Aptamers are identified through an iterative process of evolutionary selection starting from a random pool containing billions of sequences. Simultaneously to the amplification of high-affinity candidates, the diversity in the pool is exponentially reduced after several rounds of in vitro selection. Until now, cloning and Sanger sequencing of about 100 sequences was usually used to identify the enriched candidates. However, High-Throughput Sequencing (HTS) is now extensively used to replace such low throughput sequencing approaches. Providing a deeper analysis of the library, HTS is expected to accelerate the identification of aptamers as well as to identify aptamers with higher affinity. It is also expected that it can provide important information on the binding site of the aptamers. Nevertheless, HTS requires handling a large amount of data that is only possible through the development of new in silico methods. Here, this review presents these different strategies that have been recently developed to improve the identification and characterization of aptamers using HTS.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited