Billy Lau

Haplotyping germline and cancer genomes with high-throughput linked-read sequencing

Haplotyping of human chromosomes is a prerequisite for cataloguing the full repertoire of genetic variation. We present a microfluidics-based, linked-read sequencing technology that can phase and haplotype germline and cancer genomes using nanograms of input DNA. This high-throughput platform prepares barcoded libraries for short-read sequencing and computationally reconstructs long-range haplotype and structural variant information. We generate haplotype blocks in a nuclear trio that are concordant with expected inheritance patterns and phase a set of structural variants. We also resolve the structure of the EML4-ALK gene fusion in the NCI-H2228 cancer cell line using phased exome sequencing. Finally, we assign genetic aberrations to specific megabase-scale haplotypes generated from whole-genome sequencing of a primary colorectal adenocarcinoma. This approach resolves haplotype information using up to 100 times less genomic DNA than some methods and enables the accurate detection of structural variants.

High Sensitivity Detection and Quantitation of DNA Copy Number and Single Nucleotide Variants with Single Color Droplet Digital PCR

In this study, we present a highly customizable method for quantifying copy number and point mutations utilizing a single-color, droplet digital PCR platform. Droplet digital polymerase chain reaction (ddPCR) is rapidly replacing real-time quantitative PCR (qRT-PCR) as an efficient method of independent DNA quantification. Compared to quantative PCR, ddPCR eliminates the needs for traditional standards; instead, it measures target and reference DNA within the same well. The applications for ddPCR are widespread including targeted quantitation of genetic aberrations, which is commonly achieved with a two-color fluorescent oligonucleotide probe (TaqMan) design. However, the overall cost and need for optimization can be greatly reduced with an alternative method of distinguishing between target and reference products using the nonspecific DNA binding properties of EvaGreen (EG) dye. By manipulating the length of the target and reference amplicons, we can distinguish between their fluorescent signals and quantify each independently. We demonstrate the effectiveness of this method by examining copy number in the proto-oncogene FLT3 and the common V600E point mutation in BRAF. Using a series of well-characterized control samples and cancer cell lines, we confirmed the accuracy of our method in quantifying mutation percentage and integer value copy number changes. As another novel feature, our assay was able to detect a mutation comprising less than 1% of an otherwise wild-type sample, as well as copy number changes from cancers even in the context of significant dilution with normal DNA. This flexible and cost-effective method of independent DNA quantification proves to be a robust alternative to the commercialized TaqMan assay.

CRISPR–Cas9-targeted fragmentation and selective sequencing enable massively parallel microsatellite analysis

Microsatellites are multi-allelic and composed of short tandem repeats (STRs) with individual motifs composed of mononucleotides, dinucleotides or higher including hexamers. Next-generation sequencing approaches and other STR assays rely on a limited number of PCR amplicons, typically in the tens. Here, we demonstrate STR-Seq, a next-generation sequencing technology that analyses over 2,000 STRs in parallel, and provides the accurate genotyping of microsatellites. STR-Seq employs in vitro CRISPR–Cas9-targeted fragmentation to produce specific DNA molecules covering the complete microsatellite sequence. Amplification-free library preparation provides single molecule sequences without unique molecular barcodes. STR-selective primers enable massively parallel, targeted sequencing of large STR sets. Overall, STR-Seq has higher throughput, improved accuracy and provides a greater number of informative haplotypes compared with other microsatellite analysis approaches. With these new features, STR-Seq can identify a 0.1% minor genome fraction in a DNA mixture composed of different, unrelated samples.

Linked read sequencing resolves complex genomic rearrangements in gastric cancer metastases

BackgroundGenome rearrangements are critical oncogenic driver events in many malignancies. However, the identification and resolution of the structure of cancer genomic rearrangements remain challenging even with whole genome sequencing.MethodsTo identify oncogenic genomic rearrangements and resolve their structure, we analyzed linked read sequencing. This approach relies on a microfluidic droplet technology to produce libraries derived from single, high molecular weight DNA molecules, 50 kb in size or greater. After sequencing, the barcoded sequence reads provide long range genomic information, identify individual high molecular weight DNA molecules, determine the haplotype context of genetic variants that occur across contiguous megabase-length segments of the genome and delineate the structure of complex rearrangements. We applied linked read sequencing of whole genomes to the analysis of a set of synchronous metastatic diffuse gastric cancers that occurred in the same individual.ResultsWhen comparing metastatic sites, our analysis implicated a complex somatic rearrangement that was present in the metastatic tumor. The oncogenic event associated with the identified complex rearrangement resulted in an amplification of the known cancer driver gene FGFR2. With further investigation using these linked read data, the FGFR2 copy number alteration was determined to be a deletion-inversion motif that underwent tandem duplication, with unique breakpoints in each metastasis. Using a three-dimensional organoid tissue model, we functionally validated the metastatic potential of an FGFR2 amplification in gastric cancer.ConclusionsOur study demonstrates that linked read sequencing is useful in characterizing oncogenic rearrangements in cancer metastasis.

Chromosome-scale mega-haplotypes enable digital karyotyping of cancer aneuploidy

Abstract Genomic instability is a frequently occurring feature of cancer that involves large-scale structural alterations. These somatic changes in chromosome structure include duplication of entire chromosome arms and aneuploidy where chromosomes are duplicated beyond normal diploid content. However, the accurate determination of aneuploidy events in cancer genomes is a challenge. Recent advances in sequencing technology allow the characterization of haplotypes that extend megabases along the human genome using high molecular weight (HMW) DNA. For this study, we employed a library preparation method in which sequence reads have barcodes linked to single HMW DNA molecules. Barcode-linked reads are used to generate extended haplotypes on the order of megabases. We developed a method that leverages haplotypes to identify chromosomal segmental alterations in cancer and uses this information to join haplotypes together, thus extending the range of phased variants. With this approach, we identified mega-haplotypes that encompass entire chromosome arms. We characterized the chromosomal arm changes and aneuploidy events in a manner that offers similar information as a traditional karyotype but with the benefit of DNA sequence resolution. We applied this approach to characterize aneuploidy and chromosomal alterations from a series of primary colorectal cancers.

Single molecule counting and assessment of random molecular tagging errors with transposable giga-scale error-correcting barcodes

BackgroundRNA-Seq measures gene expression by counting sequence reads belonging to unique cDNA fragments. Molecular barcodes commonly in the form of random nucleotides were recently introduced to improve gene expression measures by detecting amplification duplicates, but are susceptible to errors generated during PCR and sequencing. This results in false positive counts, leading to inaccurate transcriptome quantification especially at low input and single-cell RNA amounts where the total number of molecules present is minuscule.To address this issue, we demonstrated the systematic identification of molecular species using transposable error-correcting barcodes that are exponentially expanded to tens of billions of unique labels.ResultsWe experimentally showed random-mer molecular barcodes suffer from substantial and persistent errors that are difficult to resolve. To assess our method’s performance, we applied it to the analysis of known reference RNA standards. By including an inline random-mer molecular barcode, we systematically characterized the presence of sequence errors in random-mer molecular barcodes. We observed that such errors are extensive and become more dominant at low input amounts.ConclusionsWe described the first study to use transposable molecular barcodes and its use for studying random-mer molecular barcode errors. Extensive errors found in random-mer molecular barcodes may warrant the use of error correcting barcodes for transcriptome analysis as input amounts decrease.

Joint single cell DNA-Seq and RNA-Seq of gastric cancer reveals subclonal signatures of genomic instability and gene expression

Sequencing the genomes of individual cancer cells provides the highest resolution of intratumoral heterogeneity. To enable high throughput single cell DNA-Seq across thousands of individual cells per sample, we developed a droplet-based, automated partitioning technology for whole genome sequencing. We applied this approach on a set of gastric cancer cell lines and a primary gastric tumor. In parallel, we conducted a separate single cell RNA-Seq analysis on these same cancers and used copy number to compare results. This joint study, covering thousands of single cell genomes and transcriptomes, revealed extensive cellular diversity based on distinct copy number changes, numerous subclonal populations and in the case of the primary tumor, subclonal gene expression signatures. We found genomic evidence of positive selection – where the percentage of replicating cells per clone is higher than expected – indicating ongoing tumor evolution. Our study demonstrates that joining single cell genomic DNA and transcriptomic features provides novel insights into cancer heterogeneity and biology. SIGNIFICANCE We conducted a massively parallel DNA sequencing analysis on a set of gastric cancer cell lines and a primary gastric tumor in combination with a joint single cell RNA-Seq analysis. This joint study, covering thousands of single cell genomes and transcriptomes, revealed extensive cellular diversity based on distinct copy number changes, numerous subclonal populations and in the case of the primary tumor, subclonal gene expression signatures. We found genomic evidence of positive selection where the percentage of replicating cells per clone is higher than expected indicating ongoing tumor evolution. Our study demonstrates that combining single cell genomic DNA and transcriptomic features provides novel insights into cancer heterogeneity and biology.

Abstract 438: High-quality CNV segments from low-coverage whole genome sequencing from FFPE cancer biopsies based on an evaluation of multiple CNV tools

Changes in DNA copy number, i.e., somatic CNVs, are common genetic aberrations in cancers. The effects of CNV include alteration in gene dosage across large segments of the cancer genome affecting the expression of cancer driver genes by amplifications, or cancer suppressor genes by deletions. In addition, CNVs are markers of underlying rearrangements within or between chromosomes and there is increasing evidence supporting a greater role for CNVs in developing and maintaining neoplastic cell population diversity. Copy number aberrations can be estimated from next generation sequencing data, with high sensitivity and genomic resolution by sequencing the whole genome (WGS). For this study, we demonstrated that high quality CNV calls can be extracted in a fast and cost-effective way from low-coverage whole genome sequencing. Novaseq S2 flowcells (Illumina Inc) enables to obtain an average coverage of 3-4x per sample after pooling up to 96 samples per flowcell. We examined three different copy number detection tools (CNVkit, BicSeq, and seqCBS) from paired tumor and normal WGS using microarray data as a reference. Pearson correlations were computed between the reference and CNVs from the WGS in two fashion; i) segment based and ii) gene based. The segment based comparison used sliding window of 100 K bp while gene based comparison used segments at the gene level. We found high correlations between microarray and WGS segments. The highest correlations were obtained by CNVkit, ranging from 0.964 to 0.985 (SD: 0.973 - 0.007) and BicSeq, ranging from 0.963 to 0.986 (SD: 0.975 - 0.008). These results open the prospect of assessing large cancer cohorts of hundreds of samples at a reasonable cost. We are planning to apply this method to a large cohort of Stage III colon cancer patients and determine the clinical relevance of CNVs for survival. Citation Format: HoJoon Lee, Li Charlie Xia, Stephanie Greer, John Bell, Sue M. Grimes, Christina Wood Bouwens, Giwon Shin, Billy TC Lau, Lucas Johnson, Noemi Andor, Kenneth Day, Mickey Miller, Helaman Escobar, Lincoln Nadauld, Hanlee P. Ji, Paul Van Hummelen. High-quality CNV segments from low-coverage whole genome sequencing from FFPE cancer biopsies based on an evaluation of multiple CNV tools [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 438.

Single-cell transcriptome analysis identifies distinct cell types and intercellular niche signaling in a primary gastric organoid model

The diverse cellular milieu of the gastric tissue microenvironment plays a critical role in normal tissue homeostasis and tumor development. However, few cell culture model can recapitulate the tissue microenvironment and intercellular signaling in vitro. Here we applied an air-liquid interface method to culture primary gastric organoids that contains epithelium with endogenous stroma. To characterize the microenvironment and intercellular signaling in this model, we analyzed the transcriptomes of over 5,000 individual cells from primary gastric organoids cultured at different time points. We identified epithelial cells, fibroblasts and macrophages at the early stage of organoid formation, and revealed that macrophages were polarized towards wound healing and tumor promotion. The organoids maintained both epithelial and fibroblast lineages during the course of time, and a subset of cells in both lineages expressed the stem cell marker Lgr5. We identified that Rspo3 was specifically expressed in the fibroblast lineage, providing an endogenous source of the R-spondin to activate Wnt signaling. Our studies demonstrate that air-liquid-interface-derived organoids provide a novel platform to study intercellular signaling and immune response in vitro.

Abstract 2443: Massively parallel single-cell RNA-Seq identifies diverse subpopulations displaying EMT and stem-like features

Single-cell transcriptome analysis enables a new paradigm for studying complex systems in cancer. As opposed to bulk sequencing, which averages genomic signals across thousands or millions of cells and obscures the presence of rare subtypes, single cell sequencing enables the interrogation of individual cells. In cancer, intratumoral heterogeneity is observed at both genomic and epigenomic levels, and its analysis enables the discovery of new actionable targets and treatment modalities tailored to individual subpopulations. As an example, many cancer cell lines and those derived from patients contain subpopulations marked by distinct patterns of surface markers such as CD44, and are linked to drug resistant and tumor initiating phenotypes. A complete characterization of such cellular populations ideally requires marker-free sampling, followed by clustering into distinct subgroups. In this study, we demonstrate the significant advantages of such an approach; we utilize a high-throughput single-cell RNA-Seq method to characterize the transcriptomic profiles of cellular populations. We performed single-cell RNA-Seq on thousands of cells in the matched SW480 (primary) and SW620 (metastatic) colorectal cell lines using a microfluidic droplet barcoding technology that enables the tracking of single cells during library preparation. By focusing on genes with high inter-cell variability, we discovered a small subpopulation of cells that displayed a distinct gene expression signature from the major subpopulation. Differential gene expression analysis of this subpopulation yielded genes virtually all enriched in the epithelial-to-mesenchymal transition (EMT) pathway. These cells showed significant increases in canonical mesenchymal marker genes such as VIM, CD44, and SOX9. Gene expression profiles of these subpopulations also correlated with established EMT signatures. Remarkably, this subpopulation did not display mutual exclusivity in gene expression with the epithelial marker EPCAM, which possibly indicates an intermediate mesenchymal phenotype. We also observed in the major population cluster a small subset of cells totaling less than 1% of the population that were significantly enriched for LGR5 expression, a common stem-like marker in colorectal cancer. Overall, we demonstrate the use of single-cell RNA-Seq to discover and characterize a diversity of cellular states that would otherwise be impossible from bulk analysis. Citation Format: Billy Lau, Jiamin Chen, Hanlee P. Ji. Massively parallel single-cell RNA-Seq identifies diverse subpopulations displaying EMT and stem-like features [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2443. doi:10.1158/1538-7445.AM2017-2443