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단세포 시퀀싱 컨퍼런스 - 둘째날



최근 10년간 NGS 기술이 급속히 진보하고 비용도 큰폭으로 하락하면서 게놈 시퀀싱은 보다 일상화되고 있습니다. 이전에는 상상도 할 수 없었던 일이 지금은 가능합니다. 그러나 게놈 시퀀싱에서 사용되는 DNA의 다수는 다중 세포로부터 추출된 것으로, 유전자 발현, 세포 행동, 약물 반응 제어에 중대한 영향을 미칠 수도 있는 세포별 차이를 간과할 가능성도 있습니다. 한편, 단세포 시퀀싱에도 세포 격리, DNA 증폭, 바이오인포매틱스 등에 관련된 문제가 있습니다. 또한 시퀀싱 기술이 개선되면 미세한 게놈 재배열 등 세포간 약간의 차이가 표면화할 가능성도 있습니다. 이 컨퍼런스에서는 조직내 세포 변화와 장기 기능의 관련성, 질병 원인의 구명에 초점을 맞춥니다.

첫째날 | 둘째날

8월 21일(수)

7:30 am Breakfast Technology Workshop (Sponsorship Opportunity Available)

 

단세포 연구에 도움이 되는 기술 

8:15 Chairperson's Remarks

 

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

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

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 Technology Spotlight (Sponsorship Opportunity Available)

10:05 Coffee Break in the Exhibit Hall with Poster Viewing

11:00 Diagnostic Uses of Single-Cell Genomics

James B. Hicks, Ph.D., Research Professor, Genetics, 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

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 Technology Spotlight (Sponsorship Opportunity Available)

12:15 Close of Session

12:30 Luncheon Technology Workshop (Sponsorship Opportunity Available)

 

전사와 단세포 

1:30 Chairperson's Remarks

 

Featured Presentation

1:35 Single-Cell Transcriptogenomics

Jan Vijg, Ph.D., Professor and Chair, Genetics, Albert Einstein College of Medicine

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

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

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 Technology Spotlight (Sponsorship Opportunity Available)

3:20 Refreshment Break in the Exhibit Hall, Last Chance for Poster Viewing

4:00 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.

4:30 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.

5:00 Panel Discussion with Afternoon Speakers

5:30 Close of Single-Cell Sequencing Conference

 

 

 



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