Primer and probe selection for molecular diagnostics is traditionally performed by hypothesis-based science. Basic research on the diagnostic target leads to knowledge of unique genomic regions, which in turn leads to potentially conserved and identifying sequence loci, which in turn leads to potential primer and probe designs. Hypothesized designs are tested against large numbers of samples, and the hypothesis is adjusted if the performance is unacceptable. Particularly in infectious disease, variation of the target across time and geography presents significant challenges to this paradigm. Pattern Genomics’ revolutionary new methodology takes molecular diagnostic design from being an ad hoc task performed by experts with broadly unpredictable costs and timelines to a rapid, robust, broadly-applicable, and cost-effective process enabled by next-generation sequencing and our proprietary Daydreamer™ platform. Our process
- applies to any class of assay targets that can be isolated and sequenced, including viable, non-culturable organisms – metagenomic background matrices are readily accommodated,
- leverages exponential growth of DNA sequence availability from low-cost DNA sequencing capabilities and public DNA sequence data bases,
- analyzes large collections of genomes and quickly produces optimized primers and probes that satisfy complex assay design criteria,
- accommodates whole-genome analysis so that no detailed prior knowledge of the application is necessary, allowing researchers to focus their downstream interpretation efforts on the regions identified by Daydreamer™, and
- enables facile assay updates and refinements by incorporating novel strains via de novo sequencing and re-analysis.
How does Daydreamer™ differentiate itself from tools commonly employed by computational biologists for assay design? In a nutshell, Daydreamer™ is designed to perform the whole assay design process from genomic data in a single shot; other tools handle only certain aspects. Find more details below.
| Software Type | What It Does | Examples | Limitations On Use For Comparative Genomics and Assay Design |
| Primer Design | Selects PCR primers from reference sequence | Primer3+, OMP | Requires pre-selected short stretch of target sequence, may report on matches to other genomes but does not find primers that have the desired pattern of matches |
| Database Search | Finds similar sequences in a database | BLAST, FASTA | Must first pick relatively short sequences to search against database; does not find sequences that have the desired pattern of matches. Slow for large numbers of queries. |
| Read Mapping / Variant Calling | Maps large collections of sequencing reads to target sequence / reports differences between reads and target | Bowtie, BWA (mapping), GATK (variant analysis), Newbler | Optimized for pair wise comparison of genomes; sequence one new genome to find small-scale sequence variations relative to a reference genome. |
| De Novo Genome Assemby | Takes large collection of sequencing reads, assembles consensus sequence and may annotate frequent read variations from consensus | CABOG, Mira, Newbler, Velvet, Soap de novo | Used for assembling a single, new genome, but does not provide information about similarities and differences with other genomes. |
| Whole Genome Alignment | Given one genome sequence, compare to another similar whole genome | MUMmer, Mauve | Optimized for pair wise genome comparison. Inefficient for large numbers of sequences, and de-emphasizes sequences that don’t match. |
