Kathryn M. Stephens

Massively parallel sequencing of forensically relevant single nucleotide polymorphisms using TruSeq™ forensic amplicon

The TruSeq™ Forensic Amplicon library preparation protocol, originally designed to attach sequencing adapters to chromatin-bound DNA for chromatin immunoprecipitation sequencing (TruSeq™ ChIP-Seq), was used here to attach adapters directly to amplicons containing markers of forensic interest. In this study, the TruSeq™ Forensic Amplicon library preparation protocol was used to detect 160 single nucleotide polymorphisms (SNPs), including human identification SNPs (iSNPs), ancestry, and phenotypic SNPs (apSNPs) in 12 reference samples. Results were compared with those generated by a second laboratory using the same technique, as well as to those generated by whole genome sequencing (WGS). The genotype calls made using the TruSeq™ Forensic Amplicon library preparation protocol were highly concordant. The protocol described herein represents an effective and relatively sensitive means of preparing amplified nuclear DNA for massively parallel sequencing (MPS).

Targeted sequencing of clade-specific markers from skin microbiomes for forensic human identification

The human skin microbiome is comprised of diverse communities of bacterial, eukaryotic, and viral taxa and contributes millions of additional genes to the repertoire of human genes, affecting human metabolism and immune response. Numerous genetic and environmental factors influence the microbiome composition and as such contribute to individual-specific microbial signatures which may be exploited for forensic applications. Previous studies have demonstrated the potential to associate skin microbial profiles collected from touched items to their individual owner, mainly using unsupervised methods from samples collected over short time intervals. Those studies utilize either targeted 16S rRNA or shotgun metagenomic sequencing to characterize skin microbiomes; however, these approaches have limited species and strain resolution and susceptibility to stochastic effects, respectively. Clade-specific markers from the skin microbiome, using supervised learning, can predict individual identity using skin microbiomes from their respective donors with high accuracy. In this study the hidSkinPlex is presented, a novel targeted sequencing method using skin microbiome markers developed for human identification. The hidSkinPlex (comprised of 286 bacterial (and phage) family-, genus-, species-, and subspecies-level markers), initially was evaluated on three bacterial control samples represented in the panel (i.e., Propionibacterium acnes, Propionibacterium granulosum, and Rothia dentocariosa) to assess the performance of the multiplex. The hidSkinPlex was further evaluated for prediction purposes. The hidSkinPlex markers were used to attribute skin microbiomes collected from eight individuals from three body sites (i.e., foot (Fb), hand (Hp) and manubrium (Mb)) to their host donor. Supervised learning, specifically regularized multinomial logistic regression and 1-nearest-neighbor classification were used to classify skin microbiomes to their hosts with up to 92% (Fb), 96% (Mb), and 100% (Hp) accuracy. All samples (n=72) regardless of body site origin were correctly classified with up to 94% accuracy, and body site origin could be predicted with up to 86% accuracy. Finally, human short tandem repeat and single-nucleotide polymorphism profiles were generated from skin swab extracts from a single subject to highlight the potential to use microbiome profiling in conjunction with low-biomass samples. The hidSkinPlex is a novel targeted enrichment approach to profile skin microbiomes for human forensic identification purposes and provides a method to further characterize the utility of skin microflora for human identification in future studies, such as the stability and diversity of the personal skin microbiome.

Abstract 3607: An evaluation of NGS to identify gene fusions using RNA from FFPE solid tumor samples

Gene fusions have long been considered strong drivers of cellular transformation, making the accurate and precise assessment of these variants a necessity for any tumor profiling assay. Recent studies have indicated the utility of next-generation sequencing (NGS) for tumor profiling due to increasing data output and decreasing costs of the technology. Unfortunately, because a critical facet of NGS is the evaluation of short DNA fragments, sufficiently covering all possible breakpoint regions (many of which are intronic) has proven difficult and costly. Recent studies have indicated that NGS may prove better at detecting gene fusions using RNA instead of DNA, given the higher probability of breakpoint-spanning reads. This allows for de-novo discovery of fusion partners without knowing the precise breakpoint and guarantees expression of the fusion transcript. To that end, Illumina is developing a novel method for simultaneous library preparation from low input amounts of degraded DNA and RNA from a single FFPE tumor sample. With a turnaround time from nucleic acid to data of less than 4 days, this enrichment-based assay surveys 170 genes for single nucleotide variants and small indels, 57 genes for gene amplifications, 55 genes for fusions and four genes for splice variants. To determine the limit of detection for gene fusions, a panel of different synthetic RNA transcripts were prepared in vitro, pooled at equal molar amounts, and spiked into 20ng of cell line RNA (MCF-7). Fusions were detected over several orders of magnitude down to 1×10-8 picomoles, equivalent to 3 to 15 fusion transcripts per cell. In addition, a similar range of fusion detection was observed when RNA from two different cell lines were mixed, as when RNA from a cell line with high expression of an FGFR2-COL14A1 fusion was mixed in proportional amounts with RNA from a different cell line where FGFR2 is minimally expressed. Importantly, our method allowed for fusion detection from as little as 100 picograms of cell line RNA. We then tested our new method on previously characterized FFPE solid tumor samples harboring known gene rearrangements identified by FISH and other methods. Not only was the NGS method able to detect the majority of previously characterized variants, including EML4-ALK and SDC4-ROS1, it also identified the gene fusions and their uncharacterized fusions partners by combining the non-targeted sequence information gained from using an enrichment-based assay with novel fusion calling algorithms. From this information, we were able to glean new insights into the structure of the rearrangements and how the gene fusions may be involved in tumorigenesis. These results indicate that NGS can identify fusions from the low amounts of degraded RNA from solid tumor samples, identify fusion partners not uncovered by current technologies, and further emphasizes the advantage of NGS in solid tumor profiling. Citation Format: Julianna Tdr Parks, Luo Byron, Brian Crain, Snedecor June, Zhao Chen, Tingting Du, Gabriel L. Sica, Taofee K. Owonikoko, Stewart G. Neill, Scott Newman, Debra F. Saxe, Jennifer S. LoCoco, Han-Yu Chuang, Charles Lin, Kathryn M. Stephens, Michael R. Rossi, Matthew C. Friedenberg. An evaluation of NGS to identify gene fusions using RNA from FFPE solid tumor samples. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3607.

Abstract 3624: Development of a comprehensive and highly sensitive next-generation sequencing assay for detection of copy number variations

Background: As our knowledge of how DNA alterations can drive cancer progression increases, assays that can simultaneously detect multiple types of variants in a simple and cost-effective manner are becoming increasingly crucial. This holds true of copy number variations (CNVs), where evaluation of this type of variant is an important and necessary feature of any solid tumor profiling assay. Conventional methods for detecting CNVs such as immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), and quantitative PCR (qPCR) are limited to detecting only one gene amplification at a time. This can be a significant drawback with FFPE samples, where the DNA is of low abundance and often heavily degraded, while the number of gene amplifications known to be important in cancer continues to grow. Additionally, different tumor types may express amplifications at different rates and expression may be heterogeneous within the tumor, potentially with irregular staining patterns - all of which illustrate the need for new approaches to CNV detection. Methods: Next-generation sequencing (NGS) offers the ability to assess variants in multiple genes using one sample. To that end, Illumina is developing a comprehensive, hybrid capture-based NGS assay targeting 170 key cancer genes for sequencing on the NextSeq 1 platform. The assay consists of a DNA workflow for the identification of single-nucleotide variants (SNVs), small insertions and deletions (indels), as well as an RNA workflow for the identification of splice variants and gene fusions. In addition, using the DNA workflow, a novel analysis pipeline, and CNV caller, CNVs from 57 different genes can be simultaneously assessed all by sequencing of a single sample. Results: Here we present data on both cell lines and FFPE samples of SNVs and indels down to 5% allele fraction and CNVs down to ∼2-fold amplification, all from 40 ng of DNA. To demonstrate the accuracy and precision of our CNV detection method, we tested 7 samples for CNVs using orthogonal CNV detection methods. The Illumina NGS assay detected ERBB2 amplifications in 4 out of 7 samples. Of the 4 Illumina NGS positive samples, 3 samples were positive by FISH and all 4 were positive by droplet digital PCR (ddPCR) and the Illumina TruSight Tumor 15 panel. The 3 samples that were negative for ERBB2 amplifications by the Illumina NGS assay were also negative by both FISH and ddPCR. Within these samples we also found a previously unknown FGFR1 amplification. Conclusions: The novel Illumina NGS library preparation method is an innovative and useful tool to find multiple CNVs, along with other variant types, within a single sample. The assay can detect multiple CNVs within a single FFPE sample and identify previously uncharacterized CNVs that could be important in finding the correct treatment for a cancer patient. Citation Format: Chia-Ling Hsieh, Clare Zlatkov, Byron Luo, Chen Zhao, Kathryn Stephens, Han-Yu Chuang, Lisa Kelly, Katherine Chang, Rachel Liang, Jianli Cao, Scott Lang, Ashley Adams, Naseem Ajili, Laurel Ball, Glorianna Caves, Danny Chou, Katie Clark, Brian Crain, Anthony Daulo, Sarah Dumm, Ridwana Ekram, Yonmee Han, Anne Jager, Suzanne Johansen, Li Teng, Jenn Lococo, Jaime McLean, Juli Parks, Jason Rostron, Jennifer Sayne, Jennifer Silhavy, June Snedecor, Mckenzi Toh, Stephanie Tong, Elizabeth Upsall, Paulina Walichiewicz, Xiao Chen, Amanda Young, Ali Kuraishy, Karen Gutekunst, Matt Friedenberg, Charles Lin. Development of a comprehensive and highly sensitive next-generation sequencing assay for detection of copy number variations. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3624.