Article open access publication

RUCS: rapid identification of PCR primers for unique core sequences.

Bioinformatics, Oxford University Press (OUP), ISSN 1367-4811

Volume 33, 24, 2017

DOI:10.1093/bioinformatics/btx526, Dimensions: pub.1091450474, PMC: PMC5860091, PMID: 28968748,

Affiliations

Organisations

  1. (1) Technical University of Denmark, grid.5170.3, DTU
  2. (2) State Serum Institute, grid.6203.7
  3. (3) Hvidovre Hospital, grid.411905.8, Capital Region
  4. (4) University of Copenhagen, grid.5254.6, KU

Countries

Denmark

Continents

Europe

Description

Motivation: Designing PCR primers to target a specific selection of whole genome sequenced strains can be a long, arduous and sometimes impractical task. Such tasks would benefit greatly from an automated tool to both identify unique targets, and to validate the vast number of potential primer pairs for the targets in silico. Results: Here we present RUCS, a program that will find PCR primer pairs and probes for the unique core sequences of a positive genome dataset complement to a negative genome dataset. The resulting primer pairs and probes are in addition to simple selection also validated through a complex in silico PCR simulation. We compared our method, which identifies the unique core sequences, against an existing tool called ssGeneFinder, and found that our method was 6.5-20 times more sensitive. We used RUCS to design primer pairs that would target a set of genomes known to contain the mcr-1 colistin resistance gene. Three of the predicted pairs were chosen for experimental validation using PCR and gel electrophoresis. All three pairs successfully produced an amplicon with the target length for the samples containing mcr-1 and no amplification products were produced for the negative samples. The novel methods presented in this manuscript can reduce the time needed to identify target sequences, and provide a quick virtual PCR validation to eliminate time wasted on ambiguously binding primers. Availability and implementation: Source code is freely available on https://bitbucket.org/genomicepidemiology/rucs. Web service is freely available on https://cge.cbs.dtu.dk/services/RUCS. Contact: mcft@cbs.dtu.dk. Supplementary information: Supplementary data are available at Bioinformatics online.

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NORA University Profiles

Technical University of Denmark

University of Copenhagen

Danish Open Access Indicator

2017: Realized

Research area: Science & Technology

Danish Bibliometrics Indicator

2017: Level 2

Research area: Science & Technology

Dimensions Citation Indicators

Times Cited: 3

Field Citation Ratio (FCR): 1.66

Relative Citation ratio (RCR): 0.32

Open Access Info

Hybrid