Optimized Sequence Library Design for Efficient In Vitro Interaction Mapping

• Main Authors: Puccinelli, Robert (Author), Kim, Ryan (Author), Fordyce, Polly (Author), Orenstein, Yaron (Contributor), Berger Leighton, Bonnie (Contributor)
• Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Mathematics (Contributor)
• Format: Article
• Language: English
• Published: Elsevier, 2018-05-16T13:17:47Z.
• Subjects: Article
• Online Access: Get fulltext

Sequence libraries that cover all k-mers enable universal, unbiased measurements of binding to both oligonucleotides and peptides. While the number of k-mers grows exponentially in k, space on all experimental platforms is limited. Here, we shrink k-mer library sizes by using joker characters, which represent all characters in the alphabet simultaneously. We present the JokerCAKE (joker covering all k-mers) algorithm for generating a short sequence such that each k-mer appears at least p times with at most one joker character per k-mer. By running our algorithm on a range of parameters and alphabets, we show that JokerCAKE produces near-optimal sequences. Moreover, through comparison with data from hundreds of DNA-protein binding experiments and with new experimental results for both standard and JokerCAKE libraries, we establish that accurate binding scores can be inferred for high-affinity k-mers using JokerCAKE libraries. JokerCAKE libraries allow researchers to search a significantly larger sequence space using the same number of experimental measurements and at the same cost. We present a new compact sequence design that covers all k-mers utilizing joker characters and develop an efficient algorithm to generate such designs. We show through simulations and experimental validation that these sequence designs are useful for identifying high-affinity binding sites at significantly reduced cost and space. Keywords: sequence libraries; microarray design; de Bruijn graph
National Institutes of Health (U.S.) (Grant R01GM081871)