Multiplexed SBE primer design for highly polymorphic loci.
Greg Tyrelle1, Daniel Di Giusto2, Garry C. King
1greg@kinglab.unsw.edu.au, UNSW; 2daniel@kinglab.unsw.edu.au, UNSW
Single base extension (SBE) is a valuable technique to analyse single nucleotide polymorphisms (SNPs) for purposes ranging from disease marker analysis to organism identification and quantitation of allelic expression levels. Unlike conventional sequencing, the analysis of a set of SNPs located throughout the genome can easily be achieved by multiplexed SBE (MSBE) in a variety of formats. Increased accuracy in assigning genotypes and low-frequency alleles allows MSBE to be applied to more stringent applications. However, when applied to highly polymorphic regions, SNP-interrogating primers may hybridise to variable sequence DNA, resulting in mismatches that can affect the downstream SBE reaction.
We have used large HLA and patient sample HIV sequence sets as worst-case model systems of highly mutagenic and polymorphic templates to calculate likely outcomes of SBE implementations using software developed in Python. Our software allows for the determination of a minimal and optimized primer set to genotype all required positions for any given SBE application.
We first use an information theoretic approach to derive a consensus sequence from sequence alignments. This consensus is then used as a reference to evaluate the likely data loss due to incorrect hybridisation for individual and global data sets. The software performs a number of iterations to achieve the goal of improving genotyping coverage. The algorithm obtains enhanced coverage by the inclusion of design permutations such as primer redundancy, wobble positions and dual strand typing. We find that this approach can increase potential coverage by 20% or more using these improved primer design parameters.