Novel computational methods for increasing PCR primer design effectiveness in directed sequencing.

BACKGROUND: Polymerase chain reaction (PCR) is used in directed sequencing for the discovery of novel polymorphisms. As the first step in PCR directed sequencing, effective PCR primer design is crucial for obtaining high-quality sequence data for target regions. Since current computational primer design tools are not fully tuned with stable underlying laboratory protocols, researchers may still be forced to iteratively optimize protocols for failed amplifications after the primers have been ordered. Furthermore, potentially identifiable factors which contribute to PCR failures have yet to be elucidated. This inefficient approach to primer design is further intensified in a high-throughput laboratory, where hundreds of genes may be targeted in one experiment. RESULTS: We have developed a fully integrated computational PCR primer design pipeline that plays a key role in our high-throughput directed sequencing pipeline. Investigators may specify target regions defined through a rich set of descriptors, such as Ensembl accessions and arbitrary genomic coordinates. Primer pairs are then selected computationally to produce a minimal amplicon set capable of tiling across the specified target regions. As part of the tiling process, primer pairs are computationally screened to meet the criteria for success with one of two PCR amplification protocols. In the process of improving our sequencing success rate, which currently exceeds 95% for exons, we have discovered novel and accurate computational methods capable of identifying primers that may lead to PCR failures. We reveal the laboratory protocols and their associated, empirically determined computational parameters, as well as describe the novel computational methods which may benefit others in future primer design research. CONCLUSION: The high-throughput PCR primer design pipeline has been very successful in providing the basis for high-quality directed sequencing results and for minimizing costs associated with labor and reprocessing. The modular architecture of the primer design software has made it possible to readily integrate additional primer critique tests based on iterative feedback from the laboratory. As a result, the primer design software, coupled with the laboratory protocols, serves as a powerful tool for low and high-throughput primer design to enable successful directed sequencing.

The diploid genome sequence of an individual human.

Presented here is a genome sequence of an individual human. It was produced from approximately 32 million random DNA fragments, sequenced by Sanger dideoxy technology and assembled into 4,528 scaffolds, comprising 2,810 million bases (Mb) of contiguous sequence with approximately 7.5-fold coverage for any given region. We developed a modified version of the Celera assembler to facilitate the identification and comparison of alternate alleles within this individual diploid genome. Comparison of this genome and the National Center for Biotechnology Information human reference assembly revealed more than 4.1 million DNA variants, encompassing 12.3 Mb. These variants (of which 1,288,319 were novel) included 3,213,401 single nucleotide polymorphisms (SNPs), 53,823 block substitutions (2-206 bp), 292,102 heterozygous insertion/deletion events (indels)(1-571 bp), 559,473 homozygous indels (1-82,711 bp), 90 inversions, as well as numerous segmental duplications and copy number variation regions. Non-SNP DNA variation accounts for 22% of all events identified in the donor, however they involve 74% of all variant bases. This suggests an important role for non-SNP genetic alterations in defining the diploid genome structure. Moreover, 44% of genes were heterozygous for one or more variants. Using a novel haplotype assembly strategy, we were able to span 1.5 Gb of genome sequence in segments >200 kb, providing further precision to the diploid nature of the genome. These data depict a definitive molecular portrait of a diploid human genome that provides a starting point for future genome comparisons and enables an era of individualized genomic information.