Using Computational Analysis of Frequencies and Genomic Locations of 6-8 Nucleotide Long Sequences to Improve Quality of DNA Amplification

Random primer amplification (RPA) is a technique widely used in a variety of genomic studies. Nonrandom distribution of short sequences across Human, animal, and bacterial genomes, however, causes bias which affects the amplification process and downstream analysis. The presented work focuses on computational strategies to explore statistical properties of the frequencies and location distributions of all possible short subsequences (6-8 mers) in human, animal, and bacterial genomes and use them to guide the primer design process in order to: reduce bias in single genome (human/animal) amplification and perform preferential microbial enrichment in the presence of host DNA.