Optimized Sequence Library Design for Efficient In Vitro Interaction Mapping
Name
1-s2.0-S2405471217303320-main.pdf
Size
2.4 MB
Format
Adobe PDF
Checksum (MD5)
a7fa78bdde74ed07adaea617a07f8a48
Author(s)
Puccinelli, Robert
Kim, Ryan
Fordyce, Polly
Orenstein, Yaron
Berger Leighton, Bonnie
Date Issued
September 2017
Journal
Cell Systems
Publisher
Elsevier
Citation
Orenstein, Yaron et al. “Optimized Sequence Library Design for Efficient In Vitro Interaction Mapping.” Cell Systems 5, 3 (September 2017): 230–236 © 2017 The Authors
Version
Final published version
Abstract
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
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Mathematics
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/J.CELS.2017.07.006
