Sequencing Technology

The Druley lab is focused on the translational characterization of genetic and epigenetic variation in complex disease, particularly pediatric cancer. This has been accomplished through the development and application of novel methodology such as pooled DNA sequencing, indexed hybridization capture and targeted error-corrected sequencing.

With the emergence of next-generation sequencing, but prior to the advent of individual sample indexing, we developed SNPseeker to detect single-nucleotide polymorphisms from non-indexed, pooled human genomic DNA. Based in large deviation theory, this method is capable of identifying rare single nucleotide variants below the raw error rate of massively parallel sequencing (Druley TE, Nat Methods 2009). This led us to develop SPLINTER to further improve the detection of substitutions as well as short INDELs in pooled DNA libraries. This method utilizes a synthetic DNA library inserted in each sequencing experiment to measure run-to-run variability and improve variant calling (Vallania FL, Genome Res 2010). With the addition of individual sample indexing and hybridization capture, we were able to apply this strategy for pooled exome sequencing with high accuracy and reduced cost (Ramos E, BMC Genomics 2012). More recently, we have incorporated BACs for hybridization, entitled Multiplexed Direct Genomic Selection(MDiGS),  to enable targeted sequencing of large coding and non-coding regions (Alvarado DM, Nuceic Acids Res 2014].

Additionally, with the increased recognition of subclonal heterogeneity in hematologic malignancies, the lab has developed methods for error-corrected sequencing to study the role of rare subclones in hematopoietic disease. We developed these methods because studying rare subclonal variation using conventional next-generation sequencing (NGS) is not feasible given its error profile (~1%). We are able to circumvent the error rate of NGS by tagging individual DNA molecules with a unique oligonucleotide index (molecular barcode). Multiple copies of each molecule will have the same index and are sequenced in parallel. Reads having the same index are then amalgamated bioinformatically to identify, and remove, sequencing errors. True sequence variants are then called from these error-corrected consensus sequences. We have applied these methods using PCR-based targeting to study the role of each TP53 mutations in the development of therapy-related AML in collaboration with Daniel Link (Wong TN, Nature 2014). A detailed manuscript outlining the methodology and our benchmarking experiments was recently published at Leukemia (Young AL, Leukemia 2015).