saskPrimer - an automated pipeline for design of intron-spanning PCR primers in non-model organisms

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Proceedings title2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)
ConferenceThird International Workshop on Data Mining for Biomarker Discovery, 12-15 November 2011, Atlanta, GA, USA
Pages173177; # of pages: 5
Subjectsingle nucleotide polymorphism; SNP; primer; pipeline
AbstractRobust and automated Polymerase Chain Reaction (PCR) primer design is an important pre-requisite to many strategies of large scale discovery of nucleotide variation, specifically Single Nucleotide Polymorphisms (SNPs). In many cases the design of PCR primers that amplify multiple members of gene families in complex genomes is complicated by the desire to design primers that amplify non-coding regions of the target organism’s genome. This is especially complicated in organisms that do not have a fully sequenced genome, requiring further time intensive procedures. Thus, this phase of SNP discovery is often a bottle-neck for the overall process. In order to increase the efficiency of designing conserved intron-spanning gene family specific primers, an automated pipeline that streamlines the process by reducing the dependency on human participation was developed. The automated design process is proven to significantly reduce primer design time and human participation in comparison to the semiautomated approach employed previously. The increase in performance comes with a modest reduction in overall PCR efficiency but does not significantly reduce the total number of amplified PCR products. The pipeline was tested extensively using the target organism Brassica napus with the reference organism Arabidopsis thaliana, with an overall amplification success of 80.5% of the reference inputs.
Publication date
AffiliationNRC Plant Biotechnology Institute; National Research Council Canada
Peer reviewedYes
NRC number54641
NPARC number19625613
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Record identifierb8e3c867-2b90-47c5-be22-d916fe934256
Record created2012-03-30
Record modified2016-05-09
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