为靶分子进行了HT-SELEX，并使用AptaCluster分析所得序列。AptaCluster首次对不同选择轮次中的序列关系进行了研究，揭示了SELEX方案此前未被认识到的特性。作为此类的首个工具，AptaCluster为分析和优化HT-SELEX程序提供了新方法。我们的AptaCluster算法可应要求作为非常快速的多处理器实现版本提供。
