Journal article
AnthOligo: automating the design of oligonucleotides for capture/enrichment technologies
BIOINFORMATICS, v 36(15), pp 4353-4356
01 Aug 2020
PMID: 32484858
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
A Summary A number of methods have been devised to address the need for targeted genomic resequencing. One of these methods, region-specific extraction (RSE) is characterized by the capture of long DNA fragments (15-20 kb) by magnetic beads, after enzymatic extension of oligonucleotides hybridized to selected genomic regions. Facilitating the selection of the most appropriate capture oligos for targeting a region of interest, satisfying the properties of temperature (Tm) and entropy (Delta G), while minimizing the formation of primer-dimers in a pooled experiment, is therefore necessary. Manual design and selection of oligos becomes very challenging, complicated by factors such as length of the target region and number of targeted regions. Here we describe, AnthOligo, a web-based application developed to optimally automate the process of generation of oligo sequences used to target and capture the continuum of large and complex genomic regions. Apart from generating oligos for RSE, this program may have wider applications in the design of customizable internal oligos to be used as baits for gene panel analysis or even probes for large-scale comparative genomic hybridization array processes. AnthOligo was tested by capturing the Major Histocompatibility Complex (MHC) of a random sample.
The application provides users with a simple interface to upload an input file in BED format and customize parameters for each task. The task of probe design in AnthOligo commences when a user uploads an input file and concludes with the generation of a result-set containing an optimal set of region-specific oligos. AnthOligo is currently available as a public web application with URL: http://antholigo.chop.edu.
Metrics
Details
- Title
- AnthOligo: automating the design of oligonucleotides for capture/enrichment technologies
- Creators
- Pushkala Jayaraman - College Station Medical CenterTimothy Mosbruger - College Station Medical CenterTaishan Hu - College Station Medical CenterNikolaos G. Tairis - College Station Medical CenterChao Wu - Children's Hospital of PhiladelphiaPeter M. Clark - Johnson & Johnson (United States)Monica D'Arcy - Univ N Carolina, Dept Epidemiol, Chapel Hill, NC 27515 USADeborah Ferriola - College Station Medical CenterKatarzyna Mackiewicz - Medical University of South CarolinaXiaowu Gai - Children's Hospital of Los AngelesDimitrios Monos - University of PennsylvaniaMahdi Sarmady - University of Pennsylvania
- Publication Details
- BIOINFORMATICS, v 36(15), pp 4353-4356
- Publisher
- Oxford Univ Press
- Number of pages
- 4
- Grant note
- P30DK019525 / National Institute of Diabetes and Digestive and Kidney Diseases; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Diabetes & Digestive & Kidney Diseases (NIDDK)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems; Drexel University
- Web of Science ID
- WOS:000592970900021
- Scopus ID
- 2-s2.0-85091807937
- Other Identifier
- 991019356341504721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Industry collaboration
- Domestic collaboration
- Web of Science research areas
- Biochemical Research Methods
- Biotechnology & Applied Microbiology
- Computer Science, Interdisciplinary Applications
- Mathematical & Computational Biology
- Statistics & Probability