Over the past decade, NGS technologies have moved at a rapid pace, dramatically reducing costs and making genome sequencing more routine. What was once unthinkable is now possible. However, most genomes are still sequenced from DNA extracted from multiple cells, which misses differences between cells that could be crucial in controlling gene expression, cell behavior, and drug response. Still, challenges for single-cell sequencing remain, including cell isolation, DNA amplification and bioinformatics. As the techniques are being refined, subtle differences between cells, such as the tiny genomic rearrangements, will emerge. CHI’s Single-Cell Sequencing conference focuses on the links between cell variation in tissues and organ function and further elucidates the origins of diseases.
Day 1 | Day 2
Wednesday, August 21
7:30 am Breakfast Technology Workshop (Sponsorship Opportunity Available)
8:15 Chairperson's Remarks
Xinghua Pan, Ph.D., M.D., Associate Research Scientist and Group Head, Genetics, Yale University School of Medicine
» Featured Presentation
8:20 Technology Progress and Prospect on Single-Cell Genomics
Xinghua Pan, Ph.D., M.D., Associate Research Scientist and Group Head, Genetics, Yale University School of Medicine Biography
High-throughput sequencing of the genomes and functional genomics elements for single cells is a new dimension for biological analysis. For these analyses, sensitive and faithful amplification technology is essential and difficult. We have developed a series of novel methods to generate sufficient materials for sequencing analysis, representing a full-length mRNA transcriptome, whole CpG methylome, whole genome and open chromatins. We have also established a robust measurement of telomere length for single cells and a proof-of-concept process for analysis of DNA and RNA from the same single cell. The current progresses, applications and prospects will be addressed.
8:50 Strand-Seq: Template Strand Sequencing for High-Resolution Mapping of DNA Rearrangements in Single Cells
Ester Falconer, Ph.D., Research Fellow, Terry Fox Laboratory, BC Cancer Research Centre Biography
Current single-cell sequencing techniques can mask certain genomic features such as sister chromatid exchanges (SCE) and translocations, both of which signify genomic instability, a potent driver of malignancies. We show that sequencing only the original parental template strands (Strand-Seq) in single murine and human cells can map such events with much greater resolution than traditional cytogenetic techniques, with the exchange region mapped as close as 22 bp. Importantly, Strand-Seq libraries show that the current assemblies of the mouse and human reference genomes contain multiple incorrectly oriented contigs, which in the case of the mouse genome assembly, totals nearly 1% of the genome. I will discuss how Strand-Seq can dramatically expand the range of biological questions that can be addressed in single cells.
9:20 RNA-Seq and Find: Entering the RNA Deep Field
Lior Pachter, Ph.D., Professor, Mathematics, Molecular & Cell Biology, and Electrical Engineering & Computer Science, University of California, Berkeley
9:50 Selected Oral Poster Presentation: Genome Assembly Using Single-Cell DNA Template Strand Data
Mark Hills, Ph.D., Research Scientist, Terry Fox Laboratory, BC Cancer Research Centre
Standard genome-building approaches create ever-increasing scaffolds that are built into new reference genomes. However, the return of these endeavors diminishes as the proportion of unsequenced regions decreases. Using Strand-seq, a method to sequence template strands in single cells, we show we can stratify and orient contigs from early- and late-assembly genomes. The direction of these template strands provides a unique chromosomal signature, such that contigs originating from the same chromosomes share the same template strand directionality. Using this approach we have fine-tuned the assembly of “completed” reference genomes of mouse and man, and demonstrate the ability to correctly rebuild chromosomes from contigs based solely on their template strands in an early mouse build (mm1). We can further stratify these contigs into relative orders using sister chromatid exchanges to infer genetic distances, and suggest that this strategy will find broad application in constructing genome assemblies in the future.
10:05 Coffee Break in the Exhibit Hall with Poster Viewing
11:00 Diagnostic Uses of Single-Cell Genomics
Allison Welsh, Ph.D., Research Scientist, Genitourinary Oncology, Memorial Sloan-Kettering Cancer Center and Cold Spring Harbor Laboratory
The ability to perform genomic assays on single cells provides a means to detect cancer initiation at its earliest stages and to follow response therapy using minimally invasive techniques. We will describe results from whole genome assays on blood (circulating tumor cells), urine and fine needle aspirates using NextGen sequencing to assess copy number variation (CNV) as well as specific point mutations in multiple cancer types.
11:30 Single-Cell Sequencing of Circulating Tumor Cells from Lung Adenocarcinoma Patients
Fan Bai, Ph.D., Assistant Professor, Biodynamic Optimal Imaging Center, Peking University Biography
We performed single-cell sequencing of circulating tumor cells from patients with lung adenocarcinoma. The genetic profiles of CTCs were compared with matched primary and metastatic tumor tissues from the same patient. All major mutations observed in tumor tissues were identified in CTCs. Genetic analysis of CTCs offers diagnostic advantages such as high specificity and non-invasiveness for tumor mutation assessment and targeted therapy. The genetic characteristics of CTCs may reveal genotypic transition during tumor progression.
12:00 pm Close of Session
12:30 Luncheon Technology Workshop: From Reads to Variants: Ten-Fold Reduction in Time and Cost with Improved Accuracy
Rupert Yip, Ph.D., Director, Product Marketing, Bina Technologies
Alignment and variant calling of raw NGS reads has been plagued by expensive HPC hardware and the bioinformatics personnel to support and maintain home-grown, open-source secondary analysis solutions. Such solutions can take up to weeks and $1000s per analysis. We present a genomic analysis platform that reduces, by ten-fold, the time and cost for secondary analysis while improving accuracy compared to standard pipelines. Our innovative model reduces costs by ten-fold while preventing hardware obsolescence.
1:30 Chairperson's Remarks
Jan Vijg, Ph.D., Professor and Chair, Genetics, Albert Einstein College of Medicine
» Featured Presentation
1:35 Single-Cell Transcriptogenomics
Jan Vijg, Ph.D., Professor and Chair, Genetics, Albert Einstein College of Medicine Biography
During organismal development and aging, changes in the genome of cells result in increased genetic mosaicism of the somatic tissues. To dissect this age-related intra-tissue heterogeneity, we developed single-cell, genome-wide sequencing procedures to measure both single nucleotide and structural variation. To directly link single-cell, genomic mutation loads to possible consequences at the level of the transcriptome, we then performed concurrent global mRNA amplification and whole-genome amplification of single cells followed by RNA-Seq and whole-exome sequencing, respectively. This method, "single-cell transcriptogenomics," allows us to directly track the consequences of randomly induced genetic mutations on gene expression profiles in the same single cell.
2:05 Insights into the Regulation of Protein Abundance from Proteomic and Transcriptomic Analyses
Christine Vogel, Ph.D., Assistant Professor, Center for Genomics and Systems Biology, New York University Biography
The advent of large-scale sequencing and proteomics technologies has shown that translation and protein degradation regulation are as important as transcription to fine-tune cellular gene expression levels. We investigate general principles of protein expression regulation in eukaryotic cell systems, both under normal and stress conditions.
2:35 Sequencing the Genomes and Transcriptomes of Single Human Cells
Alec Chapman, Research Scientist, X. Sunney Xie Laboratory, Chemistry and Chemical Biology, Harvard University Biography
While sequencing is rapidly revolutionizing the way biological questions are approached, the prevailing methods have been limited to studying large ensemble populations of cells, masking the heterogeneity that is crucial for understanding complex systems such as cancer and development. We have recently developed a technique—Multiple Annealing and Looping Based Amplification Cycles (MALBAC)—that is capable of uniform whole-genome amplification from single cells, achieving >90% coverage and enabling the detection of copy number variations and newly acquired single nucleotide variations with no false positives. Adapting MALBAC to transcriptome sequencing provides both improved technical reproducibility and increased sensitivity over existing methods and simultaneously sequencing the genome and transcriptome from the same cell allows us to probe the relation between genotype and phenotype in heterogeneous populations.
3:05 Refreshment Break in the Exhibit Hall, Last Chance for Poster Viewing
3:35 You Need More Power: Designing Cost-Effective Experiments for Measuring Differential Gene Expression Using RNA-Seq
Michele Busby, Ph.D., Computational Biologist, Broad Institute; former Research Scientist, Biology, Gabor T. Marth Laboratory, Boston College
RNA-Seq is a powerful tool for detecting differential gene expression, but only realizes its full potential when experiments are optimally designed. We will demonstrate how our computational tool Scotty can be used to design an experiment that contains an adequate number of samples sequenced to a sufficient depth to achieve experimental goals. We will further discuss how the performance of different RNA-Seq protocols can dramatically affect the power of an experiment and demonstrate computational techniques for assessing the performance of a protocol.
RNA-Seq Experimental Design and Bioinformatics with Michele Busby
4:05 Deconvolution of Heterogeneous Tissue Samples Based on RNA-Seq Data
Ting Gong, Ph.D., Assistant Professor, Molecular Carcinogenesis, University of Texas MD Anderson Cancer Center
The promising biomedical applications of NGS have spurred the development of new statistical methods to capitalize on the wealth of information contained in RNA-Seq datasets. However, for heterogeneous tissues, measurements of gene expression through RNA-Seq data can be confounded by the presence of multiple cell types present in each sample. Here, we present a statistical pipeline for deconvolution of heterogeneous tissues based on RNA-Seq data.
4:35 Panel Discussion with Afternoon Speakers
Moderator: Jan Vijg, Ph.D., Professor and Chair, Genetics, Albert Einstein College of Medicine
The genome sequencing of large numbers of cells, while a significant and increasingly common technological feat, is also proving less effective than single-cell sequencing, which can better reveal intercellular variations that in turn relate to disease origins, gene expression and more. This panel addresses techniques, advantages, challenges and biomedical applications of single-cell sequencing to cancer, development, aging and other biological processes.
Panelists:
Christine Vogel, Ph.D., Assistant Professor, Center for Genomics and Systems Biology, New York University
Alec Chapman, Research Scientist, X. Sunney Xie Laboratory, Chemistry and Chemical Biology, Harvard University
Michele Busby, Ph.D., Computational Biologist, Broad Institute; former Research Scientist, Biology, Gabor T. Marth Laboratory, Boston College
Ting Gong, Ph.D., Assistant Professor, Molecular Carcinogenesis, University of Texas MD Anderson Cancer Center
Andrey Shabalin, Ph.D., Research Scientist, Edwin J.C.G. van den Oord Laboratory, Center for Biomarker Research and Personalized Medicine, Pharmacotherapy and Outcomes Science, Virginia Commonwealth University
Christina Schweikert, Ph.D., Division of Computer Science, Mathematics and Science, St. John's University
5:00 Close of Single-Cell Sequencing Conference
Day 1 | Day 2