Abstract
Oligonucleotide (oligo)-based FISH has emerged as an important tool for the study of chromosome organization and gene expression and has been empowered by the commercial availability of highly complex pools of oligos. However, a dedicated bioinformatic design utility has yet to be created specifically for the purpose of identifying optimal oligo FISH probe sequences on the genome-wide scale. Here, we introduce OligoMiner, a rapid and robust computational pipeline for the genome-scale design of oligo FISH probes that affords the scientist exact control over the parameters of each probe. Our streamlined method uses standard bioinformatic file formats, allowing users to seamlessly integrate new and existing utilities into the pipeline as desired, and introduces a method for evaluating the specificity of each probe molecule that connects simulated hybridization energetics to rapidly generated sequence alignments using supervised machine learning. We demonstrate the scalability of our approach by performing genome-scale probe discovery in numerous model organism genomes and showcase the performance of the resulting probes with diffraction-limited and single-molecule superresolution imaging of chromosomal and RNA targets. We anticipate that this pipeline will make the FISH probe design process much more accessible and will more broadly facilitate the design of pools of hybridization probes for a variety of applications.
Funder
HHS | National Institutes of Health
DOD | United States Navy | ONR | Office of Naval Research Global
DOD | United States Navy | Office of Naval Research
NSF | National Science Board
Damon Runyon Cancer Research Foundation
Uehara Memorial Foundation
European Molecular Biology Organization
Human Frontier Science Program
Publisher
Proceedings of the National Academy of Sciences
Cited by
178 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献