AptaCluster - A Method to Cluster HT-SELEX Aptamer Pools and Lessons from its Application.
AptaCluster - A Method to Cluster HT-SELEX Aptamer Pools and Lessons from its Application.
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DOI：
10.1007/978-3-319-05269-4_9
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发表时间：
2014
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通过指数富集进行配体系统进化 (SELEX) 是一种成熟的实验程序，用于鉴定适体 - 与给定分子靶点结合的合成单链（核糖）核分子。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。高吞吐量 SELEX (HT-SELEX) 的出现为该领域带来了新的计算机遇和尚未解决的挑战。为了帮助分析 HT-SELEX 结果并加深对选择过程本身的理解，我们开发了 AptaCluster。该算法允许对整个 HT-SELEX 适体池进行有效聚类；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 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之间的关系进行了调查，并揭示了 SELEX 协议之前未得到重视的特性。作为此类的第一个工具，AptaCluster 提供了分析和优化 HT-SELEX 过程的新颖方法。我们的 AptaCluster 算法可根据要求作为非常快速的多处理器实现提供。
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.